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The future of work in ASEAN: A matter of sustainability

ASEAN was initiated and formed on August 8th, 1967, a decade lesson learned from EEC which was formed by the 6 countries in 1958. However, in the case of the ASEAN community, it should not be foot-steeping to the EU. Since their landscape and demography are tremendously different: from no technology(mountainous/hill tribes) to high technology(Singaporean). The high percentage of the population classified as no technology to low technology is mainly in CLMV which joined the ASEAN in the late 1990s, while the medium to high technology consumers are in the ASEAN founding member states and Brunei Darussalam. These affect various kinds of jobs, skills, performances, productions and living styles/culture, and sustainability. Since some groups of people are among the top of the world(3rd to 4th wave) while the others are far left behind(1st wave). It is interesting the question of “What and how the sustainable work would be fit to the ASEAN members?” This issue is a black box or paradox of the “One vision, one identity, one community”. However, some studies revealed that the CLMV are focal points of the FDI’s industrial landmark due to new low-cost production sites, cheap labor, special economic zones, and benefit from AFTA to a huge market of US$2.6 trillion and over 622 million people. Our study revealed that a lot of FDIs, especially those advanced technology industries, do not employ the local cheap labor but substitute by installing robots or automatic machines or importing skilled labor from their own countries or from neighboring countries. In developed regions, computer skills and information technology skills are increasingly demanded in the labor market while the technical skills for natural products or handmade value-added development are highly demanded in rural areas. Otherwise, those agriculturists could not survive due to climate change.

Published by: Phasina Tangchuang, Chatchai Sirikulpan, Phramaha Sakun Thiangchai, Chalee Pakdee

Author: Phasina Tangchuang

Paper ID: V8I3-1171

Paper Status: published

Published: May 25, 2022

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Survey Report

Teaching effectiveness and academic environment in the Government Polytechnics of Assam

Teaching effectiveness and academic environment are the two important variables that determine the quality of student output from any institution. There are large-scale variations among the polytechnics in w.r.t. teaching effectiveness and academic environment. Again, there are multiple factors that affect teaching effectiveness. The factors are related to students, teachers, teaching-learning, and the academic environment of the institution. The academic environment includes the dimensions: institutional resources and facilities, involvement of students in teaching-learning, organization of scheduled activities, interaction with faculty and other staff etc. The author carried out a study to find out any differences in teaching effectiveness and academic environment in the polytechnics of Assam. The sample of the study was final year students studying in different Government polytechnics of Assam. In the study, a total of nine Government polytechnics were targeted and a total of nineteen branches were selected by taking 50% of the total branches of each institute subject to the inclusion of at-least two branches from each institute. Fifteen final semester students were randomly selected from each branch hence, a total of 285 (two hundred eighty-five) students were included in the study. Students Evaluation of Educational Quality (SEEQ) and Academic Environment Scale (AES) tools were used for collecting the data. The study reveals that there are significant differences among the various Govt. polytechnics of Assam with respect to various dimensions of teaching effectiveness and academic environment. It was also observed that most of the dimensions of teaching effectiveness and academic environment of Assam Textile Institute had a significantly higher rating than other polytechnics wherever significant differences were observed.

Published by: Nila Kumar Singha

Author: Nila Kumar Singha

Paper ID: V8I3-1327

Paper Status: published

Published: May 24, 2022

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Research Paper

Data Compression using a Generic Approach

The amount of data being generated in the great age of Big Data is enormous, which in turn has led to a large demand for storage infrastructures. With this growing demand, the storage infrastructures that depend on natural resources like silicon for hardware will become expensive. Hence there is a need to use techniques that minimize the size required by the data and efficiently store the data in these infrastructures. Data compression is a technique that reduces the size of data. This project’s goal is to reduce the size of the original data without losing the quality of the data. We propose a generalized system with which data of any type or more commonly multimedia can be reduced in size without losing the quality of the data.

Published by: Shreyas Kalrao, Someshwar Gaikwad, Sushant Sontakke, Yash Rathi

Author: Shreyas Kalrao

Paper ID: V8I3-1320

Paper Status: published

Published: May 24, 2022

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Survey Report

Monitoring Social Distancing

Social Distancing measures are important to reduce the COVID-19 spread. In order to break the chain of spread. A deeper understanding of the epidemic suggests that a person's negligence can cause widespread harm that would be difficult to negate. This project demonstrates a system that is useful in monitoring public places like ATMs, malls, and hospitals for any social distancing violations. It would be conveniently possible to monitor individuals whether they are maintaining the social distancing in the area under surveillance and also to alert the people as and when there are any violations from the predefined limits. We aim to develop a framework that tracks humans for monitoring the social distancing being practiced.

Published by: Samanta Manojkumar Patil, Apoorva Anil Kulkarni, Bhoomika M. Ankad, Ashwini F. Asuti, P. K. Deshpande

Author: Samanta Manojkumar Patil

Paper ID: V8I3-1322

Paper Status: published

Published: May 23, 2022

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Research Paper

Real Estate Solution driven by Blockchain Technology

The notion of Blockchain was first propositioned by Stuart Haber and Scott Stornetta in 1991 with an aim to develop a secure system where data and timestamps cannot be vandalizing. Within the established period of Blockchain, there have been a many momentous data breaches. As per the data breaches reports by MIT [1], cryptocurrency amount of almost $2 billion has been stolen since 2017. Forthwith, attacks on different data systems become frequent around the clock at all possible levels. These potential breaches indicate the necessity of a fortified architecture backed with distributed database and comprehensive risk management and allayed security systems. Our paper reconnoitres the types, algorithm, cyber-attacks with their core ideas, the ways to evade the threats by stating various security solutions, with the ongoing and future technologies to make blockchain, the safest system to protect the data as real-estate blockchain architecture in which an entirely new verified mechanism is introduced in order to reduce the fraudulent activities in the sector.

Published by: Akash Tyagi, Yatin Kalra

Author: Akash Tyagi

Paper ID: V8I3-1339

Paper Status: published

Published: May 23, 2022

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Research Paper

Early-Stage Dementia Detection by Optimize Feature Weights with Ensemble Learning

Dementia has developed into a significant health problem for many over the age of 50. Numerous kinds of dementia develop gradually and incrementally. Previous researchers have received reports from persons of various ages who have had memory loss and subsequent recall from long-term memory loss as a result of this neurodegenerative illness. Memory loss that is both gradual and irreversible characterises the disorder known as dementia. Although it is more common in the elderly, an increase in cases among the younger population has raised experts' eyes and encouraged them to explore the neuro-disorder, which causes memory loss and a barrier in recalling information from memory. Dementia can slow down to some extent if diagnosed early enough. Optimize learning and an additional tree classifier are used to extract information from brain MRI images and classify dementia at an early stage. In order to discover various patterns of dementia risk, hyper-parameters resulting from XGboost were obtained and assessed. Gradient boosting is commonly used to do variable extractions from independent to dependent variables, and the resulting derived variables are the result of this process

Published by: Tanvi Mahajan, Dr. Jyoti Srivastava

Author: Tanvi Mahajan

Paper ID: V8I3-1338

Paper Status: retracted

Submitted: May 23, 2022

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