PT. PLN (Persero) Unit Pelaksana Pelayanan Pelanggan (UP3 Semarang) is an electric power distribu... more PT. PLN (Persero) Unit Pelaksana Pelayanan Pelanggan (UP3 Semarang) is an electric power distribution unit in Central Java with the largest sales of electrical energy. One of the performances that is always a concern is the monthly distribution power loss. The amount of distribution power loss is manifested in percentage every month. The power loss rate of UP3 Semarang is between 6-6.5%. This month's power loss can only be known in the middle of the month in front of waiting for the results of the income report consisting of electricity account income, follow-up bills from customers who are subject to P2TL (Electricity Usage Control), negligence costs, transformer rentals, and others are considered too late to be used as a reference for policymakers related to power loss control. So, a prediction is needed to forecast the power loss rate in the future time period. This research using Matlab Software with the Backpropogation Artificial Neural Network method to predict the monthly power loss of PT. PLN (Persero) UP3 Semarang. Furthermore, in this process, it can provide data on the amount of monthly distribution power loss of any distribution unit in the next time period. From the results of research, analysis, design, manufacture and testing of application systems with backpropagation artificial neural networks, a 7-14-1 artificial neural network model with 7 input layers, 14 neurons in the hidden layer, and 1 output layer in this distribution power loss prediction, with a regression value of 0.9924 and RMSE 0.52525 so that the results of the test are considered good enough to be used as a power loss prediction in the future period.
Sustainable supplier selection is a critical aspect of supply chain management that balances oper... more Sustainable supplier selection is a critical aspect of supply chain management that balances operational efficiency with environmental, social, and economic sustainability goals. Traditional methods often prioritize cost and delivery performance, neglecting key sustainability factors. This study proposes a machine learning framework that integrates clustering and classification techniques to enhance supplier evaluation. K-Means clustering is used to segment suppliers into three groups-sustainable, moderate, and low-performing-based on critical features such as weight, cost, and unit quantity. A Random Forest classifier is employed to predict sustainable suppliers with an accuracy of 99.95%, ensuring robust and reliable results. The study highlights the ability of machine learning to identify patterns and optimize supplier selection processes. Cluster 0 suppliers demonstrated high cost efficiency and resource utilization, aligning well with sustainability objectives, while Cluster 2 highlighted high-cost, low-efficiency suppliers requiring improvement or exclusion. The classification model's precision and recall scores validate its effectiveness in minimizing false predictions, enabling data-driven decisions. The novelty of this research lies in its integration of machine learning with sustainability metrics, providing a scalable and adaptable framework for diverse industries. This approach not only streamlines supplier evaluation but also contributes to achieving global sustainability goals. Future research can expand this work by incorporating additional metrics, dynamic datasets, and hybrid decision-making models to further refine supplier evaluation in sustainable supply chain management.
As one of the important contents of mathematics core literacy, mathematical modeling is of great ... more As one of the important contents of mathematics core literacy, mathematical modeling is of great significance for cultivating students' logical thinking, innovative consciousness and problem-solving ability. Taking "Understanding a Quadratic Equation" as an example, this paper explores how to cultivate students' mathematical modeling literacy through teaching thinking, teaching experience and teaching expression. This paper expounds how teachers can integrate the concept of "three teaching" into practical teaching through four basic processes of mathematical modeling: finding and asking questions, establishing and solving models, testing and perfecting models, and analyzing and solving problems, so as to improve students' mathematical modeling ability and promote their sustainable development.
The aim of this study was to investigate the effect of native entomopathogenic fungus (EPF) Beauv... more The aim of this study was to investigate the effect of native entomopathogenic fungus (EPF) Beauveria bassiana (Bals.) Vuill. isolates (Bb-1, Bb-18, ET-101 and ET-10) obtained from different locations and different hosts on the last instar larvae of Ceratitis capitata (Diptera: Tephritidae) under laboratory conditions. B. bassiana isolates were applied as a single dose (10 8 conidia mL-1) by spraying using a hand sprayer. Following the applications, the live individual count was documented by tallying on the 1 st , 3 rd , 5 th , and 7 th days, and the percentage mortality rate was determined. The experiments were carried out in climatic chambers with 25±1 o C temperature, 65% relative humidity, 16:8 h L: D conditions in a randomized plot experimental design with five replicates. As a result of the study, the highest mortality rate in the third day counts was determined in B. bassiana ET-10 isolate (84%) and this isolate was statistically in the same group with Bb-18 and ET-101. In the fifth day counts, the highest mortality rate was detected in the B. bassiana ET-10 isolate (88%) and all applied isolates were statistically in the same group. In the seventh day counts, 100% mortality rate was determined in all applied isolates and all isolates were statistically in the same group. The LT50 values of the applied Bb-1, Bb-18, ET-101 and ET-10 isolates were determined as 3.28, 3.17, 2.52, and 2.26 days, respectively. Native B. bassiana isolates utilized in the research were identified as promising for the biological control of the Mediterranean fruit fly. However, the effectiveness of these isolates under field conditions also needs to be determined.
This paper aims to comparatively study the construction philosophy of residential buildings in Mo... more This paper aims to comparatively study the construction philosophy of residential buildings in Mount Tai and Mount Huang, analyzing the differences in construction concepts, social and political factors, and natural factors. By exploring the Cheng-Zhu thought and commercial thinking in Huangshan residential buildings, and the Confucian thought and small-scale farming thinking in Taishan residential buildings, this paper reveals the deep-seated reasons and their influences on the construction philosophy of residential buildings in these two regions.
Humanitarian workers most of the time undergo psychological torture as they are always under pres... more Humanitarian workers most of the time undergo psychological torture as they are always under pressure. Intrusive thoughts is another phenomena associated with such experiences and is defined as recurrent and unwanted cognitive intrusions that cause cognitive traffic jams. The present research therefore examines the effects of Intrusive thoughts in relation to job performance for humanitarian workers in Southwestern Uganda. This article reviews the literature on intrusive thoughts and job performance, and the factors that act as consequences of these phenomena, as well as preventive and alleviation measures for both phenomena.
This study sought to develop a lesson guide aligned with the DepEd K-12 Mathematics Curriculum an... more This study sought to develop a lesson guide aligned with the DepEd K-12 Mathematics Curriculum and MELCs, emphasizing foundational algebraic concepts and to utilize the Playlist model. This study utilized descriptive research design to develop and evaluate the lesson guide utilizing the Playlist model. Additionally, the Backward Design Framework was used to develop a lesson guide for Grade 9 Algebra using the Playlist Model. Backward design is a systematic instructional planning approach that begins with identifying desired learning outcomes, followed by determining assessment evidence, and concluding with the planning of instructional activities. Videos and handouts integrated into the lesson guide enhanced learning by supporting visual learners and providing clear problem-solving strategies. Students valued the structured guidance on improved outcomes from well-designed materials. Collaborative problem-solving fostered engagement and understanding, while real-world applications of quadratic functions boosted appreciation and critical thinking, underscoring the Playlist Model's effectiveness. This study recommends aligning learning outcomes with curriculum standards, using accurate assessments to track progress, planning diverse activities suited to students and resources, adapting strategies during lessons, and incorporating student feedback to refine instruction.
Nonlinear models have always been a focal point of study in disciplines such as statistics, finan... more Nonlinear models have always been a focal point of study in disciplines such as statistics, finance, and econometrics, with threshold models being a typical example of nonlinear models. This paper applies the Dirichlet process to threshold models to guarantee the flexibility of the approach. The threshold value, lag parameter, and the order of the autoregressive model can be directly estimated from the data. In this paper, the innovation of the threshold model is also considered. Instead of following a zero-mean normal distribution, it follows any distribution. In combination with the MCMC algorithm, and through numerical simulation and comparison with the Ordinary Least Squares method, it is demonstrated that the estimation in this paper is more effective.
The study aims to enhance the efficiency of using CAE simulation technology in analyzing hot forg... more The study aims to enhance the efficiency of using CAE simulation technology in analyzing hot forging for SUS304 valve blanks. The simulation process utilizes three different input variables, forming a set of 15 simulations with two distinct output objectives. The results obtained from the CAE simulations will be used to construct a set of optimal solutions through the NSGA II algorithm. Subsequently, the TOPSIS method is applied to select the most optimal solution from the Pareto set of solutions. The chosen simulation software is QForm, which provides several desired results, including temperature, forging force, stress, durability, and defect analysis.
To establish an efficient finite element approximation for fourth-order equations defined in a ci... more To establish an efficient finite element approximation for fourth-order equations defined in a circular domain, polar coordinate transformation and orthogonality of Fourier sequence are utilized to decompose the two-dimensional fourth-order problem into a set of independent one-dimensional fourth-order equations, subsequently, an auxiliary second-order equation is introduced to reduce each onedimensional fourth-order problem to an equivalent second-order mixed formulation. Based on essential pole conditions, a class of weighted Sobolev spaces is defined, and the weak form, as well as its corresponding discrete scheme, is derived for each second-order mixed system. The existence and uniqueness of both the weak and numerical solutions are established using the Lax-Milgram theorem. Additionally, the error estimate between the weak solution and its numerical approximation is obtained using the Céa lemma and the interpolation approximation theorem. Finally, leveraging the properties of piecewise linear interpolation basis functions, the discrete scheme is expressed in its equivalent matrix form, and numerical experiments are presented to validate the algorithm's effectiveness and confirm the accuracy of the theoretical results.
This paper mainly focuses on the numerical solution of the two-dimensional second-kind Fredholm i... more This paper mainly focuses on the numerical solution of the two-dimensional second-kind Fredholm integral equation by the Jacobi-Legendre Spectral-Galerkin method. Based on the Gauss points related to the Jacobi weight function as the collocation points, and applying the Gauss orthogonal quadrature formula to deal with the integral term. When the kernel function and source function are smooth enough, according to the weighted discrete inner product form, the weak form of the numerical algorithm is further realized. Finally, numerical examples are given to prove the advantages of our algorithm, The results show that the effectiveness and spectral accuracy correctness of the proposed algorithm.
Face recognition on Buddha statues is a significant challenge in cultural heritage preservation r... more Face recognition on Buddha statues is a significant challenge in cultural heritage preservation research, especially when the images have a high degree of similarity, low quality, or uneven lighting. This makes identifying faces on Buddha statues in museums or historical sites difficult. This study aims to develop an effective method for detecting faces on Buddha statues using a convolutional neural network (CNN) combined with the bounding box technique to improve detection accuracy. The bounding box technique is applied to reduce the area of analysis and improve the efficiency of the face detection process. In addition, variations in the kernel size and parameter stride of CNN are analyzed to obtain optimal results in face recognition with distorted images. The experimental results show that combining CNN with a bounding box significantly improves face detection accuracy on Buddha statues, even on images with uneven lighting and low quality. This technique is superior to conventional face detection methods under difficult image conditions. This study contributes to developing more accurate face-detection techniques for cultural heritage preservation. Applying this method can improve face recognition on historical artifacts with low image quality and poor lighting and opens up opportunities for further research in technology-based cultural conservation.
The article discusses the problems of automating data analysis processes using the latest technol... more The article discusses the problems of automating data analysis processes using the latest technological developments. The relevance of this topic is justified by the increasing need for efficient processing of large amounts of information against the background of digitalization of various fields of activity. It is emphasized that automation today is becoming not only a tool for increasing productivity, but also a key factor in the competitiveness of business entities. However, the choice of methods and specific solutions is associated with several contradictions related to their adaptation to the specifics of the tasks, limitations of computing resources, and the complexity of interpreting the results. The study aims to explore the conceptual foundations, opportunities, advantages, and "bottlenecks" of innovative developments that allow automating data analysis. The results obtained make it possible to assert that the latest technologies for automation have great potential; at the same time, their successful implementation requires careful preparation, taking into account the specifics of the tasks. It is important to combine the capabilities of various tools to overcome their limitations, as well as invest in the development of specialist competencies to ensure maximum return on the steps taken. The information presented in the article will be useful to specialists in the field of analytics, developers of intelligent systems, as well as researchers dealing with the problems of digitalization.
This article examines the key aspects of applying predictive analytics in the context of the circ... more This article examines the key aspects of applying predictive analytics in the context of the circular economy (CE). It explores the evolution of resource management approaches and the transition to sustainable methods focused on minimizing waste and reusing resources. Special attention is given to the stages of implementing predictive analytics, including data collection, selection of forecasting methods, modeling, and integration into the resource management process. The study investigates the role of various forecasting methods, such as time series models, machine learning, and scenario modeling, in optimizing resource use and developing effective strategies for the transition to a CE.
This paper proposes a multi-level control strategy for hybrid microgrid management, integrating r... more This paper proposes a multi-level control strategy for hybrid microgrid management, integrating renewable energy sources such as solar and wind with conventional systems like Combined Heat and Power (CHP) units, Battery Energy Storage Systems (BESS), and grid electricity. The Oakland University campus served as a case study to evaluate the effectiveness of Adaptive Model Predictive Control (AMPC) in optimizing energy distribution, mitigating fluctuations in renewable generation, and minimizing grid dependency. The AMPC system dynamically responded to real-time conditions, efficiently charging BESS during periods of surplus generation and ensuring seamless operation during peak demand. When compared to basic MPC, AMPC exhibited enhanced performance in meeting load requirements, improving renewable energy utilization, and achieving significant cost reductions, particularly during seasonal extremes. This scalable and adaptable framework illustrates the potential of AMPC for future microgrid systems, offering a sustainable, cost-effective solution as renewable technologies continue to advance.
Positioning of a XR/VR glasses with high accuracy in the open area environments and augmentation ... more Positioning of a XR/VR glasses with high accuracy in the open area environments and augmentation of simulated objects refers to the problem to give the real environment feeling during the training in a real environment to the trainees. In this article, an image matching approach will be proposed for generating a high accuracy image matching algorithm to use in the simulation systems while maximizing interactivity in the training area using by locating the glasses user with high accuracy. Current methods use sensors and cameras of the glasses, to locate the glasses in the environment that can give erroneous results while the data generated by the sensors. This paper proposes a technique that uses image matching algorithms to locate glasses by using previously given images with a known position. HARRIS and SIFT algorithms will be compared in robustness, implementation side for usage in real time on glasses.
This study presents the application of a novel meta-heuristic algorithm called Hippopotamus optim... more This study presents the application of a novel meta-heuristic algorithm called Hippopotamus optimizer (HO) to solve the problem of clean energies-economic load dispatch (CE-ELD). The application of HO is focused on optimizing the power output of all thermal generating sources in the given system so that the value of total electricity generation cost (TEGC) is minimal. In the process of solving the considered problem, solar and wind energy are also connected to the given system to evaluate their contribution and reduce the environmental damages caused by ThS's operation. Moreover, the value of power loss and the prohibited operating zones are also employed while applying HO to the CE-ELD problem to assess its actual performance. Finally, the results achieved by HO are compared to another meta-heuristic algorithm, Frilled
Urban planning is governed by principles that create sustainable, resilient, accessible, equitabl... more Urban planning is governed by principles that create sustainable, resilient, accessible, equitable, economically vibrant, and healthpromoting cities. Formal organizations, including governmental bodies and professional associations, play a crucial role in shaping cities' physical and social fabric through systematic, multi-tiered approaches. The historical evolution of formal urban planning traces back to ancient civilizations, where foundational principles were established. Key figures like Ebenezer Howard significantly influenced modern urban planning. Howard's Garden City Movement, emerging in the late 19th century, aimed to counteract the adverse effects of rapid industrialization by proposing self-sustaining communities surrounded by greenbelts. This model harmoniously integrated urban amenities with rural landscapes, promoting a balanced lifestyle and enhancing physical and mental well-being. The formal organization of urban planning gained momentum during the Industrial Revolution, driven by the need for structured approaches to managing rapid urban growth and improving living conditions. This period highlighted the importance of comprehensive planning practices to address the challenges of urban expansion. Urban planning and design in Kenya involve a collaborative effort among national and county governments, civil society organizations, private sector entities, and academic institutions. The National Urban Development Policy (NUDP) and the New Urban Agenda guide the planning processes, focusing on inclusive, safe, resilient, and sustainable urban development. The National Land Commission and the Kenya Institute of Planners are pivotal in overseeing and implementing land use planning and urban development policies. Overall, urban planning continues to evolve, balancing historical insights with modern innovations to create sustainable and conducive environments for a high quality of life.
this research aims to determine the magnitude of the impact value generated by the influence of t... more this research aims to determine the magnitude of the impact value generated by the influence of the shape of the notch on St 37 steel. This research uses an experimental method conducted on St 37 with a cross section size of 10 x 10 mm and a length of 55 mm. This study was conducted by making 3 notch shapes namely Ս (half circle), Ц (rectangle) and V (triangle) notches. The results showed that the average impact value produced by the Ս (half circle) notch was 1.44 Joule/mm 2 , the average impact value produced by the Ц (rectangle) notch was 1.35 Joule/mm 2 and the impact value produced by the V (triangle) notch was 1.16 Joule/mm 2. In this case, the impact value of the V notch is lower because it does not require too much impact energy to break a specimen in contrast to the Ս (half-circle) notch. The Ս (half circle) notch requires the highest impact value of the two notches, because the surface of the specimen does not have a large angle so it requires a large impact energy to break or make cracks in the specimen.
Nigeria faces significant energy poverty, with millions of people lacking access to reliable and ... more Nigeria faces significant energy poverty, with millions of people lacking access to reliable and affordable electricity, particularly in rural areas. This paper explores the opportunities and challenges of transitioning to sustainable energy solutions in Nigeria. It examines the current energy landscape, focusing on disparities in energy access, and evaluates the potential of renewable energy sources such as solar, wind, hydropower, and bioenergy. The paper also discusses off-grid and mini-grid solutions, the role of government initiatives, public-private partnerships, and international cooperation in overcoming challenges like financial constraints, infrastructural barriers, and regulatory issues. Furthermore, it highlights the importance of capacity building, education, and public awareness in promoting sustainable energy adoption. The study concludes by providing policy recommendations aimed at facilitating Nigeria's shift to renewable energy to address energy poverty and achieve sustainable development.
PT. PLN (Persero) Unit Pelaksana Pelayanan Pelanggan (UP3 Semarang) is an electric power distribu... more PT. PLN (Persero) Unit Pelaksana Pelayanan Pelanggan (UP3 Semarang) is an electric power distribution unit in Central Java with the largest sales of electrical energy. One of the performances that is always a concern is the monthly distribution power loss. The amount of distribution power loss is manifested in percentage every month. The power loss rate of UP3 Semarang is between 6-6.5%. This month's power loss can only be known in the middle of the month in front of waiting for the results of the income report consisting of electricity account income, follow-up bills from customers who are subject to P2TL (Electricity Usage Control), negligence costs, transformer rentals, and others are considered too late to be used as a reference for policymakers related to power loss control. So, a prediction is needed to forecast the power loss rate in the future time period. This research using Matlab Software with the Backpropogation Artificial Neural Network method to predict the monthly power loss of PT. PLN (Persero) UP3 Semarang. Furthermore, in this process, it can provide data on the amount of monthly distribution power loss of any distribution unit in the next time period. From the results of research, analysis, design, manufacture and testing of application systems with backpropagation artificial neural networks, a 7-14-1 artificial neural network model with 7 input layers, 14 neurons in the hidden layer, and 1 output layer in this distribution power loss prediction, with a regression value of 0.9924 and RMSE 0.52525 so that the results of the test are considered good enough to be used as a power loss prediction in the future period.
Sustainable supplier selection is a critical aspect of supply chain management that balances oper... more Sustainable supplier selection is a critical aspect of supply chain management that balances operational efficiency with environmental, social, and economic sustainability goals. Traditional methods often prioritize cost and delivery performance, neglecting key sustainability factors. This study proposes a machine learning framework that integrates clustering and classification techniques to enhance supplier evaluation. K-Means clustering is used to segment suppliers into three groups-sustainable, moderate, and low-performing-based on critical features such as weight, cost, and unit quantity. A Random Forest classifier is employed to predict sustainable suppliers with an accuracy of 99.95%, ensuring robust and reliable results. The study highlights the ability of machine learning to identify patterns and optimize supplier selection processes. Cluster 0 suppliers demonstrated high cost efficiency and resource utilization, aligning well with sustainability objectives, while Cluster 2 highlighted high-cost, low-efficiency suppliers requiring improvement or exclusion. The classification model's precision and recall scores validate its effectiveness in minimizing false predictions, enabling data-driven decisions. The novelty of this research lies in its integration of machine learning with sustainability metrics, providing a scalable and adaptable framework for diverse industries. This approach not only streamlines supplier evaluation but also contributes to achieving global sustainability goals. Future research can expand this work by incorporating additional metrics, dynamic datasets, and hybrid decision-making models to further refine supplier evaluation in sustainable supply chain management.
As one of the important contents of mathematics core literacy, mathematical modeling is of great ... more As one of the important contents of mathematics core literacy, mathematical modeling is of great significance for cultivating students' logical thinking, innovative consciousness and problem-solving ability. Taking "Understanding a Quadratic Equation" as an example, this paper explores how to cultivate students' mathematical modeling literacy through teaching thinking, teaching experience and teaching expression. This paper expounds how teachers can integrate the concept of "three teaching" into practical teaching through four basic processes of mathematical modeling: finding and asking questions, establishing and solving models, testing and perfecting models, and analyzing and solving problems, so as to improve students' mathematical modeling ability and promote their sustainable development.
The aim of this study was to investigate the effect of native entomopathogenic fungus (EPF) Beauv... more The aim of this study was to investigate the effect of native entomopathogenic fungus (EPF) Beauveria bassiana (Bals.) Vuill. isolates (Bb-1, Bb-18, ET-101 and ET-10) obtained from different locations and different hosts on the last instar larvae of Ceratitis capitata (Diptera: Tephritidae) under laboratory conditions. B. bassiana isolates were applied as a single dose (10 8 conidia mL-1) by spraying using a hand sprayer. Following the applications, the live individual count was documented by tallying on the 1 st , 3 rd , 5 th , and 7 th days, and the percentage mortality rate was determined. The experiments were carried out in climatic chambers with 25±1 o C temperature, 65% relative humidity, 16:8 h L: D conditions in a randomized plot experimental design with five replicates. As a result of the study, the highest mortality rate in the third day counts was determined in B. bassiana ET-10 isolate (84%) and this isolate was statistically in the same group with Bb-18 and ET-101. In the fifth day counts, the highest mortality rate was detected in the B. bassiana ET-10 isolate (88%) and all applied isolates were statistically in the same group. In the seventh day counts, 100% mortality rate was determined in all applied isolates and all isolates were statistically in the same group. The LT50 values of the applied Bb-1, Bb-18, ET-101 and ET-10 isolates were determined as 3.28, 3.17, 2.52, and 2.26 days, respectively. Native B. bassiana isolates utilized in the research were identified as promising for the biological control of the Mediterranean fruit fly. However, the effectiveness of these isolates under field conditions also needs to be determined.
This paper aims to comparatively study the construction philosophy of residential buildings in Mo... more This paper aims to comparatively study the construction philosophy of residential buildings in Mount Tai and Mount Huang, analyzing the differences in construction concepts, social and political factors, and natural factors. By exploring the Cheng-Zhu thought and commercial thinking in Huangshan residential buildings, and the Confucian thought and small-scale farming thinking in Taishan residential buildings, this paper reveals the deep-seated reasons and their influences on the construction philosophy of residential buildings in these two regions.
Humanitarian workers most of the time undergo psychological torture as they are always under pres... more Humanitarian workers most of the time undergo psychological torture as they are always under pressure. Intrusive thoughts is another phenomena associated with such experiences and is defined as recurrent and unwanted cognitive intrusions that cause cognitive traffic jams. The present research therefore examines the effects of Intrusive thoughts in relation to job performance for humanitarian workers in Southwestern Uganda. This article reviews the literature on intrusive thoughts and job performance, and the factors that act as consequences of these phenomena, as well as preventive and alleviation measures for both phenomena.
This study sought to develop a lesson guide aligned with the DepEd K-12 Mathematics Curriculum an... more This study sought to develop a lesson guide aligned with the DepEd K-12 Mathematics Curriculum and MELCs, emphasizing foundational algebraic concepts and to utilize the Playlist model. This study utilized descriptive research design to develop and evaluate the lesson guide utilizing the Playlist model. Additionally, the Backward Design Framework was used to develop a lesson guide for Grade 9 Algebra using the Playlist Model. Backward design is a systematic instructional planning approach that begins with identifying desired learning outcomes, followed by determining assessment evidence, and concluding with the planning of instructional activities. Videos and handouts integrated into the lesson guide enhanced learning by supporting visual learners and providing clear problem-solving strategies. Students valued the structured guidance on improved outcomes from well-designed materials. Collaborative problem-solving fostered engagement and understanding, while real-world applications of quadratic functions boosted appreciation and critical thinking, underscoring the Playlist Model's effectiveness. This study recommends aligning learning outcomes with curriculum standards, using accurate assessments to track progress, planning diverse activities suited to students and resources, adapting strategies during lessons, and incorporating student feedback to refine instruction.
Nonlinear models have always been a focal point of study in disciplines such as statistics, finan... more Nonlinear models have always been a focal point of study in disciplines such as statistics, finance, and econometrics, with threshold models being a typical example of nonlinear models. This paper applies the Dirichlet process to threshold models to guarantee the flexibility of the approach. The threshold value, lag parameter, and the order of the autoregressive model can be directly estimated from the data. In this paper, the innovation of the threshold model is also considered. Instead of following a zero-mean normal distribution, it follows any distribution. In combination with the MCMC algorithm, and through numerical simulation and comparison with the Ordinary Least Squares method, it is demonstrated that the estimation in this paper is more effective.
The study aims to enhance the efficiency of using CAE simulation technology in analyzing hot forg... more The study aims to enhance the efficiency of using CAE simulation technology in analyzing hot forging for SUS304 valve blanks. The simulation process utilizes three different input variables, forming a set of 15 simulations with two distinct output objectives. The results obtained from the CAE simulations will be used to construct a set of optimal solutions through the NSGA II algorithm. Subsequently, the TOPSIS method is applied to select the most optimal solution from the Pareto set of solutions. The chosen simulation software is QForm, which provides several desired results, including temperature, forging force, stress, durability, and defect analysis.
To establish an efficient finite element approximation for fourth-order equations defined in a ci... more To establish an efficient finite element approximation for fourth-order equations defined in a circular domain, polar coordinate transformation and orthogonality of Fourier sequence are utilized to decompose the two-dimensional fourth-order problem into a set of independent one-dimensional fourth-order equations, subsequently, an auxiliary second-order equation is introduced to reduce each onedimensional fourth-order problem to an equivalent second-order mixed formulation. Based on essential pole conditions, a class of weighted Sobolev spaces is defined, and the weak form, as well as its corresponding discrete scheme, is derived for each second-order mixed system. The existence and uniqueness of both the weak and numerical solutions are established using the Lax-Milgram theorem. Additionally, the error estimate between the weak solution and its numerical approximation is obtained using the Céa lemma and the interpolation approximation theorem. Finally, leveraging the properties of piecewise linear interpolation basis functions, the discrete scheme is expressed in its equivalent matrix form, and numerical experiments are presented to validate the algorithm's effectiveness and confirm the accuracy of the theoretical results.
This paper mainly focuses on the numerical solution of the two-dimensional second-kind Fredholm i... more This paper mainly focuses on the numerical solution of the two-dimensional second-kind Fredholm integral equation by the Jacobi-Legendre Spectral-Galerkin method. Based on the Gauss points related to the Jacobi weight function as the collocation points, and applying the Gauss orthogonal quadrature formula to deal with the integral term. When the kernel function and source function are smooth enough, according to the weighted discrete inner product form, the weak form of the numerical algorithm is further realized. Finally, numerical examples are given to prove the advantages of our algorithm, The results show that the effectiveness and spectral accuracy correctness of the proposed algorithm.
Face recognition on Buddha statues is a significant challenge in cultural heritage preservation r... more Face recognition on Buddha statues is a significant challenge in cultural heritage preservation research, especially when the images have a high degree of similarity, low quality, or uneven lighting. This makes identifying faces on Buddha statues in museums or historical sites difficult. This study aims to develop an effective method for detecting faces on Buddha statues using a convolutional neural network (CNN) combined with the bounding box technique to improve detection accuracy. The bounding box technique is applied to reduce the area of analysis and improve the efficiency of the face detection process. In addition, variations in the kernel size and parameter stride of CNN are analyzed to obtain optimal results in face recognition with distorted images. The experimental results show that combining CNN with a bounding box significantly improves face detection accuracy on Buddha statues, even on images with uneven lighting and low quality. This technique is superior to conventional face detection methods under difficult image conditions. This study contributes to developing more accurate face-detection techniques for cultural heritage preservation. Applying this method can improve face recognition on historical artifacts with low image quality and poor lighting and opens up opportunities for further research in technology-based cultural conservation.
The article discusses the problems of automating data analysis processes using the latest technol... more The article discusses the problems of automating data analysis processes using the latest technological developments. The relevance of this topic is justified by the increasing need for efficient processing of large amounts of information against the background of digitalization of various fields of activity. It is emphasized that automation today is becoming not only a tool for increasing productivity, but also a key factor in the competitiveness of business entities. However, the choice of methods and specific solutions is associated with several contradictions related to their adaptation to the specifics of the tasks, limitations of computing resources, and the complexity of interpreting the results. The study aims to explore the conceptual foundations, opportunities, advantages, and "bottlenecks" of innovative developments that allow automating data analysis. The results obtained make it possible to assert that the latest technologies for automation have great potential; at the same time, their successful implementation requires careful preparation, taking into account the specifics of the tasks. It is important to combine the capabilities of various tools to overcome their limitations, as well as invest in the development of specialist competencies to ensure maximum return on the steps taken. The information presented in the article will be useful to specialists in the field of analytics, developers of intelligent systems, as well as researchers dealing with the problems of digitalization.
This article examines the key aspects of applying predictive analytics in the context of the circ... more This article examines the key aspects of applying predictive analytics in the context of the circular economy (CE). It explores the evolution of resource management approaches and the transition to sustainable methods focused on minimizing waste and reusing resources. Special attention is given to the stages of implementing predictive analytics, including data collection, selection of forecasting methods, modeling, and integration into the resource management process. The study investigates the role of various forecasting methods, such as time series models, machine learning, and scenario modeling, in optimizing resource use and developing effective strategies for the transition to a CE.
This paper proposes a multi-level control strategy for hybrid microgrid management, integrating r... more This paper proposes a multi-level control strategy for hybrid microgrid management, integrating renewable energy sources such as solar and wind with conventional systems like Combined Heat and Power (CHP) units, Battery Energy Storage Systems (BESS), and grid electricity. The Oakland University campus served as a case study to evaluate the effectiveness of Adaptive Model Predictive Control (AMPC) in optimizing energy distribution, mitigating fluctuations in renewable generation, and minimizing grid dependency. The AMPC system dynamically responded to real-time conditions, efficiently charging BESS during periods of surplus generation and ensuring seamless operation during peak demand. When compared to basic MPC, AMPC exhibited enhanced performance in meeting load requirements, improving renewable energy utilization, and achieving significant cost reductions, particularly during seasonal extremes. This scalable and adaptable framework illustrates the potential of AMPC for future microgrid systems, offering a sustainable, cost-effective solution as renewable technologies continue to advance.
Positioning of a XR/VR glasses with high accuracy in the open area environments and augmentation ... more Positioning of a XR/VR glasses with high accuracy in the open area environments and augmentation of simulated objects refers to the problem to give the real environment feeling during the training in a real environment to the trainees. In this article, an image matching approach will be proposed for generating a high accuracy image matching algorithm to use in the simulation systems while maximizing interactivity in the training area using by locating the glasses user with high accuracy. Current methods use sensors and cameras of the glasses, to locate the glasses in the environment that can give erroneous results while the data generated by the sensors. This paper proposes a technique that uses image matching algorithms to locate glasses by using previously given images with a known position. HARRIS and SIFT algorithms will be compared in robustness, implementation side for usage in real time on glasses.
This study presents the application of a novel meta-heuristic algorithm called Hippopotamus optim... more This study presents the application of a novel meta-heuristic algorithm called Hippopotamus optimizer (HO) to solve the problem of clean energies-economic load dispatch (CE-ELD). The application of HO is focused on optimizing the power output of all thermal generating sources in the given system so that the value of total electricity generation cost (TEGC) is minimal. In the process of solving the considered problem, solar and wind energy are also connected to the given system to evaluate their contribution and reduce the environmental damages caused by ThS's operation. Moreover, the value of power loss and the prohibited operating zones are also employed while applying HO to the CE-ELD problem to assess its actual performance. Finally, the results achieved by HO are compared to another meta-heuristic algorithm, Frilled
Urban planning is governed by principles that create sustainable, resilient, accessible, equitabl... more Urban planning is governed by principles that create sustainable, resilient, accessible, equitable, economically vibrant, and healthpromoting cities. Formal organizations, including governmental bodies and professional associations, play a crucial role in shaping cities' physical and social fabric through systematic, multi-tiered approaches. The historical evolution of formal urban planning traces back to ancient civilizations, where foundational principles were established. Key figures like Ebenezer Howard significantly influenced modern urban planning. Howard's Garden City Movement, emerging in the late 19th century, aimed to counteract the adverse effects of rapid industrialization by proposing self-sustaining communities surrounded by greenbelts. This model harmoniously integrated urban amenities with rural landscapes, promoting a balanced lifestyle and enhancing physical and mental well-being. The formal organization of urban planning gained momentum during the Industrial Revolution, driven by the need for structured approaches to managing rapid urban growth and improving living conditions. This period highlighted the importance of comprehensive planning practices to address the challenges of urban expansion. Urban planning and design in Kenya involve a collaborative effort among national and county governments, civil society organizations, private sector entities, and academic institutions. The National Urban Development Policy (NUDP) and the New Urban Agenda guide the planning processes, focusing on inclusive, safe, resilient, and sustainable urban development. The National Land Commission and the Kenya Institute of Planners are pivotal in overseeing and implementing land use planning and urban development policies. Overall, urban planning continues to evolve, balancing historical insights with modern innovations to create sustainable and conducive environments for a high quality of life.
this research aims to determine the magnitude of the impact value generated by the influence of t... more this research aims to determine the magnitude of the impact value generated by the influence of the shape of the notch on St 37 steel. This research uses an experimental method conducted on St 37 with a cross section size of 10 x 10 mm and a length of 55 mm. This study was conducted by making 3 notch shapes namely Ս (half circle), Ц (rectangle) and V (triangle) notches. The results showed that the average impact value produced by the Ս (half circle) notch was 1.44 Joule/mm 2 , the average impact value produced by the Ц (rectangle) notch was 1.35 Joule/mm 2 and the impact value produced by the V (triangle) notch was 1.16 Joule/mm 2. In this case, the impact value of the V notch is lower because it does not require too much impact energy to break a specimen in contrast to the Ս (half-circle) notch. The Ս (half circle) notch requires the highest impact value of the two notches, because the surface of the specimen does not have a large angle so it requires a large impact energy to break or make cracks in the specimen.
Nigeria faces significant energy poverty, with millions of people lacking access to reliable and ... more Nigeria faces significant energy poverty, with millions of people lacking access to reliable and affordable electricity, particularly in rural areas. This paper explores the opportunities and challenges of transitioning to sustainable energy solutions in Nigeria. It examines the current energy landscape, focusing on disparities in energy access, and evaluates the potential of renewable energy sources such as solar, wind, hydropower, and bioenergy. The paper also discusses off-grid and mini-grid solutions, the role of government initiatives, public-private partnerships, and international cooperation in overcoming challenges like financial constraints, infrastructural barriers, and regulatory issues. Furthermore, it highlights the importance of capacity building, education, and public awareness in promoting sustainable energy adoption. The study concludes by providing policy recommendations aimed at facilitating Nigeria's shift to renewable energy to address energy poverty and achieve sustainable development.
Based on the panel data of 42 prefecture-level cities in the Yangtze River Delta region of China ... more Based on the panel data of 42 prefecture-level cities in the Yangtze River Delta region of China from 2003 to 2017, and based on STIRPAT model and Environment Kuznets Curve (EKC) theory, this paper conducts an empirical analysis on the impact of environmental regulation on industrial pollutants emissions in the Yangtze River Delta region. The results show that there is a nonlinear inverted U-shaped relationship between environmental regulation, industrial SO 2 and industrial soot. Population size, secondary industry structure and energy consumption have significant promoting effects on the discharge of the three industrial pollutants. Foreign Direct Investment (FDI) is beneficial to reduce industrial SO 2 and industrial soot discharge, but has no significant effect on industrial wastewater emission reduction. Technological innovation has a significant effect on the emission reduction of three industrial pollutants. Education level can significantly reduce the emission of SO 2 and industrial waste water, but it has no significant effect on the emission of industrial soot. Based on the research results, the government and enterprises should formulate reasonable environmental regulation intensity to promote the development of green and innovative technologies, increase investment in energy conservation and emission reduction technologies, and attract high-quality FDI, so as to reduce the emission of industrial pollutants.
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