1 10 24 https://repository.horizon.ac.id/files/original/ebaeea563559553e054a01bb91410f35.pdf 1c4eb6f4d835bb874921f83a0a165fe3 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.3 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Sclera boundary localization using circular hough transform and a modified run-data based algorithm Subject The topic of the resource Biometrics Circular hough transfrom Compound local binary pattern Modified run-data algorithm Sclera boundary localization Description An account of the resource Security challenges over the years has led to the need for an improvement in the traditional security approaches. This led to the advent of biometrics. Recently, among the biometric approaches, sclera has been an area of imense study. This is due to its accuracy; however, segmentation of the sclera has been a limiting factor to the application of this biometric trait. Several approaches have been proposed in literature but there is still the need to improve the segmentation accuracy. This study proposes the use of circular hough transform and a modified run-data based algorithm. The study also presented a sclera recognition system using the compound local binary pattern for features extraction and Manhattan distance for classification. The system produced a segmentation accuracy of 99.9% for sclera blood vessels, periocular and iris (SBVPI) sclera database and 100% for manually captured sclera database. The system produced an accuracy of 99.98 for SBVPI sclera database and 99.99% for manually captured sclera database. Creator An entity primarily responsible for making the resource Tunde Taiwo Adeniyi1, Oladele Tinuke Omolewa1, Jide Kehinde Adeniyi2 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Feb 13, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Biometrics Circular hough transfrom Compound local binary pattern Modified run-data algorithm Sclera boundary localization https://repository.horizon.ac.id/files/original/8b91b88044506cc39180215f1c10c702.pdf ce091e7f03cfebd0f0ba6c15fa7cb4ea Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.3 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Igniting transistor to control three-phase alternating current motor servo Subject The topic of the resource Controlled Igniting Position Rate Torque Description An account of the resource The background of research try to use an open loop system, without feedback, by building torque in the target position. Theoretical basis manages the turning round of servo motor change direct currents to alternating currents by adjusting the rate input used. Methodology in simple terms, the flowchart of code processing from igniting transistors to managing the turning round of a three-phase alternating current (AC) servo motor. The result of the transistor ignition time with room phasor pulse width modulation (PWM) to set the ignition of a three-phase AC servo motor in the process of igniting as ordered, for manage position only igniting transistors in target position, and building torque at there. Discussion, igniting transistors to manage the turning round of servo motors, allows motion of servo motor, allows motion of servo motor to be added faster, accurately, soft, and steady. In conclusion, in this case the researcher uses it more specifically by turning on the transistor only at the target position, so that the torque generated is only at the target position, the servo motor motion from the start position immediately ends at the target position. Suggestions, this system igniting can be applied at a motion high-velocity system like a missile system controlled. Creator An entity primarily responsible for making the resource Syafruddin Rustam1, Andrew Ghea Mahardika2, Givy Devira Ramady1, Arif Rakhman3, Rahmad Hidayat1, Muchamad Sobri Sungkar3 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Feb 2, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Controlled Igniting Position Rate Torque https://repository.horizon.ac.id/files/original/9ca25b0e4ec739efb1581144a6453013.pdf 4dd83338be53fff73eb91b207345cbf3 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.3 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A survey on the dataset, techniques, and evaluation metric used for abstractive text summarization Subject The topic of the resource Abstractive summarization Attention mechanism Automatic text summarization Deep learning Extractive summarization Transformers Description An account of the resource Whenever there is too much information out there, it is desirable to summarize. If humans are trying to create the summary, it will take lot of time. Now to make the problem of summarizing information easier and more effortless one can automate the summarization process which can reduce the time taken in creating summary. This is called as automatic summarization. The two ways of summarization are extractive summarization and abstractive summarization. Extractive summarization and its applications have been the subject of extensive research and have received state of art solution. But abstractive summarization still is a progressive field as it is difficult to create abstractive summary as humans do. Also, it is still a question i.e., how to evaluate the quality of a summary? Therefore, this paper is a comprehensive survey on the dataset used with its details and statistics, analysis of various abstractive summarization techniques and important parameters for evaluating the quality of summary. Deep leaning based models have given new direction in this field. The author also focuses on problems and challenges faced in the generation of summary which are opening the future research scope in this domain. Creator An entity primarily responsible for making the resource Shivani Sharma1, Gaurav Aggarwal1, Bipin Kumar Rai2 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Feb 8, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Abstractive summarization Attention mechanism Automatic text summarization Deep learning Extractive summarization Transformers https://repository.horizon.ac.id/files/original/e2fdf36779a4d8edc98ff3ec75773ebf.pdf e673fc6f831e3ecd1a335f9caac2342c Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.3 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Consistency, local stability, and approximation of Shapash explanation Subject The topic of the resource Explainable artificial intelligence Interpretable artificial intelligence Interpretable machine learning Model explanation Predictive analytics Description An account of the resource Consistency, scalability, and local stability properties ensure that a model or method produces reliable and predictable outcomes. The Shapash helps users understand how the model makes its decisions. With machine learning (ML) system, healthcare experts can identify individuals at higher risk and implement interventions to reduce the occurrence and severity of disease. ML had achieved higher prediction accuracy even though the accuracy of their prediction depends on the quality and quantity of the data used for training. Despite the wider application and higher accuracy of different ML for disease prediction, the explanation of their predictive outcome is much more important to the healthcare professional, the patient, and even their developers. However, most of the ML systems do not explain their outcomes. To address the explainability issue various techniques such as local model agnostic explanation (LIME), and shapley additive explanation (SHAP) have been proposed over the recent years. Furthermore, the consistency, local stability, and approximation of the explanation remained one of the research topics in ML. This study investigated the consistency, stability, and approximation of LIME and SHAP in predicting heart disease (HD). The result suggested that LIME and SHAP generated a similar explanation (distance=0.35), compared to the active coalition of variable (ACV) explanation (distance=0.43). Creator An entity primarily responsible for making the resource Tsehay Admassu Assegie1, Bommy Manivannan2, Komal Kumar Napa3, Bindu Kolappa Pillai Vijayammal4, Rajkumar Govindarajan3, Sangeetha Murugan2, Atinkut Molla Mekonnen5 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Feb 2, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Explainable artificial intelligence Interpretable artificial intelligence Interpretable machine learning Model explanation Predictive analytics https://repository.horizon.ac.id/files/original/d74d29ece7f191f772c5f1d0ff9b2540.pdf 91cd9d7d05c657e88ba5253102f14e14 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.3 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Incorporating rivest-shamir-adleman algorithm and advanced encryption standard in payment gateway system Subject The topic of the resource Advanced encryption standard Agile methodology Credit cards Payment gateway system Rivest-shamir-adleman algorithm Description An account of the resource The rapid development of technology has led to various advancements, including the ability to conduct online payments through applications. Companies providing digital transaction payment services require a payment gateway system as an intermediary for online transactions. The system acts as an intermediary between merchants with digital wallets and banks, involving the company, merchants, and banks in its development. The system includes essential features like bill payment, user credit card verification, and transaction checking, customized to meet the specific requirements of merchants and adhere to security standards. In this study, we incorporated the rivest-shamir-adleman (RSA) algorithm and advanced encryption standard (AES) to ensure the security of a payment gateway system. We adopt the agile methodology in the development process of the system. We test the acceptance of the system to the user, and we also test the performance of the system. The results of this research show that the system can be accepted by the user, fulfill the user's needs, can be executed well, and performs adequately in handling multiple transactions concurrently. The outcome of this study can serve as valuable input for the company in building its own system, providing insights into algorithm implementation techniques and the system workflow. Creator An entity primarily responsible for making the resource Veronica1, Raymond Sunardi Oetama1, Arief Ramadhan2 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Mar 5, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Advanced encryption standard Agile methodology Credit cards Payment gateway system Rivest-shamir-adleman algorithm https://repository.horizon.ac.id/files/original/6b92a501b659261f901dbe6ff17f5f0e.pdf 594619dd4c53033f6a855ac6f55d7f86 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.3 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Advancements in wind farm layout optimization: a comprehensive review of artificial intelligence approaches Subject The topic of the resource Artificial-intelligence Metaheuristic algorithms Optimal placement Renewable energy Review Wind farm Wind turbines Description An account of the resource This article provides a detailed evaluation of cutting-edge artificial intelligence (AI) approaches and metaheuristic algorithms for optimizing wind turbine location inside wind farms. The growing need for renewable energy sources has fueled an increase in research towards efficient and sustainable wind farm designs. To address this challenge, various AI techniques, including genetic algorithms (GA), particle swarm optimization (PSO), simulated annealing, artificial neural networks (ANNs), convolutional neural networks (CNNs), and reinforcement learning, have been explored in combination with metaheuristic algorithms. The goal is to discover optimal sites for turbine placement based on a variety of parameters such as energy output, cost-effectiveness, environmental impact, and geographical restrictions. The paper examines the advantages and disadvantages of each strategy and highlights current breakthroughs in the area. This assessment adds to continuing efforts to optimize wind farm design and promote the use of clean and sustainable energy sources by offering significant insights into current advances. Creator An entity primarily responsible for making the resource Mariam El Jaadi1, Touria Haidi1, Abdelaziz Belfqih2 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Artificial-intelligence Metaheuristic algorithms Optimal placement Renewable energy Review Wind farm Wind turbines https://repository.horizon.ac.id/files/original/3a7aafeb52a50030844121b40a3c82f9.pdf 99d4954fc225abc9a2f7ecd9f8e71b81 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.3 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Advancements in accurate speech emotion recognition through the integration of CNN-AM model Subject The topic of the resource Attention mechanism Convolution neural network Emotion Recognition Signal Speech Description An account of the resource In this study, we introduce an innovative approach that combines convolutional neural networks (CNN) with an attention mechanism (AM) to achieve precise emotion detection from speech data within the context of e-learning. Our primary objective is to leverage the strengths of deep learning through CNN and harness the focus-enhancing abilities of attention mechanisms. This fusion enables our model to pinpoint crucial features within the speech signal, significantly enhancing emotion classification performance. Our experimental results validate the efficacy of our approach, with the model achieving an impressive 90% accuracy rate in emotion recognition. In conclusion, our research introduces a cutting-edge method for emotion detection by synergizing CNN and an AM, with the potential to revolutionize various sectors. Creator An entity primarily responsible for making the resource Marion Olubunmi Adebiyi1, Timothy T Adeliyi2 , Deborah Olaniyan1, Julius Olaniyan1 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Feb 21, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Attention mechanism Convolution neural network Emotion Recognition Signal Speech https://repository.horizon.ac.id/files/original/e9e301b0dc00fc6a36d13910703be9cc.pdf fdf43669d0d1b77f5b0a67a4712066bf Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.3 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Peak current control of grid-feeding inverter with low voltage ride-through capability Subject The topic of the resource Grid-connected mode Grid-feeding inverter Low-voltage ride-through Peak current control Voltage sag Description An account of the resource The grid-feeding inverter is the most popular choice for implementing a distributed generator (DG) in a photovoltaic (PV) system. Its role is to deliver active power with zero reactive power while connected to the grid. In most cases, the inverter is disconnected as soon as voltage sag disturbances occur, an operation that is known as an islanding mode. Recently, grid code regulations have been upgraded, allowing the inverter to remain connected to the grid and inject a certain amount of reactive power during voltage sags, provided that it meets grid code requirements. However, this can result in an increase in current injection by the inverter, which may cause overcurrent and damage the inverter if it exceeds the capability of the inverter. To control peak current during voltage sag disturbances, a proposed grid-feeding inverter attempts to detect voltage sag and calculate proportional injected active and reactive power. Once the disturbance has disappeared from the system, the inverters can be restored to normal operation. Prototype experiments have validated the ability of this system to control peak current during voltage sag while protecting the inverters. Creator An entity primarily responsible for making the resource Sepannur Bandri, Zuriman Anthony, Erhaneli, Fauzan Ismail Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Feb 27, 20224 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Grid-connected mode Grid-feeding inverter Low-voltage ride-through Peak current control Voltage sag https://repository.horizon.ac.id/files/original/d4d25ad5303e57ce09ab94c3fd8ad55d.pdf 42918caea269cecb09c58d3825019aad Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.3 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Metamaterial inspired circular antenna for Bluetooth band integration Subject The topic of the resource Bluetooth frequency band Circular antenna design Computer simulation technology Metamaterials Wireless communication Technologies Description An account of the resource Within the rapidly evolving landscape of wireless communication technologies, this scientific paper delves into an innovative approach by exploring the integration of the Bluetooth frequency band into a circular antenna design. Leveraging the capabilities of metamaterials. The Bluetooth frequency band a cornerstone for short-range communications, takes center stage in our study. Traditionally associated with wireless connectivity in diverse applications, its integration into a circular antenna structure opens up new avenues for optimizing performance and functionality. Our research aims to not only enhance the efficiency of short-range communication systems but also contribute to the broader discourse on antenna design evolution. The computer simulation technology (CST) studio suite is utilized to show the recommended antenna design. By scrutinizing the symbiotic relationship between the Bluetooth frequency band and the circular antenna augmented with metamaterial, our study endeavors to push the boundaries of current design paradigms. We believe that this exploration will not only address the contemporary challenges associated with wireless communication but also pave the way for the development of more sophisticated, adaptable, and compact devices in the ever-expanding realm of telecommunications. Creator An entity primarily responsible for making the resource Ismail Moumen1, Mourad Elhabchi2, Mohamed Nabil Srifi3, Raja Touahni1 Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Jan 19, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Bluetooth frequency band Circular antenna design Computer simulation technology Metamaterials Wireless communication Technologies https://repository.horizon.ac.id/files/original/57589553024f0fe681f97a27c34906f2.pdf ab98fdc16e3e385341b7981f274b55c4 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 22, NO.3 2024 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Optimized multi correlation-based feature selection in software defect prediction Subject The topic of the resource Correlation-based Feature selection High dimensional Noisy attribute Software defect Description An account of the resource In software defect prediction, noisy attributes and high-dimensional data remain to be a critical challenge. This paper introduces a novel approach known as multi correlation-based feature selection (MCFS), which seeks to address these challenges. MCFS integrates two feature selection techniques, namely correlation-based feature selection (CFS) and correlation matrix-based feature selection (CMFS), intending to reduce data dimensionality and eliminate noisy attributes. To accomplish this, CFS and CMFS are applied independently to filter the datasets, and a weighted average of their outcomes is computed to determine the optimal feature selection. This approach not only reduces data dimensionality but also mitigates the impact of noisy attributes. To further enhance predictive performance, this paper leverages the particle swarm optimization (PSO) algorithm as a feature selection mechanism, specifically targeting improvements in the area under the curve (AUC). The evaluation of the proposed method is conducted on 12 benchmark datasets sourced from the NASA metrics data program (MDP) corpus, renowned for their noisy attributes, high dimensionality, and imbalanced class records. The research findings demonstrate that MCFS outperforms CFS and CMFS, yielding an average AUC value of 0.891, thereby emphasizing it is efficacy in advancing classification performance in the context of software defect prediction using k-nearest neighbors (KNN) classification. Creator An entity primarily responsible for making the resource Muhammad Nabil Muyassar Rahman, Radityo Adi Nugroho, Mohammad Reza Faisal, Friska Abadi, Rudy Herteno Source A related resource from which the described resource is derived Journal homepage: http://telkomnika.uad.ac.id Date A point or period of time associated with an event in the lifecycle of the resource Jan 19, 2024 Contributor An entity responsible for making contributions to the resource PERI IRAWAN Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource ENGLISH Type The nature or genre of the resource TEXT Correlation-based Feature selection High dimensional Noisy attribute Software defect