Artem Lenskiy

Leaving school for a period of time can have significant effects on students’ academic success. In this article, we analyze how taking an academic break for a different number of semesters affects students’ academic performance in terms of their Grade Point Average. This study is conducted at a university in Korea by analysing academic records of 653 undergraduate students who entered the university from 1998 to 2013. In addition, 101 currently enrolled students were surveyed to collect students’ opinions on the effects of academic breaks. We investigate changes in grades before and after a school leave and compare the final grades of students who had academic breaks to students who continued their studies without having any breaks during their undergraduate education.Our results indicate that students’ grades improve after coming back to the university from a four or more consecutive semesters break, however their final GPAs did not statistically differ from their peers who studied...

... $30.00Add to Cart. 26. Estimation of MIMO Wireless Channels Using Artificial Neural Networks (pages 509-543). Kandarpa Kumar Sarma (Indian Institute of Technology, India), Abhijit Mitra (Indian Institute of Technology, India) Sample PDF | More details... $30.00Add to Cart. 27. ...

ABSTRACT In this paper we propose a system that measures eye blinking rate and eye closure duration. The system consists of skin-color segmentation, facial features segmentation, iris positioning and blink detection. The proposed skin-segmentation procedure is based on a neural network approximation of a RGB skin-color histogram. This method is robust and adaptive to any skin-color training set. The largest remaining skin-color region among skin-color segmentation results is further segmented into open/closed eyes, lips, nose, eyebrows, and the remaining facial regions using a novel texture segmentation algorithm. The segmentation algorithm classifies pixels according to the highest probability among the estimated facial feature class probability density functions (PDFs). The segmented eye regions are analyzed with the Circular Hough transform with the purpose of finding iris candidates. The finial iris position is selected according to the location of the maximum correlation value obtained from correlation with a predefined mask. The positions of irises and eye states are monitored through time to estimate eye blinking frequency and eye closure duration. The method of the driver drowsiness detection using these parameters is illustrated. The proposed system is tested on CCD and CMOS cameras under different environmental conditions and the experimental results show high system performance.

ABSTRACT Texture segmentation is a preliminary step in a wide spectrum of computer vision applications. Although the search for robust texture descriptors has been going for decades, there is still lack of texture features providing theoretical as well as practical evidence for successful segmentation. In this paper a novel algorithm for estimating scale exponents is described and applied in texture segmentation task. The estimated scale exponents are linearly dependent on generalized fractal dimensions. It has been proven that fractal dimensions are invariant under bi-Lipshitz transforms [1], which are general smooth transforms including perspective transforms. We estimate scale exponents in blocks around feature points, which allow us to characterize local regions and further segment them. In the case of finite resolution images, the proposed estimation algorithm produces robust to rotations and illumination changes features as predicted theoretically. The extracted features are applied for unsupervised segmentation using c-means fuzzy clustering by estimating spatial membership functions for each texture cluster. We experimented with textures from well-known Brodatz[2] and Vistex[3] texture database.

2) a.a. Abstract Fluctuations in heartbeat and interbreath intervals have been confirmed to exhibit scale-invariance. This property can be used to examine the effect of gender, aging, health or disease of a patient from his heartbeat and respiration signals. Sophisticated methods of scale-invariant signal analysis are based on the estimation of multifractal spectrum of the scale exponent. In this study we used an algorithm to estimate multifractal spectrum to confirm the existence of nonlinear relationship between heartbeat and interbreath interval under supine resting condition for 20 young and 20 elderly people. Using two border and one peak scale exponents which are selected from each spectrum, we constructed a 3-dimensonal feature space. The distance and the angle of the line connecting features estimated from heartbeat and respiratory dynamics for each patient were calculated and compared in both age group. Results showed that long range dependency in heartbeat dynamics degrade...

... Models Cagatay Catal, and Soumya Banerjee (2012). Machine Learning: Concepts, Methodologies, Tools and Applications (pp. 371-387). www.igi-global.com/bookstore/chapter. aspx?titleid=56152 Differential Learning Expert System in Data Management R. Manjunath (2012). ...

... 1 Terrain images segmentation in infra-red spectrum for autonomous robot navigation Artem A. Lenskiy(1), Jong-Soo Lee(2) Multimedia applications laboratory, University of Ulsan Ulsan, South Korea (I)aalensky@gmail.com, (2)jsoolee2001@yahoo.co.kr ...

... 27-30, 2010 in KINTEX, Gyeonggi-do, Korea Rugged terrain segmentation based on salient features Artem A. Lenskiy(1), Jong-Soo Lee(2) Multimedia applications laboratory, University of Ulsan Ulsan, South Korea (1)aalensky@gmail.com, (2)jsoolee2001@yahoo.co.kr ...