ppxscal/embedding_network huggingface dataset:
Prediction in electronics based on limited information
Authors: Jelena Milojkovic, Vančo Litovski
Venue: Proceedings of the 8th WSEAS international conference on Electronics, hardware, wireless and optical communication (2009)

Short time series are characterized with no trend information, no randomness and lack of periodicity. That makes prediction based on them very difficult or even impossible. On the other side there is strong need for prediction based on limited amount of data in many areas of life and business. We here propose implementation of some architectures of artificial neural networks as a potential systematic solution of that problem as opposed to heuristics that are in use. Examples will be given related to verification of Moor's law that is respected for prediction in modern electronic production, and to prediction of quantities of obsolete computers.
The Misuse of Information Systems: The Impact of Security Countermeasures
Authors: John P. D'Arcy
Venue:  (2007)

D Arcy reports on an empirical investigation of the impact of four security countermeasures (security policies, security awareness program, computer monitoring, preventive security software) on IS misuse. Using the framework of general deterrence theory, he develops and tests a conceptual model using survey responses from 507 professionals. He finds support for the effectiveness of security policies, security awareness programs, and computer monitoring in deterring IS misuse. Preventive security software appears only moderately effective. The results also suggest that the deterrent effectiveness of security countermeasures vary based on computer self-efficacy and the amount of time spent telecommuting. D Arcy s findings help explain the relationships between security countermeasures and IS misuse, while reaffirming the applicability of general deterrence theory to the IS security domain. 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
Smoothing sample extremes: The mixed model approach
Authors: Fabrizio Laurini, Francesco Pauli
Venue: Computational Statistics Data Analysis (2009)

Nonparametric regression for sample extremes can be performed using a variety of techniques. The penalized spline approach for the Poisson point process model is considered. The generalized linear mixed model representation for the spline model, with its Bayesian approach to inference, turns out to be a very flexible framework. Monte Carlo Markov chain algorithms are employed for exploration of the posterior distribution. The overall performance of the method is tested on simulated data. Two real data applications are also discussed for modeling trend of intensity of earthquakes in Italy and for assessing seasonality and short term trend of summer extreme temperatures in Milan, Italy.
Refinement of the ACP2P by sharing user-feedbacks and learning query-responder-agent-relationships
Authors: Tsunenori Mine, Akihiro Kogo, Satoshi Amamiya, Makoto Amamiya
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

This paper proposes two methods for improving the retrieval accuracy of the Agent-Community-based Peer-to-Peer information retrieval (ACP2P) method. One uses user feedbacks exchanged in a community. The other uses query-learning methods that make a middle agent to learn query-responder agent relationships. The latter methods are useful not only for improving the retrieval accuracy, but also for reducing communication loads. We conduct several experiments with test collections so that the evaluation can be done in an objective manner. The experimental results illustrate the validity of our proposed methods.
Bayesian multiscale feature detection of log-spectral densities
Authors: Sigrunn H. Sørbye, Kristian Hindberg, Lena R. Olsen, Håvard Rue
Venue: Computational Statistics Data Analysis (2009)

A fully-automatic Bayesian visualization tool to identify periodic components of evenly sampled stationary time series, is presented. The given method applies the multiscale ideas of the SiZer-methodology to the log-spectral density of a given series. The idea is to detect significant peaks in the true underlying curve viewed at different resolutions or scales. The results are displayed in significance maps, illustrating for which scales and for which frequencies, peaks in the log-spectral density are detected as significant. The inference involved in producing the significance maps is performed using the recently developed simplified Laplace approximation. This is a Bayesian deterministic approach used to get accurate estimates of posterior marginals for latent Gaussian Markov random fields at a low computational cost, avoiding the use of Markov chain Monte Carlo techniques. Application of the given exploratory tool is illustrated analyzing both synthetic and real time series.
Reviewing State of the Art AI Systems for Skin Cancer Diagnosis
Authors: Ilias Maglogiannis, Charalampos Doukas
Venue: Proceeding of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies (2007)

In the recent years artificial intelligence and vision-based diagnostic systems for dermatology have demonstrated significant progress. In this chapter, we review these systems by firstly presenting the installation, the visual features used for skin lesion classification and methods for defining them. Then we describe how to extract these features through digital image processing methods, i.e., segmentation, registration, border detection, color and texture processing and then we present how to use the extracted features for skin lesion classification by employing artificial intelligence methods, i.e., Discriminant Analysis, Neural Networks, Support Vector Machines, Wavelets. We finally list all the existing systems found in literature that deal with the specific problem.
Multi-Agent Knowledge Modelling
Authors: Marie Duží, Anneli Heimbürger, Takehiro Tokuda, Peter Vojtáš, Naofumi Yoshida
Venue: Proceeding of the 2009 conference on Information Modelling and Knowledge Bases XX (2009)

This paper contains five contributions of the participants of the panel discussion on “Multi-agent Knowledge Modelling” in the EJC 2008 conference. We addressed four main topics: (a) Semantic Web technologies, (b) reality vs. agents, (c) cross-cultural knowledge and (d) communication of agents. Each of the discussants presented his/her view of the addressed problem. Some views were rather pessimistic, other optimistic or realistic, but all of them posed questions and raised open problems as well as solution proposals. Thus this paper is a contribution to the topic of multi-agent knowledge modelling from different points of view.
A combinatorial algorithm for the Maximum Lifetime Data Gathering And Aggregation problem in sensor networks
Authors: Konstantinos Kalpakis, Shilang Tang
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

The Maximum Lifetime Data Gathering and Aggregation (MLDA) problem is concerned with maximizing the system lifetime T so that we can perform T rounds of data gathering with in-network aggregation, given the initial available energy of the sensors. A solution of value T to the MLDA problem consists of a collection of aggregation trees together with the number of rounds each such tree should be used in order to achieve lifetime T. We describe a combinatorial iterative algorithm for finding an optimal continuous solution to the MLDA problem that consists of up to n - 1 aggregation trees and achieves lifetime To, which depends on the network topology and initial energy available at the sensors. We obtain an α-approximate optimal integral solution by simply rounding down the optimal continuous solution, where α = (To−n+1)/To. Since in practice To ≫ n, α ≈ 1. We get asymptotically optimal integral solutions to the MLDA problem whenever the optimal continuous solution is ω(n). Furthermore, we demonstrate the efficiency and effectiveness of the proposed algorithm via extensive experimental results.
Kernel Density Estimation on Riemannian Manifolds: Asymptotic Results
Authors: Guillermo Henry, Daniela Rodriguez
Venue: Journal of Mathematical Imaging and Vision (2009)

The paper concerns the strong uniform consistency and the asymptotic distribution of the kernel density estimator of random objects on a Riemannian manifolds, proposed by Pelletier (Stat. Probab. Lett., 73(3):297---304, 2005). The estimator is illustrated via one example based on a real data.
Multiple indefinite kernel learning with mixed norm regularization
Authors: Matthieu Kowalski, Marie Szafranski, Liva Ralaivola
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We address the problem of learning classifiers using several kernel functions. On the contrary to many contributions in the field of learning from different sources of information using kernels, we here do not assume that the kernels used are positive definite. The learning problem that we are interested in involves a misclassification loss term and a regularization term that is expressed by means of a mixed norm. The use of a mixed norm allows us to enforce some sparsity structure, a particular case of which is, for instance, the Group Lasso. We solve the convex problem by employing proximal minimization algorithms, which can be viewed as refined versions of gradient descent procedures capable of naturally dealing with nondifferentiability. A numerical simulation on a Uci dataset shows the modularity of our approach.
NLP-based metadata extraction for legal text consolidation
Authors: PierLuigi Spinosa, Gerardo Giardiello, Manola Cherubini, Simone Marchi, Giulia Venturi, Simonetta Montemagni
Venue: Proceedings of the 12th International Conference on Artificial Intelligence and Law (2009)

The paper describes a system for the automatic consolidation of Italian legislative texts to be used as a support of an editorial consolidating activity and dealing with the following typology of textual amendments: repeal, substitution and integration. The focus of the paper is on the semantic analysis of the textual amendment provisions and the formalized representation of the amendments in terms of meta-data. The proposed approach to consolidation is metadata--oriented and based on Natural Language Processing (NLP) techniques: we use XML--based standards for metadata annotation of legislative acts and a flexible NLP architecture for extracting metadata from parsed texts. An evaluation of achieved results is also provided.
Capturing router congestion and delay
Authors: Nicolas Hohn, Konstantina Papagiannaki, Darryl Veitch
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

Using a unique monitoring experiment, we capture all packets crossing a (lightly utilized) operational access router from a Tier-1 provider, and use them to provide a detailed examination of router congestion and packet delays. The complete capture enables not just statistics as seen from outside the router, but also an accurate physical router model to be identified. This enables a comprehensive examination of congestion and delay from three points of view: the understanding of origins, measurement, and reporting. Our study defines new methodologies and metrics. In particular, the traffic reporting enables a rich description of the diversity of microcongestion behavior, without model assumptions, and at achievable computational cost.
Scrum and XP from the Trenches: Enterprise Software Development
Authors: Henrik Kniberg
Venue:  (2007)

This book aims to give you a head start by providing a detailed down-to-earth account of how one Swedish company implemented Scrum and XP with a team of approximately 40 people and how they continuously improved their process over a year's time. Under the leadership of Henrik Kniberg they experimented with different team sizes, different sprint lengths, different ways of defining "done", different formats for product backlogs and sprint backlogs, different testing strategies, different ways of doing demos, different ways of synchronizing multiple Scrum teams, etc. They also experimented with XP practices - different ways of doing continuous build, pair programming, test driven development, etc, and how to combine this with Scrum. 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
Service differentiation in OFDM-based IEEE 802.16 networks
Authors: Yi Zhou, Kai Chen, Jianhua He, Haibin Guan, Yan Zhang, Alei Liang
Venue: EURASIP Journal on Wireless Communications and Networking (2009)

IEEE 802.16 network is widely viewed as a strong candidate solution for broadband wireless access systems. Various flexible mechanisms related to QoS provisioning have been specified for uplink traffic at the medium access control (MAC) layer in the standards. Among the mechanisms, bandwidth request scheme can be used to indicate and request bandwidth demands to the base station for different services. Due to the diverse QoS requirements of the applications, service differentiation (SD) is desirable for the bandwidth request scheme. In this paper, we propose several SD approaches. The approaches are based on the contention-based bandwidth request scheme and achieved by the means of assigning different channel access parameters and/or bandwidth allocation priorities to different services. Additionally, we propose effective analytical model to study the impacts of the SD approaches, which can be used for the configuration and optimization of the SD services. It is observed from simulations that the analytical model has high accuracy. Service can be efficiently differentiated with initial backoff window in terms of throughput and channel access delay. Moreover, the service differentiation can be improved if combined with the bandwidth allocation priority approach without adverse impacts on the overall system throughput.
Advancements in Information Technology and Information Security, 1st edition
Authors: Sagar S. Jambhorkar, Arpita Gopal, Chandrani Singh
Venue:  (2007)

The National Conference on Advancements in Information Technology and Internet Security, AITIS-2008 was organized by the Department of MCA, Sinhgad Institute of Business Administration and Research, Pune, India. This conference provided a forum for the researchers and professionals from Industries, Research & Development sector, Educational Institutions, Government Organizations, Universities and Post Graduate students to share and disseminate their innovative and pioneering views about recent trends and developments in the areas of Information Technology & Internet Security. This conference covered almost all the state-of-the-art technology areas and aims to establish and strengthen relationships in research & development, through networking and collaboration of members and participants. 110 papers had been received from 11 different states, out of which 50 papers were finally selected for presentations as full papers. The review process was a double blind system with evaluations by two different reviewers, followed by a final internal review. The papers were accepted based on relevance of the topic, originality, novelty of the work done and overall appeal of the paper. The conference covers areas related to Biometrics, Digital Image and Signal Processing, Pattern Recognition, Human Computer Interaction (HCI), E-Commerce, Digital Signal Processing, Advanced Networking and Security, Data Mining, Knowledge Management, Grid Computing, Parallel Computing, Bioinformatics, Internet Security etc. This volume contains selected research papers presented in this national conference hosted by the Department of Computer Applications of SIBAR. This collection of papers will become a valuable archive for researchers and practitioners for years to come.
Memory mapped ECC: low-cost error protection for last level caches
Authors: Doe Hyun Yoon, Mattan Erez
Venue: Proceedings of the 36th annual international symposium on Computer architecture (2009)

This paper presents a novel technique, Memory Mapped ECC, which reduces the cost of providing error correction for SRAM caches. It is important to limit such overheads as processor resources become constrained and error propensity increases. The continuing decrease in SRAM cell size and the growing capacity of caches increases the likelihood of errors in SRAM arrays. To address this, redundant information can be used to correct a value after an error occurs. Information redundancy is typically provided through error-correcting codes (ECC), which append bits to every SRAM row and increase the array's area and energy consumption. We make three observations regarding error protection and utilize them in our architecture: (1) much of the data in a cache is replicated throughout the hierarchy and is inherently redundant; (2) error-detection is necessary for every cache access and is cheaper than error correction, which is very infrequent; (3) redundant information for correction need not be stored in high-cost SRAM. Our unique architecture only dedicates SRAM for error detection while the ECC bits are stored within the memory hierarchy as data. We associate a physical memory address with each cache line for ECC storage and rely on locality to minimize the impact. The cache is dynamically and transparently partitioned between data and ECC with the fraction of ECC growing with the number of dirty cache lines. We show that this has little impact on both performance (1.3% average and
Electrothermal model of optocoupler for SPICE
Authors: Krzysztof Górecki, Witold J. Stepowicz
Venue: International Journal of Numerical Modelling: Electronic Networks, Devices and Fields (2009)

In the paper a new electrothermal model of the optocoupler for SPICE is proposed. The model is based on electrical models of the LED and the bipolar phototransistor with their parameters dependent on temperature, their thermal models including both the self-heating phenomenon and the mutual thermal interactions between the LED and the phototransistor, and the dependences describing electrical power dissipated in these components. The final form of the electrothermal model of the optocoupler elaborated by the authors, dedicated to the d.c. and a.c. computations, was implemented in SPICE. The usefulness of the new model was experimentally verified for the optocoupler 4N25. Copyright &copy; 2008 John Wiley & Sons, Ltd.
Feature Selection and Outliers Detection with Genetic Algorithms and Neural Networks
Authors: Agusti Solanas, Enrique Romero, Sergio Gómez, Josep M. Sopena, Rene Alquézar, Josep Domingo-Ferrer
Venue: Proceeding of the 2005 conference on Artificial Intelligence Research and Development (2005)

This paper presents a new feature selection method and an outliers detection algorithm. The presented method is based on using a genetic algorithm combined with a problem-specific-designed neural network. The dimensional reduction and the outliers detection makes the resulting dataset more suitable for training neural networks. A comparative analysis between different kind of proposed criteria to select the features is reported. A number of experimental results have been carried out to demonstrate the usefulness of the presented technique.
Scaling Analysis of Wavelet Quantiles in Network Traffic
Authors: Giada Giorgi, Claudio Narduzzi
Venue: Proceedings of the First International Workshop on Traffic Monitoring and Analysis (2009)

The study of network traffic by flow analysis has been the subject of intense and varied research. Wavelet transforms, which form the core of most traffic analysis tools, are known to be robust to linear trends in data measurements, but may suffer from the presence of occasional non-stationarities.This paper considers how the information associated to quantiles of wavelet coefficients can be exploited to improve the understanding of traffic features. A tool based on these principles is introduced and results of its application to analysis of traffic traces are presented.
Agent-Based Model and Computing Environment Facilitating the Development of Distributed Computational Intelligence Systems
Authors: Aleksander Byrski, Marek Kisiel-Dorohinicki
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

In the paper a simple formalism is proposed to describe the hierarchy of multi-agent systems, which is particularly suitable for the design of a certain class of distributed computational intelligence systems. The mapping between the formalism and the existing computing environment AgE is also sketched out.
Brief Communication: Whole genome assembly from 454 sequencing output via modified DNA graph concept
Authors: Jacek Blazewicz, Marcin Bryja, Marek Figlerowicz, Piotr Gawron, Marta Kasprzak, Edward Kirton, Darren Platt, Jakub Przybytek, Aleksandra Swiercz, Lukasz Szajkowski
Venue: Computational Biology and Chemistry (2009)

Recently, 454 Life Sciences Corporation proposed a new biochemical approach to DNA sequencing (the 454 sequencing). It is based on the pyrosequencing protocol. The 454 sequencing aims to give reliable output at a low cost and in a short time. The produced sequences are shorter than reads produced by classical methods. Our paper proposes a new DNA assembly algorithm which deals well with such data and outperforms other assembly algorithms used in practice. The constructed SR-ASM algorithm is a heuristic method based on a graph model, the graph being a modified DNA graph proposed for DNA sequencing by hybridization procedure. Other new features of the assembly algorithm are, among others, temporary compression of input sequences, and a new and fast multiple alignment heuristics taking advantage of the way the output data for the 454 sequencing are presented and coded. The usefulness of the algorithm has been proved in tests on raw data generated during sequencing of the whole 1.84Mbp genome of Prochlorococcus marinus bacteria and also on a part of chromosome 15 of Homo sapiens. The source code of SR-ASM can be downloaded from http://bio.cs.put.poznan.pl/ in the section 'Current research'-> 'DNA Assembly'. Among publicly available assemblers our algorithm appeared to generate the best results, especially in the number of produced contigs and in the lengths of the contigs with high similarity to the genome sequence.