ppxscal/embedding_network huggingface dataset:
Real World Adobe Photoshop CS3, 1st edition
Authors: David Blatner, Conrad Chavez, Bruce Fraser
Venue:  (2007)

Anyone who relies on Photoshop to meet tough production challenges knows that when a new version arrives, especially one as chockfull of enhancements as Photoshop CS3, there's no time to fool around. You need to get up to speed on it, and you need to do so now. This book will get you there. In this copiously illustrated book, best-selling author David Blatner offers shows you how to sharpen your Photoshop production techniques and provides clear explanations of the concepts that drive them. Readers will learn about managing color, correcting colors, capturing images, getting great scans, and more. They'll also find complete coverage of Photoshop CS3's new features: a streamlined interface, nondestructive Smart Filters, a new Quick Selection and Refine Edge tools, improved Curves, automatic layer alignment and blending, and more. Throughout, the emphasis in this book is on efficiency: the timesaving tips and professional shortcuts that will allow readers to solve their everyday production challenges creatively with Photoshop CS3.
Enhancing reliability of sensor networks by fine tuning their event observation behavior
Authors: Steffen Ortmann, Peter Langendoerfer
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

Sensor Networks are envisioned to be used in large variety of applications - health care, homeland security etc. - which require high reliability. Due to the fact that the sensors need to be low cost they have only scarce resources leading to a certain level of failures of sensor nodes or sensing devices attached to the nodes. For the applications mentioned reliable and fault tolerant sensor networks are in great demand. Available fault tolerant solutions are mainly customized approaches that revealed several shortcomings. We present an event specification language that allows configuring the level of reliability of a certain sensor network. It explicitly regards heterogeneous sensing capabilities and allows defining complex events as well as tailor made voting schemes. Features for multi-event detection facets and for fine-grained event-related fault tolerance are also part of the language. Our approach significantly enhances service and maintenance features and enables online configuration of sensor networks.
A manufacturing technology machine for blind people
Authors: Kuang-Yao Lin, Tseng-Lin Hsieh, Jia-Hau Chen, Hen-Chia Hsu, Feng-Jih Wu, Shieh-Shing Lin
Venue: Proceedings of the 9th WSEAS international conference on Robotics, control and manufacturing technology (2009)

In this paper, the authors present a noble heuristic reading machine for blind people. The goal of this paper is to use intelligent-control method to settle down the reading machine by a touch-pat device for blind people. The proposed "A heuristic reading machine" can efficiently help blind people for reading and train the blind people learning the dot-touched words as well. Numerous simulations results demonstrate the proposed design is efficient and can effectively prompt learning and reading effects for blind people.
Process Automation Handbook: A Guide to Theory and Practice, 1st edition
Authors: Jonathan Love
Venue:  (2007)

To be effective as an engineer practicing in the field of process automation requires a breadth of knowledge across a wide range of disciplines: chemical engineering, instrumentation, electrical engineering, control theory, mathematics, computing and management. Previously published books exist in these areas but most are generic and, of those that are applied in nature, few are oriented towards the actual needs of the chemical and process industry. It is impractical for engineers and unreasonable for students to have to cope with this spectrum of material and lack of emphasis. The objective of Process Automation Handbook has been to distil into a single coherent handbook all the essentials of process automation at a depth sufficient for most practical purposes. The handbook focuses on the knowledge needed to cope with the vast majority of process control and automation situations. In doing so, a number of sensible balances have been carefully struck between breadth and depth, theory and practice, classical and modern, technology and technique, information and understanding. A thorough grounding is provided for every topic. If more detailed information is required, the reader is referred to more specialised texts in the knowledge that he or she has been provided with a sound platform to ask the right questions and understand the answers. Process Automation Handbook will be of value to any engineer actively concerned with process control and automation in the chemical and process industries and final-year undergraduate and postgraduate students studying process control. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Multi-objective control and clustering synchronization in chaotic connected complex networks
Authors: Jin-Qing Fang, Xin-Biao Lu
Venue: Proceedings of the 2nd WSEAS international conference on Multivariate analysis and its application in science and engineering (2009)

The conventional chaos control is only to reach single control objective at each time. Different control objective only can be realized at another time. Obviously, that is not enough for applications of chaos control, especially for chaotic connected complex networks. Therefore multi-objective control (MOC) and cluster synchronization are naturally raised and deeded in practice, as well as some methods are developed and investigated in different complex dynamical networks, such as in communication engineering, biological systems, and social networks. In this article, we review and summarize two effective control and synchronization methods for multi-objective and cluster synchronization respectively for any chaotic connected complex network. To demonstrate the method effectiveness, we take two typical examples -- beam transport network (BTN) and Kuramoto chaotic oscillator's connected network.
Optimization of a training set for more robust face detection
Authors: Jie Chen, Xilin Chen, Jie Yang, Shiguang Shan, Ruiping Wang, Wen Gao
Venue: Pattern Recognition (2009)

The performance of a learning-based method highly depends on the quality of a training set. However, it is very challenging to collect an efficient and effective training set for training a good classifier, because of the high dimensionality of the feature space and the complexity of decision boundaries. In this research, we study the methodology of automatically obtaining an optimal training set for robust face detection by resampling the collected training set. We propose a genetic algorithm (GA) and manifold-based method to resample a given training set for more robust face detection. The motivations behind lie in two folds: (1) dynamic optimization, diversity, and consistency of the training samples are cultivated by the evolutionary nature of GA and (2) the desirable non-linearity of the training set is preserved by using the manifold-based resampling. We demonstrate the effectiveness of the proposed method through experiments and comparisons to other existing face detectors. The system trained from the training set by the proposed method has achieved 90.73% accuracy with no false alarm on MIT+CMU frontal face test set-the best result reported so far to our knowledge. Moreover, as a fully automatic technology, the proposed method can significantly facilitate the preparation of training sets for obtaining well-performed object detection systems in different applications.
Synthesis of Reo Circuits from Scenario-based Specifications
Authors: Farhad Arbab, Meng Sun, Christel Baier
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

It is difficult to construct correct models for distributed large-scale service-oriented applications. Typically, the behavior of such an application emerges from the interaction and collaboration of multiple components/services. On the other hand, each component, in general, takes part in multiple scenarios. Consequently, not only components, but also their interaction protocols are important in the development process for distributed systems. Coordination models and languages, like Reo, offer powerful ''glue-code'' that encode the interaction protocols. In this paper we propose a novel synthesis technique, which can be used to generate Reo circuits directly from scenario specifications. Inspired by the way UML2.0 sequence diagrams can be algebraically composed, we define an algebraic framework for merging connectors generated from partial specifications by exploiting the algebraic structure of UML sequence diagrams.
Impact of Topology on Performance and Energy Efficiency in Wireless Sensor Networks for Source Extraction
Authors: Hongbin Chen, Chi K. Tse, Jiuchao Feng
Venue: IEEE Transactions on Parallel and Distributed Systems (2009)

In this paper, the problem of source extraction in bandwidth-constrained wireless sensor networks is considered. The sensor observations are assumed to be instantaneous linear mixtures of sources in a sensing field, possibly corrupted by noise. Because of the bandwidth constraint, the observations are quantized before being transmitted. Three kinds of sensor network topologies (cluster-based sensor network, sensor network with a fusion center, and concatenated sensor network) are considered in order to show the impact of topology on the performance and energy efficiency. The mixtures are reconstructed based on the received quantized data, and source extraction is performed by using a fast fixed-point algorithm with prewhitening. This algorithm was proposed by Hyvärinen and Oja, published in Neural Computation, and has the advantage of simplicity and fast convergence. The case of source extraction where the sensed data are undistorted is used as the performance benchmark. The results show that in all these sensor networks, the performance can be close to that of the benchmarking case. The energy efficiency and lifetime of these sensor networks are compared when the same source extraction task is executed. The effects of sensor failure and link failure on the performance are also discussed.
An adaptive scheme for distributed dynamic security assessment of large scale power systems
Authors: Xing-Zhi Wang, Zheng Yan, Li Li
Venue: WSEAS Transactions on Circuits and Systems (2009)

The requirements for significant computational resources imposed by dynamic security assessment applications have led to an increasing interest in the use of parallel and distributed computing technologies. This paper presents an adaptive scheme that involves user-friendly flat application program interfaces for scripting and an object-oriented programming environment for distributed dynamic security assessment implementation. Functional parallelism and data parallelism are supported by each of the message passing interface model and TCP/IP model. Adaptive stochastic-based objectives and conservative parameter prediction techniques are used to produce more efficient data parallelism. Tests for a 39-bus network and a 3872-bus network are reported, and the results of these experiments demonstrate that the proposed scheme is able to execute the distributed simulations on either stand-alone personal computers, cluster systems, or a computational grid infrastructure and provide efficient parallelism for the given environment.
Local Consistency and Junction Tree for Diagnosis of Discrete-Event Systems
Authors: Priscilla Kan John, Alban Grastien
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

We extend the decentralised/distributed approach of diagnosis of discrete-event systems modeled using automata. The goal is to avoid computing a global diagnosis, which is expensive, and to perform local diagnoses instead. To still ensure global consistency, we transform the topology of the system into a junction tree where each vertex represents a subsystem. Local consistency between the diagnoses of these subsystems ensures global consistency due to the tree structure. This technique will work best for systems whose natural structure is close to a tree structure, as the generated automata will be of reasonable size.
Modular, Fine-Grained Adaptation of Parallel Programs
Authors: Pilsung Kang, Naresh K. Selvarasu, Naren Ramakrishnan, Calvin J. Ribbens, Danesh K. Tafti, Srinidhi Varadarajan
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

We present a modular approach to realizing fine-grained adaptation of program behavior in a parallel environment. Using a compositional framework based on function call interception and manipulation, the adaptive logic to monitor internal program states and control the behavior of program modules is written and managed as a separate code, thus supporting centralized design of complex adaptation strategies for adapting to dynamic changes within an application. By `catching' the functions that execute in synchronization across the parallel environment and inserting the adaptive logic operations at the intercepted control points, the proposed method provides a convenient way of synchronous adaptation without disturbing the parallel execution and communication structure already established in the original program. Applying our method to a CFD (computational fluid dynamics) simulation program to implement example adaptation scenarios, we demonstrate how effectively applications can change their behavior through fine-grained control. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Communication during learning in heterogeneous teams of learning agents
Authors: Luís Nunes, Eugénio Oliveira
Venue: Intelligent Decision Technologies (2008)

The objective of this work is to determine how/if learning agents can benefit from exchanging information during learning in problems where each team uses a different learning algorithm. In recent studies several problems were exposed, such as lack of coordination, exchange of useless information and difficulties in the adequate choice of advisors. In this work we propose new solutions and test them in two different domains (predator-prey and traffic-control). Our solutions involve hybrid algorithms derived from Q-Learning and Evolutionary Algorithms. Results indicate that some combinations of learning algorithms are more suited to the use of external information than others and that the difference in the results achieved, with and without communication, is problem dependent. The results also show that, in situations where communication is useful, the gain in quality and learning-time can be significant if the right combination of techniques is used to process external information.
Digital redesign of uncertain interval systems via a hybrid particle swarm optimiser
Authors: Chen-Chien Hsu, Chun-Hwei Gao
Venue: International Journal of Innovative Computing and Applications (2008)

In this paper, a hybrid optimiser incorporating particle swarm optimisation (PSO) and an enhanced NM simplex search method is proposed to derive an optimal digital controller for uncertain interval systems having an interval plant based on frequency-response resemblance. By combining the uncertain plant and controller, extremal systems for the redesigned digital system and its continuous counterpart can be obtained as the basis for comparison. The design problem is then formulated as an optimisation problem of an aggregated error function in terms of frequency-response deviation between the redesigned digital system and its continuous counterpart, and subsequently optimised by the proposed optimiser to obtain an optimal set of parameters for the digital controller. Thanks to the performance of the proposed hybrid optimiser, frequency envelope of the redesigned digital system using the digital controller evolutionarily derived by the proposed approach bare a better resemblance to its continuous-time counterpart in comparison to those obtained using existing open-loop discretisation methods.
Design of a real-time face detection parallel architecture using high-level synthesis
Authors: Nicolas Farrugia, Franck Mamalet, Sébastien Roux, Fan Yang, Michel Paindavoine
Venue: EURASIP Journal on Embedded Systems (2008)

We describe a High-Level Synthesis implementation of a parallel architecture for face detection. The chosen face detection method is the well-known Convolutional Face Finder (CFF) algorithm, which consists of a pipeline of convolution operations. We rely on dataflow modelling of the algorithm and we use a high-level synthesis tool in order to specify the local dataflows of our Processing Element (PE), by describing in C language inter-PE communication, fine scheduling of the successive convolutions, and memory distribution and bandwidth. Using this approach, we explore several implementation alternatives in order to find a compromise between processing speed and area of the PE. We then build a parallel architecture composed of a PE ring and a FIFO memory, which constitutes a generic architecture capable of processing images of different sizes. A ring of 25 PEs running at 80MHz is able to process 127 QVGA images per second or 35 VGA images per second.
Modeling Collaborative Similarity with the Signed Resistance Distance Kernel
Authors: Jérôme Kunegis, Stephan Schmidt, Şahin Albayrak, Christian Bauckhage, Martin Mehlitz
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

We extend the resistance distance kernel to the domain of signed dissimilarity values, and show how it can be applied to collaborative rating prediction. The resistance distance is a graph kernel inspired by electrical network models where edges of a graph are interpreted as electrical resistances. We model the similarity between users of a large collaborative rating database using this signed resistance distance, generalizing the previously known regular resistance distance kernel which is limited to nonnegative values. We show that the signed resistance distance kernel can be computed effectively using the Moore-Penrose pseudoinverse of the Laplacian matrix of the bipartite rating graph, leading to fast computation based on the eigenvalue decomposition of the Laplacian matrix. We apply this technique to collaborative rating prediction on the Netflix Prize corpus, and show how our new kernel can replace the traditional Pearson correlation for rating prediction.
How do robots foster the learning of basic concepts in informatics?
Authors: Bernhard Wiesner, Torsten Brinda
Venue: ACM SIGCSE Bulletin (2009)

In the poster a project is presented that investigates the efficiency of using educational robots in early secondary computer science education. Results will be obtained from a comparative study in 9th grade informatics classes.
Distributed Project Governance Assessment (DPGA): Contextual, hands-on analysis for project governance across sovereign boundaries
Authors: William Anderson, David Carney
Venue: Proceedings of the 2009 ICSE Workshop on Software Development Governance (2009)

Managers of technology-intensive projects know that external dependencies beyond their direct control can pose significant risks to their performance. Unfortunately for them, there is a trend toward collaborative systems of systems with combined or threaded capabilities that generate many external dependencies. Today's world of networked, interoperating applications calls for a management perspective that seeks governance across sovereign boundaries.1 The Carnegie Mellon® Software Engineering Institute (SEI) proposes a Distributed Project Governance Assessment (DPGA) process, a work in progress, which helps organizations understand the number and characteristics of external dependencies. We seek to describe the proposed process and solicit community feedback on feasibility, shortcomings, or improvements.
Optimal investment problem with stochastic interest rate and stochastic volatility: Maximizing a power utility
Authors: Jinzhu Li, Rong Wu
Venue: Applied Stochastic Models in Business and Industry (2009)

In this paper, we assume that an investor can invest his-her wealth in a bond and a stock. In our wealth model, the stochastic interest rate is described by a Cox&ndash;Ingersoll&ndash;Ross (CIR) model, and the volatility of the stock is proportional to another CIR process. We obtain a closed-form expression of the optimal policy that maximizes a power utility. Moreover, a verification theorem without the usual Lipschitz assumptions is proved, and the relationships between the optimal policy and various parameters are given. Copyright &copy; 2009 John Wiley & Sons, Ltd.
Ontonym: a collection of upper ontologies for developing pervasive systems
Authors: Graeme Stevenson, Stephen Knox, Simon Dobson, Paddy Nixon
Venue: Proceedings of the 1st Workshop on Context, Information and Ontologies (2009)

Pervasive systems present the need to interpret large quantities of data from many sources. Context models support developers working with such data by providing a shared representation of the environment on which to base this interpretation. This paper presents a set of requirements for a context model that addresses uncertainty, provenance, sensing and temporal properties of context. Based on these requirements, we describe Ontonym, a set of ontologies that represent core concepts in pervasive computing. We propose a framework for evaluating ontologies in the pervasive computing domain by combining recognised techniques from the literature, and present a preliminary evaluation of Ontonym using these criteria.
Interoperability Issues in Authoring Interactive Activities
Authors: Manolis Mavrikis, Charles Hunn
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

This paper describes an attempt to integrate the suite of Cognitive Tutors Authoring Tools (CTAT) with an ITS for exploratory activities (DANTE). Despite their differences we provide positive indicators for integration and solutions that could be of use to developers of similar frameworks or authoring tools. In addition, by translating CTAT's XML representation of procedural activities to a more general one, used by a web-based ILE (WaLLiS), we identify missing information that need to be encoded after the translation and provide requirements for future changes or development of other authoring tools.
A study on diversity and cooperation in a multiagent strategy for dynamic optimization problems
Authors: David Pelta, Carlos Cruz, Juán Ramón González
Venue: International Journal of Intelligent Systems (2009)

In recent years, biological and natural processes have been increasingly influencing methodologies in science and technology. In particular, the role played by the cooperation among individuals is being studied more frequently and profoundly in diverse areas of knowledge. We present here a multiagent decentralized strategy for dynamic optimization problems where a population of cooperative agents and solutions are used to deal with the moving peaks problem. We focus on cooperation and diversity mechanisms, and we study how different alternatives affect the performance of the strategy. &copy; 2009 Wiley Periodicals, Inc.