The Impact of Semantic Web on E-Commerce

Semantic Web Technologies enable machines to interpret data published in a machine-interpretable form on the web. At the present time, only human beings are able to understand the product information published online. The emerging semantic Web technologies have the potential to deeply influence the further development of the Internet Economy. In this paper we propose a scenario based research approach to predict the effects of these new technologies on electronic markets and business models of traders and intermediaries and customers. Over 300 million searches are conducted everyday on the Internet by people trying to find what they need. A majority of these searches are in the domain of consumer ecommerce, where a web user is looking for something to buy. This represents a huge cost in terms of people hours and an enormous drain of resources. Agent enabled semantic search will have a dramatic impact on the precision of these searches. It will reduce and possibly eliminate information asymmetry where a better informed buyer gets the best value. By impacting this key determinant of market prices semantic web will foster the evolution of different business and economic models. We submit that there is a need for developing these futuristic models based on our current understanding of e-commerce models and nascent semantic web technologies. We believe these business models will encourage mainstream web developers and businesses to join the “semantic web revolution."

The Impact of High Performance Work Systems- on Firm Performance in MNCs and Local Manufacturing Firms in Malaysia

The empirical studies on High Performance Work Systems (HPWSs) and their impacts on firm performance have remarkably little in the developing countries. This paper reviews literatures on the HPWSs practices in different work settings, Western and Asian countries. A review on the empirical research leads to a conclusion that, country differences influence the Human Resource Management (HRM) practices. It is anticipated that there are similarities and differences in the extent of implementation of HPWSs practices by the Malaysian manufacturing firms due to the organizational contextual factors and, the HPWSs have a significant impact on firms- better performance amongst MNCs and local firms.

Switched Reluctance Generator for Wind Power Applications

Green house effect has becomes a serious concern in many countries due to the increase consumption of the fossil fuel. There have been many studies to find an alternative power source. Wind energy found to be one of the most useful solutions to help in overcoming the air pollution and global. There is no agreed solution to conversion of wind energy to electrical energy. In this paper, the advantages of using a Switched Reluctance Generator (SRG) for wind energy applications. The theoretical study of the self excitation of a SRG and the determination of the variable parameters in a SRG design are discussed. The design parameters for the maximum power output of the SRG are computed using Matlab simulation. The designs of the circuit to control the variable parameters in a SRG to provide the maximum power output are also discussed.

A Subtractive Clustering Based Approach for Early Prediction of Fault Proneness in Software Modules

In this paper, subtractive clustering based fuzzy inference system approach is used for early detection of faults in the function oriented software systems. This approach has been tested with real time defect datasets of NASA software projects named as PC1 and CM1. Both the code based model and joined model (combination of the requirement and code based metrics) of the datasets are used for training and testing of the proposed approach. The performance of the models is recorded in terms of Accuracy, MAE and RMSE values. The performance of the proposed approach is better in case of Joined Model. As evidenced from the results obtained it can be concluded that Clustering and fuzzy logic together provide a simple yet powerful means to model the earlier detection of faults in the function oriented software systems.

A Framework for Personalized Multi-Device Information Communicating System

Due to the mobility of users, many information systems are now developed with the capability of supporting retrieval of information from both static and mobile users. Hence, the amount, content and format of the information retrieved will need to be tailored according to the device and the user who requested for it. Thus, this paper presents a framework for the design and implementation of such a system, which is to be developed for communicating final examination related information to the academic community at one university in Malaysia. The concept of personalization will be implemented in the system so that only highly relevant information will be delivered to the users. The personalization concept used will be based on user profiling as well as context. The system in its final state will be accessible through cell phones as well as intranet connected personal computers.

Anaerobic Treatment of Produced Water

An experimental study of anaerobic treatment was performed by hybrid upflow anaerobic sludge blanket (HUASB) reactor to treat produced water (PW) of an onshore crude oil terminal (COD: 1597 mg/L, NH3-N: 14.7 mg/L, phenol: 13.8 mg/L, BOD5: 862 mg/L, sodium: 6240 mg/L and chloride 9530 mg/L). The produced water with high salinity and other toxic substances will inhibit the methanogens performance if there is no adaptation on biomass before anaerobic digestion. COD removal from produced water was investigated at five different dilutions of produced water and tap water (TW) without any nutrient addition and pre-treatment. The dilution ratios were 1PW:4TW, 2PW:3TW, 3PW:2TW, 4PW:1TW and 5PW:0TW. The reactor was evaluated at mesophilic operating condition (35 ± 2 °C) at 5 days of HRT for 250 days continuous feed. The average COD removals for 1PW:4TW, 2PW:3TW, 3PW:2TW, 4PW:1TW and 5PW:0TW were found to be approximately 76.1%, 73.8%, 70.3%, 46.3% and 61.82% respectively, with final average effluent COD of 123.7 mg/L, 240 mg/L, 294 mg/L, 589 mg/L and 738 mg/L, respectively.

Sequence-based Prediction of Gamma-turn Types using a Physicochemical Property-based Decision Tree Method

The γ-turns play important roles in protein folding and molecular recognition. The prediction and analysis of γ-turn types are important for both protein structure predictions and better understanding the characteristics of different γ-turn types. This study proposed a physicochemical property-based decision tree (PPDT) method to interpretably predict γ-turn types. In addition to the good prediction performance of PPDT, three simple and human interpretable IF-THEN rules are extracted from the decision tree constructed by PPDT. The identified informative physicochemical properties and concise rules provide a simple way for discriminating and understanding γ-turn types.

Disinfection of Water by Adsorption with Electrochemical Regeneration

Arvia®, a spin-out company of University of Manchester, UK is commercialising a water treatment technology for the removal of low concentrations of organics from water. This technology is based on the adsorption of organics onto graphite based adsorbents coupled with their electrochemical regeneration in a simple electrochemical cell. In this paper, the potential of the process to adsorb microorganisms and electrochemically disinfect them present in water has been demonstrated. Bench scale experiments have indicated that the process of adsorption using graphite adsorbents with electrochemical regeneration can be used for water disinfection effectively. The most likely mechanisms of disinfection of water through this process include direct electrochemical oxidation and electrochemical chlorination.

Antibiotic Resistance Profile of Bacterial Isolates from Animal Farming Aquatic Environments and Meats in a Peri-Urban Community in South Korea

The increasing usage of antibiotics in the animal farming industry is an emerging worldwide problem contributing to the development of antibiotic resistance. The purpose of this work was to investigate the prevalence and antibiotic resistance profile of bacterial isolates collected from aquatic environments and meats in a peri-urban community in Daejeon, Korea. In an antibacterial susceptibility test, the bacterial isolates showed a high incidence of resistance (~ 26.04 %) to cefazolin, tetracycline, gentamycin, norfloxacin, erythromycin and vancomycin. The results from a test for multiple antibiotic resistance indicated that the isolates were displaying an approximately 5-fold increase in the incidence of multiple antibiotic resistance to combinations of two different antibiotics compared to combinations of three or more antibiotics. Most of the isolates showed multi-antibiotic resistance, and the resistance patterns were similar among the sampling groups. Sequencing data analysis of 16S rRNA showed that most of the resistant isolates appeared to be dominated by the classes Betaproteobacteria and Gammaproteobacteria in the phylum Proteobacteria.

What Have Banks Done Wrong?

This paper aims to provide a conceptual framework to examine competitive disadvantage of banks that suffer from poor performance. Banks generate revenues mainly from the interest rate spread on taking deposits and making loans while collecting fees in the process. To maximize firm value, banks seek loan growth and expense control while managing risk associated with loans with respect to non-performing borrowers or narrowing interest spread between assets and liabilities. Competitive disadvantage refers to the failure to access imitable resources and to build managing capabilities to gain sustainable return given appropriate risk management. This paper proposes a four-quadrant framework of organizational typology is subsequently proposed to examine the features of competitive disadvantage in the banking sector. A resource configuration model, which is extracted from CAMEL indicators to examine the underlying features of bank failures.

Real Time Monitoring of Long Slender Shaft by Distributed-Lumped Modeling Techniques

The aim of this paper is to determine the stress levels at the end of a long slender shaft such as a drilling assembly used in the oil or gas industry using a mathematical model in real-time. The torsional deflection experienced by this type of drilling shaft (about 4 KM length and 20 cm diameter hollow shaft with a thickness of 1 cm) can only be determined using a distributed modeling technique. The main objective of this project is to calculate angular velocity and torque at the end of the shaft by TLM method and also analyzing of the behavior of the system by transient response. The obtained result is compared with lumped modeling technique the importance of these results will be evident only after the mentioned comparison. Two systems have different transient responses and in this project because of the length of the shaft transient response is very important.

Multilevel Fuzzy Decision Support Model for China-s Urban Rail Transit Planning Schemes

This paper aims at developing a multilevel fuzzy decision support model for urban rail transit planning schemes in China under the background that China is presently experiencing an unprecedented construction of urban rail transit. In this study, an appropriate model using multilevel fuzzy comprehensive evaluation method is developed. In the decision process, the followings are considered as the influential objectives: traveler attraction, environment protection, project feasibility and operation. In addition, consistent matrix analysis method is used to determine the weights between objectives and the weights between the objectives- sub-indictors, which reduces the work caused by repeated establishment of the decision matrix on the basis of ensuring the consistency of decision matrix. The application results show that multilevel fuzzy decision model can perfectly deal with the multivariable and multilevel decision process, which is particularly useful in the resolution of multilevel decision-making problem of urban rail transit planning schemes.

Network Intrusion Detection Design Using Feature Selection of Soft Computing Paradigms

The network traffic data provided for the design of intrusion detection always are large with ineffective information and enclose limited and ambiguous information about users- activities. We study the problems and propose a two phases approach in our intrusion detection design. In the first phase, we develop a correlation-based feature selection algorithm to remove the worthless information from the original high dimensional database. Next, we design an intrusion detection method to solve the problems of uncertainty caused by limited and ambiguous information. In the experiments, we choose six UCI databases and DARPA KDD99 intrusion detection data set as our evaluation tools. Empirical studies indicate that our feature selection algorithm is capable of reducing the size of data set. Our intrusion detection method achieves a better performance than those of participating intrusion detectors.

Improved Torque Control of Electrical Load Simulator with Parameters and State Estimation

ELS is an important ground based hardware in the loop simulator used for aerodynamics torque loading experiments of the actuators under test. This work focuses on improvement of the transient response of torque controller with parameters uncertainty of Electrical Load Simulator (ELS).The parameters of load simulator are estimated online and the model is updated, eliminating the model error and improving the steady state torque tracking response of torque controller. To improve the Transient control performance the gain of robust term of SMC is updated online using fuzzy logic system based on the amount of uncertainty in parameters of load simulator. The states of load simulator which cannot be measured directly are estimated using luenberger observer with update of new estimated parameters. The stability of the control scheme is verified using Lyapunov theorem. The validity of proposed control scheme is verified using simulations.

A New Solution for Natural Convection of Darcian Fluid about a Vertical Full Cone Embedded in Porous Media Prescribed Wall Temperature by using a Hybrid Neural Network-Particle Swarm Optimization Method

Fluid flow and heat transfer of vertical full cone embedded in porous media is studied in this paper. Nonlinear differential equation arising from similarity solution of inverted cone (subjected to wall temperature boundary conditions) embedded in porous medium is solved using a hybrid neural network- particle swarm optimization method. To aim this purpose, a trial solution of the differential equation is defined as sum of two parts. The first part satisfies the initial/ boundary conditions and does contain an adjustable parameter and the second part which is constructed so as not to affect the initial/boundary conditions and involves adjustable parameters (the weights and biases) for a multi-layer perceptron neural network. Particle swarm optimization (PSO) is applied to find adjustable parameters of trial solution (in first and second part). The obtained solution in comparison with the numerical ones represents a remarkable accuracy.

Estimating the Absorbed Dose to THYROID during Chest wall Radiotherapy

Thyroid cancer-s overall contribution to the worldwide cancer burden is relatively small, but incidence rates have increased over the last three decades throughout the world. This trend has been hypothesised to reflect a combination of technological advances enabling increased detection, but also changes in environmental factors, including population exposure to ionising radiation from fallout, diagnostic tests and treatment for benign and malignant conditions. The Thyroid dose received apparently shielded by cerrobend blocks was about 8cGy in 100cGy Expose

A Type of Urban Genesis in Romanian Outer-Carpathian Area: the Genoan Cities

The Mongol expansion in the West and the political and commercial interests arising from antagonisms between the Golden Horde and the Persian Ilkhanate determined the transformation of the Black Sea into an international trade turntable beginning with the last third of the XIIIth century. As the Volga Khanate attracted the maritime power of Genoa in the transcontinental project of deviating the Silk Road to its own benefit, the latter took full advantage of the new historical conjuncture, to the detriment of its rival, Venice. As a consequence, Genoa settled important urban centers on the Pontic shores, having mainly a commercial role. In the Romanian outer-Carpathian area, Vicina, Cetatea Albâ, and Chilia are notable, representing distinct, important types of cities within the broader context of the Romanian medieval urban genesis typology.

High-Speed Train Planning in France, Lessons from Mediterranean TGV-Line

To fight against the economic crisis, French Government, like many others in Europe, has decided to give a boost to high-speed line projects. This paper explores the implementation and decision-making process in TGV projects, their evolutions, especially since the Mediterranean TGV-line. This project was probably the most controversial, but paradoxically represents today a huge success for all the actors involved. What kind of lessons we can learn from this experience? How to evaluate the impact of this project on TGV-line planning? How can we characterize this implementation and decision-making process regards to the sustainability challenges? The construction of Mediterranean TGV-line was the occasion to make several innovations: to introduce more dialog into the decisionmaking process, to take into account the environment, to introduce a new project management and technological innovations. That-s why this project appears today as an example in terms of integration of sustainable development. In this paper we examine the different kinds of innovations developed in this project, by using concepts from sociology of innovation to understand how these solutions emerged in a controversial situation. Then we analyze the lessons which were drawn from this decision-making process (in the immediacy and a posteriori) and the way in which procedures evolved: creation of new tools and devices (public consultation, project management...). Finally we try to highlight the impact of this evolution on TGV projects governance. In particular, new methods of implementation and financing involve a reconfiguration of the system of actors. The aim of this paper is to define the impact of this reconfiguration on negotiations between stakeholders.

Analysis of DNA-Recognizing Enzyme Interaction using Deaminated Lesions

Deaminated lesions were produced via nitrosative oxidation of natural nucleobases; uracul (Ura, U) from cytosine (Cyt, C), hypoxanthine (Hyp, H) from adenine (Ade, A), and xanthine (Xan, X) and oxanine (Oxa, O) from guanine (Gua, G). Such damaged nucleobases may induce mutagenic problems, so that much attentions and efforts have been poured on the revealing of their mechanisms in vivo or in vitro. In this study, we employed these deaminated lesions as useful probes for analysis of DNA-binding/recognizing proteins or enzymes. Since the pyrimidine lesions such as Hyp, Oxa and Xan are employed as analogues of guanine, their comparative uses are informative for analyzing the role of Gua in DNA sequence in DNA-protein interaction. Several DNA oligomers containing such Hyp, Oxa or Xan substituted for Gua were designed to reveal the molecular interaction between DNA and protein. From this approach, we have got useful information to understand the molecular mechanisms of the DNA-recognizing enzymes, which have not ever been observed using conventional DNA oligomer composed of just natural nucleobases.

Application of the Data Distribution Service for Flexible Manufacturing Automation

This paper discusses the applicability of the Data Distribution Service (DDS) for the development of automated and modular manufacturing systems which require a flexible and robust communication infrastructure. DDS is an emergent standard for datacentric publish/subscribe middleware systems that provides an infrastructure for platform-independent many-to-many communication. It particularly addresses the needs of real-time systems that require deterministic data transfer, have low memory footprints and high robustness requirements. After an overview of the standard, several aspects of DDS are related to current challenges for the development of modern manufacturing systems with distributed architectures. Finally, an example application is presented based on a modular active fixturing system to illustrate the described aspects.