ppxscal/embedding_network huggingface dataset:
Multimedia Annotations on the Semantic Web
Authors: Giorgos Stamou, Jacco van Ossenbruggen, Jeff Z. Pan, Guus Schreiber
Venue: IEEE MultiMedia (2006)

Multimedia in all forms (images, video, graphics, music, speech) is exploding on the Web.The content needs to be annotated and indexed to enable effective search and retrieval.However, recent standards and best practices for multimedia metadata don't provide semantically rich descriptions of multimedia content.On the other hand, the World Wide Web Consortium's (W3C's) Semantic Web effort has been making great progress in advancing techniques for annotating semantics of Web resources.To bridge this gap, a new W3C task force has been created to investigate multimedia annotations on the Semantic Web. This article examines the problems of semantically annotating multimedia and describes the integration of multimedia metadata with Semantic Web.
A Mining Method for LinkedWeb Pages Using Associated Keyword Space
Authors: Yuuichi Yaguchi, Hiroshi Ohnishi, Satoshi Mori, Keitaro Naruse, Ryuichi Oka, Hironobu Takahashi
Venue: Proceedings of the International Symposium on Applications on Internet (2006)

We propose a novel method for mining knowledge from linkedWeb pages. Unlike most conventional methods for extracting knowledge from linked data, which are based on graph theory, the proposed method is based on our Associated Keyword Space (ASKS), which is a nonlinear version of linear multidimensional scaling (MDS), such as Quantification Method Type IV (Q-IV). We constructed a three-dimensional ASKS space using linked HTML data from the World Wide Web. Experimental results confirm that the performance of ASKS is superior to that of Q-IV for discriminating clusters in the space obtained. We also demonstrate a mining procedure realized by 1) finding subspaces obtained in terms of logical calculations between subspaces in an ASKS space and 2) detecting emerging spatial patterns with geometrical features.
Multisurface Proximal Support Vector Machine Classification via Generalized Eigenvalues
Authors: Olvi L. Mangasarian, Edward W. Wild
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

A new approach to support vector machine (SVM) classification is proposed wherein each of two data sets are proximal to one of two distinct planes that are not parallel to each other. Each plane is generated such that it is closest to one of the two data sets and as far as possible from the other data set. Each of the two nonparallel proximal planes is obtained by a single MATLAB command as the eigenvector corresponding to a smallest eigenvalue of a generalized eigenvalue problem. Classification by proximity to two distinct nonlinear surfaces generated by a nonlinear kernel also leads to two simple generalized eigenvalue problems. The effectiveness of the proposed method is demonstrated by tests on simple examples as well as on a number of public data sets. These examples show the advantages of the proposed approach in both computation time and test set correctness.
Partial Elastic Matching of Time Series
Authors: Longin Jan Latecki, Vasileios Megalooikonomou, Qiang Wang, Rolf Lakaemper, C. A. Ratanamahatana, E. Keogh
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

We consider the problem of elastic matching of time series. We propose an algorithm that determines a subsequence of a target time series that best matches a query series. In the proposed algorithm we map the problem of the best matching subsequence to the problem of a cheapest path in a DAG (directed acyclic graph). The proposed approach allows us to also compute the optimal scale and translation of time series values, which is a nontrivial problem in the case of subsequence matching.
Formalising Control in Robust Spoken Dialogue Systems
Authors: Hui Shi, Robert J. Ross, John Bateman
Venue: Proceedings of the Third IEEE International Conference on Software Engineering and Formal Methods (2005)

The spoken language interface is now becoming an increasingly serious research topic with application to a wide range of highly engineered systems. Such systems not only include innocuous human-computer interactions, but also encompass shared-control safety critical devices such as automotive vehicles and robotic systems. Spoken Dialogue Systems (SDS) are the language architecture used to provide linguistic interaction in these applications, but they have to date been notoriously difficult to engineer in a robust and safe manner. In this paper we report on our efforts to improve the safety and overall usability of dialogue enabled applications through the employment of formal methods in SDS development and testing. Specifically, we use Communicating Sequential Processes (CSP) as the basis of a new approach to the specification, design and verification of dialogue manager control. Moreover, to support this approach, we introduce FDMSC - the Formal Dialogue Management for Shared Control toolkit - and illustrate its use in the construction of formal methods based spoken dialogue systems.
Building Sparse Large Margin Classifiers
Authors: Mingrui Wu, Bernhard Schölkopf, Gökhan Bakir
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The added constraint explicitly controls the sparseness of the classifier and an approach is provided to solve the formulated problem. When considering the dual of this problem. it can be seen that building an SLMC is equivalent to constructing an SVM with a modified kernel function. Further analysis of this kernel function indicates that the proposed approach essentially finds a discriminating subspace that can be spanned by a small number of vectors, and in this subspace different classes of data are linearly well separated. Experimental results over several classification benchmarks show that in most cases the proposed approach outperforms the state-of-art sparse learning algorithms.
Simulating virtual crowds in emergency situations
Authors: Adriana Braun, Bardo E. J. Bodmann, Soraia R. Musse
Venue: Proceedings of the ACM symposium on Virtual reality software and technology (2005)

This paper presents a novel approach to simulate virtual human crowds in emergency situations. Our model is based on two previous works, on a physical model proposed by Helbing, where individuals are represented by a particle system affected by "social forces" that impels them to go to a point-objective, while avoiding collisions with obstacles and other agents. As a new property, the virtual agents are endowed with different attributes and individualities as proposed by Braun et al. The main contributions of this paper are the treatment of complex environments and their implications on agents' movement, the management of alarms distributed in space, the virtual agents endowed with perception of emergency events and their consequent reaction as well as changes in their individualities. The prototype reads a XML file where different scenarios can be simulated, such as the characteristics of population, the virtual scene description, the alarm configuration and the properties of hazardous events. As output, the prototype generates information in order to measure the impact of parameters on saved, injured and dead agents. In addition, some results and validation are discussed.
Evidence-Based Guidelines for Assessment of Software Development Cost Uncertainty
Authors: Magne Jorgensen
Venue: IEEE Transactions on Software Engineering (2005)

Several studies suggest that uncertainty assessments of software development costs are strongly biased toward overconfidence, i.e., that software cost estimates typically are believed to be more accurate than they really are. This overconfidence may lead to poor project planning. As a means of improving cost uncertainty assessments, we provide evidence-based guidelines for how to assess software development cost uncertainty, based on results from relevant empirical studies. The general guidelines provided are: 1) Do not rely solely on unaided, intuition-based uncertainty assessment processes, 2) do not replace expert judgment with formal uncertainty assessment models, 3) apply structured and explicit judgment-based processes, 4) apply strategies based on an outside view of the project, 5) combine uncertainty assessments from different sources through group work, not through mechanical combination, 6) use motivational mechanisms with care and only if greater effort is likely to lead to improved assessments, and 7) frame the assessment problem to fit the structure of the relevant uncertainty information and the assessment process. These guidelines are preliminary and should be updated in response to new evidence.
FeedClean: Feedback-Driven Clean Utilization Management to Improve Real-Time Data Services in Dynamic Environments
Authors: Kyoung-Don Kang
Venue: Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2005)

Real-time data services can significantly increase, e.g., the profit of online trades by processing transactions within their deadlines. However, supporting the transaction timeliness in dynamic environments such as the WWW is challenging, since transactions may arrive in a bursty manner and execute longer than expected. As a result, the degree of data/resource contention may vary, causing deadline misses. To address this problem, we refine real-time data service performance metrics and develop a novel feedback-based scheme to manage the clean CPU utilization, which is the difference between the aggregate utilization and wasted utilization due to data conflicts and deadline misses, in main memory real-time databases. According to the control signal computed in the feedback loop, the QoS of relatively large transactions, which usually incur more data/resource contention, can be degraded under high contention. Admission control can also be applied to incoming transactions, if necessary, to improve the real-time database performance under severe overload. By carefully managing the clean utilization, we can substantially improve the success ratio, i.e., the fraction of the submitted transactions that have been admitted and finished within their deadlines. In a simulation study, which models bursty arrivals of long-running transactions with timing constraints, our approach improves the success ratio by up to an order of magnitude compared to existing approaches.
Archaic to modern 1: basic tools & issues
Authors: Dan Nagle
Venue: ACM SIGPLAN Fortran Forum (2005)

Including the new Fortran 2003, there are three revisions of the Fortran standard beyond the venerable, quarter-century-old Fortran 77. While the newer revisions, Fortran 90, 95 and 2003, have standardized more features, they are (very nearly) upwards compatible with Fortran 77. In fact, many of the new features are standardisation of extensions implemented by Fortran 77 compilers, albeit each with its own spelling. Still, the introduction of modern Free Format in place of the card-image-based Fixed Format, and the overall amount of new features (many first appearing in the Fortran 90 standard), means that some applications programmers consider modern (90, 95, 2003) Fortran to be a different language than archaic (66, 77) Fortran.
Handover Optimization in Wireless Microcellular ATM Networks
Authors: S. Louvros, D. Karaboulas, S. Kotsopoulos
Venue: Wireless Personal Communications: An International Journal (2006)

Microcellular solutions in wireless ATM networks increase the network traffic control as a result of frequent handover requests. The blocking probability or the forced termination probability presents a quality of service criterion for evaluation of certain handover techniques. This paper presents a handover protocol that can avoid cell loss and guarantee cell sequence, and a two layer wireless call admission control is studied, using Markov state diagrams, in order to optimize the performance of wireless ATM networks.
Image Analysis for Efficient Categorization of Image-based Spam E-mail
Authors: Hrishikesh B. Aradhye, Gregory K. Myers, James A. Herson
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

To circumvent prevalent text-based anti-spam filters, spammers have begun embedding the advertisement text in images. Analogously, proprietary information (such as source code) may be communicated as screenshots to defeat text-based monitoring of outbound e-mail. The proposed method separates spam images from other common categories of e-mail images based on extracted overlay text and color features. No expensive OCR processing is necessary. Our method works robustly in spite of complex backgrounds, compression artifacts, and a wide variety of formats and fonts of overlaid spam text. It is also demonstrated successfully to detect screenshots in outbound e-mail.
On Some Combinatorial Properties of the Star Graph
Authors: N. Imani, H. Sarbazi-Azad, S. G. Akl
Venue: Proceedings of the 8th International Symposium on Parallel Architectures,Algorithms and Networks (2005)

The star graph, as an interesting network topology, has been extensively studied in the past. In this paper, we address some of the combinatorial properties of the star graph. In particular, we consider the problem of calculating the surface area of the star graph, answering an open problem previously posed in [12].
HAUNT-24: 24-bit Hierarchical, Application-Confined Unique Naming Technique
Authors: Ashwini Raina, Shruti Patil, V. Muthukumar, Ajith Abraham
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

The advent of tiny, inexpensive, low-power, autonomously functioning wireless sensors, has paved a way for high quality research, by posing unique challenges to researchers. Energy, cost and size of such sensors limit their communication and computation capabilities and thus robust and highly energy efficient algorithms need to be incorporated at every layer of the network model, along with an efficient network aware addressing scheme This paper proposes a 24-bit Hierarchical, Application-Confined Unique Naming Technique (HAUNT-24), which ensures mutual distinctiveness of addresses within an application, with the primary focus on in-network data aggregation. Various issues relating to the proposed addressing scheme are analyzed and its future scope is discussed. The simple aggregate queries such as MIN/MAX and AVG are applied over the proposed HAUNT-24 addressed network and it's shown how it helps in achieving in-network data aggregation.
Software quality modeling and analysis with limited or without defect data
Authors: Taghi M. Khoshgoftaar
Venue:  (2005)

The key to developing high-quality software is the measurement and modeling of software quality. In practice, software measurements are often used as a resource to model and comprehend the quality of software. The use of software measurements to understand quality is accomplished by a software quality model that is trained using software metrics and defect data of similar, previously developed, systems. The model is then applied to estimate quality of the target software project. Such an approach assumes that defect data is available for all program modules in the training data. Various practical issues can cause an unavailability or limited availability of defect data from the previously developed systems. This dissertation presents innovative and practical techniques for addressing the problem of software quality analysis when there is limited or completely absent defect data. The proposed techniques for software quality analysis without defect data include an expert-based approach with unsupervised clustering and an expert-based approach with semi-supervised clustering. The proposed techniques for software quality analysis with limited defect data includes a semi-supervised classification approach with the Expectation-Maximization algorithm and an expert-based approach with semi-supervised clustering. Empirical case studies of software measurement datasets obtained from multiple NASA software projects are used to present and evaluate the different techniques. The empirical results demonstrate the attractiveness, benefit, and definite promise of the proposed techniques. The newly developed techniques presented in this dissertation is invaluable to the software quality practitioner challenged by the absence or limited availability of defect data from previous software development experiences.
Study of breakdown in ultrathin gate dielectrics using constant voltage stress and successive constant voltage stress
Authors: L. J. Tang, K. L. Pey, C. H. Tung, R. Ranjan, W. H. Lin
Venue: Microelectronic Engineering (2005)

A comparative study on understanding the effect of conventional constant voltage stress (CVS) and successive constant voltage stress (SCVS) methodology on the post-breakdown transistor performance has been performed. In CVS stressing methodology, breakdowns in ultrathin gate oxides in narrow MOSFETs in moderate and high compliance current, Igl, range are usually associated with the formation of dielectric-breakdown-induced epitaxy (DBIE). Whereas in SCVS, due to a more controlled thermal environment in narrow MOSFET, DBIE is hardly found for breakdowns stressed under a similar Igl (as that of CVS in the moderate Igl) and gate oxide thickness. On the other hand, for both CVS and SCVS, once the DBIE is nucleated during progressive breakdown, its growth results in substantial gate dielectric thinning which is one of the mechanisms responsible for enhanced device degradation.
Dependable Software: An Oxymoron&
Authors: Daniel Jackson
Venue: Proceedings of the 13th IEEE International Conference on Requirements Engineering (2005)

Can software really be made dependable? And if it was, would we be able to recognize it? For the last two years, I've been chairing a study of the National Academy of Sciences on dependable software, and have had the opportunity to hear - in a workshop held last year, and in open sessions of the committee -anecdotes and viewpoints that have often surprised me. The conclusions of my committee will not be made public until the final report is out. In this talk, therefore, I'll share some of the things we've heard, and draw some connections to requirements engineering.
Atelier de conception et d'evaluation de syst&egrave;mes interactifs adaptables et/ou mixtes en evolution: CESAME
Authors: Gaelle Calvary, Anne-Marie Déry, Emmanuel Dubois, Dominique L. Scapin
Venue: Proceedings of the 2nd French-speaking conference on Mobility and ubiquity computing (2005)

The worshop copes with the increasing mixity and evolutivity of interactive systems. It aims at providing a common ground for envisionning and engineering such systems.
The effect of use and access on citations
Authors: Michael J. Kurtz, Guenther Eichhorn, Alberto Accomazzi, Carolyn Grant, Markus Demleitner, Edwin Henneken, Stephen S. Murray
Venue: Information Processing and Management: an International Journal (2005)

It has been shown (Lawrence, S. (2001). Online or invisible? Nature, 411, 521) that journal articles which have been posted without charge on the internet are more heavily cited than those which have not been. Using data from the NASA Astrophysics Data System (ads.harvard.edu) and from the ArXiv e-print archive at Cornell University (arXiv.org) we examine the causes of this effect.
A Study of Alert-Based Collaborative Defense
Authors: Wen-Yi Hsin, Shun-Chieh Lin, Shian-Shyong Tseng
Venue: Proceedings of the 8th International Symposium on Parallel Architectures,Algorithms and Networks (2005)

We propose a framework for collaborative defense by extending the original distributed intrusion detection model. It contains alert's collector, extractor, analyzer, report's generator, alert warehouse and alert's analysis. Besides, we develop a hybrid approach to share security information like raising the wolf smoke to warn partners. By the security information sharing, the members of CSIRT can obtain the solutions of defense, such as blacklists, detection rules, and security knowledge about alerts. The framework provides a solution to build effective cooperative security teams for academia and industry.We evaluate the feasibility of our framework and track the spreading behaviors of the SQL Slammer Worm. As a result, we can deploy security system more widely and detect the aggressor's behavior more accurately. The alert-based collaborative defense mechanism can help members to evaluate the impact of the threats and take proper actions to mitigate the risk.
Context-Aware Mobile Computing: Learning Context-Dependent Personal Preferences from a Wearable Sensor Array
Authors: Andreas Krause Asim Smailagic, Daniel P. Siewiorek
Venue: IEEE Transactions on Mobile Computing (2006)

Context-aware computing describes the situation where a wearable/mobile computer is aware of its user's state and surroundings and modifies its behavior based on this information. We designed, implemented, and evaluated a wearable system which can learn context-dependent personal preferences by identifying individual user states and observing how the user interacts with the system in these states. This learning occurs online and does not require external supervision. The system relies on techniques from machine learning and statistical analysis. A case study integrates the approach in a context-aware mobile phone. The results indicate that the method is able to create a meaningful user context model while only requiring data from comfortable wearable sensor devices.
Hierarchical Fixed Priority Pre-Emptive Scheduling
Authors: R. I. Davis, A. Burns
Venue: Proceedings of the 26th IEEE International Real-Time Systems Symposium (2005)

This paper focuses on the hierarchical scheduling of systems where a number of separate applications reside on a single processor. It addresses the particular case where fixed priority pre-emptive scheduling is used at both global and local levels, with a server associated with each application. Using response time analysis, an exact schedulability test is derived for application tasks. This test improves on previously published work. The analysis is extended to the case of harmonic tasks that can be bound to the release of their server. These tasks exhibit improved schedulability indicating that it is advantageous to choose server periods that enable some tasks to be bound to the release of their server. The use of Periodic, Sporadic and Deferrable Servers is considered with the conclusion that the simple Periodic Server dominates both Sporadic and Deferrable Servers when the metric is application task schedulability.
Product Lines for Supporting the Composition and Evolution of Service Oriented Applications
Authors: Rafael Capilla, N. Yasemin Topaloglu
Venue: Proceedings of the Eighth International Workshop on Principles of Software Evolution (2005)

In the recent years, the idea of realizing software as a service is getting wide acceptance in the software engineering community. Web services are reusable software components which can be discovered and invoked using standard Internet protocols. The development and use of service oriented systems differ from the traditional approach used in other kind of Web applications. In this position paper we try to improve the development and evolution of service oriented systems. To achieve this we propose a modification of the traditional product line approach to support composite services. We use a lightweight product line with specific variability information to facilitate web service composition as well as the evolution of such systems.