A Method for Identifying Physical Parameters with Linear Fractional Transformation

This paper proposes a new parameter identification method based on Linear Fractional Transformation (LFT). It is assumed that the target linear system includes unknown parameters. The parameter deviations are separated from a nominal system via LFT, and identified by organizing I/O signals around the separated deviations of the real system. The purpose of this paper is to apply LFT to simultaneously identify the parameter deviations in systems with fewer outputs than unknown parameters. As a fundamental example, this method is implemented to one degree of freedom vibratory system. Via LFT, all physical parameters were simultaneously identified in this system. Then, numerical simulations were conducted for this system to verify the results. This study shows that all the physical parameters of a system with fewer outputs than unknown parameters can be effectively identified simultaneously using LFT.

Clustering based Voltage Control Areas for Localized Reactive Power Management in Deregulated Power System

In this paper, a new K-means clustering based approach for identification of voltage control areas is developed. Voltage control areas are important for efficient reactive power management in power systems operating under deregulated environment. Although, voltage control areas are formed using conventional hierarchical clustering based method, but the present paper investigate the capability of K-means clustering for the purpose of forming voltage control areas. The proposed method is tested and compared for IEEE 14 bus and IEEE 30 bus systems. The results show that this K-means based method is competing with conventional hierarchical approach

A Flexible and Scalable Agent Platform for Multi-Agent Systems

Multi-agent system is composed by several agents capable of reaching the goal cooperatively. The system needs an agent platform for efficient and stable interaction between intelligent agents. In this paper we propose a flexible and scalable agent platform by composing the containers with multiple hierarchical agent groups. It also allows efficient implementation of multiple domain presentations of the agents unlike JADE. The proposed platform provides both group management and individual management of agents for efficiency. The platform has been implemented and tested, and it can be used as a flexible foundation of the dynamic multi-agent system targeting seamless delivery of ubiquitous services.

Low Resolution Face Recognition Using Mixture of Experts

Human activity is a major concern in a wide variety of applications, such as video surveillance, human computer interface and face image database management. Detecting and recognizing faces is a crucial step in these applications. Furthermore, major advancements and initiatives in security applications in the past years have propelled face recognition technology into the spotlight. The performance of existing face recognition systems declines significantly if the resolution of the face image falls below a certain level. This is especially critical in surveillance imagery where often, due to many reasons, only low-resolution video of faces is available. If these low-resolution images are passed to a face recognition system, the performance is usually unacceptable. Hence, resolution plays a key role in face recognition systems. In this paper we introduce a new low resolution face recognition system based on mixture of expert neural networks. In order to produce the low resolution input images we down-sampled the 48 × 48 ORL images to 12 × 12 ones using the nearest neighbor interpolation method and after that applying the bicubic interpolation method yields enhanced images which is given to the Principal Component Analysis feature extractor system. Comparison with some of the most related methods indicates that the proposed novel model yields excellent recognition rate in low resolution face recognition that is the recognition rate of 100% for the training set and 96.5% for the test set.

A New Model of English-Vietnamese Bilingual Information Retrieval System

In this paper, we propose a new model of English- Vietnamese bilingual Information Retrieval system. Although there are so many CLIR systems had been researched and built, the accuracy of searching results in different languages that the CLIR system supports still need to improve, especially in finding bilingual documents. The problems identified in this paper are the limitation of machine translation-s result and the extra large collections of document to be found. So we try to establish a different model to overcome these problems.

Individual Learning and Collaborative Knowledge Building with Shared Digital Artifacts

The development of Internet technology in recent years has led to a more active role of users in creating Web content. This has significant effects both on individual learning and collaborative knowledge building. This paper will present an integrative framework model to describe and explain learning and knowledge building with shared digital artifacts on the basis of Luhmann-s systems theory and Piaget-s model of equilibration. In this model, knowledge progress is based on cognitive conflicts resulting from incongruities between an individual-s prior knowledge and the information which is contained in a digital artifact. Empirical support for the model will be provided by 1) applying it descriptively to texts from Wikipedia, 2) examining knowledge-building processes using a social network analysis, and 3) presenting a survey of a series of experimental laboratory studies.

Modeling and Performance Evaluation of LTE Networks with Different TCP Variants

Long Term Evolution (LTE) is a 4G wireless broadband technology developed by the Third Generation Partnership Project (3GPP) release 8, and it's represent the competitiveness of Universal Mobile Telecommunications System (UMTS) for the next 10 years and beyond. The concepts for LTE systems have been introduced in 3GPP release 8, with objective of high-data-rate, low-latency and packet-optimized radio access technology. In this paper, performance of different TCP variants during LTE network investigated. The performance of TCP over LTE is affected mostly by the links of the wired network and total bandwidth available at the serving base station. This paper describes an NS-2 based simulation analysis of TCP-Vegas, TCP-Tahoe, TCPReno, TCP-Newreno, TCP-SACK, and TCP-FACK, with full modeling of all traffics of LTE system. The Evaluation of the network performance with all TCP variants is mainly based on throughput, average delay and lost packet. The analysis of TCP performance over LTE ensures that all TCP's have a similar throughput and the best performance return to TCP-Vegas than other variants.

Inheritance Growth: a Biology Inspired Method to Build Structures in P2P

IT infrastructures are becoming more and more difficult. Therefore, in the first industrial IT systems, the P2P paradigm has replaced the traditional client server and methods of self-organization are gaining more and more importance. From the past it is known that especially regular structures like grids may significantly improve the system behavior and performance. This contribution introduces a new algorithm based on a biologic analogue, which may provide the growth of several regular structures on top of anarchic grown P2P- or social network structures.

FPGA Based Parallel Architecture for the Computation of Third-Order Cross Moments

Higher-order Statistics (HOS), also known as cumulants, cross moments and their frequency domain counterparts, known as poly spectra have emerged as a powerful signal processing tool for the synthesis and analysis of signals and systems. Algorithms used for the computation of cross moments are computationally intensive and require high computational speed for real-time applications. For efficiency and high speed, it is often advantageous to realize computation intensive algorithms in hardware. A promising solution that combines high flexibility together with the speed of a traditional hardware is Field Programmable Gate Array (FPGA). In this paper, we present FPGA-based parallel architecture for the computation of third-order cross moments. The proposed design is coded in Very High Speed Integrated Circuit (VHSIC) Hardware Description Language (VHDL) and functionally verified by implementing it on Xilinx Spartan-3 XC3S2000FG900-4 FPGA. Implementation results are presented and it shows that the proposed design can operate at a maximum frequency of 86.618 MHz.

The Study of the Interaction between Catanionic Surface Micelle SDS-CTAB and Insulin at Air/Water Interface

Herein, we report the different types of surface morphology due to the interaction between the pure protein Insulin (INS) and catanionic surfactant mixture of Sodium Dodecyl Sulfate (SDS) and Cetyl Trimethyl Ammonium Bromide (CTAB) at air/water interface obtained by the Langmuir-Blodgett (LB) technique. We characterized the aggregations by Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR) in LB films. We found that the INS adsorption increased in presence of catanionic surfactant at air/water interface. The presence of small amount of surfactant induces two-stage growth kinetics due to the pure protein absorption and protein-catanionic surface micelle interaction. The protein remains in native state in presence of small amount of surfactant mixture. Smaller amount of surfactant mixture with INS is producing surface micelle type structure. This may be considered for drug delivery system. On the other hand, INS becomes unfolded and fibrillated in presence of higher amount of surfactant mixture. In both the cases, the protein was successfully immobilized on a glass substrate by the LB technique. These results may find applications in the fundamental science of the physical chemistry of surfactant systems, as well as in the preparation of drug-delivery system.

Demand and Supply Chain Simulation in Telecommunication Industry by Multi-Rate Expert Systems

In modern telecommunications industry, demand & supply chain management (DSCM) needs reliable design and versatile tools to control the material flow. The objective for efficient DSCM is reducing inventory, lead times and related costs in order to assure reliable and on-time deliveries from manufacturing units towards customers. In this paper the multi-rate expert system based methodology for developing simulation tools that would enable optimal DSCM for multi region, high volume and high complexity manufacturing environment was proposed.

Phase Noise Impact on BER in Space Communication

This paper deals with the modeling and the evaluation of a multiplicative phase noise influence on the bit error ratio in a general space communication system. Our research is focused on systems with multi-state phase shift keying modulation techniques and it turns out, that the phase noise significantly affects the bit error rate, especially for higher signal to noise ratios. These results come from a system model created in Matlab environment and are shown in a form of constellation diagrams and bit error rate dependencies. The change of a user data bit rate is also considered and included into simulation results. Obtained outcomes confirm theoretical presumptions.

A Complexity Measure for Java Bean based Software Components

The traditional software product and process metrics are neither suitable nor sufficient in measuring the complexity of software components, which ultimately is necessary for quality and productivity improvement within organizations adopting CBSE. Researchers have proposed a wide range of complexity metrics for software systems. However, these metrics are not sufficient for components and component-based system and are restricted to the module-oriented systems and object-oriented systems. In this proposed study it is proposed to find the complexity of the JavaBean Software Components as a reflection of its quality and the component can be adopted accordingly to make it more reusable. The proposed metric involves only the design issues of the component and does not consider the packaging and the deployment complexity. In this way, the software components could be kept in certain limit which in turn help in enhancing the quality and productivity.

System Identification Based on Stepwise Regression for Dynamic Market Representation

A system for market identification (SMI) is presented. The resulting representations are multivariable dynamic demand models. The market specifics are analyzed. Appropriate models and identification techniques are chosen. Multivariate static and dynamic models are used to represent the market behavior. The steps of the first stage of SMI, named data preprocessing, are mentioned. Next, the second stage, which is the model estimation, is considered in more details. Stepwise linear regression (SWR) is used to determine the significant cross-effects and the orders of the model polynomials. The estimates of the model parameters are obtained by a numerically stable estimator. Real market data is used to analyze SMI performance. The main conclusion is related to the applicability of multivariate dynamic models for representation of market systems.

Model of Continuous Cheese Whey Fermentation by Candida Pseudotropicalis

The utilization of cheese whey as a fermentation substrate to produce bio-ethanol is an effort to supply bio-ethanol demand as a renewable energy. Like other process systems, modeling is also required for fermentation process design, optimization and plant operation. This research aims to study the fermentation process of cheese whey by applying mathematics and fundamental concept in chemical engineering, and to investigate the characteristic of the cheese whey fermentation process. Steady state simulation results for inlet substrate concentration of 50, 100 and 150 g/l, and various values of hydraulic retention time, showed that the ethanol productivity maximum values were 0.1091, 0.3163 and 0.5639 g/l.h respectively. Those values were achieved at hydraulic retention time of 20 hours, which was the minimum value used in this modeling. This showed that operating reactor at low hydraulic retention time was favorable. Model of bio-ethanol production from cheese whey will enhance the understanding of what really happen in the fermentation process.

Design and Implementation of a Hybrid Fuzzy Controller for a High-Performance Induction

This paper proposes an effective algorithm approach to hybrid control systems combining fuzzy logic and conventional control techniques of controlling the speed of induction motor assumed to operate in high-performance drives environment. The introducing of fuzzy logic in the control systems helps to achieve good dynamical response, disturbance rejection and low sensibility to parameter variations and external influences. Some fundamentals of the fuzzy logic control are preliminary illustrated. The developed control algorithm is robust, efficient and simple. It also assures precise trajectory tracking with the prescribed dynamics. Experimental results have shown excellent tracking performance of the proposed control system, and have convincingly demonstrated the validity and the usefulness of the hybrid fuzzy controller in high-performance drives with parameter and load uncertainties. Satisfactory performance was observed for most reference tracks.

TSM: A Design Pattern to Make Ad-hoc BPMs Easy and Inexpensive in Workflow-aware MISs

Despite so many years- development, the mainstream of workflow solutions from IT industries has not made ad-hoc workflow-support easy or inexpensive in MIS. Moreover, most of academic approaches tend to make their resulted BPM (Business Process Management) more complex and clumsy since they used to necessitate modeling workflow. To cope well with various ad-hoc or casual requirements on workflows while still keeping things simple and inexpensive, the author puts forth first the TSM design pattern that can provide a flexible workflow control while minimizing demand of predefinitions and modeling workflow, which introduces a generic approach for building BPM in workflow-aware MISs (Management Information Systems) with low development and running expenses.

Modeling Oxygen-transfer by Multiple Plunging Jets using Support Vector Machines and Gaussian Process Regression Techniques

The paper investigates the potential of support vector machines and Gaussian process based regression approaches to model the oxygen–transfer capacity from experimental data of multiple plunging jets oxygenation systems. The results suggest the utility of both the modeling techniques in the prediction of the overall volumetric oxygen transfer coefficient (KLa) from operational parameters of multiple plunging jets oxygenation system. The correlation coefficient root mean square error and coefficient of determination values of 0.971, 0.002 and 0.945 respectively were achieved by support vector machine in comparison to values of 0.960, 0.002 and 0.920 respectively achieved by Gaussian process regression. Further, the performances of both these regression approaches in predicting the overall volumetric oxygen transfer coefficient was compared with the empirical relationship for multiple plunging jets. A comparison of results suggests that support vector machines approach works well in comparison to both empirical relationship and Gaussian process approaches, and could successfully be employed in modeling oxygen-transfer.

The Data Mining usage in Production System Management

The paper gives the pilot results of the project that is oriented on the use of data mining techniques and knowledge discoveries from production systems through them. They have been used in the management of these systems. The simulation models of manufacturing systems have been developed to obtain the necessary data about production. The authors have developed the way of storing data obtained from the simulation models in the data warehouse. Data mining model has been created by using specific methods and selected techniques for defined problems of production system management. The new knowledge has been applied to production management system. Gained knowledge has been tested on simulation models of the production system. An important benefit of the project has been proposal of the new methodology. This methodology is focused on data mining from the databases that store operational data about the production process.

Behavior and Strength of Slab-Edge Beam-Column Connections under Shear Force and Moment

A total of fourteen slab-edge beam-column connection specimens were tested gradually to failure under the effect of simultaneous action of shear force and moment. The objective was to investigate the influence of some parameters thought to be important on the behavior and strength of slab-column connections with edge beams encountered in flat slab flooring and roofing systems. The parameters included the existence and strength of edge beam, depth and width of edge beam, steel reinforcement ratio of slab, ratio of moment to shear force, and the existence of openings in the region next to the column. Results obtained demonstrated the importance of the studied parameters on the strength and behavior of slab-column connections with edge beams.