ppxscal/embedding_network huggingface dataset:
Learning Decision Tree for Selecting QRS Detectors for Cardiac Monitoring
Authors: François Portet, René Quiniou, Marie-Odile Cordier, Guy Carrault
Venue: Proceedings of the 11th conference on Artificial Intelligence in Medicine (2007)

The QRS complex is the main wave of the ECG. It is widely used for diagnosing many cardiac diseases. Automatic QRS detection is an essential task of cardiac monitoring and many detection algorithms have been proposed in the literature. Although most of the algorithms perform satisfactorily in normal situations, there are contexts, in the presence of noise or a specific pathology, where one algorithm performs better than the others. We propose a combination method that selects, on line, the detector that is the most adapted to the current context. The selection is done by a decision tree that has been learnt from the performance measures of 7 algorithms in various instances of 130 combinations of arrhythmias and noises. The decision tree is compared to expert rules tested in the framework of the cardiac monitoring system IP-Calicot.
Analysis of Learning Objectives in Object Oriented Programming
Authors: Peter Hubwieser
Venue: Proceedings of the 3rd international conference on Informatics in Secondary Schools - Evolution and Perspectives: Informatics Education - Supporting Computational Thinking (2008)

The paper presents an analysis of the learning objectives that have to be achieved in order to learn Object Oriented Programming. By using the prerequisite relation between these objectives we develop a sequence of concepts for a textbook. The article is closed by some considerations concerning the electronic management of learning objectives using ontologies.
Neighborhood Rough Set Model Based Gene Selection for Multi-subtype Tumor Classification
Authors: Shulin Wang, Xueling Li, Shanwen Zhang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Multi-subtype tumor diagnosis based on gene expression profiles is promising in clinical medicine application. Therefore, a great deal of research on tumor classification based on gene expression profiles has been developed, where various machine learning approaches were applied to constructing the best tumor classification model to improve the classification performance as much as possible. To achieve this goal, extracting features or finding informative genes that have good classification ability is crucial. We propose a novel gene selection approach, which adopts Kruskal-Wallis rank sum test to rank all genes and then apply an algorithm based on neighborhood rough set model to gene reduction to obtain gene subsets with fewer genes and more classification ability. Experiments on a small round blue cell tumor (SRBCT) dataset show that our approach can achieve very high classification accuracy with only three or four genes as evaluated by three classifiers: support vector machines, K-nearest neighbor and neighborhood classifier, respectively.
Algorithms for biomarker identification utilizing maldi tof mass spectrometry
Authors: Jonathan W. Valvano, Mia K. Markey
Venue:  (2006)

Currently, the best way to reduce the mortality of cancer is to detect and treat it in the earliest stages. Technological advances in genomics and proteomics have opened a new realm of methods for early detection that show potential to overcome the drawbacks of current strategies. In particular, pattern analysis of mass spectra of blood samples has attracted attention as an approach to identification of potential biomarkers for early detection of cancer. Mass spectrometry provides rapid and precise measurements of the sizes and relative abundances of the proteins present in a complex biological/chemical mixture. However, this high-throughput nature of mass spectrometry has also raised a need for the development of efficient and effective bioinformatics tools for finding biologically meaningful information. Many scholars are interested in preprocessing of raw mass spectra and in extracting and selecting features from preprocessed mass spectra. These are key issues for accurate biomarker identification. Thus, in order to improve the process of biomarker identification using mass spectrometry, I have postulated a noise model for MALDI TOF mass spectrometry from the perspective of stochastic signal processing, and have attempted to measure the spectral characteristics of components in the noise model. Noise in mass spectrometry can interfere with identification of the biochemical substances in a sample. I assumed that the noise in MALDI TOF mass spectrometry is composed of three components: noise from instrumentation, noise from random ion motions, and chemical noise. In this dissertation, I have separated and analyzed noise from instrumentation and chemical noise using parametric power spectral density estimation and wavelet-based analysis, respectively. In addition to these noise analysis studies, I also have designed an algorithm that can select independent and discriminant features from mass spectra of complex protein samples by reducing redundant and irrelevant information.
Towards a Rule-Based Matcher Selection
Authors: Malgorzata Mochol, Anja Jentzsch
Venue: Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns (2008)

The central problems w.r.t. interoperability and data integration issues in the Semantic Web are schema and ontology matching approaches. Today it takes an expert to determine the best algorithm and a decision can usually be made only after experimentation, so as both the necessary scaling and off-the-shelf use of matching algorithms are not possible. To tackle these issues, we present a rule-based evaluation method in which the best algorithms are determined semi-automatically and the selection performs prior to the execution of an algorithm.
openSDK: an open-source implementation of OPEN-R
Authors: Nuno P. Lopes, Pedro U. Lima
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

This paper describes openSDK, an open-source implementation of Sony's AIBO development kit (OPEN-R). openSDK is capable of running unmodified AIBO programs (only a recompilation is necessary) on a standard computer, using a simulator at full frame rate (currently only USARSim is supported) or on a different robotic hardware platform. openSDK also offers standard debugging facilities for AIBO programs.
Six/one router: a scalable and backwards compatible solution for provider-independent addressing
Authors: Christian Vogt
Venue: Proceedings of the 3rd international workshop on Mobility in the evolving internet architecture (2008)

The scalability of the Internet routing system suffers from an increasing demand for provider-independent, non-aggregatable IP addresses in networks at the Internet edge. New routing architectures have been proposed that mitigate this problem through indirection between provider-independent addresses at the edge and aggregatable, provider-allocated addresses in the core of the Internet. A major challenge in these architectures is backwards compatibility. Address indirection requires support at the sender and the receiver, so without appropriate backwards compatibility support, it defeats communications between the upgraded and the legacy Internet. This paper proposes an address-indirection-based solution that is backwards compatible. The solution is shown to offer the benefits of provider-independent addressing in a scalable and backwards compatible manner, and to provide the incentives necessary to foster its early deployment.
Ontology negotiation in heterogeneous multi-agent systems: The ANEMONE system
Authors: Jurriaan van Diggelen, Robbert-Jan Beun, Frank Dignum, Rogier M. van Eijk, John-Jules Meyer
Venue: Applied Ontology (2007)

In open heterogeneous multi-agent systems, communication is hampered by lack of common ontologies. Ontologies may differ in naming conventions, granularity and scope. In such an environment, the agents must possess the right conversational skills to effectively exchange information even when the speaker's ontology is only approximately translatable to the hearer's ontology. Furthermore, the agents must be able to autonomously establish an ontology translation by exchanging parts of their ontologies. In this paper, we propose a layered communication protocol in which the agents gradually build towards a semantically integrated system by establishing minimal and effective common ontologies. We tested our system, called ANEMONE, on a number of heterogeneous news agents. We show how these agents successfully exchange information on news articles, despite initial difficulties caused by heterogeneous ontologies.
Improving Real-Time Performance of a Virtual Machine Monitor Based System
Authors: Megumi Ito, Shuichi Oikawa
Venue: Proceedings of the 6th IFIP WG 10.2 international workshop on Software Technologies for Embedded and Ubiquitous Systems (2008)

This paper describes our approach to enable Gandalf VMM (Virtual Machine Monitor) to be interruptible. Although Gandalf is shown to be a lightweight VMM, the detailed performance analysis using PMC (Performance Monitoring Counters) showed Gandalf executes with interrupts disabled for a rather long duration of time. By making Gandalf interruptible, we are able to make VMM based systems more suitable for embedded and ubiquitous systems. We analyzed the requirements to make Gandalf interruptible, designed and implemented the mechanisms to realize it. The experimental results shows that making Gandalf interruptible significantly reduces a duration of execution time with interrupts disabled while it does not impact the performance.
Extending Timed Process Algebra with Discrete Stochastic Time
Authors: Jasen Markovski, Erik P. Vink
Venue: Proceedings of the 12th international conference on Algebraic Methodology and Software Technology (2008)

When extending timed process algebra with discrete stochastic time, typical standard notions like time additivity are hard to preserve in the presence of the race condition. We propose context-sensitive interpolation as a restricted form of time additivity to accommodate the extension with stochastic time. We also present a stochastic process algebra featuring an explicit account of two types of race conditions in terms of conditional random variables. The approach enables compositional modeling, a non-trivial expansion law, and explicit manipulation of maximal progress.
Ant Colony Optimization for Genome-Wide Genetic Analysis
Authors: Casey S. Greene, Bill C. White, Jason H. Moore
Venue: Proceedings of the 6th international conference on Ant Colony Optimization and Swarm Intelligence (2008)

In human genetics it is now feasible to measure large numbers of DNA sequence variations across the human genome. Given current knowledge about biological networks and disease processes it seems likely that disease risk can best be modeled by interactions between biological components, which can be examined as interacting DNA sequence variations. The machine learning challenge is to effectively explore interactions in these datasets to identify combinations of variations which are predictive of common human diseases. Ant colony optimization (ACO) is a promising approach to this problem. The goal of this study is to examine the usefulness of ACO for problems in this domain and to develop a prototype of an expert knowledge guided probabilistic search wrapper. We show that an ACO approach is not successful in the absence of expert knowledge but is successful when expert knowledge is supplied through the pheromone updating rule.
Dealing with Non-linearity in Shape Modelling of Articulated Objects
Authors: Grégory Rogez, Jesús Martínez-Del-Rincón, Carlos Orrite
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I (2007)

We address the problem of non-linearity in 2D Shape modelling of a particular articulated object: the human body. This issue is partially resolved by applying a different Point Distribution Model (PDM) depending on the viewpoint. The remaining non-linearity is solved by using Gaussian Mixture Models (GMM). A dynamic-based clustering is proposed and carried out in the Pose Eigenspace. A fundamental question when clustering is to determine the optimal number of clusters. From our point of view, the main aspect to be evaluated is the mean gaussianity. This partitioning is then used to fit a GMM to each one of the view-based PDM, derived from a database of Silhouettes and Skeletons. Dynamic correspondences are then obtained between gaussian models of the 4 mixtures. Finally, we compare this approach with other two methods we previously developed to cope with non-linearity: Nearest Neighbor (NN) Classifier and Independent Component Analysis (ICA).
Flexible hardware-software cooperation system with HwModule board and co-design framework by ET
Authors: Hiroshi Yoshikawa, Kiyoshi Akama, Hiroshi Mabuchi, Rika Satoh
Venue: Proceedings of the 7th WSEAS International Conference on Applied Computer and Applied Computational Science (2008)

When solving problems efficiently by Hardware-Software cooperation, a lot of extra work such as circuit design, software design, Hardware/Software interface design, etc, has to be done. In order to reduce this workload, we propose a co-design framework using ET, and introduce a flexible cooperation system using HwModule Board. A problem can then be easily described by ET rules, the ET description can be safely divided into hardware and software descriptions, and the cooperation system can be flexibly adapted to them via the framework.
Secure Implementation of the Stern Authentication and Signature Schemes for Low-Resource Devices
Authors: Pierre-Louis Cayrel, Philippe Gaborit, Emmanuel Prouff
Venue: Proceedings of the 8th IFIP WG 8.8/11.2 international conference on Smart Card Research and Advanced Applications (2008)

In this paper we describe the first implementation on smartcard of the code-based authentication protocol proposed by Stern at Crypto'93 and we give a securization of the scheme against side channel attacks. On the whole, this provides a secure implementation of a very practical authentication (and possibly signature) scheme which is mostly attractive for light-weight cryptography.
The Parallel Predator-Prey Model: A Step towards Practical Application
Authors: Christian Grimme, Joachim Lepping, Alexander Papaspyrou
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

In this paper, we apply the parallel predator-prey model for multi-objective optimization to a combinatorial problem for the first time: Exemplarily, we optimize sequences of 50 jobs for an instance of the bi-criteria scheduling problem 1|d j | ¿ C j ,L max with this approach. The modular building block architecture of the predator-prey system and the distribution of acting entities enables the analysis of separated problem knowledge and the design of corresponding variation operators. The actual modules are derived from local heuristics that tackle fractions of the complete problem. We unveil that it is possible to cover different areas of the Pareto-front with special property operators and make evident that the whole front can be covered if those operators are applied simultaneously to the spatial population. Further, we identify open problems that arise when the predator-prey model is applied to combinatorial problems which have not yet occurred for real-valued optimization problems.
Scalable web service-based xml message brokering across organizations
Authors: Dennis Gannon
Venue:  (2007)

Publish/subscribe model is widely used in distributed systems for information dissemination among different entities. A publish/subscribe broker decouples these entities and increases scalability of a publish/subscribe system. Web service is a promising technology to integrate heterogeneous applications in different organizations across Internet using standard XML data format. It is an important building block of the emerging service-oriented architecture (SOA). With the increasing demand for interactions among software applications in different organizations, the scope of publish/subscribe message dissemination is extended to the Internet scale. How to facilitate such an extension is a new challenge. In this dissertation, I propose a scalable service-oriented model, layered publish/subscribe model (LPS), that separates different concerns in Internet-scale publish/subscribe systems into five layers. Two related systems are developed based on this model: WS-Messenger and OpenPS. The WS-Messenger project addresses new challenges in Web service-based publish/subscribe brokering systems. It proposes a flexible and efficient mediation approach to reconcile conflicts among competing specifications in Web service-based publish/subscribe systems, namely WS-Eventing and WS-Notification. The mediation approach is based on a normalization-processing-customization (NPC) mediation model. WS-Messenger has been successfully applied to service-oriented scientific workflows in the LEAD (Linked Environments for Atmospheric Discovery) project. It addresses several practical problems to ease the deployment of event-driven systems, such as monitoring, debugging and firewall-blocked message delivering. The OpenPS project explores how to create an Internet-scale sharable publish/subscribe brokering service for message dissemination across organization boundaries. It is designed to achieve all three dimensions of scalability (load scalability, geographic scalability and administrative scalability) without losing support for expressive subscriptions. Analogous to postal service, OpenPS broker networks act as third-party services that focus on efficient and scalable message distribution across different organizations. They work together with local publish/subscribe brokers within each organization to achieve economies of scale in Web-based publish/subscribe message brokering in wide-area networks. Experimental studies conducted on these two prototype systems validate the feasibility of the LPS model.
Security policy for deducting unauthorized IP based mobile host inside the network
Authors: V. K. Sanjeevi, Veluchandhar Veluchandhar, S. Sakthivel, M. Supriya
Venue: Proceedings of the 7th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications (2008)

The technology evaluation of mobile management system has integrated with significant improvement in mobile computing. The requirements for mobile security are more important when we are accessing the sensitive data from the database. Concurrency control ensures that individual users meet consistent states of the mobile databases with security. But in the IP based mobile network the relay of data is not continuous and also the connection may lose at any time. The IP alone is not suitable for identifying the mobile host inside the network. In this paper, it is proposed a model to enhance the performance of mobile security for IP based mobile host.
Do virtual worlds create better real worlds?
Authors: Mark P. Mobach
Venue: Virtual Reality (2008)

Over the last years, virtual reality (VR) has been said to offer promise for design visualisation and has started to be included in participatory design methodology. This research provides an overview of the use of VR in architectural design and organizational space design, and explores how this application can be integrated with participatory design. The effects of the proposed integration of participatory design, VR, architecture and organization were studied in two pharmaceutical case studies. It was assessed whether the participants actually changed the design and to what extent this affected staff satisfaction and construction costs. The results show that the design was changed, staff satisfaction improved, and costs were reduced.
Forensic Artifacts of Microsoft Windows Vista System
Authors: Daniel M. Purcell, Sheau-Dong Lang
Venue: Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics (2008)

This paper reviews changes made to Microsoft Windows Vista system from earlier Windows operating system (such as XP) and directs attention to system artifacts that are of evidentiary values in typical computer forensics work. The issues addressed include: NTFS on-disk structure, file system's directory structures, symbolic links, and recycle bin; we also briefly mention artifacts related to Windows mail, paging file, thumbnail caching, and print spooling.
An Intelligent Digital Content Protection Framework Between Home Network Receiver Devices
Authors: Qingqi Pei, Kefeng Fan, Jinxiu Dai, Jianfeng Ma
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

This paper presents an intelligent digital content protection framework for various digital interfaces in consumer electronics device, named universal content protection system (UCPS).The UCPS system aims at achieving three aspects. First, it is to achieve secret transmission of audiovisual content between the interfaces in valid devices. Second, it is to achieve the integrality between the related control information in the valid devices. Third, it is to maintain the integrality of the system. The proposed framework can be have been implemented as a security core which can be transplanted to the digital interfaces including the POD-Host, HDMI, DVI, USB, IEEE 1394 used in the home network receiver devices.
Some Aspects of Message-Passing on Future Hybrid Systems (Extended Abstract)
Authors: Rolf Rabenseifner
Venue: Proceedings of the 15th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2008)

In the future, most systems in high-performance computing (HPC) will have a hierarchical hardware design, e.g., a cluster of ccNUMA or shared memory nodes with each node having several multi-core CPUs. Parallel programming must combine the distributed memory parallelization on the node inter-connect with the shared memory parallelization inside each node. There are many mismatch problems between hybrid hardware topology and the hybrid or homogeneous parallel programming models on such hardware. Hybrid programming with a combination of MPI and OpenMP is often slower than pure MPI programming. Major chances arise from the load balancing features of OpenMP and from a smaller memory footprint if the application duplicates some data on all MPI processes [1,2,3].