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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
Image based anthracnose and red-rust leaf disease detection using deep learning</text>
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                <text>Convolutional networks, Deep neural network, Image classification, Mango leaf diseases,Transfer learning</text>
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                <text>Deep residual learning frameworks have achieved great success in image&#13;
classification. This article presents the use of transfer learning which is&#13;
applied on mango leaf image dataset for its disease’s detection. New&#13;
methodology and training have been used to facilitate the easy and rapid&#13;
implementation of the mango leaf disease detection system in practice.&#13;
Proposed system can be used to identify the mango leaf for whether it is&#13;
healthy or infected with the diseases like anthracnose or red rust. This paper describes all the steps which are considered during the experimentation and design. These steps include leaf image data collection, its preparation, data assessment by agricultural experts, and selection and tranning of deep neural network architectures. A deep residual framework, residual neural network (ResNET), was used to perform deep convolutional neural network training. ResNETs are easy to optimize and can achieve better accuracies. The experimental results obtained from “ResNET architectures, such as ResNet18, ResNet34, ResNet50, and ResNet101” show the accuracies from 94% to 98%. ResNET18 architecture selected from above for system design as it gives 98% accuracy for mango leaf disease’s detection. System will help farmers to identify leaf diseases in quick and efficient manner and facilitate decision-making in this front. </text>
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                <text>Rajashree Y. Patil, Sampada Gulavani, Vishal B. Waghmare, Irfan K. Mujawar</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i6.24262</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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RoBERTa: language modelling in building Indonesian question-answering systems</text>
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                <text>This research aimed to evaluate the performance of the A Lite BERT&#13;
(ALBERT), efficiently learning an encoder that classifies token&#13;
replacements accurately (ELECTRA) and a robust optimized BERT&#13;
pretraining approach (RoBERTa) models to support the development of the Indonesian language question and answer system model. The evaluation carried out used Indonesian, Malay and Esperanto. Here, Esperanto was used as a comparison of Indonesian because it is international, which does not belong to any person or country and this then make it neutral. Compared to other foreign languages, the structure and construction of Esperanto is relatively simple. The dataset used was the result of crawling Wikipedia for Indonesian and Open Super-large Crawled ALMAnaCH coRpus (OSCAR) for Esperanto. The size of the token dictionary used in the test used approximately 30,000 sub tokens in both the SentencePiece and byte-level byte pair encoding methods (ByteLevelBPE). The test was carried out with the learning rates of 1e-5 and 5e-5 for both languages in accordance with the reference from the bidirectional encoder representations from transformers (BERT) paper. As shown in the final result of this study, the ALBERT and RoBERTa models in Esperanto showed the results of the loss calculation that were not much different. This showed that the RoBERTa model was better to implement an Indonesian question and answer system. </text>
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                <text>Wiwin Suwarningsih,  Raka Aditya Pratama, Fadhil Yusuf Rahadika, Mochamad Havid Albar Purnomo</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i6.24248</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
Weather observation and forecasting using radiosonde</text>
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                <text>Climate studies, Radiosonde, Weather baloon, Weather forecasting</text>
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                <text>Weather balloons are high-altitude meteorological balloons particularly used for carrying scientific payloads into the upper atmosphere. These data are obtained by using an instrument called as radiosonde which is attached to the helium filled weather balloon to measure the meteorological data as it ascends up into the atmosphere. For more than 100 years, weather balloons have given valuable information for climate and meteorological research In this paper, the radiosonde module is designed with negligible risk of failure and cost effectiveness. The instruments to be fixed along with the weather balloon are logging camera, temperature sensor, pressure sensor, humidity sensor, global positioning system (GPS) module and a power source. This module is used to measure and log the basic weather parameters such as pressure, temperature, humidity and this also captures the picture of a particular locality with the help of a microcontroller. This proposed work is useful for observing high altitude weather data which is essential for predicting natural disasters. Further more, it is helpful to analyze the climatological and weather details of a particular region it also plays an important role in estimating agricultural models. </text>
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                <text>Jeyaraj Jency Joseph, Rajasekaran Meenal, Francis Thomas Josh, Prawin Angel Michael, Vinoth Kumar Krishnamoorthy, Giriprasad Chandran, Selve Veerabathran</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i6.24247</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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Various control methods of permanent magnet synchronous motor drives in electric vehicle: a technical review </text>
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                <text>Direct torque control, Electric vehicle, Intelligent controller, PMSM drive, Torque ripple</text>
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                <text>Day by day use of internal combustion engines (ICE) compared to electric vehicles (EV) is deteriorating because mainly of pollution and their less fuel availability. In the present scenario, an electric vehicle plays a major role in place of an ICE vehicle. So that performance of EV can be improved by proper selection of electric motor. Initially, EV prefers induction motors for traction purposes, but complexity in controlling induction motor, permanent magnet synchronous motor (PMSM) presently used in EV by most of the electric vehicle manufacturers due to its advantages. This paper reviews on various control methods for PMSM used in EV. Various control methods are being used for EV applications. Initially, conventional direct torque control (DTC) technique being used in controlling electric motors but it has a drawback of high torque and flux ripples. Hence, intelligent controllers are predominantly using in controlling PMSM drives.</text>
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                <text>Marulasiddappa Hallikeri Basappa, Pushparajesh Viswanathan</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i6.24236</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control </text>
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                  <text>VOL. 20, NO. 6 2022</text>
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Compressive sensing-based channel estimation for high mobile systems with delay Doppler effects</text>
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                <text>In this paper, channel overhead is reduced by exploiting channel sparsity for multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system. Where, compressive sensing (CS) based dictionary design algorithms has been adopted as a channel estimation technique in high mobile systems with minimal number of pilots, such as high-speed train (HST) systems. A novel framework design of the dictionary-based CS was proposed considering both delay and Doppler effects in order to correctly recover the channel response. The channel under consideration is a 2 by 2 space-time block code (STBC) MIMO channel. Simulation tests according to the international telecommunication union (ITU) channel model demonstrated the suitability of the proposed dictionary for estimating the channel impulse response (CIR) of a liner time varying (LTV) channel with a mobility approaches 675 Km/h related to a Doppler frequency of 1500 Hz and 2.4 GHz carrier frequency. Two CS recovery algorithms were applied;&#13;
orthogonal matching pursuit (OMP) and basis pursuit (BP), where by about 7 dB gain in signal to noise ratio (SNR) was achieved with mobility of 675 Km/h using OMP as compared to BP at a bit error rate (BER) of 10−3 with 128 OFDM subcarriers.</text>
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                <text>Khalifa A. Salim, Bayan Mahdi Sabbar, Maryam K. Abboud</text>
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              <elementText elementTextId="47770">
                <text>DOI: 10.12928/TELKOMNIKA.v20i6.24233</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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            <elementTextContainer>
              <elementText elementTextId="47774">
                <text>ISSN: 1693-6930</text>
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                <text>http://journal.uad.ac.id/index.php/TELKOMNIKA</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control </text>
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                  <text>VOL. 20, NO. 6 2022</text>
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An intelligent strabismus detection method based on convolution neural network</text>
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                <text>Convolutional neural networks, IMPA-FACE, Strabismus, Vision disorders</text>
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                <text>Strabismus is one of the widespread vision disorders in which the eyes are misaligned and asymmetric. Convolutional neural networks (CNNs) are properly designed for analyzing images and detecting texture patterns. In this paper, we proposed a system that uses deep learning CNN applications for automatically detecting and classifying strabismus disorder. The proposed system includes two main stages: first, the detection of facial eye segmentation using the viola-jones algorithm. The second stage is to map the segmented eye area according to the iris position of each eye. This method is applied to three strabismus datasets, gathered as digital images. The second section covers the segmentation of the eye region. Besides, the evaluation equations for measuring system performance. The system has undergone numerous experiments in various stages to simulate and analyze the detection performance of CNN layers through different classifiers and variant thresholds ratio. The researchers investigated the experimental outcomes during the training and testing phases and obtained promising&#13;
results that exhibit the effectiveness of the proposed system. According to the results, the accuracy of this technique reached 95.62%. </text>
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                <text>Haider Shamil Hamid, Bassam AlKindy, Amel H. Abbas, Wissam Basim Al-Kendi</text>
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              <elementText elementTextId="47756">
                <text>DOI: 10.12928/TELKOMNIKA.v20i6.24232</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control </text>
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                  <text>VOL. 20, NO. 6 2022</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
A blockchain-based Aadhar system: distributed authentication system</text>
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                <text>Aadhar authentication, Bitcoin, Blockchain, Ethereum, Smart contact, Solidity</text>
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                <text>An Aadhaar is a unique number issued to every citizen in India. Aadhar’s&#13;
current identity authentication relies on the central identities data repository (CDIR) of the unique identification authority of India (UIDAI), which is at risk of a single-point fault attack. Perhaps worse, internal attacks can tamper with the sensitive data of authenticated devices without being detected. In this paper, the proposed system utilizes emerging technology: blockchain for solving the issue of centralized authentication. The proposed system provides a distributed, secure, and tamper-proof ledger platform for Aadhar in that Aadhar is implemented using blockchain ethereum technology. The proposed system considers the unique Aadhar identification (ID) for each citizen of India and registered it on the smart contract of ethereum so that this unique ID may be authenticated by each other in a peer-to-peer network without a central authority. For securing the data, the proposed framework uses hashing technique for significant data (i.e. firmware). Blockchain stores hashed data and instantly any change in the state of the data may be possible to detect. </text>
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                <text>Vikas Goel, Mukul Aggarwal, Amit Kumar Gupta, Narendra Kumar</text>
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              <elementText elementTextId="47742">
                <text>DOI: 10.12928/TELKOMNIKA.v20i6.24231</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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Deep residual neural networks for inverse halftoning</text>
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                <text>This paper presents a simple technique to perform inverse halftoning using the deep learning framework. The proposed method inherits the usability and superiority of deep residual learning to reconstruct the halftone image into the continuous-tone representation. It involves a series of convolution operations and activation function in forms of residual block elements. We investigate the usage of pre-activation function and standard activation function in each residual block. The experimental section validates the proposed method ability to effectively reconstruct the halftone image. This section also exhibits the proposed method superiority in the inverse halftoning task compared to that of the handcrafted feature schemes and former deep learning approaches. The proposed method achieves 30.37 dB and 0.9481 on the average peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) scores, respectively. It gives the improvements around 1.67 dB and 0.0481 for those values compared to the most competing scheme.</text>
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Semi-circular compact CPW-fed antenna for ultra-wideband applications</text>
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                <text>This paper presents a simple structure and small size antenna design with dimensions of 43×47 mm2 to perform an ultra-wideband (UWB) frequency range using a semicircular co-planar waveguide (CPW). This antenna has been designed and simulated by the computer simulation technology (CST) microwave studio suit. In this work, we design an ultra-wideband antenna (about 2 GHz to 10 GHz) by feeding a semi-circular compact antenna via a co-planar waveguide for input impedance of 50 Ω. The CST simulation results show that our designed antenna has a very good impedance and radiation characteristic within the intended ultra-wideband. Because of the small size and the suitable shape, this antenna can be used in many wireless communication applications, such as a radio frequency identifier (RFID), indoor wireless local area network or wireless fidelity (WiFi), internet of things (IoT), millimeter waves communications (mmWave), global positioning system (GPS), and many applications of 6G systems. </text>
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                <text>Farhad E. Mahmood, Saad Wasmi Osman Luhaib</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i6.24229</text>
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                <text>Sri Wahyuni</text>
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Application of dual-layer phosphor geometries for enhancing the optical properties of white-light LEDs</text>
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                <text>This article compares the lumen output of two packages of two-remote&#13;
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The second package is concave dual-remote phosphor (CDRP). The dispersion qualities of the white-light-emitting diode are different as a&#13;
result of their different cover designs, leading to a disparity between the&#13;
FDRPS and CDRPS configurations. The results of the study show that the FDRPS package yields a lumen output superior to that of the CDRPS&#13;
package. In the article, we can also see how the space among the phosphor films (d1) and the space among the phosphor film and the light emitting diodes (LED) outer side (d2) might affect the light characteristics in the CDRPS model. As the indicated distances shift, the characteristics of dispersion and absorptivity in the distant phosphor film will shift as well&#13;
Such an occurrence can have an impact on chromatic uniformity as well as&#13;
optical performance in white light emitting diodes (WLEDs). If we modify&#13;
the d1 and d2 values, it is necessary to change the phosphor YAG:Ce3+&#13;
concentration in the WLEDs to keep the correlated color temperature at&#13;
8500 K.</text>
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