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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 66 Documents
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Search results for , issue "Vol 15, No 3: September 2019" : 66 Documents clear
Detection of foreign objects in milk using an ultrasonic system Mohd Taufiq Mohd Khairi; Sallehuddin Ibrahim; Mohd Amri Md Yunus; Ahmad Ridhwan Wahap
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1241-1249

Abstract

This paper presents the utilization of an ultrasonic sensing system to detect foreign objects in milk. The advantage of an ultrasonic system is that it is low cost and it can detect a wide range of materials. A foreign body is any contaminated object found in food. Because of the scale of multifarious food processing levels and distribution, the utilization of the food product are sometimes difficult to control, which will inevitably lead to some complaints by consumers. Milk is widely consumed in the world as it is considered as a healthy drink due to it is high nutrients levels. However, from time to time cases of milk contamination are reported. In this paper. the relationship between the foreign bodies in terms of their dimensions and the resultant amplitude are presented. Mathematical modelling were carried out based on two ultrasonic parameters i.e. acoustic impedance and wave amplitude utilizing several types of foreign bodies with different dimensions. Three types of foreign bodies which are steel, rubber and air were investigated to determine the voltage amplitude detected by the ultrasonic receiver when the foreign bodies obstructed the ultrasonic wave propagation path. The diameters of foreign bodies were in the range from 4 mm to 11 mm. The results showed good correlations between the receiver voltage and the size of foreign bodies with correlation coefficients greater than 0.95. Each foreign body also demonstrated different voltage amplitudes when several sizes of the foreign bodies were tested which showed the ability of the system to distinguish the size of each foreign body.
A novel intelligent model for classify and evaluating non-functional security requirements form scenarios Akram AbdelKarim AbdelQader
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1578-1585

Abstract

Software requirements with its functional and non-functional methods are the first important phase in producing a software system with free errors. The functional requirements are the visual actions that may easily evaluated from the developer and from the user, but non-functional requirements are not visual and need a lot of efforts to be evaluated. One of the main important non-functional requirements is security, which focuses on generating secure systems from strangers. Evaluating the security of the system in earlier steps will help to reduce the efforts of reveals critical system threats. Security threats found because of leaking of security scenarios in requirement phase. In this paper, we purpose an intelligent model to extract and evaluate security features from scenarios based on set of security system goals and a set of security requirements saved on rich story scenarios dataset (RSSD). This model will used a support vector machine (SVM) classifier to classify the security requirement based on RSS dataset.  The using of SVM will enhance the overall process of evaluating the security requirements. The results show a significant enhancement in security improvements.
Automated brain tumor segmentation and classification for MRI analysis system Norhashimah Mohd Saad; Muhamad Faizal Yaakub; Abdul Rahim Abdullah; Nor Shahirah Mohd Noor; Nur Azmina Zainal; Wira Hidayat Mohd Saad
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1337-1344

Abstract

This paper proposed a new analysis technique of brain tumor segmentation and classification for Fluid Attenuated Inversion Recovery (FLAIR) Magnetic Resonance Images (MRI). 25 FLAIR MRI images were collected from online database of Multimodal Brain Tumor Segmentation Challenge 2015 (BRaTS’15).  The analysis comprised four stages which are preprocessing, segmentation, feature extraction and classification. Fuzzy C-Means (FCM) was proposed for brain tumor segmentation. Mean, median, mode, standard deviation, area and perimeter were calculated and utilized as the features to be fed into a rule-based classifier. The segmentation performances were assessed based on Jaccard, Dice, False Positive and False Negative Rates (FPR and FNR). The results indicate that FCM offered high similarity indices which were 0.74 and 0.83 for Jaccard and Dice indices, respectively. The technique can possibly provide high accuracy and has the potential to detect and classify brain tumor from FLAIR MRI database.
Simulation of dual stage thulium-doped fiber amplifier using pump power distribution technique Muhammad Syauqi Kusyairi bin Jamalus; Nelidya Md. Yusoff; Abdul Hadi Sulaiman
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1203-1211

Abstract

This paper shows dual stage thulium-doped fiber amplifiers (TDFAs) that use a pump power distribution technique. Simulations were done with signals ranging from 1975 nm to 2000 nm using the OptiSystem v.13 software. The results required were gathered from the software. The results of gain, noise figure, optical signal-to-noise ratio (OSNR) and output power were obtained. The highest gain and lowest noise figure results were achieved for the double pass dual stage TDFA configuration with values of 19.85 dB and 5.58 dB respectively, followed by the single pass dual stage TDFA. The OSNR and output power performances were also better for the double pass dual stage TDFA, obtaining 57.12 dB and 19.55 dBm respectively. This study shows that thulium can be used in the 2 µm region as an active gain medium and the dual stage architecture and distributed pumping technique proves to be effective techniques to obtain the desired results. Experimental work will be done in the future with the simulated results used as a reference.
Rain attenuation in broadband satellite service and worst month analysis Idrissa Abubakar; Jafri Bin Din; Lam Hong Yin; Manhal Alhilali
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1443-1451

Abstract

Satellite link design, link margin and services at lower bands of satellite spectrum has been facing the challenges of meeting the demands for higher bandwidth requirements. Satellite operators and service providers are been compelled to migrate to the use of higher frequencies above 10 GHz. These higher frequencies were discovered to be vulnerable to atmospheric degradation creating the challenge of service availability especially for tropical rain zones with higher rainfall intensities and longer rain event durations. This study strive to evaluate the profile of rainfall and the monthly and annual variability to improve the design parameters of satellite propagation. Two yeas rainfall measurement campaign was conducted in Abuja at Nigcomsat-1R ground station with a view to understanding the characteristics of Abuja rain. The location of the site is on lat. 9.06o N and lon. 7.48o E. Tipping bucket rain gauge was used for point rain rate and 1.8 m VSAT antenna was installed to monitor the rain induced attenuation on satellite broadband signal. The results shows a huge variability between month to month as well as annual average between 2016 and 2017. The performance of broadband satellite service was found to largely to depend on the quality of the carrier power above the system noise rather than bandwidth capacity or the receive signal level while higher attenuations are associated with higher rain intensities and the slant path effects.
Optimized neuro-PSO-based software maintainability prediction using relief features selection method N. Baskar; C Chandrasekar
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1517-1526

Abstract

The recent development in software engineering reveals the importance of software maintenance during the time of software development that is becoming more important in software development environment and software metrics, which are very essential for measuring the maintainability of software, software complexity, estimating size, quality and project efforts. There are various approaches through which one can estimate the software cost and predict on various kinds of deliverable items. This paper aims at developing an optimized   Neuro-PSO-based software maintainability prediction model by applying the dimensionality reduction using relief feature selection method for identifying the optimal feature subsets in order to increase the accuracy and reduce the time complexity of the prediction model. The simulation result proves the performance of the proposed model which will be more beneficial for the software developers in predicting the maintenance of the software in advance.
Domain specific concept ontologies and text summarization as hierarchical fuzzy logic ranking indicator on malay text corpus Shaiful Bakhtiar bin Rodzman; Normaly Kamal Ismail; Nurazzah Abd Rahman; Syed Ahmad Aljunid; Zulhilmi Mohamed Nor; Ahmad Yunus Mohd Noor
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1527-1534

Abstract

Ranking function is a predictive algorithm that is used to establish a simple ordering of documents according to its relevance. This step is critical because the results’ quality of a Domain Specific Information Retrieval (IR) such as Hadith Information Retrieval is fundamentally dependent of the ranking function. A Hierarchical Fuzzy Logic Controller of Mamdani-type Fuzzy Inference System has been built to define the ranking function, based on the Malay Information retrieval’s BM25 Model. The model examines three-inputs (Ontology BM25 Score, Fabrication Rate of Hadith and Shia Rate of Hadith) and four-output values of Final Ranking Score which consist of three triangular membership functions. The proposed system has outperformed the BM25 original score and the Vector Space Model (VM) on 16 queries, while the BM25 original score and Vector Space Model only yield better result in 9 and 2 queries respectively on the P@10, %no measures and MAP. P@10 represent the values of Precision at Rank 10 P@10), %no measures represent the percentage of queries with no relevant documents in the top ten retrieved and MAP represents Mean Average Precision of the queries. The results show the proposed system have capability to demote negative documents and move up the relevant documents in the ranking list and its capability to recall unseen document with the application of ontology in text retrieval. For the future works, the researcher would like to apply the usage of other Malay Semantic elements and another corpus for positive ranking indicator.
Bat algorithm and k-means techniques for classification performance improvement Rozlini Mohamed; Munirah Mohd Yusof; Noorhaniza Wahid; Norhanifah Murli; Muhaini Othman
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1411-1418

Abstract

This paper presents Bat Algorithm and K-Means techniques for classification performance improvement. The objective of this study is to investigate efficiency of Bat Algorithm in discrete dataset and to find the optimum feature in discrete dataset. In this study, one technique that comprise the discretization technique and feature selection technique have been proposed. Our contribution is in two process of classification: pre-processing and feature selection process. First, to proposed discretization techniques called as BkMD, where we hybrid Bat Algorithm technique and K-Means classifier. Second, to proposed BkMDFS as feature selection technique where Bat Algorithm is embed into BkMD. In order to evaluate our proposed techniques, 14 continuous dataset from various applications are used in experiment. From the experiment, results show that BkMDFS outperforms in most performance measures. Hence it shows that, Bat Algorithm have potential to be one of the discretization technique and feature selection technique.
Reverse biased nanocrystalline graphite (NCG)/p-Si schottky junction for methane gas sensor A. A. Nawawi; S.M. Sultan; S.F.A. Rahmah; P.I. Khalid; S.H. Pu
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1217-1222

Abstract

An investigation on the effect of the reverse biased operation of NCG/p-Si Schottky contact during methane gas exposure at room temperature has been presented. The experimental results show the larger current shift at the reverse bias operation, compared to the forward bias by exposing to methane gas. This can be attributed to the adsorption of methane gas into the metal surface layer and produces a negative charge at the junction, thus reduces the barrier height of the device. The reverse barrier height was calculated under the reverse bias condition, demonstrated the value decreased from 0.58-0.53eV towards a higher concentration of methane gas. The Schottky junction also affected by the increase in a free carrier when exposure to the reducing gas such as methane. Raman spectra are reported to be detected at G, D and 2D band with the grain size 1.88nm to exhibit single crystallite graphite properties. The results correlate well with the 3D AFM scans reveal the RMS surface roughness of 1.1 to 2.8nm.
Performance of channel selection used for Multi-class EEG signal classification of motor imagery Djelloul Kheira; M. Beladgham
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1305-1312

Abstract

In this paper, a study of a non-invasive brain-machine interfaces for the classification of 4 imaginary are presented. Performance comparisons using time-frequency analysis between the Linear Discriminant Analysis motor activities (left hand, right hand, foot, tongue) with the BCI competition III dataset IIIa is (LDA), the Support Vector Machine (SVM) and the K-Nearest Neighbors (KNN) algorithms have been carried. The number and position of electrodes for each subject were investigated to provide an improvement for the classification accuracy of the algorithm. Results show that the electrode positions varied from subject to subject; moreover , using one subset of the channels enhanced the classification performances compared to literature data. an average accuracy of 86.06% was observed among all 3 subjects.

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