ppxscal/embedding_network huggingface dataset:
Mining Open Source Component Behavior for Reuse Evaluation
Authors: Ji Wu, Chun Wang, Xiao-Xia Jia, Chao Liu
Venue: Proceedings of the 10th international conference on Software Reuse: High Confidence Software Reuse in Large Systems (2008)

Reusing Open Source Component (OSC) has become more and more popular in developing in-house applications. Before integrating an OSC into project, the component has to be evaluated according to the project. This paper proposes the usage and dependency model to help understand OSC from the interactions with its usage context. The usage and dependency model extends the traditional usage model with the context dependency and backward dependency, which are widely observed in open source project. Based on the usage model, this paper proposes three metrics to measure the interaction complexity. To construct the usage and dependency model, the invocation matrix and the mining algorithm are proposed. The framework component in open source project Junit 4.4 is selected to validate this research.
Multiple-Differential Side-Channel Collision Attacks on AES
Authors: Andrey Bogdanov
Venue: Proceeding sof the 10th international workshop on Cryptographic Hardware and Embedded Systems (2008)

In this paper, two efficient multiple-differential methods to detect collisions in the presence of strong noise are proposed - binary and ternary voting. After collisions have been detected, the cryptographic key can be recovered from these collisions using such recent cryptanalytic techniques as linear [1] and algebraic [2] collision attacks. We refer to this combination of the collision detection methods and cryptanalytic techniques as multiple-differential collision attacks (MDCA).When applied to AES, MDCA using binary voting without profiling requires about 2.7 to 13.2 times less traces than the Hamming-weight based CPA for the same implementation. MDCA on AES using ternary voting with profiling and linear key recovery clearly outperforms CPA by requiring only about 6 online measurements for the range of noise amplitudes where CPA requires from 163 to 6912 measurements. These attacks do not need the S-box to be known. Moreover, neither key nor plaintexts have to be known to the attacker in the profiling stage.
A Practical Evaluation of BioProvider
Authors: Maira Ferreira Noronha, Sergio Lifschitz, Antonio Basilio Miranda
Venue: Proceedings of the 3rd Brazilian symposium on Bioinformatics: Advances in Bioinformatics and Computational Biology (2008)

We present here an instantiation of BioProvider, a tool that efficiently provides data for biological applications, tailored to the way BLAST demands data. We briefly discuss some of the factors that may influence data availability and performances.
Bio-ontologies Tutorial
Authors: Olivier Dameron, Julie Chabalier
Venue: Proceedings of the 5th international workshop on Data Integration in the Life Sciences (2008)

We organize a three hours tutorial about bio-ontologies and OWL-DL during the DILS'2008 conference.The first part will present the motivations for using ontologies in the context of bioinformatics. Likewise, it will present the reference ontologies of the domain (Gene Ontology, BioPAX, ...) and their typical use (e.g. Gene Ontology Annotation).The second part will be more hands-on oriented and will focus on the basic principles for creating a simple ontology. We will cover the creation of subclasses and of relations. At the time of the break, we will have demonstrated the expressivity of RDFS.
The Tracking Speed of Continuous Attractors
Authors: Si Wu, Kosuke Hamaguchi, Shun-Ichi Amari
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

Continuous attractor is a promising model for describing the encoding of continuous stimuli in neural systems. In a continuous attractor, the stationary states of the neural system form a continuous parameter space, on which the system is neutrally stable. This property enables the neutral system to track time-varying stimulus smoothly. In this study we investigate the tracking speed of continuous attractors. In order to analyze the dynamics of a large-size network, which is otherwise extremely complicated, we develop a strategy to reduce its dimensionality by utilizing the fact that a continuous attractor can eliminate the input components perpendicular to the attractor space very quickly. We therefore project the network dynamics onto the tangent of the attractor space, and simplify it to be a one-dimension Ornstein-Uhlenbeck process. With this approximation we elucidate that the reaction time of a continuous attractor increases logarithmically with the size of the stimulus change. This finding may have important implication on the mental rotation behavior.
A non-conventional quality control system to detect surface faults in mechanical front seals
Authors: L. Barelli, G. Bidini, F. Mariani, M. Svanziroli
Venue: Engineering Applications of Artificial Intelligence (2008)

The Just in Time and the Total Quality policies have remarkably touched every field of modern industrial production. This context prompts companies to dedicate most of their efforts on researching and developing automatic systems of quality control to obtain the elevated standards of quality nowadays demanded by the market at every level of production. In fact the quantity of the exemplars allowed, which are not up to sample, is measured in parts per million in many sectors of production. Many methodologies have been proposed to yield high quality in the industrial production lines, in order to provide surface examination and classification. This paper describes an alternative system for surface analysis based on artificial neural networks (ANNs), developed in collaboration with the Italian manufacturer ''Meccanotecnica Umbra S.p.A''. This system was implemented and tested in order to examine three particular surfaces of mechanical seals achieving good results in comparison with the deterministic system already implemented.
A Worm Model Based on Artificial Life for Automatic Segmentation of Medical Images
Authors: Jian Feng, Xueyan Wang, Shuqian Luo
Venue: Medical Imaging and Informatics: 2nd International Conference, MIMI 2007, Beijing, China, August 14-16, 2007 Revised Selected Papers (2008)

An intelligent deformable model called worm model is constructed. The worm has a central nervous system, vision, perception and motor systems. It is able to memorize, recognize objects and control the motion of its body. The new model overcomes the defects of existing methods since it is able to process the segmentation of the image intelligently using more information available rather than using pixels and gradients only. The experimental results of segmentation of the corpus callosum from MRI brain images show that the proposed worm model is able to segment medical images automatically and accurately. For those images that are more complex or with fragmentary boundaries, the predominance of the worm model is especially clear.
P4p: provider portal for applications
Authors: Haiyong Xie, Y. Richard Yang, Arvind Krishnamurthy, Yanbin Grace Liu, Abraham Silberschatz
Venue: ACM SIGCOMM Computer Communication Review (2008)

As peer-to-peer (P2P) emerges as a major paradigm for scalable network application design, it also exposes significant new challenges in achieving efficient and fair utilization of Internet network resources. Being largely network-oblivious, many P2P applications may lead to inefficient network resource usage and/or low application performance. In this paper, we propose a simple architecture called P4P to allow for more effective cooperative traffic control between applications and network providers. We conducted extensive simulations and real-life experiments on the Internet to demonstrate the feasibility and effectiveness of P4P. Our experiments demonstrated that P4P either improves or maintains the same level of application performance of native P2P applications, while, at the same time, it substantially reduces network provider cost compared with either native or latency-based localized P2P applications.
Hierarchical SVM Classification for Localization in Multilevel Sensor Networks
Authors: Jerzy Martyna
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

We show that the localization problem for multilevel wireless sensor networks (WSNs) can be solved as a pattern recognition with the use of the Support Vector Machines (SVM) method. In this paper, we propose a novel hierarchical classification method that generalizes the SVM learning and that is based on discriminant functions structured in such a way that it contains the class hierarchy. We study a version of this solution, which uses a hierarchical SVM classifier. We present experimental results the hierarchical SVM classifier for localization in multilevel WSNs. 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
Gaming, Fine Art, and Familiar Strangers
Authors: Nuno Correia, Luis Romero, Jorge Santiago, Kalle Jegers, Mikael Wiberg, Eric Paulos, Robert Wechsler, Frieder Weiss, Duncan McCaffery, Joe Finney, Stefan Schmid, Andrew Scott, Simon Lock, Jennifer G. Sheridan, Adam T. Lindsay, Stewart Kember, Peter Phillips, Jen Allanson
Venue: IEEE Pervasive Computing (2004)

For this issue's Works in Progress, we have six abstracts in the areas of pervasive gaming, interactive entertainment, and interpersonal interactions. Three of the abstracts cover gaming systems that combine physical and virtual environments. These discuss new development frameworks and toolkits, analyze how users interact in gaming environments, and evaluate new technology for these environments. Two abstracts discuss interactive digital art: a system that observes and interacts with dancers and a methodology, and a toolkit for designing new digital art systems. The final abstract describes a system for helping individuals better understand the subtle interactions that they have with the people around them ("familiar strangers").
701 Recollections
Authors: Jerrier A. Haddad
Venue: IEEE Annals of the History of Computing (1983)

His paper describes not only the development of the 701, but also the organization and implementation of release engineering and the selection and training of customer engineers. 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
The Cordic Magnification Function
Authors: Raymond Vachss
Venue: IEEE Micro (1987)

This analysis shows that the Cordic scaling constant need not be evaluated for each word length. On the contrary, a single ?master? constant can be used for all cases. 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
A Digitally Reconfigurable Low Pass Filter for Multi-mode Direct Conversion Receivers
Authors: Gabor Csipkes, Sorin Hintea, Doris Csipkes, Cristian Rus, Lelia Festila, Hernando Fernandez-Canque
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

This paper presents a novel approach to the design of integrated reconfigurable and programmable analog filters for commercial mobile applications. The method is described in the specific context of an analog filter, dedicated to multi-mode receiver front ends employing direct frequency conversion. The filter has been designed using state variables and leap-frog OTA-C techniques, features programmable order, digitally variable frequency parameters and wide linear range, while supporting several standard approximations. The fundamental OTA cell has been implemented with fully balanced second generation current conveyors, suitable for low voltage operation. The novel method is demonstrated by presenting the simulation results of the filter, designed for a 0.18 μm CMOS technology.
Combining Classifiers through Triplet-Based Belief Functions
Authors: Yaxin Bi, Shengli Wu, Xuhui Shen, Pan Xiong
Venue: Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I (2008)

Classifier outputs in the form of continuous values have often been combined using linear sum or stacking, but little is generally known about evidential reasoning methods for combining truncated lists of ordered decisions. In this paper we introduce a novel class-indifferent method for combining such a kind of classifier decisions. Specifically we model each output given by classifiers on new instances as a list of ranked decisions that is divided into 2 subsets of decisions, which are represented by triplet-based belief functions and then are combined using Dempster's rule of combination. We present a formalism for triplet-based belief functions and establish a range of general formulae for combining these beliefs in order to arrive at a consensus decision. In addition we carry out a comparative analysis with an alternative representation dichotomous belief functions on the UCI benchmark data. We also compare our combination method with the popular methods of stacking, boosting, linear sum and majority voting over the same benchmark data to demonstrate the advantage of our approach.
Gabor-Based Discriminative Common Vectors for Gait Recognition
Authors: Xiaochao Yang, Ji Dai, Yue Zhou, Jie Yang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

This paper presents a novel method for identity recognition based on the 2D gait representation: Gait Energy Image (GEI) which is the averaged silhouette over one gait cycle. An ensemble of Gabor kernels is first convolved with GEI to extract discriminative feature. The obtained Gabor gait representation is then projected into lower dimensional subspace using discriminative common vectors (DCV) analysis. The final classification is performed in this subspace. The proposed method is tested on the USF HumanID Database. Experimental results show that Gabor-based method can improve recognition rate, and DCV is superior to other traditional dimensional reduction algorithm in the gait recognition application.
Revisiting SIMD Programming
Authors: Anton Lokhmotov, Benedict R. Gaster, Alan Mycroft, Neil Hickey, David Stuttard
Venue: Languages and Compilers for Parallel Computing: 20th International Workshop, LCPC 2007, Urbana, IL, USA, October 11-13, 2007, Revised Selected Papers (2007)

Massively parallel SIMD array architectures are making their way into embedded processors. In these architectures, a number of identical processing elements having small private storage and using asynchronous I/O for accessing large shared memory executes the same instruction in lockstep.In this paper, we outline a simple extension to the C language, called C n , used for programming a commercial SIMD array architecture. The design of C n is based on the concept of the SIMD array type architecture and revisits first principles of designing efficient and portable parallel programming languages. C n has a low level of abstraction and can also be seen as an intermediate language in the compilation from higher level parallel languages to machine code.
Maintenance of Monitoring Systems Throughout Self-healing Mechanisms
Authors: Clarissa Cassales Marquezan, André Panisson, Lisandro Zambenedetti Granville, Giorgio Nunzi, Marcus Brunner
Venue: Proceedings of the 19th IFIP/IEEE international workshop on Distributed Systems: Operations and Management: Managing Large-Scale Service Deployment (2008)

Monitoring is essential in modern network management. However, current monitoring systems are unable to recover their internal faulty entities forcing the network administrator to manually fix the occasionally broken monitoring solution. In this paper we address this issue by introducing a self-healing monitoring solution. This solution is described considering a scenario of a monitoring system for a Network Access Control (NAC) installation. The proposed solution combines the availability provided by P2P-based overlays with self-healing abilities. This paper also describes a set of experimental evaluations whose results present the tradeoff between the time required to recover the monitoring infrastructure when failures occur, and the associated bandwidth consumed in this process. Based on the experiments we show that it is possible to improve availability and robustness with minimum human intervention.
Redpin - adaptive, zero-configuration indoor localization through user collaboration
Authors: Philipp Bolliger
Venue: Proceedings of the first ACM international workshop on Mobile entity localization and tracking in GPS-less environments (2008)

Redpin is a fingerprint-based indoor localization system designed and built to run on mobile phones. The basic principles of our system are based on known systems like Place Lab or Radar. However, with Redpin it is possible to consider the signal-strength of GSM, Bluetooth, and WiFi access points on a mobile phone. Moreover, we devised methods to omit the time-consuming training phase and instead incorporate a folksonomy-like approach where the users train the system while using it. Finally, this approach also enables the system to expeditiously adapt to changes in the environment, caused for example by replaced access points.
Infrastructure Leasing Problems
Authors: Barbara M. Anthony, Anupam Gupta
Venue: Proceedings of the 12th international conference on Integer Programming and Combinatorial Optimization (2007)

Consider the following Steiner Tree leasing problem. Given a graph G = (V,E) with root r, and a sequence of terminal sets D t ¿ V for each day t ¿ [T]. A feasible solution to the problem is a set of edges E t for each t connecting D t to r. Instead of obtaining edges for a single day at a time, or for infinitely long (both of which give Steiner tree problems), we lease edges for say, { a day, a week, a month, a year }. Naturally, leasing an edge for a longer period costs less per unit of time. What is a good leasing strategy? In this paper, we give a general approach to solving a wide class of such problems by showing a close connection between deterministic leasing problems and problems in multistage stochastic optimization. All our results are in the offline setting.
Agent Based Load Balancing Middleware for Service-Oriented Applications
Authors: Jun Wang, Yi Ren, Di Zheng, Quan-Yuan Wu
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

Kinds of load balancing middleware have already been applied successfully in distributed computing. However, they don't take the services types into consideration and for different services requested by clients the workload would be different out of sight. Furthermore, traditional load balancing middleware uses the fixed and static replica management and uses the load migration to relieve overload. However, to the complex service-oriented applications, the hosts may be heterogeneous and decentralized at all and load migration is not efficient for the existence of the delay. Therefore, we put forward an Agent based autonomic load balancing middleware to support fast response, hot-spot control and balanced resource allocation among different services. Corresponding simulation tests are implemented and their result s indicated that this model and its supplementary mechanisms are suitable to complex service-oriented applications.
Using Metrics to Improve Software Testing
Authors: Alfred Sorkowitz
Venue: Proceedings of the 8th international conference on Product-Focused Software Process Improvement (2007)

Software Metrics can aid in improving your organizations Testing Process by (1) providing insight and early visibility into the "real" status of the testing effort, and (2) aid in making assessments as to whether progress, productivity and quality goals are being met. This tutorial presents a practical guide on how to start taking advantage of these new tools/techniques to aid in improving the testing process. These metric based tools and techniques have successfully been used by (1) software test teams, (2) software developers and, (3) SQA and IV V staffs. 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
Maximum Margin Active Learning for Sequence Labeling with Different Length
Authors: Haibin Cheng, Ruofei Zhang, Yefei Peng, Jianchang Mao, Pang-Ning Tan
Venue: Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects (2008)

Sequence labeling problem is commonly encountered in many natural language and query processing tasks. SVM struct is a supervised learning algorithm that provides a flexible and effective way to solve this problem. However, a large amount of training examples is often required to train SVM struct , which can be costly for many applications that generate long and complex sequence data. This paper proposes an active learning technique to select the most informative subset of unlabeled sequences for annotation by choosing sequences that have largest uncertainty in their prediction. A unique aspect of active learning for sequence labeling is that it should take into consideration the effort spent on labeling sequences, which depends on the sequence length. A new active learning technique is proposed to use dynamic programming to identify the best subset of sequences to be annotated, taking into account both the uncertainty and labeling effort. Experiment results show that our SVM struct active learning technique can significantly reduce the number of sequences to be labeled while outperforming other existing techniques.
A Dimensioning and Deployment Tool for on Demand Policy-Based Resource Management System
Authors: Kamel Haddadou, Samir Ghamri-Doudane, Yacine Ghamri-Doudane, Nazim Agoulmine
Venue: Proceedings of the 11th IFIP/IEEE international conference on Management of Multimedia and Mobile Networks and Services: Management of Converged Multimedia Networks and Services (2008)

Today the Policy-Based Management (PBM) approach is recognized as an efficient solution to simplify the complex task of managing and controlling networks. To this end, the IETF has introduced a reference framework to build PBM systems. However, this framework only addresses the provisioning of relatively long validity period services based on pre-defined SLAs (Service Level Agreements). Furthermore, very little work addresses the scalability properties of the instantiation of this framework in a real network. In our previous work, we presented an extension of the IETF PBM framework in order to support dynamic provisioning of short term services (end-system signaling) as well as an instantiation scheme that is scalable (distributed provisioning of edge routers). This instantiation scheme is based on the distribution of the provisioning process while keeping centralized only the parts that involve critical resources, namely the Bandwidth Brokerage. In this paper, we propose an extensive analytical study of this extended architecture. The results of this work are intended to be used as a guideline to help network operators to design a scalable PBM system in order to offer to their customers' services with QoS assurance in an on-demand basis.