Volume 10 | Issue 5

 Abstract

The study aimed a) to evaluate the influence of AI-based security systems on customer trust and perception of safety in fintech services, b) to analyze the impact of AI-driven security features on customer satisfaction levels in fintech-based companies, and c) to explore the correlation between AI-based security measures and customer retention rates in fintech companies. The study aimed at consumers of fintech firms and was undertaken in the Delhi NCR region with a stratified random sampling method to get respondents. The target population consists of 200 participants for the study. The study is descriptive and experimental. Primary data is gathered employing a questionnaire and secondary data is collected from journals, books, articles, reports, etc. Data collected are analyzed using statistical tools including the use of frequency tables, mean, standard deviations, correlation, and regression by use of MS Excel and SPSS. The findings underlined how AI-based security systems transform the essential elements of customer satisfaction and engagement in fintech companies. Also, it has been found that there is a moderate positive relationship between the usage of advanced safety techniques based on AI and the customers' retention percentages, which confirms the role of these remedies in creating customer satisfaction, engagement, and loyalty.

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Artificial Intelligence (AI), Customer Satisfaction, Customer Engagement, Customer Relationship Management (CRM), and FinTech Companies.

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The COVID-19 pandemic has underscored the critical importance of wearing face masks to curb the spread of the virus, especially in densely populated areas like public transportation, industrial facilities, and other crowded spaces. However, monitoring large populations to ensure compliance with mask mandates poses significant challenges for authorities. This paper introduces a Face Mask Detection System that leverages computer vision and deep learning techniques to automate the identification of individuals wearing or not wearing masks. The system utilizes a Convolutional Neural Network (CNN) architecture, built with popular frameworks such as TensorFlow, Keras, and OpenCV, to process image data and detect masks in real-time. By training the model on datasets of masked and unmasked faces, it achieves high accuracy in distinguishing between the two categories, even in dynamic environments. The system processes live video streams from webcams, efficiently detecting mask compliance in high-traffic areas like airports, shopping malls, and offices. Designed to function under diverse lighting conditions, the system is adaptable for various deployment scenarios. Its ability to provide real-time video feed analysis makes it a valuable tool for public health authorities to monitor mask-wearing behavior, reducing the need for manual surveillance. By offering a scalable, automated solution, this system significantly aids in ensuring compliance with mask regulations, thereby supporting efforts to limit virus transmission and enhance public safety during pandemics.

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Face Mask Detection, Computer Vision, Deep Learning, CNN, Real-Time Video Analysis, COVID-19 Prevention.

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This article provides an in-depth analysis of various putaway strategies implemented in SAP Extended Warehouse Management (EWM), including Manual Entry, Fixed Storage Bin, General Storage, Addition to Existing Stock, Empty Storage Bin, Bulk Storage, Pallet Storage, Near Fixed Picking Bin, and Flexible Storage. The study examines each strategy's theoretical framework, benefits, and practical applications, supported by a literature review and case studies. The findings highlight each strategy's advantages and the potential for optimizing warehouse operations, offering insights that can inspire and motivate warehouse managers and supply chain professionals. These strategies present a promising future for warehouse operations, instilling hope and optimism in the industry.

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Digitalizing supply chain, Warehousing, Putaway Strategies, Efficiency.

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Both Synge and Beckett dealt with a singular theme in their works, Synge's being the depiction of the lives of real and simple population; and Beckett's, revealing the ultimate reality of human life. But, while Beckett experimented a lot with this sole theme presenting the old wine in a new bottle each time; Synge falls prey to monotony. Beckett explored and re-explored his theme and strived to make the presentation all anew always; Synge suffered from repetition. Besides, all his works relied for the subject matter on the folklores of the same people and the language purposely made poetic which hampered variety. T. S. Eliot analyses Synge's plays and concludes, "The plays of John Millington Synge form rather a special case, because they are based upon the idiom of a rural people whose speech is naturally poetic, both in imagery and in rhythm...Synge wrote plays about characters whose originals in life talked poetic so that he could make them talk poetry and remain real people." Too much detailing, too much talk, are what destroy interest in Synge's plays. The motive of joy and realism together hampers him from being straightforward. As Synge himself overjoys the experiment he conducts and goes gaga about his innovative gesture in the Preface of The Playboy of the Western World saying, "On the stage one must have reality, and one must have joy; and that is why the intellectual modern drama has failed, and people have grown sick of the false joy of the musical comedy, that has been given them in place of the rich joy found only in what is superb and wild in reality." Actually, exaggeration of expression is the element that draws our attention away from the action and the reader feels being strangulated in the web of words.

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Samuel Beckett and J M Synge: A Comparison in Themes and Techniques

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This study focuses on the application of AI in remote patient monitoring for improvement of chronic disease management. Chronic diseases continuously pose serious problems for healthcare systems across the globe that can only be resolved by maintaining systematic monitoring and management to avoid complications and improve patient outcomes [1]. Remote patient monitoring (RPM) has become one of the main technologies for delivering proactive preventive care to patients with chronic conditions, providing real-time monitoring of vital signs and symptoms directly from the patients' home environment. AI technologies employed by RPM systems can be used to administer advanced analytics and predictive modeling and help in early detection of signs of deterioration, personalized interventions and adjusting treatment plans [1]. This report analyzes the research problem, conducts thorough literature search, and evaluates the effect of AI-enabled RPM for the management of chronic diseases in the United States, as well as its future implications for healthcare delivery transformation.AI enabled RPMs are capable of finding the best solution to the problems and cut the healthcare expenses drastically by preventing needless clinic visits, hospitalizations, or even emergency room visits. This enables healthcare providers to remotely monitor patients' health status and intervene early when warning signs of deterioration appear. The healthcare system can hence prevent costly complications and decrease the overall health burden. AI algorithms can make it possible to study whole population data and thereby find the most high-risk patient cohorts, who could be then intervened in and involved in activities dedicated to them, the result of which will be better resource allocation and better outcomes for both the patients and all the population

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Remote patient monitoring, Chronic disease management, Artificial intelligence, Predictive modeling, Healthcare innovation

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World War II left an indelible mark on India's monuments, heritage sites, and the study of history itself. This abstract explores the multifaceted impacts of the war on these aspects of Indian history. The global conflagration of World War II had far-reaching consequences on the Indian subcontinent, which was then under British colonial rule. Indian monuments, repositories of rich cultural heritage, bore witness to a range of transformations during this tumultuous period. World War II exerted a multifaceted influence on Indian monuments, heritage sites, and the study of history. It brought both destruction and restoration, prompting a reevaluation of historical narratives and the reinvigoration of cultural awareness. The legacy of this global conflict continues to shape the perception and preservation of India's rich historical and architectural heritage.

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Monuments, Sites , Heritage, Historians, world war II

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The Qur"an and the Sunnah of the Prophet Muhammad (S.A.W.) highlights on issues pertaining to the beginning of human life, moral excellence reproductive health, marriage and parenting. The Qur"an exhorts Muslims to marry, stating: "Marry those among you who are single, or the pious among your slaves......." (24:32). This verse therefore means that marriage is a desirable institution for every Muslim. Procreation of human species may be considered one of the most important aspects of marriage. From the Islamic perspective, children are a gift and blessing from Allah who should be properly maintained. Islam beliefs that the relationship between the husband, wife and the children should be based on mutual love and care, joy, happiness, co operation, peace, unity and tranquility. The husband and the wife ought to console each other in order to forfeit the adornment of life.

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Family Planning Among Muslim: A Study Of Moria Community of Sivasagar District, Assam

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The elastic and mechanical properties of Laves phase PdH2 compound have been investigated in the pressure range 0-150 GPa. The Lennard- Jones potential model has been applied to compute the second order elastic constants of PdH2. These elastic constants are found to increase monotonically in the given pressure range .The second order elastic constants are utilized to compute the pressure dependent mechanical constants such as Voigt- Reuss constants (M, C2), Young's modulus (Y), bulk modulus (B), shear modulus(G)& Possion's ratio (?). All computed parameters increase symmetrically with the increasing pressure. The results reached at, from the present investigation, have been deliberated upon, and compared with the available data from

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elastic properties, mechanical properties, palladium dihydrides.

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This study investigated the factors influencing reading literacy among Grade 4 learners in Northern Iloilo, Philippines. The study collected data from 300 learners based on sex, residence, parents' highest educational attainment, and estimated monthly income. The study found that the overall reading literacy level of the learners was "instructional." Still, learners whose parents had only completed elementary school were described as "frustration," while those whose parents were high school and college graduates were described as "instructional." The study identified learner-related, teacher-related, and school-related factors as vital contributors to reading literacy, while home-related factors were moderate contributors. The findings emphasize the need for educators to monitor reading literacy data and consider the identified factors to develop practical instructional guides to enhance learners' reading comprehension.

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learners, factors, educational attainment, instructional changes, monitoring, effective, instructional guides

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Physics, as one of the fundamental sciences, plays a pivotal role in driving technological progress, shaping society, influencing the economy, and impacting the environment. This research article aims to provide a comprehensive review of the multifaceted interactions between physics and these various aspects. By analyzing scientific literature, technological advancements, and societal changes, this paper demonstrates the indispensable link between physics and the development of modern society. The article further explores how physics-driven technologies have contributed to economic growth and sustainability, while also addressing potential environmental challenges that arise from technological progress. The findings presented here emphasize the importance of continued support for physics research and innovation to ensure a positive and sustainable future for humanity.

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Technology progress, Case studies, society, Economy, Environment

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THE IMPACT OF FISCAL POLICY ON ECONOMIC GROWTH: AN ANALYSIS

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A STUDY ON PRIVATISATION OF PUBLIC SECTOR ENTERPRISES IN INDIA - AN ECONOMIC ANALYSIS

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Slow learners, Attitude, Awareness,

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Educational Leadership, Socio-Economic Status, Effectiveness, Head, Teachers.

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IoT is an important step toward the upcoming smart era. Most devices are connected to the internet nowadays. IoT utilizes sensor data and interconnected devices to transfer information from one device to another using internet. IoT has numerous advantages, but the only disadvantage is that all the connected devices should remain on all the time to give and sense the data, which over in all consumes lots of energy. Green IoT is the concept of saving energy using various green computing techniques in IoT devices. This paper introduces GreenIoT and explains the need for Green IoT in today's era. Moreover, this paper focuses on various applications of the Green IoT. It also provides the research path in the area of GreenIoT. Finally, it discusses open challenges in Green IoT with some of the solutions and research trends in the area.

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IoT, Green IoT, Smart devices, IoT Devices, Green computing

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Population, Environment, sustainability, resource, pollution, infrastructure, management.

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Abstract This research looked at the impact of information and communication technology (ICT) on the performance of the Coca-Cola industry in Enugu as well as the role that organizational counseling might play in ensuring adequate growth in this period of global ICT revolution. A total of 260 employees from the Enugu Coca-Cola Industry participated in the survey. The study was conducted using a descriptive survey research approach. Respondents were drawn from the various units of the industry using purposeful random sampling. Pearson's moment correlation coefficient and simple linear regression statistical methods were used to evaluate three hypotheses. The study discovered that the availability of ICT infrastructure influenced Coca-Cola Industry Performance in Enugu positively, whereas inadequate ICT usage abilities and competencies of personnel influenced Coca-Cola Industry Performance in Enugu adversely. In addition, the Coca-Cola industry in Enugu's performance was significantly impacted by corporate customers' poor use of ICT. Based on the findings, this study suggests that organizations deploy appropriate ICT and use it effectively to gain a worldwide competitive edge, as effective ICT use has a significant impact on organizational performance. The study also suggested that the Coca-Cola industry in Enugu, Nigeria, form strategic alliances with other international industries in the areas of staff abilities and competencies in effective ICT use in order to gain new and practical knowledge on upgrading their technology, new programs, and new methods of production and delivery, as well as make effective use of organizational counseling and be open to embracing new emerging technological industrial innovations to increase their market share.

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Counselling, impact, industry, Information, Communication, and Technology, and Performance

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Image data captured from outdoor visual devices are usually degraded by some external factors such as fog, rainfall, snow, smoke and haze. Hence the weather condition plays a prominent role in disturbing the public transportation systems as well as some advance assistance systems which try to capture the data from outdoor cameras and then function the system.Hence in order to avoid this disruption of images from outdoor cameras, one should able to identify the weather situation and what are the possible factors that may cause due to current weather images.In primitive days there is no such automatic method which can identify the weather images and process those images and find out the possible factors related to that weather image. Hence this motivated me to develop this proposed model, in which we try to collect some weather images and apply image processing techniques and CNN model to identify the weather image and its possible outcomes in order to take preventive steps from deweathering operations (e.g., removals of haze, rain, or snow) would be correctly triggered accordingly. Here we try to collect some weather images from jehanbhathena/weather-dataset and then apply VGG-19 as best CNN model to train the application and our experimental and simulation results clearly state that our proposed system achieved nearly 96 % of accuracy compared with other primitive models and hence this proposed VGG-19 is best and accurate in order to predict the weather possibility from weather images.

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CNN Model, VGG-19 Model, Weather Images, Image Processing, Public Transportation Systems, Assistance Systems.

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Heart diseases are considered one of the most familiar causes of death worldwide. Early identification and medication can save a lot of people. There are multiple types of heart diseases that make it difficult to identify the type of disease that a patient is suffering with. Such data, whenever anticipated well ahead of time, can give significant instincts to specialists who can then adjust their conclusion and manage per patient premise. A machine must be developed such that it can identify the type of heart disease and update the machine itself by taking the experiences of the patients. (ML) can bring a compelling answer for navigation and precise forecasts. The clinical business is showing gigantic advancement in utilizing AI strategies. We work on foreseeing conceivable heart diseases in individuals utilizing Machine Learning calculations. This paper aims to build a model using multiple machine learning classifiers such as Logistic Regression (LR), Naive Bayes, Support Vector Machine (SVM), K-Nearest Neighbor (KNN) & Decision Tree. The model is able to implement hybrid classification by gaining weak and strong classifiers trained and tested on a dataset that contains multiple attributes and the efficient algorithm is considered the best. The decision tree performed best among the other algorithms with better accuracy and performance.

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Machine Learning, Logistic Regression (LR), Naive Bayes, Support Vector Machine (SVM), K-Nearest Neighbor (KNN) , Decision Tree.

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This research paper focuses on modeling a technology that will be useful in the mechanization tunneling of subsoil. Tunneling has evolved from cave creation to water management, underground transit, mineral extraction, and warfare throughout history. During the 1950s, cutting and blasting methods were replaced by the most modern and complex automated digging using tunnel boring machines. Tunnel drilling machines are significant in boring through various soil and rock types, including clays, granular soils, severely fractured or monolithic rock layers, partially saturated or saturated ground, escarpments with high loads, and sensitive metropolitan areas with little overburden [1]. Tunnel boring equipment is now common in a wider range of geotechnical situations. An overview of tunneling using tunnel boring machines and their applicability for soft ground conditions is provided in this review study.

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Tunneling, Artificial Intelligence, Laser Beams, Subsurface soil, Geological Investigation, Excavation, Civil Engineering

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 Abstract

SANTLAT KALIN BHARAT MEIN MAHILAO KI STHITI EK ADHYAYAN (AETIHASIK SANDARBH MEIN)

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SANTLAT KALIN BHARAT MEIN MAHILAO KI STHITI EK ADHYAYAN (AETIHASIK SANDARBH MEIN)

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