ppxscal/embedding_network huggingface dataset:
Using the Grid for Enhancing the Performance of a Medical Image Search Engine
Authors: Mikko Juhani Pitkanen, Xin Zhou, Antti E. J. Hyvarinen, Henning Muller
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

In this paper we show how Grid computing can be used to improve the operation of a medical image search system. The paper introduces the basic principles of a content-based image retrieval (CBIR) system and identifies the computationally challenging tasks in the system. For the computationally challenging tasks an efficient design is proposed that uses distributed Grid computing to carry out the image processing in a distributed and efficient way. The algorithms of the search system are executed by using a real medical image collection as input and a Grid computing infrastructure to provide the needed computing power. Finally, the results show how the image processing task that required tens of hours to complete can be processed by using only a fraction of the originally required computing time.
From Parallel Virtual Machine to Virtual Parallel Machine: The Unibus System
Authors: Vaidy Sunderam
Venue: Proceedings of the 15th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2008)

Network-based concurrent computing frameworks have matured over two decades. However, in the realm of multi-domain geographically distributed computing, their true potential is yet to be realized. Popularly termed "grids", these metacomputing systems have yet to see widespread adoption and use, partly due to challenges resulting from heterogeneity, deployment issues, and dynamicity. The Unibus project proposes novel strategies for unifying and dynamically conditioning shared heterogeneous resources located within multiple administrative domains. Our approach is based on client-centric overlay software that provides unified interfaces to diverse resources, complemented by runtime systems that substantially automate setup and configuration. The overlay unifies heterogeneous resources through service drivers or mediators that operate analogously to device drivers. New resources and variations in availability are handled through self-deployment of mediators and their service daemon counterparts, enabling the overlay to adaptively present applications with coherent aggregated projections of the underlying resources. Dynamic incorporation of new resources is facilitated via automated environment conditioning that uses deployment descriptors in conjunction with site-specific data to prepare platforms for execution. We will discuss the motivations and rationale behind the Unibus approach, describe the design of the framework, and present preliminary results and experiences.
(Short) Survey of Real Hypercomputation
Authors: Martin Ziegler
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

We survey and compare models of computation on real numbers exceeding the Church---Turing Hypothesis.
Epidemic Information Dissemination in Distributed Systems
Authors: Patrick T. Eugster, Rachid Guerraoui, Anne-Marie Kermarrec, Laurent Massoulieacute;
Venue: Computer (2004)

Epidemic algorithms have recently gained popularity as a potentially effective solution for disseminating information in large-scale systems, particularly peer-to-peer systems deployed on Internet or ad hoc networks. These algorithms mimic the spread of a contagious disease: Each process in a distributed system relays new information it has received to randomly chosen peers rather than to a server or cluster of servers in charge of forwarding it. In turn, each of these processes forwards the information to other randomly selected processes, and so on.Although researchers have used epidemic algorithms in applications such as failure detection, data aggregation, and database replication, their general applicability to practical, Internet-wide systems remains unproven. The authors suggest possible solutions to four key problems membership maintenance, network awareness, buffer management, and message filtering.
A Preemption Algorithm for a Multitasking Environment on Dynamically Reconfigurable Processor
Authors: Vu Manh Tuan, Hideharu Amano
Venue: Proceedings of the 4th international workshop on Reconfigurable Computing: Architectures, Tools and Applications (2008)

Task preemption is a critical mechanism for building an effective multitasking environment on dynamically reconfigurable processors. When being preempted, necessary state information of the interrupted task in registers and distributed internal memories must be correctly preserved. This paper aims at studying a method for saving and restoring the state data of a hardware task, executing on a dynamically reconfigurable processing array, taking into account the great amount and the distribution on different storage elements of data. Performance degradation caused by task preemption is minimized by allowing preemption only at predefined points where demanded resources are small. Specifically, we propose: 1) algorithms to insert preemption points subject to user-specified preemption latency and resource overhead constraints; 2) modification steps to incorporate the offered algorithms on the system design flow. Evaluation results on the NEC DRP architecture show that the proposed method achieves a reasonable hardware overhead (from 6% to 14%) while satisfying a given preemption latency.
Bio-inspired Search and Distributed Memory Formation on Power-Law Networks
Authors: Tathagata Das, Subrata Nandi, Andreas Deutsch, Niloy Ganguly
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

In this paper, we report a novel and efficient algorithm for searching P2P networks having a power law topology. Inspired by the natural immune system, it is a completely decentralized algorithm where each peer searches by sending out random walkers to a limited number of neighbors. As it finds other peers having similar content, it restructures its own neighborhood with the objective of bringing them closer. This restructuring leads to clustering of nodes with similar content, thus forming P2P communities. Alongside, the search algorithm also adapts its walk strategy in order to take advantage of the community thus formed. This search strategy is more than twice as efficient as pure random walk on the same network.
An ID-Based Random Key Pre-distribution Scheme for Wireless Sensor Networks
Authors: Tran Thanh Dai, Choong Seon Hong
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

When wireless senor networks (WSNs) are deployed in hostile areas, they indeed need to be secured by security mechanisms. To do this, cryptographic keys must be agreed on by communicating nodes. Unluckily, due to resource constraints, the key agreement problem in wireless sensor networks becomes quite intricate. In this paper, we propose a new ID-based random key pre-distribution scheme that is comparable to Du et al.'s scheme [2] in terms of network resiliency and memory usage. On the other hand, our later analysis shows that our scheme outperforms Du et al.'s scheme in terms of computational and communication overhead.
Analysis of autonomic computing concepts in computational grid based on the ACLM model
Authors: Goran Martinovic, Damir Filko, Miran Karic
Venue: Proceedings of the 7th WSEAS International Conference on Software Engineering, Parallel and Distributed Systems (2008)

This paper deals with basic concepts of autonomic computing. Each concept is associated with an autonomy indicator. Quality indicators for autonomic environments are also given. They describe system capability for self- -healing, -optimization, -configuration and -protection. The proposed Autonomic Computing Layer Model (ACLM) is described in detail. It enables a framework for implementation of autonomic computing concepts at the levels of security and authentication, policy and goals, management, translation, security as well as communication and resource level. Autonomy of a computational grid as a heterogeneous and dynamic environment is discussed. Also, usability of the proposed ACLM model for the implementation of autonomic computing concepts in the grid is analyzed.
Networking Multiword Units
Authors: Matthieu Constant, Patrick Watrin
Venue: Proceedings of the 6th international conference on Advances in Natural Language Processing (2008)

This paper details a network infrastructure for representing and sharing multiword units. It enables connecting local networks describing linguistic semi-fixed components in the form of local grammars.
A Time Zone Index Method to Identify Time-Based Mobile User Interaction Patterns
Authors: Toshihiko Yamakami
Venue: Proceedings of the 2008 7th International Conference on Mobile Business (2008)

The mobile Internet services require context-awareness and user-segment-awareness to improve usability and quality of content. The author proposes a time zone index, which aims to identify which time zones in a day the users use for a particular mobile service. The author attempts to identify user clusters with this index and examine loyalty in each cluster. From observation, the proposed method effectively partitions the users into three groups, the strong loyal users, the average users and the weak loyal users.
Simulation environment for performance evaluation of SIP handover
Authors: Rok Libnik, Ales Svigelj, Gorazd Kandus
Venue: Proceedings of the 7th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications (2008)

Wireless networks are evolving very fast and user's demands are increasing. A lot of operators already offer first fixed-mobile services. In the future operators will need to enable users to use communications independent from access technologies. In this paper we presented simulation results for handover between WLAN and HSDPA network using SIP protocol. To achieve more credible results we used characteristics of real operator's networks. Simulation results show that characteristics of today's networks are not good enough to offer seamless handover using SIP protocol and that mobile packet wireless networks will need to improve to offer lower latencies.
Image Quality Assessment Based on Wavelet Coefficients Using Neural Network
Authors: Dongxue Yue, Xinsheng Huang, Hongli Tan
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

A novel image quality metric based on the characteristics of wavelet coefficients of images is proposed in this paper. An image is decomposed into several levels by means of wavelet transform. The standard deviations of the diagonal details (HH coefficients) at each level increase with the noise standard deviation increasing and decrease with the blurring radius increasing. According to that, an image quality can be measured by analyzing the characteristics of its wavelet coefficients. Neural network is used to realize the algorithm of image quality assessment. The results of experiments demonstrate that the image quality metric is reasonable and the algorithm realization using neural network is feasible and performs well.
Cubic spline interpolation to develop contours of large reservoirs and evaluate area and volume
Authors: Panayiotis Foteinopoulos
Venue: Advances in Engineering Software (2009)

The paper describes the development of an algorithm that uses spline interpolation methods in order to calculate the ground relief contours, the area and the volume reservoir associated with a large dam. This algorithm is a great help to the engineer who designs dams in calculating the area and the volume of the reservoir for dams with specific positions and geometric characteristics, for different water levels and over a ground relief with elevation contours which one evaluates, smoothes and draws using cubic splines. The advantages of the algorithm are significant not only for specific computer programs that refer to reservoirs, but also for computer programs relevant to hydraulic calculations of reservoirs and associated structures.
Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal
Authors: Babak Mohammadzadeh Asl, Seyed Kamaledin Setarehdan, Maryam Mohebbi
Venue: Artificial Intelligence in Medicine (2008)

Objective: This paper presents an effective cardiac arrhythmia classification algorithm using the heart rate variability (HRV) signal. The proposed algorithm is based on the generalized discriminant analysis (GDA) feature reduction scheme and the support vector machine (SVM) classifier. Methodology: Initially 15 different features are extracted from the input HRV signal by means of linear and nonlinear methods. These features are then reduced to only five features by the GDA technique. This not only reduces the number of the input features but also increases the classification accuracy by selecting most discriminating features. Finally, the SVM combined with the one-against-all strategy is used to classify the HRV signals. Results: The proposed GDA- and SVM-based cardiac arrhythmia classification algorithm is applied to input HRV signals, obtained from the MIT-BIH arrhythmia database, to discriminate six different types of cardiac arrhythmia. In particular, the HRV signals representing the six different types of arrhythmia classes including normal sinus rhythm, premature ventricular contraction, atrial fibrillation, sick sinus syndrome, ventricular fibrillation and 2^oheart block are classified with an accuracy of 98.94%, 98.96%, 98.53%, 98.51%, 100% and 100%, respectively, which are better than any other previously reported results. Conclusion: An effective cardiac arrhythmia classification algorithm is presented. A main advantage of the proposed algorithm, compared to the approaches which use the ECG signal itself is the fact that it is completely based on the HRV (R-R interval) signal which can be extracted from even a very noisy ECG signal with a relatively high accuracy. Moreover, the usage of the HRV signal leads to an effective reduction of the processing time, which provides an online arrhythmia classification system. A main drawback of the proposed algorithm is however that some arrhythmia types such as left bundle branch block and right bundle branch block beats cannot be detected using only the features extracted from the HRV signal.
Detecting Alluvial Fans Using Quantitative Roughness Characterization and Fuzzy Logic Analysis
Authors: Andrea Taramelli, Laura Melelli
Venue: Proceeding sof the international conference on Computational Science and Its Applications, Part I (2008)

This research, based on a similarity geometric model, uses quantitative roughness characterization and fuzzy logic analysis to map alluvial fans. We choose to work in the Italian central Apennine intermountain basins because much human activities could mask this kind of landforms and because the timing of alluvial deposition is tied to land surface instabilities caused by regional climate changes. The main aim of the research is to understand where they form and where they extent in an effort to develop a new approach using the backscatter roughness parameters and primary attributes (elevation and curvature) derived from the SRTM DEM. Moreover, this study helps to provide a benchmark against which future alluvial fans detection using roughness and fuzzy logic analysis can be evaluated, meaning that sophisticated coupling of geomorphic and remote sensing processes can be attempted, in order to test for feedbacks between geomorphic processes and topography.
Symmetry Based Two-Dimensional Principal Component Analysis for Face Recognition
Authors: Mingyong Ding, Congde Lu, Yunsong Lin, Ling Tong
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Two-dimensional principal component analysis (2DPCA) proposed recently overcome a limitation of principal component analysis (PCA) which is expensive computational cost. Symmetrical principal component analysis (SPCA) is also a better feature extraction technique because it utilizes effectively the symmetrical property of human face. This paper presents a symmetry based two-dimensional principal component analysis (S2DPCA), which combines the advantages of 2DPCA and of the SPCA. The experimental results show that S2DPCA is competitive with or superior to 2DPCA and SPCA.
An accurate and extensible mobile IPv6 (xMIPV6) simulation model for OMNeT++
Authors: Faqir Zarrar Yousaf, Christian Bauer, Christian Wietfeld
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

MIPv6 is the IPv6 based mobility management protocol and it is expected to become the mobility management protocol of choice for the Next Generation Wireless Access Networks. In order to develop the understanding of the protocol's behavior, its suitability for deploying in a wireless environment and in order to be able to propose and develop appropriate improvements and optimizations, it is imperative to have an accurate, reliable and scalable simulation model for the MIPv6 protocol which is fully compliant to the IETF standards and specifications. This paper presents the logic, design and performance results of an extensible MIPv6 (xMIPv6) simulation model integrated into the INET20061020 framework for the OMNeT++ discrete event simulator.
A Real-Time Performance-Monitoring Tool for Emergency Networks
Authors: Shuprabha Shakya, Mohamad Abdul Awal, Dwijendra K. Das, Yasuo Tsuchimoto, Kanchana Kanchanasut
Venue: Proceedings of the 3rd Asian conference on Internet Engineering: Sustainable Internet (2007)

Emergency networks normally operate under highly unpredictable wireless environment and hence real time performance information holds a great significance that cannot be reflected by the conventional post evaluation approach. In this paper, we propose a performance monitoring tool to display the network performance in real-time for mobile ad hoc network using OLSR protocol, deployed under emergency conditions. Moreover, simplified GUI with real time visualization, network performance summarization along with run time triggering of sudden change in the network has been introduced to provide user with easier, user-friendly and comprehensible perception on the run time network performance.
An Approach to Technological Process Control Systems Based on Model with Technological Coalitions
Authors: Alexander A. Ambartsumian, Dmitry L. Kazansky
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

This paper overviews a new method of control of structures technological processes for industries with flow topology. The given method assumes the using a new discrete model of flow manufacturing as launching and shutting down some Technological Coalitions (TC). This model allows to generate every time as needed an adequate algorithm for structural maneuvering (SM-algorithm).
Noisy defenses: subverting malware's OODA loop
Authors: Daniel Bilar
Venue: Proceedings of the 4th annual workshop on Cyber security and information intelligence research: developing strategies to meet the cyber security and information intelligence challenges ahead (2008)

The question is how to deal in practice with complex evolved malicious software (malware). In light of recent empirical and theoretical findings, we propose moving beyond techniques premised on Turing Machine models towards iterative games and black-box process modeling within an interactive computational framework.
An Effective License-Plate Detection Method for Overexposure and Complex Vehicle Images
Authors: Hsiao-Yun Tseng, Ching-Hao Lai, Shyr-Shen Yu
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

License plate detection plays an important role in license plate recognition (LPR) system. If license plate can be detected exactly, the character segmentation and recognition can be implemented more precisely and efficiently. In our observation, the illumination affects the result of detecting the license plate. The aim of this paper is to extract more than one license plate from an image and to obtain the license plates in the image which is taken under different conditions. The proposed method includes six processes as follows: transferring color to grayscale, image equalization, edge detection, checking black pixel ratio, plate verification and output license plates. The experimental results show that the proposed method can gain 94% accuracy in GetRatio and 83% accuracy in GetRight.
CIDOC CRM in Action --- Experiences and Challenges
Authors: Philipp Nussbaumer, Bernhard Haslhofer
Venue: Proceedings of the 11th European conference on Research and Advanced Technology for Digital Libraries (2007)

Integration of metadata from heterogeneous sources is a major issue when connecting cultural institutions to digital library networks. Uniform access to metadata is impeded by the structural and semantic heterogeneities of the metadata and metadata schemes used in the source systems. In this paper we discuss the methodologies we applied to ingest proprietary metadata into the BRICKS digital library network and to process CIDOC CRM metadata in terms of search and retrieval, and how we strove to hide the semantic complexity from the end-user while exploiting the semantic richness of the underlying metadata.
Continuous Clustering of Moving Objects
Authors: Christian S. Jensen, Dan Lin, Beng Chin Ooi
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

This paper considers the problem of efficiently maintaining a clustering of a dynamic set of data points that move continuously in two-dimensional Euclidean space. This problem has received little attention and introduces new challenges to clustering. The paper proposes a new scheme that is capable of incrementally clustering moving objects. This proposal employs a notion of object dissimilarity that considers object movement across a period of time, and it employs clustering features that can be maintained efficiently in incremental fashion. In the proposed scheme, a quality measure for incremental clusters is used for identifying clusters that are not compact enough after certain insertions and deletions. An extensive experimental study shows that the new scheme performs significantly faster than traditional ones that frequently rebuild clusters. The study also shows that the new scheme is effective in preserving the quality of moving-object clusters.
A Physically Realistic Voxel-Based Method for Haptic Simulation of Bone Machining
Authors: Majid Moghaddam, Ali Nahvi, Mohamadreza Arbabtafti, Mohsen Mahvash
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

This paper models force of machining a piece of bone by a spherical rotating tool for haptic simulation of bone surgery. The cutting edges of the spherical tool are modeled as a set of infinitesimal cutting elements. Each cutting element in contact with the bone piece undergoes an orthogonal cutting process. The force of cutting is obtained by summing up the forces of each element of the engaged cutting element. The force of each cutting element is related to the size of the chip formed at the bone piece due to a fracture process. The coefficients that relate the chip thickness to the cutting forces are derived from the experimental results. A voxel-based method is developed to simulate chip formation and the force of bone machining. The simulation results show a close force correlation between the voxel-based method and an analytical force model at certain loading conditions. This voxel-based method offers a physics-based continuous force model for bone machining.