query: Novel DC-DC Multilevel Boost Converter

positive: Multilevel Converters-A New Breed of Power Converters AbstructMultilevel voltage source converters are emerging as a new breed of power converter options for high-power applications. The multilevel voltage source converters typically synthesize the staircase voltage wave from several levels of dc capacitor voltages. One of the major limitations of the multilevel converters is the voltage unbalance between different levels. The techniques to balance the voltage between different levels normally involve voltage clamping or capacitor charge control. There are several ways of implementing voltage balance in multilevel converters. Without considering the traditional magnetic coupled converters, this paper presents three recently developed multilevel voltage source converters: 1) diode-clamp, 2) flyingcapacitors, and 3) cascaded-inverters with separate dc sources. The operating principle, features, constraints, and potential applications of these converters will be discussed.

positive: A generalized multilevel inverter topology with self voltage balancing Multilevel power converters that provide more than two levels of voltage to achieve smoother and less distorted ac-to-dc, dc-to-ac, and dc-to-dc power conversion, have attracted many contributors. This paper presents a generalized multilevel inverter (converter) topology with self voltage balancing. The existing multilevel inverters such as diode-clamped and capacitor-clamped multilevel inverters can be derived from the generalized inverter topology. Moreover, the generalized multilevel inverter topology provides a true multilevel structure that can balance each dc voltage level automatically without any assistance from other circuits, thus, in principle, providing a complete and true multilevel topology that embraces the existing multilevel inverters. From this generalized multilevel inverter topology, several new multilevel inverter structures can be derived. Some application examples of the generalized multilevel converter will be given.

positive: Multilevel Converters as a Utility Interface for Renewable Energy Systems Electric power production in the 21 Century will see dramatic changes in both the physical infrastructure and the control and information infrastructure. A shift will take place from a relatively few large, concentrated generation centers and the transmission of electricity over mostly a high voltage ac grid (Fig. 1) to a more diverse and dispersed generation infrastructure that also has a higher percentage of dc transmission lines (Fig. 2) [1]. In the United States, generation capacity has not kept up with power demands, as over the last decade the reserve margins declined from 22% in 1990 to 16% in 1997. This declining margin trend is expected to continue over the next decade partly because of the uncertainty of how the future deregulated electrical environment will function. Less reserve margins will lead to less peaking capacity on highdemand days and more volatile energy prices [2]. This change in a physical infrastructure combined with a more deregulated electric power industry will result in more parties generating power – or distributed generation. Some of the distributed generation power sources that are expected to increase greatly their market share of the total power produced in the United States and abroad include renewable energy sources such as photovoltaics, wind, low-head hydro, and geothermal [3]. Fuel cell technology is also nearing the development point where it could start to supply a significant share of the power needs [4]. The advent of high power electronic modules has also encouraged the use of more dc transmission and made the prospects of interfacing dc power sources such as fuel cells and photovoltaics more easily attainable. A modular, scalable power electronics technology that is ideal for these types of utility applications is the transformerless multilevel converter [5].

positive: Cascaded DC-DC converter connection of photovoltaic modules New residential scale photovoltaic (PV) arrays are commonly connected to the grid by a single dc-ac inverter connected to a series string of pv panels, or many small dc-ac inverters which connect one or two panels directly to the ac grid. This paper proposes an alternative topology of nonisolated per-panel dc-dc converters connected in series to create a high voltage string connected to a simplified dc-ac inverter. This offers the advantages of a "converter-per-panel" approach without the cost or efficiency penalties of individual dc-ac grid connected inverters. Buck, boost, buck-boost, and Cu/spl acute/k converters are considered as possible dc-dc converters that can be cascaded. Matlab simulations are used to compare the efficiency of each topology as well as evaluating the benefits of increasing cost and complexity. The buck and then boost converters are shown to be the most efficient topologies for a given cost, with the buck best suited for long strings and the boost for short strings. While flexible in voltage ranges, buck-boost, and Cu/spl acute/k converters are always at an efficiency or alternatively cost disadvantage.

positive: Multilevel inverters: a survey of topologies, controls, and applications Multilevel inverter technology has emerged recently as a very important alternative in the area of high-power medium-voltage energy control. This paper presents the most important topologies like diode-clamped inverter (neutral-point clamped), capacitor-clamped (flying capacitor), and cascaded multicell with separate dc sources. Emerging topologies like asymmetric hybrid cells and soft-switched multilevel inverters are also discussed. This paper also presents the most relevant control and modulation methods developed for this family of converters: multilevel sinusoidal pulsewidth modulation, multilevel selective harmonic elimination, and space-vector modulation. Special attention is dedicated to the latest and more relevant applications of these converters such as laminators, conveyor belts, and unified power-flow controllers. The need of an active front end at the input side for those inverters supplying regenerative loads is also discussed, and the circuit topology options are also presented. Finally, the peripherally developing areas such as high-voltage high-power devices and optical sensors and other opportunities for future development are addressed.

negative: An FPGA-based AES-CCM Crypto Core For IEEE 802.11i Architecture The widespread adoption of IEEE 802.11 wireless networks has brought its security paradigm under active research. One of the important research areas in this field is the realization of fast and secure implementations of cryptographic algorithms. Under this work, such an implementation has been done for Advanced Encryption Standard (AES) on fast, efficient and low power Field Programmable Gate Arrays (FPGAs) whereby computational intensive cryptographic processes are offloaded from the main processor thus results in achieving highspeed secure wireless connectivity. The dedicated resources of Spartan-3 FPGAs have been effectively utilized to develop wider logic function which minimizes the critical paths by confining logic to single Configurable Logic Block (CLB), thus improving the performance, density and power consumption of the design. The resultant design consumes only 4 Block RAMs and 487 Slices to fit both AES cores and its key scheduling.

negative: Learning an Intrinsic Image Decomposer Using Synthesized RGB-D Dataset Intrinsic image decomposition refers to recover the albedo and shading from images, which is an ill-posed problem in signal processing. As realistic labeled data are severely lacking, it is difficult to apply learning methods in this issue. In this letter, we propose using a synthesized dataset to facilitate the solving of this problem. A physically based renderer is used to generate color images and their underlying ground-truth albedo and shading from three-dimensional models. Additionally, we render a Kinect-like noisy depth map for each instance. We utilize this synthetic dataset to train a deep neural network for intrinsic image decomposition and further fine-tune it for real-world images. Our model supports both RGB and RGB-D as input, and it employs both high-level and low-level features to avoid blurry outputs. Experimental results verify the effectiveness of our model on realistic images.

negative: Survey: Finite-state technology in natural language processing In this survey, we will discuss current uses of finite-state information in several statistical natural language processing tasks. To this end, we will review standard approaches in tokenization, part-of-speech tagging, and parsing, and illustrate the utility of finite-state information and technology in these areas. The particular problems were chosen to allow a natural progression from simple prediction to structured prediction. We aim for a sufficiently formal presentation suitable for readers with a background in automata theory that allows to appreciate the contribution of finite-state approaches, but we will not discuss practical issues outside the core ideas. We provide instructive examples and pointers into the relevant literature for all constructions. We close with an outlook on finite-state technology in statistical machine translation.

negative: Design and performance analysis of a high-speed air-cored axial-flux permanent-magnet generator with circular magnets and coils Air-cored, axial flux permanent-magnet (AFPM) machines have magnetic and mechanical characteristics considered to be ideal for compact high speed electric power generation applications. To date, research on high speed AFPM machines is primarily from a mechanical perspective, with emphasis on higher power level applications such as in hybrid vehicles. Recently, there has been an increasing interest in man-portable mobile power sources with a power envelope of around 1kW, for mission critical applications. In this paper, a high speed air-cored surface mounted AFPM machine with circular magnets and coils is proposed. Comprehensive theoretical analysis and three-dimensional (3-D) electromagnetic finite element analysis (FEA) are developed to evaluate the performance of the machine. In addition, the rotor's mechanical stresses developed by high rotational speed are evaluated to ensure mechanical integrity. Finally, a prototype machine is developed for validation. Both the experimental and predicted results demonstrate that the proposed generator possesses distinct advantages over other systems, such as high efficiency, high power factor, and a simple and robust structure that offers a high degree of technology readiness.

negative: PeerFlow: Secure Load Balancing in Tor We present PeerFlow, a system to securely load balance client traffic in Tor. Security in Tor requires that no adversary handle too much traffic. However, Tor relays are run by volunteers who cannot be trusted to report the relay bandwidths, which Tor clients use for load balancing. We show that existing methods to determine the bandwidths of Tor relays allow an adversary with little bandwidth to attack large amounts of client traffic. These methods include Tor’s current bandwidthscanning system, TorFlow, and the peer-measurement system EigenSpeed. We present an improved design called PeerFlow that uses a peer-measurement process both to limit an adversary’s ability to increase his measured bandwidth and to improve accuracy. We show our system to be secure, fast, and efficient. We implement PeerFlow in Tor and demonstrate its speed and accuracy in large-scale network simulations.

negative: Sentiment Analysis on Twitter Data Abstract – Now-a-days social networking sites are at the boom, so large amount of data is generated. Millions of people are sharing their views daily on micro blogging sites, since it contains short and simple expressions. In this paper, we will discuss about a paradigm to extract the sentiment from a famous micro blogging service, Twitter, where users post their opinions for everything. In this paper, we will discuss the existing analysis of twitter dataset with data mining approach such as use of Sentiment analysis algorithm using machine learning algorithms. An approach is introduced that automatically classifies the sentiments of Tweets taken from Twitter dataset as in [1]. These messages or tweets are classified as positive, negative or neutral with respect to a query term. This is very useful for the companies who want to know the feedback about their product brands or the customers who want to search the opinion from others about product before purchase. We will use machine learning algorithms for classifying the sentiment of Twitter messages using distant supervision which is discussed in [8]. The training data consists of Twitter messages with emoticons, acronyms which are used as noisy labels discussed in [4]. We examine sentiment analysis on Twitter data. The contributions of this survey paper are: (1) we use Parts Of Speech (POS)-specific prior polarity features. (2) We also use a tree kernel to prevent the need for monotonous feature engineering.

negative: Arrhythmia Identification with Two-Lead Electrocardiograms Using Artificial Neural Networks and Support Vector Machines for a Portable ECG Monitor System An automatic configuration that can detect the position of R-waves, classify the normal sinus rhythm (NSR) and other four arrhythmic types from the continuous ECG signals obtained from the MIT-BIH arrhythmia database is proposed. In this configuration, a support vector machine (SVM) was used to detect and mark the ECG heartbeats with raw signals and differential signals of a lead ECG. An algorithm based on the extracted markers segments waveforms of Lead II and V1 of the ECG as the pattern classification features. A self-constructing neural fuzzy inference network (SoNFIN) was used to classify NSR and four arrhythmia types, including premature ventricular contraction (PVC), premature atrium contraction (PAC), left bundle branch block (LBBB), and right bundle branch block (RBBB). In a real scenario, the classification results show the accuracy achieved is 96.4%. This performance is suitable for a portable ECG monitor system for home care purposes.

negative: Implementation of a Cognitive Radio Front-End Using Rotatable Controlled Reconfigurable Antennas This communication presents a new antenna system designed for cognitive radio applications. The antenna structure consists of a UWB antenna and a frequency reconfigurable antenna system. The UWB antenna scans the channel to discover “white space” frequency bands while tuning the reconfigurable section to communicate within these bands. The frequency agility is achieved via a rotational motion of the antenna patch. The rotation is controlled by a stepper motor mounted on the back of the antenna structure. The motor's rotational motion is controlled by LABVIEW on a computer connected to the motor through its parallel port. The computer's parallel port is connected to a NPN Darlington array that is used to drive the stepper motor. The antenna has been simulated with the driving motor being taken into consideration. A good agreement is found between the simulated and the measured antenna radiation properties.

negative: A new ultra-wideband, ultra-short monocycle pulse generator with reduced ringing We introduce a new ultra-wideband (UWB), ultra-short, step recovery diode monocycle pulse generator. This pulse generator uses a simple RC high-pass filter as a differentiator to generate the monocycle pulse directly. The pulse-shaping network employs a resistive circuit to achieve UWB matching and substantial removal of the pulse ringing, and rectifying and switching diodes to further suppress the ringing. An ultra-short monocycle pulse of 300-ps pulse duration, -17-dB ringing level, and good symmetry has been demonstrated. Good agreement between the measured and calculated results was achieved.

negative: EEHC: Energy efficient heterogeneous clustered scheme for wireless sensor networks In recent years, there has been a growing interest in wireless sensor networks. One of the major issues in wireless sensor network is developing an energy-efficient clustering protocol. Hierarchical clustering algorithms are very important in increasing the network’s life time. Each clustering algorithm is composed of two phases, the setup phase and steady state phase. The hot point in these algorithms is the cluster head selection. In this paper, we study the impact of heterogeneity of nodes in terms of their energy in wireless sensor networks that are hierarchically clustered. We assume that a percentage of the population of sensor nodes is equipped with the additional energy resources. We also assume that the sensor nodes are randomly distributed and are not mobile, the coordinates of the sink and the dimensions of the sensor field are known. Homogeneous clustering protocols assume that all the sensor nodes are equipped with the same amount of energy and as a result, they cannot take the advantage of the presence of node heterogeneity. Adapting this approach, we introduce an energy efficient heterogeneous clustered scheme for wireless sensor networks based on weighted election probabilities of each node to become a cluster head according to the residual energy in each node. Finally, the simulation results demonstrate that our proposed heterogeneous clustering approach is more effective in prolonging the network lifetime compared with LEACH. 2008 Elsevier B.V. All rights reserved.

negative: Online Adaptive Passive-Aggressive Methods for Non-Negative Matrix Factorization and Its Applications This paper aims to investigate efficient and scalable machine learning algorithms for resolving Non-negative Matrix Factorization (NMF), which is important for many real-world applications, particularly for collaborative filtering and recommender systems. Unlike traditional batch learning methods, a recently proposed online learning technique named "NN-PA" tackles NMF by applying the popular Passive-Aggressive (PA) online learning, and found promising results. Despite its simplicity and high efficiency, NN-PA falls short in at least two critical limitations: (i) it only exploits the first-order information and thus may converge slowly especially at the beginning of online learning tasks; (ii) it is sensitive to some key parameters which are often difficult to be tuned manually, particularly in a practical online learning system. In this work, we present a novel family of online Adaptive Passive-Aggressive (APA) learning algorithms for NMF, named "NN-APA", which overcomes two critical limitations of NN-PA by (i) exploiting second-order information to enhance PA in making more informative updates at each iteration; and (ii) achieving the parameter auto-selection by exploring the idea of online learning with expert advice in deciding the optimal combination of the key parameters in NMF. We theoretically analyze the regret bounds of the proposed method and show its advantage over the state-of-the-art NN-PA method, and further validate the efficacy and scalability of the proposed technique through an extensive set of experiments on a variety of large-scale real recommender systems datasets.

negative: Network-based wireless location: challenges faced in developing techniques for accurate wireless location information Wireless location refers to the geographic coordinates of a mobile subscriber in cellular or wireless local area network (WLAN) environments. Wireless location finding has emerged as an essential public safety feature of cellular systems in response to an order issued by the Federal Communications Commission (FCC) in 1996. The FCC mandate aims to solve a serious public safety problem caused by the fact that, at present, a large proportion of all 911 calls originate from mobile phones, the location of which cannot be determined with the existing technology. However, many difficulties intrinsic to the wireless environment make meeting the FCC objective challenging. These challenges include channel fading, low signal-to-noise ratios (SNRs), multiuser interference, and multipath conditions. In addition to emergency services, there are many other applications for wireless location technology, including monitoring and tracking for security reasons, location sensitive billing, fraud protection, asset tracking, fleet management, intelligent transportation systems, mobile yellow pages, and even cellular system design and management. This article provides an overview of wireless location challenges and techniques with a special focus on network-based technologies and applications.

negative: Microstrip Antennas Microstrip antennas have been one of the niost innovative topics in antenna theory and design in recent years, and are increasingly finding application in a wide range of modern microwave systems. This paper begins with a brief overview of the basic characteristics of microstrip antennas, and then concentrates on the most significant developments in microstrip antenna technology that have been made in the last several years. Emphasis is on new antenna configurations for improved electrical performance and manufacturability, and advances in the analytical modeling of microstrip antennas and arrays.

negative: Environmental impacts of polyvinyl chloride (PVC) production process The increasing demand for plastics in the world leads to pressures on the environment generated by the consumption of raw materials based on fossil fuels and the need for plastic waste reduction and absorption to diminish their environmental impacts. In this paper we evaluated the environmental impacts induced by the production of polyvinyl chloride (PVC), one of the most widely used plastics in the manufacture of various goods. The impacts were calculated based on Life Cycle Assessment methodology. The negative environmental impacts of PVC production may be reduced by recycling, a sustainable, effective, currently available alternative of waste management. Our study showed that the use of recyclable materials, such as organic biodegradable waste as raw materials instead of crude oil can lead to significant reduction of environmental impacts.

negative: On Networking of Internet of Things: Explorations and Challenges Internet of Things (IoT), as the trend of future networks, begins to be used in many aspects of daily life. It is of great significance to recognize the networking problem behind developing IoT. In this paper, we first analyze and point out the key problem of IoT from the perspective of networking: how to interconnect large-scale heterogeneous network elements and exchange data efficiently. Combining our on-going works, we present some research progresses on three main aspects: 1) the basic model of IoT architecture; 2) the internetworking model; and 3) the sensor-networking mode. Finally, we discuss two remaining challenges in this area.

negative: A Systematic Review of Service Level Management in the Cloud Cloud computing make it possible to flexibly procure, scale, and release computational resources on demand in response to workload changes. Stakeholders in business and academia are increasingly exploring cloud deployment options for their critical applications. One open problem is that service level agreements (SLAs) in the cloud ecosystem are yet to mature to a state where critical applications can be reliably deployed in clouds. This article systematically surveys the landscape of SLA-based cloud research to understand the state of the art and identify open problems. The survey is particularly aimed at the resource allocation phase of the SLA life cycle while highlighting implications on other phases. Results indicate that (i) minimal number of SLA parameters are accounted for in most studies; (ii) heuristics, policies, and optimisation are the most commonly used techniques for resource allocation; and (iii) the monitor-analysis-plan-execute (MAPE) architecture style is predominant in autonomic cloud systems. The results contribute to the fundamentals of engineering cloud SLA and their autonomic management, motivating further research and industrial-oriented solutions.

negative: Logo Retrieval Using Logo Proposals and Adaptive Weighted Pooling This letter presents a novel approach for logo retrieval. Considering the fact that logo only occupies a small portion of an image, we apply Faster R-CNN to detect logo proposals first, and then use a two-step pooling strategy with adaptive weight to obtain an accurate global signature. The adaptive weighted pooling method can effectively balance the recall and precision of proposals by incorporating the probability of each proposal being a logo. Experimental results show that the proposed method interprets the similarity between query and database image more accurately and achieves state of the art performance.

negative: Monolithically Integrated Si Photonics Transmitters in 0.25 um BiCMOS Platform for High-Speed Optical Communications Monolithically integrated electro-optical transmitters fabricated in a 0.25 μm SiGe:C BiCMOS electronic-photonic integrated circuit (EPIC) technology with fT =190 GHz are presented. The modules are based on the co-design and integration of a segmented depletion-type Si Mach-Zehnder modulator and multichannel driver amplifiers. Two driving approaches and their performance trade-offs are discussed: a linear one, with direct interface to an external digital-to-analog converter (DAC), as well as a more power efficient implementation featuring integrated 4-bit DAC functionality. High extinction ratios at high speed are demonstrated, enabled by the high breakdown voltages of the HBT transistors. The modules support several modulation formats among which pulse-amplitude-modulation (PAM)−4 eye diagrams up to 37 GBd are shown, for the first time.

negative: IT Outsourcing Strategies: Universalistic, Contingency, and Configurational Explanations of Success F on individual outsourcing decisions in IT research has often yielded contradictory findings and recommendations. To address these contradictions, we investigate a holistic, configurational approach with the prevailing universalistic or contingency perspectives in exploring the effects of IT outsourcing strategies on outsourcing success. Based on residual rights theory, we begin by identifying three dimensions of IT outsourcing strategies: degree of integration, allocation of control, and performance period. We then develop a model of fit-as-gestalt, drawing from literatures on strategy, governance, interorganizational relationships, and outsourcing. Next, based on data from 311 firms in South Korea, we test universalistic and contingency perspectives in explaining the relationship between IT outsourcing strategies and outsourcing success. We then identify three congruent patterns, or gestalts, of IT outsourcing strategies. We term these strategies independent, arm’s-length, and embedded strategies. To establish the predictive validity of these gestalts and the viability of a configurational perspective, we then explore the effects of these congruent gestalts vis-à-vis noncongruent patterns on three dimensions of outsourcing success: strategic competence, cost efficiency, and technology catalysis. We also contrast the effects of each of the three gestalts on each of the three dimensions of outsourcing success. Our findings indicate the superiority of the configurational approach over universalistic and contingency perspectives in explaining outsourcing success.

negative: An ontology for representing financial headline news This paper presents the development of an ontology to represent financial headline news. This ontology is developed using the On-To-Knowledge methodology where the focus is on the design steps of the Knowledge Meta Process. This development is part of an ongoing project which aims to design a virtual stock market simulator based on multi-agent systems. The proposed ontology has 31 concepts and includes 201 attributes. The testing results conducted on reliable headline news show that 99% of these headline news can be properly represented by the attributes of the right category in the ontology. Unreliable headline news characterized by news having uncertainties, incompleteness, ill-definition, or imprecision cannot be represented by the proposed ontology. Approaches for representing these unreliable headline

negative: The real-time video stabilization for the rescue robot When rescue robots navigate in a rough terrain, significant vibration of the video occurs unavoidably and a video stabilization system is proposed in this paper to reduce the disturbance on the visual system of the present rescue robots. The Kalman filter is applied to estimate the motion vector of the robot and the false estimation occurrence can be thus greatly reduced by applying analysis of correlation and variance of the motion vector estimation. With a hierarchical searching algorithm implemented on the TI DSP 6437, the frame rate can be improved from 10 fps to 28 fps to realize the real-time video stabilization and furthermore, the cooperative mission of multiple rescue robots has been achieved by applying the developed visual servo technique. The proposed virtual bounded motion control algorithm further leads the robots approaching the target precisely with cooperation of multiple rescue robots. The demo video is available at: http://lab816.cn.nctu.edu.tw/DemoVideo/. video stabilization

negative: Bridging Nonlinearities and Stochastic Regularizers with Gaussian Error Linear Units We propose the Gaussian Error Linear Unit (GELU), a high-performing neural network activation function. The GELU nonlinearity is the expected transformation of a stochastic regularizer which randomly applies the identity or zero map, combining the intuitions of dropout and zoneout while respecting neuron values. This connection suggests a new probabilistic understanding of nonlinearities. We perform an empirical evaluation of the GELU nonlinearity against the ReLU and ELU activations and find performance improvements across all tasks.

negative: Device-to-Device Communication Underlaying a Finite Cellular Network Region Underlay in-band device-to-device (D2D) communication can improve the spectrum efficiency of cellular networks. However, the coexistence of D2D and cellular users causes inter-cell and intra-cell interference. The former can be effectively managed through inter-cell interference coordination and, therefore, is not considered in this paper. Instead, we focus on the intra-cell interference and propose a D2D mode selection scheme to manage it inside a finite cellular network region. The potential D2D users are controlled by the base station (BS) to operate in D2D mode based on the average interference generated to the BS. Using stochastic geometry, we study the outage probability experienced at the BS and a D2D receiver, and spectrum reuse ratio, which quantifies the average fraction of successfully transmitting D2D users. The analysis shows that the outage probability at the D2D receiver varies for different locations. In addition, without impairing the performance at the BS, if the path-loss exponent on the cellular link is slightly lower than that on the D2D link, the spectrum reuse ratio can have negligible decrease, while the D2D users’ average number of successful transmissions increases with increasing D2D node density. This indicates that an increasing level of D2D communication can be beneficial in future networks.

negative: BLAT--the BLAST-like alignment tool. Analyzing vertebrate genomes requires rapid mRNA/DNA and cross-species protein alignments. A new tool, BLAT, is more accurate and 500 times faster than popular existing tools for mRNA/DNA alignments and 50 times faster for protein alignments at sensitivity settings typically used when comparing vertebrate sequences. BLAT's speed stems from an index of all nonoverlapping K-mers in the genome. This index fits inside the RAM of inexpensive computers, and need only be computed once for each genome assembly. BLAT has several major stages. It uses the index to find regions in the genome likely to be homologous to the query sequence. It performs an alignment between homologous regions. It stitches together these aligned regions (often exons) into larger alignments (typically genes). Finally, BLAT revisits small internal exons possibly missed at the first stage and adjusts large gap boundaries that have canonical splice sites where feasible. This paper describes how BLAT was optimized. Effects on speed and sensitivity are explored for various K-mer sizes, mismatch schemes, and number of required index matches. BLAT is compared with other alignment programs on various test sets and then used in several genome-wide applications. http://genome.ucsc.edu hosts a web-based BLAT server for the human genome.

negative: Accelerator-centric deep learning systems for enhanced scalability, energy-efficiency, and programmability Deep learning (DL) has been successfully deployed in various application domains ranging from computer vision, speech recognition, to natural language processing. As the network models and the datasets used to train these models scale, system architects are faced with new challenges in designing a scalable and energy-efficient high-performance computing (HPC) system for training DL algorithms. One of the key obstacles that DL researchers are facing is the memory capacity bottleneck, where the limited physical memory size of the PCIe-attached DL accelerator (whether it be a discrete GPU or ASIC accelerator like Google's Tensor Processing Unit) constrains the algorithm that can be studied. In this paper, and the associated invited special session talk, we first discuss recent research literature geared towards designing scalable HPC systems for DL. In this context, we then discuss the memory capacity wall problem and introduce the work on virtualized deep neural networks, a memory virtualization solution that systematically reduces the memory consumption of DNN training. We conclude by providing projections on future challenges DNN memory virtualization will encounter upon and suggest accelerator-centric DL system as a promising research direction for the development of a scalable and energy-efficient deep learning system architecture.

negative: Multilevel single-phase inverter based on TNPC-type A new single-phase 7-level pulse-width modulation (PWM) inverter using T-type Neutral-point-clamped (TNPC) celIs is presented to obtain high quality output voltage minimizing the number of switching devices. It includes two TNPC cells series-connected together and connected to with different voltage levels. To avoid inherent problems caused by voltage unbalance, modified Buck-boost converters are added at DC-link side to make DC voltage sources for the proposed inverter. Operational principles and the switching pattern are analyzed in this paper. To verify the performance of the proposed inverter, PSIM simulation and experimental results are also shown in this paper.

negative: 10-kV SiC MOSFET-Based Boost Converter 10-kV silicon carbide (SiC) MOSFETs are currently being developed by a number of organizations in the U.S. with prospective applications in high-voltage and high-frequency power-electronic systems. The aim of this paper is to demonstrate the high-frequency and high-temperature capability of 10-kV SiC MOSFETs in the application of a dc/dc boost converter. In this study, 10-kV SiC MOSFET and junction barrier Schottky (JBS) diode were characterized and modeled in SPICE. Following this, a dc/dc boost converter based on a 10-kV 10-A MOSFET and a 10-kV 5-A JBS diode was designed and tested under continuous operation for frequencies up to 25 kHz. The boost converter had an output voltage of 4 kV, an output power of 4 kW, and operated with a junction temperature of 174degC for the SiC MOSFET. The fast-switching speed, low losses, and high-temperature operation capability of 10-kV SiC MOSFETs demonstrated in the dc/dc boost converter make them attractive for high-frequency and high-voltage power-conversion applications.

negative: Modulation, control and capacitor voltage balancing of alternate arm modular multilevel converter with DC fault blocking capability This paper provides an overview of DC side fault tolerance issues of VSC based HVDC system and the need for fault tolerant converters. The working principle and DC fault ride through capability of recently introduced Alternate Arm Modular Multilevel Converter(AAMMC) has been discussed. The capacitor voltage balancing issues of AAMMC is analyzed and a novel scheme for balancing capacitor voltages of the wave shaping circuit is presented in this paper. The voltage balancing of capacitors of wave shaping circuits in the arm is done by introducing an overlap period during zero voltage period. Using the proposed scheme, the magnitude and direction of the current during the overlap period can be controlled by varying the switching pattern. It helps in charging or discharging of the submodule capacitors to bring them to their reference value. At the end of the overlap period, the arm current is brought to zero before opening the director switch so as to avoid the spike across the arm inductor. The efficacy of the proposed control scheme has been validated using simulation study done in PSCAD/EMTDC.

negative: Performance Enhancement of Boost Converter Based on PID Controller Plus Linear-to-Nonlinear Translator Here, A PID controller plus a novel linear-to-nonlinear translator is proposed and applied to the boost converter to improve the operating performance of the boost converter under large transient variations in load all over the quiescent dc input voltage range. The proposed translator is inserted between the PID controller and the main power stage such that the PID controller considers the behavior of the boost converter to be quasi-linear, thereby suppressing the effect of nonlinear behavior of the boost converter on the PID controller. Besides, variations in dc gain of the control-to-output transfer function with the translator are smaller than those without the translator, thus making system control easy to attain. Also, one-comparator counter-based sampling without any A-D converter is presented herein to realize the proposed control strategy. As mentioned above, the proposed control strategy can make the boost converter stably operated under large load transient responses all over the quiescent dc input voltage range.

negative: An improved MPPT technique for high gain DC-DC converter using model predictive control for photovoltaic applications This paper presents an enhanced Maximum Power Point Tracking (MPPT) of Photovoltaic (PV) systems by means of Model Predictive Control (MPC) techniques. The PV array can feed power to the load through a DC/DC converter boosting the output voltage. Due to stochastic behavior of solar energy, MPPT control technique of PV arrays is required to operate at maximum power point. Extracting the maximum power from PV systems has been widely investigated within the literature. The main contribution of this paper is enhancement of the Incremental Conductance (INC) method through a fixed step predictive control under measured fast solar radiation variation. The proposed predictive control to achieve Maximum Power Point (MPP) speeds up the control loop since it predicts error before the switching signal is applied to the selected high gain multilevel DC-DC converter. Comparing the developed technique to the conventional INC method shows significant improvement in PV system performance. Experimental validation is presented using the dSpace CP 1103 to implement the proposed MPC-MPPT.

negative: A Nonlinear Controller Based on a Discrete Energy Function for an AC/DC Boost PFC Converter AC/DC converter systems generally have two stages: an input power factor correction (PFC) boost ac/dc stage that converts input ac voltage to an intermediate dc voltage while reducing the input current harmonics injected to the grid, followed by a dc/dc converter that steps up or down the intermediate dc-bus voltage as required by the output load and provides high-frequency galvanic isolation. Since a low-frequency ripple (second harmonic of the input ac line frequency) exists in the output voltage of the PFC ac/dc boost converter due to the power ripple, the voltage loop in the conventional control system must have a very low bandwidth in order to avoid distortions in the input current waveform. This results in the conventional PFC controller having a slow dynamic response against load variations with adverse overshoots and undershoots. This paper presents a new control approach that is based on a novel discrete energy function minimization control law that allows the front-end ac/dc boost PFC converter to operate with faster dynamic response than the conventional controllers and simultaneously maintain near unity input power factor. Experimental results from a 3-kW ac/dc converter built for charging traction battery of a pure electric vehicle are presented in this paper to validate the proposed control method and its superiority over conventional controllers.

negative: Development of DC to Single-Phase AC Voltage Source Inverter With Active Power Decoupling Based on Flying Capacitor DC/DC Converter In the present, a power decoupling method without additional component is proposed for a dc to single-phase ac converter, which consists of a flying capacitor dc/dc converter (FCC) and the voltage source inverter (VSI). In particular, a small flying capacitor in the FCC is used for both a boost operation and a double-line-frequency power ripple reduction. Thus, the dc-link capacitor value can be minimized in order to avoid the use of a large electrolytic capacitor. In addition, component design, of, e.g., the boost inductor and the flying capacitor, is clarified when the proposed control is applied. Experiments were carried out using a 1.5-kW prototype in order to verify the validity of the proposed control. The experimental results revealed that the use of the proposed control reduced the dc-link voltage ripple by 74.5%, and the total harmonic distortion (THD) of the inverter output current was less than 5%. Moreover, a maximum system efficiency of 95.4% was achieved at a load of 1.1 kW. Finally, the high power density design is evaluated by the Pareto front optimization. The power densities of three power decoupling topologies, such as a boost topology, a buck topology, and the proposed topology are compared. As a result, the proposed topology achieves the highest power density (5.3 kW/dm3) among the topologies considered herein.


query: A Ka-band waveguide-based traveling-wave spatial power divider/combiner

positive: A High-Power $Ka$-Band (31–36 GHz) Solid-State Amplifier Based on Low-Loss Corporate Waveguide Combining A method of using low-loss waveguide septum combiners is developed into a high-power -band (31-36 GHz) amplifier producing 50 W at 33 GHz (Ka-band) using 32 low-power (>2 W) solid-state amplifier modules. By using low-loss waveguide combining and a packaged monolithic microwave integrated circuit with a low-loss microstrip-to-waveguide launcher, the output loss is minimized, allowing for the overall power-combining efficiency to remain high, 80% (average insertion loss of combiner < 0.7 dB and average insertion loss of launcher <0.3 dB) over 31-36 GHz. In the past, lower power-combining efficiencies have limited the number of modules that can be combined at -band, and hence, have limited the power output. The approach demonstrated in this paper, with high power-combining efficiency, allows a very large number (32) of solid-state amplifier modules to be combined to produce high powers. Greater than 50 W was demonstrated with low power modules, but even higher powers 120 W are possible. The current approach is based on corporate combining, using low-loss waveguide septum combiners that provide isolation, maintaining the true graceful degradation of a modular solid-state amplifier system.

positive: A Ka-band power amplifier based on the traveling-wave power-dividing/combining slotted-waveguide circuit An eight-device Ka-band solid-state power amplifier has been designed and fabricated using a traveling-wave power-dividing/combining technique. The low-profile slotted-waveguide structure employed in this design provides not only a high power-combining efficiency over a wide bandwidth, but also efficient heat sinking for the active devices. The measured maximum small-signal gain of the eight-device power amplifier is 19.4 dB at 34 GHz with a 3-dB bandwidth of 3.2 GHz (f/sub L/=31.8 GHz, f/sub H/=35 GHz). The measured maximum output power at 1-dB compression (P/sub out/ at 1 dB) from the power amplifier is 33 dBm (/spl sim/2 W) at 32.2 GHz, with a power-combining efficiency of 80%. Furthermore, performance degradation of this power amplifier due to device failures has also been simulated and measured.

positive: Ka band spatial power-combining amplifier structures 2.24 w power-amplifier (PA) module at 35 GHz presented using broad-band spatial power-combining system. The combiner can accommodate more monolithic microwave integrated-circuit (MMIC) PA with stagger placement structure on limited microstrip space in Ka-band waveguide structure with good return losses, and heat can dissipated into aluminum carrier quickly. This combiner is based on a slotline-to-microstrip transition structure, which also serves as a four-way power combiner. The proposed 2*2 combining structure combined by vertical stacking inside the waveguide was analyzed and optimized by finite-element-method (FEM) simulations and experiments.

positive: Broad-Band High-Power Amplifier Using Spatial Power-Combining Technique High power, broad bandwidth, high linearity, and low noise are among the most important features in amplifier design. The broad-band spatial power-combining technique addresses all these issues by combining the output power of a large quantity of microwave monolithic integrated circuit (MMIC) amplifiers in a broad-band coaxial waveguide environment, while maintaining good linearity and improving phase noise of the MMIC amplifiers. A coaxial waveguide was used as the host of the combining circuits for broader bandwidth and better uniformity by equally distributing the input power to each element. A new compact coaxial combiner with much smaller size is investigated. Broad-band slotline to microstrip-line transition is integrated for better compatibility with commercial MMIC amplifiers. Thermal simulations are performed and an improved thermal management scheme over previous designs is employed to improve the heat sinking in high-power application. A high-power amplifier using the compact combiner design is built and demonstrated to have a bandwidth from 6 to 17 GHz with 44-W maximum output power. Linearity measurement has shown a high third-order intercept point of 52 dBm. Analysis shows the amplifier has the ability to extend spurious-free dynamic range by 2 3 times. The amplifier also has shown a residual phase floor close to 140 dBc at 10-kHz offset from the carrier with 5–6-dB reductions compared to a single MMIC amplifier it integrates.

positive: Novel high efficiency broadband Ku band power combiner High power solid-state power amplifiers require a high efficiency power dividing/combining structure to keep the power loss as low as possible. The heat sinking capability of the divider/combiner also limits its maximum output power with continues wave (CW) configuration. In this paper, we introduce a novel 8-way Ku band power divider/combiner system, it demonstrate advantages of low loss, broadband and good heat sinking capability simultaneously. As its sub-components, low loss probes for waveguide-to-microstrip transition and low loss broadband 1-to-2 power combiners are designed and fabricated. The measured back-to-back insertion loss of the whole 8-way power combiner is lower than 0.5dB in the whole Ku band, and the corresponding combining efficiency is as high as 94.5%. The simulated thermal resistance of the system is as low as 0.21°C/W, indicating the proposed power combiner is able to produce 50W of CW output power with commercial available Monolithic Microwave Integrated Circuits (MMICs).

negative: Image-guided full waveform inversion Multiple problems, including high computational cost, spurious local minima, and solutions with no geologic sense, have prevented widespread application of full waveform inversion (FWI), especially FWI of seismic reflections. These problems are fundamentally related to a large number of model parameters and to the absence of low frequencies in recorded seismograms. Instead of inverting for all the parameters in a dense model, image-guided full waveform inversion inverts for a sparse model space that contains far fewer parameters. We represent a model with a sparse set of values, and from these values, we use image-guided interpolation (IGI) and its adjoint operator to compute finelyand uniformly-sampled models that can fit recorded data in FWI. Because of this sparse representation, image-guided FWI updates more blocky models, and this blockiness in the model space mitigates the absence of low frequencies in recorded data. Moreover, IGI honors imaged structures, so image-guided FWI built in this way yields models that are geologically sensible.

negative: Neural Network-Based Spectrum Estimation for Online WPE Dereverberation In this paper, we propose a novel speech dereverberation framework that utilizes deep neural network (DNN)-based spectrum estimation to construct linear inverse filters. The proposed dereverberation framework is based on the state-of-the-art inverse filter estimation algorithm called weighted prediction error (WPE) algorithm, which is known to effectively reduce reverberation and greatly boost the ASR performance in various conditions. In WPE, the accuracy of the inverse filter estimation, and thus the deverberation performance, is largely dependent on the estimation of the power spectral density (PSD) of the target signal. Therefore, the conventional WPE iteratively performs the inverse filter estimation, actual dereverberation and the PSD estimation to gradually improve the PSD estimate. However, while such iterative procedure works well when sufficiently long acoustically-stationary observed signals are available, WPE’s performance degrades when the duration of observed/accessible data is short, which typically is the case for real-time applications using online block-batch processing with small batches. To solve this problem, we incorporate the DNN-based spectrum estimator into the framework ofWPE, because a DNN can estimate the PSD robustly even from very short observed data. We experimentally show that the proposed framework outperforms the conventional WPE, and improves the ASR performance in real noisy reverberant environments in both single-channel and multichannel cases.

negative: Bayesian artificial intelligence for tackling uncertainty in self-adaptive systems: The case of dynamic decision networks In recent years, there has been a growing interest towards the application of artificial intelligence approaches in software engineering (SE) processes. In the specific area of SE for self-adaptive systems (SASs) there is a growing research awareness about the synergy between SE and AI. However, just few significant results have been published. This paper briefly studies uncertainty in SASs and surveys techniques that have been developed to engineer SASs in order to tackle uncertainty. In particular, we highlight techniques that use AI concepts. We also report and discuss our own experience using Dynamic Decision Networks (DDNs) to model and support decision-making in SASs while explicitly taking into account uncertainty. We think that Bayesian inference, and specifically DDNs, provide a useful formalism to engineer systems that dynamically adapt themselves at runtime as more information about the environment and the execution context is discovered during execution. We also discuss partial results, challenges and future research avenues.

negative: Data-driven 3D visual pronunciation of Chinese IPA for language learning In the framework of intelligent aided language learning, a real-time data-driven 3D visual pronunciation system of Chinese IPA is proposed. First, a high quality articulatory speech corpus including speech and 3D articulatory data of lips, tongue and jaw movements is collected through Electro-Magnetic Articulograph; second, the 3D articulatory modeling including shape design and motion synthesis is conducted. The articulatory shape is obtained by designing a precise 3D facial model including internal and external articulators. The articulatory motion synthesis is obtained combining parameterized model and anatomical model. The system can thus illustrate the slight differences among phonemes by synthesizing both internal and external articulatory movements. The perceptual evaluation shows the suitability of the system for instructing language learners to articulate.

negative: Conjunctive representations in learning and memory: principles of cortical and hippocampal function. The authors present a theoretical framework for understanding the roles of the hippocampus and neocortex in learning and memory. This framework incorporates a theme found in many theories of hippocampal function: that the hippocampus is responsible for developing conjunctive representations binding together stimulus elements into a unitary representation that can later be recalled from partial input cues. This idea is contradicted by the fact that hippocampally lesioned rats can learn nonlinear discrimination problems that require conjunctive representations. The authors' framework accommodates this finding by establishing a principled division of labor, where the cortex is responsible for slow learning that integrates over multiple experiences to extract generalities whereas the hippocampus performs rapid learning of the arbitrary contents of individual experiences. This framework suggests that tasks involving rapid, incidental conjunctive learning are better tests of hippocampal function. The authors implement this framework in a computational neural network model and show that it can account for a wide range of data in animal learning.

negative: Wearable impedance analyzer based on AD5933 In this paper a system for measuring impedance, based on AD5933 circuit is presented. The impedance measuring range is between 9 Ω and 18 MΩ for a 1 kHz ÷ 100 kHz frequency range. Possibilities of expanding this range of measurement are also presented in the paper. The system calibration is automatic and the relative error of the impedance modulus measurement is in the range ±2%. Measured impedance main parameters are shown locally on an OLED display but can also be stored in an SD memory card for further processing. The system is portable, modular and adaptable to a large number of applications.

negative: Fostering User Engagement: Rhetorical Devices for Applause Generation Learnt from TED Talks One problem that every presenter faces when delivering a public discourse is how to hold the listeners’ attentions or to keep them involved. Therefore, many studies in conversation analysis work on this issue and suggest qualitatively constructions that can effectively lead to audience’s applause. To investigate these proposals quantitatively, in this study we analyze the transcripts of 2,135 TED Talks, with a particular focus on the rhetorical devices that are used by the presenters for applause elicitation. Through conducting regression analysis, we identify and interpret 24 rhetorical devices as triggers of audience applauding. We further build models that can recognize applause-evoking sentences and conclude this work with potential implications. Introduction and Motivation Many academic studies have been devoted to the tasks of user engagement characterization. However, applause, as the most direct audience reaction, has till now not been fully investigated and understood. The audience do not just clap whenever they like, they do so only at certain points and are continuously looking for appropriate times when applause can possibly occur (Kuo, 2001). Having a deep understanding of audience’s applause is important because it will help the speakers to better design their speech with recognizable calls for conjoined response, and to make their presentation more appealing and engageable. Despite its importance, to date relatively limited work have been conducted on the topic of applause generation, except a few qualitative studies done by social psychologists. Atkinson (1984) first claimed that applause is closely synchronized with a number of actions on the part of the speakers, which he referred to as “rhetorical devices”. He identified three rhetorical devices that are effective in evoking applauses, including: contrasts, three-part lists, and projection of names. Heritage and Greatbatch (1986) found five other basic rhetorical devices, including: puzzlesolution, headline-punchline, combination, position taking This is a pre-print of an article appearing at ICWSM 2017. and pursuit. In addition, new categories were also identified in many recent studies, such as greetings, expressing appreciations, etc. (Bull and Feldman, 2011). To date, research on applause generation has been limited to the analysis of political speeches only. Besides, all of the aforementioned work were conducted using qualitative methods. Many critical questions, such as, What triggers the audience’s applause?, When do audience applaud?, etc., remain unanswered. To address these gaps, this work aims to identify the rhetorical devices for applause elicitation using data-driven methods. To this end, we propose two research questions: RQ1: What are the rhetorical devices that cause the audiences to applaud during a specific part of a speech? RQ2: To what extent the hypothesized rhetorical devices can be used to predict applause generation? To answer both questions, we crawl 2,135 TED talk transcripts and conduct quantitative analysis to investigate the factors that could trigger audience’s applause. We find that factors such as, gratitude expressions, phonetic structure, projection of names, emotion, etc., have significant effects on applause generation. These identified factors are later used to build machine learning models that can automatically identify applause-evoking segments.

negative: Battery Management System: An Overview of Its Application in the Smart Grid and Electric Vehicles With the rapidly evolving technology of the smart grid and electric vehicles (EVs), the battery has emerged as the most prominent energy storage device, attracting a significant amount of attention. The very recent discussions about the performance of lithium-ion (Li-ion) batteries in the Boeing 787 have confirmed so far that, while battery technology is growing very quickly, developing cells with higher power and energy densities, it is equally important to improve the performance of the battery management system (BMS) to make the battery a safe, reliable, and cost-efficient solution. The specific characteristics and needs of the smart grid and EVs, such as deep charge/discharge protection and accurate state-of-charge (SOC) and state-of-health (SOH) estimation, intensify the need for a more efficient BMS. The BMS should contain accurate algorithms to measure and estimate the functional status of the battery and, at the same time, be equipped with state-of-the-art mechanisms to protect the battery from hazardous and inefficient operating conditions.

negative: AUGMENTED REALITY VISUALIZATION TOOL FOR KINGS STORMWATER BRIDGE Augmented Reality (AR) is an emerging visualization technology that promises to change the way people see the world. The main goal of AR is to “enhance” a person’s vision of the real world with useful information about the surrounding environment. Primarily this can be done through the use of a portable computer such as a laptop and a head-mounted display (HMD) unit. When such technology is made available to scientists and engineers, Augmented Reality can provide them with the freedom to do scientific analysis at the actual location of an experiment. With this idea in mind, the goal of this paper is to investigate the development of an AR system as a visualization tool for structural engineers. This particular application will focus on monitoring the “health” of the Kings Stormwater Bridge structure. Unfortunately, since AR is still in its infancy, much of the research devoted to it has focused mainly on technical issues rather than on the development of how this technology would be used by scientists. This has led to the development of “functional” AR systems that primarily can only be operated by the developer of the system ([1], [2], [3], [12], [14]). This paper avoids this trend by focusing on the design of the visualization system so that it is useful for structural engineers. As a result, this should produce a more robust Augmented Reality system that can be used by many different users. Thus, it is the goal of this paper to show how scientists would benefit by designing a visualization system with their needs in mind.

negative: PSO-based optimization for isolated intersections signal timings and simulation In this paper, based on the analyzing the signal control problem of single intersections, a kind of real-time optimization method with PSO (particle swarm optimization) solving signal timings for single intersection is put forward. On detecting the flow of current cycle and the cycle before, estimating the flow of next circle is proceeded. Setting least delay as performance index, we get each phase time for the next cycle. A simulation experiment for the traffic model at a four-phase intersection is also performed. The result shows that the method is efficient.

negative: Android anti-forensics through a local paradigm Mobile devices are among the most disruptive technologies of the last years, gaining even more diffusion and success in the daily life of a wide range of people categories. Unfortunately, while the number of mobile devices implicated in crime activities is relevant and growing, the capability to perform the forensic analysis of such devices is limited both by technological and methodological problems. In this paper, we focus on Anti-Forensic techniques applied to mobile devices, presenting some fully automated instances of such techniques to Android devices. Furthermore, we tested the effectiveness of such techniques versus both the cursory examination of the device and some acquisition tools. a 2010 Digital Forensic Research Workshop. Published by Elsevier Ltd. All rights reserved.

negative: Tracking-based deer vehicle collision detection using thermal imaging Deer vehicle collision (DVC) is constantly a major safety issue for the driving on rural road. It is estimated that there are over 35,000 DVCs yearly in the US resulting in about 200 deaths and close to 4,000 reported property damages of one thousand dollars or more. This justifies many attempts trying to detect deer on road. However, very little success has been achieved. In order to reduce the number of DVCs, this work focused on the study of using an infrared thermal camera with tracking system to detect the presence of deer to avoid DVCs. The prototype consists of an infrared thermal temperature image grabbing and processing system, which includes an infrared thermal camera, a frame grabber, an image processing system and a motion tracking system, which includes two motors with their motion control system. By analyzing the infrared thermal images which are independent of visible light, the presence of an animal can be determined in either night or day time through pattern recognition and matching.

negative: BENCHMARKING DEEP LEARNING FRAMEWORKS FOR THE CLASSIFICATION OF VERY HIGH RESOLUTION SATELLITE MULTISPECTRAL DATA In this paper we evaluated deep-learning frameworks based on Convolutional Neural Networks for the accurate classification of multispectral remote sensing data. Certain state-of-the-art models have been tested on the publicly available SAT-4 and SAT-6 high resolution satellite multispectral datasets. In particular, the performed benchmark included the AlexNet, AlexNet-small and VGG models which had been trained and applied to both datasets exploiting all the available spectral information. Deep Belief Networks, Autoencoders and other semi-supervised frameworks have been, also, compared. The high level features that were calculated from the tested models managed to classify the different land cover classes with significantly high accuracy rates i.e., above 99.9%. The experimental results demonstrate the great potentials of advanced deep-learning frameworks for the supervised classification of high resolution multispectral remote sensing data.

negative: Subcutaneous and visceral adipose tissue: their relation to the metabolic syndrome. Methods for assessment, e.g., anthropometric indicators and imaging techniques, of several phenotypes of human obesity, with special reference to abdominal fat content, have been evaluated. The correlation of fat distribution with age, gender, total body fat, energy balance, adipose tissue lipoprotein lipase and lipolytic activity, adipose tissue receptors, and genetic characteristics are discussed. Several secreted or expressed factors in the adipocyte are evaluated in the context of fat tissue localization. The body fat distribution and the metabolic profile in nonobese and obese individuals is discussed relative to lipolysis, antilypolysis and lipogenesis, insulin sensitivity, and glucose, lipid, and protein metabolism. Finally, the endocrine regulation of abdominal visceral fat in comparison with the adipose tissue localized in other areas is presented.

negative: Deriving common malware behavior through graph clustering Detection of malicious software (malware) continues to be a problem as hackers devise new ways to evade available methods. The proliferation of malware and malware variants requires methods that are both powerful, and fast to execute. This paper proposes a method to derive the common execution behavior of a family of malware instances. For each instance, a graph is constructed that represents kernel objects and their attributes, based on system call traces. The method combines these graphs to develop a supergraph for the family. This supergraph contains a subgraph, called the HotPath, which is observed during the execution of all the malware instances. The proposed method is scalable, identifies previously-unseen malware instances, shows high malware detection rates, and false positive rates close to 0%.

negative: Liability and Computer Security: Nine Principles The conventional wisdom is that security priorities should be set by risk analysis. However, reality is subtly different: many computer security systems are at least as much about shedding liability as about minimising risk. Banks use computer security mechanisms to transfer liability to their customers; companies use them to transfer liability to their insurers, or (via the public prosecutor) to the taxpayer; and they are also used to shift the blame to other departments (“we did everything that GCHQ/the internal auditors told us to”). We derive nine principles which might help designers avoid the most common pitfalls.

negative: When Sparse Traditional Models Outperform Dense Neural Networks: the Curious Case of Discriminating between Similar Languages We present the results of our participation in the VarDial 4 shared task on discriminating closely related languages. Our submission includes simple traditional models using linear support vector machines (SVMs) and a neural network (NN). The main idea was to leverage language group information. We did so with a two-layer approach in the traditional model and a multi-task objective in the neural network. Our results confirm earlier findings: simple traditional models outperform neural networks consistently for this task, at least given the amount of systems we could examine in the available time. Our two-layer linear SVM ranked 2nd in the shared task.

negative: RAN: Radical analysis networks for zero-shot learning of Chinese characters Chinese characters have a huge set of character categories, more than 20,000 and the number is still increasing as more and more novel characters continue being created. However, the enormous characters can be decomposed into a few fundamental structural radicals, only about 500. This paper introduces the Radical Analysis Networks (RAN) that recognize Chinese characters by identifying radicals and analyzing 2D spatial structures between them. The proposed RAN first extracts visual features from Chinese character input by employing convolutional neural networks as an encoder. Then a decoder based on recurrent neural networks is employed, who aims to generate a caption of Chinese character by detecting radicals and 2D structures through a spatial attention mechanism. The manner of treating Chinese character input as a composition of radicals rather than a single picture severely reduces the size of vocabulary and enables RAN to possess the ability of recognizing unseen Chinese character classes only if their radicals have been seen, called zero-shot learning. We test a simple implementation of RAN on experiments of recognizing printed Chinese characters with seen and unseen classes and RAN simultaneously obtains convincing performance on unseen classes and state-of-the-art performance on seen classes.

negative: Age-Invariant Face Recognition One of the challenges in automatic face recognition is to achieve temporal invariance. In other words, the goal is to come up with a representation and matching scheme that is robust to changes due to facial aging. Facial aging is a complex process that affects both the 3D shape of the face and its texture (e.g., wrinkles). These shape and texture changes degrade the performance of automatic face recognition systems. However, facial aging has not received substantial attention compared to other facial variations due to pose, lighting, and expression. We propose a 3D aging modeling technique and show how it can be used to compensate for the age variations to improve the face recognition performance. The aging modeling technique adapts view-invariant 3D face models to the given 2D face aging database. The proposed approach is evaluated on three different databases (i.g., FG-NET, MORPH, and BROWNS) using FaceVACS, a state-of-the-art commercial face recognition engine.

negative: Improving the reliability of commodity operating systems Despite decades of research in extensible operating system technology, extensions such as device drivers remain a significant cause of system failures. In Windows XP, for example, drivers account for 85&percent; of recently reported failures.This article describes Nooks, a reliability subsystem that seeks to greatly enhance operating system (OS) reliability by isolating the OS from driver failures. The Nooks approach is practical: rather than guaranteeing complete fault tolerance through a new (and incompatible) OS or driver architecture, our goal is to prevent the vast majority of driver-caused crashes with little or no change to the existing driver and system code. Nooks isolates drivers within lightweight protection domains inside the kernel address space, where hardware and software prevent them from corrupting the kernel. Nooks also tracks a driver's use of kernel resources to facilitate automatic cleanup during recovery.To prove the viability of our approach, we implemented Nooks in the Linux operating system and used it to fault-isolate several device drivers. Our results show that Nooks offers a substantial increase in the reliability of operating systems, catching and quickly recovering from many faults that would otherwise crash the system. Under a wide range and number of fault conditions, we show that Nooks recovers automatically from 99&percent; of the faults that otherwise cause Linux to crash.While Nooks was designed for drivers, our techniques generalize to other kernel extensions. We demonstrate this by isolating a kernel-mode file system and an in-kernel Internet service. Overall, because Nooks supports existing C-language extensions, runs on a commodity operating system and hardware, and enables automated recovery, it represents a substantial step beyond the specialized architectures and type-safe languages required by previous efforts directed at safe extensibility.

negative: Algebraic gossip: a network coding approach to optimal multiple rumor mongering The problem of simultaneously disseminating k messages in a large network of n nodes, in a decentralized and distributed manner, where nodes only have knowledge about their own contents, is studied. In every discrete time-step, each node selects a communication partner randomly, uniformly among all nodes and only one message can be transmitted. The goal is to disseminate rapidly, with high probability, all messages to all nodes. It is shown that a random linear coding (RLC) based protocol disseminates all messages to all nodes in time ck + O (√k ln(k) ln(n)), where c < 3.46 using pull-based dissemination and c < 5.96 using push-based dissemination. Simulations suggest that c < 2 might be a tighter bound. Thus, if k ≫ (ln(n))3, the time for simultaneous dissemination RLC is asymptotically at most ck, versus the Ω(k log<inf>2</inf>(n))3 time of sequential dissemination. Furthermore, when k ≫ (ln(n))3, the dissemination time is order optimal. When k ≪ (ln(n))2, RLC reduces dissemination time by a factor of Ω(√k/ln k) over sequential dissemination. The overhead of the RLC protocol is negligible for messages of reasonable size. A store-and-forward mechanism without coding is also considered. It is shown that this approach performs no better than a sequential approach when k=∞ n. Owing to the distributed nature of the system, the proof requires analysis of an appropriate time-varying Bernoulli process.

negative: Characterizing Variation in Crowd-Sourced Data for Training Neural Language Generators to Produce Stylistically Varied Outputs One of the biggest challenges of endto-end language generation from meaning representations in dialogue systems is making the outputs more natural and varied. Here we take a large corpus of 50K crowd-sourced utterances in the restaurant domain and develop text analysis methods that systematically characterize types of sentences in the training data. We then automatically label the training data to allow us to conduct two kinds of experiments with a neural generator. First, we test the effect of training the system with different stylistic partitions and quantify the effect of smaller, but more stylistically controlled training data. Second, we propose a method of labeling the style variants during training, and show that we can modify the style of the generated utterances using our stylistic labels. We contrast and compare these methods that can be used with any existing large corpus, showing how they vary in terms of semantic quality and

negative: Deep Supervised Hashing for Fast Image Retrieval In this paper, we present a new hashing method to learn compact binary codes for highly efficient image retrieval on large-scale datasets. While the complex image appearance variations still pose a great challenge to reliable retrieval, in light of the recent progress of Convolutional Neural Networks (CNNs) in learning robust image representation on various vision tasks, this paper proposes a novel Deep Supervised Hashing (DSH) method to learn compact similarity-preserving binary code for the huge body of image data. Specifically, we devise a CNN architecture that takes pairs of images (similar/dissimilar) as training inputs and encourages the output of each image to approximate discrete values (e.g. +1/-1). To this end, a loss function is elaborately designed to maximize the discriminability of the output space by encoding the supervised information from the input image pairs, and simultaneously imposing regularization on the real-valued outputs to approximate the desired discrete values. For image retrieval, new-coming query images can be easily encoded by propagating through the network and then quantizing the network outputs to binary codes representation. Extensive experiments on two large scale datasets CIFAR-10 and NUS-WIDE show the promising performance of our method compared with the state-of-the-arts.

negative: A Hybrid Cryptosystem Based On Vigenere Cipher and Columnar Transposition Cipher Privacy is one of the key issues addressed by information Security. Through cryptographic encryption methods, one can prevent a third party from understanding transmitted raw data over unsecured channel during signal transmission. The cryptographic methods for enhancing the security of digital contents have gained high significance in the current era. Breach of security and misuse of confidential information that has been intercepted by unauthorized parties are key problems that information security tries to solve. This paper sets out to contribute to the general body of knowledge in the area of classical cryptography by developing a new hybrid way of encryption of plaintext. The cryptosystem performs its encryption by encrypting the plaintext using columnar transposition cipher and further using the ciphertext to encrypt the plaintext again using Vigenère cipher. At the end, cryptanalysis was performed on the ciphertext. The implementation will be done using java programming.

negative: Trojan data layouts: right shoes for a running elephant MapReduce is becoming ubiquitous in large-scale data analysis. Several recent works have shown that the performance of Hadoop MapReduce could be improved, for instance, by creating indexes in a non-invasive manner. However, they ignore the impact of the data layout used inside data blocks of Hadoop Distributed File System (HDFS). In this paper, we analyze different data layouts in detail in the context of MapReduce and argue that Row, Column, and PAX layouts can lead to poor system performance. We propose a new data layout, coined Trojan Layout, that internally organizes data blocks into attribute groups according to the workload in order to improve data access times. A salient feature of Trojan Layout is that it fully preserves the fault-tolerance properties of MapReduce. We implement our Trojan Layout idea in HDFS 0.20.3 and call the resulting system Trojan HDFS. We exploit the fact that HDFS stores multiple replicas of each data block on different computing nodes. Trojan HDFS automatically creates a different Trojan Layout per replica to better fit the workload. As a result, we are able to schedule incoming MapReduce jobs to data block replicas with the most suitable Trojan Layout. We evaluate our approach using three real-world workloads. We compare Trojan Layouts against Hadoop using Row and PAX layouts. The results demonstrate that Trojan Layout allows MapReduce jobs to read their input data up to 4.8 times faster than Row layout and up to 3.5 times faster than PAX layout.

negative: Monolithic Low Cost Ka-Band Wilkinson Power Dividers on Flexible Organic Substrates A millimeter wave Wilkinson power divider is presented on a thin and durable organic substrate, along with an analysis of bend topologies to reduce coupling between the output paths. The divider provides excellent performance across the entire Ka-band from 27 to 40 GHz. Insertion loss is approximately 0.3 dB and isolation between the output ports is around 30 dB at the design frequency.

negative: A planar probe double ladder waveguide power divider The successful demonstration of a 1:4 power divider using microstrip probes and a WR-430 rectangular waveguide is presented. The 15-dB return loss bandwidth of the nonoptimized structure is demonstrated to be 22% and its 0.5-dB insertion loss bandwidth 26%. While realized through conventional machining, such a structure is assembled in a fashion consistent with proven millimeter and submillimeter-wave micromachining techniques. Thus, the structure presents a potential power dividing and power combining architecture, which through micromachining, may be used for applications well above 100GHz.

negative: A Ka-Band CMOS Wilkinson Power Divider Using Synthetic Quasi-TEM Transmission Lines This work presents a Ka-band two-way 3 dB Wilkinson power divider using synthetic quasi-transverse electromagnetic (TEM) transmission lines (TLs). The synthetic quasi-TEM TL, also called complementary-conducting-strip TL (CCS TL), is theoretically analyzed. The equivalent TL model, whose production is based on the extracted results, is applied to the power divider design. The prototype is fabricated by the standard 0.18 mum 1P6M CMOS technology, showing the circuit size of 210.0 mumtimes390.0 mum without contact pads. The measurement results, which match the 50 Omega system, reveal perfect agreements with those of the simulations. The comparison reveals the following characteristics. The divider exhibits an equal power-split with the insertion losses (S21 and S31) of 3.65 dB. The return losses (S11, S22 and S33) of the prototype are higher than 10.0 dB from 30.0 to 40.0 GHz.

negative: Ring-Shaped Substrate Integrated Waveguide Wilkinson Power Dividers/Combiners This paper proposes and presents a class of substrate integrated waveguide (SIW) power dividers/combiners based on a modified Wilkinson architecture. The proposed design consists of a ring-type circuit of 1.5 λg length with three waveguide ports. Impedance variation without affecting cutoff frequency and integration of isolation resistance are the two major limitations in connection with the design of SIW Wilkinson structures. Central ring part with different thickness ensures different impedance in the first proposed scheme while the half-mode SIW in the second option. As for the second limitation, the optimal configuration of integrating the isolation resistance is studied. A version without resistance is also examined using a broad-wall series slot. To validate the proposed concept, a bilayered circuit with standard Printed circuit board prototype was fabricated and measured. A table summarizing performances of all the proposed circuits shows a bandwidth of around 25% at the 10 dB reference. A negligible additional insertion loss is observed. The proposed design techniques are found useful at millimeter-wave frequencies where reduced physical dimensions make a circuit configuration suitable for low-cost implementation. This concept is also valid for rectangular waveguide counterparts.

negative: A compact planar feed structure for Ka-band satcom-on-the-move tracking antennas The increasing interest in bi-directional mobile high data rate satellite communications in Ka-band necessitates the development of dedicated antenna tracking systems and feeds. In this paper we describe a compact feed structure based on printed circuit boards for a mobile satellite communications ground terminal with a Cassegrain reflector antenna. The novel structure provides a dual circular polarisation communication mode as well as the TM01 mode for multimode monopulse tracking. This coupler, based on carefully matched transitions from grounded coplanar lines to circular waveguides, is operational at 20GHz and 30 GHz, to cover the downlink and the uplink frequency ranges in Ka-band. This work contributes to the development of a satellite terminal for land-mobile communications in disaster scenarios.

negative: Dual-band leaky-wave antenna based on a dual-layer frequency selective surface for bi-directional satcom-on-the-move in Ka-band A 2D-periodic leaky-wave antenna for a Ka-band satcom-on-the-move ground user terminal is presented. The antenna panel operates at the 20 GHz downlink as well as the 30 GHz uplink bands with the respective circular polarizations, using a common radiation aperture and a common phase centre. The dual-band performance is achieved by a carefully designed stacked dual-layer frequency selective surface, with one layer operating at 20 GHz and being transparent at 30 GHz, and the second layer acting vice versa. The paper describes the design of the circularly polarized primary feed, the dual-layer structures, and the complete compact leaky-wave antenna panel. The measured radiation performance reveals realized-gain values above 22 dBi and efficiencies above 60%. The cross-polarization discrimination and sidelobe level are suitable to meet the power spectral requirements for satellite communications at Ka-band.

negative: A novel compact ka-band high-rejection diplexer based on substrate integrated waveguide In this paper, a compact diplexer using substrate integrated waveguide (SIW) resonators is introduced. The diplexer consists of two filters and a circulator. The diplexer channels are 4% and 5% relative bandwidth at 32GHz and 33GHz, respectively. The filters are based on SIW resonators, which have higher Q values. This paper also analyzed the factors which affect the Q value of resonators, and describes the designing procedure of Generalized Chebyshev filters, which used in this paper. The circulator also is on account of SIW. It uses inductive windows to increase bandwidth. At last, the paper gives the diplexer's simulation and measure results. And two results are similar with each other.