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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
A compressed sensing approach for antenna array calibration</text>
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                <text>Antenna arrays, Antenna measurements, Calibration, Compressed sensing, Fault diagnosis</text>
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                <text>This paper presented a compressive sensing (CS) calibration technique that simultaneously measures all the element excitations of a 2×2 active phased antenna array (APAA) instantaneously. The power patterns of the rectangular 2×2 APAA element are synchronized to orthogonally cross multiplicative sub-array system applying compressive sensing in achieving an array thinning along two 1-D sub-arrays for a fixed steered beam radiation. The far field radiation pattern direction of the 2×2 APAA is examined considering the mutual effect, complex excitation of the amplitude and phase of the antenna elements placed on the x and y axes. The unwanted array excitation with errors are calibrated using minimization vector as a standard basic pursuit problem in compressive sensing technique for the 2×2 APAA calibration. The elements amplitude and phase shift variation are compared with reference state 0 in order to evaluate the faulty error array elements. The performance evaluation of this proposed technique is measured and demonstrated to validate the effectiveness of the proposed antenna calibration technique. </text>
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                <text>Akinwale Oluwaseyi Fadamiro, Fujiang Lin</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i4.23767</text>
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                <text>Universitas Ahmad Dahlan</text>
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                <text>Sri Wahyuni</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
A new family of bidirectional DC-DC power converters with very low input and output ripples </text>
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                <text>Bidirectional DC-DC converters with very low ripple contents in the input and output sides are desirable in many applications. This paper proposes a new family of bidirectional DC-DC converters with very low input and output ripples that is derived from the conventional Cuk DC-DC converter. At first, a new family of single-phase DC-DC converter is derived. Then, extension of this family into the multiphase ones is presented. Output voltage expressions of the proposed DC-DC converters are presented. It is found that the derived DC-DC converters have lower conduction losses than the conventional DC-DC converters. Expressions of input and output ripples of the proposed DC-DC converters are then also presented. Finally, some experimental results are included to show the basic performance of the proposed converters. Thus, the outcome of the proposed DC-DC converter can be achieved by using the duty ratio is half and the multiphase technique is upper-middle inductors. It given that the current and voltage ripples of proposed DC-DC converter is very low and almost zero. </text>
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                <text>Muhammad Nuruddin Ar Rabbani, Andriazis Dahono, Arwindra Rizqiawan, Pekik Argo Dahono</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i4.24215</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;
A proposed model for text and image encryption using different techniques</text>
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                <text>DCT techniques fourth, Information security second, Encryption, MSE, PSNR, RSA3k, XOR</text>
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                <text>Data security and protection is one of the most common technologies used in the field of computer science. This is because of its great importance in all fields related to daily life, whether political, economic, and other aspects change. In this research paper, a new intelligent system that concentrates on image and text encryption and decryption is proposed. Furthermore, the image recognition rate is increased. In this paper, the Rivest Shamir Adleman 3 key (RSA3k) algorithm is used but in a new technique to encrypt and decrypt text. The proposed technique relies on using square root of public key as private key. XOR operation for colored images encryption and decryption is performed. By calculating signal to noise ratio (PSNR), mean square error (MSE), and bit error rate (BER), the most important things that we address how to provide data security for large data based on encryption techniques and increase the security of multimedia data and texture date and address the problem of time and accuracy in image matching. the results show that the quality of images after decryption is good. </text>
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                <text>Shihab A. Shawkat, Israa Al-Barazanchi</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i4.23367</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
A security services for internet of thing smart health care solutions based blockchain technology</text>
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                <text>Pervasive and ubiquitous computing has enabled people better integrate&#13;
physical things into the digital world. The internet of things (IoT) has been considerably more widely used in business and everyday life in the last decade. Innovative healthcare information and communication technologies are a vast field of research and applications that need IoT benefits, including speed, security, and low cost. The proposed modified advanced encryption standard (AES)-cipher block chaining (CBC)-based blockchain technology offers a shared key to devices that need to communicate directly with or with entities outside the smart healthcare network to give users greater control over transactions. The experiments are carried out using a Raspberry Pi 3, whereas two different sensors are employed in this case. Blockchain technology encrypts data between doctor and patient with varied user numbers. The results from experiments revealed that the proposed modified AES-CBC based blockchain technology could provide the IoT application with security services (confidentiality, integrity, and access control) with efficient execution time. </text>
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                <text>Ahmed Hashim Mohammed, Rawaa Mohammed Abdul Hussein</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i4.23765</text>
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                <text>Universitas Ahmad Dahlan</text>
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              <elementText elementTextId="46823">
                <text>Sri Wahyuni</text>
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                <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. 4 2022</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
A sink based data gathering technique by using clustering for wireless sensor networks</text>
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                <text>Clustering, Data delivery, Energy, Network, Network lifetime, Node, WSN</text>
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                <text>New advance and integrated technologies have changed the traditional&#13;
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novel data gathering techniques called a sink based data gathering&#13;
techniques (ASDG) to collect the data from the sensor nodes and further&#13;
send for decision making. Experimental results show that proposed&#13;
techniques is better than existing techniques and provide more efficient data delivery ratio with more network lifetime. The results also indicated that when using the proposed technique, the no of dead sensor nodes are less as compared to the existing ones at different rounds.</text>
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                <text>Yousra Abdul Alsahib S. Aldeen, Haider Mohammed Abdulhadi</text>
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              <elementText elementTextId="46516">
                <text>DOI: 10.12928/TELKOMNIKA.v20i4.22181</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="46520">
                <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. 4 2022</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
A voice controlled smart home automation system using artificial intelligent and internet of things </text>
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                <text>Arduino, AI, Chat form, IoT, NLP, Raspberry Pi</text>
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                <text>The objective of this work is to take a step further in this direction by&#13;
incorporating voice control and artificial intelligence (AI) into internet of&#13;
things (IoT)-based smart home systems to create more efficient automated smart home systems. Accordingly, a home automation system proposal is presented, in which the related functions can be controlled by voice commands using an android or web application via a chat form. The user issues a voice command, which is deciphered by natural language processing (NLP). To accommodate the user’s request, the NLP classifies it into operation commands. Arduino and Raspberry Pi are used to translate the commands extracted from NLP into reality. Based on this, home applications can be controlled. Also, the utilities consumption could be calculated, saved, and paid on time. This is in addition to the introduction of a machine learning (ML)-based recommendation system for automated home appliance control. In this approach, the mobile or web application is considered as the central controller, deciding the appropriate actions to fulfill the user’s desires. The presented work has been put into practice and tested. It proved to be applicable, as well as having the potential for making home life more&#13;
comfortable, economic, and safe. </text>
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              <elementText elementTextId="46795">
                <text>Mohamed A. Torad, Belgacem Bouallegue, Abdelmoty M. Ahmed</text>
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            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="46796">
                <text>DOI: 10.12928/TELKOMNIKA.v20i4.23763</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>VOL. 20, NO. 4 2022</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control &#13;
Application of a wireless apnea monitoring device for crisis alertness and sleep diagnosis </text>
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                <text>Apnea hypopnea index, Automation, Sleep apnea diagnosis, Wireless</text>
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                <text>Over the past five decades, obstructive sleep apnea has been noted as a&#13;
prevalent symptom in adults with escalated health conditions like stroke, obesity, high blood pressure, cardiovascular complications and chronic kidney diseases; to mention but a few. Apnea hypopnea index (AHI) is the average number of apnea or hypopnea events which occur during a complete sleep cycle per hour. It is a measure of determining the severity of sleep apnea, where an index range of 5 to 15 indicates mild, 15 to 30, moderate and above 30 denotes severe sleep apnea. In a bid to perform this diagnosis, several approaches have been considered. In this study vibrating sensor module and an Arduino Uno Rev3 microcontroller which retrieve breathing status data during sleep and identifies apnea events is proposed. The developed monitoring device displays the apnea count, effectively, which can be used to determine AHI. It also incorporates a Bluetooth module for wireless, real-time data monitoring which allows for more comfortable usability. The result is the successful implementation of an efficient, cost-effective system which can be used for sleep apnea diagnosis and provides preventive health care measures. </text>
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                <text>Sri Wahyuni</text>
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                <text>TELKOMNIKA Telecommunication, Computing, Electronics and Control </text>
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                  <text>VOL. 20, NO. 4 2022</text>
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Automated brain tumor detection of MRI image based on hybrid image processing techniques</text>
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                <text>Arithmetic operations, Brain MRI, Contrast correction, Morphological operations, Skull stripping, Tumor</text>
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                <text>Primary challenges are the identification, segmentation, and extraction of the afflicted area from the scanning of magnetic resonance. However, it is a time-consuming and tiresome for clinical specialists. In this paper,&#13;
an automated brain tumor system is proposed. The proposed system employs hybrid image processing techniques such as contrast correction, histogram normalization, thresholding techniques, arithmetic, and morphological operations to quarantine nearby organs and other tissue from the brain for improving the localization of the affected region. At first, the skull stripping process is proposed to segregate the non-designated regions to extract the designated brain regions. Those resultant brain region images are further subjected to discover the brain tumor. The planned scheme is studied on the magnetic resonance (MR) images with the use of T1, T2, T1c, and fluid-attenuated inversion recovery (FLAIR). The proposed hybrid method employed. The results reveal that the proposed method is quite efficient to extract the tumor region. The accuracy rate for segmentation and separation of area of interest in brain tumor reached to 95%. Finally, the significance of the proposed procedure is confirmed using the real image clinical dataset got from ten patients were diagnosed as begin, malignant, and metastatic brain tumors in Al-Yarmouk and Baghdad teaching hospital in Baghdad, Iraq. </text>
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                <text>Lina A. Salman, Ashwaq T. Hashim, Ahmed M. Hasan</text>
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                <text>DOI: 10.12928/TELKOMNIKA.v20i4.22760</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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Brain tumor segmentation using multi-level Otsu thresholding and Chan-Vese active contour model </text>
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                <text>Research on brain tumor segmentation has been developed, ranging from threshold-based methods to the use of the deep learning algorithm. In this study, we proposed a region-based brain tumor segmentation method, namely the active contour model (ACM). Tumor segmentation was carried out using fluid attenuated inversion recovery (FLAIR) modality magnetic resonance imaging (MRI) image data obtained from the multimodal brain tumor image segmentation benchmark (BRATS) 2015 dataset of 86 images. The initial stage of our segmentation method is to find the initial initialization point/area for the ACM algorithm using multi-level Otsu thresholding, with the level used in this study is 3 levels. After the initial initialization area has been obtained, the segmentation process is continued with ACM which explores the tumor area to obtain a full and accurate tumor area result. The results of this study obtained dice similarity (DS) for our study of 0.7856 with a total time required of 28.080722 seconds, which better than other method that we also compared with ours, 0.75 compared to 0.78 in term of DS. </text>
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                <text>Heru Pramono Hadi, Edi Faisal, Eko Hari Rachmawanto</text>
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              <elementText elementTextId="46454">
                <text>DOI: 10.12928/TELKOMNIKA.v20i4.21679</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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