ppxscal/embedding_network huggingface dataset:
A management scheme for distributed cross-layer reconfigurations in the context of cognitive B3G infrastructures
Authors: G. Dimitrakopoulos, K. Tsagkaris, K. Demestichas, E. Adamopoulou, P. Demestichas
Venue: Computer Communications (2007)

Current research efforts in wireless communications are targeted at the evolution of B3G (Beyond the 3rd Generation) wireless infrastructures. The operation of B3G infrastructures envisions dynamic adaptations to external stimuli, which can be facilitated through the exploitation of cognitive networking potentials. Cognitive networks dispose mechanisms for dynamically selecting their configuration (algorithms and parameter values, at different layers of the protocol stack), through appropriate management functionality that takes into account the context of operation (environment characteristics and requirements), profiles, goals, policies and knowledge that derives from previous experience. This paper focuses on such management functionality and it addresses a problem, dealing with ''Distributed, Cross-Layer Reconfigurations'' (DCLR), which aims at assessing and selecting the most appropriate configuration per network element in a cognitive network. In essence, this work contributes in four main areas. First, a fully distributed formulation and solution to the DCLR problem is provided, which is important for the management of a particular reconfigurable element in a cognitive context. Second, robust learning and adaptation, strategies are proposed, for estimating and gaining knowledge of the performance potentials of alternate reconfigurations. Third, a computationally efficient solution to the problem of exploiting the performance potentials of reconfigurations is provided, in order to rate reconfigurations and finally select the best ones. Finally, results that expose the behaviour and efficiency of the proposed schemes, are presented.
Evaluation of Single Event Upset Mitigation Schemes for SRAM based FPGAs using the FLIPPER Fault Injection Platform
Authors: M. Alderighi, F. Casini, S. D'Angelo, S. Pastore, G. R. Sechi, R. Weigand
Venue: Proceedings of the 22nd IEEE International Symposium on Defect and Fault-Tolerance in VLSI Systems (2007)

SRAM based reprogrammable FPGAs are sensitive to radiation-induced Single Event Upsets (SEU), not only in their user flip-flops and memory, but also in the configuration memory. Appropriate mitigation has to be applied if they are used in space, for example the XTMR scheme implemented by the Xilinx TMRTool and configuration scrubbing. The FLIPPER fault injection platform, described in this paper, allows testing the efficiency of the SEU mitigation scheme. FLIPPER emulates SEU-like faults by doing partial reconfiguration and then applies stimuli derived from HDL simulation (VHDL/Verilog test-bench), while comparing the outputs with the golden pattern, also derived from simulation. FLIPPER has its Device-Under-Test (DUT) FPGA on a mezzanine board, allowing an easy exchange of the DUT device. Results from a test campaign are presented using a design from space application and applying various levels of TMR mitigation.
LET: Towards More Precise Clustering of Search Results
Authors: Yi Zhang, Lidong Bing, Yexin Wang, Yan Zhang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

Web users are always distracted by a large number of results returned from search engines. Clustering can ef- ficiently facilitate users' browsing pages of certain topic. However, most traditional clustering methods are based on either content analysis or link analysis alone, which ap- pears unilateral. In this paper, we propose an expanding clustering idea with the reasonable combination of content and link analysis. Experimental results on Google's three query sets show that our LET algorithm outperforms tradi- tional methods such as K-means.
Mapping Software Design Changes to Source Code Changes
Authors: Xiangchen Tan, Tie Feng, Jiachen Zhang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02 (2007)

The combination of evolutionary development processes and object-oriented methods results in iterative change in software design and source code. In this paper, we propose an approach of mapping object-oriented design changes to program changes, so that the prediction of possible source code change effort can be made. This approach focus on the definition and taxonomy of atomic changes and composite changes at both level, according to which change impact analysis algorithms are proposed and applied to conclude the change mapping rules from UML based design model to Java source code. A supporting tool implementing the heuristics is designed and a case study on an open source project is conducted to validate our method.
Metrics-based Evaluation of Slicing Obfuscations
Authors: Anirban Majumdar, Stephen Drape, Clark Thomborson
Venue: Proceedings of the Third International Symposium on Information Assurance and Security (2007)

An obfuscation aims to transform a program, without affecting its functionality, so that some secret data within the program can be hidden for as long as possible from an adversary armed with reverse engineering tools. Slicing is a reverse engineering technique which produces a subset of a program that is dependent on a particular program point and is used to aid in program comprehension. Thus slicing could be used as a way of attacking obfuscated programs. In this contribution, we highlight a few obfuscating transforms that were proposed in an earlier publication for making attacks difficult to mount using slicers and then illustrate an experimental design to evaluate the strength of these transforms with respect to well defined slicing metrics.
Keynote Speech 2: Consumerization of Electronics and Nanometer Technologies: Implications on Test
Authors: Sanjiv Taneja
Venue: Proceedings of the 16th Asian Test Symposium (2007)

Test has long been recognized as the bridge between Design and Manufacturing. However, innovation and deep integration in design and test tools has not kept pace with the consumerization of electronics and the rapidly evolving nanometer IC design and manufacturing. As a result, the full potential of Test has not been harnessed by the mainstream semiconductor community. The consumerization of electronics places significant new demands on low power, correctness and time-to-volume production. The Test technologies need to innovate at a faster pace to enable system companies and their semiconductor suppliers -- in segments ranging from automotive to entertainment and multi-media to meet these new challenges. The rapid advances in nanometer technologies pose another set of challenges, primarily related to integration. Whereas the integration at the level of interoperability amongst different tools in the design and implementation flows has been adequate in the past, nanometer technology introduces new levels of complexity due to the advanced physics effects and higher scales of transistor integration. This in turn results in complex interaction and interdependence amongst the different design steps such as synthesis, test, floor planning, placement, routing and chip finishing. The EDA industry needs to establish a new paradigm and a "deep integration" to meet these challenges and to deliver the productivity gains that will enable our customers to meet demands on functionality, correctness, quality and time-to-volume production. The paradigm needs to shift from "Design For Test" to "Design With Test". to fully model the tight interdependencies between design and test. During the design phase, DFT steps must integrate well during the design architecture, synthesis, timing and layout steps. Later, during the manufacturing phase, the benefits of DFT must be seamlessly harnessed for rapid scan diagnostics based yield learning using not only logic information from the design database but also using timing and layout information.
Reasoning about Feature Models in Higher-Order Logic
Authors: Mikolas Janota, Joseph Kiniry
Venue: Proceedings of the 11th International Software Product Line Conference (2007)

A mechanically formalized feature modeling metamodel is presented. This theory is a generic higher-order formalization of a mathematical model synthesizing several feature modeling approaches found in the literature. This meta-model supports not only a better understanding of the various approaches to feature modeling, but also supports reasoning about and within feature model approaches, feature models, and on feature trees and their configurations.
Estimation of rotor angles of synchronous machines using artificial neural networks and local PMU-based quantities
Authors: Alberto Del Angel, Pierre Geurts, Damien Ernst, Mevludin Glavic, Louis Wehenkel
Venue: Neurocomputing (2007)

This paper investigates a possibility for estimating rotor angles in the time frame of transient (angle) stability of electric power systems, for use in real-time. The proposed dynamic state estimation technique is based on the use of voltage and current phasors obtained from a phasor measurement unit supposed to be installed on the extra-high voltage side of the substation of a power plant, together with a multilayer perceptron trained off-line from simulations. We demonstrate that an intuitive approach to directly map phasor measurement inputs to the neural network to generator rotor angle does not offer satisfactory results. We found out that a good way to approach the angle estimation problem is to use two neural networks in order to estimate the sin(@d) and cos(@d) of the angle and recover the latter from these values by simple post-processing. Simulation results on a part of the Mexican interconnected system show that the approach could yield satisfactory accuracy for real-time monitoring and control of transient instability.
An Improved Genetic Algorithm on Logistics Delivery in E-business
Authors: Taoshen Li, Jingli Wu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

With the rapid development of e-commerce, logistic industry has also experienced a new reform. Intelligent logistics is an important part of it and plays a key role to realize highly effective logistics. In the process of logistics, there are abundant operational and decision-making problems that need to be solved, and logistic vehicle routing problem is one of which. However, the vehicle routing problem with time windows(VRPTM) is a combination optimization problem and is a NP-complete problem, so we can't get satisfying results when we use exact approaches and normal heuristic ones. In this paper, an improved genetic algorithm based on RC' operator which is an improvement of Route Crossover (RC) is developed to solve the VRPTM. Computational experiments show that this improved algorithm can obtain a general optimality for all evaluated indexes on the premise of satisfying every customer's demand and its performance is superior to the genetic algorithm based on RC or partially mapped crossover(PMX).
Local polynomial estimator for narrowband interference suppression in TH-UWB systems
Authors: Yongdao Zhou, Hong Ma, Huiqi Wang, Wangyong Lv
Venue: Wireless Personal Communications: An International Journal (2007)

Ultra-wideband (UWB) technology has been considered to offer an innovative solution for future short-range high-speed wireless communications. These systems use very low transmission power, spread over a bandwidth of several gigahertz. The very low transmission power and the large bandwidth used, enable UWB radio systems to co-exist with other narrowband systems over the same frequency band without interfering the narrowband systems. Nevertheless, these narrowband systems may cause interference which may jam the UWB receiver completely. Since standard narrowband interference suppression techniques are not applicable, techniques for interference suppression have to be developed. In this paper, the method of the local polynomial estimator in time-hopping impulse radio (TH-IR) for UWB communication is considered, which should not estimate any parameter of channel. And the narrowband interference (NBI) is modeled as a stationary process. Theoretical analysis of this algorithm reveals that it can eliminate the narrowband interference almost completely and can be computed by simple expression. Moreover, the sampling rate is very low.
Changing representations during search: A comparative study of delta coding
Authors: Keith E. Mathias, L. Darrell Whitley
Venue: Evolutionary Computation (1994)

Delta coding is an iterative genetic search strategy that dynamically changes the representation of the search space in an attempt to exploit different problem representations. Delta coding sustains search by reinitializing the population at each iteration of search. This helps to avoid the asymptotic performance typically observed in genetic search as the population becomes more homogeneous. Here, the optimization ability of delta coding is empirically compared against CHC, ESGA, GENITOR, and random mutation hill-climbing (RMHC) on a suite of well-known test functions with and without Gray coding. Issues concerning the effects of Gray coding on these test functions are addressed.
Evaluating public health uses of health information exchange
Authors: Jason S. Shapiro
Venue: Journal of Biomedical Informatics (2007)

Health information exchange (HIE) initiatives are in various stages of development across the United States. They aim to bring previously unavailable clinical data from patients' disparate health records, which may be spread over multiple provider and payer networks, to the point of care where clinicians and their patients need it most. The implications of these initiatives on public health are numerous. This article provides general evaluation methods for measuring the impact of HIE on public health in six use cases: (1) mandated reporting of laboratory diagnoses, (2) mandated reporting of physician-based diagnoses, (3) public health investigation, (4) disease-based non-reportable laboratory data, (5) antibiotic-resistant organism surveillance, and (6) population-level quality monitoring.
A Sampler of Circuit Switching Networks
Authors: G. M. Masson
Venue: Computer (1979)

This overview presents several different types of circuit switching networks: concentrators, connectors, expanders, partitioners, SIMD interconnectors, and sorters.
The Software Development System
Authors: C. G. Davis
Venue: IEEE Transactions on Software Engineering (1977)

This paper contains a discussion of the Software Development System (SDS), a methodology addressing the problems involved in the development of software for ballistic missile defense systems. These are large real-time, automated systems with a requirement for high reliability. The SDS is a broad approach attacking problems arising in requirements generation, software design, coding, and testing. The approach is highly requirements oriented and has resulted in the formulation of structuring concepts, a requirements statement language, process design language, and support software to be used throughout the development cycle. This methodology represents a significant advance in software technology for the development of software for a class of systems such as BMD. The support software has been implemented and is undergoing evaluation.
A Novel Algorithm of Image Enhancement Based on Pulse Coupled Neural Network Time Matrix and Rough Set
Authors: Yide Ma, Dongmei Lin, Beidou Zhang, Chunshui Xia
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

This paper describes a novel algorithm of image enhancement based on Pulse Coupled Neural Network (PCNN) time matrix and Rough Set indiscernibility relation. Firstly, detect image noise using PCNN time matrix, and then partition the original image into three sub-images according to intensity attribute and noise attribute. Secondly, denoise using filtering methods based upon PCNN. Lastly, complete sub-images and enhance each of them by different methods. For the gray images with many object details in dark regions and badly corrupted by impulse noise, the computer simulations show excellent enhancement effect. Namely, noise can be reduced efficiently, object details can be enhanced better and the image would become clear after it is processed by this algorithm. Moreover, the effect of this algorithm is better than that of traditional image enhancement algorithm. Key words: Rough Set theory; Indiscernibility relation; Pulse Coupled Neural Network; Time matrix; Image enhancement
Exploiting Parallelism in Double Path Adders' Structure for Increased Throughput of Floating Point Addition
Authors: Alexandru Amaricai, Mircea Vladupiu, Lucian Prodan, Mihai Udrescu, Oana Boncalo
Venue: Proceedings of the 10th Euromicro Conference on Digital System Design Architectures, Methods and Tools (2007)

This paper proposes a novel approach for increasing the performance of the floating point addition, by efficiently exploiting both paths from the classical double path adder. Thus, it becomes possible to execute two floating point additions simultaneously using a single adder, each on a different path. Performing two floating point additions in this manner will requires duplication of the signs and exponent computation modules. The cost estimates show a 20% increase of the active area for the proposed adder compared with other floating point adders. In terms of performance, the latency of the proposed adder is slightly higher with respect to other double path adders. However, the increased latency is compensated by the increased throughput obtained.
Mediator: a design framework for P2P MMOGs
Authors: Lu Fan, Hamish Taylor, Phil Trinder
Venue: Proceedings of the 6th ACM SIGCOMM workshop on Network and system support for games (2007)

With widespread use of the Internet, Massively Multiplayer Online Games (MMOGs) are becoming increasingly popular. As MMOGs scale up, conventional Client/Server (C/S) architectures exhibit various drawbacks in scalability, reliability, and redundancy. This paper presents a new Peer-to-Peer (P2P) MMOG design framework, Mediator, using a super-peer network with multiple super-peer (Mediator) roles. Mediator is novel in integrating four elements: a reward scheme, distributed resource discovery, load-management and super-peer selection. The reward scheme differentiates a peer's contribution from their reputation, and pursues symmetrical reciprocity as well as discouraging misdemeanours. A deadline-driven auction protocol is proposed for distributed resource discovery. Furthermore, both common-peer and super-peer workloads are approximately balanced using a two-level load-management scheme, and super-peers are selected in a flexible policy-based way. In this framework, the functionalities of a traditional game server are distributed, capitalising on the potential of P2P networks, and enabling the MMOG to scale better in both communication and computation. A proof-of-concept prototype of this framework is described, and ongoing work is discussed.
A Perspective on Distributed Computer Systems
Authors: J. A. Stankovic
Venue: IEEE Transactions on Computers (1984)

Distributed computer systems have been the subject of a vast amount of research. Many prototype distributed computer systems have been built at university, industrial, commercial, and government research laboratories, and production systems of all sizes and types have proliferated. It is impossible to survey all distributed computing system research. Instead, this paper identifies six fundamental distributed computer system research issues, points out open research problems in these areas, and describes how these six issues and solutions to problems associated with them transect the communications subnet, the distributed operating system, and the distributed database areas. It is intended that this perspective on distributed computer system research serve as a form of survey, but more importantly to illustrate and encourage a better integration and exchange of ideas from various subareas of distributed computer system research.
Multilayer perceptron as inverse model in a ground-based remote sensing temperature retrieval problem
Authors: Esteban García-Cuesta, Inés M. Galván, Antonio J. de Castro
Venue: Engineering Applications of Artificial Intelligence (2008)

In this paper, a combustion temperature retrieval approximation for high-resolution infrared ground-based measurements has been developed based on a multilayer perceptron (MLP) technique. The introduction of a selection subset of features is mandatory due to the problems related to the high dimensionality data and the worse performance of MLPs with this high input dimensionality. Principal component analysis is used to reduce the input data dimensionality, selecting the physically important features in order to improve MLP performance. The use of a priori physical information over other methods in the chosen feature's phase has been tested and has appeared jointly with the MLP technique as a good alternative for this problem.
Handwriting Segmentation Contest
Authors: B. Gatos, A. Antonacopoulos, N. Stamatopoulos
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02 (2007)

This paper presents the results of the Handwriting Segmentation Contest that was organized in the context of ICDAR2007. The aim of this contest was to use well established evaluation practices and procedures in order to record recent advances in off- line handwriting segmentation. Two benchmarking datasets (one for text line and one for word segmentation) were used in a common evaluation platform in order to test and compare all submitted algorithms for handwritten document segmentation in realistic circumstances. The results of the evaluation of five algorithms submitted by participants as well as of two state-of-the-art algorithms are presented. The performance evaluation method is based on counting the number of matches between the text lines or words detected by the algorithms and the text line or words of the ground truth.
Hybrid Neural Network Model for Short-Term Load Forecasting
Authors: Chengqun Yin, Lifeng Kang, Wei Sun
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

Short-term load forecasting has always been the essential part of reliable and economic operation in power systems. In this paper, a hybrid neural network model combining rough set theory, principal component analysis, dynamic clustering analysis and ant colony optimization algorithm is presented. First, rough set theory is used to eliminate redundant influential factors that don't exert tremendous effect on power load. Next, principal component analysis is employed to minimize the correlations in the selected factors. Then, using dynamic clustering analysis, the historical load data are divided into several groups. According to the similarity between hourly load to be forecasted and classified categories calculated by grey relational analysis, typical samples are selected and corresponding neural network model for hourly load, training by ant colony optimization algorithm, is established. Finally, the forecasting results using actual load of Chekiang province in China proves that the proposed model is satisfactory.