ppxscal/embedding_network huggingface dataset:
Lazy Associative Classification
Authors: Adriano Veloso, Wagner Meira Jr., Mohammed J. Zaki
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Decision tree classifiers perform a greedy search for rules by heuristically selecting the most promising features. Such greedy (local) search may discard important rules. Associative classifiers, on the other hand, perform a global search for rules satisfying some quality constraints (i.e., minimum support). This global search, however, may generate a large number of rules. Further, many of these rules may be useless during classification, and worst, important rules may never be mined. Lazy (non-eager) associative classification overcomes this problem by focusing on the features of the given test instance, increasing the chance of generating more rules that are useful for classifying the test instance. In this paper we assess the performance of lazy associative classification. First we demonstrate that an associative classifier performs no worse than the corresponding decision tree classifier. Also we demonstrate that lazy classifiers outperform the corresponding eager ones. Our claims are empirically confirmed by an extensive set of experimental results. We show that our proposed lazy associative classifier is responsible for an error rate reduction of approximately 10% when compared against its eager counterpart, and for a reduction of 20% when compared against a decision tree classifier. A simple caching mechanism makes lazy associative classification fast, and thus improvements in the execution time are also observed.
Effects of Attentional Load on Auditory Scene Analysis
Authors: Claude Alain, Aaron Izenberg
Venue: Journal of Cognitive Neuroscience (2003)

The effects of attention on the neural processes underlying auditory scene analysis were investigated through the manipulation of auditory task load. Participants were asked to focus their attention on tuned and mistuned stimuli presented to one ear and to ignore similar stimuli presented to the other ear. For both tuned and mistuned sounds, long (standard) and shorter (deviant) duration stimuli were presented in both ears. Auditory task load was manipulated by varying task instructions. In the easier condition, participants were asked to press a button for deviant sounds (target) at the attended location, irrespective of tuning. In the harder condition, participants were further asked to identify whether the targets were tuned or mistuned. Participants were faster in detecting targets defined by duration only than by both duration and tuning. At the unattended location, deviant stimuli generated a mismatch negativity wave at frontocentral sites whose amplitude decreased with increasing task demand. In comparison, standard mistuned stimuli generated an object-related negativity at central sites whose amplitude was not affected by task difficulty. These results show that the processing of sound sequences is differentially affected by attentional load than is the processing of sounds that occur simultaneously (i.e., sequential vs. simultaneous grouping processes), and that they each recruit distinct neural networks.
Towards designing a trusted routing solution in mobile ad hoc networks
Authors: Tirthankar Ghosh, Niki Pissinou, Kami Makki
Venue: Mobile Networks and Applications (2005)

Designing a trusted and secure routing solution in an untrustworthy scenario is always a challenging problem. Lack of physical security and low trust levels among nodes in an ad hoc network demands a secure end-to-end route free of any malicious entity. This is particularly challenging when malicious nodes collude with one another to disrupt the network operation. In this paper we have designed a secure routing solution to find an end-to-end route free of malicious nodes with collaborative effort from the neighbors. We have also extended the solution to secure the network against colluding malicious nodes, which, to the best of our knowledge, is the first such solution proposed. We have also proposed a framework for computing and distributing trusts that can be used with out trusted routing protocol. Our proposed framework is unique and different from the other schemes in that it tries to analyze the psychology of the attacker and quantifies the behavior in the computational model. Extensive simulation has been carried out to evaluate the design of our protocol.
Sports video categorizing method using camera motion parameters
Authors: S. Takagi, S. Hattori, K. Yokoyama, A. Kodate, H. Tominaga
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

In this paper, we propose a content based video categorizing method focusing broadcasted sports videos using camera motion parameters. We define two new features in the proposed method; "camera motion extraction ratio" and "camera motion transition". Camera motion parameters in the video sequence contain very significant information for categorization of broadcasted sports video, because in most of sports video, camera motions are closely related to the actions taken in the sports, which are mostly based on a certain rule depending on types of sports. Based on the characteristics, we design a sports video categorization algorithm for identifying 6 major different sports types. In our algorithm, the features automatically extracted from videos are analyzed in a statistical manner. The experimental results show a clear tendency the applicability of the proposed method for sports genre identification.
Policy Analysis for Administrative Role Based Access Control
Authors: Amit Sasturkar, Ping Yang, Scott D. Stoller, C. R. Ramakrishnan
Venue: Proceedings of the 19th IEEE workshop on Computer Security Foundations (2006)

Role-Based Access Control (RBAC) is a widely used model for expressing access control policies. In large organizations, the RBAC policy may be collectively managed by many administrators. Administrative RBAC (ARBAC) is a model for expressing the authority of administrators, thereby specifying how an organization's RBAC policy may change. Changes by one administrator may interact in unintended ways with changes by other administrators. Consequently, the effect of an ARBAC policy is hard to understand by simple inspection. In this paper, we consider the problem of analyzing ARBAC policies, in particular to determine reachability properties (e.g., whether a user can eventually be assigned to a role by a group of administrators) and availability properties (e.g., whether a user cannot be removed from a role by a group of administrators) implied by a policy. We first establish the connection between security policy analysis and planning in Artificial Intelligence. Based partly on this connection, we show that reachability analysis for ARBAC is PSPACE-complete. We also give algorithms and complexity results for reachability and related analysis problems for several categories of ARBAC policies, defined by simple restrictions on the policy language.
Document Retrieval from Multiple Collections by Using Lightweight Ontologies
Authors: Maria Auxilio Medina, J. Alfredo Sanchez, Jaime A. Paz
Venue: Proceedings of the 15th International Conference on Computing (2006)

This paper proposes the use of lightweight ontologies to describe documents collections. A meta harvesting protocol is used to access the documents. Ontologies are constructed semi-automatically by means of data mining techniques and document clustering algorithms. They are represented in Extensible Markup Language. Resource Description Framework is used to formalize a unique interpretation of the semantic of their elements. We describe a scenario where software agents use the ontologies to support information retrieval tasks from multiple collections and we show some experimental results.
The Emerging Ethics of Humancentric GPS Tracking and Monitoring
Authors: Katina Michael, Andrew McNamee, MG Michael
Venue: Proceedings of the International Conference on Mobile Business (2006)

The Global Positioning System (GPS) is increasingly being adopted by private and public enterprise to track and monitor humans for locationbased services (LBS). Some of these applications include personal locators for children, the elderly or those suffering from Alzheimer's or memory loss, and the monitoring of parolees for law enforcement, security or personal protection purposes. The continual miniaturization of the GPS chipset means that receivers can take the form of wristwatches, mini mobiles and bracelets, with the ability to pinpoint the longitude and latitude of a subject 24/7/365. This paper employs usability context analyses to draw out the emerging ethical concerns facing current humancentric GPS applications. The outcome of the study is the classification of current state GPS applications into the contexts of control, convenience, and care; and a preliminary ethical framework for considering the viability of GPS location-based services emphasizing privacy, accuracy, property and accessibility.
A legal analysis of human and electronic agents
Authors: Steffen Wettig, Eberhard Zehendner
Venue: Artificial Intelligence and Law (2004)

Currently, electronic agents are being designed and implemented that, unprecedentedly, will be capable of performing legally binding actions. These advances necessitate a thorough treatment of their legal consequences. In our paper, we first demonstrate that electronic agents behave structurally similar to human agents. Then we study how declarations of intention stated by an electronic agent are related to ordinary declarations of intention given by natural persons or legal entities, and also how the actions of electronic agents in this respect have to be classified under German law. We discuss four different approaches of classifying agent declarations. As one of these, we propose the concept of an "electronic person" (i.e., agents with limited liability), enrolment of agents into an agent register, and agent liability funds as means to serve the needs of all contracting parties.
Towards a Flexible Middleware for Autonomous Integrated Management Applications
Authors: Mehdi Kessis, Pascal Dechamboux, Claudia Roncancio, Thierry Coupaye, Alexandre Lefebvre
Venue: Proceedings of the International Multi-Conference on Computing in the Global Information Technology (2006)

Enterprise and global-scale systems today might have thousands to millions of geographically distributed nodes and this number will increase over time. Managing efficiently such scattered systems becomes increasingly complex and requires powerful management capabilities. Traditional solutions to manage and control them seem to have reached their limits. In recent years, integrated management systems and services as well as autonomic systems have raised much interest in distributed systems and software engineering. This paper discusses the architectural issues facing the design of large-scale distributed management systems. Then it suggests a new flexible and scalable integrated management middleware to handle management problems in large-scale networked and heterogeneous systems.
Bayesian predictive inference under informative sampling and transformation: Research Articles
Authors: Balgobin Nandram, Jai Won Choi, Gang Shen, Corinne Burgos
Venue: Applied Stochastic Models in Business and Industry (2006)

We consider the problem in which a biased sample is selected from a finite population (a random sample from a super-population), and inference is required for the finite population mean and the super-population mean. The selection probabilities are linearly related to the measurements, providing a non-ignorable selection model. When all the selection probabilities are known, as in our problem, inference about the finite population mean and the super-population mean can be made. As a practical issue, our method requires normality, but the measurements are not necessarily normally distributed. Thus, the key issue is the dilemma that a transformation to normality is needed, but this transformation will destroy the linearity between the selection probabilities and the measurements. This is the key issue we address in this work. We use the Gibbs sampler and the sample importance resampling algorithm to fit the non-ignorable selection model to a simple example on natural gas production. Our non-ignorable selection model estimates the finite population mean production much closer to the true finite population mean than a model which ignores the selection probabilities, and there is improved precision of the non-ignorable selection model over this latter model. A naive 95&percnt; credible interval based on the Horvitz&ndash;Thompson estimator is too wide. Copyright &copy; 2006 John Wiley & Sons, Ltd.
Collaboration using Mobile Technologies (MCTs): When is it essential?
Authors: Damon E. Campbell, Saonee Sarker, Joseph S. Valacich
Venue: Proceedings of the International Conference on Mobile Business (2006)

With the growing popularity of mobile technologies and the increasing use of groups within organizations (with members often distributed globally, and constantly "on-the-go"), question remains as to whether mobile collaboration technologies (MCTs) provide any additional benefits (over face-to-face and conventional CMC technologies) to such collaborations. We attempt to address this specific question by comparing features of MCTs with those of F2F and CMC technologies, and creating a typology of group collaboration that would benefit (or need) MCTs. Overall, the paper hopes to highlight the benefits of MCTs, and the contexts in which it will be most beneficial (perhaps even essential).
University Reachout - The Role of Guest Speakers in Communicating with Industry and Other Institutions A Position Paper
Authors: S. M. Young, H. M. Edwards, J. B. Thompson
Venue: Proceedings of the 19th Conference on Software Engineering Education and Training Workshops (2006)

The importance of external inputs into academic environments is highlighted and the actions that have been taken by the School of Computing and Technology at the University of Sunderland to ensure that external speakers are invited from industry and academia to come and give a fresh view on issues related to computing and technology are outlined. Details are then presented on the three series of guest lectures that have been instituted by the School: (i) Distinguished Speaker series, (ii) Practitioner Series, (iii) BCS SocioTech (North) series.
Approximate Reasoning in MAS: Rough Set Approach
Authors: Andrzej Skowron
Venue: Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology (2006)

In modeling multiagent systems for real-life problems, techniques for approximate reasoning about vague concepts and dependencies (ARVCD) are necessary. We discuss an approach to approximate reasoning based on rough sets. In particular, we present a number of basic concepts such as approximation spaces, concept approximation, rough inclusion, construction of information granules in calculi of information granules, and perception logic. The approach to ARVCD is illustrated by examples relative to interactions of agents, ontology approximation, adaptive hierarchical learning of compound concepts and skills, behavioral pattern identification, planning, conflict analysis and negotiations, and perception-based reasoning.
A New Approach for an Artificial Evolving System
Authors: M. Angelica Pinninghoff, Ricardo Contreras, Andreas Polymeris, Esteban Osses
Venue: Proceedings of the Fifth Mexican International Conference on Artificial Intelligence (2006)

We have built an adaptive system (AS) that is able to evolve and improve its answering ability to all reiterative questions from an artificial environment. Indeed, we have created a basic artificial system that is able to do what is usually understood as a natural system's behavior. In this work, rather than using logic, we encourage coherence, because it is not logic correctness but harmony between the system and its environment the primary goal of our work. As a central part of the system, we have designed and implemented an Existential Machine and experimental results show that evolution is feasible for restricted environments. In this article, the core idea supporting the system is shown, a rapid view over the existential machine is presented, and a set of results pointing to future applications is discussed.
Dynamic edge tracing: recursive methods for medical image segmentation
Authors: Daniel James Withey
Venue:  (2006)

Medical image segmentation is a sufficiently complex problem that no single strategy has proven to be completely effective. Historically, region growing, clustering, and edge tracing have been used and while significant steps have been made in the first two, research into automatic, recursive, edge following has not kept pace. In this thesis, a new, advanced, edge tracing strategy based on recursive, target tracking algorithms and suitable for use in segmenting magnetic resonance (MR) and computed tomography (CT) medical images is presented. This work represents the first application of recursive, target-tracking-based, edge tracing to the segmentation of MR and CT images of the head. Three algorithms representing three stages of development are described. In the third stage, pixel classification data are combined with edge information to guide the formation of the object boundary, and smooth, subpixel-resolution contours are obtained. Results from tests in images containing noise, intensity nonuniformity, and partial volume averaging indicate that the edge tracing algorithm can produce segmentation quality comparable to that from methods based on clustering and active contours, when closed contours can be formed. In addition, low-contrast boundaries can be identified in cases where the other methods may fail, indicating that the information extracted by the edge tracing algorithm is not a subset of that from the other approaches. Additional investigation may allow: (1) the use of knowledge to further guide the segmentation process; and, (2) the formation of multiple segmentation interpretations to be provided as output to the operator or as input to higher-level, automatic processing. A literature review describing the most common medical image segmentation algorithms is also provided. Three generations of development are defined as a framework for classifying these algorithms.
Constructing Fuzzy Relations fromWordNet forWord Sense Disambiguation
Authors: Christos Diou, Giorgos Katsikatsos, Anastasios Delopoulos
Venue: Proceedings of the First International Workshop on Semantic Media Adaptation and Personalization (2006)

In this work, the problem of word sense disambiguation is formulated as a problem of imprecise associations between words and word senses in a textual context. The approach has two main parts. Initially, we consider that for each sense, a fuzzy set is given that provides the degrees of association between a number of words and the sense. An algorithm is provided that ranks the senses of a word in a text based on this information, effectively leading to word sense disambiguation. In the second part, a method based on WordNet is developed that constructs the fuzzy sets for the senses (independent of any text). Algorithms are provided that can help in both understanding and implementation of the proposed approach. Experimental results are satisfactory and show that modeling word sense disambiguation as a problem of imprecise associations is promising.
Test Technology TC Newsletter
Authors: Bruce C. Kim
Venue: IEEE Design Test (2006)

This newsletter provides information on past and upcoming events related to the IEEE Computer Society's Test Technology Technical Council and the test community.
Comparison of Global Computing with Grid Computing
Authors: Babak Behsaz, Pooya Jaferian, Mohammad Reza Meybodi
Venue: Proceedings of the Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (2006)

In recent years, Global and Grid Computing emerge as two powerful technology trends. In this paper, we compare these two approaches of distributed computing. First, we present a definition for Global Computing that accentuates the key point in this trend. This key point distinguishes Global Computing from other trends and covers many such systems. Second, we contrast two approaches in general characteristics. Then, by comparing them in technical issues, we show that the key point in our definition of Global Computing is the main source of many technical differences between these methods. Finally, we present our opinion about the probable future of Global and Grid Computing.
Flight scheduling at KLM
Authors: Peter H. M. Jacobs, Alexander Verbraeck, Jeroen B. P. Mulder
Venue: Proceedings of the 37th conference on Winter simulation (2005)

We present a specification of the optimization of KLM's flight schedule in this paper using object-oriented simulation services on top of the Java-based distributed simulation environment DSOL. The paper shows the added value of a service-based architecture for linking the simulation of KLM's operations, the operational modules for day-to-day flight optimization, the interfaces to input data, and the output visualization tools. All services are loosely coupled to the other services. The contracts as defined in the interfaces of the services allow for easy extensions of the functionality of for instance the optimization modules, without the need for making changes in other places of the model. Links to external data sources can also be easily provided. In the project, it was clearly demonstrated that the usefulness, usability, and usage of the distributed, service-based architecture for KLM is much higher than earlier implementations of their simulation-based optimization models.
Tactile interruption management: tactile cues as task-switching reminders
Authors: Pamela J. Hopp-Levine, C. A. P. Smith, Benjamin A. Clegg, Eric D. Heggestad
Venue: Cognition, Technology and Work (2006)

Tactile cuing has been suggested as a method of interruption management for busy visual environments. This study examined the effectiveness of tactile cues as an interruption management strategy in a multi-tasking environment. Sixty-four participants completed a continuous aircraft monitoring task with periodic interruptions of a discrete gauge memory task. Participants were randomly assigned to two groups; one group had to remember to monitor for interruptions while the other group received tactile cues indicating an interruption&#x2019;s arrival and location. As expected, the cued participants evidenced superior performance on both tasks. The results are consistent with the notion that tactile cues transform the resource-intensive, time-based task of remembering to check for interruptions into a simpler, event-based task, where cues assume a portion of the workload, permitting the application of valuable resources to other task demands. This study is discussed in the context of multiple resource theory and has practical implications for systems design in environments consisting of multiple, visual tasks and time-sensitive information.