ppxscal/embedding_network huggingface dataset:
MuTT: A Multi-Threaded Tracer for Java Programs
Authors: Dapeng Liu, Shaochun Xu
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

Tracing is an important technique for program comprehension and software maintenance. Existing trace tools have some limitations, such as requiring instrumentation. This paper presents a tracer, MuTT, which can be used to collect the run-time information of multi-threaded Java programs without source code or JVM instrumentation. We also propose guidelines to use MuTT for feature location in Object-Oriented Systems, particularly in the Event-Driven Systems. We conduct two case studies and the result demonstrates that MuTT can provide effective tracing and can be used for feature location, especially with the help of GREP.
Risks and Safeguards for the Requirements Engineering Process in Global Software Development
Authors: Alejandro Lopez, Joaquín Nicolas, Ambrosio Toval
Venue: Proceedings of the 2009 Fourth IEEE International Conference on Global Software Engineering (2009)

The rise of new development paradigms such as Global Software Development (GSD) forces Requirements Engineering (RE) to face up to new challenges and risks not common in traditional development models. When an organization first embarks upon a GSD project it exposes itself to plenty of risks. Many of these risks appear as a result of the lack of experience of the development team on GSD projects. A Systematic Literature Review (SLR) has led to the compilation of a repository which gathers the risks that concern RE when developed in a distributed software development environment, as well as a set of safeguards, which help overcoming such risks. This repository, open to progressive enrichment, provides a novel basis to assist in RE activities for GSD projects. It could be especially useful when the developers have little experience in distributed projects and cannot prevent communication, distance, cultural, or organizational risks. Although the repository collects the main contributions from published work in the field, it has not been validated on real GSD projects yet.
Homological Tree-Based Strategies for Image Analysis
Authors: P. Real, H. Molina-Abril, Walter Kropatsch
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

Homological characteristics of digital objects can be obtained in a straightforward manner computing an algebraic map ¿ over a finite cell complex K (with coefficients in the finite field $\textbf{F}_2=\{0,1\}$) which represents the digital object [9]. Computable homological information includes the Euler characteristic, homology generators and representative cycles, higher (co)homology operations, etc. This algebraic map ¿ is described in combinatorial terms using a mixed three-level forest. Different strategies changing only two parameters of this algorithm for computing ¿ are presented. Each one of those strategies gives rise to different maps, although all of them provides the same homological information for K. For example, tree-based structures useful in image analysis like topological skeletons and pyramids can be obtained as subgraphs of this forest.
Using coreference chains for text summarization
Authors: Saliha Azzam, Kevin Humphreys, Robert Gaizauskas
Venue: Proceedings of the Workshop on Coreference and its Applications (1999)

We describe the use of coreference chains for the production of text summaries, using a variety of criteria to select a 'best' chain to represent the main topic of a text. The approach has been implemented within an existing MUC coreference system, which constructs a full discourse model of texts, including information about changes of focus, which can be used in the selection of chains. Some preliminary experiments on the automatic evaluation of summaries are also described, using existing tools to attempt to replicate some of the recent SUMMAC manual evaluations.
Learning the past tense of English verbs: the symbolic pattern associator vs. connectionist models
Authors: Charles X. Ling
Venue: Journal of Artificial Intelligence Research (1993)

Learning the past tense of English verbs - a seemingly minor aspect of language acquisition - has generated heated debates since 1986, and has become a landmark task for testing the adequacy of cognitive modeling. Several artificial neural networks (ANNs) have been implemented, and a challenge for better symbolic models has been posed. In this paper, we present a general-purpose Symbolic Pattern Associator (SPA) based upon the decision-tree learning algorithm ID3. We conduct extensive head-to-head comparisons on the generalization ability between ANN models and the SPA under different representations. We conclude that the SPA generalizes the past tense of unseen verbs better than ANN models by a wide margin, and we offer insights as to why this should be the case. We also discuss a new default strategy for decision-tree learning algorithms.
Automatic Reverse Engineering of Malware Emulators
Authors: Monirul Sharif, Andrea Lanzi, Jonathon Giffin, Wenke Lee
Venue: Proceedings of the 2009 30th IEEE Symposium on Security and Privacy (2009)

Malware authors have recently begun using emulation technology to obfuscate their code. They convert native malware binaries into bytecode programs written in a randomly generated instruction set and paired with a native binary emulator that interprets the bytecode. No existing malware analysis can reliably reverse this obfuscation technique.In this paper, we present the first work in automatic reverse engineering of malware emulators. Our algorithms are based on dynamic analysis. We execute the emulated malware in a protected environment and record the entire x86 instruction trace generated by the emulator. We then use dynamic data-flow and taint analysis over the trace to identify data buffers containing the bytecode program and extract the syntactic and semantic information about the bytecode instruction set. With these analysis outputs, we are able to generate data structures, such as control-flow graphs, that provide the foundation for subsequent malware analysis. We implemented a proof-of-concept system calledRotalume and evaluated it using both legitimate programs and malware emulated by VMProtect and Code Virtualizer. The results show that Rotalume accurately reveals the syntax and semantics of emulated instruction sets and reconstructs execution paths of original programs from their bytecode representations.
Assessing alignment of an e-government project in the context of a developing country: a Heideggerian perspective
Authors: Nixon Muganda
Venue: Proceedings of the 2009 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists (2009)

E-Government has increasingly become an alternative for enabling public governance at various. The situation is especially poignant in developing countries where there are increasing calls to improve governance for improved national development. This study sought to investigate managerial processes in the alignment of e-government within Local Authorities in Kenya. A case study research design underpinned by critical realism assumptions was used. The analysis was grounded on empirical results of the study, and employed theoretical thematic analysis. Under the alienating conditions of social exclusion, the alignment of the e-government artifact espoused strong managerialist orientations of augmenting and reinforcing central governments control over its polity. A consequence of this alignment is a tendency towards technocratic evolution of the public service delivery system in local authorities in Kenya. However, it was also recognised that the form of e-government projects are constantly in flux, and that relying on a single case was therefore a limitation of the study. Categories and Subject Descriptors
Understanding Brain, Cognition, and Behavior in Complex Dynamic Environments
Authors: Scott E. Kerick, Kaleb Mcdowell
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

Many challenges remain for understanding how the human brain functions in complex dynamic environments. For example, how do we measure brain physiology of humans interacting in their natural environments where data acquisition systems are intrusive and environmental and biological artifacts severely confound brain source signals? How do we understand the full context within which the human brain is operating? How do we know which information is most meaningful to extract from the data? How can we best utilize that extracted information and what are the implications for human performance? The papers comprising this section address these questions from conceptual, technical, and applied perspectives. It is clearly seen that significant progress has been made since the inception of the Augmented Cognition program and that, to overcome these challenges, a continued multidisciplinary approach is required across basic and applied research from cognitive scientists, neuroscientists, computer scientists, and engineers.
Error Calibration and FDI Technology of Gyros in Redundant IMU
Authors: Shuguang Sun, Ruihua Liu
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

In this paper, we analyzed calibration method and fault detection & isolation method for gyro errors. A six sensors configuration redundant inertial measurement unit (IMU) is used for simulation. The gyro's error characters have been considered, equations to estimate the error coefficients have been formulated and validated using data got from turntable test, the fault detection & isolation (FDI) method also has been used and tested using calibrated data, the result shows that this method is useful and reliable, would be a good way to be used in redundant IMU sensor for FDI.
An Autonomous System for the Locomotion of a Hexapod Exploration Robot
Authors: Pablo Munoz-Martinez, María D. R-Moreno, Javier Gomez-Elvira, Julio J. Romeral-Planello, Sara Navarro-Lopez
Venue: Proceedings of the Third IEEE International Conference on Space Mission Challenges for Information Technology (2009)

Ptinto is a hexapod robot designed to keep the equilibrium when moving around rocky and cumbersome areas during the exploration of the Tinto river in Huelva (Spain). We have developed an integrated planning and scheduling system called PIPSS to control the locomotion of the P-Tinto robot. PIPSS tries to make the better moves for the legs in order to keep the right balance and calculate the trajectory between two points. It exchanges information with an executor system that execute the plan, and in case there are some obstacles that Ptinto cannot avoid, a new trajectory will be re-calculated.
Evaluating state-of-the-art treebank-style parsers for Coh-metrix and other learning technology environments
Authors: Christian F. Hempelmann, Vasile Rus, Arthur C. Graesser, Danielle S. McNamara
Venue: Proceedings of the second workshop on Building Educational Applications Using NLP (2005)

This paper evaluates a series of freely available, state-of-the-art parsers on a standard benchmark as well as with respect to a set of data relevant for measuring text cohesion. We outline advantages and disadvantages of existing technologies and make recommendations. Our performance report uses traditional measures based on a gold standard as well as novel dimensions for parsing evaluation. To our knowledge this is the first attempt to evaluate parsers accross genres and grade levels for the implementation in learning technology.
Study on Test Databank Construction And Algorithm of Test Paper Generation System
Authors: Xiaoying Sun
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 02 (2009)

With the help of examination theory and education mathematics, the requirements of the test paper are analyzed in details. The mathematical model of intelligent test paper generation system is set up. The paper is a tentative probe into the relevant problems of building such a databank and in particular into the policy and algorithm of test paper composition. The method of test paper auto-generation based on General Discrete particle swarm optimization is proposed.
Measuring the uncertainty of differences for contrasting groups
Authors: Jilian Zhang, Shichao Zhang, Xiaofeng Zhu, Xindong Wu, Chengqi Zhang
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

In this paper, we propose an empirical likelihood (EL) based strategy for building confidence intervals for differences between two contrasting groups. The proposed method can deal with the situations when we know little prior knowledge about the two groups, which are referred to as non-parametric situations. We experimentally evaluate our method on UCI datasets and observe that proposed EL based method outperforms other methods.
Transmission Scheduling in Data-Driven Peer-to-Peer Streaming towards Optimal Throughput
Authors: Jiqing Wu, Yuxing Peng, Feng Liu
Venue: Proceedings of the 2009 IEEE International Conference on Networking, Architecture, and Storage (2009)

Peer-to-peer media streaming has been an important service on the internet in recent years. The Data-driven (or mesh-based) structure is adopted by most working systems,in which data scheduling is one of the important problems.However, those frequently used scheduling algorithms are often faced with such a case: A neighbor peer takes up its bandwidth to deliver the packets that other neighbors can also supply, but some packets only held by it are not delivered.These packets can not be delivered in the current scheduling cycle, even though that the other neighbors have surplus bandwidth. This is a kind of waste of bandwidth and decreases the throughput of transmission. In this paper we propose anew scheduling algorithm aiming at the optimal throughput:Bipartite-matching based Block Scheduling algorithm(BBS).We convert the original data scheduling problem to a problem of finding a maximum match on the correspond bipartite graph, then assign data packets to neighbors according to the maximum match. We evaluate the performance of BBS with extensive experiments and the results show that BBSthroughput and provides better streaming quality than those frequently used scheduling algorithms.
Signal De-noising in Ultrasonic Testing Based on Stationary Wavelet Transform
Authors: Yuan Chen, Hongwei Ma
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

In ultrasonic testing, the quality of flaw echo-signals is a foundation for locating, quantitative and qualitative analysis. Thus, signal de-noising and increasing of the signal-to-noise ratio (SNR) are a key to successful application of ultrasonic NDT and NDE. In this paper, the theory of discrete wavelet transform (DWT) and stationary wavelet transform (SWT) is introduced. Moreover, differences are compared between DWT and SWT in signal decomposition and reconstruction. And according to the characteristics of ultrasonic flaw echo-signals, the principle and method of de-noising via thresholding based on SWT are studied. Finally, the experiment of signal de-noising by DWT and SWT are carried out for actual defect echo-signals. The experimental results show that SWT has the advantage of translation invariance after signal de-noising. This method not only can greatly remove the noises, but also provide the exact data for accurate localization of flaw.
Evaluation of a Client Centric Payment Protocol Using Digital Signature Scheme with Message Recovery Using Self-Certified Public Key
Authors: Miguel Viedma Astudillo, Jesús Téllez Isaac, Diego Suarez Touceda, Héctor Plaza López
Venue: Proceedings of the International Conference on Computational Science and Its Applications: Part II (2009)

In this work, we present a mobile e-payment scenario where the merchant entity has important connectivity restrictions, which is only able of communicating through short distance connections (Wi-Fi or Bluetooth). To protect the exchange of messages, our work describes a payment protocol centered in the client which applies digital signature with recovery using self-certified public keys. Additionally, security aspects have been analyzed and protocol implementation specifications have been presented.
Utilizing Secondary Input from Passive Brain-Computer Interfaces for Enhancing Human-Machine Interaction
Authors: T. O. Zander, C. Kothe, S. Welke, M. Roetting
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

A Brain-Computer Interface (BCI) directly translates patterns of brain activity to input for controlling a machine. The introduction of methods from statistical machine learning [1] to the field of brain-computer interfacing (BCI) had a deep impact on classification accuracy. It also minimized the effort needed to build up the skill of controlling a BCI system [2]. This enabled other fields of research to adapt methods from BCI research for their own purposes [3, 4]. Team PhyPA, the research group for physiological parameters of the chair for Human-Machine Systems (HMS) of the Technical University of Berlin, focuses on enabling new communication channels for HMS. Especially the use of passive BCIs (pBCI) [3, 4], not dependent on any intended action of the user, show a high potential for enhancing the interaction in HMS [5]. Additionally, as actual classification rates are still below the threshold for efficient primary control [6, 7] in HMS, we focus on establishing a secondary, BCI-based communication channel. This kind of interaction does not necessarily disturb the primary mode of interaction, providing a low usage cost and hence an efficient way of enhancement. We have designed several applications following this approach. Here we are going to present briefly the results from two studies, which show the capabilities arising from the use of passive and secondary BCI interaction. First, we show that a pBCI can be utilized to gain valuable information about HMSs, which are hard to detect by exogeneous factors. By mimicking a typical BCI interaction, we have been able to identify and isolate a factor inducing non-stationarities with a deep impact on the feature dynamics. The retained information can be utilized for automatically triggered classifier adaptation. And second, we show that pBCIs are indeed capable to enhance common HMS interaction outside the laboratory. With this, we would like to feed back our experiences made with the use of BCIs for HMS. We hope to povide new and useful information about brain dynamics which might be helpful for ongoing research in augmented cognition.
Learning and knowledge building with social software
Authors: Joachim Kimmerle, Johannes Moskaliuk, Ulrike Cress
Venue: Proceedings of the 9th international conference on Computer supported collaborative learning - Volume 1 (2009)

The progress of the Internet in recent years has led to the emergence of so-called social software. This technology concedes users a more active role in creating Web content. This has important effects both on individual learning and collaborative knowledge building. In this paper we will present an integrative framework model to describe and explain learning and knowledge building with social software on the basis of systems theoretical and equilibration theoretical considerations. This model assumes that knowledge progress emerges from cognitive conflicts that result from incongruities between an individual's prior knowledge and the information which is contained in a shared digital artifact. This paper will provide empirical support for the model by applying it to Wikipedia articles and by examining knowledge-building processes using network analyses. Finally, this paper will present a review of a series of experimental studies.
Adaptation Decisions and Profiles Exchange among Open Learning Management Systems Based on Agent Negotiations and Machine Learning Techniques
Authors: Silvia Baldiris, Ramón Fabregat, Carolina Mejía, Sergio Gómez
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part IV: Interacting in Various Application Domains (2009)

We have developed some projects [1,2] for addressing the heterogeneity problem in open learning management systems (LMS). In [3], an independent adaptation platform to support competences development through personalization is presented. Three user characteristics (competences profile, learning style, and accessing context) are modeled by means of analyzing user interaction data in a LMS. This process is supported by the assigment of independent adaptation tasks to different JADE intelligent agents. In this paper we introduce some negotiation strategies among those intelligent agents in order to: 1) select the best types of adaptation through collaborative tasks, and 2) generate standards and exchangeable user profiles based on the inferred user characteristics, describing the mechanisms to mobilize these profiles between different LMSs. These profiles support the generation of specifics learning designs for each particular user.
Lexical Affinity Measure between Words
Authors: Ivar Willegen, Leon Rothkrantz, Pascal Wiggers
Venue: Proceedings of the 12th International Conference on Text, Speech and Dialogue (2009)

In this paper we research the lexical affinity between words. Our goal is to define a distance measure which corresponds with the semantic affinity between words. This measure is based on WordNet, where two words/concepts can be connected by a string of stepwise synonyms. The number of hops defines the distance between words. In addition we present a natural language processing toolbox, developed in the course of this work, that combines a number of existing tools and adds a number of analysis tools.
Development of a Technique for Predicting the Human Response to an Emergency Situation
Authors: Glyn Lawson, Sarah Sharples, David Clarke, Sue Cobb
Venue: Proceedings of the 8th International Conference on Engineering Psychology and Cognitive Ergonomics: Held as Part of HCI International 2009 (2009)

This paper presents development work on a new approach for predicting the human response to an emergency situation. The study builds upon an initial investigation in which 20 participants were asked to predict what actions they would take in the event of a domestic fire [1]. The development work involved a retest with an additional 20 participants to investigate the reliability of the approach. Furthermore, the analysis procedure was improved such that the results represented more accurately those which could be obtained from practical application of the approach. As found in the initial investigation, the frequencies and sequences of the reported acts had significant relationships with a study of behavior in real fires [2] (Spearman's rho: 0.323, N=55, p<0.05) and (Spearman's rho: 0.340, N=37, p<0.05), respectively. Further development work is required, but the results indicate that the approach may have use for predicting human behavior in emergencies.