ppxscal/embedding_network huggingface dataset:
Adaptive software rejuvenation
Authors: Yujuan Bao
Venue:  (2004)

In this dissertation, we present a framework for adaptive software rejuvenation (ASR). Software rejuvenation is a proactive fault management technique. Its objective is to counter the phenomenon of software aging, the gradual accumulation of potential fault conditions and their impacts during system operation. Software rejuvenation has gained quick recognition since it emerged in 1995, and has broader applications as software systems have become ubiquitous in today's economic, social, medical, and other infrastructures. This dissertation addresses itself to the new, pressing, and challenging issue of adapting software rejuvenation to the dynamic changes of a system. A typical software system undergoes many changes over its lifetime, most notable in system components, resources, services, and client requirements, among others. System changes are the rule instead of the exception. The purpose of adaptive software rejuvenation (ASR) is to maintain system availability, reliability or other measures while a system undergoes the aging process and dynamic changes. Adaptive software rejuvenation poses some challenges, particularly with respect to theoretical understanding and practical implementation. The ASR framework presents a basic, integrated solution. It includes system modeling, online inspection, adaptive degradation estimation, and adaptive rejuvenation scheduling. We introduce new concepts and methodologies pertaining to all these aspects of the framework. In modeling, we have unified the modeling techniques to enable the traditional analysis of systems in ideal conditions, the incorporation of online measured data that pertains to the aging process, and the adaptive analysis of systems in degradation. In the degradation estimation, we provide a methodology to isolate the effects of the aging process, particularly resource leaks, from the other failure factors. This is essential to avoid adverse software rejuvenation. We provide a methodology to incorporate measured data with a degradation model to provide an adaptive degradation estimate. In rejuvenation scheduling, we have built a degradation-and-rejuvenation hierarchy with a rejuvenation model on top of a degradation model. We have introduced a method for providing adaptive software strategies to maintain a system under expected conditions or reach its highest potential in certain aspect. The ASR methodologies designed to realize the ASR objective are not limited to those introduced and illustrated in this dissertation. They may be more application-specific in practice or more advanced in general.
ARA: A Robust Audit to Prevent Free-Riding in P2P Networks
Authors: MyungJoo Ham, Gul Agha
Venue: Proceedings of the Fifth IEEE International Conference on Peer-to-Peer Computing (2005)

A number of solutions have been proposed to address the free-riding problem in peer-to-peer file sharing systems. The solutions are either imperfect ¿ they allow some users to cheat the system with malicious behavior, or expensive ¿ they require human intervention, require servers, or incur high mental transaction costs. We propose a method to address these weaknesses. Specifically, we introduce a utility function to capture contributions made by a user and an auditing scheme to ensure the integrity of a utility function¿s values. Our method enables us to reduce cheating by a malicious peer: we show that our approach can efficiently detect malicious peers with a probability over 98%
Active learning for sampling in time-series experiments with application to gene expression analysis
Authors: Rohit Singh, Nathan Palmer, David Gifford, Bonnie Berger, Ziv Bar-Joseph
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

Many time-series experiments seek to estimate some signal as a continuous function of time. In this paper, we address the sampling problem for such experiments: determining which time-points ought to be sampled in order to minimize the cost of data collection. We restrict our attention to a growing class of experiments which measure multiple signals at each time-point and where raw materials/observations are archived initially, and selectively analyzed later, this analysis being the more expensive step. We present an active learning algorithm for iteratively choosing time-points to sample, using the uncertainty in the quality of the currently estimated time-dependent curve as the objective function. Using simulated data as well as gene expression data, we show that our algorithm performs well, and can significantly reduce experimental cost without loss of information.
PRUS - Processor Network for Digital Circuit Implementation
Authors: Stanley Hyduke, Vladimir Hahanov, Volodymyr Obrizan, Olesya Guz
Venue: Proceedings of the 8th Euromicro Conference on Digital System Design (2005)

This paper offers high-performance technology for processing Boolean equations, based on Compiler Synchronized Parallel-processor Network-based Logic Device PRUS (Programmable Unlimited Systems) - single-bit spherical multiprocessor, implemented into ASIC. This technology allows to perform parallel, sequential and pipelined Boolean equations processing using AND, OR, NOT, XOR operations. Multiprocessor is very efficient in hardware implementation e.g. 256MB RAM is enough for processing Boolean equations containing 20 millions gates.
TERASCALE MUSIC MINING
Authors: J. Stephen Downie, Joe Futrel
Venue: Proceedings of the 2005 ACM/IEEE conference on Supercomputing (2005)

The objective of the International Music Information Retrieval Systems Evaluation Laboratory project (IMIRSEL) is the establishment of the necessary resources for the scientifically valid development and evaluation of emerging Music Information Retrieval (MIR) and Music Digital Library (MDL) techniques and technologies. IMIRSEL is located at the Graduate School of Library and Information Science (GSLIS) at the University of Illinois at Urbana- Champaign (UIUC). Project Principal Investigator is J. Stephen Downie of GSLIS and Co-Principal Investigator is Prof. Michael Welge of the Automated Learning Group (ALG) of the National Center for Supercomputing Applications (NCSA). A mission of the project is the creation of secure, yet accessible, terascale collections of music materials in a variety of audio, symbolic and metadata forms. These collections, when coupled with a set of standardized experimental tasks and standardized evaluation metrics, will allow members of the international MIR/ MDL research community to participate in the newly created, TREC-like, Music Information Retrieval Evaluation eXchange (MIREX) contests.
Indexing and Retrieval Medical images based on 2X2 DCT and IDS Compression
Authors: K. Ait saadi, A. Zemouri, Z. Brahimi, H. Meraoubi
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

Although digital images indexing and querying techniques have extensively been studied for the last years, few systems are dedicated to medical images today while the need for content-based analysis and retrieval tools increases with the growth of digital medical image databases. In this paper, we present a Content Based medical Images indexing and Retrieval technique (CBIR) using the 2x2 Discrete Cosine Transform and Information Dominance Strategy (IDS) compression. The extraction of the feature vectors is based on a 4x4 DCT model proposed in the literature. These features are directly generated from the 2x2 DCT coefficients reorganized in subbands and the search process is carried out by calculating cosine distance measure between the signatures of the query image and those stored in the database. The developed 2x2 DCT approach is expected to be very useful for a targeted seeking.
An after-the-fact compute forensics investigation with ethical consequences: experience and recommendations
Authors: Robin M. Snyder
Venue: Proceedings of the 2nd annual conference on Information security curriculum development (2005)

Computer forensics involves determining facts after-the-fact. This paper describes an after-the-fact computer forensics investigation with ethical consequences. In particular, the incident involves two students that were caught cheating on an on-line final exam held during the scheduled time in a computer classroom. Witnesses and computer forensics were used to verify and validate that what the author claimed had happened had actually happened while the student claims were discredited by the evidence. Areas for improvement and weaknesses that became evident are discussed.
Deferred Assignment Scheduling in Cluster-Based Servers
Authors: Victoria Ungureanu, Benjamin Melamed, Michael Katehakis, Phillip G. Bradford
Venue: Cluster Computing (2006)

This paper proposes a new scheduling policy for cluster-based servers called DAS (Deferred Assignment Scheduling). The main idea in DAS is to defer scheduling as much as possible in order to make better use of the accumulated information on job sizes. In broad outline, DAS operates as follows: (1) incoming jobs are held by the dispatcher in a buffer; (2) the dispatcher monitors the number of jobs being processed by each server; (3) when the number of jobs at a server queue drops below a prescribed threshold, the dispatcher sends to it the shortest job in its buffer.To gauge the efficacy of DAS, the paper presents simulation studies, using various data traces. The studies collected response times and slowdowns for two cluster configurations under multi-threaded and multi-process back-end server architectures. The experimental results show that in both architectures, DAS outperforms the Round-Robin policy in all traffic regimes, and the JSQ (Join Shortest Queue) policy in medium and heavy traffic regimes.
A New Micro-payment Protocol Based on P2P Networks
Authors: Zou Jia, Si Tiange, Huang Liansheng, Dai Yiqi
Venue: Proceedings of the IEEE International Conference on e-Business Engineering (2005)

Introducing micro-payment mechanism into P2P systems will bring economic incentives to various P2P applications and encourage peers to share their resources. In this paper, we present a new micropayment protocol, CPay, which exploits unique characteristics of P2P systems. The protocol establishes dynamic consistent hashing map between the set of all peers in the system and its subset of high performance peers. In each transaction, the payer's corresponding high performance peer checks the transaction to make sure that any illegal use of the ecoin will be timely detected. The protocol effectively exploits the heterogeneity of the P2P system and can achieve load balance.
Isolated Character Recognition by Searching Feature Points
Authors: Masakazu IWAMURA, Kazuya NEGISHI, Shinichiro OMACHI, Hirotomo ASO
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

Conventional segmentation technique cannot extract dif- ficult characters such as an isolated character and a touching character. In this paper, we propose a novel character recognition method which executes segmentation and recognition simultaneously. This method enables us to extract and recognize such difficult characters. The effectiveness of the proposed method is confirmed by experiments.
Home and Person Focused Event Framework
Authors: P. Erhan Eren, Daniel Stewart, Joe Wodka
Venue: Proceedings of the International Symposium on Applications on Internet Workshops (2006)

While networked devices have been proliferating in the home, the systems utilizing them typically operate in isolation from each other. This is partly due to the lack of a common framework that facilitates the exchange of information across these systems. Hence, we envision a home and person focused extensible event framework that provides a platform for dissemination, storage, and retrieval of events generated by such networked devices, and facilitates the extraction of high level semantics information through the application of event fusion algorithms. This will enable the delivery of personalized and relevant information to the users, and provide opportunities for new services activated by intelligent events.
Automatic Discovery and Inferencing of Complex Bioinformatics Web Interfaces
Authors: Anne H. Ngu, Daniel Rocco, Terence Critchlow, David Buttler
Venue: World Wide Web (2005)

The World Wide Web provides a vast resource to genomics researchers, with Web-based access to distributed data sources such as BLAST sequence homology search interfaces. However, finding the desired scientific information can still be very tedious and frustrating. While there are several known servers on genomic data (e.g., GeneBank, EMBL, NCBI) that are shared and accessed frequently, new data sources are created each day in laboratories all over the world. Sharing these new genomics results is hindered by the lack of a common interface or data exchange mechanism. Moreover, the number of autonomous genomics sources and their rate of change outpace the speed at which they can be manually identified, meaning that the available data is not being utilized to its full potential. An automated system that can find, classify, describe, and wrap new sources without tedious and low-level coding of source-specific wrappers is needed to assist scientists in accessing hundreds of dynamically changing bioinformatics Web data sources through a single interface. A correct classification of any kind of Web data source must address both the capability of the source and the conversation/interaction semantics inherent in the design of the data source. We propose a service class description (SCD)-a meta-data approach for classifying Web data sources that takes into account both the capability and the conversational semantics of the source. The ability to discover the interaction pattern of a Web source leads to increased accuracy in the classification process. Our results show that an SCD-based approach successfully classifies two thirds of BLAST sites with 100% accuracy and two thirds of bioinformatics keyword search sites with around 80% precision.
A Parallel Algorithm for Extracting Transcription Regulatory Network Motifs
Authors: Tie Wang, Jeffrey W. Touchman, Weiyi Zhang, Edward B. Suh, Guoliang Xue
Venue: Proceedings of the Fifth IEEE Symposium on Bioinformatics and Bioengineering (2005)

Network motifs have been demonstrated to be the building blocks in many biological networks such as transcriptional regulatory networks. Finding network motifs plays a key role in understanding system level functions and design principles of molecular interactions. In this paper, we present a novel definition of the neighborhood of a node. Based on this concept, we formally define and present an effective algorithm for finding network motifs. The method seeks a neighborhood assignment for each node such that the induced neighborhoods are partitioned with no overlap. We then present a parallel algorithm to find network motifs using a parallel cluster. The algorithm is applied on an E. coli transcriptional regulatory network to find motifs with size up to six. Compared with previous algorithms, our algorithm performs better in terms of running time and precision. Based on the motifs that are found in the network, we further analyze the topology and coverage of the motifs. The results suggest that a small number of key motifs can form the motifs of a bigger size. Also, some motifs exhibit a correlation with complex functions. This study presents a framework for detecting the most significant recurring subgraph patterns in transcriptional regulatory networks.
Server-Side Visualisation of Massive Datasets
Authors: Brett Beeson, Mark Dwyer, David Thompson
Venue: Proceedings of the First International Conference on e-Science and Grid Computing (2005)

Server-side visualisation systems comprise of a thin client connected to a rendering service located on the data server. We present a systematic and quantitative method for evaluating server-side visualisation systems. We evaluate the fundamental limitations of such systems in relation to network performance. Using these results we benchmark four common architectures by implementing clients and/or servers in each system. The suitability of each architecture is assessed for several applications, in terms of scalability, performance and ease of development.
Approach to a Theory of Software Evolution
Authors: Meir M. (Manny) Lehman
Venue: Proceedings of the Eighth International Workshop on Principles of Software Evolution (2005)

The paper briefly refers to a number of the, by now well known, results of the author's studies of Software Evolution since they provide a basis and framework for the development of a theory of the phenomenon. He will then summarise his most recent results outlining a proof that every E-type program reflects an unbounded number of assumptions about the application implemented, supported or modelled by the program. He shows that the presence of such assumptions is inevitable and that some of these will become invalid over time as a consequence of changes in the dynamic real world. Some of the finite set of known assumptions reflected in the program will also become invalid. Together the resultant ever extending invalidity will cause the software to require continuing change or to become ever more unsatisfactory or even invalid.
Putting active learning into multimedia applications: dynamic definition and refinement of concept classifiers
Authors: Ming-yu Chen, Michael Christel, Alexander Hauptmann, Howard Wactlar
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

The authors developed an extensible system for video exploitation that puts the user in control to better accommodate novel situations and source material. Visually dense displays of thumbnail imagery in storyboard views are used for shot-based video exploration and retrieval. The user can identify a need for a class of audiovisual detection, adeptly and fluently supply training material for that class, and iteratively evaluate and improve the resulting automatic classification produced via multiple modality active learning and SVM. By iteratively reviewing the output of the classifier and updating the positive and negative training samples with less effort than typical for relevance feedback systems, the user can play an active role in directing the classification process while still needing to truth only a very small percentage of the multimedia data set. Examples are given illustrating the iterative creation of a classifier for a concept of interest to be included in subsequent investigations, and for a concept typically deemed irrelevant to be weeded out in follow-up queries. Filtering and browsing tools making use of existing and iteratively added concepts put the user further in control of the multimedia browsing and retrieval process.
Efficient xpath query processing on stored and streaming xml data
Authors: Yi Chen
Venue:  (2005)

With XML emerging as the de facto standard for data representation format, efficient query evaluation on XML data is a very important research challenge. Different applications require queries to be evaluated using different processing models. In some applications, XML data needs to be stored locally for query processing, for example, scientific data. In other applications, XML data arrives continuously as a stream and requires on-line processing, such as the streams for stock and traffic information. In this thesis we discuss how to efficiently evaluate XPath queries on locally stored XML data and XML streams. We also exploit an encoding format to speed up query processing. For locally stored XML data, a Bi-LAbeling based System (BLAS) is proposed to efficiently process XPath queries by leveraging well-developed relational technology. Compared to existing work on XPath processing using relational databases, BLAS translates an XPath query to a more efficient SQL query that contains fewer selections and joins and requires fewer disk accesses to execute. For streaming XML data, an XPath query engine (TwigM) is presented. We observe that XPath evaluation algorithms on XML streams must record a potentially exponential number of pattern matches. We propose a compact data structure to encode these pattern matches rather than storing them explicitly. We then design a polynomial time algorithm to evaluate queries by probing the data structure in a lazy fashion. An Encoded XML Processing system (EXPedite) is then proposed to further speed up the performance. It consists of a general and effective encoding scheme and efficient parsing and query processing algorithms on encoded XML streams. By leveraging the encoding, processing queries over the encoded data is much more efficient than processing them over the original XML stream. We believe that the &ldquo;one size fits all&rdquo; concept in the traditional database model is no longer suitable for various application needs today. This thesis provides a comprehensive solution for XPath query processing and gives guidelines as how to choose the right techniques according to application requirements.
EQUITY and the Problem of Return on IT Investment
Authors: Karl Reed
Venue: IEEE Software (2006)

We seem to need a better understanding of the process of exploring quantifying information technology yields--that is, the economic benefit flowing from an IT project proposal. As a result, the TCSE has decided to establish the IEEE International Conference on Exploring Quantifiable Information Technology Yields (IEEE EQUITY).
Selective Attention in the Learning of Invariant Representation of Objects
Authors: Muhua Li, James J. Clark
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03 (2005)

Selective attention plays an important role in visual processing in reducing the problem scale and in actively gathering useful information. We propose a modified saliency map mechanism that uses a simple top-down taskdependent cue to allow attention to stay mainly on one object in the scene each time for the first few shifts. Such a modification allows the learning of invariant object representations across attention shifts in a multiple-object scene. In this paper, we will first introduce this saliency map mechanism and then propose a neural network model to learn invariant representations for objects across attention shifts in a temporal sequence.
Upper Semicontinuity of the Solution set to Parametric Vector Quasivariational Inequalities
Authors: Phan Quoc Khanh, Le Minh Luu
Venue: Journal of Global Optimization (2005)

We prove the upper semicontinuity (in term of the closedness) of the solution set with respect to parameters of vector quasivariational inequalities involving multifunctions in topological vector spaces under the semicontinuity of the data, avoiding monotonicity assumptions. In particular, a new quasivariational inequality problem is proposed. Applications to quasi-complementarity problems are considered
Automated court case management in the prosecutor's office
Authors: Garrett H. Byrne
Venue: ACM SIGDOC Asterisk Journal of Computer Documentation (1977)

During the early fall of 1977 the National District Attorneys Association and the Suffolk County District Attorney's Office, located in Boston, Massachusetts, completed a two-year cooperative project to design, implement and install a prototype, low cost, computer based prosecutor's case management system in the Suffolk office. The completed system, and the lessons which were learned during the development of this system represent a significant advance in functional design for automated case management for prosecutors. 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