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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>DOI: 10.12928/TELKOMNIKA.v20i6.24231</text>
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                <text>Sri Wahyuni</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
A comparative study of mango fruit pest and disease recognition</text>
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                <text>CNN, InceptionResNet-V2, Inception-V3, Mango pest and disease, ResNet50, VGG16</text>
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                <text>Mango is a popular fruit for local consumption and export commodity.&#13;
Currently, Indonesian mango export at 37.8 M accounted for 0.115% of&#13;
world consumption. Pest and disease are the common enemies of mango that degrade the quality of mango yield. Specialized treatment in export&#13;
destinations such as gamma-ray in Australia, or hot water treatment in&#13;
Korea, demands pest-free and high-quality products. Artificial intelligence helps to improve mango pest and disease control. This paper compares the deep learning model on mango fruit pests and disease recognition. This research compares Visual Geometry Group 16 (VGG16), residual neural network 50 (ResNet50), InceptionResNet-V2, Inception-V3, and DenseNet architectures to identify pests and diseases on mango fruit. We implement transfer learning, adopt all pre-trained weight parameters from all those architectures, and replace the final layer to adjust the output. All the architectures are re-train and validated using our dataset. The tropical mango dataset is collected and labeled by a subject matter expert. The VGG16 model achieves the top validation and testing accuracy at 89% and 90%, respectively. VGG16 is the shallowest model, with 16 layers; therefore, the model was the smallest size. The testing time is superior to the rest of the experiment at 2 seconds for 130 testing images. </text>
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                <text>Kusrini, Suputa, Arief Setyanto, I Made Artha Agastya, Herlambang Priantoro, Sofyan Pariyasto</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i6.21783</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</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 coverless image steganography based on robust image wavelet hashing</text>
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                <text>Coverless steganography, Discrete wavelet transform, Information hiding, Information security, Steganography</text>
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                <text>Since the concept of coverless information hiding was proposed, it has been greatly developed due to its effectiveness of resisting the steganographic tools. In this paper, a new coverless steganography is presented to hide the secret data in a more secure way and to enhance the robustness against attacks. This method depends on frequency domain. The embedding process consists of several steps. Firstly, the secret data is divided into no overlapping segments. Secondly, a set of images is collected to find appropriate images to be stego images. Thirdly, to build a hash sequence for an image, a powerful hashing algorithm is used. Fourthly, for each image hash sequence, the inverted index structure is created. Fifthly, choose the image which its hash equivalent to the secret data segment. Several tests are done to measure the robustness of the proposed method. The results of the experiments reveal that the proposed strategy is resistant to a variety of image processing attacks such as joint photographic experts group (JPEG)&#13;
compression, noise, low pass filtering, scaling, rotation and median and&#13;
mean filter, brightness, and sharpening. </text>
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                <text>Nadia A. Karim, Suhad A. Ali, Majid Jabbar Jawad</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i6.23596</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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A dynamic S-box generation based on a hybrid method of new chaotic system and DNA computing </text>
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                <text>S-box is one of the most significant structures used to construct encryption that is strong and resistant to attacks in encryption algorithms. The new 4D-hyper chaotic system and deoxyribonucleic acid (DNA) computing are used in this paper to provide a new dynamic S-box generating approach. The 4D generated numbers are processed to generate a hexadecimal number that will encode using the DNA coding method and using addition, subtraction, and exclusive-or operations to produce the final DNA string decoded to make the S-Box. The dynamic form of s-boxes is represented by a minor change in the initial conditions of the proposed chaotic method that will generate dynamic sequences of numbers. The proposed method enhances the security criteria of the block ciphers. The S-box testing criteria were done like strict avalanche, balanced, and bit independence criteria, in addition to differential approximation probability and linearity approximation probability, to test the security of the new S-Box. The results show that the new S-box has good security and is resistant to attacks. </text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i6.23449</text>
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                <text>Sri Wahyuni</text>
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                <text>ISSN: 1693-6930</text>
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A proposal model using deep learning model integrated with knowledge graph for monitoring human behavior in forest protection </text>
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                <text>In conventional monitoring of human behavior in forest protection, deep&#13;
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                <text>Van Hai Pham, Quoc Hung Nguyen, Thanh Trung Le, Thi Xuan Dao Nguyen, Thi Thuy Kieu Phan</text>
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An intelligent strabismus detection method based on convolution neural network</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>DOI: 10.12928/TELKOMNIKA.v20i6.24232</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;
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Cloud-based control system: a bibliometric analysis</text>
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                <text>Network control system (NCS) approaches for distributed closed-loop&#13;
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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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