Transient processes on the elements of installation with electric conductive material may endanger the environment in urban areas and therefore action must be taken to mitigate possible consequences and protect the environment. Installation layers of lines of underground installation (electrical, gas, water…) that are used for the flow of energy/fluids do not provide a full protection and currents of static discharge discharged into the soil are particularly dangerous. At static discharges conductors receive high potentials and a strong electric field is created around them, which will be greater as the conductivity of the soil is weaker.

If the value of the field is greater than the disruptive voltage of the soil around earth wire (probe) the breakthrough occurs and the majority of soil becomes conductive. Particular problem are components of high frequency currents or voltages. Disorders of frequency in the range of 50 Hz to 5 kHz that can affect the selection of installation parameters, in compliance with all environmental criteria, are simulated by adapted subprogram in the part of the package Sym Power MATLAB.

Many business especially Banks’s services are expanding to include services directed not only to corporate customers but also to individual customer. Furthermore, by the increment of those services, many individual applications to be processed also increases as well. Facing an immense moment, in which requiring more improvements in how it should manage or maintain its applications, some systems or procedures must be improved to match currently increasing customers’ applications. Prior to the improvements, many application forms are filled, input to machine and even to be processed and approved manually. Until recently, application fulfillment processes consists of manual information filling by applicants in an application request paper and later to be re-input by electronic data processing staff which is actually redundant. Aware of such situation, this paper proposes and idea to reduce input processes in an integrated business system by utilizing character recognition system.

With each passing day, the Web is becoming increasingly important in our lives. Hence, the need of making it more accessible to everyone, especially for the disabled and elderly spurred a great interest in automated tools, the total registered number of which has been continuously increasing and reached from forty-five software bids in 2014 to ninety-three in 2017. The purpose of this empirical research is to assess and compare eight popular and free online automated Web accessibility evaluation tools (AWAETs) such as AChecker, Cynthia Says, EIII Checker, MAUVE, SortSite, TAW, Tenon and WAVE with regard to the WCAG 2.0 conformance. As a result, significant differences were observed in terms of tool’s coverage (a maximum of 32.4%), completeness (ranges between 10% and 59%), correctness (an average of 70.7%), specificity (reaches 32%), inter-reliability (lies between 1.56% and 18.32%) and intra-reliability (the acceptable score), validity, efficiency and capacity. These eight criteria can help to determine a new role played by modern AWAETs as dependent methods in Web accessibility evaluation. Moreover, consequences of relying on AWAETs alone are quantified and concluded that applying such approaches is a great mistake since subjective and less frequent objective success criteria (SC) failed to be automated. However, using a good combination of AWAETs is highly recommended as overall results in all the mentioned quality criteria are maximized and tools could definitely validate and complete each other. Ultimately, integrating automated methods with the others is ideal and preferably at an early stage of the website development life cycle. The study also provides potential accessibility barriers that make websites inaccessible, challenges AWAETs are currently facing, nineteen pros and fourteen cons and fifteen improvement recommendations for the existing and next generation of AWAETs. Fundamentally, achieving the objectives of this study was possible due to the elaboration and implementation of a new five-phased methodology named as “5PhM-for-AWAEMs” for successful selection, evaluation and/or comparison of AWAEMs. In addition to providing detailed descriptions of the estimation process, this methodology represents eleven key criteria for effective selection of suitable AWAEMs and necessary numbers of web pages and expert evaluators for acceptable, normal or ideal assessment.

Mobile Cloud Computing is a combination of mobile, cloud and wireless network where data storage and processing happens outside the mobile device. The storage capacity, processing power and battery life can be improved by moving resource intensive applications onto the cloud. In this paper, the performance of the mobile device is measured by using four different sorting techniques. Two different strategies were used for execution. In the first strategy, the input, execution and the output happens on the mobile device. In the other strategy, the input and output happens on the mobile device while the execution of the sorting techniques is offloaded to the server. The parameters considered for measurement are the execution time and mobile device’s energy consumption. The results show that offloading the task to the server reduces the execution time and energy consumption on the mobile device.

Organizational data is essential to assist domain experts and entrepreneurs for decision making process in relation to the organizational goals but the trustworthiness of organizational data in relation to achieving the organizational goals is often questioned because of the vast amount of organizational data available. This paper proposes a methodology to evaluate organizational data that relates to the organizational goals. This refers to the importance of assisting the organization to utilize relevance of organizational data from the vast amount of available data for decision making to the organizational goals. The aim of this paper is to identify dependency relationship of organizational data that match to the organizational goals and to define a metrics as an analysis approach to measure organizational data to be considered relevant to the organizational goals. The experiment is present to implement the propose methodology in the context of Australian economy. The contribution of this paper will serve as a first step in evaluation approach and analysis of organizational data that relates to the achievement of the organizational goals.

This paper presents a new approach named Dynamic Data Cleaning (DDC) aims to improve incomplete dataset consistency by identifying, reconstructing and removing inconsistent data objects for future data analysis process. The proposed DDC approach consists of three methods:  Identify Normal Object (INO), Reconstruct Normal Object (RNO) and Dataset Quality Measure (DQM).  The first method INO divides the incomplete dataset into normal objects and abnormal objects (outliers) based on degree of missing attributes values in each individual object. Second, the  (RNO) method reconstructs missed attributes values in the normal objects by the closest object based on a distance metric and removes inconsistent data objects (outliers) with higher missed data. Finally, the DQM method measures the consistency and inconsistency among the objects in improved dataset with and without outlier. Experimental results show that the proposed DDC approach is suitable to identify and reconstruct the incomplete data objects for improving dataset consistency from lower to higher level without user knowledge.

Personal service robots will be in the short future part of our world by assisting humans in their daily chores. A highly efficient way of communication with people is through basic gestures. In this work, we present an efficient body gestures’ interface that gives the user practical communication to control a personal service robot. The robot can interpret two body gestures of the subject and performs actions related to those gestures. The service robot’s setup consists of a Pioneer P3-DX research robot, a Kinect sensor and a portable workstation. The gesture recognition system developed is based on tracking the skeleton of the user to get the body parts relative 3D positions. In addition, the system takes depth images from the sensor and extracts their Haar features, which will train the Adaboost algorithm to classify the gesture. The system was developed using the ROS framework, showing good performance during experimental evaluation with users. Our body gesture-based interface may serve as a baseline to develop practical and natural interfaces to communicate with service robots in the near future.

There are an urgent need of categorizing plant by its species, to help botanist setting up a plant species database. However, plant recognition model is still very challenging task in computer vision and can be onerous and time consuming because of inefficient representation approaches. This paper, proposes a recognition model for classifying botanical species from leaf images, using combination of variant-order statistics based measures. Hence, the spatial coordinates values of gray pixels defines the qualities of texture, for the proposed model a gray-scale approach is adopted  for analyzing the local patterns of leaves images using second and higher order statistical measures. While, first order statistical measures are used to extract color descriptors from leaves images. Evaluation of the proposed model shows the importance of combining variant-order statistics measures for enhancing the plant leaf recognition accuracy. Several experiments on Flavia dataset and swedish dataset are conducted. Experimental results indicates that; the proposed model yields to improve the recognition rate up to 97.1% and 94.7% for both Flavia and Swedish dataset respectively; while taking less execution time.