Volume 12 | Issue 7

 Abstract

With the rapid growth of technology, many people are currently working remotely and consume social media more often. Over the last few years, the Web has seen a massive growth in the number and kinds of web services. Web facilities such as online banking, gaming, and social networking have promptly evolved as people perform routine tasks. As a result, a large amount of information is uploaded on a daily basis to the Web. As these web services drive increased opportunities for people to interact, they equally offer new opportunities for criminals. URLs are launch pads for any web attacks such that any malicious intention user can steal the identity of the authorized person by sending the malicious URL. Malicious URLs are a keystone of Internet illegitimate activities. It is a form of cyber-attack, which has an adverse effect on people where the user is directed to fake websites and duped to reveal their sensitive and personal information which includes passwords of accounts, bank details, atm pin-card details etc. Hence protecting sensitive information from malwares or web phishing is difficult Aim of the phishers is to acquire critical information like username, password and bank account details. Cyber security persons are now looking for trustworthy and steady detection techniques for phishing websites detection. Hence protecting sensitive information from malwares or web phishing is difficult. By using Machine learning algorithms, we will be identifying phishing attacks and report their positives and negatives. The proposed approach is that which classifies URLs automatically by using Machine learning algorithm called logistic regression that uses binary classification.

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Cyber security, logistic regression, URL prediction, python programming language FAST API, feature extraction, preprocessing.

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ABSTRACT: In the automotive sector, sustaining brand loyalty and ensuring repeat business depend significantly on customer satisfaction. Hyundai Motor has seen tremendous expansion throughout the years. Company is focused on after sales service and customer satisfaction. In this study satisfaction of customer related to after sales service of Hyundai car in Gorakhpur district is identified. The data is gathered using a well-organized questionnaire. It was found that 58% of users being satisfied and 42% being unsatisfied during warranty period (free after sale service) by the Hyundai service center in Gorakhpur. 39% of paid service customers in the Gorakhpur showroom are satisfied with the company's after-sale support, while 61% of customers are not satisfied. "Delivery Time" was the main causes of consumer dissatisfaction.

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After Sales Service, Customer Satisfaction, Hyundai Car, Automobile, Warranty

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Using near-infrared (NIR) imaging to capture each person's vein patterns makes finger vein authentication incredibly secure and difficult to forge. These small near-infrared (NIR) sensors are ideal for use in many fields, including medicine, consumer electronics, and banking, thanks to the improved accuracy and efficiency brought about by modern machine learning and deep learning algorithms. The usage of this technology will be propelled by upcoming advancements in areas such as multi-modal biometrics, cloud computing, edge processing, and sensor technologies. Fingerprint vein authentication is a promising approach for future biometric systems because of its high level of accuracy, security, and user acceptability.

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Finger Vein Authentication, Vein Pattern, Image Processing, Deep Learning, Security, Privacy, Data Security

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The prevalence of rheumatoid arthritis in the adult Indian population using the revised ACR/EULAR criteria for the diagnosis of RA, has been found to be 0.75% projected to the whole population, this would give a total of about seven million patients in India. The prevalence of RA in India is quite similar to that reported from the developed countries. Rheumatoid Arthritis is known as Amavata in Ayurveda. This disease directly affects the quality of life of affected person. The word Amavata is a combination of two words, Ama and Vata. Ama is the apakwa ahar rasa produced in the body due to Mandagni (sluggish digestive fire). When all metabolic fires (Agni) become sluggish Ama is produced. It is Guru,Snigdha, Sthira, Sthula, and Pichhila.Ama is toxic and with the help of Vata it circulates in whole body and gets located in the Sandhis (joints), causing pain, stiffness and swelling over the joints. In Amavata, Agni (metabolic fire) plays an important role. A large number of formulations having nomenclature Amavatari Rasa are found spread across the Ayurvedic texts, But on comparing we found that most of them contain the ingredients of Amavatari Rasa as per Bhaishajya Ratnavali which has following ingredients, Parada (1 part), Gandhaka (2 part), Triphala (3 part), Chitrak (4 part), Guggulu (5 part), Eranda tail/Castor oil (Bhavana dravya).All these are having potential amapachak and agni deepan properties and hence can be used as best medicine for Amavata. Key words: Amavatari Rasa, Rheumatoid arthritis.

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Amavatari Rasa, Rheumatoid arthritis.

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Nourishing cream is a moisturizing cream to Nourish and Replenish your skin. It maximizes the skin's moisture level and makes it look soft, radiant, and smooth. It keeps your skin Nourished and Protected against dryness with a non-greasy and light effect so you can use for long duration. Nourishing cram gets quickly absorbed by the skin and suitable for all skin type especially for dry skin. Nourishing cream is a cosmetic preparation used for Protecting, Moisturizing, and Lubricating the skin. It is the complex mixture of chemical agents often occlusive help hold water in the skin after application, humectants attract moisture and Nourishment help to smooth the skin.The main aim of the work was to formulate and evaluate Nourishing cream of Cymbopogon citratus to analyze its Nourishing activity. Cymbopogon citratus was formulated and tested for Nourishing activity by topical application. Lemongrass is the medicinal plant which is richest source of bioactive compounds used in traditional and modern. The extracts were used in the formulation. After completion of formulations, it was evaluated for its physiochemical parameter like color, odor, PH, spreadability, consistency, solubility, washability, viscosity, the medicinal properties of Cymbopogon citratus since effective and easy which are used in formulation to form cream, ointment, and lotion.

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Nourish, Lubricating, Protecting.

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Diabetic neuropathy, a common complication of diabetes, causes significant nerve damage and a variety of symptoms like pain, numbness, and weakness. This review delves into how high blood sugar levels contribute to the condition through oxidative stress and metabolic issues. It covers the range of symptoms and the methods used to diagnose the disease, emphasizing the importance of thorough clinical assessments. Current treatments focus on controlling blood sugar and managing symptoms, but new therapies offer hope for better outcomes. Future research aims to overcome existing challenges and improve prevention, diagnosis, and treatment, ultimately enhancing the quality of life for those affected.

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Diabetic Neuropathy, hyperglycemia, oxidative stress, diabetic mellitus, reactive oxygen species

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Merger and acquisition (M&A) plays a vital role in corporate finance by enabling firms achieve varied objectives and financial strategies. The explosion of bank M&A has been a global phenomenon. In many emerging economies including India, bank M&A has often been driven by government policies to improve stability in the financial system. In this regards, our study aim is to examine the impact of pre and post M&A on the bank employees productivity of the largest merger of Four banks Viz., Punjab National Bank, Canara Bank, Union Bank of India and Indian Bank with six other banks in India (2017-2024) on 1st April 2020. The analysis was carried out as comparison of pre merger period (2017-2020) and post-merger period(2020-2024) ie., four years prior and four years after the merger period. The analysis was carried out to know the mean and standard deviation and paired t -test was applied to know significant difference in the selected variable via., Deposit per employee and advance per employee. The study concluded that merger and acquisition led to increase in the productivity of employees and there is significant difference in the means of pre and post merger period.

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Productivity; Merger and Acquisitions, deposits, Advances.

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Purpose - The present study investigates the impacts of physical and social infrastructures on inclusive growth and provides empirical evidence on infrastructure-inclusiveness nexus in the context of India. Data and aggregating method - This study uses annual time series data for the present analysis. In particular, we construct a composite inclusive growth index, a composite physical infrastructure index, and a composite social infrastructure index based on several developmental indicators to analyze the impact of infrastructure on inclusive growth for the period 1991 to 2015. An ad-hoc weighted method is employed to assign the weights of the indicators. Econometric methodology - The methodological approaches used in the present analysis mainly consist of time series estimation techniques. Bivariate and multivariate cointegration tests are used to analyze the long-run and short-run impacts of physical and social infrastructures on inclusive growth. In addition, the Granger causality test is performed to assess the direction of causality between the variables. Findings - The Results show that inclusive growth, physical infrastructure, and social infrastructures are cointegrated and both infrastructures have a positive and significant impact on inclusive growth in the long - run. On the other hand, physical and social infrastructures are found to have a significant and positive effect on inclusive growth in the short - run. Results of the Granger causality test confirm the existence of unidirectional causality from both physical and social infrastructure to inclusive growth. Unidirectional causality is also seen from inclusive growth to social infrastructure. Policy implications - From the policy suggestions, our empirical results suggest that policymakers should adopt policies aiming expansion of physical and social infrastructures to foster inclusive growth. Originality/Value - The present study provides empirical evidence on the infrastructure - inclusive growth nexus and examines the specific effect of physical and social infrastructures on inclusive growth in India. We consider the multidimensional nature of both inclusive growth and infrastructure while analyzing such nexus. Hence, this study makes a notable contribution to the spectrum of inclusive growth.

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Inclusive growth, Infrastructure, Physical infrastructure, Social infrastructure, Cointegration Granger causality.

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Various choices of non-zero integer solutions to non-homogeneous second degree polynomial equation with three unknowns given by are illustrated through different technical procedures.

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Mixed quadratic equation, Second degree equation with three unknowns , Integer solutions, Substitution technique, Factorization method.

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Abstract Purpose: This paper aims to provide a comprehensive analysis of the Indian steel industry's current state and future outlook, focusing on production capacity, financial performance, technological advancements, trade dynamics, and sustainability initiatives. Approach: The study employs a mixed-methods approach, utilizing secondary data from industry reports, academic journals, and government publications. It incorporates qualitative and quantitative analyses to evaluate trends, performance metrics, and strategic initiatives within the industry. Result: The findings indicate significant growth in production capacity and technological advancements, contributing to improved efficiency and product quality. However, the industry faces challenges related to environmental sustainability and regulatory compliance. Financial performance varies across companies and is influenced by market conditions and internal efficiencies. Trade dynamics reveal robust export growth but also highlight dependency on imports for certain raw materials. Practical Implications: The study's insights can guide policymakers, industry players, and investors in making informed decisions. Recommendations include investing in sustainable technologies, enhancing raw material security, and expanding market reach to ensure long-term competitiveness and growth. Originality: This paper provides a holistic view of the Indian steel industry's landscape, integrating diverse factors such as technological advancements, financial performance, and sustainability initiatives. It contributes to the existing literature by offering updated and comprehensive data-driven analysis and strategic recommendations. Paper Type: Research paper

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Keywords: Indian steel industry, production capacity, financial performance, technological advancements, trade dynamics, sustainability, regulatory compliance, strategic recommendations

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Confinement, Nanoparticle, Characterization, Diffraction Spectroscopy

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Throughout the course of civilization, there has been a significant shift in people's attitudes. The alteration in behavior is evident as individuals have actively contributed to the destruction of vegetative cover, initiated numerous industries, established housing units, and introduced various machines, among other developments. However, some of these innovations have negative repercussions on the environment. The emissions produced by machines and other equipment contribute to the depletion of the ozone layer, a crucial shield safeguarding humans, plants, animals, and other organisms from the harmful radiations of the sun. Nowadays there is a tremendous increase in the growth of various industries. Along with the development of industries, the heat of the sun reaching the ground also increased. This increase in the sun's radiation directly increases the heat on the all the structures. Most of the dwelling units suc h as flats, apartments, residential housing units etc. are made of concrete structures. Hence people may find difficulties of heat in their dwelling units. The needs of the people are increasing a lot resulting in providing more facilities and better living conditions. Many new concrete buildings are arising in the world day by day. Around 70% of total population is using concrete buildings in their day to day activities for fulfilling their various needs. Individuals rely on concrete structures for various purposes such as residential, commercial, and industrial use. Those residing in hot regions encounter significant challenges due to the thermal characteristics of concrete buildings. These structures absorb heat throughout the day and release it in the evening and night. Upon returning home after a day of strenuous activities, many people find it challenging to cope with the intense heat trapped in their residential units during the hot season. Therefore, a project has been initiated with the objective of addressing the theme "Mitigating Thermal Impact within Concrete Roof Structures for an Improved Indoor Environment," aiming to create a more comfortable atmosphere within these structures.

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Roof Structures, Residential, Commercial, and Industrial

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Ensuring road safety is vital for reducing accidents and enhancing public safety as global traffic increases. The Traffic Sign Classification System is essential for aiding both human drivers and autonomous vehicles in recognizing and obeying traffic signs. This technology utilizes advanced deep-learning algorithms, customized for specific road conditions and regions, to accurately detect signs in real-time by integrating weather, traffic history, and road environment data. The system identifies the most reliable deep-learning algorithm for traffic sign recognition through extensive analysis and validation, guaranteeing precision and reliability. This research not only supports individual drivers but also improves overall road safety, reduces traffic-related fatalities, and advances autonomous driving technologies. By promoting intelligent transportation systems, this project contributes to safer and more efficient road networks. the Traffic Sign Classification System marks a significant progression in road safety technology, offering effective solutions to modern traffic management challenges through state-of-the-art algorithms and data-driven insights.

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This research paper explores the multifaceted nature of women's involvement in household decision making within diverse sociocultural contexts. Drawing upon a combination of qualitative interviews, ethnographic observations, and survey data, the study examines the complex interplay of cultural norms, socioeconomic factors, and individual agency shaping women's roles in decision-making processes. Findings highlight the significance of contextual nuances in determining the extent of women's participation and influence, as well as the evolving nature of gender dynamics within households. The paper contributes to a deeper understanding of women's agency and empowerment within domestic spheres, offering insights for policymakers, practitioners, and researchers seeking to promote gender equality and social change.

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decision making, women, households, education, level of income, financial independence.

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Abstract: Love and hatred are complementary to each other. They are dependent also on the other. They become important variables. Love and hatred are abstract quality. Love is desirable but hatred is undesirable. These emotional aspects are reflected through real life to literature and vice versa. Ruskin Bond is a world-famous writer writing in Indian English with Indian spirit. His novella Susana's Seven Husbands bears the traces of love and hatred. From beginning to end love affairs of Susana is treated with her equal portion of hatred. Love with all lust and hatred with unfulfilled lust make the edible. RK Narayan's post-colonial novel The Guide is a romantic love history among Raju, Rousie and Nalini. This is a trilogy love and hatred story of the two male and one female character. Love is proved to be transitory whereas hatred is proved to be permanent in the lives of Raju, the guide, Rousie, the dancer and Nalini the research scholar. It also testifies that people were not free from superstition. Superstitious mass had love for unscientific faith both consciously and unconsciously. Khushwant Singh's Train to Pakistan is mostly popular for it's the theme of partition. But love and hatred theme make the partition theme authentic. India's heart is parted with the creation of new country Pakistan and India. Love between Hindu-Sikh and Muslim are divided and bitter enmity is created. That enmity takes the form of hatred, murder and anarchism in the border side Indian village Mano Majra. The protagonist, Juggat Singh is the representative of love and hatred when love a Muslim girl, Nooran and hates communalism and rioters aversely. The two novellas and one novel by the three Indian English writers of different times and temperatures help to heighten the two immortal elements love and hatred immensely.

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Key-words: love, hatred, post-colonial, partition, communalism

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This paper presents an integrated approach to enhance software defect prediction and sentiment analysis using advanced machine learning techniques. For software defect prediction, we employ a Support Vector Machine (SVM) model to identify potential defects in software components. The SVM model is trained on historical software metrics and defect logs, incorporating feature selection and engineering to improve prediction accuracy. Additionally, we address sentiment analysis by using an optimized Logistic Regression model. Text data is preprocessed and transformed using a Count Vectorizer, with hyperparameters fine-tuned via Grid Search to enhance model performance. This dual approach demonstrates the versatility and effectiveness of machine learning in various applications, showcasing significant improvements in both software defect prediction and sentiment analysis. The combined methodologies not only improve defect prediction in software development but also provide valuable insights into textual data analysis, illustrating the broad applicability and robustness of machine learning techniques.

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Software Defect Prediction, Support Vector Machine, SVM, Logistic Regression, Sentiment Analysis, Count Vectorizer, Grid Search, Machine Learning, Feature Engineering, Hyperparameter Tuning, Text Analysis, Software Quality Assurance, Predictive Modeling

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Td-algebras, multiplier, commutative, positive implicative.

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The rapid growth of big data analytics has transformed various sectors such as healthcare, finance, and marketing by enhancing decision-making, operational efficiency, and service personalization. However, this rapid growth also raises significant ethical issues that need to be addressed to ensure responsible usage. This paper examines three primary ethical concerns: economic disparity, market manipulation, and privacy invasion. The paper explores how big data can exacerbate economic inequality by reinforcing existing biases and providing disproportionate advantages to those with access to extensive data resources. It examines the implications for marginalized communities and the potential for data-driven policies to widen the economic gap. The analysis highlights how big data facilitates manipulative market practices, such as personalized pricing and targeted advertising, which can exploit consumer behaviour and undermine fair market competition. It investigates the ethical ramifications of these practices and their impact on consumer trust and market integrity. The paper addresses the pervasive issue of privacy invasion, discussing how extensive data collection and analysis can lead to significant breaches of personal privacy. It considers the balance between data utility and individual rights, evaluating the effectiveness of current data protection measures. By applying ethical theories such as utilitarianism, deontology, and virtue ethics, the paper provides a nuanced understanding of these challenges and underscores the need for robust ethical frameworks. The paper also reviews current regulations like GDPR and CCPA, highlighting regulatory gaps and proposing best practices, and policy recommendations to mitigate these challenges. Ultimately, this paper aims to emphasize the ethical concerns in big data practices and suggest strategies for fostering a more equitable and transparent data-driven economy.

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ethical, concerns, big data, artificial intelligence, machine learning, economic disparity, market manipulation, analytics, General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA)

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Mathematical models are used in applied mathematics in conjunction with engineering disciplines (computer science, electrical engineering) and natural sciences (physics, biology, earth science, and chemistry). Using mathematical modeling is a crucial for comprehending and resolving complex real-world issues. It entails utilizing mathematical terminology and ideas to theoretically model systems in order to study, forecast, and interpret their behavior. Mathematical modeling has many uses, ranging from managing pandemics to space exploration, which highlights its vital role in knowledge advancement and solving pressing global issues.

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Modeling, Analytics, Real-world problems, Prediction of Behavior

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This paper presents an accessible overview of pattern searching algorithms, which are vital tools in computer science for finding specific patterns within data. It break down the complexities of these algorithms into understandable concepts suitable for readers unfamiliar with advanced technical jargon. By employing straightforward language and examples, this paper aim to provide a clear understanding of how pattern searching algorithms function and their significance in various applications.

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Rabin karp,suffix trees,pattern mining,Deep learning

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