1 10 26 https://repository.horizon.ac.id/files/original/9ca29c1e64211499ffcf4ae94598e787.pdf 12ac70a094f863601f339f2b0abf3436 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. 23, NO.4 2025 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 compact five-band patch antenna covering WLAN, WiMAX, X, and Ku-bands Subject The topic of the resource Bidirectional pattern antenna Compact antenna Five-band antenna Multi-band antenna Rectangular patch antenna Description An account of the resource This paper introduces a compact, low-profile, five-band antenna for wireless communication systems operating across 2.4/5 GHz WLAN, 3.5 GHz Wi-Max, and 7.5 GHz X- and Ku-band frequencies. The proposed antenna utilizes a novel configuration with a dual-overlapping rectangular patch coupled to a wide circular slot and an inverted L-shaped strip. Fabricated on a single-layer FR4 substrate (εr=4.3, thickness=1.6 mm), the antenna employs a 50-ohm coplanar waveguide feed, resulting in a compact footprint of 40×40×1.6 mm³. Experimental measurements and simulations demonstrate a bidirectional radiation pattern covering five distinct frequency bands: 2.4-2.485 GHz, 3.4-3.6 GHz, 5.15-5.825 GHz, 7.25-8.4 GHz, and 13.4-17.7 GHz. The antenna exhibits a return loss better than 10 dB across all bands and provides average gains of 1.78 dBi, 3.04 dBi, 3.4 dBi, 4.27 dBi, and 4.46 dBi, respectively. These results confirm the successful development of a five-band antenna with excellent performance characteristics, making it a promising candidate for 2.4/5 GHz WLAN, Wi-Max, and X- and Ku-band satellite communications, with automotive vehicles being one example. Creator An entity primarily responsible for making the resource Suthasinee Lamultree, Wutthipong Thanamalapong, Kanawat Nuangwongsa, Charinsak Saetiaw Source A related resource from which the described resource is derived Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource May 26, 2025 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/4d7690fa548ed8cbc90df4d8fde4a230.pdf 0a0be26c831e18357c883fcce74018b9 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. 23, NO.4 2025 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 convolution neural network model for knee osteoporosis classification using X-ray images Subject The topic of the resource Accuracy Convolutional neural networks Knee osteoporosis Osteopenia X-ray Description An account of the resource Bone structure deterioration along with low levels of bone density are the hallmarks of knee osteoporosis (KOP). The conventional approach for detecting osteoporosis is accomplished using a knee radiograph, but it requires specialized knowledge. Nevertheless, X-rays can be difficult to interpret due to their large volume and minor fluctuations. In the past few decades, deep learning algorithms have minimized misinterpretation and modified medical diagnosis. In particular, algorithms based on convolutional neural networks (CNNs) have been used to speed up the procedure of diagnosis because of their innate capacity to extract significant features that often are challenging to spot by hand. A robust CNN model was proposed in this paper for KOP classification which uses a train and test approach to recognize healthy, osteopenia-predicted, and osteoporosis knee cases using 1947 X-ray images. The proposed model was designed using Jupyter Notebook and is in Python. To verify the efficiency of the model, some factors were calculated such as accuracy, precision, recall, and f1-score. In comparison with other similar systems, the results obtained showed that the accuracy of the proposed system reached 90.25%. Creator An entity primarily responsible for making the resource Omar Khalid M. Ali1, Abeer K. Ibrahim2, Bilal R. Altamer3 Source A related resource from which the described resource is derived Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource May 10, 2025 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 Accuracy Convolutional neural networks Knee osteoporosis Osteopenia X-ray https://repository.horizon.ac.id/files/original/a83f343a01d88cbce7564546f6d294c1.pdf 5b69e7cff2a5adc25dfbbfe3638ddabd 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. 23, NO.4 2025 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 new resonant-based sensor for non-invasive measurement of blood glucose levels Subject The topic of the resource Blood glucose level Dual-mode Microwave sensor Non-invasive Resonator Sensitivity Description An account of the resource This paper presents a rapidly developed non-invasive microstrip sensor for measuring blood glucose levels (BGLs). The sensor features a microstrip closed-loop square resonator integrated with an interdigital capacitor (IDC), creating a sensitive area for glucose detection when a patient’s finger is placed on it. Using odd and even mode analytical methods and transmission line theory, we analyzed the sensor’s performance. Results indicate that the second even mode demonstrates significant changes across a standard glucose concentration range. The sensor was designed and simulated in ANSYS high-frequency structure simulator (HFSS), showing a resonance frequency shift of up to 24.9 MHz at 1.94 GHz and a sensitivity of 110 kHz per mg/dL over a detection range of 0 to 216 mg/dL. Additionally, the frequency shift exhibits a high linear correlation (0.9485). In summary, the proposed sensor shows significant promise for achieving precise measurements of BGLs Creator An entity primarily responsible for making the resource Abolfazl Bijari, Faezeh Foolad, Mohammadreza Khorshidi Source A related resource from which the described resource is derived Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource May 26, 2025 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 Blood glucose level Dual-mode Microwave sensor Non-invasive Resonator Sensitivity https://repository.horizon.ac.id/files/original/c272fbfa75108960b01678bc6105d385.pdf 2fb5fb7078dee8e015ba2c1c6c40fcd5 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. 23, NO.4 2025 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 novel-shaped THz MIMO antenna with high bandwidth for advanced 6G wireless application Subject The topic of the resource 6G Communication Graphene High-gain Resistance-inductance-capacitance THz antenna Wide-bandwidth Description An account of the resource This article presents an industrial and innovation highly efficient drone-shaped slotted graphene-based multiple input multiple output (MIMO) antenna with improved isolation, designed for high-speed short-range communication, video rate imaging, medical imaging, and explosive detection in the THz band. The proposed antenna is constructed on an 88×244 μm2 polyimide substrate. Key performance parameters such as reflection coefficient, gain, directivity, radiation pattern, and antenna efficiency are evaluated at the resonating frequencies of 1.7 THz, 3.35 THz, and 5.31 THz, covering a wide bandwidth of 4.88 THz with a reflection coefficient of less than -10 dB. The antenna achieves a maximum gain of 13.92 dB and a radiation efficiency of 95.77% within the resonating band. The MIMO design parameters include an envelope correlation coefficient (ECC) of 0.00015, a diversity gain (DG) of 9.9992, and an isolation of less than -31.55 dB between its elements across the entire bandwidth. The outcomes from CST simulations were verified by designing and simulating a similar resistance-inductance-capacitance (RLC) circuit in advanced design system (ADS), with both simulators producing comparable reflection coefficients. These features underscore the potential of the proposed antenna, utilizing simulations and an equivalent RLC circuit model, as a robust candidate for THz band applications in 6G wireless communication. Creator An entity primarily responsible for making the resource Kamal Hossain Nahin1, Jamal Hossain Nirob1, Md. Ashraful Haque1, Narinderjit Singh Sawaran Singh2, Redwan Al Mahmud Bin Asad Ananta1, Md. Kawsar Ahmed1, Md. Sharif Ahammed1, Liton Chandra Paul3 Source A related resource from which the described resource is derived Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource Mar 11, 2025 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 Communication Graphene High-gain Resistance-inductance-capacitance THz antenna Wide-bandwidth https://repository.horizon.ac.id/files/original/97b371bd4774b53daae3d4f057bc2070.pdf d0535b4d94ffd928f635e674ee99c357 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. 23, NO.4 2025 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 An extensive framework for assessing the quality of websites Subject The topic of the resource Web contexts Web quality assessment systems Web quality computing methods Web quality frameworks Web quality parsers and expert systems Description An account of the resource The quality of the website is quite important in generating customer satisfaction and loyalty. A website’s quality depends on several factors, features, and characteristics. Several computational methods are necessary to evaluate the quality of each factor and subsequently determine the overall quality of the entire website. Each factor does not contribute to the same level of quality required by the end users and thus requires a weighting system. Expert systems, which are either manually defined or learnt using artificial intelligence (AI), are to be modelled for assessing the quality of a factor/sub-factor or characteristics of a sub-factor. The quality of a website varies depending on the context. Context-based quality assessment of the websites is required. There is a need to generate example sets to assess the quality of websites and to establish relationships between web-related quality factors, subfactors, and characteristics. In this paper, a comprehensive framework is presented that caters to parametric structure building and mapping, parsers for computing characteristic values, context assessment, building expert systems, and learning models for assessing the quality of websites and weighing the factors that have specific significance on the quality of the website Creator An entity primarily responsible for making the resource Sasi Bhanu Jammalamadaka1, Bala Krishna Kamesh Duvvuri2, Sastry Kodanda Rama Jammalamadaka3, Vishnu Priya Biyyapu3 Source A related resource from which the described resource is derived Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource May 26, 2025 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 Web contexts Web quality assessment systems Web quality computing methods Web quality frameworks Web quality parsers and expert systems https://repository.horizon.ac.id/files/original/fe9a00a1883b061350a267813ccc07e4.pdf b5753d2320c02e8c901d46f01be75e8a 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. 23, NO.4 2025 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 Archimides multiband micro ribbon spiral antenna for energy harvesting Subject The topic of the resource Bandwidth Microstrip antenna Radio frequency Resonant frequency Spiral coils Description An account of the resource The current need to conserve natural resources and find new ways to advance without damaging the environment has led to the search for different energy sources. In this sense, the availability of radio frequency (RF) energy is found as a favorable option for new energy sources. This work describes the design of a microstrip antenna for the collection of radiofrequency energy in the megahertz band. Using the automatic optimization software computer simulation technology (CST) Studio, a circular spiral antenna is simulated using the low-cost FR4 substrate with a thickness of 1.57 mm and copper as the conductive material with a thickness of 0.035 mm. The proposed design presents resonance frequencies in multiple bands from 550 MHz to 1900 MHz, with bandwidths between 15 MHz and 150 MHz. The antenna design is based on the resonant cavity model and presents circular polarization due to its design coil type, with modified geometry using symmetrical orthogonal slots to generate multiple working bands. The design of this antenna can capture the power emitted by the frequency bands used in mobile telephony, radio communications, broadcasting, and television. Creator An entity primarily responsible for making the resource Edison Andrés Zapata Ochoa1, Vanessa García Pineda1, Alejandro Valencia Arias2, Francisco Eugenio López Giraldo3 Source A related resource from which the described resource is derived Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource May 10, 2025 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 Bandwidth Microstrip antenna Radio frequency Resonant frequency Spiral coils https://repository.horizon.ac.id/files/original/12d97002b8d2ca32cf19eb50bd5411b6.pdf 84e7b862cbcf5317d6a393b7a3f5bf34 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. 23, NO.4 2025 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 Business intelligence system model to measure the performance of lecturers’ scientific publications Subject The topic of the resource Business intelligence Data mining Data warehouse K-means X-means Description An account of the resource Scientific publication data is sourced from the SINTA website to measure the performance of journals, institutions, and researchers in Indonesia. Accessing and analyzing data for institutional needs is restricted, and lecturer development patterns based on lecturer characteristics remain untapped. The study aims to analyze and design business intelligence system models to measure the performance of scientific publications using dimensional models, clustering, on-line analytical processing (OLAP), and prototyping. Research methods are carried out through data and information needs analysis, data warehouse design, data mining and OLAP application, business intelligence system development, and system evaluation. The resulting dimensional models are the researcher index model, the researcher score model, the publication article model, and the research subject model. Measurements of data size and processing time show that the star schema has data of 336 KB and a processing time of 0.00554 seconds, is the best model compared to the snowflake’s schema, which has data of 368 KB and a processing time of 0.00611 seconds. Davies–Bouldin Index (DBI) measurements show the best clustering performance is the X-means algorithm with K as many as 5 clusters (Kmin=3, Kmax=5) and a DBI value of 0.537040. Creator An entity primarily responsible for making the resource Miwan Kurniawan Hidayat1,2, Dedy Sugiarto2,3, Rina Fitriana2,4, Yun-Chia Liang5 Source A related resource from which the described resource is derived Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource May 10, 2025 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 Business intelligence Data mining Data warehouse K-means X-means https://repository.horizon.ac.id/files/original/63701c341fe5fe184d5f6ff268119b78.pdf b206912eb40da54dbe7d5f60fd0f8977 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. 23, NO.4 2025 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-based image super-resolution using generative adversarial networks with adaptive loss functions Subject The topic of the resource Adversarial loss Deep learning Generative adversarial networks Image resolution Loss function Pixel loss Prior loss Description An account of the resource This study investigates deep learning based single image super-resolution (SISR) and highlights its revolutionary potential. It emphasizes the significance of SISR, and the transition from interpolation to deep learning-driven reconstruction techniques. Generative adversarial network (GAN)-based models, including super-resolution generative adversarial network (SRGAN), video super-resolution network (VSRResNet), and residual channel attention-generative adversarial network (RCA-GAN) are utilised. The proposed technique describes the loss functions of the SISR models. However, it should be noted that the conventional methods frequently fail to recover lost high-frequency details, which signify their limitations. The current visual inspections indicate that the suggested model can perform better than the others in terms of quantitative metrics and perceptual quality. The quantitative results indicate that the utilised model can achieve an average peak signal-to-noise ratio (PSNR) enhancement of X dB and an average structural similarity index (SSIM) increase of Y. A range of improvements of 7.12-23.21% and 2.75-10.00% are obtained for PSNR and SSIM, respectively. Also, the architecture deploys a total of 2,005,571 parameters, with 2,001,475 of these being trainable. These results highlight the model’s efficacy in maintaining key structures and generating visually appealing outputs, supporting its potential implications in fields demanding high-resolution imagery, such as medical imaging and satellite imagery. Creator An entity primarily responsible for making the resource Hani Q. R. Al-Zoubi Source A related resource from which the described resource is derived Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource May 10, 2025 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 Adversarial loss Deep learning Generative adversarial networks Image resolution Loss function Pixel loss Prior loss https://repository.horizon.ac.id/files/original/d8db74af00c6268445968df5fc97886f.pdf 6cbb0a42ce20dfd65f22b62251d3fe07 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. 23, NO.4 2025 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 Design of a concurrent tri-band LNA based on composite right/left-handed transmission line resonators Subject The topic of the resource Composite right left handed transmmision line Low noise Low noise amplifier Multi band Split ring resonator Description An account of the resource This article presents a three-band low noise amplifier (LNA) in microstrip technology based on composite right left handed transmmision line (CRLH-TL) resonators for multi-band behavior, which has been designed to meet all the criteria that determine the quality of its operation. The transistor used is biased via a transmission line and matched by λ/4 transformer filters with CRLH-TL type resonators at the output to establish multiband behavior with improved band rejection to suppress unwanted frequencies and interference. Creator An entity primarily responsible for making the resource Faycal El Hardouzi, Mohammed Lahsaini, Mustapha Bahich, Badr Nasiri, Younes Achaoui Source A related resource from which the described resource is derived Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource May 26, 2025 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/f4e3ef1203c736d0fb6574ced494a320.pdf b5303c2b4c2264ca0bde333188b1e92a 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. 23, NO.4 2025 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 Design of a soft circular patch antenna operating in the 60 GHz band for 5G/6G applications Subject The topic of the resource 5G 60 GHz High-frequency structure simulator Medical Soft antenna patch Description An account of the resource 5G/6G technologies require higher-performance antennas in terms of bandwidth, gain, radiation, compact size, efficiency, and low cost. At the same time, fewer natural disturbances, such as rain and snow, and fewer non-natural disturbances. This is the challenge facing scientific research into antenna design and manufacture. In addition, in this paper we study and design a flexible circular microstrip patch antenna operating in the 60 GHz band for 5G/6G applications. This antenna is based on a biosourced substrate for industrial, scientific, and medical applications. For this study, we will use two techniques: one concerns the deformation of the ground plane deformation of the ground plane and substrate to improve the electrical performance of a proposed antenna. At the same time, the other is the parametric study of the appropriate position of a coaxial feed probe. This technique has the advantage of requiring no radiation contrition on the part of the coaxial probe. Next, specialized high-frequency structure simulator (HFSS) simulation software is used to design this antenna; it has a wide bandwidth above 3 GHz, a gain of 7.41 dB, a directivity of 7.53 dB, a radiated power of 13.55 dBm, an accepted power of 13.67 dBm, an incident power of 15.08 dBm, a radiation efficiency of 97.29 % and an efficiency of 98.4 %. Creator An entity primarily responsible for making the resource Salah-Eddine Didi1, Imane Halkhams2, Abdelhafid Es-Saqy1, Mohammed Fattah1, Said Mazer1, Moulhime El Bekkali1 Source A related resource from which the described resource is derived Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA Date A point or period of time associated with an event in the lifecycle of the resource May 10, 2025 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