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                  <text>VOL. 23, NO.4 2025</text>
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                <text>A compact five-band patch antenna covering WLAN, WiMAX, X, and Ku-bands</text>
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                <text>Bidirectional pattern antenna&#13;
Compact antenna&#13;
Five-band antenna&#13;
Multi-band antenna&#13;
Rectangular patch antenna</text>
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                <text>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.</text>
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                <text>Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA</text>
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                <text>EdgeShield: a robust and agile cybersecurity architecture&#13;
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                <text>Data processing&#13;
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Feature selection&#13;
Federated learning&#13;
Internet of medical things security&#13;
Intrusion detection systems&#13;
Principal component analysis</text>
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                <text>We present EdgeShield, a lightweight pipeline that streamlines internet of medical&#13;
things (IoMT) traffic analysis by pairing aggressive dimensionality-reduction&#13;
with federated model aggregation. It employs systematic preprocessing, advanced&#13;
feature selection, and robust sampling to reduce computational overhead&#13;
while enhancing performance. Through feature engineering techniques&#13;
such as principal component analysis (PCA), targeted feature selection, and embedding&#13;
methods, EdgeShield reduces dataset dimensionality by 96%, enabling&#13;
near real-time detection and prevention of cyber attacks on resource-constrained&#13;
edge devices. To harden the IoMT perimeter, EdgeShield trains ten lightweight&#13;
edge models in just 54s and merges their parameters into a single global classifier&#13;
with negligible extra delay. This method requires no additional training&#13;
or predictions, thus accelerating deployment. Additionally, by using a compact&#13;
dataset with five top-performing features and PCA with two components,&#13;
EdgeShield consistently achieves accuracy levels exceeding 99.2% for individual&#13;
edge models and the consolidated global model. With a built-in continuous&#13;
improvement loop, EdgeShield dynamically adapts to emerging data patterns&#13;
and operational conditions, driving substantial advancements in IoMT ecosystem&#13;
management. This approach delivers both rapid machine learning model&#13;
deployment and robust cyber attack detection, illustrating its potential to revolutionize&#13;
IoMT security and elevate healthcare data integrity.</text>
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                <text>Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA</text>
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                <text>Enhancing realism in hand-drawn human sketches through conditional generative adversarial network</text>
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                <text>Conditional generative adversarial network&#13;
Frechet inception distance&#13;
Hand drawn human sketches&#13;
Law enforcement applications&#13;
Realistic image generation&#13;
Sketch-to-image translation</text>
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                <text>This research focuses on enhancing the realism of hand drawn human sketches through the use of conditional generative adversarial networks (cGAN). Addressing the challenge of translating rudimentary sketches into high-fidelity images, by leveraging the capability of deep learning algorithms such as cGANs. This is particularly significant for applications in law enforcement, where accurate facial reconstruction from eyewitness sketches is crucial. Our research utilizes the Chinese University of Hang Kong Face Sketches (CUFS) dataset, a paired dataset of hand drawn human faces sketches and their corresponding realistic images to train the cGAN model. Generator network produces realistic images based on input sketches, where as discriminator network evaluates authenticity of these generated images compared to the real ones. The study involves careful preprocessing of the dataset, including normalization and augmentation, to ensure optimal training conditions. The model performance assessed through both quantitative metrics, such as frechet inception distance (FID), and qualitative evaluations, including visual inspection of generated images. The potential applications of this research extend to various fields, such as agencies of law enforcement for finding suspects and locating missing persons. Future work exploring advanced techniques for further realism, and evaluating the model’s performance across diverse datasets.</text>
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                <text>Imran Ulla Khan1,2, Depa Ramachandraiah Kumar Raja1</text>
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                <text>Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA</text>
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        <name>Conditional generative adversarial network Frechet inception distance Hand drawn human sketches Law enforcement applications Realistic image generation Sketch-to-image translation</name>
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                <text>Energy scavenging-aided NOMA uplink communications:&#13;
performance analysis</text>
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                <text>Nonorthogonal multiple access&#13;
Outage probability&#13;
Shadowed fading&#13;
Throughput&#13;
Uplink communications</text>
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                <text>Energy scavenging-aided nonorthogonal multiple access (NOMA) networks significantly&#13;
ameliorate energy-and-spectral efficiencies thanks to superimposing a&#13;
multitude of user signals for concurrent transmission and harvesting radio frequency&#13;
energy. Practically, energy harvesters possess non-linear characteristic&#13;
and their efficiency is enhanced considerably with deployment of multiple antennas.&#13;
Moreover, communication reliability and harvested energy are directly influenced&#13;
by wireless propagation which induces simultaneous effects of shadowing,&#13;
path loss, and fading. Accordingly, the current paper assesses analytically&#13;
outage probability and throughput of energy scavenging (ES)-aided NOMA uplink&#13;
communications (eNOMAu) taking into account the above-addressed realistic&#13;
factors (κ − μ shadowed fading, multi-antenna deployment, ES nonlinearity).&#13;
The results reveal considerable performance degradation caused by&#13;
ES non-linearity and wireless propagation. Additionally, desired system performance&#13;
can be reached flexibly with appropriate specification selection. In addition,&#13;
accreting a quantity of antennas drastically mitigates the outage probability&#13;
of eNOMAu, which can be minimized with optimal ES time selection. Furthermore,&#13;
the proposed eNOMAu is considerably superior to its eOMAu counterpart.</text>
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                <text>Huu Q. Tran1, Khuong Ho-Van2</text>
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                <text>PERI IRAWAN</text>
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                <text>Design of a concurrent tri-band LNA based on composite right/left-handed transmission line resonators</text>
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                <text>Composite right left handed transmmision line&#13;
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Multi band&#13;
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                <text>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%.</text>
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Small and medium enterprises&#13;
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Technology-organization-environment</text>
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                <text>As an emerging technology, blockchain has huge potential for transforming various industries, such as small and medium enterprises (SMEs). Despite its promising impact, its application in the supply chains of SMEs in developing countries is still in its infancy. This study analyzes the key factors of blockchain adoption intention in Philippine SMEs through an integrated technology-organization-environment (TOE) and technology acceptance model (TAM) with external variables. The data were obtained through a survey of 465 SME practitioners in the national capital region (NCR), Philippines, and analyzed using partial least squares and structural equation modeling (PLS-SEM). In terms of technology dimensions, relative advantage (RLA) had a positive influence on perceived usefulness (PUS) while compatibility (COM) had a positive influence on perceived ease of use (PEU), which both subsequently led to blockchain adoption intention. As regards organization, top management support (TMS) had a significant influence on the adoption intention of blockchain among SMEs. In terms of environment, only competitive pressure (CMP) had significant influence on blockchain adoption intention. In general, most of the hypothesized relationships are significant; thus, SMEs have a positive interest in adopting blockchain technology. Finally, the study serves as baseline evidence of blockchain adoption intention among SMEs in the Philippines</text>
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                <text>Modified electro-optical modulator based bipolar optical code division multiple access for free-space optics</text>
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Electro-optical modulator&#13;
Free-space optics&#13;
Optical code division multiple access&#13;
Polarization division multiplexing&#13;
Spectral amplitude coding</text>
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                <text>This study introduces a modified electro-optical modulator (EOM) to enhance bipolar optical code division multiple access (OCDMA) in free-space optical (FSO) communication. The proposed system improves signal quality, spectral efficiency, and resilience to atmospheric turbulence. Unlike conventional dual EOM techniques, the modified EOM enables simultaneous transmission of ‘0’ and ‘1’ chip values, reducing multiple access interference (MAI) and enhancing system robustness. This approach optimizes bandwidth utilization and ensures stable performance in varying environmental conditions. Simulations were conducted in an additive white Gaussian noise (AWGN) channel using three spectral amplitude coding (SAC) schemes: modified M-sequence, Walsh-Hadamard, and random diagonal (RD) codes. Results indicate that the modified EOM scheme significantly improves FSO system performance, achieving an average 47.1% lower minimum log of bit error rate (BER) in normal weather and 43.3% lower in extreme weather, ensuring superior noise suppression and signal integrity across varying environmental conditions. Additionally, the system maintains superior performance over longer distances, demonstrating its suitability for high-speed, long-range FSO applications. These findings highlight the potential of the modified EOM-based bipolar OCDMA system in advancing next-generation optical wireless networks, offering a more efficient, interference-resistant, and high-capacity communication solution for future technologies such as 6G and beyond.</text>
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                <text>Eddy Wijanto1,2, Kevin Sutanto1</text>
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                <text>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 %.</text>
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                <text>Salah-Eddine Didi1, Imane Halkhams2, Abdelhafid Es-Saqy1, Mohammed Fattah1, Said Mazer1, Moulhime El Bekkali1</text>
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          <name>Dublin Core</name>
          <description>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/.</description>
          <elementContainer>
            <element elementId="50">
              <name>Title</name>
              <description>A name given to the resource</description>
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                <elementText elementTextId="108668">
                  <text>VOL. 23, NO.4 2025</text>
                </elementText>
              </elementTextContainer>
            </element>
          </elementContainer>
        </elementSet>
      </elementSetContainer>
    </collection>
    <elementSetContainer>
      <elementSet elementSetId="1">
        <name>Dublin Core</name>
        <description>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/.</description>
        <elementContainer>
          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="108828">
                <text>Developing a robust data integrity verification framework for cloud storage utilizing Boneh-Lynn-Shacham signatures</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="108829">
                <text>Auditing&#13;
Boneh-Lynn-Shacham&#13;
Client data&#13;
Cloud computing&#13;
Heuristic search&#13;
Swarm algorithm</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="108830">
                <text>Cloud computing (CC) is a service that allows both data storage and data accessibility on the cloud through any on-demand service and application, without incurring the costs of local data storage and upkeep expenses. On the other hand, CC providers have to make sure good security among the consumers to inspire them to use the resources on the cloud as if it were their local storage, without bothering about the data quality. Therefore, data checking in the cloud gains much importance mostly at the demand of the customers for the data integrity that a third-party auditor (TPA) can be introduced to verify the data soundness. A present investigation introduced a secure and efficient auditing solution for cloud data under the Boneh-Lynn-Shacham (BLS) public identities to keep the information secure and at the same time perform auditing securely. this study restructured the public key equation with the signature equation in our proposed system so that there is an increment in complexity while quality execution speed is maintained, and the proposed system allows dynamic data processing in terms of insert, delete and modification. From the analysis of the system, which includes security and performance, the proposed system is very effective and safe.</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="108831">
                <text>Raed Abdulkareem Hasan1, Mustafa M. Akawee2, Enas Faek Aziz3, Omar A. Hammood4, Tole Sutikno5</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="48">
            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="108832">
                <text>Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="40">
            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="108833">
                <text>Mar 23, 2025</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="37">
            <name>Contributor</name>
            <description>An entity responsible for making contributions to the resource</description>
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                <text>PERI IRAWAN</text>
              </elementText>
            </elementTextContainer>
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            <name>Format</name>
            <description>The file format, physical medium, or dimensions of the resource</description>
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              <elementText elementTextId="108835">
                <text>PDF</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="44">
            <name>Language</name>
            <description>A language of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="108836">
                <text>ENGLISH</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="51">
            <name>Type</name>
            <description>The nature or genre of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="108837">
                <text>TEXT</text>
              </elementText>
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