Padmabhushan Vasantdada Patil Pratishthan's College of Engineering (PVPP COE) is an engineering college in Mumbai, India, established in 1991.The college is a tribute to the late Shri Vasantdada Patil, the Sahakar Maharshi and former Chief Minister of Maharashtra. It is registered under Societies’ Registration Act, 1860 and Bombay Public Trust Act, 1950. Former deputy Prime Minister Yeshwantrao Chavan laid the foundation of the college.Established in 1991, the college is spread over a total area of 300,000 sq ft (28,000 m2). It is located in the centre of Mumbai, on the Eastern Express Highway at Sion. It is approved by the Government of Maharashtra, University of Mumbai, and All India Council for Technical Education (AICTE) to conduct degree courses in electronics and telecommunications, computer engineering, and information technology engineering.
New avenues for studying human behaviour and cognitive processes are made possible by the integration of brain-computer interface (BCI) technology into social science studies. This study aims to investigate how real-time neural data transmission via brain-computer interfaces (BCIs) might be used to enhance our understanding of social interactions, decision-making, and emotional responses. Brain-computer interfaces (BCIs), employing recording and interpreting brain activity, offer a new way to study social phenomena. Researchers can gain a deeper understanding of the cognitive and affective processes influencing human behaviour by using this approach. This chapter examines some brain-computer interface (BCI) applications in the social science domain. Among these uses are how BCIs might improve data accuracy, research methods, and the comprehension of complex social dynamics. Using empirical studies and case analyses, this research evaluates how well BCIs improve social scientific research. The study also discusses the challenges and possibilities associated.
Wireless sensor network (WSN) contains millions of small, low-power gadgets with a lack of resources are memory and battery power. Such gadgets were deployed in a dispersed manner and were often utilized to monitor and sense applications. Owing to constraints and limited resources of WSNs, routing can be a great difficulty. Routing in WSN was the process of choosing the optimal path for data to travel from a source node to a destination node. The goal of routing in WSN offer dependable and effective transmission while minimizing network overhead and energy consumption. This study designs an Energy Efficient Colliding Bodies Optimization based Routing Protocol (EECBO-RP) for WSN. The end goal of the EECBO-RP algorithm lies in the optimal election of routes to a destination. For achieving reasonable results for the minimization of energy exploitation, the EECBO-RP system derives the fitness function using the following variables: residual energy, distance to BS, and node degree. The EECBO-RP technique chooses the relay nodes so that a way that the overall efficiency of the WSN gets maximized. The simulation values of the EECBO-RP system are tested under several dimensions and the outcomes pointed out the betterment of the EECBO-RP technique.
In this situation, there is a futile way of life in every single proficient field. It is additionally valid for the job market. A job portal is a site devoted to online data about recruiters as well as job seekers. A job portal helps both the job seekers and recruiters tracking down the right association for the representatives. On account of job seekers, as indicated by their instructive capability, experience, and their inclinations, the job portal shows the rundown of organizations to the job searcher. Furthermore, to the recruiters, gives the reasonable candidates from a pool of needs. The objective of this application is to foster a system to empower connections among employers and candidates. The assurance is to permit correspondence between the closely involved individuals and complete the assignment of enlistment rapidly.
In the past few years, the forms of data have changed drastically from the text formats to images and today, most of the data are available in the video format. With this, there is a huge demand in the techniques that can provide the overall summary of the video. In this paper, we present the summary of birds that are identified from the large datasets using convolutional neural network (CNN). CNN is one of the best image processing and video processing model. The CNN model that we have used for the task is pre-trained AlexNet. The paper clearly proves that the work proposed recognizes the various kinds of birds from the inputted video with accuracy level ranging between 85 and 99%. At last, we provide the overall summary in terms of start time and end time of existence of each bird in the video.
Cognitive radio network has gained a lot of popularity in the era of wireless communication to overcome an issue of scarce bandwidth. Cognitive radio network (CRN) has opened with tremendous research areas toward the spectrum sensing and sharing. In this paper, we will see the different techniques used for the detection of primary user’s (PU) activity and assign the spectrum to secondary user (SU) if the spectrum is unutilized by the primary user without interfering the primary user and utilized the spectrum efficiently. This paper is an attempt to through light on the primary idea of research work, which is going in the field of cognitive radio networks in wireless communication.
