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                <text>Energy-efficient certificateless signcryption for secure data transfer in wireless sensor networks</text>
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                <text>Censored regression&#13;
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Jaccard index certificateless signcryption&#13;
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Wireless sensor networks</text>
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                <text>Wireless sensor networks (WSN) have gained high popularity in the realm of technological innovation and have a prime responsibility of transferring the data safely to the sink despite the vulnerable situation presiding around the network. There needs to be a compromise made between energy consumption and the intricate network security system because they are inversely correlated. To create a safe and effective data transfer between the communicating nodes, a new censored regressive jaccard indexed certificateless signcryption (CEJICS) technique is suggested. Initially, the Gaussian likelihood censored regression is applied to identify the energy-efficient node which supports enhancing the network lifetime. The security is implemented using the rabin cryptographic jaccard indexive certificateless signcryption (RCJICS). To create a signcryption system with the characteristics of digital signature and ciphertext authenticity, the proposed work focuses on certificateless cryptography. The NS-2 simulator is used for the simulation, and performance metrics are used to evaluate it. According to the observed quantitative results, the suggested CEJICS method outperforms the other conventional methods by improving the packet delivery ratio (PDR) by 93%, achieving a minimum drop of 7%, reducing delay by 22%, reducing overhead to 17%, minimizing energy consumption by 15%, and ultimately extending the network lifetime by 10%.</text>
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                <text>Paruvathavardhini Jaganathan, Sargunam Balusamy</text>
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                <text>Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA</text>
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                <text>Business intelligence system model to measure the performance of lecturers’ scientific publications</text>
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K-means&#13;
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                <text>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.</text>
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                <text>Miwan Kurniawan Hidayat1,2, Dedy Sugiarto2,3, Rina Fitriana2,4, Yun-Chia Liang5</text>
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                <text>Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA</text>
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                  <text>VOL. 23, NO.4 2025</text>
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                <text>Optimizing signal conversion in uniform FBGs with InGaAs photodetectors for medical sensors</text>
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InGaAs&#13;
Photodetector&#13;
Reflectivity&#13;
Uniform</text>
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                <text>This study experimentally interrogates the spectral response of uniform fiber Bragg gratings (FBGs) with varying reflectivity levels of 30%, 50%, 70%, and 90% under controlled environmental stimuli. The objective is to elucidate the influence of reflectivity on the wavelength shift behavior of FBGs and to inform the optimal interrogation of these elements with indium gallium arsenide (InGaAs) photodetectors in high-performance sensing systems. Utilizing high-precision measurement procedures and specialized instrumentation, the experiments revealed that the magnitude and pattern of wavelength shifts are significantly influenced by FBG reflectivity. Specifically, lower reflectivity enhances sensitivity, while higher reflectivity contributes to greater spectral stability. These findings highlight the critical role of reflectivity in shaping the spectral modulation characteristics of FBGs, establishing a critical theoretical framework for precision optical sensor systems. The outcomes give significant contributions to the design and calibration of FBG-based sensors, particularly biomedical applications where precision and responsiveness are paramount.</text>
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                <text>Tengku Emrinaldi1, Bambang Widiyatmoko2, Bunga Meyzia1, Sumiaty Ambran3, Saktioto1,&#13;
Mohamad Syahadi2, Agitta Rianaris2, Dwi Hanto2</text>
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                <text>Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA</text>
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                <text>Artificial bee colony&#13;
Cauchy algorithm&#13;
Power losse reduction&#13;
Reconfiguration distribution network&#13;
Soft open point</text>
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                <text>Reconfiguring the distribution network by selecting open switch states is an effective approach to reduce power losses in the system. However, with the rise of distributed energy resources such as photovoltaic and wind turbines and dynamic loads such as electric vehicles, which introduce uncertainties, it has become necessary to integrate standard operating procedures (SOPs) to better control power flows. This study proposes an algorithm that combines the artificial bee colony (ABC) and Cauchy opposition-based learning (OBL) algorithms to solve the optimization problem of determining both the location and capacity of SOPs, alongside reconfiguring the distribution network. The primary objective is to minimize power losses while improving power quality and system reliability. The proposed methodology was validated on the IEEE 33-node and 69-node distribution networks under seven varied operational scenarios, evaluating outcomes both with and without the integration of SOPs. The findings demonstrate that installing SOPs optimally reduces power losses, enhances system reliability, and maintains voltage levels within acceptable limits. The integration of the two algorithms also accelerates the convergence process, increasing computational speed and avoiding local optimization issues. When compared with other methods, the proposed algorithm delivers similar performance but with faster computation times and fewer iterations, making it more efficient and reliable.</text>
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                <text>Nguyen Tung Linh1, Nguyen Quynh Anh2</text>
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                <text>Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA</text>
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                <text>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.</text>
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                <text>Hani Q. R. Al-Zoubi</text>
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                <text>Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA</text>
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                <text>PERI IRAWAN</text>
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        <name>Adversarial loss Deep learning Generative adversarial networks Image resolution Loss function Pixel loss Prior loss</name>
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                  <text>VOL. 23, NO.4 2025</text>
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                <text>Bandwidth&#13;
Microstrip antenna&#13;
Radio frequency&#13;
Resonant frequency&#13;
Spiral coils</text>
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                <text>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.</text>
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                <text>Edison Andrés Zapata Ochoa1, Vanessa García Pineda1, Alejandro Valencia Arias2, Francisco Eugenio López Giraldo3</text>
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                <text>Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA</text>
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        <name>Bandwidth Microstrip antenna Radio frequency Resonant frequency Spiral coils</name>
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