ppxscal/embedding_network huggingface dataset:
Extending the MaSE Methodology for the Development of Embedded Real-Time Systems
Authors: Iman Badr, Hisham Mubarak, Peter Göhner
Venue: Languages, Methodologies and Development Tools for Multi-Agent Systems: First International Workshop, LADS 2007, Durham, UK, September 4-6, 2007. Revised Selected Papers (2008)

Embedded real-time systems play an important role in various application areas like plant automation, product automation or car electronics. In recent years, a considerable growth in the functionality has been observed. At the same time, expectations on systems' flexibility at runtime are growing steadily. The agent-oriented software engineering approach is well suited for the development of decentralised, complex software systems with high flexibility. A number of software engineering methodologies have been introduced for developing agent-oriented systems. However, none of the existing methodologies is intended for the development of embedded real-time systems. This work presents concepts that extend the Multi-agent Systems Engineering (MaSE) methodology for the development of agent-oriented embedded real-time systems. The proposed concepts have been integrated in the traditional engineering process of MasE and evaluated by applying the extended process to the development of a flexible agent-oriented embedded system for the control of an elevator model.
Asp.net 2.0 all-in-one desk reference for dummies®
Authors: Doug Lowe, Jeff Cogswell, Ken Cox
Venue:  (2006)

Eight minibooks cover ASP.NET basics, Web controls, using HTML and ASP, C#, Visual Basic, database programming, using the .NET Framework, and advanced ASP.NET 2 (including themes, custom server controls, and Web parts) The ideal resource for Web programming newcomers as well as the 1.5 million existing ASP developers who want a complete ready-reference that covers the new ASP.NET 2 updates More than double the size of ASP.NET 2 For Dummies (0-7645-7907-X), the latest edition of the bestselling ASP beginner book that boasts combined sales of more than 100,000 copies across all editions Written by veteran Dummies author Doug Lowe, who is renowned for his ability to explain complex topics in plain English
A decoupled federate architecture for high level architecture-based distributed simulation
Authors: Dan Chen, Stephen John Turner, Wentong Cai, Muzhou Xiong
Venue: Journal of Parallel and Distributed Computing (2008)

A number of research issues arise in executing large scale High Level Architecture (HLA) based distributed simulations. Among these issues distributed simulation cloning, fault tolerance and Grid enabled architecture are particularly important and challenging. This paper presents a Decoupled Federate Architecture as the underlying infrastructure to facilitate a solution to each of the above issues. Distributed simulation cloning has been designed to improve the performance of ''what-if'' analysis, by enabling the examination of alternative scenarios concurrently within the same execution session. Furthermore, simulation federates running at different locations are liable to failure. Such risk increases with the scale of a distributed simulation. The architecture has also been exploited to form the basis of a generic framework to support runtime robustness. The development of complex simulation applications often requires geographically distributed huge computing resources and data sets. Using the architecture, Web and Grid technologies have been successfully combined with existing simulation technologies thus to enhance interoperability and execution flexibility for such simulations. Benchmark experiments have been performed to study the extra overhead incurred by the Decoupled Federate Architecture against a normal federate. Encouraging experimental results indicate that a well designed architecture can achieve performance close to the normal one in terms of latency and time synchronization. Additional experiments have been presented for evaluating the three solutions supported by the architecture.
Polynomial-TimeMaximisation Classes: Syntactic Hierarchy
Authors: Orestes Bueno, Prabhu Manyem
Venue: Fundamenta Informaticae (2008)

In Descriptive Complexity, there is a vast amount of literature on decision problems, and their classes such as P, NP, L and NL. However, research on the descriptive complexity of optimisation problems has been limited. In a previous paper [13], we characterised the optimisation versions of P via expressions in second order logic, using universal Horn formulae with successor relations. In this paper, we study the syntactic hierarchy within the class of polynomially bound maximisation problems. We extend the result in the previous paper by showing that the class of polynomially-boundNP (not just P) maximisation problems can be expressed in second-order logic using Horn formulae with successor relations. Finally, we provide an application - we show that the Bin Packing problem with online LIB constraints can be approximated to within a &Theta; (log n) bound, by providing a syntactic characterisation for this problem.
Watershed Segmentation Via Case-Based Reasoning
Authors: Maria Frucci, Petra Perner, Gabriella Sanniti Di Baja
Venue: Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2007)

This paper proposes a novel grey-level image segmentation scheme employing case-based reasoning. Segmentation is accomplished by using the watershed transformation, which provides a partition of the image into regions whose contours closely fit those perceived by human users. Case-based reasoning is used to select the segmentation parameters involved in the segmentation algorithm by taking into account the features characterizing the current image. We describe the different processing steps involved in a CBR-based image segmentation scheme. The segmentation parameters of the Watershed segmentation that can be controlled are explained. One possible case description based on statistical low-level features is given as well as the similarity measure. The performance of the chosen case description and the similarity measure for retrieval is assessed based on hierarchical clustering. Finally, we propose a method for the automatic evaluation of the segmentation results that will allow us to automatically select the best segmentation parameters and, thus, making the whole segmentation scheme to a closed-loop image-segmentation control scheme.
EZ-Entry: A clinical data management system
Authors: Qing-Bin Gao, Yu Kong, Zheng Fu, Jian Lu, Cheng Wu, Zhi-Chao Jin, Jia He
Venue: Computers in Biology and Medicine (2008)

In this paper, a new data management system named EZ-Entry is introduced. Five major functions are enclosed in this system: (1) user authentication; (2) database construction; (3) double data entry with instant alignment; (4) revision tracking; (5) query management. The practical application performed on two clinical trials indicates that EZ-Entry meets the requirements of clinical data management with high efficiency and security. This software is freely available on request from the authors for academic purposes.
Image Texture Classification Using Combined Grey Level Co-Occurrence Probabilities and Support Vector Machines
Authors: Hee-Kooi Khoo, Hong-Choon Ong, Ya-Ping Wong
Venue: Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation (2008)

Texture refers to properties that represent the surface or structure of an object and is defined as something consisting of mutually related elements. The main focus in this study is to do texture segmentation and classification for texture digital images. Grey Level Co-occurrence Probabilities (GLCP) method is being used to extract features from texture image. Gaussian Support Vector Machines (GSVM) have been proposed to do classification on the extracted features. A popular Brodatz texture album had been chosen to test out the result. In this study, a combined GLCP-GSVM shows an improvement over GLCP in terms of classification accuracy.
A Multi-measure Nearest Neighbor Algorithm for Time Series Classification
Authors: Fábio Fabris, Idilio Drago, Flávio M. Varejão
Venue: Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence (2008)

In this paper, we have evaluated some techniques for the time series classification problem. Many distance measures have been proposed as an alternative to the Euclidean Distance in the Nearest Neighbor Classifier. To verify the assumption that the combination of various similarity measures may produce a more accurate classifier, we have proposed an algorithm to combine several measures based on weights. We have carried out a set of experiments to verify the hypothesis that the new algorithm is better than the classical ones. Our results show an improvement over the well-established Nearest-Neighbor with DTW (Dynamic Time Warping), but in general, they were obtained combining few measures in each problem used in the experimental evaluation.
Diagnosis of Turbine Valves in the Kori Nuclear Power Plant Using Fuzzy Logic and Neural Networks
Authors: Hyeon Bae, Yountae Kim, Gyeongdong Baek, Byung-Wook Jung, Sungshin Kim, Jung-Pil Shin
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

This manuscript introduces a fault diagnosis system for a turbine-governor system that is an important control system in a nuclear power plant. Because the turbine governor system is operated by high oil pressure, it is very difficult to maintain the operating condition properly. The turbine valves in the turbine governor system supply an oil pressure for operation. Using the pressure change data of the turbine valves, the condition of the turbine governor control system is evaluated. This study uses fuzzy logic and neural networks to evaluate the performance of the turbine governor. The pressure data of the turbine governor and stop valves is used in the turbine governor diagnosis algorithms. The features of the pressure signals are defined to be applied in the fuzzy diagnosis system. And Fourier transformed signals of the pressure signals are used in the neural network models for diagnosis. The diagnosis results both by fuzzy logic and neural networks are compared to evaluated the performance of the designed system.
Golden Quadruplet: Optimization - Inequality - Identity - Operator
Authors: Seiichi Iwamoto
Venue: Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence (2007)

The Golden ratio is one of the most beloved numbers in human society. It is a symobol of combination of beauty and practical use. We consider the Golden ratio through four models --(i) optimization, (ii) inequality, (iii) identity and (iv) opertator --. We introduce the Golden matrices whose characteristic values are the Golden number and its conjugate. We show that the Golden matrices take an important role in the four models. Further the role is essentially equivalent.
Improving the Effectiveness of Combinational Decompressors Through Judicious Partitioning of Scan Cells
Authors: Ozgur Sinanoglu
Venue: Journal of Electronic Testing: Theory and Applications (2008)

While integrated circuits of ever increasing size and complexity necessitate larger test sets for ensuring high test quality, the consequent test time and data volume reflect into elevated test costs. Test data compression solutions have been proposed to address this problem by storing and delivering stimuli in a compressed format. The effectiveness of these techniques, however, strongly relies on the distribution of the specified bits of test vectors. In this paper, we propose a scan cell partitioning technique so as to ensure that specified bits are uniformly distributed across the scan slices, especially for the test vectors with higher density of specified bits. The proposed scan cell partitioning process is driven by an integer linear programming (ILP) formulation, wherein it is also possible to account for the layout and routing constraints. While the proposed technique can be applied to increase the effectiveness of any combinational decompression architecture, in this paper, we present its application in conjunction with a fan-out based decompression architecture. The experimental results also confirm the compression enhancement of the proposed methodology.
Using Alpha-Beta Associative Memories to Learn and Recall RGB Images
Authors: Cornelio Yáñez-Márquez, María Elena Cruz-Meza, Flavio Arturo Sánchez-Garfias, Itzamá López-Yáñez
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

In this paper, an algorithm which enables Alpha-Beta associative memories to learn and recall color images is presented. The latter is done even though these memories were originally designed by Yáñez-Márquez [1] to work only with binary patterns. Also, an experimental study on the proposed algorithm is presented, showing the efficiency of the new memories.
A Knowledge Processing Neural Network Based on Automatic Concept Hierarchization
Authors: Masahiro Saito, Masafumi Hagiwara
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

In this paper, we propose a knowledge processing neural network which is capable of inductive and deductive inference. The proposed network looks up relations between words in a concept dictionary and co-occurrence dictionary. First, the proposed network divides sentences into the subject words and the other words. Then these words are input into two-layer network. Second, hierarchical structure is composed using concept dictionary. Third, the network induces general knowledge from individual knowledge. We added a function to respond to questions in natural language with "Yes/No/I don't know" in order to confirm the validity of proposed network by evaluating the quantity of correct answers.
Analysis of Variability of Human Reaching Movements Based on the Similarity Preservation of Arm Trajectories
Authors: Takashi Oyama, Yoji Uno, Shigeyuki Hosoe
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

Human movements exhibit some variability. Based on the assumption that the main factor of movement variability is noise adding to motion commands in motion execution, it can be considered that a planned trajectory is the same during the same task. However, the human might not be able to plan the same trajectory during the same task because of some factors (e.g., the uncertainty of target location perception). We analyzed the similarity preservation of trajectories in reaching movements. The similarity preservation of trajectories cannot be reproduced by random noise in motion execution. We argue that the movement variability breaks out in motion planning.
The Tron Project
Authors: Ken Sakamura
Venue: IEEE Micro (1987)

TRON designates a family of architectures, operating system kernels, and VLSI CPU chips. It is an open specification, intended to foster the development of compatible products by many vendors.
A Novel Approach to Optimize Information Dissemination in IMS Presence System
Authors: Rongheng Lin, Hua Zou, Yao Zhao, Fangchun Yang
Venue: Proceedings of the 8th international conference, NEW2AN and 1st Russian Conference on Smart Spaces, ruSMART on Next Generation Teletraffic and Wired/Wireless Advanced Networking (2008)

Presence is an important service in IMS. The user in IMS would use presence as a necessary component. But the more user uses, the harder presence information transmits. Previous researches show that the traffic increases rapidly with the presentity number grows. In this paper, we propose an approach to optimize information dissemination in IMS Presence System. Comparing with previous researches, a new architecture is set up. In this architecture, presence information transmission is modeled as a growing tree. A k sequence method is proposed to construct the tree. And some key algorithms are introduced for the tree adjustment. With a mathematical analysis, the new method is more suitable for presence information dissemination. And in the experiment, the result shows that the method can do a better job with smaller traffic and jitter.
Label Ranking in Case-Based Reasoning
Authors: Klaus Brinker, Eyke Hüllermeier
Venue: Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2007)

The problem of label ranking has recently been introduced as an extension of conventional classification in the field of machine learning. In this paper, we argue that label ranking is an amenable task from a CBR point of view and, in particular, is more amenable to supporting case-based problem solving than standard classification. Moreover, by developing a case-based approach to label ranking, we will show that, the other way round, concepts and techniques from CBR are also useful for label ranking. In addition to an experimental study in which case-based label ranking is compared to conventional nearest neighbor classification, we present an application in which label ranking is used for node ordering in heuristic search.
Analysis of 90/150 Two Predecessor Nongroup Cellular Automata
Authors: Sung-Jin Cho, Un-Sook Choi, Han-Doo Kim, Yoon-Hee Hwang, Jin-Gyoung Kim
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

Many researchers have been studied synthesis method of 90/150 group CA. However, there is a lack of researches for synthesis method of 90/150 nongroup CA. In this paper we propose an algorithm for finding 90/150 Two Predecessor Cellular Automata. Using the proposed algorithm we analyze 90/150 two predecessor CA. Especially, we analyze 90/150 TPSACA and TPMACA which are useful to study hashing. Also we analyze two types of 90/150 two predecessor CA. One is two predecessor CA for the minimal polynomial whose type is of the form x p(x) which is useful to study two predecessor CA whose depth is 1. Another is two predecessor CA for the minimal polynomial whose type is of the form x(x + 1) p(x) which is useful to study pseudorandom number generation based on 90/150 two predecessor CA, where p(x) is some primitive polynomial.
Measuring and modeling the internet: topology, routing and their interplay
Authors: Michalis Faloutsos
Venue:  (2007)

With the size of the Internet growing exponentially, Internet topology and Internet routing behavior become more and more important in designing, simulating and deploying new routing protocols to accommodate new demands and to provide new functionalities. However, there are still three fundamental open questions. First, how do we quantitatively measure the Internet routing behavior? Second, how do we accurately measure and model the Internet topology? Third, how do we utilize the measured topology to facilitate designing and simulating a new routing protocol? In this dissertation, we attempt to address these three questions. In particular, we first study the routing asymmetry in the Internet. We design a quantitative framework to measure the extent of routing asymmetry at both link level and Autonomous System level, and discover that general commercial networks are more asymmetric than the US higher education network. Second, we examine the Autonomous System level Internet topology discovery methods. By cross-validating and comparing a number of large-scale sources of information, we identified 300% more peer-to-peer AS links compared to the commonly used data set. Furthermore, we discovered that most of the missing links are at the less-studies Internet Exchange Points. Given the new peer-to-peer edges, we find that for some ASes, more than 50% of their paths stop going through their ISP providers assuming policy-aware routing. Third, we study how to simulate Internet routing more accurately and efficiently with measured topology. We propose HBR, a network sampling method which respects the hierarchical structure of the Internet, to provide a way to conduct Internet routing simulations in a realistic and policy-aware topology much faster than in the original Internet topology. Our results show that the HBR approach can reduce the complexity of BGP simulations by several orders of magnitude, and at the same time, provide reasonable realistic result as compared to a real topology. Our approach provides a permanent solution to the difficult problem of AS-level routing evaluations: it can always be used to generate small realistic topologies in the future, producing ever newer or more complete Internet instances.
Tree Projections: Hypergraph Games and Minimality
Authors: Gianluigi Greco, Francesco Scarcello
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

A hypergraph-game characterization is provided for hypergraph tree projections (TPs) and, hence, for the special cases of generalized and fractional hypertree decompositions, where such a characterization was missing and asked for. In this game, as for the Robber and Cops game characterizing tree decompositions, the existence of winning strategies implies the existence of monotone ones, which are yet somehow preferable, because they correspond to minimal tree projections. In fact, it is shown that minimal TPs enjoy a number of nice properties, such as the same kind of connection property as (minimal) tree decompositions of graphs. Finally, it is shown that this property is somehow tight, by giving a negative answer to an open question about a slightly stronger notion of connection property, defined to speed-up the computation of hypertree decompositions.
Molecular polarizability of Si/Ge/GaAs semiconductors clusters
Authors: Francisco Torrens
Venue: Journal of Computational Methods in Sciences and Engineering (2004)

The interacting induced dipole polarization model implemented in our program for the calculation of molecular polarizabilities (POLAR) is used for the calculation of the molecular dipole-dipole polarizability ${\overline{\overline{&alpha;}}}$. POLAR is tested with Si$_{n}$, Ge$_{n}$ and Ga$_{n}$As$_{m}$ small clusters. The polarizability is an important quantity for the identification of clusters with different numbers of atoms and even for the separation of isomers. The results for the polarizability are in agreement with reference calculations performed with our version of the program PAPID (polarisabilit&eacute;s atomiques par interactions dipolaires) and with reference computations from Dr. J.R. Chelikowsky. The bulk limit for the polarizability is estimated from the Clausius-Mossotti relationship. The polarizability trend for the clusters as a function of size is different from what one might have expected. The clusters are more polarizable than what one might have inferred from the bulk polarizability. Previous experimental work yielded the opposite trend for somewhat larger clusters. At present, the origin of this difference is problematic. One might argue that smaller clusters need not behave like those of intermediate size. The high polarizability of small clusters is attributed to dangling bonds at the surface of the cluster. Indeed, most of the atoms within small clusters reside on the surface. In this respect, semiconductor clusters resemble metallic clusters.