College of Engineering, Pune

About: College of Engineering, Pune is a based out in . It is known for research contribution in the topics: Computer science & Sliding mode control. The organization has 4264 authors who have published 3492 publications receiving 19371 citations. The organization is also known as: COEP.

Process standardization of sugarcane bagasse ash to develop durable high-volume ash concrete

Abstract: The application of agro-industrial wastes in concrete production gives a sustainable solution to not only solid waste management but also to the environmental concerns associated with the construction industry. In the present study, raw sugarcane bagasse ash (SBA) was preliminarily characterized (laser particle size analysis, mineralogical phases, chemical oxides composition, morphological studies, and the thermogravimetric analysis). The objective of the research is to develop the thermo-mechanical process and to study its effect on pozzolanic characteristics of SBA. The pozzolanicity was quantified using a strength activity index, electrical conductivity test, and the Chapelle activity test. The ordinary, standard, and high-strength grade high volume ash concrete were developed by incorporating the treated SBA (TA) in it as a pozzolanic material and GGBS as a supplement to it. The mechanical performance (compressive strength, flexural strength, and splitting tensile strength), porosity performance (water absorption, and coefficient of water absorption), ultrasonic pulse velocity, durability performance (rapid chloride penetration test, chlorides and sulphate contents), and the thermal performance (thermal conductivity, and specific heat capacity) was quantified and compared with the conventional concrete. 50, 45 and 25% of cement can be optimally replaced in the manufacturing of ordinary, standard, and high-strength concrete respectively without affecting its properties.

Systolic architecture for integer point matrix multiplication using FPGA

Abstract: The paper presents a systolic architecture for integer point matrix multiplication algorithm using FPGA. Approach uses four processing elements that minimizes resources, reduces the routing complexity and improves Area/Speed metric.

COVID-19 and Mental Health: A Study of its Impact on Students

Abstract: The purpose of this study was to identify and analyze the personal, social and psychological impact of COVID −19 on the mental health of students of age group 16 to 25. A response from N= 351 students (from the most affected state in India), provided a comparative analysis based on the gender, and background via t-test with significance factor of p≤0.5, to understand the pattern in issues related to mental health during the pandemic. The results show that female students are more concerned about health, and future, and are more prone to psychological issues like feelings of uncertainty, helplessness and outbursts than male students. Urban student’s population is more mentally affected than their rural counterparts, however time spent on the internet is almost the same despite the difference in infrastructure and resources. Also, there is an increase in need for solitude, being withdrawn and self-harm in male students require attention. A shift in perception from seeing family as a source of support to that of a restriction is indicated, although the benefits of a collectivistic society are undisputed. The results indicate that there is overall increased awareness about mental health among the student population and with programs/strategies focusing on background and gender, a significant improvement is attainable. Impact Statement This study performs an analysis of the student’s response to questions based on social and self-perception as a result of COVID-19. It also discusses the nature of adaptive strategies espoused by them and their effectiveness in dealing with the pandemic, isolation, and the new normal. Funding Not applicable Conflicts of interest/Competing interests There was no conflict of interest

Recognition of cursive English handwritten characters

Abstract: This paper aims to represent the work related to recognition of cursive English handwriting. Character recognition of handwritten cursive English script is a very challenging task. In cursive English handwriting, the characters in a word are connected to each other. So the segmentation and feature extraction of cursive English script is much difficult. In the proposed work, horizontal and vertical projection methods are used for segmentation. Convex hull algorithm is used for feature extraction and SVM is used for classification and recognition.