ppxscal/embedding_network huggingface dataset:
Learning distributed bayesian network structure using majority-based method
Authors: Sachin Shetty, Min Song, Houjun Yang, Lisa Matthews
Venue: Journal of Computational Methods in Sciences and Engineering (2009)

In this paper we present a majority-based method to learn Bayesian network structure from databases distributed over a peer-to-peer network. The method consists of a majority learning algorithm and a majority consensus protocol. The majority learning algorithm discovers the local Bayesian network structure based on the local database and updates the structure once new edges are learnt from neighboring nodes. The majority consensus protocol is responsible for the exchange of the local Bayesian networks between neighboring nodes. The protocol and algorithm are executed in tandem on each node. They perform their operations asynchronously and exhibit local communications. Simulation results verify that all new edges, except for edges with confidence levels close to the confidence threshold, can be discovered by exchange of messages with a small number of neighboring nodes.
Context-Based Operational Transformation in Distributed Collaborative Editing Systems
Authors: David Sun, Chengzheng Sun
Venue: IEEE Transactions on Parallel and Distributed Systems (2009)

Operational Transformation (OT) is a consistency maintenance technique for collaborative editing systems—a special class of distributed applications for supporting human-computer-human interaction and collaboration over communication networks. The theory of causality has been the foundation of all prior OT systems, but it is inadequate to meet essential OT requirements in functionality and correctness. In this paper, we analyze the limitation of the causality theory, propose a novel theory of operation context as the new foundation for OT systems, and present a new OT algorithm—Context-based OT (COT)—which provides uniform and efficient solutions to both consistency maintenance and undo problems. The COT algorithm has been implemented and used for supporting a range of novel collaborative applications. The context theory and context vectors are potentially applicable to other distributed computing applications.
Practical calibation for upper extremety patients in haptic rehabilitation
Authors: Jilin Zhou, Francois Malric, Shervin Shirmohammadi
Venue: Proceedings of the 2009 IEEE International Workshop on Medical Measurements and Applications (2009)

As haptic devices become more affordable and economical, research in Haptic-based virtual rehabilitation systems is gaining more interest. A prototype haptic virtual rehabilitation system was developed in our lab using the CyberGrasp system with the goal of assisting patients who suffered from stroke leading to temporary upper extremity disability. However, calibration of the system for each user is currently tedious and time-consuming. In this paper, we propose a practical method to calibrate the CyberGlove using a Neural Network. The neural network is trained with the hand segment size and the manually collected calibrated data of 12 subjects. The hand segment sizes are extracted from a 2-D hand image. The preliminary results are very encouraging and show its effectiveness for the sensors on the index, the middle, the ring, the pinky fingers.
Thai License Plate Detection from a Video Frame
Authors: Chomtip Pornpanomchai, Nuchakarn Anawatmongkon
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

License plate detection and recognition system (LPDR) is applicable to wide range of uses such as highway toll collection, traffic management, and many more. One of the problems of this application is finding the position of license plate from cars because many cars have difference in uncertain positions of license plates and unclean license plates. The purpose of this project is to assess the efficiency of simple algorithm, applied to find the position of license plates from a video frame. This research can detect a license plate from the front or the rear of a car.The program in this project allows users to capture the picture from the video file and then the program will create the screenshot. Lastly, the program will detect the license plate position of that screenshot. The image captured by our program will appear in the .jpg file format. The accuracy of this project is around 82% for a video screenshot image, and 92% for a digital camera image.
Transforms and quantization design targeting the H.264/AVC intra prediction constraints
Authors: Robson Dornelles, Felipe Sampaio, Daniel Palomino, Luciano Agostini
Venue: Proceedings of the 22nd Annual Symposium on Integrated Circuits and System Design: Chip on the Dunes (2009)

This paper presents an architecture for a dedicated transforms and quantization loop targeting the Intra Prediction of the H.264/AVC video coding standard. The transforms and quantization loop is a bottleneck for the Intra Prediction, since the prediction process cannot start before the transforms and quantization loop finishes the reconstruction of the reference blocks. This work presents a low latency and high throughput architecture of the transforms and quantization loop, intending to reduce the impact of this loop in the Intra Prediction performance. The architecture was described in VHDL and synthesized to Altera Stratix II FPGA and to the TSMC 0.18&mu;m CMOS technology. The architecture reaches an operation frequency of 129.3 MHz when mapped to standardcells, and takes 4 cycles to process an I4MB block, 24 cycles to process an I16MB block, and 22 cycles to process a chroma block. Those are the best results when compared with all related works considering the Intra Prediction constraints.
GPU virtualization on VMware's hosted I/O architecture
Authors: Micah Dowty, Jeremy Sugerman
Venue: ACM SIGOPS Operating Systems Review (2009)

Modern graphics co-processors (GPUs) can produce high fidelity images several orders of magnitude faster than general purpose CPUs, and this performance expectation is rapidly becoming ubiquitous in personal computers. Despite this, GPU virtualization is a nascent field of research. This paper introduces a taxonomy of strategies for GPU virtualization and describes in detail the specific GPU virtualization architecture developed for VMware's hosted products (VMware Workstation and VMware Fusion). We analyze the performance of our GPU virtualization with a combination of applications and microbenchmarks. We also compare against software rendering, the GPU virtualization in Parallels Desktop 3.0, and the native GPU. We find that taking advantage of hardware acceleration significantly closes the gap between pure emulation and native, but that different implementations and host graphics stacks show distinct variation. The microbenchmarks show that our architecture amplifies the overheads in the traditional graphics API bottlenecks: draw calls, downloading buffers, and batch sizes. Our virtual GPU architecture runs modern graphics-intensive games and applications at interactive frame rates while preserving virtual machine portability. The applications we tested achieve from 86% to 12% of native rates and 43 to 18 frames per second with VMware Fusion 2.0.
Benchmarking of message-oriented middleware
Authors: Kai Sachs, Samuel Kounev, Stefan Appel, Alejandro Buchmann
Venue: Proceedings of the Third ACM International Conference on Distributed Event-Based Systems (2009)

Message-oriented middleware (MOM) is increasingly used as enabling technology for modern event-driven applications typically based on publish/subscribe (pub/sub) communication [1]. Many of these applications are designed for maximum scalability and flexibility and as such, they pose some serious performance issues for the underlying pub/sub middleware. Additionally, software designers face a new challenge: designing message-based communication flows which rely on asynchronous decoupled communication patterns. In order to develop good designs, system designers have to understand quality of service aspects and their performance costs. We believe that benchmarks are very helpful tools to analyse these aspects.
A two-stage hierarchical regression model for meta-analysis of epidemiologic nonlinear dose-response data
Authors: Qin Liu, Nancy R. Cook, Anna Bergström, Chung-Cheng Hsieh
Venue: Computational Statistics Data Analysis (2009)

To estimate a summarized dose-response relation across different exposure levels from epidemiologic data, meta-analysis often needs to take into account heterogeneity across studies beyond the variation associated with fixed effects. We extended a generalized-least-squares method and a multivariate maximum likelihood method to estimate the summarized nonlinear dose-response relation taking into account random effects. These methods are readily suited to fitting and testing models with covariates and curvilinear dose-response relations.
Improving Global System Development and Collaboration across Functions: Experiences from Industry
Authors: Peter Fassbinder, Volker Henz
Venue: Proceedings of the 2009 Fourth IEEE International Conference on Global Software Engineering (2009)

In large and complex organizations efficient collaboration across different locations (e.g. global system development) and different functions within the product lifecycle (e.g. sales, development, production) are key success factors in system and software engineering. As a global expert department for process consulting within the Siemens AG, we developed approaches to analyze and improve collaboration in these two scenarios and have successfully applied them in different Siemens business units. From our experiences, both approaches have similarities and often the challenges faced in industry when implementing global development are a combination of both: collaboration across locations and across functions. This presentation describes our approaches for analyzing and improving organizations with respect to these two scenarios. We emphasize their similarities and differences and show our experiences with them. The individual steps and methods (toolbox) within the workflow are explained using practical examples from Siemens organizations. In addition, challenges and questions we encountered are discussed.
Solution of Large-Scale Problems of Global Optimization on the Basis of Parallel Algorithms and Cluster Implementation of Computing Processes
Authors: Vladimir Koshur, Dmitriy Kuzmin, Aleksandr Legalov, Kirill Pushkaryov
Venue: Proceedings of the 10th International Conference on Parallel Computing Technologies (2009)

The parallel hybrid inverse neural network coordinate approxima tions algorithm (PHINNCA) for solution of large-scale global optimization problems is proposed in this work. The algorithm maps a trial value of an ob jective function into values of objective function arguments. It decreases a trial value step by step to find a global minimum. Dual generalized regression neural networks are used to perform the mapping. The algorithm is intended for cluster systems. A search is carried out concurrently. When there are multiple pro cesses, they share the information about their progress and apply a simulated annealing procedure to it.
On Making Directed Graphs Transitive
Authors: Mathias Weller, Christian Komusiewicz, Rolf Niedermeier, Johannes Uhlmann
Venue: Proceedings of the 11th International Symposium on Algorithms and Data Structures (2009)

We present the first thorough theoretical analysis of the Transitivity Editing problem on digraphs. Herein, the task is to perform a minimum number of arc insertions or deletions in order to make a given digraph transitive. This problem has recently been identified as important for the detection of hierarchical structure in molecular characteristics of disease. Mixing up Transitivity Editing with the companion problems on undirected graphs, it has been erroneously claimed to be NP-hard. We correct this error by presenting a first proof of NP-hardness, which also extends to the restricted cases where the input digraph is acyclic or has maximum degree four. Moreover, we improve previous fixed-parameter algorithms, now achieving a running time of O(2.57 k + n 3) for an n-vertex digraph if k arc modifications are sufficient to make it transitive. In particular, providing an O(k 2)-vertex problem kernel, we positively answer an open question from the literature. In case of digraphs with maximum degree d, an O(k ·d)-vertex problem kernel can be shown. We also demonstrate that if the input digraph contains no "diamond structure", then one can always find an optimal solution that exclusively performs arc deletions. Most of our results (including NP-hardness) can be transferred to the Transitivity Deletion problem, where only arc deletions are allowed.
Forecasting Fish Stock Recruitment by Using Neural Network
Authors: Lin Sun, Hongjun Xiao, Dequan Yang, Shouju Li
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

Recruitment prediction is a key element for management decisions in many fisheries. A new approach using neural network is developed as a tool to produce a formula for forecasting fish stock recruitment. In order to deal with the local minimum problem in training neural network with back-propagation algorithm and to enhance forecasting precision, neural network’s weights are adjusted by optimization algorithm. It is demonstrated that a well trained artificial neural network reveals an extremely fast convergence and a high degree of accuracy in the prediction of fish stock recruitment.
The Research and Application on Streaming Data of GIS Data Mining
Authors: Jia Liu, Lin Liu, Wei Chen
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

With the GIS (Geographic Information System) applications becoming more and more wide, and GIS data growing by magnitude, data mining of the field has become a focus and difficulty on research. In this paper, the continuous query and dynamic store method for GIS data mining is introduce, GIS data update and optimization is researched, and how to improve the efficiency of GIS data mining is discussed.
Performance Analysis of ZigBee-Based Wireless Sensor Networks with Path-Constrained Mobile Sink(s)
Authors: N. Vlajic, D. Stevanovic
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

In the wireless sensor network (WSN) literature, the use of a mobile sink is commonly viewed as one of the most successful means of load balancing as well as an effective defense against the so-called hot-spot phenomenon. The aim of this paper is to investigate the real-world applicability of the known theoretical benefits associated with the use of mobile sink(s). In particular, we examine the pros and cons of deploying path-constrained mobile sink(s) in IEEE 802.15.4 / ZigBee-based WSNs.The main contributions of this paper are as follows: First, analytically and through simulation, we demonstrate that in idealistic (zero-overhead) networks the use of a mobile sink does result in a more even distribution of routing load and longer network lifetime, as earlier suggested in the WSN literature. Moreover, in small- to medium- size zero-overhead WSNs, the outer-peripheral and the diagonal-cross trajectory appear to be more effective than other types of mobile-sink trajectories. Unfortunately, real-world networks, including ZigBee WSNs, are not zero-overhead – these networks employ special mechanisms that generate additional (overhead) traffic in order to manage congestion and node mobility. The results of our OPNET-base simulation study demonstrate that in IEEE 802.15.4 / ZigBee WSNs, once all of the overhead traffic is accounted for, the theoretical advantage of deploying a mobile- vs. deploying a static- sink completely disappears. Hence, for anybody contemplating the use of a mobile sink in ZigBee sensor networks, the minimization of protocol overhead may have to be the first course of action. In the last part of the paper, we introduce two simple mechanisms for reduction of mobility-related overhead in ZigBee WSNs. The presented simulation results suggest that with these mechanisms in place the superiority of mobile- over static- sink deployment can be regained.
The Design and Implement of Point-Model System Used in Reverse Engineering Based on CGAL
Authors: Hu Wenqiang, Qu Yi
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

The software used for Reverse Engineering is becoming more and more important to designing complex industrial equipments. Aiming to this question, this paper designs and Implements one point-model system used in reverse engineering based on CGAL. In this system,unorganized point cloud is looked as input data, then the good point cloud which can express exactly topology of original sampled object is obtained through deleting noise, registering and segmenting points, at last, mesh model is output data through reconstructing, segmenting and simplifying mesh. At the same time, the result 3D model is displayed to express the apparent geometrical feature and the physical and mechanical feature is computed. By defining the format of file as input and output, the point-model system can contact with other software without interface. Through testing the point-model system in realization item, the experimental results support that the system can decrease the handwork and improve the efficiency in mesh reconstruction of point cloud.
Dynamic characteristics and forced response of an electrostatically-actuated microbeam subjected to fluid loading
Authors: Ghader Rezazadeh, Mohammad Fathalilou, Rasool Shabani, Saeid Tarverdilou, Soheil Talebian
Venue: Microsystem Technologies (2009)

In this paper flexural vibrations of an electrostatically actuated cantilever microbeam in an incompressible inviscid stationary fluid have been studied. By applying &#x201c;Three dimensional aerodynamic theory&#x201d; pressure jump across the microbeam has been investigated and the inertial effects of fluid on microbeam dynamics have been modeled as a mass added to microbeam mass. Magnitude of the added mass has been calculated for various aspect ratios of cantilever microbeams and compared with those of clamped-clamped microbeams. To investigate the dynamic characteristics, it has been considered that the microbeam has been deflected by a DC voltage, V DC and then the dynamic characteristics and forced response of the system have been considered about these conditions. Galerkin-based step by step linearization method (SSLM) and Galerkin-based reduced order model have been applied to solve the nonlinear static and dynamic governing equations, respectively. Water by neglecting viscidity effects, as an instant has been considered as a surrounding fluid and the frequency response of the microbeam has been compared with that of vacuum conditions. It has been shown that because of the added mass effects in watery environment, the natural frequencies of the microbeam decrease. Because of the higher dielectric coefficient and increasing electrical stiffness and decreasing total stiffness consequently, maximum amplitude of the microbeam vibrations increases in watery environment, compared with vacuum. Moreover, it has been shown that increasing the DC voltage, increases the electrical stiffness and maximum amplitude of the microbeam vibrations, consequently, It has been shown that in higher voltages (near pull-in voltage), the rate of variation of resonance frequency and maximum amplitude is stronger than lower voltages.
Effects of Suffix Repetition Rates of a String on the Performance of String Matching Algorithms
Authors: Yang Wang
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

The highly efficient Boyer-Moore’s string matching algorithm utilizes information on multi-occurrences of string suffixes in a pattern string to avoid backtracks in searching the pattern string.One hypothesis is that Boyer-Moore’s algorithm even benefits more from highly self-repetitive patterns.In this paper, the author studies how multi-occurrences of string suffixes affect the performance of the Boyer-Moore’s algorithm as well as some other well known string search algorithms.The paper introduces a new concept of suffix repetition rate (SRR) to measure how frequently the suffixes of a string occur inside of the string.Using this measurement, experiments with several thousands patterns over the entire range of SRRs have been carried out, and the results show that increasing of SRR on pattern strings does not improve the performance of a searching algorithm in terms of efficiency.
Acceleration of the L4/Fiasco microkernel using scratchpad memory
Authors: S. Hessel, F. Bruns, A. Bilgic, A. Lackorzynski, H. Härtig, J. Hausner
Venue: Proceedings of the First Workshop on Virtualization in Mobile Computing (2008)

In this paper we analyze the potential of using scratchpad memory in embedded devices to accelerate the operation of the L4/Fiasco microkernel affecting basically all applications on top of the kernel including virtualization software. We examine several low-level L4 system calls using a virtual prototype of Infineon's S-GOLD&reg; platform for mobile phones based on an ARM11 processor. We present a profiling strategy identifying critical parts of the microkernel to be placed on the scratchpad memory. Applying this approach we achieve a worstcase speedup of up to 29% with one page of scratchpad memory (4 kB) and up to 63% with two pages. With regard to the real-time capability of Fiasco, worst-case interrupt latency can be improved by almost 45% with only 4 kB of scratchpad memory.
Normalization of the Vocalic Space
Authors: Jan Volín
Venue: Cross-Modal Analysis of Speech, Gestures, Gaze and Facial Expressions: COST Action 2102 International Conference Prague, Czech Republic, October 15-18, 2008 Revised Selected and Invited Papers (2009)

Phonetic units which constitute natural continuous speech display immense variation due to a substantial number of factors. Consequently, one of the key questions for speech scientists concerns the translation of individual bundles of acoustic features into conventional linguistic meanings or types. Although the problem of normalization of acoustic data is common to many areas of speech science, its solutions depend on particular applicational objectives. An overview of the development in the field of normalization is presented from the perspective of the phonetic understanding of speech communication. The explanatory value of individual methodological outcomes is discussed. Both indexical (related to the speaker identity) and contextual (related to the linguistic form) factors are considered and several normalization algorithms are compared with each other. Recent findings indicate that human listeners exploit not only visual cues but also their cumulated social experience when processing sounds of speech.
Computational Integral Imaging Reconstruction Technique with High Image Resolution
Authors: Yan Piao, Yu Wang, Jingfeng Zang
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

This paper presents a new method to improve the resolution of integral imaging. According to integral imaging system principle, a volume pixel of 3D scene is projected in several elemental images through micro-lens array. Contrary optic-ray pickup method is introduced in the CIIR process to reconstruct integral image by acquiring multiple pixels from various elemental images for corresponding volume pixel. To show the feasibility of proposed method, some experiments are performed, and the results are compared and discussed with those of the conventional method. The resolution of reconstruction image can be dramatically improved by the proposed method.