ppxscal/embedding_network huggingface dataset:
Embedded systems programming: accessing databases from Esterel
Authors: David White, Gerald Lüttgen
Venue: EURASIP Journal on Embedded Systems (2008)

A current limitation in embedded controller design and programming is the lack of database support in development tools such as Esterel Studio. This article proposes a way of integrating databases and Esterel by providing two application programming interfaces (APIs) which enable the use of relational databases inside Esterel programs. As databases and Esterel programs are often executed on different machines, result sets returned as responses to database queries may be processed either locally and according to Esterel's synchrony hypothesis, or remotely along several of Esterel's execution cycles. These different scenarios are reflected in the design and usage rules of the two APIs presented in this article, which rely on Esterel's facilities for extending the language by external data types, external functions, and procedures, as well as tasks. The APIs' utility is demonstrated by means of a case study modelling an automated warehouse storage system, which is constructed using Lego Mindstorms robotics kits. The robot's controller is programmed in Esterel in a way that takes dynamic ordering information and the warehouse's floor layout into account, both of which are stored in a MySQL database.
Using Artificial Intelligence for Intrusion Detection
Authors: François Gagnon, Babak Esfandiari
Venue: Proceeding of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies (2007)

Artificial intelligence is playing an increasingly important role in network management. In particular, research in the area of intrusion detection relies extensively on AI techniques to design, implement, and enhance security monitoring systems. This chapter discusses ways in which intrusion detection uses or could use AI. Some general ideas are presented and some actual systems are discussed. The focus is mainly on knowledge representation, machine learning, and multi-agent architectures.
Adaptive Neural-Based Fuzzy Inference System Approach Applied to Steering Control
Authors: Wang Minghui, Yu Yongquan, Lin Wei
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

We applied adaptive neural-based fuzzy inference system (ANFIS) approach to the process control of ship automation manipulating systems. This paper studied the design of ANFIS controller for ship steering control system. Using BP algorithm to the learning of premise parameters, while least square algorithm to the learning of consequent parameters, we applied ANFIS approach to ship autopilot. To perform the ship task of steering a ship effectively, a ship autopilot system based on ANFIS approach is designed for various outer surroundings at sea in performing course keeping, course-changing more robustly. The simulating results by Matlab indicate that the performance of ANFIS controller is valuable and easy to implement.
Quick parser development using modified compilers and generated syntax rules
Authors: Kazuaki Maeda
Venue: Proceedings of the international conference on Computational and information science 2009 (2009)

This paper describes some ideas about quick parser development from source code of popular free and libre open source (called FLOSS) compilers using modified parser generator. Parser development is time-consuming and laborious according to traditional approaches. In this paper's approach, a specialized scanner is built using FLOSS compilers. The scanner reads source code, analyzes it, and writes a sequence of tokens in XML. The parser generator is modified so that it generates a specialized parser and syntax rules with code to read the tokens in XML for quick parser development. In the author's experiences, it takes within one hour to implement a simple recognizer which reads C# source code, writes a sequence of tokens in XML and analyzes it.
The XMediaBox: Sensemaking through the Use of Knowledge Lenses
Authors: Aba-Sah Dadzie, José Iria, Daniela Petrelli, Lei Xia
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

Sensemaking is the process of analysing complex situations in order to make informed decisions. Semantic Web technology can be effectively used to create new sensemaking systems that focus on concepts and knowledge instead of documents. We demonstrate how this is achieved using information extraction to acquire knowledge and create a semantic repository that can then be semantically searched. A domain ontology is used to support the creation of an analysis tree; the semantic visualisation enables knowledge discovery, a core aspect of sensemaking.
The role of collective efficacy and collaborative learning behavior in learning computer science through CSCL
Authors: Shu-Ling Wang, Gwo-Haur Hwang, Ju-Chun Chu, Pei-Shan Tsai
Venue: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education (2009)

This study attempted to explore the role of group motivation (i.e. collective efficacy) and collaborative learning behavior (i.e. group cohesion; group cognitive involvement) in students' group performance in learning computer science in computer-supported collaborative learning environment. 96 Taiwanese college students (32 groups) enrolled in the course "Web Page Programming" participated in the study. The students discussed and processed their group projects using "Intelligent Collaborative Learning System". The results indicated that collective efficacy predict group cohesion significantly in CSCL. In addition, collective efficacy also showed to predict group performance in programming significantly. Moreover, the results also indicated that both group cohesion and groups with higher cognitive involvement in their discussion leaded to better group performance. In summary, this study validated the social cognitive model in learning computer science in CSCL, that is, groups with higher collective efficacy had stronger group cohesion and better performance in learning Web Page programming. Groups with higher cognitive involvement and group cohesion also leaded to better group performance.
EEAODR: An energy-efficient ad hoc on-demand routing protocol for mobile ad hoc networks
Authors: Sanjay Kumar Dhurandher, Sudip Misra, Mohammad S. Obaidat, Vikrant Bansal, Prithvi Raj Singh, Vikas Punia
Venue: International Journal of Communication Systems (2009)

Mobile ad hoc networks (MANETs) are characterized by random, multi-hop topologies that do not have a centralized coordinating entity or a fixed infrastructure that may change rapidly over time. In addition, mobile nodes operate with portable and finite power sources. In this work, we propose an energy-efficient routing protocol for MANETs to minimize energy consumption and increase the network's consistency. Traditional works mainly focused on the shortest path-based schemes to minimize energy, which might result into network failure because some nodes might exhaust fast as they are used repetitively, while some other nodes might not be used at all. This can lead to energy imbalance and to network life reduction. We propose an energy-efficient ad hoc on-demand routing protocol that balances energy load among nodes so that a minimum energy level is maintained among nodes and the network life increases. We focused on increasing the network longevity by distributing energy consumption in the network. We also compared the simulation results with a popular existing on-demand routing protocol in this area, AODV, to establish the superiority of our approach. Copyright &copy; 2009 John Wiley & Sons, Ltd. A preliminary version of this work appeared in the proceedings of the 15th IEEE International Conference on Electronics, Circuits and Systems (IEEE ICECS 2008), St. Julians, Malta, 31 August&ndash;3 September 2008.
Transforming a Non-Software Company to a Software Company by Exploiting the LYEE Methodology
Authors: Rikio Maruta, Noriko Taniguchi
Venue: Proceeding of the 2006 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the fifth SoMeT_06 (2006)

With the expectations that the LYEE (governmentaL methodologY for softwarE providencE [1]) methodology may enable to develop software systems without any detailed coding knowledge and to shorten the development time as well, it was considered that the methodology may suit for fostering system architects by going through several repetitions of actual systems development in a much shorter time than having trainees gone through conventional on-the-job-training approaches. Receiving a LyeeAll2 training first time, the LYEE methodology was successfully implanted in the authors' company. Capabilities of using LyeeAll3, the next generation tool, were then readily obtained. Through the development of a couple of actual systems, the initial expectations were confirmed and the methodology seems to be useful for developing system architects from engineers with non-software background.
Comparison between computed shearing forces by AASHTO specifications and finite element method of two continuous spans of voided slab bridge
Authors: Maher Qaqish, Emad Akawwi, Eyad Fadda, Maher Qaqish
Venue: WSEAS Transactions on Information Science and Applications (2009)

Voided slab bridge deck composed of two continuous span is 17.3m Long and 16m width with all over depth of 0.9m. The voided slab is composed of 20cm top and bottom slabs with circular voided areas of 50cm in diameter and center to center of these circles of 75cm. The locations of AASHTO loadings are positioned at certain points of deck slab to give maximum positive and negative shearings. These locations are determined from one dimensional model. The analysis of the bridge deck is carried out by two approaches. The first is AASHTO specifications where one dimensional approach is adopted and the second is three dimensional approach where finite element analysis is considered. The maximum shears obtained by both methods are found to be in good agreement with negligible differences.
A repository of free lexical resources for African languages: the project and the method
Authors: Piotr Bański, Beata Wójtowicz
Venue: Proceedings of the First Workshop on Language Technologies for African Languages (2009)

We report on a project which we believe to have the potential to become home to, among others, bilingual dictionaries for African languages. Kept in a well-structured XML format with several possible degrees of conformance, the dictionaries will be able to get usable even in their early versions, which will be then subject to supervised improvement as user feedback accumulates. The project is FreeDict, part of SourceForge, a well-known Internet repository of open source content. We demonstrate a possible process of dictionary development on the example of one of FreeDict dictionaries, a Swahili-English dictionary that we maintain and have been developing through subsequent stages of increasing complexity and machine-processability. The aim of the paper is to show that even a small bilingual lexical resource can be submitted to this project and gradually developed into a machine-processable form that can then interact with other FreeDict resources. We also present the immediate benefits of locating bilingual African dictionaries in this project. We have found FreeDict to be a very promising project with a lot of potential, and the present paper is meant to spread the news about it, in the hope to create an active community of linguists and lexicographers of various backgrounds, where common research subprojects can be fruitfully carried out.
Selective negative correlation learning approach to incremental learning
Authors: Ke Tang, Minlong Lin, Fernanda L. Minku, Xin Yao
Venue: Neurocomputing (2009)

Negative correlation learning (NCL) is a successful approach to constructing neural network ensembles. In batch learning mode, NCL outperforms many other ensemble learning approaches. Recently, NCL has also shown to be a potentially powerful approach to incremental learning, while the advantages of NCL have not yet been fully exploited. In this paper, we propose a selective NCL (SNCL) algorithm for incremental learning. Concretely, every time a new training data set is presented, the previously trained neural network ensemble is cloned. Then the cloned ensemble is trained on the new data set. After that, the new ensemble is combined with the previous ensemble and a selection process is applied to prune the whole ensemble to a fixed size. This paper is an extended version of our preliminary paper on SNCL. Compared to the previous work, this paper presents a deeper investigation into SNCL, considering different objective functions for the selection process and comparing SNCL to other NCL-based incremental learning algorithms on two more real world bioinformatics data sets. Experimental results demonstrate the advantage of SNCL. Further, comparisons between SNCL and other existing incremental learning algorithms, such Learn++ and ARTMAP, are also presented.
Triple positive solutions to third order three-point BVP with increasing homeomorphism and positive homomorphism
Authors: Yuming Wei
Venue: Journal of Computational and Applied Mathematics (2009)

In this paper, we investigate the existence of triple positive solutions for nonlinear differential equations boundary value problems with increasing homeomorphism and positive homomorphism operator. By using fixed point theorems in cones, we establish results on the existence of three positive solutions with suitable growth conditions imposed on the nonlinear term. As applications, two examples are given to demonstrate our result. The conclusions in this paper essentially extend and improve the known results.
Package hermeticity testing with thermal transient measurements
Authors: Andr&#x00e1;s Vass-V&#x00e1;rnai, M&#x00e1;rta Rencz
Venue: Microsystem Technologies (2009)

Thermal transient testing, a well known technique for thermal characterization of IC packages (Rencz and Sz&#x00e9;kely 2001) can be a suitable method for detecting hermeticity failures in packaged semiconductor and MEMS devices. In the paper this measuring technique is evaluated. Experiments were done on different measurement setups at different ambient temperature and RH levels. Based on the results, a new method for package hermeticity testing is proposed.
A Scene Graph-Oriented Particle System for Real-Time 3D Graphics
Authors: Jakub Grudziński
Venue: Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers (2008)

The paper presents a novel approach to particle systems dedicated to the use in real-time 3D graphics. A new particle system architecture is presented, with hierarchical structure of objects, implementing a scene graph- specific interfaces which automatically incorporate them into the main graph of the whole interactive scene. With the uniform parameter passing scheme, the objects can be easily edited in a way similar to any other objects (like models, lights, sounds etc.), even during the simulation, with an instant visual effect. A complex hierarchy of objects grants a unique flexibility and extensibility; either by parameterization of existing objects in an editor or by implementing additional task-specific objects, which are automatically incorporated into the whole hierarchy, any specific behaviour of particles may be achieved, which greatly increases the level of visual attractiveness of generated effects.
Geometric computation based assembly sequencing and evaluating in terms of assembly angle, direction, reorientation, and stability
Authors: Qiang Su, Sheng-jie Lai, Jun Liu
Venue: Computer-Aided Design (2009)

Assembly sequence matters much to the performance in assembly production. Focusing on the spatial assembly sequencing and evaluating, a set of geometric computation methods and algorithms are studied systematically. A method entitled 3D geometric constraint analysis (3D-GCA) is proposed based on the planar GCA method combined with the techniques of oriental bounding boxes and the separation axis theorem. With 3D-GCA, the assembly precedence relations and the spatial geometric feasible assembly sequences can be reasoned out correctly and automatically. Furthermore, four evaluation criteria, viz. assembly angle, assembly direction, reorientation, and stability, and related algorithms are defined for evaluating the assembly's complexity. For selecting the optimal sequence, a comprehensive evaluation function is constructed by integrating the four criteria and the weights are quantitatively allocated referring to fuzzy set theory, clustering analysis, and entropy theory. In addition, a software prototype system is developed and two case assemblies are studied. The analysis results and findings demonstrate that the proposed approaches and algorithms can provide significant assistance in the spatial assembly sequencing and the optimal sequence selection.
Hierarchical object oriented land cover classification method using SPOT 5 imagery in waste dump opencast coalmine area
Authors: Wei Su, Chao Zhang, Xiang Zhu, Daoliang Li
Venue: Proceedings of the 13th WSEAS international conference on Applied mathematics (2008)

Land cover classification with a high accuracy in waste dump area is very important to ecoenvironment research, vegetation condition study and soil recovery destination. Funded by the international cooperation project Novel Indicator Technologies for Minesite Rehabilitation and sustainable development, a hierarchical object oriented land cover classification is produced in this study. There are two steps: image segmentation and classification. First, the image is segmented using chessboard segmentation and multiresolution segmentation method. Second, NDVI is used to distinguish vegetation and non-vegetation. Accuracy assessment indicate that this hierarchical method can be used to do land cover classification in waste dump area, the total accuracy increases to 86.53%, and Kappa coefficient increases to 0.7907.
Plenary lecture 4: some interesting aspects of elementary distributions with applications in control algorithms design
Authors: Emil Pop, Monica Leba
Venue: Proceedings of the 8th Wseas international conference on Telecommunications and informatics (2009)

This paper presents interesting aspects of classical distributions theory and the elementary distributions, insisting on practical applications in software control of power electronics and digital control engineering. The practical real world phenomena have discontinuities, severe nonlinearities and non-derivation points and therefore cannot be represented as mathematical closed formula. In order to solve this problem using classical mathematics the discontinuous or nonlinear regions are represented using partitioning method in order to eliminate the discontinuities. But this way we eliminate also the use of derivation operator and this is a great disadvantage, because the discontinuity points represent the points where the system is actually working. The distributions theory was years ago only a mathematical theory, never used in practical applications, but the distributions theory with its remarkable properties represents a link between the continuous systems with their vast experience and the digital systems. The development of information technology and control engineering demands the use of distributions theory in order to elaborate the mathematical model. First, the paper presents the definition of elementary distributions and their properties, validated by modeling and simulation. Then, based on the elementary distributions, new properties are introduced, modeled and simulated with digital application examples. The final part of the paper presents complex control engineering applications, like: software oriented digital controllers for power electronics and industrial elevator software controller. All of these controllers algorithms based on distributions theory can be easily coded in any programming language, like microcontrollers, microprocessors or ASIC - HDL embedded solution.
Monitoring security events using integrated correlation-based techniques
Authors: Qishi Wu, Denise Ferebee, Yunyue Lin, Dipankar Dasgupta
Venue: Proceedings of the 5th Annual Workshop on Cyber Security and Information Intelligence Research: Cyber Security and Information Intelligence Challenges and Strategies (2009)

We propose an adaptive cyber security monitoring system that integrates a number of component techniques to collect time-series situation information, perform intrusion detection, and characterize and identify security events so corresponding defense actions can be taken in a timely and effective manner. We employ a decision fusion algorithm with analytically proven performance guarantee for intrusion detection based on local votes from distributed sensors. The security events in the proposed system are represented as forms of correlation networks using random matrix theory and identified through the computation of network similarity measurement. Extensive simulation results on event identification illustrate the efficacy of the proposed system.