An Approach to Concerns and Aspects Mining for Web Applications

Web applications have become very complex and crucial, especially when combined with areas such as CRM (Customer Relationship Management) and BPR (Business Process Reengineering), the scientific community has focused attention to Web applications design, development, analysis, and testing, by studying and proposing methodologies and tools. This paper proposes an approach to automatic multi-dimensional concern mining for Web Applications, based on concepts analysis, impact analysis, and token-based concern identification. This approach lets the user to analyse and traverse Web software relevant to a particular concern (concept, goal, purpose, etc.) via multi-dimensional separation of concerns, to document, understand and test Web applications. This technique was developed in the context of WAAT (Web Applications Analysis and Testing) project. A semi-automatic tool to support this technique is currently under development.

Full-genomic Network Inference for Non-model organisms: A Case Study for the Fungal Pathogen Candida albicans

Reverse engineering of full-genomic interaction networks based on compendia of expression data has been successfully applied for a number of model organisms. This study adapts these approaches for an important non-model organism: The major human fungal pathogen Candida albicans. During the infection process, the pathogen can adapt to a wide range of environmental niches and reversibly changes its growth form. Given the importance of these processes, it is important to know how they are regulated. This study presents a reverse engineering strategy able to infer fullgenomic interaction networks for C. albicans based on a linear regression, utilizing the sparseness criterion (LASSO). To overcome the limited amount of expression data and small number of known interactions, we utilize different prior-knowledge sources guiding the network inference to a knowledge driven solution. Since, no database of known interactions for C. albicans exists, we use a textmining system which utilizes full-text research papers to identify known regulatory interactions. By comparing with these known regulatory interactions, we find an optimal value for global modelling parameters weighting the influence of the sparseness criterion and the prior-knowledge. Furthermore, we show that soft integration of prior-knowledge additionally improves the performance. Finally, we compare the performance of our approach to state of the art network inference approaches.

Web Server with Multi-Agent Support for Medical Practitioners by JADE Technology

The multi-agent system for processing Bio-signals will help the medical practitioners to have a standard examination procedure stored in web server. Web Servers supporting any standard Search Engine follow all possible combinations of the search keywords as an input by the user to a Search Engine. As a result, a huge number of Web-pages are shown in the Web browser. It also helps the medical practitioner to interact with the expert in the field his need in order to make a proper judgment in the diagnosis phase [3].A web server uses a web server plug in to establish and maintained the medical practitioner to make a fast analysis. If the user uses the web server client can get a related data requesting their search. DB agent, EEG / ECG / EMG agents- user placed with difficult aspects for updating medical information-s in web server.

Software Engineering Interoperable Environment for University Process Workflow and Document Management

The objective of the research was focused on the design, development and evaluation of a sustainable web based network system to be used as an interoperable environment for University process workflow and document management. In this manner the most of the process workflows in Universities can be entirely realized electronically and promote integrated University. Definition of the most used University process workflows enabled creating electronic workflows and their execution on standard workflow execution engines. Definition or reengineering of workflows provided increased work efficiency and helped in having standardized process through different faculties. The concept and the process definition as well as the solution applied as Case study are evaluated and findings are reported.

Evaluation and Analysis of Lean-Based Manufacturing Equipment and Technology System for Jordanian Industries

International markets driven forces are changing continuously, therefore companies need to gain a competitive edge in such markets. Improving the company's products, processes and practices is no longer auxiliary. Lean production is a production management philosophy that consolidates work tasks with minimum waste resulting in improved productivity. Lean production practices can be mapped into many production areas. One of these is Manufacturing Equipment and Technology (MET). Many lean production practices can be implemented in MET, namely, specific equipment configurations, total preventive maintenance, visual control, new equipment/ technologies, production process reengineering and shared vision of perfection.The purpose of this paper is to investigate the implementation level of these six practices in Jordanian industries. To achieve that a questionnaire survey has been designed according to five-point Likert scale. The questionnaire is validated through pilot study and through experts review. A sample of 350 Jordanian companies were surveyed, the response rate was 83%. The respondents were asked to rate the extent of implementation for each of practices. A relationship conceptual model is developed, hypotheses are proposed, and consequently the essential statistical analyses are then performed. An assessment tool that enables management to monitor the progress and the effectiveness of lean practices implementation is designed and presented. Consequently, the results show that the average implementation level of lean practices in MET is 77%, Jordanian companies are implementing successfully the considered lean production practices, and the presented model has Cronbach-s alpha value of 0.87 which is good evidence on model consistency and results validation.

Comparative Study of Sedimentation in Hydraulic Structures using Sharc and Ssiim Soft Wares - A Case of the Dez and Hamidieh Intake Structures in Iran

Sedimentation formation is a complex hydraulic phenomenon that has emerged as a major operational and maintenance consideration in modern hydraulic engineering in general and river engineering in particular. Sediments accumulation along the river course and their eventual storage in a form of islands affect water intake in the canal systems that are fed by the storage reservoirs. Without proper management, sediment transport can lead to major operational challenges in water distribution system of arid regions like the Dez and Hamidieh command areas. The paper aims to investigate sedimentation in the Western Canal of Dez Diversion Weir using the SHARC model and compare the results with the two intake structures of the Hamidieh dam in Iran using SSIIM model. The objective was to identify the factors which influence the process, check reliability of outcome and provide ways in which to mitigate the implications on operation and maintenance of the structures. Results estimated sand and silt bed loads concentrations to be 193 ppm and 827ppm respectively. This followed ,ore or less similar pattern in Hamidieh where the sediment formation impeded water intake in the canal system. Given the available data on average annual bed loads and average suspended sediment loads of 165ppm and 837ppm in the Dez, there was a significant statistical difference (16%) between the sand grains, whereas no significant difference (1.2%) was find in the silt grain sizes. One explanation for such finding being that along the 6 Km river course there was considerable meandering effects which explains recent shift in the hydraulic behavior along the stream course under investigation. The sand concentration in downstream relative to present state of the canal showed a steep descending curve. Sediment trapping on the other hand indicated a steep ascending curve. These occurred because the diversion weir was not considered in the simulation model. The comparative study showed very close similarities in the results which explains the fact that both software can be used as accurate and reliable analytical tools for simulation of the sedimentation in hydraulic engineering.

Effect of Rotor to Casing Ratios with Different Rotor Vanes on Performance of Shaft Output of a Vane Type Novel Air Turbine

This paper deals with new concept of using compressed atmospheric air as a zero pollution power source for running motorbikes. The motorbike is equipped with an air turbine in place of an internal combustion engine, and transforms the energy of the compressed air into shaft work. The mathematical modeling and performance evaluation of a small capacity compressed air driven vaned type novel air turbine is presented in this paper. The effect of isobaric admission and adiabatic expansion of high pressure air for different rotor to casing diameter ratios with respect to different vane angles (number of vanes) have been considered and analyzed. It is found that the shaft work output is optimum for some typical values of rotor / casing diameter ratios at a particular value of vane angle (no. of vanes). In this study, the maximum power is obtained as 4.5kW - 5.3kW (5.5-6.25 HP) when casing diameter is taken 100 mm, and rotor to casing diameter ratios are kept from 0.65 to 0.55. This value of output is sufficient to run motorbike.

Engine Power Effects on Support Interference

Renewed interest in propeller propulsion on aircraft configurations combined with higher propeller loads lead to the question how the effects of the propulsion on model support disturbances should be accounted for. In this paper, the determination of engine power effects on support interference of sting-mounted models is demonstrated by a measurement on a four-engine turboprop aircraft. CFD results on a more generic model are presented in order to clarify the possible mechanism behind engine power effects on support interference. The engine slipstream induces a local change in angle of sideslip at the model sting thereby influencing the sting near-field and far-field effects. Whether or not the net result of these changes in the disturbance pattern leads to a significant engine power effect depends on the configuration of the wind tunnel model and the test setup.

Magnetic Field Analysis for a Distribution Transformer with Unbalanced Load Conditions by using 3-D Finite Element Method

This paper proposes a set of quasi-static mathematical model of magnetic fields caused by high voltage conductors of distribution transformer by using a set of second-order partial differential equation. The modification for complex magnetic field analysis and time-harmonic simulation are also utilized. In this research, transformers were study in both balanced and unbalanced loading conditions. Computer-based simulation utilizing the threedimensional finite element method (3-D FEM) is exploited as a tool for visualizing magnetic fields distribution volume a distribution transformer. Finite Element Method (FEM) is one among popular numerical methods that is able to handle problem complexity in various forms. At present, the FEM has been widely applied in most engineering fields. Even for problems of magnetic field distribution, the FEM is able to estimate solutions of Maxwell-s equations governing the power transmission systems. The computer simulation based on the use of the FEM has been developed in MATLAB programming environment.

Exploiting Machine Learning Techniques for the Enhancement of Acceptance Sampling

This paper proposes an innovative methodology for Acceptance Sampling by Variables, which is a particular category of Statistical Quality Control dealing with the assurance of products quality. Our contribution lies in the exploitation of machine learning techniques to address the complexity and remedy the drawbacks of existing approaches. More specifically, the proposed methodology exploits Artificial Neural Networks (ANNs) to aid decision making about the acceptance or rejection of an inspected sample. For any type of inspection, ANNs are trained by data from corresponding tables of a standard-s sampling plan schemes. Once trained, ANNs can give closed-form solutions for any acceptance quality level and sample size, thus leading to an automation of the reading of the sampling plan tables, without any need of compromise with the values of the specific standard chosen each time. The proposed methodology provides enough flexibility to quality control engineers during the inspection of their samples, allowing the consideration of specific needs, while it also reduces the time and the cost required for these inspections. Its applicability and advantages are demonstrated through two numerical examples.

Study on Scheduling of the Planning Method Using the Web-based Visualization System in a Shipbuilding Block Assembly Shop

Higher productivity and less cost in the ship manufacturing process are required to maintain the international competitiveness of morden manufacturing industries. In shipbuilding, however, the Engineering To Order (ETO) production method and production process is very difficult. Thus, designs change frequently. In accordance with production, planning should be set up according to scene changes. Therefore, fixed production planning is very difficult. Thus, a scheduler must first make sketchy plans, then change the plans based on the work progress and modifications. Thus, data sharing in a shipbuilding block assembly shop is very important. In this paper, we proposed to scheduling method applicable to the shipbuilding industry and decision making support system through web based visualization system.

The Micro Ecosystem Restoration Mechanism Applied for Feasible Research of Lakes Eutrophication Enhancement

The technique of inducing micro ecosystem restoration is one of aquatic ecology engineering methods used to retrieve the polluted water. Batch scale study, pilot plant study, and field study were carried out to observe the eutrophication using the Inducing Ecology Restorative Symbiosis Agent (IERSA) consisting mainly degraded products by using lactobacillus, saccharomycete, and phycomycete. The results obtained from the experiments of the batch scale and pilot plant study allowed us to development the parameters for the field study. A pond, 5 m to the outlet of a lake, with an area of 500 m2 and depth of 0.6-1.2 m containing about 500 tons of water was selected as a model. After the treatment with 10 mg IERSA/L water twice a week for 70 days, the micro restoration mechanisms consisted of three stages (i.e., restoration, impact maintenance, and ecology recovery experiment after impact). The COD, TN, TKN, and chlorophyll a were reduced significantly in the first week. Although the unexpected heavy rain and contaminate from sewage system might slow the ecology restoration. However, the self-cleaning function continued and the chlorophyll a reduced for 50% in one month. In the 4th week, amoeba, paramecium, rotifer, and red wriggle worm reappeared, and the number of fish flies appeared up to1000 fish fries/m3. Those results proved that inducing restorative mechanism can be applied to improve the eutrophication and to control the growth of algae in the lakes by gaining the selfcleaning through inducing and competition of microbes. The situation for growth of fishes also can reach an excellent result due to the improvement of water quality.

Performance Modeling and Availability Analysis of Yarn Dyeing System of a Textile Industry

This paper discusses the performance modeling and availability analysis of Yarn Dyeing System of a Textile Industry. The Textile Industry is a complex and repairable engineering system. Yarn Dyeing System of Textile Industry consists of five subsystems arranged in series configuration. For performance modeling and analysis of availability, a performance evaluating model has been developed with the help of mathematical formulation based on Markov-Birth-Death Process. The differential equations have been developed on the basis of Probabilistic Approach using a Transition Diagram. These equations have further been solved using normalizing condition in order to develop the steady state availability, a performance measure of the system concerned. The system performance has been further analyzed with the help of decision matrices. These matrices provide various availability levels for different combinations of failure and repair rates for various subsystems. The findings of this paper are therefore, considered to be useful for the analysis of availability and determination of the best possible maintenance strategies which can be implemented in future to enhance the system performance.

Development of a Methodology for Processing of Drilling Operations

Drilling is the most common machining operation and it forms the highest machining cost in many manufacturing activities including automotive engine production. The outcome of this operation depends upon many factors including utilization of proper cutting tool geometry, cutting tool material and the type of coating used to improve hardness and resistance to wear, and also cutting parameters. With the availability of a large array of tool geometries, materials and coatings, is has become a challenging task to select the best tool and cutting parameters that would result in the lowest machining cost or highest profit rate. This paper describes an algorithm developed to help achieve good performances in drilling operations by automatically determination of proper cutting tools and cutting parameters. It also helps determine machining sequences resulting in minimum tool changes that would eventually reduce machining time and cost where multiple tools are used.

Characteristics Analysis of Voltage Sag and Voltage Swell in Multi-Grounded Four-Wire Power Distribution Systems

In North America, Most power distribution systems employ a four-wire multi-grounded neutral (MGN) design. This paper has explained the inherent characteristics of multi-grounded three-phase four-wire distribution systems under unbalanced situations. As a result, the mechanism of voltage swell and voltage sag in MGN feeders becomes difficult to understand. The simulation tool that has been used in this paper is MATLAB under Windows software. In this paper the equivalent model of a full-scale multigrounded distribution system implemented by MATLAB is introduced. The results are expected to help utility engineers to understand the impact of MGN on distribution system operations.

The Spiral_OWL Model – Towards Spiral Knowledge Engineering

The Spiral development model has been used successfully in many commercial systems and in a good number of defense systems. This is due to the fact that cost-effective incremental commitment of funds, via an analogy of the spiral model to stud poker and also can be used to develop hardware or integrate software, hardware, and systems. To support adaptive, semantic collaboration between domain experts and knowledge engineers, a new knowledge engineering process, called Spiral_OWL is proposed. This model is based on the idea of iterative refinement, annotation and structuring of knowledge base. The Spiral_OWL model is generated base on spiral model and knowledge engineering methodology. A central paradigm for Spiral_OWL model is the concentration on risk-driven determination of knowledge engineering process. The collaboration aspect comes into play during knowledge acquisition and knowledge validation phase. Design rationales for the Spiral_OWL model are to be easy-to-implement, well-organized, and iterative development cycle as an expanding spiral.

WebGD: A CORBA-based Document Classification and Retrieval System on the Web

This paper presents the design and implementation of the WebGD, a CORBA-based document classification and retrieval system on Internet. The WebGD makes use of such techniques as Web, CORBA, Java, NLP, fuzzy technique, knowledge-based processing and database technology. Unified classification and retrieval model, classifying and retrieving with one reasoning engine and flexible working mode configuration are some of its main features. The architecture of WebGD, the unified classification and retrieval model, the components of the WebGD server and the fuzzy inference engine are discussed in this paper in detail.

Revisiting the Concept of Risk Analysis within the Context of Geospatial Database Design: A Collaborative Framework

The aim of this research is to design a collaborative framework that integrates risk analysis activities into the geospatial database design (GDD) process. Risk analysis is rarely undertaken iteratively as part of the present GDD methods in conformance to requirement engineering (RE) guidelines and risk standards. Accordingly, when risk analysis is performed during the GDD, some foreseeable risks may be overlooked and not reach the output specifications especially when user intentions are not systematically collected. This may lead to ill-defined requirements and ultimately in higher risks of geospatial data misuse. The adopted approach consists of 1) reviewing risk analysis process within the scope of RE and GDD, 2) analyzing the challenges of risk analysis within the context of GDD, and 3) presenting the components of a risk-based collaborative framework that improves the collection of the intended/forbidden usages of the data and helps geo-IT experts to discover implicit requirements and risks.

A Microcontroller Implementation of Model Predictive Control

Model Predictive Control (MPC) is increasingly being proposed for real time applications and embedded systems. However comparing to PID controller, the implementation of the MPC in miniaturized devices like Field Programmable Gate Arrays (FPGA) and microcontrollers has historically been very small scale due to its complexity in implementation and its computation time requirement. At the same time, such embedded technologies have become an enabler for future manufacturing enterprises as well as a transformer of organizations and markets. Recently, advances in microelectronics and software allow such technique to be implemented in embedded systems. In this work, we take advantage of these recent advances in this area in the deployment of one of the most studied and applied control technique in the industrial engineering. In fact in this paper, we propose an efficient framework for implementation of Generalized Predictive Control (GPC) in the performed STM32 microcontroller. The STM32 keil starter kit based on a JTAG interface and the STM32 board was used to implement the proposed GPC firmware. Besides the GPC, the PID anti windup algorithm was also implemented using Keil development tools designed for ARM processor-based microcontroller devices and working with C/Cµ langage. A performances comparison study was done between both firmwares. This performances study show good execution speed and low computational burden. These results encourage to develop simple predictive algorithms to be programmed in industrial standard hardware. The main features of the proposed framework are illustrated through two examples and compared with the anti windup PID controller.

Assessing the Effect of Thermodynamic, Hydrodynamic and Geometric of an Air Cooled Condenser on COP of Vapor Compression Cycle

In this paper, the effects of thermodynamic, hydrodynamic and geometric of an air cooled condenser on COP of vapor compression cycle are investigated for a fixed condenser facing surface area. The system is utilized with a scroll compressor, modeled based on thermodynamic and heat transfer equations employing Matlab software. The working refrigerant is R134a whose thermodynamic properties are called from Engineering Equation Software. This simulation shows that vapor compression cycle can be designed by different configurations and COPs, economical and optimum working condition can be obtained via considering these parameters.