Pub Date : 2024-07-17DOI: 10.53982/ajerd.2024.0702.08-j
Christiana Uchenna Ezeanya, Jane Ada Ukaigwe, Ignatius Nwoyibe Ogbaga, Adako Kwanashie
The need for online education has increased significantly. People now prefer to work to fulfill the necessities of life and pursue education to advance their skills because of the rising difficulty. This quest increases the demand for distance education thereby raising questions about how distance learning institutions can effectively assist their learners. Employment of Artificial Intelligence (AI) tools will not only provide solutions but also improve and render effective service and support to learners. AI-driven tools such as personalized or adaptive learning and chatbots for learner support have significantly helped to improve efficiency in virtual environments. This research aims to investigate how National Open University of Nigeria (NOUN) students view the contribution of AI tools in enhancing social interaction in their virtual learning environment. The study seeks to determine the requirements, inclinations, and challenges related to social interaction in the online learning space and explore how AI-powered solutions might effectively address these challenges to create a more dynamic and engaging learning environment. A survey was conducted to ascertain the level of awareness among the learners on the use of these tools, the challenges related to social interaction in online space and explore the ways AI-powered tools can effectively address issues in the learning environment to create a more dynamic and engaging learning environment. This study has identified that a greater number of learners in NOUN have little or no knowledge of the availability of these tools as well as how they can effectively use it. The level of awareness of the learners on the use of these tools is low. The study found 27.5% awareness and usage of AI tools provided by the institution. Several platforms were identified by respondents; however, ChatGPT was the most widely used AI platform. The study also discusses the importance of AI tools in enhancing collaboration and social engagement among learners. It identifies the challenges in integrating AI in Education and provides possible solutions to the challenges.
{"title":"Enhancing Social Engagement among Online Learners Using AI-Driven Tools: National Open University of Nigeria Learners' Perspective","authors":"Christiana Uchenna Ezeanya, Jane Ada Ukaigwe, Ignatius Nwoyibe Ogbaga, Adako Kwanashie","doi":"10.53982/ajerd.2024.0702.08-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0702.08-j","url":null,"abstract":"The need for online education has increased significantly. People now prefer to work to fulfill the necessities of life and pursue education to advance their skills because of the rising difficulty. This quest increases the demand for distance education thereby raising questions about how distance learning institutions can effectively assist their learners. Employment of Artificial Intelligence (AI) tools will not only provide solutions but also improve and render effective service and support to learners. AI-driven tools such as personalized or adaptive learning and chatbots for learner support have significantly helped to improve efficiency in virtual environments. This research aims to investigate how National Open University of Nigeria (NOUN) students view the contribution of AI tools in enhancing social interaction in their virtual learning environment. The study seeks to determine the requirements, inclinations, and challenges related to social interaction in the online learning space and explore how AI-powered solutions might effectively address these challenges to create a more dynamic and engaging learning environment. A survey was conducted to ascertain the level of awareness among the learners on the use of these tools, the challenges related to social interaction in online space and explore the ways AI-powered tools can effectively address issues in the learning environment to create a more dynamic and engaging learning environment. This study has identified that a greater number of learners in NOUN have little or no knowledge of the availability of these tools as well as how they can effectively use it. The level of awareness of the learners on the use of these tools is low. The study found 27.5% awareness and usage of AI tools provided by the institution. Several platforms were identified by respondents; however, ChatGPT was the most widely used AI platform. The study also discusses the importance of AI tools in enhancing collaboration and social engagement among learners. It identifies the challenges in integrating AI in Education and provides possible solutions to the challenges.","PeriodicalId":503569,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141830105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-17DOI: 10.53982/ajerd.2024.0702.09-j
T. E. Oshodin, K. Bello, B. Bolaji, B. Olorunfemi, Osagie Jolly Aighovbiosa, Friday Onuh
In this study, an attempt was made to develop a cooling system with an internal heat exchanger using a mixture of carbon dioxide (CO2) and liquefied petroleum gas (LPG) as refrigerants to help eliminate the global warming potential and other harmful environmental effects caused by conventional refrigerants'. The CO2 and LPG refrigeration experimental setup was constructed with varying sizes of capillary tubes, a pressure controller, an evaporator, and a gas hob. The working ranges were initially confirmed through exploratory experiments with low-pressure and high-pressure flow circuits, using and without an internal heat exchanger (IHE). The evaporator temperature helped to determine the proportional changes in the coefficient of performance (COP). The REFPROP software design was used to conduct experiments and determine the important process parameters. A confirmation test was performed to validate the expected results of the REFPROP software technique. The results showed that the experiments conducted using IHE had a COP with greater performance levels as follows: mean of 1.398 and SD of 0.367 which is greater than the value of the experiments undertaken without IHE which had a COP performance levels as follows: mean of 0.67 and SD of 0.19. The Paired Samples T-test found these differences to be significant, at p-value < 0.033. The null hypothesis was rejected, hence there is evidence to suggest that the COP of the experiment with IHE is statistically greater than the COP of the experiment without IHE, with a 95% confidence interval of -1.357 and -0.099
在这项研究中，我们尝试使用二氧化碳（CO2）和液化石油气（LPG）的混合物作为制冷剂，开发一种带有内部热交换器的冷却系统，以帮助消除传统制冷剂造成的全球升温潜能值和其他有害环境影响。二氧化碳和液化石油气制冷实验装置由不同尺寸的毛细管、压力控制器、蒸发器和燃气灶组成。通过使用或不使用内部热交换器（IHE）的低压和高压流动回路的探索性实验，初步确定了工作范围。蒸发器温度有助于确定性能系数（COP）的比例变化。REFPROP 软件设计用于进行实验和确定重要的工艺参数。为验证 REFPROP 软件技术的预期结果，进行了确认测试。结果显示，使用 IHE 进行的实验的 COP 性能水平更高：平均值为 1.398，标准差为 0.367，高于未使用 IHE 进行的实验的 COP 性能水平：平均值为 0.67，标准差为 0.19。通过配对样本 T 检验发现，这些差异显著，P 值小于 0.033。因此，有证据表明，有 IHE 的实验的 COP 统计上大于没有 IHE 的实验的 COP，95% 的置信区间为-1.357 和-0.099。
{"title":"Investigating Internal Heat Exchanger Performance in a VCR System with a CO2 and LPG Refrigerant Mixture","authors":"T. E. Oshodin, K. Bello, B. Bolaji, B. Olorunfemi, Osagie Jolly Aighovbiosa, Friday Onuh","doi":"10.53982/ajerd.2024.0702.09-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0702.09-j","url":null,"abstract":"In this study, an attempt was made to develop a cooling system with an internal heat exchanger using a mixture of carbon dioxide (CO2) and liquefied petroleum gas (LPG) as refrigerants to help eliminate the global warming potential and other harmful environmental effects caused by conventional refrigerants'. The CO2 and LPG refrigeration experimental setup was constructed with varying sizes of capillary tubes, a pressure controller, an evaporator, and a gas hob. The working ranges were initially confirmed through exploratory experiments with low-pressure and high-pressure flow circuits, using and without an internal heat exchanger (IHE). The evaporator temperature helped to determine the proportional changes in the coefficient of performance (COP). The REFPROP software design was used to conduct experiments and determine the important process parameters. A confirmation test was performed to validate the expected results of the REFPROP software technique. The results showed that the experiments conducted using IHE had a COP with greater performance levels as follows: mean of 1.398 and SD of 0.367 which is greater than the value of the experiments undertaken without IHE which had a COP performance levels as follows: mean of 0.67 and SD of 0.19. The Paired Samples T-test found these differences to be significant, at p-value < 0.033. The null hypothesis was rejected, hence there is evidence to suggest that the COP of the experiment with IHE is statistically greater than the COP of the experiment without IHE, with a 95% confidence interval of -1.357 and -0.099","PeriodicalId":503569,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141829155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-17DOI: 10.53982/ajerd.2024.0702.10-j
S. Akangbe, A. P. Adeagbo, Abiodun Ojetoye
A worldwide issue, global warming results from human activity changing the climate and having a negative impact on people, animals, and plants. However, in terms of plants, the sun provides the primary elements required for healthy growth of photosynthetic plants, which use the energy from the sun to create food for themselves. Light with varying wavelengths that serve distinct functions during the photosynthetic process are the essential elements that are captured from the sun. The wavelength of the ultraviolet (UV) component of sunlight varies, characterized as UV A (315–400 nm) and UV B (280–315 nm) are the primary components that must be precisely proportioned for a profitable farming. In order to lessen the impact of climate change on vegetable farming, this research suggests integrating light emitting diodes (LEDs) in artificial growing machines as well as planned irrigation systems as an alternate source of ultraviolet sunshine. To provide the necessary UV light combination, blue, red and white colours of light-emitting diodes (LEDs) were combined using diffusers. The red, blue, and white LEDs were used for two weeks, each 12 hours a day, to influence the plants growth, with red promoting photosynthesis, white improving it, and blue encouraging stem and leaf growth. An Arduino Uno was used to program both the hardware and software components of the automated growth machine. The outcome of planting varied vegetable plant under LED lights was contrasted with the outcome of planting the identical set of plants under direct sunlight. After the first and second weeks of planting, the plants' performances under both circumstances are comparable.
全球变暖是一个世界性问题，是人类活动改变气候的结果，对人类、动物和植物产生了负面影响。然而，就植物而言，太阳为光合作用植物的健康成长提供了所需的主要元素，光合作用植物利用太阳的能量为自己创造食物。在光合作用过程中，波长不同、功能各异的光是从太阳中捕捉到的基本要素。阳光中紫外线（UV）成分的波长各不相同，紫外线 A（315-400 nm）和紫外线 B（280-315 nm）是主要成分，必须精确配比才能实现有利可图的耕作。为了减少气候变化对蔬菜种植的影响，这项研究建议在人工种植机械和规划的灌溉系统中集成发光二极管（LED），作为紫外线阳光的替代来源。为了提供必要的紫外线组合，使用扩散器将蓝色、红色和白色发光二极管（LED）组合在一起。红色、蓝色和白色发光二极管使用了两周，每天各 12 小时，以影响植物的生长，其中红色促进光合作用，白色改善光合作用，蓝色促进茎叶生长。自动生长机的硬件和软件都是用 Arduino Uno 编程的。在 LED 灯下种植不同蔬菜植物的结果与在阳光直射下种植相同植物的结果进行了对比。经过第一周和第二周的种植，植物在两种环境下的表现不相上下。
{"title":"Mitigating the Impact of Climate Change on Vegetable Farming: An Evaluation of Artificial Planting Technique","authors":"S. Akangbe, A. P. Adeagbo, Abiodun Ojetoye","doi":"10.53982/ajerd.2024.0702.10-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0702.10-j","url":null,"abstract":"A worldwide issue, global warming results from human activity changing the climate and having a negative impact on people, animals, and plants. However, in terms of plants, the sun provides the primary elements required for healthy growth of photosynthetic plants, which use the energy from the sun to create food for themselves. Light with varying wavelengths that serve distinct functions during the photosynthetic process are the essential elements that are captured from the sun. The wavelength of the ultraviolet (UV) component of sunlight varies, characterized as UV A (315–400 nm) and UV B (280–315 nm) are the primary components that must be precisely proportioned for a profitable farming. In order to lessen the impact of climate change on vegetable farming, this research suggests integrating light emitting diodes (LEDs) in artificial growing machines as well as planned irrigation systems as an alternate source of ultraviolet sunshine. To provide the necessary UV light combination, blue, red and white colours of light-emitting diodes (LEDs) were combined using diffusers. The red, blue, and white LEDs were used for two weeks, each 12 hours a day, to influence the plants growth, with red promoting photosynthesis, white improving it, and blue encouraging stem and leaf growth. An Arduino Uno was used to program both the hardware and software components of the automated growth machine. The outcome of planting varied vegetable plant under LED lights was contrasted with the outcome of planting the identical set of plants under direct sunlight. After the first and second weeks of planting, the plants' performances under both circumstances are comparable.","PeriodicalId":503569,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141828216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-17DOI: 10.53982/ajerd.2024.0702.11-j
L. Kumbo, Shabani Bakari Juma, Martin Ludovick Mushi
This study presents a comprehensive examination of the integration of Geographic Information Systems (GIS), Augmented Reality (AR) and Artificial Intelligence (AI) in tourism promotion in Tanzania. The literature review underscores the significance of these technologies in enhancing visitor experiences, destination management, and marketing strategies. The proposed integrated system design combines GIS's spatial mapping capabilities, AI's personalised recommendations, and AR's immersive content delivery to optimise tourist satisfaction and engagement. Key components include the GIS module for spatial data management, the AI recommendation engine for personalised suggestions, and the AR interface for immersive content overlay. Discussions highlight how the proposed system, by addressing critical challenges in the tourism sector, aligns with existing research findings and reassures its effectiveness. Ultimately, the study emphasises the potential of GIS, AR and AI technologies to revolutionise tourism promotion in Tanzania, fostering sustainable growth and cultural appreciation while enhancing visitor experiences.
本研究全面考察了地理信息系统（GIS）、增强现实（AR）和人工智能（AI）在坦桑尼亚旅游推广中的整合情况。文献综述强调了这些技术在提升游客体验、目的地管理和营销战略方面的重要性。拟议的集成系统设计结合了地理信息系统的空间制图功能、人工智能的个性化推荐和 AR 的沉浸式内容交付，以优化游客的满意度和参与度。关键组件包括用于空间数据管理的地理信息系统模块、用于个性化建议的人工智能推荐引擎以及用于沉浸式内容叠加的 AR 界面。讨论强调了所提议的系统如何通过应对旅游业的关键挑战，与现有研究成果保持一致，并确保其有效性。最终，该研究强调了地理信息系统、增强现实技术和人工智能技术在彻底改变坦桑尼亚旅游推广方面的潜力，在提高游客体验的同时促进可持续增长和文化鉴赏。
{"title":"Elevating Tanzania's Tourism: Integrating GIS, AR and AI for Immersive Exploration and Promotion","authors":"L. Kumbo, Shabani Bakari Juma, Martin Ludovick Mushi","doi":"10.53982/ajerd.2024.0702.11-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0702.11-j","url":null,"abstract":"This study presents a comprehensive examination of the integration of Geographic Information Systems (GIS), Augmented Reality (AR) and Artificial Intelligence (AI) in tourism promotion in Tanzania. The literature review underscores the significance of these technologies in enhancing visitor experiences, destination management, and marketing strategies. The proposed integrated system design combines GIS's spatial mapping capabilities, AI's personalised recommendations, and AR's immersive content delivery to optimise tourist satisfaction and engagement. Key components include the GIS module for spatial data management, the AI recommendation engine for personalised suggestions, and the AR interface for immersive content overlay. Discussions highlight how the proposed system, by addressing critical challenges in the tourism sector, aligns with existing research findings and reassures its effectiveness. Ultimately, the study emphasises the potential of GIS, AR and AI technologies to revolutionise tourism promotion in Tanzania, fostering sustainable growth and cultural appreciation while enhancing visitor experiences.","PeriodicalId":503569,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141831096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-17DOI: 10.53982/ajerd.2024.0702.07-j
K. Idowu, Zakari Adamu
The prediction of blast efficiency is usually achieved by using models; this in turn, gives better and more efficient rock fragmentation. However, the accuracy of the prediction often times relies on the model development validation. In this study, models were developed and compared upon validation for predicting the blast efficiency and total charge required for efficient fragmentation using artificial neural network (ANN). Rock samples were gathered from the study are, and the uniaxial compressive strength (UCS) test was carried out on all the samples based on international standard. The average UCS obtained from the rock samples at the Eminent quarry (EQ) is 153.61 MPa. The dimension of in-situ rock mass considered in the study area is 60 m x 40 m, and the in-situ block sizes obtained vary from 2.02 m2 to 3.20 m2. The average percentage value of F50 obtained from the Split-Desktop image analyses is approximately 72.44 cm. The various results obtained from the UCS, in-situ block size distribution, image analysis of the blasted rocks and the total charge were used to develop the models for the prediction of blast efficiency. The key issue of concern about these models is that they are mostly site specific and the fact that if they perform well in a location does not guarantee the other. Hence, the validation and suitability of these models on the mine site. The blast efficiency prediction using ANN is compared with measured efficiency and the value of coefficient of determination, R2 obtained is 0.9733. The value of the coefficient of determination, R2 obtained from ANN by comparing the prediction of the total charge and the measured total charge is 0.9773. The findings showed that, the proposed ANN based mathematical models are suitable and thus, give better prediction to blasting efficiency and the possible total charge.
爆破效率的预测通常是通过使用模型来实现的，这反过来又能更好、更有效地破碎岩石。然而，预测的准确性往往取决于模型开发的验证。本研究利用人工神经网络（ANN）开发了预测爆破效率和高效破碎所需总装药量的模型，并进行了验证比较。从研究区域收集了岩石样本，并根据国际标准对所有样本进行了单轴抗压强度（UCS）测试。Eminent 采石场（EQ）岩石样本的平均单轴抗压强度为 153.61 兆帕。研究区域的原位岩块尺寸为 60 m x 40 m，获得的原位岩块尺寸从 2.02 m2 到 3.20 m2 不等。通过 Split-Desktop 图像分析获得的 F50 平均百分比值约为 72.44 厘米。从 UCS、原位块度分布、爆破岩石图像分析和总装药量中获得的各种结果被用于开发爆破效率预测模型。这些模型值得关注的关键问题是，它们大多针对具体地点，在某一地点表现良好，并不能保证在其他地点也表现良好。因此，需要对这些模型进行验证并使其适用于矿区。使用 ANN 预测的爆破效率与实测效率进行了比较，得到的判定系数 R2 值为 0.9733。通过比较总装药量的预测值和总装药量的测量值，ANN 得出的判定系数 R2 值为 0.9773。研究结果表明，所提出的基于 ANN 的数学模型是合适的，因此可以更好地预测爆破效率和可能的总装药量。
{"title":"Models Development for Prediction of Blast Efficiency and Total Charge in a Typical Quarry","authors":"K. Idowu, Zakari Adamu","doi":"10.53982/ajerd.2024.0702.07-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0702.07-j","url":null,"abstract":"The prediction of blast efficiency is usually achieved by using models; this in turn, gives better and more efficient rock fragmentation. However, the accuracy of the prediction often times relies on the model development validation. In this study, models were developed and compared upon validation for predicting the blast efficiency and total charge required for efficient fragmentation using artificial neural network (ANN). Rock samples were gathered from the study are, and the uniaxial compressive strength (UCS) test was carried out on all the samples based on international standard. The average UCS obtained from the rock samples at the Eminent quarry (EQ) is 153.61 MPa. The dimension of in-situ rock mass considered in the study area is 60 m x 40 m, and the in-situ block sizes obtained vary from 2.02 m2 to 3.20 m2. The average percentage value of F50 obtained from the Split-Desktop image analyses is approximately 72.44 cm. The various results obtained from the UCS, in-situ block size distribution, image analysis of the blasted rocks and the total charge were used to develop the models for the prediction of blast efficiency. The key issue of concern about these models is that they are mostly site specific and the fact that if they perform well in a location does not guarantee the other. Hence, the validation and suitability of these models on the mine site. The blast efficiency prediction using ANN is compared with measured efficiency and the value of coefficient of determination, R2 obtained is 0.9733. The value of the coefficient of determination, R2 obtained from ANN by comparing the prediction of the total charge and the measured total charge is 0.9773. The findings showed that, the proposed ANN based mathematical models are suitable and thus, give better prediction to blasting efficiency and the possible total charge.","PeriodicalId":503569,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141828172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Facial Recognition (FR) has been an active area of research and has diverse applicable environment, it continues to be a challenging research topic. With the development of image processing and pattern recognition technology, there are many challenges in machine learning to select the appropriate classification algorithms, most especially in the area of classification of extracted features to have low classification time, high sensitivity and accuracy of the classification algorithms, so it is very important to explore the performance of different algorithms in image classification. The three selected supervised learning classification algorithms: Learning Vector Quantization (LVQ), Relevance Vector Machine (RVM), and Support Vector Machine (SVM) performance were evaluated so as to know the most effective out of the selected algorithms for facial images classification. The development of the system has four stages, the first stage is image acquisition and 180 images were taken by digital camera under same illumination and light colour background. The second stage is pre-processing to improve the images data by suppressing unwilling distortion; grayscale and normalization were used for image pre-processing. The third stage is feature extraction; Discrete Cosine Transform (DCT) is adopted for this purpose. While the fourth stage is face recognition classification, Receiver Operating Characteristics (ROC) was used to test the performance of each the three algorithms. However the Learning Vector Quantization algorithm, Relevance Vector Machine and Support Vector Machine performance have not been compared together to the most effective out of the three algorithms in term of False Positive Rate, Sensitivity, Specificity, Precision, Accuracy and Computation Time. Hence, this work evaluated the performance of the Learning Vector Quantization; Relevance Vector Machine and Support Vector Machine classification algorithms in facial recognition system and Support Vector Machine outwit the other two algorithms in facial recognition in term of specificity, recognition time and recognition accuracy at different threshold.
{"title":"Performance Evaluation of Some Selected Classification Algorithms in a Facial Recognition System","authors":"Michael Olumuyiwa Adio, Ogunmakinde Jimoh Ogunwuyi, Mayowa Oyedepo Oyediran, Adebimpe Omolayo Esan, Olufikayo Adepoju Adedapo","doi":"10.53982/ajerd.2024.0701.17-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0701.17-j","url":null,"abstract":"Facial Recognition (FR) has been an active area of research and has diverse applicable environment, it continues to be a challenging research topic. With the development of image processing and pattern recognition technology, there are many challenges in machine learning to select the appropriate classification algorithms, most especially in the area of classification of extracted features to have low classification time, high sensitivity and accuracy of the classification algorithms, so it is very important to explore the performance of different algorithms in image classification. The three selected supervised learning classification algorithms: Learning Vector Quantization (LVQ), Relevance Vector Machine (RVM), and Support Vector Machine (SVM) performance were evaluated so as to know the most effective out of the selected algorithms for facial images classification. The development of the system has four stages, the first stage is image acquisition and 180 images were taken by digital camera under same illumination and light colour background. The second stage is pre-processing to improve the images data by suppressing unwilling distortion; grayscale and normalization were used for image pre-processing. The third stage is feature extraction; Discrete Cosine Transform (DCT) is adopted for this purpose. While the fourth stage is face recognition classification, Receiver Operating Characteristics (ROC) was used to test the performance of each the three algorithms. However the Learning Vector Quantization algorithm, Relevance Vector Machine and Support Vector Machine performance have not been compared together to the most effective out of the three algorithms in term of False Positive Rate, Sensitivity, Specificity, Precision, Accuracy and Computation Time. Hence, this work evaluated the performance of the Learning Vector Quantization; Relevance Vector Machine and Support Vector Machine classification algorithms in facial recognition system and Support Vector Machine outwit the other two algorithms in facial recognition in term of specificity, recognition time and recognition accuracy at different threshold.","PeriodicalId":503569,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140962582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-17DOI: 10.53982/ajerd.2024.0701.19-j
M. Balogun, Bilkisu Jimada-Ojuolape, James Ayo Taiwo, Titilayo Olusi
The escalating energy demands across Nigeria, especially in remote rural areas, have outpaced the capacity of the national electricity grid, necessitating the development of independent and sustainable energy sources. Among the renewable options, wind energy stands out as a promising solution. This study focuses on assessing the potential of wind energy in Ilorin, located in Kwara State, within Nigeria's north-central region. Utilizing data collected from 2007 to 2021 by the Nigerian Meteorological Agency, the research examines monthly average wind speeds at two specific coordinates in Ilorin, considering variations in air density. The study utilizes a 15-year set of monthly average wind velocities obtained from the Nigerian Meteorological Agency (NiMet) Headquarters in Abuja, measured at a height of 10 meters above ground level. By employing the 2-coefficient Weibull statistical model and extrapolation principles across different altitudes ranging from 150 to 900 meters above ground level, the study reveals distinct seasonal patterns of wind speeds ranging from 1.1 to 5.1 m/s in Ilorin. Furthermore, wind power density values ranging from 6.7 to 39.20 W/m2 are identified, with optimal wind attributes observed at altitudes exceeding 900 meters. These findings provide valuable insights for assessing the feasibility of wind energy utilization and designing efficient systems in Nigeria's north-central regions, aiding in the sustainable energy transition.
{"title":"Feasibility of Wind Energy Utilization for Sustainable Power Generation in Ilorin, Kwara State, Nigeria's North-Central Region","authors":"M. Balogun, Bilkisu Jimada-Ojuolape, James Ayo Taiwo, Titilayo Olusi","doi":"10.53982/ajerd.2024.0701.19-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0701.19-j","url":null,"abstract":"The escalating energy demands across Nigeria, especially in remote rural areas, have outpaced the capacity of the national electricity grid, necessitating the development of independent and sustainable energy sources. Among the renewable options, wind energy stands out as a promising solution. This study focuses on assessing the potential of wind energy in Ilorin, located in Kwara State, within Nigeria's north-central region. Utilizing data collected from 2007 to 2021 by the Nigerian Meteorological Agency, the research examines monthly average wind speeds at two specific coordinates in Ilorin, considering variations in air density. The study utilizes a 15-year set of monthly average wind velocities obtained from the Nigerian Meteorological Agency (NiMet) Headquarters in Abuja, measured at a height of 10 meters above ground level. By employing the 2-coefficient Weibull statistical model and extrapolation principles across different altitudes ranging from 150 to 900 meters above ground level, the study reveals distinct seasonal patterns of wind speeds ranging from 1.1 to 5.1 m/s in Ilorin. Furthermore, wind power density values ranging from 6.7 to 39.20 W/m2 are identified, with optimal wind attributes observed at altitudes exceeding 900 meters. These findings provide valuable insights for assessing the feasibility of wind energy utilization and designing efficient systems in Nigeria's north-central regions, aiding in the sustainable energy transition.","PeriodicalId":503569,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140963027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-17DOI: 10.53982/ajerd.2024.0701.16-j
Stephen Emeka Ochei, J. Agunsoye, H. Mgbemere, Kolawole Dayo Alonge
This research investigated the development of biodegradable bioplastic as a possible replacement for petroleum-based plastics, which constitute a serious environmental hazard. These hazards include but are not limited to flooding resulting from blocked sewage and danger to aquatic life in marine environments. The solution casting method was used to blend inhomogeneous kaolinite clay nano-particles with distilled water, starch, dilute acetic and nitric acids to produce different compositions of thermoplastic starch (TPS)/Clay composites with clay reinforcements ranging from 2.5 to 10 wt.%. The composites were characterized using an X-ray diffraction (XRD), and the mechanical and water absorption properties were determined. The result revealed a 9-fold improvement in the tensile strength (0.72 MPa), flexural strength increased 5-fold (3.34 MPa), and hardness increased 2-fold (23.56 HVN) as well as a reduction in water absorption by 3-fold (6.63%) when compared to the control. Furthermore, the 10 wt.% clay content composite showed the highest mechanical properties. The significant improvement in the listed properties was attributed to a reduction in crystallinity and the formation of new chemical bonds between the thermoplastic starch and the nano-clay. It was observed that the properties of the composites can be further enhanced if a synchronized machine blender (such as an extruder) is employed.
{"title":"Mechanical and Water Barrier Properties of Inhomogeneous Clay Nano-Particles Reinforced Thermoplastic Starch","authors":"Stephen Emeka Ochei, J. Agunsoye, H. Mgbemere, Kolawole Dayo Alonge","doi":"10.53982/ajerd.2024.0701.16-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0701.16-j","url":null,"abstract":"This research investigated the development of biodegradable bioplastic as a possible replacement for petroleum-based plastics, which constitute a serious environmental hazard. These hazards include but are not limited to flooding resulting from blocked sewage and danger to aquatic life in marine environments. The solution casting method was used to blend inhomogeneous kaolinite clay nano-particles with distilled water, starch, dilute acetic and nitric acids to produce different compositions of thermoplastic starch (TPS)/Clay composites with clay reinforcements ranging from 2.5 to 10 wt.%. The composites were characterized using an X-ray diffraction (XRD), and the mechanical and water absorption properties were determined. The result revealed a 9-fold improvement in the tensile strength (0.72 MPa), flexural strength increased 5-fold (3.34 MPa), and hardness increased 2-fold (23.56 HVN) as well as a reduction in water absorption by 3-fold (6.63%) when compared to the control. Furthermore, the 10 wt.% clay content composite showed the highest mechanical properties. The significant improvement in the listed properties was attributed to a reduction in crystallinity and the formation of new chemical bonds between the thermoplastic starch and the nano-clay. It was observed that the properties of the composites can be further enhanced if a synchronized machine blender (such as an extruder) is employed.","PeriodicalId":503569,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140965374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Water is considered a valuable resource and covers about 70% of the earth's surface. Tight schedule prevents regular checking of the domestic water tank level while refilling the used ones. This often leads to waste of water and increased monthly revenue payment to power utility company. Consequently, this paper presents a development of water level controller with SMS capability aimed at measuring water level smartly such that when tank is filled, message would be automatically transmitted as an alert to the owner using GSM for immediate response. The method involves interconnection of a water container that serves as tank with another open container serving as Bore-hole and a microcontroller-based device with its integrated development to generate a communication message. A flowchart that shows the procedural steps involved was developed. On completion of the prototype, components and sub-circuits effectiveness as well as experimental testing of the system effective operation were carried out. Some anticipated water level (AWL) were selected at interval of 2 centimeters (cm) starting from 3cm and the corresponding Message Operating water level (MOWL) were obtained with error deviations not greater than 0.17cm. Thus the average AWL, average MOWL and the error deviation are 11cm, 10.7cm and 0.1cm. The prototype device thus operated effectively.
{"title":"Development of Water Level Controller with SMS Capability","authors":"Lambe Mutalub Adesina, Olalekan Ogunbiyi, Bilkisu Jimada-Ojuolape","doi":"10.53982/ajerd.2024.0701.20-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0701.20-j","url":null,"abstract":"Water is considered a valuable resource and covers about 70% of the earth's surface. Tight schedule prevents regular checking of the domestic water tank level while refilling the used ones. This often leads to waste of water and increased monthly revenue payment to power utility company. Consequently, this paper presents a development of water level controller with SMS capability aimed at measuring water level smartly such that when tank is filled, message would be automatically transmitted as an alert to the owner using GSM for immediate response. The method involves interconnection of a water container that serves as tank with another open container serving as Bore-hole and a microcontroller-based device with its integrated development to generate a communication message. A flowchart that shows the procedural steps involved was developed. On completion of the prototype, components and sub-circuits effectiveness as well as experimental testing of the system effective operation were carried out. Some anticipated water level (AWL) were selected at interval of 2 centimeters (cm) starting from 3cm and the corresponding Message Operating water level (MOWL) were obtained with error deviations not greater than 0.17cm. Thus the average AWL, average MOWL and the error deviation are 11cm, 10.7cm and 0.1cm. The prototype device thus operated effectively.","PeriodicalId":503569,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140963055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-17DOI: 10.53982/ajerd.2024.0701.18-j
B. Aliemeke, Munirat Abdullawal Momoh, Mercy Onoshioze Asekhome, Christian Azuka Anani, Afoke Chief Vincent
A 1.0 KVA fuelless generator has been developed. The crave for sustainable energy solution has led to the exploration of emerging technologies targeted at reducing reliance on fossil fuels and reducing environmental impact. One such technology is the development of fuelless generators, which harness renewable energy sources or utilize unconventional mechanisms to generate electricity. This power producing mechanism is aimed to develop a targeted 1KVA power capacity through innovative design strategies. Detailed graphical modeling of the orthographic projection and isometric views brought about enhanced machine components development for stability and reliability. Careful selection of conductor materials and design considerations ensured efficient power transmission, minimizing losses within the system. Integration of power factor correction capacitors and advanced control algorithms contributed to achieving a power factor close to unity, optimizing energy utilization. Comprehensive performance testing validated the functionality and reliability of the developed generator under various load conditions. The development of a fuelless generator with a battery power capacity of 0.85 Kw, torque of 14.48 Nm, resistance of 48.35 ohms, current of 4.55 Amperes and a power factor of 0.85 signifies a significant breakthrough in sustainable energy generation. The performance test showed that that an input response brought about an increase in load (W). The success of developing the generator not only demonstrates the feasibility of clean and sustainable energy solutions but also underscores the potential for further advancements in fuelless generator technology towards a more reviving energy prospect.
{"title":"Development of a 1.0 KVA Fuelless Generator","authors":"B. Aliemeke, Munirat Abdullawal Momoh, Mercy Onoshioze Asekhome, Christian Azuka Anani, Afoke Chief Vincent","doi":"10.53982/ajerd.2024.0701.18-j","DOIUrl":"https://doi.org/10.53982/ajerd.2024.0701.18-j","url":null,"abstract":"A 1.0 KVA fuelless generator has been developed. The crave for sustainable energy solution has led to the exploration of emerging technologies targeted at reducing reliance on fossil fuels and reducing environmental impact. One such technology is the development of fuelless generators, which harness renewable energy sources or utilize unconventional mechanisms to generate electricity. This power producing mechanism is aimed to develop a targeted 1KVA power capacity through innovative design strategies. Detailed graphical modeling of the orthographic projection and isometric views brought about enhanced machine components development for stability and reliability. Careful selection of conductor materials and design considerations ensured efficient power transmission, minimizing losses within the system. Integration of power factor correction capacitors and advanced control algorithms contributed to achieving a power factor close to unity, optimizing energy utilization. Comprehensive performance testing validated the functionality and reliability of the developed generator under various load conditions. The development of a fuelless generator with a battery power capacity of 0.85 Kw, torque of 14.48 Nm, resistance of 48.35 ohms, current of 4.55 Amperes and a power factor of 0.85 signifies a significant breakthrough in sustainable energy generation. The performance test showed that that an input response brought about an increase in load (W). The success of developing the generator not only demonstrates the feasibility of clean and sustainable energy solutions but also underscores the potential for further advancements in fuelless generator technology towards a more reviving energy prospect.","PeriodicalId":503569,"journal":{"name":"ABUAD Journal of Engineering Research and Development (AJERD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140965902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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