Meslek Yüksek Okulu
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Browsing Meslek Yüksek Okulu by Department "Çankaya Üniversitesi, Meslek Yüksek Okulu, Bilgisayar Programcılığı Bölümü"
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Conference Object Citation Count: Özaydın, Selma. "A Graphical Speech Analysis Teaching Tool", 2022 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2022, 23 November 2022through 25 November 2022, pp. 23-26.A Graphical Speech Analysis Teaching Tool(2022) Özaydın, Selma; 253019The widespread use of digital speech processing in today's technologies causes many electronics and computer engineering students to need a basic background in these subjects. The paper describes a toolbox designed to support undergraduate or graduate level courses on speech processing. The proposed educational toolbox is designed as a virtual lab for basic operations in digital speech processing-based courses. This graphical user interface (GUI) based speech analysis algorithm is built with six main function modules, which are signal input, noise addition, up-sampling/down-sampling, time domain feature analysis, pitch detection and frequency domain analysis. The toolbox involves different operations for measuring important speech feature parameters such as pitch, energy, zero-crossing ratio, FFT and power spectrum of an input speech signal. The toolbox has also been developed to easily manipulate and add some other possible speech processing methods. It is thought that the tool will make it easier for students to understand the methods that form the basis of digital speech processing, increase the interest in the lesson with its visual outputs, and allow new methods to be added easily when desired thanks to its simple and modular structure. The main aim of this paper to show how such a tool facilitates students understanding of technical concepts introduced in speech courses. © 2022 IEEE.Conference Object Citation Count: Özçetin, M.; Maraş, Hadi Hakan. "CBS Tabanlı Suç Analizi Yöntemleri", Türkiye Ulusal Fotogrametri ve Uzaktan Algılama Birliği VII. Teknik Sempozyumu (TUFUAB’2013), 23-25 Mayıs 2013, KTÜ, Trabzon, 2013.CBS Tabanlı Suç Analizi Yöntemleri(2013) Özçetin, M.; Maraş, Hadi Hakan; 34410Coğrafi Bilgi Sistemleri (CBS) günlük hayatımızda önemi sürekli olarak artan uygulamalara sahiptir. CBS’nin popüler ve kritik uygulama alanlarından biri de mekânsal suç analizidir. Günümüzde suç oranları artış göstermekte ve bu yüzden suç eğilimlerini analiz etmek ve suçu önleyici tedbirler almak büyük önem arz etmektedir. Suçlar çoğu zaman mekânsal ve zamansal modeller göstermektedir. Örneğin, bazı suç türleri bazı lokasyonlarda nispeten yüksek oranlarda işlenebilmektedir. Bazıları ise gün içinde belli saat aralıklarında yüksek oranlarda olabilmektedir. Klasik suç analiz yöntemlerine coğrafi destek eklemek, tablosal veya istatistiksel metotların sunamayacağı son derece önemli ve müstesna faydalar sağlayabilir. Örneğin, belli bir suç türünün mekânsal dağılımını görmek veya farklı suç türlerinin lokasyonlarını harita üzerinde karşılaştırmak, karar verme pozisyonundaki yöneticilere kritik ve önemli ipuçları verebilir. Bu yüzden, suç analiz yöntemlerine mekânsal boyut katmak emniyet birimlerindeki çalışmalara önemli bir destek sağlamaktadırArticle Citation Count: Özaydın, Selma (2018). "Comparative Analysis of Early Studies on Turkish Whistle Language and a Case Study on Test Conditions", Open Journal of Modern Linguistics, Vol. 8, No. 4, pp. 126-136.Comparative Analysis of Early Studies on Turkish Whistle Language and a Case Study on Test Conditions(2018) Özaydın, Selma; 253019This paper examines the early studies on Turkish Whistle Language and it argues that they have some controversial results. The study considers these issues need to be discussed and searched again in terms of linguistic and phonetic form. Unfortunately, there are few research studies on Turkish whistle language and most of them were performed nearly fifty years ago despite the fact that this language still has been used in Kuskoy region. Therefore, the findings of these early research studies could give valuable information to start to a new research study on the subject. The first scientific study on Turkish Whistle language was performed by a French scientist R.G. Busnel with his multidisciplinary research team in 1967. Some of this research’s results were published in the book. A Turkish scientist O. Baskan also participated in Busnel’s research group and published a paper on TWsL in 1968. However, some assertions such as people having a tendency to understand the Turkish whistle language with three vowels and three consonants have not been in the research results of R.G. Busnel. In addition, a Turkish scientist D. Aksan in Turkey had performed another research at Kuskoy region with his own team. Their test methods were different from the previous ones. This paper analyzes these research results on a comparative basis and presents the common and conflicted issues to discuss the uncertain points. The comparative evaluation of these past research studies aims to highlight the controversial position of the results on Turkish Whistle Language. In this scope, this paper opens a discussion about the selection of test conditions for an acoustic and linguistic analysis of the Turkish whistle language.Article Citation Count: Özaydın, Selma; Ahmad, Imteyaz (2024). "Comparative Performance Analysis of Filtering Methods for Removing Baseline Wander Noise from an ECG Signal", Fluctuation and Noise Letters.Comparative Performance Analysis of Filtering Methods for Removing Baseline Wander Noise from an ECG Signal(2024) Özaydın, Selma; Ahmad, Imteyaz; 253019ECG signals play a vital role in the diagnosis of cardiovascular conditions. However, they often su®er from the e®ects of various noise sources, including baseline wandering, respiratory artifact noise, power line interference and electrode motion artifacts. To overcome these challenges, it is imperative to implement low-frequency signal noise reduction strategies. Such strategies aim to signi¯cantly improve the quality of ECG signals, thus promoting more accurate and reliable diagnosis of cardiovascular disorders. This paper conducts a comparative analysis to assess the e®ectiveness of commonly used ¯ltering and wavelet techniques in reducing Baseline Wander (BW) noise within ECG signals generated by the in°uence of breathing or electrode movements. It is common to observe the selection and evaluation of only one particular technique in the existing literature. In contrast, this study aims to provide a comprehensive comparative analysis, providing insight into the performance and relative merits of di®erent techniques. Our research uses both ¯ltering and Discrete Wavelet Transform (DWT) techniques in baseline noise removal. In this context, a reference point is established utilizing noise-free signals and a meticulous investigation of the wavelet-based approach that most e®ectively eliminates the resulting noise is provided. Subsequently, we assess the reference input and output signal via Signal-to-Noise Ratio (SNR) and Kolmogorov–Smirnov statistical test measurements. The most important contribution of this work to the scienti¯c community resides in the comprehensive examination of IIR/FIR-based and wavelet method-based ¯ltering methods capable of yielding the highest SNR levels across various ECG signals with various types of BW noise. Additionally, the e®ectiveness of the Chebychev-II ¯lter in BW noise removal is highlighted. Our study was conducted using the MATLAB platform and code command lines were shared to facilitate the reproduction of our study by other researchers. It is considered that this study will be an important reference in the selection of e®ective techniques for removing BW noise within ECG signals.Conference Object Citation Count: Özaydın, Selma. "Design of a Voice Activity Detection Algorithm based on Logarithmic Signal Energy", International Conference on Electrical and Computing Technologies and Applications (ICECTA), pp. 19-22, 2022.Design of a Voice Activity Detection Algorithm based on Logarithmic Signal Energy(IEEE, 2022) Özaydın, Selma; 253019This article presents a new method for calculating the signal energies of speech segments in voice activity detection algorithms. In the study, the µ-law signal compression method is adapted to calculate short-term signal energies. A simple voice activity detection (VAD) algorithm is designed to demonstrate the effectiveness of the proposed method. The same VAD algorithm was also run with two different conventional energy calculation formulas and the performance of each VAD was evaluated using time-domain short-time energy features. The G729 standard VAD algorithm was also used for performance comparison. During the test of the analyzed detectors, many kinds of input speech signals with various types of background environmental noise, such as restaurants, vehicles, and streets, were tested. Using the new energy calculation method, the VAD detector has improved detection accuracy compared to VAD detectors based on the other two energy methods and was able to effectively identify voice-active regions even in noisy conditions at low SNR levels. The results revealed that the VAD detector designed with the proposed new energy calculation formula outperforms traditional energy-based voice activity detection methods and provides noticeable increases in detection rate even under adverse conditions.Article Citation Count: Ahmad, Imteyaz; Özaydın, Selma (2023). "ECG Signal Denoising with SciLab", International Journal of Intelligent Systems and Applications in Engineering, Vol. 11, No. 4, pp. 853-859.ECG Signal Denoising with SciLab(2023) Ahmad, Imteyaz; Özaydın, Selma; 253019This paper presents a study on de-noising electrocardiogram (ECG) signals using Scilab, an open-source software package known for its signal processing capabilities. ECG signals are often contaminated by various noise sources, which can reduce the accurate diagnosis and monitoring of heart health. In this work, digital signal processing methods such as Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters are used to effectively suppress noise while preserving the essential features of the ECG waveform. We explore main noise sources that commonly affect ECG recordings, such as baseline wandering noise, power-line interference, and muscle artifacts, and discuss their respective challenges. The de-noising methods has been extensively evaluated and demonstrated its ability to improve signal quality and diagnostic accuracy by eliminating noise artifacts. The results highlight Scilab's potential for de-noising ECG signals and its importance in improving patient care and biomedical signal processing applications. The efficacy of the de-noising methods is thoroughly evaluated through comparative analyses with other commonly used de-noising approaches. Experimental results demonstrate its superiority in preserving the QRS complex while efficiently eliminating noise artifacts, leading to more accurate and reliable diagnostic information. In conclusion, this paper presents a comprehensive study on de-noising ECG signals using Scilab, offering a valuable contribution to the field of biomedical signal processing. Researchers and practitioners in the domain of ECG signal processing can benefit from the insights and techniques presented herein to advance their studies and further applications.Conference Object Citation Count: Özaydın, Selma. "Evaluation of Acoustic Phonetic Properties of Turkish Whistle Language", 4.international symposium of philology, 2018.Evaluation of Acoustic Phonetic Properties of Turkish Whistle Language(2018) Özaydın, Selma; 253019Conference Object Citation Count: Alak, Iman Khalil; Özaydın, Selma. "Speech Denoising with Maximal Overlap Discrete Wavelet Transform," 2022 International Conference on Electrical and Computing Technologies and Applications (ICECTA), Ras Al Khaimah, United Arab Emirates, 2022, pp. 27-30.Speech Denoising with Maximal Overlap Discrete Wavelet Transform(IEEE, 2022) Alak, Iman Khalil; Özaydın, Selma; 253019In this paper, the effectiveness of the maximum overlapping discrete wavelet transform (MODWT) method on denoising the speech signal is tested and examined. Ensuring the intelligibility of the speech signal in noisy environments by separating it from the noise is a widely researched topic today. On the other hand, being able to recover the original speech from the noisy signal with minimal distortion is a challenge due to the difficulties in removing the background noise. Numerous factors in environmental noise environments can interfere with the signal. In this study, the performance of some discrete wavelets transform methods is experimentally analyzed using different wavelet filters. The analysis program was carried out in the MATLAB environment. As the input noise speech signal, speech sounds containing different environmental background noises (train, car, station, plane, etc.) were analyzed. During the tests, these noisy input signals were filtered out from the speech signal by wavelet analysis. The input noisy speech signal is decomposed into wavelet coefficients with different thresholding methods. The reconstructed speech was compared by measuring the signal-to-noise ratio (SNR) values between the noisy input signal and the smoothed output signals. The scientific contributions of the study include a detailed comparative analysis of the performances of various wavelet methods against different background environmental noises.
