A buckle device of the type into which a tongue plate is inserted and engaged therewith. The buckle device is equipped with a lever member having a first and a second end as well as a middle section. The first end of the lever member is engaged with a locking member, which is to be engaged with the inserted tongue plate to prevent it from being extracted from the buckle device. When the second end of the lever member is depressed, the lever member is displaced, using its middle section as the fulcrum, to release the engagement between the buckle device and the tongue plate. This lever member is equipped with a displacement section for displacing the fulcrum from the side of the first end to that of the second end when the second end is depressed. Thus, when the second end is depressed, the fulcrum of the lever member is displaced toward the second end, thereby gradually diminishing the lever ratio of the lever member.

1. Field of the Invention
This invention relates to a buckle device which is used in a seat belt or the like.
2. Description of the Related Art
A buckle device used in a seat belt is equipped with a locking member which is to be engaged with a tongue plate for the purpose of locking the same. This locking member is designed to be displaceable in such a way as to release the lock of the tongue plate.
In some cases, the lock of the tongue plate in such a buckle device is released by means of a lever member using its middle section as the fulcrum.
FIG. 5 shows the mechanism of a buckle device of this type. In the example shown, a lock plate 10 serving as the locking member can be displaced in the vertical direction. When moved downwards, it is inserted into a through-hole 14 provided in a tongue plate 12, thereby locking the tongue plate 12 with respect to this buckle device. A lever 16 serving as the lever member is rotatably mounted, using its middle section as the fulcrum. When a push button 18 provided at that end of the lever 16 which is on the opposite side of the lock plate 10 is depressed downwards, that end of the lever 16 at which the lock plate 10 is provided is moved upwards to extract the lock plate 10 from the through-hole 14, thereby releasing the lock of the tongue plate 12.
In the above lever 16, the lever ratio K is determined as: K=L1/L2>1 so that the requisite force for operating the push button 18 can be relatively small. Accordingly, when the stroke for moving the lock plate 10 from the lock position to the release position is represented as S1, the stroke S2 for the push button 18 is to be represented as S1.times.K. Thus, the buckle device is required to have a relatively large thickness before the stroke S2 can be ensured, which constitutes an obstacle to miniaturization of the device.
Diminishing the lever ratio K might naturally allow the stroke K to be reduced, and consequently, the device to be miniaturized. However, this results in the requisite force for operating the push button 18 being augmented, which makes the device hard to operate.


Although DC offset reduction schemes can be applied in the analog domain, the residual static DCO in baseband is still present, significantly influencing the performance of high-level modulation schemes employed by recent high-data-rate wireless communications standards. In order to achieve satisfactory performance, DCO compensation algorithms are required in the digital domain. One such algorithm was developed which is based on joint estimation of the Channel Impulse Response (CIR) and the static DCO and ensures satisfactory performance of EDGE modem with direct conversion radio architectures. A further modification of the joint estimation algorithm, the so-called “perturbed joint L”, results in further improvement in the performance of the EDGE equalizer in critical fading channels.

The invention relates to the field of data receivers, and, in particular, to systems and methods for reducing DC offsets in wireless receivers.
The basic challenge in detection of transmitted data comes from distortion caused by the channel. Typically, channel refers to a combination of all non-ideal effects that adversely affect the ability to correctly detect the transmitted data sequence at the receiver. Such effects include, but are not limited to, effects of propagation (e.g. cable, radio channel etc.), non-linearities, or effects of transmit (TX) and receive (RX) filters. Current state-of-the-art detection techniques rely on the knowledge of the channel, which, therefore, must be estimated.
The background of the invention will be described in the wireless communication scenario, although invention can be used in any communication system. As is known in the art, in wireless communications received radio frequency signals are converted to baseband using various receivers. With a homodyne receiver, the received radio frequency signal is mixed with the local oscillator whose frequency is equal to carrier frequency of the received radio frequency signal to translate the carrier frequency to DC and thereby provide "direct conversion" of the modulation on the received radio frequency signal to a modulation at DC. Hence, a homodyne receiver is sometimes referred to as a direct conversion receiver.
While such direct conversion receivers offer the advantage of flexible architecture and educed cost, DC offset associated with such receivers is affecting the receiver performance. The level of the DC offset in direct conversion receiver may range from being significantly larger than the desired signal, i.e., modulation, to be demodulated to being comparable in level with desired signal. Thus, DC offset compensation techniques are typically required. To insure flexibility for different operating conditions, DC offset compensation can be part of the digital baseband portion of the receiver, preferably a part of the digital signal processing (DSP) firmware. One application of direct conversion receivers is in mobile or cellular communication systems. In such systems, the radio channels received signals also suffer from intersymbol interference (ISI) caused by multipath radio propagation and transmitter and/or receiver filtering. We further explain the underlying principle using the specific format of Time Division Multiple Access (TDMA) system as represented by GSM/GPRS/EDGE cellular standard.
The original GSM system, of which GPRS and EDGE are extensions, is a TDMA system, which means that a particular channel is active only during specified time periods. In this case, each channel is divided into eight time slots, with user being active at only every eight slots for voice transmission, or utilizing multiple slots for data transmission per standard specification.
GSM (including GPRS and EDGE) uses the midamble training sequence (a training sequence placed in the middle of the burst of data that occurs in a given slot) in every burst. The system parameters are chosen so that the change in Channel Impulse Response (CIR) is fairly small during one burst so that adaptive CIR estimation is not needed. The midamble training sequence minimizes the distance (in time) between the known portion of the burst (the training sequence) and the ends of the burst, thereby also minimizing CIR change with respect to the CIR estimate obtained from the training sequence.
In EDGE system, the combined channel response usually consists of the linear TX Gaussian shaping filter (CO), actual physical channel, and TX/RX filters (analog and/or digital filters). A set of channel models is used for performance evaluation and covers a wide range of typical physical propagation channels that are likely to be encountered in practice as specified by the standardization bodies (ETSI, 3GPP). These channels are denoted by:                static (no ISI or fading)        TU3 (typical urban, velocity of the mobile station (MS) 3 km/h, moderate multipath, low fading)        TU50 (typical urban, velocity of the MS 50 km/h, moderate multipath and fading)        RA250 (rural area, MS velocity 250 km/h, no multipath, severe fading) HT100 (hilly terrain, MS velocity 100 km/h, severe multipath, significant fading).
GSM training sequences (shared by GPRS and EDGE) have good autocorrelation properties. GSM/GPRS systems use GMSK modulation format, while EDGE introduces the new 8-PSK modulation format. In EDGE, training sequences for GMSK and 8-PSK modulation are identical, binary, and differ only due to different additional rotation applied to the signal in two modulation schemes. GMSK effectively rotates a signal 90 degrees every symbol, while EDGE 8-PSK uses the rotation of 3π/8 for every symbol. Properties of the training sequences are used to simplify CIR estimation. For example, due to good autocorrelation properties of training sequences, simple cross-correlation can be used for CIR estimation.
In a typical data receiver realization in GSM/GPRS/EDGE system, the whole received burst is stored and the all-digital techniques may be applied to signal processing, including DC offset compensation. Thus, referring to FIG. 1, the data receiver stores the burst of data, r(k), where k=1 . . . N and N is the number of samples in the burst. Each burst includes a mid-amble having a known sequence of bits disposed between data, (i.e., information bits) as shown. Such known sequence of bits is used to aid in equalization and more particularly for enabling channel estimation, which includes timing information, length of the CIR, calculation of CIR taps as well as the alignment of the CIR estimate with respect to the largest magnitude CIR tap, and DC offset estimation. As shown in FIG. 1, an estimate of the DC offset, Â, is calculated. The estimated DC offset, Â, is subtracted from the received burst. The result, r(k)−Â, where k=1 . . . N, is processed to find an estimate of the h. The CIR estimate, ĥ, can be obtained by a variety of methods including cross-correlating [r(k)−Â] with the known mid-amble bit sequence, using Least Square (LS) estimation as well as other advanced techniques.
The simplest method for channel estimation in GSM is cross-correlation. In cross-correlation CIR estimation, the inner 16 symbols of the training sequence are correlated with the received symbol. The received symbol at time k is given by:
      y    n    =                    ∑                  i          =          0                          L          -          1                                            h          i                                  t                      n            -            i                                +          z      n      where yk is the received signal, hk are CIR taps, tk is the known training sequence (or data), while zk is AWGN with variance σ2. The following notation is used to differentiate between the (known) training sequence and (generally unknown) data. Training sequence symbols are denoted by t0 to t25. Data for the left data burst are denoted d0 to d57, while those for the right data burst are denoted d58 to d115. By cross-correlation with the inner 16 training sequence symbols:
                                          h            ^                    k                =                              1            16                                                        ∑                              j                =                5                            20                                                                  y                                  k                  +                  j                                                                          t                j                                                                            =                              1            16                                                        ∑                              j                =                5                            20                                                                  t                j                                                          (                                                                            ∑                                              i                        =                        0                                                                    L                        -                        1                                                                                h                        i                                                                                t                                                  j                          -                          i                          +                          k                                                                                +                                      z                                          j                      +                      k                                                                      )                                                                            =                                            1              16                                                                  ∑                                  i                  =                  0                                                  L                  -                  1                                                                                h                  i                                                                                ∑                                          j                      =                      5                                        20                                                                                t                      j                                                                                t                                              j                        -                        i                        +                        k                                                                                +                                    1              16                                                                  ∑                                  j                  =                  5                                20                                                                            t                  j                                                                                z                                          j                      +                      k                                                        .                                                                        Due to autocorrelation properties of the training sequences,
                    ∑                  j          =          5                20                                    t          j                                  t                      j            -            i            +            k                                =    0    ,unless i=k (provided |k−i|<5),
                                          h            ^                    k                =                              1            16                                                        ∑                              j                =                5                            20                                                                  y                                  k                  +                  j                                                                          t                j                                                                            =                              h            k                    +                                    1              16                                                                  ∑                                  j                  =                  5                                20                                                                            t                  j                                                                  z                                      j                    +                    k                                                                                =                              h            k                    +                      Δ                                                                                h                k                            .                                          Δhk denotes CIR tap estimation error due to noise. The main limitation of cross-correlation CIR estimation is that it can only provide accurate estimates of up to 6 CIR taps. If CIR is longer than 6, and HT100 channel profiles span seven symbols when convolved with Gaussian pulse CO (3 symbols span), cross-correlation CIR estimation produces inaccurate estimates for all but six initial taps.
For example, for CIR length of 6, in matrix notation, ĥ is given by:
            h      ^        =                  C                          (                      Th            +            z                    )                                                    where            C    =          [                                                  t              5                                                          t              6                                            ⋯                                              t              20                                            0                                ⋯                                ⋯                                0                                                0                                              t              5                                            ⋯                                ⋯                                              t              20                                            0                                ⋯                                0                                                ⋮                                ⋰                                ⋰                                                                                ⋰                                ⋰                                ⋮                                                ⋮                                                                                ⋰                                ⋰                                                                                ⋰                                0                                                0                                ⋯                                ⋯                                0                                              t              5                                            ⋯                                ⋯                                              t              20                                          ]            T    =          [                                                  t              5                                                          t              4                                            ⋯                                              t              0                                                                          t              6                                                          t              5                                            ⋯                                              t              1                                                            ⋮                                                                                ⋮                                                              t              25                                            ⋯                                ⋯                                              t              20                                          ]
In general, matrix T is equal to
  T  =      [                                        t                          L              -              1                                                            t                          L              -              2                                                ⋯                                      t            0                                                            t            L                                                t                          L              -              1                                                ⋯                                      t            1                                                ⋮                                                                                ⋮                                                  t            25                                    ⋯                          ⋯                                      t                          25              -              L              +              1                                            ]  and matrices C and T are of dimensions (16+L−1×L) and (26−L+1×L), respectively. This form of matrix T assumes perfect synchronization (i.e., exact knowledge of the length of the channel and position of the training sequence). It should be noted that matrix T will consist only of training sequence symbols as long as 26−L+1>=16+L−1, which implies that L<=6. In the case L>6, matrix T must include some data samples in addition to training sequence symbols. For example,
  T  =      [                                        t            5                                                t            4                                    ⋯                                      t            0                                                d            57                                                            t            6                                                t            5                                    ⋯                                      t            1                                                t            0                                                ⋮                          ⋮                                                                          ⋮                          ⋮                                                  t            25                                                t            24                                    ⋯                                      t            20                                                t            19                                                            d            58                                                t            25                                    ⋯                                      t            21                                                t            20                                ]  Thus, estimates for CIR taps 0 and 6, in this case, become:
                    h        ^            0        =                  h        0            +                        1          16                                  (                                                    t                5                                                          d                57                                      +                                          ∑                                  j                  =                  6                                20                                                                            t                  j                                                                  t                                      j                    -                    6                                                                                )                                  h          6                    +              f                          (          z          )                                        h        ^            6        =                  h        6            +                        1          16                                  (                                                    t                20                                                          d                58                                      +                                          ∑                                  j                  =                  6                                19                                                                            t                  j                                                                  t                                      j                    +                    6                                                                                )                                  h          0                    +                        f                                (            z            )                          .            It can be seen that both the first and last CIR tap estimates will be distorted. This is much more significant in the case of the last tap, h6, as the first tap can, in some cases, be very large.
In matrix notation, cross-correlation CIR estimates are given by
      h    ^    =                    1        16                  Cr        =                            1          16                                  C                                (                          Th              +              z                        )                              =                        h          +                                    1              16                                    Cz                          =                  h          +                      Δ                                                                          h
A CIR error covariance matrix is given by
      E              [              Δ                                                  h                                                  Δ                                                            h          H                    ]        =                    1                  16          2                                  E                          [                                    Czz              H                                                  C              H                                ]                      =                            σ          2                          16          2                                  CC        H            where (for L<=5, and perfect synchronization) CCH is approximately equal to 16 I (I is identity matrix). If L>=7, or in case of imperfect synchronization, the estimation error covariance matrix becomes a function of CIR and data in addition to the error caused by AWGN. In general, CIR estimation error covariance is roughly equal to a σ2/16 for all taps with cross-correlation CIR estimation.
In order to start CIR estimation, the position of the training sequence needs to be identified. The first synchronization step takes place on a once-per-symbol sampled received signal. Synchronization is performed by correlating the entire training sequence with the received signal. The result is given by
                                                                        a                k                                                        =                                                ∑                                      j                    =                    0                                    25                                                                                y                                          k                      +                      j                                                                                t                    j                                                                                =                                                      ∑                                          j                      =                      0                                        25                                                                                t                      j                                                                                (                                                                                ∑                                                          i                              =                              0                                                                                L                              -                              1                                                                                h                              i                                                                                t                                                              j                                -                                i                                +                                k                                                                                +                                                  z                                                      j                            +                            k                                                                                )                                                                                =                                                                            ∑                                              i                        =                        0                                                                    L                        -                        1                                                                                h                        i                                                                                ∑                                                      j                            =                            0                                                    25                                                                                t                            j                                                                                t                                                          j                              -                              i                              +                              k                                                                                +                                                            ∑                                              j                        =                        0                                            25                                                                                t                        j                                                                                z                                                  j                          +                          k                                                                                a                k                            =                                                                    ∑                                          i                      =                      0                                                              L                      -                      1                                                                                h                      i                                                                                ∑                                                  j                          =                          0                                                25                                                                                t                          j                                                                                t                                                      j                            -                            i                            +                            k                                                                                +                                                      ∑                                          j                      =                      0                                        25                                                                                t                      j                                                                                z                                              j                        +                        k                                                                                =                                                                            h                      k                                                                                T                                                                    (                        0                        )                                                                              +                                                            ∑                                                                        i                          ≠                          k                                                                          i                          =                          0                                                                                L                        -                        1                                                                                h                        i                                                                                T                                                                          (                                                      k                            -                            i                                                    )                                                                                +                                      f                                                              (                                              t                        ,                        z                                            )                                                                                where T(0) is the auto-correlation of the training sequence at delay of 0 (equal to 26) while T(k−i) are auto-correlations of the training sequence at different delays combined with cross-correlation with data symbols. In this case, T(k−i) are typically significantly smaller than T(0) so that ak is roughly equal to hkT(0). Consequently, the index of the largest magnitude ak corresponds to the position of the training sequence start, shifted by the position of the largest magnitude CIR tap with respect to the first CIR tap (tap 0).
After finding the approximate position of the largest magnitude CIR tap, the CIR span and the actual start of the training sequence (and therefore the whole burst) need to be established. The received burst can be envisioned as a superimposition of several copies of the original data—echoes—due to different CIR taps. As the largest magnitude CIR tap is not necessarily the first tap in the CIR, the echo corresponding to this tap does not necessarily correspond to the real start of the training sequence. Thus, a solution is needed to identify how many taps are present in the CIR and where the CIR starts (i.e. how many taps exist in front of the largest magnitude tap).
Usually, the length of the CIR is determined in advance and is supposed to be sufficient to cover the span in the worst-case scenario. In EDGE that is the HT100 channel, with about 7 taps. The extent of the CIR is determined as follows: after finding the location of the largest magnitude taps, rough estimates are obtained of another ten taps on both sides of the largest magnitude tap using cross-correlation CIR estimation. These ten taps are selected based on the properties of the training sequence. Since the largest magnitude tap is a part of the CIR, the remaining taps that can be correctly estimated using cross-correlation must be on either side or both sides of the largest magnitude tap. Thus, these extra ten taps are estimated, with the knowledge that at least five of them are correct. These are usually the largest magnitude taps out of the estimated eleven. Thus, the next step is usually to apply the so-called maximum energy algorithm. The magnitudes of all tentatively estimated taps are computed. Then, the CIR energy is computed given that CIR should have L taps by adding the magnitudes of L taps for different valid delays. The maximum energy delay is taken as the correct CIR span. If the index of the largest magnitude tap is given by max_idx, and the shift of the maximum energy CIR span with respect to max_idx is tap_shift, then the start of the burst is given by max_idx-tap_shift-61.
In Least Squares CIR estimation, a matrix representation model for the channel is given by r=Th+z, where
                    T        =                  [                                                                      t                                      L                    -                    1                                                                                t                                      L                    -                    2                                                                              ⋯                                                              t                  0                                                                                t                  L                                                                              t                                      L                    -                    1                                                                              ⋯                                                              t                  1                                                                                ⋮                                                                                ⋮                                                                                t                  25                                                            ⋯                                            ⋯                                                              t                                      25                    -                    L                    +                    1                                                                                ]                                                  h          =                                    [                                                h                  0                                                                                h                  1                                                                                …                                                                                h                                      L                    -                    1                                                              ]                        T                          ,                  r          =                                    [                                                r                                      L                    -                    1                                                                                r                  L                                                                                r                                      L                    +                    1                                                                                …                                                                                r                  25                                            ]                        T                          ,                                          and                                                              z                =                                            [                                                z                                      L                    -                    1                                                                                z                  L                                                                                z                                      L                    +                    1                                                                                …                                                                                z                  25                                            ]                        T                    .
Then, the LS CIR estimate is given byĥ=(THT)−1THr=(THT)−TH(Th+z)=h+(THT)−1THz=h+Δh
Unlike the cross-correlation CIR estimation, the LS CIR estimation is a coupled problem. In a LS CIR estimate, every estimated CIR tap depends on other estimated CIR taps. Thus, the value of the estimated taps in the LS CIR estimate depends on the time alignment of the estimator with respect to the largest magnitude tap, inasmuch as the contribution of every omitted significant CIR tap is distributed between the remaining taps in the LS CIR estimation. Consequently, while the initial synchronization step remains unchanged with respect to cross-correlation CIR estimation, the optimal CIR alignment step is significantly different.
To find the optimal CIR span and alignment with respect to the largest magnitude CIR tap, all CIR estimates need to be identified with particular L that include the largest magnitude CIR tap and then pick the one that is the best fit in some sense (for example, model fitting error).
Unfortunately, this procedure is very complex—about three to six times more complex than cross-correlation CIR estimation. Furthermore, the simplest way to reduce the complexity of the CIR alignment step, by obtaining a rough LS CIR estimate consisting of 11 CIR taps, as with cross-correlation CIR estimation, results in a CIR estimation error that is far inferior to that achievable with cross-correlation CIR estimation.
Consequently, if the optimal CIR alignment procedure is too complex, the cross-correlation CIR estimate can be used as a rough CIR estimate and thus obtain the parameters required to find a better CIR estimate, CIR length L, and the alignment of the CIR estimate with respect to the largest magnitude CIR tap. The procedure for obtaining these parameters is the same as for cross-correlation CIR estimation (described above).
For LS CIR estimation, an estimation error is given by Δh=(THT)−1THz, while estimation error covariance matrix is given by:E[ΔhΔhH]=E[(THT)−1THzzHT(THT)−1]=σ2(THT)−1 Error covariance for individual taps is given by diagonal elements of the estimation error covariance matrix and is roughly equal to σ2/(26−L+1) for LS CIR estimation. As off-diagonal elements of (THT)−1 are in general not equal to zero (although small), LS CIR estimation errors are correlated, but only slightly.
Parameters obtained by channel estimation, including DC offset and CIR estimates, are further sent to data receiver and are used to enable the demodulation process (e.g. prefilter calculation, equalization algorithm selection, calculation of the path metric of trellis based equalizers, etc.)

Method for joint DC offset correction and channel coefficient estimation in a receiver


An optical decoder and a multi-functional printer using the same are provided. The optical decoder includes a directional light source, a light guide bar and a light receiving unit. The light guide bar disposed on a light-emitting side of the directional light source has multiple scales. The light receiving unit is disposed on a side of the light guide bar, wherein the directional light source and the light receiving unit are disposed on different sides of the light guide bar. The light receiving unit is used to move along the light guide bar and read the scales of the light guide bar. The overall volume of a multi-functional printer can be reduced by applying the optical decoder therein.

1. Field of the Invention
The invention relates to an optical decoder and a multi-functional printer, and more particularly to an optical decoder and a multi-functional printer capable of reducing step operation generated errors as well as improving accuracy.
2. Description of Related Art
FIG. 1 is a schematic sectional view of a conventional multi-functional printer. Referring to FIG. 1, a motor 110 drives a gear 120 and a timing belt 130 when a piece of paper is sent to a printing platform. An inkjet head 140 also moves since a bearing seat 150 of the inkjet head 140 is connected to the timing belt 130. Learning that the inkjet head 140 reaches the printing area via signals of a strip 160 and an optical encoder 170, an electronic system initiates a printing process.
FIG. 2 is a schematic view of the strip and the optical decoder of FIG. 1. Referring to FIG. 2, the conventional strip 160 is formed with translucent and opaque areas arranged in a staggered pattern thereon. Moreover, the strip 160 is in a striped configuration or a plating configuration. The optical encoder 170 includes a light emitting element 172 and a light receiving unit 174. The strip 160 is placed between the light emitting element 172 and the light receiving unit 174.
When the opaque areas of the strip 160 pass through the optical encoder 170, light emitted from the light emitting element 172 cannot penetrate the opaque areas. As a result, the light receiving unit 174 produces no signal. However, light emitted from the light emitting element 172 penetrates the translucent areas when the translucent areas of the strip 160 pass through the optical encoder 170. The light receiving unit 174 produces signals accordingly
Space needs to be reserved to accommodate the strip 160 and the optical encoder 170 in the multi-functional printer since the strip 160 needs to be placed between the light emitting element 172 and the light receiving unit 174. As a result, the overall volume of the multi-functional printer can't be reduced effectively.

Optical decoder and multi-functional printer using the same

Cal-Comp Electronics & Communications Company Limited


In a dust collector, dust and waste materials such as wood chips and shavings are collected in its casing through a dust collecting duct by a dust collecting fan rotated by a motor. The dust and waste materials thus collected are compressed and extruded by an extruding screw which is rotated by the motor, whereby the dust and waste materials can be readily discarded.

1. Field of the Invention
This invention relates to small portable dust collector.
2. Background of the Invention
A conventional dust collector is so designed as to collect dust or waste materials in a dust collecting chamber provided inside a machine. Therefore, the maximum amount of dust which can be collected thereby is limited. Especially in the case of collecting waste materials such as wood chips or shavings formed during woodworking, which are relatively bulky and loose, the dust collecting chamber is quickly filled up with the waste materials, and therefore it must be emptied frequently. This process of discharging the waste material is rather troublesome.
Japanese Utility Model Application (OPI) No. 4358/1983 has disclosed a dust collector which is so designed that two bags are provided for receiving dust from a dust sucking section, and, when one of the two bags is filled up with dust, a damper is operated to allow the other bag to receive the dust.
The conventional dust collector thus designed is advantageous in that the bag filled up with dust can be replaced by a new one without stopping the dust collector. However, it is still disadvantageous in the following points. In the case of collecting waste materials such as wood chips or shavings, the bag is soon filled up with them. That is, the frequency of exchanging the bag is relatively high. Furthermore, the replacement of the bag is troublesome, a number of bags must be prepared, or special bags must be designed for the dust collector. Moreover, since dust and waste materials are collected together with air, the dust and waste materials thus collected is bulky in the bag, thus taking time and labor for removal and disposal.


A process for fabricating a composite article is disclosed. A surface of a preconsolidated fiber reinforced glass matrix composite structure is pretreated to promote adhesion to the surface, a mass of fiber-containing uncured resin is molded in contact with the pretreated surface and the resin is cured to consolidate a fiber reinforced resin matrix composite structure and simultaneously bond the resin matrix composite structure to the glass matrix composite structure. An external flap for a gas turbine engine fabricated by the above process is also disclosed.

It has been widely recognized that the selective use of fiber reinforced composite materials to replace metals can result in significant performance benefits. These benefits arise from the exceptional combination of high stiffness, high strength and low density that characterize fiber reinforced composite materials and from the ability to tailor the properties of a particular composite article to fit the demands of a particular application. The use of composites has expanded rapidly, particularly within the aerospace and automotive industries.
The range of applications to which composite materials may theoretically be applied is broadly defined by such absolute limits as the maximum use temperature obtainable with current materials. However, the range of applications to which composite materials may practically be applied is more narrowly defined by practical limits reflecting the trade-off of properties inherent in the design of any composite article. For example, while a graphite fiber reinforced metal matrix composite might conceivably be used in a relatively low temperature application for which the properties of a fiber reinforced epoxy matrix composite would be adequate, it would be impractical to do so because of the increase in cost, density and difficulty of fabrication and the lack of any significant benefit attending the substitution. Similarly, there are applications that fall within the broad scope of the current state of the composite art, in which composites might theoretically be used, but where the trade-off of properties and cost renders such uses impractical.
There is a constant intensive search in this art for means by which composite articles having a more advantageous balance of properties may be obtained in order to further expand the range of applications in which the use of composite materials is beneficial.
What is needed in this art is a technique by which composite articles having a broader range of application may be fabricated.

Hybrid composite structures of fiber reinforced glass and resin matrices


A Heating System is provided for heating the hydraulic fluid of a hydraulic unit used with a power source and having a reservoir for retaining hydraulic fluid. The heating system comprises a heating element located in the reservoir. A switch is included along with a power line for connecting the power source to the switch. An electrical line is connected to the switch and is connected to the power line when the switch is closed. A relay is connected to the electrical line. A return line is connected to the relay and to the power source and a heater line connected to the relay and to the heater.

1. Field of the Invention
This Invention relates to heating systems and, more specifically, to a heating system for heating hydraulic fluid such as used to operate a snow plow.
2. Prior Art
The use of snow plows on vehicles is comon place in areas which have snow. Snow plows, regardless of manufacture, must be raised and lowered from and to the ground and also be turned to the right and to the left. Pistons and cylinders are used for these purposes and the pistons and cylinders are activated by hydraulic fluid pumped into them under pressure. The pumps can be activated by the vehicle engine but, in the more recent designs, the pump is powered by an electric motor.
The hydraulic system for snow plows is not a closed circuit but rather draws hydraulic fluid from a reservoir and returns the hydraulic fluid to the reservoir as required to operate the plow. Hydraulic fluid is pumped out of the reservoir while air is drawn into the reservoir. Obviously, in cold and snowy weather, the air is moist and moisture forms in the reservoir. That moisture ultimately freezes forming ice in the reservoir. The ice blocks the hydraulic system making the snow plow inoperative. At that point, the vehicle on which the snow plow is mounted must be placed in a heated garage to allow the ice to melt and the moisture to be drawn off the reservoir. Such a delay in the ability to provide plowing services results in customer dissatisfaction and financial loss to the snow plow operator.


A valve timing adjusting device includes: a first rotor rotating integrally with a crankshaft; a second rotor integrally secured to an intake or exhaust camshaft; and an engaging cavity provided in one of the first rotor and the second rotor. A lock pin is housed in a housing hole provided in the other of the first rotor and the second rotor, protruded by the energizing force of an energizing device at the time of hydraulic pressure reduction, to thus abut on the wall of the engaging cavity from an oblique direction to give a relative rotating force to the first rotor and the second rotor.

A conventional valve timing adjusting device includes: a first rotor that integrally fixes the following three parts, a housing having the bearing of a camshaft, a case internally having a plurality of shoes projecting therefrom and having hydraulic chambers formed between the shoes, and a cover covering the hydraulic chambers, and that rotates integrally with a crankshaft; and a second rotor that has a plurality of vanes each dividing each of the hydraulic chambers into an advanced-angle hydraulic chamber and a retarded-angle hydraulic chamber, can relatively rotate through a predetermined angle within the first rotor, and is integrally fixed with an intake or exhaust camshaft, wherein the hydraulic pressure of an oil pump for supplying oil to the sliding portion of an engine is supplied and discharged, and this hydraulic pressure controls the relative position of the second rotor with respect to the first rotor.
In the constitution described above, when there exits no hydraulic power used at the time of engine start-up, the shoe of the first rotor and the vane of the second rotor repeat to abut on and separate from each other to cause slapping sounds. For this reason, one of the first rotor and the second rotor is provided with an engaging cavity, and the other thereof is provided with a lock pin engaging in and disengaging from the engaging cavity; and when there is no hydraulic pressure power used at the time of engine start-up, the lock pin is caused to engage in the engaging cavity by an energizing member, thus fixing the relative position between the first rotor and the second rotor to prevent the occurrence of the slapping sounds. In addition, this lock pin travels to the releasing direction by means of hydraulic power resisting the energizing force of the energizing member. During this traveling, the back pressure existing at the rear of the lock pin is discharged outside.
In this case, a minute or micro clearance is provided between the lock pin and the engaging cavity so that the cylindrical lock pin smoothly engages in the engaging cavity, and the first rotor and the second rotor can relatively rotate through a minute angle even in a lock-pin engaging state. Consequently, this minute-angle-relative rotation causes slapping sounds, and further, causes angular misalignments when the device is assembled to the engine. This is a problem when high-precise assembly is demanded.
For this reason, in order to prevent this minute rotation, the lock pin and the engaging cavity are given the shape of a taper, and thereby, these parts are caused to interengage without a clearance, as disclosed by JP-A-2002-004816 and JP-A-2003-328708.
Patent Reference 1: JP-A-2002-004816
Patent Reference 2: JP-A-2003-328708
The conventional valve timing adjusting device is arranged as mentioned above, thus requiring fine manufacturing tolerances or precision and the high cost of production to give the tapered shape to the lock pin and the engaging cavity. Moreover, there is a problem that the lock pin is accidentally released from the engaging cavity by the component force of the alternative force of the cam to produce slapping sounds.
The present invention has been accomplished to solve the above-mentioned problem. An object of the present invention is to provide a valve timing adjusting device capable of suppressing the accidental release of the lock pin from the engaging cavity by a simple configuration and further preventing the occurrence of slapping sounds.


An inflatable board, which can be used for floating or paddling on water, with a thin layer of inelastic material, such as acrylic, bonded between the layers of material forming the top or bottom surfaces of an inflatable board. The thin layer of inelastic material is bonded between the inner material and the outer material. The thin layer of inelastic material is bendable, so that the un-inflated board may be rolled-up for storage or transportation. When inflated, the thin layer of inelastic material bonded between the layers of the top or bottom surfaces of the board increases the rigidity of the board and the board's ability to resist flexing and bending.

1. Field of the Invention
This invention relates to a stiffener for an inflatable water recreation board, such as an inflatable "Stand Up Paddle" ("SUP") board, especially for such a board constructed of drop-stitch material.
2. Background
Inflatable SUP boards are most often used for recreational purposes, such as paddling and catching waves in the ocean and paddling and riding rapids in rivers. Inflatable SUP boards, and inflatable water sports boards in general, are useful, because they are more easily transported than traditional, rigid boards made of fiberglass or hard plastics, insofar as an inflatable board can be deflated, rolled up, and put in a car trunk or even carried by a hiker, whereas traditional boards must be carried on a car's roof rack or schlepped under a surfer's arm or the surfer's head. This advantage has long been recognized in the art, for example in U.S. Pat. No. 2,018,548 to William T. Currey, issued in 1935, for an inflatable "Surf Board", where one of the problems the invention was intended to solve was that the prior art boards could not "be readily collapsed to occupy small space for transportation." Id., at col. 1, lines 22-24, and at col. 1, lines 38-40 (the invention could "be collapsed or inflated as desired, the device when collapsed occupying a relatively small space"). Another long-recognized disadvantage of traditional rigid boards is that, owing to their rigidity, they can injure the user or other nearby persons if the board hits them. See, e.g., U.S. Pat. No. 1,206,696 to Gulbrandsen, issued in 1916, for a "Surf Coaster", at col. 1, lines 19-22. Inflatable boards, which are made of air-tight, rubbery materials, are less likely to cause injury to persons hit by them. Yet another disadvantage of rigid boards, especially when used in riding river rapids, is that they are easily damaged and dinged when they strike a rock. Inflatable boards can absorb and withstand these impacts, usually without any damage.
However, inflatable surfboards have always had a nagging defect, in that they are not rigid and, as a result, tend to bend and distort when used. This defect makes inflatable boards much less desirable, especially when they are used for riding waves or rapids. Various attempts at overcoming this problem have been proposed. For example, U.S. Pat. No. 3,657,753 to Le Blanc., Sr., issued in 1972, for a "Folding Inflatable Surfboard", disclosed an inflatable surfboard that resisted longitudinal bowing by use of a flexible, but substantially non-elastic, convex panel placed over the top surface of the un-inflated board. Id., Abstract. When the board is inflated, the panel is held in a bowed condition, which secures the panel and prevents the board from flexing. Id.
In the years following World War II, efforts were made to develop an inflatable material with increased rigidity and from this work "drop-stitch" construction was created. See, e.g., U.S. Pat. No. 2,753,573 to Barker, issued in 1951, for an "Inflatable Mattress", U.S., Pat. No. 4,251,573 to McCrory et al., issued in 1981, for "Inflatable Boat For High Speed Use". This use of drop-stitch construction was adapted to inflatable rescue boards (see e.g., U.S. Pat. No. 3,775,782 to Rice et al., issued in 1973, for an "Inflatable Aquatic Rescue Board And Method Of Rescue"), and has in recent years found success in inflatable SUP boards. Yet, while drop-stitch construction substantially increases an inflatable board's rigidity when compared to earlier inflatable water craft, the problem has not been fully solved and the flexing problem persists.
What is needed is an inflatable board that overcomes the problem of flexing. More particularly, needed is an inflatable board of drop-stitch construction, which retains the advantages of being easily transported and posing less risk of injury to the user or others, yet provides increased rigidity and a resistance to bowing and flexing.

Stiffener for inflatable drop-stitch stand-up paddle board and method of manufacturing same


The high temperature particle velocity meter is comprised of a pair of spaced apart conducting portions having disposed on each of their upstream edges a first and second non-conducting portion. The bombardment of the particles on the conducting and non-conducting portions creates charged particles in the pneumatically transported material. These particles discharge an electric current through the conducting portions to respective conductors and then to respective signal generating means. The signal generating means convert the electric discharges to an electronic signal. The electronic signals from each of the signal generating means are fed into a calculating means which calculate the particle velocity of the material based on the respective electronic signals. In another embodiment, the device can be used in a ceramic pipeline or a metal pipeline having its inner surface ceramically lined. In this embodiment, the device does not include the non-conducting portions as the pipe is already non-conducting. An associated method is also disclosed for each type of pipeline.

1. Field Of The Invention:
This invention relates to a velocity flow meter and more particularly to an apparatus which measures the velocity of high temperature pneumatically transported solids.
2. Description Of The Prior Art:
An important operation in several industries is the pneumatic transport of solids. A crucial variable in the transportation of solids is the velocity of the particles in the pipeline. The velocity of the particles is needed to calculate energy losses and erosion of the transport lines. The problem is compounded when high temperature solids, such as hot ash products from combustion and coal gasification units, are transported.
A known method of calculating particle velocities is by using estimations from correlations. This involves determination of the terminal velocity of the particle and calculating the particle velocity as the difference between the gas velocity and the terminal velocity. Correlations, which are based on estimates, do not provide accurate actual measurements of particle flow velocities.
It is known to calculate the velocity of a fluid by measuring a property of the fluid at each of two points a known distance apart. See U.S. Pat. Nos. 4,509,366; 3,789,663 and 4,402,230.
It is also known to measure solid matter mass flow by providing an upstream set of electrical devices and a downstream set of electrical devices connected to circuits which provide a measurement of the velocity of the material. U.S. Pat. No. 3,635,082.
U.S. Pat. No. 4,483,199 discloses using radiation sources and detectors to calculate solid mass measurements.
Despite these known devices, there still remains a need for a particle velocity meter which is accurate and reliable and which can be used in association with transporting high temperature solids.

High temperature particle velocity meter and associated method


Methods for injecting charge include providing a target comprising a first layer on a second layer, coupling a conductive base to the second layer, and providing a medium which is in contact with at least a portion of the first layer. An electrode is positioned to face and is spaced from the first layer and is at least partially in contact with the medium. An electric field is provided across the first and second layers to inject charge to an interface between the first layer and the second layer.

Embedded electronic charge technology is utilized in a variety of different types of MEMS devices and applications, such as those disclosed in U.S. Pat. Nos.: 6,597,560; 6,638,627; 6,688,179; 6,717,488; 6,750,590; and 6,773,488 and in U.S. Patent Application Publication Nos.: 2002/0131228; 2002/0182091; 2003/0079543; 2003/0201784; and 2004/0023236 by way of example. Embedded electronic charge technology is also extendable to a variety of applications in the macroscopic realm, such as heel strike power generation or for electrical generation from local environmental sources, such as the wind or waves.
These devices with embedded electronic charge use charge injection to trap charge at an interface of dissimilar insulators. Typically, the charge injection techniques used to embed the charge are high field injection or ballistic injection. High field injection requires a conducting material be placed on each side of the material into which charge is to be injected. The conducting materials on each side must be in substantial alignment with each other and a high voltage is applied across the conducting materials. Ballistic injection requires a ballistic charge source, such as an electron gun, a vacuum chamber, and a device to control energy, dose, and spatial coordinates of the ballistic charge source.
Unfortunately, it is difficult to inject electronic charge over an arbitrarily large surface and likewise to do so as a single step. If high field injection with conducting electrodes is used, a single defect, such as a short, in the material being injected will preclude charge injection. If ballistic injection is used, a very large and hence expensive vacuum chamber is required.

Methods for distributed electrode injection


A lateral flow assay device includes a housing, and a test strip disposed within the housing having a membrane with a detection region and a collection region. A sample meter includes a first end for absorption of a test sample, and a storage section that receives and stores at least a component of the test sample. An opening in the housing is sized for insertion of the sample meter into the housing such that the storage section of the sample meter is disposed adjacent the collection region of the membrane. The test sample component is transferable from the storage section to the collection region for subsequent migration to the detection region. An activatable isolation mechanism is provided within the housing and is disposed so as to isolate portions of the sample meter storage section upon activation thereof such that a defined length of the storage section is presented to the collection region of the membrane.

Test strips are often used for qualitative and quantitative analysis of blood components or other fluids. With the lateral flow method, a spatial separation is defined in the strips between the sample application area and detection zone. Most conventional lateral flow strips are designed for test samples that are readily available in large quantities (e.g., urine). However, when the test sample is blood, the collection of a large sample may cause undue pain to the patient. Thus, one technique that has been utilized to accommodate smaller test sample volumes is to "spot" the sample directly on the membrane surface of the test strip. Thereafter, a diluent is used to wash away the test sample and carry it to the detection zone. Unfortunately, variations associated with sample transfer and diffusion of the sample to the membrane result in a flow that is largely uncontrolled and uneven before reaching the detection zone. This may have an adverse effect on the accuracy of the device because the amount of analyte and/or label captured across the detection zone is not consistent at the time of measurement.
In addition, various tests on blood samples require separation of the red blood cell components from the sample to obtain plasma or serum that is essentially free of red blood cells. The sample can then be used in various assays without interference from red blood cell components. In this regard, filter arrangements have been proposed for production of serum or plasma from whole blood. For example, U.S. Pat. No. 5,423,989 describes a membrane filtering arrangement with a first coarse membrane coated with a fibrous protein and a second fine membrane for removing red blood cells from a test sample.
As such, a need currently exists for a simple and efficient technique for metering and filtering a low volume blood test sample such that a known volume of blood plasma or serum may be easily transferred to a detection zone of a lateral flow assay device.

This patent is subject to a terminal disclaimer.


A climate management system includes a controller configured to receive an input indicative of an airflow rate setpoint for each zone of a plurality of zones of the climate management system. The controller is further configured to determine a respective airflow rate adjustment for each airflow rate setpoint and adjust each airflow rate setpoint based on the respective airflow rate adjustment to determine a respective adjusted airflow rate for each zone of the plurality of zones, where the respective airflow rate adjustment for each zone of the plurality of zones is based on a current annual season of a plurality of annual seasons.

The disclosure relates generally to heating, ventilation, and air conditioning (HVAC) systems, and specifically, to adjusting operations of an HVAC system.
This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present disclosure, which are described below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements are to be read in this light, and not as admissions of prior art.
Environmental control systems are utilized in residential, commercial, and industrial environments to control environmental properties, such as temperature and humidity, for occupants of the respective environments. The environmental control system may control the environmental properties through control of an airflow delivered to and ventilated from the environment. For example, an HVAC system may transfer heat between the airflow and refrigerant flowing through the system and then direct the airflow to areas to be conditioned, such as rooms. It is now recognized that certain operations of the HVAC system may be adjusted, such as based on factors related to the location of the areas to be conditioned, to improve an efficiency of the HVAC system and/or to make the conditioned areas more comfortable to occupants of the areas.


The invention relates to a method and apparatus for controlling video cameras (15, 16) using microphones (10) where the space-time coordinates of a sound event are calculated by first estimating with high precision the time delays of arrival for select microphone pairs, and then applying the Total Least Squares method.

Equipment of this kind can be used in video-teleconferencing systems or in systems for the surveillance of controlled access areas, whether indoors or outdoors. The control of these systems is very complex, owing to the multiplicity of the acoustic signals produced by the environment, background noise and the size of the area controlled, which generally make it impossible for a human operator to distinguish the useful information from the useless.
In an automatic apparatus, the video camera is driven by a sound source location system which works by processing the signals generated by microphones. Many well-known systems use microphone arrays to capture acoustic signals and apply to the sampled signals digital processing methods based on the estimation of the time delay of arrival of the sound wavefront across select microphone pairs (hereinafter also referred to as "time delay" for short) [see C. H. Knapp, G. C. Carter, The generalized correlation method for estimation of time delay, IEEE Transaction on Acoustic Speech and Signal Processing, Bol. ASP-24, No. 4, August 1976].
Known location systems permit estimation of the position of the sound source in space but do not provide any information about the time sequence of the acoustic events. This constitutes a serious shortcoming for systems where it is necessary to reconstruct the order in which events have taken place (for example, requests to speak by participants at a conference).

Method and apparatus for automatically controlling video cameras using microphones


The invention relates to a method of processing messages in a Factory Automation, FA, architecture comprising a FA network comprising at least one device, and an external network, said method being implemented by a network probe and comprising: intercepting (201) a message issued from the external network and intended for a device among the at least one device of the FA network; classifying (202) the message among a predefined set of categories based at least on the device for which the message is intended; deciding (203) to issue an alert based at least on the category in which the message is classified.

The approaches described in this section could be pursued, but are not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated herein, the approaches described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
The Seamless Message Protocol, SLMP, is originally a serial communications protocol developed for use with Programmable Logic Controllers, PLCs, by the applicant. The description of its usage, format and functions are explained in the SLMP Reference Manual published by Mitsubishi Electric that is publicly available online.
This protocol is similar to the ModBUS protocol with similar usage, functions and deployment.
Those protocols enable communications among many industrial devices connected to the same network for management and control purposes.
For example, an industrial system can measure temperature and humidity and can communicate the results to a computer. SLMP as well as ModBUS can be transported over a plurality of underlying network layers such as EIA/TIA-232, EIA/TIA-485 or Ethernet+TCP/IP.
Those industrial management protocols are based on a simple request/response scheme with a maximum message size.
Protocol functions include reading values from discrete inputs/coils (bit-size entities) or registers (16-bit-word entities), writing values to coils and registers, performing diagnoses for the servers and managing running software. After the server receives and processes a request from a client, it sends the corresponding response back to the client. The response can be either a normal response or an error (an exception) response.
The client shall wait for the response before sending a new request.
The data model or description is a very simple set of serial tables, all of them with different features. It allows a simple bit access to different devices located within the PLC such as discrete input and coils (i.e. relay), or 16-bit word access to input and internal registers.
The addressing model used to access the different devices is also very simple and generally consists in a fixed range of addresses to access the different serial tables.
However, these protocols were not initially designed with cyber-security issues. Therefore, they lack security mechanisms to avoid the well-known information security threats. For instance, these protocols do not include a way of ciphering the traffic, checking the integrity of messages and authenticating client and server.
The new generation of industrial systems (Industry 4.0 concept) will require connecting more and more the Factory Automation, FA, networks to external Information Technology (IT) networks and cloud servers, enforcing the risk of cyber-attacks. Indeed, an attacker may try to penetrate the Control and Field-Bus levels of the FA network to obtain confidential information, make disruption in the factory process, make some data unavailable for operators, returns some fake information to operators, etc.
As originally introduced, the communication used for FA management and control relies on unsecured protocols that may be directly varied over TCP or UDP.
Therefore an attacker is likely to compromise:                Confidentiality since the traffic goes clear over the network;        Integrity because it is currently impossible to know if the original message has been changed throughout the communication links; and/or        Availability due to the possibility for the attacker to use crafted packets or to reuse legitimated packets to consume either network resources, client resources or server resources (for example resetting TCP connections, performing flooding attacks, etc).
A simple FA network architecture may comprise an IT-Ethernet-based network connected to a FA network (at the control level and field bus) via a Relay Station acting as an interface between the IT protocols (Ethernet, TCP/IP) and the FA network protocols.
Sometimes, a PLC device may directly integrate the Ethernet standard to directly communication with IT devices, without transiting through the Relay Station.
In such architecture, an attacker may compromise one station of the FA network that is connected to the IT network, and may try to send malicious commands to some PLC located in the FA network, making damages on a robot connected to the fieldbus and controlled by the attacked PLC.
As explained above, application protocols such as SLMP and ModBUS used for management and control of FA networks do not include any security mechanisms.
Because of the evolution of the FA network topologies, they are now intensively used over standard communication layers such as TCP, or UDP and Ethernet, and are more and more used over IT communication network inter-connected to FA network.
Some attackers are able to compromise FA networks, which results in some potential major disruption in the FA installation and in the production lines.
There is therefore a need for an efficient attack detection method that is able to detect malicious messages emitted by some compromised IT devices towards the FA network over the (Ethernet) IT network.
Some methods according to the prior art were developed to detect potential intrusion tentative within the FA network.
Some of them consist in using a model-based approach for detecting intrusions. The basic idea is to construct models that characterize the expected/acceptable behaviour of the different communicating entities of FA network architecture. This approach detects attacks that cause the system to behave outside of the constructed models, and is applicable for attacks on the FA management protocols, on the Operating System OS platforms and on the networking infrastructure.
Unlike a signature-based approach, an advantage of the model-based approach is the possibility to detect unknown attacks. It is particularly well adapted to FA networks since there are few examples of attacks that are publicly known.
Anomalous activity such as flooding based Denial-of-Service, DoS, attack, is generally accompanied by a change in the statistical properties of the parameters indicating the anomaly (for example, the rate of received requests).
Hence, the problem of detecting such anomalous activities can be considered as a change detection problem with the aim to detect changes in the observed parameters with minimal delay and minimal false detection rate.
Different methods have been proposed and are often used to detect sharp changes: moving average, cumulative sum, spectral analysis, etc.
Signature detection methods are used to detect known attacks but they require knowing instances of attacks in advance and their corresponding traffic traces or features. These methods can detect byte sequences that aim to exploit vulnerabilities in running software. They are widely used by antivirus software deployed in IT systems.
As an alternative, they can also be used to efficiently detect legitimate traffic. When applied to industrial management protocols, the signature detection methods may be able to detect read or write request access to some particular resources, and to trigger alarms when they are issued from an unusual or non-trusty station.
However, an efficient and applicable detection method cannot rely only on signature attack detection methods since very few examples of FA attacks are known, and network traffic traces and features are not available.
In addition, attacks are designed for some specific FA deployments and particular network architectures: considering the diversity of FA applications and network topologies, building a relevant signature database is a very hard task and is quite difficult to maintain up-to-date.
Thus, there are needs for implementing a security policy that overcomes at least some of the above mentioned shortcomings.

Network probe and method of processing message


Disclosed is a negative type photosensitive resin composition comprising (A) a polyamide having a photopolymerizable unsaturated double bond, (B) a monomer having a photopolymerizable unsaturated double bond, (C) a photopolymerization initiator and (D) a melamine resin.

Hitherto, polyimide resins having all of excellent heat resistance, electric characteristics and mechanical characteristics have been used for passivation films, surface protective films and layer insulation films in insulation materials of electronic parts and semiconductor devices. Of these polyimide resins, in the case of those which are used in the form of negative type photosensitive polyimide precursor compositions, heat resistant relief pattern films can be easily formed by coating them and subjecting the coating to exposure, development and hot imidation. Such negative type photosensitive polyimide precursor compositions have the advantage that the steps involved can be considerably shortened as compared with when conventional non-sensitive polyimides are used.
However, when the above negative type photosensitive polyimide precursor compositions are used, it is necessary to use organic solvents such as pyrrolidones and ketones in a large amount as developers in the developing step, and it is required not to use organic solvents from the points of view of safety and recent growing interest in environmental protection. Under the circumstances, various proposals for heat resistant photosensitive resin materials which can be developed with a dilute aqueous alkali solution, as well as photo resists, have recently been made in the above-mentioned fields of materials.
Among them, the utilization of a hydroxypolyamide soluble in an aqueous alkali solution, for example, polybenzoxazole precursors, has recently been made. As these methods, there are known a method of using a positive type photosensitive material formed by mixing a polybenzoxazole precursor and a photoactive component such as quinonediazide (JP-B-1-46862, JP-A-63-96162, etc.), a method of using a negative type photosensitive material prepared by introducing a photopolymerizable unsaturated double bond-containing group into a part of phenolic hydroxyl groups of a polybenzoxazole precursor, followed by mixing with a monomer having a photopolymerizable unsaturated double bond, a photopolymerization initiator and the like (JP-A-2002-12665), and others.
In the case of a negative type photosensitive material, a resin having a photopolymerizable unsaturated double bond or the like is polymerized by irradiation with light and as a result, becomes insoluble in the developer. On the other hand, in the case of a positive type photosensitive material, a resin which is lower in solubility in the developer due to the interaction with a mixed photoactive component becomes soluble in the developer due to the decomposition of the photoactive component caused by irradiation with light. Therefore, when a resin is used as a negative type photosensitive material, in which the difference in solubility in the developer between the light irradiated part and the light non-irradiated part can be made greater, process margins can be made much broader than when it is used as a positive photosensitive material, and hence the relief pattern can be easily formed after development. Moreover, in general, the negative photosensitive materials are higher than the positive photosensitive materials in the storage stability of the composition.
Furthermore, since a polybenzoxazole film has similar thermosetting characteristics to those of a polyimide film, a negative type photosensitive polybenzoxazole precursor which can be developed with a dilute aqueous alkali solution is expected to be a promising substitute material for a organic solvent developing type negative type photosensitive polyimide precursor.
On the other hand, there are various changes in the method of packaging a semiconductor device in which the above materials are used. Recently, from the viewpoints of improvement of integration and function, and miniaturization of chip size, there is a marked tendency to use a multilayer interconnection package, and the conditions to which the polyimide film or polybenzoxazole film is exposed during the process of formation of the structures are further diversified. Therefore, the semiconductor materials are required to have higher chemical resistance to strong acids and strong bases.
Moreover, for the same reasons, the method for mounting semiconductor devices on print wiring substrates is changing from the conventional mounting method using a metal pin and a lead-tin eutectic solder to the methods in which a polyimide film or polybenzoxazole film of the semiconductor devices directly contacts with solder bumps, such as BGA (ball grid array) and CSP (chip size packaging) according to which a higher density mounting can be attained. The solders used are also being changed to those of high melting point free from lead for the purpose of reduction of environmental load, and furthermore the solders for bumps are generally those which are further higher in melting point than those for mounting on substrates.
That is, the polyimide films or polybenzoxazole films of semiconductor devices are exposed to unexpectedly high temperatures while contacting with flux at the reflow step of solder bumps, and hence they are required to have higher heat resistance and high-temperature flux resistance.
An object of the present invention is to provide a method for forming on a substrate a relief pattern having conspicuously high heat resistance and chemical resistance after curing with heating and a negative type photosensitive resin composition of high efficiency used for the above method. Another object is to provide a method for producing semiconductor devices using the above method or the above negative type photosensitive resin composition.

Highly heat-resistant, negative-type photosensitive resin composition


The present invention relates to a organopolysiloxane graft polymer including an organopolysiloxane segment as a main chain thereof and an unsaturated monomer-derived polymer segment as a side chain thereof, in which the unsaturated monomer-derived polymer segment contains a repeating unit derived from N,N-dimethyl acrylamide in an amount of not less than 50% by mass and not more than 100% by mass, and a content of the organopolysiloxane segment in the organopolysiloxane graft polymer is not less than 10% by mass and not more than 70% by mass.

Organopolysiloxanes have various excellent characteristics. Therefore, the organosiloxanes of various configurations have been used as a touch improver or the like which may be compounded in shampoos, hair conditioners, etc.
For example, Patent Literature 1 discloses a polyacryl-modified organopolysiloxane that is capable of imparting excellent gloss, luster and a feeling of smoothness to hair without stickiness and exhibiting a good hair style retentivity, and is free from accumulation on hair even when repeatedly used for a long period of time and any significant problem concerning formulation thereof.
In addition, Patent Literature 2 aims at providing a hairdressing method that is capable of imparting a soft touch and a natural finish feeling to hair, firmly fixing a hair style, maintaining the hair style for a long period of time without change even when exposed to external factors (such as combing of hand or fingers through hair, wind, vibrations, etc.), and further hairdressing the hair again, and discloses such a hairdressing method including the steps of applying a hair cosmetic containing a poly(N-acyl alkylene imine)-modified organopolysiloxane to hair, shaping the hair at a hair temperature of 50° C. or higher, and then cooling the hair to a temperature of lower than 50° C. to fix a style of the hair thus shaped.


A device and method of encrypting a sequence. The method (300) encrypts data (Di) over a sequence of encryption periods (Ti) by generating (315) a sequence of forward encryption keys (GKfi) each associated with a respective encryption period (Ti). Each forward encryption key is generated recursively by applying a forward one way function (FFi−1) to the forward encryption key (GKFi−1) associated with the preceding encryption period (Ti−1). Next the method (300) generates (320) a sequence of reverse encryption keys (GKRi), each associated with a respective encryption period (Ti), each reverse encryption key being generated recursively by applying a reverse one way function (FRi−1) to the reverse encryption key (GKRi+1) associated with the subsequent encryption period (Ti+1). Encrypting (325) the data (Di) for each encryption period (Ti) with a respective forward encryption key (GKFi) and a respective reverse encryption key (GKFi) is then performed.

With the increased bandwidth provided by third generation mobile phone technologies such as CDMA2000 and UMTS, providing secure access control in broadcast schemes for electronic devices incorporating these technologies is an active research area. Examples of broadcasting services include providing highlights of sporting fixtures and recent news, popular music audio and accompanying video tracks, weather and financial market updates, popular soap or comedy TV programs, and even movies. Whilst such content may be broadcast continuously, a subscriber will typically only want to subscribe to some of this content for a correspondingly limited duration or subscription period. The content is encrypted prior to broadcast, and a subscriber must obtain the appropriate decryption key by subscribing using some form of payment in order to access the desired content. Various encryption schemes are known in order to address how to allow access to the encrypted content for different subscribers over different periods.
The conventional group key scheme provides a common decryption key to all members of a subscription group which each want to access the same content, for example a music video. However this scheme has a high key management and transmission overhead as the group of subscribers is often changing, requiring changing the keys of the group and retransmitting the keys to all members of the group when a new user joins/leaves. This is very costly and impractical in a highly dynamic broadcast subscription environment, such as in a wireless network where subscribers will typically only want content of short duration.
Another approach is the Point-to-Point (PTP) protocol in which a server sends an individual copy of the data item for each subscriber. However this requires a separate key for each subscriber and therefore increases the key management and transmission/bandwidth requirements, as well as the broadcast bandwidth requirements.
An intermediate approach is the Group Key (GK) method which forms groups of clients for each data item and assigns a key for the group that remains valid until the group changes. In such a system it is necessary to change the group key every time a user joins or leaves the subscription. For a user leaving the subscription it is necessary to change the GK to prevent the user from accessing the future broadcast content. For a user joining the subscription it is necessary to change the GK to prevent the user from accessing the previous broadcast content. The GK approach performs well when the groups do not change very often, however in applications where there are a large number of users and frequent additions or deletions to the group membership this key management scheme can introduce a significant management and communication burden. Broadcasting in a wireless network environment is highly dynamic in terms of subscribers joining and dropping from broadcasts. Furthermore the bandwidth for transmitting keys to subscribers is limited.
The Drop Groups (DG) protocol attempts to address this scalability problem by a grouping criterion which assigns each subscriber to predetermined groups, and assigns each group a group key valid until the group changes. In DG a group of data items are further divided into subgroups using an additional criterion, the time to drop, which is simply the amount of time until a subscriber's subscription for a data item expires. Subscription expirations are bunched together at discrete epochs, however if the minimum epoch length is 1 hour, and a subscriber wants to subscribe to a data item for 2.5 hours, according to DG it must choose to subscribe for either two or three hours.


The present invention discloses a method for administering SN-38-loaded polymeric micelles into the central nervous system of a human subject via a convection-enhanced delivery system. The convection-enhanced delivery is achieved by using an osmotic pump or an infusion pump. Further, SN-38-loaded polymeric micelles are administered into a target region of the brain of the subject.

Malignant brain tumors, such as glioblastoma, remain the most difficult neoplasms to treat despite intensive multimodal treatment including surgical resection, radiation therapy, and systemic chemotherapy. Systemic chemotherapy requires high doses of many anticancer drugs because of poor penetration of the blood-brain barrier (see Groothuis D R. The blood-brain and blood-tumor barriers: a review of strategies for increasing drug delivery. Neuro Oncol. 2000; 2(1):45-59. Also, see Huynh G H, Deen D F, Szoka F C Jr. Barriers to carrier mediated drug and gene delivery to brain tumors. J Control Release. 2006; 110(2):236-259). Consequently, systemic side effects are the limiting factor in chemotherapeutic protocols for patients with brain tumor, and emphasize the need for efficient, specific methods of delivery in the treatment of human glioblastoma.
Convection-enhanced delivery (CED) is a delivery system that circumvents the blood-brain barrier by delivering agents directly into the tumor and surrounding parenchyma based on continuous positive-pressure infusion (see Bobo R H, Laske D W, Akbasak A, Morrison P F, Dedrick R L, Oldfield E H. Convection-enhanced delivery of macromolecules in the brain. Proc Natl Acad Sci USA. 1994; 91(6):2076-2080). CED can achieve large volumes of distribution, as it is driven not only by the diffusive spread derived from concentration gradients, but also by continuous positive-pressure infusion (see Chen M Y, Lonser R R, Morrison P F, Governale L S, Oldfield E H. Variables affecting convection-enhanced delivery to the striatum: a systematic examination of rate of infusion, cannula size, infusate concentration, and tissue-cannula sealing time. J Neurosurg. 1999; 90(2):315-320). Importantly, CED provides direct access to the tumor bed, thus resulting in high local concentrations of drug with minimal systemic absorption (see Yun J, Rothrock R J, Canoll P, Bruce J N. Convection-enhanced delivery for targeted delivery of antiglioma agents: the translational experience. J Drug Deliv. 2013; 2013:107573). Currently, CED has been clinically tested in the treatment of neurodegenerative diseases, such as Parkinson's disease (see Eberling J L, Jagust W J, Christine C W, et al. Results from a phase I safety trial of hAADC gene therapy for Parkinson disease. Neurology. 2008; 70(21):1980-1983. Also, see Gill S S, Patel N K, Hotton G R, et al. Direct brain infusion of glial cell line-derived neurotrophic factor in Parkinson disease. Nat Med. 2003; 9(5):589-595), and neuro-oncology (see Kunwar S. Convection enhanced delivery of IL13-PE38QQR for treatment of recurrent malignant glioma: presentation of interim findings from ongoing phase 1 studies. Acta Neurochir Suppl. 2003; 88:105-111. Also, see Mardor Y, Roth Y, Lidar Z, et al. Monitoring response to convection-enhanced taxol delivery in brain tumor patients using diffusion-weighted magnetic resonance imaging. Cancer Res. 2001; 61(13):4971-4973).

CED of SN-38-loaded micelles against brain tumor