Management System Research Articles

Pelvic Traumas and Hybrid Emergency Medicine System: Literature Review Based on Two Cases

Objective: Bleeding, the most common life-threatening complication of pelvic trauma occurs due to injuries of pelvic arterial and venous structures and bone fractures. The outcomes of patients can be improved by a timely performed angioembolisation (AE). Hybrid Emergency Service System (HERS) has been recently introduced a novel approach which provides trauma resuscitation room equipped with computerized tomography, fluoroscopy, and an operating room, thus effects the outcomes of trauma patients. Cases: We presented two pelvic traumas and in both cases with the most common life-threatening complication was bleeding. In both cases, whole-body computed tomography (WBCT), endovascular procedures (Resuscitative Endovascular Balloon Occlusion of the Aorta (REBOA), transcatheter arterial embolization (TAE)), and injury control surgery can be simultaneously performed without the need to transport a patient to an operating room which is called HERS resuscitation. Both patients were discharged and remained free of any medical problem at long-term (12 months) follow-up. Conclusion: Considering the recently introduced HERS system in patient management and integrating it into emergency services will be extremely useful in the management of trauma and trauma-induced bleeding.

Enhanced Multi‐Objective Optimization Model for Bridge Performance Assessment and Prediction, Based on Improved PCA, K‐Means Clustering, and Kaplan–Meier Survival Algorithm

ABSTRACTThe research proposes a hybrid algorithm model that combines model‐driven and data‐driven approaches for the direct application of bridge health monitoring technology in bridge management. This comprehensive study encompasses a series of analytical techniques and methodologies to build a multi‐objective optimization model for bridge performance assessment and prediction. It focuses on the processing of multi‐source heterogeneous data, selection of key sub‐parameters using Principal Component Analysis (PCA), enhanced K‐means clustering analysis, determination of structural component target thresholds, time‐dependent survival probability analysis, regression fitting, and timing prediction of the bridge system for both the components of double‐layer truss arch bridge and the bridge system. The initial phase of the study concentrates on the diversification and decentralization of monitored data from various sources, integrating and cleaning data obtained from different sources to ensure data quality and consistency. PCA technique is applied to identify key sub‐parameters that have significant impacts on the performance of structural components. Enhanced K‐means clustering analysis is carried out to effectively group and classify the identified key sub‐parameters. Numerical simulations, including structural nonlinear analysis, are conducted to determine the target thresholds of bridge structure, providing important benchmarks for performance evaluation. Finally, a multi‐parameter regression model is used to evaluate and update the performance of the bridge structure, taking into account survival probability (using the Kaplan–Meier method), maintenance history, and material deterioration to estimate the most critical time for the bridge system. A case study is conducted to validate the suggested comprehensive algorithms for a double‐layer truss arch combination bridge, which contributes to enhancing performance evaluation and predicting the most critical time for structural components and bridge system in the bridge management and maintenance practices. It should not be ignored that, the accuracy and reasonability of bridge structure system performance evaluation and prediction depend largely on the selection of target thresholds.

BIM/IFC as input for registering apartment rights in a 3D Land Administration Systems – A prototype webservice

The need for 3D Land Administration Systems (LAS) is growing. In this respect, research is carried out in the field of 3D LAS with respect to data sources, registration of 3D Rights, Restrictions and Responsibilities and dissemination services. Within this context, BIM/IFC models are considered promising sources for 3D LAS, even though the reuse of such models from practice has not yet been examined adequately. Evaluating BIM/IFC-models from practice is crucial, since they are created for different purposes, fulfilling various design criteria. This paper investigates the technical challenges encountered when using real-world BIM/IFC-models for apartment rights’ registration in a 3D LAS. It addresses the validation of five Dutch real-world BIM/IFC-models against four technical criteria, namely: existence of IfcSpace; geometric validity; no overlap and georeferencing. The results of the validation show that the collected BIM/IFC-models lack georeference, IfcSpace and a reference to attributes related to the respective legal units in the Dutch 3D LAS. After validation the models are stored in a 3D LAS Database management system (DBMS), in which the legal spaces are enriched with information of the Rights, Restrictions and Responsibilities (RRR’s) in line with the Land Administration Domain Model (LADM - ISO 19152:2012). The contents of the 3D LAS DBMS are visualised in a web viewer. Additionally, the design for a webservice is introduced, aiming to automate the process of validation, conversion and visualisation. The paper concludes with recommendations and guidelines for creators of BIM/IFC-models based on the outcome of the validation, as well as challenges and recommendations for implementing a validation webservice.

Does smartphone use encourage farmers to participate in centralized household waste disposal?

The centralization of household waste disposal represents a significant stride toward achieving ecological viability in rural China. This initiative can substantially alleviate the grassroots government's burden of managing rural household waste. The proliferation and utilization of smartphones, a powerful tool that can expedite and reduce the cost of imparting environmental protection knowledge to producers, is a beacon of hope in the fight against waste. This article, utilizing Probit modeling and micro-survey data from 2126 agricultural households in China, examines the effect of smartphone usage on farmers' participation in centralized household waste disposal. The findings indicate that smartphone usage significantly enhances farmers' engagement in centralized domestic waste disposal, motivating them to participate actively. Notably, this finding persists even after robustness tests. Further heterogeneity analyses indicate that older and low-income populations exhibit a more pronounced level of engagement in centralized household waste disposal. This paper presents these findings and underscores the importance of the proposed policies to enhance farmers' consciousness regarding the environmental implications of smartphone usage. These policies are not just suggestions but urgent and necessary steps towards a more technologically advanced and efficient waste management system, and their implementation is crucial for the future of waste management.

Exploring the Challenges and Opportunities of Blended Learning in a Technology–Enabled Education Environment

Technology integration in education has led to blended learning, a pedagogical approach combining traditional face-to-face instruction with online learning components. Through a comprehensive review of existing literature and empirical research, this investigation examines the impact of blended learning on both students and educators. It delves into this approach's diverse range of technologies, including Learning Management Systems, video conferencing tools, and digital content platforms. Through qualitative and quantitative analysis, the research identifies the opportunities that arise from adopting blended learning. It investigates the advantages of increased student flexibility, personalised learning experiences, and enhanced access to educational resources. The study explores how interactive content and virtual collaboration tools can boost student engagement and motivation. However, the study also uncovers educators' and students' challenges when implementing blended learning. These obstacles include technology access and proficiency issues, consistent communication, and addressing individual learning needs. The study addresses potential resistance to change from traditional teaching methods and the importance of teacher training and support. It compares students' achievements in blended learning environments with those in traditional classrooms and analyses the role of technology in influencing these outcomes. Based on the findings, the research concludes by providing insights into the future implications of blended learning in technology-enabled education environments. Keywords: Blended Learning; Learning Management System; Technology-enabled learning

Research on the Storage Process Management System Based on RFID

With the continuous development and complexity of the global supply chain, warehouse automation and intelligent technology have become the key means to improve the efficiency and accuracy. The application of radio frequency identification (RFID) in storage process management is discussed, Use RFID technology to manage the storage process, pretreatment the goods, and improve the overall logistics speed. At the same time, the visualization technology is used to monitor the status of the goods, The full state of cargo preprocessing to the end of the task is visible.

Optimization model for mass casualty management system using qos-aware routing protocol and casualty triage prediction

Abstract Purpose Unexpected events, whether man-made or natural, cause significant distress and disorder. The number and magnitude of disasters and catastrophes have been rising globally in recent decades, according to historical data. Continued real-time monitoring of mass casualty along with the arrangement of needed medical resources to handle the mass casualty is required to reduce the mortality and morbidity rates. Methods Electronic tag-based casualty monitoring and machine learning-based Decision Support Systems are emerging as a more effective and proactive solution that provides continuous remote monitoring of patients. A novel framework based on Body-to-Body Network, Prediction model, and Genetic Algorithm-based medical resource optimization is proposed for the continuous monitoring of the mass casualty and medical resource allocation at the incident. The aim of this work is to give priority to the handling of critical casualties. Firstly, a Quality of Service and load-sensitive routing protocol for transmitting mass casualties' physiological parameters across a wireless network is proposed, with the critical casualty being emphasized. Secondly, the clinical seriousness degree of the mass casualty is predicted using Backpropagation Artificial Neural Network. Finally, an optimization model using a Genetic algorithm and queuing theory is proposed to find the required optimal number of medical resources to handle critical and non-critical casualties separately. Also, the proposed optimization model considers the predicted clinical level transition rates of the mass casualty. Results The performance and accuracy of the proposed framework are evaluated using the MIMIC-II dataset. The outcome demonstrates that the framework emphasizes critical casualty management. Furthermore, the framework allocates an adequate number of servers by incorporating the proposed routing protocol in comparison to the AODV protocol. Conclusion The inclusion of a prediction model in the framework aids in allocating an adequate number of servers by considering the predicted clinical deteriorating transition rates of casualties at a mass casualty incident. In terms of the estimated length of the casualty at the incident, the results suggest that incorporating a medical resource optimization model outperforms the non-optimal option.

Driving License Management System Using Finger Print Sensors with Seat Belt Monitoring System

The finger print based driving license management is an advanced technology that is designed for security purposes. This system consists of a fingerprint sensor, which is used to identify the status of the driver, whether he/she obtained a license or not. This is a very highly secured system. The driver's fingerprint is already stored in the system for comparison purposes. Nowadays, accidents are increasing day by day. In the recent days minor people are driving the vehicles without the license; this may cause future accidents. In order to conquer this, we proposed this system. This system not only checks the license status, and here a further IR sensor is used to check whether the seat belt wore or not. By using this system, there are tremendous advantages, like accidents will be reduced, high security, and reduced vehicle theft. Keywords: Finger print sensor, microcontroller, and IR sensor.

Enhanced composite controller for PV/PMSG/PEMFC and BESS‐based DC microgrids voltage regulation: Integrating integral terminal sliding mode controller and recursive backstepping controller

AbstractThe variability of renewable energy sources due to weather patterns often leads to a mismatch between power generation and consumption within microgrids (MGs). This challenge is exacerbated when integrating bio‐renewable units, complicating stability maintenance in MGs. This research work introduces a novel solution to address this issue: a composite controller merging an integral terminal sliding mode controller with a recursive backstepping controller for direct current MGs (DCMGs). The proposed DCMG incorporates solar photovoltaic units, wind farms based on permanent magnet synchronous generators, proton exchange membrane fuel cells fuelled by hydrogen gas, an electrolyser, battery energy storage systems, and DC loads. First, a comprehensive mathematical model for the components within the DCMG is developed to design the proposed composite controller. This controller not only overcomes the inherent limitations and convergence issues of conventional SMCs but also ensures stable DC‐bus voltage and maintains power balance across various operational conditions. Moreover, a fuzzy logic‐based energy management system is introduced to regulate power flow, considering factors like battery state of charge and renewable energy sources' total power output. The control Lyapunov function confirms the DCMG system's asymptotic stability. Finally, the proposed controller's effectiveness is validated through simulations on both MATLAB/Simulink and Arduino Mega 2650 processor‐in‐the‐loop platforms under various operational conditions. In both platforms, the proposed controller surpasses an existing controller in terms of settling time, overshoot, and tracking error of the DC‐bus voltage.

Research on the Optimization Path of Strategic Cost Management under the Background of the Digital Economy

Under the background of the digital economy, the research on the optimization path of strategic cost management for enterprises is particularly important. This paper discusses key paths such as data-driven cost management systems, intelligent cost control, and collaborative cost management, revealing the profound impact of the digital economy on corporate cost management and proposing a series of optimization strategies. The data-driven cost management system requires enterprises to establish comprehensive data collection and analysis mechanisms, using big data and advanced analytical tools to achieve real-time monitoring and dynamic analysis of costs. This not only improves the accuracy of cost management but also enhances the enterprise's ability to respond to market changes. Secondly, the implementation of intelligent cost control, through automated and predictive cost management, enables enterprises to more effectively control and predict cost changes, thereby improving the efficiency of resource allocation and the quality of cost management decisions. Furthermore, the development of collaborative cost management emphasizes the synergy between internal departments of enterprises and with external partners. By breaking down information silos and promoting resource sharing and business collaboration, enterprises can achieve cost optimization throughout the entire value chain.

Self-Powered, Flexible, Wireless and Intelligent Human Health Management System Based on Natural Recyclable Materials.

Combining wearable sensors with modern technologies such as internet of things and big data to monitor or intervene in obesity-induced chronic diseases, such as obstructive sleep apnea, type II diabetes, cardiovascular diseases, and Alzheimer's disease, is of great significance to the self-health management of human beings. This study designed a loofah-conducting graphite four friction layer enhanced triboelectric nanogenerator (LG-TENG) and developed a health management system for human motion recognition and early warning of sleep breathing abnormalities. By uniformly spraying and depositing conductive graphite on the surface of the loofah and the elastic film cross-interlocking bending structure design, the signal strength of the LG-TENG has been improved by 390%. The stable output signal is still maintained after 1500 s of continuous operation at a frequency of 2 Hz. LG-TENG can realize accurate motion analysis by muscle contraction state. Combining different deep learning models resulted in 98.1% accuracy in recognizing seven categories of displacement speeds for an individual and 96.46% accuracy in recognizing seven categories of displacement speeds for three individuals. In addition, the sleep breathing monitoring early warning system was developed by integrating Bluetooth wireless transmission and upper computer analysis technology. This system aims to analyze and provide real-time warnings for sleep-breathing abnormalities. This research promotes an innovation of TENG technology based on the advantages of natural materials, recyclability and low cost. It offers new ideas for self-health management and scientific exercise for obese people, showing a broad application prospect.

Validating Circular End-of-Life Strategies for Domestic Post-Consumer Materials in the Latin American Region: A Life Cycle Assessment Approach

This study examines the domestic solid waste management system in the LATAM region, using the city of Guayaquil in Ecuador as a case study. Through the life cycle assessment (LCA) methodology, the study compares domestic and external recycling processes, evaluating their effects on global warming potential, fossil resource scarcity, and terrestrial ecotoxicity. The results reveal that increasing recycling rates significantly reduces environmental impacts, with domestic recycling offering slightly higher environmental benefits than external options. A demographic analysis using machine learning techniques identifies distinct patterns of waste generation across different population clusters, highlighting the need for tailored waste management strategies. The study also emphasizes the importance of accurate local data and the integration of recycling initiatives with market realities, particularly in the light of policies mandating recycled content in products like PET bottles. A sensitivity analysis of the waste recovery indicator (WRI) demonstrates the potential for substantial environmental and economic benefits with higher recycling rates. The findings suggest that, to advance towards a circular economy, Latin American cities like Guayaquil must enhance their recycling infrastructure, refine waste management policies, and focus on demographic-specific strategies. This research contributes to the broader understanding of sustainable waste management in developing regions, offering insights for future policy and infrastructure development.

Analysis of the status and influencing factors of dignity impairment symptoms in critically ill patients after ICU treatment

To investigate the status of dignity impairment symptoms in critically ill patients after ICU treatment and conduct a systematic analysis of its influencing factors, aiming to provide reference for clinical medical decision-making by healthcare professionals. A cross-sectional survey study. From April 15th to 21st, 2024, a cross-sectional survey was conducted in 40 tertiary Grade A comprehensive hospitals in 9 provinces, municipalities, and autonomous regions including Sichuan Province, Zhejiang Province, and Chongqing Municipality. Various critically ill patients who were admitted to ICU treatment were surveyed using a general information questionnaire and the Dignity Inventory. A total of 346 questionnaires were collected in this survey, with 333 valid questionnaires and an effective response rate of 96%. The incidence rate of dignity impairment symptoms in critically ill patients after ICU treatment was 39%. Multifactor logistic regression analysis showed that age [OR = 1.124, 95%CI=(1.067–1.184)], frequency of visits [OR = 1.875, 95%CI=(1.075–3.269)], length of ICU stay [OR = 1.352, 95%CI=(1.108–1.649)], and tracheotomy upon discharge [OR = 2.269, 95%CI=(1.273–4.044)] were risk factors for dignity impairment symptoms in critically ill patients after ICU treatment. Number of children [OR = 0.247, 95%CI=(0.106–0.576)] was a protective factor for dignity impairment symptoms in critically ill patients after ICU treatment. Although the incidence of dignity impairment symptoms in critically ill patients after ICU treatment is relatively low, the psychological trauma it causes cannot be ignored. Healthcare professionals must actively establish and improve its prevention and management system.

Pattern of Adverse Drug Reactions and Performed Monitoring Laboratory-Tests in Patients Receiving Anti Tuberculosis Treatment in an Endemic Region, Zabol

Background: Efficient anti TB treatment considered crucial globally. Anti TB drugs can cause various adverse drug reactions (ADRs). Clinical and laboratory monitoring will decrease rate of these ADRs, improve patient safety as well as drug adherence and treatment outcome. Methods: In this cross-sectional study total of 136 newly diagnosed TB patients were included. All patients received standard anti-TB 4 drug regimen. Predesigned data collection forms were used to gather patient’s lab data as well as clinical symptoms they experienced during treatment course. Monthly follow up visits or phone calls were also performed by investigators and all health issues were recorded. Results: The majority of our patients aged over 70-year-old. About 54% of them were female. We recorded at least one ADR in 80.8% of patients, and hepatic-gastrointestinal (GI) ADRs ranked first (64.7%). Although ADRs were more common in women and patients over 70-year-old, but there was no statistically significant relationship between sex or age and rate of ADRs (P> 0.05). We also observed that recommended baseline laboratory tests for monitoring anti TB treatment was not performed in any of our patients, except complete blood count (CBC) that was performed in 11 cases. This led to diagnoses of anemia and thrombocytopenia in one case. Conclusion: The majority of our patients experienced ADR. Recommended drug monitoring tests that could guarantee safe and effective treatment were not performed routinely in our TB management centres. These facts highlighted the importance of improving surveillance system for TB management based on national standards.

Elderly Care Provision under National Policy on Older Persons 2013: A Cross-Sectional Study in Dhaka City, Bangladesh

Bangladesh is undergoing a notable demographic transition, characterized by a substantial rise in the proportion of elderly individuals within its population. This demographic transition presents a range of economic, social and cultural issues that necessitate prompt attention and intervention. The aim of this study was to examine the current state of elderly care services and facilities available for older adults in urban landscape by taking into account the ‘National Policy on Older Persons 2013.’ This study was conducted in Dhaka city by employing a cross-sectional study design. The study population covers elderly people aged 60+ years, living in Dhaka City for more than five years continuously and are able to speak well with someone. The study was based on a sample of 240 and the respondents were chosen using convenient sampling technique. The data were collected through face-to-face interview using structured questionnaire and they were analyzed utilizing descriptive statistics. This study found that the existing elderly care services and available opportunities are below the satisfactory level for most of the older adults of the city, even though the ‘National Policy on Older Persons 2013’ was adopted a decade ago. The elderly people in Dhaka city encountered a number of difficulties considering their physical health, psychological and social well-being. In the case of availability of the affordable and quality healthcare services for older adults in their community, 30.4% of the respondents said that the availability, accessibility and affordability of quality healthcare services are very poor, followed by 24.6% below average and 26.3% at the average level. Nearly 75% of the study people said that they had ever experienced unfair treatment for being aged. Indeed, they receive care and support in an inconsistent, disorganized and incoherent manner. The study clearly revealed that there is a need to prioritize person-centered care as well as integrated care system for the effective management of the ageing population in Bangladesh. Jagannath University Journal of Science, Volume 11, Number 1, June 2024, pp. 118−134

Database Construction and Application of Large-scale Geospatial Data

Abstract. Geospatial data refers to data that related to spatial location. It is the abstract representation of objects, events, or other characteristic information located on or near the surface of the Earth. It characterizes attribute features, spatial features, and associated information of geospatial features. Geospatial data commonly include various data types such as point, polyline, polygon, and so on. Geospatial database is the basic method to store and manage geospatial data. It is also the important component of geographic information systems (GIS). Geospatial database generally stores data in a specific structure in a medium, which can achieve efficient management of geospatial data. Users can add, modify, and delete data efficiently. Furthermore, query retrieval and statistical analysis can be quickly performed based on geospatial database. In this paper, distributed geospatial database is constructed by using database partition tables storage technology. Meanwhile, database construction software is developed to achieve the construction, management, and application of large-scale geospatial data. It can improve data import, query and retrieval efficiency significantly. The database application service system can directly connect to the database for displaying statistical analysis results. At the same time, geospatial data are processed to vector tiles, which stored in the tile database. Furthermore, standard online service is then published, which can be used for database management and application service system. It can be used for natural resource management work such as basic surveying, survey and monitoring, and so on.

Design and Testing of a Web-Based Student Information Management System

Politeknik Piksi Ganesha is an institution of higher learning located in Bandung, Indonesia, specializing in engineering and technological curricula. The research's general objective is to describe the design and implementation of the web-based Student Information Management System (SIMS) to manage student data at Politeknik Piksi Ganesha Bandung. The functional and non-functional specifications are represented using Unified Modeling Language (UML) based on broad data collection through observation, interviews, and a literature review. It also entails black-box testing, which measures the system's performance against set criteria, focusing on the output without the details of its internal workings. The significant findings indicate that SIMS enhances highly administrative processes, accuracy in data, and good communication among stakeholders by applying clear UML diagrams of the system. This successful system development meets the institution's requirements and adds to the bar for other developments within the educational technology sector. The result has also emphasized the need for practical design methodologies and testing frameworks to develop reliable information systems to improve decision-making in academic institutions. The research has contributed significantly to the discipline because it has shown how different technological innovations can alleviate the problems surrounding managing student information at higher education levels.

Path analysis of coal mine accident risk factors based on the 24Model.

Coal mine accidents seriously affect China's coal safety production and sustainable development. The present study aimed to reveal the risk factors in coal mine accidents and explore the causal relationship among risk factors. This study utilized text mining to analyse 450 coal mine accident reports, identifying 50 risk factors and efficiently mapping them into the 24Model. The association rule algorithm was then used to mine the strong association rules among the risk factors within the 24Model, establishing the interaction mechanism among them. Based on the strong association rules, related hypotheses were proposed. Finally, the hierarchical and logical relationships of risk factors within the 24Model were analysed, and the causal and mediating effects were tested by path analysis. The safety management system has a direct effect on unsafe acts, unsafe conditions, habitual behaviour and organizational safety culture. Moreover, external influence has an effect on unsafe acts, organizational safety culture and habitual behaviour through the mediating effect of the safety management system. Based on the results obtained, this study proposes a series of specific measures to prevent risks in coal mines, providing a new perspective for the analysis and prevention of accidents.

Strategic Transformation and Sustainability: Unveiling the EFQM Model 2025

The EFQM Model (European Foundation for Quality Management), established in 1991, serves as a framework for organizational excellence, helping achieve sustainable success through an integrated management system. The Model’s evolution is driven by the need to adapt to global trends, threats, and technological innovations such as digital transformation, employee engagement and well-being, remote work, agile performance management, diversity, equity and inclusion (DEI), sustainability, AI (Artificial Intelligence), and big data. The new EFQM Model 2025, presented in Istanbul in June 2024, introduces significant changes, emphasizing sustainability, innovation, and technology. These changes are analyzed based on the logic of three questions: Why, How, and What. Why: There is a necessity for better alignment of organizations with contemporary challenges through flexibility, risk resilience, and innovation capabilities in a dynamic business environment, including alignment with the Unated Nations Sustainable Development Goals (SDGs). How: The Model introduces an integrated approach to performance management and transformation, incorporating advanced technologies such as AI and data analytics. What: Implementing the EFQM Model 2025 enhances organizational adaptability, innovation, and flexibility, improving financial, operational, and strategic outcomes. Better alignment with sustainability goals leads to long-term value and social responsibility. Improved stakeholder engagement methods enhance understanding and satisfaction. The use of advanced technologies supports innovation and operational efficiency, while better strategic and operational performance and risk management ensure greater stability and the ability to anticipate future challenges.

Energy Management System and Control of Plug-in Hybrid Electric Vehicle Charging Stations in a Grid-Connected Microgrid

In the complex environment of microgrid deployments targeted at geographic regions, the seamless integration of renewable energy sources meets a variety of essential challenges. These include the unpredictable nature of renewable energy, characterized by intermittent energy generation, as well as ongoing fluctuations in load demand, the vulnerabilities present in distribution network failures, and the unpredictability that results from unfavorable weather conditions. These unexpected events work together to disturb the delicate balance between energy supply and demand, raising the alarming threat of system instability and, in the worst cases, the sudden advent of damaging blackouts. To address this issue, a fuzzy logic-based energy management system has been developed to monitor, manage, and optimize energy consumption in microgrids. This study focuses on the control of diesel generators and utility grids in a grid-connected microgrid which manages and evaluates numerous energy consumption and distribution features within a specified system, e.g., building or a microgrid. An energy management system is suggested based on fuzzy logic as a swift fix for complications with effective and competent resource management, and its presentation is compared with both the grid-connected and off-grid modes of the microgrid. In the end, the results exhibit that the proposed controller outclasses the predictable controllers in dropping sudden variations that arise during the addition of sources of renewable energy, supporting the refurbishment of the constant system.