Musa H. Asyali
Antalya Bilim University, Electrical and Electronic Engineer, Faculty Member
- Math provides the keys to unlock the natures secrets.. Therefore, I'm a math and biology/medicine fan researcher..edit
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Bu calismada, pi (TT)sayisini Monte-Carlo metoduyla ve Gregory-Leibniz formuluyle hesaplama yollari arastirilmis ve karsilastirilmistir. Monte-Carlo metodu karesel bir alan icinde kalacak sekilde tekduze dagilimdan uretilen gelisiguzel... more
Bu calismada, pi (TT)sayisini Monte-Carlo metoduyla ve Gregory-Leibniz formuluyle hesaplama yollari arastirilmis ve karsilastirilmistir. Monte-Carlo metodu karesel bir alan icinde kalacak sekilde tekduze dagilimdan uretilen gelisiguzel noktalardan dairesel bir bolgeye dusen noktalari saymaya dayanir. Gregory-Leibniz formulu ise arctanjant fonksiyonun Taylor serisi acilimini yaparak n sayisini bulur. Bu iki metodu da C programlama dilinde gercekledik ve sonuclarini hassasiyet ve hesaplama hizi acisindan karsilastirdik. Elde ettigimiz sonuclara gore, her ne kadar Monte-Carlo metodu anlamasi/anlatmasi daha kolay bir metot ise de, Gregory-Leibniz formulu, 7t sayisini hesaplamak icin daha hassas ve hizli sonuclar uretir.
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Research Interests: Computer Science, Biomedical Engineering, Electroencephalography, Medicine, Control system, and 15 moreHumans, Obstructive sleep apnea, Impulse response, Male, Arousal, Respiratory System, Airway, Dynamic Stability, Chemical Control, Apnea, Electrical And Electronic Engineering, Respiratory Mechanics, Case Control Studies, Pulmonary Gas Exchange, and Continuous Positive Airway Pressure
Research Interests: Computer Science, Electroencephalography, Medicine, Humans, Sleep Quality, and 15 moreObstructive sleep apnea, Sleep, ROC Curve, Time Frequency Analysis, Middle Aged, Arousal, Receiving Operating Characteristic, Adult, Eye Movement, Area Under the Curve, Receiver Operating Characteristics, Power spectral density, Sleep Stages, Psychology and Cognitive Sciences, and Medical and Health Sciences
Although next generation sequencing applications are getting dominant in molecular genetics, there are still many institutions that want to utilize their legacy sequencers as much as possible. An important concern in sequencing services... more
Although next generation sequencing applications are getting dominant in molecular genetics, there are still many institutions that want to utilize their legacy sequencers as much as possible. An important concern in sequencing services is the quality of trace files presented to the customers. In this respect, the quality of the trace files should be screened and low quality files should be handled differently before reaching to customers. The quality scores already present in the trace files provide some useful information, however by incorporating auxiliary information we can improve to reliability of these scores. To this end, we used a feature based supervised classification strategy which requires a set of training and testing trace files qualities of which are determined manually. We tested several machine learning algorithms, namely k-nearest neighbors, Naive Bayes, Support Vector Machines and Random Forest, on a public DNA trace repository. Our results indicate that RF method with only 4 simple features provides a classification accuracy rate of 94.68% with a high level of reliability of concurrence (Kappa=0.8679).
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Harmonics are the major power quality problems in industrial and commercial power systems. Several methods for detection of power system harmonics have been investigated by engineers due to increasing harmonic pollution. Since the... more
Harmonics are the major power quality problems in industrial and commercial power systems. Several methods for detection of power system harmonics have been investigated by engineers due to increasing harmonic pollution. Since the non-integer multiple harmonics (inter and sub-harmonics) become wide spread, the importance of harmonic detection has increased for sensitive filtration. This paper suggests parametric spectral estimation methods for
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... Anahtar Kelimeler: Tomografi, Fan Huzmesi Geri-izdüşüm Metodu. * Bilgisayar Mühendisliği Bölümü, Yaşar Üniversitesi, Bornova 35500, İzmir, musa.asyali@yasar. edu.tr ... [2] İrfan Karagöz, Osman Eroğul. Tıbbi Görüntüleme Sistemleri. ...
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ABSTRACT Liver biopsy is considered to be the gold standard for analyzing chronic hepatitis and fibrosis; however, it is an invasive and expensive approach, which is also difficult to standardize. Medical imaging techniques such as... more
ABSTRACT Liver biopsy is considered to be the gold standard for analyzing chronic hepatitis and fibrosis; however, it is an invasive and expensive approach, which is also difficult to standardize. Medical imaging techniques such as ultrasonography, computed tomography (CT), and magnetic resonance imaging are non-invasive and helpful methods to interpret liver texture, and may be good alternatives to needle biopsy. Recently, instead of visual inspection of these images, computer-aided image analysis based approaches have become more popular. In this study, a non-invasive, low-cost and relatively accurate method was developed to determine liver fibrosis stage by analyzing some texture features of liver CT images. In this approach, some suitable regions of interests were selected on CT images and a comprehensive set of texture features were obtained from these regions using different methods, such as Gray Level Co-occurrence matrix (GLCM), Laws' method, Discrete Wavelet Transform (DWT), and Gabor filters. Afterwards, sequential floating forward selection and exhaustive search methods were used in various combinations for the selection of most discriminating features. Finally, those selected texture features were classified using two methods, namely, Support Vector Machines (SVM) and k-nearest neighbors (k-NN). The mean classification accuracy in pairwise group comparisons was approximately 95% for both classification methods using only 5 features. Also, performance of our approach in classifying liver fibrosis stage of subjects in the test set into 7 possible stages was investigated. In this case, both SVM and k-NN methods have returned relatively low classification accuracies. Our pairwise group classification results showed that DWT, Gabor, GLCM, and Laws' texture features were more successful than the others; as such features extracted from these methods were used in the feature fusion process. Fusing features from these better performing families further improved the classification performance. The results show that our approach can be used as a decision support system in especially pairwise fibrosis stage comparisons.
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ABSTRACT Both neural networks (NN) and Volterra series (VS) are widely used in nonlinear dynamic system identification. In VS approach, the system is modeled using a set of kernel functions that correspond to different order convolutions.... more
ABSTRACT Both neural networks (NN) and Volterra series (VS) are widely used in nonlinear dynamic system identification. In VS approach, the system is modeled using a set of kernel functions that correspond to different order convolutions. Kernels in VS are typically estimated using an orthogonal expansion technique. In this study, we discuss the method of obtaining VS representation of nonlinear systems from their NN models as an alternative approach and compare its modeling performances against the popular Laguerre basis expansion (LBE) technique. In LBE approach, the critical issues are to select a suitable pole parameter and number of basis functions to be used in the expansions, so that the kernels can be accurately represented. We devised novel approaches to address both issues, the pole parameter is selected using a systematic optimization approach and the number of basis functions is decided using the minimum description length criterion. Our preliminary results on synthetic data indicate that when used with these provisions, LBE yields more accurate kernels estimation results than the NN approach. However, LBE is typically used without these provisions in literature. We demonstrate that with its typical use, kernels estimated using the LBE approach can be quite misleading even though the estimation error may seem to be reasonable. Therefore, we suggest the use NN approach as a reference method to confirm the morphology of the kernels estimated via other approaches, including LBE.
... Bio. Eng. Comput. (2006) 44:1031-1051. [5] Ö. ... [7] Doruk A., Türkbay T., Yelboga Z., Çiyiltepe M., Iyisoy A., Sütçigil L., Özşahin A. "Autonomic nervous system imbalance in young adults with developmental... more
... Bio. Eng. Comput. (2006) 44:1031-1051. [5] Ö. ... [7] Doruk A., Türkbay T., Yelboga Z., Çiyiltepe M., Iyisoy A., Sütçigil L., Özşahin A. "Autonomic nervous system imbalance in young adults with developmental stuttering" Bulletin of Clinical Psychopharmacology, 18:274-281, (2008). ...
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Reliability of continuous and dichotomous responses is usually assessed by means of the intraclass correlation coefficient (ICC). We derive the optimal allocation of the number of subjects k and the number of repeated measurements n that... more
Reliability of continuous and dichotomous responses is usually assessed by means of the intraclass correlation coefficient (ICC). We derive the optimal allocation of the number of subjects k and the number of repeated measurements n that minimize the variance of the estimated ICC. Cost constraints are discussed for the case of normally distributed responses. Tables showing optimal choices of k and n are given, along with guidelines for the design of reliability studies in light of our results and those reported by others.
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A serious limitation in microarray analysis is the unreliability of the data generated from low signal intensities. Such data may produce erroneous gene expression ratios and cause unnecessary validation or post-analysis follow-up tasks.... more
A serious limitation in microarray analysis is the unreliability of the data generated from low signal intensities. Such data may produce erroneous gene expression ratios and cause unnecessary validation or post-analysis follow-up tasks. Therefore, elimination of unreliable signal intensities will enhance reproducibility and reliability of gene expression ratios produced from the microarray data. In this study, we applied Fuzzy c-Means
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Segmentation or separation of spots from the background in cDNA microarray images is one of the earlier steps in gene expression data analysis. Performance of the segmentation method may profoundly impact the performance of the subsequent... more
Segmentation or separation of spots from the background in cDNA microarray images is one of the earlier steps in gene expression data analysis. Performance of the segmentation method may profoundly impact the performance of the subsequent stages of data extraction and analysis. Several methods have already been suggested to segment microarray spots. In this study, we propose a new approach
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Morphological filtering techniques are considered in an attempt to eliminate baseline wander in ECG records. Using the sequence processing morphological filters that utilize the basic transformations of mathematical morphology, the... more
Morphological filtering techniques are considered in an attempt to eliminate baseline wander in ECG records. Using the sequence processing morphological filters that utilize the basic transformations of mathematical morphology, the authors have processed ECG records off-line. As the results clearly indicate, the technique selectively removes the baseline variation without introducing any distortion that the hardware or software linear filtering may
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ABSTRACT EEG tools are used for diagnosing and interpreting brain diseases at neurology clinics. In this study, EEG data collected from healthy, migraine, and pregnant women were analyzed using Modified Covariance (a parametric spectral... more
ABSTRACT EEG tools are used for diagnosing and interpreting brain diseases at neurology clinics. In this study, EEG data collected from healthy, migraine, and pregnant women were analyzed using Modified Covariance (a parametric spectral analysis method) and Welch (a non-parametric method) methods, in an attempt to re-evaluate the value EEG in migraine diagnosis. We have also compared the performance of different spectral analysis methods in distinguishing different conditions. Further, we have examined changes in the EEG spectral characteristics that occur due to migraine in the pregnancy term.
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... 978-1-4244-3606-4/09/$25.00 ©2009 IEEE Page 2. olduğu bölgeye bir LED aracılığı ile ışık demeti gönderilmesi ve burdan yansıyan ışığın ölçülmesi ile gerçekleştirilmektedir. Kalp her kasıldığında kan periferik damarlara doğru ...
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... Evaluation of Fatty Liver Ultrasonography Images Semra İçer1, Türkan İkizceli 2, Abdulhakim Coşkun2, Musa Hakan Asyalı1 ... [13] Mustafa Seçil, Temel ultrasonografi ve Doppler, Meta Basım Matbaacılık Hizmetleri, İzmir, 2008 s-118. ...
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A serious limitation in microarray analysis is the unreliability of the data generated from low signal intensities. Such data may produce erroneous gene expression ratios and cause unnecessary validation or post-analysis follow-up tasks.... more
A serious limitation in microarray analysis is the unreliability of the data generated from low signal intensities. Such data may produce erroneous gene expression ratios and cause unnecessary validation or post-analysis follow-up tasks. Therefore, elimination of unreliable signal intensities will enhance reproducibility and reliability of gene expression ratios produced from the microarray data. In this study, we applied Fuzzy c-Means
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In this study, we investigated modeling performances of two popular nonlinear system identification methods, namely fuzzy modeling and Volterra series. In literature a general approach to nonlinear structure modeling does not exist,... more
In this study, we investigated modeling performances of two popular nonlinear system identification methods, namely fuzzy modeling and Volterra series. In literature a general approach to nonlinear structure modeling does not exist, therefore both fuzzy models and Volterra series are interesting and widely used as they can approximate a large class of nonlinear functions. In fuzzy modeling, a dynamic system
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DNA microarray is an important tool for the study of gene activities but the resultant data consisting of thousands of points are error-prone. A serious limitation in microarray analysis is the unreliability of the data generated from low... more
DNA microarray is an important tool for the study of gene activities but the resultant data consisting of thousands of points are error-prone. A serious limitation in microarray analysis is the unreliability of the data generated from low signal intensities. Such data may produce erroneous gene expression ratios and cause unnecessary validation or post-analysis follow-up tasks. In this study, we describe an approach based on normal mixture modeling for determining optimal signal intensity thresholds to identify reliable measurements of the microarray elements and subsequently eliminate false expression ratios. We used univariate and bivariate mixture modeling to segregate the microarray data into two classes, low signal intensity and reliable signal intensity populations, and applied Bayesian decision theory to find the optimal signal thresholds. The bivariate analysis approach was found to be more accurate than the univariate approach; both approaches were superior to a conventional method when validated against a reference set of biological data that consisted of true and false gene expression data. Elimination of unreliable signal intensities in microarray data should contribute to the quality of microarray data including reproducibility and reliability of gene expression ratios.
Research Interests: Algorithms, Research Design, Gene expression, Biological Sciences, Environmental Sciences, and 15 moreHumans, Nucleic Acids, Bayesian decision theory, Microarray Analysis, Monocytes, Mixture Model, Reproducibility of Results, Data Consistency, Bayes Theorem, Reference Values, Biological Data, Endotoxins, Microarray Data, Gene expression profiling, and Gene Expression Data
... Özetçe EKG (Elektro KardiyoGram) kayıtlarının yazılım tabanlı uzman sistemler tarafından yorumlanması 1960'lı yıllara dayanmaktadır. ... Literatürde önerilen YSA modelleri, çok karmaşıkyazılım tabanlı çözümlerdir ve... more
... Özetçe EKG (Elektro KardiyoGram) kayıtlarının yazılım tabanlı uzman sistemler tarafından yorumlanması 1960'lı yıllara dayanmaktadır. ... Literatürde önerilen YSA modelleri, çok karmaşıkyazılım tabanlı çözümlerdir ve bunlar gerçek zamanlı çalışmazlar. ...
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Page 1. Mikroorganizma Türlerinin Ayırma Analizi ile Sınıflandırılması Classification of Microorganism Species using Discriminant Analysis Bekir Hakan Aksebzeci1, Sadık Kara2, Musa Hakan Asyalı3, Yasemin Kahraman4, Özgür Er4, Esma Kaya5,... more
Page 1. Mikroorganizma Türlerinin Ayırma Analizi ile Sınıflandırılması Classification of Microorganism Species using Discriminant Analysis Bekir Hakan Aksebzeci1, Sadık Kara2, Musa Hakan Asyalı3, Yasemin Kahraman4, Özgür Er4, Esma Kaya5, Hatice Özbilge5 ...
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... Using Image Texture Analysis Techniques On B-Scan Images, 1998 IEEE [8] Sobia Nawaz andAmir Hanif Dar, Hepatic Lesions Classification by ... of the IEEE EMBS San Francisco, CA, USA September 1-5, 2004 [11] A. Ahmadian, A. Mostafa,... more
... Using Image Texture Analysis Techniques On B-Scan Images, 1998 IEEE [8] Sobia Nawaz andAmir Hanif Dar, Hepatic Lesions Classification by ... of the IEEE EMBS San Francisco, CA, USA September 1-5, 2004 [11] A. Ahmadian, A. Mostafa, , MD Abolhassani, Y. Salimpour ...
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... Mehmet Akif Özçoban1, Fatma Latifoğlu2, Ahmet Ülgen3, Musa.H. Asyalı4 ... Önerilen yöntem ile ileriki çalışmalarda toplam vücut su oranı tayini ve hemodiyaliz hastalarında vücut kuru ağırlık oranının tespitine yönelik çalışmalar... more
... Mehmet Akif Özçoban1, Fatma Latifoğlu2, Ahmet Ülgen3, Musa.H. Asyalı4 ... Önerilen yöntem ile ileriki çalışmalarda toplam vücut su oranı tayini ve hemodiyaliz hastalarında vücut kuru ağırlık oranının tespitine yönelik çalışmalar yapılması amaçlanmaktadır. Abstract ...
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Images which are obtained in clinical radiology are generally evaluated visually. Some information which is available in the images, but not possible to be seen visually can be useful for diagnosis of some diseases. Cyst hydatid which is... more
Images which are obtained in clinical radiology are generally evaluated visually. Some information which is available in the images, but not possible to be seen visually can be useful for diagnosis of some diseases. Cyst hydatid which is a parasitic liver disease is still an important health problem in countries where animal breeding is widespread. In this study, we aimed
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Research Interests: Biomedical Engineering, Data Mining, Heart rate variability, Heart Failure, Humans, and 15 moreStandard Deviation, Female, Male, Heart rate, Young Adult, Aged, Middle Aged, Classification and Regression Tree, Adult, Chronic Heart Failure, Retrospective Studies, Clinical Study, Non parametric statistics, Electrical And Electronic Engineering, and Exhaustive Search
Research Interests: Physiology, Electrophysiology, Drosophila melanogaster, Information Processing, Patch-clamp and imaging techniques, and 15 moreSignal Transduction, Animals, Negative Feedback, Light, Temperature, Feedback, The, Synaptic Transmission, Microelectrodes, Medical Physiology, Nervous System, Visual Evoked Potentials, Wireless Control Network, Interneurons, and General Physiology
Research Interests: Biomedical Engineering, Electroencephalography, Control system, Humans, Obstructive sleep apnea, and 12 moreImpulse response, Male, Statistical Significance, Steady state, Arousal, Respiratory System, Dynamic Stability, Chemical Control, Electrical And Electronic Engineering, Respiratory Mechanics, Case Control Studies, and Pulmonary Gas Exchange
Research Interests: Algorithms, Biomedical Engineering, Signal Processing, Nonlinear dynamics, Drosophila melanogaster, and 12 moreComputer Simulation, Volterra series, Mathematical Analysis, Animals, Light, Multiple Regression, Nonlinear system, Nonlinear system identification, Discrete Time Systems, Laguerre function, Electrical And Electronic Engineering, and Kernel Estimate
In this study, identification of nonlinear systems via Laguerre network based fuzzy model is introduced. We first describe the proposed modeling approach in detail and suggest a fast learning scheme for its training. The proposed approach... more
In this study, identification of nonlinear systems via Laguerre network based fuzzy model is introduced. We first describe the proposed modeling approach in detail and suggest a fast learning scheme for its training. The proposed approach is applied in three dynamic system modeling problems including Box–Jenkins gas furnace data and forced Van der Pol oscillator. When we compare the performance of the proposed approach against the classical Sugeno and adaptive network based fuzzy inference system modeling, our approach is found to have superior modeling performance and generalization capability.
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Research Interests: Electroencephalography, Time-Frequency Analysis, Humans, Sleep Quality, Obstructive sleep apnea, and 11 moreSleep, ROC Curve, Middle Aged, Arousal, Receiving Operating Characteristic, Adult, Eye Movement, Visual Quality Inspection Systems, Area Under the Curve, Power spectral density, and Sleep Stages
In this study, we have analyzed electroencephalography (EEG) signals to investigate the following issues, (i) which frequencies and EEG channels could be relatively better indicators of preference (like or dislike decisions) of consumer... more
In this study, we have analyzed electroencephalography (EEG) signals to investigate the following issues, (i) which frequencies and EEG channels could be relatively better indicators of preference (like or dislike decisions) of consumer products, (ii) timing characteristic of "like" decisions during such mental processes. For this purpose, we have obtained multichannel EEG recordings from 15 subjects, during total of 16 epochs of 10 s long, while they were presented with some shoe photographs. When they liked a specific shoe, they pressed on a button and marked the time of this activity and the particular epoch was labeled as a LIKE case. No button press meant that the subject did not like the particular shoe that was displayed and corresponding epoch designated as a DISLIKE case. After preprocessing, power spectral density (PSD) of EEG data was estimated at different frequencies (4, 5, …, 40 Hz) using the Burg method, for each epoch corresponding to one shoe presentation. Each subject's data consisted of normalized PSD values (NPVs) from all LIKE and DISLIKE cases/epochs coming from all 19 EEG channels. In order to determine the most discriminative frequencies and channels, we have utilized logistic regression, where LIKE/DISLIKE status was used as a categorical (binary) response variable and corresponding NPVs were the continuously valued input variables or predictors. We observed that when all the NPVs (total of 37) are used as predictors, the regression problem was becoming ill-posed due to large number of predictors (compared to the number of samples) and high correlation among predictors. To circumvent this issue, we have divided the frequency band into low frequency (LF) 4-19 Hz and high frequency (HF) 20-40 Hz bands and analyzed the influence of the NPV in these bands separately. Then, using the p-values that indicate how significantly estimated predictor weights are different than zero, we have determined the NPVs and channels that are more influential in determining the outcome, i.e., like/dislike decision. In the LF band, 4 and 5 Hz were found to be the most discriminative frequencies (MDFs). In the HF band, none of the frequencies seemed offer significant information. When both male and female data was used, in the LF band, a frontal channel on the left (F7-A1) and a temporal channel on the right (T6-A2) were found to be the most discriminative channels (MDCs). In the HF band, MDCs were central (Cz-A1) and occipital on the left (O1-A1) channels. The results of like timings suggest that male and female behavior for this set of stimulant images were similar.