Volume-9, Issue-5

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Volume-9, Issue-5

September-October, 2023

Research Paper

1. Liver disease detection using Machine Learning techniques

Liver disease is the leading reason of death worldwide, The liver is responsible for metabolic, strength-storing, and waste-filtering functioning in your body. The aim of this study is to develop a machine learning-based technique for liver disease prediction in people. This study on liver disease detection models is meant to determine the best techniques for selecting and synthesizing the many studies of high quality. The majority of health data is nonlinear, correlation-structured, and complex, making it complex to evaluate. The use of ML-based techniques in healthcare has been ruled out. This work uses various machine learning algorithms like decision trees, Naïve Bayes, SVM, Random Forest, CatBoost, and Soft Voting Classifier on the Indian Liver patient dataset to predict liver disease. The research work gives the correct or maximum accuracy model showing that the model is able to predict liver diseases effectively. Our end result shows that the Voting classifier attains higher accuracy as compared to other machine-learning models

Published by: Taranpreet Kaur, Dr.Vinay ChopraResearch Area: Machine Learning

Organisation: DAV Institute of Engineering and Technology, Jalandhar, PunjabKeywords: Liver Disease, SVM, NB, Random Forest, Catboost, Soft Voting Classifier

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Research Paper

2. Improving performance in Central Sterile Supply Department(CSSD) management through performance measurements utilizing user satisfaction surveys and intervention.

Surgical procedures leading to surgical site infections, and medical procedures associated with iatrogenic infections can be made negligible with sterilization and decontamination of instruments and medical devices The Central Sterile Services Department (CSSD) is the hub in the hospital working to provide sterile instruments and packs to all areas of the hospital. The quality of services provided by the CSSD Department in AIIMS Bibinagar regarding the processing as well as the service was to be assessed by all the user departments. The questionnaire was devised after discussion and distributed to the end-user personnel. There were 19 questions addressing the timing, etiquette, equipment, damages, delays, validation as well as feedback regarding improvement. There were a total of 107 respondents of whom 87 were nursing officers and 25 were doctors from medical, surgical, obstetric, orthopedic, ENT, and ophthalmological specialties. The data collected was collated in Microsoft Excel and descriptive analysis was done. The results showed that more than 90% were satisfied with the validation process, the packing of items, the etiquette of the personnel, and the cleanliness of the equipment. Critical responses to consider for intervention included a lack of awareness regarding the indicators and the validation of the sterilization process, nearly 68% lacked knowledge of this. Further, there was dissatisfaction regarding updates and any recent innovations in the system. Only 62% were overall satisfied with the CSSD service, with 11% not sure as to what can be improved. Interventions to improve the services to address the issues raised from the feedback were created utilizing the available resources

Published by: Dr. S. Kalyani Surya Dhana Lakshmi, Dr. A. Bhargav Ram, Rahul K.Research Area: Hospital Administration

Organisation: All India Institute of Medical Sciences, Bibinagar, TelanganaKeywords: Central Sterile Services Department, Quality Of Services, Feedback , Questionnaire, User Satisfaction

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Review Paper

3. Analyzing the potential role of Artificial Intelligence in overcoming limitations of robots in space exploration

Robotic systems are an integral part of space exploration missions. These robots can explore and navigate extraterrestrial terrain and can survive in the harsh environments of space. Autonomous navigation and mapping capabilities are just some of the components that are essential for us to efficiently traverse and gather scientific data. This research paper aims to explore the application of artificial intelligence (AI) techniques in enhancing the exploration efficiency of planetary robots. The paper also discusses the limitations of robots in space exploration and outlines how AI can be used to overcome them.

Published by: Siddharth KannanResearch Area: Aerospace Engineering

Organisation: Prabhavati Padamshi Soni International Junior College, Mumbai, MaharashtraKeywords: AI, Space Exploration, Algorithms, Autonomous Navigation

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Research Paper

4. Evaluation of limestone resources in parts of Palnad basin, Nalgonda district, Telangana

Palnad Basin is the storehouse of limestone which is equivalent to the Narji limestones of the Kurnool Basin. Krishna stream cut over the Palnad Basin generally is EW course and limestones uncovered on either side. Palnad Basin covers parts of Nalgonda district of Telangana and the Krishna & Guntur districts of Andhra Pradesh. The Palnad limestones are lithologically similar to the Narji limestones of the Kurnool basin (Madhusudhan Rao, 1964). (Madhusudhan Rao, 1964). They are well exposed on either side of the Krishna River to the North of river Krishna in Nalgonda, to the South of river Krishna in Guntur district of Andhra Pradesh, and to the East of river Krishna in Krishna district of Andhra Pradesh. Nalgonda district is located in the southern part of Telangana state in India and encompasses an area of roughly 14,240 square kilometers. The district has abundant natural resources, including limestone, and quartz. The geology of Nalgonda district is diversified, with rocks ranging in age from the Archean to the Quaternary. The district is separated into four major geological units: the Archean Gneissic Complex, the Proterozoic Cuddapah Supergroup, the Mesozoic Deccan Traps, and the Recent Alluvium. Limestones display a considerable range in hue viz., purple, green, pale green, chocolate, buff, dark grey, and light grey. The limestones are fine-grained with shallow dips across the whole basin, but rolling dips are not unusual. Limestone resources evaluated in

Published by: Raju Macharla, A. Narsing RaoResearch Area: Geology

Organisation: Osmania University, Hyderabad, TelanganaKeywords: Palnad Basin, Limestones, Nalgonda, Resource Evaluation,

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Research Paper

5. Vehicle Diagnostics Systems and Intelligent Failure Prediction

The automotive industry's rapid growth has led to increased vehicle numbers and subsequently higher failure rates. Conventional diagnostics react to failures, lacking preventive capabilities. Current On-Board Diagnostics are no longer sufficient, necessitating upgrades. To address this, I propose implementing Internet of Things (IoT) devices and Deep Learning Models to predict failures in advance, saving costs and avoiding mishaps. These models utilize historical data and vehicle tests to establish threshold values, triggering warnings if the system detects potential failures. The system comprises an OBD device sending data to a remote server, which updates a dashboard with real-time failure alerts.

Published by: Suyash PustakeResearch Area: Computer Science

Organisation: AISSMS College of Engineering, Pune, MaharashtraKeywords: Vehicle Diagnostics, Sensor Fusion, Predictive Analytics, Deep Learning

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Research Paper

6. Utilizing LSTM neural networks for sentiment analysis of tweets

Deep Neural Networks are considered as one of the most powerful machine learning methods of recent times. Recurrent neural networks, including LSTM variations, exhibit exceptional performance in sequence-oriented assignments, while also falling within the domain of autoregressive models, wherein forecasts are tied to the historical input context. In this paper, we experiment with LSTM for Twitter sentiment analysis. Leveraging advances in Natural Language Processing (NLP), we show the efficacy of our algorithm with extremely competitive results.

Published by: Manan GangwaniResearch Area: Natural Language Processing/Machine Learning

Organisation: Podar International School, Maharashtra, MumbaiKeywords: Neural Networks Long-short term memory Sentiment Analysis

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Research Paper

7. Free-body modal analysis of a Baja SAE vehicle chassis

With the growing need to design increasingly efficient and complex systems, engineering studies are increasingly resorting to computer simulation techniques to analyze the performance and behavior of physical systems. These simulations help to reduce the time and cost of developing new projects. The aim of this article was to carry out a free-body modal simulation of the chassis of a Baja SAE off-road mini vehicle, using the finite element method. The study used Solidworks software to generate the 3D model of the chassis and Ansys software to carry out the simulations. At the end of the simulations, it was possible to see that the chassis structure has natural frequencies between 36 and 86 Hertz (Hz) when the structure is free, which are different from the frequencies of the main source of forced vibration in the structure. In this way, it can be concluded that the structure does not enter the resonance phenomenon, meeting the design assumptions.

Published by: Leandro de Paula Freire, Luiz Augusto Ferreira de Campos VianaResearch Area: Mechanical Engineering

Organisation: Instituto Federal de Educação, Ciência e Tecnologia de Minas Gerais, Arcos - MG, 35588-000, BrazilKeywords: Finite Elements, Modal Analysis, Mechanical Vibrations, Baja Sae, Chassis

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Research Paper

8. Periodicity of the Probability Distribution of a Particle in a Box

We consider a particle in a two-dimensional infinite potential square well in states that are superpositions of either two or three energy eigenstates. These have probability distributions that are periodic in time. We compute the periods in both cases and simulate the time dependence of the probability distributions.

Published by: Jettae SchroffResearch Area: Quantum Mechanics

Organisation: Cambridge Centre for International Research, Cambridge, United KingdomKeywords: Physics, Quantum Mechanics, Probability Distributions, Eigenstates, Simulation, Particle In A Box

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Research Paper

9. Smart Water Management

The shortage of water supplies has emerged as a pressing worldwide issue in a world that must contend with the twin problems of a growing population and climate change. The need for effective water management has grown, and it is all too easy to see the results of carelessness and human mistake in managing water resources. Artificial Intelligence (AI), however, is a promising solution in the realm of computer science. A developing area of computer science called artificial intelligence has the power to completely alter how we manage our water resources. Computers, as opposed to people, are known for their accuracy and dependability. Utilizing AI in water management could not only correct past mistakes but also save millions of liters of water each year, thereby helping the world's population, which is always expanding. At its foundation, smart water management comprises effectively managing water resources with the least amount of human involvement. Data-driven "intelligent" applications have already revolutionized many elements of our daily lives in the digital age. Water utilities that are forward-thinking can greatly improve their operational performance by using this digital technology revolution. For water utilities starting their journey toward digital transformation, this abstract offers an introduction to the core AI ideas. It puts a strong emphasis on streamlining water distribution processes and dealing with the urgent problem of unaccounted-for water. Water utilities may use a wealth of data and information to improve service delivery, lower operating costs, and make better decisions by utilizing the power of AI algorithms and big data analytics. This succinct review describes the wide-ranging uses of big data analytics and AI-related algorithms in the water supply industry. It also explores how water utilities might use AI to predict and reduce unaccounted-for water, a problem that persists in the industry. Finally, actionable suggestions for implementing AI are offered, along with first cost projections.

Published by: Pranav PradhanResearch Area: Computer Science

Organisation: Pune Vidyarthi Griha's College of Engineering and Technology, Pune, MaharashtraKeywords: Artificial Intelligence, Water Management, Hydraulic Modelling 1.0, Hydraulic Modelling 2.0, Big Data.

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Research Paper

10. The Plight of People below The Poverty Line in India

One of India's most pressing societal problems is poverty. A sizable portion of the Indian population is impacted. Due to the recession brought on by the COVID-19 pandemic, the number of impoverished people in India has more than doubled from 60 million to 134 million in only one year. As a result, India has once again returned to the category of "country of mass poverty" after 45 years. The negative effects of poverty on our country's children include subpar housing, homelessness, poor nutrition, and food security, inadequate child care, a lack of access to health care, hazardous neighbourhoods, and underfunded schools. It is a must to take prompt, appropriate action to address the issue of poverty. Farmers should be provided with enough amenities that they can make farming viable and avoid moving to cities in search of work. People who lack literacy should be provided with the necessary training so they may earn their living. Family planning should be practiced to stop the population from growing. Additionally, steps should be taken to eradicate corruption so that we can address the wealth disparity. The issue of poverty affects the entire country, not just one individual. For India's people, society, and economy to thrive sustainably and inclusively, poverty must be eradicated.

Published by: Aleya Masand, Samara MasandResearch Area: Sociology

Organisation: Bombay Scottish School, Mumbai, MaharashtraKeywords: Absolute Poverty, Relative Poverty, Urban Poverty, Cyclical Poverty, Chronic Poverty, United Nations Development Programme (UNDP), Oxford Poverty and Human Development Initiative (OPHI), Dalit, Livelihood, Panchayati Raj Institutions (PRIs), Antyodaya Anna Yojana (AAY), Swarna Jayanti Shahari Rozgar Yojana (SJSRY), Prime Minister’s Rozgar Yojana (PMRY), Sampoorna Grameen Rozgar Yojana (SGRY), Indebtedness, Rag Pickers, Beggars, Push-Cart Vendors, Street Cobble, Zamindari System, Global Hunger Index, Multidimensional Poverty Index, World Health Organisation (WHO)

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Research Paper

11. A study to examine the efficacy of the nurse-driven client-centered intervention on sexuality among middle adulthood in the primary health center, Achankuttapatty at salem -Pilot study

Middle adulthood, typically spanning from the ages of 40 to 65, is a significant phase in an individual's life characterized by various physical, emotional, and psychological changes. Among these changes, the evolution of one's sexual identity and experience remains a critical aspect of overall well-being. Nurses, as frontline healthcare providers, are ideally positioned to address these issues through client-centered interventions. This research study aims to investigate the efficacy of nurse-driven client-centered interventions in addressing sexuality-related issues among middle-aged adults. It will explore the impact of such interventions on sexual health outcomes, emotional well-being, and overall quality of life in this population. Methods: The research approach adopted for the study was a true experimental design. The selection of subjects was done by Simple random sampling technique method and the sample consisted of 10 middle adulthoods residing in Achankuttapatty, Salem, Tamil Nadu. The data was collected by administering Multi-dimensional Sexuality Questionnaire (MSCQ) questionnaires The validity and reliability of the tool were obtained. The collected data were analyzed by using descriptive and inferential statistics in terms of Frequency, Percentage distribution chi-square test, and independent ‘t-test. Results: In the experimental group most (75%) of them were moderate satisfaction whereas in the control group most (60%) of them were severe satisfaction. The overall mean percentage in the experimental group was 83% whereas in the control group, it was 66%, revealing a difference of 17%. The paired test value in the experimental group was 19.1 whereas in the control group, it was. The unpaired test value was 8.4, which shows that there is a highly significant difference between the experimental group and the control group post post-test scores of sexuality in middle adulthood. Conclusion: From the findings it can be concluded that hallmark Vs resilience training and behavioral intervention were effective in improving the functions of sexuality in middle adulthood.

Published by: S. Nasira, Dr. P. PadmavathiResearch Area: Nursing

Organisation: Vivekanandha College of Nursing, Namakkal, Tamil NaduKeywords: Nurse Driven Client Centered Intervention, Sexuality, Middle Adulthood

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Research Paper

12. Impact of procrastination on everyday life

The purpose of this study was to shed light upon a very common issue in everyday life, focusing on adolescents as the target group. A survey research design was used to perform this study, where respondents were asked the degree to which they agreed with 18 statements on a scale of 1-5. Findings show that most adolescents do struggle with this phenomenon as a part of their daily lives, and also touch upon the causes of why this might occur. Although this varies from individual to individual, a common trend is visible and must be addressed.

Published by: Anivartin DagaResearch Area: Behavioural Psychology

Organisation: Vasant Valley School, New Delhi, DelhiKeywords: Procrastination, Behavioural Psychology, Deadlines, Priorities, Socio-Personal Variables, Productivity, Short-Term Pleasure, Emotional Well-Being, Psychophysiological Reactivity, Structured Goal Setting, Time Management, Self-Efficacy

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Research Paper

13. Impact of Foreign Direct Investment in Banking Sector in India

In India, the banking industry is incredibly dominating. Due to globalization, Indian banks compete on the basis of their cutting-edge goods and strong financial standing. Since India embraced economic reforms in 1991, the Indian banking system has advanced significantly. Foreign direct investment is being sought after as a vehicle for technology transfers, as a way to achieve competitive efficiency by building a significant global connectivity network, and as a source of non-debt inflows. FDI has made a significant contribution to the improvement of the Indian banking sector's efficiency, the development of novel financial products, and the improvement of banks' capitalization by making them more flexible to changing market conditions.

Published by: Antara RauResearch Area: Business Studies And Finance

Organisation: Cathedral and John Connon School, Mumbai, MaharashtraKeywords: Foreign Direct Investment (FDI), Economic Growth, Reserve Bank of India (RBI), Private Sector, Public Sector, Non-Performing Assets (NPAs), Insolvency, Bankruptcy, PJ Nayak Committee, Leverage, Liberalization, Organisation for Economic Cooperation and Development (OECD), Capitalization

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Review Paper

14. A Survey Based on Twitter data using Sentiment Analysis

available to internet users thanks to the development and growth of online technologies. The internet has developed into a forum for online education, idea sharing, and opinion exchange. Social networking services like Twitter, Facebook, and Google+ are quickly gaining popularity as a result of the ability for users to share and express their opinions on many subjects, engage in conversation with various communities, and broadcast messages globally. The study of sentiment in Twitter data has received a lot of attention. This study primarily focuses on sentiment analysis of Twitter data, which is useful for analyzing information in tweets when opinions are very unstructured, varied, and occasionally neutral. The strategies for opinion mining that are currently in use, such as lexicon-based approaches and machine learning, are surveyed, compared, and evaluated in this work along with evaluation measures. We present research on Twitter data streams using different machine learning techniques such as Naive Bayes, Max Entropy, and Support Vector Machine. Additionally, we covered the general difficulties and uses of sentiment analysis on Twitter.

Published by: Mayank Devani, Dr. Harsha Padheriya, Vijaysinh K. JadejaResearch Area: Machine Learning

Organisation: SAL College of Engineering, Ahmedabad, GujaratKeywords: Twitter, Sentiment Analysis (SA), Opinion Mining, Machine Learning, Naive Bayes (NB), Maximum Entropy, Support Vector Machine (SVM).

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Research Paper

15. A study to assess the effectiveness of a structured teaching program on knowledge regarding HIV-AIDS among the students of selected JR. College in Aurangabad city.

India is one of the largest and most populated countries in the world, with over one billion inhabitants of this number, it’s estimated that around 2.5 million people are currently living with HIV. One group pre-test and post-test design was used in this study. A purposive sampling technique was used to select 60 Jr. College students. Based on the objective collected data was analyzed by using descriptive and inferential statistics like mean, median, standard deviation, paired t-test, and chi-square test. An analysis finding depicts that the corresponding p<0.05, so the null hypothesis is rejected. The change in the post-test knowledge score (23.76) of Jr. College students is significantly higher than the pre-test score (15.73). The structured teaching program is proven an effective method to improve the knowledge of Jr. College students regarding HIV-AIDS. The study also had a significant association between knowledge score and Age and other variables are not significant.

Published by: Shaikh Ateeq AhmedResearch Area: Nursing

Organisation: Dr. Prafulla Patil BSc Nursing College, Parbhani, MaharashtraKeywords: Effectiveness, Structured Teaching Program, Students, HIV-AIDS.

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Review Paper

16. Assessment of cybercrime investigations in forensic medicine

"Assessment of Cybercrime Investigations in Forensic Medicine" is an interesting and relevant topic that intersects the fields of cybercrime, digital forensics, and forensic medicine. Here's a breakdown of how you could structure your paper presentation on this topic:

Published by: Dr. G. Panneer SelvamResearch Area: Forensic Medicine

Organisation: Swamy Vivekanandha Medical College and Research Institute, Namakkal, Tamil NaduKeywords: Cybercrime Investigations, Forensic Medicine in Cybercrime Digital Forensics, Cybercrime Computer Crime Investigations, Cybercrime Forensics Cybercrime Evidence Analysis, Digital Evidence Examination, Cybercrime Forensic Techniques, Cybercriminal Profiling, Cybercrime Forensic Tools, Digital Forensics Technologies, Cybercrime Case Analysis

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Research Paper

17. A novel risk assessment and screening tool for Learning Disorders in children

Learning disorders (LDs) are neurodevelopmental disabilities with a worldwide prevalence of 5-15%. Lack of awareness paired with heterogeneity in testing methods results in non-identification of LDs in children. Assessment tests presently used to diagnose LDs require the physical presence of a medical professional, are time-consuming and expensive, and adopt a non-child-centric approach. DysDiag proposes novel, accessible, and easy-to-administer risk assessment and screening tests (based on DSM-5 criteria), for LDs in children (5-8 years). DysDiag’s test for Dyslexia consists of a gamified, visual-based quiz that accesses the child’s phonemic, auditory, and visual-based skills followed by a pronunciation test and parental questionnaire. The test for Dysgraphia includes 2 Machine Learning Image Classification Models that classify the child’s handwritten sample as dysgraphic or normal and further evaluate the sample for 6 diagnostic symptoms. The models recorded F1 scores of 0.785 and 0.964 respectively. The test of Dyscalculia includes a facial emotion recognition model alongside a response-time-based math quiz and a parental questionnaire. DysDiag was tested on 40 children consisting of a case group of pre-diagnosed children (n=20, mean age=6yrs) and a control group (n=20, mean age=7yrs). The children were tested by a registered medical professional followed by DysDiag’s screening tests. DysDiag recorded a sensitivity and specificity of 90%, a Positive Predictive Value of 94.73%, and a Negative Predictive Value of 90.47%. DysDiag was also reviewed and rated by 15 psychologists and pediatricians. DysDiag proved to be a clinically viable tool that can aid in the early identification and mass screenings for LDs at elementary schools.

Published by: Spurti NimbaliResearch Area: Behavioral and Social Sciences

Organisation: Delhi Public School R.K. Puram, New Delhi, DelhiKeywords: Learning Disorders, Neurodevelopmental Disorders, Dyslexia, Dysgraphia, Dyscalculia, Behavioral And Social Sciences, Learning Disabilities, Reading Difficulties, Case-Control Study On Learning Disorders, Risk-Assessment For Learning Disorders

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Research Paper

18. A Study to Examine the Efficacy of Nurse Driven Client Centered Intervention on Sexuality Among Middle Adulthood in Primary Health Center, Achankuttapatty at Salem-Pilot study

Background: Middle adulthood, typically spanning from the ages of 40 to 65, is a significant phase in an individual's life characterized by various physical, emotional, and psychological changes. Among these changes, the evolution of one's sexual identity and experience remains a critical aspect of overall well-being. Nurses, as frontline healthcare providers, are ideally positioned to address these issues through client-centered interventions. This research study aims to investigate the efficacy of nurse-driven client-centered interventions in addressing sexuality-related issues among middle-aged adults. It will explore the impact of such interventions on sexual health outcomes, emotional well-being, and overall quality of life in this population. Methods: The research approach adopted for the study was a true experimental design. The selection of subjects was done by Simple random sampling technique method and the sample consisted of 10 middle adulthoods residing in Achankuttapatty, Salem, Tamil Nadu. The data was collected by administering Multi-dimensional Sexuality Questionnaire (MSCQ) questionnaires The validity and reliability of the tool were obtained. The collected data were analyzed by using descriptive and inferential statistics in terms of Frequency, Percentage distribution chi-square test, and independent ‘t-test. Results: In the experimental group most (75%) of them were moderate satisfaction whereas in the control group most (60%) of them were severe satisfaction. The overall mean percentage in the experimental group was 83% whereas in the control group, it was 66%, revealing a difference of 17%. The paired test value in the experimental group was 19.1 whereas in the control group, it was. The unpaired‘t test value was 8.4, which shows that there is a highly significant difference between the experimental group and control group post-test scores of sexuality in middle adulthood. Conclusion: From the findings it can be concluded that hallmark Vs resilience training and behavioral intervention was effective in improving the functions of sexuality in middle adulthood.

Published by: S. Nasira, Dr. P. PadmavathiResearch Area: Nursing

Organisation: Vivekanandha College of Nursing, Elayampalayam, Tamil Nadu, Affiliated to the Tamil Nadu Dr. M. G. R. Medical University Chennai Tamil NaduKeywords: Nurse Driven Client Centered Intervention, Sexuality, Middle Adulthood

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Technical Notes

19. Forensic pathology and autopsy techniques

forensic medicine and pathology play a vital role in the justice system and society at large. The techniques and expertise of forensic pathologists are instrumental in determining the cause of death, solving crimes, and ensuring justice is served. This field continues to evolve with advancements in technology, making it a critical aspect of modern law enforcement and public health.

Published by: Dr. G. Panneer SelvamResearch Area: Forensic Medicine

Organisation: Swamy Vivekanandha Medical College and Research Institute, Namakkal, Tamil NaduKeywords: Forensic Medicine, Forensic Pathology, Autopsy Forensic Pathologist, Histopathology ,Radiology DNA Analysis

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Research Paper

20. Application of Catboost algorithm as a predictive tool in a CNC turning process

In this paper, an ensemble learning method, in the form of a Categorical boost (Catboost) algorithm is adopted as an effective predictive tool for envisaging values of average surface roughness and material removal rate during the CNC turning operation of C45 steel workpiece with a tungsten carbide cutting tool. In order to develop the related models, a grid with combinations of different hyperparameters is created and tested for all the possible hyperparametric combinations of the model. The configurations having the optimal values of the considered hyperparameters and yielding the lowest training error are finally employed for predicting the response values in the CNC turning process. The performance of the developed models is finally validated with the help of root mean squared percentage error. It can be observed that Catboost can be efficiently applied as a predictive tool with excellent accuracy in machining processes.

Published by: Lalitkishore N., Shriraam ManoharanResearch Area: Mechanical Engineering

Organisation: Kumaraguru College of Technology, Coimbatore, Tamil NaduKeywords: Catboost, LSTM, Material removal rate, Root Mean Square Error, Root Mean Squared Percentage Error (RMSPE)

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Review Paper

21. Therapeutic use of psilocybin to treat alcohol use disorder: New York University

Alcoholism, a pervasive global health issue, demands innovative and effective treatment modalities. Recent interest in psychedelic drug therapy has opened new possibilities for addressing the complexities of alcohol use disorder (AUD). This research paper provides a comprehensive analysis of the groundbreaking trial conducted by New York University, which investigated the therapeutic potential of psilocybin, a classic psychedelic substance, in treating alcoholism. The trial's methodology included a double-blind randomized clinical trial measuring the efficacy of psilocybin against a placebo.Results indicated that 50% of the patients who received psilocybin stopped drinking altogether. These findings signify the potential of psychedelic drug therapy as a transformative intervention for alcoholism and highlight the need for further research in this promising field.

Published by: YutiResearch Area: Neuroscience

Organisation: Independent ResearcherKeywords: Ethical, Psilocybin, AUD( Alcohol Use Disorder), Psychedelic, Clinical Trial, Placebo

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Review Paper

22. Ethical Guideline for Use of AL and ML Algorithms in Decision Making

Decision-making is a structured process involving the identification of objectives, the collection of relevant information, and the evaluation of potential solutions. This process fosters an environment conducive to innovation. Artificial Intelligence (AI) and Machine Learning (ML) algorithms comprise a set of instructions that enable machines to learn and make decisions based on acquired knowledge. The rapid evolution of research, development, and application of these technologies has led to their increasing integration into decision-making processes. To ensure the ethical use of AI and ML algorithms, comprehensive guidelines have emerged. These guidelines provide a framework for the responsible development and deployment of technology. By incorporating principles of transparency, fairness, accountability, and accuracy into AI and ML algorithms, these guidelines aim to build trust and mitigate bias. Despite the existence of various guidelines, they often lack specific applicability to particular use cases. To address these challenges and provide practical guidance, we have derived actionable guidelines for the ethical use of AI and ML algorithms in decision-making from existing ethics. This review paper analyzes these guidelines and provides a detailed overview of the ethical principles underpinning them.

Published by: Diksha Gaikwad, Aditee Thute, Akanksha Jadhav, Apurva ShelkeResearch Area: AI and ML

Organisation: Bharati Vidyapeeth's College of Engineering Pune, MaharashtraKeywords: Artificial Intelligence, Machine Learning, Guideline, Ethics, Decision-making.

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Research Paper

23. A study on the impact of binge-watching on dissociation

To study the impact of Binge-watching on Dissociation Binge-watching is a relatively new phenomenon that has gained popularity recently. Due to Covid 19 Lockdown, OTT platforms have seen a 65% increase in new subscriptions. Many studies have looked upon binging as a behavior, but minimal studies investigate the specific bingeing aspect, of binge-watching and the effects it might be causing. This study analyses binge-watching and its impact on dissociation-normative dissociation. The study consists of a survey design that helps to understand the relationship between binge-watching and dissociation. It comprised 125 responses divided into two age groups viz. 18-25 years and 25-30 years. The individuals were compared using the Binge Watching Engagement and Symptom Questionnaire (BWESQ) and the Cambridge Depersonalization Scale (CDS). It was hypothesized that there is no correlation between binge-watching and dissociation, there is no difference between excessive and non-excessive binge-watchers concerning dissociation, and there is no difference between the two age groups 18-25 and 25-30 concerning binge-watching and dissociation. Post correlation analysis, it was found that Binge-watching correlated positively with Dissociation. A difference is observed with respect to excessive binge-watchers and non-excessive binge-watchers for dissociation. It was also found that there is no difference between the age groups 18-25 and 26-30 on binge-watching and dissociation. These findings suggest that further research can be done on neuropsychological, executive functioning, and structural aspects of the same.

Published by: Arushi Aniruddha BhorkarResearch Area: Psychology

Organisation: Mount Carmel College, Bengaluru, KarnatakaKeywords: Binge- Watching, Dissociation

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Research Paper

24. Spatiotemporal variability time-series analysis of North American wildfire intensity on vegetation recovery using NDVI, EVI, and GPP

Wildfires are major disturbances that can leave lasting impacts on the ecosystem, biodiversity, and our society. Just this past year, over 4 million acres of land were burned across California, making the 2020 fire season the largest ever recorded in the state. Using three indices derived from satellite data, NDVI, EVI, and GPP, the post-fire recovery values in the indices were analyzed, and the results were used to determine whether vegetation type could affect the recovery. Three fires from the 2004 fire season in Alaska were selected to mimic the forest ecosystems in California without direct disturbances from human activities. MODIS-derived images were extracted from the Earth Explorer database every year from 2000-2018 and individually processed in QGIS to calculate NDVI, EVI, and GPP. The data of pre-fire areas from 2000-2003 was averaged and used as a control and reference area. NDVI and EVI values in post-fire recovery were extremely similar in areas with dense conifer populations and took an average of 8 years to recover, while GPP values show quicker recovery at only 3 years. Results also demonstrate that an area with a balance of 46% shrubs and 40% conifers recovered much faster, at around 3 years for all indices, in comparison to areas with 76% dense conifer populations. Using only one index is not enough for the most accurate results and it is critical to implement a variety of remote-sensing techniques in forest planning and recovery.

Published by: Amy ZhengResearch Area: Earth And Environmental Sciences

Organisation: Monta Vista, CA, USAKeywords: Satellite Imagery, NDVI, EVI, GPP, Wildfire

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Research Paper

25. Assessing a set of policies and the usage of smart tech to mitigate and minimize the risk of school shootings in the United States

Analyze how the implementation of smart guns, along with other policies to enhance the efficiency of this technology, should mitigate the risk of public and private school shootings, as well as the possible psychological ramifications it might have on students and the quality of the education that they receive.

Published by: Dia Bagla, Jiho Choi, Aditya Gupta, Ammu SantoshResearch Area: Economics

Organisation: The International School Bangalore, Bengaluru, KarnatakaKeywords: Illegal Markets, Unlicensed Misuse, School Shootings, Antidepressants, Chronic Absenteeism, Smart Guns

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Research Paper

26. Optimizing Regulatory Compliance in Accounting: A Holistic Approach through Audits, Training, and Technology

With the constantly evolving regulatory landscape, organizations face high financial, legal, and reputational risks. To cope with these risks effectively, a holistic approach needs to be implemented, which includes periodic audits, targeted employee training, and cutting-edge regulatory technology. In this paper, we present a framework that employs machine learning techniques to predict regulatory violation rates. By using advanced algorithms and data analytics, our model not only identifies potential compliance breaches but also facilitates proactive decision-making and risk prevention. The use of machine learning enhances the accuracy and efficiency of compliance predictions, thereby enabling organizations to be a step ahead of regulatory challenges. We conduct a detailed analysis of real-world data from different sectors, employing a range of machine-learning algorithms to develop a predictive model. The results of the model demonstrate the efficacy of our approach in accurately forecasting regulatory violations. Additionally, we explore the effects of periodic audits, employee training programs, and regulatory technology to enhance overall compliance. This paper contributes valuable insights to the field of regulatory compliance and machine learning applications. The findings from the research provide a path for companies to proactively prevent financial losses, legal complications, and reputational damage. By embracing this holistic approach, organizations can create a culture of compliance, ensuring sustainable growth and resilience in the face of regulatory challenges. It also emphasizes the importance of continuous improvement, suggesting that a dynamic approach to compliance, informed by real-time data and machine learning insights, is pivotal in maintaining robust regulatory adherence and safeguarding organizational integrity.

Published by: Vaishnav Bhujbal, Dheeraj NaleResearch Area: Data Science And Machine Learning

Organisation: Pune Vidyarthi Griha's College of Engineering and Technology, Pune, MaharashtraKeywords: Regulatory Compliance, Accounting, Machine Learning, Predictive Modelling, Data Analytics, Proactive Risk Prevention.

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Thesis

27. Flexible Pavement Evaluation by Falling Weight Deflectometer Test Using IIT-Pave and KGP Back Software.

It is now possible to regularly apply an analytical-empirical (or mechanistic) method of structural pavement evaluation because to the rapid development of technology and software over the past ten years. It is described how to determine the modulus of each structural layer in a pavement system. These moduli are determined non-destructively and in situ under conditions very similar to those caused by heavy traffic. The method is analyzed using empirical evidence, and some practical examples are given to illustrate its use. An analytical-empirical approach is recommended for the structural design of pavement systems. An "analytical method" or a "mechanistic method," as it has an important empirical component, is often referred to as such, and therefore the term "Analysisal-Empirical" is more appropriate. FWD test has been conducted at the designated sites, with KGP Back software being used to analyze the results (IRC 115-2014), and IIT-Pave software verifying the design.

Published by: Mohd. Irshad Iqbal Ansari, Sachin BhardwajResearch Area: Civil Engineering

Organisation: Geeta Engineering College, Naultha, HaryanaKeywords: FWD, Strain, IIT-Pave, KGP Back

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Research Paper

28. Quantum computing and its potential to revolutionize information processing

Quantum Computing has emerged as a promising field with the potential to revolutionize information processing. Unlike classical computers that rely on the binary system, quantum computers use qubits, which can exist in multiple states simultaneously, which allows them to solve problems more quickly and efficiently. Hence, this research paper explores the principles of quantum computing, its advantages, and how it has the potential to revolutionize information processing. Furthermore, it also considers the challenges that need to be resolved in order to make it a practical reality.

Published by: Shaurya JindalResearch Area: Computer Engineering

Organisation: Vivek High School, Sector 38, ChandigarhKeywords: Quantum Computers, Quantum Mechanics, Information Processing, Qubits, Binary System, Superconducting Qubits, Superposition, Quantum Advantage

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Research Paper

29. Effect of parental involvement on adolescents’ academic performance

The purpose of this study was to analyze parental involvement and the extent to which it has an effect on adolescents, primarily their academic performance and education. Findings indicated that the sample of 25 students felt that their parent(s) played an active role in their life and education and felt motivated by their involvement. The survey research method was used to collect data for the study.

Published by: Shreyasi JindalResearch Area: Psychology

Organisation: Vasant Valley School, New Delhi, DelhiKeywords: Adolescents, Parental Involvement, Academic Performance, Education, Ecological Systems Theory, Reinforcement, Positive Reinforcement

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Research Paper

30. Analysis of the effectiveness of the digital enrollment and grading system

The Online Enrollment and Grading System of Bato Institute of Science and Technology is a comprehensive platform that helps manage all aspects of student enrollment and grading. It provides an efficient way to store and manage student data, grade reports, and enrollment records, ensuring that all relevant information is tracked from the beginning of a student's course until the end. The system uses a completely computerized process, reducing the chance of human error and maintaining accurate data. The system also includes a backup system that allows for the retrieval of important information in case of any system malfunctions, ensuring that student and organizational data is secure. There are two access modes: administrator and user. The administrator module is responsible for maintaining the system by creating user accounts, scheduling system updates, and making sure everything runs smoothly. The user module allows staff and students to access their grades and other reports. To evaluate the system's effectiveness, the researcher used Descriptive Developmental Research to gather feedback from both staff and students. Based on the results of the data, the researcher concluded that the Online Enrollment and Grading System is highly effective with a "very good" rating. However, there is always room for improvement in any system to prevent potential issues. Therefore, the researchers recommend continuous evaluation and improvement of the platform to maintain high standards of service and efficiency. In conclusion, the Online Enrollment and Grading System of Bato Institute of Science and Technology is an efficient and effective platform that meets the needs of both staff and students, providing a valuable solution for managing enrollment and grading processes.

Published by: Mary Jane Pagay Cierva, Rhoderick D. MalangsaResearch Area: Information Technology

Organisation: Southern Leyte State University, Southern Leyte, PhilippinesKeywords: Computerization, Management System, Online Enrollment, Web-Based System

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Research Paper

31. Care: Cardiac attack risk estimation using Machine Learning

We are revolutionizing heart attack risk assessment with our ground-breaking initiative, "CARE: Cardiac Attack Risk Estimation Using Machine Learning," by utilizing machine learning models' predictive power. Our technology uses past data analysis to forecast the likelihood of a subsequent heart attack based on user-supplied details such as physical attributes, symptoms, and medical background. Our project's main goal is to reduce the burden on the healthcare system by providing users with remote access to screening facilities that can identify people at both low and high risk.With the goal of improving the precision of heart attack risk predictions, our ground-breaking platform, the "Heart Attack Risk Predictor," is a groundbreaking venture into the field of machine learning.

Published by: Patan Imran Khan, Kothamasu Surya Ratna, Meda Gopi Krishna, Nutalpati AshokResearch Area: Machine Learning

Organisation: Vasireddy Venkatadri Institute of Technology, Guntur, Andhra PradeshKeywords: Revolutionizing, Forecast, Data analysis, Precision, Screening Facilities

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Research Paper

32. Hybrid deep approach for malware detection

Malware is malicious software designed to compromise computer systems, and poses a significant threat to businesses, with potential repercussions ranging from financial losses to damaged reputations and eroded customer trust. To address this challenge, we propose a hybrid deep learning approach that combines the power of Long Short Term Memory (LSTM) and Gated Recurrent Units (GRUs), both of which are models in the Recurrent Neural Network (RNN) family. Our research focuses on assessing the potential improvements achieved by this hybrid approach, leveraging a benchmark dataset known as NSL-KDD+. This dataset offers a temporal dimension and encompasses a diverse array of malware samples and network traffic scenarios for comprehensive testing and evaluation. We employ a range of performance metrics, including Accuracy, Precision, F1 Score, Mean Absolute Error (MAE), and others, to comprehensively gauge the effectiveness of our proposed approach.

Published by: Vadduri Uday Kiran, P. Shiva Prasad Reddy, V. Sri Harsha, R. Vijay Kumar, Y. Venkata NarayanaResearch Area: DeepLearning

Organisation: Vasireddy Venkatadri Institute of Technology, Guntur, Andhra PradeshKeywords: Intrusion, Malware Detection, LSTM and GRU, and RNN neural network, Deep Learning RNN Intrusion Detection

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Review Paper

33. The Dilemma in Quantum Mechanics

This study possesses the ambition to further investigate and indulge in the world of quantum mechanics and its complexities and possibly ascertain a solution for one major issue attributed to it: the measurement problem, which refers to, in layman's words, the issue of how and why a wave function collapses. According to papers published during the late 1930s, the measurement problem was an issue that could be partially resolved by utilizing the loosely shaped ideas of the Copenhagen Interpretation, which was later coined by Werner Heisenberg during the 1950s, as well as the newborn Pilot-Wave theory, which was further developed and brought to prominence by David Bohm’s work during the 1950s. However, due to the deficiency of new information from modernized research modalities and experiments, these papers lack the new approaches proposed by various physicists, which places a circumscription on the aptitude possessed on this topic. Hence, through this paper, I possess the ambition to utilize the theories of Many Worlds (MWI), QBism, and the further developed Pilot Wave Theory (PWT) to hopefully solve this issue. Contrary to what has customarily been believed, the measurement problem can be partially solved by twisting the functioning of quantum mechanics according to certain theories, which would then act as a base for them and substantiate their claims regarding the measurement issue, such as the MWI theory going against traditional quantum theory and claiming that particles possess definite properties, with many other theories doing something similar, which I will be articulating upon in this paper. To deduce this prolonged abstract, I hope to provide you with a higher magnitude of perception on this infamous issue and probably resolve some of your pertaining doubts on quantum physics.

Published by: Samarth Krishna MathurResearch Area: Physics

Organisation: Heritage Xperiential Learning School, Gurugram, HaryanaKeywords: Quantum Mechanics, Copenhagen Interpretation, Pilot-Wave Theory, Many Worlds Interpretation (MWI), and QBism

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Research Paper

34. SMS spam detection in Machine Learning using Natural Language Processing

This paper presents the identification of Spam and ham messages using supervised machine learning algorithms Random forest Classifier, and Logistic Regression algorithms and Analyzes how each filter performs when detecting Ham and Spam. A spam message is a big issue in mobile communication to reduce this effective spam detection techniques should be built Preprocessing is done using the NLTK library with various Stemming Algorithms, Word clouds are used and tokenizing is also performed. The data set is divided into two categories for training and testing the classifiers . the results demonstrated that the performance of Random Forest is better than Logistic Regression. Random forest achieved a better accuracy of 97%.

Published by: Thanniru Lakshman, Singarapu Sanjay Kumar, Ulligaddala Satish Kumar, Yenikepalli Sri Sekhar, Yellamati SureshResearch Area: Machine Learning

Organisation: Vasireddy Venkatadri Institute of Technology, Guntur, Andhra PradeshKeywords: SMS, Machine Learning, Random Forest, Logistic Regression, NLP, Spam, Ham.

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Research Paper

35. Fingerprint Sensing Gun

In this modern age of science and technology, threats to our lives are exposed to a lot of unplanned factors, one of them which could being shot by a gun, rather intentionally or not! Fingerprint-sensing gun technology can prove to be a great savior for this crisis. It allows fast authentication of one’s fingerprint to unlock the gun and is used only when necessary. Unauthorized users cannot fire the weapon which itself gives an upper hand to the owner of the weapon. By the use of a handful of electronic components, such a gun can be designed. It could prevent children from shooting a family member and untrained individuals.

Published by: Rohitkumar Mukeshbhai Mistri, Kapil Virbhadra MathpatiResearch Area: Human Safety And Security, Advancements In Mechatronics.

Organisation: JSPM's Imperial College of Engineering and Research, Pune, MaharashtraKeywords: Gun, Security, Technology, Life, Threat, Shootings, Advancement, Fingerprint, Sensors, Protection, Mechanical, Electronics, Mechatronics

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Research Paper

36. Keyword-Based Search Engine Using Cosine Similarity

The development of search engines that can retrieve relevant content based on user-specified keywords is necessary due to the increasing volume of digital information available on the internet. In this abstract, a novel approach is presented to build a keyword-based search engine that uses cosine similarity to enhance search result relevance and precision. Our search engine, which is keyword-based and uses cosine similarity, has several benefits over traditional search engines. The accuracy of search results is improved by taking into account semantic relationships between words, leading to a more contextually relevant ranking. With increased precision and efficiency, users can expect better search experiences when searching for the information they need.

Published by: Ancha Venkata Lakshmi Narasimha, Athalury Rohith, Bakkamantala Teja Kumar, Chakka Venkateswara Rao, Rekha Sudha KishoreResearch Area: Machine Learning

Organisation: Vasireddy Venkatadri Institute of Technology, Guntur, Andhra PradeshKeywords: Based on Search Engine, Cosine Similarity, Search Results, Ranking, Threshold Value, Information Retrieval

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