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Research Paper

Obstacles and possible enablers to corporate governance practices in Yemen

The main objective is to measure and evaluate the stakeholders’ views regarding the barriers and potential enablers to the application of corporate governance in Yemen. Executives and internal auditors work in the banking sector as internal stakeholders and external auditors as external stakeholders. A questionnaire is the data collection tool. The study concluded that 'the spread of corruption in the government sector is the most crucial barrier. Simultaneously, 'the cost of applying governance is higher than its benefits' is the least affected barrier. In contrast, enhancing professional accounting and auditing bodies, the inclusion of corporate governance in the University Education program; the adoption of international accounting and auditing standards are the most crucial enablers. A study recommended that the government should update financial and supervisory laws and legislations, and the executive authority should monitor their implementation, supporting the anti-corruption process, establish the stock market, spreading the concept of governance in Yemeni society, adding corporate governance as a scientific subject taught in universities and develop and implement training programs to raise the awareness of corporate governance among employees.

Published by: Aiman Alasbahi, Ishwara P.

Author: Aiman Alasbahi

Paper ID: V7I3-1903

Paper Status: published

Published: June 16, 2021

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Research Paper

Deploying Plant Tissue Culture Simulation use case for E-Infrastructures

E-Infrastructures can be defined as networked tools, data, and resources that support a community of practice (CoP), broadly including all those who participate in and benefit from research. During the UNESCO-HP BGI project (2009-2012), the University of Nigeria team conducted experiments on plant tissue culture under the theme, “sustaining the plant tissue culture component of grid computing”. Plant Tissue culture is a method for plant propagation under in vitro conditions. Different types and parts of plants (known as explants) may be cultivated in vitro. Because plant tissue culture is still in its empirical stage, it is time-consuming, cost-intensive, and manpower demanding. These necessitated the design and development of a plant tissue culture simulation application that predicts explant yields using multiple regression models. The initial version that was developed during the BGI project with a prediction accuracy of about 67%, unfortunately, was not deployable on an e-infrastructure like the grid or the cloud. Hence, during the Sci-GaIA project (2014-2017), a use case for the development of a newer version, Plantisc2, that is deployable on e-infrastructure was proposed. The outcome of which is reported in this paper.

Published by: Dr. Collins N. Udanor, Florence Akaneme, Emmanuel Ukekwe

Author: Dr. Collins N. Udanor

Paper ID: V7I3-1825

Paper Status: published

Published: June 16, 2021

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Survey Report

Automatic Helmet Detection and License plate recognition using CNN and GAN

Enforcing use of helmet on every bike- rider is mandatory nowadays because of high accident rate and poor road conditions. There are laws regarding safety measures which ensure use of helmet. But for now, they involve manual intervention which is not so effective as of now because bike-riders sometimes tend to escape without any penalty/fine after breaking the safety rules like wearing a helmet while riding. Automation is better way to deal with this problem but automation in this area comes with its own challenges. To name a few, Low quality image frames (low image resolution, pixel density etc.), rain, dew and fog and partly hidden faces. The robustness of detection methodology strongly depends on the strength of extracted features and also the ability to deal with the lower quality of extracted data. The first goal of this project is to boost the potency of helmet detection and then recognizing the license number plate recognition. This model consists of many essential steps developed using today’s most advanced amp; optimized CNN, GAN models amp; libraries. It is a classification based model that uses supervised learning approach to train CNN and Character Segmentation algorithm. The proposed helmet detection model can be used to detect helmet and recognizes license plate even in adverse conditions using character segmentation and CNN.

Published by: Pranav Sanjay Patil, Damini Kailas Pawar, Shruti Vilas Bairagi, Varun Deepak Bharambe, Nilesh Wankhede

Author: Pranav Sanjay Patil

Paper ID: V7I3-1885

Paper Status: published

Published: June 16, 2021

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Research Paper

Anaerobic Digestion of Food Waste for Production of Purified Methane and Bio-Fertilizers

Anaerobic digestion is a biochemical process in which the organic substances are digested by microorganisms to methane (biogas) and carbon dioxide in the absence of oxygen. This process is spontaneous but the control on large scale requires good knowledge. The search for appropriate models of this entire system of bio gas production with filtration process by providing benefits to society, economy, and environment at the same time make biogas as a sustainable energy resource is covered. The aim of this study is- bio kinetics of anaerobic digestion on several aspects such as microbial activity, substrate degradation and methane production in all economical* aspects. For *this, we developed a system of purifying the biogas by separating the other gases from methane. Purified methane can be used in various fields as domestic and industrial (cooking, electricity, transport and other motive power applications).

Published by: Mayur Kumbhare, Krunal Ghatole

Author: Mayur Kumbhare

Paper ID: V7I3-1862

Paper Status: published

Published: June 15, 2021

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Research Paper

Runes symbols and palmistry- A secret of psychosymbology

Runes symbols are used for various purposes. But it is a hidden treasure. Secrets of runes are revealed in this paper.

Published by: Nandhini

Author: Nandhini

Paper ID: V7I3-1855

Paper Status: published

Published: June 15, 2021

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Research Paper

Study on geopolymer concrete with quarry dust

In order to address environmental effects associated with Portland cement, there is need to develop alternative binders to make concrete. An effort in this regard is the development of Geopolymer concrete, synthesized from the materials of geological origin or by product materials such as fly ash, which are rich in silicon and aluminum. This paper presents results of an experimental study on the compressive strength of Geopolymer concrete. The experiments were conducted on three types of different mixes (M1,M2,M3) containing different amount of sand and Quarry Dust with sunlight curing. The replacement of cement with fly ash is 100%with 10 Molarity of alkaline solution. The ratio of alkaline liquid to fly ash was fixed as 0.4. For all the samples the rest period was kept as 2 days. The compressive strength test was conducted for each sample and the results showed that there is an increase in compressive strength with the increase in age of specimens. The mix M1 containing 40% sand 60% Quarry Dust shows higher compressive strength as it may replace our conventional concrete.

Published by: Saurabh Sambhaji Naik, Omkar Loke, Ajay Sathe, Nitin Khandade, Kiran Akangire, Vinay Pawara, Chaitanya Pawar, Dr. S. R. Bhagat, P. P. Mahajan

Author: Saurabh Sambhaji Naik

Paper ID: V7I3-1868

Paper Status: published

Published: June 15, 2021

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