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The present study was carried out with 120 Native Tamil speakers to know the effects of age and instructional language on narrative comprehension and inference-making ability. Children from 3rd to ...

Nowadays, mobile photography plays a pivotal role in major parts of human lives. Every individual captures a lot of photographs in their personal device. However, management of these photographs by person becomes very crucial. Hence, photobook provides an attractive solution for personal storing and printing. In fact, today many commercial products are available to support the above point. But all of them require human annotation which is a time-consuming process and also leads to unreliable authentication. Hence, in this work, face recognition and deep learning techniques are utilized for photobook creation, wherein the user can create albums for a particular group of people or individuals and annotate them. Also, for every new photograph captured, the photobook will update itself automatically. Further, user interaction is introduced in the proposed work which makes it more reliable and results in good performance.

It is common for most people to check Amazon reviews of competing products before a purchase decision. However, the ratings and reviews could be from a customer who has not actually purchased the product on Amazon. There is also a chance that the reviews are doctored by paid reviewers either to enhance a particular product's appeal or lower that of a competitor's product. So, the ratings and reviews do not always reflect the reality. We provide a mechanism to eliminate un-authenticated reviews prioritizing them based on their credibility score and summarize both positive and negative keywords. In this paper, we present a methodology to eliminate un-authenticated reviews based on three levels of pruning. The final rating of the review is adjusted using helpfulness ratio of the review, how old the review is and the helpfulness and experience of the reviewer. We also summarize the positive and negative keywords using ‘term frequency-inverse document frequency’ and ‘Long Short-Term Memory networks’. The reviews are prioritized the based on their credibility score. We were able to summarize and prioritize the reviews for easy analysis by the user. We also did an empirical validation of our proposed solution and found that the overall helpfulness factors improved.

Environmentally aware organizations, as we re-enter a time of progress, should become more popular. Although CO2 growth during the recession may have stabilized, it is expected to rise again as companies increase production and other business operations. In addition, several businesses’ principal environmental focus during the recession was on waste management and resource optimization. Nowadays businesses are introducing a strategic method, EMS (Environmental Management System), to achieve competitive advantage. This program offers greater oversight of the environmental impacts of the company. It involves participation, strategy, planning, execution, assessment and evaluation, updating and developing HR processes that suit the culture and long-term objectives of the organization. Globally, companies are implementing green management practices and policies for sustainability in different management fields, and out of respect for environmental security. Organizations adopting ‘green’ HR practices can have huge impact on the engagement, commitment, efficiency, quality of work life and human resource retention of the organization. Strategic Green HRM – incorporation of environmental management into HRM – is becoming increasingly necessary. Green HR policies will focus on any aspect of an employee career process from recruitment / onboarding to leaving an employee.

This book uses spatio-temporal analysis to understand urbanisation in Indian cities and explain the concept and impact of global greenhouse gas (GHG) emissions. It creates a GHG footprint for Indian cities and engages in a discussion about the United Nations Sustainable Development Goals (SDGs) and smart city initiatives within an Indian context. Understanding the spatial patterns of land use/land cover (LULC) dynamics in the rapidly urbanising cities of India, the readers will be able to simulate future urbanisation patterns and use spatial temporal analysis as a tool for implementing appropriate mitigation measures. Features Analyses the complete urbanisation and urban sprawl of major cities in India using advanced geospatial modelling techniques Highlights the best practices and methods used in modelling urban growth Discusses greenhouse gas emissions from various sectors and their effects in local environments Addresses the increase of local temperature in cities due to unplanned land use change and its impact on environmental sustainability and resilience Fills the need for data-driven governance and policy decisions by introducing various analyses through spatial mapping Highlighting some of the best practices and tools being used for modelling urban growth through case studies, the book is useful to those interested in using new technologies and methods for data collection and problem solving. It focuses on the major environmental issues in India, which are prevalent in most developing countries.