bluuebunny/crossref_metadata_2025 huggingface dataset:
The Cost Realization on Time Frame Shift of Securities
Authors: Sagarkumar Buyya, Baswaraj Gadgay, Shubhangi D C
Published: December 2023

Investors use a variety of investing methods depending on the time scales () of their short-term and long-term investment time horizons (ITH). The nature of the market varies greatly depending on the type of investment. Hurst exponents (H) and normalised variance (NV) techniques based on empirical mode decomposition (EMD) have been used to identify key features of the market over various time horizons. For the stock price's decomposed intrinsic mode functions (IMF), the values of H and NV have been estimated. We found H1 0.5 0.04 and H1 0.75 for the IMFs with time periods ranging from a few days to 3 months and 5 months, respectively. Two time series from the IMFs have been reconstructed based on the value of H1: a) Short-term time series [XST (t)] with H1 = 0.5.b) long-term time series [XLT (t)] with H1 0.75 and a time span of 5 months. The XST (t) and XLT (t) indicators reveal that market dynamics in short-term ITH are random and connected in long-term ITH. We also discovered that the NV is very low in short-term ITH and gradually increases in long-term ITH. The results also reveal that in the long run, stock prices are connected with the company's fundamental factors. The discovery may aid investors in developing investment and trading strategies for both short-term and long-term investment goals.
A Comparative Study on Fuzzy Time Series Forecasting and Autoregressive Integrated Moving Average Models
Authors: S. Imalin, V. Anithakumari, V. M. Arul Flower Mary
Published: December 2023

To ensure the sustainable growth of coal production, it is necessary to analyse the growth, to ground the plans and management decisions on effective diagnostics and prediction of current and future situation at the coal production. This study presents a application of fuzzy time series forecasting methods, The new technique is applied to forecasting the coal production data using a fuzzy approach. For testing the methodology, statistical data on the coal production from 1980- to 2019. The Sturges rule is proposed to use as the universe of discourse. The intervals of variation of such indicators as growth rate are calculated when applying the approach to all defined fuzzy sets. The ARIMA model algorithm was applied by using the R - software to find the forecasted values. The forecasting results, obtained by the fuzzy time series method, are supposed to have more accuracy rate than time series model.
Role of Technology in Improving English Communication Skills of Rural Engineering Students in Tamil Nadu
Authors: M. Geetha, Dr. S.V. Karthiga
Published: December 2023

The world has witnessed the growing demand for learning, practicing, and using English in almost every walk of life. Globalization, technological advancements, government reforms, changing demands of business, and educational reforms have underlined and created a sense of urgency to develop and enhance English communication skills. English is not only a medium of instruction but is also considered one of the employability skills for graduates. Many vernacular background students face challenges in learning and improving English communication skills from business perspectives. The present article aims to identify the major challenges college students face from an employability perspective and analyzes how technology contributes to minimizing communication barriers and improving communication skills at the college level. This article is empirical in nature. The structured questionnaire is administered to target respondents of 180 students studying Engineering courses in the state of Tamil Nadu. The study is significant keeping the educational reforms in the form of National Education Policy 2020, technological advancements, e-learning, quality education, and sustainable education perspectives.
Formulation and evaluation of dabigatran loaded microballoons for prolonged drug release
Authors: Aryan Jain, Amit Jain
Published: December 2023

The objective of the present investigation was to formulate microballoons loaded with dabigatran in the polymeric core for achieving sustained release and hence improved bioavailability. Microballoons loaded with dabigatran in the polymer shell were prepared by simple solvent evaporation method using either ethyl cellulose alone or a blend of ethyl cellulose with HPMC/PVP-K30/Eudragit S100/Methyl cellulose in a fixed ratio. The percent yield of the microballoons ranged from 38.7 to 62.4% with highest yield obtained in F3. The particle size was measured using optical microscopy and the particles were observed to be spherical in shape. The particle size ranged from 28.50 ± 16.378 µm (F3) to 48.14 ± 16.748 µm (F1). The angle of repose ranged from 26.37° to 28.09° and the Carr’s index and Hausner’s ratio were in between 6.38 to 19.95 and 1.07 to 1.25 respectively. It was found that all the formulations exhibited buoyancy in the range of 61.42 to 71.71% over a period of 8h. This suggests that the formulations were able to float for sufficient time and would be able to control the release of dabigatran for longer duration. The in vitro drug release study depicted that the highest amount of drug was released from F3 (66.79%) while the lowest was released from F1 (50.27%) at the end of 8 hours of study.
Assessment of wound healing action of ethanolic extract of Melaleuca bracteata leaf
Authors: Piyush Gupta, Sandeep Jain
Published: December 2023

The objective of the present investigation was to evaluate the wound healing action of Melaleuca bracteata leaf extract in rats. The powdered leaves were defatted with petroleum ether and extracted with ethanol using soxhlet apparatus. The extraction yield was found to be 21.4%. The total phenolic content of ethanolic extract of M. bracteata was 74.27±0.59 GAE mg/g. The topical application of 5 % w/w of the Melaleuca bracteata extract containing ointments on the wound resulted in an enhanced and statistically significant (p < 0.05) wound healing activity in vivo using the excision model. The plant extract exhibited 80.104 ± 5.86 % contraction of wound on the 20th day whereas only 47.739 ± 5.46 % contraction of wound was found in the control animals. The occurrence of tannins in the ethanolic extract could be attributed for the effective wound healing action by the ethanolic extract.
In Vitro Evaluation of Antidiabetic Activity of Stem Extracts of Oroxylum Indicum
Authors: Mital Manvar Falgun Dhabaliya,
Published: December 2023

Background: It is estimated 180 million people in the world have diabetes mellitus.  The ethnobotanical information reports about 1000 plants that may possess antidiabetic activity. Roots, leaves, seeds, fruits and stems of Oroxylum indicum have been used as a single drug or as a component of certain compound drug preparations in the Indian Ayurvedic system of medicine.,

Aim: The current study designed In vitro evaluation of antidiabetic activity of aqueous and methanolic stem extracts of Oroxylum indicum.

Materials & Methods: About 100, 200, 300, 400, 500 μg concentrations of acarbose, aqueous, and ethanolic stem extracts of O. indicum were used for the study. The absorbance values were taken in spectrophotometer at 540 nm and 546 nm for α-amylase and α-glucosidase enzyme, respectively.

Results: Dose-dependent % inhibition of α-amylase and α-glucosidase enzymes are observed with the both extracts. However, compare with aqueous extract, methanolic extract shows more % inhibition.

Conclusion: In this study, aqueous and methanolic stem extracts of O. indicum showed the in vitro antidiabetic activity.
Fixed Point Theorems in Fuzzy 2 – Banach Space Using CLR Property and Implicit Relation
Authors: S.N. Leena Nelson S. Princiya,
Published: December 2023

The purpose of this paper is to obtain common fixed point theorems for weakly compatible mappings satisfying the Common Limit Range property  using implicit relation in Fuzzy 2 – Banach Space. This Property  plays a major role in fixed point theorems and by using this property we can obtain fixed points in Fuzzy 2-Banach Space.
Integrating AI with Green Internet of Things in Healthcare for Achieving UN’s SDGs
Authors: Alandjani Gasim
Published: December 2023

The integration of the Green Internet of Things (Green-IoT) and Artificial Intelligence (AI) in healthcare has the potential to revolutionize a wide range of industries, including healthcare wherein Green-IoT-connected medical devices and wearables can collect health data, which can be analyzed by AI algorithms to improve patient outcomes and support better decision-making by healthcare professionals. The convergence of AI and IoT in the field of smart health coupled with machine learning algorithms are enabling new and innovative solutions for healthcare delivery and management. AI algorithms and machine learning techniques can be used to analyze vast amounts of data generated by IoT devices, such as wearable devices, sensors, and smart home health devices, to provide insights into patient health and well-being. This research presents a review of patients’ healthcare services. Particularly, we ﬁrst give an overview of essential parameters of patients’ healthcare services through Green-IoT-enabled sensor technologies under the use case scenario. We then present a basic architecture for IoT-based healthcare systems considering key requirements in the light of the UN’s Sustainable Development Goals discussing their strengths and weaknesses in the context of the framework for patients’ healthcare services. Finally, we explored various security threats for AI-based architecture and their solutions with a comprehensive methodology to design robust and resilient patients healthcare services system needed in the context of the UN’s sustainable development goals.
Abused Children: Psychotherapist from behind the Screen: The Case Study of Incest in the Arab Sector in Israel
Authors: Aysin Sinal Yasmine Yehia,
Published: December 2023

We know that child sexual abuse (CSA) and incest does not occur in isolation, but often in conjunction with emotional and physical abuse, neglect, and domestic violence within the family (Tener, et al., 2021). The more types of child maltreatment experienced, the greater the negative impact on abused children mental health. The family situation greatly affects the mother's ability to respond positively toward the disclosure of CSA. A recent cluster analysis of 35 psychotherapists from behind the screen in Israel in dealing with incest in the Arab sector has been discussed in this study.  This study used a qualitative methodology based on interviews with 35 psychotherapists who work from behind the screen with sexually abused children based on the case study of incest in the Arab region. Interviews were utilized to gather qualitative information regarding the abuse in the Arab sector in Israel. These abused Arab youngsters had undergone counselling and psychological treatment before the interviews. The last themes that emerged were: characteristics of the therapist that support behind the screen therapeutic connection, narrative therapy, turning points, and counsel for therapists working with abused children in the Arab sector in Israel. The factor that affected the participants the most was confidence in the therapeutic alliance based on precise boundaries between the therapist and the abused child presented themes offered helpful therapeutic ideas and tactics that aided in speeding up the healing process.
Design and Development of RF Energy Harvesting Module for Low Power Device using Propulsion Concepts in Renewable Energy
Authors: Shobha A.S. , Dr. T. C. Manjunath
Published: December 2023

Energy harvesting is the need of the hour to operate small, portable and low power electronic devices for self-reliance. We focus our research on radio frequency energy harvesting. We have designed micro strip patch antenna to operate at 2.4GHz. We have analysed the capture of ambient radio frequency energy at various physical locations. We have successfully demonstrated the RF energy harvesting technique proposed for operating devices like LED, scientific calculator and battery charging. In this paper we have verified the RF energy harvesting technique through Hardware implementation.
Artificial Intelligences (AI) In Education
Authors: Dr. N. A. Arshiya Afrin
Published: December 2023

In this study, the researcher mainly focuses on how artificial intelligence (AI) has fused in the education system, How the learners and educators are using it in appropriate way. The main objective of this study is to understand the level of awareness and impact of AI in the education field. The statistical tools used for this study is Factorial ANOVA. In this study, the researcher highlights on various factors (knowledge level and year of experience) helps in determining level of awareness. Similarly, (implication of AI and Usage of AI) helps in determining level of impact. This study is based on both primary and secondary sources of data. Primary data is acquired through conducting interviews to the users of AI, and by circulating questionnaires to AI users. Whereas, secondary data is compiled with the help of many research journals, articles, and books. sample size of 25 is considered for measuring the replies from the selected respondents Some of the important findings of this paper by applying statistical tools can be concluded as the overall level of awareness is fairly higher and good, which shows learners has a good awareness level about AI in the education field along with that it is analyzed that the execution of AI technology in the education field will positively impact the overall effect of AI technology.
Dynamic Load Balancing for Improved Resource Allocation in Cloud Environments
Authors: Dr. Atul Nandwal, Mr. Ritesh Jain, Dr. Preeti Nandwal
Published: December 2023

Cloud computing has emerged as a revolutionary paradigm in information technology, offering scalable and on-demand access to computing resources. Efficient resource allocation is a crucial aspect in ensuring optimal performance and cost-effectiveness of cloud environments. Load balancing algorithms play a vital role in distributing workloads across available resources, preventing resource overutilization and underutilization. This research focuses on optimizing resource allocation in cloud computing through the application of advanced load balancing algorithms. The primary objective is to enhance resource utilization, minimize response time, and improve overall system performance. Traditional load balancing techniques often fall short in addressing the dynamic and heterogeneous nature of cloud environments. Therefore, this study investigates novel algorithms that leverage real-time resource monitoring, predictive analytics, and adaptive decision-making to intelligently allocate workloads. The research involves the design, implementation, and evaluation of multiple load balancing algorithms. Comparative analysis is conducted to assess the efficiency of the proposed algorithms against existing methods. Performance metrics such as response time, throughput, resource utilization, and scalability are used to gauge the effectiveness of the algorithms under various workload scenarios. this research explores the impact of load balancing strategies on energy consumption and environmental sustainability. Energy-efficient load balancing algorithms are developed to align resource allocation with energy consumption patterns, contributing to the overall green computing initiative.
Empowering the Marginalized: Technology and Quality of Life in Amritsar's Smart City Slums
Authors: Rajan Maurya Gurwinder Singh Badal,  Adarsh Sharma,
Published: December 2023

Amritsar is the largest city in Punjab, north India, quantified based on its slum population. The present paper attempts to study the accessibility of essential facilities like safe drinking water, bathing provision, drainage connectivity, fuel used for cooking and electricity availability, and evaluate the quality of life in Amritsar slums. Primary data were collected using a multi-module interview schedule between August and September 2022 to achieve these research goals. Thus, 614 households were selected for a preliminary survey based on the location of slums in the city. The analysis identified that the availability of basic amenities and quality of life of slum dwellers varies among various slums; at the same time, the provision of these amenities also depends on the type, location and magnitude of multiple slums. Further, it was concluded that public planning agencies have failed to supply the required facilities to the economically weaker sections of society. In addition to Government efforts, there is a need to strengthen the private sector's role in slum up-gradation, participatory planning for slum areas and other inclusive planning measures to ensure basic amenities and better quality of life for the slum dwellers.
Steiner Distance Related Parameters of Wheel graphs
Authors: V. Sheeba Agnes T.L. AbilaTheres ,
Published: December 2023

For a connected graph of order at least  and  the Steiner distance  among the vertices of  is the minimum size among all the connected subgraphs whose vertex sets contain  In this paper, we calculate the Steiner distance parameters such as Steiner degree distance, Steiner Gutman index, Steiner Harary index and Steiner reciprocal degree distance of a wheel graphs.
An Amalgamated Deep Learning Approach for Lung Segmentation using X-Ray Images
Authors: Annu Mishra, Pankaj Gupta, Peeyush Tewari
Published: December 2023

The X-ray images are considered to be an affordable means to diagnose the diseases especially the cardio vascular diseases. Chest X-rays are even examined by modern doctors in order to identify the disease and cure them accordingly. Due to opacified nature of the X-Ray images and different morphology of human body, the lung segmentation of human chest becomes very tedious. In this paper, we have introduced an approach to overcome this limitation and achieve the art-of-state lung segmentation despite of different anatomy and opacity. The approach involves division formula based on U-Net. The used the previously trained models MobileNetV2 and InceptionResNetV2. The result acquired shows the increase in the efficiency of segmentation by 2.5% with respect to Dice score and 2.37% with respect to IoU when compared it with the tradition U-Net.
The Future of Work: Implications of Artificial Intelligence on Hr Practices
Authors: Dr. Bijja Vishwanath, Dr. Surendar Vaddepalli
Published: December 2023

The integration of Artificial Intelligence (AI) into Human Resources (HR) procedures has heralded the dawn of a new age in the workplace. The purpose of this research study is to shed light on how AI-driven innovations are transforming recruiting, talent management, employee engagement, and the broader HR function. It examines AI's possibilities for decreasing prejudice, increasing efficiency, and optimizing HR decision-making, while also addressing the ethical quandaries and concerns that arise from this fundamental transition. The growing importance of AI and machine learning (ML) in altering HR practices cannot be emphasized. The advent of 'Big Data,' combined with the spread of the Internet of Things (IoT), has created a hospitable environment for breakthrough AI solutions. AI is increasingly being used by businesses to automate HR duties. As a result, AI has the ability to reduce the administrative burden on HR professionals by allowing them to make decisions based on solid data patterns rather than mere guesswork. This conversation digs into AI integration in HR, its benefits, implementation issues, and next steps. Adopting AI and machine learning is critical for precise decision-making and effective staff management. It is critical for HR staff to overcome their fears in order to handle these obstacles. This paper aims to provide a complete knowledge of the emerging HR landscape in the age of AI, presenting insights and ideas to steer enterprises toward a future in which human and artificial intelligence coexist together in the workplace.
Analytical Study on Role of Social Sites in Consumer Engagement in India
Authors: Preeti Singh Ashok Kumar,
Published: December 2023

The significance of social media's influence on consumer behavior and corporate strategy in India cannot be overstated, given the country's multifaceted culture, quickly expanding population, and evolving digital landscape. Fans of a specific Facebook brand page were polled using questionnaires to collect the data utilized in this study. Online consumer engagement was found to be significantly influenced by both media and post content type. It also stressed that client involvement would increase in proportion to the extent to which social media marketing was used. This research uncovered five aspects that greatly affect consumer involvement. The article also highlights the larger social consequences of social media, such as its involvement in social and political movements and its support to government projects like Digital India. In essence, the article highlights the fact that social media has become a key factor in the political, economic, and social transformation of India.
Augmentation of Digital Financial Services in the Pandemic: A Micro Level Study in Delhi
Authors: Bathula Srinivasu Ankita Gupta,
Published: December 2023

Pandemic has provided impetus to the use of digital financial services during the pandemic. At the same time, the role of digital financial services in financial management and health protection during the crisis is an important challenge. Against this backdrop, the paper analyses the impact of the pandemic on the adoption and use of digital financial services and the perception of government and private employees regarding role of digital financial services during COVID-19. The paper exhibits that majority of the respondents had an access to digital financial services before the pandemic itself. But interestingly, there has been an upward mobility in the use of digital financial services during the pandemic. An individual being a female, educated and a government employee increases the probability of increase in the use of digital financial services while age has a non-negative relationship with the increase in the use of digital financial services. However, COVID-19 has still been unable to close the digital loop since the use of digital mode for merchant payments still remains restricted among respondents, more particularly among women. The use of digital financial services led to the health protection more than the financial management during the pandemic.  Male and the general category could experience better financial management as a result of the use of digital financial services during the pandemic than females and other social classes respectively. Also, the younger individuals could better protect their health due to the use of digital financial services than elderly. Poor network connectivity, high risk, low awareness, digital illiteracy and lack of trust are significant challenges that have been identified during the pandemic.
Anonymity Maintenance Algorithm (Ama) Of Health Care Data from IoT Devices Using Edge System with Transfer Learning
Authors: A.  Anitha, Dr. K. Selvam
Published: December 2023

In order to fully leverage the potential of the Internet of Things (IoT), it is crucial to safeguard against potential threats and prioritize the security and privacy of data collected and extracted from IoT devices. However, the implementation of security and privacy technology within IoT presents a number of unique challenges. This is due to the fact that IoT solutions comprise a diverse array of security and privacy solutions that are designed to safeguard IoT data at the device, infrastructure/platform, and application layers. As a result, ensuring end-to-end privacy protection across these three layers is a significant challenge within IoT. IoT devices implemented with recent advancements utilize edge system and monitors fitness of a person privately. In our proposed concept anonymity maintenance done along with privacy preserving in query processing in accordance with health monitoring values. In this edge system transfer learning applied to transfer minimum data which is privacy preserved to equip edge system about IoT devices in spite of their location. De-duplication will be done in edge system in health values monitoring thus frequency learning will be inculcated to know the frequency of that device in specified location. In health-oriented processing of query the privileges will be granted for each category of people to access integrity of data according to their standard of authentication. While granting privileges concerned person can handle all their available personal data using their authentic login details. Best edge system will be chosen using PSO or GWO techniques thus de-duplication implemented efficiently.
An Advanced Cloud Data Streaming Framework for Optimized Container Resource Allocation, Job Scheduling, And Security Enhancement
Authors: R. Kokila, Dr. S. Radha Rammohan
Published: December 2023

In the realm of cloud data streaming, the central concerns are Container resource allocation and job scheduling. Cloud infrastructure relies on container virtualization to facilitate construction and migration processes. Previous models have employed migration techniques to manage cloud container allocation and resource scheduling, but these come at the cost of increased response time and network traffic. To address these challenges, a novel approach is introduced, the Reduced Optimal Migration model (ROM). This model selectively triggers migration processes based on recommendations, optimizing resource allocation through a Machine Learning (ML) Algorithm. Job scheduling is enhanced through a dedicated Task Scheduling Algorithm. For robust data security during migration, a security-based technique is implemented in the 'Security-based Container Scheduling Model,' which ensures data integrity and safeguards against attacks. This system operates seamlessly online and offline, utilizing Edge Computing. During offline periods, defensive containers maintain data security until the system owner restores online connectivity. This holistic framework proves highly effective in resolving complex issues associated with large-scale optimization of resource allocation, migration, and security. Empirical results confirm its efficiency and security enhancements. The proposed work introduces an advanced cloud data streaming framework that optimizes container resource allocation and job scheduling while enhancing security during migration. It proves effective in addressing the challenges inherent in large-scale cloud data streaming processes.
Cultural Practices and its impact on Educated Women: A Study on Nemuguri Village of Sivasagar
Authors: Happy Saikia
Published: December 2023

Culture is the whole complex of distinctive spiritual, material, intellectual and emotional features that characterize a society or a social group. It includes modes of life, the fundamental rights of the human being, value systems, traditions and beliefs.  In 21st century women’s are going very high, where women’s are able to rule the country, and do the military assignments etc. At the same time many educated women are not able to enjoy their rights due to some of the practices or belief systems of a society. Even the educated women in many areas are socially discriminated and suppressed with great consequences on their individual futures and that of the society. The present study provides an insight view about influence of culture and belief system of a society on women’s right of educated women. The present study adopted descriptive survey research design. The population of the study comprise all the educated women of Nemugri village. The sample consisted of 25 educated women from the Nemuguri village. The researcher used a self- developed questionnaire to gather data. The collected data were analyzed by using simple statistical technique i.e., master table. Major findings of the present study revealed that culture and traditional belief of a society has major impact on women’s right. Some of the socio -cultural practices militating against educated women and it creates women rights violation in many extents. Some of the recommendation made in the present study are women should be sensitized for ones right. There is need to create awareness among the people.
Empowering Child PTSD with Academic and Emotional Resilience
Authors: Dr. Tibi Thomas R.S, Dr. D. Radharamanan Pillai
Published: December 2023

This research paper seeks to examine the potential influence of Suggestopedia as a therapeutic   intervention on the academic achievement of students diagnosed with Post-Traumatic Stress Disorder (PTSD). Suggestopedia, a pedagogical technique crafted to augment learning through relaxation and suggestion, is posited to mitigate the adverse impact of PTSD on learning and cognitive abilities. The study will utilize a mixed-methods methodology, encompassing quantitative assessments of academic performance and qualitative interviews, to thoroughly investigate the impact of Suggestopedia on students grappling with PTSD.
QFD-Driven Rotational Moulding Optimization and Quality Control to Reduce Defects and Increase Efficiency in LLDPE Fuel Tank Production
Authors: Rachayya Arakerimath, Vilas Umbare
Published: December 2023

The present study utilized a House of Quality (HoQ) methodology to develop a fuel tank manufactured using the rotational moulding process, employing LLDPE material. In order to methodically tackle this issue, three House of Quality (HoQ) charts were created, outlining consumer demands, functional necessities, and production control parameters. The results of the study emphasize the critical significance of identifying and adapting essential customer requirements, functional prerequisites, and production control parameters throughout the design and production phases of rotational moulded fuel tanks. The inquiry findings emphasized that the major customer requirements were on the provision of a fuel tank that possesses qualities of strength, longevity, reliability, and cost-effectiveness, while also ensuring a prolonged lifespan and an aesthetically pleasing external appearance. Furthermore, it was determined that the material qualities and tank design are the most crucial functional requirements. In addition, the precise regulation of oven temperature and the automation of the moulding process have been identified as crucial control criteria in guaranteeing the quality and functionality of the fuel tanks.
A Review of Machine Translation Techniques and Proposal to Automatic Translation of Videos
Authors: Sailesh Iyer Shenbagaraj Ramachandran,
Published: December 2023

Translation of videos including propulsion technology videos has been one of the toughest jobs to do during the eLearning development process. We have tried it earlier by involving mostly manual work and found it to be tiresome. After the fast evolution of Machine learning and Natural language processing techniques, it is feasible now to do the translation involving and inculcating intelligent techniques in the process. We have reviewed the technologies and techniques and presenting it in this paper.
Magical Realism in Indian Literature
Authors: Dr. R. Hithayath Khan
Published: December 2023

Magic realism or magical realism is a genre where magical or unreal elements play a natural part in an otherwise realistic environment. Although it is most commonly used as a literary genre, magic realism also applies to film and the visual arts. An example of magic realism occurs when a character in the story continuous to be alive beyond the normal length of life and this is subtly depicted by the character being present throughout many generations. On the surface the story has no clear magical attributes and everything is conveyed in a real setting and breaks the rules of our real world. Magic realism is term used to describe the everyday reality with supernatural events. The two terms ‘magic’ and ‘realism’ have become to intertwined that strange, unearthly happenings become almost an accepted, even normal part of daily life. Magic realism considers being a postcolonial phenomenon. Magic realism is to be found only in the post colonial texts. The writers of colonized countries incorporate magic realism in their writings as a mode of resistance to western rationalism. There is no place for logic in magic realism. In countries like India, People believe in myths and ghosts as they believe in history. Magical things do not constitute the Indian culture. There is realism also. Diaspora writers’ characters make use of magic realism to escape to a world of fantasy for it provides them pleasure, relief, and an escape from the excruciating pain they experience in an alien land. The term magical realism was introduced by Franz Roh, a German art critic in 1952. When Roh coined the term the mean it to create an art category the strayed from the strict guidelines of realism, but the term did not name an artistic movement until the 1940s in Latin America and the Caribbean. Magic realism or Magical realism is a genre of 20th century English literature. This paper deals Magical Realism in Indian literature and its authors.
Customer Segmentation using Machine Learning Techniques
Authors: Aazmaan Ahmed Khan R. Amutha,
Published: December 2023

The objective of this customer segmentation endeavor is to utilize machine learning methodologies, Python programming, and the Streamlit framework in order to deliver individualized suggestions pertaining to savings plans, loans, and strategies for wealth management. Through the division of customers according to their demographic data, purchase patterns, and online navigation tendencies, this initiative empowers financial establishments to gain deeper insights into their customer demographics and customize their services to cater to specific requirements.

The project involves several stages, including data collection, data preprocessing, feature selection, model training, and evaluation. The acquired customer data is refined to resolve any inconsistencies or missing information. Important characteristics are identified, and an exploratory analysis of the data is conducted to uncover hidden patterns and relationships. We then select an appropriate machine learning algorithm, such as K-means clustering, hierarchical clustering, or Gaussian Mixture Models, to categorize the customer base into distinct clusters.

After the completion of model training and assessment, a Streamlit-based web application is constructed, offering an interactive platform for users. This application permits users to input their particulars and obtain tailored suggestions grounded in their designated segment. The suggestions encompass fitting savings schemes, loan alternatives, and wealth management approaches that harmonize with their financial objectives and risk appetite.

The deployed application facilitates a seamless user experience, providing real-time recommendations and insights. Continuous improvement of the model and application is encouraged through user feedback, allowing for refinement and better customization of recommendations over time.
Generalized -Revrse Derivations in non ideal on Prime Rings
Authors: G.Ramachandrudu K. Subbarayudu  ,   A.Sivakameshwara Kumar  ,
Published: December 2023

Let  be a prime ring,  be a non-zero ideal on , and  be a automorphisms of . Suppose that  is a generalized -reverse derivation on  associated with -reverse derivation  on  respectively  and . In this paper, we studied the following  identities in prime rings: (i) ; (ii) ; (iii) ; (iv) ; (v) ; (vi) ; (vii) ; (viii) ; (ix) ; (x) ; for all  in some suitable sub sets of .
Cancer Disease Treatment Classification Using Extended Rough based Intuitionistic Fuzzy C-means Learning Methodology
Authors: Sridevi Gadde, Dr. A. S. N. Chakravarthy, Dr. M. Murali
Published: December 2023

Because of the sensitivity of magnetic resonance to noise for the diagnosis and study of cancer, classifying magnetic resonance disease treatments is a medically complex and vitally important process. To sum up, these are the most pressing problems with the current system for describing how to treat cancer. Mathematical methods like rough sets, fuzzy sets, and rough sets are utilized to assess and cope with the ambiguity and uncertainty present in medical cancer disease treatments. Rough sets and rough sets-based techniques have both been offered in past, but depending on the parameters, each has its own special set of issues. The Extended Rough based Intuitionistic Fuzzy C-means Learning Technique (ERIFCM) with estimation of weight bias parameter for Cancer Disease Treatment Classification presented in this work is a novel method for computing the disease treatment classification. Using the non-membership and membership values in intuitionistic Rough based fuzzy sets, a generalised kind of fuzzy, rough sets and their representative components are evaluated. The approach that is proposed in this research uses existing clustering's standard features to lower the intensity and noise associated with cancer treatments without the need for spatial weight context data. In addition, the cluster centroid is initialized using the max-dist evaluation method, which is based on the weight measure, before the proposed algorithm is executed. This helps to reduce the number of iterations required for clustering. In contrast to existing segmented approaches developed for Cancer Disease Treatment and similar Disease Treatments, experimental results of the proposed approach yielded effective Disease Treatment Classification results. The main component of the proposed method is a more thorough analysis of experimental results.
Analysis of End-User Mashup Application in Web applications
Authors: Nawaf A. Almolhis, Mohammed A. Alsubhi
Published: December 2023

Mashup technologies that enable users to edit Web content are used to create end-user application development paradigms. It is not just a crucial technique that must be understood; it is also a crucial mechanism for developing effective end-user apps. It is recognised that consumers without computer programming experience can easily deploy and use mashup technology This paper describes research that aims to conduct an experiment to confirm this claim. Observable end-user application development requirements are also outlined, along with the research methodology and measuring techniques used to present the findings. The remix of a meta-application to evaluate mashup development employed two different Application Programming Interfaces (APIs), one from Flickr and the other from Google Map. The experimenters instructed the participants to create their own meta-application using any of the three mashup tools: Yahoo! Pipes, Intel Mash Maker, and Dapper. The findings disproved the notion that mashup development is simple enough for non-programmers to perform, demonstrating that creating mashup meta-applications is difficult for end users who lack programming and Information and Communication Technologies (ICT) abilities.
Real Time Voltage Stability Estimation under Contingencies by Generalized Curve Fit Method using PMU
Authors: Surya Bhushan Dubey, Pankaj Sahu Padmesh Singh, Awadhesh Kumar,
Published: December 2023

An accurate voltage stability monitoring scheme is necessary to take possible remedial action. Recent developments in Phasor Measurement Units (PMUs) technology provide the foundation for online voltage stability monitoring of a power system network.  In this paper, the generalized curve fit method using PMUs in the system has been used to access voltage stability of the system and a sensitivity based approach has been used to identify critical buses of the system. Voltage stability margin has been obtained and compared using generalized curve fit method and continuation power flow method using PMUs in the system. Variations in voltage stability margin caused by changing load patterns have also been considered while estimating voltage stability under contingencies.  Nose curves obtained using generalized curve fit and continuation power flow methods are also compared. Case studies have been performed on a standard IEEE 14-bus system and practical 246-bus Northern Regional Power Grid (NRPG) system representing power network of nine states of India, with the help of Real Time Digital Simulation (RTDS) and Power System Analysis Toolbox (PSAT) software.
A Comprehensive Study of New Fuzzy Logic Metric Based on Interval Type-2 Fuzzy Sets Using Real Application
Authors: Kaur Shivdeep
Published: December 2023

One of the crucial subjects used in operations research is decision-making processes. Multi-Criteria Decision-Making (MCDM) is one of the topics of this problem that is utilized rather often. In terms of ease and effectiveness, Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) is one of the most used MCDM techniques. To increase the applicability and simplicity of MCDM methods, Interval Type-2 Fuzzy Numbers (IT2FN), a specific type of Type-2 Fuzzy Sets (T2FS), are widely employed in combination with them. Defuzzification methods are used to find the best solution before the problem's ultimate step of resolution, however. Before the last phase of the process, switching to crisp numbers diminishes the use of the IT2FNs. A brief overview of fuzzy IT2FNs applications is given in this study. The review is based on 25 studies carried out between 2015 and 2023. Supply chains, the environment, energy sources, business, and healthcare are just a few of the application areas that were reviewed and segregated from fuzzy logic articles of various sorts that were the most pertinent and often discussed. The analysis and comparison of fuzzy logic implementations takes into account a wide range of alternatives and criteria, including the use of fuzzy logic mixed with additional techniques, such as the fuzzy Analytic Hierarchical Process (AHP), or improvements for group decision-making, fuzzy sets, hesitant fuzzy sets, intuitionistic fuzzy sets, or improvements for fuzzy logic. The merits and limitations of a variety of FLS types that have been employed for system identification are evaluated. Their effectiveness in various applications is also evaluated.
Enhancing Collaborative Governance through IT for Specialized Job Market Programs in Banten Province's Vocational High Schools
Authors: Muhamad Juwayni, Kamal Alamsyah, Iwan Satibi
Published: December 2023

INTRODUCTION: Several facts on the ground show that the implementation of Collaborative governance in the Special Job Exchange Program in Banten Province has not been effective. So, it is necessary to analyze and look for the formulation of the ideal Collaborative governance model that can optimize the implementation of the Special Job Exchange policy program in Banten Province.

OBJECTIVE: This study aims to determine the concept of collaborative governance and formulate an ideal collaborative governance model in the BKK SMK policy program in Banten Province.

METHOD: This study used a qualitative approach with descriptive analysis. To produce an effective collaborative governance model in the SMK BKK Program in Banten Province, researchers used the Soft System Methodology (SSM) method.

RESULT: Collaborative governance in the SMK Special Job Exchange Program in Banten Province has not been implemented effectively. Factors in the implementation of collaborative governance in the Vocational High School Special Job Exchange Program in Banten Province are system context, drivers, collaboration dynamics, collaboration action, collaborative outcomes and adaptation factors that have not been optimal. The ideal model to be applied in collaborative governance in the Vocational High School Special Job Exchange Program in Banten Province is a model that involves the five elements of collaboration with equal roles, as well as strengthening in the dissemination of collaboration regulations that govern the roles of each collaboration stakeholder namely government, industry, society, academia, mass media, and legislative.

CONCLUSION: The government must immediately formulate a concept for elemental participation in the BKK SMK program, and is advised to encourage and maximize the use of IT and the participation of all stakeholders involved in the BKK SMK program in Banten Province.
IoT Based Electric Vehicle Battery Management System for Enhance Battery Life
Authors: B. Urmila S. Abdul Razak Miah,
Published: December 2023

This abstract describes the concept of an IoT-based electric vehicle battery management system that can enhance the battery life of electric vehicles.By utilizing IoT technologies such as cloud computing, big data analytics, and machine learning algorithms, this system can monitor and analyze data in real-time, including charging patterns, driving habits, and battery performance. This enables the system to optimize the charging and discharging process, which in turn prolongs the battery life. In this project, we propose an Internet of Things (IoT) based BMS for EVs that integrates real-time data monitoring, analysis, and control to enhance battery life.The proposed system includes a range of sensors, such as temperature sensors, current sensors, and voltage sensors, that collect real-time data from the EV battery. This data is transmitted wirelessly to an IoT gateway, which then forwards it to a cloud-based platform for analysis and storage. The platform uses machine learning algorithms to identify patterns and anomalies in the data, and provides insights to improve battery performance and extend battery life.
Assessment of Intelligent Vehicle Damage and Cost Estimator for Insurance Companies
Authors: G. Ravindranth,Sai Leela B., G. Chandrika B. Naga Rajesh, S. Ramesh Babu,
Published: December 2023

Now a day’s many accidents are taking place, Suppose if an accident had taken place and they want to claim with the respective car insurer they need to likely go through the process of having a person inspect the car's damage at your home or a repair centre and then needing to wait for an official estimate and approval to go ahead with getting the necessary repair work done. While this traditional process can be lengthy and keep your car off the road longer than you'd like, artificial intelligence can now play a role in speeding up the process by taking over the appraiser's work. Vehicle damage detection is used to reduce claims leakage during insurance processing. Visual inception and validation are usually done. As it takes a long time because a person needs to come and inspect the damage. Here we are trying to automate the procedure. Using this automation, we can avoid time conception for the insurance claim procedure. In this we are using the VGG16 model to predict the damage of vehicle. We get the accuracy of 94.56% of VGG16.