ppxscal/embedding_network huggingface dataset:
Using web information for creating publication venue authority files
Authors: Denilson Alves Pereira, Berthier Ribeiro-Neto, Nivio Ziviani, Alberto H. F. Laender
Venue: Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries (2008)

Citations to publication venues in the form of journal, conference and workshop contain spelling variants, acronyms, abbreviated forms and misspellings, all of which make more difficult to retrieve the item of interest. The task of discovering and reconciling these variant forms of bibliographic references is known as authority work. The key goal is to create the so called authority files, which maintain, for any given bibliographic item, a list of variant labels (i.e., variant strings) used as a reference to it. In this paper we propose to use information available on the Web to create high quality publication venue authority files. Our idea is to recognize (and extract) references to publication venues in the text snippets of the answers returned by a search engine. References to a same publication venue are then reconciled in an authority file. Each entry in this file is composed of a canonical name for the venue, an acronym, the venue type (i.e., journal, conference, or workshop), and a mapping to various forms of writing its name in bibliographic citations. Experimental results show that our Web-based method for creating authority files is superior to previous work based on straight string matching techniques. Considering the average precision in finding correct venue canonical names, we observe gains up to 41.7%.
Discrete-time GeoX/G/1 queue with unreliable server and multiple adaptive delayed vacations
Authors: Yinghui Tang, Xi Yun, Shujuan Huang
Venue: Journal of Computational and Applied Mathematics (2008)

In this paper we consider a discrete-time Geo^X/G/1 queue with unreliable server and multiple adaptive delayed vacations policy in which the vacation time, service time, repair time and the delayed time all follow arbitrary discrete distribution. By using a concise decomposition method, the transient and steady-state distributions of the queue length are studied, and the stochastic decomposition property of steady-state queue length has been proved. Several common vacation policies are special cases of the vacation policy presented in this study. The relationship between the generating functions of steady-state queue length at departure epoch and arbitrary epoch is obtained. Finally, we give some numerical examples to illustrate the effect of the parameters on several performance characteristics.
Multi-rate Integration and Modern Taylor Series Method
Authors: Jirí Kunovský, Martina Drozdová, Jirí Petrek, Pavla Sehnalová, Frantiek Zboril
Venue: Proceedings of the Tenth International Conference on Computer Modeling and Simulation (2008)

It is the aim of the paper to describe both new developed Modern Taylor Series Method (MTSM) and well-known multi-rate integration method in real-time simulations. An example is used to demonstrate methodology of both integration methods. To show how simple it is to solve problem using Taylor series the multi-rate integration is described in a great detail.
Homomorphism preservation theorems
Authors: Benjamin Rossman
Venue: Journal of the ACM (JACM) (2008)

The homomorphism preservation theorem (h.p.t.), a result in classical model theory, states that a first-order formula is preserved under homomorphisms on all structures (finite and infinite) if and only if it is equivalent to an existential-positive formula. Answering a long-standing question in finite model theory, we prove that the h.p.t. remains valid when restricted to finite structures (unlike many other classical preservation theorems, including the &Lstrok;o&sacute;--Tarski theorem and Lyndon's positivity theorem). Applications of this result extend to constraint satisfaction problems and to database theory via a correspondence between existential-positive formulas and unions of conjunctive queries. A further result of this article strengthens the classical h.p.t.: we show that a first-order formula is preserved under homomorphisms on all structures if and only if it is equivalent to an existential-positive formula of equal quantifier-rank.
Reactive Common Sense Reasoning for Knowledge-Based HMI
Authors: Michael Cebulla
Venue: Proceedings of the Fourth International Conference on Autonomic and Autonomous Systems (2008)

In our approach we show how to integrate traditional BDI-Logics and reactive commonsense reasoning. Our goal consists in supporting efficient runtime inferences in the course of distributed decision making. For this sake we take a highly reactive calculus (membrane computing) and combine it with high-level modeling concepts. In order to obtain efficient inference mechanisms we use quotient-based reasoning. With this framework we are able to introduce situational knowledge into knowledge-based human machine interaction. We think that this kind of situational reasoning is highly important for human-machine interaction in the age of disappearing computing.
Advances in Digital Speech Transmission
Authors: Rainer Martin, Ulrich Heute, Christiane Antweiler
Venue:  (2008)

Speech processing and speech transmission technology are expanding fields of active research. New challenges arise from the 'anywhere, anytime' paradigm of mobile communications, the ubiquitous use of voice communication systems in noisy environments and the convergence of communication networks toward Internet based transmission protocols, such as Voice over IP. As a consequence, new speech coding, new enhancement and error concealment, and new quality assessment methods are emerging. Advances in Digital Speech Transmission provides an up-to-date overview of the field, including topics such as speech coding in heterogeneous communication networks, wideband coding, and the quality assessment of wideband speech. Provides an insight into the latest developments in speech processing and speech transmission, making it an essential reference to those working in these fields Offers a balanced overview of technology and applications Discusses topics such as speech coding in heterogeneous communications networks, wideband coding, and the quality assessment of the wideband speech Explains speech signal processing in hearing instruments and man-machine interfaces from applications point of view Covers speech coding for Voice over IP, blind source separation, digital hearing aids and speech processing for automatic speech recognition Advances in Digital Speech Transmission serves as an essential link between the basics and the type of technology and applications (prospective) engineers work on in industry labs and academia. The book will also be of interest to advanced students, researchers, and other professionals who need to brush up their knowledge in this field.
Scalability Analysis for Wireless Sensor Networks Routing Protocols
Authors: Lubna K. Alazzawi, Ali M. Elkateeb, Aiyappa Ramesh, Waleed Aljuhar
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

Scalability of routing protocols used in wireless sensor networks (WSNs) is a critical issue due to the extremely high node numbers and relatively high node density. A good routing protocol has to be scalable and adaptive to the changes in the network topology. Thus protocols must perform well as the network grows larger or as the workload increases. In this paper, we performed a mathematical verification and the evaluation for proposed scalable property of a given WSN has been computed. This computation showed the limitation and capability of the WSN scalability and specifically for Flooding and SPIN protocols.
IntellBatt: towards smarter battery design
Authors: Suman K. Mandal, Praveen S. Bhojwani, Saraju P. Mohanty, Rabi N. Mahapatra
Venue: Proceedings of the 45th annual Design Automation Conference (2008)

Battery lifetime and safety are primary concerns in the design of battery operated systems. Lifetime management is typically supervised by the system via battery-aware task scheduling, while safety is managed on the battery side via features deployed into smart batteries. This research proposes IntellBatt; an intelligent battery cell array based novel design of a multi-cell battery that offloads battery lifetime management onto the battery. By deploying a battery cell array management unit, IntellBatt exploits various battery related characteristics such as charge recovery effect, to enhance battery lifetime and ensure safe operation. This is achieved by using real-time cell status information to selects cells to deliver the required load current, without the involvement of a complex task scheduler on the host system. The proposed design was evaluated via simulation using accurate cell models and real experimental traces from a portable DVD player. The use of a multi-cell design enhanced battery lifetime by 22% in terms of battery discharge time. Besides a standalone deployment, IntellBatt can also be combined with existing battery-aware task scheduling approaches to further enhance battery lifetime.
Optimization of fuzzy partitions for inductive reasoning using genetic algorithms
Authors: J. Acosta, A. Nebot, P. Villar, J. M. Fuertes
Venue: International Journal of Systems Science (2007)

Fuzzy Inductive Reasoning (FIR) is a data-driven methodology that uses fuzzy and pattern recognition techniques to infer system models and to predict their future behavior. It is well known that variations on fuzzy partitions have a direct effect on the performance of the fuzzy-rule-based systems. The FIR methodology is not an exception. The performance of the model identification and prediction processes of FIR is highly influenced by the discretization parameters of the system variables, i.e. the number of classes of each variable and the membership functions that define its semantics. In this work, we design two new genetic fuzzy systems (GFSs) that improve this modeling and simulation technique. The main goal of the GFSs is to learn the fuzzification parameters of the FIR methodology. The new approaches are applied to two real modeling problems, the human central nervous system and an electrical distribution problem.
Cloud-top pressure retrieval using the oxygen A-band in the IRS-3 MOS instrument
Authors: R. Preusker, J. Fischer, P. Albert, R. Bennartz, L. Schüller
Venue: International Journal of Remote Sensing (2007)

Backscattered solar radiation as measured by MOS (Modular Optoelectronical Scanner) on the IRS3 (Indian Remote sensing Satellite 3) has been used in an algorithm to retrieve cloud top pressure. The algorithm uses a radiance ratio between absorbing channels in the Oxygen-A absorption band at 761 nm and a window channel at 750 nm. The ratios are directly related to the average photon path length, which is mainly determined by the cloud top pressure. This paper presents the principles of the retrieval scheme, results of a sensitivity study and a first validation using radiosondes.
Pulse Signals Detection by Digital Image Correlation
Authors: Zhang Aihua, Li Yongping, Yu Dong, Guo Weigang
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 02 (2008)

The pulse diagnosis is an essential method in traditional Chinese medicine and the pulse wave embodies the abundant physiological and pathological information about the health status. In order to obtain the complete and objective pulse tactile information, the sensor for detecting pulse tactile image was developed. By adopting this sensor the image sequence of the pulse motion was collected from the radial artery. A method of acquiring the pulse wave based on digital image correlation was presented. Then the single point pulse signal and the multi-dimensional pulse signals from the pulse tactile images were detected. The results show that the pulse tactile signals can be objectively obtained by the presented method. It provides a new idea and approach to the objective study on the pulse diagnosis.
Incremental exemplar learning schemes for classification on embedded devices
Authors: Ankur Jain, Daniel Nikovski
Venue: Machine Learning (2008)

Although memory-based classifiers offer robust classification performance, their widespread usage on embedded devices is hindered due to the device's limited memory resources. Moreover, embedded devices often operate in an environment where data exhibits evolutionary changes which entails frequent update of the in-memory training data. A viable option for dealing with the memory constraint is to use Exemplar Learning (EL) schemes that learn a small memory set (called the exemplar set) of high functional information that fits in memory. However, traditional EL schemes have several drawbacks that make them inapplicable for embedded devices; (1) they have high memory overheads and are unable to handle incremental updates to the exemplar set, (2) they cannot be customized to obtain exemplar sets of any user-defined size that fits in the memory and (3) they learn exemplar sets based on local neighborhood structures that do not offer robust classification performance. In this paper, we propose two novel EL schemes, $\mathsf{EBEL}$ (Entropy-Based Exemplar Learning) and $\mathsf{ABEL}$ (AUC-Based Exemplar Learning) that overcome the aforementioned short-comings of traditional EL algorithms. We show that our schemes efficiently incorporate new training datasets while maintaining high quality exemplar sets of any user-defined size. We present a comprehensive experimental analysis showing excellent classification-accuracy versus memory-usage tradeoffs using our proposed methods.
Trade-offs in optimization of GMDH-type neural networks for modelling of a complex process
Authors: N. Nariman-Zadeh, E. Haghgoo, A. Jamali
Venue: Proceedings of the 6th WSEAS International Conference on Systems Theory & Scientific Computation (2006)

Evolutionary Algorithms (EAs) are deployed for multi-objective Pareto optimal design of Group Method of Data Handling (GMDH)-type neural networks that have been used for modelling of a complex process (such as explosive cutting process) using some input-output experimental data. In this way, EAs with a new encoding scheme is firstly presented to evolutionary design of the generalized GMDH-type neural networks in which the connectivity configurations in such networks are not limited to adjacent layers. Multi-objective EAs (non-dominated sorting genetic algorithm, NSGA-II) with a new diversity preserving mechanism are secondly used for Pareto optimization of such GMDH-type neural networks. Optimal Pareto fronts are obtained which exhibit the trade-off between pair of conflicting objectives and, thus, provide different nondominated optimal choices of GMDH-type neural networks models for such complex process.
Unsaturated diaziridines thermal cleavage possibilities: disrotatory or conrotatory
Authors: S. Arshadi, M. Forouzani, A. Qarepour, A. R. Karami
Venue: Proceedings of the 1st WSEAS International Conference on Computational Chemistry (2007)

Ab initio calculations are carried out at UB3LYP/6-311++G (3df, 2p) levels of theory, on electrocyclic thermal cleavage of four (R) derivatives of diaziridines, 1X-R, to their corresponding (Z) and (E) azomethine imides (2X-Z, 2X-E, 3X-Z and 3X-E), where X = -H, -Me, -t-Bu and -Ph. Cleavage of 3X-R Series to 3X-Z (Path 3) emerged as the more favored, for producing the most stable products, 3X-Z. In IRC calculations that were shown in Path 3 and 4, C6-N5 bond was cleavage, before reaching reaction rate determinating step (transition state).
A Risk-aware Trust Based Secure Resource Discovery (RTSRD) Model for Pervasive Computing
Authors: Sheikh I. Ahamed, Moushumi Sharmin, Shameem Ahmed
Venue: Proceedings of the 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications (2008)

To address the challenges posed by device capacity and capability, and also the nature of ad-hoc network of pervasive computing, a resource discovery model is needed that can resolve security and privacy issues with simple solutions. The use of complex algorithms and powerful fixed infrastructure is infeasible due to the volatile nature of pervasive environment and tiny pervasive devices. In this paper, we present a risk-aware trust based secure resource discovery model, RTSRD (Risk-aware Trust Based Secure Resource Discovery) for a truly pervasive environment. Our model is an adaptive hybrid one that allows both secure and non-secure discovery of services on adaptive trust. RTSRD also incorporates a risk model for sharing resources with unknown devices. Hence, the two contributions of this paper are: adaptive trust, and risk model for resource discovery in pervasive computing environments.
Analysis of High-throughput DNA Methylation Bead Arrays Utilizing Bayesian Genotyping Algorithms
Authors: Yuanyuan Xiao, Mark R. Segal, E. Andres Houseman, Joe Wiemels, John Wiencke, Shichun Zheng, Margaret Wrensch, Brock Christensen, Carmen Marsit, Karl Kelsey, Heather Nelson, Margaret Karagas, Ru-Fang Yeh
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

We present a statistical framework, MAMS-M, for determining the methylation status of hundreds of cancer related CpG sites. MAMS-M extends and adapts our previous SNP genotyping algorithm, MAMS, to methylation bead array data, exploiting the similarities in data structure between the two platforms. MAMS-M employs a multi-site, multi-array model-based clustering approach to derive initial methylation calls, and then recalibrate these calls and associated confidence measures using site-specific adjustments. We demonstrate the performance of MAMS-M using a real-life data set with cancer applications.
A Critical Analysis of RFID Security Protocols
Authors: Atif Sharif, Vidyasagar Potdar
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

RFID, Radio Frequency Identification Systems, have gains its popularity for automated identificationand supply chain applications. This paper describes the technical fundamentals of RFID systems, recent technical research on the problems of privacy/security, and some security proposals are presented for this new radio technology i.e. RFID.
A method for THAI isolated word recognition using Ant Colony algorithm
Authors: Saritchai Predawan, Prasit Jiyapanichkul, Chom Kimpan, Chai Wutiwiwatchai
Venue: Proceedings of the 5th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics (2006)

This paper presents Thai isolated word recognition system, which is based on the Ant-Miner algorithm. The system employs fundamental frequency (F0) extraction from input speech signal, analysis of F0 contour for feature extraction, and classification of each tone using the extracted features. In the F0 feature extraction, the polynomial regression functions are employed to fit the segmented F0 curve where its coefficients are used as a feature vector. All attributes are used for construct the classification rules by an Ant-Miner algorithm in order to classify 10 Thai digits utterances. For this experiment, the Ant-Miner algorithm is adapted, with a small change to increase the recognition rate. The result of this experiment is a 95% recognition rate.
Spatial and temporal probabilities of obtaining cloud-free Landsat images over the Brazilian tropical savanna
Authors: E. E. Sano, L. G. Ferreira, G. P. Asner, E. T. Steinke
Venue: International Journal of Remote Sensing (2007)

Remotely sensed data are the best and perhaps the only possible way for monitoring large-scale, human-induced land occupation and biosphere-atmosphere processes in regions such as the Brazilian tropical savanna (Cerrado). Landsat imagery has been intensively employed for these studies because of their long-term data coverage (>30 years), suitable spatial and temporal resolutions, and ability to discriminate different land-use and land-cover classes. However, cloud cover is the most obvious constraint for obtaining optical remote sensing data in tropical regions, and cloud cover analysis of remotely sensed data is a requisite step needed for any optical remote sensing studies. This study addresses the extent to which cloudiness can restrict the monitoring of the Brazilian Cerrado from Landsat-like sensors. Percent cloud cover from more than 35 500 Landsat quick-looks were estimated by the K-means unsupervised classification technique. The data were examined by month, season, and El Niño Southern Oscillation event. Monthly observations of any part of the biome are highly unlikely during the wet season (October-March), but very possible during the dry season, especially in July and August. Research involving seasonality is feasible in some parts of the Cerrado at the temporal satellite sampling frequency of Landsat sensors. There are several limitations at the northern limit of the Cerrado, especially in the transitional area with the Amazon. During the 1997 El Niño event, the cloudiness over the Cerrado decreased to a measurable but small degree (5% less, on average). These results set the framework and limitations of future studies of land use/land cover and ecological dynamics using Landsat-like satellite sensors.
Perception-aware Depth Cueing for Illustrative Vascular Visualization
Authors: Alan Chu, Wing-Yin Chan, Jixiang Guo, Wai-Man Pang, Pheng-Ann Heng
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

Illustrative visualization of complex vasculature hasbeen one of the indispensable components in medical educationand training. In this paper, we propose a rendering pipeline which incorporates various perception-aware techniques for informative vascular illustration. Chromostereopsis rendering, isophote-based line hatching, and enhanced silhouette drawing have been integrated seamlessly through multiple shader passes. With advanced GPU acceleration techniques including render to texture (RTT), framebuffer object (FBO) and fast image convolution, areal-time frame-rate can be achieved.
Performance measures in courses using computer-aided personalized system of instruction
Authors: Crystal R. Springer, Joseph J. Pear
Venue: Computers Education (2008)

Archived data from four courses taught with computer-aided personalized system of instruction (CAPSI) - an online, self-paced, instructional program - were used to explore the relationship between objectively rescored final exam grades, peer reviewing, and progress rate - i.e., the rate at which students completed unit tests. There was a strong positive correlation (r=.68, p
Ul'yanov-type inequality for bounded convex sets in Rd
Authors: Z. Ditzian, A. Prymak
Venue: Journal of Approximation Theory (2008)

For @W@?R^d, a convex bounded set with non-empty interior, the moduli of smoothness @w^r(f,t)"L"""q"("@W") and the norm @?f@?"L"""q"("@W") are estimated by an Ul'yanov-type expression involving @w^r(f,t)"L"""p"("@W") where 0
2008 Special Issue: Sensory adaptation in human balance control: Lessons for biomimetic robotic bipeds
Authors: Arash Mahboobin, Patrick J. Loughlin, Mark S. Redfern, Stuart O. Anderson, Christopher G. Atkeson, Jessica K. Hodgins
Venue: Neural Networks (2008)

This paper describes mechanisms used by humans to stand on moving platforms, such as a bus or ship, and to combine body orientation and motion information from multiple sensors including vision, vestibular, and proprioception. A simple mechanism, sensory re-weighting, has been proposed to explain how human subjects learn to reduce the effects of inconsistent sensors on balance. Our goal is to replicate this robust balance behavior in bipedal robots. We review results exploring sensory re-weighting in humans and describe implementations of sensory re-weighting in simulation and on a robot.