2 10 24 https://repository.horizon.ac.id/files/original/3cb8428af5b5af6a698857e14227c030.pdf 4b14b6fc128e4e4e1a4bbb88f67a0c76 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 Tungsten disulfide based wearable antenna in terahertz band for sixth generation applications Subject The topic of the resource 6G antenna 2D materials Wearable electronics Micro-strip patch antenna Tungsten disulfide Description An account of the resource Wireless communication networks could become quicker and more dependable as sixth generation (6G) antennas develop. One difficult development in the field of wearable technology is wearable textile antennas. Wearable textile antennas require flexible building materials, primarily textiles with planar structures. This study will concentrate on the design and specification of microstrip rectangular patch antennas that use a variety of fabrics as the substrate, such as lycra, polyester, and washed cotton. Using two-dimensional (2D) materials in the terahertz (THz) range, the study presented here will help in the construction of appropriate wearable antennas. This work may significantly improve materials science and engineering by investigating and using 2D materials, such as tungsten disulfide, in antenna design. The suggested antennas’ resonance frequencies are 1.1254 THz for polyester substrates, 4.4019 THz for washed cotton, and 2.9861 THz for lycra substrates. For substrate materials such as lycra, polyester, and washed cotton, the measured return loss was -44.92 dB, -38.17 dB, and -20.75 dB. This study could lead to the creation of new technologies and materials, such tungsten disulfide, which would have far-reaching uses outside of wearable electronics and provide significant advantages for society. Creator An entity primarily responsible for making the resource Avijit Roy, Md. Razim Bhuiyan, Md. Ariful Islam, Pahil Saha, Sumit Hassan Eshan, Raja Rashidul Hasan, Rinku Basak 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 1, 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 6G antenna 2D materials Wearable electronics Micro-strip patch antenna Tungsten disulfide https://repository.horizon.ac.id/files/original/c71d6a74cce9c6d882879bf618bbe3c8.pdf 115d01d3daf68d15534467089f62df56 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 Adaptive handover control parameters based on cell load capacity in a B5G/6G heterogeneous network Subject The topic of the resource Adaptive handover parameters B5G/6G Environmental constraints Handover decision Throughput Description An account of the resource In the B5G/6G network, the deployment of small cells increased to keep up with the growth of mobile traffic. This deployment will increase the number of handovers (HOs) between cells. Ping-pong handover (PPHO) and radio link failure (RLF) are considered the two major problems in HO that may occur. So, the challenge is to set the handover control parameters (HCPs) carefully to find out the proper HO decision that should be appropriate to the environmental constraints. Therefore, in our paper, we propose an adaptive HCPs algorithm that adapts to environmental constraints. In addition, the proposed algorithm will have immunity to RLF and will significantly minimize the amount of PPHO compared to other workers. In the simulation results, our proposed model is evaluated using two frequency plans. By using frequency plan 1, the user mean throughput increased from 270 Kbps to 281 Kbps when the serving cell was fully loaded. By using frequency plan 2, the user mean throughput increased from 6 Mbps to 20 Mbps when the serving cell was fully loaded. In addition, the amount of ping-pong handover between overlapped small cells decreased and will not exceed one PPHO compared to another literature model. Creator An entity primarily responsible for making the resource Maryhan M. Mohamed1, Hesham M. Elbadawy2, Abdelhady Abdelazim Ammar 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 3, 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 https://repository.horizon.ac.id/files/original/ba82cf1919aca097fe5979dd12195ea7.pdf f0d9a0837f012b9eaff5916b81bdf55d 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 Novel intelligent TOPSIS variant to rank regions for disaster preparedness Subject The topic of the resource COVID-19 Decision support system Disaster management Multi-criteria decision-making Technique for order of preference by similarity to ideal solution Description An account of the resource An important facet of disaster mitigation is discovering regions based on their lack of preparedness for combating disaster. Accordingly, organizations can lay down appropriate risk management strategies and guidelines to minimize loss due to disaster. “Technique for order of preference by similarity to ideal solution (TOPSIS)” is a popular multi-criteria decision-making (MCDM) method that is deployed for ranking alternatives based on multiple pre-specified criteria. However, the method’s efficiency in ranking region as per multiple criteria for disaster management is far from the ground truth. The authors propose a novel intelligent method HCF-TOPSIS, an extension of traditional TOPSIS, to deliver an efficient ranking mechanism for regional safety assessment of disaster affected regions. HCF-TOPSIS capitalizes on entropy (H), closeness (C), and farness (F) metrics to obtain efficient ranking scores of the disaster affected regions. Extensive experimentation validates the claim and proves the superiority of HCF-TOPSIS over existing TOPSIS variants. The proposed research presents many benefits, especially to governments and stakeholders, intending to take appropriate actions to contain disasters. Creator An entity primarily responsible for making the resource Harita Ahuja1, Sharanjit Kaur1, Sunita Narang1, Rakhi Saxena2 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 19 Jan 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 COVID-19 Decision support system Disaster management Multi-criteria decision-making Technique for order of preference by similarity to ideal solution https://repository.horizon.ac.id/files/original/85c925aaf91ab7cef338063d3f9b37b1.pdf 21191dca4a8dcdfa022d7c0cb3e504b9 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 Deep learning ensemble framework for multiclass diabetic retinopathy classification Subject The topic of the resource Convolutional neural networks Explainability Deep learning Diabetic retinopathy Uncertainty Description An account of the resource Diabetic retinopathy (DR) is the leading cause of blindness among adults and has no visible symptoms. Early detection is the key to prevent vision loss. Computer-aided deep learning using convolutional neural networks (CNN) have recently gained momentum for DR diagnosis as the cost can be significantly reduced while making the diagnosis more accessible. In this work, we present a fully automated framework DR network (DRNET) that fuses both image texture features and deep learning features to train the CNN model. The framework aggregates predictions from three CNN models using ensemble learning for more precise and accurate DR diagnosis when compared to standalone CNN. To strengthen the confidence of medical practitioners in acceptance of automated DR diagnosis, we extend the DRNET framework by producing model uncertainty scores and explainability maps along with the classification results. Creator An entity primarily responsible for making the resource Mudit Saxena1, Pratap Narra1, Mayank Saxena2, Rakhi Saxena3 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 29, 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 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 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/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/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/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/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