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31,456 Article Results

Evaluation of SVM performance in the detection of lung cancer in marked CT scan dataset

10.11591/ijeecs.v21.i3.pp1731-1738
Hamdalla Fadil Kareem , Muayed S AL-Huseiny , Furat Y. Mohsen , Enam A. Khalil , Zainab S. Hassan
This paper concerns the development/analysis of the IQ-OTH/NCCD lung cancer dataset. This CT-scan dataset includes more than 1100 images of diagnosed healthy and tumorous chest scans collected in two Iraqi hospitals. A computer system is proposed for detecting lung cancer in the dataset by using image-processing/computer-vision techniques. This includes three preprocessing stages: image enhancement, image segmentation, and feature extraction techniques. Then, support vector machine (SVM) is used at the final stage as a classification technique for identifying the cases on the slides as one of three classes: normal, benign, or malignant. Different SVM kernels and feature extraction techniques are evaluated. The best accuracy achieved by applying this procedure on the new dataset was 89.8876%.
Volume: 21
Issue: 3
Page: 1731-1738
Publish at: 2021-03-01

Expert role in image classification using CNN for hard to identify object: distinguishing batik and its imitation

10.11591/ijai.v10.i1.pp93-100
Zohanto Widyantoko , Titik Purwati Widowati , Isnaini Isnaini , Paras Trapsiladi
In this research we try to solve the recognition problem in differentiating between batik and its imitation. Batik is an Indonesian heritage of process in making traditional textile product that is now endangered by the existence of imitation products. We try to compare two popular CNN model to classify batik products into five classes. The classes are tulis, cap, print warna, print malam, cabut warna. Tulis and cap are genuine batik, and the other three are an imitation. We realize that this problem is go beyond the recognition of fine grained image problem, it is a hard to identify image problem because even the batik experts is having a hard time identifying batik and its imitation if only based on its picture. The two CNN models, inceptionV3 and mobilenetV2 were trained on three types of image. One type is a freely taken image, the other two were taken based on the experts suggestion. The accuracy score shows that the model trained with the suggestion based picture perform better than the one trained with the random picture.
Volume: 10
Issue: 1
Page: 93-100
Publish at: 2021-03-01

Satellite image inpainting with deep generative adversarial neural networks

10.11591/ijai.v10.i1.pp121-130
Mohamed Akram Zaytar , Chaker El Amrani
This work addresses the problem of recovering lost or damaged satellite image pixels (gaps) caused by sensor processing errors or by natural phenomena like cloud presence. Such errors decrease our ability to monitor regions of interest and significantly increase the average revisit time for all satellites. This paper presents a novel neural system based on conditional deep generative adversarial networks (cGAN) optimized to fill satellite imagery gaps using surrounding pixel values and static high-resolution visual priors. Experimental results show that the proposed system outperforms traditional and neural network baselines. It achieves a normalized least absolute deviations error of (  &  decrease in error compared with the two baselines) and a mean squared error loss of  (  &  decrease in error) over the test set. The model can be deployed within a remote sensing data pipeline to reconstruct missing pixel measurements for near-real-time monitoring and inference purposes, thus empowering policymakers and users to make environmentally informed decisions.
Volume: 10
Issue: 1
Page: 121-130
Publish at: 2021-03-01

Validating the teaching, learning, and assessment quality of Malaysian ECCE instrument

10.11591/ijere.v10i1.20857
Hishamuddin Ahmad , Nordin Mamat , Mazlina Che Mustafa , Syahida Iryani Mohd Yusoff
Several instruments that measure the teaching, learning, and assessment quality have been developed and published. However, a psychometrically sound instrument to measure teaching, learning, and assessment quality in early childhood care and education that suitable for the Malaysian context needs to be validated. Therefore, this study aimed to validate on teaching, learning, and assessment quality in early childhood care and education instrument, which contains 68 items. The sample comprised 3,498, selected by stratified random sampling from a population of all Malaysian kindergarten teachers. Data were analyzed based on the Polytomous Item Response Theory (IRT) using the Xcalibre software. Samejima's Graded Rating Model (SRGM) was found to be the fit model with the data. Unidimensionality assumption and local independence were tested using the exploratory factor analysis and were fulfilled. The instrument’s reliability was overall very good (α=0.966) and the construct validity was also fairly fulfilled with the value of 58.17% total variance explained. Therefore, this instrument is suggested to be used as fairly to measure the quality of Malaysian early childhood care and education among teachers so that appropriate follow-up actions can be implemented towards the betterment of early childhood education quality.
Volume: 10
Issue: 1
Page: 135-141
Publish at: 2021-03-01

A hybrid strategy for emotion classification

10.11591/ijeecs.v21.i3.pp1400-1406
Hussah Nasser Aleisa
Human emotion recognition is an upcoming research field of human computer interaction based on facial gestures and is being used for real-time analysis in classifying cognitive affective states from a facial video data. Since computers have become an integral part of life, many researchers are using emotion recognition and classification of data based on audio and text. But these approaches offer limited accuracy and relevance in emotion classification. Therefore we have introduced and analyzed a hybrid approach which could outperform the existing strategies that uses an innovative approach supported by selection of audio and video data characteristics for classification. The research uses SVM for classifying the data using audio-visual savee database and the results obtained show maximum classification accuracy with respect to audio data about 91.6 could be improved to 99.2% after the application of hybrid strategy.
Volume: 21
Issue: 3
Page: 1400-1406
Publish at: 2021-03-01

Technical experience with tempera paintings in a bachelor degree course in Turkey

10.11591/ijere.v10i1.20667
Gonca Erim , Ismail Tetikci , Remziye Ersoy
This article aims to understand the place of the tempera technique in art history, which is thought to be encountered for the first time by art education undergraduate students, and to determine the effects on the participants after the application. The study consists of the findings and results of the first and second research questions in the master thesis “Tempera technique and its use in the course of painting courses on undergraduate level.” In this study the “case study” pattern was used, and is one of the qualitative research approaches. The participants of the research are eight students studying in Bursa Uludag University, Faculty of Education, Department of Fine Arts Education in the 2018-2019 academic year. The data collection tools of literature review and two interview forms interview were used. The findings obtained were evaluated by thematic analysis technique. According to the findings obtained in the research, it was observed that the participants did not have prior knowledge about the tempera technique before oral presentation and application. It was concluded that there were differences in the levels of interest and knowledge after the teaching process, and that there were positive changes in their opinions regarding the technique.
Volume: 10
Issue: 1
Page: 245-254
Publish at: 2021-03-01

Fusion for medical image based on discrete wavelet transform coefficient

10.11591/ijeecs.v21.i3.pp1407-1416
Zahraa Yaseen Hasan , Rusul Altaie , Hawraa Abd Al-kadum Hassan
More recent digital camera introduced enormous facilities for users from different specifications to take images easily, but the user still wants to improve these images, which it contains different problems like ambiguous and colors is not clear, because not enough light, cloudy weather, bright light, dark region and it's taken from remote distances. This paper aims to use a new approach for fusion images by using a wavelet coefficient based on PSNR and SNR measure (the technical result) instead of using the max, min, average values, and so on in the previous methods. The wavelet coefficient of each sub band is compared between them, the sub band had a value higher of measure is selected for fusion. Firstly, a discrete wavelet transform has been applied to the medical images with 2level. Then, the peak signal to noise ratio and signal to noise ratio measures have been computed for each sub-band. After that PSNR and SNR values have been compared for each sub-band to opposite sub-band and it selected the better value of measures. Secondly, PSNR and SNR values have been gathered for each image. Then select the image that contains value higher PSNR and lower value of SNR for purpose fusion. Finally, perform an inverse discrete wavelet on the fused image to transform it from the frequency to the spatial domain. The results of the work showed that the wavelet coefficient is used to preserve the image details and removed the noise. PSNR value of 1level of dwt is higher than 2level. This paper makes the image more clearer and informative than the original images. 
Volume: 21
Issue: 3
Page: 1407-1416
Publish at: 2021-03-01

An investigation of teacher and teacher candidates’ views on the course of school experience

10.11591/ijere.v10i1.20745
Emine Begüm Akkuş , Lütfi Üredi
One of the most important elements involved in the development of countries is teachers. Therefore, developing countries should pay attention to training good teachers. Thus, the purpose of this study was to present the opinions of teachers and prospective teachers on the “teaching experience” course. The study is based on a qualitative research. The data were collected from 84 teachers in Şanlıurfa, an eastern city of Turkey and 88 prospective teachers (undergraduate seniors) studying at Mersin University, Turkey. Semi-structured interview form was utilized to collect the required data. Besides, content analysis was applied in the study. The data have been expressed in numbers. Results have displayed that there are problems arising from the stakeholders in the “teaching experience” lesson. The types of schools attending internships are not inclusive. Not all stakeholders are working cooperatively. Moreover, the following suggestions were accordingly put forward: 1) The internship duration can be extended; 2) Applications covering all types of schools should be added; and 3) Stakeholders should be encouraged to work in a collaborative way.
Volume: 10
Issue: 1
Page: 262-272
Publish at: 2021-03-01

Successful online learning factors in COVID-19 era: Study of Islamic higher education in West Papua, Indonesia

10.11591/ijere.v10i1.21036
Agus Yudiawan , Budi Sunarso , Suharmoko Suharmoko , Fatma Sari , Ahmadi Ahmadi
This study aimed to map and tests the factors that influence online learning success in the COVID-19 era in Islamic Religious Higher Education in the West Papua region. Factors to be analyzed are student characteristics, internal motivation, instructor characteristics, quality of institutions and services, infrastructure and system quality, quality of courses and information, online learning environment. The sample size obtained from the Slovin formula was 302 students. Data collected through surveys by distributing questionnaires. Analysis of the regression model used to carry out data analysis. The results showed that the seven factors tested influenced online learning success in the COVID-19 era, with varying significance. Infrastructure and system quality are the most dominant influences (94.2%), while institutions' variety and services have no significant impact (6.3%). The conclusion is that the seven factors can be used to determine the success of online learning in the COVID-19 era in Islamic Religious Higher Education in the West Papua region.
Volume: 10
Issue: 1
Page: 193-201
Publish at: 2021-03-01

An automatic system for detecting voltage leaks in houses to save people's lives

10.11591/ijeecs.v21.i3.pp1485-1492
Hussein M. Haglan , Hussam Jasim Ali
Many people are exposed to many dangers, such as electrical leakage into parts of the home that lead to death, injury, or loss of material resources. With the great developments that happen daily in the field of technology, one of the most important examples of these developments is the Arduino. The Arduino is a company that produces a software and electronic parts that are open source for companies and students in order to design and build digital devices, design and implement projects and systems that can be linked together or linked with the Internet to facilitate their use to serve society and humanity. It became easier to deploy this technology to solve problems that put people at risk. Many systems that detect leakage of gas, liquids and fires were built using these modern technologies to protect the lives of people and their resources, but no one has actually used these technologies to detect unexpected electrical voltage leaks into the home's water network or walls that resulting from damage in some parts of electrical devices. Therefore, in this paper, we have proposed and designed a system that can detect an unexpected voltage leak from some electric devices to the water network or walls in houses, alarm of house owners by sound, and cut off the electrical current to the house in order to save people's lives and resources.
Volume: 21
Issue: 3
Page: 1485-1492
Publish at: 2021-03-01

Binding site identification of COVID-19 main protease 3D structure by homology modeling

10.11591/ijeecs.v21.i3.pp1713-1721
Marion Adebiyi , Oludayo O. Olugbara
The influx of coronavirus in 2019 (COVID-19) from Wuhan of China has led to a global pandemic, undesirable hiatus, and recorded millions of infection cases with several deaths worldwide. The strain of COVID-19 has neither known treatments nor vaccines, but recent studies have shown that a few of its enzymes may have been considered as potential drug target. Since its influx, the virus has been well-studied, but a lot is not known about its protease yet.  The purpose of this work was to identify the binding site in-silico and present 3D structure of COVID-19 main protease (Mpro) by homology modeling through multiple alignment followed by optimization and validation. The modeling was done by Swiss-Model template library and basic local alignment search tool (BLAST). The obtained homotrimer oligo-state model was verified for reliability using structural validation software such as PROCHECK, Verify3D, MolProbity and QMEAN. The HHBlits software was used to determine the structures that matched the target sequence by evolution. Best template, 6u7h.1.A was used to build a tertiary structure for Mpro with ProMod3 3.0.0 on the Swiss-Model workspace. Self-optimized prediction method with alignment (SOPMA) was applied to compute features of the secondary structure. The verification of quality of COVID-19 structure through Ramachandran plot showed an abundance of 99.3% of amino acid residues in allowed regions while 0.1% in disallowed region. The Verify3D rated the structure a 90.87% PASS of residues having an average 3D-1D score of at least 0.2, which validates a good environment profile for the COVID-19 Mpro model. The features of the secondary structure indicated that the modeled 3D structure of Mpro contains 32.05% α-helix and 37.17% random coil with 25.92 extended strand. DeepSite algorithm elucidates the binding site area that captured local patterns in the structure and exposed the surface cavity of the binding pocket of this protein. The main result of this study suggests that blocking expression of the protein may constitute an efficient approach for transmission blockage. Hence, our thought is that Mpro of COVID-19 may be considered a potential drug target. Nevertheless, more experimental analyses, verification and validation experiments will be required as a targeted drug or vaccine design against COVID-19 virus.
Volume: 21
Issue: 3
Page: 1713-1721
Publish at: 2021-03-01

High sensitivity sapphire FBG temperature sensors for the signal processing of data communications technology

10.11591/ijeecs.v21.i3.pp1567-1574
Mahmoud M. A. Eid , Ashraf S. Seliem , Ahmed Nabih Zaki Rashed , Abd El-Naser A. Mohammed , Mohamed Yassin Ali , Shaimaa S. Abaza
This study has outlined the fiber bragg grating (FBG) temperature sensors signal processing for data communications by using OptiGrating simulation software. The reflectivity of the silica and sapphire fiber grating spectrum is reported against the grating wavelength for internal and external temperature variations. As well as apodized Gaussian reflectivity of the silica and sapphire fiber grating spectrum is simulated and clarified against the grating wavelength for high temperature variations. The temperature sensitivity of sapphire FBG nearly 0.11 pm/0C, where its value is three times higher than silica FBG. It is observed that silica and Sapphire FBG sensors were tested up to 1000 0C by using Gaussian apodization type, side lobes in reflectivity spectrum are totally suppressed.
Volume: 21
Issue: 3
Page: 1567-1574
Publish at: 2021-03-01

Remote sensing data driven bathing water quality assessment using sentinel-3

10.11591/ijeecs.v21.i3.pp1634-1647
Antonia Senta , Ljiljana Šerić
In this paper we are investigating the possibility of usage of remote sensing satellite data, more precisely sentinel-3 OLCI and SLSTR data, for assessment of bathing water quality. In this research we used data driven approach and analysis of data in order to pinpoint aspects of remote sensing data that can be useful for bathing water quality assessment. For this purpose we collected satellite images for period from start of June till end of September of 2019 and results of in-situ measurement for the same period. Results of in-situ measurement were correlated with satellite images bands and analyzed. We propose a simple method for rapid assessment of possible deterioration of bathing water quality to be used by public health authorities for better planning of in situ measurements. Results of implementation of predictive models based on k-nearest neighbour (KNN) and decision tree (DT) are described.
Volume: 21
Issue: 3
Page: 1634-1647
Publish at: 2021-03-01

Effect of thiourea on structure, morphology, and optical properties of spray deposited CZTS thin films for solar cell applications

10.11591/ijaas.v10.i1.pp39-46
Ramesh B. Mahewar , Ravikumar R. Vidule , Limbraj S. Ravangave
Cu2ZnSnS4 (CZTS) films of different Thiourea (SC (NH2)2) molarity were deposited by using a simple chemical spray technique at substrate temperature 275 °C. Analytical reagent Grade Copper chloride (CuCl2), Zinc chloride (ZnCl2), and Tin chloride (SnCl4.5H2O) were used as Cu+, Zn+, and Sn+ ion sources respectively and thiourea (SC(NH2)2) (0.02, 0.04, 0.06, 0.08, and 0.1 M) was used as an S- ion source. A set of five CZTS films was deposited using five different molarity of thiourea. The structure, morphology, elemental analysis, and optical properties of these films were studied using X-ray diffractometer (XRD), scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDX), and UV-visible spectroscopy techniques respectively. The XRD spectra showed that all films are polycrystalline tetragonal structures with preferential orientation along 112 planes. The calculated crystallite size was increased with an increase in thiourea concentration. Variations of optical band gap with thiourea molarity have been investigated using Tauc plots. SEM micrographs exhibit CZTS spherical granules regularly arranged with some void spaces. The purity of deposited films was investigated using EDX analysis. All the CZTS films exhibit a higher absorption coefficient (α>104) cm-1 and a band gap in the reported range (1.2 to 1.53 eV) can be used as an absorber layer in solar cells.
Volume: 10
Issue: 1
Page: 39-46
Publish at: 2021-03-01

Evaluation of healthcare science student learning styles based VARK analysis technique

10.11591/ijere.v10i1.20718
Izdihar Kamal , Muhammad Khalis Abdul Karim , Mohd Mustafa Awang Kechik , Xinni Ni , Hairil Rashmizal Abdul Razak
This study aimed to evaluate the learning styles among healthcare students and to study the relationship with their academic achievement. This cross-sectional study was conducted among 137 healthcare students from six different courses. Data was collected using a self-administered questionnaire and developed based on the original visual, aural/auditory, read/write, and kinesthetic (VARK) assessment. The questionnaire was divided into two sections: the demographic status and the learning style perspective. A total of 119 respondents (86.8%) has chosen unimodal as their learning styles, while the rest of the 18 respondents (13.2%) choose multimodal as their preferred learning method. Among the unimodal learning styles, visual (32%) and reading (26%) were most preferred among respondents. The auditory and kinesthetic methods of learning were less and accounted for 10% to 20%. Notably, in multimodal learning styles preferences, 4% of students prefer a combination learning style of visual and kinesthetic methods. There was no significant relationship between learning styles and academic achievement using Pearson’s Chi-square test (p>0.05). Hence, both were independent of one another. Hence, some of the dominant learning styles needed to be considered based on their future profession.
Volume: 10
Issue: 1
Page: 255-261
Publish at: 2021-03-01
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