149 results
Search Results
Now showing 1 - 10 of 149
Article Citation - WoS: 10Citation - Scopus: 15Increasing Innovative Working Behaviour of Information Technology Employees in Vietnam by Knowledge Management Approach(Mdpi, 2020) Quoc Trung Pham; Anh-Vu Pham-Nguyen; Misra, Sanjay; Damasevicius, Robertas; Pham-nguyen, Anh-vu; Pham, Quoc TrungToday, Knowledge Management (KM) is becoming a popular approach for improving organizational innovation, but whether encouraging knowledge sharing will lead to a better innovative working behaviour of employees is still a question. This study aims to identify the factors of KM affecting the innovative working behaviour of Information Technology (IT) employees in Vietnam. The research model involves three elements: attitude, subjective norm and perceived behavioural control affecting knowledge sharing, and then, on innovative working behaviour. The research method is the quantitative method. The survey was conducted with 202 samples via the five-scale questionnaire. The analysis results show that knowledge sharing has a positive impact on the innovative working behaviour of IT employees in Vietnam. Besides, attitude and perceived behavioural control are confirmed to have a strong positive effect on knowledge sharing, but the subjective norm has no significant impact on knowledge sharing. Based on this result, recommendations to promote knowledge sharing and the innovative work behaviour of IT employees in Vietnam are made.Article Citation - WoS: 33Citation - Scopus: 56Smart irrigation system for environmental sustainability in Africa: An Internet of Everything (IoE) approach(Amer inst Mathematical Sciences-aims, 2019) Adenugba, Favour; Misra, Sanjay; Maskeliunas, Rytis; Damasevicius, Robertas; Kazanavicius, EgidijusWater and food are two of the most important commodities in the world, which makes agriculture crucial to mankind as it utilizes water (irrigation) to provide us with food. Climate change and a rapid increase in population have put a lot of pressure on agriculture which has a snowball effect on the earth's water resource, which has been proven to be crucial for sustainable development. The need to do away with fossil fuel in powering irrigation systems cannot be over emphasized due to climate change. Smart Irrigation systems powered by renewable energy sources (RES) have been proven to substantially improve crop yield and the profitability of agriculture. Here we show how the control and monitoring of a solar powered smart irrigation system can be achieved using sensors and environmental data from an Internet of Everything (IoE). The collected data is used to predict environment conditions using the Radial Basis Function Network (RBFN). The predicted values of water level, weather forecast, humidity, temperature and irrigation data are used to control the irrigation system. A web platform was developed for monitoring and controlling the system remotely.Article Citation - WoS: 35Citation - Scopus: 59A Review of Soft Techniques for Sms Spam Classification: Methods, Approaches and Applications(Pergamon-elsevier Science Ltd, 2019) Abayomi-Alli, Olusola; Misra, Sanjay; Abayomi-Alli, Adebayo; Odusami, ModupeBackground: The easy accessibility and simplicity of Short Message Services (SMS) have made it attractive to malicious users thereby incurring unnecessary costing on the mobile users and the Network providers' resources. Aim: The aim of this paper is to identify and review existing state of the art methodology for SMS spam based on some certain metrics: AI methods and techniques, approaches and deployed environment and the overall acceptability of existing SMS applications. Methodology: This study explored eleven databases which include IEEE, Science Direct, Springer, Wiley, ACM, DBLP, Emerald, SU, Sage, Google Scholar, and Taylor and Francis, a total number of 1198 publications were found. Several screening criteria were conducted for relevant papers such as duplicate removal, removal based on irrelevancy, abstract eligibility based on the removal of papers with ambiguity (undefined methodology). Finally, 83 papers were identified for depth analysis and relevance. A quantitative evaluation was conducted on the selected studies using seven search strategies (SS): source, methods/ techniques, AI approach, architecture, status, datasets and SMS spam mobile applications. Result: A Quantitative Analysis (QA) was conducted on the selected studies and the result based on existing methodology for classification shows that machine learning gave the highest result with 49% with algorithms such as Bayesian and support vector machines showing highest usage. Unlike statistical analysis with 39% and evolutionary algorithms gave 12%. However, the QA for feature selection methods shows that more studies utilized document frequency, term frequency and n-grams techniques for effective features selection process. Result based on existing approaches for content-based, non-content and hybrid approaches is 83%, 5%, and 12% respectively. The QA based on architecture shows that 25% of existing solutions are deployed on the client side, 19% on server-side, 6% collaborative and 50% unspecified. This survey was able to identify the status of existing SMS spam research as 35% of existing study was based on proposed new methods using existing algorithms and 29% based on only evaluation of existing algorithms, 20% was based on proposed methods only. Conclusion: This study concludes with very interesting findings which shows that the majority of existing SMS spam filtering solutions are still between the "Proposed" status or "Proposed and Evaluated" status. In addition, the taxonomy of existing state of the art methodologies is developed and it is concluded that 8.23% of Android users actually utilize this existing SMS anti-spam applications. Our study also concludes that there is a need for researchers to exploit all security methods and algorithm to secure SMS thus enhancing further classification in other short message platforms. A new English SMS spam dataset is also generated for future research efforts in Text mining, Tele-marketing for reducing global spam activities.Article Citation - WoS: 11Citation - Scopus: 13Choice Functions for Autonomous Search in Constraint Programming: Ga Vs. Pso(Univ Osijek, Tech Fac, 2013) Soto, Ricardo; Crawford, Broderick; Misra, Sanjay; Palma, Wenceslao; Monfroy, Eric; Castro, Carlos; Paredes, Fernando; Computer EngineeringThe variable and value ordering heuristics are a key element in Constraint Programming. Known together as the enumeration strategy they may have important consequences on the solving process. However, a suitable selection of heuristics is quite hard as their behaviour is complicated to predict. Autonomous search has been recently proposed to handle this concern. The idea is to dynamically replace strategies that exhibit poor performances by more promising ones during the solving process. This replacement is carried out by a choice function, which evaluates a given strategy in a given amount of time via quality indicators. An important phase of this process is performed by an optimizer, which aims at finely tuning the choice function in order to guarantee a precise evaluation of strategies. In this paper we evaluate the performance of two powerful choice functions: the first one supported by a genetic algorithm and the second one by a particle swarm optimizer. We present interesting results and we demonstrate the feasibility of using those optimization techniques for Autonomous Search in a Constraint Programming context.Article Citation - WoS: 1Citation - Scopus: 2Potential of Support-Vector Regression for Forecasting Stream Flow(Univ Osijek, Tech Fac, 2014) Radzi, Mohd Rashid Bin Mohd; Shamshirband, Shahaboddin; Aghabozorgi, Saeed; Misra, Sanjay; Akib, Shatirah; Kiah, Laiha Mat; Kiah, Miss Laiha Mat; Computer EngineeringStream flow is an important input for hydrology studies because it determines the water variability and magnitude of a river. Water resources engineering always deals with historical data and tries to estimate the forecasting records in order to give a better prediction for any water resources applications, such as designing the water potential of hydroelectric dams, estimating low flow, and maintaining the water supply. This paper presents three soft-computing approaches for dealing with these issues, i.e. artificial neural networks (ANNs), adaptive-neuro-fuzzy inference systems (ANFISs), and support vector machines (SVMs). Telom River, located in the Cameron Highlands district of Pahang, Malaysia, was used in making the estimation. The Telom River's daily mean discharge records, such as rainfall and river-level data, were used for the period of March 1984-January 2013 for training, testing, and validating the selected models. The SVM approach provided better results than ANFIS and ANNs in estimating the daily mean fluctuation of the stream's flow.Conference Object Citation - WoS: 1A Cognitive Evaluation for Meetings in Software Development Process(Springer-verlag Berlin, 2009) Misra, Sanjay; Akman, IbrahimSoftware development; includes number of different type of meetings in the whole development process. The cognitive activities also play an important role in decision making activities in these meetings since they are carried out, by human being. In this paper, we evaluated the relevance of meetings in different phases of the software development process with reference to cognitive aspects.Conference Object Embryo Spatial Model Reconstruction(Springer international Publishing Ag, 2020) Dirvanauskas, Darius; Maskeliunas, Rytis; Raudonis, Vidas; Misra, SanjayTime lapse microscopy offered new solutions to study embryo development process. It allows embryologist to monitor embryo growth in real time and evaluate them without interfering into their growth environment. Embryo evaluation during growth process is one of the key criteria in embryo selection for fertilization. Live embryo monitoring is time consuming and new tools are offered to automate part of process. Our proposed algorithm gives new possibilities for embryo monitoring. It uses embryo images which are taken from different embryo layers, extracts embryo cell features and returns metrical evaluation to compare different embryos. High number of extracted features shows embryo fragmentation. Other tool whichwe present is spatial embryo model. Features extracted from embryo layers are combined together to spatial model. It allows embryologist to examine embryo model and compare different layers in one space. The obtained spatial embryo model will be later used to develop new algorithms for embryo analysis tasks.Article Citation - WoS: 38Citation - Scopus: 59Career Abandonment Intentions among Software Workers(Wiley, 2014) Colomo-Palacios, Ricardo; Casado-Lumbreras, Cristina; Misra, Sanjay; Soto-Acosta, PedroWithin the software development industry, human resources have been recognized as one of the most decisive and scarce resources. Today, the retention of skilled IT (information technology) personnel is a major issue for employers and recruiters as well, since IT career abandonment is a common practice and means not only the loss of personnel, knowledge, and skills, but also the loss of business opportunities. This article seeks to discover the main motivations young practitioners abandon the software career. To achieve this objective, two studies were conducted. The first study was qualitative (performed through semistructured interviews) and intended to discover the main variables affecting software career abandonment. The second study was quantitative, consisting of a Web-based survey developed from the output of the first study and administered to a sample of 148 IT practitioners. Results show that work-related, psychological, and emotional variable are the most relevant group of variables explaining IT career abandonment. More specifically, the three most important variables that motivate employees to abandon the career are effort-reward imbalance, perceived workload, and emotional exhaustion. In contrast, variables such as politics and infighting, uncool work, and insufficient resources influence to a lesser extent the decision to leave the career. (c) 2012 Wiley Periodicals, Inc.Article Citation - WoS: 21Citation - Scopus: 22A Discussion on the Role of People in Global Software Development(Univ Osijek, Tech Fac, 2013) Misra, Sanjay; Colomo-Palacios, Ricardo; Pusatli, Tolga; Soto-Acosta, Pedro; Computer EngineeringLiterature is producing a considerable amount of papers which focus on the risks, challenges and solutions of global software development (GSD). However, the influence of human factors on the success of GSD projects requires further study. The aim of our paper is twofold. First, to identify the challenges related to the human factors in GSD and, second, to propose the solution(s), which could help in solving or reducing the overall impact of these challenges. The main conclusions of this research can be valuable to organizations that are willing to achieve the quality objectives regarding GSD projects.Article Citation - WoS: 23Citation - Scopus: 30Secure Ear Biometrics Using Circular Kernel Principal Component Analysis, Chebyshev Transform Hashing and Bose-Chaudhuri Error-Correcting Codes(Springer London Ltd, 2020) Olanrewaju, L.; Oyebiyi, Oyediran; Misra, Sanjay; Maskeliunas, Rytis; Damasevicius, RobertasEar biometrics has generated an increased interest in the domain of biometric identification systems due to its robustness and covert acquisition potential. The external structure of the human ear has a bilateral symmetry structure. Here, we analyse ear biometrics based on ear symmetry features. We apply iterative closest point and kernel principal component analysis with circular kernel for feature extraction while using a circular kernel function, combined with empirical mode decomposition into intrinsic mode functions perceptual hashing using and fast Chebyshev transform, and a secure authentication approach that exploits the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem error-correcting codes to generate 128-bit crypto keys. We evaluate the proposed ear biometric cryptosecurity system using our data set of ear images acquired from 103 persons. Our results show that the ear biometric-based authentication achieved an equal error rate of 0.13 and true positive rate TPR of 0.85.
