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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14411/18
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Article Citation - WoS: 44Citation - Scopus: 84Text Messaging-Based Medical Diagnosis Using Natural Language Processing and Fuzzy Logic(Hindawi Ltd, 2020-09-29) Omoregbe, Nicholas A. I.; Ndaman, Israel O.; Misra, Sanjay; Abayomi-Alli, Olusola O.; Damasevicius, RobertasThe use of natural language processing (NLP) methods and their application to developing conversational systems for health diagnosis increases patients' access to medical knowledge. In this study, a chatbot service was developed for the Covenant University Doctor (CUDoctor) telehealth system based on fuzzy logic rules and fuzzy inference. The service focuses on assessing the symptoms of tropical diseases in Nigeria. Telegram Bot Application Programming Interface (API) was used to create the interconnection between the chatbot and the system, while Twilio API was used for interconnectivity between the system and a short messaging service (SMS) subscriber. The service uses the knowledge base consisting of known facts on diseases and symptoms acquired from medical ontologies. A fuzzy support vector machine (SVM) is used to effectively predict the disease based on the symptoms inputted. The inputs of the users are recognized by NLP and are forwarded to the CUDoctor for decision support. Finally, a notification message displaying the end of the diagnosis process is sent to the user. The result is a medical diagnosis system which provides a personalized diagnosis utilizing self-input from users to effectively diagnose diseases. The usability of the developed system was evaluated using the system usability scale (SUS), yielding a mean SUS score of 80.4, which indicates the overall positive evaluation.Article Citation - WoS: 37Citation - Scopus: 43A Computationally Efficient Method for Hybrid Eeg-Fnirs Bci Based on the Pearson Correlation(Hindawi Ltd, 2020-01) Hasan, Mustafa A. H.; Khan, Muhammad U.; Mishra, DeeptiA hybrid brain computer interface (BCI) system considered here is a combination of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). EEG-fNIRS signals are simultaneously recorded to achieve high motor imagery task classification. This integration helps to achieve better system performance, but at the cost of an increase in system complexity and computational time. In hybrid BCI studies, channel selection is recognized as the key element that directly affects the system's performance. In this paper, we propose a novel channel selection approach using the Pearson product-moment correlation coefficient, where only highly correlated channels are selected from each hemisphere. Then, four different statistical features are extracted, and their different combinations are used for the classification through KNN and Tree classifiers. As far as we know, there is no report available that explored the Pearson product-moment correlation coefficient for hybrid EEG-fNIRS BCI channel selection. The results demonstrate that our hybrid system significantly reduces computational burden while achieving a classification accuracy with high reliability comparable to the existing literature.Article Citation - WoS: 1Citation - Scopus: 2Oscillation Results for a Class of Nonlinear Fractional Order Difference Equations with Damping Term(Hindawi Ltd, 2020-06-01) Selvam, A. George Maria; Alzabut, Jehad; Jacintha, Mary; Ozbekler, Abdullah; Liu, LishanThe paper studies the oscillation of a class of nonlinear fractional order difference equations with damping term of the form Delta[psi(lambda)z(eta) (lambda)] + p(lambda)z(eta) (lambda) + q(lambda)F(Sigma(lambda-1+mu)(s=lambda 0) (lambda - s - 1)((-mu)) y(s)) = , where z(lambda) = a(lambda) + b(lambda)Delta(mu) y(lambda), Delta(mu) stands for the fractional difference operator in Riemann-Liouville settings and of order mu, 0 < mu <= 1, and eta >= 1 is a quotient of odd positive integers and lambda is an element of N lambda 0+1-mu. New oscillation results are established by the help of certain inequalities, features of fractional operators, and the generalized Riccati technique. We verify the theoretical outcomes by presenting two numerical examples.Article Citation - WoS: 105Citation - Scopus: 116(α<i>,</I>ψ)-meir-keeler Contraction Mappings in Generalized <i>b</I>-metric Spaces(Hindawi Ltd, 2018) Karapinar, Erdal; Czerwik, Stefan; Aydi, HassenWe present a fixed point theorem for generalized (alpha, Psi)-Meir-Keeler type contractions in the setting of generalized b-metric spaces. The presented results improve, generalize, and unify many existing famous results in the corresponding literature.Article Citation - WoS: 31Citation - Scopus: 34Development of Decision Support Model for Selecting a Maintenance Plan Using a Fuzzy Mcdm Approach: a Theoretical Framework(Hindawi Ltd, 2018-11-01) Abdulgader, Fathia Sghayer; Eid, Rajeh; Rouyendegh (B Erdebilli), Babak Daneshvar; Rouyendegh , Babak DaneshvarIn complex decision making, using multicriteria decision-making (MCDM) methodologies is the most scientific way to ensure an informed and justified decision between several alternatives. MCDMs have been used in different ways and with several applications that proved their efficiency in achieving this goal. In this research, the advantages and disadvantages of the different MCDM methodologies are studied, along with the different techniques implemented to increase their accuracy and precision. The main aim of the study is to develop a hybrid MCDM process that combines the strengths of several MCDM methods and apply it to choose the best fit maintenance policy/strategy for industrial application. Moreover, fuzzy linguistic terms are utilized in all of the used MCDM techniques in order to eliminate the uncertainty and ambiguity of the results. Through an extensive literature review performed on studies that have used MCDM methods in a hybrid context and using fuzzy linguistic terms, a model is developed to use fuzzy DEMATEL-AHP-TOPSIS hybrid technique. The model with its application is the first of its kind, which combines the strengths of fuzzy DEMATEL in establishing interrelationships between several criteria, as well as performing a pairwise comparison between the criteria for prioritization using the fuzzy AHP method. Thereafter, the alternatives are compared using fuzzy TOPSIS method by establishing negative and positive solutions and calculating the relative closeness for each of the alternatives. Furthermore, six main criteria, twenty criteria, and five alternatives are selected from the literature for the model application.Article Citation - WoS: 27Citation - Scopus: 35Security Awareness Level of Smartphone Users: an Exploratory Case Study(Hindawi Ltd, 2019-05-13) Koyuncu, Murat; Pusatli, TolgaAs smartphone technology becomes more and more mature, its usage extends beyond and covers also applications that require security. However, since smartphones can contain valuable information, they normally become the target of attackers. A physically lost or a hacked smartphone may cause catastrophic results for its owner. To prevent such undesired events, smartphone users should be aware of existing threats and countermeasures to be taken against them. Therefore, user awareness is a critical factor for smartphone security. This study investigates the awareness level of smartphone users for different security-related parameters and compares the awareness levels of different user groups categorized according to their demographic data. It is based on a survey study conducted on a population with a different range of age, education level, and IT security expertise. According to the obtained results, in general, the awareness level of participants is fairly low, which needs considerable improvement. In terms of age, the oldest group has the lowest level followed by the youngest group. Education level, in general, has a positive effect on the awareness level. Having knowledge about IT is another factor increasing the security awareness level of smartphone users.Article Citation - WoS: 14Citation - Scopus: 35Sentimental Analysis of Twitter Users From Turkish Content With Natural Language Processing(Hindawi Ltd, 2022-04-13) Balli, Cagla; Guzel, Mehmet Serdar; Bostanci, Erkan; Mishra, AlokArtificial Intelligence has guided technological progress in recent years; it has shown significant development with increased academic studies on Machine Learning and the high demand for this field in the sector. In addition to the advancement of technology day by day, the pandemic, which has become a part of our lives since early 2020, has led to social media occupying a larger place in the lives of individuals. Therefore, social media posts have become an excellent data source for the field of sentiment analysis. The main contribution of this study is based on the Natural Language Processing method, which is one of the machine learning topics in the literature. Sentiment analysis classification is a solid example for machine learning tasks that belongs to human-machine interaction. It is essential to make the computer understand people emotional situation with classifiers. There are a limited number of Turkish language studies in the literature. Turkish language has different types of linguistic features from English. Since Turkish is an agglutinative language, it is challenging to make sentiment analysis with that language. This paper aims to perform sentiment analysis of several machine learning algorithms on Turkish language datasets that are collected from Twitter. In this research, besides using public dataset that belongs to Beyaz (2021) to get more general results, another dataset is created to understand the impact of the pandemic on people and to learn about public opinions. Therefore, a custom dataset, namely, SentimentSet (Balli 2021), was created, consisting of Turkish tweets that were filtered with words such as pandemic and corona by manually marking as positive, negative, or neutral. Besides, SentimentSet could be used in future researches as benchmark dataset. Results show classification accuracy of not only up to similar to 87% with test data from datasets of both datasets and trained models, but also up to similar to 84% with small "Sample Test Data" generated by the same methods as SentimentSet dataset. These research results contributed to indicating Turkish language specific sentiment analysis that is dependent on language specifications.Article Citation - WoS: 4Citation - Scopus: 6On the Oscillation of Even-Order Nonlinear Differential Equations With Mixed Neutral Terms(Hindawi Ltd, 2021-10-14) Kaabar, Mohammed K. A.; Özbekler, Abdullah; Grace, Said R.; Alzabut, Jehad; Ozbekler, Abdullah; Siri, Zailan; Özbekler, Abdullah; Mathematics; MathematicsThe oscillation of even-order nonlinear differential equations (NLDiffEqs) with mixed nonlinear neutral terms (MNLNTs) is investigated in this work. New oscillation criteria are obtained which improve, extend, and simplify the existing ones in other previous works. Some examples are also given to illustrate the validity and potentiality of our results.Article Citation - WoS: 20Citation - Scopus: 48Some Common Fixed Point Theorems in Partial Metric Spaces(Hindawi Ltd, 2011-01) Karapinar, Erdal; Yuksel, Ugur; Karapnar, ErdalMany problems in pure and applied mathematics reduce to a problem of common fixed point of some self-mapping operators which are defined on metric spaces. One of the generalizations of metric spaces is the partial metric space in which self-distance of points need not to be zero but the property of symmetric and modified version of triangle inequality is satisfied. In this paper, some well-known results on common fixed point are investigated and generalized to the class of partial metric spaces.Article Citation - WoS: 8Citation - Scopus: 9Life Behavior of a System Under Discrete Shock Model(Hindawi Ltd, 2012-01) Eryilmaz, SerkanWe study the life behavior of a system which is subjected to shocks of random magnitudes over discrete time periods. We obtain the survival function and mean time to failure of the system assuming that the sizes of the shocks follow a discrete probability distribution under cumulative and mixed shock models.