ppxscal/embedding_network huggingface dataset:
Analysis of a Dobutamine Stress Echocardiography Dataset Using Rough Sets
Authors: Kenneth R. Revett
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

Stress echocardiography is an important functional diagnosis and prognostic tool that is now routinely applied to evaluate the risk of cardiovascular artery disease (CAD). A complete dataset containing data on 558 subjects undergoing a prospective longitudinal study is employed to investigate what attributes correlate with the final outcome. The dataset was examined using rough sets, which resulted in a series of decision rules that predict which attributes influence the outcomes measured clinically and recorded in the dataset. The results indicate that the ECG attribute was very informative. In addition, prehistory information has a significant impact on the classification accuracy.
Design and Industrialization Challenges of Memory Dominated SOCs
Authors: J. M. Daga
Venue: Proceedings of the 17th international workshop on Integrated Circuit and System Design. Power and Timing Modeling, Optimization and Simulation (2007)

The quest for the universal memory has attracted many talented researchers and number of investors for years now. The objective is to develop a low cost, high-speed, low power, and reliable non-volatile memory. In practice, the universal memory system is more like an optimized combination of execution and storage memories, each of them having its own characteristics. Typically, execution memories manage temporary data and must be fast, with no endurance limitations. Different types of RAM memories are used to build an optimized hierarchy, including different levels of cache. In addition to RAM memories, non-volatile memories such as ROM or NOR flash used for code storage can be considered as execution memories when in place execution of the code is possible.
3D2Real: Simulation League Finals in Real Robots
Authors: Norbert Michael Mayer, Joschka Boedecker, Rodrigo Silva Guerra, Oliver Obst, Minoru Asada
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

We present a road map for a joint project of the simulation league and the humanoid league that we call 3D2Real. This project is concerned with the integration of these two leagues which is becoming increasingly important as the research fields are converging. Currently, a lot of work is duplicated across the leagues, collaboration is sparse, and knowhow is not transfered effectively. This binds resources to solve the same problems over and over again. To address this, we discuss the current situation of both leagues with respect to these points and focus on open issues that have to be fixed. In addition, we describe existing open standards and contributions from the RoboCup community that we plan to use for the project. As a milestone, we propose to conduct the finals of the 3D simulation tournament on real robots by the year 2008. Finally, we propose a database of simulated parts and algorithms in which each league can benefit and contribute with their expertise. These contributions facilitate synergies to be used across individual leagues for the benefit of the RoboCup project and the year 2050 goal.
Real-Time Illumination of Foliage Using Depth Maps
Authors: Jesus Gumbau, Miguel Chover, Cristina Rebollo, Inmaculada Remolar
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

This article presents a new method for foliage illumination which takes into account direct, indirect illumination and self-shadowing. Both indirect illumination and self-shadowing are approximated by means of a novel technique using depth maps. In addition, a new shadow casting algorithm is developed to render shadows produced by the foliage onto regular surfaces which enhances the appeareance of this kind of shadows compared to traditional shadow mapping techniques.
Enhanced feature selection models using gradient-based and point injection techniques
Authors: D. Huang, Zhaohui Gan, Tommy W. S. Chow
Venue: Neurocomputing (2008)

This paper focuses on enhancing the effectiveness of filter feature selection models from two aspects. First, feature-searching engine is modified based on optimization theory. Second, a point injection strategy is designed to improve the regularization capability of feature selection. The second topic is important, because overfitting is usually experienced. To evaluate the proposed strategies, we implement these strategies to modify two classic filter feature selection models. One model is based on sequential forward search scheme and the other employs genetic algorithms (GA) for feature selection. Comparing the original and modified models on synthetic and real data, the contributions of our modification are shown.
A Chip Multithreaded Processor for Network-Facing Workloads
Authors: Sanjiv Kapil, Harlan McGhan, Jesse Lawrendra
Venue: IEEE Micro (2004)

The article describes an early implementation of a chip multithreaded (CMT) processor, Sun Microsystem's technology to support its throughput computing strategy. CMT processors are designed to handle workloads consisting of multiple threads with light computational demands, typical of Web servers and other network-facing systems.
Low power shift register using MTCMOS edge-trigger D flip flop transmission gate in sub-threshold region
Authors: Sameh Andrawes, Leila Koushaeian, Ronny Veljanovski
Venue: Proceedings of the 7th WSEAS International Conference on Microelectronics, Nanoelectronics, Optoelectronics (2008)

low power design is most required nowadays due to scaling down the technology where minimizing the voltage level is the most effective way to minimize the power consumption. This paper presents the design and implementation of a low power Complementary Metal Oxide Semiconductor (CMOS) ten-bit shift register by using negative latch D Flip-Flop (DFF) in the sub-threshold region with high speed in the active mode and low power consumption during the sleep mode using Multi-threshold Complementary Metal Oxide Semiconductor (MTCMOS) technique. The circuit was implemented in 90 nm from STM CMOS technology, with oxide thickness of 16A0, 250 mV power supply, 5 MHz clock frequency with 10 % activity, average power consumption is 6.43 nW and power delay product (PDP) is 24.43 aJ. The shift register has been designed and simulated by using Cadence tools.
Adaptive preprocessing of scanned documents
Authors: Roumen Kountchev, Vladimir Todorov, Roumiana Kountcheva
Venue: Proceedings of the 10th WSEAS International Conference on Mathematical Methods and Computational Techniques in Electrical Engineering (2008)

A new approach for scanned documents preprocessing, aimed at their efficient archiving with retained visual quality is presented in this paper. The preprocessing is based on image filtration, which consists of Gaussian noise removal with adaptive digital Wiener filter, followed by correction of the uneven background illumination with 2D digital filtration. Then the texts (graphics) are extracted using a special method for image segmentation. The presented approach permits further adaptive processing of the extracted texts and their background in result of which higher compression with retained image quality is obtained. The method ensures very good results when old documents with complicated image structure are processed and archived.
Secrecy in Multiagent Systems
Authors: Joseph Y. Halpern, Kevin R. O'Neill
Venue: ACM Transactions on Information and System Security (TISSEC) (2008)

We introduce a general framework for reasoning about secrecy requirements in multiagent systems. Our definitions extend earlier definitions of secrecy and nondeducibility given by Shannon and Sutherland. Roughly speaking, one agent maintains secrecy with respect to another if the second agent cannot rule out any possibilities for the behavior or state of the first agent. We show that the framework can handle probability and nondeterminism in a clean way, is useful for reasoning about asynchronous systems as well as synchronous systems, and suggests generalizations of secrecy that may be useful for dealing with issues such as resource-bounded reasoning. We also show that a number of well-known attempts to characterize the absence of information flow are special cases of our definitions of secrecy.
A Semiautomatic Content Adaptation Authoring Tool for Mobile Learning
Authors: Hsuan-Pu Chang, Chun-Chia Wang, Timothy K. Shih, Louis R. Chao, Shu-Wei Yeh, Chen-Yu Lee
Venue: Proceedings of the 7th international conference on Advances in Web Based Learning (2008)

A lot of studies about automatic content adaptation have been done and are proposed to overcome the drawbacks of browsing regular content with handheld devices such as pocket PCs and smartphones. But we argue that the total automatic adaptation algorithm designed by an engineer to transform Web Page presentation is still appropriate to be applied on educational content. Therefore, this paper proposes a learning content adaptation tool that provides different adaptation templates to help the author automatically and efficiently reproduce high-quality learning content for specific handhelds. Furthermore, the author will not only be able to preview the adaptation result before publishing the course but also be able to adjust the template parameters manually to affect the process if they are not satisfied with the current result. Finally the new adapted content can be packaged with original content as a multi-version learning course.
Choosing the Kernel Parameters for the Directed Acyclic Graph Support Vector Machines
Authors: Kuo-Ping Wu, Sheng-De Wang
Venue: Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition (2007)

The directed acyclic graph support vector machines (DAGSVMs) have been shown to be able to provide classification accuracy comparable to the standard multiclass SVM extensions such as Max Wins methods. The algorithm arranges binary SVM classifiers as the internal nodes of a directed acyclic graph (DAG). Each node represents a classifier trained for the data of a pair of classes with the specific kernel. The most popular method to decide the kernel parameters is the grid search method. In the training process, classifiers are trained with different kernel parameters, and only one of the classifiers is required for the testing process. This makes the training process time-consuming. In this paper we propose using separation indexes to estimate the generalization ability of the classifiers. These indexes are derived from the inter-cluster distances in the feature spaces. Calculating such indexes costs much less computation time than training the corresponding SVM classifiers; thus the proper kernel parameters can be chosen much faster. Experiment results show that the testing accuracy of the resulted DAGSVMs is competitive to the standard ones, and the training time can be significantly shortened.
LibGeoDecomp: A Grid-Enabled Library for Geometric Decomposition Codes
Authors: Andreas Schäfer, Dietmar Fey
Venue: Proceedings of the 15th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2008)

In this paper we present first results obtained with LibGeoDecomp, a work in progress library for scientific and engineering simulations on structured grids, geared at multi-cluster and grid systems. Today's parallel computers range from multi-core PCs to highly scaled, heterogeneous grids. With the growing complexity of grid resources on the one hand, and the increasing importance of computer based simulations on the other, the agile development of highly efficient and adaptable parallel applications is imperative. LibGeoDecomp is to our knowledge the first library to support all state of the art features from dynamic load balancing and exchangeable domain decomposition techniques to ghost zones with arbitrary width and parallel IO, along with a hierarchical parallelization whose layers can be adapted to reflect the underlying hierarchy of the grid system.
Classification of Obstructive Sleep Apnea by Neural Networks
Authors: Zhongyu Pang, Derong Liu, Stephen R. Lloyd
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Electroencephalogram (EEG) is a common tool to explore brain activities ranging from concentrated cognitive efforts to sleepiness. For the issue of sleepiness, pupil behavior can provide some information regarding alertness. The issue of sleepiness can be reflected by EEG energy. Specifically, intrusion of EEG theta wave activity into the beta activity of active wakefulness has been interpreted as ensuing sleepiness. This paper develops an innovative signal classification method that is capable of differentiating subjects with sleep disorder of obstructive sleep apnea (OSA) which cause excessive daytime sleepiness (EDS) from normal control subjects who do not have a sleep disorder. The theta energy ratios are calculated from the 2-second sliding windows by Fourier transform. An artificial neural network of modified ART2 is utilized to identify subjects with OSA from a combined group of subjects including healthy controls. This grouping from the neural network is then compared with the actual diagnostic classification of subjects as OSA or healthy controls and it is found to be 91% accurate in differentiating between the two groups.
On Abstraction and Interpretability: A Behavioural Perspective
Authors: Raphael Pfaff, Keith J. Burnham
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

The process of abstracting physical systems to obtain models and interpret these for the desired purpose is considered from a perspective originating from the behavioural framework. It is pointed out that for the purpose of modelling regenerative processes or passive controllers, the behavioural framework and bond graphs are well suited. To both techniques, a brief introduction is presented, focusing on the key concepts and applying illustrative examples and a simulation.
Which Symmetric Homogeneous Polynomials Can Be Proved Positive Semi-definite by Difference Substitution Method?
Authors: Liangyu Chen, Zhenbing Zeng
Venue: Computer Mathematics: 8th Asian Symposium, ASCM 2007, Singapore, December 15-17, 2007. Revised and Invited Papers (2008)

Recently a method based on substitution of difference of variables has been developed by Yang [12] for verifying the positive semi-definiteness of homogeneous polynomials. In this paper, we investigate the structure of the cone formed by all symmetric homogeneous polynomials whose positive semi-definiteness can proven by difference substitution method.
A Novel DC Nodal Pricing Method Based on Linear Programming in Competitive Electricity Market
Authors: Bo Yang, Yun-Ping Chen, Zun-Lian Zhao, Qi-Ye Han
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

AC based nodal pricing method makes market rule less transparent and affects market decisions on risk and opportunity in short-run and long-run periods. Therefore, AC based nodal pricing formulation is simplified into DC based nodal pricing formulation, which maximizes total social welfare with the condition of satisfying Kirchhoff's laws and other operational constraints in modified DC optimal power flow model. Then, a simple but practical linear programming based nodal pricing method, which can be applied to solve market clearing mode with piecewise constant supply and demand curves, is proposed. The proposed method is tested on IEEE 30 bus system. Test results show that it can avoid premature and divergent phenomenon, which always occurs in the solution of AC based nodal pricing formulation, and has potential application in competitive electricity market.
Faster Multi-exponentiation through Caching: Accelerating (EC)DSA Signature Verification
Authors: Bodo Möller, Andy Rupp
Venue: Proceedings of the 6th international conference on Security and Cryptography for Networks (2008)

When verifying digital signatures, achieving a high throughput can be crucial. We present a technique that is useful for ECDSA and DSA signatures. It assumes that common domain parameters are used (which is typical of ECDSA) and that at least some signers recur (as in many application scenarios). We can achieve noticeable speedups in very different environments-- from highly restricted ones where memory is very scarce to larger machines without severe memory restrictions. Requirements for the target platform are very small for a beneficial application of our technique. This makes it attractive for embedded systems, where ECDSA is a signature scheme of choice.More generally, what we consider is the task of computing power products $\prod_{1 \leq i \leq k} g_i^{e_i}$ ("multi-exponentiation") where base elements g 2, ..., g k are fixed while g 1 is variable between multi-exponentiations but may repeat, and where the exponents are bounded (e.g., in a finite group). We present a new technique that entails two different ways of computing such a product. The first way applies to the first occurrence of any g 1 where, besides obtaining the actual result, we create a cache entry based on g 1, investing very little memory or time overhead. The second way applies to any multi-exponentiation once such a cache entry exists for the g 1 in question and provides for a significant speed-up.
Reconfigurable Real-Time Middleware for Distributed Cyber-Physical Systems with Aperiodic Events
Authors: Yuanfang Zhang, Christopher Gill, Chenyang Lu
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

Different distributed cyber-physical systems must handle a periodic and periodic events with diverse requirements. While existing real-time middleware such as Real-Time CORBA has shown promise as a platform for distributed systems with time constraints, it lacks flexible configuration mechanisms needed to manage end-to-end timing easily for a wide range of different cyber-physical systems with both aperiodic and periodic events. The primary contribution of this work is the design, implementation and performance evaluation of the first configurable component middleware services for admission control and load balancing of a periodic and periodic event handling in distributed cyber-physical systems. Empirical results demonstrate the need for, and the effectiveness of, our configurable component middleware approach in supporting different applications with a periodic and periodic events, and providing a flexible software platform for distributed cyber-physical systems with end-to-end timing constraints.
A Thorough Analysis of the Suppressed Fuzzy C-Means Algorithm
Authors: László Szilágyi, Sándor M. Szilágyi, Zoltán Benyó
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

Suppressed fuzzy c-means (s-FCM) clustering was introduced in [Fan, J. L., Zhen, W. Z., Xie, W. X.: Suppressed fuzzy c-means clustering algorithm. Patt. Recogn. Lett. 24, 1607---1612 (2003)] with the intention of combining the higher speed of hard c-means (HCM) clustering with the better classification properties of fuzzy c-means (FCM) algorithm. They added an extra computation step into the FCM iteration, which created a competition among clusters: lower degrees of memberships were diminished according to a previously set suppression rate, while the largest fuzzy membership grew by swallowing all the suppressed parts of the small ones. Suppressing the FCM algorithm was found successful in the terms of accuracy and working time, but the authors failed to answer a series of important questions. In this paper we attempt to clarify the view upon the optimality and the competitive behavior of s-FCM via analytical computations and numerical analysis.
Realistic Threats to Self-Enforcing Privacy
Authors: Giampaolo Bella, Francesco Librizzi, Salvatore Riccobene
Venue: Proceedings of the 2008 The Fourth International Conference on Information Assurance and Security (2008)

A recent privacy protocol for secure e-polls aims at ensuring the submitting individuals that the pollster will preserve the privacy of their submitted preferences. Otherwise the individuals can indict the pollster, provided that the pollsterparticipates actively in this phase. The analysis of the protocol in a realistic threat model denounces that a malicious pollster that abuses the private preferences by disclosure will arguably not help out during its own indictment. Therefore, the protocol ensures insufficient fairness among their participants because it gives the pollster some advantage over the individuals. Two variant protocols are introduced and analysed in the same threat model — one is found to move the advantage over the individuals, the otheris found to achieve a satisfactory level of fairness.
Integrating heterogeneous agent programming platforms within artifact-based environments
Authors: Alessandro Ricci, Michele Piunti, L. Daghan Acay, Rafael H. Bordini, Jomi F. Hübner, Mehdi Dastani
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

"Agents and Artifacts" (A&A) and CARTAGO are becoming increasingly popular as, respectively, a general-purpose programming model and a related infrastructure for developing shared computational environments in agent-based software systems. However, so far there has been no work on developing multiagent systems (MAS) where agents implemented and deployed in different agent-programming platforms can interact as part of the same MAS with a shared environment. Due to the generality of CARTAGO environments and its Java-based implementation, we have successfully implemented an open multi-agent system where heterogeneous agents developed with different platforms---namely Jason, 2APL as BDI-based approaches and simpA as an activity-oriented approach rather than BDI-based---work together in shared workspaces where they interact and cooperate by dynamically creating and using shared artifacts, analogously to human working environments. This paper shows how this was achieved by first presenting a general model for incorporating a theory of use and observation of artifacts in cognitive agents, then describing a general approach for developing such heterogeneous MAS using CARTAGO integrated with existing agent-oriented programming platforms.
Semantic Text Classification of Emergent Disease Reports
Authors: Yi Zhang, Bing Liu
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

Traditional text classification studied in the information retrieval and machine learning literature is mainly based on topics. That is, each class represents a particular topic, e.g., sports and politics. However, many real-world problems require more refined classification based on some semantic perspectives. For example, in a set of sentences about a disease, some may report outbreaks of the disease, some may describe how to cure the disease, and yet some may discuss how to prevent the disease. To classify sentences at this semantic level, the traditional bag-of-words model is no longer sufficient. In this paper, we study semantic sentence classification of disease reporting. We show that both keywords and sentence semantic features are useful. Our results demonstrated that this integrated approach is highly effective.