ppxscal/embedding_network huggingface dataset:
Computations of endohedral fullerenes: The Gibbs energy treatment
Authors: Zdeněk Slanina, Filip Uhlík, Shyi-Long Lee, Ludwik Adamowicz, Shigeru Nagase
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

The paper reports computations on endohedral fullerene systems, combining the treatments of quantum chemistry and statistical mechanics. Relative concentrations of five isomers of Ca@C$_{72}$ are presented as an illustration, using the Gibbs energy based on density-functional theory computations. Anharmonicity effects are probed on a simple model system of C$_{6}$. The temperature-pressure stabilization of metallofullerenes is visualized on Li@C$_{60}$.
Bandwidth intensive 3-D FFT kernel for GPUs using CUDA
Authors: Akira Nukada, Yasuhiko Ogata, Toshio Endo, Satoshi Matsuoka
Venue: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008)

Most GPU performance "hypes" have focused around tightly-coupled applications with small memory bandwidth requirements e.g., N-body, but GPUs are also commodity vector machines sporting substantial memory bandwidth; however, effective programming methodologies thereof have been poorly studied. Our new 3-D FFT kernel, written in NVIDIA CUDA, achieves nearly 80 GFLOPS on a top-end GPU, being more than three times faster than any existing FFT implementations on GPUs including CUFFT. Careful programming techniques are employed to fully exploit modern GPU hardware characteristics while overcoming their limitations, including on-chip shared memory utilization, optimizing the number of threads and registers through appropriate localization, and avoiding low-speed stride memory accesses. Our kernel applied to real applications achieves orders of magnitude boost in power&cost vs. performance metrics. The off-card bandwidth limitation is still an issue, which could be alleviated somewhat with application kernels confinement within the card, while ideal solution being facilitation of faster GPU interfaces.
A magnetically coupled low-cost high-speed shaft position digitizer
Authors: Arthur J. Winter
Venue: Proceedings of the February 4-6, 1953, western computer conference (1953)

The outputs of many precision devices occur as shaft rotations. When the position of such a shaft must be determined to an accuracy beyond the reach of analog instruments, or when the data has to be processed by digital equipment, an analog to digital conversion must be made. It is nearly always desirable and often essential that the digitizer present no appreciable mechanical load to the shaft under measurement. A further requirement which often must be met is that readings be taken on the fly. That is, positional information may be called for when the shaft is in motion at speeds that may vary from zero to many hundreds of rpm. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A New Self-managing Hardware Design Approach for FPGA-Based Reconfigurable Systems
Authors: S. Jovanović, C. Tanougast, S. Weber
Venue: Proceedings of the 4th international workshop on Reconfigurable Computing: Architectures, Tools and Applications (2008)

Given the scale and complexity of today's systems, it is of increasing importance that they handle and manage system's problems on their own in an intelligent and autonomous way. To cope with all non-deterministic changes and events that dynamically occur in a system's environment, a new "self-managing based" design approaches must be developed. Within this framework, an architectural network-based approach can be a good solution for the high demanding computation and self-managing needs. In this paper, we present the basic concept of such a design approach, its main properties and uses. A case study that proves the feasibility of this approach is demonstrated and validated on a small image-processing application.
Low Latency Vertical Handover Using MIH L2-Trigger Algorithm in Mobile IP Networks
Authors: Jin-Man Kim, Jong-Wook Jang
Venue: Proceedings of the 5th international symposium on Parallel and Distributed Processing and Applications (2007)

Recently, information communication market is reorganized focused on the digital convergence service used for integrating the communication, broadcasting and internet media by connecting the communication equipment, broadcasting equipment and computer via a network. The mobility support protocol enabling the effective handover between heterogeneous networks is emerged as the hot issue in relation with these next generation communication networks. In this paper, we are to suggest the MIH Vertical handover procedure required for the implementation of MIH over MIPv4 Low-Latency vertical handover by analyzing the handover performance in the overlap area between wireless networks using the vertical handover function of MIPv4 Mobile IP Technology of IETF and considering the expected problems. Also, we are to suggest the MIH L2-Trigger generation algorithm required for deciding the optimal handoff. We evaluate the vertical handover performance of MIPv4 low-latency in the overlap area between wireless networks by using the NS-2 and applying the IEEE 802.21 MIH (Media Independent Handover) based on the suggested technique and algorithm.
Predicting Software Metrics at Design Time
Authors: Wolfgang Holz, Rahul Premraj, Thomas Zimmermann, Andreas Zeller
Venue: Proceedings of the 9th international conference on Product-Focused Software Process Improvement (2008)

How do problem domains impact software features? We mine software code bases to relate problem domains (characterized by imports) to code features such as complexity, size, or quality. The resulting predictors take the specific imports of a component and predict its size, complexity, and quality metrics. In an experiment involving 89 plug-ins of the ECLIPSE project, we found good prediction accuracy for most metrics. Since the predictors rely only on import relationships, and since these are available at design time, our approach allows for early estimation of crucial software metrics.
Evolutionary Market Agents for Resource Allocation in Decentralised Systems
Authors: Peter R. Lewis, Paul Marrow, Xin Yao
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

We introduce self-interested evolutionary market agents, which act on behalf of service providers in a large decentralised system, to adaptively price their resources over time. Our agents competitively co-evolve in the live market, driving it towards the Bertrand equilibrium, the non-cooperative Nash equilibrium, at which all sellers charge their reserve price and share the market equally. We demonstrate that this outcome results in even load-balancing between the service providers.Our contribution in this paper is twofold; the use of on-line competitive co-evolution of self-interested service providers to drive a decentralised market towards equilibrium, and a demonstration that load-balancing behaviour emerges under the assumptions we describe.Unlike previous studies on this topic, all our agents are entirely self-interested; no cooperation is assumed. This makes our problem a non-trivial and more realistic one.
Weighted MDS for Sensor Localization
Authors: Duc Vo, Nhat Vo, Subhash Challa
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

Multidimensional Scaling (MDS) has been recently applied to node localization in sensor networks and gained some very impressive performance. MDS treats dissimilarities of pair-wise nodes directly as Euclidean distances and then makes use of the spectral decomposition of a doubly centered matrix of dissimilarities. However dissimilarities mainly estimated by Received Signal Strength (RSS) or by the Time of Arrival (TOA) of communication signal from the sender to the receiver used to suffer much errors when the distances between nodes are far. From this observation, Weighted Multidimensional Scaling (WMDS) is proposed in this paper. Different from MDS, WMDS incorporates weighting factors to account for the impact of pair-wise estimated dissimilarities in MDS framework. The further distance between two nodes is, the less "impact" weight should be considered. The experiment on real sensor network measurements of RSS and TOA shows the efficiency and novelty of WMDS for sensor localization problem in term of sensor location-estimated error.
Business Process Modeling for Organizational Knowledge Management
Authors: Luca Abeti, Paolo Ciancarini, Rocco Moretti
Venue: Concurrency, Graphs and Models: Essays Dedicated to Ugo Montanari on the Occasion of His 65th Birthday (2008)

The growing complexity of a networked and information-dependent economy requires the innovation of the adopted processes together with their related services. In particular, many Small and Medium-sized Enterprises (SME's) currently base their organizational models in a resource-centric view rather than in a knowledge-based organizational model which is a fundamental bound to their innovation capabilities. This paper presents a framework for organizational knowledge management. Our approach is based on Business Process Modeling (BPM), that is the main modeling practice connecting the management and engineering disciplines in software development. The aim is to present how the software requirements analysis can help in formalizing and sharing the knowledge concerning the business processes. Besides, we show how the service and ontology abstractions can be useful for software development.
Consistent Query Answering: The First Ten Years
Authors: Jan Chomicki
Venue: Proceedings of the 2nd international conference on Scalable Uncertainty Management (2008)

Usually, the data in a database instance is supposed to be consistent and satisfy the database integrity constraints. However, it is quite common for the two to diverge. The data may fail to satisfy the constraints for various reasons: it may be erroneous, out of date, or come from mutually inconsistent sources.
Joint Detection of the Carotid Boundaries in Longitudinal B-Mode Images
Authors: Rui Rocha, Aurélio Campilho, Jorge Silva
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

This paper proposes a new approach for the automatic segmentation of the carotid adventitia in longitudinal B-scans, with and without the presence of plaque. The top and bottom adventitia contours are jointly detected with a 3D dynamic programing scheme that searches for the best pair of boundaries according to a specified fuzzy cost function. Some discriminating features of the adventitia in B-mode images are used to reduce the attraction by other edges. The final contours are filtered with a smoothing spline fitting.The proposed approach was quantitatively evaluated in a set of 38 images. In order to avoid high correlation of the results, a maximum of two images was selected from each patient. The carotid boundaries manually traced by a medical expert were used as the ground truth. Several statistics show that the proposed algorithm gives good results in most of the cases, including many poor quality images. Examples of the detected contours are presented and compared with the ground truth.
A comparative experimental study of parallel file systems for large-scale data processing
Authors: Zoe Sebepou, Kostas Magoutis, Manolis Marazakis, Angelos Bilas
Venue: First USENIX Workshop on Large-Scale Computing (2008)

Large-scale scientific and business applications require data processing of ever-increasing amounts of data, fueling a demand for scalable parallel file systems comprising hundreds to thousands of disks. Modern parallel file system architectures however, span a large and complex design space. As a result, IT architects are faced with a challenge when deciding on the most appropriate parallel file system for a specific scientific or industrial application in a large-scale computing installation. Typically, the right choice depends on the characteristics of the application as well as the design assumptions built into a parallel file system. In this study, we take a close look at two prominent modern parallel file systems, PVFS2 and Lustre, and compare them experimentally on a range of benchmark-driven scenarios modeling specific real-world applications.
A Density-Based Data Reduction Algorithm for Robust Estimators
Authors: L. Ferraz, R. Felip, B. Martínez, X. Binefa
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

In this paper we present a non parametric density-based data reduction technique designed to be used in robust parameter estimation problems. Existing approaches are focused on reducing the amount of data preserving the density function. In our case the reduction is oriented to automatically remove the samples that are considered non interesting while taking into account those that are meaningful, those that have a high density associated. We use this filtering process to simplify the data sets in order to improve the performance of robust parameter estimators. We show its results when used along an existing estimator on synthetic and real LADAR data.
Educators' Symposium
Authors: Miroslaw Staron
Venue: Models in Software Engineering: Workshops and Symposia at MoDELS 2007, Nashville, TN, USA, September 30 - October 5, 2007, Reports and Revised Selected Papers (2008)

Models are an integral part of every engineering discipline, as they become in software engineering. Modeling can be done in many ways and with different levels of formality. Teaching modeling is as important as the modeling itself since it educates the future engineers in good modeling practices. Without proper education in modeling software engineering cannot evolve into mature engineering discipline. This year's symposium was devoted to invited talks by practitioners and researchers who teach modeling and cooperate with industry. This document summarizes the symposium and the main discussion points. It also outlines the main future research directions in education in modeling.
An entropy-based measurement framework for component-based hierarchical systems
Authors: Murat M. Tanik
Venue:  (2007)

Component-Based software systems are becoming larger and more complex. The quantification of these systems is possible through representation in a hierarchical structure with the use of software metrics. Metrics provide information about such features as complexity, design, quality, size, development time, effort, and cost. Entropy-based software metrics promise important improvements in measuring complexity, design quality, and information flow. The entropy-based measurement framework, the core of this dissertation, offers quantitative representation and decomposition processes to apply the entropy-based metrics that we developed: Design Information Content, Interaction Complexity, Interaction Coupling, and Interaction Cohesion. The objective is to achieve a hierarchical representation of the system in which we can see the logic flow and quantify the interaction among the components. The framework is useful to both the designer and the user in the design and maintenance phases to detect structural complexity issues and comprehend the interaction of the software modules. Another motivation of this work is to lead the way to the development of measurement software which uses entropy-based methods. The representation-decomposition methods are based on graph theory, mainly cubic control flowgraphs, and the computation methods are based on information theory, mainly entropy; thus, the entropy-based measurement framework has a solid foundation to become an analytical measurement framework for Component-Based systems.
Equilibrium Points and Stability Analysis of a Class of Neural Networks
Authors: Xiaoping Xue
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

This paper discusses a mathematical model of network, which is more general than the cellular neural networks(CNNs). In this study, we discuss some dynamical properties of this type of network, such as the distribution of equilibrium points and the influence of external input on stability. Moreover, we give some criterions, which ensure the complete stability of this network.
An Algorithm to Determine the Chromaticity Under Non-uniform Illuminant
Authors: Sivalogeswaran Ratnasingam, Steve Collins
Venue: Proceedings of the 3rd international conference on Image and Signal Processing (2008)

Colour based object recognition is a difficult problem because of the effect of scene illuminant and geometry on the captured image. In this paper the ability of an algorithm proposed by Finlayson and Drew [1] to separate similar colours is assessed. A new variant of this algorithm is then proposed that results in a slight improvement in performance. A significant performance improvement is achieved by optimising the characteristics of the sensors that are used to acquire the data for this algorithm. This optimisation process results in several combinations of sensors and associated data projections that have a comparable performance when required to distinguish between similar colours. Since this performance is comparable to that of the human visual system it is suggested that with the correct sensors this algorithm is capable of obtaining useful chromaticity information under varying illumination conditions.
Real-Time Data Services for Cyber Physical Systems
Authors: Kyoung-Don Kang, Sang H. Son
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

Cyber Physical Systems (CPSs) have grand visions with great socio-economic impacts such as blackout-free electricity supply and real-time disaster recovery. A key challenge is providing real-time data services for CPSs. Existing real-time data management techniques and wireless sensor networks (WSNs) fall far short to support timely, secure real-time data services for CPSs. In this paper, we present a novel information-centric approach to supporting these requirements in CPSs. In our approach, network-enabled real-time embedded databases (nRTEDBs) communicate with each other and control and communicate with wireless sensors in a secure, timely manner. Unlike sensor databases such as TinyDB, nRTEDBs collaboratively derive global knowledge of real world phenomena. Based on the collective information, they actively control a WSN to extract important data directly relevant to an event of interest. In this way, nRTEDBs considerably enhance the overall timeliness, security, and efficiency.
Multiplayer role games applied to problem based learning
Authors: Pilar Sancho, Pedro Pablo Gómez-Martín, Baltasar Fernández-Manjón
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

The educational community is willing to approach the learning applications to the engaging and immersive formats of multimedia and video games as a way of increasing the motivation of the so called "digital natives" [19]. During this decade the interest for videogames as a way of combining learning with fun has grown exponentially. But despite the best intentions of teachers and technologists, the efforts to integrate games into the curriculum have often fallen flat. Most students see learning through videogames as "chocolate covered broccoli" [1] while many teachers consider games as a waste of time. In this paper we propose an approach, the NUCLEO framework, that is getting good results in several testing implementations for the Spanish higher education context, turning a whole problem based learning scenario into a role game. The conceptual framework and the system presented here are aimed at getting effective learning in a motivating environment that seeks a student's change of attitude towards learning. It is intended to be used within the context of a LMS (Learning Management System), complementing its features with new interfaces and modes of content interaction.
A New Approach to Memory Partitioning in On-Board Spacecraft Software
Authors: Santiago Urueña, José A. Pulido, Jorge López, Juan Zamorano, Juan A. Puente
Venue: Proceedings of the 13th Ada-Europe international conference on Reliable Software Technologies (2008)

The current trend to use partitioned architectures in on-board spacecraft software requires applications running on the same computer platform to be isolated from each other both in the temporal and memory domains. Memory isolation techniques currently used in Integrated Modular Avionics for Aeronautics usually require a Memory Management Unit (MMU), which is not commonly available in the kind of processors currently used in the Space domain. Two alternative approaches are discussed in the paper, based on some features of Ada and state-of-the art compilation tool-chains. Both approaches provide safe memory partitioning with less overhead than current IMA techniques. Some footprint and performance metrics taken on a prototype implementation of the most flexible approach are included.
An Intrusion Plan Recognition Algorithm Based on Max-1-Connected Causal Networks
Authors: Zhuo Ning, Jian Gong
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

Intrusion plan prediction and recognition is a critical and challenging task for NIDS. Among several approaches proposed so far, probability inference using causal network seems to be one of the most promising mechanisms. Our analysis shows that the polytree is limited in its expressiveness, and belief updating in max-k-connected networks is hard for all k ¿2 [12]. To find a tradeoff between expressive power and inference efficiency, this paper extends the structure of causal network from polytree to max-1-connected Bayesian network, and proposes a new intrusion plan prediction algorithm IPR on it. We evaluate the approach using LLOS1.0, and the results demonstrate that IPR can predict the occurrence probability of DDOS when Sandmind attack occurs to gain root privilege, and then confirm the prediction in the beginning of Syn flooding.
Document Clustering Based on Spectral Clustering and Non-negative Matrix Factorization
Authors: Lei Bao, Sheng Tang, Jintao Li, Yongdong Zhang, Wei-Ping Ye
Venue: Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence (2008)

In this paper, we propose a novel non-negative matrix factorization (NMF) to the affinity matrix for document clustering, which enforces non-negativity and orthogonality constraints simultaneously. With the help of orthogonality constraints, this NMF provides a solution to spectral clustering, which inherits the advantages of spectral clustering and presents a much more reasonable clustering interpretation than the previous NMF-based clustering methods. Furthermore, with the help of non-negativity constraints, the proposed method is also superior to traditional eigenvector-based spectral clustering, as it can inherit the benefits of NMF-based methods that the non-negative solution is institutive, from which the final clusters could be directly derived. As a result, the proposed method combines the advantages of spectral clustering and the NMF-based methods together, and hence outperforms both of them, which is demonstrated by experimental results on TDT2 and Reuters-21578 corpus.