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31,456 Article Results

Ananas comosus crown image thresholding and crop counting using a colour space transformation scheme

10.12928/telkomnika.v18i5.13895
Wan Nurazwin Syazwani; Universiti Teknologi MARA Rahimi , Muhammad Asraf; Universiti Teknologi MARA H. , Megat Syahirul Amin Megat; Universiti Teknologi MARA Ali
The implementation of unmanned aerial vehicle (UAV) technology having image processing capabilities provides an alternative way to observe pineapple crowns captured from aerial images. In the majority of pineapple plantations, an agricultural officer will physically count the crop yield prior to harvesting the Ananas Comosus, also known as pineapple. This process is particularly evident in large plantation areas to accurately identify pineapple numbers. To alleviate this issue, given it is both time-consuming and arduous, automating the process using image processing is suggested. In this study, the possibilities and comparisons between two techniques associated with an image thresholding scheme known as HSV and L*A*B* colour space schemes were implemented. This was followed by determining the threshold by applying an automatic counting (AC) method to count the crop yield. The results of the study found that by applying colour thresholding for segmentation, it improved the low contrast image due to different heights and illumination levels on the acquired colour image. The images that were acquired using a UAV revealed that the best distance for capturing the images was at the height of three (3) metres above ground level. The results also confirm that the HSV colour space provides a more efficient approach with an average error increment of 47.6% when compared to the L*A*B*colour space.
Volume: 18
Issue: 5
Page: 2472-2479
Publish at: 2020-10-01

Kernal based speaker specific feature extraction and its applications in iTaukei cross language speaker recognition

10.12928/telkomnika.v18i5.14655
Satyanand; Fiji National University Singh , Pragya; Fiji National University Singh
Extraction and classification algorithms based on kernel nonlinear features are popular in the new direction of research in machine learning. This research paper considers their practical application in the iTaukei automatic speaker recognition system (ASR) for cross-language speech recognition. Second, nonlinear speaker-specific extraction methods such as kernel principal component analysis (KPCA), kernel independent component analysis (KICA), and kernel linear discriminant analysis (KLDA) are summarized. The conversion effects on subsequent classifications were tested in conjunction with Gaussian mixture modeling (GMM) learning algorithms; in most cases, computations were found to have a beneficial effect on classification performance. Additionally, the best results were achieved by the Kernel linear discriminant analysis (KLDA) algorithm. The performance of the ASR system is evaluated for clear speech to a wide range of speech quality using ATR Japanese C language corpus and self-recorded iTaukei corpus. The ASR efficiency of KLDA, KICA, and KLDA technique for 6 sec of ATR Japanese C language corpus 99.7%, 99.6%, and 99.1% and equal error rate (EER) are 1.95%, 2.31%, and 3.41% respectively. The EER improvement of the KLDA technique-based ASR system compared with KICA and KPCA is 4.25% and 8.51% respectively.
Volume: 18
Issue: 5
Page: 2488-2497
Publish at: 2020-10-01

Fast lightweight block cipher design with involution substitution permutation network (SPN) structure

10.11591/ijeecs.v20.i1.pp361-369
Omar A. Dawood
In the present paper, a new cryptographic lightweight algorithm has been developed for the internet of things (IoT) applications. The submitted cipher designed with the involution Substitution Permutation Network SPN structure. The involution structure means that the same encryption algorithm is used in the decryption process except the ciphering key algorithm is applied in reverse order. The introduced algorithm encrypts the data with a block size of 128-bit 192-bit or 256-bit, which iterative with 10, 12 and 14-rounds respectively similar to the AES cipher. The design aspect supports an elegant structure with a secure involution round transformation. The main round is built without S-Box stage instead that it uses the on-fly immediate computing stage and the involution of mathematical invertible affine equations. The proposed cipher is adopted to work in a restricted environment and with limited resources pertaining to embedded devices. The proposed cipher introduces an accepted security level and reasonable gate equivalent (GE) estimation with fast implementation.
Volume: 20
Issue: 1
Page: 361-369
Publish at: 2020-10-01

A survey on security and privacy issues in IoV

10.11591/ijece.v10i5.pp5409-5419
Tanvi Garg , Navid Kagalwalla , Prathamesh Churi , Ambika Pawar , Sanjay Deshmukh
As an up-and-coming branch of the internet of things, internet of vehicles (IoV) is imagined to fill in as a fundamental information detecting and processing platform for astute transportation frameworks. Today, vehicles are progressively being associated with the internet of things which empower them to give pervasive access to data to drivers and travelers while moving. Be that as it may, as the quantity of associated vehicles continues expanding, new prerequisites, (for example, consistent, secure, vigorous, versatile data trade among vehicles, people, and side of the road frameworks) of vehicular systems are developing. Right now, the unique idea of vehicular specially appointed systems is being changed into another idea called the internet of vehicles (IoV). We talk about the issues faced in implementing a secure IoV architecture. We examine the various challenges in implementing security and privacy in IoV by reviewing past papers along with pointing out research gaps and possible future work and putting forth our on inferences relating to each paper.
Volume: 10
Issue: 5
Page: 5409-5419
Publish at: 2020-10-01

A novel method for digital data encoding-decoding

10.12928/telkomnika.v18i5.14279
Amjad Y.; Al-Balqa Applied University Hindi
Cryptography is one of the paramount and most vital data treatment processes, it allows us to be secure in our electronic transactions. The process of cryptography protects our valuable data such as private account numbers and transaction amounts, electronic signatures replace handwritten signatures or credit card authorizations, and public-key encryption provides confidentiality. The objective of data encryption is to keep digital data confidentiality save as it is stored on computer systems and transferred using the internet or other computer networks. In this paper we will focus in enhancing security level of the encryption-decryption process by introducing a novel method, which uses any digital color image to encode-decode secret message, the using of a special key to encrypt-decrypt the encoded-decoded message, the color image will be known only by the transmitter and receiver to keep the process of data treatment confidential, the obtained experimental results by the proposed method will be analyzed to prove the enhancement in process efficiency and confidentiality.
Volume: 18
Issue: 5
Page: 2772-2779
Publish at: 2020-10-01

Gender voice classification with huge accuracy rate

10.12928/telkomnika.v18i5.13717
Mustafa Sahib; Al Muthanna University Shareef , Thulfiqar; Al Muthanna University Abd , Yaqeen S.; Al-Esraa University College Mezaal
Gender voice recognition stands for an imperative research field in acoustics and speech processing as human voice shows very remarkable aspects. This study investigates speech signals to devise a gender classifier by speech analysis to forecast the gender of the speaker by investigating diverse parameters of the voice sample. A database has 2270 voice samples of celebrities, both male and female. Through Mel frequency cepstrum coefficient (MFCC), vector quantization (VQ), and machine learning algorithm (J 48), an accuracy of about 100% is achieved by the proposed classification technique based on data mining and Java script.
Volume: 18
Issue: 5
Page: 2612-2617
Publish at: 2020-10-01

Integrated bio-search approaches with multi-objective algorithms for optimization and classification problem

10.12928/telkomnika.v18i5.15141
Mohammad Aizat; Universiti Malaysia Terengganu Basir , Mohamed Saifullah; Universiti Malaysia Terengganu (UMT) Hussin , Yuhanis; Universiti Utara Malaysia Yusof
Optimal selection of features is very difficult and crucial to achieve, particularly for the task of classification. It is due to the traditional method of selecting features that function independently and generated the collection of irrelevant features, which therefore affects the quality of the accuracy of the classification. The goal of this paper is to leverage the potential of bio-inspired search algorithms, together with wrapper, in optimizing multi-objective algorithms, namely ENORA and NSGA-II to generate an optimal set of features. The main steps are to idealize the combination of ENORA and NSGA-II with suitable bio-search algorithms where multiple subset generation has been implemented. The next step is to validate the optimum feature set by conducting a subset evaluation. Eight (8) comparison datasets of various sizes have been deliberately selected to be checked. Results shown that the ideal combination of multi-objective algorithms, namely ENORA and NSGA-II, with the selected bio-inspired search algorithm is promising to achieve a better optimal solution (i.e. a best features with higher classification accuracy) for the selected datasets. This discovery implies that the ability of bio-inspired wrapper/filtered system algorithms will boost the efficiency of ENORA and NSGA-II for the task of selecting and classifying features.
Volume: 18
Issue: 5
Page: 2421-2431
Publish at: 2020-10-01

Transmission spectra of single ring coupled-waveguide resonator configuration by finite difference time domain method

10.12928/telkomnika.v18i5.12621
Haryana bin Mohd; Universiti Teknologi MARA Hairi , Saktioto; Universitas Riau Saktioto , Romi Fadli; Universitas Riau Syahputra , Okfalisa; Universitas Islam Negeri Sultan Syarif Kasim Okfalisa , Sofia; Universitas Riau Anita
Development of optical waveguide resonators have greatly expanded and continues to grow since they have kinds potential applications such as wavelength filtering, switching, coupling and multiplexing. One of resonators, coupled waveguides, ring resonators are designed and operated using various coupling configurations. Ring resonators can be particularly used as wavelength filter if the wavelength can fit a whole multiple time in the circumference of the ring. This article proposes to investigate the transmission spectra from the power source and amplify it in linearized ring resonator configurations and varies the input amplitude on five different wavelengths. With finite difference time domain method, the geometry and power source are simulated to obtain the better result and configuration. The results show the intensity phenomena of filtering in optical circuit.
Volume: 18
Issue: 5
Page: 2251-2256
Publish at: 2020-10-01

A new eliminating EOG artifacts technique using combined decomposition methods with CCA and H.P.F. techniques

10.12928/telkomnika.v18i5.14143
Fadia Noori Hummadi; University of Baghdad Al-Nuaimy
Normally, the collected EEG signals from the human scalp cortex by using the non-invasive EEG collection methods were contaminated with artifacts, like an eye electrical activity, leading to increases in the challenges in analyzing the electroencephalogram for obtaining useful clinical information. In this paper, we do a comparison of using two decomposing methods (DWT and EMD) with CCA technique or High Pass Filter, for the elimination of eye artifacts from EEG. The eye artifacts (EOG) signals were extracted from the un-cleaned or raw EEG signals by DWT and EMD with CCA approach or H.P.F. The root means square error ratio of the uncontaminated EEG signal to the contaminated EEG signal with eye artifacts were the performance indicators for both elimination methods, which indicate that the combined CCA method outperforms the combined H.P.F method in the elimination of eye blinking contamination artifact from the EEG signal.
Volume: 18
Issue: 5
Page: 2580-2586
Publish at: 2020-10-01

Coplanar waveguide low pass filter based on square complementary split ring resonator with wide rejection

10.12928/telkomnika.v18i5.15862
Mohammed; University Hasan I Bendaoued , Rachid; University Hasan I Mandry , Larbi El; University Hasan I Abdellaoui , Aytouna; Abdelmalek Essaadi University Fouad , Mohamed; IETR Rennes Latrach , Ahmed; University of Quebec in Outaouais Lakhssassi
In this paper, we present a novel coplanar waveguide low pass filter (LPF)structure based on the use of square complementary split ring resonators (CSRRs) in order to enhance the performances of a low pass filter. Especially, to enlarge the bandwidth of the LPF, the insertion losses and to increase the rejection of the LPF. The CSRRs are optimised and inserted periodically along the center conductor of the CPW line with a CPW ground integrating stubs permitting to enlarge the bandwidth. The simulation results of this filter show a -3 dB cut-off frequency equal to fc = 5.28 GHz. The designed filter has a good rejection in the stop band which below -20 dB and presents a good insertion loss in the bandwidth. The proposed filter has been fabricated and tested which give a good agreement between simulation and measurement results, the whole dimensions of the validated filter are 35.48x21.16 mm2. The originality of this work is the wide rejection band and the miniature dimensions.
Volume: 18
Issue: 5
Page: 2314-2319
Publish at: 2020-10-01

Towards IR4.0 implementation in e-manufacturing: artificial intelligence application in steel plate fault detection

10.11591/ijeecs.v20.i1.pp430-436
Adeleke Abdullahi , Noor Azah Samsudin , Mohd Rasidi Ibrahim , Muhammad Syariff Aripin , Shamsul Kamal Ahmad Khalid , Zulaiha Ali Othman
Fault detection is the task of discovering patterns of a certain fault in industrial manufacturing. Early detection of fault is an essential task in industrial manufacturing. Traditionally, faults are detected by human experts. However, this method suffers from cost and time. In this era of Industrial revolution IR 4.0, machine learning (ML) methods and techniques are developed to solve fault detection problem. In this study, three standard ML models: LR, NB, and SVM are developed for the classification problem. The experimental dataset used in this study consists of steel plates faults. The dataset is retrieved from UCI machine learning repository. Three standard evaluation methods: accuracy, precision, and recall are validated on the classification models. Logistic regression (LR) model achieved the highest accuracy and precision scores of 94.5% and 0.756 respectively. In addition, the SVM model had the highest recall score of 0.317. The results showed the significant impact of AI/ML approach in steel plates fault diagnosis problem. 
Volume: 20
Issue: 1
Page: 430-436
Publish at: 2020-10-01

Optimation economic order quantity method for a support system reorder point stock

https://ijece.iaescore.com/index.php/IJECE/article/view/22000
Linda Perdana Wanti , Ratih Hafsarah Maharrani , Nur Wachid Adi Prasetya , Eka Tripustikasari , Ganjar Ndaru Ikhtiagung
The success of a company is measured by the ability to provide goods and services at the right time and place. Besides, one of the factors of the company's progress is also supported by inventory management which functions to control the company's inventory by neither hoarding lots of products nor running out of products. The development of technology requires a company's inventory management that is fast, precise and accurate to support its’ performance. In fact, some companies have difficulty in determining the stock of their goods production so that it impedes the fulfillment of consumer needs in the event of high market demand. This study is to determine the reorder point stock of a company that determines the number of purchases and sales of the company's products, therefore the amount of expenses and income can be presented to the board of directors to be followed up quickly and accurately. The method used is a statistical approach to the economic quantity model where safety stock analysis is first performed. This method is used to put the company's products to the inventory so that there are no excess or even shortages of products. System development method used is a user centered design, which is the most suitable to the study. The output of the activity is information in the form of advice to the company leaders in making decisions about production planning, controlling stock inventory, detailing market demand quickly, precisely and accurately and developing a decision support system that is made by taking into account the details of user needs.
Volume: 10
Issue: 5
Page: 4992-5000
Publish at: 2020-10-01

An innovative IoT service for medical diagnosis

10.11591/ijece.v10i5.pp4918-4927
Safia Abbas
Due to the misdiagnose of diseases that increased recently in a scarily manner, many researchers devoted their efforts and deployed technologies to improve the medical diagnosis process and reducing the resulted risk. Accordingly, this paper proposed architecture of a cyber-medicine service for medical diagnosis, based internet of things (IoT) and cloud infrastructure (IaaS). This service offers a shared environment for medical data, and extracted knowledge and findings between patients and doctors in an interactive, secured, elastic and reliable way. It predicts the medical diagnosis and provides an appropriate treatment for the given symptoms and medical conditions based on multiple classifiers to assure high accuracy. Moreover, it entails different functionalities such as on-demand searching for scientific papers and diseases description for unrecognized combination of symptoms using web crawler to enrich the results. Where such searching results from crawler, are processed, analyzed and added to the resident knowledge base (KB) to achieve adaptability and subsidize the service predictive ability.
Volume: 10
Issue: 5
Page: 4918-4927
Publish at: 2020-10-01

The cubic root unscented kalman filter to estimate the position and orientation of mobile robot trajectory

10.11591/ijece.v10i5.pp5243-5250
Omar Bayasli , Hassen Salhi
In this paper we introduce a Cubic Root Unscented Kalman Filter (CRUKF) compared to the Unscented Kalman Filter (UKF) for calculating the covariance cubic matrix and covariance matrix within a sensor fusion algorithm to estimate the measurements of an omnidirectional mobile robot trajectory. We study the fusion of the data obtained by the position and orientation with a good precision to localize the robot in an external medium; we apply the techniques of Kalman Filter (KF) to the estimation of the trajectory. We suppose a movement of mobile robot on a plan in two dimensions. The sensor approach is based on the Cubic Root Unscented Kalman Filter (CRUKF) and too on the standard Unscented Kalman Filter (UKF) which are modified to handle measurements from the position and orientation. A real-time implementation is done on a three-wheeled omnidirectional mobile robot, using a dynamic model with trajectories. The algorithm is analyzed and validated with simulations.
Volume: 10
Issue: 5
Page: 5243-5250
Publish at: 2020-10-01

Modeling and control of double star induction machine by active disturbance rejection control

10.12928/telkomnika.v18i5.14377
Aichetoune; Mohammed V University Oumar , Rachid; Laboratory of Innovation in Management and Engineering for Enterprise (LIMITE) Chakib , Mohamed; Mohammed V University Cherkaoui
This paper aims to contribute to the modeling and control of the double star induction machine (DSIM) by a robust method called active disturbance rejection control (ADRC). The ADRC has become in the last decade one of the most important techniques of regulation. This method is based on the use of an ESO (Extended State Observer) which estimates in real-time and at the same time the external disturbances and the errors due to the variations of the parameters of the machine and to the uncertainties of modeling. The two stators of DSIM are powered by three-phase inverters based on transistors and MLI control and the entire system is modeled in Park's reference. We analyze in the Matlab/Simulink environment the dynamic behavior of the system and the different ADRC controllers under different operating conditions. The result has demonstrated the performance and effectiveness of the ADRC.
Volume: 18
Issue: 5
Page: 2718-2728
Publish at: 2020-10-01
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