Department of Information Systems Engineering

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http://hdl.handle.net/20.500.11905/1214

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Browsing Department of Information Systems Engineering by Subject "information technology"

Now showing 1 - 5 of 5
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    A CASE STUDY FOR DESIGNING AN ADAPTIVE LEARNING ENVIRONMENT BY APPLYING VARK MODEL
    (2017-05-02) Jaballa, Rabieaa Abdusalam Massaud; Eryılmaz, Meltem
    The styles of learning are personal traits that affect how students relate with their learning environment, peers, and instructor. Four of the most popular are reading / writing, visual, auditory and kinetic, which used by students to gain information. Number of students is visual learners, while others are kinesthetic or audio or read /write learners. While some other students use a combination all of them to gain information, they seem to have preferences in how to learn better. Teachers must teach as more of these preferences as possible, in order to assist students learn. Teachers can put together these learning styles into core curriculum activities so that students can succeed in their classes. This study shows some parts of development framework to identify students learning styles and combination it automatically. This system is based on VARK learning style model and VARK questionnaire to measure students’ learning styles, it is hosting by internet to help students to use it. This study has used a sample of participants that consisted of 50 of engineering students from Atilim University. In addition, this study contain, an experimental design with a pre-post test Control group was utilized. Accordingly analysis of the data, the results show that distribution for t-test for two groups (Control group and Experimental group) was normality distribution and it was determined that the difference in mean scores between the Experimental group and the Control group was significantly in help of the Experimental group and the achievement level in the Experimental group, which applied the VARK teaching model, was higher compared to the Control group. In addition, student satisfaction questionnaire instrument, 10-items that measure students’ satisfaction by using the system, as the results found that students’ satisfaction with the system was significant very high.
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    A HYBRID METHOD FOR MISSING VALUE IMPUTATION
    (2022-02-16) Al-Brge, Basma; Koyuncu, Murat
    Missing data arises in almost all serious statistical analyses. Statistical analyses have a variety of methods to handle missing data, including some relatively simple approaches that can often yield reasonable results such as the random imputation approach. The missing data imputation process must be modeled in order to perform imputations correctly. Using datasets in empirical applications is very common to perform some tasks; however, missing values in datasets should be extracted from the datasets or should be estimated before they are used for processing to produce correct association rules or clustering in the preprocessing stage of data mining and processing. In this thesis, a hybrid approach is used that combines K-Nearest Neighbor (KNN) with Singular Value Decomposition (SVD) algorithm to improve the data imputation and produce data with high correlation with original missing values. The test results of the proposed hybrid method are compared with the results of several alternative methods for different rate of missing values and the results of the proposed method yields better performance than the others. The results are also compared with the reported results in the literature to give an idea about its performance.
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    ENHANCEMENTS IN FINGERPRINT AUTHENTICATION
    (2017-06-02) Alsubaihawi, Mohammed Abdulraheem Taqi; BOSTAN, Atila
    Fingerprint identification and verification tasks are among the most challenging tasks in image processing and machine learning domains. Fingerprint processing presents a key issue in the biometric technologies and information security. According to the fraction of the people population based on the complete detection of the biometric fingerprint feature such as ridge structure, incomplete (portion) fingerprint image identification and verification task is very difficult to be accomplished. The main challenge in this problem is that the partial loss of the ridge structure in the incomplete fingerprint image. In this thesis, we studied the effectiveness of global feature approach in fingerprint identification and verification task that can deal with the partial image loss or incomplete fingerprint image. Global feature vector extraction is the main global approach that we contribute in this thesis. In this case, we implemented global geometrics based feature extraction for fingerprint identification and verification task. A set of global features (seven-moment values) were extracted from the partial fingerprint (incomplete fingerprint image). The study shows that global feature vector can more efficiently deal with incomplete fingerprint recognition problem when compared with the classical approach to the fingerprint identification and verification problem which is based on extracting minutia features from the fingerprint rides as well as the pores in different feature extraction levels. The studied system has been tested using a database that was randomly generated out of some random incomplete fingerprint images. Randomly generated incomplete fingerprint images were sorted into 10 groups according to the size of the missing part in each image. Then we randomly selected random images from each group to compose a new challenge dataset to be tested in two different approaches which are global, and Local feature extraction approaches. The experimental results show that global approach has about 87% while the local approach has 17% of identification and verification effectiveness. This means global approach improves the performance of the fingerprint identification and verification system on partial (incomplete) fingerprint images by 70% more than the classical approach.
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    PERCEPTIONS AND ATTITUDES OF LIBYAN HEALTHCARE PROVIDER TOWARDS ELECTRONIC HEALTH RECORDS
    (2022-02-17) Osman, Magdah; Çağıltay, Nergiz Ercil
    Electronic health records may have several benefits for hospitals, health professionals as well as patients. Electronic Health Record (EHR) systems provide basic clinical data that increase the quality of healthcare provided to citizens and benefits the community. The aim of this study is to evaluate and estimate the healthcare providers’ perceptions and attitudes towards the use of EHR in their environments in Libya. A sample of 110 health sector participants from various medical specialties in Libyan hospitals was targeted. The purpose of this research was to determine the perceptions and attitudes of Libyan healthcare providers towards EHR usage, by analyzing their demographics, organizational characteristics and the social, technical factors that possibly affect the EHR usage. Accordingly, survey method based on the previous studies is implemented through Survey Monkey environment; after the data collection was completed SPSS was used for statistical analysis, the results of the research lead to EHR factors Management support, Involvement and Adequate training have positive correlations with healthcare provider’s perceptions and Attitudes, while Autonomy and healthcare provider-patient communication have negative correlations with healthcare provider’s perceptions and had significant strong positive correlations with Attitude.
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    UNIVERSITY STUDENTS’ ATTITUDES TOWARDS CAPTCHA USE
    (2022-02-15) ELATRESH, Khalid; KOYUNCU, Murat
    Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA) is a type of techniques that is utilized in order to be able to distinguish the actual human users from bots or for determining the users that are authorized to access a website or a file on the Internet. This thesis aims at determining attitudes of Libyan students towards different types of CAPTCHA in WWW environment. It also analyzes user attitudes according to demographic and Internet usage information including gender, age, education level, for how many years they have been using the Internet, and how often they use the Internet. To fulfill the purpose of the study, a questionnaire was prepared and Libyan students studying in different levels and departments answered to the questionnaire that is published through the Internet. The data obtained is processed using SPSS 18.0 software package. The obtained results reflect that the participants are familiar with all of types of CAPTCHA since they use them every day through navigating in the Web for books or scientific articles. However, user familiarity for text-based CAPTCHA is higher than the others. The No CAPTCHA reCAPTCHA type is the most favored one from different perspectives including error freeness, easiness, and security. Therefore, we conclude that the No CAPTCHA reCAPTCHA type is the most preferred type by users.