Element Detection in Japanese Comic Book Panels

Comic books are a unique and increasingly popular form of entertainment combining visual and textual elements of communication. This work pertains to making comic books more accessible. Specifically, this paper explains how we detect elements such as speech bubbles present in Japanese comic book panels. Some applications of the work presented in this paper are automatic detection of text and its transformation into audio or into other languages. Automatic detection of elements can also allow reasoning and analysis at a deeper semantic level than what’s possible today. Our approach uses an expert system and a machine learning system. The expert system process information from images and inspires feature sets which help train the machine learning system. The expert system detects speech bubbles based on heuristics. The machine learning system uses machine learning algorithms. Specifically, Naive Bayes, Maximum Entropy, and support vector machine are used to detect speech bubbles. The algorithms are trained in a fully-supervised way and a semi-supervised way. Both the expert system and the machine learning system achieved high accuracy. We are able to train the machine learning algorithms to detect speech bubbles just as accurately as the expert system. We also applied the same approach to eye detection of characters in the panels, and are able to detect majority of the eyes but with low precision. However, we are able to improve the performance of our eye detection system significantly by combining the SVM and either the Naive Bayes or the AdaBoost classifiers

Development of Chemical-and Bio-sensor for Environmental Monitoring

Joint Research on Environmental Science and Technology for the Eart

DESIGN AND DEVELOPMENT OF MEMBRANE CHIP SYSTEM FOR STRESS SENSOR

Joint Research on Environmental Science and Technology for the Eart

DESIGN AND DEVELOPMENT OF OXIDATIVE STRESS RESPONSIVE LIPOSOME MEMBRANE WITH ENZYMATIC ACTIVITY (LIPOZYME) AND ITS APPLICATION TO CHEMICAL/BIOSENSOR

Joint Research on Environmental Science and Technology for the Eart

Prevalence of co-occurring mental disorders among in-patients at the Alcohol & Drug Abuse Rehabilitation Unit, Moi Teaching & Referral Hospital in Eldoret

Globally, the burden of mental disorders among patients attending treatment for substance use disorders is substantial. Little has been done to explore this subject in Kenya. The aim of this study was to investigate the prevalence rates of mental disorders among persons undergoing inpatient rehabilitation for substance use disorders at the Alcohol and Drug Rehabilitation (ADAR) Unit, Moi Teaching and Referral Hospital. This was a descriptive cross-sectional study. The Mini International Neuropsychiatric Interview Version 7.0 was used to investigate the lifetime  DSM-5 mental disorder diagnoses. Fifty three (53) adult patients consecutively admitted to the unit between June 2019 and May 2020 were interviewed by the investigators two weeks after admission. The data was analyzed using descriptive statistics. The mean age for the respondents was 38.13 years (SD=9.26 years). All 53 (100.0%) of the participants had at least one lifetime mental disorder diagnosis. Antisocial personality disorder (69.8%), Social Anxiety Disorder (49.1%), and Major Depressive Disorder (47.2%) were the most common mental disorder diagnoses. A large proportion of in-patients at the ADAR unit, MTRH had a lifetime mental disorder. We recommend routine screening for mental disorders for patients admitted for inpatient rehabilitation at the facility. In addition, management approaches for in-patient substance use disorder rehabilitation should address cooccurring mental disorders

Faster STR-IC-LCS Computation via RLE

The constrained LCS problem asks one to find a longest common subsequence of two input strings A and B with some constraints. The STR-IC-LCS problem is a variant of the constrained LCS problem, where the solution must include a given constraint string C as a substring. Given two strings A and B of respective lengths M and N, and a constraint string C of length at most min{M, N}, the best known algorithm for the STR-IC-LCS problem, proposed by Deorowicz (Inf. Process. Lett., 11:423-426, 2012), runs in O(MN) time. In this work, we present an O(mN + nM)-time solution to the STR-IC-LCS problem, where m and n denote the sizes of the run-length encodings of A and B, respectively. Since m <= M and n <= N always hold, our algorithm is always as fast as Deorowicz\u27s algorithm, and is faster when input strings are compressible via RLE

IMMOBILIZED-LIPOSOME SENSOR SYSTEM FOR DETECTION OF DAMAGED PROTEINS

Joint Research on Environmental Science and Technology for the Eart

Effect of Axial Agitator Configuration (Up-Pumping, Down-Pumping, Reverse Rotation) on Flow Patterns Generated in Stirred Vessels

Single phase turbulent flow in a tank stirred with two different axial impellers - a pitched blade turbine (PBT) and a Mixel TT (MTT)- has been studied using Laser Doppler Velocimetry. The effect of the agitator configuration, i.e. up-pumping, down-pumping and reverse rotation, on the turbulent flow field, as well as power, circulation and pumping numbers has been investigated. An agitation index for each configuration was also determined. In the down-pumping mode, the impellers induced one circulation loop and the upper part of the tank was poorly mixed. When up-pumping, two circulation loops are formed, the second in the upper vessel. The PBT pumping upwards was observed to have a lower flow number and to consume more power than when down-pumping, however the agitation index and circulation efficiencies were notably higher. The MTT has been shown to circulate liquid more efficiently in the up-pumping configuration than in the other two modes. Only small effects of the MTT configuration on the power number, flow number and pumping effectiveness have been observed

DESIGN AND DEVELOPMENT OF NANO-ARTIFICIAL-CELL MEMBRANE BASED NOVEL BIOSENSOR : APPLICATION FOR MONITORING OF AQUEOUS STRESSES

Joint Research on Environmental Science and Technology for the Eart