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31,456 Article Results

Outage probability analysis in DF power-splitting full-duplex relaying network with impact of Co-channel interference at the destination

10.12928/telkomnika.v18i4.13716
Phu Tran; Industrial University of Ho Chi Minh City Tin , Duy Hung; Ton Duc Thang University Ha , Minh; Ton Duc Thang University Tran
Nowadays, improving the WPCN efficiency problem is the leading research direction in the communication network. In this research, the outage probability (OP) analysis in DF power-splitting (PS) full-duplex (FD) relaying network with impact of co-channel interference at the destination is proposed and investigated. In the system model section, we present the DF PS FD Relaying Network with Impact of Co-channel interference at the destination. Then in the system performance section, we analyze and derive the closed-form expression of the OP and investigate the effect of the main system parameters on the system network performance. Then, we perform the Monte Carlo simulation to verify the analytical section. This research can provide a new recommendation for the communication network.
Volume: 18
Issue: 4
Page: 1828-1833
Publish at: 2020-08-01

Handwriting identification using deep convolutional neural network method

10.12928/telkomnika.v18i4.14864
Oka; Udayana University Sudana , I Wayan; Udayana University Gunaya , I Ketut Gede; Udayana University Darma Putra
Handwriting is a unique thing that produced differently for each person. Handwriting has a characteristic that remain the same with single writer, so a handwriting can be used as a variable in biometric systems. Each person have a different form of handwriting style but with a small possibility that same characters have something commons. This paper proposes a handwriting identification method using sentence segmented handwriting forms. Sentence form is used to get more complete handwriting characteristics than using a single characters or words. Dataset used is divided into three categories of images, binary, grayscale, and inverted binary. All datasets have same image with different in color and consist of 100 class. Transfer learning used in this paper are pre-trained model VGG19. Training was conducted in 100 epochs. Highest result is grayscale images with genuince acceptance rate of 92.3% and equal error rate of 7.7%.
Volume: 18
Issue: 4
Page: 1934-1941
Publish at: 2020-08-01

Uric acid detection in visible spectrum

10.12928/telkomnika.v18i4.14993
Afiqah; Universiti Tun Hussein Onn Malaysia Yaacob , Nor Hafizah; Universiti Tun Hussein Onn Malaysia Ngajikin , Nurfatihah Che Abd; Universiti Tun Hussein Onn Malaysia Rashid , Siti Hajar Aminah; Universiti Tun Hussein Onn Malaysia Ali , Maslina; Universiti Tun Hussein Onn Malaysia Yaacob , Suhaila; Universiti Teknologi Malaysia Isaak , Noran Azizan; Universiti Tun Hussein Onn Malaysia Cholan
The measurement of uric acid based on the optical absorption at visible light spectrum is investigated and tested. Sensing in the visible region was conducted for determination of suitable wavelength that produces high sensitivity and accuracy performance based on the Beer-Lambert law calculation. In this work, the uric acid is detected by detecting sodium urate as a product of chemical reaction between uric acid with sodium hydroxide buffer. The setup has been tested for uric acid concentration ranging from 15 mg/dL to 85 mg/dL. Three wavelengths have been analyzed which are 460 nm, 525 nm and 630 nm. Measured data at 460nm wavelength exhibits the highest sensitivity, which is 0.0012 (mg/dL)-with 86.51% accuracy. Detection of uric acid at visible light spectrum offers a low-cost sensor based on visible LEDs and photodiode is possible to be realized.
Volume: 18
Issue: 4
Page: 2035-2041
Publish at: 2020-08-01

Teaching challenges on the use of storytelling in elementary science lessons

10.11591/ijere.v9i3.20596
Hajah Nuruljannah Haji Matamit , Roslinawati Roslan , Masitah Shahrill , Hardimah Mohd Said
This study investigated the use of storytelling in teaching elementary science on the topic of ‘Sense Organs’ at the Grade 1 level. A total of 21 students from one of the elementary schools in Brunei Darussalam participated in the study. The qualitative analyses of the observations and video recordings resulted in the classifications of the challenges faced when storytelling was used in the lessons. The four identified categories were the language aspect, development aspect, external challenges and existing knowledge. These categories were then used to investigate further any aspect that would develop the challenges into the teaching and learning of science using storytelling. Despite identifying the challenges in using storytelling in teaching science, storytelling may enhance the students’ understanding of science concepts.
Volume: 9
Issue: 3
Page: 716-722
Publish at: 2020-08-01

Real power loss diminution by predestination of particles wavering search algorithm

10.11591/ijict.v9i2.pp92-99
Kanagasabai Lenin
In this work Predestination of Particles Wavering Search (PPS) algorithm has been applied to solve optimal reactive power problem. PPS algorithm has been modeled based on the motion of the particles in the exploration space. Normally the movement of the particle is based on gradient and swarming motion.  Particles are permitted to progress in steady velocity in gradient-based progress, but when the outcome is poor when compared to previous upshot, immediately particle rapidity will be upturned with semi of the magnitude and it will help to reach local optimal solution and it is expressed as wavering movement. In standard IEEE 14, 30, 57,118,300 bus systems Proposed Predestination of Particles Wavering Search (PPS) algorithm is evaluated and simulation results show the PPS reduced the power loss efficiently.
Volume: 9
Issue: 2
Page: 92-99
Publish at: 2020-08-01

Plant acoustic frequency technology control system to increase vegetative growth in red-lettuce

10.12928/telkomnika.v18i4.14158
Yusuf; Universitas Brawijaya Hendrawan , Adamsyah Harika; Universitas Brawijaya Putra , Sumardi Hadi; Universitas Brawijaya Sumarlan , Gunomo; Universitas Brawijaya Djoyowasito
The application of plant acoustic frequency technology (PAFT) can spur plant growth, increase productivity, immune system, quality, and extend the shelf life of agricultural products after harvest. The application of sound waves in plants can stimulate the opening of the stomata to optimally absorb nutrients and water. This study aims to determine the effect of frequency and time of PAFT exposure by utilizing Javanese gamelan traditional music on the vegetative growth of red-lettuce (Lactuca sativa var.). Javanese gamelan music used was titled Puspawarna with variations in the frequency of 3-5, 7-9, and 11-13 kHz. The variation of exposure time of sound waves was 1, 2, and 3 hours. PAFT exposure was given routinely in the morning and evening. The results of this study indicated that the best treatment was at 3-5 kHz with an exposure time of 2 hours. This treatment gave a significantly better effect when compared to plants without PAFT. The best combination of frequency and time of PAFT exposure produced 10 leaves, plant height of 9.4 cm, wet weight of 4 g, dry weight of 0.22 g, leaf area of 27.19 cm2, leaf red mean of 63, and stomata opening width of 145.44~206.59 µm.
Volume: 18
Issue: 4
Page: 2042-2052
Publish at: 2020-08-01

Strategy to determine the foot plantar center of pressure of a person through deep learning neural networks

10.12928/telkomnika.v18i4.15200
Henry Hernández; Universidad Distrital Francisco José de Caldas Martínez , Holman Montiel; Universidad Distrital Francisco José de Caldas Ariza , Luz Andrea Gaviria; Universidad Internacional de la Rioja Roa
Some case studies treated by physiotherapists or orthopedists to measure the alignment of the lower extremities during a gait cycle are based on empirical methods of visual observation. This methodology does not guarantee total success, since it depends on the experience of the specialist, what can cause irreversible damage to patients, such as: hip displacement, wear and overload of the joints of a single lower limb. Although, this problem has been addressed in the investigation by means of devices implementation with sensors or methods of processing sequences of images and videos, this topic is still under investigation because the current methods depend on many external elements and data given by an expert in the area. Therefore, this paper proposes a partial solution to this problem by systematizing the experience of a specialist through a computational learning method.
Volume: 18
Issue: 4
Page: 1954-1961
Publish at: 2020-08-01

Indonesian news classification using convolutional neural network

10.11591/ijeecs.v19.i2.pp1000-1009
Muhammad Ali Ramdhani , Dian Sa’adillah Maylawati , Teddy Mantoro
Every language has unique characteristics, structures, and grammar. Thus, different styles will have different processes and result in processed in natural language processing (NLP) research area. In the current NLP research area, data mining (DM) or machine learning (ML) technique is popular, especially for deep learning (DL) method. This research aims to classify text data in the Indonesian language using convolutional neural network (CNN) as one of the DL algorithms. The CNN algorithm used modified following the Indonesian language characteristics. Thereby, in the text pre-processing phase, stopword removal and stemming are particularly suitable for the Indonesian language. The experiment conducted using 472 Indonesian news text data from various sources with four categories: ‘hiburan’ (entertainment), ‘olahraga’ (sport), ‘tajuk utama’ (headline news), and ‘teknologi’ (technology). Based on the experiment and evaluation using 377 training data and 95 testing data, producing five models with ten epoch for each model, CNN has the best percentage of accuracy around 90,74% and loss value around 29,05% for 300 hidden layers in classifying the Indonesian News data.
Volume: 19
Issue: 2
Page: 1000-1009
Publish at: 2020-08-01

Software engineering model based smart indoor localization system using deep-learning

10.12928/telkomnika.v18i4.14318
Zainab Mohammed; University of Technology-Iraq Resan , Muayad Sadik; University of Technology-Iraq Croock
During the last few years, the allocation of objects or persons inside a specific building is highly required. It is well known that the global positioning system (GPS) cannot be adopted in indoor environment due to the lack of signals. Therefore, it is important to discover a new way that works inside. The proposed system uses the deep learning techniques to classify places based on capturing images. The proposed system contains two parts: software part and hardware part. The software part is built based on software engineering model to increase the reliability, flexibility, and scalability. In addition, this part, the dataset is collected using the Raspberry Pi III camera as training and validating data set. This dataset is used as an input to the proposed deep learning model. In the hardware part, Raspberry Pi III is used for loading the proposed model and producing prediction results and a camera that is used to collect the images dataset. Two wheels’ car is adopted as an object for introducing indoor localization project. The obtained training accuracy is 99.6% for training dataset and 100% for validating dataset.
Volume: 18
Issue: 4
Page: 1904-1916
Publish at: 2020-08-01

A simplified spatial Modulation MISO-OFDM scheme

10.12928/telkomnika.v18i4.13873
Vian S.; Al-Rafidain University College Al-Doori , Emad H.; Al-Nahrain University Al-Hemiary
Index modulation is one of the promising techniques for future communications systems due to many improvement over the classical Orthogonal frequency division multiplexing systems such as single RF chain, increased throughput for the same modulation order, achieved tradeoff between the efficiencies of the power and the spectral, and elimination of inter-channel interference. Many forms of index modulation researches exist where symbols are conveyed in antennas, subcarriers, time slots, and the space-time matrix.  Spatial modulation is one member of index modulation family where symbols are conveyed in activating transmit/receive antennas. In this paper, a modification to a standard multiple input single output scheme by integrating spatial modulation using simplified mathematical procedure is achieved. In the transmitter side, data and activation symbols are distributed simultaneously using mathematical module and floor functions. At the receiver, a simplified maximum likelihood detector is used to obtain transmitted pair of symbols. To verify this, MATLAB SIMULINK is used to simulate a downlink system where spatial modulation is applied to a base station. Results for different transmit antenna number and modulation order are obtained in the form of bit error rate versus signal to noise ratio.
Volume: 18
Issue: 4
Page: 1738-1745
Publish at: 2020-08-01

A feasibility study of electrical energy generation from municipal solid waste in Iraq: Najaf case study

10.11591/ijece.v10i4.pp3403-3411
Othman M. Anssari , Esam A. Alkaldy , Naseem Almudhaffar , Abbas Nasir AlTaee , Nabeel Salih Ali
In several developing countries, the electricity crisis obstructs both socio-economic and technological sustainable evolution. Also, it leads to reducing job availability due to shut down several industries or relocate to neighbouring countries to such an issue. A Najaf City is an important holy and tourist city in the middle of Iraq country. Indeed, waste management in An Najaf City needs to be reconsidered to be used as an energy source. In this article, we investigated and listed the waste quantity which produced recently (one year) respect to waste types and types of content. Data collected from the waste products for one year and are used as a key factor to study the feasibility of generating electrical energy from collected MSWs. The proposed model was simulated and tested respect to cost analysis factor of the suggested power plant by Homer pro simulation software. Results were very encouraging and competitive to the current energy production cost based on the production cost of the Kwh prospective among the conventional methods in Iraq. The proposed scenario provide proper and secure waste proposal technique with low-cost.
Volume: 10
Issue: 4
Page: 3403-3411
Publish at: 2020-08-01

Speaker specific feature based clustering and its applications in language independent forensic speaker recognition

10.11591/ijece.v10i4.pp3508-3518
Satyanand Singh , Pragya Singh
Forensic speaker recognition (FSR) is the process of determining whether the source of a questioned voice recording (trace) is a specific individual (suspected speaker). The role of the forensic expert is to testify by using, if possible, a quantitative measure of this value to the value of the voice evidence. Using this information as an aid in their judgments and decisions are up to the judge and/or the jury. Most existing methods measure inter-utterance similarities directly based on spectrum-based characteristics, the resulting clusters may not be well related to speaker’s, but rather to different acoustic classes. This research addresses this deficiency by projecting language-independent utterances into a reference space equipped to cover the standard voice features underlying the entire utterance set. The resulting projection vectors naturally represent the language-independent voice-like relationships among all the utterances and are therefore more robust against non-speaker interference. Then a clustering approach is proposed based on the peak approximation in order to maximize the similarities between language-independent utterances within all clusters. This method uses a K-medoid, Fuzzy C-means, Gustafson and Kessel and Gath-Geva algorithm to evaluate the cluster to which each utterance should be allocated, overcoming the disadvantage of traditional hierarchical clustering that the ultimate outcome can only hit the optimum recognition efficiency. The recognition efficiency of K-medoid, Fuzzy C-means, Gustafson and Kessel and Gath-Geva clustering algorithms are 95.2%, 97.3%, 98.5% and 99.7% and EER are 3.62%, 2.91 %, 2.82%, and 2.61% respectively. The EER improvement of the Gath-Geva technique based FSRsystem compared with Gustafson and Kessel and Fuzzy C-means is 8.04% and 11.49% respectively
Volume: 10
Issue: 4
Page: 3508-3518
Publish at: 2020-08-01

SVC device optimal location for voltage stability enhancement based on a combined particle swarm optimization-continuation power flow technique

10.12928/telkomnika.v18i4.13073
Oum El Fadhel Loubeba; Dr. Moulay Tahar University Bekri , Abdellah; University of Quebec in Chicoutimi UQAC Chehri , Tounsia; Mouloud Mammeri University Djamah , Mohamed Karim; DjillaliLiabès University Fellah
The increased power system loading combined with the worldwide power industry deregulation requires more reliable and efficient control of the power flow and network stability. Flexible AC transmission systems (FACTS) devices give new opportunities for controlling power and enhancing the usable capacity of the existing transmission lines. This paper presents a combined application of the particle swarm optimization (PSO) and the continuation power flow (CPF) technique to determine the optimal placement of static var compensator (SVC) in order to achieve the static voltage stability margin. The PSO objective function to be maximized is the loading factor to modify the load powers. In this scope, two SVC constraints are considered: the reference voltage in the first case and the total reactance and SVC reactive power in the second case. To test the performance of the proposed method, several simulations were performed on IEEE 30-Bus test systems. The results obtained show the effectiveness of the proposed method to find the optimal placement of the static var compensator and the improvement of the voltage stability.
Volume: 18
Issue: 4
Page: 2101-2111
Publish at: 2020-08-01

Arabic digits speech recognition and speaker identification in noisy environment using a hybrid model of VQ and GMM

10.12928/telkomnika.v18i4.14215
Abdelkbir; Sultan Moulay Slimane University Ouisaadane , Said; Sultan Moulay Slimane University Safi , Miloud; LAC Laboratory Caen-Normandie University Frikel
This paper presents an automatic speaker identification and speech recognition for Arabic digits in noisy environment. In this work, the proposed system is able to identify the speaker after saving his voice in the database and adding noise. The mel frequency cepstral coefficients (MFCC) is the best approach used in building a program in the Matlab platform; also, the quantization is used for generating the codebooks. The Gaussian mixture modelling (GMM) algorithms are used to generate template, feature-matching purpose. In this paper, we have proposed a system based on MFCC-GMM and MFCC-VQ Approaches on the one hand and by using the Hybrid Approach MFCC-VQ-GMM on the other hand for speaker modeling. The White Gaussian noise is added to the clean speech at several signal-to-noise ratio (SNR) levels to test the system in a noisy environment. The proposed system gives good results in recognition rate.
Volume: 18
Issue: 4
Page: 2193-2204
Publish at: 2020-08-01

Mobile cloud game in high performance computing environment

10.12928/telkomnika.v18i4.14896
Dedy Prasetya; Raharja University Kristiadi , Ferry; Raharja University Sudarto , Evan Fabian; Bina Nusantara University Rahardja , Naufal Rayfi; Bina Nusantara University Hafizh , Christopher; Bina Nusantara University Samuel , Harco Leslie Hendric Spits; Bina Nusantara University Warnars
Mobile cloud game is a solution to play high-end games in indigent thin clients with a diversity of end-user devices, and as real-time gaming, mobile cloud game hosting game engines in the cloud. Moreover, frequent change in network quality is another issue that should be limited to run the real fast cloud game. Thus, reliable software components between cloud and user devices as clients, including using artificial intelligence (AI) algorithms such as machine learning, deep learning and so on will enhance the game performance, particularly in multiplayer and real-time conditions. In this paper, we list the mobile cloud game architecture in the high-performance computing (HPC) environment, where a load of the game will be distributed between servers as cloud and clients. The server node as clouds or clients will consist of more than one server with many processors (cores) or sometimes can be recognized as distributed computing. Using HPC for cloud games will boost the game performance where the execution times will be dispersed not only in some node in servers and clients but in many cores of each server or client. The involvement of the internet of things (IoT) and ubiquitous access from heterogeneous devices will give benefit to enjoyment in the game itself.
Volume: 18
Issue: 4
Page: 1983-1989
Publish at: 2020-08-01
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