Volume 12 | Issue 7

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Definition of the plurality of Puru?a in Samkhya Darshana.

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Aging is a biological process and experienced by mankind in all times. It refers to a sequence of changes across a life span of an individual. Sleep is a state of reduced mental and physical activity in which consciousness is altered and sensory activity is inhibited to certain extent. Reflexology is one of the emerging techniques to reduce the stress. It mainly focuses on application of pressure on the certain points at specific places like fingers, toes on foot etc. it promotes relaxation in the body. Methodology: Quantitative approach with a pre-experimental design was used by using PSQI Scale. Settings and Design: A preexperimental design was adopted to fulfill the purpose of the study. The study was conducted at a selected Old Age Home in Dehradun. Results: Data was analyzed with both descriptive and inferential statistical methods. Paired 't' Test was used to analyses the effectiveness of intervention and Independent "t" test was Used to know the effectiveness of experimental group between pre-test and post-test. After giving foot reflexology, in experimental group there was an improvement in Quality of sleep among elderly people. The pre-test mean and standard deviation values are 7.13 and 1.682 respectively. The post-test mean and standard deviation values are4.43 and 1.566 respectively; mean difference between pre-test and post-test is 2.7; Paired 't' test value of group is 9.297 and two-tailed 'p' value is less than 0.05 which is Highly significant at p<0.05. Hence, it indicates that there is improvement in sleep Quality after giving foot reflexology among elderly people. Conclusions: Based on the study findings foot reflexology among elderly provide the statistical Evidence which indicates that foot reflexology can improve the quality of sleep and reduce the sleep disturbance.

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Quality of sleep, foot reflexology, Elderly people

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This article examines the current research on self-presentation in social media or social networking sites to guide future studies. Social media and social networking sites provide numerous opportunities for deliberate self-presentation. Based on established self-presentation theories, an analysis of research on self-presentation in social media or social networking sites identified three important context and audience variables that were incorporated into a model. Firstly, three aspects of social media - anonymity, persistence, and visibility - were explored, as studies have shown the moderating effects of these aspects on the relationship between self-presentation goal and the content shared in social media. For instance, it is expected that social media users are more likely to present their authentic selves under conditions of reduced anonymity, increased persistence, and greater visibility. Conversely, the freedom associated with more anonymous, less persistent, and less visible social media may lead to idealized self-presentation. The second finding highlighted the influence of externally generated content such as likes, comments, tags, and shares on social media users' self-presentation content, influenced by how they choose to manage such content. The third theme focused on the moderating effect of context collapse on the connection between goals and self-presentation content. The composition of an impression manager's audience varies across social media platforms, impacting and often complicating the achievement of self-presentation goals amidst merging networks of people. Social media users have adopted different strategies to navigate the complexities of context collapse in their pursuit of self-presentation. Despite the valuable insights gained from this body of literature, a more comprehensive theory of self-presentation in the hypermedia age is necessary to further advance this area of research.

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Social media / Social Network Sites, Self-presentation, Anonymity, Visibility, Persistence, Moderating,

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ABSTRACT Health and economy are the key features of our life. Livestock are the important part of our economy and therefore their health perspectives are equally important. Majority of farmer community deals with their traditional procedure for healing and treatment for their livestock. Such traditional procedures include ethnoveterinary knowledge. This paper deals some commonly used ethnoveterinary medicinal plants used by the farmer community to cure animal disease in Uttarkashi District of Garhwal Himalaya. Four villages, Gawana, Jaspur, Dharali and Purali were randomly selected for study. Ethnoveterinary information was gathered through individual interviews and personal observations among the farmer community. A total of 45 species of ethnoveterinary belongs to 32 families and 40 genera were recorded in the study with the help of ethnoveterinary traditional healers. During the survey, it was noted that these ethno veterinary plants used to treat various veterinary diseases such as basic first aid for food poison, indigestion, snake bite, bone fracture, anti-bacterial, antifungal activity over cuts and wounds, insect repellent, deworming in cattle, diarrhea, reproduction and increase cattle lactation. The information provided in this study would bring new insights on the development of environment friendly, effective medicines to control veterinary diseases in the future. In addition, this study may be highly useful to protect and conserve medicinal plants as well as traditional knowledge of farmers of Uttarkashi District of Garhwal Himalaya.

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Keywords: Ethnoveterinary, Medicinal

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In many regions experiencing economic growth worldwide, ancient communities still persist, engaging in activities such as food gathering, fishing, and agriculture. Tribes and mountain residents primarily sustain themselves through food collection, hunting, and fishing, exemplified by groups like Kerala's Kadar, Bihar's Kariya, and others. Dense forest inhabitants, including tribes like Naga, Bhil, Kuki, Gond, and Shantal, rely on hunting, with men often leaving to hunt while women tend to household chores.

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Economic, Social, Demographic, Growth etc.

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RP-HPLC, Method Development, hesperidin, diosmin, Column Etc.

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????????? ?? ??? ????????? ?? ???????? ?????? ???? ???? ????????? ?? ? ????? ?? ????????? ?? ?????????????? ?? ?? ?????? ?? ????? ???? ?? ????? ??????? ?????????? ??????? ?? ?? ?????? ??? ????? ??? ????? ??? ??????? ??????? ???????, ???????, ?????????? ???????? ?? ???? ???? ??? ?? ??? ???? ??? ?? ??? ?????????? ?? ???? ??? ??????? ??????? ?????????? ?????? ???????? ?? ?????? ???????? ???? ????? ?????? ?????? ?? ????????? ???? ???? ?? ?? ???? ??? ?? ??? ????????? ?? ?????? ??? ?????? ?? ????? ???????? ?????? ?? ???????, ?????? ?? ???????? ?????? ??? ??? ?? ???????? ???????? ???? ?? ?????? ???

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???? ????????, ??? ????????, ????????? ?????? ????????, ???????????, ????????

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Obesity is a persistent, complex multifactorial, and morbid disease characterized by excess adiposity, which is excess body fat that has a negative impact on health. Obesity is a global health concern with a significant increase in occurrence over the previous limited years. Obesity has a complex etiology that involves interactions between hormones, the environment, and genetics. The foremost reason for obesity is a persistent energy disproportion between ingested and depleted calories. Excess energy intake triggers lipocytes and fat cell overgrowth, and the creation of organ fat or intra-abdominal fat in non-adipose tissues, resulting in cardiovascular and liver diseases. The complications of obesity are very extensive. There are various problems linked to obesity are hypercholesterolemia, hypertriglyceridemia, atherosclerosis, hypertension, type-2 diabetes mellitus, hyperinsulinemia, cholelithiasis or gallstone, non-alcoholic fatty liver disease, osteoarthritis, respiratory problems, obstructive sleep apnea, hypoventilation or pick-wickian syndrome, stroke, cancer, dementia, depression, gynaecologic problems, polycystic ovarian syndrome, skin problems, social-psychological problems, chronic kidney disease and urologic problems. Based on genetic involvement, obesity can be classified into 3 types that is syndromic obesity, monogenic obesity and polygenic obesity. The anti-obesity agents may be evaluated using the following techniques that are diet-induced obesity, seasonal obesity, exotic models of obesity, non-human primate models of obesity, virus-induced obesity, hypothalamic obesity, genetic obesity models, assays of anti-obesity activities, assays of obesity-regulating peptide hormones and other models of obesity and associated metabolic changes. There are various approaches for the management and treatment of obesity, that is lifestyle modifications, anti-obesity medicines, bariatric surgery and faecal microbiota transplantation. Lifestyle modification is still the backbone of managing obesity. Anti-obesity medicines are used when an individual whose body mass index is superior than 30 kilograms per meter squared, is not able to reduce weight by lifestyle modifications. Bariatric surgical procedure, also acknowledged as weight loss surgery, is used for people with a body mass index of more than 35 or 40 kilograms per meter squared, who have coexisting and are unable to reduce weight with lifestyle modifications and anti-obesity medicines. Transplantation of healthy human faecal microbiota microorganisms into obese patients may have an impact on weight loss and management by faecal microbiota transplantation method.

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obesity, adiposity, pick-wickian syndrome, body mass index, bariatric surgery and faecal microbiota transplantation.

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Couples with two careers seem to be making up a larger portion of the workforce. Because of social pressures and economic realities, working women's roles have evolved globally. As a result, professional women now face enormous pressure to pursue careers that are as robust as those of their male colleagues while continuing to be actively involved in their personal lives. The working couple is suffering from increased work pressure, which is reducing their personal time. In this day of information, the growing personal duties coupled with the benefits of modern technology--such as sophisticated cell phones and notepads--that enable seamless integration of work and personal life also lead to stress on both the personal and professional levels. Achieving work-life balance is therefore essential to a dual professional couple's ability to lead fulfilling lives. This research aims to investigate the difficult obstacles that a couple with two careers faces in juggling their personal and professional lives. This study has looked at the several work-life balance techniques influencing a dual career couple.

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Dual career, workforce, economic conditions and social demands

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This article focuses on general overview of Slavic mythological belief system with special emphasis on popular mythological characters and their relevance in Russian literature and culture. Slavic mythology as the ancient Slavs' idea of the world around them is one of the components of Russian cultural heritage. Like all ancient people, Slavic people, who lived in the forests, tried to understand how the world works and to comprehend their place in it. Till present days Russian culture is full of beliefs based on ancient Slavic belief system of pre-Christian era, especially folk mysticism. Since childhood all Russians know folk tales about such Slavic mythological characters as Baba Yaga and Koschei Bessmertny. Every person of Estern Slavic origion is aware that water is abode of water spirits i.e. rusalki and vodyanoi and before entering a forest it is better to please a forest spirit Leshy. And all Slavic people are united by glorifying the initial ancient Slavic God Rod with the words Slava Rodu! The features of Slavic mythology are reflected not only in public life and traditional beliefs, but also in literature. Mythological subjects and images occupy a significant place not only in the oral folk tradition, but also in the works of Russian writers and poets at different historical stages of the development of literature. This article is the analysis of the origin of Russian traditional beliefs with the empasis on Slavic mythological characters and their relevance in Russian literature, culture and festivals.The author uses such research methods as theoretical analysis of academic literature, linguistic and cultural analysis of Slavic mythology.

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Slavic mythology, folk mysticism, Russian folklore, Slavic beliefs, Russian literature, traditional Russian tales, Baba Yaga, Leshy, Rusalka

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The early and accurate detection of plant diseases is crucial for ensuring agricultural productivity and food security. Traditional methods of disease detection are often labor-intensive, time-consuming, and prone to human error. In recent years, machine learning (ML) has emerged as a powerful tool to enhance the precision and efficiency of plant disease detection. This paper presents a comprehensive review of the application of machine learning techniques in identifying plant diseases. We explore various ML algorithms, including convolutional neural networks (CNNs), support vector machines (SVMs), and random forests, and their roles in analyzing complex plant disease patterns from diverse data sources such as images, spectral data, and environmental factors. The integration of ML with advanced imaging technologies and the Internet of Things (IoT) enables real-time monitoring and rapid diagnosis, significantly improving response times and reducing crop losses. We discuss the challenges associated with implementing ML solutions in agricultural settings, such as data acquisition, model training, and scalability. Additionally, we highlight case studies and recent advancements that demonstrate the effectiveness of ML in disease detection across different types of crops. Our findings underscore the potential of machine learning to revolutionize plant disease management, paving the way for more resilient and sustainable agricultural practices.

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Plant disease detection, machine learning, convolutional neural networks (CNNs), support vector machines (SVMs), random forests, agricultural technology, real-time monitoring, IoT, precision agriculture, crop management.

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: A difficult threat known as "crypto-ransomware" encrypts user files and demands a ransom to be paid by the victim in order to obtain the decryption key. Cybercriminals can make a significant profit from this kind of malware, as it generates millions of dollars in income annually. Due to the inefficiency of traditional detection-based defenses like antivirus and anti-malware software in thwarting attacks, ransomware is becoming increasingly widespread. Moreover, this particular infection employs advanced encryption algorithms and targets a broader spectrum of file formats. Cybercriminals benefit from this, and no one is safe from becoming their next victim. File encryption ransomware targets both small and large enterprises as well as regular home users. In this research, we look at how ransomware spreads by analyzing the factors that put an individual or an organization at risk of falling victim to its demands. Finally, we make some recommendations based on our projections regarding the future evolution of ransomware.

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Ransomware, Cybersecurity, Antivirus, Malware, Ransomware prevention, Ransomware detection

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Recent decades have seen a transformation in the tobacco industry thanks to the electronic cigarette, or "e-cigarette," which has been viewed as an effective replacement for standard cigarettes. Because e-liquid heats as opposed to burning tobacco in e-cigarettes, several manufacturers have claimed that smoking e-cigarettes have fewer adverse respiratory effects than utilizing tobacco. Many customers have been won over by additional revolutionary characteristics including the option to customize the nicotine dosage and the variety of delicious flavours. But since there is no proof to support either position, there is still controversy concerning the safety of e-cigarette use and its ability to serve as a way to quit smoking strategy. Furthermore, the heating process itself has been found to have the potential to produce distinct, potentially hazardous breakdown products. Multiple investigations have been conducted both in vivo and in vitro for better insight of the effects.

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Electronic Cigarettes, Cessation, Tobacco, Battery-powered, Nicotine-replacement

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Half-Heusler semiconductor alloys have emerged as a compelling class of materials renowned for their extraordinary electronic, thermoelectric, and magnetic properties. This research paper provides a comprehensive analysis of Half-Heusler alloys, encompassing their crystal structure, electronic band properties, physical characteristics, synthesis methodologies, and potential applications. Computational simulations employing Wien2k software and DFT (Density Functional Theory) have been utilized extensively to elucidate these properties. These alloys, typically denoted by the chemical formula XYZ where X, Y, and Z represent different elements, exemplify the versatility of composite materials. Specifically, the CoVSn alloy, comprising cobalt (Co), vanadium (V), and tin (Sn), showcases synergistic properties that surpass those of its individual constituents. The crystal structure of Half-Heusler alloys, often cubic with XYZ ordering, contributes to their robust mechanical stability and favorable electronic band structures for various applications in solid-state electronics and thermoelectric devices. Moreover, their tunable electronic properties, dictated by the choice and arrangement of constituent elements, offer a promising avenue for designing materials with tailored functionalities. Advances in synthesis techniques, including vacuum arc melting and spark plasma sintering, have enabled precise control over alloy composition and microstructure, further enhancing their applicability in high-performance electronic and energy conversion devices. Ongoing research continues to explore novel Half-Heusler compositions and nanostructuring approaches to optimize their thermoelectric efficiency and magnetic properties, promising breakthroughs in sustainable energy and advanced electronics.

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Half-Heusler Alloy, Thermo-electric Material, Semiconductor Alloy, Composite Material.

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The Dental-X project is an integrated platform designed to streamline dental appointment management and enhance the accuracy of dental X-ray image classification. In many dental practices, using separate systems for image capture and patient management leads to inefficiencies and potential errors in data transfer. Dental-X addresses these challenges by combining image classification and appointment management functionalities into a single, user-friendly platform.The primary objective of Dental-X is to provide a comprehensive solution for dental professionals to manage their appointments, analyze X-ray images for caries detection, and perform tooth segmentation. This platform allows dentists to set their availability, manage their profiles, and view patient histories. Patients can register, book appointments, select time slots, and view past treatments and medications.Dental-X leverages machine learning models to analyze dental X-ray images, assisting dentists in detecting caries and identifying fillings, cavities, or implants. By integrating these features into one platform, Dental-X aims to improve the efficiency and accuracy of dental practices, ultimately enhancing patient care and streamlining administrative processes .Key features of Dental-X include appointment scheduling, slot availability checking, caries detection through image analysis, tooth segmentation, and comprehensive patient history management. The platform also provides statistical insights for dentists to track and analyze treatment outcomes. Dental-X is designed to be a robust, scalable, and user-friendly solution that meets the needs of modern dental practices.By integrating advanced machine learning techniques with efficient appointment management, Dental-X aims to set a new standard in dental practice management, offering both convenience and precision to dental professionals and their patients.

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Machine Learning, Administrative Efficiency, Image Analysis, Statistical Insights.

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The purpose of this research is to solve this constraint by designing a transdermal drug delivery system for quercetin that may be administered once daily. This system will provide greater patient compliance, increased bioavailability, and prolonged release compared to other methods. On the other hand, its therapeutic value is restricted due to difficulties associated with poor solubility, low bioavailability, and unpredictable pharmacokinetics when it is administered orally. For the purpose of determining drug flow and permeation parameters, skin permeation experiments are carried out. This is followed by the use of in vitro or in vivo models for the purpose of evaluating the potential for skin irritation caused by the prepared patches. The study aims to achieve several objectives: to formulate a transdermal delivery system capable of sustained release of quercetin over 24 hours. A once-daily transdermal delivery system for quercetin that has sustained release properties is one of the outcomes that is anticipated. The formulation included namely dichloromethane and methanol in a ratio of 1:1, using a method called solvent evaporation. Therefore, linseed oil and eugenol were added to the polymer solution in order to improve the penetration. Polyethylene glycol was employed as a plasticizer, and menthol was added in order to counteract the irritation caused by the polymer. Following the preparation of the films in this manner, they attached to the layer of adhesive bandage that had been acquired from the neighbourhood store.

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Storage conditions, Accelerated aging, adhesive properties, Drug content uniformity, Controlled release.

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Objective: Khashkhash (Papaver somniferum seed) is one of the important drug mentioned in Unani literature. The description of Poppy seeds is mentioned in various classical Unani books. Renowned Unani scholar Avicenna had also described poppy seeds in his famous book "The Canon of Medicine". According to Unani philosophy, Khashkhash is in the second-degree category according to its temperamental nature. Poppy seed oil is also a good source of essential fatty acids, especially linoleic acid, as compared to the other edible oilseeds. Pantothenic acid in poppy seeds was found in the greatest amount, followed by the vitamin's niacin and thiamin. Methods: Unani classical literature was searched from recent to past available in different libraries. For phytochemistry, pharmacology and preclinical studies to prove the importance computerized databases such as Medline, PubMed, Google Scholar and Science-direct were searched. All the information of plant available in Urdu, Persian, Arabic and studies published abstract were included in the study. Results: The action of Khashkhash mentioned in Unani classical literature are Mukhaddir (Anesthetic), Q?bi? (Astringent), Munawwim (Sedative), Musakkin-i-Alam (Analgesic), H?bis-i-Dam (hemostyptic), Muqaww?-i-Dim?gh (Brain tonic), Mun?ij (concoctive), Mudirr-i-Bawl (Diuretic), Mu?arrik (Stimulant), H??im (Astringent), Mubarrid (Refrigerant) etc and useful in Sahar (Insomnia), Malankh?liya (Melancholia), Nafth al-Dam (Haemoptysis), Ish?l (Purgation), Zah?r (Dysentery), Nazla (Catarrh), Su'?l(Cough), Hirqatul Math?na (Burning in bladder) etc. Papaver somniferum seed showed many pharmacological effects included Antitussive, Anti-diarrheal, Antibacterial activity, Hypoglycemic, Anticarcinogenic and Antiallodynic activity activities in different clinical and experimental studies. Conclusion: This presentation is an attempt to showcase the action, uses mentioned in Unani literature, chemical constituent and pharmacological and toxicological effects in one place. It may also be observed that the drug has many actions which may be beneficial in diseases.

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Khashkhash, Papaver somniferum seed, Unani medicine

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This compilation analyzes the application of artificial intelligence in web indexing, covering diverse sectors including crawler classifications, profound learning models, insightful frameworks, and moral contemplations. This investigation features key discoveries identifying with the viability of unique crawler sorts, the utilization of factual models for anticipating out connections, and the advancement of occasion focused looking frameworks. The audit additionally stresses the significance of clearness, pertinent data, achievability, quantifiability, and good conduct consistency in web scraping ventures. All in all, this wide ranging assessment shows the huge potential for AI to upgrade web looking and information investigation for an assortment of uses. The report incorporates both long, intricate passages and short, direct sentences to catch various points of view on this creating field.

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Crawler, CAIMANS, NLP

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Accurately predicting taxi ride durations is crucial for optimizing the efficiency of taxi dispatch systems in ride-hailing services. This research aims to develop and evaluate predictive models that estimate taxi ride durations before the start of the trip, leveraging historical ride data. Various machine learning techniques, including linear regression, K-Nearest Neighbors (KNN), Ridge regression, and Lasso regression, are explored using data from New York City taxi trips.The study aims to understand the key factors influencing ride durations and build models that can provide accurate estimates. Accurate predictions can improve dispatch decisions, reduce idle times for drivers, and decrease wait times for passengers, thus enhancing operational efficiency and service quality in the ride-hailing industry.We collect a comprehensive dataset of taxi trips, enriched with external data such as weather conditions and traffic information. The data undergoes preprocessing steps like cleaning, normalizing, and feature engineering. Key variables influencing ride durations include trip distance, pickup time, day of the week, weather conditions, and traffic patterns.The modeling approach involves developing predictive models, including a benchmark linear regression model, a KNN model, and regularized linear models such as Ridge and Lasso regression. Hyperparameter tuning optimizes model performance, and cross-validation ensures robustness. Performance is evaluated using metrics like Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R-squared. The linear regression model serves as a baseline, capturing some variability in ride durations but limited in modeling non-linear interactions. The KNN model improves performance by considering data point similarity, while Ridge and Lasso regression models enhance accuracy by incorporating regularization terms. Lasso also performs feature selection by setting some coefficients to zero.This study highlights the importance of feature engineering and real-time data integration. Future research should focus on integrating real-time data sources, such as live traffic updates and weather conditions, to improve prediction accuracy further. Advanced machine learning techniques, such as ensemble methods and deep learning, should be explored to capture more complex relationships in the data.Ethical considerations and data privacy are critical in the use of predictive models in ride-hailing services. Ensuring passenger and driver privacy, and maintaining transparency and fairness in algorithmic decision-making, are essential for responsible use of data-driven models.

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data science, Machine learning, Taxi duration prediction

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