ppxscal/embedding_network huggingface dataset:
Cryptanalysis of Two Multisignature Schemes with Distinguished Signing Authorities
Authors: Eun-Jun Yoon, Kee-Young Yoo
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 01 (2006)

In 2005, Huang and Chang proposed two multisignature schemes with distinguished signing authorities. The two schemes are based on a RSA cryptosystem and a discrete logarithm with composite modulus. One scheme is suitable for sequential architecture and the other for broadcasting. However, the current paper demonstrates an attack on Huang-Chang's two multisignature schemes in which attacker can derive a user's secret key and forge multisignatures schemes in arbitrary messages.
Extending UML 2.0 to Augment Control Over Enterprise Information System Engineering Process
Authors: M. Nikolaidou, N. Alexopoulou, A. Tsadimas, A. Dais, D. Anagnostopoulos
Venue: Proceedings of the International Conference on Software Engineering Advances (2006)

Enterprise Information Systems can be described according to the Open Distributed Processing Reference Model (RM-ODP), where five different viewpoints are specified analyzing various aspects of the system. Configuration issues are explored in the Engineering Viewpoint of RM-ODP. In practice, configuration issues are explored in discrete stages, supported by autonomous software tools, each of which adopts its own metamodel for system representation. We propose a platform independent framework, which focuses on the Engineering Viewpoint of Enterprise Information Systems managing application configuration and network design issues independently of application development progress. In order to apply this framework using existing tools, model exchangeability and tool coordination must be supported by standard, open methods. Thus, a common metamodel is proposed to generate enterprise information system models, which are stored in XML. A UML 2.0 profile is defined to visualize these models, facilitate the designer to interact with them and coordinate specific tool invocation.
A Lightweight Approach towards Autonomic Service-Oriented Computing System Development
Authors: Guoyong Cai, Ji Gao, Bin Hu
Venue: Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing (2006)

Autonomic service-oriented computing system, which exposes much flexbility and intelligence, is taken as a promising paradigm to deal with drawbacks appearing in current complex large scale heterogeneous computing systems, such as difficulties in construction, administration and maintenance. However presently there are not suitable approaches to design and implement such kind of systems. In this paper, a lightweight approach to autonomic service-oriented computing system development is proposed. The approach consists of three parts: an architectural style which entails quite a few flexible and intelligent properties; a lightweight process to design computing system under the proposed architectural style; a high level executable modeling language to implement the designed system. A case study is given to illustrate the approach.
The Neurophysiology of Functionally Meaningful Categories: Macaque Ventrolateral Prefrontal Cortex Plays a Critical Role in Spontaneous Categorization of Species-Specific Vocalizations
Authors: Gordon W. Gifford,  III, Katherine A. Maclean, Marc D. Hauser, Yale E. Cohen
Venue: Journal of Cognitive Neuroscience (2005)

Neurophysiological studies in nonhuman primates have demonstrated that the prefrontal cortex (PFC) plays a critical role in the acquisition of learned categories following training. What is presently unclear is whether this cortical area also plays a role in spontaneous recognition and discrimination of natural categories. Here, we explore this possibility by recording from neurons in the PFC while rhesus listen to species-specific vocalizations that vary in terms of their social function and acoustic morphology. We found that ventral prefrontal cortex (vPFC) activity, on average, did not differentiate between food calls that were associated with the same functional category, despite having different acoustic properties. In contrast, vPFC activity differentiated between food calls associated with different functional classes and specifically, information about the quality and motivational value of the food. These results suggest that the vPFC is involved in the categorization of socially meaningful signals, thereby both extending its previously conceived role in the acquisition of learned categories and showing the significance of using natural categorical distinctions in the study of neural mechanisms.
Semantic Abstraction of IA-64 Multimedia Instructions
Authors: Xuemeng Zhang, Rongcai Zhao, Jianmin Pang
Venue: Proceedings of the Second International Conference on Semantics, Knowledge, and Grid (2006)

This paper presents an effective approach to semantic abstraction of IA-64 multimedia instructions, which is important to binary translation. In particular, the authors take example for multimedia instructions used in motion estimation to describe the details of generating higher-level intermediate representation from IA-64 assembly language. Finally, the originality and soundness of the approach is proved.
Parallel divide-and-conquer scheme for 2D Delaunay triangulation: Research Articles
Authors: Min-Bin Chen, Tyng-Ruey Chuang, Jan-Jan Wu
Venue: Concurrency and Computation: Practice Experience (2006)

This work describes a parallel divide-and-conquer Delaunay triangulation scheme. This algorithm finds the affected zone, which covers the triangulation and may be modified when two sub-block triangulations are merged. Finding the affected zone can reduce the amount of data required to be transmitted between processors. The time complexity of the divide-and-conquer scheme remains O(n log n), and the affected region can be located in O(n) time steps, where n denotes the number of points. The code was implemented with C, FORTRAN and MPI, making it portable to many computer systems. Experimental results on an IBM SP2 show that a parallel efficiency of 44&ndash;95&percnt; for general distributions can be attained on a 16-node distributed memory system. Copyright &copy; 2006 John Wiley & Sons, Ltd.
A computer-supported cooperative learning system with multiagent intelligence
Authors: Leen-Kiat Soh, Nobel Khandaker, Xuliu Liu, Hong Jiang
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

In this paper, we describe an innovative infrastructure to support student participation and collaboration and help the instructor manage large or distance classrooms using multiagent system intelligence. The system, called I-MINDS, has a host of intelligent agents for each classroom: a teacher agent ranks and categorizes real-time questions from the students and collects statistics on student participation, a number of group agents that each maintains a collaborative group and facilitate student discussions, and a student agent for each student that profiles a student and finds compatible students to form the student's "buddy group". Each agent is capable of machine learning, thus improving its performance and services over time. These agents also interact and collaborate among themselves to exchange information and form coalitions dynamically to better serve the users. We have pilot-tested I-MINDS in GIS lectures, deployed I-MINDS in an introductory computer science course (CS1)'s laboratory, and evaluated the impact of I-MINDS based on student assessment. The results showed that students using I-MINDS performed (and outperformed in some aspects) as well as students in traditional settings.
Research and Implementation of the AC Cache Mechanism and Its Update Algorithm in Grid
Authors: Shaomin Zhang, Xiaoyan Liang, Baoyi Wang
Venue: Proceedings of the Second International Conference on Semantics, Knowledge, and Grid (2006)

PMI(Privilege Management Infrastructure) is a solution of the privilege management problem in grid environment, and has the advantage of distribution, dynamic, vast, and fine-grained. The calling of AC (Attribute Certificates) from LDAP server is a fundamental and frequent process on account of ACs holding authorization information in PMI. In grid, LDAP server is designed as a grid service, when an AC is called, additional time is taken on transferring the information on network. So it brings a bottleneck to the system's performance. To solve this problem, we develop an AC cache mechanism. We research and implement the cache mechanism, and discuss the effects of the hit rate on the performance. An improved update algorithm is used to guarantee the hit rate by defining and identifying "not-often-use ACs". The experiment results show that the response performance of the PMI is improved indeed.
The Influence of Working-Memory Demand and Subject Performance on Prefrontal Cortical Activity
Authors: Bart Rypma, Jeffrey S. Berger, Mark D'esposito
Venue: Journal of Cognitive Neuroscience (2002)

Brain imaging and behavioral studies of working memory (WM) converge to suggest that the ventrolateral prefrontal cortex (PFC) mediates a capacity-limited storage buffer and that the dorsolateral PFC mediates memory organization processes that support supracapacity memory storage. Previous research from our laboratory has shown that the extent to which such memory organization processes are required depends on both task factors (i.e., memory load) and subject factors (i.e., response speed). Task factors exert their effects mainly during WM encoding while subject factors exert their effects mainly during WM retrieval. In this study, we sought to test the generalizability of these phenomena under more difficult memory-demand conditions than have been used previously. During scanning, subjects performed a WM task in which they were required to maintain between 1 and 8 letters over a brief delay. Neural activity was measured during encoding, maintenance, and retrieval task periods using event-related functional magnetic resonance imaging. With increasing memory load, there were reaction time increases and accuracy rate decreases, ventrolateral PFC activation decreases during encoding, and dorsolateral PFC activation increases during maintenance and retrieval. These results suggest that the ventrolateral PFC mediates WM storage and that the dorsolateral PFC mediates strategic memory organization processes that facilitate supracapacity WM storage. Additionally, high-performing subjects showed overall less activation than low-performing subjects, but activation increases with increasing memory load in the lateral PFC during maintenance and retrieval. Low-performing subjects showed overall more activation than high-performing subjects, but minimal activation increases in the dorsolateral PFC with increasing memory load. These results suggest that individual differences in both neural efficiency and cognitive strategy underlie individual differences in the quality of subjects' WM performance.
"Tail-Splitting" to Predict Failing Software Modules - with a Case Study on an Operating Systems Product
Authors: Ram Chillarege, P. Santhanam
Venue: Proceedings of the 17th International Symposium on Software Reliability Engineering (2006)

"Tail-Splitting" is a new technique to identify defect prone modules by enhancing the focus of the Pareto distribution by a development process factor. The simple yet powerful influence of a varying tail membership as a function of development process phases is captured by the tail-split-string which tags each module. The case studies on an operating systems product demonstrate that the tailsplit- string identifies a small set of modules with a high probability of field failure. The tail-boundary in the algorithm provides for a natural tuning parameter to control the size of the identified set to suit the resources available for rework. Release managers have found that the method is particularly useful to sift modules, with low false positive, for late stage rework.
Multiple-camera people localization in an indoor environment
Authors: Valery A. Petrushin, Gang Wei, Anatole V. Gershman
Venue: Knowledge and Information Systems (2006)

With the rapid proliferation of video cameras in public places, the ability to identify and track people and other objects creates tremendous opportunities for business and security applications. This paper presents the Multiple Camera Indoor Surveillance project which is devoted to using multiple cameras, agent-based technology and knowledge-based techniques to identify and track people and summarize their activities. We also describe a people localization system, which identifies and localizes people in an indoor environment. The system uses low-level color features &#x2013; a color histogram and average vertical color &#x2013; for building people models and the Bayesian decision-making approach for people localization. The results of a pilot experiment that used 32 h of data (4 days &#x00d7; 8 h) showed the average recall and precision values of 68 and 59% respectively. Augmenting the system with domain knowledge, such as location of working places in cubicles, doors and passages, increased the average recall to 87% and precision to 73%.
Digital Control for Semi-Active Isolation System with Magnetorheological Damper
Authors: Cunzhi Pan, Shaopu Yang
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

In this paper, based on a designed vibration isolation system with magnetorheological (MR) damper, a schematic illustration for digital implementation of the on-off control strategies is presented, and the effect of the sampling is assessed. Simulations show that the performance of the controlled system is highly influenced by the sampling interval. From this point of view, a method for synthesizing time delay compensation and the real time controller implementation are introduced.
Computational topology of spline curves for geometric and molecular approximations
Authors: Thomas J. Peters
Venue:  (2006)

This dissertation provides sufficient conditions and tractable algorithms that guarantee the topological embedding of geometric approximations commonly used by modern geometric design systems. Particular focus is on approximating spline curve geometry via subdivision while using ambient isotopy as the measure of topological equivalence, which is stricter than the more traditional use of homeomorphism. Experimental work is provided to ensure the new methods developed will be rapid enough for graphics animation and robust enough for future Computer-Aided Geometric Design (CAGD) and Computer-Aided Molecular Design (CAMD) systems. The results of this work contribute to the emerging field of computational topology, while providing more accurate and efficient modeling methods to the geometric and molecular design communities.
Simulating the Panama Canal: present and future
Authors: Luiz Augusto G. Franzese, Luiz Otávio Abdenur, Rui Carlos Botter, Darrel Starks, Arnoldo R. Cano
Venue: Proceedings of the 36th conference on Winter simulation (2004)

This paper presents the methodologies and preliminary results of the project to develop a simulation model of the Panama Canal, one of the most famous waterway and locks system of the world. The case is based on the project conducted by Rockwell Software and Paragon Consulting Solutions, helping Panama Canal Authority design a strategic planning tool, based on Arena Simulation Software.
Adequacy, Accuracy, Scalability, and Uncertainty of Architecture-based Software Reliability: Lessons Learned from Large Empirical Case Studies
Authors: Katerina Go!seva-Popstojanova, Margaret Hamill, Xuan Wang
Venue: Proceedings of the 17th International Symposium on Software Reliability Engineering (2006)

Our earlier research work on applying architecture-based software reliability models on a large scale case study allowed us to test how and when they work, to understand their limitations, and to outline the issues that need future research. In this paper we first present an additional case study which confirms our earlier findings. Then, we present uncertainty analysis of architecture-based software reliability for both case studies. The results show that Monte Carlo method scales better than the method of moments. The sensitivity analysis based on Monte Carlo method shows that (1) small number of parameters contribute to the most of the variation in system reliability and (2) given an operational profile, components' reliabilities have more significant impact on system reliability than transition probabilities. Finally, we summarize the lessons learned from conducting large scale empirical case studies for the purpose of architecture-based reliability assessment and uncertainty analysis.
A System for Learning Statistical Motion Patterns
Authors: Weiming Hu Xuejuan Xiao Zhouyu Fu Dan Xie Tieniu Tan, Steve Maybank
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K{\hbox{-}}\rm means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.
Design and Simulation of Autonomous Control System of Satellite
Authors: Xiang Junhua, Zhang Yulin
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

Analyzed the influence of main perturbation sources including non-spherical gravitational perturbation, atmospheric drag perturbation and third body gravitation perturbation to the satellite orbit, compensates the influence through the method that biased the semi-major axis and the inclination angle, which enhanced the orbital stability of satellite. Designed the satellite autonomous orbital control system, and discussed the method that through controlling the semi-major axis, the eccentricity and the inclination angle to complete the revisions to ascending node right ascension deviation and phase deviation. Finally through the simulation and the experiment of a satellite which running on nearly earth regression, circular orbit, simulation results indicated the system scheme satisfied the demand of satellite autonomous control.
Evaluation of an Efficient Measurement Concept for P2P Multiprotocol Traffic Analysis
Authors: Holger Bleul, Erwin P. Rathgeb, Stefan Zilling
Venue: Proceedings of the 32nd EUROMICRO Conference on Software Engineering and Advanced Applications (2006)

The ability to accurately detect peer-to-peer (P2P) network traffic associated with different applications has become crucial for a broad range of network management tasks including application-specific traffic engineering and capacity planning. Since traditional methods like port-based identification have become highly inaccurate, as P2P applications nowadays tend to camouflage their communications, a new measurement concept based on application layer signatures has been developed [1]. In this paper we present the results of a detailed laboratory reference evaluation of our implementation, which validates the detection accuracy of this approach. We further present the results from a P2P traffic analysis at a large campus network, which show that this P2P traffic measurement concept provides the performance and scalability required for practical applications.
Neural Correlates of Lexical Access during Visual Word Recognition
Authors: J. R. Binder, K. A. Mckiernan, M. E. Parsons, C. F. Westbury, E. T. Possing, J. N. Kaufman, L. Buchanan
Venue: Journal of Cognitive Neuroscience (2003)

People can discriminate real words from nonwords even when the latter are orthographically and phonologically word-like, presumably because words activate specific lexical and/or semantic information. We investigated the neural correlates of this identification process using event-related functional magnetic resonance imaging (fMRI). Participants performed a visual lexical decision task under conditions that encouraged specific word identification: Nonwords were matched to words on orthographic and phonologic characteristics, and accuracy was emphasized over speed. To identify neural responses associated with activation of nonsemantic lexical information, processing of words and nonwords with many lexical neighbors was contrasted with processing of items with no neighbors. The fMRI data showed robust differences in activation by words and word-like nonwords, with stronger word activation occurring in a distributed, left hemisphere network previously associated with semantic processing, and stronger nonword activation occurring in a posterior inferior frontal area previously associated with grapheme-to-phoneme mapping. Contrary to lexicon-based models of word recognition, there were no brain areas in which activation increased with neighborhood size. For words, activation in the left prefrontal, angular gyrus, and ventrolateral temporal areas was stronger for items without neighbors, probably because accurate responses to these items were more dependent on activation of semantic information. The results show neural correlates of access to specific word information. The absence of facilitatory lexical neighborhood effects on activation in these brain regions argues for an interpretation in terms of semantic access. Because subjects performed the same task throughout, the results are unlikely to be due to task-specific attentional, strategic, or expectancy effects.
Independent Component Analysis Based on Learning Updating with Forms of Matrix Transformations and the Diagonalization Principle
Authors: Shuxue Ding
Venue: Proceedings of the Japan-China Joint Workshop on Frontier of Computer Science and Technology (2006)

Power iteration (PI) is a new algorithm for independent component analysis (ICA)[6, 5], which has some desired features. One of features is that the algorithm does not include any predetermined parameter such as the learning step size as in the gradient-based algorithm, which is especially expected for ICA applications with unknown types of sources. Another feature is that, in each iteration, the updating of ICA matrix is fully-multiplicative, rather than the additive updating in the conventional gradient learning algorithms. The criterion for the independence between outputs is based on diagonality of a non-linearized covariance matrix that is defined by ICA outputs and non-linear mapped ICA outputs. In this paper, we study the algorithm mathematically to analyze why and how the algorithm works. We show that in the algorithm the learning updating is in the form of matrix transformation acting on the ICA matrix. Such a updating allows a finite scale learning, which is essentially different from that only the small enough scale learning controlled by the learning step size is allowed, in a gradient-based algorithm. We also analyze the relation with the well known algorithms, such as, the Bussgang algorithm and the non-linear PCA.