ppxscal/embedding_network huggingface dataset:
Software orchestration of instruction level parallelism on tiled processor architectures
Authors: Anant Agarwal, Saman Amarasinghe
Venue:  (2005)

Projection from silicon technology is that while transistor budget will continue to blossom according to Moore's law, latency from global wires will severely limit the ability to scale centralized structures at high frequencies. A tiled processor architecture (TPA) eliminates long wires from its design by distributing its resources over a pipelined interconnect. By exposing the spatial distribution of these resources to the compiler, a TPA allows the compiler to optimize for locality, thus minimizing the distance that data needs to travel to reach the consuming computation. This thesis examines the compiler problem of exploiting instruction level parallelism (ILP) on a TPA. It describes Rawcc, an ILP compiler for Raw, a fully distributed TPA. The thesis examines the implication of the resource distribution on the exploitation of ILP for each of the following resources: instructions, registers, control, data memory, and wires. It designs novel solutions for each one, and it describes the solutions within the integrated framework of a working compiler. Performance is evaluated on a cycle-accurate Raw simulator as well as on a 16-tile Raw chip. Results show that Rawcc can attain modest speedups for fine-grained applications, as well speedups that scale up to 64 tiles for applications with such parallelism. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Empirical findings on persuasiveness of recommender systems for customer decision support in electronic commerce
Authors: Jung P. Shim
Venue:  (2005)

More and more companies are making online presence by opening online stores and providing customers with company and products information but the overwhelming amount of information also creates information overload for the customers. Customers feel frustrated when given too many choices while companies face the problem of turning browsers into actual buyers. Online recommender systems have been adopted to facilitate customer product search and provide personalized recommendation in the market place. The study will compare the persuasiveness of different online recommender systems and the factors influencing customer preferences. Review of the literature does show that online recommender systems provide customers with more choices, less effort, and better accuracy. Recommender systems using different technologies have been compared for their accuracy and effectiveness. Studies have also compared online recommender systems with human recommendations and recommendations from expert systems. The focus of the comparison in this study is on the recommender systems using different methods to solicit product preference and develop recommendation message. Different from the technology adoption and acceptance models, the persuasive theory used in the study is a new perspective to look at the end user issues in information systems. This study will also evaluate the impact of product complexity and product involvement on recommendation persuasiveness. The goal of the research is to explore whether there are differences in the persuasiveness of recommendation given by different recommender systems as well as the underlying reasons for the differences. Results of this research may help online store designers and ecommerce participants in selecting online recommender systems so as to improve their products target and advertisement efficiency and effectiveness.
A New Process Neural Network Algorithm of Soft Sensor for Time-Varying System
Authors: Zaiwen LIU, Xiaoyi WANG, Xiaoqin LIAN, Zhengxiang WANG, Chaozhen HOU
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

A new algorithm of data processing and a method of soft sensor based on process neural network (PNN) for time-varying system are represented in the paper. Process neural network is an extension of traditional neural network, in which the inputs and outputs are time-variation. An aggregation operator is introduced to process neuron, and it makes the neuron network has the ability to deal with the information of space-time two dimensions at the same time, so the data processing enginery of biological neuron is imitated better than traditional neuron. Through analyzing the reasons of low-speed constringency of the network, two improvements on the foundation of original algorithm were put forward, and an improved algorithm for BP network and algorithm research based on function orthogonal basis expansion in process neural network for soft sensor were discussed. A good training result of soft sensor was obtained by simulation in. sewage disposal system.
Efficient interference-aware TDMA link scheduling for static wireless networks
Authors: Weizhao Wang, Yu Wang, Xiang-Yang Li, Wen-Zhan Song, Ophir Frieder
Venue: Proceedings of the 12th annual international conference on Mobile computing and networking (2006)

We study efficient link scheduling for a multihop wireless network to maximize its throughput. Efficient link scheduling can greatly reduce the interference effect of close-by transmissions. Unlike the previous studies that often assume a unit disk graph model, we assume that different terminals could have different transmission ranges and different interference ranges. In our model, it is also possible that a communication link may not exist due to barriers or is not used by a predetermined routing protocol, while the transmission of a node always result interference to all non-intended receivers within its interference range. Using a mathematical formulation, we develop synchronized TDMA link schedulings that optimize the networking throughput. Specifically, by assuming known link capacities and link traffic loads, we study link scheduling under the RTS/CTS interference model and the protocol interference model with fixed transmission power. For both models, we present both efficient centralized and distributed algorithms that use time slots within a constant factor of the optimum. We also present efficient distributed algorithms whose performances are still comparable with optimum, but with much less communications. Our theoretical results are corroborated by extensive simulation studies.
Ontology-Based QoS Driven GIS Grid Service Discovery
Authors: Wen-jun Li, Shu-neng Zhao, Heng Sun, Xiao-bin Zhang
Venue: Proceedings of the Second International Conference on Semantics, Knowledge, and Grid (2006)

A semantic based approach for QoS driven service discovery is proposed to help clients select the currently best services matching their requests in a dynamic GGS (GIS Grid Services) Virtual Organization. Services are selected according to the functional requirements and dynamic Qualities of Services (QoS) requirements. This framework utilizes ontology to define the terminologies on GGS functions and dynamic QoS semantics. A Semantic Registry Service is designed, which accepts service registration with semantics and updates the QoS metadata dynamically. Furthermore, the discovery process is based on ontology reasoning and can choose better service fulfill the QoS request. We have built the prototype system with the Globus Toolkit 4(GT4).
Decisioneering, Inc.: Crystal Ball
Authors: Lucie Trepanier
Venue: Proceedings of the 37th conference on Winter simulation (2005)

This presentation will show how Crystal Ball&reg; Software--a suite of Microsoft&reg; Excelbased applications for Monte Carlo simulation, forecasting, optimization and real options analysis--transforms your spreadsheets into dynamic models. See how the software helps you to understand, communicate and manage the risks associated with uncertainty and variability.
Using Product Line Techniques to Build Adaptive Systems
Authors: Svein Hallsteinsen, Erlend Stav, Arnor Solberg, Jacqueline Floch
Venue: Proceedings of the 10th International on Software Product Line Conference (2006)

Adaptive systems are able to adapt their properties and resource requirements at runtime in response to dynamically varying user needs and resource constraints. With the emergence of mobile and service oriented computing, such variation is becoming increasingly common, and the need for adaptivity is increasing accordingly. Software product line engineering has proved itself as an efficient way to deal with varying user needs and resource constraints. In this paper we present an approach to building adaptive systems based on product line oriented techniques such as variability modeling and component based architectures. By representing the product line architecture at runtime, we are able to delegate much of the complexity of adaptation to a reusable adaptation platform. To validate our approach we have built a prototype adaptation platform and developed a few pilot applications exploiting the platform to achieve adaptivity.
Adaptive Manufacturing: A Real-Time Simulation-Based Control System
Authors: Benoit Saenz de Ugarte, Abdelhakim Artiba, Khalid Jbaida, Robert Pellerin
Venue: Proceedings of the International Conference on Software Engineering Advances (2006)

This paper presenst a real-time execution system to support adaptive manufacturing strategies. We propose a functional architecture integrating optimisation and simulation techniques with Enterprise Resource Planning and Manufacturing Execution Systems. The model allows the implementation of real-time decision-making components and feedback-loop mechanisms. A demonstrative example based on a real life production scenario is presented to illustrate how such integration can be achieved.
Design and evaluation of a collaborative telelearning activity aimed at teacher training
Authors: Barbara Wasson
Venue: Proceedings of the 1999 conference on Computer support for collaborative learning (1999)

This paper describes VisArt, a collaborative telelearning scenario aimed at teacher training. Students at three educational institutions in Norway collaborated at a distance through Team Wave Workplace to design a learning activity for some subject of their choice. At the University of Bergen, VisArt was part of a graduate course assignment where the students had to participate in VisArt and write a report reflecting on their participation from a theoretical perspective. Salomon's ideas on genuine interdependence and Gutwin et al.'s notions of awareness formed the foundation for the student's theoretical reflection. This paper describes the VisArt scenario, the evaluation studies being carried out within the DoCTA project, and summarises the student's own theoretical reflections.
An Undergraduate Success Story: A Computer Science and Electrical Engineering Integrative Experience
Authors: Grant A. Jacoby, Jean R. S. Blair
Venue: IEEE Pervasive Computing (2006)

A client-oriented, team-based approach for teaching system integration to undergraduate students at the United States Military Academy's Department of Electrical Engineering and Computer Science has proved highly effective. The two-semester course gives them their first real research and development experience in a carefully monitored and guided environment that translates theory into product. This experience helps demonstrate how students can become what employers seek and how educational institutions can provide what society needs.
Privacy-preserving performance measurements
Authors: Matthew Roughan, Yin Zhang
Venue: Proceedings of the 2006 SIGCOMM workshop on Mining network data (2006)

Internet performance is an issue of great interest, but it is not trivial to measure. A number of commercial companies try to measure this, as does RIPE, and many individual Internet Service Providers. However, all are hampered in their efforts by a fear of sharing such sensitive information. Customers make decision about "which provider" based on such measurements, and so service providers certainly do not want such data to be public (except in the case of the top provider), but at the same time, it is in everyones' interest to have good metrics in order to reduce the risk of large network problems, and to test the effect of proposed network improvements.This paper shows that it is possible to have your cake, and eat it too. Providers (and other interested parties) can make such measurements, and compute Internet-wide metrics securely in the knowledge that their private data is never shared, and so cannot be abused.
Location-aware multimedia proxy handoff over the IPv6 mobile network environment
Authors: Chung-Ming Huang, Chao-Hsien Lee, Yuan-Tse Yu, Chung-Yi Lai
Venue: Journal of Systems and Software (2006)

In a server-proxy-client 3-tier networking architecture that is executed in the mobile network, proxies should be dynamically assigned to serve mobile hosts according to geographical dependency and the network situation. The goal of proxy handoff is to allow a mobile host still can receive packets from the corresponding server while its serving proxy is switched from the current one to another one. Once proxy handoff occurs, a proper proxy should be selected based on the load balance concern and the network situation concern. In this paper, a 3-tier Multimedia Mobile Transmission Platform, called MMTP, is proposed to solve the proxy handoff problem in the IPv6-based mobile network. A proxy handoff scheme based on the application-layer anycasting technique is proposed in MMTP. A proper proxy is selected from a number of candidate proxies by using the application-layer anycast. An experimental environment based on MMTP is also built to analyze the performance metrics of MMTP, including load balance among proxies and handoff latency.
Mesoscopic Continuous and Discrete Channels for Quantum Information Transfer
Authors: Ferdinando Pasquale, Gian Luca Giorgi, Simone Paganelli
Venue: Open Systems Information Dynamics (2006)

We study the possibility of realizing perfect quantum state transfer in mesoscopic devices. We discuss the case of the Fano-Anderson model extended to two impurities in a single excitation regime. For a channel with an infinite number of degrees of freedom, we obtain coherent behaviour in the case of strong coupling or in weak coupling off-resonance. For a finite number of degrees of freedom, coherent behaviour is associated to weak coupling and resonance conditions.
A flexible multiport content-addressable memory
Authors: Takeshi Kumaki, Keisuke Iwai, Takakazu Kurokawa
Venue: Systems and Computers in Japan (2006)

This paper is concerned with content-addressable memory (CAM), which is a kind of functional memory. Flexible multiport content-addressable memory (FMCAM) is proposed, in which flexible retrieval functions and a multiport structure are realized. The implementation and an evaluation are presented. It is known that CAM offers high speed of the matching retrieval function. On the other hand, there are problems in practice concerning the relation between the processing speed and the number of comparators, and also the problem of cost, which have prevented its widespread use. Consequently, we developed the following FMCAM. Multiport CAM is realized by reducing the increase of the number of comparators while retaining high-speed matching retrieval functions. Functions for flexible retrieval can be added by implementation in an FPGA. By the categorization process and the use of a ring counter, multiple processing operations can be performed immediately while reducing the number of comparators. This improves the performance of the CAM itself. Another advantage is that FMCAM alone can perform the same processing in situations in which parallel CAM should be applied. After implementing the proposed FMCAM, several tests were performed for comparison. Excellent values were obtained: the AT product was 37.5&percnt; lower on average than in conventional CAM, and the increase in hardware complexity was by a factor of 1.57 even if the number of ports was increased by a factor of 4. &copy; 2006 Wiley Periodicals, Inc. Syst Comp Jpn, 37(11): 57&ndash;67, 2006; Published online in Wiley InterScience (). DOI 10.1002&sol;scj.20148
Comparing Belief Propagation and Graph Cuts for Novelty Detection
Authors: Shyjan Mahamud
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

Novelty detection or background subtraction methods for surveillance with a fixed camera typically model each pixel independently of its neighbours. More recently [11], a Markov Random Field (MRF) prior has been used to model consistencies among neighbouring foreground/background labels. Graph Cut methods have been used to find the maximum of the resulting posterior distribution for the labels for each frame. However, for increased efficiency and accuracy, we propose the use of loopy belief propagation. A major reason for increased efficiency is the fact that the output labels from the previous frame can be used as initialisation for the current frame in belief propagation. The Graph Cuts approach is empirically compared with both the "sumproduct" as well as "max-product" rules of belief propagation on real video sequences. Significantly, while the "max-product" rule has similar peak precision-recall performance as graph-cuts, the "sum-product" rule gives even better peak performance. This can be attributed to the fact that latter rule finds the marginals over the entire posterior distribution for the labels rather than just the maximum of the posterior which is more prone to noise.
Spread Spectrum Audio Steganography Using Sub-band Phase Shifting
Authors: Hosei Matsuoka
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

This paper presents an improvement of spread spectrum audio data hiding methods. We introduce phase shifting in audio signals to reduce the correlation with PN signal per each sub-band. It allows easy detection of the embedded data signal from audio when de-spreading the compound signal. The paper reports the subjective test results and the measurements of noise resiliency. The proposed method generates the quality degradation at the same level of NMR +3dB, but accests +6dB noise, therefore, the method has 3dB benefits.
An Approach to Support Vector Regression with Genetic Algorithms
Authors: Oscar Herrera, Angel Kuri
Venue: Proceedings of the Fifth Mexican International Conference on Artificial Intelligence (2006)

Support Vector Machines (SVM) are learning methods useful for solving supervised learning problems such as classification (SVC) and regression (SVR). SVM's are based on the Statistical Learning Theory and the minimization of the Structural Risk [1], an enhancement over neural networks such as Multi-Layer Perceptrons. However, the major drawback is the high computational cost of the constrained Quadratic Problem (QP) combined with the selection of the kernel parameters they involve. Here we discuss \varepsilon -SVRVGA, a detailed implementation of SVR that uses the non-traditional Vasconcelos Genetic Algorithm (VGA) [2] as tool for solving the associated QP along with the tuning of the kernel parameters. This work does not explore the automatic tuning of the regularization parameter C associated to the VC dimension [1] of the SVM what is considered an open research area. The \varepsilon -SVRVGA fitting capability was tested with onedimensional Time Series (TS) data by reconstructing their n-dimensional state space [3] and adding Gaussian noise. Results show that \varepsilon -SVRGVA is able to model successfully the TS in spite of a noisy environment as well as the self-selection of kernel parameters.
Integrating Stateful Services in Workflow
Authors: Zakir Laliwala, Vikram Sorathia, Sanjay Chaudhary, Prateek Jain
Venue: Proceedings of the XIII Asia Pacific Software Engineering Conference (2006)

Long running business processes require composition of services for task accomplishment. BPEL provide a mechanism to model business workflow among collaborating Web Services distributed across organizations. For effective execution and consistent outcomes from such composite services in a loosely coupled environment, management of state, transaction, notification and execution monitoring are the key requirements. After the emergence of WS-RF, stateful Web services have become integral part of Grid environment. Grid supports execution monitoring, resource sharing, integration and management of large-scale applications. Such capabilities are the backbone for any large-scale enterprise applications. Process oriented workflow execution in a grid environment with the support to manage state, transaction and notification is a challenging issue. In this paper we have proposed architecture to achieve integration of stateful services for a grid workflow. Development of stateful services is based on WS-RF specification to build services to support state management, transaction, notification and execution monitoring of a business process in a large-scale grid environment.
A Component Model and Infrastructure for a Fluid Web
Authors: Andre Santanche Claudia Bauzer Medeiros
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

The Web is evolving from a space for publication/consumption of documents to an environment for collaborative work, where digital content can travel and be replicated, adapted, decomposed, fusioned, and transformed. We call this the Fluid Web perspective. This view requires a thorough revision of the typical document-oriented approach that permeates content management on the Web. This paper presents our solution for the Fluid Web, which allows moving from the document-oriented to a content-oriented perspective, where "content” can be any digital object. The solution is based on two axes: a self-descriptive unit to encapsulate any kind of content artifact—the Digital Content Component (DCC) and a Fluid Web infrastructure that provides management and deployment of DCCs through the Web, and whose goal is to support collaboration on the Web. Designed to be reused and adapted, DCCs encapsulate data and software using a single structure, thus allowing homogeneous composition and processing of any digital content, executable or not. These properties are exploited by our Fluid Web infrastructure, which supports DCC multilevel annotation and discovery mechanisms, configuration management, and version control. Our work extensively explores taxonomic ontologies and Semantic Web standards, which serve as a semantic bridge, unifying DCC management vocabularies, and improving DCC description/indexing/discovery. DCCs and infrastructure have been implemented and are illustrated by means of a running example, for a scientific application.
Emotion Recognition Using Physiological Signals from Multiple Subjects
Authors: Lan Li, Ji-hua Chen
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

The ability to recognize emotion is one of the hallmarks of emotional intelligence. This paper proposed to recognize emotion using physiological signals obtained from multiple subjects without much discomfort from the body surface. Four signals, electrocardiogram (ECG), skin temperature (SKT), skin conductance (SC) and respiration were selected to extract features for recognition. We collected a set of data from 60 undergraduates when experiencing the target emotion elicited by film clips. Canonical correlation analysis was used to find the relationship between emotion and extracted features. Using 17 features, 20 features and 22 features, recognition accuracy is 82%, 85.3%, 85.3% respectively.