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

Mintesnot Gizaw — 2023-08-01

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.

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

P Muthulakshmi — 2023-08-14

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

Ali Abderrazak Tadjeddine — 2023-07-31

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.

Analysis of Improved Particle Swarm Algorithm in Wireless Sensor Network Localization

Yafeng Chen — 2023-09-11

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

Miguel Bernabé-Custodio — 2023-07-11

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)

Raed Naif Alahamidi — 2023-08-09

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

Yu Zhang — 2023-01-24

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

Jiangbo Liu — 2023-03-12

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

Mengfan Xu — 2023-05-03

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

Binbin Han — 2023-05-30

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

Chen Ding — 2023-06-22

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.

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

Aram Mohammed-Amin Qadir — 2023-09-06

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

Xinyang Zhang — 2023-07-27

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

Na Meng — 2023-09-19

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

Lei Song — 2023-09-19

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

Yuqi Bian — 2023-09-22

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

Xiang Li — 2023-09-22

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

Wen Wang — 2023-09-26

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

Erika Gabriela Ramos-Liza — 2023-09-29

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.

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

Jenitha R. — 2023-06-22

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.

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

Shenao Chen — 2023-08-23

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.