Informatics Publishing Limited

Shaila Bantanur ¹, Mahua Mukherjee ², R. Shankar ²

Affiliations
1 Department of Architecture, Srinivas Institute of Technology, Velachil, Mangalore 574 143, IN
2 Department of Architecture and Planning, IIT Roorkee, Roorkee 247 667, IN

Abstract

Institutions of higher education serve as models for excellence in education. They also have an added responsibility in providing guidance to the community for social upliftment and environmental sustainability. The present study conducted in the Indian Institute of Technology Roorkee (IITR) examines the students' perception on the importance of sustainability to the campus. One hundred sixty-five students participated in the survey. The survey focuses on three broad categories, namely environmental, educational and research, and management factors. Environmental factors are more significant compared to management factors. Education and research is given less importance compared to environmental and management factors. Findings provide a useful extension to both the management and administrative strategies in decision-making process to improve the sustainability of the campus.

Keywords

Education and Research, Environmental Parameters, Green Guidelines, Management Strategies.

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A. Sathesh ¹, R. P. Santhosh ², R. Shankar ²

Affiliations
1 Department of Electronics and Communication Engineering, Karunya University, Coimbatore, IN
2 Department of Electronics and Communication Engineering, Karunya University, Coimbatore, Tamil Nadu, IN

Abstract

The home security is of prior importance to everyone in this time and the need for security devices is on the rapid rise in Indian market, according to an article in the Times of India. Most of the security devices that are currently available need an extra display device to view the video from the camera located outside the door. This increases the cost of the entire system. Moreover, when anyone knocks the door while you watch a very interesting program in TV, may be the last over of the world cup finals, your mind won't allow you to think about your guest standing at your door. To overcome this problem, we come out with a security system which eliminates the need for an extra display device, by using a PIP processor. When someone stands at the door, a pop up showing the camera video will be generated over the TV screen and it disappears automatically when the person leaves. With this, one will not be missing the existing TV program and the person standing outside the door as well.

Keywords

QUAD/MUX, Outdoor Surveillance, Picture in Picture.

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V. Santhi ¹, R. Shankar ²

Affiliations
1 Associate Professor and Head, Department of Humanities, PSG College of Technology, Coimbatore – 641004, Tamil Nadu, IN
2 Assistant Professor, Department of Humanities, PSG College of Technology, Coimbatore - 641004, Tamil Nadu, IN

Abstract

The environment of the world plays a dominant role in the entire wellbeing of the nation. Now-a-days, due to emergence of huge number of industries and tremendous change in the life style of people, the global environment faces a big challenge. In order to overcome the negative impact of pollution, green aspect in almost all the fields is emerging. The green initiatives undertaken by the countries have created awareness among the public and its implementation has become mandatory amidst the prevailing global environmental concern. Traditionally, most of the industries followed the green initiatives driven by laws and regulations. But, the situation has seen a drastic change from control to prevention. The information technology industry is not an exception. In this regard, the present study focuses on analyzing the impact of Green Employee Engagement and Green Human Resource Management on employees’ productivity in IT companies in Coimbatore district. By employing simple random sampling technique, data has been collected from 150 employees working in various IT companies in the study area. Various statistical tools namely simple percentage analysis, chi-square test and multiple regression analysis have been employed for analysis. It was found that the Green Employee Engagement and Green Human Resource Management has a significant impact on employees’ productivity.

Keywords

Green Employee Engagement, Green Human Resource Management and Green Initiatives.

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R. Shankar ¹, Tharani Vimal ²

Affiliations
1 Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, IN
2 Department of Information Technology, St. Peter’s College of Engineering and Technology, Avadi, Chennai, Tamil Nadu, IN

Abstract

With the emergence of accessing Smartphones in day-to-day life, Mobile Cloud Computing (MCC) technology has become popular with the advantage of resolving the resource constraints in mobile devices through the offloading method. The existing models have presented the different resource allocation solutions to ensure the seamless execution of the applications for the resource-constrained mobile devices with the Quality of Service (QoS). The optimization of resource allocation is the process of potentially allocating remote resources to mobile users without violating the Service Level Agreements (SLAs). However, resource allocation is still becoming a major constraint in the Mobile Cloud (MC) data centers due to higher consumption of energy and time factors during the execution of mobile requests on the remote cloud. The consumption of the energy and response time of the offloaded tasks or applications heavily relies on the cloud resource allocation for the mobile users. Hence, Resource Allocation Optimization (RAO) emerged as the significant objective to select the appropriate cloud resources for the requested tasks to increase the lifetime of the devices with improved time efficiency. Thus, this work focuses on optimizing MC resource allocation by optimizing the allocation of both the computation and communication resources. The proposed RAO model considers two potential factors, such as the energy and response time while allocating the computational and communicational resources. Initially, the Energy and Response time-driven RAO (EARO) approach prioritizes the request generated from the mobile users based on the estimated execution time. Modeling the Estimated Communication and Execution Time (ECET) algorithm tends to allocate the cloud resources and accomplish the minimal response time of the application requests. The EARO approach intends to minimize the execution time as well as the response time towards the target of alleviating the energy consumption during the resource allocation. Moreover, it selects the resources for the inter-VM communication with the knowledge of the minimal migration time ensuring bandwidth resources. Thus, EARO preserves the device's energy with minimal application completion time. The experimental results illustrate that the time efficiency of the proposed EARO model outperforms the existing resource allocation model in the MC environment.

Keywords

MCC, Resource Allocation, Computation, Communication, Optimization, Energy Consumption, Bandwidth, Response Time.

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R. Shankar ¹, Nir Orion ², Chris King ³, Anish Kumar Warrier ⁴, A. M. Narahari ⁵, S. G. S. Swamy ⁶

Affiliations
1 International GeoScience Education Organisation, Bengaluru, IN
2 Weizmann Institute of Science, Rehovot, IL
3 Keele University, Keele, Staffs, ST5 5BG, GB
4 Manipal Institute of Technology, Manipal University, Manipal 576 104, IN
5 St Aloysius College (Autonomous), Mangaluru 575 003, IN
6 Karnataka State Council for Science and Technology, Indian Institute of Science Campus, Bengaluru 560 012, IN

Abstract

The International GeoScience Education Organisation, Bengaluru organized three teacher training workshops in Goa, Mangaluru and Bengaluru. These workshops were organized as a pilot project to test the impact of such an approach in an Indian setting.

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Aditya Mishra ¹, B. D. S. Negi ¹, Argha Banerjee ², H. C. Nainwal ¹, R. Shankar ³

Affiliations
1 Department of Geology, H.N.B. Garhwal University, Srinagar Garhwal 246 174, IN
2 Indian Institute of Science and Educational Research, Pune 411 008, IN
3 The Institute of Mathematical Sciences, Chennai 600 113, IN

Abstract

Total volume of stored ice in the Himalayan glaciers is an important quantity for water resource management of the Himalayan catchments. However, direct measurement of glacier-ice thickness is rare in the Indian Himalaya. We have estimated the ice thickness of the debris-covered Satopanth Glacier (SPG) using a ground penetrating radar (GPR). Multiple bistatic, unshielded antennae with frequencies of 16, 20, 40 and 80 MHz were used for this purpose. We have done GPR surveys at various locations over the ablation zone of SPG. However, satisfactory results were obtained only on two transects. Near the glacier snout, a transverse GPR profile shows an ice thickness of 38 ± 3.5–50 ± 3.5 m. We have obtained 98 ± 7–112 ± 7 m ice thickness at a longitudinal transect in the upper ablation zone. To measure the speed of the radar waves in ice, a common midpoint survey was carried out. Our results for the speed of the electromagnetic waves are slightly lower than the standard values of such waves through pure ice.

Keywords

Common Midpoint Survey, Debris-Covered Glaciers, Ground Penetrating Radar, Ice Thickness.

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S. Arulmozhi ¹, R. Shankar ¹, S. Duraisamy ¹

Affiliations
1 Department of Computer Science, Chikkanna Government Arts College, IN

Abstract

Pancreatic Cancer (PC) may be a leading reason behind death worldwide and its prognosis is extremely poor within the present scenario. There are numerous methods and techniques for tumor identification in brain, breast, lungs, but limited work was done on pancreatic tumor detection. Pancreatic tumor image classification is usually provided by computer-aided screening (CAD), diagnosis and quantitative evaluations in radiology images like CT and MRI. Tumor classification through these methods may help to trace, predict and endorse customized therapy as part of effective treatment, without invasions of cancer. Nowadays, Convolutional Neural Networks (CNN) have shown promising results for precise pancreatic image classification. As a prominent, the algorithms are required to work out and classify the categories of pancreatic tumors at early stages for saving most of the life. Because of the various shapes, huge sample size, processing and analyzing big databases, new statistical methods are to be implemented. On the opposite hand, detection of tumors within the medical images also become difficult since the standard of input images. This paper mainly concentrates on a study of carcinoma and also the recent research on tumor detection and classification in medical images. The convolution neural network (CNN) developed in recent years has been widely utilized in the sector of image processing because it's good at handling image classification and recognition problems and has brought great improvement within the accuracy of the many machine learning tasks. One in every of the foremost powerful approaches to resolve image recognition and classification problem is that the CNN. The experimental results demonstrate that the proposed approach can improve the performance of the classification accuracy.

Keywords

CNN, Classification, Deep Learning, Medical Image Analysis, Pancreatic Cancer, Adenocarcinomas.

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