https://journal.umy.ac.id/index.php/jrc/issue/feedJournal of Robotics and Control (JRC)2024-03-22T05:24:57+07:00JRC Editorjrcofumy@gmail.comOpen Journal Systems<p align="justify"><strong>Journal of Robotics and Control (JRC) p-ISSN: <a href="https://portal.issn.org/resource/ISSN/2715-5056" target="_blank">2715-5056</a>, e-ISSN: <a href="https://portal.issn.org/resource/ISSN/2715-5072" target="_blank">2715-5072</a> </strong>is an international peer-review open-access journal published bi-monthly, six times a year by Universitas Muhammadiyah Yogyakarta in collaboration with <strong><a href="https://ptti.web.id/publication/" target="_blank">Peneliti Teknologi Teknik Indonesia</a></strong>. <span>The Journal of Robotics and Control (JRC) invites scientists and engineers worldwide to exchange and disseminate theoretical and practice-oriented topics of development and advances in <strong>robotics</strong> and <strong>control</strong> within the whole spectrum of robotics and control. </span><strong>Journal of Robotics and Control (JRC) </strong>has been indexed by <strong><a href="https://www.scopus.com/sourceid/21101058819" target="_blank">SCOPUS</a></strong> and is available in <strong><a href="https://www.scimagojr.com/journalsearch.php?q=21101058819&tip=sid&clean=0" target="_blank">SCIMAGO</a></strong>.</p><table class="data" width="100%" bgcolor="#f0f0f0"><tbody><tr valign="top"><td width="20%">Journal title</td><td width="80%"><strong> Journal of Robotics and Control (JRC)</strong></td></tr><tr valign="top"><td width="20%">Abbreviation</td><td width="80%"> <strong>JRC</strong></td></tr><tr valign="top"><td width="20%">Frequency</td><td width="80%"><strong> 6 issues per year</strong></td></tr><tr valign="top"><td width="20%">Type of Review</td><td width="80%"><strong> Double Blind Review</strong><strong><br /></strong></td></tr><tr valign="top"><td width="20%">Print ISSN</td><td width="80%"> <a href="https://portal.issn.org/resource/ISSN/2715-5056" target="_blank"><strong>2715-5056</strong></a></td></tr><tr valign="top"><td width="20%">Online ISSN</td><td width="80%"> <a href="https://portal.issn.org/resource/ISSN/2715-5072" target="_blank"><strong>2715-5072</strong></a></td></tr><tr valign="top"><td width="20%">Editor</td><td width="80%"> <strong>See</strong> <a href="/index.php/jrc/about/editorialTeam" target="_self"><strong>Editor</strong></a></td></tr><tr valign="top"><td width="20%">Publisher</td><td width="80%"> <a href="http://www.umy.ac.id/" target="_blank"><strong>Universitas Muhammadiyah Yogyakarta</strong></a>, in collaboration with <a href="https://ptti.web.id/publication/" target="_blank"><strong>Peneliti Teknologi Teknik Indonesia (PTTI)</strong></a></td></tr><tr valign="top"><td width="20%">Organizer</td><td width="80%"> <a href="https://ptti.web.id/journal/" target="_blank"><strong>Peneliti Teknologi Teknik Indonesia (PTTI)</strong></a></td></tr><tr valign="top"><td width="20%">Citation Analysis</td><td width="80%"> <strong><a href="https://scholar.google.co.id/citations?view_op=list_works&hl=en&user=3-o13vEAAAAJ" target="_blank">Google Scholar</a> | <a href="https://www.scopus.com/sourceid/21101058819" target="_blank">Scopus</a> | <a href="https://app.dimensions.ai/discover/publication?search_mode=content&and_facet_source_title=jour.1385953" target="_blank">Dimensions</a> | <a href="https://www.scimagojr.com/journalsearch.php?q=21101058819&tip=sid&clean=0" target="_blank">Scimago</a> <strong>|</strong> <a href="/index.php/jrc/pages/view/wos_citation" target="_blank">Web of Science</a></strong></td></tr><tr valign="top"><td width="20%"><span>Abstracting & Indexing</span></td><td width="80%"> <a href="https://www.ebsco.com/m/ee/Marketing/titleLists/aci-coverage.htm" target="_blank"><strong>EBSCO</strong></a></td></tr><tr valign="top"><td width="20%">Digital Marketing</td><td width="80%"> <strong><a href="https://mail.cloudmatika.com/" target="_blank">Direct Email</a> | <a href="https://www.youtube.com/c/AlfianCenter" target="_blank">Youtube Channel</a> | <a href="https://www.instagram.com/portalpublikasi/" target="_blank">Instagram</a> | Twitter</strong></td></tr></tbody></table><p> </p><table class="data" width="100%" bgcolor="#f0f0f0"><thead><tr><th style="text-align: center;" width="33%">Time to First Decision</th><th style="text-align: center;" width="33%">Review Time</th><th style="text-align: center;" width="33%">Publication Time</th></tr><tr><th style="text-align: center;" width="30%">2 Weeks</th><th style="text-align: center;" width="33%">4 weeks</th><th style="text-align: center;" width="33%">2 Weeks</th></tr></thead></table><p align="justify"> </p><table><thead><tr><td><p align="justify"> </p><div style="height: 100px; width: 180px; font-family: Arial, Verdana, helvetica, sans-serif; background-color: #ffffff; display: inline-block;"><div style="padding: 0px 16px;"><div style="padding-top: 3px; line-height: 1;"><div style="float: left; font-size: 28px;"><span id="citescoreVal" style="letter-spacing: -2px; display: inline-block; padding-top: 7px; line-height: .75;">4.7</span></div><div style="float: right; font-size: 14px; padding-top: 3px; text-align: right;"><span id="citescoreYearVal" style="display: block;">2022</span>CiteScore</div></div><div style="clear: both;"> </div><div style="padding-top: 3px;"><div style="height: 4px; background-color: #dcdcdc;"><div id="percentActBar" style="height: 4px; background-color: #007398; width: 66%;"> </div></div><div style="font-size: 11px;"><span id="citescorePerVal">66th percentile</span></div></div><div style="font-size: 12px; text-align: right;">Powered by <span><img style="width: 50px; height: 15px;" src="https://www.scopus.com/static/images/scopusLogoOrange.svg" alt="Scopus" /></span></div></div></div></td><td> </td><td><p> <a title="SCImago Journal & Country Rank" href="https://www.scimagojr.com/journalsearch.php?q=21101058819&tip=sid&exact=no"><img src="https://www.scimagojr.com/journal_img.php?id=21101058819" alt="SCImago Journal & Country Rank" border="0" /></a></p></td></tr></thead></table><p> </p>https://journal.umy.ac.id/index.php/jrc/article/view/20896Optimizing Solar Energy Production in Partially Shaded PV Systems with PSO-INC Hybrid Control2024-03-21T15:54:20+07:00Sarah AbboudSarahabboud24@gmail.comAzeddine Loulijatrehalloulijat@gmail.comAbdellah Boulalboulalabdellah@gmail.comEl Alami Semmasemmaalam@yahoo.frRachid Habachirachid.habachi@uhp.ac.maHamid Chojaahamid.chojaa@usmba.ac.maAlfian Ma'arifalfianmaarif@ee.uad.ac.idIswanto Suwarnoiswanto_te@umy.ac.idMahmoud A. Mossamahmoud_a_mossa@mu.edu.egPartial shading, from obstacles such as buildings or trees, is a major challenge for photovoltaic systems, causing unpredictable fluctuations in solar energy production and underlining the need for advanced energy management strategies. In this paper, we propose an innovative approach that combines hybrid metaheuristic optimization with maximum power point tracking control (MPPT), using particle swarm optimization (PSO) in conjunction with the incremental conductance (IC) algorithm. We compare the proposed method with the conventional Perturb and Observation (P&O) algorithm. The choice of P&O as a comparison method is due to its simplicity, its familiarity with the scientific literature, its low cost of implementation. The main objective of swarm optimization combined with the IC algorithm lies in its ability to overcome the challenges posed by partial shading, ensuring accurate and efficient tracking of the point of maximum power, thanks to dynamic adaptation to variations in solar irradiation, thus enhancing the performance and resilience of the photovoltaic system. This approach is of crucial importance, offering considerable potential for solving the complex challenges associated with partial shading. Our results show that this hybrid MPPT algorithm offers superior tracking efficiency > 98% , faster convergence 500ms , better stability and increased robustness compared to traditional MPPT approaches. The system is composed of a PV and a boost converter that connects the input to the resistive load. The algorithms were implemented with MATLAB/Simulink as the simulation tool. These results not only reinforce the viability of sustainable energy solutions, but also open the way for the development of more sustainable energy solutions.The perspectives of this work are oriented towards a practical and extended integration of the proposed hybrid approach in real photovoltaic systems, with a particular emphasis on experimental validation.2024-02-07T11:49:29+07:00Copyright (c) 2024 Sarah Abboud, Azeddine Loulijat, Abdellah Boulal, El Alami Semma, Rachid Habachi, Hamid Chojaa, Alfian Ma'arif, Iswanto Suwarno, Mahmoud A. Mossahttps://journal.umy.ac.id/index.php/jrc/article/view/21127Soft Actuator Based on a Novel Variable Stiffness Compound Extensor Bending-Pneumatic Artificial Muscle (CEB-PAM): Design and Mathematical Model2024-03-21T15:54:21+07:00Wafaa Al-Mayahiengpg.wafaa.daraj@uobasrah.edu.iqHassanin Al-Fahaamhassanin.husein@uobasrah.edu.iq<p>Soft robots have gained prominence in various fields in recent years, particularly in medical applications such as rehabilitation, due to their numerous advantages. The primary building blocks of a soft robot are often pneumatic artificial muscles (PAM). The Extensor PAM (EPAM), including Extensor Bending PAM (EB-PAM), is characterized by its low stiffness, and because stiffness is important in many robotic applications, for example, in rehabilitation, the degree of disability varies from one person to another, such as spasticity, weakness, and contracture. Therefore, it was necessary to provide an actuator with variable stiffness whose stiffness can be controlled to provide the appropriate need for each person, this study presents a new design for the EB-PAM that combines the EB-PAM and contractor PAM (CPAM), It has higher stiffness than traditional EPAM, A stiffness of over 850 N/m was achieved, whereas EB-PAM only reached a stiffness of less than 450 N/m, it is also possible to change its stiffness at a specific bending angle. It is also possible to obtain fixed stiffness at different angles. A mathematical model was developed to calculate the output force of the new muscle by calculating its size and the pressure applied to it and comparing the model with experimental results. The mathematical model was enhanced by calculating the wasted energy consumed by the actuator before the bladder begins to expand, and also by calculating the thickness of the bladder and the sleeve. To make the muscle lighter, cheaper, and work under low pressures, balloons were used in manufacturing, offering practical advantages for soft robotic applications.</p>2024-02-09T16:44:37+07:00Copyright (c) 2024 Wafaa Al-Mayahi, Hassanin Al-Fahaamhttps://journal.umy.ac.id/index.php/jrc/article/view/20850Review of Intelligent and Nature-Inspired Algorithms-Based Methods for Tuning PID Controllers in Industrial Applications2024-03-21T15:54:21+07:00Ramakant S Patilramakant.patil@rait.ac.inSharad P. Jadhavharad.jadhav@rait.ac.inMachhindranath D. Patilmdpatil1610@gmail.com<p>PID controllers can regulate and stabilize processes in response to changes and disturbances. This paper provides a comprehensive review of PID controller tuning methods for industrial applications, emphasizing intelligent and nature-inspired algorithms. Techniques such as Fuzzy Logic (FL), Artificial Neural Networks (ANN), and Adaptive Neuro Fuzzy Inference System (ANFIS) are explored. Additionally, nature-inspired algorithms, including evolutionary algorithms like Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO), Simulated Annealing (SA), Artificial Bee Colony (ABC), Firefly Algorithm (FA), Cuckoo Search (CS), Harmony Search (HS), and Grey Wolf Optimization (GWO), are examined. While conventional PID tuning methods are valuable, the evolving landscape of control engineering has led to the exploration of intelligent and nature-inspired algorithms to further enhance PID controller performance in specific applications. The study conducts a thorough analysis of these tuning methods, evaluating their effectiveness in industrial applications through a comprehensive literature review. The primary aim is to offer empirical evidence on the efficacy of various algorithms in PID tuning. This work presents a comparative analysis of algorithmic performance and their real-world applications, contributing to a comprehensive understanding of the discussed tuning methods. Findings aim to uncover the strengths and weaknesses of diverse PID tuning methods in industrial contexts, guiding practitioners and researchers. This paper is a sincere effort to address the lack of specific quantitative comparisons in existing literature, bridging the gap in empirical evidence and serving as a valuable reference for optimizing intelligent and nature-inspired algorithms-based PID controllers in various industrial applications. Keywords— PID controller; Intelligent and Nature-Inspired Algorithms; Fuzzy Logic; Artificial Neural Network; Adaptive NeuroFuzzy Inference System; Genetic Algorithm; Particle Swarm Optimization; Differential Evolution; Ant Colony Optimization; Simulated Annealing; Artificial Bee Colony; Firefly Algorithm; Cuckoo Search; Harmony Search; Grey Wolf Optimization.</p>2024-02-12T19:54:34+07:00Copyright (c) 2024 Ramakant S Patil, Sharad P. Jadhav, Machhindranath D. Patilhttps://journal.umy.ac.id/index.php/jrc/article/view/21083Application of Software Robots Using Artificial Intelligence Technologies in the Educational Process of the University2024-03-21T15:54:21+07:00Serik Yeslyamovsyeslyamov@gmail.com<p>The use of artificial intelligence (AI) in education has gained interest due to its increasing application in various fields. This study explores the potential of AI-based software robots in higher education and their ability to revolutionize educational methodologies. The research purpose is to examine the positive impact of the use of software robots in educational settings. The study focuses on evaluating the prospects of expanding the use of AI-based software robots in higher education. The research uses a combination of observational techniques and practical case studies. It includes an experimental investigation of the basic principles of developing an AI-based robot teacher, with the aim of eventually implementing it in educational processes. The research findings indicate that integrating AI-driven software robots into university education can provide substantial benefits and significant improvements over traditional teaching models. These robots can enhance the educational process and address various developmental challenges. The study highlights the transformative impact of AI-based software robots in modernizing university education. The findings demonstrate the potential of these technologies to reshape the current higher education system.</p>2024-02-16T12:53:13+07:00Copyright (c) 2024 Serik Yeslyamovhttps://journal.umy.ac.id/index.php/jrc/article/view/21227Improving the Efficiency of Open Cathode PEM Fuel Cell Through Hydrogen Flow Control Using Wavelet-Clipping2024-03-21T15:54:21+07:00Triyanto Pangaribowotriyanto.pangaribowo@mercubuana.ac.idWahyu Mulyo Utomowahyu@uthm.edu.myAbdul Hamid Budimanabdu031@brin.go.idDeni Shidqi Khaerudinideni.shidqi.khaerudini@brin.go.idAfarulrazi Abu Bakarafarul@uthm.edu.my<p class="Keywords">Open cathode proton exchange membrane fuel cells (OC-PEMFC) are devices that produce electrical energy through an electrochemical reaction between hydrogen and oxygen gas. Rapid load changes often lead to fluctuations in the flow of hydrogen entering the OC-PEMFC system. Increased load directly correlates with higher hydrogen gas consumption. However, if there is a delay in adjusting the gas flow rate to changes in load, it can trigger fluctuations in the amplitude and frequency of the output voltage. This fluctuation ultimately disrupts the stability of the power supply to the load, and reducing efficiency. Therefore, this paper presents a novel hybrid system that integrates wavelet and clipping techniques to regulate a more stable hydrogen flow, enhancing efficiency and accuracy under constant load conditions. A wavelet control system is used to mitigate noise, coupled with amplitude limitation through clipping techniques. This control system is implemented in OC-PEMFC model that is validated with experimental data. The performance analysis of this hybrid system reveals a 1.95 % increase in efficiency and attains high accuracy, as evidenced by a low ISE value of 0.028 during interference.</p>2024-02-16T13:39:19+07:00Copyright (c) 2024 Triyanto Pangaribowo, Wahyu Mulyo Utomo, Abdul Hamid Budiman, Deni Shidqi Khaerudini, Afarulrazi Abu Bakarhttps://journal.umy.ac.id/index.php/jrc/article/view/20711Analysis of Problems and Prospects for Improving Automatic Control Systems of Interconnected Electric Drives2024-03-21T15:54:21+07:00Nurgali Nalibayevnurgalinalibayev@outlook.comBolat Kozhageldikozhageldibolat@gmail.comZhaksylyk Omarovzha_omarov@outlook.comAizhan ZhanpeiissovaA.Zhanpeiissova@hotmail.comMurat Tashimbetovmurat.tashimbetov@hotmail.com<p>The aim of this study was to analyse the problems and prospects for improving automatic control systems of interconnected electric drives. Various methods, including analytical, classification, functional, statistical, and synthesis, were used to provide recommendations for error correction in the design processes of these systems and to detail their functioning. The study revealed the peculiarities and differences of automatic control systems of interconnected electric drives. The study analysed the errors made during the operation of these systems and the reasons for their occurrence. It also identified uncertainties in the development process and their impact on the functioning of the systems. The mechanism's efficiency, development, and complexity in different spheres were analysed. The text also considered issues related to estimating the operation of systems, limitations during operation, and the influence of limitations on results. Recommendations for promoting more effective regulation have been provided. The research showed that these systems play a crucial role in complex technological processes. The results have vague practical implications for developing the mechanism of automatic control systems for interconnected electric drives to apply and influence a certain device. In conclusion, the study analysed the problems and prospects for improving automatic control systems for interconnected electric drives.</p>2024-02-17T13:03:14+07:00Copyright (c) 2024 Nurgali Nalibayev, Bolat Kozhageldi, Zhaksylyk Omarov, Aizhan Zhanpeiissova, Murat Tashimbetovhttps://journal.umy.ac.id/index.php/jrc/article/view/20327Sorting Line Assisted by A Robotic Manipulator and Artificial Vision with Active Safety2024-03-21T15:54:21+07:00María F. Mogromfmogro@espe.edu.ecFausto A. Jácomefajacome1@espe.edu.ecGuillermo M. Cruzgmcruz@espe.edu.ecJonathan R. Zuritajrzurita1@espe.edu.ecThis article presents the design, implementation and evaluation of an object classification and manipulation system in industrial environments by integrating artificial vision and a MELFA RV-2SDB robotic manipulator. The central problem lies in the need to achieve rapid and accurate classification of objects for palletizing, while ensuring the safety of operators. To address this challenge, a machine vision system based on Logitech C920 HD Pro cameras and force and torque sensors was used on the robotic manipulator. The methodology focused on the use of object and person detection algorithms, as well as direct and inverse kinematics to calculate adaptive movements of the manipulator. The experiments covered evaluation of the system's accuracy and efficiency under various lighting and environmental conditions, as well as testing people detection and geometric shape classification. The results indicated that the system allowed precise and efficient manipulation, adapting in real time to the position and characteristics of the detected objects. The conclusions highlighted the effectiveness of the system in improving productivity and safety in collaborative industrial environments, highlighting the importance of integrating cutting-edge technologies to address automation challenges in the industry.2024-02-21T13:34:05+07:00Copyright (c) 2024 María Fernanda Mogro, Fausto Andrés Jácome, Guillermo Mauricio Cruz, Jonathan Raphael Zuritahttps://journal.umy.ac.id/index.php/jrc/article/view/20581Power Management and Voltage Regulation in DC Microgrid with Solar Panels and Battery Storage System2024-03-21T15:54:21+07:00Ashraf Abdualateef Mutlageee.21.10@grad.uotechnology.edu.iqMohammed Kdair Abdmohammed.k.abd@uotechnology.edu.iqSalam Waley Shneensalam_waley73@yahoo.comPhotovoltaics are one of the most important renewable energy sources to meet the increasing demand for energy. This led to the emergence of Microgrid s, which revealed a number of problems, the most important of which is managing and monitoring their operation, this research contributes mainly by using a maximum power tracking algorithm Which depends on artificial neurons and integrating it with a proposed algorithm for energy management in Standalone DC Microgrid, in order to control the distribution of power and maintain the DC bus voltage level. Maximum Power Point Tracking (MPPT) algorithm based on ANN+PID is used. Where ANN tracks the maximum power point by estimating the reference voltage using real-time data such as temperature and solar radiation. The PI controller reduces the error between the measured voltage and the reference voltage and makes the necessary adjustments in order to control the boost converter connected to the photovoltaic panels. While the process of controlling the DC bus voltage level is done by controlling the battery charging and discharging process through the power management algorithm and controlling the Bidirectional converter switches according to the battery’s state of charge. The simulation results obtained by used MATLAB Simulink are shown that the used MPPT algorithm achieved the maximum power with the least amount of fluctuation, the method's efficiency was 99.92%, and its accuracy was 99.85%, as well as the success of the power management algorithm controlling the battery charging/discharging process and maintaining the DC voltage level at the specified value in different operating scenarios.2024-02-22T15:40:54+07:00Copyright (c) 2024 Ashraf Abdualateef Mutlag, Mohammed Kdair Abd, Salam Waley Shneenhttps://journal.umy.ac.id/index.php/jrc/article/view/21208Ophthalmic Diseases Classification Based on YOLOv82024-03-21T15:54:21+07:00Ahmed Tuama Khalafahmed.t.khalaf@st.tu.edu.iqSalwa Khalid Abdulateefkhalid.salwa@tu.edu.iqWith the rising prevalence of retinal diseases, identifying eye diseases at an early stage is crucial for effective treatment and prevention of irreversible blindness. But Ophthalmologists face challenges in detecting subtle symptoms that may indicate the presence of a disease before it progresses to an advanced stage Among these challenges, eye diseases can present with a wide range of symptoms, and some conditions may share similar signs. To solve these difficulties, in the research proposed YOLOV8(You Only Look Once) Lightweight Self-Attention model to classify seven different retinal diseases. In this regard, the dataset that have been used in this study contains 5787 images from three different sources (Roboflow, Kaggle and Medical Clinics) were included in the seven classes of Glaucoma, Age-related Macular Degeneration (AMD), Cataract, Diabetic retinopathy (DR), and Retinal Vein Occlusion, which comprises of Branch Retinal Vein Occlusion (BRVO) and Central Retinal Occlusion (CRVO) and normal. As a results, the model has proven excellent performance in its classification ability. Boasting an average classification accuracy of 94% across the seven disease with precsition 96.2%, recall 96.6%and f1 score was 96.3% At the time of training it was 0.6 Houres(H). When compaired with Resnet50, VGG16 results underscore the model’s superior performance in precision and computational efficiency compared. The algorithm's evaluation reveals its superiority when compared to earlier pertinent research, making it a trustworthy method for classifying retinal illnesses.2024-02-23T11:04:44+07:00Copyright (c) 2024 Ahmed Tuama Khalaf, Salwa Khalid Abdulateefhttps://journal.umy.ac.id/index.php/jrc/article/view/21342Design of PID, IMC and IMC based PID Controller for Hydro Turbine Power System of Non-minimum Phase Dynamics2024-03-21T15:54:21+07:00Supriya Y. Bhuransupriya.bhuran@rait.ac.inSharad P. Jadhavsharad.jadhav@rait.ac.inThe primary objective of this paper is to design and assess the performance of conventional Proportional Integral Derivative (PID), Internal Model Controller (IMC), and IMCbased PID controllers tailored for Hydro Turbine Power Systems (HTPS) exhibiting Non-Minimum Phase (NMP) dynamics. The focus is on overcoming the limitations of existing approaches in handling such complex system dynamics. Existing literature underscores the difficulty of crafting controllers for such systems. The current study represents a sincere endeavour to design and evaluate the performance of conventional Proportional Integral and Derivative (PID), Internal Model Controller (IMC), and IMCbased PID controllers tailored for HTPS characterized by NMP behaviour. The design case study and simulations were conducted using MATLAB and Simulink. The closed-loop responses of HTPS with PID, IMC, and IMC-PID are presented, and the controller performances are scrutinized in both time and frequency domains. To validate the effectiveness of the controllers, performance indices such as Integrated Squared Error (ISE), Integrated Absolute Error (IAE), Integrated Time-weighted Absolute Error (ITAE), Integrated Time Squared Error (ITSE) are calculated, as well as control efforts are calculated using 2-norm and infinity-norms. These performance indices and control effort norms offer a comprehensive evaluation of the controllers’ performance in terms of minimizing error, handling system dynamics, and optimizing control effort across different time scales. Analysing these metrics aids in selecting and refining controllers for optimal performance in HTPS with NMP behaviour. Our findings illustrate that IMCbased PID controllers exhibit superior performance compared to conventional PID controllers in effectively handling the NonMinimum Phase (NMP) dynamics of Hydro Turbine Power Systems (HTPS). This superiority is substantiated by enhanced performance indices, including reductions in ISE, IAE, ITSE, and ITAE.2024-02-25T16:03:50+07:00Copyright (c) 2024 Supriya Yogesh Bhuran, Sharad P. Jadhavhttps://journal.umy.ac.id/index.php/jrc/article/view/21422Enhancing Pulmonary Disease Classification in Diseases: A Comparative Study of CNN and Optimized MobileNet Architectures2024-03-21T15:54:21+07:00Omar Nadhim Mohammedomar.n1dhem@gmail.com<p>Background: Deep learning technologies, especially Convolutional Neural Networks (CNNs), are revolutionizing the field of medical imaging by providing advanced tools for the accurate classification of pulmonary diseases from chest X-ray (CXR) images. In our study, we employed both traditional CNN models and MobileNet architectures to classify various chest diseases using CXR images. Initially, a conventional CNN model was utilized to estab- lish a baseline accuracy. Subsequently, we adopted MobileNet, known for its efficiency in processing image data, to enhance classification performance. To further optimize the system, we applied Energy Valley Optimization (EVO) for hyperparameter tuning. The baseline CNN model achieved an accuracy of 85.91%. The implementation of MobileNet significantly improved this metric, reaching a pre-optimization accuracy of 93.30%. Post-EVO optimization, the accuracy was further enhanced to 94.18%. Comparative analysis of accuracy, precision, recall, F1-score, and ROC curves was conducted to illustrate the impact of hyperparameter tuning on model performance in medical diagnostics. Our findings demonstrate that while standard CNNs provide a solid foundation for CXR image classification, the integration of MobileNet architectures and EVO for hyperparameter adjustment significantly boosts diagnostic accuracy. This advancement in automated medical image analysis could potentially transform the landscape of pulmonary disease diagnosis, offering a more robust framework for accurate and efficient patient care.</p>2024-02-27T11:10:40+07:00Copyright (c) 2024 Omar Nadhim Mohammedhttps://journal.umy.ac.id/index.php/jrc/article/view/21419Optimizing Latent Space Representation for Tourism Insights: A Metaheuristic Approach2024-03-21T15:54:21+07:00Thinzar Aung Winthinzar.w@kkumail.comKhamron Sunatskhamron@kku.ac.th<p class="Abstract">In the modern digital era, social media platforms with travel reviews significantly influence the tourism industry by providing a wealth of information on consumer preferences and behaviors. However, these textual reviews' complex and varied nature poses analytical challenges. This research employs advanced Natural Language Processing (NLP) techniques to process and analyze vast amounts of travel data efficiently, tackling the challenges posed by the diverse and detailed content in the tourism field. We have developed an innovative text clustering methodology that combines BERT's deep linguistic analysis capabilities (Bidirectional Encoder Representations from Transformers) with the thematic organization strengths of LDA (Latent Dirichlet Allocation). This hybrid model, further refined with the dimensionality reduction capabilities of ELM-AE and the optimization precision of PPSO (Phasor Particle Swarm Optimization), yields concise, contextually enriched text representations. Such refined data representations enhance the accuracy of K-means clustering, facilitating nuanced topic identification within the complex domain of travel reviews. This approach streamlines feature extraction and ensures rapid training and minimal loss, underscoring the model's effectiveness in distilling and reconstructing textual features. Our application of this hybrid LDA-BERT model to analyze TripAdvisor reviews of Thailand's shopping destinations reveals meaningful insights, significantly aiding in understanding customer experiences. Despite its contributions, this study acknowledges limitations, including biases in user-generated content and the intricacies of accurately interpreting sentiments and contexts within reviews. This research marks a significant step forward in utilizing NLP for tourism industry analysis, providing a pathway for future investigations to build upon.</p>2024-02-27T12:48:45+07:00Copyright (c) 2024 Thinzar Aung Win, Khamron Sunathttps://journal.umy.ac.id/index.php/jrc/article/view/20900Unveiling the Advancements: YOLOv7 vs YOLOv8 in Pulmonary Carcinoma Detection2024-03-21T15:54:21+07:00Moulieswaran Elavarasuemoulieswaran@gmail.comKalpana Govindarajukalpanag@srmist.edu.in<p>In this work, precision and recall measures are used to assess the performance of YOLOv7 and YOLOv8 models in identifying pulmonary carcinoma on a distinct collection of 700 photos. The necessity of early disease detection is increasing, thus choosing a reliable object detection model is essential. The goal of the research is to determine which model works best for this purpose, taking into account the unique difficulties that pulmonary cancer presents. The work makes a contribution to the field by showcasing the improvements made to YOLOv8 and underlining how well it detects both benign and malignant. YOLOv7 and YOLOv8 were used to independently train custom models using the pulmonary carcinoma dataset. The models' performance was measured using precision, recall, and mean average precision measures, which allowed for a comprehensive comparison examination. When it came to precision (58.2%), recall (61.2%), and mean average precision at both the 0.5:0.95 (33.3%) and 0.5 (53.3%) criteria, YOLOv8 outperformed YOLOv7. The 3.0% accuracy gain highlights YOLOv8's improved capabilities, especially in identifying small objects. YOLOv8's enhanced accuracy can be attributed to the optimisation of the detection process through its anchor-free design. According to this study, YOLOv8 is a more reliable model for pulmonary carcinoma identification than YOLOv7. The results indicate that YOLOv8 is the better option because of its higher recall, precision, and enhanced capacity to detect smaller objects—all of which are critical for early illness detection in medical imaging.</p>2024-02-27T15:59:21+07:00Copyright (c) 2024 Moulieswaran Elavarasu, Kalpana Govindarajuhttps://journal.umy.ac.id/index.php/jrc/article/view/19921Reliable Wireless Sensor Network Planning with Multipath Topology through Relay Placement Optimization2024-03-21T15:54:21+07:00Kasyful Amronkasyful@ub.ac.idWuryansari M Kusumawinahyuwmuharini@ub.ac.idSyaiful Anamsyaiful@ub.ac.idWayan F Mahmudywayanfm@ub.ac.idRecent developments in Wireless Sensor Networks (WSN) focus on scalability and reliability. This research addresses the challenge of improving reliability in WSNs through optimal relay placement and multipath topology design. A heuristic method with a Multi-Objective Optimization (MOO) approach is proposed to solve this problem. The proposed method integrates a modified Genetic Algorithm (GA) with Particle Swarm Optimization (PSO) characteristics. The hybrid approach aims to minimize the number of relays and associated communication costs while maintaining network reliability. The method encodes relay positions and quantities into GA chromosomes that are updated by mutation, crossover, and PSO-inspired particle motion. Simulations are performed in a simplified square area with twenty randomly placed sensors, a hundred and thirty-two arranged relays, and a single sink node. As a result, the simulation generated two multipath topologies that offer unique advantages. The first emphasizes relay efficiency (61 relays, with 2096 costs), while the second ensures lower communication costs (64 relays, 1832 costs). Comparisons with alternative algorithms, including Dijkstra, A-star, GA, and PSO, prove the superiority of the proposed approach. The optimum results obtained with a composition of 95% GA and 5% PSO, outperform alternative algorithms in terms of relay efficiency and communication cost. This research contributes to the field by providing a robust solution for designing reliable multipath WSNs with a minimum number of relays.2024-03-01T16:47:23+07:00Copyright (c) 2024 Kasyful Amron, Wuryansari Muharini Kusumawinahyu, Syaiful Anam, Wayan Firdaus Mahmudyhttps://journal.umy.ac.id/index.php/jrc/article/view/20915The Use of Arduino and PID Control Approach for the Experimental Setup of HVAC Temperature Testing2024-03-21T15:54:21+07:00Vincenzo Ballerinivincenzo.ballerini2@unibo.itCesare Bisernicesare.biserni@unibo.itGiampietro Fabbrigiampietro.fabbri@unibo.itPaolo Guidorzipaolo.guidorzi@unibo.itEugenia Rossi di Schioeugenia.rossidischio@unibo.itPaolo Valdiserripaolo.valdiserri@unibo.itThe experimental setup of HVAC testing requires easy but accurate instrumentation, and recent analyses focus on the control based on the mean radiant temperature in order to better perform respect to the users satisfaction. Indeed, the research contribution of this work is the use of Arduino to develop a PID control for an electric heater. As a main feature, this control system can operate by maintaining the set-point on the air temperature or on the mean radiant temperature of the environment where it is placed. The paper describes the design and development of the PID control, as well as the testing of the control system applied to an electric heater, to heat a room in a laboratory in Bologna (Italy). In an Appendix the Matlab script employed to store data on the local pc an to send data to Google Sheets is reported, together with the Google script code employed to write the data from Matlab to the online sheet. As result, the developed PID is accurate in maintaining the required set-point temperature, with minimal deviations from the set-point, in the interval ± 0.2 K.2024-03-01T17:41:52+07:00Copyright (c) 2024 Vincenzo Ballerini, Cesare Biserni, Giampietro Fabbri, Paolo Guidorzi, Eugenia Rossi di Schio, Paolo Valdiserrihttps://journal.umy.ac.id/index.php/jrc/article/view/20722Robust Adaptive Trajectory Tracking Sliding Mode Control for Industrial Robot Manipulator using Fuzzy Neural Network2024-03-21T15:54:21+07:00Quynh Nguyen Xuanquynhnx@haui.edu.vnCuong Nguyen Congnguyencongcuong@haui.edu.vnNghien Nguyen Banguyenbanghien_cntt@haui.edu.vnThis paper presents a control method for a two-link industrial robot manipulator system that uses Fuzzy Neural Networks (FNNs) based on Sliding Mode Control (SMC) to investigate joint position control for periodic motion and predefined trajectory tracking control. The proposed control scheme addresses the challenges of designing a suitable control system that can achieve the required approximation errors while ensuring the stability and robustness of the control system in the face of joint friction forces, parameter variations, and external disturbances. The control scheme uses four layers of FNNs to approximate nonlinear robot dynamics and remove chattering control efforts in the SMC system. The adaptive turning algorithms of network parameters are derived using a projection algorithm and the Lyapunov stability theorem. The proposed control scheme guarantees global stability and robustness of the control system, and position is proven. Simulation and experiment results from a two-link IRM in an electric power substation are presented in comparison to PID and AF control to demonstrate the superior tracking precision and robustness of the proposed intelligent control scheme.2024-03-05T12:58:59+07:00Copyright (c) 2024 Quynh Nguyen Xuan, Cuong Nguyen Conghttps://journal.umy.ac.id/index.php/jrc/article/view/20496Enhancement of Underwater Video through Adaptive Fuzzy Weight Evaluation2024-03-21T15:54:22+07:00Jitendra Sonawanejitendra.sonawane@rait.ac.inMukesh Patilmukesh.patil@rait.ac.inGajanan K Birajdargajanan.birajdar@rait.ac.inUnderwater video enhancement plays a critical role in improving the visibility and quality of underwater imagery, which is essential for various applications such as marine biology, underwater archaeology, and offshore inspection. In this article, we present a novel approach for enhancing underwater videos. Our method employs fuzzy logic and a unique fuzzy channel weight coefficient to effectively address challenges in underwater imaging. The method aims to improve the perceptual quality of underwater videos by enhancing contrast, reducing noise, and increasing overall image clarity. The key component in our approach is the integration of fuzzy logic based channel weight coefficient which is adaptively selected to enhance the video frames. The fuzzy channel weight coefficient-based method assigns weights to different color channels in a manner that optimally addresses the underwater imaging conditions. To evaluate the performance of our fuzzy enhancement algorithm, we conducted experiments on the Fish4Knowledge database, a widely used benchmark dataset for underwater video analysis. We quantitatively assessed the improvement in video quality using various metrics, including Peak Signal-to-Noise Ratio (PSNR), Root Mean Square Error (RMSE), Structural Similarity Index (SSIM), and entropy. Our results demonstrate that the proposed fuzzy logic-based enhancement method outperforms existing techniques in terms of video quality enhancement and underwater image correction in terms of PSNR, RMSE and SSIM.2024-03-07T13:01:43+07:00Copyright (c) 2024 Jitendra Sonawane, Mukesh Patil, Gajanan K Birajdarhttps://journal.umy.ac.id/index.php/jrc/article/view/21101Design and Analysis of IO and FO Controllers to Investigate the Effects of Process Parameter Perturbations on Lag-Dominant Time Delay Systems2024-03-21T15:54:22+07:00Diptee Patildiptee.patil@rait.ac.inSharad Jadhavsharad.jadhav@rait.ac.in<p>This paper focuses on the design, analysis and implementation of Integer-order (IO) and Fractional-order (FO) controllers for systems characterized by lag-dominant time delays. The existing literature has been examined to analyze the methodology employed in tuning IO and FO controllers for first-order time delay system for perturbations in process parameters. It is observed that there is scope to investigate better controllers for lag-dominant time delay systems. The five different structures of controllers are chosen. The paper proposes IO and FO controllers tailored for a test group comprising 16 first-order systems with time delays. These IO and FO controllers are designed to fulfil design specifications: phase margin, peak overshoot, IAE, ITAE and ISE using Modified Bode’s Ideal Loop Transfer Function with delay method. For comparison conventional IO tuning method, Gain-Phase Margin Tester (GPMT) and Fractional Ms Constrained Integral Gain Optimization Method (F-MIGO) is used. The simulation results and performance evaluation for both IO and FO controllers are obtained for a range of values of relative dead time of the system represented by τ. The τ value is obtained by varying conditions of delay (L) and time constant (T). Two scenarios are taken into account: the first involves varying L while keeping T constant, and the second involves keeping L constant while varying T. The main objective of the paper is to analyze IO and FO controllers based on time and frequency domain parameters, performance error indices, disturbance rejection, gain variations, Total Variation (TV) and control efforts for perturbations in process parameters. The simulation results indicate that FO controllers show superior tolerance to perturbations in L and T when compared to IO counterparts. This observation was noted during the analysis of the control system by varying values of L and T to obtain a consistent value of τ . Thus, the extensive simulation studies demonstrate that the FO controller tailored for lag-dominant time delay systems outperforms its IO counterpart in terms of robustness, closed-loop stability and error performance metrics.</p>2024-03-09T12:24:52+07:00Copyright (c) 2024 Diptee Subhash Patil, Sharad P. Jadhavhttps://journal.umy.ac.id/index.php/jrc/article/view/20441AI-based Bubbles Detection in the Conformal Coating for Enhanced Quality Control in Electronics Manufacturing2024-03-21T15:54:22+07:00Nizar Zouhrinizar.zouhri@etu.uae.ac.maAimad El Mourabitaelmourabit@uae.ac.maAlaoui Ismaili Zine El Abidinez.alaoui@um5s.net.ma<p>This research pioneers the application of artificial intelligence (AI) methodologies—machine learning, deep learning, hybrid models, transfer learning, and edge AI deployment—in enhancing bubble detection within conformal coatings, a critical as- pect of electronics manufacturing quality control. By addressing the limitations of traditional detection methods, our work offers a novel approach that significantly improves automation, accuracy, and speed, thereby ensuring the reliability of electronic assemblies and contributing to economic and safety benefits. We navigate through the challenges of creating diverse datasets, system robustness, and the imperative for industry-wide standardization, proposing strategies for overcoming these obstacles. Our findings highlight the transformative impact of AI on quality control processes, demonstrating substantial advancements in detection capabilities. Furthermore, we advocate for future research, development, and collaboration to extend these AI-driven improvements across the manufacturing spectrum. This study underscores the potential of AI to revolutionize electronics manufacturing, emphasizing the need for continued innovation and standardization to realize safer, more efficient, and cost-effective production methodologies.</p>2024-03-12T15:49:19+07:00Copyright (c) 2024 Nizar Zouhri, Aimad El Mourabit, Alaoui Ismaili Zine El Abidinehttps://journal.umy.ac.id/index.php/jrc/article/view/21613Model Predictive Control in Hardware in the Loop Simulation for the OnBoard Attitude Determination Control System2024-03-21T15:54:22+07:00Herma Yudhi Irwantoherm007@brin.go.idPurnomo Yusgiantoropurnomoys@idu.ac.idZainal Abidin Sahabuddinzainal.sahabuddin@idu.ac.idRomie O. Buraromiebura@idu.ac.idEndro Artonoendr004@brin.go.idArif Nur Hakimarif014@brin.go.idRatno Nuryadiratn005@brin.go.idRika Andiartirika001@brin.go.idLilis Marianilili007@brin.go.idRocket flight tests invariably serve a purpose, one of which involves area monitoring or aerial photography. Consequently, the rocket necessitates the installation of a camera that remains consistently oriented toward the Earth's surface throughout its trajectory. Thus, ensuring the rocket's stability and preventing any rotation becomes imperative. To achieve this, the Onboard Attitude Determination Control System (OADCS) was researched and developed, fully controlled by NI myRIO with Labview as the programming language, ensures the rocket's attitude control and maintains a rolling angle of 0 degrees during flight. The MyRIO oversees the retrieval of attitude and position data from the X-Plane flight simulator, offering feedback through actuator control. The development of the OADCS proceeded incrementally through stages utilizing the Software in the Loop Simulation (SILS) and Hardware in the Loop Simulation (HILS) techniques, to ensure the verification of the system's functionality before its application to the rocket for real flight testing. In the OADCS control scheme, Model Predictive Control (MPC) is chosen, and it is compared with a PID controller to serve as a benchmark for processing speed. Because the rocket's flight time is short and its speeds of up to Mach 4. The simulation results indicate that MPC can halt the rocket's rotation 12 times more rapidly than PID control. Additionally, the MPC's ability to maintain a zero-degree rotation can persist throughout the rocket's flight time. Employing SILS and HILS enhances the OADCS rocket development process by incorporating MPC, which holds promise for application in real rockets.2024-03-14T11:50:57+07:00Copyright (c) 2024 Herma Yudhi Irwanto, Purnomo Yusgiantoro, Zainal Abidin Sahabuddin, Romie O. Bura, Endro Artono, Arif Nur Hakim, Ratno Nuryadi, Rika Andiarti, Lilis Marianihttps://journal.umy.ac.id/index.php/jrc/article/view/20474Solvability and Weak Controllability of Fractional Degenerate Singular Problem2024-03-21T15:54:22+07:00Achab Fatmaachabfatma2019@gmail.comIqbal Batihai.batiha@zuj.edu.joRezzoug Imadimad.rezzoug@univ-oeb.dzOussaeif Takieddinetaki_maths@live.frAdel Ouannasdr.ouannas@gmail.com<p>In this paper, our objective is to investigate the unique solvability and the weak controllability of the fractional degenerate and singular problem. The energy inequality method is gives a sufficient conditions for the existence and the uniqueness of the strong solution of our problem. This problem is ill-posed in the sense of Hadamard. To address this, we attempt regularization through a fractional Tikhonov regularization method, which not only establishes weak controllability but also provides a full characterization of the optimal control.</p>2024-03-16T13:34:22+07:00Copyright (c) 2024 Achab Fatma, Iqbal Batiha, Rezzoug Imad, Oussaeif Takieddine, Adel Ouannashttps://journal.umy.ac.id/index.php/jrc/article/view/21145Road Object Detection using SSD-MobileNet Algorithm: Case Study for Real-Time ADAS Applications2024-03-21T15:54:22+07:00Omar Bouaziziomar.bouazizi@etu.uae.ac.maChaimae Azroumahlic.azroumahli@emsi.maAimad El Mourabitaelmourabit@uae.ac.maMustapha Oussouaddimustapha.oussouaddi@etu.uae.ac.maObject detection has played a crucial role in Advanced Driver Assistance Systems (ADAS) applications, particularly with integrating deep learning techniques. These advancements have improved ADAS applications by enabling more precise object identification, thereby enhancing real-time decision-making. Object detection models can be categorized into two main groups: two-stage and one-stage models. While prior studies reveal that one-stage detectors generally achieve higher frames per second (FPS) at the expense of some accuracy, they remain better suited for real-time ADAS applications. Our study aims to analyze the performance of an object detection model created using SSD-MobileNet, a one-stage detector approach. We focused on identifying road-related objects such as vehicles, and traffic signs. The contribution of our work lies in developing an object detection model using a pre-trained SSD-MobileNet and employing transfer learning. This process involves introducing a new fully connected layer tailored for the specific identification of objects in road scenes. The retraining of the SSD-MobileNet model is executed through GPU-accelerated transfer learning on the MS COCO dataset, incorporating appropriate pre-processing to exclusively include road-related objects. Our findings indicate promising results for the retrained SSD-MobileNet model, achieving an F1 score of 0.801, and a Mean Average Precision (mAP) of 65.41 at 71 FPS. A comparative analysis with other one-stage and two-stage detectors demonstrates the model's performance, surpassing some existing works in the literature related to road object detection. Notably, our model exhibits improved mAP while maintaining a higher FPS, rendering it more apt for ADAS applications.2024-03-18T12:59:42+07:00Copyright (c) 2024 Omar Bouazizi, Chaimae Azroumahli, Aimad El Mourabit, Mustapha Oussouaddihttps://journal.umy.ac.id/index.php/jrc/article/view/20589Ovarian Tumors Detection and Classification on Ultrasound Images Using One-stage Convolutional Neural Networks2024-03-22T05:24:57+07:00Van-Hung Levan-hung.le@mica.edu.vnThi-Loan Phamphamthiloan2011@gmail.comCurrently, the advent of CNN (Convolutional Neural Network) has brought very convincing results to computer vision problems. One-stage CNNs are a suitable choice for research and development to have an overview of the current results of the process of detecting and classifying OTUM from ovarian ultrasound images. In this paper, we have performed a comprehensive study on one-stage CNNs for the problem of detecting and classifying OTUM on ovarian ultrasound images. The OTUM datasets we tested were two popular OTUM datasets: OTU and USOVA3D. The one-stage CNNs we tested and evaluated belong to the YOLO (You Only Look Once) family (YOLOv5, YOLOv7, YOLOv8 variations, and YOLO-NAS), and the SSD (Single Shot MultiBox Detector) family (VGG16-SSD, Mb1-SSD, Mb1-SSDLite, Sq-SSD-Lite, and Mb2-SSD-Lite). The results of detecting OTUM (with or without OTUM on ovarian ultrasound images) are high (with Mb1-SSD of Acc = 98.90%, P = 98.58%, R = 98.9% on “USOVA3D 2D f r1 80 20” set; with Mb2-SSD-Lite of Acc = 97.87%, P = 97.16%, R = 97.87% on “USOVA3D 2D f r2 80 20” set). The results of detecting and classifying OTUM into 8 classes are low (the highest is Acc = 92.04%, P = 74.81%, R = 92.04% on the OTU-2D dataset). Regarding computation time, CNNs of the YOLO family have faster computation times than networks of the SSD family. The above results show that the problem of classifying ovarian tumors on ultrasound images still contains many challenges that need to be resolved in the future.2024-03-19T15:05:36+07:00Copyright (c) 2024 Van-Hung Le, Thi-Loan Phamhttps://journal.umy.ac.id/index.php/jrc/article/view/21540Adaptive Vector Field Histogram Plus (VFH+) Algorithm using Fuzzy Logic in Motion Planning for Quadcopter2024-03-21T15:54:22+07:00Khitam Mohammedengpg.khitam.mohamed@uobasrah.edu.iqAli Aliedaniali.nabeel@uobasrah.edu.iqAlaa Al-Ibadialaa.abdulhassan@uobasrah.edu.iqThis work introduces the adaptive version of the vector field histogram plus (VFH+) motion planning algorithm, which is designed for unmanned aerial vehicles, particularly quadcopters, to enhance its performance in navigation tasks. The method suggests incorporating fuzzy control to adaptively modify the VFH+ look-ahead distance parameter by analysis continuous environmental and motion conditions. Simulation tests were completed using different scenarios that varied in obstacle quantity, density, distribution, and size and waypoint quantity. Simulation results showed the successful outcomes of this strategy in enhancing quadcopter motion performance in various contexts. The results indicated notable enhancements in obstacle avoidance, smoother motion trajectories, and decreased travel time compared to the traditional VFH+ method. One of the most important aspects of creating real-time motion planning systems is handling uncertainty. This is accomplished by incorporating a fuzzy system knowledge base for automatic algorithmic modification into the planning process and employing advanced motion-planning techniques. The adaptive algorithm improves the quadcopter's ability to deal with high uncertainty levels by incorporating fuzzy logic for dynamic parameter adjustment, allowing for accurate and efficient navigation in various environments, even in uncertain conditions.2024-03-19T16:09:08+07:00Copyright (c) 2024 Khitam Mohammed, Ali Aliedani, Alaa Al-Ibadihttps://journal.umy.ac.id/index.php/jrc/article/view/21541A Systematic Literature Review of Performance Hospital Supply Chain Management2024-03-21T15:54:22+07:00Soulaiman Louahsoulaiman.louah@etu.uae.ac.maHicham Sarirhsarrir@uae.ac.maMohamed Kriouichmohamed.kriouich@etu.uae.ac.maOver the last few decades, globalization has driven up the demand for hospital Supply Chain Management (SCM) with the goal of bio-medical development and improving performance. This review aims to offer both a qualitative and quantitative comprehension of the hospital SCM re-search field's overall developmental trend. By using the methodology science mapping approach are visualize the organization of academic knowledge, 87 significant papers, that were published between 2002 and 2023 in total due to their importance in recent years, were located, expanded upon, and summarized. Bibliographic analysis for under-standing the global research state and academic develop-ment was performed on visualized statistics can help identi-fy trends in data about co-occurring keywords, interna-tional cooperation, journal allocation/co-citation, and view clusters of study subjects based on this five categorization, 22 sub-branches in total of hospital SCM identification and topical discussion of knowledge were conducted, namely (i) technologies; (ii) planning; (iii) supply chain field in hospi-tals; (iv) logistics and (v) environmental. Lastly, suggestions for future study directions and current knowledge gaps were made due to constraints of international cooperation and insufficient platforms to quickly advance innovation technology research. The results contribute to a methodical intellectual representation of the current state of hospital SCM research. Furthermore, it offers heuristic ideas to practitioners and researchers to control the quality of de-veloped healthcare and logistics services.2024-03-21T15:36:23+07:00Copyright (c) 2024 Soulaiman Louah, Hicham Sarir, Mohamed Kriouich