ppxscal/embedding_network huggingface dataset:
Surface Analysis Methods
Authors: James Beck, Rida Farouki, John Hinds
Venue: IEEE Computer Graphics and Applications (1986)

Parametric polynomial surfaces defined to satisfy given interpolatory or boundary constraints often suffer extraneous undesired features because of poor control over their many degrees of freedom. Current techniques for detecting and remedying such unexpected surface characteristics are primitive and inadequate. This article describes several surface analysis tools useful in detecting such anomalous surface features. These include standard techniques such as contouring and high-resolution shaded image displays based on direct ray tracing, and some novel methods such as maps of the principal curvatures, the integration of lines of curvature to show the variation ofthe principal directions, and the determination of geodesic paths on the surface.
A Data Classifier Based on TOPSIS Method
Authors: Wei Jiang, Xiaoqiang Zhong
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

As a multiple criteria decision making (MCMD) tech- nique, the technique for order preference by similarity to ideal solution(TOPSIS) traditionally has been applied in multiple criteria decision analysis. Based on D.Wu's data mining model, the TOPSIS model presented in this paper has improved from two aspects. Firstly, it extents to deal with both crisp and fuzzy data; Secondly, in order to re- ally following automatic machine learning principles to the largest extent, the weights must be immune to the subjective element and the data noise. Here, the weights are obtained from data sets based on support vector regression(SVR), which is a more robust and efficient data regression method than the traditional data regression method. Thus the pro- posed model can provide additional efficient tool for com- parative analysis of data sets. We apply it in supply chain complexity evaluation, and simulation is used to validate the proposed models.
Pulse Input Asynchronous Sequential Circuits
Authors: G. Frosini, G. B. Gerace
Venue: IEEE Transactions on Computers (1971)

Traditionally, synchronous sequential circuits are considered controlled by input pulses, and asynchronous sequential circuits by input levels. The aim of this note is to study the general properties of a class of asynchronous circuits with some inputs that can be thought of as driven by "pulses." The synthesis process and the internal structure of these circuits, called pulse input asynchronous sequential circuits (PA circuits), are investigated, and they are compared with pulse input synchronous circuits and with level input asynchronous circuits. Procedures are described to transform any flow table describing a synchronous circuit into a flow table describing an equivalent PA circuit, and to realize any normal mode asynchronous circuit by a PA circuit. Specific techniques for PA circuit state reduction and PA circuit state assignment are described in other papers.
Production Yield and Self-Configuration in the Future Massively Defective Nanochips
Authors: Piotr Zajac, Jacques Henri Collet
Venue: Proceedings of the 22nd IEEE International Symposium on Defect and Fault-Tolerance in VLSI Systems (2007)

We address two problems in this work, namely, 1) the resilience challenge in the future chips made up of massively defective nanoelements and organized in replicative multicore architectures and 2) the issue of preserving the production yield. Our main suggestion is that the chip should be self-configuring at the architectural level, enabling with almost no external control mechanisms, core mutual-test to isolate the defective core and self-configuration of communications to discover the routes in the defective network. Our contribution is a systematic study of the dependence of the production yield versus the core failure probability (possibly as high as 0.4) in several networks with different node connectivity ranging from 3 to 5. The result is obtained in terms of a probabilistic metrics to warrant that a minimal fraction of nodes can be contacted by the input-output port for participating to the processing.
Program Fragmentation as a Metamorphic Software Protection
Authors: Bobby D. Birrer, Richard A. Raines, Rusty O. Baldwin, Barry E. Mullins, Robert W. Bennington
Venue: Proceedings of the Third International Symposium on Information Assurance and Security (2007)

Unauthorized reverse-engineering of programs and algorithms is a major problem for the software industry. Reverse-engineers search for security holes in the program to exploit or try to steal competitors' vital algorithms. To discourage reverse-engineering, developers use a variety of static software protections to obfuscate their programs. Metamorphic software protections add another layer of protection to traditional static obfuscation techniques, forcing reverse-engineers to adjust their attacks as the protection changes. Program fragmentation combines two obfuscation techniques, outlining and obfuscated jump tables, into a new, metamorphic protection. Sections of code are removed from the main program flow and placed throughout memory, reducing the program's locality. These fragments move and are called using obfuscated jump tables, making program execution difficult to follow. This research assesses the performance overhead of a program fragmentation engine and provides analysis of its effectiveness against reverse-engineering techniques. Results show that program fragmentation has low overhead and is an effective technique to complicate disassembly of programs using two common disassembler/debugger tools.
Optimally regularized adaptive filtering algorithms for room acoustic signal enhancement
Authors: Toon van Waterschoot, Geert Rombouts, Marc Moonen
Venue: Signal Processing (2008)

In many room acoustic signal processing applications, a room impulse response identification is needed to eliminate undesired effects such as echo, feedback, or reverberation. This is typically done using an adaptive filter driven by a speech or audio input signal. However, such signals exhibit poor excitation properties, which cause standard adaptive filtering algorithms to be very sensitive to disturbing signals, especially in the underdetermined case. A popular remedy is regularization, which is usually implemented with a scaled identity regularization matrix. This type of regularization is governed by a single regularization parameter, the value of which is often chosen in an arbitrary way. We propose to regularize the adaptive filter using a non-identity regularization matrix, in which prior knowledge on the unknown room impulse response may be incorporated. When knowledge of the disturbing signal is also used to add prefiltering and weighting in the adaptation, a new family of regularized adaptive filtering algorithms is obtained, which is shown to be optimal in a mean square error sense. Existing regularized algorithms can then be obtained as special cases, assuming limited or no prior knowledge is available. When combined with a recently proposed method of extracting prior knowledge from the acoustic setup, our algorithms exhibit superior convergence behaviour compared to existing algorithms in different simulation scenarios, while the additional computational cost is small.
Displays on Display
Authors: F. Crow, C. Csuri
Venue: IEEE Computer Graphics and Applications (1982)

"Vases with shadow." Produced by Hsuen-Chung Ho of the Computer Graphics Research Group at Ohio State University, the image was generated by a combination of a scanline conversion algorithm (on the shadow) and a depth priority algorithm (on the vases).
Distributed Parallel Algorithm For Nonlinear OptimizationWithout Derivatives
Authors: Congying Han, Guoping He, Huanqing Cui, Xuping Zhang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02 (2007)

This paper formulates a pattern search method for non-linear programming. A distributed parallel algorithm is given based on the pattern search method by distributing the direction to every processor. Promising experimental results of the distributed parallel pattern method are obtained on a sixteen-machines cluster system by running the environment MPI.
Kavosh: An Intelligent Neuro-Fuzzy Search Engine
Authors: Amin Mibani Fard, Reza Ghaemi, Muhammad R. Akbarzadeh T., Hoda Akbari
Venue: Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications (2007)

In this paper we propose a neuro-fuzzy architecture for Web content taxonomy using hybrid of Adaptive Resonance Theory (ART) neural networks and fuzzy logic concept. The search engine called Kavosh1 is equipped with unsupervised neural networks for dynamic data clustering. This model was designed for retrieving images without metadata and in estimating resemblance of multimedia documents; however, in this work only text mining method is implemented. Results show noticeable average precision and recall over search results.
Region-by-region modeling of laminated composite plates
Authors: P. M. Mohite, C. S. Upadhyay
Venue: Computers and Structures (2007)

Several plate models have been proposed in the literature for the analysis of laminated plates. These are based either on an equivalent through-thickness formulation or a layerwise formulation. It is shown in the literature that while the equivalent models are economical, the layerwise models are expensive but are also more accurate, especially with respect to the transverse stresses. Generally, the same model is used throughout the domain. The current study addresses the issue of economical and accurate computation of local stresses, strains and displacements (as well as global quantities) using combinations of layerwise, equivalent or intermediate models in various regions of the domain. A region-by-region modeling strategy is presented for a chosen general family of equivalent, intermediate and layerwise models. The proposed strategy allows the user to put any model (of any order in the thickness direction) in any desired region of interest. The effectiveness of the strategy is demonstrated through numerical examples. It is shown that this approach can significantly reduce computational cost and can also lead to good resolution of the local stress and displacement fields for domains with unsymmetric laminae, cut-outs, local damage, corner edges, sudden transition of boundary conditions and material.
Face Recognition Based on WT, FastICA and RBF Neural Network
Authors: Ming Li, Fuwen Wu, Xueyan Liu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 02 (2007)

Face is a complex multidimensional visual model and it is difficult to develop a computational model for recognition. A novel approach is presented to face recognition in this paper, which uses wavelet transform (WT), fast independent component analysis (FastICA) and radial basis function (RBF) neural networks. Firstly, low frequency subband images are extracted from original face image by 2D wavelet transform. Secondly, for reducing computational cost and converges difficultly, improved FastICA is applied to extract features from the low frequency subband image. Then, the extracted features are classified through RBF neural networks. Lastly, the proposed algorithm is tested on the ORL face database and result shows that it has good performance both in terms of recognition accuracy and robustness.
Self-optimizing block transfer in web service grids
Authors: Anastasios Gounaris, Christos Yfoulis, Rizos Sakellariou, Marios D. Dikaiakos
Venue: Proceedings of the 9th annual ACM international workshop on Web information and data management (2007)

Nowadays, Web Services (WSs) play an increasingly important role in Web data management solutions, since they offer a practical solution for accessing and manipulating data sources spanning administrative domains. Nevertheless, they are notoriously slow and transferring large data volumes across WSs becomes the main bottleneck in such WS-based applications. This paper deals with the problem of minimizing at runtime, in a self-managing way, the datatransfer cost of a WS encapsulating a data source. To reducethe transfer cost, the data volume is typically divided intoblocks. In this case, response time exhibits a quadratic-like, non-linear behavior with regards to the block size; as such, minimizing the transfer cost entails finding the optimum block size. This situation is encountered in several systems, such as WS Management Systems (WSMSs) for DBMS-like data management over wide area service-based networks, and WSs for accessing and integrating traditional DBMSs. The main challenges in this problem include (i) the unavailability of an analytical model; (ii) the presence of noise, which incurs local minima; (iii) the volatility of the environment, which results into a moving optimum operating point; and (iv) the requirements for fast convergence to the optimal size of the request from the side of the client rather than of the server, and for low overshooting. This paper presents two novel solutions for detecting the optimum block size during data transmission, thus yielding lower response times. The solutions are inspired by the broader areas of runtime optimization and switching extremum control. They incorporate heuristics to avoid local optimal points, and address all the afore-mentioned challenges. The effectiveness andeffciency of the solutions is verified through empirical evaluation in real cases.
RIG, Rochester's Intelligent Gateway: System Overview
Authors: J. E. Ball
Venue: IEEE Transactions on Software Engineering (1976)

Rochester's Intelligent Gateway (RIG) system provides convenient access to a wide range of computing facilities. The system includes five large minicomputers in a very fast internal network, disk and tape storage, a printer/plotter and a number of display terminals. These are connected to larger campus machines (IBM 360/65 and DEC KL10) and to the ARPANET. The operating system and other software support for such a system present some interesting design problems. This paper contains a high-level technical discussion of the software designs, many of which will be treated in more detail in subsequent reports.
Fault Tolerance-Genetic Algorithm for Grid Task Scheduling using Check Point
Authors: S. Baghavathi Priya, M. Prakash, K. K. Dhawan
Venue: Proceedings of the Sixth International Conference on Grid and Cooperative Computing (2007)

One motivation of Grid computing is to aggregate the power of widely distributed resources, and provide non-trivial services to users. To achieve this goal, an efficient Grid fault tolerance system is an essential part of the grid. Rather than covering the whole Grid fault tolerance area, this survey provides a review of the subject mainly from the perspective of check point. In this review the challenges for fault tolerance are identified. In Grid environments, execution failures can occur for various reasons such as network failure, overloaded resource conditions, or non-availability of required software components. Thus, fault-tolerant systems should be able to identify and handle failures and support reliable execution in the presence of concurrency and failures In scheduling a large number of user jobs for parallel execution on an open-resource Grid system, the jobs are subject to system failures or delays caused by infected hardware, software vulnerability, and distrusted security policy. In this paper we propose a task level fault tolerance. Task-level techniques mask the effects of the execution failure of tasks. Four task level techniques are Retry, alternate resource, Check point and Replication. Check point technique strategy achieves optimal load balance across different grid sites These Fault tolerance task level techniques can upgrade grid performance significantly at only a moderate in extra resources or scheduling delays in a risky Grid computing environment.
The Application of Neuro-FDT in Urban Short-Term Traffic Flow Prediction
Authors: Jin Hongxia
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

Today, the problems are more and more serious such as urban traffic accident, traffic jam, environment pollution and energy consume etc. Intelligence transportation system is one of valid methods to resolve the problem of road traffic jam and reduce traffic accident, etc. Traffic control and inducement system are the constitution part of the intelligence traffic system. Moreover, how to finish the short-term traffic forecast is becoming premise and key of achieving traffic control and inducement. Therefore, to build up a dependable and accurate forecast model for short-time transportation flows is a popular and core topic in the ITS research realm. In this paper, a new forecast method for city short-term transportation flows is presented. The model based on Neuro-fuzzy decision tree modeling method is different from traditional modeling methods. Neural networks-fuzzy decision tree improves FDT's classification accuracy and extracts more accuracy human interpretable classification rules. The result of the positive research indicated that this method is very valid for short-term transport flows prediction and it will have a good application prospect in this area.
A model for computing and energy dissipation of molecular QCA devices and circuits
Authors: Xiaojun Ma, Jing Huang, Fabrizio Lombardi
Venue: ACM Journal on Emerging Technologies in Computing Systems (JETC) (2008)

Quantum-dot Cellular Automata is an emerging technology that offers significant improvements over CMOS. Recently QCA has been advocated as a technology for implementing reversible computing. However, existing tools for QCA design and evaluation have limited capabilities. This paper presents a new mechanical-based model for computing in QCA. By avoiding a full quantum-thermodynamical calculation, it offers a classical view of the principles of QCA operation and can be used in evaluating energy dissipation for reversible computing. The proposed model is mechanically based and is applicable to six-dot (neutrally charged) QCA cells for molecular implementation. The mechanical model consists of a sleeve of changing shape; four electrically charged balls are connected by a stick that rotates around an axle in the sleeve. The sleeve acts as a clocking unit, while the angular position of the stick within the changing shape of the sleeve, identifies the phase for quasi-adiabatic switching. A thermodynamic analysis of the proposed model is presented. The behaviors of various QCA basic devices and circuits are analyzed using the proposed model. It is shown that the proposed model is capable of evaluating the energy consumption for reversible computing at device and circuit levels for molecular QCA implementation. As applicable to QCA, two clocking schemes are also analyzed for energy dissipation and performance (in terms of number of clocking zones).
A genetic approach for efficient outlier detection in projected space
Authors: Sanghamitra Bandyopadhyay, Santanu Santra
Venue: Pattern Recognition (2008)

In this paper we present a genetic solution to the outlier detection problem. The essential idea behind this technique is to define outliers by examining those projections of the data, along which the data points have abnormal or inconsistent behavior (defined in terms of their sparsity values). We use a partitioning method to divide the data set into groups such that all the objects in a group can be considered to behave similarly. We then identify those groups that contain outliers. The algorithm assigns an 'outlier-ness' value that gives a relative measure of how strong an outlier group is. An evolutionary search computation technique is employed for determining those projections of the data over which the outliers can be identified. A new data structure, called the grid count tree (GCT), is used for efficient computation of the sparsity factor. GCT helps in quickly determining the number of points within any grid defined over the projected space and hence facilitates faster computation of the sparsity factor. A new crossover is also defined for this purpose. The proposed method is applicable for both numeric and categorical attributes. The search complexity of the GCT traversal algorithm is provided. Results are demonstrated for both artificial and real life data sets including four gene expression data sets.
Evaluating the Internal Consistency of the Base Questions in the Express Process Appraisal
Authors: N. G. Lester, F. G. Wilkie, D. McFall, M. P. Ware
Venue: Proceedings of the 33rd EUROMICRO Conference on Software Engineering and Advanced Applications (2007)

This paper describes a study to assess the reliability of a CMMI® ARC 1.1 Class C process appraisal method called Express Process Appraisal (EPA). The EPA was developed by the Centre for Software Process Technologies to address the process improvement appraisal needs of small to medium sized software development organisations in Northern Ireland. The results from a series of appraisals are subjected to Cronbach's Alpha Coefficient analysis in order to determine the internal consistency of the question set used by the EPA. This approach identified issues in the questions associated with two process areas. This paper details these issues, the data, and analysis method used, as well as providing a discussion into possible reasons behind the identified issues.
The internet-based laboratory system for technical education
Authors: Durmus Karayel, Sinan Serdar Ozkan, Adem Caliskan, Ibrahim Ozsert
Venue: Proceedings of the sixth conference on IASTED International Conference Web-Based Education - Volume 2 (2007)

This study explains an Internet - Based Mechatronic Laboratory which has been setup as a solution for problems encountered in the practical training of technical education. The study consists of five sections. In the first section, the problem is defined and the earlier studies about this subject are presented. The second section explains the Internet - Based Technical Education and the effects of the web based laboratory on education system. In the third section, the system architecture which consists of mechatronic system, server, user units and simulation interface is analyzed generally. After that, all of the modules are explained into detail. In the forty sections, the working principle of the system is presented together examples. In the last section, the study is evaluated and its contributions on education and training are explained.