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EBIFRY, a programming language for embedded systems - Combining simplicity with stability

systems and Computers in Japan 2005年第10期36卷 72-81页

作者： Oyama, Hiroshi Ryoki, Masato Matsumoto, Tadahiro Naoi, Tohru Goto, Munehiro FA System Division OkumaCorp Aichi 480-0193 Japan Faculty of Engineering Gifu University Gifu 501-1193 Japan Society of Instrument and Control Engineers of Japan IT Products Department Information Processing Society of Japan Japan Society for Software Science and Technology Department of Engineering and Applied Information Sciences Information Processing Society of Japan Japan Society for Software Science and Technology EATCS Department of Engineering Gifu University Information Processing Society of Japan Japanese Society for Artificial Intelligence IEEE

EBIFRY (a language for EmBedded Instruments in the FactoRY) is a programming language for embedded systems designed with the joint objectives of providing the simplicity of a scripting language while making it possible for programmers of all levels to create stable programs. We believe that the issue of memory management is of significant importance in seeking to achieve these objectives and selected a memory management strategy that can automatically manage dynamically created objects through their lifetimes, while keeping an approach that is fundamentally based on static object creation. In this paper we present the requirements that were designed for the EBIFRY language specifications in order to achieve the above objectives, describe some programs that were actually developed using EBIFRY, and show that the memory management strategy adopted in EBIFRY can be used effectively in practice. © 2005 Wiley Periodicals, Inc.

关键词： Computer programming languages

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Editorial

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International Journal of web Engineering and technology 2005年第2-3期2卷 145-147页

作者： Frasincar, Flavius Houben, Geert-Jan Van Ossenbruggen, Jacco Eindhoven University of Technology PO Box 513 NL-5600 MB Eindhoven Netherlands Centrum voor Wiskunde en Informatica PO Box 94079 NL-1090 GB Amsterdam Netherlands Department of Information Systems Erasmus University Rotterdam Netherlands Department of Information Systems Vrije Universiteit Brussel Belgium WISE Laboratory for Web and Information System Engineering Netherlands Technische Universiteit Eindhoven Netherlands CWI Netherlands Multimedia and Human-computer Interaction Group Netherlands

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Study of classification rules on weighted coronary heart disease data

Study of classification rules on weighted coronary heart dis...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Gang Zheng Ya-Lou Huang Peng-Tao Wang Guang-Fu Shu Department of Computer Science TianJin University of Technology Tianjin China College of Information Technical Science NanKai University Tianjin China College of Computer Software NanKai University Tianjin China System Institute Chinese Academy and Sciences Beijing China

This paper studies the data weighting affection of rules that derived from different decision tree algorithms. The data that we study is collected from patients with coronary heart disease; it has 1723 records and 71 attributes in each record. The weighting methods we used are system reconstruction method and principle component analysis, from which we get two weighted data sets. The analysis based on the weighted data sets and the original not weighted data set. The analysis methods we adapted are some decision tree algorithms; they are C4.5, CART, CHAID and Exhausted CHAID. In the analysis, we compare the quantity and quality of rules which are proved correct by medical specialists and clinical doctors. According to the result from experiments, we know that weighted data sets can improve rule quality, which is better than the result from not weighted data set.

关键词： Cardiac disease Decision trees Reconstruction algorithms Algorithm design and analysis Cardiovascular diseases Educational institutions Medical diagnostic imaging Classification tree analysis Data mining Data analysis

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An architecture design of the intelligent agent for speech recognition and translation

An architecture design of the intelligent agent for speech r...

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IEEE TENCON 2004 - 2004 IEEE Region 10 Conference: Analog and Digital Techniques in Electrical Engineering

作者： Bin Ahmad, Abd. Manan Bin Ag.Nordin, Ag.Noorajis Saaim, Emrul Hamide Md. Bin Samaon, Den Fairol Bin Ibrahim, Mohd Danial Department of Software Engineering Faculty of Computer Science and Information System University of Technology Malaysia

An architecture design of the intelligent agent for speech recognition and translation is presented in this paper. The design involves the agent architecture and the method of the agent is used. The architecture design will show the relationship between the intelligent agent and speech recognition also translation. The intelligent agent for speech recognition is called S - AGENT and T- AGENT for translation. The purpose of the S - AGENT is to facilitate for transmitting the speech data via internet or network. The S - AGENT is acting as a data transmit control to ensure the transmitted speech data will secure delivered The task of the T - AGENT is different from the S - AGENT. The T - AGENT is acting as information retrieval. It will process the output from the speech recognition and translates the output based on its information memory database. If the information cannot be found on its memory, it will search the information required from the database dictionary provided. At the same time, it learns the information and saves the information to its memory for the future purposed © 2004IEEE.

关键词： Speech recognition

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An architecture design of the intelligent agent for speech recognition and translation

An architecture design of the intelligent agent for speech r...

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IEEE Region 10 International Conference TENCON

作者： A.M.B. Ahmad A.N.B.A. Nordin E.H.M. Saaim Den Fairol bin Samaon M.D.B. Ibrahim Speech Recognition Laboratory Department of Software Engineering Faculty of Computer Science and Information System University of Technology Malaysia

An architecture design of the intelligent agent for speech recognition and translation is presented in this paper. The design involves the agent architecture and the method of the agent is used. The architecture design shows the relationship between the intelligent agent and speech recognition also translation. The intelligent agent for speech recognition is called S-AGENT and T-AGENT for translation. The purpose of the S-AGENT is to facilitate for transmitting the speech data via Internet or network. The S-AGENT is acting as a data transmit control to ensure the transmitted speech data is securely delivered. The task of the T-AGENT is different from the S-AGENT. The T-AGENT is acting as information retrieval. It processes the output from the speech recognition and translates the output based on its information memory database. If the information cannot be found on its memory, it searches the information required from the database dictionary provided. At the same time, it learns the information and saves the information to its memory for the future purpose.

关键词： Intelligent agent Speech recognition Computer architecture Speech processing Data mining IP networks Databases Decoding Dictionaries Internet

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Genetic algorithm for edge extraction of glomerulus area

Genetic algorithm for edge extraction of glomerulus area

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International Conference on information and Automation (ICIA)

作者： Jun Zhang Hong Zhu XueMing Qian Tao Huang Institute of Information and Automation Engineering Xi''an University of Technology Xi'an Shaanxi China Department of system integration Shannxi GLNPU Software Company Limited Xi'an Shaanxi China

ISBN: (纸本)0780386299

The automatic analysis of kidney-tissue image is an important subsystem in the computer aided diagnosis system of kidney disease. In this subsystem, the correct extraction of glomerulus is an important premise to the exact analysis of kidney-tissue image. A glomerulus edge extraction method based on genetic algorithm (GA) is proposed by considering complex characteristics of the image. Firstly, different scale binary images are obtained by adjusting the parameters of LOG filter. Secondly, the crude spline curve fitting for the glomerulus area boundary is got by genetic algorithm based on the small-scale binary image. Thirdly, elaborate adjustment of spline fitting curve is performed according to more boundary information of large-scale binary image to get the optimal spline curve. Finally, the glomerulus area can be extracted correctly according to the fitting curve. Experimental result indicates high precision of glomerulus edge extraction from the kidney-tissue image.

关键词： Genetic algorithms Curve fitting Data mining Filters Spline Pathology Image analysis Diseases Biopsy Automation

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A TV program generation system using digest video scenes and a scripting markup language

A TV program generation system using digest video scenes and...

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Annual Hawaii International Conference on system Sciences (HICSS)

作者： Y. Shirota T. Hashimoto A. Nadamoto T. Hattori A. Iizawa K. Tanaka K. Sumiya Software Research Center Imaging System Business Group Ricoh Company Limited Japan Division of Information and Media Science Graduate School of Science and Technology Kobe University Japan Department of Computer and Systems Engineering Graduate School of Science and Technology Kobe University Japan Division of Urban Information Systems Research Center for Urban Safety and Security Kobe University Japan

ISBN: (纸本)0769509819

This paper describes a TV program generation system using digest video scenes that are retrieved from video streams with the program indexes. The key features of the system are: (1) TV programs can be dynamically generated from digest video scenes selected by user preference. (2) Directions can be added using a happiness or sadness level based on the user preferences. (3) Personalized TV programs for an individual viewer can be made. The procedures taken by the system are as follows: (1) Conjunctive expressions between scenes are automatically generated; (2) Emotional expressions are automatically generated by user preference; (3) TV program metaphors are defined; (4) Direction templates corresponding to the metaphors are defined; (5) These expressions and definitions are coded using a markup language, and (6) Contents such as virtual characters and movies are synchronized. The resultant program can be shown on a TV set.

关键词： Layout Markup languages TV broadcasting Satellite broadcasting information retrieval Broadcast technology Digital TV Companies Streaming media Character generation

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Load adjustment and filtering based on process criticality

Load adjustment and filtering based on process criticality

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IEEE International Conference on Embedded and Real-Time Computing systems and Applications (RTCSA)

作者： Tei-Wei Kuo Shie-Kai Ni Giun-Haur Huang Real Time Systems Laboratory Department of Computer Science and Information Engineering National Chung Cheng University Chiayi Taiwan Department of New Technology Development Platform Software Division Acer Incorporated Taipei Taiwan System Software Laboratory Institute for Information Industry Taipei Taiwan

ISBN: (纸本)081869209X

This paper generalizes the load scaling techniques proposed in (Kuo and Mok, 1991) for fixed-priority real-time applications. A framework is proposed to adjust the system workload by relating the criticality and flexibility of a process to the resource allocation problem. A load adjustment procedure based on the approximation algorithm (Ni et al., 1997) is proposed to maximize the system profit in an on-line fashion. When the list of allowable configurations is implicitly given by scalable periodic processes, the corresponding load filtering problem is shown to be NP-complete. We also prove the upper bound of the system profit and provide a mechanism to balance the schedulability and the maximum profit of the system.

关键词： Filtering Resource management Job shop scheduling Timing Real time systems Approximation algorithms Upper bound Laboratories Frequency Computer science

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ROLE OF SIMULATION IN RAPID PROTOTYPING FOR CONCEPT DEVELOPMENT

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NAVAL ENGINEERS JOURNAL 1991年第3期103卷 204-211页

作者： KING, JF BARTON, DE J. Fred King:is the manager of the Advanced Technology Department for Unisys in Reston Virginia. He earned his Ph.D. in mathematics from the University of Houston in 1977. He has been principal investigator of research projects in knowledge engineering pattern recognition and heuristic problem-solving. Efforts include the development of a multi-temporal multispectral classifier for identifying graincrops using LANDSAT satellite imagery data for NASA. Also as a member of the research team for a NCI study with Baylor College of Medicine and NASA he helped develop techniques for detection of carcinoma using multispectral microphotometer scans of lung tissue. He established and became technical director of the AI Laboratory for Ford Aerospace where he developed expert scheduling modeling and knowledge acquisition systems for NASA. Since joining Unisys in 1985 he has led the development of object-oriented programming environments blackboard architectures data fusion techniques using neural networks and intelligent data base systems. Douglas E. Barton:is manager of Logistics Information Systems for Unisys in Reston Virginia. He earned his B.A. degree in computer science from the College of William and Mary in 1978 and did postgraduate work in London as a Drapers Company scholar. Since joining Unisys in 1981 his work has concentrated on program management and software engineering of large scale data base management systems and design and implementation of knowledge-based systems in planning and logistics. As chairman of the Logistics Data Subcommittee of the National Security Industrial Association (NSIA) he led an industry initiative which examined concepts in knowledge-based systems in military logistics. His responsibilities also include evaluation development and tailoring of software engineering standards and procedures for data base and knowledge-based systems. He is currently program manager of the Navigation Information Management System which provides support to the Fleet Ballistic Missile Progr

A valuable technique during concept development is rapid prototyping of software for key design components. This approach is particularly useful when the optimum design approach is not readily apparent or several known alternatives need to be rapidly evaluated. A problem inherent in rapid prototyping is the lack of a "target system" with which to interface. Some alternatives are to develop test driver libraries, integrate the prototype with an existing working simulator, or build one for the specific problem. This paper presents a unique approach to concept development using rapid prototyping for concept development and scenario-based simulation for concept verification. The rapid prototyping environment, derived from artificial intelligence technology, is based on a blackboard architecture. The rapid prototype simulation capability is provided through an object-oriented modeling environment. It is shown how both simulation and blackboard technologies are used collectively to rapidly gain insight into a tenacious problem. A specific example will be discussed where this approach was used to evolve the logic of a mission controller for an autonomous underwater vehicle.

关键词： Military Engineering

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Context-Aware Auto-Encoded Graph Neural Model for Dynamic Question Generation using NLP

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ACM Transactions on Asian and Low-Resource Language information Processing 1000年

作者： Suresh Dara CH. Srinivasulu CH Madhu Babu Ananda Ravuri Tirumala Paruchuri Abhishek Singh Kilak Ankit Vidyarthi Department of Computer Science and Engineering PACE Institute of Technology & Sciences India Department of Computer Science and Engineering Institute of Aeronautical Engineering (IARE). India Department of CSE B V Raju Institute of Technology. India Senior Software Engineer Intel Corporation Hillsboro 97124 USA Department of Management Information System Jazan University Kingdom of Saudi Arabia Department of CSE Engineering College Bikaner India Jaypee Institute of Information Technology Noida Department of CSE&IT India

Question generation is an important task in natural language processing that involves generating questions from a given text. This paper proposes a novel approach for dynamic question generation using a context-aware auto-encoded graph neural model. Our approach involves constructing a graph representation of the input text, where each node in the graph corresponds to a word or phrase in the text, and the edges represent the relationships between them. We then use an auto-encoder model to learn a compressed representation of the graph that captures the most important information in the input text. Finally, we use the compressed graph representation to generate questions by dynamically selecting nodes and edges based on their relevance to the context of the input text. We evaluate our approach on four benchmark datasets (SQuAD, Natural Questions, TriviaQA, and QuAC) and demonstrate that it outperforms existing state-of-the-art methods for dynamic question generation. In the experimentation, to evaluate the result four performance metrics are used i.e. BLEU, ROUGE, F1-Score, and Accuracy. The result of the proposed approach yields an accuracy of 92% on the SQuAD dataset, 89% with QuAC, and 84% with TriviaQA. while on the natural questions dataset, the model gives 79% accuracy. Our results suggest that the use of graph neural networks and auto-encoder models can significantly improve the accuracy and effectiveness of question generation in NLP. Further research in this area can lead to even more sophisticated models that can generate questions that are even more contextually relevant and natural-sounding.

关键词： Natural Language Processing Graph Neural Network Question-answer generation Auto Encoder information Processing

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