Abstract: In this paper the speech emotion verification using two most popular methods in speech processing and analysis based on the Mel-Frequency Cepstral Coefficient (MFCC) and the Gaussian Mixture Model (GMM) were proposed and analyzed. In both cases, features for the speech emotion were extracted using the Short Time Fourier Transform (STFT) and Short Time Histogram (STH) for MFCC and GMM respectively. The performance of the speech emotion verification is measured based on three neural network (NN) and fuzzy neural network (FNN) architectures; namely: Multi Layer Perceptron (MLP), Adaptive Neuro Fuzzy Inference System (ANFIS) and Generic Self-organizing Fuzzy Neural Network (GenSoFNN). Results obtained from the experiments using real audio clips from movies and television sitcoms show the potential of using the proposed features extraction methods for real time application due to its reasonable accuracy and fast training time. This may lead us to the practical usage if the emotion verifier can be embedded in real time applications especially for personal digital assistance (PDA) or smart-phones.

Abstract: This paper surveys the role ontologies might play in the whole software development life cycle. Use of ontologies in each phase of software development yields competitive advantage over traditional approach enabling greater information sharing and reuse. In this survey paper, we present a concise description of various ontology-based approaches in Software Engineering ordered by their position in the Software Engineering life cycle. We also report ontology editor tool Protege as part of our survey.

Abstract: In this paper, we present reliable algorithms for fuzzy k$means and C$means that could improve MRI se gmentation. Since the k$means or FCM method aims to minimize th e sum of squared distances from all points to their cluster centers, this should result in compact clusters. Therefore the distance of the points from their cluster centre is used to determine whether the clusters are compact. For this purpose, we use the intra$cluster distance measure, which is simply the median distance between a point and its cluster centre. The intra$c luster is used to give us the ideal number of clusters automatically; i.e a centre of the first cluster is used to estimate the second cluster, while an intra$cluster of the seco nd cluster is obtained. Similar, the third cluster is estimated based on the second cluster information (centre and intra cluster), so on, and only stop when the intra$cluster is smaller than a prescribe value. Th e proposed algorithms are evaluated and compared with established fuzzy k$ means and C$means methods by applying them on simul ated volumetric MRI and real MRI data to prove their efficiency. These evaluations, which are not easy to specify in the absence of any prior knowledge about resulted clusters, for real MRI dataset are judged visually by specialists since a real MRI dataset cannot give us a quantitative measure about how much they are successful.

Abstract: Data engineering becomes increasingly important with the increasing popularity of service oriented architecture (SOA) and web services. Such data engineering requires a design methodology within an ontology framework. In this paper, the System Entity Structure (SES) serves as an abstract ontology framework for world state descriptionsontology framework for world state descriptions particularly involving dynamics in space and time. It is implemented within a software tool, the SESBuilder, employing the extended markup language XML. Pruned Entity Structures (PES) represent the logically possible set of world state descriptions consistent with the SES. At the implementation level, an SES is represented by a schema or DTD whose instance documents represent possible prunings. The SESBuilder supports convenient specification of SESs, pruning to create PESs, and transformation to XML representations, all through natural language and graphical interfaces. Thus the software provides a capable data engineering work space. In this paper, we illustrate its application to data modeling of US Climate Normals for the purpose of automated generation of weather simulation models. Key WordsSES, PES, SESBuilder, XML, Data

Abstract: In this paper we present an energy efficient framework for processing spatial alarms on mobile clients, while maintaining low computation and storage costs. Our approach to spatial alarms provides two systematic methods for minimizing energy consumption on mobile clients. First, we introduce the concept of safe distance to reduce the number of unnecessary mobile client wakeups for spatial alarm evaluation. This mechanism not only reduces the amount of unnecessary processing of the spatial alarms but also significantly minimizes the energy consumption on mobile clients, compared to periodic wakeups, while preserving the accuracy and timeliness of the spatial alarms. Second, we develop a suite of techniques for minimizing the number of location triggers to be checked for spatial alarm evaluation upon each wakeup. This further reduces the computation cost and energy expenditure on mobile clients. We evaluate the scalability and energy-efficiency of our approach using a road network simulator. Our client based framework for spatial alarms offers significant improvements on both system performance and battery lifetime of mobile clients, while maintaining high quality of spatial alarm services, especially compared to the conventional approach of periodic wakeup and checking all alarms upon wakeup.

Abstract: In this paper, we analyze web traffic characters and the relationship with software failures. Results indicate hourly web access traffic is the lowest from 3:00 to 4:00 am, while the traffic load gradually reaches peak between 14:00 and 16:00, before declining. In daily base, web traffic fluctuates in the 25 observed days. The hourly access hits appear in similar patterns to the software failures. The web site reliability is 0.9878. The mean time between failures is 82.03 hits. Five popular software reliability models are calibrated with real data. The validations show that Goel-Okumoto and Gompertz models accurately describe web software failures. Further investigations indicate that both models have some deviations in prediction accuracy starting from the 20th day. Using similar approach to change-point solutions, we recalibrate the models with different parameter values after 20th day. The results appear that two sets of parameter values greatly improve model prediction accuracy.

Abstract: In computational linguistics, word sense disambiguation (WSD) is the problem of determining in which sense a word having a number of distinct senses is used in a given sentence . This paper handles text document clustering as one of the major tasks of text processing. Document clustering is the process of finding out groups of information from the text documents and cluster these documents into the most relevant groups. Large document corpus suffers from ambiguity problems like synonyms, polysemous and other semantic relations. For this reason we perform WSD task for all terms in all documents to get the best sense to be used as document features in the clustering process. Our experimental results proved that the efficiency of document clustering using WSD increases linearly with the size of the documents dataset. Different part of speech (POS) taggers were tested to determine the best; also the effect of different window sizes on WSD task was compared.

Abstract: A flame-retardant resin having excellent moldability composed essentially of a fluorine-containing copolymer obtained by the copolymerization of tetrafluoroethylene, chlorotrifluoroethylene and ethylene, wherein the copolymer comprises from 10 to 60 molar % of tetrafluoroethylene, from 20 to 60 molar % of chlorotrifluoroethylene and from 20 to 40 molar % of ethylene, and has a thermal decomposition temperature of at least 325 DEG C.

Abstract: The Agile methodologies have shown success over plan-driven methodologies especially in web development due to their ability to adapt to new requirement changes. Because of the importance of the development of Graphical User Interfaces (GUI), we have proposed a new agile practice, “Early User Interface Development” (EUID), for developing GUI at early stages in our previous paper [1,2]. To speed up the process of producing the output of our practice, we propose a framework for representing the GUI structure and behavior. Besides, the framework can be used for automating the development of GUI according to the EUID process.

Abstract: Enterprise information systems distinguish the Domain layer that handles the major business logic of an application, from the Data (Persistent) layer that handles storage concerns alone. The integration of these layers is not straightforward since usually the requirement is for partial persistency, i.e., persistency is required only for a subset of the Domain layer classes. Industry tools provide partial help by supporting convenient abstractions on top of concrete database systems. Nevertheless, the developer still has to design the concrete ties between the layers. Full automation can be a great improvement in complex system development, and goes along with the Model Driven Engineering approach. In this paper we introduce a set of independent Data Access Patterns that provide the missing link towards full automation of the Domain-Data layer interaction. Each pattern is a simple refactoring that yields some Data Access layer constructs, and relies on local information in the Domain layer. All patterns are Domain layer transparent, i.e., their application leaves the Domain layer intact. We provide an algorithm for combined pattern application and show its correctness. An implementation of our method is on the way.

Abstract: Due to the heterogeneity of the existing platforms, IT Environments became very extremely complex, consequently the communication between the organizations more difficult. The service oriented architecture (SOA) claims that the interactions between different parities will be easier. 1. Service Oriented Architecture (SOA) and Enterprise Resource Planning

Abstract: Business Process Execution Language for Web Services (BPEL) is an industry standard language for web services composition. BPEL allows users to compose and execute web services-based business workflows, utilizing distributed web services. Standard BPEL allows dynamic execution of web services, but automatic service selection is not supported. We propose to extend BPEL to allow users to specify Quality of Service (QoS) parameters that will guide a BPEL execution engine to select appropriate service providers during run-time that will consequently improve the engine performance towards higher system throughputs. We implemented our proposal by extending an open-source BPEL engine to support QoS constraints. We present preliminary results showing that QoSsupported BPEL execution improves the overall system throughput by lowering the average execution times of BPEL processes.

Abstract: Scalable and Distributed Data Structures (SDDS) are a class of data structures completely dedicated to distributed environments. They allow the management of large amounts of data while maintaining steady and optimum performances. Several families of SDDS have been proposed: LH*, RP*, DRT*, CTH*. None of these SDDS deals with the mobile environment. In this paper we present a novel architecture that uses a scalable and distributed data structure to manage insert/find/range query operations for mobile clients. We describe the design and the implementation of a mobile CTH* prototype. Our experimental results prove the validity of the design choices and show interesting access performances. The capabilities of the mobile CTH* platform oer new perspectives for high performance and ubiquitous data intensive applications.

Abstract: Highly purified T cell replacing factor (TRF or BIF) essentially free of IL-2 and Interferon activities is obtained in the invention. BIF is useful for treatment of immunoregulatory disorders and/or stimulation of production of immunoglobulins. A method for production of BIF and BGF is described. B cell lines for BIF assays are described as well as an assay for B cell receptor variants and a method for obtaining B cell variants from a variety of source materials.

Abstract: Monoethylenically unsaturated copolymerizable monomers are disclosed which improve the adhesion of copolymers (especially those produced by aqueous emulsion copolymerization to provide latex paint). These monomers are the reaction product of one equivalent of a monoethylenically unsaturated compound which resists homopolymerization and which carries a single isocyanate-reactive hydrogen atom, such as 2-hydroxy propyl monobutyl maleate, one mole of an organic polyisocyante, such as 2, 4-toluene diisocyanate, and sufficient alkyl alkylene urea carrying a single isocyanate-reactive hydrogen atom on the alkyl group, such as 2-hydroxyethyl ethylene urea, to consume the remaining isocyanate functionality on the polyisocyanate. An improved method of producing these monomers from a mixture of all three reactants is also disclosed.

Abstract: Management systems for moving objects such as automobiles, airplanes, ships, and humans, must not only manage the moving objects efficiently but also quickly provide information about their surroundings on demand, because a moving object must know its environment to determine optimal solutions, e.g., the best path to a destination. In this paper, an efficient method for managing moving objects is proposed. This method is developed by extending the spatial data structure, MD-tree, through the introduction of two novel concepts, internal leaf and improvements in bottom-up search. The internal leaf that is managed by corresponding internal node in a tree has pointers to moving objects and helps reduce the update cost of the tree. The improved bottom-up search of the tree reduces the retrieval costs by managing the non-overlapped areas of split data space. Moreover, the usual spatial searches and updates of the tree can be executed as efficient as the MD-tree.

Abstract: We introduce the information retrieval oriented data structure to build very large, scalable, loosely structured and unstructured distributed data storage. The main idea is to represent data as a set of structured storage units on which a semi-metric can be defined which characterizes the relative relevance of each unit. Then a complex graph can be constructed whose vertices are the storage units and the edges are selected in such a way that the graph has the small world properties and is in accordance with the introduced metric (Metrized Small World Feature). Addition and removal of the data items causes the graph to evolve, while the retrieval of information is based on generating a new vertex, connecting it to the graph and setting up a search process of the data vertices metrically close to the request vertex. Due to the special properties of the constructed graph, the search is accomplished on average in the number of steps logarithmic of the storage size. We built a prototype of such a storage where the data items are represented by XML documents and the graph is expressed by means of XLink. The analysis of the graph properties we performed confirmed the possibility of building efficient XML data storages which contain hundreds of petabytes of data.

Abstract: A novel 3D shape preserving data reduction technique for managing the amount of data acquired by laser scanning is presented that overcomes the shortcomings of existing filter-based methods. The technique is based on a discrete Gaussian image of the scanned points which is obtained by estimating surface normals and projecting them into a Gaussian sphere. The discrete Gaussian image is then used to partition the points into cells. In each cell, a reference point and its neighbours are used to determine the cell representative point and all other points are removed. The performance of the proposed method is illustrated using a range of point clouds scanned from typical engineering surfaces.

Abstract: This research has the main objective of enhancing the Rational Unified Process to better address the emerging new Globalization and Internationalization requirements of modern software, focusing on integrating the Globalization Processes, Artifacts, Roles, Activities, and best practices into the Rational Unified Process (RUP). RUP is a well established Software Development Process (SDP) that intends to guarantee quality by controlling the project schedule, budget, communication, productivity, and trustworthiness. Meanwhile, the gRUP - produced in the coarse of this research - intends to guarantee that the developed software is ready for globalization, matches the required globalization and internationalization requirements, and ensures the implementation of best practices and tests to guarantee that the produced software is globalization ready. gRUP is constructed by incorporating essential globalization activities and artifacts into RUP, and incorporates an additional Globalization Discipline to the standard nine RUP disciplines.

Abstract: Artificial ventilation is an important treatment for the patients in the intensive care unit (ICU). An important step in building an efficient decision support system for intelligent ventilation is to develop a patient model. The patient model gives an idea of how the patient will behave under different ventilator settings. The feasibility of using neuro-fuzzy systems to model the physiology of the ventilated patient was assessed. Feature selection was also performed to explore other important input variables that could model the physiological state of the patients more accurately. Even though the overall patient model do not provide a good matched prediction of the patient's arterial oxygen tension, but it is still able to provide satisfactory arterial carbon dioxide tension predictions. This thus opens up new opportunity to model the ventilated patient.