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.

New Algorithm for Protection of Double Circuit Transmission Lines Using Modal Currents

Abstract: This paper presents a new protection algorithm for double circuit transmission lines using the sum of ratios of modal currents. Relay-operating characteristics is proposed using the complex ratio of modal currents. The proposed algorithm estimates modal domain line parameters and identifies the faulty phases for single pole-tripping applications even during inter-circuit faults. The scheme is sensitive to high resistance internal faults and also detects internal faults with outfeed. The proposed scheme is immune to mutual coupling and is found robust to uncertainties in parameter estimation due to measurement inaccuracies. The scheme is tested for its effectiveness to deal with current transformer saturation and synchronisation error. The scheme protects series compensated double circuit transmission lines even in the presence of current inversion. Exhaustive case studies in electromagnetic transient program (EMTP)/alternate transient program are performed on 400 kV, 300 km, double circuit transmission lines and the proposed protection algorithm is implemented in MATLAB. The results confirm the superiority of the proposed scheme.

EEG Spectral Analysis on OM Mantra Meditation: A Pilot Study

Abstract: Mantra meditation is easy to practice. “OM” Mantra is the highest sacred symbol in Hinduism. The present study investigated the temporal dynamics of oscillatory changes after OM mantra meditation. Twenty-three naive meditators were asked to perform loud OM chanting for 30 min and the EEG were subsequently recorded with closed eyes before and after it. To obtain new insights into the nature of the EEG after OM chanting, EEG signals were analyzed using spectral domain analysis. Statistical analysis was performed using repeated measures of analysis of variance. It did not reveal any specific band involvement into OM mantra meditation. But significantly increase in theta power was found after meditation when averaged across all brain regions. This is the main effect of OM mantra meditation. However, the theta power showed higher theta amplitude after condition at all regions in comparison to the before condition of meditation. Finding was similar to other studies documenting reduction in cortical arousal during a state of relaxation. The study argues for the potential role of loud ‘OM’ chanting in offering relaxation. It provides a new perspective of meditation to the naive meditators. This information may help to demystify meditation and encourage those considering this as beneficial practice.

Rice quality analysis using image processing techniques

Abstract: In agricultural industries grain quality evaluation is very big challenge Quality control is very important in food industry because after harvesting, based on quality parameters food products are classified and graded into different grades Grain quality evaluation is done manually but it is relative, time consuming, may be varying results and costly To overcome these limitations and shortcoming image processing techniques is the alternative solution can be used for grain quality analysis Rice quality is nothing but the combination of physical and chemical characteristics Grain size and shape, chalkiness, whiteness, milling degree, bulk density and moisture content are some physical characteristics while amylose content, gelatinization temperature and gel consistency are chemical characteristics of rice The paper presents a solution of grading and evaluation of rice grains on the basis of grain size and shape using image processing techniques Specifically edge detection algorithm is used to find out the region of boundaries of each grain In this technique we find the endpoints of each grain and after using caliper we can measure the length and breadth of rice This method requires minimum time and it is low in cost

QoS Aware Machine Learning Algorithms for Real-Time Applications in Wireless Sensor Networks

Abstract: Wireless Sensor Networks (WSNs) are employed in a range of applications these days and can be employed in even additional applications within the future. However, WSNs seems to be not as much reliable as the wired networks. With increasing range of applications particularly within the real-time WSN developments need extremely reliable and time-constrained data transmission schemes. In real-time scenario, like industrial automation, environmental monitoring, etc., the network must assure the guaranteed and timeliness delivery of data packets to the sink node. In light of the kind of use, it is fundamental to allow various degrees of Quality of Service (QoS) in WSNs. This paper heighted, QoS prerequisites for delay bounded WSNs applications. Some existing QoS aware agreements to help these applications are examined with application-specific benefits and limitations. Moreover, in such applications, researchers worked on providing dedicated MAC scheduling as well as QoS aware routing based on application area and requirements. This paper also discussed some machine learning approaches used to attain the quality of service requirements in WSNs considering parameters Energy, delay, and trustworthiness. A machine learning based algorithm will help to reduce the average delay of critical packets.

Data Analytics: COVID-19 Prediction Using Multimodal Data

Abstract: Globally, there is massive uptake and explosion of data, and the challenge is to address issues like scale, pace, velocity, variety, volume, and complexity of this big data. Considering the recent epidemic in China, modeling of COVID-19 epidemic for cumulative number of infected cases using data available in early phase was big challenge. Being COVID-19 pandemic during very short time span, it is very important to analyze the trend of these spread and infected cases. This chapter presents medical perspective of COVID-19 toward epidemiological triad and the study of state of the art. The main aim of this chapter is to present different predictive analytics techniques available for trend analysis, different models and algorithms, and their comparison. Finally, this chapter concludes with the prediction of COVID-19 using Prophet algorithm indicating more faster spread in short term. These predictions will be useful to government and healthcare communities to initiate appropriate measures to control this outbreak in time.