ppxscal/embedding_network huggingface dataset:
Generalization-Based Privacy-Preserving Data Collection
Authors: Lijie Zhang, Weining Zhang
Venue: Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery (2008)

In privacy-preserving data mining, there is a need to consider on-line data collection applications in a client-server-to-user (CS2U) model, in which a trusted server can help clients create and disseminate anonymous data. Existing privacy-preserving data publishing (PPDP) and privacy-preserving data collection (PPDC) methods do not sufficiently address the needs of these applications. In this paper, we present a novel PPDC method that lets respondents (clients) use generalization to create anonymous data in the CS2U model. Generalization is widely used for PPDP but has not been used for PPDC. We propose a new probabilistic privacy measure to model a distribution attack and use it to define the respondent's problem (RP) for finding an optimal anonymous tuple. We show that RP is NP-hard and present a heuristic algorithm for it. Our method is compared with a number of existing PPDC and PPDP methods in experiments based on two UCI datasets and two utility measures. Preliminary results show that our method can better protect against the distribution attack and provide good balance between privacy and data utility.
Understanding and Improving Collective Attention Economy for Expertise Sharing
Authors: Yunwen Ye, Kumiyo Nakakoji, Yasuhiro Yamamoto
Venue: Proceedings of the 20th international conference on Advanced Information Systems Engineering (2008)

The importance and benefits of expertise sharing for organizations in knowledge economy are well recognized. However, the potential cost of expertise sharing is less well understood. This paper proposes a conceptual framework called collective attention economy to identify the costs associated with expertise sharing and provide the basis for analyzing and understanding the cost-benefit structure of different communication mechanisms. To demonstrate the analytical power of the conceptual framework, the paper describes a new communication mechanism--Dynamic Mailing List (DML)--that is developed by adjusting certain cost factors.
Reduction of Visual Information in Neural Network Learning Visualization
Authors: Matúš Užák, Rudolf Jakša, Peter Sinčák
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

Visualization of neural network learning faces the problem of overwhelming amount of visual information. This paper describes the application of clustering methods for reduction of visual information in the response function visualization. If only clusters of neurons are visualized instead of direct visualization of responses of all neurons in the network, the amount of visually presented information can be significantly reduced. This is useful for user fatigue reduction and also for minimization of the visualization equipment requirements. We show that application of Kohonen network or Growing Neural Gas with Utility Factor algorithm allows to visualize the learning of moderate-sized neural networks. Comparison of both algorithms in this task is provided, also with performance analysis and example results of response function visualization.
Extracting Social Networks Among Various Entities on the Web
Authors: Yingzi Jin, Yutaka Matsuo, Mitsuru Ishizuka
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

Social networks have recently attracted much attention for their importance to the Semantic Web. Several methods exist to extract social networks for people (particularly researchers) from the web using a search engine. Our goal is to expand existing techniques to obtain social networks among various entities. This paper proposes two improvements, i.e. relation identification and threshold tuning, which enable us to deal with complex and inhomogeneous communities. Social networks among firms and artists (of contemporary) are extracted as examples: Several evaluations emphasize the effectiveness of these methods. Our system was used at the International Triennale of Contemporary Art (Yokohama Triennale 2005) to facilitate navigation of artists' information. This study contributes to the Semantic Web in that we increase the applicability of social network extraction for several studies.
Constrained Control of a Class of Uncertain Nonlinear MIMO Systems Using Neural Networks
Authors: Dingguo Chen, Jiaben Yang
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

This paper attempts to present a neural inverse control design framework for a class of nonlinear multiple-input multiple-output (MIMO) system with uncertainties. This research effort is motivated by the following considerations: (a) An appropriate reference model that accurately represents the desired system dynamics is usually assumed to exist and to be available, and yet in reality this is not the case often times; (b) In real world applications, there are many cases where controls are constrained within a physically allowable range, which presents another layer of difficulties to directly apply the reference model based inverse control; (c) It is difficult to consider optimal control even for the reference model as in general the analytic solution to the optimal control problem is not available. The simulation study is conducted on a single-machine infinite-bus (SMIB) system to illustrate the proposed design procedure and demonstrates the effectiveness of the proposed control approach.
An overview of segmentation techniques for target detection in visual images
Authors: G. N. Srinivasan, G. Shobha
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

This paper presents an overview of the methodologies and algorithms for segmenting 2D images as a means in detecting target objects embedded in visual images for an Automatic Target Detection application.
A Dynamic Immunity-Based Model for Computer Virus Detection
Authors: Yu Zhang, Tao Li, Renchao Qin
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

Internet provides a fertile medium for new breeds of computer viruses. Many people who have access to a wealth of information via Internet are attacked by more computer viruses than they can effectively process. We present a dynamic computer virus detection model that can detect known viruses and previously unknown viruses to prevent information systems from damage. This model is inspired by biological immune systems that protect the body against damage from pathogens. The architecture of this model, the formal definitions of self, nonself, antigen, antibody, and vaccine gene library are introduced. Furthermore, the evolution of self and nonself, the generation of the antibody, the evolution of the virus vaccine gene, and the detection of the antigen are depicted. Experiment results show that this model has better capacity of self-adaptability and self-learning in detecting unknown viruses than traditional models.
Subject-Adaptive Real-Time BCI System
Authors: Han Sun, Liqing Zhang
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

Brain Computer Interface (BCI) provides people with motor disabilities a new channel for communication and control. In this paper, we first introduce a framework of BCI system, consisting of EEG Acquisition, Signal Preprocess, Feature Extractor, Pattern Classifier, Subject Task Generation and Visualization. The system is able to adapt to subjects online and to work in real time condition with high accuracy and short latency. The BCI system is based on analysis of EEG patterns of object's left and right motor imagery. Independent Component Analysis and temporal filter are employed for artifacts removal and noise reduction. Spatial filter and autoregressive model are used as feature extractor, from which feature vectors are classified by SVM. The best classification accuracy of all objects' is up to 99% in offline analysis and 80% in online condition.
Parallel DEM Software for Simulation of Granular Media
Authors: Algirdas Maknickas, Arnas Kačeniauskas, Rimantas Kačianauskas, Robertas Balevičius, Algis Džiugys
Venue: Informatica (2006)

The paper describes the development and performance of parallel algorithms for the discrete element method (DEM) software. Spatial domain decomposition strategy and message passing inter-processor communication have been implemented in the DEMMAT code for simulation of visco-elastic frictional granular media. The novel algorithm combining link-cells for contact detection, the static domain decomposition for parallelization and MPI data transfer for processors exchanging particles has been developed for distributed memory PC clusters. The parallel software DEMMAT_PAR has been applied to model compacting of spherical particles in the rectangular box. Two benchmark problems with different numbers of particles have been solved in order to measure parallel efficiency of the code. The inter-processor communication has been examined in order to improve domain decomposition topology and to achieve better load balancing. The speed-up equal to 11 has been obtained on 16 processors. The parallel performance study has been performed on the PC cluster VILKAS of Vilnius Gediminas Technical University, Lithuania.
Non-preemptive Fixed Priority Scheduling of Hard Real-Time Periodic Tasks
Authors: Moonju Park
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

This paper addresses the problem of scheduling periodic tasks on a uniprocessor using static priority assignment without preemption. The problem of non-preemptive fixed priority scheduling has received little attention until recently, while real-life applications are often based on non-preemptive systems especially in case of embedded systems. In this paper, we show that Rate Monotonic priority assignment is optimal for non-preemptive scheduling when each task's relative deadline is equal to its period. We have derived a schedulability bound for non-preemptive Rate Monotonic scheduling by using period ratio of the tasks to provide a guarantee that tasks will meet their deadlines. Since the obtained bound is relatively small comparing with the preemptive scheduling, we also propose a method for designing high-utilization non-preemptive system to enhance the utilization bound.
A Tool for the Calculation of Molecular Descriptors in the Development of QSAR Models
Authors: Irene Luque Ruiz, Miguel Ángel Gómez-Nieto
Venue: Proceeding sof the international conference on Computational Science and Its Applications, Part I (2008)

Molecular descriptors are used in QSAR applications for the development of theoretical model for the prediction of activity of chemicals compounds. In this paper we describe a fully Java developed environment devoted to the calculation of molecular descriptors. This tool allows the management of chemical compounds large databases and the calculation of around 200 molecular descriptors. Users, in a windows based tool, can manage different chemicals databases, select the desired molecular descriptors to be calculated and obtain the results in a graphic and tabular mode, analyzing and storing the results for the building of QSAR models. The tool uses a free Java library (MDC) of molecular descriptors also described in this paper.
Extending Haptic Device Capability for 3D Virtual Grasping
Authors: Zoran Najdovski, Saeid Nahavandi
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

This paper presents an investigation into the workspace constraints observed through the use of multiple single point haptic interfaces, which lead to the design of a novel grasping device that improves upon current commercial haptic interfaces. The presented device is desktop based, and has been designed to maximise the haptic workspace while offering the ability to grasp and manipulate virtual objects, which is a function that current commercial interfaces are limited in providing. The performance of the commercial haptic interface in producing sustained effective operation and increased workspace with the attached haptic gripper is evaluated, and the improvement of both has been determined.
Controllability level of a hyperbolic system with non zero boundary conditions
Authors: Jerzy Stefan Respondek
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

The objective of the article is the numerical analysis of the controllability level of a hyperbolic system with non zero boundary conditions. Precisely the non zero Dirichlet conditions for the considered PDE controllability level are the main novelty of the article. As a result we presented the graph with the level of the controllability for the hyperbolic PDE.
An improvement on the mechanic eccentric punch power presser dynamics
Authors: Sanda Victorinne Paturca, Mircea Covrig, Costin Cepisca, Stefan Gheorghe
Venue: Proceedings of the 7th WSEAS International Conference on Application of Electrical Engineering (2008)

This paper presents a study on the improvement of the punch presser dynamic by using variable frequency drives. It was realized a punch presser dynamic model, which was experimentally validated by measurements. Computer aided data acquisition was made for the presser motor fed directly from the power network and fed by a Voltage Source Inverter (VSI). Three control schemes were investigated: Open Loop Volt-Hertz, Closed Loop Volt-Hertz and Direct Torque Control (DTC). A brief on the operation principle and the Simulink models of each control scheme are presented. The comparative graphical results can illustrate their effect on the power presser dynamics.
Frequency Distribution of Contextual Patterns in the Game of Go
Authors: Zhiqing Liu, Qing Dou, Benjie Lu
Venue: Proceedings of the 6th international conference on Computers and Games (2008)

In this paper, we present two statistical experiments on the frequency distribution of patterns in the game of Go. In these experiments, we extract contextual patterns of Go as spatial combinations of moves. An analysis of a collection of 9447 professional game records of Go shows that the frequency distribution of contextual patterns in professional games displays a Mandelbrot fit to Zipf's law. Additionally, we show that the Zipfian frequency distribution of Go patterns in professional games is deliberate by rejecting the null hypothesis that the frequency distribution of patterns in random games exhibits a Zipfian frequency distribution.
HLS: Tunable Mining of Approximate Functional Dependencies
Authors: Jeremy T. Engle, Edward L. Robertson
Venue: Proceedings of the 25th British national conference on Databases: Sharing Data, Information and Knowledge (2008)

This paper examines algorithmic aspects of searching for approximate functional dependencies in a database relation. The goal is to avoid exploration of large parts of the space of potential rules. This is accomplished by leveraging found rules to make finding other rules more efficient. The overall strategy is an attribute-at-a-time iteration which uses local breadth first searches on lattices that increase in width and height in each iteration. The resulting algorithm provides many opportunities to apply heuristics to tune the search for particular data-sets and/or search objectives. The search can be tuned at both the global iteration level and the local search level. A number of heuristics are developed and compared experimentally.
Resistor reliability---whose responsibility?: some case histories
Authors: Jesse Marsten
Venue: Papers and discussions presented at the Dec. 8-10, 1953, eastern joint AIEE-IRE computer conference: information processing systems---reliability and requirements (1953)

Component reliability is a subject that has had the attention, in whole or in part, of almost every electronics symposium or conference the last few years. The failure rate of equipment, claimed to be caused by component failure, warranted this attention. As a result the cry has been for better and better components. This is good. Components should be and are being constantly improved, just as computers and other electronic gear should be constantly improved. 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
Detection of Cardiac-Related Diseases Using Nonlinear Analysis of Short-Term ECG Signal with Aural Stimuli
Authors: Rafal Ladysz, Tomasz Fabiszak, Wojciech Pospiech, Marta Pilaczynska-Cemel, Jacek Kubica
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

Risk stratification for sudden cardiac death is one of the most compelling challenges of modern cardiology. An ECG-derived method of assessment of Heart Rate Variability (HRV) is one of few diagnostic modalities for that purpose whose applicability has been widely acknowledged. Contemporary methods for measurement of HRV usually employ the Holter ECG recording where a portable device continuously monitors the electrical activity of the heart for 24 hours or longer. Our approach is based on much shorter 30-minute signals and: (i) standardization of controlled external stimuli (Pilot-1 and Pilot-2), (ii) introducing novel NLD complexity measures of the stimuli-perturbed ECG signal and (iii) applying supervised classification methods as a step to incorporate our framework into a diagnostic decision support system.
Multi-granular Control of Double Inverted Pendulum Based on Universal Logics Fuzzy Neural Networks
Authors: Bin Lu, Juan Chen
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

The control of double-inverted pendulum is one of the most difficult control problems, especially for the control of parallel-type one, because of the high complexity of control systems. To attain the prescribed accuracy in reducing control complexity, a multi-granular controller for stabilizing a double inverted pendulum system is presented based on universal logics fuzzy neural networks. It is a universal multi-granular fuzzy controller which represents the process of reaching goal at different spaces of the information granularity. When the prescribed accuracy is low, a coarse fuzzy controller can be used. As the process moves from high level to low level, the prescribed accuracy becomes higher and the information granularity to fuzzy controller becomes finer. In this controller, a rough plan is generated to reach the final goal firstly. Then, the plan is decomposed to many sub-goals which are submitted to the next lower level of hierarchy. And the more refined plans to reach these sub-goals are determined. If needed, this process of successive refinement continues until the final prescribed accuracy is obtained. In the assistance of universal logics fuzzy neural networks, more flexible structures suitable for any controlled objects can be easy obtained, which improve the performance of controllers greatly. Finally, simulation results indicate the effectiveness of the proposed controller.
Special Investigation of Variable Star Delta Cephei via Neural Network
Authors: Sehwan Yoo, Jinsuk Kang, Jangho Lee, Taikyeong Jeong
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

We investigated that the brightness magnitude of the Del Cephei had been adapted to three different training values and each training had four different hidden layers in the back-propagation neural network (BPNN) models. The best forecasting mean through different approaches in the BPNN model was obtained at 15% training with four hidden layers. However, the difference in forecasting accuracies of the different levels was not statistically significant.
Parallel Preconditioning Methods with Selective Fill-Ins and Selective Overlapping for Ill-Conditioned Problems in Finite-Element Methods
Authors: Kengo Nakajima
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

In the present paper, parallel preconditioning methods with selective fill-ins and selective overlapping for contact problems have been developed and evaluated on PC clusters with 64 cores. The proposed methods provide robust convergence with efficiency. Finally, the proposed methods have been applied to ill-conditioned problems with heterogeneity and robustness, and their efficiency has been evaluated on TSUBAME super-cluster with up to 512 cores.
Computational Complexity of the Distance Constrained Labeling Problem for Trees (Extended Abstract)
Authors: Jiří Fiala, Petr A. Golovach, Jan Kratochvíl
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

An L(p,q)-labeling of a graph is a labeling of its vertices by nonnegative integers such that the labels of adjacent vertices differ by at least p and the labels of vertices at distance 2 differ by at least q. The span of such a labeling is the maximum label used. Distance constrained labelings are an important graph theoretical approach to the Frequency Assignment Problem applied in mobile and wireless networks.In this paper we show that determining the minimum span of an L(p,q)-labeling of a tree is NP-hard whenever q is not a divisor of p. This demonstrates significant difference in computational complexity of this problem for q = 1 and q > 1. In addition, we give a sufficient and necessary condition for the existence of an H(p,q)-labeling of a tree in the case when the metric on the label space is determined by a strongly vertex transitive graph H. This generalizes the problem of distance constrained labeling in cyclic metric, that was known to be solvable in polynomial time for trees.
Some IP security issues
Authors: Zoran Bojkovic
Venue: Proceedings of the 10th WSEAS International Conference on Mathematical Methods and Computational Techniques in Electrical Engineering (2008)

This work seeks to provide some important Internet Protocol (IP) security issues. From the point of view of multimedia networks, security is important to be recognized for current and future users and implements. In the first part, some protocols are presented. For both IPv4 and IPv6, the choice of Encapsulating Security Payload (ESP) protocol and Authentication Header (AH) is offered. Internet Key Exchange (IKE) protocol is included, too. The next parts cover frameworks for basic security concepts and security technology. Also, infrastructure security for future mobile networks is pointed out, because they will be open to different services and service providers. Finally, network operator's security requirements together with requirements from user's, network's and service's perspective conclude the presentation.
A Compact Encoding of Rectangular Drawings with Efficient Query Supports
Authors: Katsuhisa Yamanaka, Shin-Ichi Nakano
Venue: Proceedings of the 3rd international conference on Algorithmic Aspects in Information and Management (2007)

A rectangular drawing is a plane drawing in which every face is a rectangle. In this paper we give a simple encoding scheme for rectangular drawings. Given a rectangular drawing R with maximum degree 3, our scheme encodes R with $\frac{5}{3}m + o(n)$ bits for each n-vertex rectangular drawing R, where m is the number of edges of R, and supports a rich set of queries, including adjacency and degree queries on the faces, in constant time.