ppxscal/embedding_network huggingface dataset:
BegBunch: benchmarking for C bug detection tools
Authors: Cristina Cifuentes, Christian Hoermann, Nathan Keynes, Lian Li, Simon Long, Erica Mealy, Michael Mounteney, Bernhard Scholz
Venue: Proceedings of the 2nd International Workshop on Defects in Large Software Systems: Held in conjunction with the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2009) (2009)

Benchmarks for bug detection tools are still in their infancy. Though in recent years various tools and techniques were introduced, little effort has been spent on creating a benchmark suite and a harness for a consistent quantitative and qualitative performance measurement. For assessing the performance of a bug detection tool and determining which tool is better than another for the type of code to be looked at, the following questions arise: 1) how many bugs are correctly found, 2) what is the tool's average false positive rate, 3) how many bugs are missed by the tool altogether, and 4) does the tool scale. In this paper we present our contribution to the C bug detection community: two benchmark suites that allow developers and users to evaluate accuracy and scalability of a given tool. The two suites contain buggy, mature open source code; bugs are representative of "real world" bugs. A harness accompanies each benchmark suite to compute automatically qualitative and quantitative performance of a bug detection tool. BegBunch has been tested to run on the Solaris&trade;, Mac OS X and Linux operating systems. We show the generality of the harness by evaluating it with our own Parfait and three publicly available bug detection tools developed by others.
Rough-set-based approaches to data containing incomplete information: possibility-based cases
Authors: Michinori Nakata, Hiroshi Sakai
Venue: Proceeding of the 2005 conference on Advances in Logic Based Intelligent Systems: Selected Papers of LAPTEC 2005 (2005)

Methods based on rough sets to data containing incomplete information are examined under a possibilty-based interpretation for whether a correctness criterion is satisfied or not. The correctness criterion is to give the same results as methods by possible tables. The methods proposed so far do not give the same results as methods by possible tables. Therefore, we show a new formula not using implication operators in methods by valued tolerance relations. The formula bears the results that agree with ones from using possible tables. Thus, by using the formula the methods by valued tolerance relations satisfy the correctness criterion.
New Perspectives on the Internet 7th Edition: New Perspectives Thomson Course Technology, 7th edition
Authors: Jessica Evans, Gary P. Schneider
Venue:  (2008)

With our critical-thinking, problem-solving approach, users will learn the basic to more advanced features of the Internet from browsing, navigating, and searching the Internet, to using email, and other Web topics. The case-based tutorials challenge users to apply what they are learning to real-life tasks, preparing them to easily transfer skills to new situations. With the New Perspectives Series approach, learners understand why they're learning what they're learning, and are better situated to retain skills beyond the classroom.
A fuzzy biclustering algorithm for social annotations
Authors: Lixin Han, Hong Yan
Venue: Journal of Information Science (2009)

In recent years, there has been considerable interest in the analysis of social annotations. Social annotations allow users to annotate web resources more easily, openly and freely than do taxonomies and ontologies. In this paper, we propose a novel algorithm for social annotations. It introduces a fuzzy biclustering algorithm to social annotations for identifying subgroups of users and of resources, and discovering the relationships between those users for social annotations. The algorithm employs a combination of pattern search and compromise programming to construct hierarchically structured biclusters. The pattern search method is used to compute a single objective optimal solution, and the compromise programming is used to trade-off between multiple objectives. The algorithm is not subject to the convexity limitations, and does not need to use the derivative information. It can automatically identify user communities and achieve high prediction accuracies.
Forecasting conditional correlations in stock, bond and foreign exchange markets
Authors: Abdul Hakim, Michael McAleer
Venue: Mathematics and Computers in Simulation (2009)

The paper forecasts conditional correlations between three classes of international financial assets, namely stock, bond and foreign exchange. Two countries are considered, namely Australia and New Zealand. Forecasting will be conducted using three multivariate GARCH models, namely the CCC model [T. Bollerslev, Modelling the coherence in short-run nominal exchange rates: a multivariate generalized ARCH model, Rev. Econ. Stat. 72 (1990) 498-505], VARMA-GARCH model [S. Ling, M. McAleer, Asymptotic theory for a vector ARMA-GARCH model, Econometric Theory 19 (2003) 280-310], and VARMA-AGARCH model [M. McAleer, S. Hoti, F. Chan, Structure and asymptotic theory for multivariate asymmetric volatility, Econometric Rev., in press]. A rolling window technique is used to forecast 1-day ahead conditional correlations. To evaluate the impact of model specification on conditional correlations forecasts, this paper calculates and compares the correlations between conditional correlations forecasts resulted from the three models. The paper finds the evidence of volatility spillovers and asymmetric effect of negative and positive shock on the conditional variance in most pairs of series. However, it suggests that incorporating volatility spillovers and asymmetric do not contribute to better conditional correlations forecasts.
Jackknife Estimator for Tracking Error Variance of Optimal Portfolios
Authors: Gopal K. Basak, Ravi Jagannathan, Tongshu Ma
Venue: Management Science (2009)

We develop a jackknife estimator for the conditional variance of a minimum tracking error variance portfolio constructed using estimated covariances. We empirically evaluate the performance of our estimator using an optimal portfolio of 200 stocks that has the lowest tracking error with respect to the S&P 500 benchmark when three years of daily return data are used for estimating covariances. We find that our jackknife estimator provides more precise estimates and suffers less from in-sample optimism when compared to conventional estimators.
Tonight's Dessert: Semantic Web Layer Cakes
Authors: James A. Hendler
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

Tim Berners-Lee's "Semantic Web Layer Cake" is one of the most used figures in our field. It has changed numerous times over the years, as new technologies have come along, and as the field has changed. Despite this, it appears to be incomplete --- lots happening in the field is not included. In this talk, we take a look at the layer cake as it has changed over time and see what it can tell us about current and future Semantic Web work.
Archipelago: nonparametric Bayesian semi-supervised learning
Authors: Ryan Prescott Adams, Zoubin Ghahramani
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

Semi-supervised learning (SSL), is classification where additional unlabeled data can be used to improve accuracy. Generative approaches are appealing in this situation, as a model of the data's probability density can assist in identifying clusters. Nonparametric Bayesian methods, while ideal in theory due to their principled motivations, have been difficult to apply to SSL in practice. We present a nonparametric Bayesian method that uses Gaussian processes for the generative model, avoiding many of the problems associated with Dirichlet process mixture models. Our model is fully generative and we take advantage of recent advances in Markov chain Monte Carlo algorithms to provide a practical inference method. Our method compares favorably to competing approaches on synthetic and real-world multi-class data.
Paragraph Development Schemata to Support English Composition
Authors: Hidenobu Kunichika, Akira Takeuchi
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

We propose “paragraph development schemata” in English to help learners learn good paragraph structures for English composition. Each schema is expressed by standardized and fine grain sized terminology. Owing to the schemata, learners will be able to know what paragraph structures exist, recognize how each structure is different, and when a learner selects one schema she can be aware of the lack of necessary information by herself.
A Vision-Based System For Automatic Detection and Extraction Of Road Networks
Authors: Charalambos Poullis, Suya You, Ulrich Neumann
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

In this paper we present a novel vision-based system for automatic detection and extraction of complex road networks from various sensor resources such as aerial photographs, satellite images, and LiDAR. Uniquely, the proposed system is an integrated solution that merges the power of perceptual grouping theory(gabor filtering, tensor voting) and optimized segmentation techniques(global optimization using graph-cuts) into a unified framework to address the challenging problems of geospatial feature detection and classification. Firstly, the local presicion of the gabor filters is combined with the global context of the tensor voting to produce accurate classification of the geospatial features. In addition, the tensorial representation used for the encoding of the data eliminates the need for any thresholds, therefore removing any data dependencies. Secondly, a novel orientation-based segmentation is presented which incorporates the classification of the perceptual grouping, and results in segmentations with better defined boundaries and continuous linear segments. Finally, a set of gaussian-based filters are applied to automatically extract centerline information (magnitude, width and orientation). This information is then used for creating road segments and then transforming them to their polygonal representations.
An expert trajectory design for control of nuclear research reactors
Authors: Ramazan Coban, Burhanettin Can
Venue: Expert Systems with Applications: An International Journal (2009)

In this study, an expert trajectory was proposed for control of nuclear research reactors. The trajectory being followed by the reactor power is composed of three parts. In order to calculate periods at the midpoint of each part of the trajectory, a period generator was designed based on artificial neural networks. The contribution of the expert trajectory to the reactor control system was investigated. Furthermore, the behavior of the controller with the expert trajectory was tested for various initial and desired power levels, as well as under disturbance. It was seen that the controller could control the system successfully under all conditions within the acceptable error tolerance.
Design of the notification system for failure detectors
Authors: Naohiro Hayashibara, Makoto Takizawa
Venue: International Journal of High Performance Computing and Networking (2009)

It is widely recognised that distributed systems would greatly benefit from the availability of a generic failure detection service. In this paper, we highlighted the issue on the construction of the monitoring network of failure detectors. We proposed an algorithm to construct and manage the monitoring network that each failure detector is monitored by some failure detectors. Notification of failures is propagated along the network. Especially it can involve various types of failure detectors from simple timeout-based failure detectors to accrual failure detectors, and help to spread information on suspected processes&#47;nodes. In addition, we have made a simulation of the proposed algorithm for constructing the monitoring network. It shows that the algorithm is scalable for increasing the number of failure detectors.
Interlinear glossing and its role in theoretical and descriptive studies of African and other lesser-documented languages
Authors: Dorothee Beermann, Pavel Mihaylov
Venue: Proceedings of the First Workshop on Language Technologies for African Languages (2009)

In a manuscript William Labov (1987) states that although linguistics is a field with a long historical tradition and with a high degree of consensus on basic categories, it experiences a fundamental devision concerning the role that quantitative methods should play as part of the research progress. Linguists differ in the role they assign to the use of natural language examples in linguistic research and in the publication of its results. In this paper we suggest that the general availability of richly annotated, multi-lingual data directly suited for scientific publications could have a positive impact on the way we think about language, and how we approach linguistics. We encourage the systematic generation of linguistic data beyond what emerges from fieldwork and other descriptive studies and introduce an online glossing tool for textual data annotation. We argue that the availability of such an online tool will facilitate the generation of in-depth annotated linguistic examples as part of linguistic research. This in turn will allow the build-up of linguistic resources which can be used independent of the research focus and of the theoretical framework applied. The tool we would like to present is a non-expert-user system designed in particular for the work with lesser documented languages. It has been used for the documentation of several African languages, and has served for two projects involving universities in Africa.
Source code and binary analysis of software defects
Authors: Daniel Quinlan, Thomas Panas
Venue: Proceedings of the 5th Annual Workshop on Cyber Security and Information Intelligence Research: Cyber Security and Information Intelligence Challenges and Strategies (2009)

This extended abstract presents the techniques to identify a selected set of software defects (bugs, bad practices, etc.) within both source code and binary executables. We present the results from six different static analysis tests applied on both the source code and the binary executables (with and without optimization) on three different applications. We compare the precision of the static analysis results from the source code and the binary executable forms of the same software. Ideally the results from an analysis of source code and its binary would be identical, but in practice the source code and binary representation cause slightly different techniques to be used with different amounts and types of information readily available. Our work defines a few defect analyses to support what might later be a larger collection of analyses. Our goal is to more thoroughly evaluate software quality and eliminate, as much as possible, the classic asymmetry of information about software, specifically quality as understood by the software developer vs. the software user. It is not well studied how static analysis of source code and binaries are related for purposes of evaluating general quality and our work is focused in this direction; much less are the tools for such work openly available. Our work also presents an open framework well suited for identifying general software properties of both source code and binary executables.
Multistability of HNNs with almost periodic stimuli and continuously distributed delays
Authors: Zhenkun Huang, Sannay Mohamad, Honghua Bin
Venue: International Journal of Systems Science (2009)

In this article, we investigate multistability of Hopfield neural networks (HNNs) with almost periodic stimuli and continuously distributed delays. By employing the theory of exponential dichotomy and Schauder's fixed point theorem, sufficient conditions are gained for the existence of 2N almost periodic solutions which lie in invariant regions. Meanwhile, we derive some new criteria for the networks to converge toward these 2N almost periodic solutions and the domain of attraction is also given. The obtained results are new, general and improve corresponding results existing in previous literature.
Intelligent file scoring system for malware detection from the gray list
Authors: Yanfang Ye, Tao Li, Qingshan Jiang, Zhixue Han, Li Wan
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Currently, the most significant line of defense against malware is anti-virus products which focus on authenticating valid software from a white list, blocking invalid software from a black list, and running any unknown software (i.e., the gray list) in a controlled manner. The gray list, containing unknown software programs which could be either normal or malicious, is usually authenticated or rejected manually by virus analysts. Unfortunately, along with the development of the malware writing techniques, the number of file samples in the gray list that need to be analyzed by virus analysts on a daily basis is constantly increasing. In this paper, we develop an intelligent file scoring system (IFSS for short) for malware detection from the gray list by an ensemble of heterogeneous base-level classifiers derived by different learning methods, using different feature representations on dynamic training sets. To the best of our knowledge, this is the first work of applying such ensemble methods for malware detection. IFSS makes it practical for virus analysts to identify malware samples from the huge gray list and improves the detection ability of anti-virus software. It has already been incorporated into the scanning tool of Kingsoft's Anti-Virus software. The case studies on large and real daily collection of the gray list illustrate that the detection ability and efficiency of our IFSS system outperforms other popular scanning tools such as NOD32 and Kaspersky.
StarTrack: a framework for enabling track-based applications
Authors: Ganesh Ananthanarayanan, Maya Haridasan, Iqbal Mohomed, Doug Terry, Chandramohan A. Thekkath
Venue: Proceedings of the 7th international conference on Mobile systems, applications, and services (2009)

Mobile devices are increasingly equipped with hardware and software services allowing them to determine their locations, but support for building location-aware applications remains rudimentary. This paper proposes tracks of location coordinates as a high-level abstraction for a new class of mobile applications including ride sharing, location-based collaboration, and health monitoring. Each track is a sequence of entries recording a person's time, location, and application-specific data. StarTrack provides applications with a comprehensive set of operations for recording, comparing, clustering and querying tracks. StarTrack can efficiently operate on thousands of tracks.
Active suspension system - experiments
Authors: Antonin Stribrsky, Katerina Hyniova Jaroslav Honcu, Ales Kruczek
Venue: Proceedings of the 4th WSEAS/IASME international conference on Dynamical systems and control (2008)

Suspension system is an important part of the car design, because it influences both the comfort and safety of the passengers. In this paper an active suspension using linear electric motor is designed. In particular, this article is focused on experiments with active suspension - developing an appropriate input signal for the test bed and evaluation of the results. Second important point of the active suspension design is energy demands of the system. Modification of the standard controller which allows changing amount of energy required by the system has been designed. Functionality of the modification was verified taking various experiments.
Statistical performance evaluation, system modeling, distributed computation and signal pattern matching for a compton medical imaging system
Authors: Neal H. Clinthorne, W. Leslie Rogers
Venue:  (2008)

Radionuclide cancer therapy requires imaging radiotracers that concentrate in tumors and emit high energy charged particles that kill tumor cells. These tracers, such as 131I, generally emit high energy gamma photons that need to be imaged to estimate tumor dose and changes in size during treatment.This research describes the performance of a dual-planar silicon-based Compton imaging system and compares it to a conventional parallel-hole collimated Anger camera with high energy general purpose lead collimator for imaging higher energy photons emitted from 131I.The collimated Anger camera imposes a tradeoff between resolution and sensitivity because of the physical constraints resulting from the mechanical collimation. As the &gamma;-ray photons exceed 364keV, increased septal penetration and scattering further degrade the imaging performance. Simulations of the Anger camera and the Compton imaging system demonstrate a 20-fold advantage in detection efficiency and higher spatial resolution for detecting high energy photons by the Compton camera since it decouples the resolution-sensitivity tradeoff.The system performance and comparison are also analyzed using the modified uniform Cramer-Rao bound algorithms we developed and verified along with the Monte Carlo calculations and system modeling. The bound calculations show that the effect of Doppler broadening is the limiting factor for Compton camera performance for imaging 364keV photons. Performance of the two systems was compared and analyzed by simulating a 2D disk with uniform activities. For the case in which the two imaging systems detected the same number of events, the proposed Compton imaging system has lower image variance than the Anger camera with HEGP when the FWHM of the desired point source response is less than 1.2 cm. This advantage was also demonstrated by imaging and reconstructing a 2D hot spot phantom.In addition to the performance analysis, the distributed and parallel Maximum Likelihood Maximization Expectation algorithm with chessboard data partition was evaluated for speeding up image reconstruction for the Compton imaging system. A 1 x 64 distributed computing system speeded computation by about a factor of 22 compared to a single processor. Finally, a real time signal processing and pattern matching system employing state-of-the-art digital electronics is described for solving problems of event pile-up raised by high photon count rate in the second detector.
A platform-based design environment for synthetic biological systems
Authors: Douglas Densmore, Anne Van Devender, Matthew Johnson, Nade Sritanyaratana
Venue: The Fifth Richard Tapia Celebration of Diversity in Computing Conference: Intellect, Initiatives, Insight, and Innovations (2009)

Genomics has reached the stage at which the amount of DNA sequence information in existing databases is quite large. Synthetic biology is now using these databases to catalog sequences according to their functionality thus creating a system of standard biological parts. Flexible tools are needed which both permit access and modification to that data and also allow one to perform meaningful, intelligent manipulation. A Platform-Based Design approach views genetic information as having a particular functionality and assembles platforms (collections of DNA elements) to perform this functionality. Specifically this paper presents the Clotho toolset which uses these concepts to create a complete design environment for standardized biological parts.