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This paper proposes a kind of remote rendering method based on awareness model. This method takes the additional cost caused by the movement of the viewpoint into cost calculation and designs a cost prediction algorithm based on the vision field divided by awareness model. The simulation results show that the improved method can not only improve the quality of the remote rendering, but also make full use of the bandwidth of the network, as well as make the remote rendering more fluent when the viewpoint moves fast. [ABSTRACT FROM AUTHOR]

This paper presents a novel physically-based model for virtual Chinese brush. Compared with previous works, the main advantage of our method lies in the use of physically based modeling methods that describe the behavior of the real brush's deformation in terms of the interaction of the external and internal forces with the virtual writing paper. Instead of simulating the brush using bristles, we use points to simulate the whole brush bundle, which can drastically decrease the complexity inherent in the conventional bristle-level approach. A spring network is derived to calculate the physical deflection of brush according to the force exerted on it. With this model, we can get a more effective simulation of real brush painting. [ABSTRACT FROM AUTHOR]

Several features of today's grid are based on centralized or hierarchical services. However, as the grid size increasing, some of their functions especially resource discovery should be decentralized to avoid performance bottlenecks and guarantee scalability. A novel grid resource discovery method based on adaptive k-Nearest Neighbors clustering is presented in this paper. A class is formed by a collection of nodes with some similarities in their characteristics, each class is managed by a leader and consists of members that serve as workers. Resource requests are ideally forwarded to an appropriate class leader that would then direct it to one of its workers. This method can handle resource requests by searching a small subset out of a large number of nodes by resource clustering which can improve the resource query efficiency; on the other hand, it also achieves well scalability by managing grid resources with adaptive mechanism. It is shown from a series of experiments that the method presented in this paper achieves more scalability and efficient lookup performance than other existing methods. [ABSTRACT FROM AUTHOR]

Reading and literature exploration are important tasks of scientific research. However, conventional retrieval systems provide limited support for these tasks by concentrating on identifying relevant materials. New generation systems should provide additional support functionality by focusing on analyzing and organizing the retrieved materials. A framework of literature exploration support systems is proposed. Techniques of granular computing are used to construct granular knowledge structures from the contents, structures, and usages of scientific documents. The granular knowledge structures provide a high level understanding of scientific literature and hints regarding what has been done and what needs to be done. As a demonstration, we examine granular knowledge structures obtained from an analysis of papers from two rough sets related conferences. [ABSTRACT FROM AUTHOR]

In this paper, we study the problem of scheduling a set of n periodic preemptive independent hard real-time tasks on the minimum number of processors. We assume that the partitioning strategy is used to allocate the tasks to the processors and the EDF method is used to schedule the tasks on each processor. It is known that this scenario is NP-hard; thus, it is unlikely to find a polynomial time algorithm to schedule the tasks on the minimum number of processors. In this work, we derive a lower and an upper bound for the number of processors required to satisfy the constraints of our problem. We also compare a number of heuristic algorithms with each other and with the bounds derived in this paper. Numerical results demonstrate that our lower bound is very tight and it is very close to the optimal solution. [ABSTRACT FROM AUTHOR]

The present paper is an attempt to construct a theoretical model of the context of social action based on a reinterpretation of the sociological theory of social fields as developed by Pierre Bourdieu. Using his notions of different types of capital and other tools, a multidimensional model of context is presented in which dimensions are defined as fields affected by (and affecting) a given social action. Focus in the paper is on discursive behaviour, but following the assumptions of linguistic pragmatics, discourse is considered here just as a specific form of broadly defined social action. Thus an attempt is made at linking studies on context from linguistics with those from sociology. Social action is theorized, as in Bourdieu's models, as a process of conversion of different types of capital. The strategic use of particular types of capital is considered as another dimension of contextualization of social action. [ABSTRACT FROM AUTHOR]

In this paper we propose a two-pass classification method and apply it to face recognitions. The method is obtained by integrating together two approaches, the hyper-ellipsoid neural networks (HENN's) and the SVM's with error correcting codes. This method realizes a classification operation in two passes: the first one is to get an intermediate classification result for an input sample by using the HENN's, and the second pass is followed by using the SVM's to re-classify the sample based on both the input data and the intermediate result. Simulations conducted in the paper for applications to face recognition showed that the two-pass method can maintain the advantages of both the HENN's and the SVM's while remedying their disadvantages. Compared with the HENN's and the SVM's, a significant improvement of recognition performance over them has been achieved by the new method. [ABSTRACT FROM AUTHOR]

We are glad to present the papers of the special session on Performance in Industrial Holonic Systems (Pi-HolS 2007) at the 3d International Conference on Industrial Applications of Holonic and Multi-Agent Systems (HoloMAS 2007). The session brought together researchers and practitioners in the areas of holonic and multi-agent systems, knowledge engineering, and performance management to share their views and experience in design, development, deployment, and application of technologies for measuring, assessing and optimizing the performance of industrial systems based on holonic principles. [ABSTRACT FROM AUTHOR]

The core content of action research (AR) is being able to solve organisational problems through intervention and to contribute to scientific knowledge. The main emphasis when discussing AR has been on the "research part". In this paper we focus on "action part" of AR in order to generate rigorous research, to solve local problems and to deal with evident dilemmas in AR. Action elements are addressed by situations in a project on one-stop government e-service development. As a result of the analysis action is illustrated. Action elements: action, actor, motive, space, time are analysed together with roles. The paper also shows a need to understand initiation, problem and situation addressing as an ongoing process in an AR project. A breakdown in the project is also highlighted and situations where problems discovers the action researcher and vice versa. [ABSTRACT FROM AUTHOR]

Request Processing Systems should exhibit predictable behavior by guaranteeing Quality-of-Service parameters. One of the important requirements of predictability is that requests should have maximum acceptable response time thresholds, denoted as deadlines in this paper. In order to provide QoS, the system should try to guarantee these deadlines. This way, it is desirable to use a load-balancing algorithm that tries to both maximize the throughput and minimize the missed deadlines. Assuming that all requests durations are known a priori, this paper shows, with the help of a simulator, how the control over the big tasks plays a crucial role in the pursuit of the objective. Finally, this paper presents a derived form of the traditional Least-Work-Remaining algorithm, named Task Assignment by Isolating Big Tasks, that proved to be a better alternative in such scenarios. [ABSTRACT FROM AUTHOR]

UML is being increasing used for the analysis and design of Web Information Systems. At the same time, many XML-based languages are cornerstones in the development of this kind of system. As a consequence of the predominance of these languages, there are many works in the literature devoted to exploring the relationships between UML and XML. In this paper we present a survey of current approaches to the transformation of UML models into XML schemas. The study is focused on the case of transformation of UML class diagrams to XML schemas, since we have not found any proposal regarding other kinds of UML diagrams. [ABSTRACT FROM AUTHOR]

In sensor networks, queries need to be jointly designed, in order to minimize the power consumption and maximize the lifetime. Data reduction techniques can be employed to decrease the size of data to be transferred in the network, and therefore save energy of sensor nodes. This paper presents a novel method for optimizing multi-query in sensor networks. Our approach is, by using packet combination techniques, to reduce the data size of multiple simultaneous queries, so that the energy for data transmission can be saved to the best extent. A delay item is specified together with the query by the application. Then an optimal query plan can be obtained by studying the best time of sending local data to sink that can lead to the minimum cost. Algorithm is described in detail. Performance analysis is performed to validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper introduces an indexing technique for fuzzy numerical data which relies on the classical, well-known and well-spread B+tree index data structure. The proposed indexing technique is specifically devised to increase the performance of query processing when a possibility measured flexible condition is involved. The proposal relies on the use of an indexing data structure implemented in virtually every database management system. This feature makes the proposal a good candidate to be used, with very low implementation effort, in a fuzzy database management system created as an extension of a classical one. The paper includes a performance analysis of the proposed indexing technique in contrast with other purpose equivalent techniques in order to evaluate the suitability of the proposal. [ABSTRACT FROM AUTHOR]

This paper describes some results of a project that studied how multimedia can help the worker in an assembly task. The test case was a deep-cut assembly of a grid-anode for a cathodic protection system. A multimedia tool was implemented and compared with the conventional support method for the same task. The tool helps the worker by providing training and background information. During the task the tool acts as a guide and a set of well-defined instructions. The comparison of the methods was done by means of a field experiment. The results show that the use of the implemented tool helps to produce a slight increase to the quality of the work. However, the execution time of the work was not better when using the multimedia tool. According to a user questionnaire done in the test situation, the multimedia tool was more useful and easier to use, and gave the users more confidence than the conventional support method. It can be said that the use of multimedia support helps the worker to produce better quality in the task. [ABSTRACT FROM AUTHOR]

The paper discusses a distributed approach for monitoring and diagnosing the execution of a plan where concurrent actions are performed by a team of cooperating agents. The paper extends the notion of plan diagnosis(introduced by Roos et al. for the execution of a multi-agent plan) with the notion of agent diagnosis. While plan diagnosis is able to capture the distinction between primary and secondary failures, the agent diagnosis makes apparent the actual health status of the agents. The paper presents a mechanism of failure propagation which captures the interplay between agent diagnosis and plan diagnosis; this mechanism plays a critical role in the understanding at what extent a fault affecting the functionalities of an agent affects the global plan too. A relational formalism is adopted for modeling both the nominal and the abnormal execution of the actions. [ABSTRACT FROM AUTHOR]

In this paper, we suggest a postal RFID application model that can be used for real time trace and tracking system implementation of parcel processing and pallet management. This paper also shows the tag recognition performance of parcels by speed and mounting tag material such as thin cans, water bottles, and paper using an implemented postal RFID system to find the best solution for RFID adaptation in postal logistics. [ABSTRACT FROM AUTHOR]

In order to discover services in business-driven Web service composition conveniently, accurately, and efficiently, this paper proposes a business process-oriented service discovery approach. In order to link business property with services, this paper proposes a business related description model of operations. Based on the business related relation model proposed in this paper, a relation-driven discovering algorithm for business process-oriented service discovery is presented. Compared with other discovering approach, the proposed discovering approach considers the business relation between operations and can solve the problem of discovering services with meaningful business relation. The experimentation shows the better performance of this algorithm. [ABSTRACT FROM AUTHOR]

Generally, it is difficult to find constant patterns on identifiers in a container image, since the identifiers are not normalized in color, size, and position, etc. and their shapes are damaged by external environmental factors. This paper distinguishes identifier areas from background noises and removes noises by using an ART2-based quantization method and general morphological information on the identifiers such as color, size, ratio of height to width, and a distance from other identifiers. Individual identifier is extracted by applying the 8-directional contour tracking method to each identifier area. This paper proposes a refined ART2-based RBF network and applies it to the recognition of identifiers. Through experiments with 300 container images, the proposed algorithm showed more improved accuracy of recognizing container identifiers than the others proposed previously, in spite of using shorter training time. [ABSTRACT FROM AUTHOR]

Object-level vertical search engine has been the research focus recently where the resource collecting problem is still an open area. It is difficult to adapt the traditional link-based web crawler for this task because of the sparse linkage and data-centered webpage of the relevant resources. In this paper, we propose a meta-search based method enhanced with auxiliary crawling to address the problem caused by sparse linkage of the relevant resources. And to retrieve the data-centered webpages efficiently, domain schema is defined to describe the target resource, and representative data instances are selected for meta-search query composing. Moreover, evaluation criteria for the domain resource survey are also proposed as the guideline for query composing and auxiliary crawling, which enable the resource discovery to be automatically performed by computers. Experiment results on real-world data show that our method is effective and efficient. [ABSTRACT FROM AUTHOR]

This paper gives a survey of the current state of ARTIC - the modern Czech concatenative corpus-based text-to-speech system. All stages of the system design are described in the paper, including the acoustic unit inventory building process, text processing and speech production issues. Two versions of the system are presented: the single unit instance system with the moderate output speech quality, suitable for low-resource devices, and the multiple unit instance system with a dynamic unit instance selection scheme, yielding the output speech of a high quality. Both versions make use of the automatically designed acoustic unit inventories. In order to assure the desired prosodic characteristics of the output speech, system-version-specific prosody generation issues are discussed here too. Although the system was primarily designed for synthesis of Czech speech, ARTIC can now speak three languages: Czech (both female and male voices are available), Slovak and German. [ABSTRACT FROM AUTHOR]

Performance on a statistical language processing task relies upon accurate information being found in a corpus. However, it is known (and this paper will confirm) that many perfectly valid word sequences do not appear in training corpora. The percentage of n-grams in a test document which are seen in a training corpus is defined as n-gram coverage, and work in the speech processing community [7] has shown that there is a correlation between n-gram coverage and word error rate (WER) on a speech recognition task. Other work (e.g. [1]) has shown that increasing training data consistently improves performance of a language processing task. This paper extends that work by examining n-gram coverage for far larger corpora, considering a range of document types which vary in their similarity to the training corpora, and experimenting with a broader range of pruning techniques. The paper shows that large portions of language will not be represented within even very large corpora. It confirms that more data is always better, but how much better is dependent upon a range of factors: the source of that additional data, the source of the test documents, and how the language model is pruned to account for sampling errors and make computation reasonable. [ABSTRACT FROM AUTHOR]

It is not easy to develop a game that applies physical laws. In this paper we proposed a physics editor to make it easy to produce a physics game. The physics editor uses XML for processing attribute values of each object. This paper presents the architecture of the physics editor, and describes its detailed components. The physics editor provides an efficient method that is easily applied to physical attributes of all objects in the game. In this paper, we showed the process of a car's creation, using the physics editor. The physics editor that is presented in this paper automatically creates physical objects, but it is limited to the rigid body for car racing. [ABSTRACT FROM AUTHOR]

This paper proposed an automatic recognition system of shipping container identifiers using fuzzy-based noise removal method and ART2-based self-organizing supervised learning algorithm. Generally, identifiers of a shipping container have a feature that the color of characters is black or white. Considering such a feature, in a container image, all areas excepting areas with black or white colors are regarded as noises, and areas of identifiers and noises are discriminated by using a fuzzy-based noise detection method. Noise areas are replaced with a mean pixel value of the whole image and areas of identifiers are extracted by applying the edge detection by Sobel masking operation and the vertical and horizontal block extraction in turn to the noise-removed image. Extracted areas are binarized by using the iteration binarization algorithm, and individual identifiers are extracted by applying 8-directional contour tacking method. This paper proposed an ART2-based self-organizing supervised learning algorithm for the identifier recognition, which creates nodes of the hidden layer by applying ART2 between the input and the hidden layers and improves the performance of learning by applying generalized delta learning and Delta-bar-Delta algorithm between the hidden and the output layers. Experiments using many images of shipping containers showed that the proposed identifier extraction method and the ART2-based self-organizing supervised learning algorithm are more improved compared with the methods previously proposed. [ABSTRACT FROM AUTHOR]

This paper introduces an analytical approach which is provided to calculate the downlink and uplink capacities of the time division duplex (TDD) system utilizing the underused frequency division duplex (FDD) uplink which shares the same frequency band. Then the ratio of downlink and uplink slots in one frame is adjusted, so as to prevent the radio resource waste due to asymmetric traffic characteristic in mobile multimedia services. The computer simulation shows that the resource waste problem can be considerably solved through the asymmetric slot allocation. Thus, this paper can be useful as a guideline in the course of planning a two-layer hierarchical cell structure (HCS) employing the TDD system as a microcell and FDD system as a macrocell as well as a mean to increase the performance of such a system. [ABSTRACT FROM AUTHOR]

This paper proposed an automatic recognition system of shipping container identifiers using fuzzy-based noise removal method and ART2-based self-organizing supervised learning algorithm. Generally, identifiers of a shipping container have a feature that the color of characters is black or white. Considering such a feature, in a container image, all areas excepting areas with black or white colors are regarded as noises, and areas of identifiers and noises are discriminated by using a fuzzy-based noise detection method. Noise areas are replaced with a mean pixel value of the whole image and areas of identifiers are extracted by applying the edge detection by Sobel masking operation and the vertical and horizontal block extraction in turn to the noise-removed image. Extracted areas are binarized by using the iteration binarization algorithm, and individual identifiers are extracted by applying 8-directional contour tracking method. This paper proposed an ART2-based self-organizing supervised learning algorithm for the identifier recognition, which creates nodes of the hidden layer by applying ART2 between the input and the hidden layers and improves the performance of learning by applying generalized delta learning and Delta-bar-Delta algorithm between the hidden and the output layers. Experiments using many images of shipping containers showed that the proposed identifier extraction method and the ART2-based self-organizing supervised learning algorithm are more improved compared with the methods previously proposed. [ABSTRACT FROM AUTHOR]

The neuron based nonlinear PID control method for plant with uncertainties is proposed in this paper. In this control system, the neuron based nonlinear PID controller is constructed by selecting the neuron inputs, and the control action of the nonlinear PID controller are determined by modifying the neuron weights on-line. The neuron based nonlinear PID controller produces the control signal in model-free way. With an example of the basis weight control of a paper machine, the experiments are made. The simulation results show that the neuron model-free controller has good control performance, fast transient response and strong robustness. [ABSTRACT FROM AUTHOR]

TSP(Traveling Salesman Problem) used widely for solving the optimization is the problem to find out the shortest distance out of possible courses where one starts a certain city, visits every city among N cities and turns back to a staring city. At this time, the condition is to visit N cities exactly only once. TSP is defined easily, but as the number of visiting cities increases, the calculation rate increases geometrically. This is why TSP is classified into NP-Hard Problem. Genetic Algorithm is used representatively to solve the TSP. Various operators have been developed and studied until now for solving the TSP more effectively. This paper applied the new Population Initialization Method (using the Random Initialization method and Induced Initialization method simultaneously), solved TSP more effectively, and proved the improvement of capability by comparing this new method with existing methods. Keywords: Genetic Algorithm, GA, Optimization, Initialization. [ABSTRACT FROM AUTHOR]

This paper introduces the invited session of "Intelligent Agents and their Applications" being presented at the 10th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems. This session concentrates on discussing Intelligent Agents and uses some applications to demonstrate the theories reported. An update on last years session [1] is included to report on several key advances in technology that further enable the ongoing development of multi-agent systems. A brief summary of the impediments presented to researchers is also provided to highlight why innovation must be used to sustain the evolution of Artificial Intelligence. This year a variety of challenges and concepts are presented, together with a collection of thoughts about the direction and vision of Intelligent Agents ands their Applciations. [ABSTRACT FROM AUTHOR]

Name disambiguation can occur when one is seeking a list of publications of an author who has used different name variations and when there are multiple other authors with the same name. We present an efficient integrative framework for solving the name disambiguation problem: a blocking method retrieves candidate classes of authors with similar names and a clustering method, DBSCAN, clusters papers by author. The distance metric between papers used in DBSCAN is calculated by an online active selection support vector machine algorithm (LASVM), yielding a simpler model, lower test errors and faster prediction time than a standard SVM. We prove that by recasting transitivity as density reachability in DBSCAN, transitivity is guaranteed for core points. For evaluation, we manually annotated 3,355 papers yielding 490 authors and achieved 90.6% pairwise-F1. For scalability, authors in the entire CiteSeer dataset, over 700,000 papers, were readily disambiguated. [ABSTRACT FROM AUTHOR]

It is well known that connectivity analysis of linked documents provides significant information about the structure of the document space for unsupervised learning tasks. However, the ability to identify distinct clusters of documents based on link graph analysis is proportional to the density of the graph and depends on the availability of the linking and/or linked documents in the collection. In this paper, we present an information theoretic approach towards measuring the significance of individual words based on the underlying link structure of the document collection. This enables us to generate a non-uniform weight distribution of the feature space which is used to augment the original corpus-based document similarities. The experimental results on the collection of scientific literature show that our method achieves better separation of distinct groups of documents, yielding improved clustering solutions. [ABSTRACT FROM AUTHOR]

Adaptive Hypermedia builds upon the annotation and adaptation of content. As manual annotation has proven to be the main bottleneck, all means for supporting it by reusing automatically generated metadata are helpful. In this paper we discuss two issues. The first is the integration of a generic AH authoring environment MOT into a semantic desktop environment. In this setup, the semantic desktop environment provides a rich source of automatically generated meta-data, whilst MOT provides a convenient way to enhance this meta-data manually, as needed for an adaptive course environment. Secondly, we also consider the issue of source schema heterogeneity, especially during the automatic metadata generation process, as semantic desktop metadata are generated through a lot of different tools and at different times, so that schemas are overlapping and evolving. Explicitly taking into account all versions of these schemas would require a combinatorial explosion of generation rules. This paper investigates a solution to this problem based on malleable schemas, which allow metadata generation rules to flexibly match different versions of schemas, and can thus cope with the heterogeneous and evolving desktop environment. [ABSTRACT FROM AUTHOR]

Recommender algorithms have been quite successfully employed in a variety of scenarios from filtering applications to recommendations of movies and books at Amazon.com. However, all these algorithms focus on single item recommendations and do not consider any more complex recommendation structures. This paper explores how semantically rich complex recommendation structures, represented as RDF graphs, can be exchanged and shared in a distributed social network. After presenting a motivating scenario we define several annotation ontologies we use in order to describe context information on the user's desktop and show how our ranking algorithm can exploit this information. We discuss how social distributed networks and interest groups are specified using extended FOAF vocabulary, and how members of these interest groups share semantically rich recommendations in such a network. These recommendations transport shared context as well as ranking information, described in annotation ontologies. We propose an algorithm to compute these rankings which exploits available context information and show how rankings are influenced by the context received from other users as well as by the reputation of the members of the social network with whom the context is exchanged. [ABSTRACT FROM AUTHOR]

The paper reports on the development of the formal framework to design strategies for multi-issue non-symmetric meaning negotiations among software agents in a distributed information retrieval system. The advancements of the framework are the following. A resulting strategy compares the contexts of two background domain theories not concept by concept, but the whole context to the other context by accounting the relationships among concepts, the properties, the constraints over properties, and the available instances. It contains the mechanisms for measuring contextual similarity through assessing propositional substitutions and to provide argumentation through generating extra contexts. It uses presuppositions for choosing the best similarity hypotheses and to make the mutual concession to the common sense monotonic. It provides the means to evaluate the possible eagerness to concede through semantic commitments and related notions of knowledgeability and degree of reputation. [ABSTRACT FROM AUTHOR]

Increasing the smooth degree of data series is key factor of grey model's precision. In this paper, the more general method is put forward on the basis of summarizing several kinds of ways to improve smooth degree of data series, and a new transformation is represented. The practical application shows the effectiveness and superiority of this method. [ABSTRACT FROM AUTHOR]

A method based on multi-feature and multi-stage verification is proposed in this paper. The direction and texture features obtained by Gabor filter are used for the first-stage verification. Then the sham dynamic features representing the writing force are used for the second-stage verification. Considering the number of samples for training is limited, the support vector machine (SVM) is selected as the classifier. The experimental results show that this method can not only increase the accuracy, but also satisfy the requirement of speed in real-time system as well. [ABSTRACT FROM AUTHOR]

Accurate cancer classification is very important to cancer diagnosis and treatment. As molecular information is increasing for the cancer classification, a lot of techniques have been proposed and utilized to classify and predict the cancers from gene expression profiles. In this paper, we propose a method based on speciated evolution for the cancer classification. The optimal combination among several feature-classifier pairs from the various features and classifiers is evolutionarily searched using the deterministic crowding genetic algorithm. Experimental results demonstrate that the proposed method is more effective than the standard genetic algorithm and the fitness sharing genetic algorithm as well as the best single classifier to search the optimal ensembles for the cancer classification. [ABSTRACT FROM AUTHOR]

This paper discusses two statistical shape descriptors, the Edge Co-occurrence Matrix (ECM) and the Contour Co-occurrence Matrix (CCM), and their use in surface defect classification. Experiments are run on two image databases, one containing metal surface defects and the other paper surface defects. The extraction of Haralick features from the matrices is considered. The descriptors are compared to other shape descriptors from e.g. the MPEG-7 standard. The results show that the ECM and the CCM give superior classification accuracies. [ABSTRACT FROM AUTHOR]

Motivated by three applications which are under investigation at the Honeywell Research Laboratory in Minneapolis, we introduce a class of large scale control problems. In particular we show that a formation flight problem, a paper machine control problem and the coordination of cameras in a monitoring network can be cast into this class. In the second part of the paper we propose a decentralized control scheme to tackle the complexity of the problem. The scheme makes use of logic rules which improve stability and feasibility of the decentralized method by enforcing coordination. The decentralized control laws which respect the rules are computed using hybrid control design. [ABSTRACT FROM AUTHOR]

Summary: Dive headfirst into Microsofts Computer Vision APIs through sample-driven scenarios! Imagine an app that describes to the visually impaired the objects around them, or reads the Sunday paper, a favorite magazine, or a street sign. Or an app that is capable of monitoring what is happening inside an area without human control, and then makes a decision based on interpreting an occurrence detected with a live camera. This book teaches developers Microsoft's Computer Vision APIs, a service capable of understanding and interpreting the content of any image. Author Del Sole begins by providing a succinct need to knowoverview of the service with descriptions. You then learn from hands-on demonstrations that show how basic C# code examples can be re-used across platforms. From there you will be guided through two different kinds of applications that interact with the service in two different ways: the more common means of calling a REST service to get back JSON data, and via the .NET libraries that Microsoft has been building to simplify the job (this latter one with Xamarin).רat Youll Learn Understand AIs role and how devices and applications use sophisticated algorithms to improve peoples lives and business tasks. Analyze images for Optical Character Recognition to detect written words and sentences Think about the next-generation applications in relation to your customersneeds Get up-to-speed on the latest version of the Computer Vision service, which now comes through Azure Set up an Azure subscription in order to access the Cognitive Services within the portal After reading this book, you will be able to get started with AI services from Microsoft in order to begin building powerful new apps for your company or customers.רo This Book Is Forĥvelopers just getting familiar with artificial intelligence. A minimal knowledge of C# is required.

We regret to report that we have found an error in our paper "On the Hardness of Embeddings Between Two Finite Metrics," which appeared in the Proceedings of the 32nd International Colloquium on Automata, Languages and Programming (ICALP), Lisboa, Portugal, July 2005. [ABSTRACT FROM AUTHOR]

Summary: Conceptual modeling has always been one of the main issues in information systems engineering as it aims to describe the general knowledge of the system at an abstract level that facilitates user understanding and software development. This collection of selected papers provides a comprehensive and extremely readable overview of what conceptual modeling is and perspectives on making it more and more relevant in our society. It covers topics like modeling the human genome, blockchain technology, model-driven software development, data integration, and wiki-like repositories and demonstrates the general applicability of conceptual modeling to various problems in diverse domains. Overall, this book is a source of inspiration for everybody in academia working on the vision of creating a strong, fruitful and creative community of conceptual modelers. With this book the editors and authors want to honor Prof. Antoni Olivé for his enormous and ongoing contributions to the conceptual modeling discipline. It was presented to him on the occasion of his keynote at ER 2017 in Valencia, a conference that he has contributed to and supported for over 20 years. Thank you very much to Antoni for so many years of cooperation and friendship.

This edited volume contains the papers selected for presentation at the Second Workshop on Data Mining for Biomedical Applications (BioDM'07) held in Nanjing, China on 22nd of May 2007. The workshop was held in conjunction with the 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2007), a leading international conference in the areas of data mining and knowledge discovery. The aim of this workshop was to provide a forum for discussing research topics related to biomedical applications where data mining techniques were found to be necessary and/or useful. [ABSTRACT FROM AUTHOR]

Despite an impressive body of research,parallel and distributed computing remains a complex task prone to subtle software bugs, which can affect both the correctness and the performance of the computation. The increasing demand to distribute computing over large-scale distributed platforms, such as grids and large clusters, overlaps with an increasing pressure to make computing more dependable. To address these challenges, the parallel and distributed computing community continuously requires better tools and environments to design, program, debug, test, tune, and monitor programs. This topic aims to bring together tool designers, developers, and users to share their concerns, ideas, solutions, and products, covering a wide range of platforms. [ABSTRACT FROM AUTHOR]

The Software Engineering track received 63 papers from which 7 papers were selected after an intensive reviewing and selection process. Many good papers could not be selected due to lack of space in the program. The selected papers cover a diverse range of topics within software engineering: from software reliability prediction to middle-ware for component management to runtime validation and code generation. The paper by Roychoudhury, Negi and Mitra analyzes programs loops for estimating program execution time. They use constraint propagation techniques to detect infeasible paths followed by timing analysis that employ memoization techniques. The paper by Sengupta and Cleaveland presents the operational semantics of timed message sequence charts to help detect errors and inconsistencies in specifications. Tripathi and Mall present a method for making predictions about reliability of software during the software development process itself when the failure data from the field cannot be available. The paper by Wang presents a logic programming framework for integrating architecture description languages (ADLs) which allows tools developed for one ADL to be used even though the architectural specification is written in another ADL. In a similar vain, the paper by Stevenson, Fu and Dong presents a framework for automated and validated realization of software architecture designs. The paper by Bhattarcharjee and Shyamsundar presents a method for validated code generation for activity diagrams which are useful in model driven design of software. Finally, the paper by Mousavi et al presents techniques that exploit symmetry for tackling the state-space explosion problem that arises in model checking. [ABSTRACT FROM AUTHOR]

In this paper we consider disaster management as the coordination of resources in space and time, and contrast this with the Joint Operational Picture (JOP) used in military planning. The basic premise is that the processes involved in the collection and management of information could interfere with the priorities of dealing with immediate demands on ‘rescuers' and their managers. Thus, we explore ways in which collaboration could be made as implicit as possible. The paper includes small-scale user trials of prototypes to highlight potential benefits and shortcomings. The paper concludes with consideration of how brokering approaches to coordination could be realized using the prototypes described in this paper. [ABSTRACT FROM AUTHOR]

Across Europe emergency physicians are still using paper-based emergency report forms to document medical procedure at accident scenes. The forms are quite similar, but they differ in certain parameters or attributes. There are ongoing endeavours to combine the paper-based protocols and then transfer this new protocol standard into a software-based Emergency Patient Care Report Form (EPCRF). However during the transformation from a paper-based to an electronic solution, many problems occur. To keep the users' acceptance of the emergency medical services personnel, it is crucial that electronic EPCRF supports the central process efficiently. Therefore key elements within the emergency report form are the anatomical diagrams and the chronological sequence diagrams. These diagrams allow the emergency physician to track and record patient's parameters in a very fast and understandable and user friendly way. [ABSTRACT FROM AUTHOR]

The design of easy-to-use mobile systems for collecting and handling emergency medical care data in the field can significantly improve the effectiveness of rescue operations. In particular, this paper focuses on the design and evaluation of a mobile application that replaces ambulance run paper sheets. First, we discuss the limitations of traditional ambulance run paper sheets. Then, we present the PDA-based system we have developed. Finally, we discuss in detail the usability study we have carried out with first responders. [ABSTRACT FROM AUTHOR]

In recent years, dynamic reconfigurable processor which can achieve reconfiguration with a few cycles is proposed. The fast recon- figuration makes run-time reconfiguration possible, and the run-time reconfiguration gives a new possibility to the dynamic reconfigurable processor, i.e. the dynamic reconfigurable processor can also execute partitioned independent subtasks with repeated reconfigurations and executions. However, to achieve an execution with the run-time reconfiguration, performance should be evaluated with various overheads: reconfiguration, memory accesses, etc. The overheads depend on reconfigurable architectures, and it is generally difficult to evaluate the overhead. As the overhead may critically affect the performance, designers should carefully explore design space for suitable architectures. In this paper, we propose a dynamic reconfigurable architecture exploration method based on Parameterized Reconfigurable Processor model (PRP-model) and task partitioning optimization algorithm for architecture exploration corresponding to proposed PRP-model. Experimental results showed that the proposed PRP-model and the task partitioning algorithm for PRP-model can fast evaluate various reconfigurable architectures, and designers can easily find suitable reconfigurable architectures by changing the PRPmodel parameters. [ABSTRACT FROM AUTHOR]

With the popularization of networks, digitalization and automation, demand for enterprise informatization becomes more urgent. There are many factors leading to the demand for EIS. Some of the factors are from enterprise development, while others are from policy driven. In this paper, we present a relationship model by using system dynamics method to characterize the cause-result (C-R) of demand drivers of enterprise informatization. Based on the empirical studies, we reveal how the factors affect the demand for enterprise informatization, which form a cluster of causation to be used as the cause variables in our model. This procedure is to settle on the interim variables and result variables, which formed systematic dynamics C-R charts. Questionnaires and interviews from dozens of enterprises, Delphi Expert Decision method are made and analyzed, which verified the relationship between variables. The results presented in this paper provide good insights for the enterprise managers' optimal decisions. [ABSTRACT FROM AUTHOR]

This paper describes a system capable of semi-automatically filling an XML template from free texts in the clinical domain (practice guidelines). The XML template includes semantic information not explicitly encoded in the text (pairs of conditions and actions/recommendations). Therefore, there is a need to compute the exact scope of conditions over text sequences expressing the required actions. We present in this paper the rules developed for this task. We show that the system yields good performance when applied to the analysis of French practice guidelines. [ABSTRACT FROM AUTHOR]