ppxscal/embedding_network huggingface dataset:
A holistic approach for selecting a third-party reverse logistics provider in the presence of vagueness
Authors: Tuğba Efendigil, Semih Önüt, Elif Kongar
Venue: Computers and Industrial Engineering (2008)

Growing environmental concerns have motivated businesses to carefully assess the environmental impact of their products and services at all stages of a life-cycle. Reverse logistics plays an important role in achieving ''green supply chains'' by providing customers with the opportunity to return the warranted and/or defective products to the manufacturer. An efficient reverse logistics structure may lead to a significant return on investment as well as a significantly increased competitiveness in the market. In order to ensure efficiency, many organizations outsource their reverse logistics activities by engaging third-party logistics providers that implement reverse logistics programs designed to gain value from returned products. The selection of third-party providers is a crucial step in initializing reverse logistics related practices. This study aims to efficiently assist the decision makers in determining the ''most appropriate'' third-party reverse logistics provider using a two-phase model based on artificial neural networks and fuzzy logic in a holistic manner. A numerical example is also included in the study to demonstrate the steps of the proposed model.
An Efficient Computation of Statistically Critical Sequential Paths Under Retiming
Authors: Mongkol Ekpanyapong, Xin Zhao, Sung Kyu Lim
Venue: Proceedings of the 2007 Asia and South Pacific Design Automation Conference (2007)

In this paper we present the Statistical Retiming-based Timing Analysis (SRTA) algorithm. The goal is to compute the timing slack distribution for the nodes in the timing graph and identify the statistically critical paths under retiming, which are the paths with a high probability of becoming timing-critical after retiming. SRTA enables the designers to perform circuit optimization on these paths to reduce the probability of them becoming timing bottleneck if the circuit is retimed as a post-process. We provide a comparison among static timing analysis (= STA), statistical timing analysis (= SSTA), retiming-based timing analysis (= RTA), and our statistical retiming-based timing analysis (SRTA). Our results show that the placement optimization based on SRTA achieves the best performance results.
Evaluation of Register-Level Protection Techniques for the Advanced Encryption Standard by Multi-Level Fault Injections
Authors: P. Maistri, P. Vanhauwaert, R. Leveugle
Venue: Proceedings of the 22nd IEEE International Symposium on Defect and Fault-Tolerance in VLSI Systems (2007)

Some protection techniques had been previously proposed for encryption blocks and applied to an AES encryption IP described at RT Level. One of these techniques had been validated by purely functional fault injections (i.e. algorithmic-level fault injections) against single- and multiple- bit errors. RT-Level fault injections have been performed recently on a few AES IPs and this paper summarizes the main results obtained, highlighting the new results and comparing the outcomes of the two fault injection le
Sliced mean variance-covariance inverse regression
Authors: Simon J. Sheather, Joseph W. McKean, Kimberly Crimin
Venue: Computational Statistics Data Analysis (2008)

Inverse regression methods have gained popularity over the last 10 years or so. More recently these methods have been applied to the classification problem. Sliced inverse regression (SIR) is equivalent to linear discriminant analysis and as such it detects mean differences between the classes. Sliced average variance estimation (SAVE) is designed to detect differences between the means, variances and covariances of the predictors across the classes. However, in SAVE each difference in variance across the groups takes up a dimension, and hence SAVE can have difficulty detecting mean differences and covariance differences. In this paper, we propose a new data analytic method, called sliced mean variance-covariance regression (SMVCIR) which can readily detect both first and second order differences between the classes even when many variance differences exist. Further, our procedure is based on an ordering of the dimensions based on their relative importance which is quite beneficial to interpretation. In particular, we demonstrate that useful data-analytic information about mean and covariance differences can be obtained from SMVCIR when SAVE finds many dimensions due to variance differences. Finally, the advantages of SMVCIR over SIR and SAVE are exemplified using a new data set from the enology literature.
Oscillation Criteria of Second-Order Delay Dynamic Equations on Time Scales
Authors: Zhenlai Han, Shurong Sun
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

By means of Riccati transformation technique, we establish some new oscillation criteria for the second-order delay dynamic equations. Our results in this paper not only extend the results given in Sahiner [?] but also unify the oscillation of the second order nonlinear delay differential equation and the second order nonlinear delay difference equation.
International Cooperation to Fight Transnational Cybercrime
Authors: Ana I. Cerezo, Javier Lopez, Ahmed Patel
Venue: Proceedings of the Second International Workshop on Digital Forensics and Incident Analysis (2007)

The ever growing use of computers and information communication technologies in the world of "e-everything" has opened up a range of new activities for crime to take place through electronic means on a global scale, irrespective of national and transnational borders. The effective combating, investigation and prosecution of such crimes require international cooperation between countries, law enforcement agencies and institutions backed by laws, international relations, conventions, directives and recommendations culminating in a set of international guidelines to fight cybercrime. There are many challenges to international cooperation and establishing international guidelines to fight global cybercrime across borders. There is a prerequisite for the harmonization of countries' criminal laws, the sanction of complex jurisdictional issues and the development of new cooperation procedures to challenge cybercrime, its extent and location. It is necessary to identify the perpetrators across borders anywhere in the world, and to investigate and to secure electronic evidence of their crimes so that they may be brought to justice in any compliant jurisdiction with fairness and compliance with human rights standards. This is a daunting task in itself. This paper presents and discusses approaches to overcoming these and other difficulties faced by law enforcement agencies at an international level as well as indicates what possible future work might be required to overcome such difficulties.
An Evaluation of the Robustness of MTS for Imbalanced Data
Authors: Chao-Ton Su, Yu-Hsiang Hsiao
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

In classification problems, class imbalance problem will cause bias on the training of classifiers, and will result in the lower sensitivity of detecting the minority class examples. Mahalabobis-Taguchi System (MTS) is a diagnosis and forecasting technique for multivariate data. MTS establishes a classifier by constructing a continuous measurement scale rather than directly learning from the training set. Therefore, it is expected that the construction of an MTS model will not be influenced by data distribution, and this property is helpful to overcome the class imbalance problem. To verify the robustness of MTS for imbalanced data, this study compares MTS with several popular classification techniques. The results indicate that MTS is the most robust technique to deal with the classification problem on imbalanced data. In addition, this study develops a "probabilistic thresholding method" to determine the classification threshold for MTS, and it obtains a good performance. Finally, MTS is employed to analyze the RF inspection process of mobile phone manufacture. The data collected from the RF inspection process is typically an imbalanced type. Implementation results show that the inspection attributes are significantly reduced and that the RF inspection process can also maintain high inspection accuracy.
Neural Network for Text Classification Based on Singular Value Decomposition
Authors: Cheng Hua Li, Soon Cheol Park
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

This paper proposed new text classification models based on artificial neural networks and Singular Value Decomposition (SVD). The neural networks are trained by Multi-Output Perceptron Learning algorithm (MOPL) and Back-Propagation Neural Network (BPNN). Most classic classification systems represent the contents of documents with a set of index terms, it has been known as vector space model (VSM). However, this method need a high dimensional space to represent the documents, and it dose not take into account the semantic relationship between terms, which could lead to poor classification performance. In this paper, we introduce singular value decomposition to our systems. SVD was used to learn and represent relations among very large numbers of words and very large numbers of natural text passages in which they occurred. It could not only greatly reduce the dimensional but also discover the important associative relationships between terms. It also helps to accelerate the training speed and improve the classification accuracy. We test our classification systems on the standard Reuter-21578 collection. Experimental evaluations show that the systems training with SVD are much fast then the original systems with VSM, and also achieve better classification results.
Feature Diagrams and Logics: There and Back Again
Authors: Krzysztof Czarnecki, Andrzej Wasowski
Venue: Proceedings of the 11th International Software Product Line Conference (2007)

Feature modeling is a notation and an approach for modeling commonality and variability in product families. In their basic form, feature models contain mandatory/ optional features, feature groups, and implies and excludes relationships. It is known that such feature models can be translated into propositional formulas, which enables the analysis and configuration using existing logicbased tools. In this paper, we consider the opposite translation problem, that is, the extraction of feature models from propositional formulas. We give an automatic and efficient procedure for computing a feature model from a formula. As a side effect we characterize a class of logical formulas equivalent to feature models and identify logical structures corresponding to their syntactic elements. While many different feature models can be extracted from a single formula, the computed model strives to expose graphically the maximum of the original logical structure while minimizing redundancies in the representation. The presented work furthers our understanding of the semantics of feature modeling and its relation to logics, opening avenues for new applications in reverse engineering and refactoring of feature models.
Measuring the Performance and Behavior of Icon Programs
Authors: C. A. Coutant
Venue: IEEE Transactions on Software Engineering (1983)

The importance of the ability to measure the performance of programs written in high-level languages is well known. Performance measurement enables users to locate and correct program inefficiencies where automatic optimizations fail and provides a tool for understanding program behavior. This paper describes performance measurement facilities for the Icon programming language, and shows not only how these facilities provided insight into program behavior, but also how they were used to improve the implementation.
Game Theoretic Distributed Energy Control in Sensor Networks
Authors: Jia Zeng, Chundi Mu, Min Jiang
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

Standard wireless sensor networks models emphasize energy efficiency and distributed decision- making by considering unattended sensors. Wireless sensor networks are confronted with the challenges of performance and energy consumption. To prolong the lifetime of the sensor networks, a game theoretic energy balance routing (GTEBR) algorithm is proposed. This algorithm aims at the balanceable energy consumption in sensor networks. A game theoretic method presented in this algorithm can make the sensor nodes more rational to take part in the routes by considering the consumption and other factors. Thus, the consumption shares by the whole sensor networks and the energy consumption becomes more even. Finally, the existence of Nash equilibrium in this energy control model is proved. The experiment results show that GTEBR algorithm reduces the consumption of some hot-area nodes and prolong the lifetime of the sensor networks. At the same time, this algorithm has desirable convergence and response.
Study and Application of Web-based Data Mining in E-Business
Authors: Yanguang Shen, Lili Xing, Yiting Peng
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

The paper is engaged in a discussion over applications of Web mining to the intelligent search engine, customer relationship management, personalized service and commercial credit evaluation in e-business. And analysis and reasoning of the mass of information in e-business are made by the technology of Web mining, which can dig out potential modes and predict customers' action, to help enterprises' decision-makers adjust their marketing strategy, reduce the risk, make right decisions and get competitive advantage.
Adaptive web-page content identification
Authors: John Gibson, Ben Wellner, Susan Lubar
Venue: Proceedings of the 9th annual ACM international workshop on Web information and data management (2007)

Identifying which parts of a Web-page contain target content (e.g., the portion of an online news page that contains the actual article) is a significant problem that must be addressed for many Web-based applications. Most approaches to this problem involve crafting hand-tailored rules or scripts to extract the content, customized separately for particular Web sites. Besides requiring considerable time and effort to implement, hand-built extraction routines are brittle: they fail to properly extract content in some cases and break when the structure of a site's Web-pages changes. In this work we treat the problem of identifying content as a sequence labeling problem, a common problem structure in machine learning and natural language processing. Using a Conditional Random Field sequence labeling model, we correctly identify the content portion of web-pages anywhere from 80-97% of the time depending on experimental factors such as ensuring the absence of duplicate documents and application of the model against unseen sources.
Review: Using an artificial neural network to improve the transformation of coordinates between classical geodetic reference frames
Authors: A. Tierra, R. Dalazoana, S. De Freitas
Venue: Computers Geosciences (2008)

Advances in technology have allowed for the improvement of geodetic reference systems (GRSs). Relating different GRSs can be done by employing transformation parameters which may not, however, be satisfactory in certain applications due to the heterogeneous and local character of deformations caused by the procedures adopted in classical networks. Classical networks were established basically by procedures of triangulation and traverse survey, and the existence of these deformations justifies the search for new transformation methodologies. This study evaluated artificial neural networks (ANNs) as a tool for the transformation between GRSs. Frames points with known geodetic coordinates (latitude and longitude) in the South American Datum of 1969 (SAD69) system and in the older Corrego Alegre system, both still in use in Brazil, were chosen for this study. The SAD69 coordinates of the frame points were transformed into Corrego Alegre coordinates and then the computed coordinates were compared with known ones. Four tests were carried out in order to transform the coordinates. The first test involved the use of official transformation parameters and the formulas of Molodensky. In the second test, new transformation parameters were employed. In the third test new regional transformation parameters were determined, while the fourth test employed an ANN to predict the Corrego Alegre coordinates of the check points. Results indicated that the employment of an ANN transformed the coordinates most accurately, and indicated that they can be useful in modeling deformations in classical networks.
A Minimization Technique for Tant Networks
Authors: Kyung Shik Koh
Venue: IEEE Transactions on Computers (1971)

A TANT network is a three-level network composed solely of AND-NOT gates having only uncomplemented inputs. A method of minimal gate TANT realization of a Boolean function is presented. The procedure permits hand solution of four-and five-variable problems. A computer program will be required to handle more complex cases.
A co-simulation platform for actuator networks
Authors: Ahmad Al-Hammouri, Vincenzo Liberatore, Huthaifa Al-Omari, Zakaria Al-Qudah, Michael S. Branicky, Deepak Agrawal
Venue: Proceedings of the 5th international conference on Embedded networked sensor systems (2007)

Actuator networks will enable an unprecedented degree of distributed control of physical environments, and further progress will critically depend on the availability of a simulation platform that can capture both the physical and the communication dynamics.
The NEXT framework for logical XQuery optimization
Authors: Alin Deutsch, Yannis Papakonstantinou, Yu Xu
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

Classical logical optimization techniques rely on a logical semantics of the query language. The adaptation of these techniques to XQuery is precluded by its definition as a functional language with operational semantics. We introduce Nested XML Tableaux which enable a logical foundation for XQuery semantics and provide the logical plan optimization framework of our XQuery processor. As a proof of concept, we develop and evaluate a minimization algorithm for removing redundant navigation within and across nested subqueries. The rich XQuery features create key challenges that fundamentally extend the prior work on the problems of minimizing conjunctive and tree pattern queries.
Knowledge-system theory in society: Charting the growth of knowledge-system models over a decade, 1994&ndash;2003
Authors: Paul J. Graham, Harley D. Dickinson
Venue: Journal of the American Society for Information Science and Technology (2007)

The second half of the twentieth century saw the emergence of three knowledge-system models: Mode 2 knowledge production, the Triple Helix, and Post-Normal Science (PNS). Today, this emphasis on knowledge use is the focus of such important health movements as evidence-based medicine. Building on the methodological work of Shinn (2002) and the theoretical work of Holzner and Marx (1979), we conducted a bibliometric study of the extent to which the three knowledge-system models are used by researchers to frame problems of health-knowledge use. By doing so, we reveal how these models fit into a larger knowledge system of health and evidence-based decision making. The study results show clearly that although these knowledge models are extremely popular for contextualizing research, there is a distinct lack of emphasis on use of the models in knowledge utilization or evidence-based medicine. We recommend using these models for further research in three specific dimensions of health systems analysis: (a) differences in language use, (b) transformative thinking about health-knowledge functions, and (c) ethical analysis of institutional linkages. &copy; 2007 Wiley Periodicals, Inc.
Transducer-based analysis of cryptographic protocols
Authors: Ralf Küsters, Thomas Wilke
Venue: Information and Computation (2007)

Cryptographic protocols can be divided into (1) protocols where the protocol steps are simple from a computational point of view and can thus be modeled by simple means, for instance, by single rewrite rules-we call these protocols non-looping-and (2) protocols, such as group protocols, where the protocol steps are complex and typically involve an iterative or recursive computation-we call them recursive. While much is known on the decidability of security for non-looping protocols, only little is known for recursive protocols. In this paper, we prove decidability of security (with respect to the standard Dolev-Yao intruder) for a core class of recursive protocols and undecidability for several extensions. The key ingredient of our protocol model is specifically designed tree transducers which work over infinite signatures and have the ability to generate new constants (which allow us to mimic key generation). The decidability result is based on an automata-theoretic construction which involves a new notion of regularity, designed to work well with the infinite signatures we use.
Integrity auditing of outsourced data
Authors: Min Xie, Haixun Wang, Jian Yin, Xiaofeng Meng
Venue: Proceedings of the 33rd international conference on Very large data bases (2007)

An increasing number of enterprises outsource their IT services to third parties who can offer these services for a much lower cost due to economy of scale. Quality of service is a major concern in outsourcing. In particular, query integrity, which means that query results returned by the service provider are both correct and complete, must be assured. Previous work requires clients to manage data locally to audit the results sent back by the server, or database engine to be modified for generating authenticated results. In this paper, we introduce a novel integrity audit mechanism that eliminating these costly requirements. In our approach, we insert a small amount of records into an outsourced database so that the integrity of the system can be effectively audited by analyzing the inserted records in the query results. We study both randomized and deterministic approaches for generating the inserted records, as how these records are generated has significant implications for storage and performance. Furthermore, we show that our method is provable secure, which means it can withstand any attacks by an adversary whose computation power is bounded. Our analytical and empirical results demonstrate the effectiveness of our method.
MRST: an efficient monitoring technology of summarization on stream data
Authors: Xiao-Bo Fan, Ting-Ting Xie, Cui-Ping Li, Hong Chen
Venue: Journal of Computer Science and Technology (2007)

Monitoring on data streams is an efficient method of acquiring the characters of data stream. However the available resources for each data stream are limited, so the problem of how to use the limited resources to process infinite data stream is an open challenging problem. In this paper, we adopt the wavelet and sliding window methods to design a multi-resolution summarization data structure, the Multi-Resolution Summarization Tree (MRST) which can be updated incrementally with the incoming data and can support point queries, range queries, multi-point queries and keep the precision of queries. We use both synthetic data and real-world data to evaluate our algorithm. The results of experiment indicate that the efficiency of query and the adaptability of MRST have exceeded the current algorithm, at the same time the realization of it is simpler than others.