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Research Paper

Evaluation of crop depredation by Asian Elephant (Elephas maximus) in Badrama Wildlife Sanctuary, Odisha, India

We investigated the human-elephant conflict in eight different ranges in Badrama Wildlife Sanctuary under Bamra (Wildlife) Division, Odisha, India. Elephants were responsible for human casualty, large-scale crop, and property damage; which caused serious human-elephant conflicts in the region were assessed. During 2011-12 – 2015-16, a total of 03 nos. of human killing and 380 human injury cases caused by elephants were recorded. Damage to agricultural crops by elephant was of varying extents i.e. 212.89 acres. As a result, people have developed an antagonistic attitude towards the elephant which adversely affects conservation efforts.

Published by: Barun Kumar Behera, Rabindra Kumar Mishra, Hemanta Kumar Sahu, Prithwiraj Sahu, Sanath Kumar N.

Author: Barun Kumar Behera

Paper ID: V6I4-1432

Paper Status: published

Published: August 20, 2020

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Review Paper

Autism Action Plan of Canada and Northern Ireland – A comparative review

Autism Spectrum Disorder refers to a range of conditions characterised by some degree of impaired social behaviour, communication and language, and a narrow range of interests and activities that are both unique to the individual and carried out in repetition. This paper reviews the Autism Action Plan of two countries, Canada and Northern Ireland and to find out the similarities and differences in their Action Plan and to throw light on their vision, personnel involved (actors) and the policy process. To do this, the health policy triangle has been chosen as a tool to compare and analyse these policies.

Published by: Joshitha Sankam

Author: Joshitha Sankam

Paper ID: V6I4-1385

Paper Status: published

Published: August 20, 2020

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Research Paper

Soil Based, Aeroponic and Hydroponic Systems in Space with Microgravity and Hypogravity Conditions

Colonizing space in the future is a widely discussed topic in this generation, and sustaining it requires a strong agricultural system in the hypogravity and microgravity conditions. Potential agricultural systems have been considered to be put into action since Tsiolkovsky’s works in the early 20th Century. Some of these systems include soil based hydraulics and bioregenerative systems, hydroponic and aeroponic systems which are suitable means to support plants in lower gravity conditions. Testing and data collection on soils and other controls have been done for each method by NASA, Kyushu University etc; and it has been evaluated along with results broadly in terms of input and output factors. The input includes conditions such as water (or medium such as soil), nutrient control, atmospheric control, temperature, humidity and output refers to the yield received. The Controlled Ecological Life Support Systems (CELSS) Program at NASA’s Kennedy Space Centre did hydroponic testing that focused on controlled environment production of wheat, soybean, potato, lettuce, sweet potato etc. Further experiments of Silverstone in Biosphere 2 tested the growth of crops in a Martian-like environment that could fulfill the calorie requirement of a four person crew. At Kyushu University, aeroponic nutrient delivery is tested in a microgravity plant growth unit containing radish seeds. The effect of gravity has also been brought about in each method where soil based agriculture loses points due to the toxic gas emissions and suffocation of roots. Even in the comparison of efficiency between aeroponic and hydroponic systems, aeroponic systems are more suitable than soil based space agriculture. A relative weighted comparison between hydroponics and aeroponics reveals that aeroponics is a slightly more efficient system due to higher nutrient control, less space consumption, high nutrient intake, low water requirement, less nutrient wastage, fast growth and germination rate, fewer chances of disease transmission and better utilization of water supply.

Published by: Saranyaa Kashyap

Author: Saranyaa Kashyap

Paper ID: V6I4-1408

Paper Status: published

Published: August 20, 2020

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Research Paper

Effectiveness of mHealth app on self –management of ascites in terms of knowledge and attitude of chronic liver disease patients

Among all the chronic diseases, Liver Diseases was ranked as the fifth most common cause of death (National Statistics of UK, 2010). The presence of Ascites is a sign of poor prognosis in patients with Chronic Liver Diseases. So, the aim of the present study was to provide an emphasize on Self-Management of Ascites for patients who are living with Chronic Liver Diseases. For this purpose Quantitative approach with Two groups, Pretest-Posttest designs were adopted and a study conducted in Hepatology OPD, ILBS. A total of 60 patients were enrolled based on sampling criteria and consent has been taken. The data was collected by assessing Knowledge and Attitude with Structured Knowledge Questionnaire and Likert Attitude Scale, respectively. These scales were highly reliable and valid. On the same day of assessment of the Experiment group, the mHealth app was introduced and given to the subjects. MS Excel and SPSS 22.0 were used for analysis. The data obtained were analyzed using Descriptive (Mean, Percentage, and chi-square) and Inferential statistics (Paired t-test, Independent t-test, Karl Pearson’s correlation, and Krushkal Wallis test). The study results showed that the majority of patients in both the Experiment and Comparison group were upper-middle-class, male, aged between 47-60 years, married, and residing in urban areas. Independent t-test was computed which showed a significant (p= 0.04) difference between the post-test Knowledge score of Experiment and Comparison group. In the Experiment group, a statistically significant positive correlation (r=0.37, p=0.04) was found between Posttest Knowledge and Posttest Attitude score. Based on the findings of the study, it is concluded that mHealth app was effective in Self –Management of Ascites in terms of Knowledge of CLD Patients.

Published by: Rachna Sharma, Dr. Mini George, Dr. Shasthry SM

Author: Rachna Sharma

Paper ID: V6I4-1425

Paper Status: accepted

Submitted: August 20, 2020

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Research Paper

Review on software defect prediction with role of Machine Learning and Feature Selection

Machine Learning approaches are helpful & have well-tried to be helpful in resolution issues & technical problems that lack data. In most cases, the package domain issues may be characterized as a method of learning that depends on the assorted circumstances and changes of the technical issue being addressed in keeping with the principles of machine learning, a prophetic model is made by exploitation machine learning approaches and classified into defective and non-defective modules. Machine learning techniques facilitate developers to retrieve helpful data when the classification of kinds of technical problems being addressed in an exceedingly specific field. This successively permits them to analyze knowledge from totally different views, which may be used because of the formation base of constructive concepts & varied techniques to handle the technical problems. Machine learning techniques are well-tried to be helpful within the detection of package bugs

Published by: Megha Saloni, Sucheta

Author: Megha Saloni

Paper ID: V6I4-1420

Paper Status: published

Published: August 20, 2020

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Research Paper

Review on credit card fraud detection and classification by Machine Learning and Data Mining approaches

The strategies for this are divided into 2 broad types: fraud detection as well as consumer activity analysis. The initial category of strategies works with controlled recognition processes at transaction stage. Transactions are classified as illegitimate or regular depending on preceding historical evidence in such systems. This dataset can then be used to construct classified models that can forecast the status of new documents (normal or fraudulent). A standard two-classification function, including rule inference, decision trees, as well as neural networks, has various model development approaches. This method has been shown to accurately identify most previously found fraud techniques, often known as identification of misuse essential to illustrate the main discrepancies in an overview of consumer behaviour and methods to fraud investigation. The system of fraud detection can identify established tricks from fraud, with a small false positive rate. Such schemes derive the sign as well as pattern of fraudulent strategies provided in the revelation data set as well as can therefore quickly decide precisely that frauds; the machine is witnessing at the moment.

Published by: Aaushi Sharma, Neha Bathla

Author: Aaushi Sharma

Paper ID: V6I4-1419

Paper Status: published

Published: August 20, 2020

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