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.

Glycolytic Aminolysis of Poly (Ethylene Terephthalate) Waste at Atmospheric Pressure for Recovery of a Value Added Insecticide

Abstract: Reaction of poly (ethylene terephthalate) waste (PETW) powder with ethylene glycol (EG) in the presence of tetrahydrofurane (THF) using 0.003 mol zinc acetate as a catalyst was carried out in a batch reactor at 470 K and at atmospheric pressure. Reactions were undertaken with various particle size ranges from 50–512.5 µm, and reaction time from 30–70 min at 10 min intervals for reaction of PETW. A low molecular weight product of PETW was obtained during this step. In the next stage hydroxylamine hydrochloride (HAHC), cyclohexylamine (CHA), and potasium hydroxide solution were introduced to convert the low molecular weight product of PETW into terephthalohydroxamic acid (TPHA) by introduction of HCl as per stoichiometric requirement. The TPHA is used as insecticide, and it is highly expensive. To increase the PETW conversion rate, an external catalyst (zinc acetate) was introduced during the reaction. The product was deposited on the surface of unreacted PETW that was removed from the surface by ...

Full-Scale Laboratory Accelerated Test on Geotextile Reinforced Unpaved Road

Abstract: This paper examines the behavior of full-scale unreinforced and geotextile reinforced unpaved road using an indigenously developed full-scale laboratory accelerated pavement testing set up. The models of the unpaved road were subjected to 35,000 loading cycles of standard axle load. The effect of reinforcement on the vertical stress distribution at the base–subgrade interface was investigated. The test results show that the inclusion of geotextile significantly reduced the magnitude of vertical stress in the reinforced road as compared with the unreinforced road. This reduction of vertical stress magnitude is comparable to 9°–16° increases in the stress distribution angle; this may be attributed to stretching of the geotextile due to the tendency of lateral spreading of aggregates in the base course. The limited number of load cycles confirmed the lateral restraint of base course aggregates by the geotextile reinforcement and thus a reduction in the magnitude of vertical stress. The test results also confirmed about 22% reduction in base course thickness due to geotextile reinforcement, thus one step towards sustainability by saving of the expensive natural base course aggregate.

Identification of Medicinal Plant Using Image Processing and Machine Learning

Abstract: Medicinal plants are the backbone of the system of medicines; they are the richest bioresource of drugs of traditional systems of medicine, modern medicines, nutraceuticals, food supplements, folk medicines, pharmaceutical intermediates, and chemical entities for synthetic drugs. These plants are classified according to their medicinal values. Classification of medicinal plants is acknowledged as a significant activity in the production of medicines along with the knowledge of its use in the medicinal industry. Medicinal plant classification based on parts such as leaves has shown significant results. An automated system for the identification of medicinal plants from leaves using Image processing and Machine Learning techniques has been presented. This paper provides knowledge of the process of identification of medicinal plants from features extracted from the images of leaves and different preprocessing techniques used for feature extraction from a leaf. Many features were extracted from each leaf such as its length, width, perimeter, area, color, rectangularity, and circularity. It is expected that for the automatic identification of medicinal plants, a web-based or mobile computer system will help the community people to develop their knowledge on medicinal plants, help taxonomists to develop more efficient species identification techniques and also participate significantly in the pharmaceutical drug manufacturing.

Diet recommendation based on Prakriti and season using Fuzzy ontology and Type-2 Fuzzy Logic

Abstract: People becoming very conscious about their health. Universe is changing at every moment and results in seasonal variations. These seasonal variations affect on human body. Every human being having their own particular type of Prakriti from their birth. Prakriti is one type of energy to control physical and mental state of human body. Imbalance in these energies results in illnesses and different diseases. For maintaining health and prevent from any diseases, in Ayurveda diet is the best medicine. People follow different diet plans recommended from different dietician. In this paper proposed a method to recommend diet based on prakriti of person and current season and data is collected from different websites where different dieticians recommended different diet plans for different prakriti. In this paper the proposed method uses Type-2 Fuzzy Logic to handle uncertainty and Ontology is integrated with fuzzy logic to represent food knowledge. The results of the execution of the fuzzy logic which shows the efficient and accurate diet recommendation.

Genetic Algorithm Approach for Obstacle Avoidance and Path Optimization of Mobile Robot

Abstract: The path planning is an important issue of mobile robots. Its task is to find a collision free path from the start position to the target position with an algorithm which requires less time and minimum path distance. The scheduling and planning is NP-Hard (NP-Complete) problem. Autonomous robot vehicles can be used in variety of applications including space exploration, household and transportation. In known static environment path planning algorithms such as Sub Goal network, A* algorithm, D* Star algorithm, Artificial Potential Method are used. These are classical and heuristic search based algorithms. The above mentioned algorithms have some drawbacks such as local minima, deadlock of robot, and oscillation of robot. We have proposed an algorithm which will overcome these drawbacks present in existing classical algorithms.