XML Schema Automatic Matching Solution

Schema matching plays a key role in many different applications, such as schema integration, data integration, data warehousing, data transformation, E-commerce, peer-to-peer data management, ontology matching and integration, semantic Web, semantic query processing, etc. Manual matching is expensive and error-prone, so it is therefore important to develop techniques to automate the schema matching process. In this paper, we present a solution for XML schema automated matching problem which produces semantic mappings between corresponding schema elements of given source and target schemas. This solution contributed in solving more comprehensively and efficiently XML schema automated matching problem. Our solution based on combining linguistic similarity, data type compatibility and structural similarity of XML schema elements. After describing our solution, we present experimental results that demonstrate the effectiveness of this approach.

One Hour Ahead Load Forecasting Using Artificial Neural Network for the Western Area of Saudi Arabia

Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This article presents the development of an ANN-based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data and historical electric load-related data using the data from the calendar years 2001, 2002, 2003, and 2004 for training. The model tested for one week at five different seasons, typically, winter, spring, summer, Ramadan and fall seasons, and the mean absolute average error for one hour-ahead load forecasting found 1.12%.

The Study of the Variability of Anticipatory Postural Adjustments in Recurrent Non-specific LBP Patients

The study of the variability of the postural strategies in low back pain patients, as a criterion in evaluation of the adaptability of this system to the environmental demands is the purpose of this study. A cross-sectional case-control study was performed on 21 recurrent non-specific low back pain patients and 21 healthy volunteers. The electromyography activity of Deltoid, External Oblique (EO), Transverse Abdominis/Internal Oblique (TrA/IO) and Erector Spine (ES) muscles of each person was recorded in 75 rapid arm flexion with maximum acceleration. Standard deviation of trunk muscles onset relative to deltoid muscle onset were statistically analyzed by MANOVA . The results show that chronic low back pain patients exhibit less variability in their anticipatory postural adjustments (APAs) in comparison with the control group. There is a decrease in variability of postural control system of recurrent non-specific low back pain patients that can result in the persistence of pain and chronicity by decreasing the adaptability to environmental demands.

Detecting Email Forgery using Random Forests and Naïve Bayes Classifiers

As emails communications have no consistent authentication procedure to ensure the authenticity, we present an investigation analysis approach for detecting forged emails based on Random Forests and Naïve Bays classifiers. Instead of investigating the email headers, we use the body content to extract a unique writing style for all the possible suspects. Our approach consists of four main steps: (1) The cybercrime investigator extract different effective features including structural, lexical, linguistic, and syntactic evidence from previous emails for all the possible suspects, (2) The extracted features vectors are normalized to increase the accuracy rate. (3) The normalized features are then used to train the learning engine, (4) upon receiving the anonymous email (M); we apply the feature extraction process to produce a feature vector. Finally, using the machine learning classifiers the email is assigned to one of the suspects- whose writing style closely matches M. Experimental results on real data sets show the improved performance of the proposed method and the ability of identifying the authors with a very limited number of features.

Engineering Geological Characteristics of Soil Materials, East Nile Delta, Egypt

This paper is concerned with the study of mineralogy and engineering characteristics of soil materials derived from the eastern part of Nile Delta. The clay minerals of the studied soil by using X- ray diffraction are mainly illite (average 72.6 %) and kaolinite (average 2.6 %), expandable portion in illite-smectite mixed layer (average 7 %). Smectite is more abundant in fluviatile clays, whereas kaolinite is more abundant in lagoonal clays. On the other hand, illite and illite-smectite are more abundant in marine clays. The geotechnical results show that the soil under study consists mainly of about 0.3 % gravel, 5 % sand, 51.5 % silt and 42.2 % clay in average. The average shrinkage limit attains 11 % whereas the average value of the plasticity index is 23.4 %. The free swelling ranges from 40 % to 75 % and has a value of 55 % giving an indication about the inadequacy of such soil under foundations. From a construction point of view, the soil under investigation poses many problems even under light foundations due to the swelling and shrinkage. Such swelling and shrinkage is due to the high content of soil materials in the expandable clay minerals of illite and smectite. Based on the results of the present and earlier studies, trial application of soil stabilisation is recommended.

Preparing Project Managers to Achieve Project Success - Human Management Perspective

The evolution in project management was triggered by the changes in management philosophy and practices in order to maintain competitive advantage and continuous success in the field. The purpose of this paper is to highlight the practicality of cognitive style and unlearning approach in influencing the achievement of project success by project managers. It introduces the concept of planning, knowing and creating style from cognitive style field in the light of achieving time, cost, quality and stakeholders appreciation in project success context. Further it takes up a discussion of the unlearning approach as a moderator in enhancing the relationship between cognitive style and project success. The paper bases itself on literature review from established disciplines like psychology, sociology and philosophy regarding cognitive style, unlearning and project success in general. The analysis and synthesis of literature in the subject area a conceptual paper is utilized as the basis of future research to form a comprehensive framework for project managers in enhancing the project management competency.

BugCatcher.Net: Detecting Bugs and Proposing Corrective Solutions

Although achieving zero-defect software release is practically impossible, software industries should take maximum care to detect defects/bugs well ahead in time allowing only bare minimums to creep into released version. This is a clear indicator of time playing an important role in the bug detection. In addition to this, software quality is the major factor in software engineering process. Moreover, early detection can be achieved only through static code analysis as opposed to conventional testing. BugCatcher.Net is a static analysis tool, which detects bugs in .NET® languages through MSIL (Microsoft Intermediate Language) inspection. The tool utilizes a Parser based on Finite State Automata to carry out bug detection. After being detected, bugs need to be corrected immediately. BugCatcher.Net facilitates correction, by proposing a corrective solution for reported warnings/bugs to end users with minimum side effects. Moreover, the tool is also capable of analyzing the bug trend of a program under inspection.

Crash Severity Modeling in Urban Highways Using Backward Regression Method

Identifying and classifying intersections according to severity is very important for implementation of safety related counter measures and effective models are needed to compare and assess the severity. Highway safety organizations have considered intersection safety among their priorities. In spite of significant advances in highways safety, the large numbers of crashes with high severities still occur in the highways. Investigation of influential factors on crashes enables engineers to carry out calculations in order to reduce crash severity. Previous studies lacked a model capable of simultaneous illustration of the influence of human factors, road, vehicle, weather conditions and traffic features including traffic volume and flow speed on the crash severity. Thus, this paper is aimed at developing the models to illustrate the simultaneous influence of these variables on the crash severity in urban highways. The models represented in this study have been developed using binary Logit Models. SPSS software has been used to calibrate the models. It must be mentioned that backward regression method in SPSS was used to identify the significant variables in the model. Consider to obtained results it can be concluded that the main factor in increasing of crash severity in urban highways are driver age, movement with reverse gear, technical defect of the vehicle, vehicle collision with motorcycle and bicycle, bridge, frontal impact collisions, frontal-lateral collisions and multi-vehicle crashes in urban highways which always increase the crash severity in urban highways.

A Study of the Relationship of PSI and LMX to Service Providers' CS in Hospitality Industry

The purpose of the current study is to gain insight into the relative role of professional self-image (PSI) for service providers among leader-member exchange (LMX), career success. Lack of studies demonstrated that PSI of service providers affect on their CS. So, it is necessary to, according to service providers- perspective, explore the relationship among LMX and CS in hospitality industry. The result of the current study can suggest strategic directions for hospitality practitioners in terms of constructing LMX relationship, so as to make service providers realize and build their PSI, and to promote their CS. Implications of these findings for hospitality implementations as well as future research directions are subsequently discussed.

Direct and Indirect Somatic Embryogenesis from Petiole and Leaf Explants of Purple Fan Flower (Scaevola aemula R. Br. cv. 'Purple Fanfare')

Direct and indirect somatic embryogenesis (SE) from petiole and leaf explants of Scaevola aemula R. Br. cv. 'Purple Fanfare' was achieved. High frequency of somatic embryos was obtained directly from petiole and leaf explants using an inductive plant growth regulator signal thidiazuron (TDZ). Petiole explants were more responsive to SE than leaves. Plants derived from somatic embryos of petiole explants germinated more readily into plants. SE occurred more efficiently in half-strength Murashige and Skoog (MS) medium than in full-strength MS medium. Non-embryogenic callus induced by 2, 4-dichlorophenoxyacetic acid was used to investigate the feasibility of obtaining SE with TDZ as a secondary inductive plant growth regulator (PGR) signal. Non-embryogenic callus of S. aemula was able to convert into an “embryogenic competent mode" with PGR signal. Protocol developed for induction of direct and indirect somatic embryogenesis in S. aemula can improve the large scale propagation system of the plant in future.

Detection of Ultrasonic Images in the Presence of a Random Number of Scatterers: A Statistical Learning Approach

Support Vector Machine (SVM) is a statistical learning tool that was initially developed by Vapnik in 1979 and later developed to a more complex concept of structural risk minimization (SRM). SVM is playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM was applied to the detection of medical ultrasound images in the presence of partially developed speckle noise. The simulation was done for single look and multi-look speckle models to give a complete overlook and insight to the new proposed model of the SVM-based detector. The structure of the SVM was derived and applied to clinical ultrasound images and its performance in terms of the mean square error (MSE) metric was calculated. We showed that the SVM-detected ultrasound images have a very low MSE and are of good quality. The quality of the processed speckled images improved for the multi-look model. Furthermore, the contrast of the SVM detected images was higher than that of the original non-noisy images, indicating that the SVM approach increased the distance between the pixel reflectivity levels (detection hypotheses) in the original images.

Challenges to Technological Advancement in Economically Weak Countries: An Assessment of the Nigerian Educational Situation

Nigeria is considered as one of the many countries in sub-Saharan Africa with a weak economy and gross deficiencies in technology and engineering. Available data from international monitoring and regulatory organizations show that technology is pivotal to determining the economic strengths of nations all over the world. Education is critical to technology acquisition, development, dissemination and adaptation. Thus, this paper seeks to critically assess and discuss issues and challenges facing technological advancement in Nigeria, particularly in the education sector, and also proffers solutions to resuscitate the Nigerian education system towards achieving national technological and economic sustainability such that Nigeria can compete favourably with other technologicallydriven economies of the world in the not-too-distant future.

Possible Futures for Doctoral Research Training in Design

In this paper, we argue that Design research is basic to countries- national productivity and competition agendas at the same time that vagaries of research training presents as one of the barriers faced by Design Higher Degree by Research students in engaging those agendas. We argue that, given industry requirements for research-trained recruits, students have the right to expect that research training will provide the foundations of a successful career on an academic or research pathway or a professional pathway, but that universities have yet to address problems in their provision of research training for Design doctoral students. We suggest that to facilitate this, rigorous research conducted on the provision of Doctoral programs in Design would serve to inform future activities in Design research in productive ways.

Drafting the Design and Development of Micro- Controller Based Portable Soil Moisture Sensor for Advancement in Agro Engineering

Moisture is an important consideration in many aspects ranging from irrigation, soil chemistry, golf course, corrosion and erosion, road conditions, weather predictions, livestock feed moisture levels, water seepage etc. Vegetation and crops always depend more on the moisture available at the root level than on precipitation occurrence. In this paper, design of an instrument is discussed which tells about the variation in the moisture contents of soil. This is done by measuring the amount of water content in soil by finding the variation in capacitance of soil with the help of a capacitive sensor. The greatest advantage of soil moisture sensor is reduced water consumption. The sensor is also be used to set lower and upper threshold to maintain optimum soil moisture saturation and minimize water wilting, contributes to deeper plant root growth ,reduced soil run off /leaching and less favorable condition for insects and fungal diseases. Capacitance method is preferred because, it provides absolute amount of water content and also measures water content at any depth.

Analytical Study of Component Based Software Engineering

This paper is a survey of current component-based software technologies and the description of promotion and inhibition factors in CBSE. The features that software components inherit are also discussed. Quality Assurance issues in componentbased software are also catered to. The feat research on the quality model of component based system starts with the study of what the components are, CBSE, its development life cycle and the pro & cons of CBSE. Various attributes are studied and compared keeping in view the study of various existing models for general systems and CBS. When illustrating the quality of a software component an apt set of quality attributes for the description of the system (or components) should be selected. Finally, the research issues that can be extended are tabularized.

Rapid Development of Sport and Sport Management at the Beginning of the Third Millennium

Most people know through experience and intuition what the word „sport“ means. Sport includes a combination of these configurations when it involves team competitions, tournaments, or matches in dual sports or individual sports. Sport management - it is an area of professional endeavor in which a variety of sport-related managerial careers exist and it is also an area of academic professional preparation. Exists three unique aspects of sport management: sport marketing, sport enterprise financial structures and sport industry career paths. The aim of the paper was to highlight the growing importance of sport in contemporary society, especially to emphasize its socio-economic benefits and refer to the development of sport management and marketing. The article has shown that sport contributes 2-3% to gross domestic product in the Czech Republic and that the demand for experts, specialists educated for the sports manager profession is growing.

Classifying Students for E-Learning in Information Technology Course Using ANN

This research’s objective is to select the model with most accurate value by using Neural Network Technique as a way to filter potential students who enroll in IT course by Electronic learning at Suan Suanadha Rajabhat University. It is designed to help students selecting the appropriate courses by themselves. The result showed that the most accurate model was 100 Folds Cross-validation which had 73.58% points of accuracy.

The Importance of Class Attendance and Cumulative GPA for Academic Success in Industrial Engineering Classes

The affect of the attendance percentage, the overall GPA and the number of credit hours the student is enrolled in at specific semester on the grade attained in specific course has been studied. This study has been performed on three courses offered in industrial engineering department at the Hashemite University in Jordan. Study has revealed that the grade attained by a student is strongly affected by the attendance percentage and his overall GPA with a value of R2 of 52.5%. Another model that has been investigated is the relation between the semester GPA and the attendance percentage, the number of credit hours enrolled in at specific semester, and the overall GPA. This model gave us a strong relationship between the semester GPA and attendance percentage and the overall GPA with a value of R2 of 76.2%.

A Survey on Metric of Software Cognitive Complexity for OO design

In modern era, the biggest challenge facing the software industry is the upcoming of new technologies. So, the software engineers are gearing up themselves to meet and manage change in large software system. Also they find it difficult to deal with software cognitive complexities. In the last few years many metrics were proposed to measure the cognitive complexity of software. This paper aims at a comprehensive survey of the metric of software cognitive complexity. Some classic and efficient software cognitive complexity metrics, such as Class Complexity (CC), Weighted Class Complexity (WCC), Extended Weighted Class Complexity (EWCC), Class Complexity due to Inheritance (CCI) and Average Complexity of a program due to Inheritance (ACI), are discussed and analyzed. The comparison and the relationship of these metrics of software complexity are also presented.

Evolution of Developing Flushing Cone during the Pressurized Flushing in Reservoir Storage

Sedimentation in reservoirs and the corresponding loss of storage capacity is one of the most serious problems in dam engineering. Pressurized flushing, a way to remove sediments from the reservoir, is flushing under a pressurized flow condition and nearly constant water level. Pressurized flushing has only local effects around the outlet. Sediment in the vicinity of the outlet openings is scoured and a funnel shaped crater is created. In this study, the temporal development of flushing cone under various hydraulic conditions was studied experimentally. Time variations of parameters such as maximum length and width of flushing and also depth of scouring cone was measured. Results indicated that an increase in flow velocity (and consequently in Froude number) established new hydraulically conditions for flushing mechanism and so a sudden growth was observed in the amount of sediment released and also scouring dimenssions. In addition, a set of nondimensional relationships were identified for temporal variations of flushing scour dimenssions, which can eventuallt be used to estimate the development of flushing cone.