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Article Citation - WoS: 17Citation - Scopus: 30Analysis of Cultural and Gender Influences on Teamwork Performance for Software Requirements Analysis in Multinational Environments(Wiley, 2012) Fernandez-Sanz, L.; Misra, SanjaySoftware development is mainly a social activity where teams of developers should work as a coordinated unit to fulfill the needs of customers. Studies have shown the importance of teamwork ability as the main skill for software professionals both in local settings and in global software development. Teamwork performance can be evaluated according to different approaches but we need deeper analysis within software teams of differences in individuals' performance related to culture, nationality or even gender. We applied a simple evaluation experience named teamwork benefits awareness (TBA) to groups of last-year students of computing degrees with experience as junior IT professionals during intensive multinational workshops based on international software projects. TBA allowed to measure individual and team performance during a requirements analysis session based on a real project. Results segmented by nationality and gender are presented and analysed in comparison with the data collected from computing professionals in local settings. In general, no significant differences have been found out although interesting relations are suggested with two Hofstede's country indicators. TBA is also perceived as a good technique for highlighting both teamwork benefits as well as the nature of real situations of software requirements analysis and orientation to customer needs.Article Citation - WoS: 3Citation - Scopus: 5Particle Swarm Optimization of the Spectral and Energy Efficiency of an Scma-Based Heterogeneous Cellular Network(Wiley, 2022) Noma-Osaghae, Etinosa; Misra, Sanjay; Ahuja, Ravin; Koyuncu, MuratBackground The effect of stochastic small base station (SBS) deployment on the energy efficiency (EE) and spectral efficiency (SE) of sparse code multiple access (SCMA)-based heterogeneous cellular networks (HCNs) is still mostly unknown. Aim This research study seeks to provide insight into the interaction between SE and EE in SBS sleep-mode enabled SCMA-based HCNs. Methodology A model that characterizes the energy-spectral-efficiency (ESE) of a two-tier SBS sleep-mode enabled SCMA-based HCN was derived. A multiobjective optimization problem was formulated to maximize the SE and EE of the SCMA-based HCN simultaneously. The multiobjective optimization problem was solved using a proposed weighted sum modified particle swarm optimization algorithm (PSO). A comparison was made between the performance of the proposed weighted sum modified PSO algorithm and the genetic algorithm (GA) and the case where the SCMA-based HCN is unoptimized. Results The Pareto-optimal front generated showed a simultaneous maximization of the SE and EE of the SCMA-based HCN at high traffic levels and a convex front that allows network operators to select the SE-EE tradeoff at low traffic levels flexibly. The proposed PSO algorithm offers a higher SBS density, and a higher SBS transmit power at high traffic levels than at low traffic levels. The unoptimized SCMA-based HCN achieves an 80% lower SE and a 51% lower EE than the proposed PSO optimized SCMA-based HCN. The optimum SE and EE achieved by the SCMA-based HCN using the proposed PSO algorithm or the GA are comparable, but the proposed PSO uses a 51.85% lower SBS density and a 35.96% lower SBS transmit power to achieve the optimal SE and EE at moderate traffic levels. Conclusion In sleep-mode enabled SCMA-based HCNs, network engineers have to decide the balance of SBS density and SBS transmit power that helps achieve the desired SE and EE.Article Citation - WoS: 6Citation - Scopus: 9Experimental Simulation-Based Performance Evaluation of an Sms-Based Emergency Geolocation Notification System(Hindawi Ltd, 2017) Osebor, Isibor; Misra, Sanjay; Omoregbe, Nicholas; Adewumi, Adewole; Fernandez-Sanz, LuisIn an emergency, a prompt response can save the lives of victims. This statement generates an imperative issue in emergency medical services (EMS). Designing a system that brings simplicity in locating emergency scenes is a step towards improving response time. This paper therefore implemented and evaluated the performance of an SMS-based emergency geolocation notification system with emphasis on its SMS delivery time and the system's geolocation and dispatch time. Using the RAS metrics recommended by IEEE for evaluation, the designed system was found to be efficient and effective as its reliability stood within 62.7% to 70.0% while its availability stood at 99% with a downtime of 3.65 days/year.Review Citation - WoS: 22Citation - Scopus: 39Cybersecurity Deep: Approaches, Attacks Dataset, and Comparative Study(Taylor & Francis inc, 2022) Barik, Kousik; Misra, Sanjay; Konar, Karabi; Fernandez-Sanz, Luis; Murat, KoyuncuCyber attacks are increasing rapidly due to advanced digital technologies used by hackers. In addition, cybercriminals are conducting cyber attacks, making cyber security a rapidly growing field. Although machine learning techniques worked well in solving large-scale cybersecurity problems, an emerging concept of deep learning (DL) that caught on during this period caused information security specialists to improvise the result. The deep learning techniques analyzed in this study are convolution neural networks, recurrent neural networks, and deep neural networks in the context of cybersecurity.A framework is proposed, and a real-time laboratory setup is performed to capture network packets and examine this captured data using various DL techniques. A comparable interpretation is presented under the DL techniques with essential parameters, particularly accuracy, false alarm rate, precision, and detection rate. The DL techniques experimental output projects improvise the performance of various real-time cybersecurity applications on a real-time dataset. CNN model provides the highest accuracy of 98.64% with a precision of 98% with binary class. The RNN model offers the second-highest accuracy of 97.75%. CNN model provides the highest accuracy of 98.42 with multiclass class. The study shows that DL techniques can be effectively used in cybersecurity applications. Future research areas are being elaborated, including the potential research topics to improve several DL methodologies for cybersecurity applications.Article Citation - WoS: 43Citation - Scopus: 80Text Messaging-Based Medical Diagnosis Using Natural Language Processing and Fuzzy Logic(Hindawi Ltd, 2020) Omoregbe, Nicholas A. I.; Ndaman, Israel O.; Misra, Sanjay; Abayomi-Alli, Olusola O.; Damasevicius, RobertasThe use of natural language processing (NLP) methods and their application to developing conversational systems for health diagnosis increases patients' access to medical knowledge. In this study, a chatbot service was developed for the Covenant University Doctor (CUDoctor) telehealth system based on fuzzy logic rules and fuzzy inference. The service focuses on assessing the symptoms of tropical diseases in Nigeria. Telegram Bot Application Programming Interface (API) was used to create the interconnection between the chatbot and the system, while Twilio API was used for interconnectivity between the system and a short messaging service (SMS) subscriber. The service uses the knowledge base consisting of known facts on diseases and symptoms acquired from medical ontologies. A fuzzy support vector machine (SVM) is used to effectively predict the disease based on the symptoms inputted. The inputs of the users are recognized by NLP and are forwarded to the CUDoctor for decision support. Finally, a notification message displaying the end of the diagnosis process is sent to the user. The result is a medical diagnosis system which provides a personalized diagnosis utilizing self-input from users to effectively diagnose diseases. The usability of the developed system was evaluated using the system usability scale (SUS), yielding a mean SUS score of 80.4, which indicates the overall positive evaluation.Correction Software Development Outsourcing: Challenges and Opportunities in Nigeria (vol 17, Pg 267, 2014)(Taylor & Francis inc, 2015) Casado-Lumbreras, Cristina; Colomo-Palacios, Ricardo; Ogwueleka, Francisca N.; Misra, Sanjay[No Abstract Available]

