ppxscal/embedding_network huggingface dataset:
Study of structural features of handwritten grapheme "th' for writer identification
Authors: Vladimir Pervouchine, Graham Leedham
Venue: Proceedings of the Third International Symposium on Information Assurance and Security (2007)

In this paper we present a study of 25 structural micro features of handwriting extracted automatically from images of grapheme "th'. The study was carried out on a total of 3823 samples collected from 165 different writers, between 15 and 27 samples per writer. The methods of feature extraction are presented along with the results. We present a direct analysis of the feature usefulness. A measure of usefulness specific to handwriting examination was designed and the usefulness of the features was estimated. It was shown that most of the extracted micro features of "th' do possess discriminative power. Ranking of features allows simple comparison of their discriminative power.
A WebML-based Visual Language for the Development of Web GIS Applications
Authors: S. Di Martino, F. Ferrucci, L. Paolino, M. Sebillo, G. Vitiello, G. Avagliano
Venue: Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing (2007)

In the present paper, we propose a visual language meant to support the design of Web GIS applications. The proposal is based on the observation that Web GIS can be considered as a particular class of data-intensive Web applications, since they are mainly devoted to handle (spatial) information to and from the user. The success of WebML (Web Modeling Language) for designing traditional data-intensive Web applications suggested us to extend this visual formalism to model relevant interaction and navigation operations typical of Web GIS. The proposed extension consists of a set of content units specifically tailored for GIS concepts and tasks.
GRIDL: high-performance and distributed interactive data language
Authors: S. G. Shasharina, O. Volberg, P. Stoltz, S. Veitzer
Venue: Proceedings of the High Performance Distributed Computing, 2005. HPDC-14. Proceedings. 14th IEEE International Symposium (2005)

Grid technologies provide a valuable solution for distributed scientific applications but are not readily available for the 4th Generation Languages (4GLs) widely used in physics, climate modeling and medicine. Examples of 4GLs are interactive data language (IDL) and MATLAB. There is a need for tools allowing 4GLs to interoperate with the grid. This paper describes our design and the status of the tools under development, which include IDL bindings for Web services and tools for running and managing parallel and serial IDL processes on grids and clusters.
Identification of stratigraphic formation interfaces using wavelet and Fourier transforms
Authors: Shih-Yu Pan, Bieng-Zih Hsieh, Ming-Tar Lu, Zsay-Shing Lin
Venue: Computers Geosciences (2008)

The purpose of this study was to identify the formation interfaces from geophysical well log data using the wavelet transform, and a combination of the wavelet transform and the Fourier transform methods. In the wavelet transform method, the identification of formation interfaces is based on the wavelet coefficients from the wavelet transform of spontaneous potential (SP) log and gamma ray (GR) log data. In the combination of the wavelet transform and the Fourier transform methods, the wavelet transform, spectrum analysis, and logarithmic transform of well logs were applied to the SP and GR log data successively to obtain clear signals for identifying the stratigraphic formation interface. In this study, a set of ideal log data was first created and analyzed to test the validity of the developed procedures. In analyzing the SP and GR logs from a field, both the wavelet transform method and conventional well log analysis showed similar results. The results from a combination of the wavelet transform and the Fourier transform methods, however, were better than those from the wavelet transform method and the conventional well log analysis.
Analysis of the electrical characteristics of power LDMOSFETs having different design parameters under various temperature
Authors: Yong-Seo Koo
Venue: Microelectronics Journal (2007)

In this paper, we have investigated the electrical characteristics of power lateral double-diffused MOSFETs (LDMOSFETs) having different gate lengths (2.1-3@mm) and drift lengths (6.6-12.6@mm) in the temperature range 100-500K. The results of this study indicate that gate length and drift region length have a great effect on electrical characteristics, but they have little effect on temperature dependence. The specific on-resistance and the off-state breakdown voltage increase with temperature. The result shows that the specific on-resistance increases exponentially with the exponent 2.2 and, by contrast, the off-state breakdown voltage increases linearly with a slope of 100mV/K (drift region concentration of measured device: 2x10^1^5cm^-^3). As a result, R"o"n/BV, known for a figure of merit of power device, increases with temperature.
A Co-training Approach based TEF-WA technique
Authors: Tang Huanling, Lu Mingyu, Liu Na
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

Traditional categorization algorithm suffers from not having sufficient labeled training data for learning, while large amount unlabeled data are easily available. We investigate co-training algorithm and its assumption that the features set can be split into two compatible and independent views. However, the assumption is usually violated to some degree in practice and sometimes the natural feature split does not exist. So we adopt TEF_WA technique which utilizes term evaluation functions to split features set and construct multiple views. We can choose a pair of views which are compatible and independent to certain degree. Based TEF_WA technique we develop a semi-supervised categorization algorithm Co_CLM. Experimental results show Co_CLM can significantly decrease the classification error utilizing unlabeled data especially labeled data is sparse. Our experimental results also indicate Co_CLM will achieve more satisfactory performance with the more independent view pairs.
QoS Driven Service Discovery Method Based on Extended UDDI
Authors: Wenli Dong
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

The inclusion of QoS in Web service has been pointed out in previous work in both academia and industry. Challenge in this area addresses importance of QoS. This paper proposes a QoS driven service discovery method based on extended UDDI with the help of Semantic Web. First, a Extending UDDI Model based on QoS driven is proposed, QoS ontology is analyzed to reduce misunderstanding. Second, a matching algorithm based on fuzzy correlation calculate is proposed to filter the unqualified service to improve the discovery accuracy. Third, a discovery process based on policy is build based on Semantic Web technology. The experience results show the QoS driven Web service discovery method possesses high discovery accuracy.
Stimulus generation for constrained random simulation
Authors: Nathan Kitchen, Andreas Kuehlmann
Venue: Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design (2007)

Constrained random simulation is the main workhorse in today's hardware verification flows. It requires the random generation of input stimuli that obey a set of declaratively specified input constraints, which are then applied to validate given design properties by simulation. The efficiency of the overall flow depends critically on (1) the performance of the constraint solver and (2) the distribution of the generated solutions. In this paper we discuss the overall problem of efficient constraint solving for stimulus generation for mixed Boolean/integer variable domains and propose a new hybrid solver based on Markov-chain Monte Carlo methods with good performance and distribution.
Analysis of Source Codes Created by Beginners in Programming Education
Authors: Toyoshiro Nakashima, Chieko Matsuyama, Naohiro Ishii
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02 (2007)

The creation of animations was made as a subject of university programming course in order to make students understand the process of program creation, and tackle programming with interest. However programs created by students had many problems. In this paper, the formats and composition of the programs were investigated. It was clarified by the analysis of source codes that there were a lot of problems related to such matters as how to use indentation, how to apply comments and functions etc. in the programming for the format and the composition of the source codes.
Hierarchical hybrid fuzzy-neural networks for approximation with mixed input variables
Authors: Di Wang, Xiao-Jun Zeng, John A. Keane
Venue: Neurocomputing (2007)

Real-world systems usually involve both continuous and discrete input variables. However, in existing learning algorithms of both neural networks and fuzzy systems, these mixed variables are usually treated as continuous without taking into account the special features of discrete variables. It is inefficient to represent each discrete input variable having only a few fixed values by one input neuron with full connection to the hidden layer. This paper proposes a novel hierarchical hybrid fuzzy neural network to represent systems with mixed input variables. The proposed model consists of two levels: the lower level are fuzzy sub-systems each of which aggregates several discrete input variables into an intermediate variable as its output; the higher level is a neural network whose input variables consist of continuous input variables and intermediate variables. For systems or function approximations with mixed variables, it is shown that the proposed hierarchical hybrid fuzzy neural networks outperform standard neural networks in accuracy with fewer parameters, and both provide greater transparency and preserve the universal approximation property (i.e., they can approximate any function with mixed input variables to any degree of accuracy).
A Unified Paradigm For Scalable Multi-Projector Displays
Authors: Niranjan Damera-Venkata, Nelson Chang, Jeffrey Dicarlo
Venue: IEEE Transactions on Visualization and Computer Graphics (2007)

We present a general framework for the modeling and optimization of scalable multi-projector displays. Based on this framework, we derive algorithms that can robustly optimize the visual quality of an arbitrary combination of projectors without manual adjustment. When the projectors are tiled, we show that our framework automatically produces blending maps that outperform state-of-the-art projector blending methods. When all the projectors are superimposed, the framework can produce high-resolution images beyond the Nyquist resolution limits of component projectors. When a combination of tiled and superimposed projectors are deployed, the same framework harnesses the best features of both tiled and superimposed multi-projector projection paradigms. The framework creates for the first time a new unified paradigm that is agnostic to a particular configuration of projectors yet robustly optimizes for the brightness, contrast, and resolution of that configuration.In addition, we demonstrate that our algorithms support high resolution video at real-time interactive frame rates achieved on commodity graphics platforms. This work allows for inexpensive, compelling, flexible, and robust large scale visualization systems to be built and deployed very efficiently.
Tight Bound for the Mean Node Degree in Ad Hoc Networks with pportunistic Communications
Authors: Jean-Marie Gorce, Ruifeng Zhang, Herv Parvery
Venue: Proceedings of the Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (2007)

Many work has been devoted to evaluating the connec- tivity of ad hoc networks. In most of these works, radio links are assumed ideal, i.e. with no transmission errors. To fulfill this assumption, the reception threshold is assumed high enough so that considering valid only the radio links having a successful transmission probability above a target value. All unreliable links are thus dismissed making the work of routing protocols easier because the links are all stable. This approach proves to be suboptimal in terms of either capacity or energy reduction since long hops albeit unreliable may contribute significantly to the overall con- nectivity. An open issue is then to quantify how much the connectivity could be improved by taking unreliable links into account. This issue is addressed in this paper in the case of having block-fading channels. A tight bound is an- alytically derived for the mean node degree from a cross- layer point of view. Modulation, packet size, power detec- tion level and link reliability are all considered in the pro- posed formulation.
Bandwidth Allocation Mechanism of ForCES Transport Mapping Layer Based on TCP/IP
Authors: Jianqun Chen, Weiming Wang, Bin Zhuge
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

In order to avoid the DoS attack for the ForCES router from redirect messages, the paper proposes a bandwidth allocation mechanism called Rate and Queue controlled Dynamic Probabilistic Priority (RQDPP) based on ForCES Transport Mapping Layer (ForCES TML). The algorithm tries to calculate refusing probability of an incoming packet by per-flow estimated arrival rate and buffer occupancy. According to message's kind and refusing probability, the algorithm dynamically adjusts probability parameter which is used for scheduler to allocate and transmit different messages. Simulation results show the effect
Rule-based intelligent adaptation in mobile information systems
Authors: Shiow-yang Wu, Chun-Shun Chang, Shih-Hsun Ho, Hung-Shun Chao
Venue: Expert Systems with Applications: An International Journal (2008)

The ability to adapt to changes is among the most important issues in mobile information systems. We propose a rule-based modular framework for building self-adaptive applications in mobile environments. A common mobile event engine for all applications is employed to detect the status changes. The rule system plays the role of a reactive component for making proper decisions in response to the changes. A general database interface ensures seamless integration of the rule system with database systems for flexible information access. For efficient rule processing, we develop techniques that combine static and dynamic analysis to uncover phase structure and data access semantics of a rule program. The semantic information is used to facilitate intelligent caching and prefetching for conserving limited bandwidth and reducing rule processing cost. A distributed data management and rule execution strategy enable adaptive information services over changing environment, even under disconnection. We devise a performance model to characterize the exact condition for our approach to be superior than traditional approach. Trace-driven simulation results successfully demonstrate the feasibility and potential of our approach. The modularity of the framework permits fast implementation based on off-the-shelf rule systems and database packages. We present a prototype implementation and preliminary evaluation results to show that our techniques can be effectively materialized.
Creating and visualizing test data from programming exercises
Authors: Petri Ihantola
Venue: Informatics in education (2007)

Automatic assessment of programming exercises is typically based on testing approach. Most automatic assessment frameworks execute tests and evaluate test results automatically, but the test data generation is not automated. No matter that automatic test data generation techniques and tools are available. We have researched how the Java PathFinder software model checker can be adopted to the specific needs of test data generation in automatic assessment. Practical problems considered are: how to derive test data directly from students' programs (i.e., without annotation) and how to visualize and how to abstract test data automatically for students? Interesting outcomes of our research are that with minor refinements generalized symbolic execution with lazy initialization (a test data generation algorithm implemented in PathFinder) can be used to construct test data directly from students' programs without annotation, and that intermediate results of the same algorithm can be used to provide novel visualizations of the test data.
Serial Hybrid Computation and Errors in Hybrid Loops
Authors: W. D. Little
Venue: IEEE Transactions on Computers (1973)

This paper considers the stability and errors associated with various combinations of hybrid simulation modes, sampling sequences, and compensating schemes.
Performance Modelling of Priority Queuing Discipline under Self-Similar and Poisson Traffic
Authors: Xiaolong Jin, Geyong Min
Venue: Proceedings of the 32nd IEEE Conference on Local Computer Networks (2007)

The priority queueing discipline plays a crucial role in the Differentiated Services (DiffServ) architecture. Analytical modelling and performance evaluation of priority queueing systems have received significant research efforts in the telecommunication community. However, most existing studies have primarily focused on the analysis of such systems under either Short Range Dependent (SRD) or Long Range Dependent (LRD) traffic only. With the aim of investigating the impact of heterogeneous traffic on the design and performance of telecommunication networks, this paper presents an analytical model for priority queueing systems subject to heterogeneous LRD self-similar and SRD Poisson traffic. We extend the application of the generalized Schilder's theorem to deal with heterogeneous traffic and further develop the analytical upper and lower bounds for the queue length distributions of individual traffic flows. Through extensive comparisons between analytical bounds and simulation results, we validate the effectiveness and accuracy of the developed model.
Identifying opinion leaders in the blogosphere
Authors: Xiaodan Song, Yun Chi, Koji Hino, Belle Tseng
Venue: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management (2007)

Opinion leaders are those who bring in new information, ideas, and opinions, then disseminate them down to the masses, and thus influence the opinions and decisions of others by a fashion of word of mouth. Opinion leaders capture the most representative opinions in the social network, and consequently are important for understanding the massive and complex blogosphere. In this paper, we propose a novel algorithm called InfluenceRank to identify opinion leaders in the blogosphere. The InfluenceRank algorithm ranks blogs according to not only how important they are as compared to other blogs, but also how novel the information they can contribute to the network. Experimental results indicate that our proposed algorithm is effective in identifying influential opinion leaders.
BeepBeep: a high accuracy acoustic ranging system using COTS mobile devices
Authors: Chunyi Peng, Guobin Shen, Yongguang Zhang, Yanlin Li, Kun Tan
Venue: Proceedings of the 5th international conference on Embedded networked sensor systems (2007)

We present the design, implementation, and evaluation of BeepBeep, a high-accuracy acoustic-based ranging system. It operates in a spontaneous, ad-hoc, and device-to-device context without leveraging any pre-planned infrastructure. It is a pure software-based solution and uses only the most basic set of commodity hardware -- a speaker, a microphone, and some form of device-to-device communication -- so that it is readily applicable to many low-cost sensor platforms and to most commercial-off-the-shelf mobile devices like cell phones and PDAs. It achieves high accuracy through a combination of three techniques: two-way sensing, self-recording, and sample counting. The basic idea is the following. To estimate the range between two devices, each will emit a specially-designed sound signal ("Beep") and collect a simultaneous recording from its microphone. Each recording should contain two such beeps, one from its own speaker and the other from its peer. By counting the number of samples between these two beeps and exchanging the time duration information with its peer, each device can derive the two-way time of flight of the beeps at the granularity of sound sampling rate. This technique cleverly avoids many sources of inaccuracy found in other typical time-of-arrival schemes, such as clock synchronization, non-real-time handling, software delays, etc. Our experiments on two common cell phone models have shown that we can achieve around one or two centimeters accuracy within a range of more than ten meters, despite a series of technical challenges in implementing the idea.
A Population-Based Incremental Learning Algorithm with Elitist Strategy
Authors: Qingbin Zhang, Tihua Wu, Bo Liu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

The Population-Based Incremental Learning (PBIL) is a novel evolutionary algorithm combined the mechanisms of the Genetic Algorithm with competitive learning. In this paper, the influence of the number of selected best solutions on the convergence speed of the PBIL is studied by experiment. Based on experimental results, a PBIL algorithm with elitist strategy, named Double Learning PBIL (DLPBIL), is proposed. The new algorithm learns both the selected best solutions in current population and the optimal solution found so far in the algorithm at same time. Experimental results show that the DLPBIL out-performs the standard PBIL. Both the convergence speed and the solution quality are improved.
Biswapped Networks and Their Topological Properties
Authors: Wenjun Xiao, Weidong Chen, Mingxin He, Wenhong Wei, Behrooz Parhami
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02 (2007)

In this paper, we propose a new class of interconnection networks, called "biswapped networks" (BSNs). Each BSN is built of 2n copies of some n-node basis network using a simple rule for connectivity that ensures its regularity, modularity, fault tolerance, and algorithmic efficiency. In particular, if the basis network is a Cayley digraph then so is the resulting BSN. Our proposed networks provide a systematic construction strategy for large, scalable, modular, and robust parallel architectures, while maintaining many desirable attributes of the underlying basis network that comprises its clusters. We show how key parameters of a BSN are related to the corresponding parameters of its basis network and obtain a number of results on internode distances, Hamiltonian cycles, and node-disjoint paths. We also discuss the relationship between BSNs and swapped or OTIS networks.
Dialogs taking into account experience, emotions and personality
Authors: Anne-Gwenn Bosser, Guillaume Levieux, Karim Sehaba, Axel Buendia, Vincent Corruble, Guillaume de Fondaumière
Venue: Proceedings of the 2nd international conference on Digital interactive media in entertainment and arts (2007)

This paper describes the DEEP project (Dialogs taking into account Experience, Emotions and Personality, adapted to computer games), which started in June 2006. The aim of the project is to provide generic solutions for the integration of autonomous Non Player Characters (NPCs) in next-generation adventure games. DEEP NPCs, equipped with a personality and a believable emotional engine, will use context-based information from the game environment and the player behavior to provide entertaining, rich and relevant dialogs.