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TELKOMNIKA (Telecommunication Computing Electronics and Control)
Published by Universitas Ahmad Dahlan
ISSN : 16936930     EISSN : 23029293     DOI : 10.12928
Core Subject : Science,
Computer Science & IT
Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of submissions that TELKOMNIKA has received during the last few months the duration of the review process can be up to 14 weeks. Communication Engineering, Computer Network and System Engineering, Computer Science and Information System, Machine Learning, AI and Soft Computing, Signal, Image and Video Processing, Electronics Engineering, Electrical Power Engineering, Power Electronics and Drives, Instrumentation and Control Engineering, Internet of Things (IoT)
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 25 Documents
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Search results for , issue "vol 21, no 2: april 2023" : 25 Documents clear
Driving cycle development methods: case study in Malaysia Nurru Anida Ibrahim; Siti Norbakyah Jabar; Arunkumar Subramaniam; Wan Nural Jawahir Wan Yussof; Salisa Abdul Rahman
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 2: April 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i2.24265

Abstract

Over the years, many models have been created to estimate pollution inventories and fuel usage. These models can be divided into two types: travel-based and fuel-based. One of the most used travel-based models for estimating emission inventories is driving cycles. It can be used for a variety of different things, such as establishing pollution regulations, traffic control, and calculating journey time. For these goals, researchers have previously attempted to use easily available, well-established driving cycles. In many ways, however, the local environment differs greatly from that of the driving cycle’s genesis. As a result, these cycles’ applications have failed to provide high-quality results. This research aims to analyse the various approaches utilised for driving cycle construction in various locations of Malaysia under varied operational situations.
Ensemble learning approach for multi-class classification of Alzheimer’s stages using magnetic resonance imaging Ambily Francis; Immanuel Alex Pandian
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 2: April 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i2.23352

Abstract

Alzheimer’s disease (AD) is a gradually progressing neurodegenerative irreversible disorder. Mild cognitive impairment convertible (MCIc) is the clinical forerunner of AD. Precise diagnosis of MCIc is essential for effective treatments to reduce the progressing rate of the disease. The other cognitive states included in this study are mild cognitive impairment non-convertible (MCInc) and cognitively normal (CN). MCInc is a stage in which aged people suffer from memory problems, but the stage will not lead to AD. The classification between MCIc and MCInc is crucial for the early detection of AD. In this work, an algorithm is proposed which concatenates the output layers of Xception, InceptionV3, and MobileNet pre-trained models. The algorithm is tested on the baseline T1-weighted structural magnetic resonance imaging (MRI) images obtained from Alzheimer’s disease neuroimaging initiative database. The proposed algorithm provided multi-class classification accuracy of 85%. Also, the proposed algorithm gave an accuracy of 85% for classifying MCIc vs MCInc, an accuracy of 94% for classifying AD vs CN, and an accuracy of 92% for classifying MCIc vs CN. The results exhibit that the proposed algorithm outruns other state-of-the-art methods for the multi-class classification and classification between MCIc and MCInc.
Research on advancing chromatic reproduction and luminosity of a WLED using triple-layer remote phosphor arrangement Ha Thanh Tung; Huu Phuc Dang
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 2: April 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i2.24744

Abstract

In this study, the use of triple-sheet phosphor arrangement (TRP) in performing significant improvements to both color quality and luminous flux of white light emitting diode (WLEDs) is introduced. The phosphor layer of CaLaB3O7:Ce3+,Mn2+ is to accomplish green-spectra enhancement for the boost of luminous efficacy (LE), while MgB2O4:Mn2+ red phosphor layer is for red-spectra enhancement to better color rendering index (CRI) of WLEDs. The changes in these two phosphors’ concentrations present considerable effects on the yellow phosphor YAG:Ce3+ concentration, the color quality scale (CQS), CRI, and LE. Findings display the decrease of YAG:Ce3+ concentration accompanying the increase of red and green phosphor concentrations, for the stabilized average correlated color temperatures (ACCTs) between 6000 and 8500 K. Results also reveal that greater content of MgB2O4:Mn2+ leads to greater CRI value. Meanwhile using the increasing CaLaB3O7:Ce3+,Mn2+ concentration, the CRI lowers considerably. CQS, on the other hand, can increase with CaLaB3O7:Ce3+,Mn2+ concentration from 10% to 14%. Especially, given the enhancement for the CRI as well as CQS, LE value will surge to more than 40% due to the reduction of scattering light and the addition of green light. The outcome of the study is a priceless reference for light emitting diode (LED) producers.
Inverse modeling of few-mode fiber for high-speed optical communication networks Bhagyalaxmi Behera; Shailendra Kumar Varshney; Mihir Narayan Mohanty
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 2: April 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i2.23773

Abstract

Few-mode fibers have been used in contemporary communication with mode multiplexing and space-division-multiplexing techniques to enhance the capacity crunch in recent communication links. The design parameters of the proposed fiber are predicted through machine learning-based inverse design approach, using regression model. The proposed few-mode fibre profile parameters are predicted with an accuracy of 99.95% to guide five to ten modes with weak coupling among the guided modes. In second phase of this work, the authors used a finite difference method-based solver to obtain the modal characteristics of the proposed fibre with predicted parameters for six guided modes, namely, LP01, LP11, LP21, LP31, LP41, and LP51. The numerical simulation results show that the predicted profile parameter maximizes effective mode-area and minimizes the inter-channel crosstalk for mode division multiplexing transmission over C-band. Besides this, the proposed ring-core few-mode fiber also exhibits nearly zero-dispersion for LP01 mode at 1550 nm along with low dispersion for other higher-order modes. Finally, an intensity-modulation and direct-detection mode multiplexed transmission link without erbium-doped fiber amplifier is established with six-spatial channels over 50 km and an attenuation of 0.18 dB/km to achieve minimum bit-error-rate of 4.45×10-9.
Optimised coordinate generation for Arduino-based focus and motion control system for deployment in time-lapse photography Johannes Jacobus Myburgh; Nicolaas Johannes Luwes
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 2: April 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i2.22198

Abstract

This paper demonstrated the design and implementation of a unique algorithm used to generate interim coordinates for focus transitions in time-lapse photography. Through a prototype design methodology, the unique algorithm was developed to function within the limitations imposed by a low-cost 8-bit microcontroller for the development of a cost-effective focus and motion control system for deployment in photographic higher education. Through conceptualization and virtualization in MathLab and comparison with values generated in simulated real-world use-case, the proposed algorithm was tested for function and efficacy in generating interim coordinates that included focus coordinate estimation to facilitate smooth non-linear motion with focus transitions during image sequence capture. The 8-bit Arduino Mega 2560 proved capable of completing calculations required by the developed algorithm and generated coordinate data sets identical to sets generated in simulation. The generated coordinated illustrated effective user-defined control over motion and the smoothness of focus transitions. The developed algorithm is thus capable of facilitating the required movement and focus transition coordinate calculation and estimation required while deployed on a low-cost 8-bit microcontroller and is well suited for deployments in time-lapse capture applications.
Hybrid convolutional neural networks-support vector machine classifier with dropout for Javanese character recognition Diyah Utami Kusumaning Putri; Dinar Nugroho Pratomo; Azhari Azhari
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 2: April 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i2.24266

Abstract

This research paper explores the hybrid models for Javanese character recognition using 15600 characters gathered from digital and handwritten sources. The hybrid model combines the merit of deep learning using convolutional neural networks (CNN) to involve feature extraction and a machine learning classifier using support vector machine (SVM). The dropout layer also manages overfitting problems and enhances training accuracy. For evaluation purposes, we also compared CNN models with three different architectures with multilayer perceptron (MLP) models with one and two hidden layer(s). In this research, we evaluated three variants of CNN architectures and the hybrid CNN-SVM models on both the accuracy of classification and training time. The experimental outcomes showed that the classification performances of all CNN models outperform the classification performances of both MLP models. The highest testing accuracy for basic CNN is 94.2% when using model 3 CNN. The increment of hidden layers to the MLP model just slightly enhances the accuracy. Furthermore, the hybrid model gained the highest accuracy result of 98.35% for classifying the testing data when combining model 3 CNN with the SVM classifier. We get that the hybrid CNN-SVM model can enhance the accuracy results in the Javanese characters recognition.
Wearable sensor network for lower limb angle estimation in robotics applications Andres L. Jutinico; Gustavo A. R. Rodriguez; Julian R. Rolando Camargo Lopez
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 2: April 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i2.23483

Abstract

In human-robot interaction, sensors are relevant in guaranteeing stability and high performance in real-time applications. Nonetheless, accuracy and portable sensors for robots usually have high costs and little flexibility to process signals with free software. Therefore, we propose a wearable sensor network to measure lower limb angular position in human-robot interaction systems. The methodology employed to achieve the aim consisted in implementing a wireless network using low-cost devices, verifying design requirements, and making a validation via a proof of concept. The requirements to design the network include low loss of information, real-time communication, and sensor fusion to estimate the angular position using a gyroscope and accelerometer. Hence, the sensor network developed has a client-server architecture based on ESP8266 microcontrollers. In addition, this network uses the standard 802.11 b/g/n to transmit angular velocity and acceleration measures. Furthermore, we implement the user datagram protocol (UDP) protocol to operate in real-time with a sample time of 10 ms. Finally, we implement a proof of concept to show the system’s effectiveness. Thus, we use the Kalman filter to estimate the angular position of the foot, shin, thigh, and hip. Results indicate that the implemented sensor network is suitable for real-time robotic applications.
Medium access in cloud-based for the internet of things based on mobile vehicular infrastructure Yassine Sabri; Najib El Kamoun
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 2: April 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i2.24745

Abstract

Smart cities are made up of a large number of smart, intelligent gadgets that can sense, compute, act, and communicate. Focusing on how data is transferred between sensory devices and applications in the internet of things (IoT), and cyber-physical systems have led to 5G/IoT integration. This paper proposes a revolutionary architecture for mobile vehicular cloud infrastructure that takes variable weather, road, and traffic circumstances into consideration. It proposes a dynamic speed management system for smart cities. To optimize system flexibility and reduce costs, the system makes advantage of the most recent advancements in wireless communication and utilizes current telecommunication infrastructures utilized in data streaming, sound, and video. The study presents an internet protocol (IP) real-time subsystem-network-based framework for requesting bandwidth from free wireless channel resources using the channell quality indicator channel.
A novel Ethernet based processing system for remote source harmonic detection Mazin R. Khalil; Laith A. Mohammed; Omar N. Yousif
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 2: April 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i2.24091

Abstract

This work is carried out to objectively establish a new method to detect harmonics and measure the total harmonic distortion (THD) in a remote source, such as a high voltage transformer. The proposed approach utilized embedded design techniques to construct an embedded processor system with Ethernet intellectual property core to acquire data from a remote harmonics source. The designed system has several notable merits, namely, it is portable that can be applied in the work field, and it avoids workers from being subject to a hazard high voltage shock as well as its simplicity and high accuracy. The harmonics detection and analysis are achieved by inserting a microcontroller system near the high voltage transformer to acquire the necessary data and transmit it to a remote embedded processor system that is used to detect and analyze the harmonics. The microcontroller and the processor systems are connected by a wide-area network (WAN) through Ethernet and transmission control protocol/internet protocol (TCP/IP) protocols. The processor system is accommodated to perform 128 points fast Fourier transform for harmonics detection. Matlab simulations are used to validate the results. It is found that the results match very accurately the simulation results with an error of less than 0.02%.
Hybrid models for computing fault tolerance of IoT networks Bhupati Chokara; Sastry Kodanda Rama Jammalamadaka
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 2: April 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i2.22429

Abstract

Many Internet of Things (IoT) - based networks are being built to develop applications spanning multiple domains. Many small to large devices connected in various ways increases the risk of IoT networks failing. Small devices in the devices layer frequently fail due to their small size and high usage. Intermittent failures of the IoT networks lead to catastrophes at times. The IoT systems must be designed to be fault-tolerant. Fault tolerance of IoT networks must be computable so that the same can be considered while designing IoT networks. However, the computation of fault tolerance of IoT networks is complex, especially when heterogeneous structures are used for building a specific IoT network. Fault tree-based models are not suitable for computing fault-tolerance of complex models, which requires probability assessment. Hybrid fault tolerance computing models have been presented in this paper that consider both linear and probabilistic methods of computing the fault tolerance considering many complex networking topologies used in each layer of IoT networks. The fault-tolerance computing models are formal methods that can be used to compute the fault tolerance of any IoT network built with any internal processing. The accuracy of fault tolerance computing is 12.9% higher than other methods.

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