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(IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 6, 2011 A Fuzzy Clustering Based Approach for Mining Usage Profiles from Web Log Data Zahid Ansari1, Mohammad Fazle Azeem2, A. Vinaya Babu3 and Waseem Ahmed4 1,4 Dept. of Computer Science Engineering 2 Dept. of Electronics and Communication Engineering P.A. College of Engineering Mangalore, India 1 email@example.com 2 firstname.lastname@example.com 4 firstname.lastname@example.com 3 Dept. of Computer Science Engineering Jawaharlal Nehru Technological University Hyderabad, India email@example.com Abstract— The World Wide Web continues to grow at an assignment tasks. Finally we compare our soft computing based amazing rate in both the size and complexity of Web sites and is approach of session weight assignment with the traditional hard well on it's way to being the main reservoir of information and computing based approach of small session elimination. data. Due to this increase in growth and complexity of WWW, web site publishers are facing increasing difficulty in attracting Keywords- web usage mining; data preprocessing, fuzzy and retaining users. To design popular and attractive websites Clustering, knowledge discovery; publishers must understand their users' needs. Therefore analyzing users' behaviour is an important part of web page I. INTRODUCTION design. Web Usage Mining (WUM) is the application of datamining techniques to web usage log repositories in order to Due to the digital revolution and advancements in computer discover the usage patterns that can be used to analyze the user's hardware and software technologies, digitized information is navigational behavior [1]. WUM contains three main steps: easy to capture and fairly inexpensive to store [6], [7]. As a preprocessing, knowledge extraction and results analysis. The result huge amount of data have been collected and stored in goal of the preprocessing stage in Web usage mining is to databases. The rate at which such data is stored is growing at a transform the raw web log data into a set of user profiles. Each phenomenal rate. The fast growing tremendous amount of data such profile captures a sequence or a set of URLs representing a collected and stored in large and numerous data repositories, user session. has far exceeded our human ability for comprehension without powerful tools. The abundance of data, coupled with the need This sessionized data can be used as the input for a variety of for powerful data analysis tools has been described as a "data data mining tasks such as clustering [2], association rule mining rich but information poor" situation. Hence, there is an urgent [3], sequence mining [4] etc. If the data mining task at hand is need for a new generation of computational techniques and clustering, the session files are filtered to remove very small sessions in order to eliminate the noise from the data [5]. But tools to assist humans in extracting useful information direct removal of these small sized sessions may result in loss of a (knowledge) from the rapidly growing volumes of data [8]. significant amount of information especially when the number of Data mining is the process of exploration and analysis, by small sessions is large. We propose a "Fuzzy Set Theoretic" automatic or semi-automatic means, of large quantities of data approach to deal with this problem. Instead of directly removing in order to discover meaningful patterns or rules. It deals with all the small sessions below a specified threshold, we assign the "knowledge in the database" [8]. The term KDD refers to weights to all the sessions using a "Fuzzy Membership Function" the overall process of knowledge discovery in databases. Data based on the number of URLs accessed by the sessions. After mining is a particular step in this process, involving the assigning the weights we apply a "Fuzzy c-Mean Clustering" application of specific algorithms for extracting patterns from algorithm to discover the clusters of user profiles. In this paper, data. The additional steps in the KDD process, such as data we discuss our methodology to preprocess the web log data preparation, data selection, data cleaning, incorporation of including data cleaning, user identification and session appropriate prior knowledge, and proper interpretation of the identification. We also describe our methodology to perform results of mining, ensures that useful knowledge is derived feature selection (or dimensionality reduction) and session weight from the data [9]. 70 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 6, 2011 Data mining often builds on an interdisciplinary bundle of is a complicated task. By filtering out useless data, we can specialized techniques from fields such as statistics, artificial reduce log file size to enhance the upcoming mining tasks. intelligence, machine learning, data bases, pattern recognition, computer-based visualization etc. The more common model functions in current data mining practice include classification, regression clustering, rule generation, discovering association, summarization and sequence analysis [10]. The World Wide Web as a large and dynamic information source, that is structurally complex and ever growing, is a fertile ground for data mining principles or Web Mining. Web mining is primarily aimed at deriving actionable knowledge from the Web through the application of various data mining techniques [11]. Web data is typically unlabelled, distributed, heterogeneous, semi-structured, time varying, and high dimensional. Web data can be grouped into the following categories [12]: i) Contents of actual Web pages, ii) Intra-page structures of the web pages, iii) Inter page structures specifying linkage structures between Web pages, iv) Web usage data describing how Web pages are accessed and v) User profiles which include demographic and registration information about users. Web Usage Mining is the discovery of user access Figure 2. Web Log Processing to Discover Weighted Sessions. patterns from Web servers [1]. Web Usage Mining analyzes results of user interactions with a Web server, including Web User identification refers to the process of identifying logs, click streams, and database transactions at a Web site or a unique users from the user activity logs. Usually the log file in group of related sites. Web usage mining includes clustering Extended Common Log format provides only the computer's (e.g. finding natural groupings of users, pages etc.), address and the user agent. For Web sites requiring user associations (e.g. which URLs tend to be requested together), registration, the log file also contains the user login. In such and sequential analysis (the order in which URLs tend to be cases this information can be used for user identification. For accessed) [13]. As with any knowledge, discovery and data those cases where user login information is not available, we mining (KDD) process, WUM performs three main steps: consider each IP as a user. User Session identification is the preprocessing, pattern extraction and results analysis. Figure 1 process of segmenting the user activity log of each user into describes the WUM process. sessions, each representing a single visit to the site. Identification of user sessions from the web log file is a complicated task, due to the existence of proxy servers, dynamic addresses, and cases of multiple users access the same computer [23][2][25][26]. It is also possible that one user might be using multiple browsers or computers. This sessionized data can be used as the input for a variety of data mining algorithms. Once user sessions are discovered, this sessionized data can be used as the input for a variety of data mining tasks such as clustering, association rule mining, sequence mining etc. If the Figure 1. Web Usage Mining Process. data mining task at hand is clustering, the session files are filtered to remove very small sessions in order to eliminate the The goal of the preprocessing stage in Web usage mining is noise from the data. But direct removal of these small sized to transform the raw click stream data into a set of user sessions may result in loss of a significant amount of profiles. Each such profile captures a sequence or a set of information especially when the number of small sessions is URLs representing a user session. Web usage data large. We propose a "Fuzzy Set Theoretic" approach to deal preprocessing exploit a variety of algorithms and heuristic with this problem. Instead of directly removing all the small techniques for various preprocessing tasks such as data fusion sessions below a specified threshold, we assign weights to all and cleaning, user and session identification etc. Figure 2 the sessions using a "Fuzzy Membership Function" based on depicts the primary tasks involved in web log data the number of URLs accessed by the sessions. After assigning preprocessing in order to discover the user sessions. the weights we apply a "Fuzzy c-Mean Clustering" algorithm to discover the clusters of user profiles. Fuzzy clustering Data fusion refers to the merging of log files from several techniques perform non-unique partitioning of the data items Web servers. This requires global synchronization across these where each data point is assigned a membership value for each servers [14]. Data cleaning involves tasks such as, removing of the clusters. This allows the clusters to grow into their extraneous references to embedded objects, style files, graphics, natural shapes [15]. A membership value of zero indicates that or sound files, and removing references due to spider the data point is not a member of that cluster. A non-zero navigations. Popular Web sites generate the log file of the size membership value shows the degree to which the data point measured in gigabytes per hour. Manipulating such large files represents a cluster. Fuzzy clustering algorithms can handle the 71 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 6, 2011 outliers by assigning them very small membership degree for explicitly request all of the graphics that are on a Web page, the surrounding clusters. Thus fuzzy clustering is more robust they are automatically downloaded due to the HTML tags. method for handling natural data with vagueness and Since the main purpose of Web Usage Mining is to get a uncertainty. picture of the user's behavior, it does not make sense to include file requests that the user did not explicitly request. During the Rest of the paper is organized as follows: in section-II, we Data cleaning process we removed the extraneous references to describe the techniques to preprocess the web log data embedded objects, style files, graphics and sound files. including data cleaning, user and session identification. In Elimination of the irrelevant items was accomplished by Section III, we describe our methodology for feature selection checking the suffix of the URL name. All log entries with (or dimensionality reduction) and session weight assignment. filename suffixes such as, gif, jpeg, GIF, JPEG, jpg, JPG, and In this section we also discuss our work to apply Fuzzy c- map were removed. Default list of suffixes were used to Mean Clustering algorithms to weighted user sessions. Section remove undesired files. Another main activity of the cleaning IV provides the experimental results of our methodology process is removal of robots' requests. Web Robots or spiders applied to a real Web site access logs. Finally section V scan a Web site to extract its content. Web robots automatically discusses the conclusion and future work. access all the hyperlinks from a Web page. The number of requests from a web robot is at least the number of the site's II. PREPROCESSING OF WEB LOG DATA URLs. Removing WR-generated log entries removes The primary data sources used in Web usage mining are the uninteresting sessions from the log file and simplifies server log files, which include Web server access logs and subsequent the mining tasks. In order to identify WR hosts we application server logs. used as list of all user agents known as robots as suggested by [16]. We obtained this list from the site "http://www.robotstxt.org". Figure 4 describes the algorithm 1212265085.247 741 192.168.23.62 TCP MISS/200 10858 GET for data cleaning and transformation. http://www.pace.edu.in/index.php - DEFAULT PARENT/192.168.20.1 Mozilla/5.0 Input: Access log file W Figure 3. A Sample Web Log Entry. Output: Cleaned file C For each line L ε W do A sample web server log file entry in Extended Common Log Format (ECLF) is given in Figure 3 and description of 1) Split L and extract various fields various fields is given in Table I. 2) If the URL includes the query string then remove it 3) Remove all the irrelevant requests whose URL suffix specified TABLE I. DESCRIPTION OF LOG FIELDS in the irrelevant suffix list 4) Remove all WR-generated requests Field Value Description 5) Encrypt IP address to hide user's identity 1212265085.247 The time of request, in 6) Store URL in a URL map along with corresponding URL coordinated universal time number 741 The elapsed time for HTTP request 7) Print required fields in to the output file 192.168.23.62 IP address of the client Figure 4. A Sample Web Log Entry. TCP_MISS/200 HTTP reply status code Table II describes the format of the output file C generated as 10858 Bytes sent by the server in a result of cleaning and transformations of the web logs. The response to the request. output file shows that client IP addresses are replaced with GET The requested action aliases in order to hide the identity of the user. The URL http://www.pace.edu.in/index.php URI of the object being requested column of the table shows that URL strings are replaced by - client user name, lf disabled, it is numbers in order to enhance further processing. We maintain a logged as - map of URL strings and corresponding URL numbers. DEFAULT_PARENT/192.168.20 Hostname of the machine where we got the object. TABLE II. FILE FORMAT AFTER DATA CLEANING - Content Type of the object User Elapsed Time IP Bytes URL Agent Time 20080601014805 IP1 UA1 741 10858 1 A. Data Cleaning 20080601014806 IP1 UA1 1735 19247 2 20080601014808 IP2 UA2 239 209 1 A user's request to view a particular page often results in 20080601014809 IP1 UA3 674 156 3 several log entries since graphics and scripts are down-loaded 20080601014813 IP2 UA2 680 179 4 in addition to the HTML file. In most cases, only the log entry of the HTML file request is relevant and should be kept for the user session file. This is because, in general, a user does not 72 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 6, 2011 B. User Identification Time-oriented heuristic TOH1 uses an upper bound on the Once web log files have been cleaned, next step in the data time spent in the entire site during a visit. The timestamp of preparation is the identification of the user. Since the log files every URL access request is compared with that of the first of web server we are working on do not contain the user login access request of the current session. If the time difference is information, we consider each unique IP and User-Agent larger than β, this request becomes the first request of the new combination as a separate user. Next we separate out all the session; otherwise it belongs to the current session. On the requests corresponding to each individual user. Figure 5 other hand Time-oriented heuristic TOH2 uses an upper bound describes the algorithm to generate requests corresponding to on page-stay time. The timestamp of every URL access request each individual user. is compared with that of the previous access request. If the time difference is larger than β, this request becomes the first request of the new session; otherwise it belongs to the current Input: File C, the cleaned access log file session. We have selected 30 minutes as the value of threshold time β for both of the above schemes. Output: File U that contains user wise list of URLs accessed by them 1) For each line L ε C do Input: File U, containing access logs of various users. b) Split L to get required fields c) Store them in a map M1 with IP, UserAgent as the Output: File S, the file that contains different sessions based on TOH1 key and another map M2 as value. Key of the map For each line L ε U do M2 is time and value is rest of the fields 1) if L represents a user then 2) Sort the inner map M2 based on the time key 2) UserId ← L 3) Print contents of the map M1 to the output file U 3) Output L to file S 4) else if L is the first accessed log of the user then Figure 5. Algorithm to separate requests for each individual user 5) T1 ← L.time 6) else 7) T2 ← L.time The format of the output file U generated after user // Compare the timestamps of current and the first request identification is depicted in Table III below: 8) if T2 - T1 ≤ β then 9) Output L to file S 10) else TABLE III. FILE FORMAT AFTER USER IDENTIFICATION 11) Output UserId to file S 12) Output L to file S Elapsed 13) T1 ← L.time User Time Bytes URL Time U1 20080601014805 741 10858 1 20080601014806 1735 19247 2 Figure 6. Algorithm to generate User Sessions based on TOH1 … … … … U2 20080601014809 674 156 3 Algorithm to generate the users sessions based on the time … … … … oriented heuristics TOH1 is specified in Figure 6. U3 20080601014808 239 209 1 20080601014813 680 179 4 TABLE IV. FILE FORMAT AFTER USER SESSION IDENTIFICATION C. User Session Identification User Session identification is the process of segmenting the User Elapsed Time Bytes URL user activity log of each user into sessions, each representing a Session Time single visit to the site. Web sites without user authentication U1-S1 20080601014805 741 10858 1 information mostly rely on heuristics methods for 20080601014806 1735 19247 2 sessionization. The sessionization heuristic helps in extracting … … … … the actual sequence of actions performed by one user during U1-S2 … … … … … … … … one visit to the site. In order to identify user sessions we … experimented with two different time oriented heuristics (TOH) … as described below: U2-S1 20080601014809 674 156 3 • TOH1 : The time duration of a session must not exceed … … … … a threshold β. Let timestamp of the first URL request in … a session is T1. A URL request with timestamp Ti is U3-S1 20080601014808 239 209 1 20080601014813 680 179 4 assigned to this session if and only if Ti – T1 ≤ β. The first URL request with timestamp larger than T1 + β is considered as the first request of the next session. Table IV shows the format the of the output file S containing • TOH2: The time spent on a page visit must not exceed user sessions. Once user sessions are generated we scan each a threshold β. Let Ti be the timestamp of the URL most session and remove the duplicate URLs from each session. For recently assigned to a session. The next URL request each unique URL within a user session a single copy of the with timestamp Ti+1 belongs to the same session if and URL is kept along with it's frequency of occurrence. We also only if Ti+1 – Ti ≤ β. Otherwise, this URL is considered maintain the count of the total number of unique URLs in each to be the first of the next session. session. 73 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 6, 2011 III. DISCOVERY OF USER SESSION CLUSTERS W ( si ) = 0, if si ≤ LB A. Feature Subset Selection of User Sessions Each user session can be thought of a single transaction of W ( si ) = 1, if si ≥ LB . (1) many URL references. We map the user sessions as vectors of s − LB URL references in a n-dimensional space. Let U be a set of n W ( si ) = i , otherwise UB − LB unique URLs appearing in the preprocessed log then U = { u1 , u 2 , … , un } and let S be a set of m user sessions discovered by preprocessing the web log data. Then C. Clustering the User Sessions S = { s1 , s 2 , … , s m } where each user session si ∈ S can be Once use sessions are represented in the form of a vector, represented as a bit vector s = { wu1 , wu2 , … , wum } where wui =1; if clustering algorithm can be run against them. The goal of this process is to discover session clusters that represent similar w i ∈s; and wui = 0; otherwise. u URL access patterns. For example, two session vectors are similar if the Euclidean distance between them is short enough. Instead of binary weights, feature weights can also be used Clustering aims to divide a data set into groups or clusters to represent a user session. These feature weights may be based where inter-cluster similarities are minimized while the intra on frequency of occurrence of a URL reference within the user cluster similarities are maximized. Details of various clustering session, the time a user spends on a particular page or the techniques can be found in survey articles [18][19][20]. The number of bytes downloaded by the uses from a page. However, ultimate goal of clustering is to assign data points to a finite the URLs appearing in the access logs and could number in the system of k clusters. Union of these clusters is equal to a full thousands. Distance-based clustering methods often perform dataset with the possible exception of outliers. very poor when dealing with very high dimensional data. Therefore filtering the logs by removing references to low The k-means clustering algorithm is one of the most support URLs (i.e. that are not supported by a specified number commonly used methods for partitioning the data. This of user sessions) can provide an effective dimensionality algorithm partitions a set of m objects into k clusters. The reduction method while improving clustering. algorithm proceeds by computing the distances between a data point and each cluster center in order to assign the data item to B. Assiging Weights to User Sessions one of the clusters so that intra-cluster similarity is high but inter-cluster similarity is low. Euclidian distance can be used as If the data mining task at hand is clustering, the session files a measure to calculate the distance between various data points can be filtered to remove very small sessions in order to and cluster centers. eliminate the noise from the data [5]. But direct removal of these small sized sessions may result in loss of a significant n 2 ∑ amount of information especially when the number of small i d ( xi , v j ) = x k − vkj (2) sessions is large. We propose a "Fuzzy Set Theoretic" k =1 approach to deal with this problem. Instead of directly where , removing all the small sessions below a specified threshold, we assign weights to all the sessions using a "Fuzzy Membership xi is the i th data point Function" based on the number of URLs accessed by the v j is the j th cluster center sessions. d ( xi , v j ) is the distance between xi and v j n is the number of dimensions of each data point i xk is the value of k th dimensions of xi vkj is the value of k th dimensions of v j The k-means clustering first initializes the cluster centers randomly. Then each data point xi is assigned to some cluster vj which has the minimum distance with this data point. Once all the data points have been assigned to clusters, cluster centers are updated by taking the weighted average of all data points in Figure 7. Fuzzy membership function for session weight assignment that cluster. This recalculation of cluster centers results in better cluster center set. The process is continued until there is Figure 7 depicts a linear Fuzzy membership function for no change in cluster centers. Although k-means clustering session weight assignment. Here LB represents a lower bound algorithm is efficient in handling the crisp data which have on the number of URLs accessed in a session and UB clear cut boundaries, but in real world data clusters have ill represents an upper bound on the number of URLs accessed in defined boundaries and often overlapping clusters. This a session. Let si be the number of URLs accessed in session happens because many times the natural data suffer from Ambiguity, Uncertainty and Vagueness [21]. si then the fuzzy membership function takes the following Fuzzy c-means clustering incorporates fuzzy set theoretic values: concept of partial membership and may result in the formation 74 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 6, 2011 of overlapping clusters. The algorithm calculates the cluster 1 / (q −1) 1 centers and assigns a membership value to each data item corresponding to every cluster within a range of 0 to 1. The algorithm utilizes a fuzziness index parameter q where uij = 2 ( d ij x i , v j ) (6) 1 / (q −1) q ∈ [1, ∞] [22] which determines the degree of fuzziness in the n ∑ 1 clusters. As the value of q reaches to 1, the algorithm works like a crisp partitioning algorithm. Increase in the value of q k =1 2 ( d ij x i , v j ) results in more overlapping of the clusters. In order to decide the number of optimum clusters for the Let X = {xi | i = 1L m} be a set of n-dimensional data point data set X we use a validity function S which is the ratio of vectors where m is the number of data points and each compactness to separation [22] as given below: xi = {x1i , x 2 ,L, xn }∀i = 1L m . Let V = {x j | j = 1L c} represent a i i c m 2 set of n-dimensional vectors corresponding to the cluster center corresponding to each of the c clusters and each ∑∑j =1 i =1 2 uij xi − v j S= (7) v j = {v1j , v2j ,L , vnj }∀j = 1L c Let uij represent the grade of 2 membership of data point xi in cluster j. m. min v l − v k l ≠k u ij ∈ [1,0] ∀i = 1L m and ∀j = 1L c . The n × c matrix U = [u ij ] is a for each c = cmin ,L, cmax fuzzy c-partition matrix, which describes the allocation of the data points to various clusters and satisfies the following conditions: Let c denote the optimal candidate at each c then, the solution to the following minimization problem yields the most c valid fuzzy clustering of the data set. ∑u ij = 1, ∀i = 1L m min min S j =1 (3) (8) c cmin ≤c≤cmax Ωc 0< ∑ uij < m, ∀j = 1Lc Clusters formed by the applications clustering algorithms j =1 represent a group of user sessions that are similar based on co- The performance index J(U,V,X) of fuzzy c-mean clustering occurrence patterns of URL references. Clustering of user can be specified as the weighted sum of distances between the sessions results in a set C = { c1 , c2 , … , ck } of clusters, where data points and the corresponding centers of the clusters. In each ci is a subset of S, i.e., a set of user sessions. Each cluster general it takes on the form: represents a group of users with similar navigational patterns. ∑∑ u d (x , v ) c m q 2 J (U ,V , X ) = ij ij i j (4) IV. EXPERIMRNTAL RESULTS j =1 i =1 In order to discover the clusters that exist in user accesses where , sessions of a web site, we carried out a number of experiments. q ∈ [1, ∞ ] is the fuzziness index of the clustering The Web access logs were taken from the P.A. College of 2 ( ) d ij x i , v j is the disatnce between x i and v j Engineering, Mangalore web site, at URL http://www.pace.edu.in. The site hosts a variety of information, (x , v ) = ∑ w(x ) x n 2 i j including departments, faculty members, research areas, and d ij i j i k − vk course information. The Web access logs covered a period of k =1 one month, from February 1, 2011 to March 1, 2011. There w( xi ) is the weight of the data point xi were 74,924 logged requests in total. Minimization of the performance Index J(U,V,X) is usually After performing the cleaning step the output file contains achieved by updating the grade of memberships of data points 30720 entries. Number of the site URLs with access count and centers of the clusters in an alternating fashion until greater than or equal to 5 are 159. Total numbers of unique convergence. This performance Index is based on the sum of users identified are 24. Table V depicts the results of cleaning the squares criterion. During each of the iterations, the cluster and user identification steps. centers are updated as follows: m TABLE V. RESULTS OF CLEANING AND USER IDENTIFICATION ∑u i =1 q ij x i Items Count vj = m (5) ∑u q Initial No of Log Entries 74924 ij i =1 Log Entries after Cleaning 30720 Membership values are calculated by the following No. of site ULRs 159 formula: No of Users Identified 24 75 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 6, 2011 As far as clustering of the User Sessions is concerned those URLs which are accessed only once do not play any significant role in forming the clusters since they appear in only one of the user sessions. Therefore we eliminate all such URL requests from our further analysis. This type of URL filtering is important in removing noise from the data. Since a user session is represented by an n-dimensional vector, where n represents the number of the site URLs accessed in the log files. Reduction in the number of URLs also reduces the session vector dimensions. The count of the URLs which are accessed only once is 5372. After eliminating them the total number of unique URLs for sub sequent analysis is 1478. In order to identify the user sessions we applied two different kinds of time oriented heuristics TOH1 and TOH2. Details of these Figure 8. Percentage of URLs versus URL Access Frequency results and the comparisons of these approaches can be found from our previous work [17]. The result of application of TOH1 is given in Table VI. Graph in Figure 9 depicts the results of TABLE VI. RESULTS OF CLEANING AND USER IDENTIFICATION application of Time oriented heuristics TOH1 and TOH2. Items Count Figure 10 shows the number of URLs and their No. of User Sessions 968 968 corresponding session support count. Our result shows that 396 Minimum no. of URLs accessed in a session 1 URLs have a session support count of one. We eliminate these Maximum no. of URLs accessed in a session 545 URLs since they can't play any significant role clusters formation. This type of session support filtering provides a Average no. of URLs accessed in a session 26.12 form of dimensionality reduction in subsequent clustering tasks Minimum no. of unique URLs accessed in a session 1 where URLs appearing in the session file are used as features. Maximum unique URLs Accessed in a session 158 Table 4 shows the results of user session identification after the Average unique URLs Accessed in a session 6.5 elimination of these low support URLs. Total number of unique URLs of the Web Site present in the log file entries is 6850. Figure 6 shows the percentage of the URLs against how many times they are accessed in the log file. It is clear from the graph that 78% of URLs were accessed only once, 16% of them were accessed twice and only 6% of them are accessed three or more times. Maximum access count for a URL is 2234. On average each URL is accessed 4.47 times. Figure 10. No. of URLs Versus No. of Sessions They are Associated with Figure 9. Sessionization results for TOH1 and TOH2 Figure 11. No. of Sessions Versus No. of URLs 76 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 6, 2011 Figure 11 depicts the session counts against various URL counts. Our results show that there are quite a large number of user sessions containing only few URLs. For example there are 67 sessions containing one only URL, 134 containing two URLs and 56 sessions containing three URLs. User sessions with smaller number of URLs are less significant for the purpose of clustering. We are interested in only those sessions that access more than a certain number of URLs, say MinURLs. For example, it is not very useful to cluster user sessions which just access the URL for home page and leave. Therefore we impose certain constraints desirable for better clustering performance and outcome by using a Fuzzy set theoretic approach to assign the weights to various user sessions based on the number of URLs Figure 12. No. of Clusters Versus Performance Index they contain. Instead of directly removing all the small sessions below a specified threshold, we assign weights to all the In order to decide the number of optimum clusters we sessions using a "Fuzzy Membership Function" based on the calculated the validity index (S), which is the ratio of number of URLs accessed by the sessions. compactness to separation using the equation (7). Based on the sessionization result as shown in graph of figure 11, we choose the lower bound on the number of URLs accessed in a session (LB) as 1 and an upper bound on the number of URLs accessed in a session (UB) as 6. Using equation (1) weights assigned to various sessions are specified in Table VII. TABLE VII. SESSION WEIGHTS BASED ON THE URL COUNT Session URL Count Session Weight 1 0 2 0.2 3 0.4 4 0.6 5 0.8 Figure 13. Validity Index Versus No. of Clusters for Weighted Sessions 6 or more 1 Once use sessions are assigned the weights based on the URL count, Fuzzy c-Mean clustering algorithm is applied to discover session clusters that represent similar URL access patterns. Application of the Fuzzy c-means clustering algorithm resulted in the formation of overlapping clusters. The performance Index J(U,V,X) of fuzzy c-mean clustering is calculated using equation (4). It is the weighted sum of distances between the data points and the corresponding centers of the clusters. Minimization of the performance Index J(U,V,X) is achieved by updating the grade of memberships of data points and centers of the clusters in an alternating fashion using the equations (6) and (5) respectively, until convergence. Fuzzy c-Mean clustering is first applied by choosing the Figure 14. Validity Index Vs. No. of Clusters for Non-Weighted Sessions number of clusters as 4. During each of the iterations we increased the number of clusters by 1 till the number of clusters Figures 13 and 14 provide the graphs of validity index (S) is reached to 60. We repeated the above process for weighted versus number of clusters for weighted and non-weighted as well as non-weighted sessions. Graph is figure 12 shows the sessions respectively. Our results show that for the weighted performance index (J) versus number of clusters for weighted sessions validity index is minimized when value chosen for the as well as non-weighted sessions. From the graph it is clear that number of clusters is 8. On the other hand for the case of non- "Fuzzy Set Theoretic" weighted session approach results in weighted sessions, validity index is minimized when the better minimization of the performance index than non- number of clusters is 21. Thus the optimal number of clusters weighted session approach. for weighted sessions is 8 and for non-weighted sessions it is 21. 77 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 6, 2011 V. CONCLUSION AND FUTURE WORK [11] P. Kolari and A. Joshi, "Web mining: research and practice," Computing in Science and Engineering, vol. 6, no. 4, pp. 49–53, 2004. In this paper, we discussed our methodology to preprocess [12] W. Tong and H. Pi-lian, "Web log mining by an improved aprioriall the web log data including data cleaning, user identification algorithm," in In proceeding of world academy of science, engineering, and session identification. We also discussed the details about and technology, 2005, pp. 97–100. how to apply the Fuzzy c- Mean Clustering algorithm in order [13] A. Joshi and R. Krishnapuram, "Robust fuzzy clustering methods to to cluster the user sessions. support web mining," 1998. [14] D. Tanasa and B. Trousse, "Advanced data preprocessing for intersites In order improve the clustering results; we proposed a web usage mining," IEEE Intelligent Systems, vol. 19, no. 2, pp. 59–65, "Fuzzy Set Theoretic" approach for the removing the sessions 2004. with very few URLs. Instead of directly removing all the small [15] F. Klawonn and A. Keller, "Fuzzy clustering based on modified distance sessions below a specified threshold, we assign weights to all measures," in Advances in Intelligent Data Analysis, ser. Lecture Notes the sessions using a "Fuzzy Membership Function" based on in Computer Science, D. Hand, J. Kok, and M. Berthold, Eds. Springer Berlin / Heidelberg, 1999, vol. 1642, pp. 291–301. the number of URLs accessed by the sessions. We described [16] D. Tanasa and B. Trousse, "Data preprocessing for wum," Intelligent our methodology to perform feature subset selection of session Systems, IEEE, vol. 23, no. 3, pp. 22–25, 2004. vectors and session weight assignment. Finally we compared [17] Z. Ansari, M. F. Azeem, A. V. Babu, and W. Ahmed, "Preprocessing our soft computing based approach of session weight users web page navigational data to discover usage patterns," in The assignment with the traditional hard computing based approach Seventh International Conference on Computing and Information of small session elimination. Our results show that the "Fuzzy Technology, Bangkok, Thailand, May 2011, proceeding vol. 1 pp. 18- Set Theoretic" approach of session weight assignment results in 189. better minimization of clustering performance index than [18] P. Berkhin, "Survey of clustering data mining techniques," Springer, 2002. without session weight assignment. [19] B. Pavel, "A survey of clustering data mining techniques," in Grouping We believe that the above results can be further improved if Multidimensional Data. Springer Berlin Heidelberg, 2006, pp. 25–71. we use fuzzy set theoretic approach for the inclusion of a URL [20] R. Xu and I. Wunsch, D., "Survey of clustering algorithms," Neural in user session instead of using crisp time threshold β. In our Networks, IEEE Transactions on, vol. 16, no. 3, pp. 645–678, May 2005. current strategy a URL is not included in the current sessions if [21] M. Chau, R. Cheng, B. Kao, and J. Ng, "Uncertain data mining: An it comes even one second later then the specified time example in clustering location data," in Advances in Knowledge Discovery and Data Mining, ser. Lecture Notes in Computer Science, W. threshold. We can apply a similar Fuzzy set theoretic approach Ng, M. Kitsuregawa, J. Li, and K. Chang, Eds. Springer Berlin / to the assign the weights to the URLs based on how many Heidelberg, 2006, vol. 3918, pp. 199–204. times they are accessed. [22] X. L. Xie and G. Beni, "A validity measure for fuzzy clustering," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. PAMI-13, p. 841847, 1987. REFERENCES [23] R. Cooley, B. Mobasher, J. Srivastava et al., "Data preparation for mining world wide web browsing patterns," Knowledge and Information [1] R. Cooley, B. Mobasher, and J. Srivastava, "Web mining: Information Systems, vol. 1, no. 1, pp. 5–32, 1999. and pattern discovery on the world wide web," in Ninth IEEE [24] B. Berendt, B. Mobasher, M. Nakagawa, and M. Spiliopoulou, "The International Conference on Tools with Artificial Intelligence, impact of site structure and user environment on session reconstruction Proceedings, 1997, pp. 558–567. in web usage analysis," in WEBKDD 2002 - MiningWeb Data for [2] Y. Fu, K. Sandhu, and M. Shih, "A generalization-based approach to Discovering Usage Patterns and Profiles, ser. Lecture Notes in Computer clustering of web usage sessions," Lecture Notes in Computer Science, Science. Springer Berlin / Heidelberg, 2003, vol. 2703, pp. 159–179. pp. 21–38, 2000. [25] L. D. Catledge and J. E. Pitkow, "Characterizing browsing strategies in [3] H. L. T. Mobasher, B.and Dai and M. Nakagawa, "Effective the world-wide web," Computer Networks and ISDN Systems, vol. 27, personalization based on association rule discovery from web usage no. 6, pp. 1065–1073, 1995, proceedings of the Third International data." in In: Proceedings of the 3rd ACM Workshop on Web World-Wide Web Conference. Information and Data Management (WIDM01), Atlanta, Georgia [26] B. Berendt and M. Spiliopoulou, "Analysis of navigation behaviour in November, 2001. web sites integrating multiple information systems," The VLDB [4] M. Spiliopoulou and L. C. Faulstich, "Wum: A web utilization miner," Journal,vol.9, pp. 56-75, 2000. in In Proceedings of EDBT Workshop WebDB98, Valencia, Spain, LNCS 1590, Springer Verlag., 1999. AUTHORS PROFILE [5] B. Mobasher, R. Cooley, and J. Srivastava, "Automatic personalization based on web usage mining," Commun. ACM, vol. 43, pp. 142–151, Zahid Ansari is a Ph.D. candidate in the Department of CSE, August 2000. Jawaharlal Nehru Technical University, India. He received his ME [6] U. Fayyad and R. Uthurusamy, "Data mining and knowledge discovery from Birla Institute of Technology, Pilani, India. He has worked at in databases," Communications of ACM, vol. 39, pp. 24–27, 1996. Tata Consultancy Services (TCS) where he was involved in the [7] W. H. Inmon, "The data warehouse and data mining," Communications development of cutting edge tools in the field of model driven of ACM, vol. 39, pp. 49–50, 1996. software development. His areas of research include data mining, soft [8] M. K. Jiawei Han, Data Mining: Concepts and Techniques. Academic computing and model driven software development. He is currently Press, Morgan Kaufmarm Publishers, 2001. with the P.A. College of Engineering, Mangalore as a Faculty. He is [9] P. S. U. M. Fayyad, G. Piatetsky-Shapiro and E. R. Uthurusamy, also a member of ACM. "Advances in knowledge discovery and data mining," in CA: AAAI/MIT Press, 1996. Mohammad Fazle Azeem is working as Professor and Director of [10] J. H. Ming-Syan Chen, "Data mining an overview from database department of Electronics and Communication Engineering, P.A. perspective," Knowledge and data Engineering, IEEE Transactions on, College of Engineering, Mangalore. He received his B.E. in electrical vol. 8, 1996. engineering from M.M.M. Engineering College, Gorakhpur, India, 78 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 6, 2011 M.S. from Aligarh Muslim University, Aligarh, India and Ph.D. from His current research interests are algorithms, information retrieval Indian Institute of Technology (IIT) Delhi, India. His interests and data mining, distributed and parallel computing, Network include robotics, soft computing, evolutive computation, clustering security, image processing etc. techniques, application of neuro-fuzzy approaches for the modeling, and control of dynamic system such as biological and chemical Waseem Ahmed is a Professor in CSE at P.A. College of processes. Engineering, Mangalore. He obtained his BE from RVCE, Bangalore, MS from the University of Houston, USA and PhD from the Curtin A.Vinaya Babu is working as Director of Admissions and Professor University of Technology, Western Australia. His current research of CSE at J.N.T. University Hyderabad, India. He received his interests include multicore/multiprocessor development for HPC and M.Tech. and PhD in Computer Science Engineering from JNT embedded systems, and data mining. He has been exposed to University, Hyderabad. He is a life member of CSI, ISTE and academic/work environments in the USA, UAE, Malaysia, Australia member of FIE, IEEE, and IETE. He has published more than 35 and India where he has worked for more than a decade. He is a research papers in International/National journals and Conferences. member of the IEEE. 79 http://sites.google.com/site/ijcsis/ ISSN 1947-5500
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The Isthmus Guest List is back with another round of free tickets to amazing concerts, shows and more fun events around Madison. This week's contests include tickets to: The Dandy Warhols, Abigail Washburn & the Sparrow Quartet, and Suzanne Westenhoefer at the Barrymore; Walls of Jericho at the Annex; Tender Meat at the Project Lodge; Apparatus, The John Masino Band, and LUBE at The Club Tavern; The Derek Trucks Band and Great Big Sea at the Majestic; the Real ID Act and Lorenzo's Music at The Frequency; and more.
In this week's list:
- Apparatus and The Nod team up to stir up the crowd at the Club Tavern on Friday, August 22. Win tickets here!
- Bring your dancing shoes to boogie all night long with the Real ID Act, El Valiente, Czarbles, and Pat Boone's Farm at The Frequency Lounge on Friday, August 22. Win tickets here!
- Harmonious Wail, Gypsy Rhythm Project, Gonzalo Bergara with Kevin Nolan (from the John Jorgenson Quintet and The Robin Nolan Trio), Hot Club of Detroit, and others will keep you moving during the Midwest Gypsy Swing Festival on Friday, August 22 and Saturday, August 23 at Art in the Barn. Win tickets here!
- The Trek Urban Assault Ride is a funky bike scavenger hunt that involves street-smart riding, obstacle courses, and a huge party. Enter here for a place on the Isthmus team!
- Walls of Jericho, 36 Crazyfists, It Dies Today, Sea of Treachery and Flatline will keep you rocking all night long in a show at the Annex on Saturday, August 27. Win tickets here!
- The John Masino Band will share its tuneful passion in a show at the Club Tavern on Saturday, August 30. Win tickets here!
- Three-time Madison Area Music Awards winner Lorenzo's Music will rock the audience in a CD release party at the Frequency Lounge on Saturday, August 30. Win tickets here!
- The high-energy rock band LUBE will wow audiences at the Club Tavern on Saturday, September 6. Win tickets here!
- The Derek Trucks Band will bring its blend of jazz, rock, blues, Latin, Eastern Indian, and other sounds to a show at the Majestic Theatre on Tuesday, September 9. Win tickets here!
- The Dandy Warhols return to town in support of its new album Earth to the Dandy Warhols with a show at the Barrymore Theatre on Wednesday, September 10. Win tickets here!
- Great Big Sea will share its mix of traditional Celtic and pop tunes with a show at the Majestic Theatre on Thursday, September 11. Win tickets here!
- Tender Meat, Trin-Tran, Peaking Lights, Gay Beast will set up camp for a show at The Project Lodge on Saturday, September 13. Win tickets here!
- Abigail Washburn & the Sparrow Quartet will be joined by Bela Fleck for a performance that crosses global and cultural lines at the Barrymore Theatre on Tuesday, September 16. Win tickets here!
- Hilarious stand-up comedienne Suzanne Westenhoefer performs at the Barrymore Theatre on Friday, September 19 . Win tickets here!

subset: commoncrawl


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Understand the Cause of Depression
…or molybdenum from the diet can all be the problem. Excessive copper has also been linked to high blood pressure, ringing in the ears, premature baldness, joint pain, insomnia and pigmentation of the face. Bringing copper levels to normal can usually be done naturally with additional zinc and vitamin…Read More


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Wounded Veteran Receives Bionic Ankle
January 4, 2012
A Mississippi veteran who lost his leg after returning from Vietnam receives a bionic ankle…a computerized, battery-powered ankle that acts as a calf muscle and an achilles tendon. David Kenney reports.
Topics: Anatomy, Human anatomy, Achilles tendon, Triceps surae, Achilles, Tendons, Calf, Greek mythology, Biology


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" City: Arequipa / Country: Peru / World Region: South America "
* Prices may differ from that shown
Arequipa is a Peruvian city in the far south of the country that is nestled 2380m above sea level in the Andes, about a half a day drive from the coast. Known as the "White city", from its white stone buildings of unique architecture dating from the Spanish days, it has a very strong European feel. The city is Peru's second biggest city after Lima. We arrived here by bus from the coast which meant it gave us our initial experience of high altitude - take it easy and acclimatize gradually before you attempt to do anything!
===Plaza de Armas===
The heart and main square in the city is the Plaza de Armas and is probably the most beautiful of any city that we visited in Peru. During our stay, we saw a concert taking place there in the evening, and a demonstration during the day. Shops and cafes adorn the square and are a good place to take a leisurely breakfast. On the square is the city's colonial era Cathedral - an imposing site that is a definite must see. It is hard to give a precise age for the cathedral, since was damaged in earthquakes and fires several times in the 16th and 17th century.
We stayed in the Conquistador hotel. This was a three star hotel that was about 5 minute walk from the Plaza de Armas. It was comfortable and clean and had internet acces and televisions in the hotel rooms. The rooms currently cost US$49 per night for a twin room according to their web site and the hotel had a restaurant that served a passable breakfast that was included in the price.
We visited several restaurants during our stay, but only one stuck out as a bit different - restaurant Zigzag. It is a two-tier restaurant close to the Plaza de Armas. Meat eaters can tuck into a trio of stone-grilled ostrich, alpaca and beef steaks, and get given a stylish bib with a cartoon animal on representing the animal being eaten. Vegetarians should try one of the quinoa dishes - this is a staple seed of South America which is highly nutritious and tastes a little like cous cous. Dinner here cost about US$25 including wine.
===Night life===
The night life here is extremely varied. Live music was easy to find, as were bars and clubs. The restaurants are open very late, so a relaxed late dinner is another option. The busy streets felt a little overcrowded, though, and we were warned about crime against tourists in the evening - mainly pick pocketing rather than violent crime.
This is a good place to buy souvenirs, but the city of Cuzco is better, if you are visiting. Alpaca wool clothes are extremely cheap in comparison to the UK, but make sure your luggage allowance is sufficient - they are heavy. I came back with nearly twice as much luggage by weight as I went out with!
===El Mirador===
If you have the opportunity, do take a taxi out of the city to the viewing tower at Sachaca in time for sunset. From here there are unrivalled views of nearby El Misti, a snow-capped volcano that is over 5800m high. At dusk, the mountain was coloured a bright red colour, which makes for spectacular photographs. The viewing tower (el Mirador in Spanish) is a five storied high white tower located in a small village in the middle of vast flat fields, making for a stunning panorama. If you are newly arrived at this altitude, take care to take it slowly as you climb the tower - it's a fairly strenuous climb if you can't breathe as easily because of the reduced oxygen levels.
To get there, we piled four deep into the back of a taxi (and one in the front), then started a hair-raising experience that made us glad we were so tightly wedged in, since there were no seatbelts. The driving style involved veering between mini-gaps in the traffic to make progress - I'm sure they must have teleport technology installed in the cars to make such navigation possible. The driver then waited around for us and picked us up after sunset. The trip back to the city was even more alarming because the taxi had no lights after the electrics caught fire and billowed smoke from the bonnet and air vents. This excursion cost us around $15 per person.
===Juanita, the Ice Princess===
Arequipa is the current resting place of Juanita, the Inca Maiden and ice mummy. She was a young girl who lived during the Inca period around 560 years ago and who was selected as a sacrifice on behalf of her people, a ritual called capacocha. Child sacrifices occurred during important or difficult periods (e.g. crop failure) and were of the most perfect children. These children were fattened up before being taken up high into the mountains, given calming drugs and then sacrificed. Their bodies were reverently wrapped and buried or placed in sheltered places near the summit, together with many burial goods, such as dolls. This was Juanita's fate, and the year-round snowy climate can caused excellent preservation of the body in a natural mummification process. Then, centuries later in the 1990s, she was discovered by climbers. After intensive study, she was put on display in the Museu Satuarios Andinos museum in Arequipa, where I visited her. Visiting this museum costs US$5.
===Some other activities nearby===
We weren't feeling up to it because of the altitude, but mountain biking is a very popular activity around Arequipa. For the real hiking enthusiast, there are some very strenuous trails in the mountains, including up El Misti.
Deserving entire reviews in their own right are Colca Canyon and Santa Catalina convent. In brief, Colca canyon is one of the few places in the world to go to see Andean Condors (which inspired the tune El Condor Pasa, a tune that soon annoys with its omnipresence in all the cafes and hotels in Peru). The canyon is deeper than the Grand canyon, and requires a good head for heights to visit.
Santa Catalina Convent is located in the city centre and is a cloistered convent that is open to tourists to see how the nuns lived and worked in their sheltered world.
Arequipa is a beautiful and unique city that is nothing like the rest of Peru. If you visit Peru, you must come here for a few days to look at the colonial era architecture.
Review will be posted elsewhere


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The Comedy In Fifty Shades of Grey
By Amy Nicholson
Wild Tales Lays Bare Everyone's Awfulness
By Stephanie Zacharek
Approaching the Elephant Is a Bracing Education Doc
By Calum Marsh
By Stephanie Zacharek
By Inkoo Kang
The Results of Our 2014 Film Critics' Poll
By Voice Film Critics
By Alan Scherstuhl
The Blue Room (La Chambre bleue)
By Alan Scherstuhl
Sure to become a sacred text to surf-movie enthusiasts, but surprisingly watchable even for those who think "goofy-footing" is a new Southern hip-hop dance craze, Dana Brown's Highwater visits Oahu's North Shore during the three biggest surf tournaments of the year. As a sports story, Brown's movie underwhelms: In a fruitless attempt to keep up with the leaderboards of three separate men and women's events, his intrusive voiceover pulls more and more characters into the film. And anyway, these competitions took place in 2005; you can Google the winners. But for devotees of the Surf God archetype—sun-kissed, wild-haired, with low-riding board shorts and dazed eyes—it's required viewing. And as an exploration of one of the more interesting corners of America, a place where country living meets big money eight weeks out of the year, Highwater is legitimately compelling. Brown doesn't shy away from the North Shore's inherent conflicts—"I pray for another hurricane to come through and rip down these houses," Hawaiian-born Sunny Garcia grouses—and he captures the North Shore's unique vibe through lively interviews with the surfers devoted to its beaches, from world-class pros to a homegrown loon known for surfing Waimea Bay on a rescue board wearing a football jersey.
Shot mostly on digital video, Highwater's actual surf footage is less vivid than the gorgeous blue tableaux of Brown's 2003 classic Step Into Liquid—or, for that matter, his dad Bruce's Endless Summer. Highwater's emphasis on competition surfing, with its difficulty requirements and time limits, means that most on-the-water sequences cut quickly from move to move, offering little in the way of context. (It's not for lack of coverage; often, we can see more wet-suited cameramen bobbing in the waves than surfers.) Only in the film's final sequence, a duel at the Pipeline Masters between local underdog Kalani Chapman and No. 1 seed Kelly Slater, does Brown treat viewers to long, breathtaking rides through perfectly formed pipes. It's at that moment that even a nonsurfer can understand what North Shore native Mark Healey is talking about when he describes the pleasures of surfing the big waves of Sunset Beach in December: "It makes you feel really small," the blond dreamboat says winningly. "I love that feeling."
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Man arrested for suspected loanshark harassment after splashing paint on cars
Published on Aug 8, 2014 9:38 AM
SINGAPORE - A 39-year-old man was arrested for suspected loanshark harassment of vehicle owners in Woodlands and Yishun.
The police said on Friday that they received reports between July 21 and July 30 of vehicles parked at carparks in the two estates that had been splashed with red paint, and discovered debtors notes.
Officers from the Criminal Investigation Department identified the man and he was arrested on Thursday afternoon at Admiralty Link. He is believed to be responsible for targeting seven vehicles. The police also seized mobile phones and a notebook believed to contain debtors' records.
If found guilty of acting on behalf of an unlicensed moneylender and committing or attempting to commit any acts of harassment, he may be jailed for up to five years, fined between $5,000 and $50,000 and receive between three and six strokes of the cane.


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Celebrities Strut The Runway At The Etisalat Launch
On April 05th 2012, one of Nigeria's leading telecommunication giants Etisalat, launched its new brand communication campaign with an evening full of attitude, swag and style.
Celebrities models showed their support to the communication network by strutting their stuff down the runway.
Check out some pictures..
- Post a comment


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SANANTONIO Ozzy Osborne is back in the Alamo City.
He's not here in person, but on a Fiesta medal.
Artpace, a local non-profit dedicated to the advancement of contemporary art, featured the rocker on its first ever Fiesta medal.
We sold out in 48 hours online, said Artpace executive director Amanda Cruz.
The medal was designed by artist Jim Mendiola and Ruben Ortiz-Torres, reflecting a project from 2001. It pictures Ozzy as a bat, with an upside down Alamo serving as each wing.
Ozzy has a well-known history in San Antonio -- particularly at the Alamo. He was supposedly banned from ever performing in San Antonio after he was arrested in 1982 for urinating on the Alamo. It's a sore subject to some proud Texans, but also a quirky mishap that earned San Antonio another mention in rock and roll history.
It's all in good fun, Cruz said.
It would be a fun conversation starter, said Michael Helms, who was shown the medal at the NIOSA celebration on Thursday afternoon.
Not everyone agreed. One Fiesta-goer said, Hell no, I would not wear it.
Sarah Reveley described Ozzy as a rock singer who is still a drug addict.
What do you think?Join the conversation on the KENS 5 Facebook page!


text: Spadra Recreation Area & Campground River Valley Region View Website Calculate Trip Clarksville Save to foursquare Get Directions Overview:Located on the Arkansas River in the west-central part of the state, this lake is a major unit of the Arkansas River Navigation Project. The lake stretches 50 miles up the Arkansas River Valley from Dardanelle Lock and Dam to Ozark-Jeta Taylor Lock and Dam. About 315 miles of shoreline give the visitor ample fishing and camping opportunities. A visitor's center, located 1.5 miles west of Hwy. 7 at the Old Post Road Park, has exhibits that explain the development of the Arkansas River Valley from the days of the Indians to the present through interpretive exhibits entitled "Renaissance of a River." Address: Spadra Recreation Area & Campground Ark. 103 South Clarksville, AR 72830 Phone: 479-968-5008 Website: www.swl.usace.army.mil/Missions/Recreation/ArkansasRiver/Dardanelle.aspx E-mail: email@example.com GPS: N35.4255 W93.4739 Miscellaneous No Smoking Restaurant on Site/Nearby Recreation Pets Accepted Picnic Area Accessible On or Near: Lake Dardanelle Marina Details Snack/Groceries Campground Details Campsites: 30 RV/Tent with E and shared water Facilities: Flush toilets, water, showers, marina, restaurant, boat dock and ramp, pavilion, trailer dump station. (Open year-round). User's fee charged.


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The 1000 Genomes Project, an international public-private consortium to build the most detailed map of human genetic variation to date, announces the completion of three pilot projects and the deposition of the final resulting data in freely available public databases for use by the research community. In addition, work has begun on the full-scale effort to build a public database containing information from the genomes of 2,500 people from 27 populations around the world.
Launched in 2008, the 1000 Genomes Project first conducted three pilot studies to test multiple strategies to produce a catalogue of genetic variants that are present in one percent or greater frequency in the different populations chosen for study (European, African and East Asian). Disease researchers will use the catalogue, which is being developed over the next two years, to study the contribution of genetic variation to illness. In addition to distributing the results on the Project's own web sites, the pilot data set is available via the Amazon Web services (AWS) computing cloud to enable anyone to access this unprecedentedly large data set, even if they do not have capacity to download it locally.
"I am indebted to all the project researchers who are making this collaboration so successful," said Richard Durbin, PhD, of the Wellcome Trust Sanger Institute, who is co-chair of the consortium. "In the pilot projects we have made significant progress in optimising the use of next generation sequencing platforms to study human genetic variation, and we can now apply what we have learned to accelerate our efforts to sequence this reference collection of human genomes."
"Completing the goals of the initial pilot projects has been critical to informing how to apply next-generation sequencing in human genetic research, and provides a solid foundation the next stage of the project," said David Altshuler, MD, PhD, of the Broad Institute, Cambridge, Massachusetts, and
|Contact: Don Powell
Wellcome Trust Sanger Institute


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Student Driver Safety Course Information
Students must review the Student Driving requirements contained in the Driving College Owned and Rented Vehicles Section as there are multiple steps in the process to be approved to drive Ithaca College owned, leased and rented vehicles.
As of 08/04/2014 the mandatory Student Driver Safety Course will ONLY be offered online through United Educators, hereinafter referred to as UE.
*Important: United Educators is a resource to offer driver safety awareness and training; the course is not meant to completely fulfill each institution's needs, but rather it enhances driver awareness. Please keep in mind that the Ithaca College Driving College Vehicles Policy and the Student Driver Handbook always supersede, so it is important to be familiar with the policies and procedures.
As an example; below are a few instances where the online training differs:
- Students are restricted to mini-vans that do not exceed a 7 person occupancy limit.
- College vehicles do not currently have all emergency equipment referenced in the training.
- Student drivers should not exceed three hours of driving before switching to another driver.
Prior to driving a College owned, rented or leased vehicle, a student must: complete the following in the order listed:
- Read the Ithaca College Student Driver Handbook
- Become familiar with the Ithaca College Driving College Vehicles Policy.
- Take the UE online Safety Course; allow for two (2) hours to register and complete the online Safety Course including the test at the conclusion.
- Provide the test Transcript/Certificate from the UE Website to the Office of Risk Management, please be sure that your grade is showing on the document.
- Submit a Driver Information Form to Risk Management. (Please note: the Driver Information Form must be signed by you, at this time electronic signatures are not accepted, your form will not be processed.)
The instructions for accessing the online UE Student Driver Course can be found here. Please follow steps 9 & 10 in order to print the required course transcript.
The link for accessing the UE Student Driver Course can be found here.


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May 29, 2015
Sea shell lovers from all over the country gathered at the Panama City Senior Center over the weekend to showcase some their most prized possessions.
The 16th Annual Shell Show, hosted by the Gulf Coast Shell Club, wrapped up Sunday.
Some collectors at the show had shells for sale and others were just showcasing some of their best finds.
Prizes were awarded in multiple different categories, including artistic and scientific.
Linda Bruner, President of the Gulf Coast Shell Club says, "We are a non-profit organization. We do it as a community service to educate people to let them see shells from all over the world."
Carol Mitchell has been collecting shells all her life. "I just love shells. I grew up on the Atlantic Sea Coast and I have collected shells there and all over the world and here!"
All the proceeds from the event will go towards the Shell Club's effort to provide scholarships and research for the community.
Click Here to access the online Public Inspection File
Viewers with disabilities can get assistance accessing this station's FCC Public Inspection File by contacting the station with the information listed below. Questions or concerns relating to the accessibility of the FCC's online public file system should be directed to the FCC at 888-225-5322, 888-835-5322 (TTY), or firstname.lastname@example.com.


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Atlanta Property Management
What we do as your Atlanta Property Manager
We focus on your desire to gain the highest return possible, Platinum Property Management works diligently toward finding a quality tenant. We don't offer a "guaranteed tenant placement in 10 days" We focus on quality and that process may take an additional two weeks to investigate a potential tenant's background,but we know that is is worth the wait. Focusing on quality tenants who pay on time, ensuring a reliable stream of income.
This is a short overview of our Inclusive Service Offerings. Contact us (678-710-8056) to discuss a completed list of all services included with management.
Evaluate the property
- Determine accurate rental rate
- Help establish good ROI
- Suggest recommendations to prepare home for market
Market property for rent
- Manage aspects of tenant-landlord relationship marketing as required by HUD
- Fair housing
- State and local antidiscrimination laws
- GA Real Estate Laws
- Tenant Landlord laws
Application processing
- Background, credit, employment verification.
- Landlord history and bank statements/proof on income.
- Negotiate contingency items with landlord and tenant
Preparing for Move in
- Prepare lease
- Collect funds
- Pictorial timeline
- Accounting Services
- Annual Statements for tax purposes
- Itemized statement of expenses, rent receipts and direct deposits online.
- Archive historical data
- Online monthly owner cash flow statements
Rent Collections
- Receiving rent, streamlines via online portals
- Collection of late payments and enforcing late payments
- Pictorial timeline. Move in , move out and anniversary photo
- Periodic Inspections with photos and reports
Responsive Maintenance Systems
- No surcharges
- Notification of maintenance requests
- 24x7 emergency hotline
- Updating owners and tenants of status of requests
Tenant Move Out
- Assess deductions for cleaning, damages and unpaid rent
- Security deposit itemization as governed by GA Real Estate Laws, tenant landlord laws and fair housing laws
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Sidney Stephens
We switched to PPM after a terrible experience with another management company that left us without a renter and with an improperly listed property. Phil and Jennifer with PPM assured us that we would be taken care of and delivered. The week we signed with them we had a showing, and soon after a tenant. They have exceeded our expectations and been very communicative. We are looking forward to a long-term relationship with PPM.
Charlie Rolader
Platinum has been our property management company for more than four years and our experience has been terrific! The entire Platinum Team has been very professional, responsive, and helpful in keeping our property cared for, and our tenants happy as well. We are more than 600 miles away from our residence and we could not have managed this entire process without the help of Platinum. If we need a property management company in the future, it will definitely be Platinum! A special thank you to Jan Pederson as well who has been exceptionally helpful to us.
Chuck Corcoran
Great service, very professional, and never had an issue in over 3 years.
Dennis Moore
I worked with Jennifer and she was a go getter and a true professional. She was on top of all the small details that could have very easily slipped through the cracks. She listed my home and had a contract in less than 3 weeks. She kept me in the loop on everything to do with the house. A pleasure to work with!
Kathy Sheffield
Less than two weeks after signing with Platinum a tenant had paid their deposit and planned to move in. We had gone through an arduous renovation of a 1920 farmhouse but were a little unsure if our property would be perceived by others as we saw it. Cassie's first visit assured us a tenant would be easily found for our "charming" little house. All the staff walked us through the process, the paperwork and answered our many questions promptly. What a nice group! We look forward to a long relationship.
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GREAT company!!! We at ClimateSmith, LLC work with other property management groups and there's none like Platinum Properties. Jan is very prompt with communicating all heating and cooling problems with our office. This is very important when the temperatures are extremely hot or cold outside. Communicating problems and obtaining approval during these temperatures are critical for any property management company. Other companies we've worked with do not make this a priority which causes BIG headaches with tenants. Thanks Jan and the team at Platinum for your GREAT effort.
Debra, Sarah, James and Jason.
Atlanta Area Info
Forbes Lists Atlanta as one of the best places for business and careers and job growth.
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- Itzza Pizza Party - Standup
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An Itzza Pizza Party themed party is a fun way to celebrate your child's birthday. BirthdayExpress.com has a variety of Itzza Pizza party supplies, like our centerpieces, dessert plates, invitations, and more.Read More
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"One Mississippi, two Mississippi…," students in Laura Patterson's fifth grade class counted as they filled plastic bags with water from the bathroom faucets of Mountain Elementary School. This activity was part of a water audit done by the students in the Gifted and Talented Education (GATE) program as an important step in their quest to create a more sustainable Mountain school.
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|Omni Hotels Millsboro hotels are provided below. Search for cheap and discount Omni Hotels hotel rooms in Millsboro, DE for your personal or business trip. We list the best Omni Hotels Millsboro hotels/lodging so you can review the Millsboro Omni Hotels hotel list below to find the perfect place.
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Scheduled alongside the Listed Mornington Cup and Listed Hareeba Stakes, the $250,000 Inglis Premier run over 1200m, is restricted to two-year-olds nominated to the Inglis Race Series which were offered at last year's Inglis Melbourne Premier Yearling Sale.
Last year's victor Masthead followed up his Inglis Premier win with a third placing in the Group One MRC Blue Diamond Stakes ten days later. Masthead's victory in the 2011 Inglis Premier guaranteed his spot in the Blue Diamond field with first place prizemoney in the Inglis Premier allowed when assessing Blue Diamond ballot conditions.
This year's race will be hotly contested with two last start stakes-placed horses taking their place in the field. The Gerald Ryan trained Snitzerland is attempting to win the Inglis Premier first-up following her narrow defeat at Flemington on Melbourne Cup day in the Listed Emirates Airline Plate. The Sydney filly was an impressive trial winner at Rosehill last week.
Caulfield trainer Clinton McDonald has targeted the Inglis Premier with No Smoken. The colt ran second at his only start in the Listed Blue Diamond Preview (C&G) behind The Travelling Man. Both No Smoken and Snitzerland are sired by one of the nation's leading sire of two-year-olds in Snitzel.
Another interesting runner is the Charge Forward gelding Road Trippin. The Stephen Theodore trained galloper already has a start at the track under his belt with a second placing behind subsequent stakes winner Armed For Action at Mornington last month.
The Ken Keys trained Excitus is the lone first starter in the field. Whilst the Excites filly is the most inexperienced in the race, she showed promise in her trial last October defeating Blue Diamond contender Members Joy.
Click here for breeding and sale price information of the entire field.
In addition to the $250,000 in race prizemoney on offer, the winning trainer of the 2012 Inglis Premier will receive a set of Swarovski Optik EL 42 Swarovision binoculars valued at $3,000. The winning trainer and owner will also receive an exclusive piece of Antler Luggage from the New Size Zero range.
As part of the Melbourne Festival of Racing, the 2012 Inglis Melbourne Premier Yearling Sale will be held at Oaklands on 27-29 February and 1 March. The online catalogue of 790 lots is available HERE. All yearlings sold at this sale are eligible for nomination to the lucrative $5m Inglis Race Series including the new $2.4m Inglis Triple Crown Bonus for two-year-olds and three-year-olds.
Three runners in tomorrow's race have relatives catalogued in this year's Premier Yearling Sale.
· Bellerive Stud will offer a full brother to Road Trippin, as lot 173.
· Yallambee Stud will offer a half-brother to Repousser, by Haradasun as lot 251.
· Blue Gum Farm will offer a half-brother to Weekend Getaway, by Elvstroem as lot 339.
For further information on the Inglis Race Series please visit www.inglis.com.au/races or email email@example.com
$250,000 – 2YO Inglis Premier, 1200m – Mornington VIC, 15 Feb 2012
$50,000 BONUS – 2YO Lightning Ridge Plate, 1000m – Canberra ACT, 26 Feb 2012
$50,000 BONUS – 3YO Bendigo Guineas, 1400m – Bendigo VIC, 17 Mar 2012
$50,000 BONUS – 3YO Albury Guineas, 1400m – Albury NSW, 23 Mar 2012
$100,000 – 2YO Inglis Autumn Plate, 1100m – Bendigo VIC, 11 Apr 2012
$50,000 BONUS – 2YO Open Hcp, 1200m – Warrnambool VIC, 3 May 2012
$50,000 BONUS – 2YO Open Hcp, 1200m – Wagga NSW, 3 May 2012
$50,000 BONUS – 2YO Open Hcp, 1200m – Hawkesbury NSW, 5 May 2012
Spelling & Agistment New Directory Click for details


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Fantasy: Football 2012 Mock Draft 4.0
Round Two
(13) Team Decker - DeMarco Murray RB
(14) Team Tanner - Marshawn Lynch RB
(15) Team Brown - Cam Newton QB
(16) Team Miller - Maurice Jones-Drew RB
(17) Team Evans - Jimmy Graham TE
(18) Team Cuzman - Adrian Peterson RB
(19) Team Simcox - A.J. Green WR
(20) Team Sutchar - Rob Gronkowski TE
(21) Team Prep - Andre Johnson WR
(22) Team MAGETO - Roddy White WR
(23) Team layne - Vernon Davis TE
(24) Dave Layne Is - Wes Welker WR
Round Two analysis: I imagine Team Miller feels great about getting MJD at No. 16 overall. I don't. He is not the droid you are looking for. I swear, I was not running Team Layne's team. I expect a huge season from Vernon Davis, but there's no reason to draft him in the second round. It feels right, Graham going ahead of Gronkowski. Graham will have the better season. I'm growing fonder of Green by the second. I feel like he and Julio Jones will be trying to one-up each other for the better part of the next decade. He will certainly be the leader of an incredibly inexperienced group of receivers in Cincinnati. The fact Peterson will not play in the preseason tells me he's not healthy enough for me to consider him this high. There's being cautious, and then there's worrying there is a significant chance of re-injury. I'm afraid Minnesota isn't only being cautious here.
My Pick: My dream scenario is taking a quarterback round one, and matching him with a running back like Forte or Murray or a receiver like White. I like Newton, I really do. It's just of the Top 5 quarterbacks, he has the most potential to bust. I don't say that because I think last season was a fluke. I actually expected last season -- or at least the level of success he had throwing the ball -- to happen. He reminds me a lot of his mentor, Warren Moon. No matter his athleticism, I never expected 14 rushing touchdowns. No, I feel the potential to bust comes from his style. The other Top 5 quarterbacks are purely pocket passers -- with the exception of Rodgers every now and then -- and are protected by the NFL's rules. Newton rushed the ball 126 times last season. That's a lot of opportunities to get hit by really vicious, large, angry men, who may or may not have money on the line if they can knock him out of the game. Like I said, if I have to, I will take him in the first round and hope the Under Armour lives up to its name.
Round Three
(25) Dave Layne Is - Jamaal Charles RB
(26) Team layne - Willis McGahee RB
(27) Team MAGETO - Steven Jackson RB
(28) Team Prep - Peyton Manning QB
(29) Team Sutchar - Michael Turner RB
(30) Team Simcox - Trent Richardson RB
(31) Team Cuzman - Fred Jackson RB


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Faulkner stories optioned with HBO
Oxford literary great William Faulkner's work may no longer lay dying on the shelves.
Select Faulkner novels and short stories are just a couple years away from making it to the big screen, as a new, first-look option with producer David Milch was announced Wednesday.
The result of two years of discussion after the Faulkner Conference in 2010 led to the partnership with Milch and the Faulkner Literary Estate. (December 1, 2011, Page 1)
More Faulkner movies in our future?
Here's some exciting news for fans of William Faulkner: David Milch's Redboard Productions has entered into an agreement with the William Faulkner Literary Estate to produce films and television series based on Faulkner's vast body of works. The deal, according to a news release issued this morning by the Bing Communications Group in Los Angeles, notes that the agreement covers all 19 novels and 125 short stories in the estate, "as well as other works, with the exception of those currently contracted with other parties." (November 30, 2011)
Gifts that have a long shelf life
For News Editor Jonathan Scott, Christmas and books are practically synonymous. With the big shopping weekend coming up, Scott takes the opportunity to point out the large number of local authors and locally-oriented books that are available for those looking for gift ideas. (November 23, 2011, Page 4A)
Faulkner shot at me and missed, (Thank God)
Guest columnist J.W. "Jay" Mitchell discusses what it was like for him moving to Oxford from the Mississippi Delta shortly after World War II and an encounter with literary great William Faulkner on a hunting trip. (November 21, 2011, Page 4A)
Faulkner Heritage Festival next week in Ripley
Historian Jack Lamar Mayfield writes about the Faulkner Heritage Festival held in Ripley that is planned for Nov. 4 at the Falkner House, a two-story home previously owned by Col. Willian C. Falkner, Faulkner's great-grandfather. (October 28, 2011, Page 3B)
Dean Faulkner Wells 1936-2011
OXFORD TOWN – An Oxford icon, Dean Faulkner Wells, passed away on Wednesday, July 27, just months after her memoir "Every Day By The Sun" published and was featured on the cover of Oxford Town. OT columnist and long time friend of the Wells family, Jim Dees, has gathered photos and passages from interviews and the late author's' book to pay tribute to one of Oxford's favorite daughters who is already greatly missed. Check out the moving tribute on Page 5 in this week's issue of Oxford Town. (July 28, 2011, Page 5)
Double Decker tours take riders back in time
Historical tours are sponsored by the Oxford Tourism Council and lead by local historian, Jack Lamar Mayfield, who delights those on the tour with stories about Oxford's more famous residents like William Faulkner and L.Q.C. Lamar and describes a little bit about what life was like in Oxford when the town was brand new. (July 22, 2011, Page 1B)
Come explore Faulkner's world
The 38th annual Faulkner Conference opens this Sunday with a special panel discussion on Rowan Oak with former and current curators of the museum – the center of Faulkner's universe. (July 15, 2011, Page 1A, 5a)
Exhibit of images of Faulkner opens Sunday
The 38th annual Faulkner & Yoknapatapha Conference opens Sunday with a reception for "Fauklner's Geographies: A Photographic Journey" at 1 to 3 p.m. at the University Museum where 35 photographs with Faulkner as their subject will be on display through Oct. 1. (July 15, 2011, Page 1B)
38th Annual Faulkner Conference begins Sunday, July 17
OXFORD TOWN – The complexities of space and place, borders impenetrable or porous, will be explored at the 38th annual Faulkner & Yoknapatawpha Conference, scheduled July 17-21 at the University of Mississippi. Page 11 in this week's issue of Oxford Town has information about the 38th Annual Faulkner Conference to be held at Ole Miss beginning this Sunday. (July 14, 2011, Page 11)


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We have enjoyed this but it isn't something that inspires us top take it out often. I think it was worn what I paid for it though.Published 14 months ago by Serenity Wilson
Steve Jackson who? I write this review as someone that has not played any other of Steven Jackson's games, nor do I care who he is.
This can barely be called a game. Read more
I picked this up a few days ago, and got the chance to try it out tonight with two friends. Well, to start with. Read morePublished on August 9, 2012 by Atalanta Pendragonne
Another great game from Steve Jackson! I decided to add this one to the game night collection we have and it was an instant hit. Read morePublished on July 26, 2012 by gutterdoll
It was shipped out fast! We have played it several times since, and it is a great game if you are looking to waste a little while, or between big games. Read morePublished on May 17, 2012 by Cynthia D. Calamia
I actually enjoy this game quite a bit, though the rules are a little convoluted. We end up playing with house rules more often than not. Read morePublished on April 30, 2012 by Amber M. Neely
Every item accounted for, and I got a dice pouch to keep it all in. Portable fun with the Ancient One! Very nice game to play on the go.Published on March 21, 2012 by Robert N.
This easy, fun game is something everyone should have lying around the house. It's social, fun, and easy to learn. A game only takes a few minutes and next to no intense thouht. Read morePublished on January 19, 2012 by SavageCole


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Fan Portal Joomla Template 18494
Joomla 1.5 Template that was composed by our webmaster artist Delta. It is also available as Drupal Template 20132.
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Description, Sources, Software & Requirements
Music fan site template with a red, gray, and white color scheme. The template has three columns with black text and red accents. There is a turn table in the header with some arrow decorations and headphones. The content areas have white backgrounds with black and gray text split into three columns. Fan Portal Joomla Template 18494 is available in the following sources: .PSD, and .PHP. Software required includes Winzip 9+ (Windows) or Stuffit Expander 10+ (Mac) for uncompressing .zip files, Adobe Photoshop CS+, Adobe Dreamweaver 8+ (or any php-editor), Joomla! 1.5.0, and Joomla! 1.5.x. It has had a total of total of 9 downloads since it first appeared.


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Trouble With A Video Script In Tabber
Posted 27 May 2012 - 04:14 PM
Here is a privately listed video that walks you through my difficulty:
NB that I have increased the number of tabs following the information in the codex.
Posted 29 May 2012 - 05:49 AM
Posted 29 May 2012 - 06:39 AM
Posted 29 May 2012 - 08:05 AM
So glad you got the issue figured out!
Please let us know if you have any other questions!


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The Centers for Medicare & Medicaid Services has substantially revised its physician supervision policy by modifying the definition of direct supervision, identifying services that require direct supervision only at initiation of the service and intending to establish a process to evaluate supervision levels for specific therapeutic services.
In the 2011 outpatient prospective payment system (OPPS) final rule, the Centers for Medicare & Medicaid Services (CMS) has substantially revised its physician supervision policy by...
Please see full article below for more information.
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- 341Promote
Throw Pillow
Fractal patternby Budi Satria Kwan
Throw Pillow made from 100% spun polyester poplin fabric, a stylish statement that will liven up any room. Individually cut and sewn by hand, each pillow features a double-sided print and is finished with a concealed zipper for ease of care. Sold with or without faux down pillow insert.
very cool!
Awesome! Looks so good on the products.
..good art picture. B.
very nice!
Nice work!
wonderful!! very well done :)
yeah~looks great on the phone.
wow, quite beautiful.
Very cool pattern piece!
Love it!
Very cool!
Oh Yeah, ✯ ✯ ✯ ✯ ✯ 👍 !!!
cool artwork, I will promote you.
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The lights are on
Put yourself in this positon walk up to a pack of raiders thinking you are all big with your perfect condition plasma rifle and perfect power armor. You kill them. But wait another pack comes out of no where and your healths lower then your comfertable with. So what do you do? Thats right reach in your trusted bag for some health. But wait theres no stimpacks. Thats ok you can always heal with some good ol' Suger bombs. mmmmmm. yummy. But it only did so much. Oh no your out of health aids! What do you do? You run! Start running twords a rock or somthing that would often keep you well hiddin. Make sure on your compass there are no red marks. In case u havnt noticed on the game no red marks basicly means theres no enemys. There for it makes you hiddin. Pull up ur pip boy and run to rivet city and heal yourself.
yeahif u wanna be a coward about it LOL stand and fightforever hold your ground be a badass LOL
It is not a good escape if you have already been spotted by the other group because they will chase you and it is hard to run away from an enemy.
RAIDERS?! i use my weakest gun on em. ill also never run out of stimpaks cause i have 1000 of em. only good with people that are level 2


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Vacation Rentals Little Cayman Island,, Cayman Islands - Little Cayman Island is one of the premier scuba diving vacation destinations in the world. Our ocean front two and three bedroom townhomes all with spectacular beach views can be your home away from ...
Find a vacation rental home in South Sound Cayman Islands for your vacation. Stay at one of our rustic cabins, cozy cottages, or authentic condos in South Sound Cayman Islands. We have everything from large rental homes to small villas. Rent for a weekend, week, month, or entire season! Vacation rentals are great accommodations for families and large groups. Enjoy the convenience of a full kitchen and save money by eating in. Living like the locals at a vacation rental assures you an authentic travel experience. Browse our vacation rentals in South Sound Cayman Islands and plan your vacation today!


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Mike Childs
Lives in United Kingdom
Joined on Mar 19, 2009
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On Mushrooms in Nature challenge (5 comments in total)
Mushroom explictly or does the term "mushroom" mean all fungi??
On faces that fill the frame challenge (19 comments in total)
Agreed. Maybe they have not been viewed yet. Thankless task hosting I guess!
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Organising Academy
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The main aim of the TUC's Organising Academy is to support unions to build organisational capacity and run effective campaigns.
This is done primarily through our training programme for union officers, organisers and leaders.
We also continue to offer our longstanding Diploma in Organising and a dedicated award for union support staff to enable them to contribute to the organising and campaign work undertaken by their unions. Our programme is delivered in partnership with Ruskin College.
If you would like more information on how we can support your union, please contact the TUC Organising Academy – email@example.com
What makes a 'strategic campaign' strategic? Is a question that is often asked, and with the introduction of Strategic Campaigns training as part of the new Organising Academy programme, Becky Wright, Director of the TUC's Organising Academy takes time to answer that question in a video:
25 September 2014
It's been nearly five months in the making but we are pleased to release the TUC's Organising Academy brochure for 2014-15! Alongside our existing courses, union staff will also be able to access three new short courses. In April we went out and asked union officers what they would like...
24 September 2014
If you are a union staff member and would like to register your interest in any of the courses below, please follow the link: https://www.surveymonkey.com/s/OrgAcad Course Dates Location Diploma in Organising 18-21 Nov London 20-23 January 24-27 March 19-22 May Oxford 7-10 July Certificate in Advanced Organising 11-14 Nov 10-13...
15 August 2014
Your Name: Claire Ronald Name of Course: Diploma in Organising Course Dates: January – August 2014 Your union: Chartered Society of Physiotherapy Your role: Senior negotiating officer Please describe your experience of the Organising Academy programme: I enrolled on the organising course as I was having a persistent problem in...
08 August 2014
Your Name: John Coote Name of Course: Advanced Organising Certificate Course Dates: Feb 14 – June 14 Your union: PCS Union Your role: Organising Industrial Offices Please describe your experience of the Organising Academy programme: Having been working at PCS for over 10 years in various organising and negotiating roles,...
08 August 2014
Name: Tania Bassett Name of Course: Communications Award Course Dates: 7 th – 9 th May 2014 Union: Napo Your role: National Official Press, Parliament & Campaigns Please describe your experience of the Organising Academy programme: Being relatively new to my role, having started last August, I wanted to gain...
08 August 2014
Name: Kristin Hamada Name of Course: Diploma in Organising Course Dates: Jan 2014-Aug 2014 Union: Equity Role: Equalities, Recruitment and Retention Organiser Please describe your experience of the Organising Academy programme: When I signed up to the organising diploma I wanted to get a better understanding of good practice with...
08 August 2014
Vin Wynne, Senior Organiser at the NUT Vin Wynne works across the Northern Region helping to organise union activities. Here he talks about his experience of going on an TUC Organising Academy course. The Advanced Certificate in Organising is a course run by the TUC Organising Academy, aimed at union...
30 July 2014
Organising Academy Advanced Certificate in Organising course In June, participants from ATL, CSP, CWU, Equity, the MU, NASUWT, NUT, Prospect, PCS completed the Organising Academy's 12 day course on Advanced Organising. During this time, participants studied three key areas of organising work; strategic campaigns which focuses on how to craft...
16 July 2014
The TUC has today (Tuesday) announced the winners of this year's Congress awards at its annual conference in Bournemouth.
10 September 2013


text: While trying to get scratches out of the refrigerator door i scratched the handle and then after trying to rub out those scratches caused more damage Yvonne B. • San Diego, CA • May 09, 2014 My Repair & Advice By the time I had done all the damage I discovered I could have taken the handle off. The rest is history - found I could order a new handle and presto - the refrigerator looks great again. Was this review helpful to you?