EAI Endorsed Transactions on Energy Web

Investigation of Sustainable Technology Options: Wind, Pumped-hydro-storage and Solar potential to Electrify Isolated Ziway Islanders in Ethiopia

2023-08-01T09:47:53+00:00

This research at supplying electricity to Ziway lake islanders in Ethiopia, through studying the wind, pumped hydro-storage (PHS), and solar energy potentials. A wind mast is erected, and measurements at 10,50, and 70m heights are taken for a year long. The wind is of class-4 with wind speeds of 7m/s at 50m, and 7.87m/s. The energy density is 318.8 kWh/m² (50m). GIS-based 3D digital elevation model (DEM) is used to investigate the PHS, with the lake as lower-reservoir and a dried-out crater pond of an extinct volcano as upper reservoir. The head is extracted using optical remote sensing technology, DEM(LiDAR) 12.5m. Constraints considered are topography, area, head, and slope. Twelve upper reservoirs are identified within head range of 50-250,50-200, and 50-100m. The results showed a PHS capacity of 5976 KWh at head of 60m can be developed. The solar energy potential is 6.1KWh/m² /day. The finding proved the viability of electricity supply to the community.

Frequency control of power system with electric vehicles using hybrid african vultures optimization algorithm and pattern search tuned fuzzy PID controller

2023-10-30T11:01:46+00:00

This work suggests a hybrid African Vultures Optimization Algorithm (AVOA) and Pattern search (hAVOA-PS) based Fuzzy PID (FPID) structure for frequency control of a nonlinear power system with Electric Vehicles (EVs). To illustrate the dominance of the projected hAVOA-PS algorithm, initially PI controllers are considered and results are compared with AVOA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods. To further enhance the dynamic performance, PID and FPID controllers are considered. The dominance of FPID over PID and PI controllers is shown. In the next step, EVs are incorporated in the test system and a comparative analysis of hAVOA-PS based PI/PID/FPID and FPID+EV is presented. To exhibit the superiority of projected frequency control scheme in maintaining the stability of system under different disturbance conditions like load increase in area-1 only, load decrease/increase in all areas, and large load increase in all areas are considered. It is noticed that the suggested hAVOA-PS based FPID controller n presence of EV is able to maintain system stability for all the considered cases where as other compared approaches fail to maintain stability in some cases.

Impact and challenges to Adopting Electric Vehicles in developing countries – a case study in India

2023-08-14T08:42:01+00:00

Climate change is one of the current threats facing the world. Pollution is the primary factor causing climate change, in it, air pollution plays a major part. Almost all developed and developing countries emit a lot of greenhouse gases (GHG). The transportation sector is responsible for the majority of GHG emissions. Nowadays, almost all nations make an effort to lower CO2 emissions from transportation. India also has a strategy to achieve zero emissions through several programmes. When considering ways to lower GHG emissions from the transportation sector, electric vehicles (EVs) are the first choice that comes to mind. The main goal of this case study is to identify why and how India is having trouble launching EVs. India faces significant obstacles in the areas of infrastructure, electricity, battery technology, and consumer behaviour. India already has the infrastructure necessary for the general usage of fuel-powered automobiles. Suddenly changing to another technology and expecting to complete the requirement is a little problematic in emerging nations like India. The majority of electric vehicles (EVs) use lithium-ion batteries, and India is in a position to buy these batteries from other nations. As a result, the battery is a little expensive in India. Nothing is difficult to overcome the barriers compared to the benefits of EVs. Finally, this study makes several recommendations for eliminating the barriers to India's EV adoption.

VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene

2023-07-31T14:40:12+00:00

The Fluctuations in demand and weather conditions have a significant impact on the frequency and the voltage of Algeria's isolated PIAT power grid. To maintain stability and reliable power supply, it is crucial to keep these quantities close to their expected levels. An automatic (FRR) is employed to regulate real-time frequency deviations caused by integrating variable renewable energy (VRE), specifically wind and solar power in the Kabertene region. In order to mitigate wind power fluctuations, a power system stabilizer is implemented, which helps dampen oscillations. The use of Maximum Power Point Tracking (MPPT) techniques optimizes the extraction of power from solar panels under varying conditions. For efficient scheduling and dispatch of VRE generation, particle swarm optimization (PSO)-based algorithms are used. These algorithms ensure optimal utilization of renewable energy sources by considering their intermittent nature. This study proves the effectiveness of these techniques in enhancing grid stability, reducing frequency deviations, and improving VRE integration. Valuable insights are provided on their practical implementation, playing a crucial role in transitioning to a cleaner and more sustainable energy system.

Transformer-Based Object Detection with Deep Feature Fusion Using Carafe Operator in Remote Sensing Image

2023-08-23T12:37:41+00:00

Recently, broad applications can be found in optical remote sensing images (ORSI), such as in urban planning, military mapping, field survey, and so on. Target detection is one of its important applications. In the past few years, with the wings of deep learning, the target detection algorithm based on CNN has harvested a breakthrough. However, due to the different directions and target sizes in ORSI, it will lead to poor performance if the target detection algorithm for ordinary optical images is directly applied. Therefore, how to improve the performance of the object detection model on ORSI is thorny. Aiming at solving the above problems, premised on the one-stage target detection model-RetinaNet, this paper proposes a new network structure with more efficiency and accuracy, that is, a Transformer-Based Network with Deep Feature Fusion Using Carafe Operator (TRCNet). Firstly, a PVT2 structure based on the transformer is adopted in the backbone and we apply a multi-head attention mechanism to obtain global information in optical images with complex backgrounds. Meanwhile, the depth is increased to better extract features. Secondly, we introduce the carafe operator into the FPN structure of the neck to integrate the high-level semantics with the low-level ones more efficiently to further improve its target detection performance. Experiments on our well-known public NWPU-VHR-10 and RSOD show that mAP increases by 8.4% and 1.7% respectively. Comparison with other advanced networks also witnesses that our proposed network is effective and advanced.

Analysis of Improved Particle Swarm Algorithm in Wireless Sensor Network Localization

2023-09-11T08:45:17+00:00

WSN localization occupies an important position in the practical application of WSN. To complete WSN localization efficiently and accurately, the article constructs the objective function based on the target node location constraints and maximum likelihood function. It avoids premature convergence through the PSO algorithm based on chaos search and backward learning. Based on linear fitting, the node-flipping fuzzy detection method is proposed to perform the judgment of node flipping fuzzy phenomenon. And the detection method is combined with the localization algorithm, and the final WSN localization algorithm is obtained after multi-threshold processing. After analysis, it is found that compared with other PSO algorithms, the MTLFPSO algorithm used in the paper has better performance with the highest accuracy of 83.1%. Different threshold values will affect the favorable and error detection rates of different WSNs. For type 1 WSNs, the positive detection rate of the 3-node network is the highest under the same threshold value, followed by the 4-node network; when the threshold value is 7.5 (3 ), the positive detection rate of the 3-node network is 97.8%. Different numbers of anchor nodes and communication radius will have specific effects on the number of definable nodes and relative localization error, in which the lowest relative localization error of the MTLFPSO algorithm is 3.4% under different numbers of anchor nodes; the lowest relative localization error of MTLFPSO algorithm is 2.5% under different communication radius. The article adopts the method to achieve accurate and efficient localization of WSNs.

Energy efficiency management according to ISO 50001: A case study in the brick industry

2023-07-11T16:40:30+00:00

This research presents the methodology and results of implementing energy efficiency management in the brick industry, given the problem of high electricity consumption in the production processes. Based on the ISO 50001 standard, energy efficiency management has as its structure the PHVA methodology of the Deming cycle and indicators that meet the standard's requirements. Energy consumption in tons of bricks produced is established as an indicator, allowing proposals for improving performance and efficient energy use, as well as implementing a management system, minimizing energy waste, and implementing engineering tools in the processes. Energy consumption data were collected before and after implementation, these data were analyzed, and the decrease in monthly electricity consumption was verified through a pre-test conducted at the beginning of the research, recording parameters of 543,800 kWh. After implementation, a post-test was conducted, recording parameters of 500,296 kWh, resulting in a saving of 43,504 kWh; in monetary units, the saving is S/18,067.21 for each month of production. Obtaining an annual decrease of 522,048 kWh, represented in monetary units S/216,806.53 (US$ 59,891.30 exchange rate S/3.62). Therefore, it is proven that implementing the methodology is feasible through the management of energy efficiency based on ISO 50001 and contributes strategically to the brick industry by increasing the efficiency associated with the reduction of 8% monthly electricity consumption.

Gap Analysis of data for urban transport planning in the developing countries: Comparative study of United Kingdom (UK) and the Kingdom of Saudi Arabia (KSA)

2023-08-09T14:40:47+00:00

This study performed a gap analysis of data for urban transport planning in two countries, one developing, and one developed with a view to conducting a gap analysis in the two countries and then comparing the results. The study commenced with an exploration of the background study of the research area by highlighting the importance of data collection and the types of data that are collected for urban transport planning. The specific types of data that are identified as collected were listed in order to enable the contextualisation of the work to be carried out in the subsequent sections of the study. Furthermore, the identified data collection methods in transport planning were identified and discussed, the key methods were highlighted, and the future directions identified in the background area were discussed. Thereafter, the activities directed towards the collection of data and the actual collection of data for public transport planning in the UK and KSA were discussed. The gap analysis showed that the UK has a robust framework for the collection of data for urban transport planning which the KSA does not, and in fact it was discovered that the most importance concern of the KSA government is how to reduce the number of private motor vehicles on its roads and increase the number of buses, and thereby reduce greenhouse gas emissions with a currently a serious cause for concern. The UK also needs to concentrate more on the collection of data for the management of Connected and Autonomous Vehicles (CAVs), and Mobility as a Service (MaaS), in preparation for the deployment of both forms of transport.

International Gateway Hub Construction and Air Logistics Industry Development Based on Multivariate Strategy Improvement Grey Wolf Algorithm

2023-08-14T13:57:52+00:00

INTRODUCTION: The global economic development pattern is changing, international economic and trade rules are being questioned, the global economy is not optimistic in the post-epidemic era, and it is more difficult to find growth points.

OBJECTIVES: How to achieve economic growth has become a more complex global issue. China, as the world's second largest economy and the world's second largest consumer market, is also a key issue to be addressed: how to promote a strong economic recovery and maintain a high level of public confidence in the state of our economy. The aviation industry chain plays a relatively good role in achieving supply stability as well as industry chain stability, and has a strong positive effect on the domestic and foreign double-cycle strategy. Shenzhen, as a window of China's opening up, has policies, resources and places to promote the development of aviation logistics industry.

METHODS: Information is obtained through literature review and fieldwork. Through the history of the development of aviation industry, the history of aviation logistics development and the current situation of the construction of China's aviation logistics are deeply reviewed and sorted out.

RESULTS: The specific path to be taken for the development of aviation industry, aviation logistics development and air express and related industries is explained. It also makes a long-term plan for the subsequent development of aviation industry, aviation logistics and air express development of Shenzhen airport, and analyzes the related objectives, and finally uses the relevant theoretical knowledge to make a relevant outlook on aviation industry, aviation logistics and aviation industry development, and summarizes the experience of aviation logistics company development. Combined with the construction of Shenzhen domestic airport, the relevant design concept is proposed.

CONCLUSION: Through the analysis of different routes, we finally found that the air logistics business of Shenzhen airport should take the road of synergistic development. In this way, the air logistics of Shenzhen airport should be built around five implementation points and six guarantee points in order to achieve a high-quality development in line with the new era.

Analysis of anti-slip control system and dynamic performance of mechanical engineering drive based on improved social engineering algorithm

2023-08-14T14:21:18+00:00

INTRODUCTION: The field of mechanical engineering technology is an emerging technology field with many research directions, and there are many directions of intersection with other disciplines, among which the field of mechanical engineering has outstanding research advantages. With the continuous development of mechanical engineering technology, the research direction of mechanical engineering applied to the field of mechanical engineering is also continuously enriched and developed. Mechanical engineering research focuses on realizing the monitoring and control of the dynamic performance of mechanical systems, as well as realizing the integration of design and system control.

OBJECTIVES: In order to improve the disassembly efficiency, reduce the disassembly cost and disassembly energy consumption, it is optimized using social engineering methods to achieve better results and reduce the disassembly cost and energy consumption.

METHODS: Aiming at the drive and anti-skid control strategy of four-wheel hub motor, it was simulated using improved social engineering algorithms, and based on this, three road recognition algorithms were selected for low, medium, and high adhesion road verification.

RESULTS: Through the study of automobile anti-skid control system, the basic structure of automobile anti-skid control system is summarized and some solution measures are proposed. A new type of drive anti-skid control system is proposed for the problems of high vibration and noise of automobile brake. The drive anti-slip control system is characterized by simple structure, easy maintenance, simple control and reliable operation, and high operation efficiency.

CONCLUSION: This study shows that the system not only has excellent drive anti-slip effect, but also has good control performance. In addition, this drive anti-slip system is able to ensure the safe and reliable operation of mechanical brakes in various harsh environments. This new drive anti-slip control system is a new type of drive device that can be widely used for driving force on various mechanical brakes and drive wheels, and the study of this device is of great significance.

Construction Schedule of Medium Voltage Overhead Distribution Network Optimization Based on Neural Network Algorithm

2023-09-06T09:03:08+00:00

INTRODUCTION: The medium voltage overhead distribution network is a complex planning problem, and monitoring the construction progress of the medium voltage overhead distribution network is an important aspect of the planning problem. Regarding the structure of the medium voltage overhead distribution network, it is one of the important components in China's distribution network system. If the construction progress of the medium voltage overhead distribution network is optimized, it will affect the normal operation of the entire power grid system in a certain region. Optimizing the construction progress of medium voltage overhead distribution networks using modern development related technologies or algorithms is one of the practical research topics.

OBJECTIVES: To better predict various issues that may arise during the construction progress of the distribution network. Complex geographical conditions lead to construction difficulties, and lack of technology leads to frequent stoppages of construction, further leading to frequent power outages in various regions. In terms of the overall power supply system, the reliability of power supply is not high.

METHODS: By comparing the BP neural network algorithm with the CNN network algorithm, the actual operation effect is evaluated by experts.

RESULTS: This article predicts the implementation progress of the medium voltage overhead distribution network, and the results show that the accuracy of the BP model for predicting the construction progress of the medium voltage overhead distribution network can reach 88%; The accuracy of the CNN medium voltage overhead distribution network construction progress prediction model reaches 77%.

CONCLUSION: The use of neural network algorithms to optimize the construction schedule of medium voltage overhead distribution networks has been evaluated by experts in practical applications, and the medium voltage overhead distribution network in power supply systems has potential application value.

Application of Robot Automation Technology Based on Machine Assisted and Artificial Intelligence in Distribution Network Overhead Line Engineering

2023-09-06T09:03:05+00:00

INTRODUCTION: The development of artificial intelligence technology in the context of the intelligent era shows vigorous vigor and vitality, and artificial intelligence fusion of robotic automation technology can assist manpower to complete all kinds of difficult operations, distribution network overhead line as the current power transmission lines equipped with the main way for domestic power transmission and regional power safety is of great significance.

OBJECTIVES: In order to reduce the labor intensity of operators, reduce the occurrence of power outages, and ensure the reliability of power supply, we discuss the application of robotic automation technology of machine-assisted and artificial intelligence in the distribution network overhead line project.

METHODS: Distribution network with power operation intelligent robot will grid lines in the wave speed information through the sensor transmission to the computer system, the computer system will grid lines in the wave speed converted to the wave speed of the overhead line, can be mixed lines in the wave speed inconsistent problem to provide a good solution.

RESULTS: At the scene of the work, the artificial intelligence distribution network power-carrying operation robot integrating artificial intelligence technology has a good application effect for the wiring in the distribution network overhead line project.

CONCLUSION: Robot automation technology incorporates the advantages of artificial intelligence, can rely on sensor systems and computer systems to perceive and identify things, and can autonomously control their own behavior, automated processing of complex actions, with a certain degree of perception, planning and collaborative ability, can be applied to the distribution network overhead line project.

Optimization and application of artificial intelligence in robotic automated distribution network overhead line engineering

2023-09-06T09:03:02+00:00

INTRODUCTION: Artificial intelligence is a product of high-end technological development since the 21st century, which has subverted people's traditional cognition in many aspects and greatly enriched and improved people's lives. Artificial intelligence has covered every aspect of life, and the distribution network overhead line project is also one of them. The combination of the two symbolizes the combination of modern technology and infrastructure construction, which is of great significance for modern economic and social development and transformation and upgrading.

OBJECTIVES: In order to solve the practical problems in the design of artificial intelligence and distribution network overhead line engineering, this paper focuses on the practical use of such artificial intelligence as robots in distribution network overhead line engineering.

METHODS: The models of spatial perception, target recognition and automatic calculation are established, and some key technical problems of robots put into actual engineering are simulated and calculated.

RESULTS: In the spatial perception model, the combination of robotic arm and laser device is utilized to solve the problem of direct sunlight, which affects the localization. In the target recognition model, combining the algorithms of minimum spanning tree and maximum critical path, the computational accuracy is improved to 1 mm. in the automatic computation model, the introduction of auxiliary lines and the secondary confirmation of manpower make the error of the work further reduced.

CONCLUSION: This paper's simulation algorithm for the reality of the distribution network overhead line project provides a more detailed solution to improve the technical content of the distribution network overhead line project and the quality of construction management is not a simple task, the need for the relevant distribution network overhead line project enterprises as well as the corresponding distribution network overhead line project personnel to take targeted measures.

Intelligent Control of Solar LED Street Lamp Based on Adaptive Fuzzy PI Control

2023-11-16T13:38:47+00:00

As road traffic develops, energy-saving and efficient street lights have become a key research field for relevant professionals. To reduce street lights energy consumption, a fireworks algorithm is used to optimize the membership function parameters of fuzzy control and the initial parameters of PI control. A fireworks algorithm improved adaptive fuzzy PI solar LED street light control system is designed. The results showed that in the calculation of Root-mean-square deviation and Mean absolute error, the Root-mean-square deviation of the adaptive fuzzy PI control system improved by the fireworks algorithm was 0.213, 0.258, 0.243, 0.220, and the Mean absolute error was 0.143, 0.152, 0.154, 0.139, respectively, which proved that the prediction accuracy was high and the stability was good. In the calculation of the 1-day power consumption of the solar LED intelligent control system, the average power consumption of the designed solar LED intelligent control system was about 2000W, which was 25.9%, 47.4%, and 42.9% lower than the other three control methods, respectively. This proves that its energy consumption is low, and its heat generation is low, and the battery service life is long. The research and design of an adaptive fuzzy PI control solar LED street light intelligent control system has good performance, which can effectively achieve intelligent management and energy conservation and emission reduction in smart cities.

Platformization and the Metaverse: Opportunities and Challenges for Urban Sustainability and Economic Development

2023-09-06T12:48:57+00:00

In simpler terms, our day-to-day life, from various urban sectors to all deep corners of city life, is becoming hugely influenced by digital platforms' data systems, economic tactics, and ways of management. This is a trend that we call "platformization." It's taken us to a point where we now live in what's often described as a "platform society" because these platforms now largely control urban civilizations. What's fascinating is that this platformization trend has created something pretty striking: the Metaverse. The Metaverse is an impressive global platform project launched by Meta, the company we used to know as Facebook. This project brings to life a potential "virtual world" that mirrors our reality. The idea is that the Metaverse can serve as a virtual version of the future cities – not too different from what we think of as smart cities. Thanks to cutting-edge technologies like Artificial Intelligence, Big Data, Internet of Things (IoT), and Digital Twins, we now have enough resources and understanding of human behavior to make a project like the Metaverse possible. The promise is that the Metaverse can revolutionize how we design cities and deliver public services, making cities more efficient, accountable, and with a higher quality performance. But of course, the arrival of the Metaverse isn't without its worries. There are many questions over the ethical, human, social, and cultural implications the Metaverse may have. Particularly, there are concerns about the kind of impact it may have on the quality of human social relationships and how it may reshape urban life. To unpack all of these, this research work aims to thoroughly examine available literature on this topic. The paper further looks into the new products and services coming into being because of the Metaverse, examining how they might help smart cities, especially those aiming for better environment, economy, and social sustainability. The insights gathered here could help city leaders understand the Metaverse's potential for technology-driven urban practices and future city plans. It also takes a critical stance, challenging whether the Metaverse might significantly change how reality is constructed in our increasingly platform-driven urban world. This discussion, hopefully, can fuel future research and critical conversation on this hot topic.

Power Outage Fault Judgment Method Based on Power Outage Big Data

2023-09-19T08:36:18+00:00

INTRODUCTION: With the deepening of the application of big data technology, the power sector attaches great importance to power outage judgment. However, many factors affect the judgment result of power outage, and the analysis process is very complicated, which can not achieve the corresponding accuracy.

OBJECTIVES: Aiming at the problem that it is impossible to accurately judge the result in judging power failure, a deep mining model of big data is proposed.

METHODS: Firstly, the research data set is established using power outage big data technology to ensure the results meet the requirements. Then, the power failure judgment data are classified using big data theory, and different judgment methods are selected. Using big data theory, the accuracy of power failure judgment is verified.

RESULTS: The deep mining model of big data can improve the accuracy of power failure judgment and shorten the judgment time of power failure under big data, and the overall result is better than the statistical method of power failure.

CONCLUSION: The deep mining model based on power outage big data proposed can accurately judge the power outage fault and shorten the analysis time.

Automatic Fault Diagnosis Technology of Roller Bearings of High-speed Rail Based on IFD and AE

2023-09-19T08:52:03+00:00

INTRODUCTION: With the development of technology and policy support, high-speed rail's temporal and spatial layout is gradually expanding, and it becomes essential to ensure high-safety operation.

OBJECTIVES: The real-time correlation fault diagnosis technology of critical components of electromechanical systems of high-speed trains is analyzed, and a new method of automatic fault diagnosis based on genetic support vector machine is proposed.

METHODS: In this study, the Author combines two techniques, IFD and AE, and introduces an adaptive weighting algorithm to fuse the data of the two and experimentally verify their accuracy.

RESULTS: The experimental results show that in the IFD experiment, the 2-point frequency at 1050 speed is 347.6 Hz, and the 3-point frequency is 498.4 Hz, both of which are very close to the 2 and 3 times frequencies of the 1-point frequency, and the multiplicative relationship is much more straightforward.

CONCLUSION: Combining IFD and AE can realize automatic and accurate diagnosis of bearing state and pre-diagnosis of bearings by adaptive weighted fusion algorithm, which is effective in the practical mechanical diagnosis of rolling bearing faults in high-speed railroads.

Similarity-Based Algorithm for Urban Street Refinement Design Model Extraction Research

2023-09-19T09:22:59+00:00

INTRODUCTION: The function of many public street spaces in Chinese cities is declining, but urban street space is essential in cities. How to enhance the street's fireworks and reshape the street's rich living atmosphere is worthy of further research and discussion.

OBJECTIVES: Based on the similarity algorithm urban street enhancement-related theories, paper summarizes the current problems of urban street space in China, researches the corresponding enhancement strategies according to the issues, and makes a strategic research and summary on the relationship between the interfaces of the scope of the visual field and the human behavior, as well as the relationship between the pedestrian and the vehicular traffic.

METHODS: An in-depth study after defining the concept, summarizing the idea and extracting the urban street refinement design model using the similarity algorithm.

RESULTS: The new urban street refinement design model can improve the psychological satisfaction of people walking in the application; the street space design model of the walking experience will also use the algorithm to simulate the joy; lastly, a recommended optimization technique is presented for the construction of a humanized street scale and other related factors.

CONCLUSION: The study of urban street space is a refined design strategy for the improvement of the urban landscape; the growth of the happiness index of urban residents is of great significance and, at the same time, for the enhancement of China's modernization level, improve the human habitat environment are of great importance, and should pay attention to the urban street refinement design.

Territorial Edge Computing Enabling Green Tourism and Green Development of CIPP Model Analytics

2023-09-22T08:19:05+00:00

INTRODUCTION: Eco-development is an essential national strategy, which has become an effective way to sustain China's tourism industry in the new era. Nowadays, the problem of climate change is becoming more and more serious, and the restriction on natural resources and the environment is becoming more and more serious. Improving the economic efficiency of the tourism industry and advancing the reform of its economic efficiency are critical priorities for the high-quality development of the tourism industry. Therefore, it is crucial for edge computing to empower green tourism and green growth.

OBJECTIVES: The purpose is to enhance the development of green tourism in China and promote the sustainable development of China's tourism industry; to solve the problems of severe environmental damage and resource consumption in the development of the tourism industry; and to promote the application of information technology, such as full-area edge computing, in the development of China's tourism industry, and to realize the combination of the CIPP education concept and the concept of green tourism promotion.

METHODS:Firstly, the authors find the necessity of researching the CIPP model of green tourism and green development empowered by the whole domain edge computing by using the study of literature and theory; secondly, the Author analyzes the importance of the education of the concept of green tourism and green development by using the method of analyzing the CIPP model; and lastly, the authors measure and enhance the effectiveness of green tourism and green development by using the mobile whole domain edge computing.

RESULTS: The whole-domain edge computing has better stability for green tourism and green development measurement, and the use of the CIPP model can better deepen tourists' tourism concepts of green tourism and green development and promote green tourism development.

CONCLUSION: The level of innovation in China's tourism industry is improving, and multivariate analysis shows that innovation is the key force driving industrial change and quality development. Therefore, it is essential to continue supporting an innovative and technology-driven tourism industry and continuously improving its innovative technologies and content. Greater emphasis will be placed on training and improving the quality of tourism staff. Tourism talent is the basis for innovation in tourism management and services and a critical factor in the development of an innovative system for tourism.

Technology for Power Outage Research and Judgment-dependent Data Feature Noise Analysis

2023-09-22T08:28:52+00:00

INTRODUCTION: Power grid blackouts occur frequently, which significantly impacts social impact. Because these accidents are dynamic and random, predicting and evaluating them is challenging.

OBJECTIVES: To explore the complexity of the power grid itself, analyzes the critical changes of the self-organizing model during power grid fault, extracts the data characteristics related to the steady-state maintenance of abnormal systems, and puts forward an effective outage prediction model.

METHODS: Starting with cluster analysis, The authors can reduce data fluctuation and eliminate noise interference to optimize data. The evaluation indexes of initial fault occurrence possibility and fault propagation speed in the power grid are constructed.

RESULTS: The validation of the outage forecasting model has produced promising results, achieving 96.4% forecasting accuracy and a meager error rate. In addition, the evaluation index developed in this study accurately reflects the possibility and spread speed of power outage accidents.

CONCLUSION: The research proves the feasibility of establishing an outage prediction model based on the power grid system data characteristics. The model has high accuracy and reliability and is a valuable tool for power outage research and judgment.

3D-dimensional Effective Stress Analysis of Wetting and Wetting Trapping Process in Wet-submerged Loess Tunnel Surrounding Rock Based on BP Neural Network

2023-09-26T09:18:26+00:00

INTRODUCTION: China's loess is vast. Loess has apparent high strength and resistance to deformation once encountered with water immersion and humidification, fusible salts precipitated on the surface of soil particles, the soil's carry alkalization strength is relatively reduced, while the vertical tubular pores in the soil accelerate the infiltration of water, the earth will be in the self-weight or the overlying loads of the additional action of the soil body will produce a significant settlement deformation, which results in the structural damage of the upper building, which is the loss of the wetting of subsidence.

OBJECTIVES: From China's practical point of view, the humidification and wetting process of wetted loess tunnel peripheral rock is deeply discussed and analyzed, and the water content distribution characteristics of wetted loess tunnel peripheral rock are sought.

METHODS: Using the particle swarm algorithm, four neural optimization network models, namely, radial basis neural network (RBFNN), generalized regression neural network (GRNN), wavelet neural network (WNN), and fuzzy neural network (FNN), are simulated and created for the analysis of three-dimensional effective stresses in the process of humidity and wetness subsidence in the surrounding rock of loess tunnels of a northwestern city in China and a central city in China.

RESULTS: By analyzing the comparison graphs between the predicted and actual values of these four models on the test data of two sets of experimental data, the distribution of the proportion of the expected difference to the true value, and the results of the calculation of the three error indexes, it can be found that when using the four neural networks, namely, RBFNN, GRNN, WNN, and FNN, for the analysis of the three-dimensional effective stresses during the process of increasing wetting and wetting of the surrounding rock of the tunnel in the soil-wetted loess, the prediction performance of the WNN is the best.

CONCLUSION: The soil's unsaturated settlement characteristics differ for different water contents and humidification times. The shorter the period, the more the soil column water content difference. With the continuous increase of water content change in the soil layer, the distribution of water content change in the loess soil column tends to be relatively uniform, and the difference in damage rate between the upper and lower layers tends to be reduced—the amount, time, and pressure of humidification controls wet subsidence.

Climate change and its impact on the population of Northern Lima

2023-09-29T13:49:23+00:00

Introduction: The impact caused by climate change at present presents a high risk in the health field with consequences in the social and environmental fields. For example, there has been an increase in illnesses and social concern due to the lack of information among citizens.

Aim: This study seeks to explain why climate change is having an impact on the population of Puente Piedra.

Methods: The research is explanatory and quantitative. For this reason, a survey was used to find out how informed citizens are about this issue and thus be able to describe the impact on health and recognize the effects on the social and environmental surroundings.

Results: The survey showed the lack of knowledge of citizens on the subject, concern about the increase in temperatures and lack of awareness to take action and address this problem.

Conclusions: It is suggested to carry out more studies taking the other cones of the capital as references to obtain better information at regional level.

Evaluating the Environmental Footprint: BPE Framework for Sustainable and Energy-Efficient Residential Buildings in India

2023-10-13T07:52:33+00:00

In the context of enhancing building performance assessment, this study introduces the BPE (Building Performance Evaluation) framework and explores its application through a residential complex in India. An expert evaluation of the questionnaire is carried out to investigate the main element and obstacles to the execution of BPE. The framework, designed to scrutinize five parameters, initially assesses design aspects, including building form, orientation, and aesthetics. Findings reveal that the building design lacks efficient circulation, storage facilities, and satisfactory spatial allocation. Building energy monitoring, essential for comprehensive analysis, faces limitations due to insufficient data availability, emphasizing the need for thorough planning. Thermal comfort analysis, based on temperature and humidity measurements, unveils significant fluctuations beyond comfort thresholds. Expert surveys and occupant feedback further expose reduced utilization of natural ventilation, high air conditioner adoption rates, and adaptive behaviours. The framework's insights prompt opportunities for improvement, yet validation requires broader application across diverse buildings. The study's academic survey emphasizes the importance of integrating BPE in industries with government policies. Field observations highlight challenges in space utilization, material selection, and occupant engagement. This study's findings underscore the BPE-RBPI framework's potential to refine performance assessment, sustainable and energy efficient to foster industry confidence, and drive holistic improvements in India's building sector.

Accuracy Assessment of different classifiers for Sustainable Development in Landuse and Landcover mapping using Sentinel SAR and Landsat-8 data

2023-10-13T08:10:42+00:00

Sentinel satellites make use of Synthetic Aperture Radar (SAR) which produces images with backscattered signals at fine spatial resolution from 10 m to 50 m. This study is mainly focused on evaluating and assessing the accuracy of various supervised classifiers like Random Forest classifier, Minimum Distance to mean classifier, KDTree KNN classifier, and Maximum Likelihood classifier for landuse / landcover mapping in Maduranthakam Taluk, Kancheepuram district, Tamilnadu, India. These classifiers are widely used for classifying the Sentinel SAR images. The SAR images were processed using speckle and terrain correction and converted to backscattered energy. The training datasets for the landcover classes, such as vegetation, waterbodies, settlement, and barren land, were collected from Google Earth images in high-resolution mode. These collected training datasets were given as input for the various classifiers during the classification. The obtained classified output results of various classifiers were analyzed and compared using the overall classification accuracy. The overall accuracy achieved by the Random Forest classifier for the polarization VV and VH was 92.86%, whereas the classified accuracy of various classifiers such as KDTree KNN, Minimum distance to mean, and Maximum Likelihood are found to be 81.68%, 83.17%, and 85.64% respectively. The random forest classifier yields a higher classification accuracy value due to its greater stability in allocating the pixels to the right landuse class. In order to compare and validate the results with sentinel data, the random classifier is applied with optical Landsat-8 satellite data. The classification accuracy obtained for Landsat-8 data is 84.61%. It is clearly proved that the random forest classifier with sentinel data gives the best classification accuracy results due to its high spatial resolution and spectral sensitivity. Thus accurate landuse and landcover mapping promote sustainable development by supporting decision-making at local, regional, and national levels.

Big Data and Machine Learning Framework for Temperature Forecasting

2023-10-20T12:35:59+00:00

This research aims to develop a Supporting Big Data and ML with a Framework for temperature forecasting using Artificial Neural Networks (ANN). The proposed framework utilizes a massive amount of historical weather data to train the ANN model, which can effectively learn the complex non- correlations that are linear with the parameters and temperature. The input variables include various weather parameters, such as humidity, wind speed, precipitation, and pressure. The framework involves three main stages: data pre-processing, model training, and temperature forecasting. In the data pre-processing stage, the raw weather data is cleaned, normalized, and transformed into a suitable format for model training. The data is then split into training, validation, and testing sets to ensure model accuracy. In model instruction stage, the ANN trained model using a backpropagation algorithm to adjust affected by the inherent biases and model based on the input and output data. The training process is iterative, and Using the validation, the efficiency of the model is measured. set to prevent overfitting. Finally, in the temperature forecasting stage, the trained ANN model is used to predict the temperature for a given set of weather parameters. The accuracy of the temperature forecasting is evaluated using the testing set, and the results are compared to other forecasting methods, such as statistical methods and numerical weather prediction models. The proposed framework has several advantages over traditional temperature forecasting methods. Firstly, it utilizes a vast amount of data, which enhances the accuracy of the forecast. Secondly, the ANN model can learn the interactions between the input variables that are not linear and temperature, which cannot be captured by traditional statistical methods. Finally, the framework can be easily extended to incorporate additional weather parameters or to forecast other environmental variables. The results of this research show that the proposed framework can effectively forecast temperature with high accuracy, outperforming traditional statistical methods and numerical weather prediction models. Therefore, it has the potential to improve weather forecasting and contribute to various applications, such as agriculture, energy management, and transportation.

The Advancement of Electronic Gadgets in 21st Century

2023-10-20T13:05:42+00:00

The 21st Century was full of innovation when it came to the Tech Sector alone, be it the introduction of the Iphone, or the launch of the big conglomerates such as Facebook and Twitter. The 21st Century gave rise to the concepts of the Curved Displays on phones and the Foldable phones. There were numerous problems which were associated with the flat screen displays, and the shortcomings have been overcome by the Curved Displays and the Foldable phones as discussed in the paper. They have revolutionized the Technological market since their launch. Many Conglomerates such as Samsung, Honor, Xiaomi have invested millions of dollars in availing this new technology. However, currently Samsung has the lead over all its Chinese competitors, and with different companies investing in the new technology, the competition is predicted to become more intense. This will surely give customers a huge variety of phones to choose from. However, this technology did not come without its drawbacks. There were multiple issues associated with the Foldable Phones such as the weight associated with the phone when folded, the tensile strength of the Foldable phones is very low, and the User Interface is not something one could get excited about. Similar issues existed with Curved Displays as well, including costly repair costs, and it is harder to get a grip on compared to the Foldable phones due to the thinning of the edges. The paper discusses in depth the shortcomings of all the types of Phones, as well as which would be the best fit for the user, along with the current trend of the users, and what the Future holds for this segment of Technology.

Power Quality Improvement Using TID based DVR Controller

2023-10-20T14:42:43+00:00

The effectiveness of power utilized by electronic devices is crucial for various reasons. Firstly, high-quality power results in better efficiency, allowing devices to operate at optimal energy levels. This article aims to clarify the significance of Power Quality by highlighting the benefits of using a Dynamic Voltage Restorer (DVR) to improve power quality for electricity consumers. The proposed method employs a hysteresis voltage control system that operates with variable switching frequency to enhance DVR reliability and ease of operation. Using a Tilt Integral Derivative (TID) controller, a type of fractional order controller similar to the PID controller, voltage compensation under disturbances is achieved with satisfactory results demonstrated via simulation. The primary objective of this project is to mitigate power quality issues such as voltage swell and sag in a distribution power system by enhancing power quality with a TID controller and comparing the results with those obtained from a previously implemented PID controller, using MATLAB software. Keywords: Dynamic Voltage Restorer (DVR), Tilt Integral Derivative controller (TID), Total Harmonic Distortion, MATLAB software.

Water contamination due to oil spill in Ancon

2023-10-23T10:26:07+00:00

The general objective of the research in charge was to analyze the actual state of the area after the water pollution caused by the oil spill in Ancon 2022; in the same way, it showed a quantitative approach of non-experimental design of descriptive transversal type, the scope of the research was descriptive; Similarly, it reached a sample of 50 people affected, a survey was used as a technique and the questionnaire as an instrument, validated under criteria which was based on 20 questions for the variable of water pollution through the Likert scale, for this, a previous sample of 20 people was used for the reliability of Cronbach's Alpha; likewise, the data collected were compared by the Microsoft Excel program and the statistical software Jamovi cloud 2. 3. 26; finally, it was concluded that the consequences of water pollution from the oil spill were very harmful to the marine ecosystem, the environment, the surrounding people and the economy.

Analysis of Artificial Intelligence Design Incorporated into Design of Street Space in Small Cities

2023-10-24T09:53:19+00:00

INTRODUCTION: At present, China's urbanization continues to develop, but the level of urban planning and design has not kept pace with the progress of development, especially the creation of street space in small cities, which is still not able to adapt to the current needs of people's cultural life. With the development of the economy and science and technology, artificial intelligence and other information technologies are constantly integrated into daily life. Therefore, utilizing artificial intelligence for street space design research is significant.

OBJECTIVES: To improve the development level of artificial intelligence, information technology, and the application level of artificial intelligence in China; to solve the problem of the relatively low level of street space design in the current city, especially in small towns, to meet the needs of people's cultural life; to promote the improvement of the level of artificial intelligence in China for the convenience of civil life, and to further improve the level of street space design in China.

METHODS: Firstly discusses the theories, such as the principles of street space design in small cities, to illustrate the necessity of integrating AI into street space design in small towns; secondly, the model established by AI is used to optimize the street space in small cities; finally, the feasibility of integrating AI design into street space design in small towns is illustrated through cases and examples.

RESULTS: Street space design in small cities in China needs more design aesthetics, and artificial intelligence needs to be integrated into street space design. Artificial intelligence has a noticeable optimization effect on street space design, and using artificial intelligence can improve the design level of limited space. Also illustrates that artificial intelligence can be better integrated into the street space design of small cities through cases.

CONCLUSION: In the context of the digital era, the street space design of small cities needs to apply artificial intelligence. In modernization-oriented urban construction, the street space design level of small towns should be further strengthened to improve the modernization level of cities.

Grouping Analysis of QCA for International Ecotourism Destinations in Cloud Computing Era of Geo-ecology

2023-10-24T10:01:33+00:00

INTRODUCTION: The Internet era has made the world more closely connected, and ecotourism has also caught up with the Internet era of cloud computing, making more and more international ecotourism destinations in China known to the world. China's global ecotourism industry has made significant progress, but it needs to be better to construct international ecotourism destinations. Therefore, conducts the grouping analysis of QCA of international ecotourism destinations in the cloud computing era of geo-ecology.

OBJECTIVES: To improve the construction level of China's international ecotourism destinations and promote the in-depth development of China's global ecotourism; to solve the dilemma that China's ecotourism destinations are imperfectly constructed, and the brand can not go out; and to promote the enhancement of tourism concepts of international ecotourism destinations in the age of computers.

METHODS: Firstly, the feasibility analysis of international ecotourism destination construction in the cloud computing era is carried out by using QCA analysis and histogram analysis; secondly, the relevant QCA model is established to analyze the influencing factors of international ecotourism destination construction; lastly, the tripartite game model is utilized to explore the benefits of international ecotourism destinations for the residents, the government, and the enterprises.

RESULTS: The construction of international ecotourism destinations in China is feasible from the perspectives of functional spatial configuration, economic development, cultural tradition, and natural environment; the structure of international ecotourism destinations has an apparent positive driving effect on the construction sites; the tripartite game model shows that there are positive benefits not only for the residents, government, and enterprises but also for the related groups and tourists.

CONCLUSION: From the full text of the study, the construction of international ecotourism destinations has a significant driving effect on China's economy; however, the tourism industry in the era of cloud computing needs to be further standardized, and the construction of international ecotourism destinations should be strengthened.

Digital Smart Manufacturing Context Urban Street Space Design Landscape Elements Retrofit Analysis

2023-10-24T10:08:08+00:00

INTRODUCTION: With the growth of the economic level, China's urban residents' urban living standards are also increasingly high, which has produced the story of an urban street space design to improve the requirements. Moreover, with intelligent manufacturing and other computer technology to enhance the efficiency of various industries, smart manufacturing applied to urban spatial design landscapes also has a prototype.

OBJECTIVES: To improve the level of digitization in China, the application of intelligent manufacturing in urban street space design; to promote the transformation of urban landscape elements, urban modernization will increase the level; to solve the problem of the urban environment improvement and economic development is not synchronized; to promote the modernization of urban development, enhance the level of urban informatization and intelligence.

METHODS: Firstly establishes the Wells equation of the optimal path of intelligent manufacturing through the technique of theoretical exposition; secondly, analyzes people's demand for urban street space design by using the method of data statistics and analysis; lastly, summarizes the principles to be followed in the creation of urban street space and the construction outlook through case study.

RESULTS: The Wells equation of the optimal path of smart manufacturing shows that intelligent manufacturing has a significant positive effect on the efficiency of urban street space design; the results of data statistics and analysis show that the current level of urban street space design cannot meet people's growing spiritual and cultural needs; the results of the case study show that the design of urban street space should follow the design principles of safety, closeness to nature, and human-centeredness.

CONCLUSION: Urban street space design in the context of digital intelligent manufacturing should be done promptly, and the level of urban landscape design should be strengthened to meet people's growing spiritual and cultural needs in the post-New Crown epidemic era.

Geo-Tagged Spoofing Detection using Jaccard Similarity

2023-10-26T13:35:50+00:00

In recent years, position evaluation of mobile devices has developed as an essential part of social movement. Meantime, the criminals may interfere with the information of geographical position (geo-position), and they can adjust the geo-position for their convenience. Therefore, it is important to identify the authenticity of geo-position. In this paper, an instant messaging platform-based geo-tagged spoof image detection system is created using Jaccard similarity. With the help of a Fuzzy filter, the input, as well as spoofing images, are subjected to camera footprint extraction, and their corresponding outputs are fused by Dice Coefficient. Moreover, the input as well as spoofed images is subjected to geotagged process, and their corresponding geotagged input, and geotagged spoofed images are fused by Tanimoto similarity. At last, the fused images from Dice Coefficient, and Tanimoto similarity are employed for the spoof detection process, where the Jaccard similarity compares the two images using Dicerete Cosine Transform (DCT). Consequently, the spoofed images are detected, and their effectiveness is measured in terms of accuracy, False Positive Rate (FPR), and True Positive Rate (TPR), as well as the corresponding values are attained like 0.099, 0.892, and 0.896 respectively.

Perception on Investing in Stocks With ESG Relevance: A Descriptive View on Influence of Key Demographic Variables and Risk Profiling of Investors

2023-10-30T08:44:47+00:00

INTRODUCTION: To be purposeful beyond the return consideration by the way of giving importance to environment, society and governance of company through investing in companies that give priority to aforementioned factors by investors and their perception towards ESG is the crux of this research paper. For this several factors that measures the environment, social and governance are itemized and considered as the dependent variable.

OBJECTIVES: To know whether the influences of the three risk-acceptance levels on environment, social and governance factors were different based on selected demographic variables

METHODS: Some of the key demographic variables like Age range, Annual income and Employment status are taken as independent variables with another key variable the tolerance towards risk of the investors. The individual and interactive effect of the demographic variable along with the key variable (risk tolerance) in manipulating the effects over the dependent variables (ESG) in the key concept of discussion in this research. The research was conducted through a structured questionnaire among the investors in Chennai region of Tamilnadu (India). Data was analyzed through SPSS and the tool used to explain the purpose of the research was MANOVA.

RESULTS: All the three demographic variables considered in the research had a significant influence over the risk tolerance of the investors in manipulating the considerations over the ESG factors.

CONCLUSION: All the three demographic variables considered in the research had a significant influence over the risk tolerance of the investors in manipulating the considerations over the ESG factors.

Classification and Analysis of Soil Types using Bayesian Models for the Crop Agronomy

2023-10-30T09:04:59+00:00

The core objective of this research paper is to classify soil a particular region and also perform the scientific study for the prediction of suitable crops, which will yield more profit to the agronomist. The production of agriculture is mainly depends on soil type, cultivation seasons (climate), irrigation method (such as surface, sprinkler, drip/trickle, subsurface etc) and fertilizers (to increase the crop productivity). Soil is classified based on its physical properties (color, texture, structure, porosity, density etc) and chemical properties (phosphorous, nitrogen, carbon, calcium, magnesium, sodium, pH, potassium, sulfur etc). In this research paper soil types are classified by applying Bayesian models to decision tree algorithm and performed various analysis to verify that soil types are correctly classified and as wells to predict suitable crop cultivation during Kharif (monsoon), Rabi (winter) and Zaid (summer) seasons along with suitable irrigation methods and proper use of fertilizers to increase the crop productivity. The proposed algorithm offers unique features by adopting other tree inducers which produce optimum results even though the conditions are leads to chaotic behavior. The final results obtained are presented which illustrates optimum results and generates best decision tree for classification of soil type from the soil dataset. The Bayesian approach guarantees that the classifications of soil types are more accurate than the existing Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and Decision Tree (DT) algorithms.

Empirical Study on Influencing Factors of Rural Environmental Behavior in Informatization

2023-11-03T10:23:25+00:00

INTRODUCTION: With the advent of the information technology era, rural areas face new environmental protection challenges and opportunities. The rapid development of information technology provides new possibilities for changes in rural ecological behavior. However, understanding the influencing factors of rural environmental behavior in the context of information technology remains an important research topic.

OBJECTIVES: This study aims to reveal the influencing factors of rural environmental behavior in the context of information technology to help governments and policymakers develop effective environmental protection strategies. Specifically, the researchers will focus on the extent to which factors such as education level, ecological awareness, economic status, and social participation influence the environmental behavior of rural residents.

METHODS: A questionnaire survey was used in this study, and residents of a particular rural area were selected as the research subjects. A questionnaire containing questions on education level, environmental awareness, economic status, social participation, and environmental behavior was designed, and a large amount of data was collected through random sampling. Statistical analysis methods, such as regression and correlation analyses, were used to process and interpret the data.

RESULTS: The study's results showed that the education level significantly affected the environmental behavior of rural residents. Residents with higher levels of education were more inclined to take positive ecological protection actions such as waste separation and energy conservation. In addition, environmental awareness was also found to be closely related to environmental behavior, with residents with higher ecological awareness being more concerned about environmental protection and taking action accordingly. Economic status and social participation affected rural residents' environmental behavior to a certain extent but to a lesser extent than education level and ecological awareness.

CONCLUSION: Rural environmental behavior in the context of informatization is affected by a combination of factors. To promote rural ecological protection, the government should strengthen investment in education and improve rural residents' education level and environmental awareness. In addition, social organizations and public participation should also be supported to encourage rural residents to actively participate in environmental protection actions. These measures will help to promote a change in ecological behavior in rural areas and achieve the goal of sustainable development.

A Novel Approach for Earthquake Prediction Using Random Forest and Neural Networks

2023-11-08T08:45:48+00:00

INTRODUCTION: This research paper presents an innovative method that merges neural networks and random forest algorithms to enhance earthquake prediction.

OBJECTIVES: The primary objective of the study is to improve the precision of earthquake prediction by developing a hybrid model that integrates seismic wave data and various extracted features as inputs.

METHODS: By training a neural network to learn the intricate relationships between the input features and earthquake magnitudes and employing a random forest algorithm to enhance the model's generalization and robustness, the researchers aim to achieve more accurate predictions. To evaluate the effectiveness of the proposed approach, an extensive dataset of earthquake records from diverse regions worldwide was employed.

RESULTS: The results revealed that the hybrid model surpassed individual models, demonstrating superior prediction accuracy. This advancement holds profound implications for earthquake monitoring and disaster management, as the prompt and accurate detection of earthquake magnitudes is vital for effective mitigation and response strategies.

CONCLUSION: The significance of this detection technique extends beyond theoretical research, as it can directly benefit organizations like the National Disaster Response Force (NDRF) in their relief efforts. By accurately predicting earthquake magnitudes, the model can facilitate the efficient allocation of resources and the timely delivery of relief materials to areas affected by natural disasters. Ultimately, this research contributes to the growing field of earthquake prediction and reinforces the critical role of data-driven approaches in enhancing our understanding of seismic events, bolstering disaster preparedness, and safeguarding vulnerable communities.

Dynamic Voltage Restorer to Mitigate Voltage Sag/Swell using Black Widow Optimization Technique with FOPID Controller

2023-11-08T10:51:21+00:00

The efficiency with which electrical equipment use electricity is essential for several reasons. First, superior power quality (PQ) improves efficiency and facilitates peak performance in electronic equipment. This article's goal is to make the advantages of installing a Dynamic Voltage Restorer (DVR) to enhance PQ for energy users clearer. To improve DVR dependability and user friendliness, the suggested technique uses a hysteresis voltage control system that works with variable switching frequency. Simulation findings show that voltage compensation is successful under disturbances when a black widow optimization (BWO) based Factional order proportional derivative (FOPID) controller is used. This paper proposed is to improve PQ using a BWO- FOPID controller and compare the outcomes to those achieved from a previously developed PI controller in a distribution power system using MATLAB.

Analysis of Factors Influencing Successful Implementation of ODA Projects for Rural Development: The Case of Kyrgyzstan

2023-11-14T14:25:58+00:00

This paper aims to identify factors that influence the successful implementation of ODA rural development projects for developing countries. To this end, it has analysed the implementation process of a project, ‘The Integrated Rural Development Project in Kyrgyz Republic’, currently being carried out in Kyrgyzstan via Good Neighbors International (GNI) with support from KOICA (Korean International Cooperation Agency). The analysis method employed in this study is decision tree analysis. By means of a review of previous studies on the implementation of ODA projects, variables that are believed to have an impact on the successful implementation of ODA rural development projects were derived. The values of each variable for thirty villages in Kyrgyzstan were derived and used as independent variables, and decision tree analysis was performed using the overall execution performance score for each village as the dependent variable. As a result, it was found that co-operation between field managers active at the project site and village residents was the most important determining factor of success.

Informational Interventions in Environmental Behavior of Rural Residents: Example of Waste Separation and Water Quality Enhancement

2023-11-22T10:59:07+00:00

INTRODUCTION: The ongoing progress in China's rural revitalization and precision poverty alleviation has led to the gradual implementation of environmental improvement initiatives for rural residents. As a result, rural residents' environmental behavior is now being influenced by informatization interventions. With the deepening of these interventions, various environmental behaviors have emerged. Therefore, it is crucial to study the impact of informatization interventions on rural residents' ecological behavior, focusing specifically on garbage classification and water quality enhancement.

OBJECTIVES: To improve the level of China's rural habitat improvement, to improve the mechanism of informatization intervention in the environmental behavior of rural residents; to solve the problem of garbage classification and water quality improvement in the environment of rural residents under the background of informatization intervention, and to improve the level of modernization of China's agriculture and rural areas.

METHODS: First, using the theory of informatization intervention to establish a model of informatization intervention in the environmental behavior of rural residents; secondly, using the questionnaire method to investigate and analyze the ecological behavior of rural residents under the background of informatization intervention in the case townships; finally, using the model to analyze the results of the survey and establish the relevant principles of environmental improvement under the background of informatization intervention.

RESULTS: Under the background of informatization intervention, there is a significant improvement in the environmental behavior of rural residents, and the efficiency of garbage classification is significantly improved compared with the traditional model; the application of informatization intervention has dramatically improved the efficiency of environmental remediation in the case townships, and the informatization intervention can also play a significant role in the improvement of water quality.

CONCLUSION: In the continuous process of rural revitalization and precise poverty alleviation work, to strengthen the informatization intervention of rural residents' environment and comprehensively improve the quality level of rural habitat environment, it is crucial to carry out from various aspects and construct informatization.

Monitoring and analysis of carbon monoxide and methane using Sensors and Remotely Piloted Aircraft Systems

2023-11-22T17:53:17+00:00

INTRODUCTION: Air pollution in urban areas becomes a severe challenge to global health; exposure to polluting gases can lead to different diseases and even human mortality. In this sense, monitoring the concentration of polluting gases such as carbon monoxide and methane is important.

OBJECTIVES: This document focuses on developing a Remotely Piloted Aircraft System (RPAS) to monitor the concentration of carbon monoxide and methane at different altitudes.

METHODS: This includes a Parrot AR Drone 2.0, where the measurement prototype was mounted. The data was transmitted and reception at a ground control station through an application programmed in LabVIEW 15.0.

RESULTS: The experimental measurements showed that the concentration of carbon monoxide remains almost unchanged regardless of variations in altitude. In contrast, methane concentration reduces linearly with the increase in height with respect to ground level in Puerto Maldonado.

CONCLUSION: We implemented an RPAS to monitor in real time, record data in a control station and analyze the concentration of carbon monoxide and methane in the South Eastern Peruvian Amazon.

Automated System for forecasting and capacity management in BPO

2023-11-23T09:59:19+00:00

In the virtual world, every decision made by executives today need forecasting. Sound forecasting of demand and variations are no longer an extravagance but a necessity, since Operations in the organizations have to deal with the seasonality, sudden changes in capacity management, cost-cutting strategies of the competition, and enormous dynamics of the economy.

This paper details the development of a Forecasting and Capacity Planning model to empower operations to consistently forecast incoming volume for scheduling/rostering. A combination of past process-specific data, algorithmic forecasting, Subject Matter Expert (SME) inputs, and modelling results in a forecast with a daily accuracy of up to 85% per month out and approximately 95%-98% per week. The tool leverages the generated forecast to envisage capacity and resource planning. This Capacity Planning tool gives the capacity requirement for the forecasted volume, scheduling, and staffing. The tool has been deployed across 150+ client area. POC (Proof of Concepts) was done across all domains to test the tool and as expected the tools is generating the forecast and schedule with the accuracy of 96.77%.

Assessment of Road Condition: Traffic Safety Requirement

2023-11-24T11:37:35+00:00

Road deaths and injuries highly affect the lives of people worldwide. road injuries and deaths happen due to improper driving, unfit motor vehicles, traffic laws disobeying persons and poor road condition. An effort is made here to assess the factors of poor road conditions which can be improved by prioritizing. Multi criteria technique is applied to prioritize the factors. Ann technique is adopted to assess the road condition. The methodology suggested can be used to determine the level of contribution of parameters towards safety hazard. Accordingly, appropriate mitigation measures may be adopted. A further detailed study needs to be conducted on a large scale by carrying out sensitivity analysis to test the stability of the ranking obtained by the suggested methods.

Stand-alone Micro Grid based on Artificially Intelligent Neural Network (AI-NN)

2023-06-22T14:10:57+00:00

INTRODUCTION: Hybrid stand-alone Small Wind Solar Energy System offers a feasible solution in remote areas where grid connectivity is either financially or physically unavailable. A small wind turbine (SWT) and a solar photovoltaic system are part of the hybrid energy system, which is effectively employed to meet the energy needs of rural household loads.

OBJECTIVE: This research suggests an effective analysis of wind solar hybrid system controllers taking energy demands into account. The controller should be designed in such a way as to intelligently monitor the availability of wind energy and solar energy and store the energy without spilling it out.

METHODS: In order to cope with the challenging factors involved in designing the controller, intelligent power tracking with an artificially intelligent neural network (AI-NN) is designed. Added to that, the whole process has been designed and analysed with the MATLAB SIMULINK tool.

RESUSTS: The results of the simulation, infer that AI-NN achieved the regression value of 0.99 when compared with the Perturb & Observe algorithm (P&O), and the Fuzzy Logic Control (FLC) algorithm, and has a higher tracking speed. Also, the AI-NN attained 2.62kW whereas the P&O has attained 2.52kW and Fuzzy logic has attained 2.43W of power which is 3.89% higher than P&O algorithm and 7.52% higher than fuzzy MPPT algorithm.

CONCLUSION: The designed controller module enhances the system by artificially intelligent algorithm. The AI-NN attains the better power performance with lesser tracking time and higher efficiency. Thus, it is evident that AI-NN MPPT suits well for the hybrid system.