ppxscal/embedding_network huggingface dataset:
Fingerprint Matching Using Invariant Moment Features
Authors: Ju Cheng Yang, Jin Wook Shin, Dong Sun Park
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

A method for fingerprint matching using invariant moment features is proposed. The fingerprint image is first preprocessed to enhance the original image by the Short Time Fourier Transform (STFT) analysis. Then, a set of seven invariant moment features is extracted to represent the fingerprint image from a Region of Interest (ROI) based on the reference point of the enhanced fingerprint image. The reference point is determined by the complex filters method. Finally, a Back Propagation Neural Network (BPNN) is trained with the features for matching. Experimental results show the proposed method has better performance with higher accuracy and faster speed comparing to the traditional Gabor feature-based fingerCode method.
Investigation of Dynamic Reconstruction Methods for Remote Sensing Image Pyramids Based on Multi-resolution Characteristic of Wavelet Transformation
Authors: Jingyu Yang, Song Ji, Yongsheng Zhang, Hui Gong, Zhaohua Liu, Jianping Guo
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 1 - Volume 01 (2008)

Base on multi-resolution characteristic of wavelet transformation, a dynamic reconstruction method of image pyramids for remote sensing imagery is proposed in this paper. The method can solve the data redundant problems caused by traditional reconstruction methods, for which the correlation characteristic of the data between different pyramid layers is not used. It can effectively reduce the amount of data storage and network data transmission, and form a stream data transferring mode. Therefore, it is fairly appropriate for the network distributing of remote sensing imagery. Systematic experiments were done for this method. And compared with traditional methods, the response efficiency is improved significantly, which verifies the feasibility and superiority of the method in the storage and transmission of remote sensing imagery.
Quantum-Behaved Particle Swarm Optimization with Binary Encoding
Authors: Jun Sun, Wenbo Xu, Wei Fang, Zhilei Chai
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

The purpose of this paper is to generalize Quantum-behaved Particle Swarm Optimization (QPSO) Algorithm to discrete binary search space. To design Binary QPSO (BQPSO), we redefine the position vector and the distance between two positions, and adjust the iterative equations of QPSO to binary search space. The operations designed for BQPSO are far different from those in BPSO, but somewhat like those in Genetic Algorithms (GAs). Therefore, BQPSO integrates strongpoint of GA with the features of PSO, which make it able to find out the global optimum of the problem more efficiently than BPSO, as shown by the experiment results of BQPSO and BPSO on De Jong's five test functions.
Portable and Mobile Systems in Assistive Technology
Authors: R. Manduchi, J. Coughlan
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

Computing power, communications and internet access are becoming increasingly untethered from the desktop and moving to the realm of portable, wireless technology. Devices such as mobile (cell) phones and PDAs (personal digital assistants) have become affordable and ubiquitous, and offer not only substantial computational power but also telephone and internet access, as well as a variety of sensors such as cameras, GPS and RFID readers. While the overwhelming majority of such devices are being marketed primarily to able-bodied users (primarily young, tech-savvy people without obvious disabilities), there is enormous potential to harness their capabilities for use in assistive technology. As of yet, however, this potential remains largely untapped, with very few commercially available systems of this type.
On the Evaluation of Large and Sparse Graph Reachability Queries
Authors: Yangjun Chen
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

Given a directed graph G with n nodes and e edges, to check whether a node v is reachable from another node u through a path is often required. Such a problem is fundamental to numerous applications, including geographic navigation, Internet routing, ontology queries based on RDF/OWL, and metabolic network, as well as XML indexing. Among them, some involve huge but sparse graphs and require fast answering of reachability queries. In this paper, we propose a novel method called core labeling to handle reachability queries for massive, sparse graphs. The goal is to optimize both query time and labeling time. Our method consists of two schemes: Core-I and Core-II. For the Core-I labeling scheme, both the time and space requirements are bounded by O(n + e + s·b), where s is the number of the start nodes of all non-tree edges (edges that do not appear in the spanning tree of G); andb is the width of a subgraph of G. The size of that subgraph is bounded by O(t), where t is the number of all the non-tree edges. The query time of Core-I is bounded by O(logb). The Core-II labeling scheme has constant query time, but the labeling time is increased to O(n + e + s·b·logb).
Proving Bounds on Real-Valued Functions with Computations
Authors: Guillaume Melquiond
Venue: Proceedings of the 4th international joint conference on Automated Reasoning (2008)

Interval-based methods are commonly used for computing numerical bounds on expressions and proving inequalities on real numbers. Yet they are hardly used in proof assistants, as the large amount of numerical computations they require keeps them out of reach from deductive proof processes. However, evaluating programs inside proofs is an efficient way for reducing the size of proof terms while performing numerous computations. This work shows how programs combining automatic differentiation with floating-point and interval arithmetic can be used as efficient yet certified solvers. They have been implemented in a library for the Coq proof system. This library provides tactics for proving inequalities on real-valued expressions.
P-IDC: Information Security and Consideration in Building Internet Data Centers for Pervasive Environment
Authors: Jae-Min Yang, Jong-Geun Kim, Jong-In Im
Venue: Proceedings of the APWeb/WAIM 2007 DBMAN, WebETrends, PAIS and ASWAN international workshops on Advances in Web and Network Technologies, and Information Management (2007)

Internet Data Center (IDC) offers servers and networks, and manages all contents in an enterprise. All servers should run 24 hours at no failure because the servers are very sensitive to keep their business continues. IDC has launched and operated already in many countries. IDC offers the enterprises to achieve their business goals and provides faster and safer service by converging all data services to one place for physical handling. In this paper, we propose Pervasive Internet Data Center (P-IDC) for preservation of high security on confidential information for large enterprises. The proposed model is appropriate for an enterprise which plans to build IDC and has many family companies in different business field. Definitely P-IDC should provide the solution to the problems ordinary IDC have.
Efficient Approximate Mining of Frequent Patterns over Transactional Data Streams
Authors: Willie Ng, Manoranjan Dash
Venue: Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery (2008)

We investigate the problem of finding frequent patterns in a continuous stream of transactions. It is recognized that the approximate solutions are usually sufficient and many existing literature explicitly trade off accuracy for speed where the quality of the final approximate counts are governed by an error parameter, ¿. However, the quantification of ¿ is never simple. By setting a small ¿, we achieve good accuracy but suffer in terms of efficiency. A bigger ¿ improves the efficiency but seriously degrades the mining accuracy. To alleviate this problem, we offer an alternative which allows user to customize a set of error bounds based on his requirement. Our experimental studies show that the proposed algorithm has high precision, requires less memory and consumes less CPU time.
Model-Based Motion Capture for Crash Test Video Analysis
Authors: Juergen Gall, Bodo Rosenhahn, Stefan Gehrig, Hans-Peter Seidel
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

In this work, we propose a model-based approach for estimating the 3D position and orientation of a dummy's head for crash test video analysis. Instead of relying on photogrammetric markers which provide only sparse 3D measurements, features present in the texture of the object's surface are used for tracking. In order to handle also small and partially occluded objects, the concepts of region-based and patch-based matching are combined for pose estimation. For a qualitative and quantitative evaluation, the proposed method is applied to two multi-view crash test videos captured by high-speed cameras.
Efficient Training of RBF Networks Via the BYY Automated Model Selection Learning Algorithms
Authors: Kai Huang, Le Wang, Jinwen Ma
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

Radial basis function (RBF) networks of Gaussian activation functions have been widely used in many applications due to its simplicity, robustness, good approximation and generalization ability, etc.. However, the training of such a RBF network is still a rather difficult task in the general case and the main crucial problem is how to select the number and locations of the hidden units appropriately. In this paper, we utilize a new kind of Bayesian Ying-Yang (BYY) automated model selection (AMS) learning algorithm to select the appropriate number and initial locations of the hidden units or Gaussians automatically for an input data set. It is demonstrated well by the experiments that this BYY-AMS training method is quite efficient and considerably outperforms the typical existing training methods on the training of RBF networks for both clustering analysis and nonlinear time series prediction.
News@hand: A Semantic Web Approach to Recommending News
Authors: Iván Cantador, Alejandro Bellogín, Pablo Castells
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

We present News@hand, a news recommender system which applies semantic-based technologies to describe and relate news contents and user preferences in order to produce enhanced recommendations. The exploitation of conceptual information describing contents and user profiles, along with the capability of inferring knowledge from the semantic relations defined in the ontologies, enabling different content-based collaborative recommendation models, are the key distinctive aspects of the system. The multi-domain portability, the multi-media source applicability, and addressing of some limitations of current recommender systems are the main benefits of our proposed approach.
Brief paper: On input-to-state stability of systems with time-delay: A matrix inequalities approach
Authors: Emilia Fridman, Michel Dambrine, Nima Yeganefar
Venue: Automatica (Journal of IFAC) (2008)

Nonlinear matrix inequalities (NLMIs) approach, which is known to be efficient for stability and L"2-gain analysis, is extended to input-to-state stability (ISS). We first obtain sufficient conditions for ISS of systems with time-varying delays via Lyapunov-Krasovskii method. NLMIs are derived then for a class of systems with delayed state-feedback by using the S-procedure. If NLMIs are feasible for all x, then the results are global. When NLMIs are feasible in a compact set containing the origin, bounds on the initial state and on the disturbance are given, which lead to bounded solutions. The numerical examples of sampled-data quantized stabilization illustrate the efficiency of the method.
Resource Discovery in a Grid System Based on Matchmaking-Routers
Authors: Konstantinos I. Karaoglanoglou, Helen D. Karatza
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

This paper studies the Resource Discovery problem in a Grid system based on Matchmaking-Routers. The proposed framework suggests that a Grid can be seen as an environment comprised by matchmaking-routers and resources. Each matchmaking-router is in charge of its local resources. The goal is to discover the appropriate resource for a specific request and then effectively direct the request to the resource within that environment. Matchmaking-routers are responsible of providing the set of resources that can satisfy a specific request and then directing the request to the resource that is capable of satisfying it.
An Empirical Study Identifying High Perceived Value Practices of CMMI Level 2
Authors: Mahmood Niazi, Muhammad Ali Babar, Suhaimi Ibrahim
Venue: Proceedings of the 9th international conference on Product-Focused Software Process Improvement (2008)

We have conducted face-to-face questionnaire based interview sessions with twenty-three Malaysian software practitioners in order to determine the perceived value associated with the specific practices of "requirements management", "process and product quality assurance" and "configuration management" process areas of CMMI level 2 in the stage representation. The objective of this study is to identify the extent to which a CMMI practice is used in order to develop a finer-grained framework, which encompasses the notion of perceived value within specific practices. This will provide software process improvement (SPI) practitioners with some insight into designing appropriate SPI implementation strategies.We asked practitioners to choose and rank "requirements management", "process and product quality assurance" and "configuration management" practices against the five types of assessments (high, medium, low, zero or do not know). From this, we propose the notion of 'perceived value' associated with each practice. We have identified 'high' and `medium' perceived values CMMI level 2 practices. We have also identified the viewpoints of developers and managers about these practices.
An Improved Laplacian Smoothing Approach for Surface Meshes
Authors: Ligang Chen, Yao Zheng, Jianjun Chen, Yi Liang
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

This paper presents an improved Laplacian smoothing approach (ILSA) to optimize surface meshes while maintaining the essential characteristics of the discrete surfaces. The approach first detects feature nodes of a mesh using a simple method, and then moves its adjustable or free node to a new position, which is found by first computing an optimal displacement of the node and then projecting it back to the original discrete surface. The optimal displacement is initially computed by the ILSA, and then adjusted iteratively by solving a constrained optimization problem with a quadratic penalty approach in order to avoid inverted elements. Several examples are presented to illustrate its capability of improving the quality of triangular surface meshes.
Students' thoughts about the importance and costs of their mobile devices' features and services
Authors: Anastasios A. Economides, Amalia Grousopoulou
Venue: Telematics and Informatics (2009)

In recent years, handheld devices have become one of the fastest growing communication gadgets. Mobile technology is becoming widespread and research in this area is urgently needed. Using a survey instrument, the thoughts of male and female students regarding the importance and costs of mobile devices were investigated. It was found that students tend to consider the following features important: battery life, mp3 player, video camera, photo camera, storage memory, Bluetooth, design and elegance, clock, calendar, organizer and reminder. Also, they are eager to spend an amount of money so as their mobile device to support them. On average, both genders would pay extra money for such features. However, the majority of females think less of the price than males do. On the contrary, most of the respondents do not consider the following important: touch screen, voice commands, chat, teleconference, encryption and cryptography, common use of files, printing. Therefore, they would not spend any money for these features. Interested decision makers would try to increase their interest on such features. Moreover, all respondents appear to own a mobile phone while most of them do not have Internet connection at home. In general, some gender differences are found in the importance and costs of the mobile devices, but they are not statistically significant.
A Privacy Protection Scheme for a Scalable Control Method in Context-Dependent Services
Authors: Rei Yoshida, Rie Shigetomi, Kazuki Yoshizoe, Akira Otsuka, Hideki Imai
Venue: Research in Cryptology: Second Western European Workshop, WEWoRC 2007, Bochum, Germany, July 4-6, 2007, Revised Selected Papers (2008)

Provision of context-dependent services is triggered when the context satisfies an execution condition. To deliver these services, users' contexts have to be determined by terminals such as GPS. However, GPS has efficiency (it must collect as many contexts as possible to provide services appropriately) and privacy problems (all data is concentrated on one place). Previous studies have addressed only either one of the two problems. We propose a scheme that protects users' privacy while maintaining efficiency by using the Randomized Response Technique.
Analysis of Human Brain NMR Spectra in Vivo Using Artificial Neural Networks
Authors: Erik Saudek, Daniel Novák, Dita Wagnerová, Milan Hájek
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

Magnetic resonance has proven to be a successful method of in-vivo imaging. Although MRI can help detect various pathologies, its ability to classify the nature of the pathological tissue is limited. Magnetic resonance spectroscopy allows identifying metabolite content of the tissue and estimating the metabolite concentration. Map of metabolite concentration along with the MR image allows proper classification of many pathologies, for example progressive tumorous tissue identification in brain. Standard methods used to analyze nuclear magnetic resonance spectra such as singular value decomposition or curve fitting algorithms are very time consuming taking several minutes to analyze spectrum from a single voxel. To analyze the spectra from a chemical shift imagine sequence (CSI) in maximal resolution hundreds of spectra need to be processed. The suggested ANN framework proved to be much faster. Networks were trained on the outputs of LCModel curve fitting algorithm. Time needed to process a spectrum from a single voxel was reduced to the order of seconds. The total time needed to analyze a CSI in full resolution (hundreds of spectra) was significantly reduced to 5 minutes.
The Microprocessor Universal Format for Object Modules
Authors: T. Pittman, G. Baldwin
Venue: IEEE Micro (1983)

A universal format for object modules, designed to apply to a variety of microprocessors, permits linking and relocating to be isolated from the specification of target architecture.
Language Extensions in Support of Compiler Parallelization
Authors: Jun Shirako, Hironori Kasahara, Vivek Sarkar
Venue: Languages and Compilers for Parallel Computing: 20th International Workshop, LCPC 2007, Urbana, IL, USA, October 11-13, 2007, Revised Selected Papers (2007)

In this paper, we propose an approach to automatic compiler parallelization based on language extensions that is applicable to a broader range of program structures and application domains than in past work. As a complement to ongoing work on high productivity languages for explicit parallelism, the basic idea in this paper is to make sequential languages more amenable to compiler parallelization by adding enforceable declarations and annotations. Specifically, we propose the addition of annotations and declarations related to multidimensional arrays, points, regions, array views, parameter intents, array and object privatization, pure methods, absence of exceptions, and gather/reduce computations. In many cases, these extensions are also motivated by best practices in software engineering, and can also contribute to performance improvements in sequential code. A detailed case study of the Java Grande Forum benchmark suite illustrates the obstacles to compiler parallelization in current object-oriented languages, and shows that the extensions proposed in this paper can be effective in enabling compiler parallelization. The results in this paper motivate future work on building an automatically parallelizing compiler for the language extensions proposed in this paper.
Keeping Elderly People at Home: A Multi-agent Classification of Monitoring Data
Authors: Ali Rammal, Sylvie Trouilhet
Venue: Proceedings of the 6th international conference on Smart Homes and Health Telematics (2008)

We propose software architecture to monitor elderly people in their own homes. We want to build patterns of monitored people dynamically from data about activity, movements and physiological information. To obtain this macroscopic view, we use a multi-agent method of classification: every agent has a simple skill of classification. They generate partial partitions and cooperate to obtain a set of patterns. The patterns are used at a personal level, for example to raise an alert, but also to evaluate global risks. These data are dynamic; the system has to maintain the built patterns and has to create new patterns. Therefore, the system is adaptive and can be spread on a large scale.
New solutions for a generalized Benjamin-Bona-Mahony-Burgers equation
Authors: Maria S. Bruzon, Maria L. Gandarias
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

In this paper we make a full analysis of the symmetry reductions of a generalized Benjamin-Bona-Mahony- Burgers equation (BBMB) by using the classical Lie method of infinitesimals. The functional forms, for which the BBMB equation can be reduced to ordinary differential equations by classical Lie symmetries, are obtained. We have used the symmetry reductions as a basis for deriving new exact solutions that are invariant with respect to the symmetries. The exact solutions include compactons, solitons, kinks and antikinks.
Flips in planar graphs
Authors: Prosenjit Bose, Ferran Hurtado
Venue: Computational Geometry: Theory and Applications (2009)

We review results concerning edge flips in planar graphs concentrating mainly on various aspects of the following problem: Given two different planar graphs of the same size, how many edge flips are necessary and sufficient to transform one graph into another? We overview both the combinatorial perspective (where only a combinatorial embedding of the graph is specified) and the geometric perspective (where the graph is embedded in the plane, vertices are points and edges are straight-line segments). We highlight the similarities and differences of the two settings, describe many extensions and generalizations, highlight algorithmic issues, outline several applications and mention open problems.