ppxscal/embedding_network huggingface dataset:
How to represent meanings in an ontology
Authors: Miklós Szöts, Tamás Gröbler, András Simonyi
Venue: Acta Cybernetica (2007)

We work on a method for giving a formal semantic representation of natural language texts. The semantic representation is generated in an ontology, on the basis of morphological and syntactic information. The task of the semantic analysis is to create instances in the ontology that contains the world model, i.e. to create those individuals and relations that correspond to the situation described by the text. The knowledge base of the semantic analyser is stored in an OWL ontology. This paper gives an overview of the system, and we discuss those questions of ontology design that require special attention in the context of meaning representation. We also present a software prototype that is based on the method and generates electronic medical records from free-form medical texts.
The singular value decomposition (SVD) in tensors (multidimensional arrays) as an optimization problem. solution via genetic algorithms and method of Nelder-Mead
Authors: Nikos E. Mastorakis
Venue: Proceedings of the 6th WSEAS International Conference on Systems Theory & Scientific Computation (2006)

In this paper, an attempt to solve the Singular Value Decomposition problem in Tensors (multidimensional arrays) using a computational scheme of Evolutionary Computing (Genetic Algorithms) accompanied by the Nelder-Mead method is proposed.
Local invariant feature detectors: a survey
Authors: Tinne Tuytelaars, Krystian Mikolajczyk
Venue: Foundations and Trends® in Computer Graphics and Vision (2008)

In this survey, we give an overview of invariant interest point detectors, how they evolvd over time, how they work, and what their respective strengths and weaknesses are. We begin with defining the properties of the ideal local feature detector. This is followed by an overview of the literature over the past four decades organized in different categories of feature extraction methods. We then provide a more detailed analysis of a selection of methods which had a particularly significant impact on the research field. We conclude with a summary and promising future research directions.
Power quality disturbance identification using wavelet packet energy entropy and weighted support vector machines
Authors: Guo-Sheng Hu, Feng-Feng Zhu, Zhen Ren
Venue: Expert Systems with Applications: An International Journal (2008)

In this paper, wavelet packet energy entropy and weighted support vector machines are used to automatically detect and classify power quality (PQ) disturbances. Electric power quality is an aspect of power engineering that has been with us since the inception of power systems. The types of concerned disturbances include voltage sags, swells, interruptions. Wavelet packet are utilized to denoise the digital signals, to decompose the signals and then to obtain five common features for the sampling PQ disturbance signals. A weighted support vector machine is designed and trained by 5-dimension feature space points for making a decision regarding the type of the disturbance. Simulation cases illustrate the effectiveness.
Osteochondral defect repair using a novel tissue engineering approach: Sheep model study
Authors: R. M. Pilliar, R. A. Kandel, M. D. Grynpas, P. Zalzal, M. Hurtig
Venue: Technology and Health Care (2007)

Porous calcium polyphosphate (CPP) constructs of desired density were formed by sintering CPP powders. Articular cartilage was formed on these constructs in cell culture over an 8-week period with the resulting cartilage layer forming on the CPP surface and within the near surface pores thereby mechanically anchoring the cartilage to the CPP. The biphasic constructs so formed were implanted in sheep femoral condyle sites and left for short-term periods (3 to 4 months) or longer periods (9 months). Implant fixation within the condyle sites was achieved through bone ingrowth into the inferior CPP pores. The properties and characteristics of the as-in vitro-formed, short- and long-term implanted tissues were compared. The results indicated that such implants might be useful for repair of small subchondral defects.
Turbulent modeling effects on finite volume solution of three dimensional aerated hydraulic jumps using volume of fluid
Authors: Saeed-Reza Sabbagh-Yazdi, Fatemeh Rostami, Nikos E. Mastorakis
Venue: Proceedings of the 12th WSEAS International Conference on Applied Mathematics (2007)

This paper aims at characterizing the turbulent flow in hydraulic jumps. The paper starts by giving briefly insight into the dynamics of the flow and discussing mathematical description of aerated flow as well as the turbulent models which are suitable for numerical solution of hydraulic jump. The numerical models, which include an algorithm for air entrainment, have been implemented in a finite volume flow solver. Numerical simulations undertaken in present three dimensional work use k-ε and RNG turbulent models. Results are compared with observations of mean flow (Chanson & Brattberg 2000 and S. Wu & N. Rajaratnam 1996).
On-line admission control and circuit routing for high performance computing and communication
Authors: B. Awerbuch
Venue: Proceedings of the 35th Annual Symposium on Foundations of Computer Science (1994)

This paper considers the problems of admission control and virtual circuit routing in high performance computing and communication systems. Admission control and virtual circuit routing problems arise in numerous applications, including video-servers, real-lime database servers, and the provision of permanent virtual channel in large-scale communications networks. The paper describes both upper and lower bounds on the competitive ratio of algorithms for admission control and virtual circuit routing in trees, arrays, and hypercubes (the networks most commonly used in conjunction with nigh performance computing and communication). Our results include optimal algorithms for admission control and virtual circuit routing in trees, as well as the first competitive algorithms for these problems on non-tree networks. A key result of our research is the development of on-line algorithms that substantially outperform the greedy-based approaches that are used in practice.
FPGA Based Implementation of Robust Watermarking System
Authors: Hesham Abdel Slam Aly Elzouka
Venue: Proceedings of the Fifth International Conference on Information Technology: New Generations (2008)

The study of communication security includes not just encryption but also traffic security, whose essence lies in hiding information. In the paper we are going to introduce a new approach that enables us to conceal the very existence of the message: The host digital media file will be unchanged, but a key which is based on a seed number will be communicated and generates a sequence of numbers that identifies bits in the host digital media file that contains the secret message. Therefore, no statistical artifacts that would aid anyone trying to crack the code are introduced. However, the limitation of capacity has led us to think about an improved approach which can be achieved through hardware implementation systems on a help of a programmable gate array (FPGA) board.
Towards mining past content of Web pages
Authors: A. Jatowt, K. Tanaka
Venue: The New Review of Hypermedia and Multimedia (2007)

While much attention has recently focused on preserving the past content of the Web, there is still a lack of efficient tools for utilizing data stored in Web archives. Web archives constitute large data sources that could be extensively analysed and mined for knowledge discovery. In this paper, we describe the issues involved with mining Web archive data. We discuss several concepts related to collecting and analysing historical content of Web pages and briefly describe two knowledge discovery tasks-temporal summarization and object history detection.
Operating Rules Classification System of Water Supply Reservoir Based on LCS
Authors: Xiao-lin Wang, Zheng-jie Yin
Venue: Proceedings of the First International Workshop on Knowledge Discovery and Data Mining (2008)

Genetic algorithm-based learning classifier system (LCS) is a massively parallel, message-passing and rule-based machine learning system. But its potential self-adaptive learning capability has not been paid enough attention in reservoir operation research. In this paper, an operating rule classification system based on LCS , which learns through credit assignment (the bucket brigade algorithm) and rule discovery(the genetic algorithm), is established to extract water-supply reservoir operating rules. The proposed system acquires the online identification rate 95% for training samples and offline rate 85% for testing samples in a case study, and further discussions are made about the impacts on the performances or behaviors of the rule classification system from three aspects of obtained rules, training or testing samples and the comparisons between the rule classification system and the artificial neural network (ANN). The results indicate the learning classifier system is feasible and effective for the system to obtain the reservoir supply operating rules.
A neural network-based approach for optimising rubber extrusion lines
Authors: A. González Marcos, A. V. Pernía Espinoza, F. Alba Elías, A. García Forcada
Venue: International Journal of Computer Integrated Manufacturing (2007)

The current study shows how data mining and artificial intelligence techniques can be used to introduce improvements in the rubber extrusion production process. One of the keys for planning manufacturing values is prior knowledge of the properties of the material to be extruded. At present, such information is obtained through laboratory trials performed on samples taken off line after the elastomers have been manufactured, with the subsequent cost and delays. In view of these problems, the present study proposes a neural model capable of predicting the characteristics of rubber from the composition of the mixture and the mixing conditions, without having to wait for laboratory results, thus guaranteeing the traceability of the product in the process and the values according to their specific characteristics and also achieving a reduction in costs deriving from smaller amounts of discarded material during the performance of the tests, etc.
Neural Network Control for Tele-rehabilitation Robot based on Variable Gain
Authors: Guo Xiaobo, Song Aiguo, Zhai Yan
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 02 (2008)

The patient’s muscle spasm can cause the tele-rehabilitation robot system with force feedback to become instable and result in the slave unsmoothness of movement, which make the physical rehabilitative exercise inefficient during the tele-rehabilitative training. In order to guarantee the stability and reduce its fluctuation of the speed, a new method based on variable gain with back propagation neural network control was brought forward. With neural network adapting the control gains, not only the stability was guaranteed, but also the slave speed unsmoothness was lessened. The system can be used by sorts of rehabilitants and exhibits strong robustness. The simulation results demonstrate that this method is much more stable and smooth than that of the traditional control.
Enhanced direct torque control using a three-level voltage source Inverter
Authors: R. Zaimeddine, E. M. Berkouk
Venue: Proceedings of the 9th WSEAS International Conference on Systems (2005)

The object of this paper is to study a new control structure for sensorless induction machine dedicated to electrical drives using a three-level voltage source inverter (VSI). The output voltages of the three-level VSI can be represented by four groups : the zero voltage vectors, the small voltage vectors, the middle voltage vectors and the large voltage vectors in (d, q) plane. Then, the amplitude and the rotating velocity of the flux vector can be controlled freely. Both fast torque and optimal switching logic can be obtained. The selection is based on the value of the stator flux and the torque. Both approaches are simulated for a induction motor. The results obtained show superior performances over the conventional DTC one without need to any mechanical sensor.
Numerical solution of coupled nonlinear Schrödinger equation by Galerkin method
Authors: M. S. Ismail
Venue: Mathematics and Computers in Simulation (2008)

The coupled nonlinear Schrodinger equation models several interesting physical phenomena presents a model equation for optical fiber with linear birefringence. In this paper we derive a finite element scheme to solve this equation, we test this method for stability and accuracy, many numerical tests have been conducted. The scheme is quite accurate and describe the interaction picture clearly.
Hardware Implementation of ADABOOST ALGORITHM and Verification
Authors: Yuehua Shi, Feng Zhao, Zhong Zhang
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

Adaboost algorithm is difficult to implement on embedded platform for real-time face detection by software due to its high computation load and data throughput. This article presents a cell array architecture using parallel technology. Detection procedure can be greatly speeded up with its multipipeline. Besides it makes use of the continuity of image data to decrease the accesses to RAM. This article uses Electronic System Level (ESL) tools to develop and simulate a cycle-accurate model of the cell array architecture. The result shows that cell array architecture with 200MHz clock can process 12 million HAAR features per second and detect faces on a 176*144 image at the frame rate of 103 frames per second, which is 14 times speedup compared with software implementation.
Rate-Distortion Functions for Nonstationary Gaussian Autoregressive Processes
Authors: Robert M. Gray, Takeshi Hashimoto
Venue: Proceedings of the Data Compression Conference (2008)

The Shannon rate-distortion function R(D) of a random process provides a lower bound to the minimal average distortion given a constraint on the average rate. When a positive source coding theorem with a fidelity criterion applies,the lower bound is achievable in the limit of large block length and hence R(D) characterizes the optimal performance for source cording or lossy data compression. The source coding theorem for possibly nonstationary Gaussian autoregressive sources was established over three decades ago, but two apparently different formulas for R(D) have appeared in the literature, resulting in long standing confusion about which is correct. There has also been related confusion about the asymptotic eigenvalue distributions of the inverse covariance matrices of such processes. We here establish the equality of the two formulas under fairly general conditions and clarify the confusion regarding asymptotic eigenvalue distributions.
Scheduling real-time multi-item requests in wireless on-demand broadcast networks
Authors: Jun Chen, Victor C. S. Lee, Edward Chan
Venue: Proceedings of the 4th international conference on mobile technology, applications, and systems and the 1st international symposium on Computer human interaction in mobile technology (2007)

On-demand broadcast is an effective data dissemination approach for mobile computing and wireless communication. Previous studies on real-time data scheduling in on-demand broadcast focus on single item requests. With rapid growth of time-critical information dissemination services in emerging applications, there is an increasing need for systems to support real-time multi-item requests. However, we observe that scheduling algorithms for single item requests are unable to manage multi-item requests efficiently. In this paper we study the problem arising in on-demand broadcast with time-critical multi-item requests and propose an innovative algorithm that integrates both request and data scheduling. The performance of our simulation shows that the new algorithm is superior to the classical algorithms designed for single item requests. Our algorithm not only reduces deadline miss rate of requests, but also saves broadcast channel bandwidth.
A Group Key Management Scheme with Revocation and Loss-tolerance Capability for Wireless Sensor Networks
Authors: Linchun Li, Jianhua Li, Yue Wu, Ping Yi
Venue: Proceedings of the 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications (2008)

In this paper, we propose a new group key management scheme for wireless sensor networks in terms of the unreliable wireless channel and unsafe environment. Our proposed scheme implements node revocation through a broadcast polynomial to counteract the node compromise attack and inherits the idea of loss tolerance in LiSP to provide a reliable communication. The analysis shows that the proposed scheme can efficiently revoke the compromised sensor nodes, implicitly authenticate the updated group keys and tolerate the key-update message loss under the unreliable wireless communication channel.
An Entropy Based Algorithm to Find Critical Traffic Matrices
Authors: Hong Wang, Zhenhu Gong, Zexin Lu, Jinshu Su, Sudan Li
Venue: Proceedings of the Seventh International Conference on Networking (2008)

The entropy is a measure of diversity and homogeneity of one microstate in thermodynamic, which reflects the probably distribution of one microstate of the system. A traffic matrix has tremendous potential utility for many IP network engineering applications [1,2]. In practical networking applications, dealing with thousands of measured traffic matrices is often inconvenient. This seriously limits the applicability of traffic matrices. So it is highly desirable to be able to extract a small number of “critical” traffic matrices [3]. We study the problem of Critical Traffic Matrices Selection (CTMS) in this paper. We developed an approximation algorithm called MinMat which preselects a group of matrices as critical matrix candidates based on entropy analysis. We evaluated MinMat by a large collection of real traffic matrices collected in campus network and Abilene network [4]. Our results demonstrated that MinMat algorithm are effective than K-means, Hierarchical Agglomeration and by simulating on totem [5] we concluded that a small number of critical traffic matrices suffice to yield satisfactory performance.
Extended color gamut and adaptive pixel resolution with the immersive laser projection system Elbe Dom
Authors: Wolfram Schoor, Steffen Masik, Rüdiger Mecke, Gerhard Müller, Michael Schenk, Andreas Deter
Venue: Proceedings of the 2008 workshop on Immersive projection technologies/Emerging display technologiges (2008)

The immersive visualization of virtual interactive environments presents an immense challenge to current representation techniques, especially to applications with the demand of realistic visualizations. This paper presents a novel solution to meet the fundamentally increasing demand for greater degrees of realism and immersion in representation techniques: Full 360 degree continuous projection in the Elbe Dom with an extended color gamut.
Graphs without isometric rays and invariant subgraph properties, I
Authors: Norbert Polat
Venue: Journal of Graph Theory (1998)

A ray of a graph G is isometric if every path in R is a shortest path in G. A vertex x of G geodesically dominates a subset A of V(G) if, for every finite S &sube; V(G - x), there exists an element a of A - {x} such that the interval (set of vertices of all shortest paths) between x and a is disjoint from S. A set A &sube; V(G) is geodesically closed if it contains all vertices which geodesically dominate A. These geodesically closed sets define a topology, called the geodesic topology, on V(G). We prove that a connected graph G has no isometric rays if and only if the set V(G) endowed with the geodesic topology is compact, or equivalently if and only if the vertex set of every ray in G is geodesically dominated. We prove different invariant subgraph properties for graphs containing no isometric rays. In particular we show that every self-contraction (map which preserves or contracts the edges) of a chordal graph G stabilizes a non-empty finite simplex (complete graph) if and only if G is connected and contains no isometric rays and no infinite simplices. &copy; 1998 John Wiley Sons, Inc. J Graph Theory 27: 99109, 1998
An efficient hash-based algorithm for minimal k-anonymity
Authors: Xiaoxun Sun, Min Li, Hua Wang, Ashley Plank
Venue: Proceedings of the thirty-first Australasian conference on Computer science - Volume 74 (2008)

A number of organizations publish microdata for purposes such as public health and demographic research. Although attributes of microdata that clearly identify individuals, such as name and medical care card number, are generally removed, these databases can sometimes be joined with other public databases on attributes such as Zip code, Gender and Age to re-identify individuals who were supposed to remain anonymous. "Linking" attacks are made easier by the availability of other complementary databases over the Internet. k-anonymity is a technique that prevents "linking" attacks by generalizing and/or suppressing portions of the released microdata so that no individual can be uniquely distinguished from a group of size k. In this paper, we investigate a practical model of k-anonymity, called full-domain generalization. We examine the issue of computing minimal k-anonymous table based on the definition of minimality described by Samarati. We introduce the hash-based technique previously used in mining associate rules and present an efficient hash-based algorithm to find the minimal k-anonymous table, which improves the previous binary search algorithm first proposed by Samarati.
Intelligent control for permanent magnet synchronous motor with improved particle swarm optimization
Authors: Song Zhengqiang, Hou Zhijian, Jiang Chuanwen
Venue: Proceedings of the 5th WSEAS/IASME International Conference on Systems Theory and Scientific Computation (2005)

This paper presents a new intelligent controller for a permanent-magnet synchronous machine in a HEV (hybrid-electric vehicle) application. IPSO (Improved Particle Swarm Optimization) will be used to optimize three proportional parameters ka, kb, ku of FLC (Fuzzy Logical Controller) online increasing the robustness of overall system. Finally, the overall system will be simulated under various operating conditions. The use of IPSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and intensitive to load variation. The system is tested using a step change signal of load. The simulation results show good dynamic response with fast recovery time.