Browsing by Subject "PCA"

Now showing 1 - 7 of 7

Open Access
Classification of histopathological cancer stem cell images in h&e stained liver tissues
(2016-03) Akbaş, Cem Emre
Microscopic images are an essential part of cancer diagnosis process in modern medicine. However, diagnosing tissues under microscope is a time-consuming task for pathologists. There is also a signi cant variation in pathologists' decisions on tissue labeling. In this study, we developed a computer-aided diagnosis (CAD) system that classi es and grades H&E stained liver tissue images for pathologists in order to speed up the cancer diagnosis process. This system is designed for H&E stained tissues, because it is cheaper than the conventional CD13 stain. The rst step is labeling the tissue images for classi cation purposes. CD13 stained tissue images are used to construct ground truth labels, because in H&E stained tissues cancer stem cells (CSC) cannot be observed by naked eye. Feature extraction is the next step. Since CSCs cannot be observed by naked eye in H&E stained tissues, we need to extract distinguishing texture features. For this purpose, 20 features are chosen from nine di erent color spaces. These features are fed into a modi ed version of Principal Component Analysis (PCA) algorithm, which is proposed in this thesis. This algorithm takes covariance matrices of feature matrices of images instead of pixel values of images as input. Images are compared in the eigenspace and classi es them according to the angle between them. It is experimentally shown that this algorithm can achieve 76.0% image classi cation accuracy in H&E stained liver tissues for a three-class classi cation problem. Scale invariant feature transform (SIFT), local binary patterns (LBP) and directional feature extraction algorithms are also utilized to classify and grade H&E stained liver tissues. It is observed in the experiments that these features do not provide meaningful information to grade H&E stained liver tissue images. Since our aim is to speed up the cancer diagnosis process, computationally e cient versions of proposed modi ed PCA algorithm are also proposed. Multiplication-free cosine-like similarity measures are employed in the modi ed PCA algorithm and it is shown that some versions of the multiplication-free similarity measure based modi ed PCA algorithm produces better classi cation accuracies than the standard modi ed PCA algorithm. One of the proposed multiplication-free similarity measures achieves 76.0% classi cation accuracy in our dataset containing 454 images of three classes.
Open Access
Correlations in metal release profiles following sorption by Lemna minor
(Taylor and Francis Inc., 2016) Tunca, E. Ü.; Ölmez, T.T.; Özkan, A. D.; Altındağ, A.; Tunca, E.; Tekinay, T.
ABSTRACT: Following the rapid uptake of contaminants in the first few hours of exposure, plants typically attempt to cope with the toxic burden by releasing part of the sorbed material back into the environment. The present study investigates the general trends in the release profiles of different metal(loid)s in the aquatic macrophyte Lemna minor and details the correlations that exist between the release of metal(loid) species. Water samples with distinct contamination profiles were taken from Nilüfer River (Bursa, Turkey), Yeniçağa Lake (Bolu, Turkey), and Beyşehir Lake (Konya, Turkey) and used for release studies; 36 samples were tested in total. Accumulation and release profiles were monitored over five days for 11 metals and a metalloid (208Pb, 111Cd, 52Cr,53Cr,60Ni,63Cu,65Cu,75As,55Mn, 137Ba, 27Al, 57Fe, 66Zn,68Zn) and correlation, cluster and principal component analyses were employed to determine the factors that affect the release of these elements. Release profiles of the tested metal(loid)s were largely observed to be distinct; however, strong correlations have been observed between certain metal pairs (Cr/Ni, Cr/Cu, Zn/Ni) and principal component analysis was able to separate the metal(loid)s into three well-resolved groups based on their release.
Open Access
Entrepreneurial environment and varieties of capitalism
(2023-01) Açıköz, Fatima Kurnia
A countries' variety of capitalism could become vulnerable to change under the existence of an external factor. This thesis seeks answers for "In which varieties of capitalisms does the entrepreneurial environment have a statistically significant impact on the enrolment rates of secondary school vocational education and training (VET)?", and in the varieties of capitalism where we find statistically significant impact, "Which entrepreneurial factors (i.e., prominent principal components (PCs)) structure the entrepreneurial environment the most?" By using the Feasible Generalized Least Square and Principal Component Analysis models, I argue that the entrepreneurial environment shapes the institutional educational VET structure of a country, in other words, varieties of capitalism, by statistically significantly impacting the secondary school VET enrolment rates. I found that the entrepreneurial environment impacts the VET structures of Emerging Market Economies (EMEs ), Advanced EMEs, and European Market Economies. In addition, the most prominent PCs in the Brazilian, Chilean, Chinese, and Hungarian entrepreneurial environments are risk capital, internationalization, and product innovation. Lastly, I finalize this thesis by stating further research suggestions and policy implications.
Open Access
Experimental and model based investigation of the effects of high stimulus presentation rate on code-modulated visual evoked potential based brain-computer interfaces
(2018-09) Başaklar, Toygun
Objective. Previous studies on code-modulated visual evoked potentials (c- VEP) have yielded important results regarding the performance of c-VEP based brain-computer interfaces (BCIs) in recent years. Since, speed is the key factor in BCI applications and since the monitor refresh rate limits the stimulation time and thus limits the performance of the system, this study aims at investigating the effects of high stimulus presentation rates (refresh rate of the monitor) on a c-VEP based speller BCI. Furthermore, Robinson's corticothalamic model, which has not yet been studied for c-VEP responses, is used to simulate the salient behaviors that are observed in our experiments. Approach. Six subjects participated in three different experiments with refresh rates of 60 Hz (E1), 120 Hz (E2) and 240 Hz (E3), where a 127-bit m-sequence is used. Canonical Correlation Analysis (CCA) was used in the training stage to obtain 36 target templates from 100 averages of 8 EEG channels. Information transfer rate (ITR) and accuracy values were calculated for each experiment and subject. Subjects also answered a questionnaire asking at which refresh rate they felt more comfortable. Robinson's corticothalamic model was used to simulate the c-VEP experiments. Power spectral density (PSD) estimates of c-VEP responses and results of principal component analysis (PCA) were evaluated both for the simulation data and the experimental data. Main Results. Average ITR and accuracy values for E1 are 86.17 bits/min and 93%, for E2 are 90.68 bits/min and 95% and for E3 are 70.89 bits/min and 81% respectively. Also 5 out of 6 subjects stated that E3, and 1 subject stated that E2 is the most comfortable experiment. The c-VEP responses are band-limited although the input m-sequence is a wide-band signal. The spectral densities of c-VEP templates are concentrated on several frequency intervals, especially for E3. This periodicity leads to target misclassification. PCA shows that only 73, 52, and 26 well distinguishable responses can be obtained with a 127-bit length m-sequence for E1, E2, and E3 respectively. The results from simulations shows great similarity with the results from experiments. Considering all results and observations, we suggest that 120 Hz refresh rate is best to use in BCIs with high number of targets whereas 240 Hz refresh rate is reasonable for low number of targets. Results from modeling study suggest that the response of the visual system to the high frequency components in the input at higher refresh rates tends to diminish. Significance. Important results are obtained regarding characteristics of c-VEP responses and the effects of high refresh rates on c-VEP based BCIs. Robinson's corticothalamic model is found to be capable of explaining some of the salient behaviors in the experiments and this could be a basis for practical studies on improving the performance of c-VEP paradigm.
Open Access
A multi scale motion saliency method for keyframe extraction from motion capture sequences
(2010) Halit, Cihan
Motion capture is an increasingly popular animation technique; however data acquired by motion capture can become substantial. This makes it di cult to use motion capture data in a number of applications, such as motion editing, motion understanding, automatic motion summarization, motion thumbnail generation, or motion database search and retrieval. To overcome this limitation, we propose an automatic approach to extract keyframes from a motion capture sequence. We treat the input sequence as motion curves, and obtain the most salient parts of these curves using a new proposed metric, called 'motion saliency'. We select the curves to be analyzed by a dimension reduction technique, Principal Component Analysis. We then apply frame reduction techniques to extract the most important frames as keyframes of the motion. With this approach, around 8% of the frames are selected to be keyframes for motion capture sequences. We have quanti ed our results both mathematically and through user tests.
Open Access
Multiscale motion saliency for keyframe extraction from motion capture sequences
(John Wiley & Sons Ltd., 2011) Halit, C.; Capin, T.
Motion capture is an increasingly popular animation technique; however data acquired by motion capture can become substantial. This makes it difficult to use motion capture data in a number of applications, such as motion editing, motion understanding, automatic motion summarization, motion thumbnail generation, or motion database search and retrieval. To overcome this limitation, we propose an automatic approach to extract keyframes from a motion capture sequence. We treat the input sequence as motion curves, and obtain the most salient parts of these curves using a new proposed metric, called 'motion saliency'. We select the curves to be analysed by a dimension reduction technique, Principal Component Analysis (PCA). We then apply frame reduction techniques to extract the most important frames as keyframes of the motion. With this approach, around 8% of the frames are selected to be keyframes for motion capture sequences. © 2011 John Wiley & Sons, Ltd.
Open Access
Strain-and region-specific gene expression profiles in mouse brain in response to chronic nicotine treatment
(Wiley-Blackwell Publishing, 2008) Wang, J.; Gutala, R.; Hwang, Y. Y.; Kim J. -M.; Konu, O.; Ma, J. Z.; Li, M. D.
A pathway-focused complementary DNA microarray and gene ontology analysis were used to investigate gene expression profiles in the amygdala, hippocampus, nucleus accumbens, prefrontal cortex (PFC) and ventral tegmental area of C3H/HeJ and C57BL/6J mice receiving nicotine in drinking water (100 μg/ml in 2% saccharin for 2 weeks). A balanced experimental design and rigorous statistical analysis have led to the identification of 3.5-22.1% and 4.1-14.3% of the 638 sequence-verified genes as significantly modulated in the aforementioned brain regions of the C3H/HeJ and C57BL/6J strains, respectively. Comparisons of differential expression among brain tissues showed that only a small number of genes were altered in multiple brain regions, suggesting presence of a brain region-specific transcriptional response to nicotine. Subsequent principal component analysis and Expression Analysis Systematic Explorer analysis showed significant enrichment of biological processes both in C3H/HeJ and C57BL/6J mice, i.e. cell cycle/proliferation, organogenesis and transmission of nerve impulse. Finally, we verified the observed changes in expression using real-time reverse transcriptase polymerase chain reaction for six representative genes in the PFC region, providing an independent replication of our microarray results. Together, this report represents the first comprehensive gene expression profiling investigation of the changes caused by nicotine in brain tissues of the two mouse strains known to exhibit differential behavioral and physiological responses to nicotine.