ppxscal/embedding_network huggingface dataset:
\leK, D\ge-Interleaving Structuring Technique for Peer-Peer Overlay Network
Authors: Khaled Ragab, Akinori Yonezawa
Venue: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology (2006)

Rendezvous Overlay Network (RvON) enables the smaller/medium Service Providers (SP) to publish their services' advertisements. Moreover, it allows end-users to discover the services associated with these advertisements. An autonomic K-interleaving step-step construction scheme is proposed [2] that autonomously organizes RvON into RvON-Clusters, where (K+1) is the physical number of hops between any two rendezvous nodes stored the same advertisement in RvON. Thus, end-users accessing from different areas are able to discover services' advertisements within a constant K physical number of hops. However in dense networks, increasing the size of RvON-Clusters induces a long diameter that manifests high stress per physical links and high delay to discover service's advertisement. This paper limits the expansion of RvON-Cluster within a specific diameter D. Each RvON-Cluster is organized with at most D logical hops over K physical hops. Thus, doubtless end-users are able to efficiently discover services' advertisements within D logical hops over K physical hops with reasonable storage and bandwidth consumption.
Design of OWL Ontology in R&D Project Management Meeting
Authors: Misoo Kwon, Hoyeon Ryu, Gunhee Kim, Sungdo Ha
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 01 (2006)

An ontology as the core technology of semantic web is an explicit specification of a conceptualization. The ontology has been proposed as an important tool for expressing real world knowledge by conceptual modeling, and provides a basis for effectively managing the knowledge. In this work, an ontology for R&D project management meeting is designed and established. Various meetings and related data accompanied in the progress of R&D projects are to be managed for successful projects. Information sharing and data retrieval are difficult for meeting attendants, and management for meeting data is not systematic. An ontology is designed and implemented by analyzing and classifying the meeting and related data in R&D project meeting systematically. Thereafter this can be applied to meeting management and service provision of an intelligent meeting examples.
Improved cognitive information complexity measure: a metric that establishes program comprehension effort
Authors: Dharmender Singh Kushwaha, A. K. Misra
Venue: ACM SIGSOFT Software Engineering Notes (2006)

Understanding the software system is known as program comprehension and is a cognitive process. This cognitive process is the driving force behind creation of software that is easier to understand i.e. has lower cognitive complexity, because essentially it is the natural intelligence of human brain that describes the comprehensibility of software. The research area carrying out this study is cognitive informatics. This work has developed an improved cognitive information complexity measure (CICM) that is based on the amount of information contained in the software and encompasses all the major parameters that have a bearing on the difficulty of comprehension or cognitive complexity of software. It is also able to establish the relationship between cognitive complexity of a program and time taken to understand the program, thus mapping closely to the comprehension strategy of a person.
Integrating Functional and Security Requirements with Use Case Decomposition
Authors: Josh Pauli, Dianxiang Xu
Venue: Proceedings of the 11th IEEE International Conference on Engineering of Complex Computer Systems (2006)

Misuse case modeling is a viable option to depict the security requirements together with functional requirements. To investigate the interplay between functional and security requirements, this paper presents an approach to decomposing use cases, misuse cases, and mitigation use cases. We identify relationships among decomposed cases for each case type (use, misuse, mitigation use) and ensure consistency among the cases as decomposition occurs by properly modeling shared and optional cases. We also assign applicable actors to the decomposed cases. Decomposition is conducted for each case type independently and then integrated with the "threatens" and "mitigates" relationships. We provide processes for the proper use of the "threatens" relationship between misuse cases and use cases and the "mitigates" relationship between mitigation use cases and misuse cases at different levels of abstraction. Thus, a complete set of security-centric requirements can be specified from the project outset to guide subsequent software development phases.
Computational methods for the design of ultraspecific pathogen signatures
Authors: Yuriy Fofanov
Venue:  (2006)

Designing nucleic acid-based assays for pathogen identification and detection with the necessary specificity, sensitivity, and reliability is computationally challenging. Using the set of novel algorithms and data structures introduced in this manuscript, it is now possible to efficiently calculate the frequency of all subsequences (n-mers) of length 5 to 25+ nucleotides in any sequenced genome. These algorithms can also compute all sequences one, two, three, etc. changes away from the nearest genome sequence. Thus, all subsequences present in or within a certain number of changes from the host/background genome can be excluded in the signature design step with greatly increased speed and predictability in comparison to current alignment-based methods. An evolutionary programming approach has been developed to complement these algorithms and data structures to identify the optimal combination of signatures. This new computational approach has lead to the creation of a new, more robust technology for pathogen identification.
Fast Compact City Modeling for Navigation Pre-Visualization
Authors: Nico Cornelis, Kurt Cornelis, Luc Van Gool
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

Nowadays, GPS-based car navigation systems mainly use speech and aerial views of simplified road maps to guide drivers to their destination. However, drivers often experience difficulties in linking the simple 2D aerial map with the visual impression that they get from the real environment, which is inherently ground-level based. Therefore, supplying realistically textured 3D city models at ground-level proves very useful for pre-visualizing an upcoming traffic situation. Because this pre-visualization can be rendered from the expected future viewpoints of the driver, the latter will more easily understand the required maneuver. 3D city models can be reconstructed from the imagery recorded by surveying vehicles. The vastness of image material gathered by these vehicles, however, puts extreme demands on vision algorithms to ensure their practical usability. Algorithms need to be as fast as possible and should result in compact, memory efficient 3D city models for future ease of distribution and visualization. For the considered application, these are not contradictory demands. Simplified geometry assumptions can speed up vision algorithms while automatically guaranteeing compact geometry models. We present a novel city modeling framework which builds upon this philosophy to create 3D content at high speed which could allow for pre-visualization of any conceivable traffic situation by car navigation modules.
Middleware for Protocol-Based Coordination in Mobile Applications
Authors: Kurt Schelfthout, Danny Weyns, Tom Holvoet
Venue: IEEE Distributed Systems Online (2006)

In distributed mobile applications, component interaction is complicated by dynamics in the environment. ObjectPlaces middleware supports the development of interaction protocols in dynamic, mobile environments to facilitate component coordination.
Build What You Use
Authors: Roy Want
Venue: IEEE Pervasive Computing (2006)

To prove success in ubiquitous computing research, you must implement your ideas and deploy them in support of a work practice or community activity. Anything less, and the design's utility will always be doubted, even if the core engineering is outstanding.
Using Time Decompositions to Analyze PubMed Abstracts
Authors: Rui Zhang, Parvathi Chundi
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

Constructing time decompositions of time stamped documents is an important step for uncovering temporal relationships and trends of keywords and topics contained in the document set. This paper describes the use of time decompositions to extract temporal information from a small set of PubMed abstracts related to the Wnt Signaling Pathway. A time decomposition of the document set is constructed to identify temporal information such as keywords/topics significant in some time interval and to also identify temporal progression of the significant keywords. Keywords were assigned temporal significance values using two different measure functions based on notions of entropy and ratio. It is shown how optimal lossy decompositions of the document set are effective in reducing noise both in terms of the number of keywords as well as in terms of smoothing out the temporal progressions of keywords. Several optimal lossy decompositions for the document set are constructed and it is shown that the temporal information captured by an optimal lossy decomposition increases as its size (number of intervals) increases.
Arithmetic Operations in Finite Fields of Medium Prime Characteristic Using the Lagrange Representation
Authors: Jean-Claude Bajard
Venue: IEEE Transactions on Computers (2006)

In this paper, we propose a complete set of algorithms for the arithmetic operations in finite fields of prime medium characteristic. The elements of the fields {\hbox{\rlap{I}\kern 2.0 pt{\hbox{F}}}}_{p^k} are represented using the newly defined Lagrange representation, where polynomials are expressed using their values at sufficiently many points. Our multiplication algorithm, which uses a Montgomery approach, can be implemented in O(k) multiplications and O(k^2 \log k) additions in the base field {\hbox{\rlap{I}\kern 2.0 pt{\hbox{F}}}}_p. For the inversion, we propose a variant of the extended Euclidean GCD algorithm, where the inputs are given in the Lagrange representation. The Lagrange representation scheme and the arithmetic algorithms presented in the present work represent an interesting alternative for elliptic curve cryptography.
ICA/RBF-Based Prediction of Varying Trend in Real Exchange Rate
Authors: Ling Huang, Fenggang Li, Lin Xin
Venue: Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing (2006)

The flexibility of Radial Basis Function Neural Network to handle complex patterns in the data has lead to the diffusion and implementation of such models in economics and econometrics. The financial time series such as real exchange rate are Multivariate data containing many underlying factors. In this paper, ICA as one of the most popular signal decomposition technologies in recent years is introduced to excavate the potential information for better analysis of real exchange rate where ICA plays an important role of preprocessing. We address the essential difference of dimension reduction using PCA and ICA; show that these two approaches are different at the aspect of sensitivity to dimensions although they both are pre-processing methods of dynamic data, even if the accumulative contribution rate of ICA is less than that of PCA, the former still attains the same prediction results as the latter. With ICA/RBF mixed prediction model, not only we can compress the dimensions of input data greatly, but also find the factors behind to better direct prediction. In the analysis of real exchange rate, independent influence factors such as the policy influence of the enhancement of currency interest and the customer marketing period of exchange are mined to rich knowledge base for make better prediction strategy.
Pose and Motion Recovery from Feature Correspondences and a Digital Terrain Map
Authors: Ronen Lerner Ehud Rivlin, Hector P. Rotstein
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

A novel algorithm for pose and motion estimation using corresponding features and a Digital Terrain Map is proposed. Using a Digital Terrain (or Digital Elevation) Map (DTM/DEM) as a global reference enables the elimination of the ambiguity present in vision-based algorithms for motion recovery. As a consequence, the absolute position and orientation of a camera can be recovered with respect to the external reference frame. In order to do this, the DTM is used to formulate a constraint between corresponding features in two consecutive frames. Explicit reconstruction of the 3D world is not required. When considering a number of feature points, the resulting constraints can be solved using nonlinear optimization in terms of position, orientation, and motion. Such a procedure requires an initial guess of these parameters, which can be obtained from dead-reckoning or any other source. The feasibility of the algorithm is established through extensive experimentation. Performance is compared with a state-of-the-art alternative algorithm, which intermediately reconstructs the 3D structure and then registers it to the DTM. A clear advantage for the novel algorithm is demonstrated in variety of scenarios.
A Necessary and Sometimes Sufficient Condition for the Feasibility of Sets of Sporadic Hard-Deadline Tasks
Authors: Theodore P. Baker, Michele Cirinei
Venue: Proceedings of the 27th IEEE International Real-Time Systems Symposium (2006)

This report describes a necessary condition for feasibility of scheduling a set of sporadic hard-deadline tasks on identical multiprocessor platforms, which is also a sufficient condition if there is only a single processor. The key contribution is the characterization of the maximum, over all time intervals of a given length, of the amount of computation that must be completed to meet all deadlines, and a method of computing this function efficiently to any desired degree of accuracy. Empirical data are provided to verify that the new infeasibility test can be computed efficiently and is an improvement over previously known checks for infeasibility.
Failed Suppression of Direct Visuomotor Activation in Parkinson's Disease
Authors: P. Praamstra, F. M. Plat
Venue: Journal of Cognitive Neuroscience (2001)

The response times in choice-reaction tasks are faster when the relative spatial positions of stimulus and response match than when they do not match, even when the spatial relation is irrelevant to response choice. This spatial stimulus&ndash;response (S&ndash;R) compatibility effect (i.e., the Simon effect) is attributed in part to the automatic activation of spatially corresponding responses, which need to be suppressed when the spatial location of stimulus and correct response do not correspond. The present study tested patients with Parkinson's disease and healthy control subjects in a spatial S&ndash;R compatibility task in order to investigate whether basal ganglia dysfunction in Parkinson's disease leads to disinhibition of direct visuomotor activation. High-density event-related brain potential recordings were used to chart the cortical activity accompanying attentional orientation and response selection. Response time measures demonstrated a failure to inhibit automatic response activation in Parkinson patients, which was revealed by taking into account a sequence-dependent modulation of the Simon effect. Event-related potential (ERP) recordings demonstrated that visuospatial orientation to target stimuli was accompanied by signal-locked activity above motor areas of the cortex, with similar latencies but an enhanced amplitude in patients compared to control subjects. The results suggest that inhibitory modulation of automatic, stimulus-driven, visuomotor activation occurs after the initial sensory activation of motor cortical areas. The failed inhibition in Parkinson's disease appears therefore related to a disturbance in processes that prevent early attention-related visuomotor activation, within motor areas, from actually evoking a response.
A Study of Weighted Signal Subspace Spatial Spectrum Estimation in Constant Beam Width Beam Space
Authors: Cui Huailin, Feng Xi an, Li Zhishun
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

The noise in constant beam width beam space is spatial correlative and color (non white), which affects the performance of wideband beam space high resolution DOA (Direction of Arrival) estimator. By analyzing the noise property in constant beam width beam space, a weighted signal subspace spatial spectrum (WSS) estimation method in constant beam width beam space is presented. In the new method, both eigenvalues and eigenvectors of wideband beam space covariance matrix are unitedly employed to represent noise subspace accurately, which can effectively overcome the effect of the beam space color noise and therefore improve the wideband beam space high resolution DOA performance. Computer simulation results demonstrate the effectiveness of the proposed approach. The resolution probability and mean square error from Monte Carlo experiments show that the resolution threshold of the new method is about 1 dB lower than that obtained with the wideband beam space MUSIC algorithm.
Unit Tests Reloaded: Parameterized Unit Testing with Symbolic Execution
Authors: Nikolai Tillmann, Wolfram Schulte
Venue: IEEE Software (2006)

Unit tests are popular. However, it's an art to write them in a way that specifies a program's behavior well, and it's laborious to write enough of them to have confidence in an implementation's correctness. Symbolic execution techniques can help increase code coverage by finding relevant variations of existing unit tests. These techniques can also automatically generate unit tests from an implementation when no prior unit tests exist. Commercial testing tools are already adopting these techniques.This article is part of a special issue on Software Testing.
Proceedings of the 1996 international conference on Learning sciences
Authors: Daniel C. Edelson, Eric A. Domeshek
Venue: International Conference on Learning Sciences (1996)

ICLS 96, the Second International Conference on the Learning Sciences, follows on the extremely successful First International Conference on the Learning Sciences held at Northwestern in 1991. In a world in which political and economic leaders alike are calling for educational reform, and pushing for an increased role for technology in teaching and learning, research in the Learning Sciences is going to be increasingly important.The goal of this conference series is to provide a much-needed opportunity for researchers and practitioners concerned with learning and instruction in a broad range of disciplines to come together in one community. Historically research on learning and instruction has been conducted in the fields of education, cognitive psychology, artificial intelligence, instructional technology, and others, with little interchange across disciplinary boundaries. The Learning Sciences encompass the diverse range of approaches to the study of teaching and learning; the International Conference on the Learning Sciences is designed to bring together researchers and practitioners at the forefront of these fields to share their challenges and insights.The theme of ICLS 96 is "Learning for the Real World." The emphasis on the real world captures the need for theory and implementation that meet the challenges of real world education and training. This emphasis reflects the need for researchers in the Learning Sciences to consider learning and teaching not just under ideal conditions, but also under the realistic conditions in which schools, corporations, and other organizations attempt to educate diverse populations of learners. Papers that reported results from research conducted in real world educational and training settings were given preference in the review process and are well-represented in these proceedings.With ICLS 96, we are establishing the International Conference on the Learning Sciences as a biennial conference. ICLS 98 will be hosted by Georgia Tech in Atlanta, GA. The work reported in these proceedings will contribute to the ongoing dialogue within the fields of the Learning Sciences that will be continued in Atlanta in 1998.The conference has received generous financial support from a number of organizations. The conference is being partially supported by a grant from the National Science Foundation's Program in Advanced Applications of Technology. Andersen Consulting is the sponsor of the ICLS 96 Doctoral Consortium. The Northwestern Committee on Cognitive Science provided additional support for the Doctoral Consortium.
Efficient Optimal Kernel Placement for Reliable Visual Tracking
Authors: Zhimin Fan, Ming Yang, Ying Wu, Gang Hua, Ting Yu
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

This paper describes a novel approach to optimal kernel placement in kernel-based tracking. If kernels are placed at arbitrary places, kernel-based methods are likely to be trapped in ill-conditioned locations, which prevents the reliable recovery of the motion parameters and jeopardizes the tracking performance. The theoretical analysis presented in this paper indicates that the optimal kernel placement can be evaluated based on a closed-form criterion, and achieved efficiently by a novel gradient-based algorithm. Based on that, new methods for temporal-stable multiple kernel placement and scale-invariant kernel placement are proposed. These new theoretical results and new algorithms greatly advance the study of kernel-based tracking in both theory and practice. Extensive real-time experimental results demonstrate the improved tracking reliability.
Naïve filterbots for robust cold-start recommendations
Authors: Seung-Taek Park, David Pennock, Omid Madani, Nathan Good, Dennis DeCoste
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

The goal of a recommender system is to suggest items of interest to a user based on historical behavior of a community of users. Given detailed enough history, item-based collaborative filtering (CF) often performs as well or better than almost any other recommendation method. However, in cold-start situations - where a user, an item, or the entire system is new - simple non-personalized recommendations often fare better. We improve the scalability and performance of a previous approach to handling cold-start situations that uses filterbots, or surrogate users that rate items based only on user or item attributes. We show that introducing a very small number of simple filterbots helps make CF algorithms more robust. In particular, adding just seven global filterbots improves both user-based and item-based CF in cold-start user, cold-start item, and cold-start system settings. Performance is better when data is scarce, performance is no worse when data is plentiful, and algorithm efficiency is negligibly affected. We systematically compare a non-personalized baseline, user-based CF, item-based CF, and our bot-augmented user- and item-based CF algorithms using three data sets (Yahoo! Movies, MovieLens, and EachMovie) with the normalized MAE metric in three types of cold-start situations. The advantage of our "naïve filterbot" approach is most pronounced for the Yahoo! data, the sparsest of the three data sets.