ppxscal/embedding_network huggingface dataset:
Surveying the Risks and Benefits of IT Outsourcing
Authors: G. Reza Djavanshir
Venue: IT Professional (2005)

In a global economy fueled by advances in telecommunications and information technologies, offshore outsourcing is evolving from conventional international-trade practices. Today, companies are looking at all their business activities with an eye toward retaining some in-house and outsourcing others. A recent survey conducted by the author of senior IT managers provides insight into both the pros and cons of offshore outsourcing.
Statistical analysis of simulation output data
Authors: Robert G. Sargent
Venue: ACM SIGSIM Simulation Digest (1977)

This paper is a tutorial paper on how to obtain point estimates and confidence intervals of steady state means of simulation output data. The methods of using replications, batch means, and regenerative cycles for obtaining these point and interval estimates are discussed in detail and are applied to a simple time-shared computer model to illustrate their use. A brief discussion is included on using time series methods to obtain these estimates. The advantages and disadvantages of the various methods are given, including specific recommendations as to when certain methods might be used.
Network Management Challenges for Next Generation Networks
Authors: Mo Li, Kumbesan Sandrasegaran
Venue: Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary (2005)

Generally, current network management technologies follow two approaches: ITU-T's recommendations for Telecommunication Management Network (TMN) and IETF's Simple Network Management Protocol (SNMP) that favors IP networks. The applications based on these approaches are specifically targeted at a variety of independent networks including the standard Public Switched Telephone Network (PSTN), the Public Switched Data Network (PSDN), the Public Land Mobile Network (PLMN), and the Wireless Local Area Network (WLAN), etc., all of which will be integrated into a single IP-based infrastructure referred to as Next Generation Networks (NGN) in the near future. The services, network architectures and traffic pattern in NGN will dramatically differ from the current networks. The heterogeneity and complexity of NGN bring a number of challenges to its network management. In this paper, we first introduce the current network management approaches and describe some deficiencies of current solutions. Then, the network management challenges in NGN are presented and discussed. Finally, some emerging approaches towards network management in NGN are illustrated.
Evolutionary and efficient context management in heterogeneous environments
Authors: Ricardo Couto A. da Rocha, Markus Endler
Venue: Proceedings of the 3rd international workshop on Middleware for pervasive and ad-hoc computing (2005)

Mobile computing and pervasive environments are mainly characterized by heterogeneity of devices, with different capabilities, resources, operating systems and applications. In a realistic scenario for context-aware computing, middleware should be deployable in the whole distributed system, despite device's resource limitations, and the developer should be able to evolve the context model when new context-aware applications or context providers are introduced. This paper discusses how context modeling and design of middleware architecture can impact on the efficiency of provision, distribution and access of context information in heterogeneous environments. This paper describes a middleware architecture and design strategies in order to address such requirements.
Predictive sunlight simulation for the remodeling of the Real Madrid stadium
Authors: Fermin Gomez, Francisco Seron, Justiniano Aporta, Diego Gutierrez
Venue: Proceedings of the 3rd international conference on Computer graphics and interactive techniques in Australasia and South East Asia (2005)

The present paper shows the result of using light simulation as a predictive tool. It is applied to the remodeling of the Santiago Bernabeu, the Real Madrid football stadium, in order to solve the problems of glare in the new president's box and lack of sufficient insolation of the grass during the winter. The reliability of the algorithms used, as well as the images obtained, are due to the physic validation in controlled experiments. Based on the results obtained in the simulations, the architects could try different solutions in the digital realm until finally coming up with the optimal one. The remodeled Santiago Bernabeu now incorporates the changes shown here.
Cluster Computing on the Fly: resource discovery in a cycle sharing peer-to-peer system
Authors: D. Zhou, V. Lo
Venue: Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid (2004)

Peer-to-peer computing, the harnessing of idle compute cycles throughout the Internet, offers exciting new research challenges in the converging domains of networking and distributed computing. Our system, Cluster Computing on the Fly, seeks to harvest cycles from ordinary users in an open access, non-institutional environment. We conduct a comprehensive study of generic searching methods in a highly dynamic peer-to-peer environment for locating idle cycles for workpile applications which are heavy consumers of cycles. We compare four scalable search methods: expanding ring, advertisement-based, random walk and rendezvous point. We model a variety of workloads, simple scheduling strategies and stabilities of hosts. Our preliminary results show that under light workloads, rendezvous point performs best, while under heavy workloads, its performance falls below the other techniques. We expected rendezvous point to consistently outperform the other search techniques because of its inherent advantage in gathering knowledge about the idle cycles. However in a peer-to-peer environment, which satisfies requests on-demand, large jobs may dominate, resulting in delays for scheduling smaller jobs.
Social structure simulation and inference using artificial intelligence techniques
Authors: Maksim Tsvetovat
Venue:  (2005)

The study of complex social and technological systems, such as organizations, requires a sophisticated approach that accounts for the underlying psychological and sociological principles, communication patterns and the technologies within these systems. Social Network Analysis and link analysis have since inception operated on the cutting edge bringing together mathematical analysis of social structures and qualitative reasoning and interpretation. As available computing power grew, social network-based models have become not only an analysis tool, but also a methodology for building new theories of social behaviour and organizational evolution, frequently through the creation of simulation models. This work examines the past approaches of creating Social Network-based semantically consistent and interpretable models of social structure and social networks, as well as social simulation tools. I propose the creation of a multi-theory, multi-level simulation model of social structure that relies on social network theory and Artificial Intelligence algorithms. I further propose the creation of a robust and scalable social structure semantic that facilitates interpretable reasoning about evolution of social structure.
Choosing a language for an MBA system modeling and simulation course
Authors: Norman P. Archer
Venue: ACM SIGSIM Simulation Digest (1985)

Simulation languages develop and evolve over time, and the courses in which modeling and simulation are taught must also evolve to keep pace. In the McMaster University MBA program, a study was undertaken in order to select a new simulation language for a system modeling and simulation course in which GPSS had previously been used, in order to demonstrate a broader possible selection of possible application areas for simulation. The language which was selected was SLAM II, and this selection was confirmed by monitoring the reactions and perceptions of the students to both the old and new languages, which were taught concurrently in two separate sections.
Exact Algorithm for Concave Knapsack Problems: Linear Underestimation and Partition Method
Authors: X. L. Sun, F. L. Wang, D. Li
Venue: Journal of Global Optimization (2005)

Integer programming problems with a concave cost function are often encountered in optimization models involving economics of scale. In this paper, we propose an efficient exact algorithm for solving concave knapsack problems. The algorithm consists of an iterative process between finding lower and upper bounds by linearly underestimating the objective function and performing domain cut and partition by exploring the special structure of the problem. The lower bound is improved iteratively via cutting and partitioning the domain. This iteration process converges to the optimality in a finite number of steps. Promising computational results are reported for large-scale concave knapsack problems with up to 1200 integer variables. Comparison results with other existing methods in the literature are also presented.
Recursive neural networks learn to localize faces
Authors: M. Bianchini, M. Maggini, L. Sarti, F. Scarselli
Venue: Pattern Recognition Letters (2005)

Localizing faces in images is a difficult task, and represents the first step towards the solution of the face recognition problem. Moreover, devising an effective face detection method can provide some suggestions to solve similar object and pattern detection problems. This paper presents a novel approach to the solution of the face localization problem using Recursive neural networks (RNNs). The proposed method assumes a graph-based representation of images that combines structural and symbolic visual features. Such graphs are then processed by RNNs, in order to establish the possible presence and the position of faces inside the image. A novel RNN model that can deal with graphs with labeled edges has been also exploited. Some experiments on snapshots from video sequences are reported, showing very promising results.
A Branch-and-Bound Algorithm for Concave Network Flow Problems
Authors: Dalila B. Fontes, Eleni Hadjiconstantinou, Nicos Christofides
Venue: Journal of Global Optimization (2006)

In this paper a Branch-and-Bound (BB) algorithm is developed to obtain an optimal solution to the single source uncapacitated minimum cost Network Flow Problem (NFP) with general concave costs. Concave NFPs are NP-Hard, even for the simplest version therefore, there is a scarcity of exact methods to address them in their full generality. The BB algorithm presented here can be used to solve optimally single source uncapacitated minimum cost NFPs with any kind of concave arc costs. The bounding is based on the computation of lower bounds derived from state space relaxations of a dynamic programming formulation. The relaxations, which are the subject of the paper (Fontes et al., 2005b) and also briefly discussed here, involve the use of non-injective mapping functions, which guarantee a reduction on the cardinality of the state space. Branching is performed by either fixing an arc as part of the final solution or by removing it from the final solution. Computational results are reported and compared to available alternative methods for addressing the same type of problems. It could be concluded that our BB algorithm has better performance and the results have also shown evidence that it has a sub-exponential time growth.
Paraphrasing spoken Chinese using a paraphrase corpus
Authors: Yujie Zhang, Kazuhide Yamamoto
Venue: Natural Language Engineering (2005)

One of the key issues in spoken-language translation is how to deal with unrestricted expressions in spontaneous utterances. We have developed a paraphraser for use as part of a translation system, and in this paper we describe the implementation of a Chinese paraphraser for a Chinese-Japanese spoken-language translation system. When an input sentence cannot be translated by the transfer engine, the paraphraser automatically transforms the sentence into alternative expressions until one of these alternatives can be translated by the transfer engine. Two primary issues must be dealt with in paraphrasing: how to determine new expressions, and how to retain the meaning of the input sentence. We use a pattern-based approach in which the meaning is retained to the greatest possible extent without deep parsing. The paraphrase patterns are acquired from a paraphrase corpus and human experience. The paraphrase instances are automatically extracted and then generalized into paraphrase patterns. A total of 1719 paraphrase patterns obtained using this method and an implemented paraphraser were used in a paraphrasing experiment. The results showed that the implemented paraphraser generated 1.7 paraphrases on average for each test sentence and achieved an accuracy of 88%.
A trade-off curve computation for linear antenna arrays using an evolutionary multi-objective approach
Authors: A. Panduro, A. Brizuela, David Covarrubias, Claudio Lopez
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2006)

This paper deals with the main beam width and the maximum minor lobes height trade-off curve approximate computation for linear antenna arrays. Antenna elements with uniform and non-uniform separations are considered. A well-known genetic algorithm is proposed as the methodology for the computation. For the uniform separation case the proposed algorithm is validated against an exact method based on Chebychev polynomials. Experimental results show that non-uniform separation arrays with uniform current excitation outperform uniform separation arrays. This outperformance is given under the criteria of main beam width and height of the maximum minor lobe.
Engineering XML Solutions Using Views
Authors: R. Rajugan, Elizabeth Chang, Tharam S. Dillon, Ling Feng
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

In industrial informatics, engineering data intensive Enterprise Information Systems (EIS) is a challenging task without abstraction and partitioning. Further, the introduction of semi-structured data (namely XML) and its rapid adaptation by the commercial and industrial systems increased the complexity for data engineering. Conversely, the introduction of OMG's MDA presents an interesting paradigm for EIS and system modeling, where a system is designed at a higher level of abstraction. This presents an interesting problem to investigate data engineering XML solutions under the MDA initiatives, where, models and framework requires higher level of abstraction. In this paper we investigate a view model that can provide layered design methodology for modeling data intensive XML solutions for EIS paradigm, with sufficient level of abstraction.
A High Frequency, Low Jitter Auto-Calibration Phase-Locked Loop with Built-in-Self-Test
Authors: Sadeka Ali, Gregory q. Briggs, Martin Margala
Venue: Proceedings of the 20th IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems (2005)

A phase-lock loop circuit which reacts to measured jitter by adjusting the VCO input control voltage is described. This self-calibration process alters the VCO response in order to lower the jitter in its 2.4 GHz output for Bluetooth application. As this adjustment takes place, it intrinsically adjusts the VCO output towards the desired operating frequency. The programmable synthesizer has a digitally controlled VCO that provides wide tuning range of 710 MHz. The auto-calibration technique adjusts the manufacture and process variation. The synthesizer, designed in TSMC 0.18- µm technology, has an edge jitter standard deviation of 0.86-ps having a 20% improvement over PLL with no self-calibration.
A support vector method for multivariate performance measures
Authors: Thorsten Joachims
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

This paper presents a Support Vector Method for optimizing multivariate nonlinear performance measures like the F1-score. Taking a multivariate prediction approach, we give an algorithm with which such multivariate SVMs can be trained in polynomial time for large classes of potentially non-linear performance measures, in particular ROCArea and all measures that can be computed from the contingency table. The conventional classification SVM arises as a special case of our method.
PathScale InfiniPath: A First Look
Authors: Lloyd Dickman, Greg Lindahl, Dave Olson, Jeff Rubin, Jeff Broughton
Venue: Proceedings of the 13th Symposium on High Performance Interconnects (2005)

Clusters are now a dominant model for high-capacity, scalable computing based on a commodity cost structure. This paper describes the first generation PathScale™ InfiniPath™ adapter — a single chip ASIC directly connecting HyperTransport™ attached processors, such as the AMD Opteron™, to the InfiniBand™ network fabric. In addition to providing ultra-low communications latency, the PathScale InfiniPath adapter achieves high bandwidth from very small to large message sizes. Its performance also scales on multi-core processor nodes. Use of the InfiniBand switching fabric permits high bandwidth to be realized at a commodity fabric price point.
An advisor for web services security policies
Authors: Karthikeyan Bhargavan, Cédric Fournet, Andrew D. Gordon, Greg O'Shea
Venue: Proceedings of the 2005 workshop on Secure web services (2005)

We identify common security vulnerabilities found during security reviews of web services with policy-driven security. We describe the design of an advisor for web services security configurations, the first tool both to identify such vulnerabilities automatically and to offer redial advice. We report on its implentation as a plugin for Microsoft Web Services Enhancents (WSE).
Robust Vera Coding Techniques for Gate-Level and Tester-Compliant SoC Verification Environments
Authors: Mark Litterick, Joachim Geishauser
Venue: Proceedings of the Fifth International Workshop on Microprocessor Test and Verification (2004)

Real world requirements such as low-power modes of operation and multiple clock domains often necessitate gate-level System-on-Chip (SoC) verification environments. Additional complexities introduced by tester compliance impose restrictions on the control and repeatability of simulations over all situations, including register-transfer-level (RTL) and different gate-level conditions. Making full use of the Vera high-level verification language in these circumstances requires special considerations and techniques not normally applied in a module-level RTL testbench. If the intent is to reuse Vera monitors, drivers and result-checkers in the gate-level SoC environment then the code must be designed appropriately. This paper first explores the generic issues of interacting with a gate-level SoC in a tester compliant manner and then proceeds to derive Vera coding guidelines that ensure robust operation across a range of testbench abstractions from module-level RTL through to tester-compliant gate-level SoC implementations.
jContractor: Introducing Design-by-Contract to Java Using Reflective Bytecode Instrumentation
Authors: Murat Karaorman, Parker Abercrombie
Venue: Formal Methods in System Design (2005)

Design by Contract is a software engineering practice that allows semantic information to be added to a class or interface to precisely specify the conditions that are required for its correct operation. The basic constructs of Design by Contract are method preconditions and postconditions, and class invariants.This paper presents a detailed design and implementation overview of jContractor, a freely available tool that allows programmers to write "contracts'' as standard Java methods following an intuitive naming convention. Preconditions, postconditions, and invariants can be associated with, or inherited by, any class or interface. jContractor performs on-the-fly bytecode instrumentation to detect violation of the contract specification during a program's execution. jContractor's bytecode engineering technique allows it to specify and check contracts even when source code is not available. jContractor is a pure Java library providing a rich set of syntactic constructs for expressing contracts without extending the Java language or runtime environment. These constructs include support for predicate logic expressions, and referencing entry values of attributes and return values of methods. Fine grain control over the level of monitoring is possible at runtime. Since contract methods are allowed to use unconstrained Java expressions, in addition to runtime verification they can perform additional runtime monitoring, logging, and analysis.
On feature point matching, in the calibrated and uncalibrated contexts, between widely and narrowly separated images
Authors: Etienne Vincent
Venue:  (2004)

In this work, the correspondence problem for feature points between images is investigated. In this context, two important factors greatly influence the choice of a strategy: whether the camera system is calibrated or not, and how large is the separation between viewpoints. This work is divided into four parts, for the four important matching situations generated by these two factors. In the case of uncalibrated narrowly separated views, a framework for empirically evaluating matching constraints is presented. Then, various new and existing constraints are compared. In the case of calibrated narrowly separated views, a new type of feature is introduced, epipolar gradient features. These are then shown to be especially appropriate for matching in the context of quick reconstruction. The features are then matched with a new constraint based on trinocular line transfer. In the case of uncalibrated widely separated views, it is shown how the shape of feature points can be used to recover local perspective deformation between two views, and improve matching results. To this end, a new corner detector that generates the required information is also introduced. In the case of calibrated widely separated views, a more accurate estimate of local perspective deformation is obtained by incorporating the knowledge of the epipolar geometry. An application to fundamental matrix estimation is also introduced.
Privacy-Preserving Frequent Pattern Mining across Private Databases
Authors: Ada Wai-Chee Fu, Raymond Chi-Wing Wong, Ke Wang
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

Privacy consideration has much significance in the application of data mining. It is very important that the privacy of individual parties will not be exposed when data mining techniques are applied to a large collection of data about the parties. In many scenarios such as data warehousing or data integration, data from the different parties form a many-to-many schema. This paper addresses the problem of privacy-preserving frequent pattern mining in such a schema across two dimension sites. We assume that sites are not trusted and they are semi-honest. Our method is based on the concept of semi-join and does not involve data encryption which is used in most previous work. Experiments are conducted to study the efficiency of the proposed models.