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Telematics as a Transformative Agent for the Zimbabwean Auto Insurance Ecosystem

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Journal of computer and Communications 2024年第7期12卷 39-58页

作者： Prosper Tafadzwa Denhere Joyce Denhere Gracious Mutipforo Chipo Katsande Allan Muzenda Nelson Matanana Gibson Muridzi department of computer science and information systems Manicaland State University of Applied Sciences Mutare Zimbabwe department of Risk Advisory Manicaland State University of Applied Sciences Mutare Zimbabwe department of Business sciences Manicaland State University of Applied Sciences Mutare Zimbabwe

Zimbabwe has witnessed the evolution of information Communication Technology (ICT). The vehicle population soared to above 1.2 million hence rendering the Transport and Insurance domains complex. Therefore, there is a need to look at ways that can augment conventional Vehicular Management information systems (VMIS) in transforming business processes through Telematics. This paper aims to contextualise the role that telematics can play in transforming the Insurance Ecosystem in Zimbabwe. The main objective was to investigate the integration of Usage-Based Insurance (UBI) with vehicle tracking solutions provided by technology companies like Econet Wireless in Zimbabwe, aiming to align customer billing with individual risk profiles and enhance the synergy between technology and insurance service providers in the motor insurance ecosystem. A triangulation through structured interviews, questionnaires, and literature review, supported by information systems Analysis and Design techniques was conducted. The study adopted a case study approach, qualitatively analyzing the complexities of the Telematics insurance ecosystem in Zimbabwe, informed by the TOGAF framework. A case-study approach was applied to derive themes whilst applying within and cross-case analysis. Data was collected using questionnaires, and interviews. The findings of the research clearly show the importance of Telematics in modern-day insurance and the positive relationship between technology and insurance business performance. The study, therefore revealed how UBI can incentivize positive driver behavior, potentially reducing insurance premiums for safe drivers and lowering the incidence of claims against insurance companies. Future work can be done on studying the role of Telematics in combating highway crime and corruption.

关键词： Telematics Vehicle Tracking systems Usage Based Insurance Digital Insurance Vehicle Management information systems Intelligent Transportation systems

An Assessment on the Impact of Technological Addiction on Workplace Productivity: Case of the Public Sector in Zimbabwe

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World Journal of Engineering and Technology 2024年第3期12卷 635-650页

作者： Nelson Matanana Prosper Tafadzwa Denhere David Chibhoyi Allen Mutumwa Sithole Morgen Noah Ariel Mutongoreni department of computer science and information systems at manicaland state university of applied sciences Mutare Zimbabwe department of Human Resources Management at manicaland state university of applied sciences Mutare Zimbabwe department of applied Business sciences at manicaland state university of applied sciences Mutare Zimbabwe

With the increasing integration of technology in modern workplaces, concerns have emerged regarding the addictive nature of technology and its potential consequences on employee productivity. This research aims to investigate the impact of technological addiction on workplace productivity within the public sector of Zimbabwe. The study employed a mixed-methods approach, combining surveys, interviews, and a case study analysis, to examine the prevalence and effects of technological addiction in affecting productivity in the public sector of Zimbabwe. The findings indicate that excessive use of social media, and other digital distractions is a growing concern in the public sector, leading to decreased focus, missed deadlines, and strained teamwork. Factors such as unrestricted internet access, lack of clear usage policies, and inadequate self-regulation contribute to the problem The research outcomes also highlight the need for awareness and interventions to address social media addiction in the workplace, promote healthier technology use, and uphold productivity and employee well-being.

关键词： Technology Addiction Workplace Productivity Technology Public Sector Zimbabwe

Evaluating and Addressing Interoperability Constraints in Health information systems for Enhanced Healthcare Delivery in Zimbabwe

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Journal of computer and Communications 2024年第7期12卷 133-154页

作者： Prosper Tafadzwa Denhere Nelson Matanana Munyaradzi Zhou Caleb Manjeese Talent Mawere department of Marketing and information sciences Midlands State University Gweru Zimbabwe department of computer science and information systems Manicaland State University of Applied Sciences Mutare Zimbabwe department of Mathematics and computer science Great Zimbabwe University Masvingo Zimbabwe

Interoperability constraints in health information systems pose significant challenges to the seamless exchange and utilization of health data, hindering effective healthcare delivery. This paper aims to evaluate and address these constraints to enhance healthcare delivery. The study examines the current state of interoperability in health information systems, identifies the key constraints, and explores their impact on healthcare outcomes. Various approaches and strategies for addressing interoperability constraints are discussed, including the adoption of standardized data formats, implementation of interoperability frameworks, and establishment of robust data governance mechanisms. Furthermore, the study highlights the importance of stakeholder collaboration, policy development, and technical advancements in achieving enhanced interoperability. The findings emphasize the need for a comprehensive evaluation of interoperability constraints and the implementation of targeted interventions to promote seamless data exchange, improve care coordination, and enhance patient outcomes in healthcare settings.

关键词： Health information System Interoperability Interoperability Constraints

Contrast Normalization Strategies in Brain Tumor Imaging:From Preprocessing to Classification

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computer Modeling in Engineering & sciences 2024年第8期140卷 1539-1562页

作者： Samar M.Alqhtani Toufique A.Soomro Faisal Bin Ubaid Ahmed Ali Muhammad Irfan Abdullah A.Asiri department of information systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia department of Electronic Engineering The University of LarkanoLarkanaSindh75660Pakistan computer science department Sukkur IBA UniversitySukkurSindh65200Pakistan Eletrical Engineering department Sukkur IBA UniversitySukkurSindh65200Pakistan Electrical Engineering department College of EngineeringNajran UniversityNajran61441Saudi Arabia Radiological sciences department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia

Cancer-related to the nervous system and brain tumors is a leading cause of mortality in various *** resonance imaging(MRI)and computed tomography(CT)are utilized to capture brain *** plays a crucial role in the diagnosis of brain tumors and the examination of other brain ***,manual assessment of MRI images by radiologists or experts is performed to identify brain tumors and abnormalities in the early stages for timely ***,early diagnosis of brain tumors is intricate,necessitating the use of computerized *** research introduces an innovative approach for the automated segmentation of brain tumors and a framework for classifying different regions of brain *** proposed methods consist of a pipeline with several stages:preprocessing of brain images with noise removal based on Wiener Filtering,enhancing the brain using Principal Component Analysis(PCA)to obtain well-enhanced images,and then segmenting the region of interest using the Fuzzy C-Means(FCM)clustering technique in the third *** final step involves classification using the Support Vector Machine(SVM)*** classifier is applied to various types of brain tumors,such as meningioma and pituitary tumors,utilizing the Contrast-Enhanced Magnetic Resonance Imaging(CE-MRI)*** proposed method demonstrates significantly improved contrast and validates the effectiveness of the classification framework,achieving an average sensitivity of 0.974,specificity of 0.976,accuracy of 0.979,and a Dice Score(DSC)of ***,this method exhibits a shorter processing time of 0.44 s compared to existing *** performance of this method emphasizes its significance when compared to state-of-the-art methods in terms of sensitivity,specificity,accuracy,and *** enhance the method further in the future,it is feasible to standardize the approach by incorporating a set of classifiers to increase the robustness of the brain classi

关键词： Brain tumor magnetic resonance imaging principal component analysis fuzzy c-clustering support vector machine

Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features

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computers, Materials & Continua 2024年第3期78卷 3683-3701页

作者： Asifa Mehmood Qureshi Naif Al Mudawi Mohammed Alonazi Samia Allaoua Chelloug Jeongmin Park department of Creative Technologies Air UniversityIslamabad46000Pakistan department of computer science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia department of information systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia department of information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia department of computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Road traffic monitoring is an imperative topic widely discussed among *** used to monitor traffic frequently rely on cameras mounted on bridges or ***,aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger *** this end,different models have shown the ability to recognize and track ***,these methods are not mature enough to produce accurate results in complex road ***,this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image *** extracted frames were converted to grayscale,followed by the application of a georeferencing algorithm to embed coordinate information into the *** masking technique eliminated irrelevant data and reduced the computational cost of the overall monitoring ***,Sobel edge detection combined with Canny edge detection and Hough line transform has been applied for noise *** preprocessing,the blob detection algorithm helped detect the *** of varying sizes have been detected by implementing a dynamic thresholding *** was done on the first image of every ***,to track vehicles,the model of each vehicle was made to find its matches in the succeeding images using the template matching *** further improve the tracking accuracy by incorporating motion information,Scale Invariant Feature Transform(SIFT)features have been used to find the best possible match among multiple *** accuracy rate of 87%for detection and 80%accuracy for tracking in the A1 Motorway Netherland dataset has been *** the Vehicle Aerial Imaging from Drone(VAID)dataset,an accuracy rate of 86%for detection and 78%accuracy for tracking has been achieved.

关键词： Unmanned Aerial Vehicles(UAV) aerial images dataset object detection object tracking data elimination template matching blob detection SIFT VAID

Intelligent Solution System for Cloud Security Based on Equity Distribution:Model and Algorithms

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computers, Materials & Continua 2024年第1期78卷 1461-1479页

作者： Sarah Mustafa Eljack Mahdi Jemmali Mohsen Denden Mutasim Al Sadig Abdullah M.Algashami Sadok Turki department of computer science and information College of Science at ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia department of computer science College of Computing and InformaticsUniversity of SharjahSharjahUnited Arab Emirates Higher Institute of computer science and Mathematics University of MonastirMonastir5000Tunisia Mars Laboratory University of SousseSousseTunisia department of Logistic and Maintenance UFR MIM at MetzUniversity of LorraineMetzFrance department of computer and information Technologies College of Telecommunicationand Information Riyadh CTITechnical and Vocational Training Corporation TVTCRiyadh12464Saudi Arabia department of computer science Higher Institute of Applied Sciences of SousseSousse UniversitySousse4000Tunisia

In the cloud environment,ensuring a high level of data security is in high *** planning storage optimization is part of the whole security process in the cloud *** enables data security by avoiding the risk of data loss and data *** development of data flow scheduling approaches in the cloud environment taking security parameters into account is *** our work,we propose a data scheduling model for the cloud *** is made up of three parts that together help dispatch user data flow to the appropriate *** first component is the Collector Agent whichmust periodically collect information on the state of the network *** second one is the monitoring agent which must then analyze,classify,and make a decision on the state of the link and finally transmit this information to the *** third one is the scheduler who must consider previous information to transfer user data,including fair distribution and reliable *** should be noted that each part of the proposedmodel requires the development of its *** this article,we are interested in the development of data transfer algorithms,including fairness distribution with the consideration of a stable link *** algorithms are based on the grouping of transmitted files and the iterative *** proposed algorithms showthe performances to obtain an approximate solution to the studied problem which is an NP-hard(Non-Polynomial solution)*** experimental results show that the best algorithm is the half-grouped minimum excluding(HME),with a percentage of 91.3%,an average deviation of 0.042,and an execution time of 0.001 s.

关键词： Cyber-security cloud computing cloud security algorithms heuristics

Clinically adaptable machine learning model to identify early appreciable features of diabetes

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Intelligent Medicine 2024年第1期4卷 22-32页

作者： Nurjahan Nipa Mahmudul Hasan Riyad Shahriare Satu Walliullah Koushik Chandra Howlader Mohammad Ali Moni department of information and Communication Technology Bangabandhu Sheikh Mujibur Rahman Digital UniversityBangladeshKaliakairGazipur1750 Bangladesh department of applied Mathematics Noakhali Science and Technology UniversityNoakhali3814Bangladesh department of Management information systems Noakhali Science and Technology UniversityNoakhali3814Bangladesh department of computer science and Telecommunication Engineering Noakhali Science and Technology UniversityNoakhali3814Bangladesh department of computer science North Dakota State UniversityFargo58105NDUnited States School of Health and Rehabilitation sciences Faculty of Health and Behavioural SciencesThe University of QueenslandSt LuciaQLD 4072Australia

Objective Diabetes mellitus is a serious disease where the body of affected patients are failed to produce enough insulin that causes an abnormality of blood *** disease happens for a number of reasons including modern lifestyle,lethargic attitude,unhealthy food consumption,family history,age,overweight,*** aim of this study was to propose a machine learning based prediction model that detected diabetes at the *** In this work,we collected 520 patients records from the university of California,Irvine(UCI)machine learning repository of Sylhet Diabetes Hospital,***,a similar questionnaire of that hospital was followed and assembled 558 patients records from all over Bangladesh through this ***,we accumulated patient records of these two *** the next step,these datasets were cleaned and applied thirty five state-of-arts classifiers such as logistic regression(LR),K nearest neighbors(KNN),support vector classifier(SVC),Nave Byes(NB),decision tree(DT),random forest(RF),stochastic gradient descent(SGD),Perceptron,AdaBoost,XGBoost,passive aggressive classifier(PAC),ridge classifier(RC),Nu-support vector classifier(NuSVC),linear support vector classifier(LSVC),calibrated classifier CV(CCCV),nearest centroid(NC),Gaussian process classifier(GPC),multinomial NB(MNB),complement NB,Bernoulli NB(BNB),categorical NB,Bagging,extra tree(ET),gradiant boosting classifier(GBC),Hist gradiant boosting classifier(HGBC),one vs rest classifier(OVsRC),multi-layer perceptron(MLP),label propagation(LP),label spreading(LS),stacking,ridge classifier CV(RCCV),logistic regression CV(LRCV),linear discriminant analysis(LDA),quadratic discriminant analysis(QDA),and light gradient boosting machine(LGBM)to explore best stable predictive *** performance of the classifiers has been measured using five metrics such as accuracy,precision,recall,F1-score,and area under the receiver operating ***,these outcomes were interpret

关键词： Diabetes Early features Machine learning Classification

Complex-frequency waves:beat loss and win sensitivity

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Light(science & Applications) 2024年第2期13卷 181-183页

作者： Qingqing Cheng Tao L School of Optical-Electrical and computer Engineering University of Shanghai for Science and TechnologyShanghai200093China department of Respiratory Diseases and Critical Medicine Quzhou Hospital Affiliated to Wenzhou Medical UniversityQuzhou324000China National Laboratory of Solid state Microstructures College of Engineering and Applied SciencesNanjing UniversityNanjing210093China

Recent experiments have demonstrated that synthesized complex-frequency waves can impart a virtual gain to molecule sensing systems,which can effectively restore information lost due to intrinsic molecular *** enhancement notably amplifies the signal of trace molecular vibrational fingerprints,thereby substantially improving the upper limit of sensitivity.

关键词： thereby Complex limit

Unbalanced private set intersection with linear communication complexity

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science China(information sciences) 2024年第3期67卷 79-93页

作者： Quanyu ZHAO Bingbing JIANG Yuan ZHANG Heng WANG Yunlong MAO Sheng ZHONG department of computer science and Technology Nanjing University Purple Mountain Lab

The private set intersection(PSI) protocol allows two parties holding a set of integers to compute the intersection of their sets without revealing any additional information to each other. The unbalanced PSI schemes consider a specific setting where a client holds a small set of the size n and a server holds a much larger set of the size m(n ■ m). The communication overhead of state-of-the-art balanced PSI schemes is O(m + n) and the unbalanced PSI schemes are O(nlogm). In this paper, we propose a novel secure unbalanced PSI protocol based on a hash proof system. The communication complexity of our protocol grows only linearly with the size of the small set. In other words, our protocol achieves communication overhead of O(n). We test the performance on a personal computer(PC) machine with a local area network(LAN)setting for the network. The experimental results demonstrate that the client only takes 2.01 s of online computation, 4.27 MB of round trip communication to intersect 1600 pieces of 32-bit integers with 220pieces of 32-bit integers with the security parameter λ = 512. Our protocol is efficient and can be applied to resource-constrained devices, such as cell phones.

关键词： unbalanced private set intersection Hash proof system linear communication complexity small set resource-constrained devices