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Review Citation - WoS: 16Citation - Scopus: 20Assessing the Coverage of E-Health Services in Sub-Saharan Africa a Systematic Review and Analysis(Georg Thieme verlag Kg, 2017) Adeloye, Davies; Adigun, Taiwo; Misra, Sanjay; Omoregbe, NicholasBackground: E-Health has attracted growing interests globally. The relative lack of facilities, skills, funds and information on existing e-Health initiatives has affected progress on e-Health in Africa. Objectives: To review publicly available literature on e-Health in sub-Saharan Africa (sSA) towards providing information on existing and ongoing e-Health initiatives in the region. Methods: Searches of relevant literature were conducted on Medline, EMBASE and Global Health, with search dates set from 1990 to 2016. We included studies on e-Health initiatives (prototypes, designs, or completed projects) targeting population groups in sSA. Results: Our search returned 2322 hits, with 26 studies retained. Included studies were conducted in 14 countries across the four sub-regions in sSA (Central, East, South and West) and spreading over a 12-year period, 2002-2014. Six types of e-Health interventions were reported, with 17 studies (65%) based on telemedicine, followed by mHealth with 5 studies (19%). Other e-Health types include expert system, electronic medical records, e-mails, and online health module. Specific medical specialties covered include dermatology (19%), pathology (12%) and radiology (8%). Successes were 'widely reported' (representing 50% overall acceptance or positive feedbacks in a study) in 10 studies (38%). The prominent challenges reported were technical problems, poor inter net and connectivity, participants' selection biases, contextual issues, and lack of funds. Conclusion: E-Health is evolving in sSA, but with poorly published evidence. While we call for more quality research in the region, it is also important that population-wide policies and on-going e-Health initiatives are contextually feasible, acceptable, and sustainable.Review Citation - WoS: 3Citation - Scopus: 9An Empirical Evaluation of Software Quality Assurance Practices and Challenges in a Developing Country: a Comparison of Nigeria and Turkey(Springer international Publishing Ag, 2016) Sowunmi, Olaperi Yeside; Mısra, Sanjay; Misra, Sanjay; Fernandez-Sanz, Luis; Crawford, Broderick; Soto, Ricardo; Mısra, Sanjay; Computer Engineering; Computer EngineeringBackground: The importance of quality assurance in the software development process cannot be overemphasized because its adoption results in high reliability and easy maintenance of the software system and other software products. Software quality assurance includes different activities such as quality control, quality management, quality standards, quality planning, process standardization and improvement amongst others. The aim of this work is to further investigate the software quality assurance practices of practitioners in Nigeria. While our previous work covered areas on quality planning, adherence to standardized processes and the inherent challenges, this work has been extended to include quality control, software process improvement and international quality standard organization membership. It also makes comparison based on a similar study carried out in Turkey. The goal is to generate more robust findings that can properly support decision making by the software community. The qualitative research approach, specifically, the use of questionnaire research instruments was applied to acquire data from software practitioners. Results: In addition to the previous results, it was observed that quality assurance practices are quite neglected and this can be the cause of low patronage. Moreover, software practitioners are neither aware of international standards organizations or the required process improvement techniques; as such their claimed standards are not aligned to those of accredited bodies, and are only limited to their local experience and knowledge, which makes it questionable. The comparison with Turkey also yielded similar findings, making the results typical of developing countries. The research instrument used was tested for internal consistency using the Cronbach's alpha, and it was proved reliable. Conclusion: For the software industry in developing countries to grow strong and be a viable source of external revenue, software assurance practices have to be taken seriously because its effect is evident in the final product. Moreover, quality frameworks and tools which require minimum time and cost are highly needed in these countries.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.Article Citation - WoS: 23Citation - Scopus: 26Reconstruction of 3d Object Shape Using Hybrid Modular Neural Network Architecture Trained on 3d Models From Shapenetcore Dataset(Mdpi, 2019) Kulikajevas, Audrius; Maskeliunas, Rytis; Damasevicius, Robertas; Misra, SanjayDepth-based reconstruction of three-dimensional (3D) shape of objects is one of core problems in computer vision with a lot of commercial applications. However, the 3D scanning for point cloud-based video streaming is expensive and is generally unattainable to an average user due to required setup of multiple depth sensors. We propose a novel hybrid modular artificial neural network (ANN) architecture, which can reconstruct smooth polygonal meshes from a single depth frame, using a priori knowledge. The architecture of neural network consists of separate nodes for recognition of object type and reconstruction thus allowing for easy retraining and extension for new object types. We performed recognition of nine real-world objects using the neural network trained on the ShapeNetCore model dataset. The results evaluated quantitatively using the Intersection-over-Union (IoU), Completeness, Correctness and Quality metrics, and qualitative evaluation by visual inspection demonstrate the robustness of the proposed architecture with respect to different viewing angles and illumination conditions.Article Measuring the Reusable Quality for Xml Schema Documents(Budapest Tech, 2013) Thaw, Tinzar; Misra, SanjayeXtensible Markup Language (XML) based web applications are widely used for data describing and providing internet services. The design of XML schema document (XSD) needs to be quantified with software with the reusable nature of XSD. This nature of documents helps software developers to produce software at a lower software development cost. This paper proposes a metric Entropy. Measure of Complexity (EMC), which is intended to measure the reusable quality of XML schema documents. A higher EMC value tends to more reusable quality, and as well, a higher EMC value implies that this schema document contains inheritance feature, elements and attributes. For empirical validation, the metric is applied on 70 WSDL schema files. A comparison with similar measures is also performed. The proposed EMC metric is also validated practically and theoretically. Empirical, theoretical and practical validation and a comparative study proves that the EMC metric is a valid metric and capable of measuring the reusable quality of XSD.Article Citation - WoS: 3Citation - Scopus: 3Impact of Mobile Received Signal Strength (rss) on Roaming and Non-Roaming Mobile Subscribers(Springer, 2023) Karanja, Hinga Simon; Misra, Sanjay; Atayero, A. A. A.Mobile phones have transitioned from voice-centric devices to smart devices supporting functionalities like high-definition video and games, web browsers, radio reception, and video conferencing. Mobile phones are used in telemedicine, health monitoring applications, navigation tools, and gaming devices, among other applications. Given the above, Mobile broadband connectivity affects mobile access to the internet and voice communications. This paper assesses the impact of the Reference Signal Received Power (RSRP) and broadband connectivity around Covenant University. LTE, GSM, and HSPA mobile signal measurement campaigns were conducted around Covenant University in Ota, Ogun state, Nigeria. To investigate the best optimized mobile network for mobile subscribers on roaming services and subscriber's high performance and data rates. After the experiment, exploratory data analysis was used to visualize the best mobile network; GSM proved as stable than LTE and HSPA.Article Citation - WoS: 85Citation - Scopus: 133Detecting Cassava Mosaic Disease Using a Deep Residual Convolutional Neural Network With Distinct Block Processing(Peerj inc, 2021) Oyewola, David Opeoluwa; Dada, Emmanuel Gbenga; Misra, Sanjay; Damasevicius, RobertasFor people in developing countries, cassava is a major source of calories and carbohydrates. However, Cassava Mosaic Disease (CMD) has become a major cause of concern among farmers in sub-Saharan Africa countries, which rely on cassava for both business and local consumption. The article proposes a novel deep residual convolution neural network (DRNN) for CMD detection in cassava leaf images. With the aid of distinct block processing, we can counterbalance the imbalanced image dataset of the cassava diseases and increase the number of images available for training and testing. Moreover, we adjust low contrast using Gamma correction and decorrelation stretching to enhance the color separation of an image with significant band-to-band correlation. Experimental results demonstrate that using a balanced dataset of images increases the accuracy of classification. The proposed DRNN model outperforms the plain convolutional neural network (PCNN) by a significant margin of 9.25% on the Cassava Disease Dataset from Kaggle.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: 29Citation - Scopus: 40Software Code Smell Prediction Model Using Shannon, Renyi and Tsallis Entropies(Mdpi, 2018) Gupta, Aakanshi; Suri, Bharti; Kumar, Vijay; Misra, Sanjay; Blazauskas, Tomas; Damasevicius, RobertasThe current era demands high quality software in a limited time period to achieve new goals and heights. To meet user requirements, the source codes undergo frequent modifications which can generate the bad smells in software that deteriorate the quality and reliability of software. Source code of the open source software is easily accessible by any developer, thus frequently modifiable. In this paper, we have proposed a mathematical model to predict the bad smells using the concept of entropy as defined by the Information Theory. Open-source software Apache Abdera is taken into consideration for calculating the bad smells. Bad smells are collected using a detection tool from sub components of the Apache Abdera project, and different measures of entropy (Shannon, Renyi and Tsallis entropy). By applying non-linear regression techniques, the bad smells that can arise in the future versions of software are predicted based on the observed bad smells and entropy measures. The proposed model has been validated using goodness of fit parameters (prediction error, bias, variation, and Root Mean Squared Prediction Error (RMSPE)). The values of model performance statistics (R-2, adjusted R-2, Mean Square Error (MSE) and standard error) also justify the proposed model. We have compared the results of the prediction model with the observed results on real data. The results of the model might be helpful for software development industries and future researchers.Article Citation - WoS: 20Citation - Scopus: 25Quantitative Quality Evaluation of Software Products by Considering Summary and Comments Entropy of a Reported Bug(Mdpi, 2019) Kumari, Madhu; Misra, Ananya; Misra, Sanjay; Fernandez Sanz, Luis; Damasevicius, Robertas; Singh, V. B.A software bug is characterized by its attributes. Various prediction models have been developed using these attributes to enhance the quality of software products. The reporting of bugs leads to high irregular patterns. The repository size is also increasing with enormous rate, resulting in uncertainty and irregularities. These uncertainty and irregularities are termed as veracity in the context of big data. In order to quantify these irregular and uncertain patterns, the authors have appliedentropy-based measures of the terms reported in the summary and the comments submitted by the users. Both uncertainties and irregular patterns have been taken care of byentropy-based measures. In this paper, the authors considered that the bug fixing process does not only depend upon the calendar time, testing effort and testing coverage, but it also depends on the bug summary description and comments. The paper proposed bug dependency-based mathematical models by considering the summary description of bugs and comments submitted by users in terms of the entropy-based measures. The models were validated on different Eclipse project products. The models proposed in the literature have different types of growth curves. The models mainly follow exponential, S-shaped or mixtures of both types of curves. In this paper, the proposed models were compared with the modelsfollowingexponential, S-shaped and mixtures of both types of curves.
