ppxscal/embedding_network huggingface dataset:
New vertical handoff algorithm based on hysteretic level
Authors: Shengdong Xie, Meng Wu
Venue: Proceedings of the 2008 International Conference on Advanced Infocomm Technology (2008)

This paper proposes a new vertical handoff algorithm in heterogeneous wireless networks which are composed of cellular network (CN) and wireless local network (WLAN). It is an amelioration of the traditional handoff algorithm based-on hysteretic level, which utilizes two levels in different handoff directions and makes handoff decision in a probability which is a function of the received signal strength indicator (RSSI). Simulations show that our method could increase the available bandwidth and lower the number of handoffs only at cost of a little blocking probability which is tolerable to traffics in packetswitch networks.
Stability cannot be derived from local structure in biochemical networks
Authors: Domenico Bellomo, Peter van Nes, Marcel J. T. Reinders, Dick de Ridder
Venue: Proceedings of the 3rd International Conference on Bio-Inspired Models of Network, Information and Computing Sytems (2008)

In recent literature, the relationship between structure and dynamics in biochemical networks has been intensively investigated. In fact, the scarcity of information about such networks has led to attempts to predict some of their dynamic features based exclusively on more easily available structural information. A recent finding relating structure to dynamics is that network motifs (a structural feature) that are structurally stable (a dynamic feature) are enriched in some biochemical networks [21]. In this work, we systematically investigate the method in [21] and the assumptions it relies on. Our findings suggest that the conclusions drawn on the considered biological networks (over-representation of structurally stable motifs) cannot be generalized, as they critically depend on a user-defined choice of null model in the motif enrichment analysis. We have further applied the method in [21] to metabolic networks, which provide an excellent test-bed, as a relatively large amount of information is available about the type, strength and activity of metabolic interactions. For metabolic networks we arrive at the same conclusion: stability cannot be derived from local structure.
Presence & placement: exploring the benefits of multiple shared displays on an intellective sensemaking task
Authors: Christopher Plaue, John Stasko
Venue: Proceedings of the ACM 2009 international conference on Supporting group work (2009)

Relatively little is known about how the presence and location of multiple shared displays changes the performance and dynamics of teams collaborating. We conducted a case study evaluating several shared display configurations with groups collaborating on a data-intensive, sense-making task. Teams completed the same task using either a single display, side-by-side dual, or opposing dual shared displays. The location of the second shared display significantly impacted the ability for teams to make logical connections amongst the data. Users were also significantly more satisfied with the collaboration process using the side-by-side dual display condition than those using a single display.
Numerical solution of some partial differential equations by means of a deterministic method of approximate functional integration
Authors: V. D. Rushai
Venue: Numerische Mathematik (2009)

A numerical method of solution of some partial differential equations is presented. The method is based on representation of Green functions of the equations in the form of functional integrals and subsequent approximate calculation of the integrals with the help of a deterministic approach. In this case the solution of the equations is reduced to evaluation of usual (Riemann) integrals of relatively low multiplicity. A procedure allowing one to increase accuracy of the solutions is suggested. The features of the method are investigated on examples of numerical solution of the Schr&#x00f6;dinger equation and related diffusion equation.
Using self-organizing maps to build an attack map for forensic analysis
Authors: H. Güneş Kayacik, A. Nur Zincir-Heywood
Venue: Proceedings of the 2006 International Conference on Privacy, Security and Trust: Bridge the Gap Between PST Technologies and Business Services (2006)

In this work, we focus on developing behavioral models of known attacks to help security experts to identify the similarities between attacks. Furthermore, these attack behavior models can be used to analyze zero-day attacks, which security experts have limited knowledge of. To this end, a Self Organizing Feature Map (SOM) is employed to model the relationship between known attacks and U-Matrix representation is used to create a two dimensional topological map of known attacks. The approach is evaluated on KDD'99 data set. Results show that attacks with similar behavior patterns are placed together on the map. Moreover, when new attacks are presented, SOM assigned similar labels to the attacks that are newer versions of the known attacks.
Automated Testing of Planning Models
Authors: Klaus Havelund, Alex Groce, Gerard Holzmann, Rajeev Joshi, Margaret Smith
Venue: Model Checking and Artificial Intelligence: 5th International Workshop, MoChArt 2008, Patras, Greece, July 21, 2008. Revised Selected and Invited Papers (2009)

Automated planning systems (APS) are maturing to the point that they have been used in experimental mode on both the NASA Deep Space 1 spacecraft and the NASA Earth Orbiter 1 satellite. One challenge is to improve the test coverage of APS to ensure that no unsafe plans can be generated. Unsafe plans can cause wasted resources or damage to hardware. Model checkers can be used to increase test coverage for large complex distributed systems and to prove the absence of certain types of errors. In this work we have built a generalized tool to convert the input models of an APS to Promela, the modeling language of the Spin model checker. We demonstrate on a mission sized APS input model, that we with Spin can explore a large part of the space of possible plans and verify with high probability the absence of unsafe plans.
Low complexity LMS-type adaptive algorithm with selective coefficient update for stereophonic acoustic echo cancellation
Authors: Khaled Mayyas
Venue: Computers and Electrical Engineering (2009)

Stereophonic acoustic echo cancellation (SAEC) has brought up recently much attention and found a viable place in a number of hands-free applications. In this paper, we propose an LMS-type algorithm for SAEC based on decomposing the long adaptive filter of each channel of the SAEC system into smaller subfilters. We further reduce the complexity of the algorithm by employing the selective coefficient update (SCU) method in each subfilter. This leads to a significant improvement in the convergence rate of the algorithm with low computational overhead. However, the algorithm has a high final mean-square error (MSE) at steady-state that increases as number of subfilters increases. A combined-error algorithm is presented that achieves fast convergence without compromising the steady state error level. Simulations demonstrate the convergence speed advantages of the combined-error algorithm.
Simple Bayesian binary framework for discovering significant genes and classifying cancer diagnosis
Authors: Tae Young Yang
Venue: Computational Statistics Data Analysis (2009)

Given a microarray dataset consisting of two classes, type I and type II, the proposed coherent binary framework sequentially combines a gene-rank algorithm and a classifier. Genes that are expressed at a consistently high level in one type and at a consistently low level in the other type are of much interest. The wider the gap between the expression levels, the more significant the gene is as a discriminator. A new distance metric is used to measure the gap and is obtained using Bayesian nonparametric approaches involving Dirichlet process priors. Significant genes are ranked separately based on the pattern (the genes are over-expressed in type I and under-expressed in type II) or the pattern (the genes are under-expressed in type I and over-expressed in type II). An out-of-sample cross-validation approach is suggested for use in deciding how many significant genes are necessary for the classifier. The classifier uses each selected top-ranked gene to calculate a classification score when a test sample is presented. The sample is then classified as having the type with the larger score. Empirical studies using two public datasets show that top-ranked genes in each pattern clearly distinguish the existing pattern, and the classifier uses a few significant genes to classify the types in the test samples correctly. The framework is a simple, easy alternative to more complex models in terms of its accuracy and robustness.
Strategic network design for reverse logistics and remanufacturing using new and old product modules
Authors: Akshay Mutha, Shaligram Pokharel
Venue: Computers and Industrial Engineering (2009)

Establishment of reverse logistics (RL) networks for various original equipment manufacturers (OEM's) is gaining significant importance. Various green legislations are forcing OEMs to take back their used, end-of-lease or end-of-life products, or products under warranty to minimize wastes and conserve resources. Therefore OEMs have turned to a better design of their products for maximum reuse and recycling and to retrieve back the used products through a network for reuse, remanufacture, recycle or disposal, so that maximum value can be achieved from their used products. However, designing of network points and assigning capacities to them depend not only on the volume of returned products but also on the demand for remanufactured products and the parts of used products. If OEMs are not able to add value to the used product, there would be no incentive to design a complex network. In this paper, a mathematical model for the design of a RL network is proposed. It is assumed that the returned products need to be consolidated in the warehouse before they are sent to reprocessing centres for inspection and dismantling. Dismantled parts are sent for remanufacturing or to the secondary market as spare parts. Recycling and disposal of these modules are also considered in the model. The use of the model is shown through its application in a numerical example.
Finding Good Itemsets by Packing Data
Authors: Nikolaj Tatti, Jilles Vreeken
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

The problem of selecting small groups of itemsets that represent the data well has recently gained a lot of attention. We approach the problem by searching for the itemsets that compress the data efficiently. As a compression technique we use decision trees combined with a refined version of MDL. More formally, assuming that the items are ordered, we create a decision tree for each item that may only depend on the previous items. Our approach allows us to find complex interactions between the attributes, not just co-occurrences of 1s. Further, we present a link between the itemsets and the decision trees and use this link to export the itemsets from the decision trees. In this paper we present two algorithms. The first one is a simple greedy approach that builds a family of itemsets directly from data. The second one, given a collection of candidate itemsets, selects a small subset of these itemsets. Our experiments show that these approaches result in compact and high quality descriptions of the data.
Constructing business simulations with service patterns
Authors: Richard B. Lam
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

Typically, system dynamics-based simulations of business processes are constructed in an ad hoc manner, with a modeler creating low-level components and defining inter-relationships one-by-one. As the numbers of process components or variables grow, the resulting model becomes ever more difficult to manage and extend. This paper discusses the definition and use of high-level business patterns that have predefined system dynamics sub-models. These patterns enable rapid construction of arbitrarily complex system dynamics models of business processes through abstraction, reuse, and unification of sub-model elements.
A study on SOA based multi agent under RTE environment
Authors: Min Je Cho, Hyung Rim Choi, Hyun Soo Kim, Soon Goo Hong, Young Jae Park, Jae Un Jung, Jung Ho Son
Venue: Proceedings of the 8th conference on Applied computer scince (2008)

Recently, business environment is spreading from singular business to supply-chain problem. On keen competition environment, not individual enterprise, but efficient building and running of total supply-chain decided to survival competitive of supply-chain. On the other hand, SCM (Supply Chain Management) is changing from closed and static to opened and dynamic environment, so these environment changes of SCM require to enterprise different approach than past. As supply-chain is becoming opened and dynamic, a claim is being naming that it can promote the enterprise competitive if it converses the real-time of recognition of supply-chain problem, search and choice of alternative plans to solve this problem and the time leads to the reaction To realize these conceptions of RTE(Real-Time Enterprise), not a conception of individual enterprise, but it needs to see total supply-chain as an organization and needs efficiency to converse the management activities between these enterprises. But until present, the research to deal with these changes of SCM and RTE is on insufficient situation. Thus in this paper proposes the agent system by a way of realizing dynamic supply-chain and RTE. The agent is going to accomplish the management activities in real-time depends on environment and given condition and designed for solving problems development and maintenance and repair of existing normal application system problems. Also, algorithms performance of the agent is tested on TAC SCM environment and realized dashboard so it can monitor the management activities of supply-chain.
Gabor-Based Kernel Partial-Least-Squares Discrimination Features for Face Recognition
Authors: Vitomir Štruc Nikola Pavešić
Venue: Informatica (2009)

The paper presents a novel method for the extraction of facial features based on the Gabor-wavelet representation of face images and the kernel partial-least-squares discrimination (KPLSD) algorithm. The proposed feature-extraction method, called the Gabor-based kernel partial-least-squares discrimination (GKPLSD), is performed in two consecutive steps. In the first step a set of forty Gabor wavelets is used to extract discriminative and robust facial features, while in the second step the kernel partial-least-squares discrimination technique is used to reduce the dimensionality of the Gabor feature vector and to further enhance its discriminatory power. For optimal performance, the KPLSD-based transformation is implemented using the recently proposed fractional-power-polynomial models. The experimental results based on the XM2VTS and ORL databases show that the GKPLSD approach outperforms feature-extraction methods such as principal component analysis (PCA), linear discriminant analysis (LDA), kernel principal component analysis (KPCA) or generalized discriminant analysis (GDA) as well as combinations of these methods with Gabor representations of the face images. Furthermore, as the KPLSD algorithm is derived from the kernel partial-least-squares regression (KPLSR) model it does not suffer from the small-sample-size problem, which is regularly encountered in the field of face recognition.
Approximation Space and LEM2-like Algorithms for Computing Local Coverings
Authors: Jerzy W. Grzymala-Busse, Wojciech Rząsa
Venue: Fundamenta Informaticae (2008)

In this paper we discuss approximation spaces that are useful for studying local lower and upper approximations. Set definability and properties of the approximation space, including best approximations, are considered as well. Finding best approximations is a NP-hard problem. Finally, we present LEM2-like algorithms for determining local lower and upper coverings for a given incomplete data set. Lower and upper approximations, associated with these coverings, are sub-optimal.
Improved Algorithm of Spectrum Allocation Based on Graph Coloring Model in Cognitive Radio
Authors: Jiao Wang, Yuqing Huang, Hong Jiang
Venue: Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 03 (2009)

Cognitive radio technology is proposed to solve the problem of the scarce radio spectrum resources. In view of the spectrum allocation in cognitive radio technology, this paper first analyses the three allocation rules based on graph coloring theory which include the sum reward rules, the max-min reward rules and the proportional-fair reward rules. The simulations of the three algorithms adopt the average user-reward. And we can gain the optimal rule among the three rules by the comparing simulation. This paper also proposes an improved algorithm based on graph coloring theory. The simulation results indicate that the proposed algorithm can reduce the computation effectively and have no effect on the system reward.
Interconnecting P2PSIP and IMS
Authors: Jani Hautakorpi, Arturo Salinas, Erkki Harjula, Mika Ylianttila
Venue: Proceedings of the 2008 The Second International Conference on Next Generation Mobile Applications, Services, and Technologies (2008)

Interpersonal communication using the information networks can be accomplished in many different ways. Users may communicate, for example, by using a specific communication application on an end-user terminal, typical mobile phone, or IP Multimedia Subsystem (IMS) client. Quite often there is no interconnection mechanisms between these different communication methods, and this is emphasized with regards to various communication applications. We propose an architecture for interconnecting Peer-to-peer Session Initiation Protocol (P2PSIP) and IMS networks. The actual gateway, that enables the interconnection, is seen as a peer in the P2PSIP side and as an Application Server (AS) in the IMS side. Furthermore, we present a prototype from the proposed interconnection architecture.
Conjugate unitary ESPRIT for real sources adapted to the coherent case
Authors: Zhigang Liu, Jinkuan Wang, Fuli Wang
Venue: Signal Processing (2009)

By virtue of real-valued property of some real sources, in this paper, we suggest a conjugate unitary ESPRIT (CU-ESPRIT) algorithm to exploit the conjugate information of partial array element outputs. To deal with correlated or coherent sources, we design a virtual centro-symmetric array and divide it into the virtual subarrays. Compared with the unitary ESPRIT for non-circular sources (NC unitary ESPRIT), CU-ESPRIT achieves a relative reduction of the computational complexity and an improved resolution for uncorrelated or coherent sources. Specifically, this algorithm can estimate as many as M-1 coherent sources for an array of M elements. Simulation results show the validity of our approach.
Neural Network-Based Computer-Aided Diagnosis in Classification of Primary Generalized Epilepsy by EEG Signals
Authors: Seyfettin Noyan Oğulata, Cenk Şahin, Rızvan Erol
Venue: Journal of Medical Systems (2009)

Epilepsy is a disorder of cortical excitability and still an important medical problem. The correct diagnosis of a patient's epilepsy syndrome clarifies the choice of drug treatment and also allows an accurate assessment of prognosis in many cases. The aim of this study is to classify subgroups of primary generalized epilepsy by using Multilayer Perceptron Neural Networks (MLPNNs). This is the first study classifying primary generalized epilepsy using MLPNNs. MLPNN classified primary generalized epilepsy with the accuracy of 84.4%. This model also classified generalized tonik---klonik, absans, myoclonic and more than one type seizures epilepsy groups correctly with the accuracy of 78.5%, 80%, 50% and 91.6%, respectively. Moreover, new MLPNNs were constructed for determining significant variables affecting the classification accuracy of neural networks. The loss of consciousness in the course of seizure time variable caused the largest decrease in the classification accuracy when it was left out. These outcomes indicate that this model classified the subgroups of primary generalized epilepsy successfully.
Standard error classification to support software reliability assessment
Authors: John B. Bowen
Venue: Proceedings of the May 19-22, 1980, national computer conference (1980)

A standard software error classification is viable based on experimental use of different schemes on Hughes-Fullerton projects. Error classification schemes have proliferated independently due to varied emphasis on depth of casual trace-ability and when error data was collected. A standard classification is proposed that can be applied to all phases of software development. It includes a major casual category for design errors. Software error classification is a prerequisite both for feedback for error prevention and detection, and for prediction of residual errors in operational software.
A Collaborative Filtering Recommendation Algorithm Based on Item Similarity of User Preference
Authors: Tieli Sun, Lijun Wang, Qinghe Guo
Venue: Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining (2009)

The increasing users and items restrict the development of collaborative filtering recommendation systems. Then a series of problems, such as sparsity, cold start and scalability, come out. In this paper, we add user preference based on item genre, compute the similarity aimed at user preference. It can reduce the amount of data and improve the rapidity when computing similarity between items, and it can be more veracious and better recommendation quality. The experiment result shows that problems above can be solved with this approach.
Flaneur: digital see-through telescope
Authors: Hiroshi Sakasai, Hiroshi Kato, Takako Igarashi, Miho Ishii, Maki Sugimoto, Masahiko Inami, Masahiko Inakage, Naohito Okude
Venue: ACM SIGGRAPH ASIA 2008 artgallery: emerging technologies (2008)

Flaneur is a digital telescope that helps viewers see shops and objects behind buildings as they stroll though town. As they turn the device, Flaneur displays images related to specific directions as 3D images.
Optimization of Cooperation Sensing Spectrum Performance
Authors: Deah J. Kadhim, Shimin Gong, Wei Liu, Wenqing Cheng
Venue: Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 01 (2009)

Cooperation spectrum sensing in cognitive radio networks has an analogy to a distributed decision in wireless sensor networks, where each sensor make local decision and those decision result are reported to a fusion center to give the final decision according to some fusion rules. In this paper the performance of cooperative spectrum sensing examines using new optimization strategy to find optimal weight and threshold curves that enables each secondary user senses the spectrum environment independently according to a floating threshold with respect to his local environment. Our proposed approach depends on proving the convexity of the famous optimization problem in cooperative spectrum sensing that stated maximizing the probability of detection for a given value of probability of false alarm. We show that our proposed approach reduce the detection time and thus increase the overall agility gain and win the probability of detection.
Using semantic web technologies for information adaptation
Authors: Vojtech Jirkovsky, Ivan Jelinek
Venue: Proceedings of the 9th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing (2008)

This paper summarizes actual state of semantic and adaptive web and its mutual close relation. Current technologies, ideas, massive usage in e-learning and problems are mentioned. Examples for understanding of technologies are given. Human brain researches and adaptation privacy issue is also briefly discussed.