ppxscal/embedding_network huggingface dataset:
A flexible model for multi-agent based simulation of software development process
Authors: David Umphress
Venue:  (2007)

Inadequate use of project management techniques in software development can be traced to the lack of efficient education strategies for managers [24]. Software development processes are complex and therefore it is hard to predict how changes made to some part of the process can affect the overall outcome of the process. Introducing change in the process is often time consuming and there is no assurance that the change implemented will result in an improvement. Simulation of software development process provides an easy way for managers to test the different configurations of the process and understand the effects of various policies. In this work, the users of the simulation can act as managers without caring about the risks of the failures of real software projects. This simulation is a learning-by-doing model where software developers and students can understand the concepts of software process and the underlying risk, and other decision making activities. This project aims at developing a software process simulation with an agent architecture, where the agents are the entities that mimic the real software developers within the simulation. The individual behavior of the agents is based on the statistical data collected over a period of time using Personal Software Process (PSP). Given the statistics collected, expected behavior of the individuals can be enacted over time during the scope of software development. The provision of having a user constantly monitoring the software development within the simulation is made. In this work, simulation processes can be changed during the model execution. The simulation accepts the feedback from the user after every period of time. The simulation interface displays the actual vs. planned matrix. Based on these matrices of comparison, the user can introduce any changes to the software process that he thinks might improve the overall development cycle of the project. Using agent directed simulation to mimic the software development process at the individual level also would enable us to introduce a new phase of software development without having to change the simulation code. This simulation would start with a given number of agents initialized by the user. At any point of time, the user may change the number of developers or assign developers on different phases of the software development depending on their performance and capabilities.
A Novel Audio Steganalysis Based on High-Order Statistics of a Distortion Measure with Hausdorff Distance
Authors: Yali Liu, Ken Chiang, Cherita Corbett, Rennie Archibald, Biswanath Mukherjee, Dipak Ghosal
Venue: Proceedings of the 11th international conference on Information Security (2008)

Steganography can be used to hide information in audio media both for the purposes of digital watermarking and establishing covert communication channels. Digital audio provides a suitable cover for high-throughput steganography as a result of its transient and unpredictable characteristics. Distortion measure plays an important role in audio steganalysis - the analysis and classification method of determining if an audio medium is carrying hidden information. In this paper, we propose a novel distortion metric based on Hausdorff distance. Given an audio object x which could potentially be a stego-audio object, we consider its de-noised version x¿ as an estimate of the cover-object. We then use Hausdorff distance to measure the distortion from x to x¿. The distortion measurement is obtained at various wavelet decomposition levels from which we derive high-order statistics as features for a classifier to determine the presence of hidden information in an audio signal. Extensive experimental results for the Least Significant Bit (LSB) substitution based steganography tool show that the proposed algorithm has a strong discriminatory ability and the performance is significantly superior to existing methods. The proposed approach can be easily applied to other steganography tools and algorithms.
Margin-Based First-Order Rule Learning
Authors: Ulrich Rückert, Stefan Kramer
Venue: Inductive Logic Programming: 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers (2007)

Learning sets of first-order rules has a long tradition in machine learning and inductive logic programming. While most traditional systems follow a separate-and-conquer approach, many modern systems are based on statistical considerations, such as ensemble theory, large margin classification or graphical models. In this work, we frame relational learning as a statistical classification problem and apply tools and concepts from statistical learning theory to design a new statistical first-order rule learning system. The system's design is motivated by the goal of finding theoretically well-founded answers to some of the greatest challenges faced by first-order learning systems. First, using strict binary-valued logic as a representation language is known to be suboptimal for noisy, imprecise or uncertain data and background knowledge as frequently encountered in practice. As in many other state-of-the-art rule learning approaches [1], we therefore assign weights to the rules. In this way, a rule set represents a linear classifier and one can optimize margin-based optimization criteria, essentially reducing the misclassification error on noisy data. Since we aim at comprehensible models, we employ margins without the kernel trick. Second, the problem of finding a hypothesis that explains the training set is known to be NP-hard even for the simplest possible classifiers, from propositional monomials to linear classifiers. To avoid the computational complexity of optimizing the empirical training error directly, we use a feasible margin-based relaxation, margin minus variance (MMV), as introduced recently for propositional domains [2]. MMV minimization is linear in the number of instances and therefore well-suited for large datasets. Third, in multi-relational learning settings, one can formulate almost arbitrarily complex queries or clauses, to describe a training or test instance. Thus, there is a potentially unlimited number of features that can be used for classification and overfitting avoidance should be of great importance. We derived an error bound based on MMV, giving us a theoretically sound stopping criterion controlling the number of rules in a weighted rule set. The rule generation process is based on traditional first-order rule refinement and declarative language bias. It is possible to choose from a variety of search strategies, from a predefined order of clauses to rearranging the order based on the weights attached to clauses in the model so far. The system is implemented as a stand-alone tool integrating a Prolog engine.
Representative democracy and information society - A postmodern perspective
Authors: P. H. A. Frissen
Venue: Information Polity (2002)

This article is based upon the Machiavelli Lecture 2000. This yearly lecture was given by the author at the occasion of the presentation of the Machiavelli Prize 2000 for Government Communication. The lecture was entitled 'The Anarchist Republic'. The prize was awarded to J. van Nieuwenhoven, at that time chairwoman of the Dutch Parliament.
Design and analysis of WiMAX's security system on FPGA
Authors: Reza Ebrahimi Atani, Mehdi Baboli, Sattar Mirzakuchaki
Venue: Proceedings of the 7th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications (2008)

WiMAX, or the IEEE 802.16 standard for broadband wireless access, is increasingly gaining in popularity as a technology with significant market potential. This paper first provides an overview of the existing and developing 802.16 standards and then the paper describes different test platforms for post synthesis simulation and validation of the FPGA implementation of the WiMax's security system (CCMP). For this, KAT and MCT tests and power analysis have been used. Power analysis of the implementation has been estimated using XPower of ISE (Xilinx).
Mining Frequent Trajectories of Moving Objects for Location Prediction
Authors: Mikołaj Morzy
Venue: Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition (2007)

Advances in wireless and mobile technology flood us with amounts of moving object data that preclude all means of manual data processing. The volume of data gathered from position sensors of mobile phones, PDAs, or vehicles, defies human ability to analyze the stream of input data. On the other hand, vast amounts of gathered data hide interesting and valuable knowledge patterns describing the behavior of moving objects. Thus, new algorithms for mining moving object data are required to unearth this knowledge. An important function of the mobile objects management system is the prediction of the unknown location of an object. In this paper we introduce a data mining approach to the problem of predicting the location of a moving object. We mine the database of moving object locations to discover frequent trajectories and movement rules. Then, we match the trajectory of a moving object with the database of movement rules to build a probabilistic model of object location. Experimental evaluation of the proposal reveals prediction accuracy close to 80%. Our original contribution includes the elaboration on the location prediction model, the design of an efficient mining algorithm, introduction of movement rule matching strategies, and a thorough experimental evaluation of the proposed model.
Hiding Sensitive Associative Classification Rule by Data Reduction
Authors: Juggapong Natwichai, Maria E. Orlowska, Xingzhi Sun
Venue: Proceedings of the 3rd international conference on Advanced Data Mining and Applications (2007)

When data sharing becomes necessary, there is a dilemma in preserving privacy. On one hand sensitive patterns such as classification rules should be hidden from being discovered. On the other hand, hiding the sensitive patterns may affect the data quality. In this paper, we present our studies on the sensitive classification rule hiding problem by data reduction approach, i.e., removing the whole selected records. In our work, we focus on a particular type of classification rule, called canonical associative classification rule. And, the impact on data quality is evaluated in terms of the number of affected non-sensitive rules. We present the observations on the data quality based on a geometric model. According to the observations, we can show the impact precisely without any re-computing. This helps to improve the hiding algorithms from both effectiveness and efficiency perspective. Additionally, we present the algorithmic steps to demonstrate the removal of the records so that the impact on the data quality is potentially minimal. Finally, we conclude our work and outline future work directions for this problem.
Classification of Continuous Heart Sound Signals Using the Ergodic Hidden Markov Model
Authors: Yong-Joo Chung
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I (2007)

Recently, hidden Markov models (HMMs) have been found to be very effective in classifying heart sound signals. For the classification based on the HMM, the continuous cyclic heart sound signal needs to be manually segmented to obtain isolated cycles of the signal. However, the manual segmentation will be practically inadequate in real environments. Although, there have been some research efforts for the automatic segmentation, the segmentation errors seem to be inevitable and will result in performance degradation in the classification. To solve the problem of the segmentation, we propose to use the ergodic HMM for the classification of the continuous heart sound signal. In the classification experiments, the proposed method performed successfully with an accuracy of about 99(%) requiring no segmentation information.
How Single Ant ACO Systems Optimize Pseudo-Boolean Functions
Authors: Benjamin Doerr, Daniel Johannsen, Ching Hoo Tang
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

We undertake a rigorous experimental analysis of the optimization behavior of the two most studied single ant ACO systems on several pseudo-boolean functions. By tracking the behavior of the underlying random processes rather than just regarding the resulting optimization time, we gain additional insight into these systems. A main finding is that in those cases where the single ant ACO system performs well, it basically simulates the much simpler (1+1) evolutionary algorithm.
MSO Logic for Unambiguous Shared-Memory Systems
Authors: Rémi Morin
Venue: Proceedings of the 12th international conference on Developments in Language Theory (2008)

Shared-memory systems appear as a generalization of asynchronous cellular automata. In this paper we relate the partial-order semantics of shared-memory systems to Mazurkiewicz trace languages by means of a new refinement construction. We show that a set of labeled partial orders is recognized by some unambiguous shared-memory system if and only if it is definable in monadic second-order logic and media-bounded.
Solution Architecture for Visitor Segmentation and Recommendation Generation in Real Time
Authors: Philip Limbeck, Josef Schiefer
Venue: Proceedings of the 9th international conference on E-Commerce and Web Technologies (2008)

With increasing product portfolios of eCommerce companies it is getting harder for their customers to find the products they like best. A solution to this problem is to analyze the customer's behavior, and recommend products based on ratings. By considering click-stream data, the customer is unburdened with explicitly rating his favored. In this paper, we introduce a system for segmenting visitors and recommending adequate items in real time by using an event-based system called Sense and Respond Infrastructure (SARI) for processing click-stream data. We present the architecture and components for a real-time click-stream analysis which can be easily customized to business needs of domain experts and business users. SARI provides functionality to monitor visitor and customer behavior, respond accordingly and at the same time optimize and adapt customer processes in real time. To illustrate this approach, we introduce a reference implementation, its underlying infrastructure and business scenarios.
On the role of the weight function in the truncation quality of high dimensional model representation
Authors: Pinar Tiryaki, N. A. Baykara, Metin Demiralp
Venue: Proceedings of the 1st WSEAS International Conference on Multivariate Analysis and its Application in Science and Engineering (2008)

This paper investigates the role of the weight function in the quality of the High Dimensional Model Representation's (HDMR) truncations at different levels of multivariance. This is done by evaluating the additivity measurers at different levels of multivariance, for specified weight functions and targets for HDMR. The observations imply that the weight functions picking function values from regions where the addive nature of the target function dominates.
Designing Persuasive Dialogue Systems: Using Argumentation with Care
Authors: Hien Nguyen, Judith Masthoff
Venue: Proceedings of the 3rd international conference on Persuasive Technology (2008)

Persuasive dialogue systems that aim to change people's attitudes and behaviours have drawn much attention in recent years due to their great practical potential. Current systems rely heavily on argumentation and advice-giving to form their persuasive messages. Many findings in psychology, and some counselling intervention methods such as Motivational Interviewing (MI) dispute this confrontational approach. Our project sets out to investigate whether MI can provide an alternative way to develop a more effective system. In this paper, we discuss the limitations of the argumentation-based approach, review a number of argumentation-based systems, and present the results of an evaluation study which compares people's perception of the persuasibility of two argumentation-based dialogues and a MI-based counterpart. Our results show a higher perceived persuasiveness for the MI-based dialogue.
The Well-Tempered Architecture
Authors: Grady Booch
Venue: IEEE Software (2007)

Virtually all well-structured music, music that pleases the ear and moves the spirit, is full of patterns. By comparing musical and software patterns, the author helps clarify the purposes and forms of patterns. Architectural and design patterns make software-intensive systems easier to understand and adapt to because of their regularity and simplicity.
An Accurate and Fast WLAN User Location Estimation Method Based on Received Signal Strength
Authors: Minghua Zhang, Shensheng Zhang
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Location estimation is a crucial component of location-aware applications. Positioning based on received signal strength (RSS) in wireless networks is considered a promising and inexpensive solution. Existing techniques only use RSS from some fixed access points (APs) deployed within the area of interest to estimate user location. Through experiments on the properties of RSS, it is found that RSS from far access points can distinguish different locations more easily. In this paper, we propose to introduce RSS from APs outside of the area to increase location estimation accuracy. We also present an online maximum matching method to select the most possible locations first, thus reducing the computational cost incurred by using more RSS values and improving the speed of location estimation. Our new location estimation method is implemented and compared with related work in a practical wireless network. Experimental results illustrate that the proposed method can give a higher degree of accuracy.
OCR for printed Kannada text to machine editable format using database approach
Authors: B. M. Sagar, G. Shobha, P. Ramakanth Kumar
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

This paper describes an Optical Character Recognition (OCR) system for printed text documents in Kannada, a South Indian language. The proposed OCR system for the recognition of printed Kannada text, which can handle all types of Kannada characters. The system first extracts image of Kannada scripts, then from the image to line segmentation then segments the words into sub-character level pieces. For character recognition we have used database approach. The level of accuracy reached to 100%.
The Latest on Standards-Corrected
Authors: Paul Croll
Venue: IEEE Software (2004)

The chairman of the Technical Council on Software Engineering's Software and Systems Engineering Standards Committee provides an update on the committee's activities.
Case Provenance: The Value of Remembering Case Sources
Authors: David Leake, Matthew Whitehead
Venue: Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2007)

Case-based reasoning systems routinely record the results of prior problem-solving, but not the provenance of new cases: the way in which the new cases were derived. This paper proposes the value of tracking provenance information in CBR, especially when timely feedback may not be available. It illustrates the use of provenance information with studies of the application of provenance information to guide case-base maintenance. Experiments with two data sets illustrate the benefit of using provenance to propagate maintenance and to target maintenance effort.
A contribution to the design of stable fuzzy controllers
Authors: Dragan Z. Šaletic, Nikos E. Mastorakis
Venue: Proceedings of the 9th WSEAS International Conference on Fuzzy Systems (2008)

The paper considers the general fuzzy controllers design problem from a stability viewpoint. A control surface of this kind of expert systems is considered. A kind of inverted pendulum system is described. The contribution to the fuzzy controller design approach is proposed. Conclusions are given and possibilities for further work are pointed out.
An Improved Robust Fuzzy Extractor
Authors: Bhavana Kanukurthi, Leonid Reyzin
Venue: Proceedings of the 6th international conference on Security and Cryptography for Networks (2008)

We consider the problem of building robust fuzzy extractors, which allow two parties holding similar random variables W, W¿ to agree on a secret key R in the presence of an active adversary. Robust fuzzy extractors were defined by Dodis et al. in Crypto 2006 to be noninteractive, i.e., only one message P, which can be modified by an unbounded adversary, can pass from one party to the other. This allows them to be used by a single party at different points in time (e.g., for key recovery or biometric authentication), but also presents an additional challenge: what if R is used, and thus possibly observed by the adversary, before the adversary has a chance to modify P. Fuzzy extractors secure against such a strong attack are called post-application robust.We construct a fuzzy extractor with post-application robustness that extracts a shared secret key of up to (2m ¿ n)/2 bits (depending on error-tolerance and security parameters), where n is the bit-length and m is the entropy of W. The previously best known result, also of Dodis et al., extracted up to (2m ¿ n)/3 bits (depending on the same parameters).
Sentence Ordering for Coherent Multi-document Summary Generation
Authors: C. R. Chowdary, P. Sreenivasa Kumar
Venue: Proceedings of the 25th British national conference on Databases: Sharing Data, Information and Knowledge (2008)

Web queries often give rise to a lot of documents and the user is overwhelmed by the information. Query-specific extractive summarization of a selected set of retrieved documents helps the user to get a gist of the information. The current extractive summary generation systems focus on extracting query-relevant sentences from the documents. However, the selected sentences are presented either in the order in which the documents were considered or in the order in which they were selected. This approach does not guarantee a coherent summary. In this paper, we propose incremental integrated graph to represent the sentences in a collection of documents. Sentences from the documents are merged into a master sequence to improve coherence and flow. The same ordering is used for sequencing the sentences in the extracted summary. User evaluations indicate that the proposed technique markedly improves the user satisfaction with regard to coherence in the summary.
Specification and Implementation of a Folding Parametric Operator to Assist Architectural Conception at the Drafting Stage
Authors: Jean-Paul Wetzel, Salim Belblidia, Jean-Claude Bignon
Venue: Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation (2008)

In the early stage of creation, the architect tests his work hypotheses by making many adjustments while designing. During the sketching phase, the existing modeling tools are not compatible with the iterative nature of this process. So the challenge lies in the definition of a model which will allow the whole creative process with its various trying and going back during the phase of conception. We will illustrate this model by implementing a parametric operator allowing the action of folding. Its parametric specificity will enable the architect, in the design phase, to make the numerous moves and returns required to obtain an optimal shape.