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Fake News Detection and Classify the Category
Everyone depends on numerous sources of E-news in today's world when the internet is ubiquitous. Online content abounds, especially social media feeds, many of which are unreliable and may not always be factual. For people to utilise social media platforms like Facebook, Twitter, and others, fake news is a topic that may be studied through Natural Language Processing techniques. Using ideas from natural language processing and machine learning applied to social media, our goal in this work is to conduct categorization of different news items that are available online. Our intention is to empower the user to utilise NLP (Natural Language Processing) methods to identify 'fake news,' which refers to misinformed material that may be categorised as genuine or false using software like Python. The model focuses on identifying false news sources based on several articles from a website, categorising the news as false or true, and determining its veracity using unreliable sources like scikit-learn and NLP for textual analysis of the website distributing the news. When a source is identified as a publisher of false news, which can be predicted with high vectorization and also suggested using the Python scikit-learn module to do tokenization and feature development, biased viewpoints may be identified and categorised in any subsequent articles from that source. 2022 IEEE. -
Fake News Detection using Machine Learning and Deep Learning Hybrid Algorithms
Spreading misinformation or fake news for personal, political, or financial gain has become very common these days. The influence of this misinformation on peoples opinions can be significant, i.e., the 2016 presidential election in the United States was a perfect illustration of how false news may be used to deceive people. In todays fast-paced world, automatic detection of fake news has become an importantrequirement. In this paper, multiple machine learning algorithms have been implemented to perform classification. A proposition of a hybrid architecture consisting of CNN along with LSTM has also been made. The proposed model outperforms the other traditional approaches. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Fake News Detection Using TF-IDF Weighted with Word2Vec: An Ensemble Approach
Social media platforms' utilization for news consumption is steadily growing due to their accessibility, affordability, appeal, and ability to propagate misinformation. False information, whether intentionally or unintentionally created, is being disseminated across the internet. Certain individuals spread inaccurate information on social media to gain attention, financial benefits, or political advantage. This has a detrimental impact on a substantial portion of society that is heavily influenced by technology. It is imperative for us to develop better discernment in distinguishing between fake and genuine news. In this research paper, we present an ensemble approach for detecting fake news by using TF-IDF Weighted Vector with Word2Vec. The extracted features capture specific textual characteristics, which are converted into numerical representations for training the models and balanced dataset with the Random over Sampling technique. The implementation of our proposed framework utilized the ensemble approach with majority voting which combines 2 machine learning models like Random Forest and Decision Tree. The proposed strategy was adopted empirically evaluated against contemporary techniques and basic classifiers, including Gaussian Nae Bayes, Logistic Regression, Multilayer Perceptron, and XGBoost Classifier. The effectiveness of our approach is validated through the evaluation of the accuracy, F1-Score, Precision, Recall, and Auc curve, yielding an impressive accuracy score of 94.24% on the FakeNewsNet dataset. 2023, Ismail Saritas. All rights reserved. -
Fake News Detection: An Effective Content-Based Approach Using Machine Learning Techniques
Fake news is any information fabricated to mislead readers to spread an idea for certain gains (usually political or financial). In today's world, accessing and sharing information is very fast and almost free. Internet users are growing significantly than ever before. Therefore, online platforms are perfect grounds to spread information to a broader section of society. What could circulate between a relative few can now circulate globally overnight. This advantage also marked the increase in the number of fake news attacks by its users, which is unsuitable for a healthy society. Therefore, there is a need for good algorithms to identify and take down fake information as soon as they appear. This paper aims at solving the problem by automating the process of identifying fake news using its content. Evaluation metrics like the accuracy of correct classification, precision, recall and f1-score assess the performance of the approach. The machine learning approach achieved its best performance with 96.7 percentage accuracy, 96.2 percentage precision, 97.5 percentage recall and 96.9 percentage f1 score on the ISOT dataset. 2022 IEEE. -
Falling cat inspired intelligent quadrupedal robot to assist people during risky mountain trekking /
Patent Number: 202141048690, Applicant: Dr.S.Balamurugan.A falling cat always goes from feet-up position to feet-down position, in a falling reference frame without violating the conversation of angular momentum. The first thing a cat does while falling is figuring out which way is up. This is capable using the gyro in the cats ears. Research shows that the safe landing of a falling cat is due to a phenomenon called cat riding reflex. Once a cat falls, it divides its body into two separate rotational axes that are tilted from one another. During falling the front part is released with decreased moment of inertia so that it can spin faster. At the back the moment of inertia is increased, so that a large twist in the front part is equivalent to the smaller twist in the latter. -
Families Experience with Family Therapy: A Qualitative Inquiry
Various studies have found out that the experiences of the families with family therapy in several countries have generally been positive and the number of the people who benefit from family therapy is also high. Studies reveal that though there is a heightened need for family therapy in India, there is a kind of reluctance among the people towards it. When there is good number of literature in India that reveals the general attitude of Indian population towards family therapy, there is a lack of studies that explore the lived experience of the family members who have undergone family therapy. This study was designed to examine therapy from the point of view of the families. The participants of this study were eight families from Kerala and Karnataka who had completed entire family therapy under the trained professionals in the duration of last five months. The data was collected through in-depth interviews. The study reveals the common factors that led the families to family therapy, their experience with the whole therapeutic process, the barriers that prevented them and the perceived benefits of family therapy. Ten global themes and twenty seven organizing themes have been identified on the whole in relation with the research query. The findings are described along with the practical implication, suggestions and future research agendas. Keywords: Therapeutic process, Rapport building, Working phase, Termination, Interventions, Mental well-being -
Family Caregiving in Dementia in India: Challenges and Emerging Issues
This chapter would provide an overview of the caregiving scenario in India with a focus on families as the mainstay of support and care for people with dementia. The various aspects of caregiving in dementia would be discussed in the light of the Indian sociocultural context. The impact of caregiving and challenges faced by the family and informal caregivers would be described in the light of the changing demographics and urbanization in India. The need for different kinds of caregiver education and training programmes tailored to the domiciliary and socioeconomic status of the family would be discussed. The resources available for family caregivers, like existing programmes for psychoeducation, family self-care, online and other resources for support would be described. We would discuss the challenges faced in developing culturally appropriate interventions for India that can be delivered within existing resources, such as supporting families in their role as caregivers and providing training and support for them. The chapter would discuss the emerging issues in the models of care for low- and middle-income countries like India, where the care is primarily home-based. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021. -
Family Factors Associated with Problematic Use of the Internet in Children: A Scoping Review
Background: Problematic use of the internet (PUI) is a growing concern, particularly in the young population. Family factors influence internet use among children in negative ways. This study examined the existing literature on familial or parental factors related to PUI in children. Methods: A scoping review was conducted in EBSCOhost, PubMed, ScienceDirect, JSTOR, Biomed Central, VHL Regional Portal, Cochrane Library, Emerald Insight, and Oxford Academic Journal databases. Studies reporting data on family factors associated with PUI in children, published in English in the 10 years to July 2020 were included. The following data were extracted from each paper by two independent reviewers: methodology and demographic, familial, psychiatric, and behavioral correlates of PUI in children. Results: Sixty-nine studies fulfilled the eligibility criteria. Three themes emerged: parenting, parental mental health, and intrafamilial demographic correlates of PUI in children. Parenting styles, parental mediation, and parentchild attachment were the major parenting correlates. Conclusion: Literature on significant familial and parental factors associated with PUI in children is scarce. More research is required to identify the interactions of familial and parental factors with PUI in children, to develop informed management strategies to address this issue. 2022 Indian Psychiatric Society - South Zonal Branch. -
FAMILY OF CONGRUENCES FOR (2, ?)?REGULAR BIPARTITION TRIPLES
Though congruences have their limitations, they have significant importance in the field of number theory and helps in proving many interesting results. Thus, this article has adopted the technique and properties of congruences to identify and prove a set of congruent properties for integer partition. The partition of a positive integer is a way of expressing the number as a sum of positive integers. One such partitions known as regular bipartition triple are discussed in this article. New congruences modulo even integers and modulo prime (p ? 5) powers are derived for (2, ?)?regular bipartition triples. Also infinite families of congruences modulo 2 for some (2, ?)?regular bipartition triples are derived. The theorems stated in this article are proved using the q?series notation and some of the prominent results such as Eulers pentagonal number theorem and Jacobis triple product identities. There are certain lemmas which are derived using these results that help in proving the major results of this article. 2022, RAMANUJAN SOCIETY OF MATHEMATICS AND MATHEMATICAL SCIENCES. All rights reserved. -
Farm bills in the parliament: impact of farmers protest and the democratisation of legislative process in India
This research article analyses the impact of the farmers agitation on the legislative process in India. The Indian farmers protest against the 2020 Indian Agriculture Reform Acts, dubbed as Kala Kanoon (black laws), not only voiced dissatisfaction with the contents of the farm bills but also confronted the undemocratic legislative practices. We provide descriptive evidence by discussing five major dimensions of the impact of the protest and the outcome i.e. the repeal of the laws. First, the protest movement and the resultant repeal helped discern a valuable public policy lesson to abandon top-down policy-making. Second, the protest questioned the bureaucratic approach to legislation that excluded the primary stakeholder group from policy-making. Third, it revealed the diminished role of the legislature and the concentration of power in the executive. Fourth, it exposed vulnerabilities in the parliamentary system when the ruling party holds a brute majority. Fifth, the protest emphasized the importance of state autonomy and legislative accountability to hold the executive accountable. We conclude with the summation of the major arguments from the discussion by highlighting the implications of the farmers movement for Indias future legislative processes. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Farm field security system using CNN and GSM module
Loss of crops and the destruction of livestock have been a major problem for many people in rural areas due to grass-fed animals whose food is derived from plants. According to research 32% are herbivores [1]. Reduced emissions from deforestation as well as deforestation are the main reason for wildlife moving towards urban areas. It results in wildlife infestation and human and animal conflicts. Therefore, compensating for the rapid loss of crops and the slaughter of livestock requires animal shelter and isolation in order to restrict the entry of animals into farm fields. The paper describes an effective and reliable way to identify and repel wildlife from farmland and to send real-time data to the farmer indicating animal attack on fields. An image of an animal will be obtained by convolution neural networks using intensive reading algorithms that provide a message to the farmer using the GSM module. It uses a user alert system and the animal scaring method. The test results show that the proposed algorithm has high visual accuracy. The detection level of the test set is achievable and the detection result is reliable. 2024 Author(s). -
Farm food and beverage: An attractive element of gastronomy in agritourism
The admixture of agriculture and tourism creates new fields of area like agritourism. The primary activity of agritourism is providing unique agritourism attractions to the visitors. Among the interests, farm food and beverages act as substantial components that intrigue the visitors. Food gastronomy is connected with farm food and beverage and its inception. Tourists in the agritourist destination want to explore the culinary practices there. Hence, this book chapter provides an idea of the concepts of agritourism and gastronomy, the applications of gastronomy in agritourism, the significance and dimensions of farm food and beverage in agritourism, factors influencing travelers' food choices, the benefits of gastronomy in agritourism and the value-added advantage of gastronomy in agritourism. Food is always a determinant element of the quality of service in the tourist place. 2024, IGI Global. All rights reserved. -
Farmers' Protests, Death by Suicides, and Mental Health Systems in India: Critical Questions
Ongoing farmers' protests have once again brought back the spotlight on the agrarian crisis in India. Even though upstream factors that perpetuate farmers' suffering, including the role of the state in promoting agrocapitalism, have been discussed extensively by scholars and activists across the spectrum, mental health discourses almost always frame it as a mental health problem to be addressed by increasing access to psychopharmaceuticals. Drawing on developments around farmers' protests and analysis of articles published in flagship journals of largest professional bodies of clinical psychologists and psychiatrists in India, I highlight the intimate relationship between neoliberal state and farmers' distress to which the mental health system shuts its ears and eyes obscuring and downplaying socio-structural determinants of farmers' mental health. Copyright 2021 Springer Publishing Company, LLC. -
Farming Futures: Leveraging Machine Language for Potato Leaf Disease Forecasting and Yield Optimization
Crop yield prediction is of paramount importance in modern agriculture. It serves as a linchpin for ensuring food security, efficient resource management, risk mitigation, environmental sustainability, and socioeconomic development. Accurate predictions enable us to maintain a stable food supply, optimize resource allocation, and manage the uncertainties associated with climate and market fluctuations. By fostering sustainable farming practices, crop yield prediction also plays a crucial role in reducing environmental impact and promoting rural development. Integrating artificial intelligence (AI) and machine learning (ML) in modern agricultural practices offers the potential to revolutionize the way we produce food, making it more sustainable, efficient, and resilient. This study has demonstrated the effectiveness of convolutional neural networks (CNNs) in the classification of potato leaf disease, achieving remarkable results with a test loss of 0.0757 and a test accuracy of 0.9741. 2024 Taylor & Francis Group, LLC. -
Fast and effective removal of textile dyes from the wastewater using reusable porous nano-carbons: a study on adsorptive parameters and isotherms
In the present study, recyclable porous nano-carbons (PNCs) were used to remove textile dyes (mainly methylene blue, methyl orange, and rhodamine B) from an aqueous environment. Due to their high surface area and mesoporous nature, PNCs exhibited extremely fast and efficient adsorption behavior. PNCs synthesized at an elevated temperature of 1000 C are used in batch experiments, as they showed maximum dye removal with high surface area. Batch mode was used to optimize operational parameters such as initial dye concentration, contact time, adsorbent dose and pH as a function of time. Within ~7 minutes of treatment, PNCs achieved a maximum removal efficacy of ~99 percent for methylene blue. The recyclability of PNCs was investigated, and it retained its efficiency even after seven cycles. The efficacy of PNCs in treating industrial water contaminated with methylene blue dye was assessed. Different adsorption isotherms were carried out to determine maximum amount of dye that can be adsorbed on to surface of PNCs. The maximum adsorption capacity attained using Langmuir isotherm for methylene blue was around 1216.54 mg g-1. Adsorption kinetics were applied on experimental data to identify the rate of adsorption. It was confirmed that novel onion peel-based porous PNCs were successful in removing methylene blue dye effectively with short duration in comparison with other dyes mainly rhodamine B and methyl orange. Graphical abstract: [Figure not available: see fulltext.] 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Fast Fashion Brands: Sustainable Marketing Practices and Consumer Purchase Behaviour; [Blagovne znamke hitre mode: trajnostne trne prakse in nakupovalno vedenje potronikov]
The fast fashion boom is faced with economic, environmental and social justice objections. Sustainable marketing initiatives have become a new style statement, and brands are shifting to environment-friendly manufacturing. This study explores how fashion apparel brands adopt sustainable marketing practices to promote sustainable purchase behaviour. A cross-sectional survey using a quantitative research design was followed to collect responses from fashion brand consumers. Variance-based partial least squares-structural equation modelling (PLS-SEM) was used to assess the hypothesized model. Two-step bootstrapping was conducted to explore the mediating role of brand perception in the relationship between sustainable marketing activity and brand loyalty. The study suggests that firms can support sustainable marketing practices by creating a brand image and building trust. This can influence consumers' perceptions of sustainability and promote brand loyalty. The study also emphasizes the significance of brand loyalty in developing sustainable purchase behaviour that endures over time. The study provides insights into sustainable marketing strategies and policies in indigenous markets. 2024, University of Ljubljana Press. All rights reserved. -
Fate of AI for Smart City Services in India: A Qualitative Study
With the rollout of the smart city initiative in India, this study explores potential risks and opportunities in adopting artificial intelligence (AI) for citizen services. The study deploys expert interview technique, and the data collected from various sources are analyzed using qualitative analysis. It was found that AI implementation needs a critical examination of various socio-technological factors to avoid any undesirable impacts on citizens. Fairness, accountability, transparency, and ethics (FATE) play an important role during the design and execution of AI-based systems. This study provides vital insights into AI implications to smart city managers, citizen groups, and policymakers while delivering promised smart city experience. The study has social implications in terms of ensuring that proper guidelines are developed for using AI technology for citizen services, thereby bridging the ever-critical trust gap between citizens and city administration. Copyright 2022, IGI Global. -
Fatigue surface analysis of AL A356 alloy reinforced hematite metal matrix composites
This study intends to investigate how copper chill affects the fatigue behaviour of composites made of aluminium alloy A356 and hematite. It was cast by altering the weight fraction particles of hematite (0 to 12%wt in increments of 3%wt) by sand casting method with and without copper chills at its end to get isotropic and homogenous significant characteristics under liquid metallurgical way. The test specimens were prepared in accordance with ASTM specifications. Ducom-type fatigue testing equipment (rotating bending-low cycle fatigue) is used in experiments to examine fatigue behaviour. The micrographic images were taken with a scanning electron microscope (SEM) and interpreted uniform reinforcement of hematite particles, and X-ray diffraction (XRD) patterns were used to reveal microscopic details. The existence of the hematite particles and their phases was revealed by the X-ray diffraction analysis. The results show that the composites cast with copper chills have significantly greater fatigue strength than the casting obtained without copper chills. It was also observed that at 9%wt, copper chilled composite shows improve in fatigue strength about 10.2% as compared without chilled composites. 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Fault Analysis and Clearance in FL-APC DC-AC Converter; [Analyse et imination des dauts dans le convertisseur CC-CA FL-APC]
The traditional active neutral-point-clamped (APC) dc-ac converter maintains great common-mode voltage with high-frequency (CMV-HF) reduction capability, so it has limited voltage gain. This article presents a new five-level APC (FL-APC) dc-ac converter capable of voltage step-up in a single-stage inversion. In the suggested design, a common ground not only reduces the CMV-HF but also improves dc-link voltage usage. While comparing with traditional two-stage FL-APC dc-ac converter, the proposed design has lower voltage stresses and greater uniformity. While improving overall efficiency, the suggested clamped dc-ac converter saves three power switches and a capacitor. Modeling and actual tests have proven the suggested APC inverter's overall operation, efficacy, and achievability. The proposed circuit is finally tested with fault clearance capability. 2023 IEEE. -
Fault Analysis and Compensation in a Five Level Multilevel DC-AC Converter
Existing Neutral clamped active (NCA) inverters have the property of high frequency common mode voltage, which can reduce the severity with less voltage gain. A newly designed five level (5L) NCA inverter can capable have achieved voltage step-up with a one stage inversion process. The proposed circuit common ground enhances DC link voltage usage while also mitigating common mode voltage with high frequency. The proposed topology is more compact and has less voltage stress than the conventional two stage topology. The proposed circuit contains merely seven power switches and two capacitors, whereas the conventional topology has ten switches and three capacitors, resulting in a more efficient layout. The proposed topology is developed in the simulink platform, and the simulation results are validated in a proto-type model with a power rating of 2000 W to validate its feasibility and performance with fault clearance capabilities. 2023, TUBITAK. All rights reserved.