Search results for: Artificial Intelligence ‎Approaches

Authors: Konstantinos C. Giotopoulos, Christos E. Alexakos, Grigorios N. Beligiannis, Spiridon D.Likothanassis

Abstract:

In this contribution a newly developed elearning environment is presented, which incorporates Intelligent Agents and Computational Intelligence Techniques. The new e-learning environment is constituted by three parts, the E-learning platform Front-End, the Student Questioner Reasoning and the Student Model Agent. These parts are distributed geographically in dispersed computer servers, with main focus on the design and development of these subsystems through the use of new and emerging technologies. These parts are interconnected in an interoperable way, using web services for the integration of the subsystems, in order to enhance the user modelling procedure and achieve the goals of the learning process.

Keywords: E-learning environments, intelligent agents, user modeling, Bayesian Networks, computational intelligence.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1829

Authors: Xun Ge, Jinjin Li, Ying Ge

Abstract:

Adopting Zakowski-s upper approximation operator C and lower approximation operator C, this paper investigates granularity-wise separations in covering approximation spaces. Some characterizations of granularity-wise separations are obtained by means of Pawlak rough sets and some relations among granularitywise separations are established, which makes it possible to research covering approximation spaces by logical methods and mathematical methods in computer science. Results of this paper give further applications of Pawlak rough set theory in pattern recognition and artificial intelligence.

Keywords: Rough set, covering approximation space, granularitywise separation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1634

Authors: T. C. Manjunath, C. Ardil

Abstract:

This paper deals with the design and the implementation of an automatic task planner for a robot, irrespective of whether it is a stationary robot or a mobile robot. The aim of the task planner nothing but, they are planning systems which are used to plan a particular task and do the robotic manipulation. This planning system is embedded into the system software in the computer, which is interfaced to the computer. When the instructions are given using the computer, this is transformed into real time application using the robot. All the AI based algorithms are written and saved in the control software, which acts as the intelligent task planning system.

Keywords: AI, Robot, Task Planner, RT, Algorithm, Specs, Controller.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 575

Authors: Hidehiko Okada, Yuki Fujii

Abstract:

Researchers have been applying artificial/ computational intelligence (AI/CI) methods to computer games. In this research field, further researchesare required to compare AI/CI methods with respect to each game application. In thispaper, we report our experimental result on the comparison of evolution strategy, genetic algorithm and their hybrids, applied to evolving controller agents for MarioAI. GA revealed its advantage in our experiment, whereas the expected ability of ES in exploiting (fine-tuning) solutions was not clearly observed. The blend crossover operator and the mutation operator of GA might contribute well to explore the vast search space.

Keywords: Evolutionary algorithm, autonomous game controller agent, neuroevolutions, MarioAI

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1690

Authors: Jagadish H. Pujar

Abstract:

Fuzzy Load forecasting plays a paramount role in the operation and management of power systems. Accurate estimation of future power demands for various lead times facilitates the task of generating power reliably and economically. The forecasting of future loads for a relatively large lead time (months to few years) is studied here (long term load forecasting). Among the various techniques used in forecasting load, artificial intelligence techniques provide greater accuracy to the forecasts as compared to conventional techniques. Fuzzy Logic, a very robust artificial intelligent technique, is described in this paper to forecast load on long term basis. The paper gives a general algorithm to forecast long term load. The algorithm is an Extension of Short term load forecasting method to Long term load forecasting and concentrates not only on the forecast values of load but also on the errors incorporated into the forecast. Hence, by correcting the errors in the forecast, forecasts with very high accuracy have been achieved. The algorithm, in the paper, is demonstrated with the help of data collected for residential sector (LT2 (a) type load: Domestic consumers). Load, is determined for three consecutive years (from April-06 to March-09) in order to demonstrate the efficiency of the algorithm and to forecast for the next two years (from April-09 to March-11).

Keywords: Fuzzy Logic Control (FLC), Data DependantFactors(DDF), Model Dependent Factors(MDF), StatisticalError(SE), Short Term Load Forecasting (STLF), MiscellaneousError(ME).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2426

Authors: Jeewanee Bamunusinghe, Damminda Alahakoon

Abstract:

Visual inputs are one of the key sources from which humans perceive the environment and 'understand' what is happening. Artificial systems perceive the visual inputs as digital images. The images need to be processed and analysed. Within the human brain, processing of visual inputs and subsequent development of perception is one of its major functionalities. In this paper we present part of our research project, which aims at the development of an artificial model for visual perception (or 'understanding') based on the human perceptive and cognitive systems. We propose a new model for perception from visual inputs and a way of understaning or interpreting images using the model. We demonstrate the implementation and use of the model with a real image data set.

Keywords: Image understanding, percept, visual perception.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1659

Authors: Konstantinos C. Giotopoulos, Christos E. Alexakos, Grigorios N. Beligiannis, Spiridon D.Likothanassis

Abstract:

In this contribution a newly developed e-learning environment is presented, which incorporates Intelligent Agents and Computational Intelligence Techniques. The new e-learning environment is constituted by three parts, the E-learning platform Front-End, the Student Questioner Reasoning and the Student Model Agent. These parts are distributed geographically in dispersed computer servers, with main focus on the design and development of these subsystems through the use of new and emerging technologies. These parts are interconnected in an interoperable way, using web services for the integration of the subsystems, in order to enhance the user modelling procedure and achieve the goals of the learning process.

Keywords: Computational Intelligence, E-learning Environments, Intelligent Agents, User Modelling, Bayesian Networks.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1711

Authors: R. Boondao, A. J. Hurst, J. I. Sheard

Abstract:

In the globalized e-learning environment, students coming from different cultures and countries have different characteristics and require different support designed for their approaches to study and learning styles. This paper explores the ways in which cultural background influences students- approaches to study and learning styles. Participants in the study consisted of 131 eastern students and 54 western students from an Australian university. The students were tested using the Study Process Questionnaire (SPQ) for assessing their approaches to study and the Index of Learning Styles Questionnaire (ILS) for assessing their learning styles. The results of the study led to a set of principles being proposed to guide personalization of e-learning system design on the basis of cultural differences.

Keywords: Approaches to study, Cultural influences, Learningstyles, Personalization, e-learning system.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1739

Authors: Hamid R. S. Mojaveri, Seyed S. Mousavi, Mojtaba Heydar, Ahmad Aminian

Abstract:

The aim of this paper is to present a methodology in three steps to forecast supply chain demand. In first step, various data mining techniques are applied in order to prepare data for entering into forecasting models. In second step, the modeling step, an artificial neural network and support vector machine is presented after defining Mean Absolute Percentage Error index for measuring error. The structure of artificial neural network is selected based on previous researchers' results and in this article the accuracy of network is increased by using sensitivity analysis. The best forecast for classical forecasting methods (Moving Average, Exponential Smoothing, and Exponential Smoothing with Trend) is resulted based on prepared data and this forecast is compared with result of support vector machine and proposed artificial neural network. The results show that artificial neural network can forecast more precisely in comparison with other methods. Finally, forecasting methods' stability is analyzed by using raw data and even the effectiveness of clustering analysis is measured.

Keywords: Artificial Neural Networks (ANN), bullwhip effect, demand forecasting, Support Vector Machine (SVM).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1967

Authors: Asaad Moosa

Abstract:

In recent years with the rapid development of Internet and the Web, more and more web applications have been deployed in many fields and organizations such as finance, military, and government. Together with that, hackers have found more subtle ways to attack web applications. According to international statistics, SQL Injection is one of the most popular vulnerabilities of web applications. The consequences of this type of attacks are quite dangerous, such as sensitive information could be stolen or authentication systems might be by-passed. To mitigate the situation, several techniques have been adopted. In this research, a security solution is proposed using Artificial Neural Network to protect web applications against this type of attacks. The solution has been experimented on sample datasets and has given promising result. The solution has also been developed in a prototypic web application firewall called ANNbWAF.

Keywords: Artificial Neural Networks ANN, SQL Injection, Web Application Firewall WAF, Web Application Scanner WAS.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5580

Authors: S. Mehrab Amiri, Nasser Talebbeydokhti

Abstract:

Modeling sediment transport processes by means of numerical approach often poses severe challenges. In this way, a number of techniques have been suggested to solve flow and sediment equations in decoupled, semi-coupled or fully coupled forms. Furthermore, in order to capture flow discontinuities, a number of techniques, like artificial viscosity and shock fitting, have been proposed for solving these equations which are mostly required careful calibration processes. In this research, a numerical scheme for solving shallow water and Exner equations in fully coupled form is presented. First-Order Centered scheme is applied for producing required numerical fluxes and the reconstruction process is carried out toward using Monotonic Upstream Scheme for Conservation Laws to achieve a high order scheme.  In order to satisfy C-property of the scheme in presence of bed topography, Surface Gradient Method is proposed. Combining the presented scheme with fourth order Runge-Kutta algorithm for time integration yields a competent numerical scheme. In addition, to handle non-prismatic channels problems, Cartesian Cut Cell Method is employed. A trained Multi-Layer Perceptron Artificial Neural Network which is of Feed Forward Back Propagation (FFBP) type estimates sediment flow discharge in the model rather than usual empirical formulas. Hydrodynamic part of the model is tested for showing its capability in simulation of flow discontinuities, transcritical flows, wetting/drying conditions and non-prismatic channel flows. In this end, dam-break flow onto a locally non-prismatic converging-diverging channel with initially dry bed conditions is modeled. The morphodynamic part of the model is verified simulating dam break on a dry movable bed and bed level variations in an alluvial junction. The results show that the model is capable in capturing the flow discontinuities, solving wetting/drying problems even in non-prismatic channels and presenting proper results for movable bed situations. It can also be deducted that applying Artificial Neural Network, instead of common empirical formulas for estimating sediment flow discharge, leads to more accurate results.

Keywords: Artificial neural network, morphodynamic model, sediment continuity equation, shallow water equations.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 835

Authors: Jennifer Chen-Hua Min

Abstract:

The concept of self-efficacy refers to people’s beliefs in their ability to perform certain behaviors and cope with environmental demands. As such, self-efficacy plays a key role in linking ability to performance. Therefore, this study examines the relationships of self-efficacy, emotional intelligence (EI), and well-being among tour guides, who act as intermediaries between tourists and an unfamiliar environment and significantly influence tourists’ impressions of a destination. Structural equation modeling (SEM) is used to identify the relationships between these factors. The results found that self-efficacy is positively associated with EI and well-being, and a positive link was seen between EI and well-being. This study has practical implications, as the results can facilitate the development of interventions for enhancing tour guides’ EI and self-efficacy competencies, which will benefit them in terms of both enhanced achievements and improved psychological happiness and well-being.

Keywords: Self-efficacy, tour guides, tourism, emotional intelligence.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1412

Authors: Younis R. Elhaddad, Aiman S.Gannous

Abstract:

The particular interests of this paper is to explore if the simple Genetic Algorithms (GA) starts with population of only two individuals and applying different crossover technique over these parents to produced 104 children, each one has different attributes inherited from their parents; is better than starting with population of 100 individuals; and using only one type crossover (order crossover OX). For this reason we implement GA with 52 different crossover techniques; each one produce two children; which means 104 different children will be produced and this may discover more search space, also we implement classic GA with order crossover and many experiments were done over 3 Travel Salesman Problem (TSP) to find out which method is better, and according to the results we can say that GA with Multi-crossovers is much better.

Keywords: Artificial intelligence, genetic algorithm, order crossover, travel salesman problem.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1366

Authors: Sri Hartati, 1Agus Harjoko, Brad G. Nickerson

Abstract:

A prototype of an anomaly detection system was developed to automate process of recognizing an anomaly of roentgen image by utilizing fuzzy histogram hyperbolization image enhancement and back propagation artificial neural network. The system consists of image acquisition, pre-processor, feature extractor, response selector and output. Fuzzy Histogram Hyperbolization is chosen to improve the quality of the roentgen image. The fuzzy histogram hyperbolization steps consist of fuzzyfication, modification of values of membership functions and defuzzyfication. Image features are extracted after the the quality of the image is improved. The extracted image features are input to the artificial neural network for detecting anomaly. The number of nodes in the proposed ANN layers was made small. Experimental results indicate that the fuzzy histogram hyperbolization method can be used to improve the quality of the image. The system is capable to detect the anomaly in the roentgen image.

Keywords: Image processing, artificial neural network, anomaly detection.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2066

Authors: Karima Qayumi, Alex Norta

Abstract:

The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets.

Keywords: Agent-oriented modeling, business Intelligence management, distributed data mining, multi-agent system.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1339

Authors: Janusz Bobulski, Kamila Pasternak

Abstract:

Despite many years of effort and research, the problem of waste management is still current. There is a lack of fast and effective algorithms for classifying individual waste fractions. Many programs and projects improve statistics on the percentage of waste recycled every year. In these efforts, it is worth using modern Computer Vision techniques supported by artificial intelligence. In the article, we present a method of identifying plastic waste based on the asymmetry analysis of the histogram of the image containing the waste. The method is simple but effective (94%), which allows it to be implemented on devices with low computing power, in particular on microcomputers. Such de-vices will be used both at home and in waste sorting plants.

Keywords: Computer vision, environmental protection, image processing, waste management.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 203

Authors: Himanshu Payal, Sachin Maheshwari, Pushpendra S. Bharti

Abstract:

Electrical discharge machining (EDM), a non-conventional machining process, finds wide applications for shaping difficult-to-cut alloys. Process modeling of EDM is required to exploit the process to the fullest. Process modeling of EDM is a challenging task owing to involvement of so many electrical and non-electrical parameters. This work is an attempt to model the EDM process using artificial neural network (ANN). Experiments were carried out on die-sinking EDM taking Inconel 825 as work material. ANN modeling has been performed using experimental data. The prediction ability of trained network has been verified experimentally. Results indicate that ANN can predict the values of performance measures of EDM satisfactorily.

Keywords: Artificial neural network, EDM, metal removal rate, modeling, surface roughness.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1114

Authors: S. Areerachakul

Abstract:

Nowadays, the increase of human population every year results in increasing of water usage and demand. Saen Saep canal is important canal in Bangkok. The main objective of this study is using Artificial Neural Network (ANN) model to estimate the Chemical Oxygen Demand (COD) on data from 11 sampling sites. The data is obtained from the Department of Drainage and Sewerage, Bangkok Metropolitan Administration, during 2007-2011. The twelve parameters of water quality are used as the input of the models. These water quality indices affect the COD. The experimental results indicate that the ANN model provides a high correlation coefficient (R=0.89).

Keywords: Artificial neural network, chemical oxygen demand, estimate, surface water.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2223

Authors: Alexei M. Mikhailov

Abstract:

The paper attempts to elucidate the columnar structure of the cortex by answering the following questions. (1) Why the cortical neurons with similar interests tend to be vertically arrayed forming what is known as cortical columns? (2) How to describe the cortex as a whole in concise mathematical terms? (3) How to design efficient digital models of the cortex?

Keywords: Cortex, pattern recognition, artificial neural cortex, computational biology, brain and neural engineering.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1748

Authors: Qais M. Yousef, Yasmeen A. Alshaer

Abstract:

Over the last few years, the amount of data available on the globe has been increased rapidly. This came up with the emergence of recent concepts, such as the big data and the Internet of Things, which have furnished a suitable solution for the availability of data all over the world. However, managing this massive amount of data remains a challenge due to their large verity of types and distribution. Therefore, locating the required file particularly from the first trial turned to be a not easy task, due to the large similarities of names for different files distributed on the web. Consequently, the accuracy and speed of search have been negatively affected. This work presents a method using Electroencephalography signals to locate the files based on their contents. Giving the concept of natural mind waves processing, this work analyses the mind wave signals of different people, analyzing them and extracting their most appropriate features using multi-objective metaheuristic algorithm, and then classifying them using artificial neural network to distinguish among files with similar names. The aim of this work is to provide the ability to find the files based on their contents using human thoughts only. Implementing this approach and testing it on real people proved its ability to find the desired files accurately within noticeably shorter time and retrieve them as a first choice for the user.

Keywords: Artificial intelligence, data contents search, human active memory, mind wave, multi-objective optimization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 872

Authors: Ģirts Brasliņš, Ilja Arefjevs, Nadežda Tarakanova

Abstract:

The objective of countercyclical capital buffer is to encourage banks to build up buffers in good times that can be drawn down in bad times. The aim of the report is to assess such decisions by banks derived from three approaches. The approaches are the aggregate credit-to-GDP ratio, credit growth as well as banking sector profits. The approaches are implemented for Estonia, Latvia and Lithuania for the time period 2000-2012. The report compares three approaches and analyses their relevance to the Baltic States by testing the correlation between a growth in studied variables and a growth of corresponding gaps. Methods used in the empirical part of the report are econometric analysis as well as economic analysis, development indicators, relative and absolute indicators and other methods. The research outcome is a cross-Baltic comparison of two alternative approaches to establish or release a countercyclical capital buffer by banks and their implications for each Baltic country.

Keywords: Basel III, countercyclical capital buffer, banks, credit growth, Baltic States.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1834

Authors: H. Bonakdari, I. Ebtehaj

Abstract:

The prediction of scour depth around bridge piers is frequently considered in river engineering. One of the key aspects in efficient and optimum bridge structure design is considered to be scour depth estimation around bridge piers. In this study, scour depth around bridge piers is estimated using two methods, namely the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). Therefore, the effective parameters in scour depth prediction are determined using the ANN and ANFIS methods via dimensional analysis, and subsequently, the parameters are predicted. In the current study, the methods’ performances are compared with the nonlinear regression (NLR) method. The results show that both methods presented in this study outperform existing methods. Moreover, using the ratio of pier length to flow depth, ratio of median diameter of particles to flow depth, ratio of pier width to flow depth, the Froude number and standard deviation of bed grain size parameters leads to optimal performance in scour depth estimation.

Keywords: Adaptive neuro-fuzzy inference system, ANFIS, artificial neural network, ANN, bridge pier, scour depth, nonlinear regression, NLR.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 878

Authors: M. Hassani, Y. Hassani, N. Ajudanioskooei, N. N. Benvid

Abstract:

Laser Forming process as a non-contact thermal forming process is widely used to forming and bending of metallic and non-metallic sheets. In this process, according to laser irradiation along a specific path, sheet is bent. One of the most important output parameters in laser forming is bending angle that depends on process parameters such as physical and mechanical properties of materials, laser power, laser travel speed and the number of scan passes. In this paper, Artificial Neural Network and Fuzzy Logic System were used to predict of bending angle in laser forming process. Inputs to these models were laser travel speed and laser power. The comparison between artificial neural network and fuzzy logic models with experimental results has been shown both of these models have high ability to prediction of bending angles with minimum errors.

Keywords: Artificial neural network, bending angle, fuzzy logic, laser forming.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 919

Authors: Kamel Khoualdi, Radia Benghezal

Abstract:

Research in distributed artificial intelligence and multiagent systems consider how a set of distributed entities can interact and coordinate their actions in order to solve a given problem. In this paper an overview of this concept and its evolution is presented particularly its application in the design of intelligent tutoring systems. An intelligent tutor based on the concept of agent and centered specifically on the design of a pedagogue agent is illustrated. Our work has two goals: the first one concerns the architecture aspect and the design of a tutor using multiagent approach. The second one deals particularly with the design of a part of a tutor system: the pedagogue agent.

Keywords: Intelligent tutoring systems, Multiagent systems, Pedagogue agent, Planning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1454

Authors: Abdel-Badeeh M. Salem

Abstract:

Case based reasoning (CBR) methodology presents a foundation for a new technology of building intelligent computeraided diagnoses systems. This Technology directly addresses the problems found in the traditional Artificial Intelligence (AI) techniques, e.g. the problems of knowledge acquisition, remembering, robust and maintenance. This paper discusses the CBR methodology, the research issues and technical aspects of implementing intelligent medical diagnoses systems. Successful applications in cancer and heart diseases developed by Medical Informatics Research Group at Ain Shams University are also discussed.

Keywords: Medical Informatics, Computer-Aided MedicalDiagnoses, AI in Medicine, Case-Based Reasoning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2903

Authors: N.K.K. Welgama, W.A.D.P. Wanigasundera

Abstract:

Small tanks, the ancient man-made rain water storage systems, support the pheasant life and agriculture of the dry zone of Sri Lanka. Many small tanks were abandoned with time due to various reasons. Such tanks, rehabilitated in the recent past, were found to be less sustainable and most of these rehabilitation approaches have failed. The objective of this research is to assess the impact of the rehabilitation approaches in the management of small tanks in the Kurunegala District of Sri Lanka with respect to eight small tanks. A Sustainability index was developed using seven indicators representing the ability and commitment of the villagers to maintain these tanks. The sustainability index of the eight tanks varied between 79.2 and 47.2 out of a total score of 100. The conclusion is that, the approaches used for tank rehabilitation have a significant effect on the sustainability of the management of these small tanks.

Keywords: Minor irrigation schemes, Participatory, Small Tanks, Sustainable, Water resource management.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1738

Authors: Nisha Harry

Abstract:

The study discussed in this article sought to assess whether a sense of professional efficacy mediates the relationship between personal factors and career adaptability. A quantitative cross-sectional survey approach was followed. A non–probability sample of (N = 409) of which predominantly early career and permanently employed black females in call centres in Africa participated in this study. In order to assess personal factors, the participants completed sense of meaningfulness and emotional intelligence measures. Measures of professional efficacy and career adaptability were also completed. The results of the mediational analysis revealed that professional efficacy significantly mediates the meaningfulness (sense of coherence) and career adaptability relationship, but not the emotional intelligence–career adaptability relationship. Call centre agents with professional efficacy are likely to be more work engaged as a result of their sense of meaningfulness and emotional intelligence.

Keywords: Call centre, professional efficacy, career adaptability, emotional intelligence.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 578

Authors: Hanaa T. El-Madany, Faten H. Fahmy, Ninet M. A. El-Rahman, Hassen T. Dorrah

Abstract:

Renewable energy resources are inexhaustible, clean as compared with conventional resources. Also, it is used to supply regions with no grid, no telephone lines, and often with difficult accessibility by common transport. Satellite earth stations which located in remote areas are the most important application of renewable energy. Neural control is a branch of the general field of intelligent control, which is based on the concept of artificial intelligence. This paper presents the mathematical modeling of satellite earth station power system which is required for simulating the system.Aswan is selected to be the site under consideration because it is a rich region with solar energy. The complete power system is simulated using MATLAB–SIMULINK.An artificial neural network (ANN) based model has been developed for the optimum operation of earth station power system. An ANN is trained using a back propagation with Levenberg–Marquardt algorithm. The best validation performance is obtained for minimum mean square error. The regression between the network output and the corresponding target is equal to 96% which means a high accuracy. Neural network controller architecture gives satisfactory results with small number of neurons, hence better in terms of memory and time are required for NNC implementation. The results indicate that the proposed control unit using ANN can be successfully used for controlling the satellite earth station power system.

Keywords: Satellite, neural network, MATLAB, power system.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1834

Authors: Gurmeet Kaur, Jyoti Pruthi

Abstract:

Agile Software development approaches and techniques are being considered as efficient, effective, and popular methods to the development of software. Agile software developments are useful for developing high-quality software that completes client requirements with zero defects, and in short delivery period. In agile software development methodology, quality is related to coding, which means quality, is managed through the use of approaches like refactoring, pair programming, test-driven development, behavior-driven development, acceptance test-driven development, and demand-driven development. The quality of software is measured using metrics like the number of defects during the development and improvement of the software. Usage of the above-mentioned methods or approaches reduces the possibilities of defects in developed software, and hence improves quality. This paper focuses on the study of agile-based quality methods or approaches for software development that ensures improved quality of software as well as reduced cost, and customer satisfaction.

Keywords: Agile software development, ASD, Acceptance test-driven development, ATDD, Behavior-driven development, BDD, Demand-driven development. DDD, Test-driven development, TDD.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 605

Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

Abstract:

Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotiv EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: Brain Computer Interface (BCI), Electroencephalogram (EEG), EEGLab, BCILab, Emotiv, Emotions, Interval features, Spectral features, Artificial Neural Network, Control applications.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5258