ppxscal/embedding_network huggingface dataset:
Polyglot: automatic extraction of protocol message format using dynamic binary analysis
Authors: Juan Caballero, Heng Yin, Zhenkai Liang, Dawn Song
Venue: Proceedings of the 14th ACM conference on Computer and communications security (2007)

Protocol reverse engineering, the process of extracting the application-level protocol used by an implementation, without access to the protocol specification, is important for many network security applications. Recent work [17] has proposed protocol reverse engineering by using clustering on network traces. That kind of approach is limited by the lack of semantic information on network traces. In this paper we propose a new approach using program binaries. Our approach, shadowing, uses dynamic analysis and is based on a unique intuition - the way that an implementation of the protocol processes the received application data reveals a wealth of information about the protocol message format. We have implemented our approach in a system called Polyglot and evaluated it extensively using real-world implementations of five different protocols: DNS, HTTP, IRC, Samba and ICQ. We compare our results with the manually crafted message format, included in Wireshark, one of the state-of-the-art protocol analyzers. The differences we find are small and usually due to different implementations handling fields in different ways. Finding such differences between implementations is an added benefit, as they are important for problems such as fingerprint generation, fuzzing, and error detection.
The Current State of Business Intelligence
Authors: Hugh J. Watson, Barbara H. Wixom
Venue: Computer (2007)

Business intelligence is emerging as a key enabler for increasing value and performance.
Verifying UML Diagrams with Model Checking: A Rewriting Logic Based Approach
Authors: Farid Mokhati, Patrice Gagnon, Mourad Badri
Venue: Proceedings of the Seventh International Conference on Quality Software (2007)

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Rigorous hitting times for binary mutations
Authors: Josselin Garnier, Leila Kallel, Marc Schoenauer
Venue: Evolutionary Computation (1999)

In the binary evolutionary optimization framework, two mutation operators are theoretically investigated. For both the standard mutation, in which all bits are flipped independently with the same probability, and the 1-bit-flip mutation, which flips exactly one bit per bitstring, the statistical distribution of the first hitting times of the target are thoroughly computed (expectation and variance) up to terms of order l (the size of the bitstrings) in two distinct situations: without any selection, or with the deterministic (1 + l)-ES selection on the OneMax problem. In both cases, the 1-bit-flip mutation convergence time is smaller by a constant (in terms of l) multiplicative factor. These results extend to the case of multiple independent optimizers.
High-Speed DC Coupled Digit Detector
Authors: D. J. Lynes
Venue: IEEE Transactions on Computers (1969)

The requirements, design, and performance of an integrable dc coupled digit detector array for high-speed memory systems such as the plated wire is described. The array consists of 12 detectors on 100-mil centers, on a tantalum film glass substrate using beam-lead monolithic chips. There are 218 resistors and 144 beam lead transistors formed or bonded with an area of 0.8 × 1.2 inch. Ninety-six of the transistors are monolithic differential pairs.
Quantum lower bounds by entropy numbers
Authors: Stefan Heinrich
Venue: Journal of Complexity (2007)

We use entropy numbers in combination with the polynomial method to derive a new general lower bound for the nth minimal error in the quantum setting of information-based complexity. As an application, we improve some lower bounds on quantum approximation of embeddings between finite dimensional L"p spaces and of Sobolev embeddings.
Test Data and Test Time Reduction for LOS Transition Test in Multi-Mode Segmented Scan Architecture
Authors: Sying-Jyan Wang, Po-Chang Tsai, Hung-Ming Weng, Katherine Shu-Min Li
Venue: Proceedings of the 16th Asian Test Symposium (2007)

Launch-off-Shift (LOS) is a widely used technique for delay test in scan-based design. Test data compression for LOS patterns, however, is less efficient. In this paper, we first analyze the reason for low compression rate in LOS patterns, and present an LOS test enabled scan architecture that supports three operation modes: broadcast, multicast, and serial. Efficient LOS test data compression can be achieved under this architecture with limited hardware overhead. An ATPG method for LOS test patterns under the proposed architecture is also presented. Experimental results show that most of the serial scan operations can be replaced by multicast operations, and thus achieve much better compression rate.
Error-Correcting Codes and Self-Checking Circuits
Authors: D. K. Pradhan
Venue: Computer (1980)

Error-control coding techniques, implemented by means of self-checking circuits, will improve system reliability.
Automated conversion of table-based websites to structured stylesheets using table recognition and clone detection
Authors: Andy Y. Mao, James R. Cordy, Thomas R. Dean
Venue: Proceedings of the 2007 conference of the center for advanced studies on Collaborative research (2007)

Web standards such as XHTML and CSS are rapidly coming into practice and have many advantages, including compatibility, consistency across browsers, and increased ease of maintenance. Unfortunately large numbers of existing websites still use the deprecated table-based layout style in which page style is unique to each page. Existing tools for automating the transition to stylesheets provide little help, converting page-by-page using a flattened structure and local inline styles rather than a common CSS stylesheet. This approach ignores hierarchical structure and defeats the main purpose of moving to the new standard, losing all of the advantages. In this work we present an automated method for converting table-based layout websites to standards-compliant modern CSS stylesheet-based websites using a two-step process. Pages of the site are first converted page-by-page using table recognition technology to preserve hierarchical structure and layout semantics in local styles. Software clone detection technology is then utilized to recognize common layout styles in the pages and extract and minimize them to a common CSS stylesheet for the site. The result is a maintainable, efficient modern standards-compliant website with the same look and feel as the original but with all the maintenance advantages of a custom programmed new site.
Adaptive extremal optimization by detrended fluctuation analysis
Authors: K. Hamacher
Venue: Journal of Computational Physics (2007)

Global optimization is one of the key challenges in computational physics as several problems, e.g. protein structure prediction, the low-energy landscape of atomic clusters, detection of community structures in networks, or model-parameter fitting can be formulated as global optimization problems. Extremal optimization (EO) has become in recent years one particular, successful approach to the global optimization problem. As with almost all other global optimization approaches, EO is driven by an internal dynamics that depends crucially on one or more parameters. Recently, the existence of an optimal scheme for this internal parameter of EO was proven, so as to maximize the performance of the algorithm. However, this proof was not constructive, that is, one cannot use it to deduce the optimal parameter itself a priori. In this study we analyze the dynamics of EO for a test problem (spin glasses). Based on the results we propose an online measure of the performance of EO and a way to use this insight to reformulate the EO algorithm in order to construct optimal values of the internal parameter online without any input by the user. This approach will ultimately allow us to make EO parameter free and thus its application in general global optimization problems much more efficient.
Using a phenomenographic approach in evaluating hypermedia stories
Authors: Peter Thomas, Elaine Martin
Venue: Computers Education (2008)

This paper builds on research into using multimedia and hypermedia as creative writing tools and reports on a study in using a hypermedia authoring program with middle-years students at an Australian secondary school. The study explored a classroom where collaborative work built on the technical facilities and expertise of young people. The paper presented here focuses on the authors' development of an assessment matrix for evaluating hypermedia stories. The aim is to provide an effective feedback mechanism on the hypermedia work and to give teachers guidelines for planning lessons, and for making summative as well as formative judgments. Four, equally important dimensions are identified as the key components of hypermedia: image, language, interactivity and structural design. Image relates to how the screen looks: the background and foreground, positioning, colour, animation and source of images (e.g. clipart, photographs, or the use of hand-drawing). Language involves written language as signs, or captions within the created hypermedia world, or as attached commentary. Language may also be audio-files containing conversations, commentary, or even chanting or singing. Interactivity refers to the way the viewer or the interactor comes into a relationship with the hypermedia. This involves the interactive nature of the screen, that is, what can be opened up and explored within each screen as well as how the viewer/interactor moves between screens. Structural Design relates to the way the story fits together image, language and interactivity, and the way one aspect relates to another in terms of complexity and cohesion. In order to systematically assess the qualitative variation across the range of students' hypermedia stories, each of the four aspects highlighted above was also considered in terms of the five-level 'SOLO' taxonomy (structure of learning outcomes). This taxonomy includes the following five levels:*Pre-structural - where the response is really not relevant to the question. *Uni-structural - where an appropriate but minimalist response is given. *Multi-structural - where several responses (or answers) are given and the responses are appropriate, but there is no relationship between the responses. *Relational - where all responses are related into a reasonably coherent argument. *Extended abstract - where responses come together in an argument, which goes beyond any of the information previously given or hinted at. When the four dimensions mentioned above are mapped against the five qualitatively different levels of response, a series of taxonomies is produced, which gives a clear indication of the strengths within each story, as well as the variation in quality across all the stories. In so far as this method maps and explores qualitative variation within a specific phenomenon it can be seen as phenomenographic. In this paper, three of the hypermedia stories' matrices are explored and one story is assessed using the whole method.
Effective phrase prediction
Authors: Arnab Nandi, H. V. Jagadish
Venue: Proceedings of the 33rd international conference on Very large data bases (2007)

Autocompletion is a widely deployed facility in systems that require user input. Having the system complete a partially typed "word" can save user time and effort. In this paper, we study the problem of autocompletion not just at the level of a single "word", but at the level of a multi-word "phrase". There are two main challenges: one is that the number of phrases (both the number possible and the number actually observed in a corpus) is combinatorially larger than the number of words; the second is that a "phrase", unlike a "word", does not have a well-defined boundary, so that the autocompletion system has to decide not just what to predict, but also how far. We introduce a FussyTree structure to address the first challenge and the concept of a significant phrase to address the second. We develop a probabilistically driven multiple completion choice model, and exploit features such as frequency distributions to improve the quality of our suffix completions. We experimentally demonstrate the practicability and value of our technique for an email composition application and show that we can save approximately a fifth of the keystrokes typed.
Lisp, second edition
Authors: Daniel Weinreb
Venue: ACM SIGPLAN Lisp Pointers (1987)

Winston and Horn's Lisp is a textbook on symbolic computation and the Lisp language. It was originally published in 1981, based on a set of course notes developed for the introductory course in artificial intelligence at MIT.
SPG: An Effective Use of Performance and Usage Data
Authors: J. A. Cooperman, H. W. Lynch, W. H. Tetzlaff
Venue: Computer (1972)

The Statistics Gathering Package, SGP, is an information retrieval program supplemented with a variety of summarization techniques. It is used to access a data base of performance and usage information collected by OS, SMF, and LASP. SGP provides information that is needed by installation management, system programmers, consultants and computer users to make decisions.
PEPS2007 - Stochastic Automata Networks Software Tool
Authors: Leonardo Brenner, Paulo Fernandes, Brigitte Plateau, Ihab Sbeity
Venue: Proceedings of the Fourth International Conference on Quantitative Evaluation of Systems (2007)

PEPS is a tool package for modeling and solving models expressed in Stochastic Automata Networks (SAN). The SAN formalism defines a compact storage scheme for the transition matrix of the Markov chain and it uses tensor algebra to handle the basic vector matrix multiplications. This paper presents a short timeline of PEPS previous versions and the new features included in version 2007.
Supporting personalized top-k skyline queries using partial compressed skycube
Authors: Jongwuk Lee, Gae-won You, IkChan Sohn, Seung-won Hwang, Kwangil Ko, Zino Lee
Venue: Proceedings of the 9th annual ACM international workshop on Web information and data management (2007)

As near-infinite amount of data are becoming accessible on the Web, it is getting more and more important to support intelligent query mechanisms, to help each user to identify the ideal results of manageable size. As such mechanism, skyline queries have gained a lot of attention lately for its intuitive query formulation. This intuitiveness, however, has a side-effect of generating too many results, especially for high-dimensional data, to satisfy a wide range of user's needs. Our goal is to support personalized skyline queries as identifying "truly interesting" objects based on user-specific preference and retrieval size k. While this problem has been studied previously, the proposed solution identifies top-k results by navigating a "skycube", which incurs exponential storage overhead to data dimensionality and excessive one-time computational overhead for skycube construction. In contrast, we develop novel techniques to significantly reduce both storage and computation overhead. Our extensive evaluation results validate this framework on both real-life and synthetic data.
The impact of Web service integration on grid performance
Authors: F. Taiani, M. Hiltunen
Venue: Proceedings of the High Performance Distributed Computing, 2005. HPDC-14. Proceedings. 14th IEEE International Symposium (2005)

The past few years have seen an increasingly tight link between grid computing and Web services, with the latest standards defining a grid computing architecture as a set of services built using Web services standards and protocols. However, the reputation of these technologies (SOAP, XML, WSDL, HTTP) is that they are heavyweight and slow, something that is potentially a concern given the current and anticipated application mix for high performance grid architectures. This paper reports the results of a performance evaluation carried out on Globus 3.9.4, a reference implementation of the new GGF standards that are built on the Web services resource framework (WSRF). The evaluation approach combines low interference measurement (black box) techniques with more sophisticated sampling-based profiling (gray box) techniques. The results indicate possible opportunities for optimization, as well as provide useful input for the designers of grid services.
RβHpred: Prediction of Right-Handed β-Helix Fold from Protein Sequence Using SVM and Protein Threading
Authors: Siddharth Singh, Krishnan Hajela, Ashwini Ramani
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

The right-handed single-stranded helix proteins characterized as virulence factors, allergens and toxins are threat to human health. Identification of these proteins from primary sequence is of great importance in bio-medicine and medical microbiology. In this paper, support vector machine (SVM) has been used to predict the presence of β-helix fold in protein sequences using dipeptide composition. Input vector of 400 dimensions is used to search for the presence of conserved secondary structure called rungs in β-helix proteins. A maximum accuracy of 90.1% and Matthew's correlation coefficient of 0.77 is obtained in a 5-fold cross-validation procedure. In addition, a position specific scoring matrix(PSSM) is also used to score putative rung sequences identified by SVM. Finally, the predicted β-helix proteins are threaded against a custom β-helix template library to achieve high prediction confidence. The method recognizes right-handed β-helices with 100% sensitivity and 99.8% specificity on a test set of known protein structures.
Software Project Risk Management Modeling with Neural Network and Support Vector Machine Approaches
Authors: Yong Hu, Jiaxing Huang, Juhua Chen, Mei Liu, Kang Xie
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

Software project development has high failure rate. Software project risk management may gain a high rate of return in investment. Establishing an intelligent risk evaluation model for project will be valuable in the analysis and control of project risks. In this paper, we employed neural network (NN) and support vector machine (SVM) approaches to establish a model for risk evaluation in project development. In the model, the input is a vector of software risk factors that were obtained through interview with 30 experts, and the output is the final outcome of the project. The data for modeling were collected from 120 real software projects through questionnaires. The experiment shows the model is valid. Interestingly, SVM is a powerful supervised learning method, and some believe that it is a more promising classification method that may someday supercede NN. In our study, the standard neural network model had lower prediction accuracy compared to SVM due to its tendency in finding local optima. However, after attempt in optimizing the neural network model with genetic algorithm, the experimental results showed that our enhanced model surpassed SVM in performance.
Applying supply chain optimization techniques to workforce planning problems
Authors: D. L. Gresh, D. P. Connors, J. P. Fasano, R. J. Wittrock
Venue: IBM Journal of Research and Development (2007)

The IBM Research Division has developed the Resource Capacity Planning (RCP) Optimizer to support the Workforce Management Initiative (WMI) of IBM. RCP applies supply chain management techniques to the problem of planning the needs of IBM for skilled labor in order to satisfy service engagements, such as consulting, application development, or customer support. This paper describes two RCP models and presents two approaches to solving each of them. We also describe the motivation for using one approach over another. The models are built using the Watson Implosion Technology toolkit, which consists of a supply chain model, solvers for analysis and optimization, and an Application Programming Interface (API) for developing a solution. The models that we built solve two core resource planning problems, gap/glut analysis and resource action planning. The gap/glut analysis is similar to material requirements planning (MRP), in which shortages (gaps) and excesses (gluts) of resources are determined on the basis of expected demand. The goal of the resource action planning problem is to determine what resource actions to take in order to fill the gaps and reduce the gluts. The gap/glut analysis engine is currently deployed within the IBM service organization to report gaps and gluts in personnel.
Efficient development of highly reusable distributed systems using the TCAO
Authors: Santokh Singh, Sheri Zidie Xu, Harveen Kaur
Venue: Proceedings of the third conference on IASTED International Conference: Advances in Computer Science and Technology (2007)

Currently there are neither structured nor efficient ways to develop and reuse non-trivial and complex distributed systems despite the fact that there exist numerous sources of software, components and knowledge relating to this field. In this paper we describe how we use a novel all-encompassing development methodology called the Total Components Aspect-Oriented (TCAO) methodology to efficiently and rapidly design and develop reusable distributed systems of any size, functionality and complexity. We further describe our other novel concepts of using Early Aspect-Oriented Components (EAOC) and Early Aspect-Oriented Software (EAOS), collectively known as early systemic-entities, to get an early head-start in the development process starting from the requirements engineering phase itself and spanning throughout all the phases. TCAO also encompasses the activities of deployment, maintenance and refactoring to add any further remoting functionalities if the need arises. We further describe how we use TCAO to identify, isolate and use aspects, which are systemic cross-cutting concerns, to make the analysis, design, modelling and implementations of reusable distributed systems easier to understand, manage and control. With the aid of an exemplar software system, we also describe how a non-trivial reusable distributed system can be efficiently and rapidly developed by using our methodology to facilitate technology transfer and reuse.
Multiple-Period Modified Fuzzy Time-Series for Forecasting TAIEX
Authors: Ching-hsue Cheng, Tai-liang Chen, Hia-jong Teoh
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

In fuzzy time-series methods, mining Fuzzy Logical Relation (FLR) from time-series is one of most critical processes to influence forecasting accuracy. However, in stock markets, investors usually make their investment decisions according to recent stock information such as market news, technical indicators or yesterday price. In this paper, we propose a new fuzzy time-series, which integrates linear relationships between recent periods of stock prices and non-linear relationships (FLR) in forecasting processes, to improve forecasting performance. To verify the proposed method, in this paper, we employ a nine-year period of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) data as experimental dataset and three fuzzy time-series methods, Chen's, Yu's and Huarng's methods, as comparison methods. The comparison results show that our method outperforms the listing methods which only consider FLR in forecasting processes.