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                <text>TELKOMNIKA Telecommunication Computing Electronics and Control&#13;
Improving gain of ultra-wideband planar antennas: a grounded frequency-selective surface reflector</text>
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                <text>This paper introduces a method to enhance the gain of ultra-wideband (UWB) planar antennas by employing a grounded frequency-selective surface (FSS) as a reflector. The grounded FSS reflector comprises square patch structures (SPSs) of unit cells with a complete ground plane. The designed FSS utilizes miniaturized unit cells that are printed on both sides of an FR4 substrate, making it highly suitable for a wide range of applications, particularly as a reflector to optimize the gain of UWB omnidirectional radiators. This concept is demonstrated by employing a circular monopole UWB antenna as the radiator. The measured outcomes of the suggested antenna with the grounded FSS maintain a broad frequency range of bandwidth of 9.162 GHz, spanning from 2.638 GHz to 11.8 GHz. The antenna, in combination with the FSS, achieves a significant measured gain of 7.6 dBi and a high efficiency of 93% at 9.6 GHz. The attributes of the suggested UWB FSS make it an ideal solution&#13;
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                <text>TELKOMNIKA Telecommunication Computing Electronics and Control&#13;
Design zigzag edge of S shape slot antenna by using SIW technology for 5G application</text>
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Substrate integrated waveguide&#13;
technology&#13;
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                <text>This study offers a 5G substrate integrated waveguide (SIW) antenna with vertical S zigzag shape slot. The suggested antenna's radiating patch depends on the shape of the slot. Two types of slots have been used, straight and zigzag S shape slot with vertical and horizontal direction, slots are etched on the patch to increase the antenna's overall bandwidth and gain. The suggested straight and zigzag SIW S slot antennas both resonate at 28 GHz, and the overall structure size is 7.10×14.93 mm. The presented design could achieve high gain, efficiency, and minimal losses, which are all important concerns. The presented antenna may produce a gain of 9.48 dB, a 95% efficiency, and a wider bandwidth of no less than 3.25 GHz at 28 GHz. </text>
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Comprehensive review of the human body communication system for wireless body area network applications</text>
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IEEE 802.15.6&#13;
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                <text>Chaitra Soppinahally Nataraju, Desai Karanam Sreekantha, Kanduri V S S S S Sairam</text>
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Geographical and maximum distance on-demand routing algorithm G-MDORA</text>
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Mobile ad-hoc network&#13;
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                <text>A vehicular ad hoc network (VANET) is an intelligent technology that allows efficient communication, secure data transmission, and traffic management. VANET allows vehicles in the network to communicate wirelessly with roadside units (RSUs) or between vehicles within a coverage area. The primary goal of adopting VANET is to reduce the frequency of accidents in specific urban regions drastically. It has a significant impact on passenger safety and the ability of drivers to drive safely in metropolitan areas. As the number of cars on the road grows, so does the number of accidents. As a result, a better traffic system is required to address this issue. VANET is a cutting-edge network that primarily delivers intelligent transportation system (ITS) services to end-users to facilitate data exchange and ensure safety. In this paper, we propose geographical and maximum distance on-demand routing algorithm (G-MDORA) that combines the advantages of geographic routing protocol (GRP) and MDORA protocol for Ad hoc routing between vehicle to vehicle (V2V). Our proposed model provides an idea that can be used to improve the performance of the GRP and MDORA protocol. Moreover, the performance of the G-MDORA, GRP, and MDORA protocol was compared in terms of end-to-end delay, communication overhead, throughput, and packet loss ratio. </text>
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                <text>TELKOMNIKA Telecommunication Computing Electronics and Control&#13;
Enhancing of coverless image steganography capacity based on image block features</text>
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            </elementTextContainer>
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Coverless steganography&#13;
Hashing generation&#13;
Hiding capacity&#13;
Information hiding</text>
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            <description>An account of the resource</description>
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                <text>The idea of coverless information hiding has seen a great deal of development since it was initially introduced due to its effectiveness in&#13;
defeating steganalysis tools. However, the capacity for general coverless&#13;
information hiding methods to conceal information is limited, as well as no previous methods worked at the other requirements such as robustness. In this paper, a coverless image steganography (CIS) method for increasing capacity is proposed while retaining the robustness. The proposed method consists of several steps. Firstly, the secret data is segmented into segments of the n length. Secondly, a suitable image that has features similar to the secret message is selected and divided into non-overlapping blocks. Thirdly, these blocks are transformed into the frequency domain by applying discreet wavelet transform (DWT). Fourthly, building a hash sequence table using a suggested hashing algorithm. Fifthly, to reduce search time an indexing table is built based on the generated hash sequence. Sixthly, match each segment with the generated hash sequences and save the auxiliary information for each matched segment in the image in a file. Lastly, send the stego image and the auxiliary information file to the receiver. The experimental results&#13;
show that the CIS method produces high capacity compared with revious&#13;
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        <name>Information hiding</name>
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        <name>Jurnal Nasional Informatika</name>
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                  <text>VOL. 21, NO. 6 2023</text>
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    <elementSetContainer>
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        <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>
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            <description>A name given to the resource</description>
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                <text>TELKOMNIKA Telecommunication Computing Electronics and Control&#13;
Automatic point cloud segmentation using RANSAC and DBSCAN algorithm for indoor model</text>
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                <text>Density-based spatial clustering&#13;
of application&#13;
Low-cost terrestrial laser&#13;
scanners&#13;
Machine learning&#13;
Point cloud&#13;
Random sample consensus</text>
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            <description>An account of the resource</description>
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                <text>Indoor modeling is a crucial aspect of architecture, engineering, and construction (AEC) projects. While terrestrial laser scanners (TLS) are the most popular tool for acquiring indoor geometry, processing point clouds from TLS scans with manual methods can be inefficient and error-prone. This study proposes a machine learning algorithm to automatically segment point clouds acquired by low-cost TLS. Random sample consensus (RANSAC), a simple yet effective algorithm for segmenting planar surfaces such as walls, ceilings, and floors, is used in the segmentation process. The resulting segmentation is then refined using density-based spatial clustering of application with noise (DBSCAN) to group nearby points that were not segmented correctly by RANSAC into the appropriate segment. The result is a segmented point cloud consisting of five indoor elements: wall, ceiling, floor, column, and interior. The algorithms were found to be effective for segmenting small and simple rooms. For larger or more complex rooms, segmentation can be performed by dividing the room into several parts and applying the algorithms to each partition. Overall, the study demonstrates the&#13;
potential of machine learning algorithms for automating point cloud&#13;
segmentation tasks in indoor modeling, especially for low-cost TLS scans.</text>
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                <text>Harintaka, Calvin Wijaya</text>
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                <text>http://telkomnika.uad.ac.id</text>
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                <text>peri irawan</text>
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        <name>Jurnal Nasional Informatika</name>
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      <tag tagId="10115">
        <name>Low-cost terrestrial laser scanners</name>
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      <tag tagId="10116">
        <name>Machine learning Point cloud</name>
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        <name>of application</name>
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                  <text>VOL. 21, NO. 6 2023</text>
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    <elementSetContainer>
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              <elementText elementTextId="49666">
                <text>TELKOMNIKA Telecommunication Computing Electronics and Control&#13;
Investigation of classical segmentation's impact on paddy disease classification performance</text>
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                <text>Computer vision&#13;
Image classification&#13;
Image segmentation&#13;
Machine learning&#13;
Paddy disease</text>
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            <description>An account of the resource</description>
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                <text>The key source of information for disease diagnosis and classification in  paddy diseases is the leaves. Applying hybrid techniques, such as image processing-pattern recognition (IP-PR) and computer vision-based  technologies, is the answer to assessing the health of plants. The following paddy diseases are considered in this paper: bacterial leaf blight (BLB), brown spot (BS), leaf smut (LS), and narrow brown spot (NBS) from the machine learning repository. A classical colour threshold-based segmentation method is implemented newly to separate the patterns of image pixels into the diseased part and the normal part. The human visual impression (VI), a subjective method, and a parametric-based method with an average error rate (ER) and overlap rate (OR) are used to assess the uniqueness of the suggested segmentation technique. Using a multi-class support vector machine (MSVM) classifier, the analysis yielded segmented images using the proposed method with an accuracy of 92% over the existing method with an accuracy of 76.60%. The BLB disease achieved the highest identification accuracy of 91%. Our proposed method evaluates the segmentation performance and achieved consistent accuracy higher than the previous segmentation work. </text>
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                <text>Hemanthakumar R. Kappali, Sadyojatha KalapurMath</text>
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            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="49670">
                <text>http://telkomnika.uad.ac.id</text>
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                <text>peri irawan</text>
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            <name>Language</name>
            <description>A language of the resource</description>
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        <name>Image classification</name>
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        <name>Image segmentation</name>
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      <tag tagId="5408">
        <name>Jurnal Nasional Informatika</name>
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                  <text>VOL. 21, NO. 6 2023</text>
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                <text>TELKOMNIKA Telecommunication Computing Electronics and Control&#13;
Optimization of an ANN-based speed and position estimator for an FOC-controlled PMSM using genetic algorithm</text>
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                <text>Artificial neural networks&#13;
Genetic algorithm&#13;
PMSM&#13;
Sensorless field oriented&#13;
control</text>
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            <description>An account of the resource</description>
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                <text>To further improve the performance of sensorless permanent magnet&#13;
synchronous motor (PMSM) implementations, this study develops a neural network-based estimator for the speed and position estimation of a PMSM using field oriented control (FOC) as its control scheme. The proposed neural network’s hyperparameters are optimized using genetic algorithm. The neural network is trained and optimized based on a training dataset obtained from the Simulink simulation of the motor control system. The hyperparameters optimized include the training algorithm parameters, batch size, and the number of hidden layers and the corresponding neurons. The proposed estimator performed with better estimation accuracy than conventional estimators such as the sliding mode observer (SMO), model reference adaptive system (MRAS), and two other neural network configurations. The qualifications were made on steady-state and dynamic conditions. In terms of efficiency, the proposed estimator has a relatively lower power consumption but still falls short of the power drawn when using an actual sensor. The qualification process verified that the optimization of the neural network’s hyperparameters using genetic algorithm can provide a better performance in the estimation of motor parameters in sensorless motor&#13;
applications. </text>
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                <text>Juan Paolo Quismundo, Edwin Sybingco, Maria Antonette Roque, Alvin Chua, Leonard Ambata</text>
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                <text>http://telkomnika.uad.ac.id</text>
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          <element elementId="37">
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              <elementText elementTextId="49384">
                <text>peri irawan</text>
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              <elementText elementTextId="49386">
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      <tag tagId="7026">
        <name>Genetic algorithm</name>
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        <name>Jurnal Nasional Informatika</name>
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                  <text>VOL. 21, NO. 6 2023</text>
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                <text>TELKOMNIKA Telecommunication Computing Electronics and Control&#13;
Reconfigurable meander line dipole antenna based on two rectangular defected ground structure</text>
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                <text>CST microwave studio&#13;
Defected ground structure&#13;
Meander line&#13;
Positive-intrinsic-negative&#13;
diode&#13;
Reconfigurable antenna</text>
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            <description>An account of the resource</description>
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                <text>In this study, a reconfigurable double-sided meander line dipole antenna (RMLA) incorporated with a tapered balun was developed to function at&#13;
0.9 GHz, 2.4 GHz, and 3.7 GHz. Furthermore, the suggests antenna&#13;
functions at three modes at different frequency bands with pattern&#13;
reconfiguration. Two positive-intrinsic-negative (PIN) diodes were&#13;
embedded in the two rectangular defected ground structures to accomplish frequency and pattern reconfigurability. With excellent impedance matching, the return loss in each of these bands keeps beneath -10 dB. The suggested antenna was designed using computer simulation technology 2020 and constructed on a FR-4 substrate with a thickness of 1.6 mm, and dielectric constant of 4.3 mm respectively. Additionally, for antenna size reduction, meander line technique was embedded. The fundamental working mechanism of this reconfigurable antenna is accomplished by changing the status of a radio frequency (RF) switches, which is carried out in on or off mode. For the three resonant bands, the suggested antenna has a voltage standing waves ratio (VSWR) &lt; 2. Up to 80%, the suggested structure radiation efficiency and gain (1−2.8) dBi are calculated. The suggested antenna is well suitable for global system mobile, wireless fidelity (WiFi) and C-band applications because of its notable features of high efficiency, good gain and frequency reconfigurability. </text>
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The second and third levels of digital divide among Malaysian university students during the Covid-19 pandemic</text>
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Online learning&#13;
Private and public universities&#13;
Malaysia&#13;
Second and third levels of&#13;
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                <text>Adaptation of online learning among Malaysian universities during the Covid-19 pandemic stressed the dire need to tackle digital divide. Lack of&#13;
empirical evidence, generic highlights on accessibility to technologies and&#13;
lack of focus given on gaps in skills, usage and outcomes obscures the extent of digital divide among Malaysian students. Data was collected from 356 undergraduate students of private and public universities to identify the differences in second and third levels of digital divide, where the former entails divide in terms of digital skills and digital usage, then the latter concerns online learning outcomes between students from both types of Malaysian universities. Descriptive results unveiled the persistence of digital divide in the second and the third level among both public and private university students, with exception of students from public universities showing an advanced grasp of digital skills. Path analysis have also highlighted that having digital skills would encourage digital usage. Although digital usage equips students with resources and support for their learning attainment, at the same it also creates digital distraction, which diverts students from acquiring online learning fulfilment.  </text>
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                <text>Latha Subramaniam, Farah Waheeda Jalaludin, Kai Wah Hen, Ching Seng Yap</text>
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