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Energy Access Assessment Report Focusing on Energy Poverty and Energy Demand for Rwanda

Energy Access Assessment Report Focusing on Energy Poverty a...

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Sciences and Techniques of Automatic Control and computer engineering MI-STA, IEEE International Maghreb Meeting of the Conference on

作者： Adimchinobi Asiegbu Ali Almaktoof Abdurazag Khalat Dep. of Electrical Electronics and Computer Engineering Cape Peninsula University of Technology Cape Town South Africa Dep. of Electrical and Electronics Engineering Sabratha University Sabratha Libya

This technical report is a researched document that examines energy access in Rwanda, focusing on energy poverty assessment and energy demand assessment. The key findings and observations can help mitigate the energy access problems and improve access to modern energy in Rwanda. Studies have shown that sub-Saharan African countries have poor access or no access to modern energy, Rwanda being part of sub-Saharan Africa also has Poor access to modern and clean energy. To carefully study these energy access problems and proffer solutions to increase energy access in Rwanda based on realities in today’s Africa, (where most households fall below poverty lines, with social issues, low Purchasing Power Parity (PPP) and Gross Domestic Power (GDP)), an assessment of these energy problems is done based on Energy Poverty Assessment (EPA) and Energy Demand Assessment (EDA) Composite Multidimensional Indicators (CMDI), respectively. Based on the findings of this research, non-poor energy households increased their energy consumption by 29.26% to 0.68 billion kWh. The clean cooking gas usage in Rwanda is very low at 2.1%, The 2016 estimated electricity consumption is 0.5273 billion kWh, growing by 57.41% to 0.83 billion kWh for energy-poor households in 2021, compared to 52.6% predicted by International Energy Agency (IEA). Finally, there is a direct relationship between energy access and economic development including quality of life, standard of living, per capita income, urbanization, modern infrastructure, etc. Thus, the key findings and observations in this research report will improve economic and infrastructural development in Rwanda, if implemented.

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Classification and Evaluation Framework of Automated testing tools for agile software: Technical Review

Classification and Evaluation Framework of Automated testing...

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Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Mogeeb A.A. Moseh Nashwan Ameen Al-Khulaidi Abdu H. Gumaei Ayman Alsabry Ali A. A. Musleh Software Engineering Dept Faculty of Engineering & Information Technology Taiz University Taiz Yemen Industrial Dept. Engineering Dep Faculty of Engineering & Information Technology Taiz Univerity Taiz Yemen Computer Science Dept. College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz University Al-Kharj Saudi Arabia Department of Computer Science International University of Technology Twintech Sana’a Yemen Faculty of Computer Science & Information Technology International University of Technology Twintech Sana’a Yemen

ISBN: (数字)9798350354133

ISBN: (纸本)9798350354140

Test automation is crucial for agile software projects to enable frequent delivery of working software with cost and time and minimal bugs. However, selecting the right automated testing tool is considered challenging due to the wide range of such existing tools. Additionally, the challenges occur clearly due to several issues such as the programming code language, the categorization of the developed system, and the tester’s knowledge and skills. This paper aims to address this gap by proposing an evaluation framework for comparing and classifying the existing automated testing tools used in agile projects. The framework is developed based on an extensive literature review of existing agile testing methodologies and common commercial automation testing techniques. The key criteria for tool evaluation are identified to cover the main testing objective aspects such as test design support, testing interfaces, reporting capabilities, etc. These criteria are considered the core methodology for this study used to analyze and compare the popular open-source and commercial tools. The proposed evaluation framework provides agile practitioners with guidelines to assist in selecting the appropriate tools based on their specific project needs such as budget, timelines, and technical expertise. This study is considered a comparative evaluation of existing agile testing tools to highlight their key strengths and limitations. The findings of this study categorized the testing tools based on the interface, code, design, and report features. This research contributes to assisting the project developer and tester in selecting suitable tools for the adoption of automated testing tools in their agile software projects. It also identifies the direction for future work, such as integrations with modern development methodologies and technologies.

关键词： Codes Automation Reviews Agile software development Programming Software Software measurement

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Location-enabled IoT (LE-IoT): Indoor Localization for IoT Environments using Machine Learning

Location-enabled IoT (LE-IoT): Indoor Localization for IoT E...

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International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Tanveer Ahmad Xue Jun Li Muhammad Ashfaq Michalis Savva Iacovos Ioannou Vasos Vassiliou Department of Computer Science University of Cyprus Nicosia Cyprus Dep of Electrical and Electronic Engineering Auckland University of Technology Auckland New Zealand Department of Electronics Engineering University of Engineering & Technology Taxila Pakistan Department of Computer Science University of Cyprus & CYENS Centre of Excellence Nicosia Cyprus

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

In recent years, the concept of the Internet of things (IoT) has become ubiquitous among several applications. However, traditional localization methods face challenges in accurately measuring sensor node positions, particularly in scenarios involving wireless signal instability, energy harvesting, anchor mobility, latency, and dense environmental conditions. However, these problems open the new ways to utilize machine learning (ML) and self-calibration for localization. To defeat these problems, in this paper, we have proposed a new localization technique, which reduces the localization error caused by the iterations in a triangulation method and drastically shortens the computation time for full network coverage despite noisy environments. First, we present a localization technique based on a looped network. The link quality induction (LQI) is used to formulate multiple feature vectors for the localization problem, solved using linear regression. Second, we examine the appropriateness of a few algorithms under different tradeoffs by testing the localization accuracy for different network parameters, including the anchor node density, additive noise, and quality of the wireless channel. The simulation achieves exciting results that the adoption of a support vector machine (SVM) and nonlinear regression model applied with a radial basis function (RBF) kernel leads to an enhanced localization error with Root-Mean Square Error (RMSE) of 0.25m. Furthermore, we gain 48.5% accuracy in the localization error by implementing two models.

关键词： Location awareness Support vector machines Wireless communication Wireless sensor networks Accuracy Machine learning algorithms Vectors

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Deep Learning Technique for Real-Time Forest Fire Detection from Video Streams

Deep Learning Technique for Real-Time Forest Fire Detection ...

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Intelligent Systems and Embedded Design (ISED), International Conference on

作者： Nidhi Gupta Sujata Chakravarty Satyabrata Dash Dept. of Computer Science & Engineering Centurion University of Technology & Management Odisha India Dep. of Computer Science and Engineering Gandhi Institute of Technology & Management (GITAM Deemed to be University) Andhra Pradesh India

Forest fires are currently the most common issue that we are dealing with. The resources that have been lost are irreplaceable. Forest fires are uncontrollable fires that occur in nature as a result of human involvement or any other natural event. Forest fires can be so large that putting them out takes a long time. Contrasting with previous years, there has been a striking surge in the frequency of forest fires. Changes in climatic conditions are the key factor affecting the scope of forest fires. Long dry spells in the spring and summer make the woodlands particularly vulnerable. The extent of forest fires is mostly determined by weather conditions such as precipitation and wind, as well as the terrain's architecture. Long dry spells in the spring and summer make the woodlands particularly vulnerable. The extent of forest fires is mostly determined by weather conditions such as precipitation and wind, as well as the terrain's architecture. The incorporation of a Video Fire Detection model significantly enhances the efficiency of fire detection systems, particularly in large spaces. Establishing a video fire detection system involves focusing on spatial, spectral, and temporal indicators, as well as flame picture segmentation, recognition, tracking, and prediction. Analytical techniques, specifically utilizing ResNet50 and VGG16 models, can be applied to identify pool fire images through these segmentation processes, contributing to more robust fire detection capabilities.

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Brain Tumor Classification System Using Decision Tree Algorithm

Brain Tumor Classification System Using Decision Tree Algori...

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Cybernetics and Innovations (ICCI), International Conference on

作者： Sattarpoom Thaiparnit Thanakrit Janchidfah Adil Farooq Dep. Of Information System and Computer Business Faculty of Business Administration Rajamangala University of Technology Suvarnabhumi Suphan Buri Thailand dep. Of Digital Media Technology Muban Chombueng Rajabhat University Ratchaburi Thailand Department of Electronic Engineering Maynooth University Ireland

ISBN: (数字)9798331533267

ISBN: (纸本)9798331533274

This research aims to study, design, and develop a brain tumor classification system using artificial intelligence, specifically decision tree algorithms. The system's primary objective is to assist medical personnel in making decisions, as distinguishing between two types of brain tumors-benign and malignant (cancerous)-can be challenging, especially for less experienced medical staff. Due to the similarities between these two types of tumors, it may be difficult for medical practitioners with limited expertise to differentiate between them in a timely manner. The proposed brain tumor classification system is designed to address this challenge. The research team conducted the study over approximately seven months, starting from the second semester of the 2023 academic year through the first semester of the 2024 academic year. Experimental results revealed that among the tree-based algorithms, Random Forest achieved the highest accuracy, followed by M5P. The best average accuracy from the experiments was obtained using a 70% training and 30% testing split, yielding an accuracy of 96.83%. Therefore, the research team selected the 70% training and 30% testing split for model development, as it provided the highest accuracy compared to the 60% training and 40% testing split, and the 80% training and 20% testing split, which showed lower accuracy. The results demonstrate that the 70% training and 30% testing approach is optimal for the brain tumor classification system, ensuring high accuracy in classifying brain tumors.

关键词： Training Technological innovation Accuracy Machine learning algorithms Brain tumors Brain modeling Classification algorithms Decision trees Testing Cancer

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Performance Analysis of Intelligent Reflecting Surfaces for 5G/6G-Enabled Future Smart Industries with a Focus on Millimeter-Wave Band Communications

Performance Analysis of Intelligent Reflecting Surfaces for ...

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IEEE International Conference on Communications Workshops, ICC

作者： Muhammad Farhan Khan Ali Raza Adeel Iqbal Adnan Rashid Muhammad Ali Jamshed Dirk Pesch School of Computer Science and Information Technology University College Cork Cork Ireland Dep. of Electrical and Computer Engineering COMSATS University Islamabad Pakistan Dep. of Info. & Com. Engineering Yeungnam University Gyeongsan-si Republic of Korea Dep. of Electrical & Information Engineering Politecnico di Bari Bari Italy James Watt School of Engineering University of Glasgow Glasgow U.K

ISBN: (数字)9798350304053

ISBN: (纸本)9798350304060

Industry 4.0's emergence necessitates reliable communication systems. Millimeter-wave (mmWave) communication is a promising solution, but challenges like limited coverage and atmospheric absorption persist. The Intelligent Reflecting Surfaces (IRS) offers transformative potential by dynamically manipulating wave propagation to improve millimeter-wave (mmWave) communication. This research investigates the impact of the distance of Industrial User Equipment (iUE) from the IRS and Base Station (BS), and the height of the IRS from the ground, along with the impact of sum throughput by increasing the number of IRS elements. The IRS-assisted system exhibits enhanced performance within the mmWave frequency band compared to the sub-6 GHz band. The observed achievable rate gains, exceeding 200% on average, underscore the significant performance enhancement enabled by IRS deployments. Moreover, increasing the number of IRS elements significantly enhances the overall throughput. The decrease in required transmit power with an increasing number of Intelligent Reflecting Surfaces IRS elements can be attributed to the enhanced ability of IRS to efficiently reflect and manipulate electromagnetic waves. As more IRS elements are deployed, they collectively contribute to optimizing signal propagation, allowing for better control and redirection of the transmitted signals. This phenomenon enables the system to achieve the desired communication objectives with less overall transmit power. Additionally, the attainable capacity of the examined IRS-assisted wireless communication system exhibits growth alongside an increase in the elevation of the IRS installation. Results showcase the potential of IRSs to enhance coverage and communication reliability, providing valuable insights for designing efficient wireless systems in smart factories and Industry 4.0 applications.

关键词： Wireless communication Industries Surface waves Conferences Throughput Millimeter wave propagation Reliability engineering

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GUI-PV Application Tool for Teaching Performance of PV System using MATLAB-Graphical User Interface Environment 1

GUI-PV Application Tool for Teaching Performance of PV Syste...

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1st IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and computer engineering, MI-STA 2021

作者： Almaktoof, Ali Shebani, Nafaa Elfallah, Ali Cape Peninsula University of Technology Electrical Electronics and Computer Engineering Dep. Cape Town South Africa

ISBN: (纸本)9781665418560

A MATLAB-Graphical User Interface (GUI) based educational software which could aid in the analysis and education of photovoltaic (PV) modules is presented in this paper. The MATLAB-GUI for studying the PV module based on the evaluation of the current, voltage and power characteristics as well as performance evaluation of the PV module under different values of radiation and temperature are presented. The Graphical User Interface-Photovoltaic (GUI-PV) application is developed to simulate the characteristics of PV module and show the effects of temperature and solar radiation on the PV modules. In addition, the GUI-PV can provide PV module specifications and parameters including maximum power, current and voltage, fill factor and efficiency,...etc. Two GUI-PV models are developed for PV module characteristics and performance evaluation of solar module. Testing of the GUI-PV platform exposes that students who are trained using GUI-PV software easily understood the concept of a solar PV panel and defined the maximum power of the solar photovoltaic modules and some other parameters. © 2021 IEEE.

关键词： MATLAB

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TIoT: A Trust by Design Architecture for Secure and Private Internet of Things (IoT) 21

TIoT: A Trust by Design Architecture for Secure and Private ...

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21st International Multi-Conference on Systems, Signals and Devices, SSD 2024

作者： Alsheakh, H. Mahdi, Tareq Nasser Kadhm, Mustafa S. Al Shammari, Abeer Abdulsahib, Fatimah I. Taher, Hazeem B Algriree, Waleed Alobaidi, Marwa Q. Mohammed, Hayder Dhafer College of Science Mustansiriyah University Department of Computer Science Baghdad Iraq College of Pharmacy Mustansiriyah University Clinical Laboratory Science Baghdad Iraq Ministry of Science and Technology Baghdad Iraq Szechenyi Istvan Egyetem Department of Computer Science Gyor9026 Hungary University of Thi-Qar Department of Computer Science Thi-Qar Iraq University Putra Malaysia Dep. of Wireless Communication and Network Engineering Selangor Malaysia National Engineering School of Sfax Sfax University Sfax Tunisia College of Pharmacy Mustansiriyah University Baghdad Iraq

ISBN: (纸本)9798350374131

The Internet of Things (loT) facilitates the interconnection of a vast array of devices, services, and individuals for data exchange in multi-domain loT ecosystems, the social, physical, and cyber domains. That emerges various security, privacy, and trust issues, such as vulnerabilities, threats, and attacks. Addressing these challenges requires innovative solutions. New controls (solutions) are needed. Trust by design can be one of these controls, supporting security and privacy (among other system components). This paper proposes a Trusted loT (TloT), a trust-by-design model, and highlights the author's principal contributions. First, it advocates for implementing Tlo T through trust services. Second, it outlines an architecture for using trust by design in loT, including the design of its top-level structure and activities. Minor contributions include overviews of loT and trust, as well as looking at security and privacy in terms of security services and privacy services, respectively. © 2024 IEEE.

关键词： Internet of things

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Automated Crop Harvesting, Growth Monitoring and Disease Detection System for Vertical Farming Greenhouse 3

Automated Crop Harvesting, Growth Monitoring and Disease Det...

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3rd International Conference on Advancements in Computing, ICAC 2021

作者： Jayasekara, Charith Banneka, Sajani Pasindu, Gihan Udawaththa, Yukthi Wellalage, Sasini Abeygunawardhane, Pradeep K.W. Sri Lanka Institute of Information Technology Dep. of Computer Systems Engineering Malabe10115 Sri Lanka

ISBN: (纸本)9781665408622

Greenhouses are a type of cultivation method used to optimize the production of crops by using controlled climatic conditions and other external factors. They are widely used in agriculture both globally and locally. Vertical farming is the modern practice of growing crops in vertically stacked layers in warehouses that aims to optimize and develop plant growth by using controlled environment agriculture. This type of agriculture concept is practiced in Sri Lanka at present. This research paper proposes a robot which consists of a specific navigation system and harvesting mechanism that can be used inside greenhouses. The proposed system can be implemented to harvest lettuce in the vertical farming greenhouses where lettuce needs to be harvested with care to ensure the supermarket quality. The above-mentioned system helps to detect the diseases of plants also where a lot of time can be saved, and less effort is made with the use of this type of implementation. © 2021 IEEE.

关键词： Greenhouses

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Experimental Comparison of Global Planners for Trajectory Planning of Mobile Robots in an Unknown Environment with Dynamic Obstacles

Experimental Comparison of Global Planners for Trajectory Pl...

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Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Zehra Tüfekçi Gökhan Erdemir Department of Computer Engineering Istinye University İstanbul Turkiye Department of Computer Science and Engineering Istanbul Sabahattin Zaim University Dep. of Engineering Management & Technology University of Tennessee at Chattanooga Tennessee USA

Interacting with their workspace, detecting obstacles, and real-time path planning in the field to reach the goal in the unknown environment are current working areas of mobile robotics. Working in an unknown environment with dynamic obstacles is a challenging topic for autonomous robots, which need to protect themselves from the dynamic obstacles they encounter, not damage the obstacle, and re-plan their path according to their new position. This study performed an experimental comparison of three different global planners for trajectory planning of mobile robots in an unknown environment with dynamic obstacles. Global Planner, Carrot Planner, and NavfnROS planners in the ROS package were used as global planners in two different mazes with dynamic obstacles. The durations from the start to the goal point in the two designed environments were determined for each global planner.

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