ppxscal/embedding_network huggingface dataset:
Reducing International Roaming Costs for Global Enterprise Mobility
Authors: John Buford
Venue: Proceedings of the The 2007 International Conference on Next Generation Mobile Applications, Services and Technologies (2007)

Global enterprises typically face large costs for worker mobility, particularly for high-volume communications in international roaming. This is the case whether the enterprise manages their own communications network or relies on a service provider. As both carrier and enterprise communications networks move to SIP-based signaling, the challenge is to support seamless mobility economically while retaining rich call processing features and unified communications. We describe an architecture we are implementing and compare it with other possible approaches.
Scaled conjugate gradient algorithms for unconstrained optimization
Authors: Neculai Andrei
Venue: Computational Optimization and Applications (2007)

In this work we present and analyze a new scaled conjugate gradient algorithm and its implementation, based on an interpretation of the secant equation and on the inexact Wolfe line search conditions. The best spectral conjugate gradient algorithm SCG by Birgin and Martínez (2001), which is mainly a scaled variant of Perry's (1977), is modified in such a manner to overcome the lack of positive definiteness of the matrix defining the search direction. This modification is based on the quasi-Newton BFGS updating formula. The computational scheme is embedded in the restart philosophy of Beale---Powell. The parameter scaling the gradient is selected as spectral gradient or in an anticipative manner by means of a formula using the function values in two successive points. In very mild conditions it is shown that, for strongly convex functions, the algorithm is global convergent. Preliminary computational results, for a set consisting of 500 unconstrained optimization test problems, show that this new scaled conjugate gradient algorithm substantially outperforms the spectral conjugate gradient SCG algorithm.
A Heuristic Procedure for the Partitioning and Mapping of Computer Logic Graphs
Authors: R. L. Russo, P. H. Oden, P. K. Wolff
Venue: IEEE Transactions on Computers (1971)

A heuristic procedure for partitioning or mapping a set of interconnected blocks into subsets called modules is presented. Each module may be constrained in terms of the number of blocks and/or the number of intermodule connections that it can accommodate. The procedure allows given blocks to be mapped to more than one module in order to reduce the number of modules required if such reduction is desirable. Results obtained from applying the procedure, by means of a computer program, to the partitioning and mapping of computer logic gates into chips and cards are presented.
A heuristic routing mechanism using a new addressing scheme
Authors: M. Ravanbakhsh, Y. Abbasi-Yadkori, M. Abbaspour, H. Sarbazi-Azad
Venue: Proceedings of the 1st international conference on Bio inspired models of network, information and computing systems (2006)

Current methods of routing are based on network information in the form of routing tables, in which routing protocols determine how to update the tables according to the network changes. Despite the variability of data in routing tables, node addresses are constant. In this paper, we first introduce the new concept of variable addresses, which results in a novel framework to cope with routing problems using heuristic solutions. Then we propose a heuristic routing mechanism based on the application of genes for determination of network addresses in a variable address network and describe how this method flexibly solves different problems and induces new ideas in providing integral solutions for variety of problems. The case of ad-hoc networks is where simulation results are more supportive and original solutions have been proposed for issues like mobility.
A Business Modeled Approach for Trust Management in P2P
Authors: T. Srinivasan, Vidya Priyadarshini, Smrithika Appaiah
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

P2P communities, is a method for arranging large numbers of peers in a self configuring peer relationship based on declared attributes (or interests) of the participating peers. This method is expected to have an impact in sharing of resources and pruning of search spaces based on the interests of the clients. Current peer-to- peer systems are targeted for information sharing, file storage, searching and indexing often using an overlay network. In this paper we expand the scope of peer-to-peer systems to include the concept of a business environment analogous to a "stock market". Our work focuses on efficient methods to discover trustworthy peers in the P2P network. We investigate the behavior of randomly created relationships formed during transaction between Vendors and Emptors. Discovering services on the fly is essential to being able to identify profitable oriented transactions. In addition, efficient Vendor/Emptor based algorithms allow us to manage quickly changing market trends. Moreover the inclusion of the concept of trading policies among business communities enhances the probability of mutual gain.
Extending CSP to Allow Dynamic Resource Management
Authors: A. Silberschatz
Venue: IEEE Transactions on Software Engineering (1983)

In his paper "Communicating Sequential Processes," Hoare suggested the use of the input/output construct and Dijkstra's guarded commands for handling the task of communication and synchronization in distributed systems. Hoare's proposal was intended for programming general parallel systems; as a result, little consideration was given by Hoare to the question of how his mechanisms could be utilized in the construction of reliable dynamic resource management schemes. In this paper, we examine this problem and propose several simple extensions to Hoare's constructs that will make the extended Communicating Sequential Processes concept more suitable for the handling of such management schemes.
A Implementation of Object Oriented Database Security
Authors: Premchand B. Ambhore, B. B. Meshram, V. B. Waghmare
Venue: Proceedings of the 5th ACIS International Conference on Software Engineering Research, Management & Applications (2007)

This paper is to address high-level authorization specifications and its efficient implementation in object oriented database scenario. Premchand Ambhore is with higher and technical education, maharashtra state, india, Email: pbambhore@yahoo.com . The rest of the paper is organized as follows. Section 2 specifies object oriented database system; section 3 incorporates authorization rules into database and section 4 maps the specification into a logic programming language and implements the language. Section 5 concludes the paper. The integration of object-oriented programming concepts with databases is one of the most significant advances in the evolution of database system, therefore the problems involved in providing data security for object oriented databases have been receiving very great attention from researchers. As a matter of fact, data are the most sensitive part of any system and its loss or compromise can have disastrous consequences. We discuss three different types of access: Discretionary access control (DAC), Mandatory access control (MAC) and role based access control (RBAC) in Relational DBMS and object oriented data bases. We have identified some of the issues and current proposals; current security models in object oriented database systems and outline possible direction issues for future research.
Information extraction from calls for papers with conditional random fields and layout features
Authors: Karl-Michael Schneider
Venue: Artificial Intelligence Review (2006)

For members of the research community it is vital to stay informed about conferences, workshops, and other research meetings relevant to their field. These events are typically announced in calls for papers (CFPs) that are distributed via mailing lists. We employ Conditional Random Fields for the task of extracting key information such as conference names, titles, dates, locations and submission deadlines from CFPs. Extracting this information from CFPs automatically has applications in building automated conference calendars and search engines for CFPs. We combine a variety of features, including generic token classes, domain-specific dictionaries and layout features. Layout features prove particularly useful in the absence of grammatical structure, improving average F1 by 30% in our experiments.
A Framework for False Positive Suppression in Video Segmentation
Authors: Min Han Tun, Geoff West, Tele Tan
Venue: Proceedings of the 14th International Conference on Image Analysis and Processing (2007)

Object detection in video surveillance is typically done through background subtraction or temporal differencing. While these techniques perform very well under scenes where there are minimal light changes, they begin to fail when the scene contains rapid illumination changes. The effects of this is most profound in indoor environments. Under these conditions, the background modeling techniques produce large numbers of false positives. This paper proposes a sequential approach to suppressing these false positives. Both frame and region level spatial scales are considered to detect sudden light changes and make use of Gabor filter responses and edge maps to identify and remove false positives.
Visual pivot-table components for web application development
Authors: Takao Shimomura, Kenji Ikeda, Quan Liang Chen, Nhor Sok Lang, Muneo Takahashi
Venue: Proceedings of the third conference on IASTED International Conference: Advances in Computer Science and Technology (2007)

This paper presents the automatic generation of Web applications that make use of pivot tables. The pivot tables sum up various kinds of data in two dimensions as in Microsoft Excel. They reduce the amount of code to be written by developers greatly. The paper also describes the BioPro system that implements these tables as visual Web components. This system assists in the development of Web applications based on the page-transition framework that models a Web application as a set of transitions of Web pages, and using visual Web components, makes it easier to write processes executed when a Web page transfers to another.
Robust hybrid architecture to signals from manufacturing and machine monitoring sensors
Authors: Ahmed Hambaba
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2000)

The design and implementation of effective control of manufacturing processes depends on the successful monitoring and recognition of process signals. In this paper, we describe an application of robust hybrid model to the prediction of plasma etcher outcome; etcher rate, selectivity, and uniformity. The robust hybrid model consists of two main architectures: robust model and recurrent neural network with real-time recurrent learning. The residual errors are used for the tuning of the weights of the recurrent neural network. The robust hybrid model's performance is compared to Ordinary Least-Square method, Alpha-trimmed mean, and Back-Propagation neural network. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Tutorial: Computer System Advantages of Magnetic Bubble Memories
Authors: D. P. Bhandarkar
Venue: Computer (1975)

Magnetic bubbles, which offer improved access time over most conventional fixed-head disks, are now serious contenders for memory applications in computer systems. Current literature abounds in descriptions of various technological advances that have led to experimental memory systems.1,2,3Bubble memory chips containing up to 20,510 bits per chip have been exercised through transfer-read-transfer-circulate cycles in good loops at 100 KHz data rate.1An overview of current technology capabilities and a look into the future have been presented by H. Chang.4
Incorporating prior knowledge in support vector regression
Authors: Fabien Lauer, Gérard Bloch
Venue: Machine Learning (2008)

This paper explores the incorporation of prior knowledge in support vector regresion by the addition of constraints. Equality and inequality constraints are studied with the corresponding types of prior knowledge that can be considered for the method. These include particular points with known values, prior knowledge on any derivative of the function either provided by a prior model or available only at some specific points and bounds on the function or any derivative in a given domain. Moreover, a new method for the simultaneous approximation of multiple outputs linked by some prior knowledge is proposed. This method also allows consideration of different types of prior knowledge on single outputs while training on multiple outputs. Synthetic examples show that incorporating a wide variety of prior knowledge becomes easy, as it leads to linear programs, and helps to improve the approximation in difficult cases. The benefits of the method are finally shown on a real-life application, the estimation of in-cylinder residual gas fraction in spark ignition engines, which is representative of numerous situations met in engineering.
A general model for performance optimization of sequential systems
Authors: Dmitry Bufistov, Jordi Cortadella, Mike Kishinevsky, Sachin Sapatnekar
Venue: Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design (2007)

Retiming, c-slow retiming and recycling are different transformations for the performance optimization of sequential circuits. For retiming and c-slow retiming, different models that provide exact solutions have already been proposed. An exact model for recycling was yet unknown. This paper presents a general formulation that covers the combination of the three schemes for performance optimization. It provides an exact model based on integer linear programming that resorts to the structural theory of marked graphs. A set of experiments has been designed to show the benefits in performance obtained by combining retiming and recycling. The results also show the applicability of the method in large circuits.
A Context-Aware Framework for Mobile Navigation Service
Authors: Wonik Choi, Hyunduk Kim, Jinsu Kim, Jinseok Chae
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

As cellular network technologies continue to evolve, various network standards must coexist in most CDMA-based cellular networks. This means that mobile device users access mobile services over different network bandwidths according to the users' positions or the mobile devices' network access capabilities. Such differences of network bandwidths result in considerable differences in service response times. To address this problem, we present CANS (Context-Aware Framework for Mobile Navigation Services), a context-aware framework which takes into account the user's network profile to adapt the content for mobile device-based navigation services. Experimental results show that CANS can provide similar service response times regardless of type of wireless network to which users connect by adapting the content to network bandwidths.
A generic model for quantifiable software deployment
Authors: Peter H. Hughes, Jakob Sverre Lovstad
Venue: Proceedings of the International Conference on Software Engineering Advances (2007)

Model-driven design and development is based on the principle that all relevant attributes of a design can be associated with a design model. For performance-related attributes this is a difficult challenge. In component-oriented software development, recent approaches are based on associating performance annotations with the UML design descriptions. These are then transformed to an appropriate performance model. Problems with annotation approaches include that there are numerous design descriptions, none of which were developed for performance modelling purposes, and that the deployment aspect of UML is relatively underdeveloped. In this paper we offer a different approach, based on the Structure and Performance modelling paradigm (SP). This is a variable granularity static modelling framework designed specifically to capture those properties of software and its deployment which affect system performance. A coarsegrained structural model may be defined early in the design and refined as development proceeds, removing the need for a separate deployment model. By appropriate decomposition, it enables each designer or developer to provide quantitative estimates within their own domain. These can then be combined automatically. This helps to overcome the semantic gap between designers/developers and performance analysts. We consider two alternative avenues for exploiting the benefits of SP: either by enhancing the UML deployment diagram with OCL constraints, or by simply replacing it. The latter approach offers an evolutionary design/deployment model with the built-in advantage of quantifiability.
Meta tools for implementing domain specific visual languages
Authors: John Hosking, John Grundy
Venue: Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering (2007)

In this tutorial we present an overview of Domain-specific visual languages (DSVLs), DSVL-based software engineering tools and meta-tools for constructing DSVL-based tools. We present a motivation for DSVL usage in software engineering; examine several DSVL exemplar tools; illustrate the design of DSVLs including meta-model, notation and view type design; and compare and contrast several tools to realizing DSVLs. Included are three short group exercises in DSVL design.
Boosted Classification Trees and Class Probability/Quantile Estimation
Authors: David Mease, Abraham J. Wyner, Andreas Buja
Venue: The Journal of Machine Learning Research (2007)

The standard by which binary classifiers are usually judged, misclassification error, assumes equal costs of misclassifying the two classes or, equivalently, classifying at the 1/2 quantile of the conditional class probability function P[y=1|x]. Boosted classification trees are known to perform quite well for such problems. In this article we consider the use of standard, off-the-shelf boosting for two more general problems: 1) classification with unequal costs or, equivalently, classification at quantiles other than 1/2, and 2) estimation of the conditional class probability function P[y=1|x]. We first examine whether the latter problem, estimation of P[y=1|x], can be solved with LogitBoost, and with AdaBoost when combined with a natural link function. The answer is negative: both approaches are often ineffective because they overfit P[y=1|x] even though they perform well as classifiers. A major negative point of the present article is the disconnect between class probability estimation and classification. Next we consider the practice of over/under-sampling of the two classes. We present an algorithm that uses AdaBoost in conjunction with Over/Under-Sampling and Jittering of the data "JOUS-Boost". This algorithm is simple, yet successful, and it preserves the advantage of relative protection against overfitting, but for arbitrary misclassification costs and, equivalently, arbitrary quantile boundaries. We then use collections of classifiers obtained from a grid of quantiles to form estimators of class probabilities. The estimates of the class probabilities compare favorably to those obtained by a variety of methods across both simulated and real data sets.
An ABC Supported QoS Unicast Routing Scheme Based on the Ant Algorithm
Authors: Xingwei Wang, Guang Liang, Min Huang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 02 (2007)

In this paper, by introducing knowledge of fuzzy mathematics and microeconomics, a QoS unicast routing scheme with ABC supported is proposed based on the ant algorithm. Simulation results have shown that it is both feasible and effective with better performance.
Energy Sharing for Swarms Modeled on the Common Vampire Bat
Authors: Mark Witkowski
Venue: Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems (2007)

This article reports on observations arising from the use of a simulator in the conteXt of energy sharing (trophallaXis) that might be applied to swarms or communities of energy critical robots. Using food-sharing behavior reported for the common vampire bat species Desmodus rotundus, it is presumed that such robots would gather naturally occurring but limited fuel materials and convert them to energy as required. Energy sharing can bring substantial benefits to the group as a whole in situations where suitable materials are encountered unevenly by members of the population, in a manner insufficient to guarantee the continuing survival of any individual. Using the simulator the survivability of groups is investigated under various regimes, including sharing and non-sharing, the effects of energy dependents, group size and non-sharing defaulters. The role of reciprocation in feeding is also considered.
Middle Zone Component Extraction and Recognition of Telugu Document Image
Authors: Pratap Reddy L., Satyaprasad L., A. S. C. S. Sastry
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02 (2007)

Telugu is one of the ancient languages of South India. It has a complex orthography with a large number of distinct character shapes composed of simple and compound characters. The work reported in literature till the recent period is based on the connected component approach. Less attention is observed on the generalized character model and its application in the OCR development. Script syllable follows canonical structure where a consonant vowel core is preceded by one or two optional consonants .Formation of a syllable posses unique structural nature. In the present work, structural features of the syllable and the component model are combined to extract middle zone components. The shape of the middle zone components is closely related to a circle whereas other components are found with different topological features. Recognition rate of 99 percent is observed with the proposed method.
Presentation sensei: a presentation training system using speech and image processing
Authors: Kazutaka Kurihara, Masataka Goto, Jun Ogata, Yosuke Matsusaka, Takeo Igarashi
Venue: Proceedings of the 9th international conference on Multimodal interfaces (2007)

In this paper we present a presentation training system that observes a presentation rehearsal and provides the speaker with recommendations for improving the delivery of the presentation, such as to speak more slowly and to look at the audience. Our system "Presentation Sensei" is equipped with a microphone and camera to analyze a presentation by combining speech and image processing techniques. Based on the results of the analysis, the system gives the speaker instant feedback with respect to the speaking rate, eye contact with the audience, and timing. It also alerts the speaker when some of these indices exceed predefined warning thresholds. After the presentation, the system generates visual summaries of the analysis results for the speaker's self-examinations. Our goal is not to improve the content on a semantic level, but to improve the delivery of it by reducing inappropriate basic behavior patterns. We asked a few test users to try the system and they found it very useful for improving their presentations. We also compared the system's output with the observations of a human evaluator. The result shows that the system successfully detected some inappropriate behavior. The contribution of this work is to introduce a practical recognition-based human training system and to show its feasibility despite the limitations of state-of-the-art speech and video recognition technologies.