ppxscal/embedding_network huggingface dataset:
Study on the Application of A* Shortest Path Search Algorithm in Dynamic Urban Traffic
Authors: Hao Yue, Chunfu Shao
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

This paper studies the application of A* shortest path search algorithm in dynamic urban traffic in the search of optimal path in real-time and dynamic traffic environment. At first, this paper introduces A* search algorithm and the characteristics of urban traffic. Then, the A* search algorithm application processes in optimal path searching of urban traffic is analyzed. The analysis focuses on the heuristic function of A* search algorithm. In the course of algorithm design, not only are the accuracy of the prediction of travel time and the characteristics of urban traffic considered, but also the factor of time similarity in urban traffic is taken into account.
Software Reliability Models: Assumptions, Limitations, and Applicability
Authors: A. L. Goel
Venue: IEEE Transactions on Software Engineering (1985)

A number of analytical models have been proposed during the past 15 years for assessing the reliability of a software system. In this paper we present an overview of the key modeling approaches, provide a critical analysis of the underlying assumptions, and assess the limitations and applicability of these models during the software development cycle. We also propose a step-by-step procedure for fitting a model and illustrate it via an analysis of failure data from a medium-sized real-time command and control software system.
Knowledge discovery in virtual community texts: Clustering virtual communities
Authors: A. M. Oudshoff, I. E. Bosloper, T. B. Klos, L. Spaanenburg
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2003)

Automatic knowledge discovery from texts (KDT) is proving to be a promising method for businesses today to deal with the overload of textual information. In this paper, we first explore the possibilities for KDT to enhance communication in virtual communities, and then we present a practical case study with real-life Internet data. The problem in the case study is to manage the very successful virtual communities known as 'clubs' of the largest Dutch Internet Service Provider. It is possible for anyone to start a club about any subject, resulting in over 10,000 active clubs today. At the beginning, the founder assigns the club to a predefined category. This often results in illogical or inconsistent placements, which means that interesting clubs may be hard to locate for potential new members. The ISP therefore is looking for an automated way to categorize clubs in a logical and consistent manner. The method used is the so-called bag-of-words approach, previously applied mostly to scientific texts and structured documents. Each club is described by a vector of word occurrences of all communications within that club. Latent Semantic Indexing (LSI) is applied to reduce the dimensionality problem prior to clustering. Clustering is done by the Within Groups Clustering method using a cosine distance measure appropriate for texts. The results show that KDT and the LSI method can successfully be applied for clustering the very volatile and unstructured textual communication on the Internet.
Independent Component Analysis for Optimal Passive Sonar Signal Detection
Authors: N. N. de Moura, J. M. Seixas, William Soares Filho, Ana V. Greco
Venue: Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications (2007)

The estimation of the Direction Of Arrival (DOA) of sig- nals in a set of sensors has applications in different en- gineering areas. In submarine acoustics, the DOA esti- mates for a passive sonar system has the objective to in- form the presence of a target (ship) in one determined di- rection (bearing). In accordance to the bearing's resolu- tion, space interference can occur, which contaminates sig- nals received in adjacent bearings. In this work, the inde- pendent component analysis (ICA) is applied for separating the interference sources and obtain optimal target detection in the respective direction. Results are presented for the passive reception of signals from merchant ships using two algorithms, JADE and FASTICA. The good performance achieved for blind separation points out that the proposed method can assist target detection, being used as a prepro- cessing tool.
Capital-Intensive Software Technology Part 1: Software Components
Venue: IEEE Software (1984)

Software components are the capital-intensive building blocks from which large programs are constructed. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
An Efficient Method to Determine the Diagonal Loading Factor for PAM Communication System
Authors: Wenlong Liu, Shuxue Ding
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

Minimum variance distortionless response (MVDR) beamformer are known to degrade due to the effects of imprecise knowledge about the steering vector and finite sample size. The diagonal loading method is a simple and efficient method that improves the robustness of beamformers. However, determining an ideal diagonal loading factor (DLF) is not a trivial problem, one that still has not been adequately addressed. Although beamformers are widely used in radar, sonar, and many other applications, in this paper, we consider only the pulse-amplitude modulation (PAM) digital communication applications. In this paper we take advantage of the binary feature in PAM digital communication system and present an effective method to determine the DLF. Since the binary feature is used, the new method does not require extra assumptions as in other methods. Numerical experiments show that the method improves the robustness of beamformers against mismatch caused by effects related to imprecise knowledge of the steering vector and finite sample size.
Automatic Keyphrase Extraction from Chinese Books
Authors: Yijiang Chen, Xiaodong Shi, Changle Zhou, Chang Su
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

This paper presents an approach of Automatic Keyphrase Extraction from Chinese Books. In this paper, the Local Reoccurrence Measure is proposed to greatly improve the automatic keyphrase recognition. This measure can also be applied to enhance keyphrase extraction of foreign language. The approach is tested on 1740 Chinese books and the experiment results are satisfactory.
Intrusion Detection System by Integrating PCNN and Online Robust SVM
Authors: Hengjie Li, Jiankun Wang
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

This paper proposes the application of principal component neural networks for intrusion feature extractions, the extracted features are employed by online Robust SVM for classification. The MIT `s KDD Cup 99 dataset is used to evaluate the proposed method compared to conventional SVMs, ANN and KNN in separating normal usage profiles from intrusive profiles of computer programs, which clearly demonstrates that PCNN-based feature extraction method can greatly reduce the dimension of input space without degrading or even boosting the classification performance, and indicates the superiority of online Robust SVM not only can achieve high intrusion detection accuracy and low false positives but also can be trained online and the results outperform the original ones with fewer support vectors and less training time without decreasing detection accuracy. Both of these achievements could significantly benefit an effective online intrusion detection system.
An efficient method to identify critical gates under circuit aging
Authors: Wenping Wang, Zile Wei, Shengqi Yang, Yu Cao
Venue: Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design (2007)

Negative Bias Temperature Instability (NBTI) is the leading factor of circuit performance degradation. Due to its complex dependence on operating conditions, especially signal probability, it is a tremendous challenge to accurately predict the degradation rate in reality. On the other hand, we demonstrate in this work that it is feasible to reliably predict the relative importance of gates under NBTI. By identifying critical gates that are the most important ones for timing degradation, we will be able to effectively protect the circuit from aging, with the minimum design overhead. The proposed method is based on a new timing analysis framework that integrates a NBTI-aware library. For each potential critical path, we prove that there exists a particular signal probability, which leads to the worst case of timing degradation. The search of such worst case signal probability provides a safe guardband for the degradation, yet avoiding overly pessimistic analysis. By applying this method to ISCAS and ITC benchmark circuits at the 65nm node, we demonstrate that in average only 1% of total gates need to be protected in order to control the timing degradation within 10% in ten years. Since this method only requires one-time analysis of each critical path, it is very efficient in computation. With the information of critical gates available, it further enables other resilient design techniques to mitigate circuit aging under NBTI.
Linguistic properties based on American Sign Language isolated word recognition with artificial neural networks using a sensory glove and motion tracker
Authors: Cemil Oz, Ming C. Leu
Venue: Neurocomputing (2007)

Sign language (SL), which is a highly visual-spatial, linguistically complete, and natural language, is the main mode of communication among deaf people. Described in this paper are two different American Sign Language (ASL) word recognition systems developed using artificial neural networks (ANN) to translate the ASL words into English. Feature vectors of signing words taken at five time instants were used in the first system, while histograms of feature vectors of signing words were used in the second system. The systems use a sensory glove, Cyberglove(TM), and a Flock of Birds^(R) 3-D motion tracker to extract the gesture features. The finger joint angle data obtained from strain gauges in the sensory glove define the hand shape, and the data from the tracker describe the trajectory of hand movement. In both systems, the data from these devices were processed by two neural networks: a velocity network and a word recognition network. The velocity network uses hand speed to determine the duration of words. Signs are defined by feature vectors such as hand shape, hand location, orientation, movement, bounding box, and distance. The second network was used as a classifier to convert ASL signs into words based on features or histograms of these features. We trained and tested our ANN models with 60 ASL words for a different number of samples. These methods were compared with each other. Our test results show that the accuracy of recognition of these two systems is 92% and 95%, respectively.
Combinatorial Merging and Huffman's Algorithm
Authors: D. S. ,  Jr Parker
Venue: IEEE Transactions on Computers (1979)

Huffman's algorithm produces an optimal weighted r-ary tree on a given set of leaf weights, where the weight of any parent node is the maximum of the son weights plus some positive constant. If the weights are viewed as (parallel) completion times, the algorithm has useful applications to combinatorial circuit designespecially for merging, or "fanning-in," a set of inputs with varying ready times: the weight of the tree's root node is then the completion time of the whole merging process. In this note we give new, tight upper and lower bounds on the weight of this root node (extending some work of Golumbic), and briefly describe an application in multiplexor design which exercises both of these bounds.
Customer Ranking Authority-Hub Algorithm for Mobile Communications in China
Authors: Sen Wu, Lingyu Wu, Haiyan Jin, Shujuan Gu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

Because of the open policy, the competition is much severe in mobile communications industry in China. Facing the large number of mobile users and huge amount of business operation data, mobile communications companies turn to data mining techniques to analyze customers in order to gain competence advantage. In this paper, we propose a Customer Ranking Authority-Hub Algorithm (CRAHA), which measures customer values to the company not only considering the customers themselves but also taking the interactional relationships among customers into account. The idea is developed from Web structure mining algorithm Hyperlink-Induced Topic Search (HITS) for the similarity that both mobile phone call and Web pages link reinforce the importance or values of the connected two sides. But due to the intrinsic difference between web search and mobile communications, the classical web search engine algorithm HITS can not be used in customer ranking directly. Using the idea of mutual reinforcement from HITS, we give the mobile call structure model and concepts of Authority, Hub and Rank of mobile customers, based on which the effective customer ranking algorithm is developed. Both theoretical analysis and test show that the customer ranking result of the new algorithm CRAHA is more reasonable.
Security auditing course development
Authors: Yin Pan
Venue: Proceedings of the 8th ACM SIGITE conference on Information technology education (2007)

As people increasingly depend on computers and network systems, security auditing has become one of the most effective security practices to achieve defense-in-depth in organizations. It follows an effective process to measure policies, procedures and controls in identifying and managing risks associated with networks and various operating systems. This has raised the need to develop specialists in the cyber security auditing field. This paper presents the author's experience in developing an undergraduate course on security auditing. It discusses the course design, procedures, and a series of innovative laboratory projects that are aimed to simulate real-world security concerns. This course is one of the core courses of the newly established B. S. in security program in the Department of Network, Security, and Systems Administration at RIT. This paper also reports experiences learned by both the students and instructors when the course was first offered. The course was well received by students, albeit there are areas for improvement.
Effect of Scheduling Discipline on CPU-MEM Load Sharing System
Authors: Lei Shi, Yuyan Sun, Lin Wei
Venue: Proceedings of the Sixth International Conference on Grid and Cooperative Computing (2007)

Scheduling schemes have important effects on the performance of load sharing in distributed systems. Because the load sharing policy based on CPUmemory has made the system memory an important role in effecting the system performance, it can reduce the paging fault and enhance the usage of the system resource. In light of the characteristics of the load sharing based on the CPU-memory and the variation of the jobs in executing, new CPU local scheduling schemes named more memory-request more CPU Slice based on Round Robin (RR-MMMCS) mechanism and more memory-request more CPU slice based on predicting (MMMCS-P) mechanism, are presented. Furthermore, the effects on the load sharing policy based on the CPU-memory of the variance of the interarrival time and service time are discussed. The tracedriven simulations show that the load sharing policy based on the CPU-memory and RR-MMMCS, MMMCS-P scheduling schemes are effective and have better performance in average response time for both CPU-memory and memory-bound jobs.
A Requirements Engineering Methodology for Real-Time Processing Requirements
Authors: M. W. Alford
Venue: IEEE Transactions on Software Engineering (1977)

This paper describes a methodology for the generation of software requirements for large, real-time unmanned weapons systems. It describes what needs to be done, how to evaluate the intermediate products, and how to use automated aids to improve the quality of the product. An example is provided to illustrate the methodology steps and their products and the benefits. The results of some experimental applications are summarized.
Automatic eye winks interpretation system for human-machine interface
Authors: Che Wei-Gang, Chung-Lin Huang, Wen-Liang Hwang
Venue: Journal on Image and Video Processing (2007)

This paper proposes an automatic eye-wink interpretation system for human-machine interface to benefit the severely handicapped people. Our system consists of (1) applying the support vector machine (SVM) to detect the eyes, (2) using the template matching algorithm to track the eyes, (3) using SVM classifier to verify the open or closed eyes and convert the eye winks into a sequence of codes (0 or 1), and (4) applying the dynamic programming to translate the code sequence to a certain valid command. Different from the previous eye-gaze tracking methods, our system identifies the open or closed eye, and then interprets the eye winking as certain commands for human-machine interface. In the experiments, our system demonstrates better performance as well as higher accuracy.
Lower Bounds on Crosspoints in Concentrators
Authors: S. Nakamura
Venue: IEEE Transactions on Computers (1982)

Lower bounds on the required number of crosspoints in concentrators, a class of interconnection networks, are given. The lower bounds are obtained from a straightforward necessary condition on the number of crosspoints in sparse crossbar full capacity concentrators. Because this condition must be satisfied by all full capacity concentrators embedded in more general concentrators, the general necessary condition is established. Several sparse crossbar designs that contain the minimum number of crosspoints are presented. An extension of the results to a more general class of interconnection networks is described.
Comments on "Minimization of Fuzzy Functions"
Authors: A. Kandel
Venue: IEEE Transactions on Computers (1973)

This correspondence points out the insufficiency of the method for minimization of fuzzy functions as presented in a recent short note.1 Two lemmas, which are the basis for a new minimization technique [2], are represented.
PROMALS
Authors: Jimin Pei, Nick V. Grishin
Venue: Bioinformatics (2007)

Motivation: Accurate multiple sequence alignments are essential in protein structure modeling, functional prediction and efficient planning of experiments. Although the alignment problem has attracted considerable attention, preparation of high-quality alignments for distantly related sequences remains a difficult task. Results: We developed PROMALS, a multiple alignment method that shows promising results for protein homologs with sequence identity below 10%, aligning close to half of the amino acid residues correctly on average. This is about three times more accurate than traditional pairwise sequence alignment methods. PROMALS algorithm derives its strength from several sources: (i) sequence database searches to retrieve additional homologs; (ii) accurate secondary structure prediction; (iii) a hidden Markov model that uses a novel combined scoring of amino acids and secondary structures; (iv) probabilistic consistency-based scoring applied to progressive alignment of profiles. Compared to the best alignment methods that do not use secondary structure prediction and database searches (e.g. MUMMALS, ProbCons and MAFFT), PROMALS is up to 30% more accurate, with improvement being most prominent for highly divergent homologs. Compared to SPEM and HHalign, which also employ database searches and secondary structure prediction, PROMALS shows an accuracy improvement of several percent. Availability: The PROMALS web server is available at: http://prodata.swmed.edu/promals/ Contact: jpei@chop.swmed.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Semantic Web Based Simulation Service Customization and Composition
Authors: Tong Zhang, Yun-sheng Liu, Ya-bing Zha
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

In order to achieve rapid composition of simulation systems, we propose service oriented simulation development, which is based on service-oriented architecture and semantic web technologies to implement Simulations-on-Internet via simulation service composition. First, definitions of domain ontology, service ontology, goal ontology, and simulation services have been put forward, upon which we construct a simulation service customization model, and realize the mechanism of goal-driven service customization. Further, we discuss the general process of simulation service composition, in which we present an agent-based matchmaking protocol to mediate between requirement goals and simulation services. In the end, a case study is proposed to testify the feasibility of our method.
Measuring referential integrity in distributed databases
Authors: Carlos Ordonez, Javier García-García, Zhibo Chen
Venue: Proceedings of the ACM first workshop on CyberInfrastructure: information management in eScience (2007)

Distributed relational databases are used by different organizations located at multiple sites that work together on common projects. In this article, we focus on distributed relational databases with incomplete and inconsistent content. We propose to measure referential integrity errors in them for integration and interoperability purposes. We propose local and global referential integrity metrics at three levels: column, table and database. We assume each table can be asynchronously updated at any site and new records are periodically broadcasted to all sites. We explain several distributed query optimization issues. Our proposal is useful in database integration, multiple database interoperability and data quality assurance. We discuss applications of our proposal in distributed scientific databases.
Seniority Logic: A Logic for a Committee Machine
Authors: M. Osborne
Venue: IEEE Transactions on Computers (1977)

A logic for a committee of perceptrons, called seniority logic, and a local adjustment algorithm for training a seniority committee are described. Like a majority committee, a seniority committee has the capacity to solve any two-class problem in which the classes are disjoint. Unlike a majority committee, a seniority committee may have members added during training, and a seniority committee is free to attain a size needed to solve a problem. In computer simulations on patterns with binary components a seniority committee has a higher recognition rate and needs fewer members than a majority committee. Solutions learned during training have high recognition rates on the training set and are reasonably free of bias.