Spectral Clustering with Jensen-type kernels and their multi-point extensions

Motivated by multi-distribution divergences, which originate in information theory, we propose a notion of `multi-point' kernels, and study their applications. We study a class of kernels based on Jensen type divergences and show that these can be extended to measure similarity among multiple points. We study tensor flattening methods and develop a multi-point (kernel) spectral clustering (MSC) method. We further emphasize on a special case of the proposed kernels, which is a multi-point extension of the linear (dot-product) kernel and show the existence of cubic time tensor flattening algorithm in this case. Finally, we illustrate the usefulness of our contributions using standard data sets and image segmentation tasks.Comment: To appear in IEEE Computer Society Conference on Computer Vision and Pattern Recognitio

EXPERIMENTAL INVESTIGATION ON DRYING OF BLANCHED BITTER GOURD SLICES IN A TRIPLE PASS SOLAR DRYER

This paper involves with the experimental performance study of a triple pass solar flat plate collector integrated with  thermal energy storage medium for drying of blanched bitter gourd slices. The experimental setup consists of a blower, triple pass flat plate collector and a drying chamber. The experimets were carried out in the meterological conditions of Coimbatore, Tamil Nadu, India. The mass flow rate of air through the system was set as 0.06 kgs-1. From the results, it could be comprehended that, (i) triple pass arrangement of air improves the performance of flat plate collector (ii) thermal energy storage medium played an important role in consistent outlet air temperature and the thermal efficiency (iii) triple pass solar dryer took 5 hours to reach the final moisture content of bitter gourd (9% on wet basis) which is 29 % and 37.5% faster than without thermal storage and open sun drying system. It could be concluded that triple pass solar air collector performs better than without thermal storage and open sun drying

A Study on Occupational Aspiration Skill and Personality Traits of Institutionalized Adolescent Orphans in Kerala as Related to their Realistic and Idealistic Mode of Evaluation

The present trend suggests that students are pressurized by the society to select an occupation of their choice that can fetch easy money. That is why there is a heavy rush towards medicine, nursing, para-medical and engineering streams. This often negates the potential of each student and suppresses his or her innate caliber that negatively affects the prospects of the individual and society. The choice of occupation is one of the very important decisions a person makes in life. Psychologically each student has her/his own interests, aptitudes, attitudes, aspirations etc. It is a fact that parents, relatives, teachers, friends, media and society can influence the students in the modification of interests, aptitudes, attitudes, aspirations etc. If a person gets her/his education on their preferred vocation, he/she can get job satisfaction from the vocation and the individual shall be well placed. Aspirations add to the efficiency of the person by bringing out the best in him on the job

Application of a Machine Learning Algorithm in a Multi Stage Production System

This paper examines a permutation flow-shop scheduling problem, which is a complex combinatorial problem encountered in many practical applications. The objective of the research is to reduce the maximum completion time, i.e., the makespan of all jobs. In order to increase productivity and to meet the demand, manufacturers are continuously under pressure to attain the shortest possible completion time. Estimation of accurate cycle time can tremendously help production planning and scheduling in manufacturing industries. Since production planning is characterised by NP-hardness and a wide range, traditional optimization methods and heuristic rules are unable to find satisfactory solutions. Q-learning, a type of reinforcement learning algorithm, is used in this paper to find a solution that is close to being optimal. Q-learning is a branch of machine learning referring to the way an intelligent agent should act in order to maximize the concept of cumulative reward in a given environment. To validate the performance of the algorithm, Taillard’s benchmark problems were solved and compared with the upper bound value. The results showed that the performance of the algorithm is better and has low computational time. Based on the performance of the proposed algorithm, two case studies were done and the solutions are compared with the performance of a metaheuristic algorithm. The result shows that the proposed algorithm can effectively and efficiently solve the problem stated above and that it is an interesting solution to resolving complex scheduling problems

X-ray studies on crystalline complexes involving amino acids and peptides. XXI. Structure of a (1:1) complex between L-phenylalanine and D-valine

This article does not have an abstract

Tobacco and health: What can the medical profession do?

Tobacco consumption, that leads to three million deaths every year of which about one million occur in developing countries is a social evil(1). Tobacco smoke is a complex mixture of as many as 4700 individual constituents including carcinogens, irritants, ciliotoxic substances and poisonous gases. There is no dearth of information about the health hazards to smokers. it has been implicated as a major risk factor in a variety of chronic diseases including cardiac, cerebrovascular, malignant, respiratory and other diseases (2), Most of the smoking related lung diseases (e.g. chronic obstructive lung disease and lung carcinoma) are dose dependent. it is often the cumulative dose of smoking which determines the risk. Parameters like pack-year (PY) have been used to express exposure to tobacco smoke. One PY implies one packet of cigarettes (or 20 gms. tobacco) smoked each day over a course of one year (3). In India the number of cigarettes and bidis per packet is quite variable. A standard packet of cigarette and bidis per packet is quite variable

Synthesis of polythiophene n-type and p-type doping and compensation

The synthesis of pdythiophene leading to the formation of n-type potythiophene, p-type polythiophene and neutral polythiophene has been investigated through electropolymerization with different dopant ions. The influence of doping level over conductivity of the polymer matrix has also been studied which reveals that a preselected room temperature conductivity can easily be imparted to the parent polymer chain. It has also been found that the compensation of one type of conductivity over other occurs during the process of dedoping and redopin