bluuebunny/crossref_metadata_2025 huggingface dataset:
Charging Station Power System Data Prediction Model Based on Deep Learning
Authors: Hu Houpeng , Xiao Yanhong , Ou Jiaxiang , Chen Zerui , He Peilin , Deng Yuedan , Yang Shang
Published: October 2024

The increase growth and adoption of electric vehicles (EVs) are playing a crucial role in advanced transportation system, helping to minimizing the emissions of harmful greenhouse gases and enhancing environmental sustainability. The need for EVs to be charged immediately has gained significant attention due to the rise in EVs sales over the last years. As a result of this, need for electric car charging is important to reducing the impact of electric network and providing minimum charging fares. In order to calculate the demand for charging EVs, a novel Deep Learning (DL)-based Long-Short Term Memory (LSTM) recurrent neural network predictor model is attempted to be developed in this research study. The Modified Aquilla Optimizer Algorithm (MAOA) is used to optimizing the parameter of the new Deep LSTM (DLSTM) neural predictor models and Independent Component Analysis (ICA) is utilized to solve the input time series data while conserving its properties.  In this research, a novel ICA—AOA—DLSTM neural predictor model was developed to addressed the challenges of vanishing and exploding gradient in basic recurrent neural learnings. The predictor model was tested on the EV charging dataset from Georgia Tech, Atlanta, USA, indicating its performance. During simulation, the predictor achieved a prediction accuracies of 96.24% with a mean absolute errors of 0.1083 and a RMSE errors of 3.0629 × 10^-5, outperforming previous techniques. Additionally, the mean absolute error was found to be 0.2083, with a mean square error of 3.25516 × 10^-10. These results highlight the effectiveness of the novel deep learning LSTM neural predictor for this dataset compared to existing techniques.
Research on Teaching Planning and Teacher Evaluation Integrating Sustainable Development and Renewable Energy Concepts
Authors: Yan Dongdong
Published: October 2024

Energy is an essential basis for human survival, social progress and economic development. With the rapid development of China's economy and the acceleration of urbanization, the problem of energy shortage is increasingly serious, and the problem of energy security is prominent. Based on stochastic power flow algorithm, this paper proposes the safety assessment and teaching planning of wind power generation in renewable energy. Firstly, the dynamic safety domain and thermal stability safety domain of wind power systems are proposed in this paper. Within the selected security domain, the key factors that are most likely to lead to the risk of a distribution network are selected by means of entropy-modified analytic hierarchy process (AHP). The incompleteness of the single weighting method is solved, and the total evaluation score of each layer of the index system is calculated from the subjective and objective perspectives to determine the weak link in the occurrence of accidents in the distribution network. The total score is less than 90 points, which is prone to failure risk. Finally, based on the safety index system, PLF is introduced into the uncertainty safety assessment of wind power systems to overcome the inefficiency of traditional uncertainty assessment methods. Methods PLF was used as a means of system state analysis to replace a lot of conventional power flow analysis in uncertain safety assessment, and related safety indexes were defined based on PLF results. The test system ST-PLF is taken as an example to verify the rationality of the proposed method. The results show that the proposed method can effectively realize the static security assessment of the system and identify the potentially vulnerable elements of the system. The evaluation time of the proposed method is 0.73 s, while that of the traditional method is 48.54 s. The evaluation speed of the proposed method is greatly improved, and the time is only 1.55% of that of Monte Carlo method.
Optimization Effectiveness of Multi-Intelligence Consistent Energy System Based on Digital Advertising and Data Analysis
Authors: Shan Lin
Published: October 2024

This paper introduces a novel approach to address the issue of overestimation of state-action values in reinforcement learning algorithms based on the Q-framework. It integrates a dual-layer Q-learning algorithm with a grey wolf intelligent optimization method, enabling rapid search for optimal allocations in unknown search spaces. This integration results in the development of a multi-agent collaborative Area-Grid Coordination (A-GC) strategy, termed the grey wolf double Q (GWDQ) strategy, tailored for multi-area energy interconnection scenarios. The proposed GWDQ strategy is evaluated through simulation experiments on comprehensive energy system models, including mixed gas turbine systems, Combined Cooling, Heating, and Power (CCHP) systems, and a multi-area energy-interconnected Northeast power grid model. A centralized architecture is established to analyze the optimization effects of digital advertising. The performance of the GWDQ strategy is compared with traditional reinforcement learning algorithms through simulation and empirical data validation. Results indicate that the GWDQ strategy exhibits stronger learning capabilities, improved stability, and enhanced control performance compared to traditional methods. It demonstrates superior optimization for digital advertising and enables swift acquisition of optimal coordination in A-GC processes across multiple regions. Additionally, the paper analyzes the environmental and economic impacts of the proposed strategy.
On the Internationalization of English Teaching System in the Planning of Sustainable Development of Future Renewable Energy
Authors: Liu Xianfeng
Published: October 2024

Energy is an essential element of human production and business activities. At present, China's energy development and utilization is facing the contradiction between increasing environmental pressure and high emission energy consumption structure. Based on the optimal power flow algorithm, this paper optimizes the scheduling and international teaching of the power system with a high proportion of renewable energy. The probability density function of fan output and photovoltaic output is obtained by wind speed and light intensity model, and the probability density function of load is also proposed. Then, interruptible load, microgrid and energy storage are used as flexible resources to improve the system’s flexibility to meet the random fluctuations caused by a high proportion of wind and light, so as to maintain the stable operation of the power grid. The mathematical model of process optimization power flow satisfying process constraints is a nonlinear time-varying system. The key to process optimization power flow algorithm is to find a simple and effective linearization and discretization method that is in line with the actual power network. On the basis of ensuring the accuracy of the model, the theory, model and algorithm of the process optimization power flow are studied on the basis of the proposed linear time period, the approximate linear time variability of the node voltage, and the goal of greatly simplifying the problem. Finally, through simulation analysis, comparing the results of model 1 and model 2, we can see that from the point of view of the power abandonment cost, the power abandonment cost of model 1 is 2.29 million yuan, which is less than the 8 million yuan of model 2. From the perspective of depth peaking and start-stop times, the total depth peaking of model 1 is 331 times, which is greater than that of model 2, 258 times. The total start-stop of model 1 is 15 times, which is more than 9 times of model 2, so the total cost of optimized electricity of wind and light in model 2 is less than that in model 1. According to the optimal scheduling model of wind and light renewable energy, the effective utilization rate of renewable energy in China is low, and the teaching system should pay attention to this problem. Therefore, this paper puts forward an international English teaching strategy for the utilization rate of renewable energy.
Asymmetrical Six-phase GaN-based Drive Performance Analysis with Variable Switching Frequency Control
Authors: Maitane Carrasco  , Amaia Lopez-de-Heredia  , Irma Villar
Published: October 2024

This paper analyses the performance ofa GaN-based multiphase drive when a variable switching frequency control is implemented for EV applications. The GaN-based inverters allow a wide switching frequency range, and the power losses of the inverter are reduced in comparison with other technologies such as Si. To be able to benefit from this wide switching frequency range, a variable switching frequency control with the objective of maintaining a ratio frequency ???????? = 17 is implemented. This control reduces the switching frequency losses above 30% in the three analysed speed points in comparison with maintaining a constant switching frequency. Hence, an efficiency improvement is achieved with the variable switching frequency control tackling one of the main problems of the EV.
Dynamic Evaluation Method of Electric Power New Energy and River Basin Ecological Restoration
Authors: Dang Tianjiao
Published: October 2024

The wide application of renewable energy can reduce the carbon emissions to the environment and the consumption of petrochemical resources, improve the improvement rate of the natural environment, and at the same time, ecological restoration can improve the ecology of the river basin and produce sustainable improvement of the environment together with renewable energy. In this paper, renewable energy is taken as the research object, and the ecological restoration method of the river basin is jointly evaluated to comprehensively evaluate the natural environment. First, the carbon neutrality data of ecological restoration and renewable energy in the river basin were collected, classified, collated and integrated, and the analysis indicators included CO2 emissions, plant coverage, soil and water conservation, and the cost of power generation. Then, the spatial regression model was used for data processing and calculation, and the ecological coefficient and carbon emission coefficient were determined in an iterative manner. Finally, the actual case is used for dynamic evaluation and analysis. The results show that the new power and watershed ecological restoration methods can improve the natural environment, improve the plant coverage rate and soil and water conservation rate, with an increase rate of 25~30%, reduce carbon dioxide emissions and power generation costs, and reduce the reduction rate of 10~30%, and at the same time, a good ecological environment will also react to new energy and expand the development space of new energy, with an expansion rate of 10%. Therefore, the method of electric power new energy and river basin ecological restoration can improve the natural environment, promote the development of electric power new energy, and optimize the overall structure of new energy.
Optimized Genetic Algorithms: Study of the Impact on Load Distribution in the Power System
Authors: Huang Sheng , Xie Ruibiao , Wu Jintao , Chen Yufeng , Li Chuanjian
Published: October 2024

In order to balance the power flow, voltage and current between renewable energy power generation and thermal power generation, this paper takes renewable energy as the research object, analyzes the power flow and voltage after grid connection, and proposes an improved genetic algorithm for research. Firstly, the log function is used to analyze the power flow and voltage data before and after grid connection, reduce the complexity of the data, and calculate the proportion of photovoltaic energy. Then, the load analysis of the power system was carried out by genetic iteration to identify the overloaded nodes, and the identification standard was greater than 80% of the rated load. Finally, a load set is formed, and information such as changes, power flow, and voltage of different power generation nodes is recorded. The results show that the genetic algorithm can maximize the proportion of renewable energy to 50% and reduce the power flow change rate of the power system to 10%. At the same time, improve the load efficiency of the power system, so that the node load is between 75~80%, average the load of each node, especially the photovoltaic matrix and fan, and shorten the load deployment time, so that it is 10s smaller. Compared with the previous algorithms, the genetic algorithm proposed in this paper is better, which can meet the load distribution requirements of the power system and expand the energy proportion of renewable energy.
Optimising energy efficiency enhancing NILM through high- resolution data analytics
Authors: C. Rodriguez-Navarro  , F. Portillo  , L. Castro-Santos  , A. Filgueira-Vizoso  , F. G. Montoya  , A. Alcayde
Published: October 2024

This study introduces a novel approach to enhancing energy efficiency by building a high-resolution dataset for Non-Intrusive Load Monitoring, addressing the challenges of monitoring a wide range of devices. To achieve optimal energy efficiency, it is essential to have advanced monitoring of electrical variables. In this context, the second version of openZmeter is presented, which supports up to 4 devices, each capable of 160 measurements, including voltage, current and power harmonics on each channel. To carry out this purpose, the Non-Intrusive Load Monitoring Toolkit is adapted for the new openZmeter v2. The main objective of this study is to offer a new pragmatic approach to generating artificial intelligence models to optimise energy use, analysing the results through an exhaustive experimental analysis under various casuistry and conditions. Numerous comparative studies are provided using classical disaggregation algorithms with different requirements. Conclusively, the research emphasises the transformative potential of artificial intelligence for energy efficiency strategies, offering insights for scholars and practitioners.
Use of a Decision Tree to Define Transformer Oil Contamination from On-Load Tap-Changer Gases to Ensure Power Quality in the Grid
Authors: S. Bustamante  , J. L. M. Lastra  , M. Manana  , A. Arroyo
Published: October 2024

Power transformers are one of the most important and critical assets in the electricity distribution and transmission network. Power quality (PQ) can be disturbed when a power transformer is brought into or out of service, so it is very important to be sure of the reason for this action. Dissolved gas analysis (DGA) in oil can be used to diagnose the condition of transformer insulation. There may be situations where the DGA results indicate the presence of a serious fault which would lead to the transformer being taken out of service, when in fact the high gas concentrations are due to the leakage into the main oil tank of gases generated in the on-load tap-changer (OLTC) during normal operation. In previous work, using machine learning techniques and a distribution system operator's DGA database, a decision tree (DT) was developed to identify oil contamination from OLTC gases. In this work, the developed DT is applied to a new DGA database to identify contaminated transformers and test its accuracy. A total of 1161 DGA results from 95 transformers with OLTC were used, giving an initial DT accuracy of 83.13% when all samples were analysed and 85.26% when the last DGA result from each transformer was used.
4D hybridisable interpolation methodology aimed at system modelling: application to a fuel cell blower
Authors: J. Rodriguez-Gongora  , F.J. Asensio  , A. Ordono  , M. Gonzalez-Perez  , G. Saldaña  , O. Oñederra
Published: October 2024

This paper focuses on providing an empirical model construction methodology based on Piecewise Cubic Hermite Interpolation Polynomials (PCHIP). The proposed methodology is suitable for modelling systems with high non-linearity between system parameters, process variables and/or operation variables. A detailed description of the 4D interpolation methodology is given and a practical application for a fuel cell (FC) blower black-box model obtaining is shown. The results of the algorithm-based model are compared to datasheet specifications to validate the FC blower model. The validation shows a good precision in the operation limits estimation. Additionally, some FC-related applications suitable for the obtained blower model utilization are described.
Monitoring of Pests and Diseases by New Energy Aerial Mapping Methods
Authors: He Yuanyuan
Published: October 2024

To expand the application of new energy technology in agriculture and improve the monitoring effect of agricultural pests and diseases, this paper proposes a new energy aerial tracing method to extract the identification indicators of pests and diseases in aerial photography. Then, combined with the occurrence area and occurrence rate of pests and diseases, the calculation and analysis were carried out, and the early warning was carried out according to the point characteristics of pests and diseases. The results show that the monitoring and identification of pests and diseases can improve the identification rate of flying pests, plant pests and underground pests by combining the new energy aerial mapping method, improve the identification accuracy from 74.68% to 88.67%, and carry out early warning, reduce the cost of agricultural loss by 38 million~154 million yuan, and the identification range from 14,500 hectares~16,500 hectares, and reduce the monitoring time by 74.5~87.5%. Therefore, new energy technology can meet the monitoring requirements of agricultural pests and diseases, which is helpful to promote the development of new energy further.
Fault detection and mitigation in MVDC grids using a Non-Unit Voltage Ratio Derivative Algorithm
Authors: A. Blazquez  , M.J. Pérez-Molina  , P. Eguia  , D.M. Larruskain  , A. Iturregi  , E. Torres
Published: October 2024

Future MVDC grids will be used to reinforce the grid infrastructure enhancing transmission capabilities, minimizing losses, and providing capability to compensate reactive power as well as to control load flows. This paper addresses the protection of MVDC grids, which is one of the main challenges to be overcome, before taking advantage of all the inherent benefits that this technology will bring. The main objective of this paper is to validate a non-unit voltage derivative fault detection algorithm in a MVDC grid with green hydrogen production. The performance is analyzed with different fault cases and fault locations. As a main conclusion, the distance is the most relevant factor, which affects detection and tripping times.
Influence of offshore wind turbine size in levelised cost of energy
Authors: I. Arrambide
Published: October 2024

Offshore wind energy is developing rapidly in recent years. Within the offshore wind energy industry, the main advance that has occurred has been the wind turbine growth. In fact, the offshore turbines have changed from small turbines adapted to the marine environment to turbines that currently range between 16~18 MW. This increase has been done in order to cut down costs and get longer production of wind energy, consequently, reducing the levelized cost of energy. The current mechanisms for assigning marine sites are based on successive auctions organized by government agencies. In some countries, these auctions are carried out through reverse bidding, that is, they are awarded to the promoters who present the lowest sales price for the energy generated or, in the case of other countries, that price marked in the auction has a partial weight of 60%~80% in the final ranking. Other countries organize a second type of reverse auction to award subsidies, which, being limited, are awarded to the promoters who present the lowest energy sales price. In this article, a comparative study developed for evaluation of the value of levelized cost of energy, as a result of bigger nameplate capacity of the offshore wind turbines. The results show that the bigger turbine capacity, the lower the levelized cost of energy is obtained.
Educational Station for the Generation and Use of Green Hydrogen
Authors: C. Capellán-Villacián  , A. Falces  , P.J. Zorzano-Santamaría  , E. Zorzano-Alba  , M. Mendoza-Villena  , P.M. Lara-Santillán  , E. García-Garrido  , L.A. Fernández-Jiménez
Published: October 2024

Globally, electrical energy predominantly derives from fossil fuels such as coal, oil, and natural gas, which significantly emit greenhouse gases, thereby accelerating ecosystem degradation and climate change. In response, recent decades have witnessed a surge in the development of clean, sustainable electricity generation technologies such as wind and solar photovoltaic systems. These renewable sources are expected to replace fossil fuel-based methods but are limited by their dependency on variable weather conditions, which cannot align with electricity demand. Periods when energy production exceeds demand highlight the critical role of innovative storage solutions. Notably, surplus energy can be utilized for hydrogen production via water electrolysis, producing “Green Hydrogen”, which generates no polluting emissions. This shift towards sustainable technologies necessitates novel educational approaches. It is essential to revise curricula to include these technologies, ensuring students are well-prepared for the evolving energy sector. This article discusses the design and construction of a green hydrogen educational station built with commercial materials for laboratory use, embodying the integration of renewable energy technologies into academic programs and promoting hands-on learning experiences in energy management and sustainability.
Dynamic modelling and optimal operation of the photovoltaic/thermal
Authors: K. Sredenšek  , E. Simonič  , S. Seme
Published: October 2024

This paper aims to introduce a dynamic model for a photovoltaic/thermal system, highlighting an approach and synthesis of existing dynamic models to depict the full photovoltaic/thermal system. The model was validated using data from an experimental setup at the Institute of Energy Technology, Faculty of Energy Technology, University of Maribor, under different weather conditions. The model's accuracy was assessed through normalized Root Mean Square Error, normalized Mean Bias Error, Correlation Coefficient, and the coefficient of determination error metrics, focusing on the temperature and electrical output power of the photovoltaic/thermal modules, as well as the temperature of the thermal energy storage tank. Furthermore, the paper also focuses on the optimal operation of the photovoltaic/thermal system under different mass flow rates of the working medium.
Analysis of the Impact of Renewable Energy Application on the Cost of Green Building Projects
Authors: Tang Linmei
Published: October 2024

Green building is a sustainable ecological building, and the application of renewable energy to green buildings can protect the ecological environment and reduce energy consumption to a certain extent, so this paper makes an in-depth analysis of the impact of renewable energy application on the cost of green building projects. Firstly, the grey correlation analysis was used to analyze the characteristic indicators of renewable energy applied to the cost of green building projects, and the estimation index system of green building projects was constructed. Then, the improved genetic algorithm was used to construct the explanatory variables and control variables of green building project cost control, the variation factors of green building project cost control were analyzed through principal component analysis, and the elastic modulus and regression discriminant method were combined to complete the impact analysis of renewable energy application to green building project cost. The simulation results show that the algorithm can effectively reduce the economic cost of green buildings, ensure the quality of buildings, and protect the natural ecological environment.
Evaluation of MCP Correlation Algorithms Applied to Wind Data Series
Authors: A. Moreira  , T. Rocha  , J. Mendonça  , R. Pilão  , P. Pinto
Published: October 2024

This work aimed to develop methodologies for analysing statistical correlations among wind data series using various Measure-Correlate-Predict (MCP) methods, with the goal of selecting the most suitable method for extrapolating long-term data with minimal associated uncertainty. It was analysed the minimum time required for a wind measurement campaign when applying this methodology. Fifteen local wind measurement stations were selected. The long-term wind data reanalysis series that exhibited the strongest correlation with the measured wind data at each station was then chosen. Multiple tests were conducted with different simultaneous periods between the measured data series and the long-term series. Fifteen correlation algorithms were tested for each concurrent period. The performance of each model was evaluated using the RMSE (Root Mean Square Error) and MBE (Mean Bias Error) associated with each MCP. Analysis of the errors identified measurement periods with the lowest associated error ranging from 1 to 5 years and a single-factor ANOVA analysis was conducted. Finally, t-significance tests were performed. The study concluded that the Neural Network was the most effective MCP method. Additionally, it was determined that the minimum number of years required for a local measurement campaign should be between 2 and 3 years.
Effect of soy flour and flour improvers on nutritional value, texture, colour and sensory characteristics of wafer biscuits
Authors: Alkhalalieh Nazieh , Frehat Ghadeer
Published: October 2024

Biscuits are a popular and desirable snack food by consumers. Still, the quality of these products decreases during the storage process, so this study focuses on improving the wafer's quality and nutritional value and reducing their fragility by partially replacing wheat flour with soybean flour in the following proportions: 5% (T1),  10%  (T2),  15% (T3), 20% (T4), and adding ammonium carbonate in different quantities. The sensory evaluation showed that the best wafer treatment was supported with 15% soy flour and 150 g of ammonium carbonate. At the same time, the mean for sensory evaluation is 8.80. Also, the results of the chemical analysis (protein, moisture, fat, carbohydrate, ash, fibre) texture and colour after direct manufacturing and after three months of storage. The result showed a significant increase in the percentage of protein and fat from 6.56±0.30 to 12.19 ± 0.35,  11.56±0.10 to 19.64±0.55, respectively the moisture content was higher in the control was 3.88±0.02 for wafer sample 2.47±0.13, while fibre was 1.93±0.15. The carbohydrates in the control sample were higher than in other treatments. Texture and colour were improved compared with the control. Commercial-batter biscuits with high nutritional value content and high-quality properties can be prepared by replacing wheat flour with 15% soy flour and adding 150 g of ammonium carbonate.
El genocidio del pueblo Gitano, proceso histórico y actualidad. Desafíos educativos
Authors: Nin María Cristina , Shmite Stella Maris , Molini Judith
Published: October 2024

Los roma o romaníes conforman un mosaico de grupos diversificados, pero más allá de estar fragmentados en la actualidad son la minoría más numerosa de Europa y su presencia en América lleva siglos. La dispersión geográfica del conjunto poblacional de este pueblo se caracteriza por las relaciones que se sostienen en el conjunto global y a su vez por características propias de cada grupo en la organización social, cultural y política. El conocimiento de la situación de la minoría gitana es una problemática territorial que trasciende las fronteras de Europa y, por lo tanto, requiere de su interpretación en diferentes escalas. En este trabajo se propone abordar en clave geo-histórica dicho proceso y el análisis de las posibilidades pedagógicas desde la mirada de las políticas y normativas vinculadas con la inclusión de minorías al sistema educativo argentino. La intención es valorar y visibilizar la historia y cultura gitana con el propósito de generar debates de temáticas marginales en el curriculum y en las propuestas pedagógicas de los diferentes niveles de enseñanza. Además, se realiza un análisis de la inclusión de la comunidad gitana en el sistema educativo de La Pampa a partir de dos experiencias. Se concluye acerca de la relevancia de abordar la temática desde las dimensiones curricular y de la inclusión educativa.
A COMPREHENSIVE ANALYSIS ON THE STRATEGIC IMPORTANCE OF INDO-PACIFIC REGION IN GLOBAL POLITICS
Authors: Shah Faisal Muhammad Inam Khan Yousafzai, Muhammad Usama
Published: October 2024

The Indo-pacific region is enfolding the vast areas and islands which surroundings either the Indian Ocean or the Pacific Ocean. In the geopolitical theme the term earliest used by the German geopolitician in 1920s in his numerous work on geopolitics. The region significance reinvigorate in the contemporary world politics. Australia, Japan and India popularized the term they conducted trilateral dialogues and sometimes discuss the region under the US umbrella. In the contemporary world the Indo-pacific region lay down implications on the global politics due to its huge importance. This research paper aim to examine the Indo-pacific region and to unfolding its different sides which are connected with the global politics. The paper thoroughly investigate currents ongoing geopolitical and geo-economics significance of the region. Major and Middle powers have been trying to acquire their respective national interest from the region. The United States trying to persist her hegemony in the region reactive the quadrilateral security dialogue which is the group of foursome Australia, India, Japan and US and leading by US to contain the broader engagements of China in the Indo-Pacific region and concentrating to mitigate the China geopolitical and geo-economics influences through different strategy. This paper assess the China Belt and Road Initiatives which mainly focusing on the geo-economics connectivity of multiple countries for the targeted purposes. China increasing leadership influences in the region is impelling United States and its partner countries such as India, Japan, US, Taiwan, South Korea and Philippines which have been confronting against China interest and the region is transferring into a new regional geopolitical tension and seeming to drag into new cold war between Sino-US. The free and open Indo-pacific concept reinvigorate 1906 by the Japanese prim minister Shinzo Abe with the American cooperation. In 2019, United States has formalized the concept and referred many Southeast Asia and European Union States to the Indo-Pacific. The concept has been criticized by the China official that it a closed and exclusive group structure and called for open and inclusive Asia-Pacific which does not target any third country.
ECONOMIC SECURITY CHALLENGES TO PAKISTAN DURING POST PANDEMIC ERA
Authors: Samer Fatima
Published: October 2024

Pakistan’s economy has faced many challenges since the inception of Pakistan as an independent state. The economy of country was largely dependent on agrarian resources during the initial decades and then industrial bases afterwards. During the past three decades it the economy of Pakistan depends on loans and financial aids from international financial institutions such as, IMF along the industrial growth. The world economy slowed down after the pandemic and it also had consequences on Pakistan economy. Covid-19 caused major disruption in Pakistan economy. As, Before pandemic the GDP growth rate was 2.50% in 2019 and it fell in negative point -1.27% during the fiscal year 2020. The economic challenges to Pakistan raised during pandemic era such as its GDP growth rate decreased in negative points, its fiscal debt increased to 12.74% in 2020 as compare to 2019. Unemployment, shut down of small businesses, increase in job displacement, fiscal deficit, decline in foreign direct investment are the few challenges to name. Therefore, the economic security of Pakistan had faced many challenges during the post pandemic era. The drastic impact of covid-19 forced government to take immediate steps to counter economic challenges. The first national security policy of Pakistan in this regard made economic indicators as a challenge and made economic security a part of national policy
Static Analysis of Single Shaft Hub Wheel Cover to Determine The Strength Level of The Cover
Authors: Kurnia Ishak Rizaldy Eka , Muttaqin Benazir Imam Arif , Huki Chandra
Published: October 2024

The cover on the wheel hub serves to protect the most important components and support the weight coming from the body, so it must be designed as well as possible to support the existing weight. The cover on the wheel hub also functions as a balance when driving so that the cover is made with strong material and is not easy to corrode because the part is often subjected to mechanical pressures. The problems that occur in the Nusantara Energy Manufacturing company (MEN) make researchers want to develop a cover design on a single shaft wheel hub to increase the strength of the cover in receiving pressure from vehicles, drivers, and passengers. In this research, a simulation study is carried out to design the cover and perform static simulations to determine the value of deformation and stress that occurs in the single shaft wheel hub cover. The material used in the cover design is Aluminum Alloy 6061 with a load value of 2177 N and 2912 N. The maximum deformation value on the MEN cover is 0.272 mm, a strain value of 0.007, and a stress value of 730.805 N/m2 with a load of 2177 N. At 2912 N loading, the maximum deformation value is 0.111 mm, a strain value of 0.003, and a stress of 307.538 N/m2. It can be concluded that the MEN cover has a higher static value than the YMMotorcover. There are several factors such as the thickness of the cover on the parts used as supportpoints.
Design and Implementation of Tire Pressure and Temperature Monitoring System for Hatchback and Multi-Purpose Vehicle Based on IoT
Authors: Briantoro Hendy , Budikarso Anang , Arifin  , Rahman Md. Mahbubur
Published: October 2024

Tire Pressure Monitoring Systems (TPMS) have developed into an essential element in vehicles to improve safety and driving experience. In general, TPMS systems rely on special hardware to collect and transmit tire pressure data to the vehicle's on-board computer and this data can only be viewed by the driver and passengers in the vehicle. In this study, we developed a remote tire pressure and temperature monitoring system using IoT technology. The MQTT protocol facilitated communication between the cloud server and controller, while the system uses Docker container to simplify program integration. The results revealed the optimal standard deviation for tire pressure in hatchback vehicles to be 2.24, and for Multi-Purpose Vehicles (MPVs), it was 2.97. For tire temperature, the best standard deviation in hatchback vehicles was 1.93, compared to 1.05 in MPVs. This system effectively monitors tire pressure and temperature changes in real time, accessible remotely via smartphones and computers.
Implementation of Website-Based UI UX Using the Design Thinking Method: Case Study at PT Jesinra Makmur Group
Authors: Firdani Ella Fadila , Hanif Isa Faqihuddin , Muhammad Febriansyah  , Widsono Maulana Yusuf
Published: October 2024

In the era of globalization, the imported goods shipping industry is growing rapidly. PT Jesinra Makmur Group, as a provider of imported goods delivery services, needs to ensure that the user experience (UI/UX) on its website platform is optimal. This research aims to redesign the UI/UX of the PT Jesinra Makmur Group website using a Design Thinking approach. The Design Thinking method consists of several stages, namely empathize, define, ideate, prototype, and testing. In this research, researchers will understand user needs, identify problems, generate creative ideas, create prototypes, and test proposed solutions. This research uses the System Usability Scale (SUS) to measure the success of UI/UX design, and a score of 87.75% was obtained, which indicates a high level of excellence. This shows that users feel comfortable and that it is easy to use the website. The results of this research are expected to provide a better solution for PT Jesinra Makmur Group to provide an optimal user experience through their website. By implementing the Design Thinking method, it is hoped that PT Jesinra Makmur Group can improve the UI/UX of their website and provide better service to customers.
ON THE ISSUE OF KAZAKHSTAN’S USE OF NATIONAL HISTORY AS AN ELEMENT OF SOFT POWER
Authors:   R.B. Suleimenov Institute of Oriental Studies, Duisen Galymzhan , Sabyrov Ayan ,   Scientific Fellow of the R.B. Suleimenov Institute of Oriental Studies
Published: October 2024

The article discusses the possibility of Kazakhstan’s using its national history as an element of soft power in its foreign policy. Particular attention is paid to the conceptual and methodological foundations of soft power, as well as to the analysis of the world-renowned ratings of soft power in terms of their applicability in assessing the «resourceness» of national history. The article proposes some perspective ways of promoting the national history of Kazakhstan among the international audiences.
Laparoscopic peritoneal lavage – a new treatment strategy in spontaneous bacterial peritonitis and liver cirrhosis
Authors: Anghelici Gheorghe , Zugrav Tatiana , Pisarenco Sergiu , Crudu Oleg , Lupu Gheorghe , Apascaritei Ana
Published: October 2024

Introduction Bacterial infections in cirrhotic patients represent a major clinical problem, occuring 4-5 times more frequently compared to the general population and increasing mortality by leading to acute on chronic liver failure, subsequent decompensation, and multiorgan failure. The study’s purpose is to determine the possibilities of laparoscopy in the treatment of spontaneous bacterial peritonitis with decompensated liver cirrhosis. Materials and methods A retrospective descriptive study was conducted on 82 patients diagnosed with liver cirrhosis and spontaneous bacterial peritonitis, who were admitted to the Constantin Tibirna Surgery department No2, Holy Trinity Municipal Clinical Hospital and the Scientific Research Laboratory of Hepatic Surgery, Nicolae Testemițanu State University of Medicine and Pharmacy, Chisinau, Republic of Moldova, between January 2012 and December 2021. Patients who underwent surgical drainage of the abdominal cavity by laparoscopy with postoperative peritoneal lavage with antibiotics were selected. All patients received standard treatment for the correction of liver function and complications of portal hypertension. The data were extracted from the medical records of the hospital archive, and the patient database was compiled. Data analysis was performed using simple statistical calculations. Results Positive ascitic fluid bacterial culture was in 29.2% (24 patients), while 70.7% (58 patients) had culture-negative ascites and peritonitis. The most frequent bacterial species was E. coli, present in 54.1% (13 patients). Mortality was 8.5% (7 patients) due to progressive liver failure. Recurrence of ascites and peritonitis at 1 month was 6.0% (5 patients). Conclusions The laparoscopic approach in spontaneous bacterial peritonitis in patients with decompensated liver cirrhosis allows for better sanitation of the abdominal cavity, improves peritoneal absorption, and deserves establishment as clinical practice for patients with ascites and peritonitis and cirrhosis.
Deep endometriosis – impact on infertility, endometriosis fertility index, and reproductive prognosis (comparative study)
Authors: Codreanu Nadejda , Ivanova Elena
Published: October 2024

Introduction Deep infiltrating endometriosis (DIE) is the most severe form of endometriosis, contributes to pelvic pain syndrome, extragenital symptoms, fertility problems, and diminished reproductive prognosis for affected individuals. It is recommended to use the Endometriosis Fertility Index (EFI) to assess reproductive prognosis and conduct clinical research to compare reproductive prognosis in different forms of endometriosis. Objective Comparison of the impact of the DIE and others forms of endometriosis on EFI, patients' fertility and on reproductive prognosis to understand the management approach. Materials and methods A cohort study included 190 reproductive-age women, divided according to the #Enzian classification: the main group - 85 patients with DIE, the control group - 105 women with other forms of endometriosis. The EFI was utilized for reproductive prognosis. Pain was evaluated with Visual Analog Scale (VAS). Statistical analyses were performed using SPSS, with calculation of the Mann-Whitney U and Pearson's chi-square test (χ²). Results In main group, the frequency of infertility was 83.5% compared to the control group's 71.4% (p > 0.05). The EFI in main group was 7.18±0.25 points vs the control group's 7.13±0.28 points (p = 0.852). Patients in the main group suffered from intense pelvic pain (>7 points by the VAS, p < 0.01), including severe dyspareunia (7.85±0.33 points vs 2.18±0.46 points in control group, p < 0.01). Conclusions Our results suggest that infertility in women with DIE may be more often associated with sexual abstinence due to significant dyspareunia rather than organic impairments. Thus, EFI in patients with DIE does not reflect all aspects of infertility and has reservations, and consideration of both physical symptoms and sexual health is crucial in managing DIE to optimize fertility outcomes. These findings open the way to the feasibility of surgical treatment of DIE to improve sexual quality of life, which will reduce the need for IVF and increase the chances of spontaneous pregnancy in patients, but this conclusion requires further investigation in randomized clinical trials.
Temporary splinting in periodontally mobile teeth: review before application
Authors: Ceban Mariana , Ceban Victor , Pantea Vitalie
Published: October 2024

Introduction Temporary splinting of mobile, periodontally compromised teeth is an important stage in the complex treatment of periodontitis, used to improve mastication, aesthetics, and the prognosis for teeth with pathological mobility. It helps prevent this phenomenon and consolidate the success of conservative and surgical treatment, which also has a positive effect on the patient's psycho-emotional state. Material and methods 12 patients (6 female and 6 male), aged 26–60 years, with pathological teeth mobility due to chronic generalized periodontitis, were included in the study. Temporary splinting was performed using fiberglass threads braided with polyester microfibers, polyethylene fibers, and aramid fibers, and in all clinical cases, it was secured with photo-composite material designed for teeth splinting. Results Temporary splinting is a very important step in periodontitis treatment, and dynamic monitoring is necessary throughout the entire period of splinting. The interval between visits is determined based on the type of splinting, the risk of complications, the severity of periodontitis, systemic and local factors, the level of individual oral hygiene, and the patient's motivation. The interval can be 6 months, 4 months, or, in aggressive forms of periodontitis, 2 months. Conclusions Temporary splinting contributes to the effectiveness of pathogenetic and symptomatic therapy.
Management of diabetic retinopathy in pregnancy
Authors: Scerbatiuc Cristina
Published: October 2024

Introduction The onset and development of diabetic retinopathy are more common during pregnancy. Pregnancy has no long-term effect on diabetic retinopathy; however, in 50-70% of cases, changes in retinopathy continues. The probability of worsening is highest in the second trimester and up to one year postpartum. Additional factors that have been associated with disease progression include duration of diabetes, the degree of retinopathy at the time of conception, management of hyperglycemia, anemia, and development of associated hypertension. In cases of severe non-proliferative retinopathy, it is recommended to promptly initiate laser photocoagulation rather than wait for early proliferative changes. Maintaining good diabetic control before and during pregnancy can help prevent disease progression and serious vision loss. Material and methods Diabetic retinopathy management in pregnancy was the subject of a comprehensive review of the scientific and medical literature. A structured search was performed in the PubMed, Scopus and HINARI databases, considering relevant articles published in the last 10 years. The search terms used (in English) were: „Diabetic retinopathy”; „pregnancy”; „laser photocoagulation”; „intravitreal steroids”; „anti-vascular endothelial growth factor”. Results It is suggested that women with diabetes receive pre-conception and post-pregnancy counselling from a multidisciplinary team including an ophthalmologist, endocrinologist, and perinatologist, as diabetic retinopathy may worsen during pregnancy. The risk of progression of the disease and the importance of appropriate metabolic control before and during pregnancy should be clearly explained to the patient. Careful monitoring is required in patients with advanced gestation, significant retinopathy, concomitant hypertension, and nephropathy. Conclusion The risk of retinopathy development may increase during pregnancy. Serious effects can arise for both the mother and the fetus, even though retinopathy is not common during pregnancy. It is possible to avoid significant retinopathy by carefully planning a young diabetic woman's pregnancy and proceeding promptly to laser photocoagulate in cases of severe non-proliferative retinopathy. A tendency for regress is frequently seen in diabetic retinopathy during the post-natal period. Subsequent pregnancies do not significantly increase the risk of progression if the retinopathy is stable before pregnancy.
Frequency Analysis of Gas Discharge Based Memristor Emulator for Ferroresonance
Authors: S. Poornima
Published: October 2024

The nonlinear resistance for suppression of ferroresonance modes can be realized using memristive circuits. Based on voltage requirement, gas discharge memristive circuit has been chosen. As a primary requirement, the nonlinear characteristics of memristive circuit have been investigated in this work. The memristive nature at all chosen frequencies are analyzed interms of hysteresis nature. The suitability of chosen circuit against all modes of ferroresonance is identified interms of nonlinear index and memductance values obtained using Simulink. The nonlinear index with respect to symmetrical hysteresis response decreases as the frequency increases. The memductance has been calculated to verify the load requirement under the ferroresonance frequencies. As the frequency increases, the memristive emulator loses its symmetry gradually from fundamental frequency.
SYNTHESIS OF A FUZZY PID-CONTROLLER USING THERMAL OBJECT LABORATORY SIMULATOR
Authors:   Lipetsk State Technical University, BATISHCHEV R.V. , BESTIKOV D.S. ,   Lipetsk State Technical University, LARINA E.V. ,   Lipetsk State Technical University
Published: October 2024

This article presents the results of modeling on the Thermal Object laboratory facility, in particular, transfer functions along the input voltage – temperature channel are used. Fuzzy controllers are synthesized and investigated.
PECULIARITIES OF TORQUE DISTRIBUTION BY POWER LOCK DIFFERENTIAL WHEN INSTALLED IN THE REAR DRIVE AXLE OF A WHEELED TRACTOR
Authors:   Lipetsk State Technical University, KAZ’MIN B.N. , YUROV M.D. ,   Lipetsk State Technical University
Published: October 2024

The article considers the possibility of ensuring the operation of a self-locking differential of the driving axle of a wheel tractor with a high value of the blocking coefficient in various operating conditions.