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ENHANCING FAKE NEWS DETECTION ON SOCIAL MEDIA THROUGH ADVANCED MACHINE LEARNING AND USER PROFILE ANALYSIS
Social media news consumption is growing in popularity. Users find social media appealing because it's inexpensive, easy to use, and information spreads quickly. Social media does, however, also contribute to the spread of false information. The detection of fake news has gained more attention due to the negative effects it has on society. However, since fake news is created to seem like real news, the detection performance when relying solely on news contents is typically unsatisfactory. Therefore, a thorough understanding of the connection between fake news and social media user profiles is required. In order to detect fake news, this research paper investigates the use of machine learning techniques, covering important topics like feature integration, user profiles, and dataset analysis. To generate extensive feature sets, the study integrates User Profile Features (UPF), Linguistic Inquiry and Word Count (LIWC) features, and Rhetorical Structure Theory (RST) features. Principal Component Analysis (PCA) is used to reduce dimensionality and lessen the difficulties presented by high-dimensional datasets. The study entails a comprehensive assessment of multiple machine learning models using datasets from "Politifact" and "Gossipofact," which cover a range of data processing methods. The evaluation of the XGBoost classification model is further enhanced by the analysis of Receiver Operating Characteristic (ROC) curves. The results demonstrate the effectiveness of particular combinations of features and models, with XGBoost outperforming other models on the suggested unified feature set (ALL). 2023 Little Lion Scientific. -
REVIEW OF CENSORING SCHEMES: CONCEPTS, DIFFERENT TYPES, MODEL DESCRIPTION, APPLICATIONS AND FUTURE SCOPE
Survival analysis is one of the key techniques utilized in the domains of reliability engineering, statistics, and medical domains. It focuses on the period between the initialization of an experiment and a subsequent incident. Censoring is one of the key aspects of survival analysis, and the techniques created in this domain are designed to manage various censoring schemes with ease, ensuring accurate and insightful time-to-event data analysis. The statistical efficiency of parameter estimates is improved by accurately incorporating censoring information by making use of the available data. This paper reviews the concepts, model descriptions, and applications of conventional and hybrid censoring schemes. The introduction of new censoring schemes from conventional censoring schemes has evolved by rectifying the drawbacks of the previous schemes, which are explained in detail in this study. The evolution of hybrid censoring schemes through the combination of various conventional censoring schemes, the data structures, concepts, methodology, and existing literature works of hybrid censoring schemes are reviewed in this work. 2024, Gnedenko Forum. All rights reserved. -
Improved reptile search algorithm with sequential assignment routing based false packet forwarding scheme for source location privacy protection on wireless sensor networks
Source Location Privacy (SLP) in Wireless Sensor Networks (WSNs) refers to a set of techniques and strategies used to safeguard the anonymity and confidentiality of the locations of sensor nodes (SNs) that are the source of transmitted data within the network. This protection is important in different WSN application areas like environmental monitoring, surveillance, and healthcare systems, where the revelation of the accurate location of SNs can pose security and privacy risks. Therefore, this study presents metaheuristics with sequential assignment routing based false packet forwarding scheme (MSAR-FPFS) for source location privacy protection (SLPP) on WSN. The contributions of the MSAR-FPFS method revolve around enhancing SLP protection in WSNs through the introduction of dual-routing, SAR technique with phantom nodes (PNs), and an optimization algorithm. In the presented MSAR-FPFS method, PNs are used for the rotation of dummy packets using the SAR technique, which helps to prevent the adversary from original data transmission. Next, the MSAR-FPFS technique uses an improved reptile search algorithm (IRSA) for the optimal selection of routes for real packet transmission. Moreover, the IRSA technique computes a fitness function (FF) comprising three parameters namely residual energy (RE), distance to BS (DBS), and node degree (ND). The experimental evaluation of the MSAR-FPFS system was investigated under different factors and the outputs show the promising achievement of the MSAR-FPFS system compared to other existing models. 2024-IOS Press. All rights reserved. -
Effect of functionalization on the energy storage performance of super capacitors derived from wood charcoal
The electrochemical performance of wood charcoal is investigated with respect to the disorders in the system after subjecting to oxidation and exfoliation conditions. The Cyclic voltammetry and galvanostatic charge discharge curves indicate an improvement in the electrochemical behavior, resulting in a marginal increase in the specific capacitance values at higher exfoliation temperatures. The improvement is predominantly due to the change in the structural disorder in the system accompanied by the incorporation of oxygen functional groups which act as electrochemical active species. The exfoliation of wood charcoal at 160 and 200C yield a specific capacitance of 6.23 and 12.24 F/g at a current density of 0.01 A/g. The ESR values representing the overall resistance of the system are observed to be 6.07 ? for 200C as opposed to 10.41 ? of the bare material, making the material more conducting. The drastic change in the structural morphology along with the optimal amount of oxygen functional groups can be the reason for this behavior. The acquired results offer useful information for investigating the possibilities of fabricating supercapacitors with wood charcoal by tuning the defects of the system. 2024 American Institute of Chemical Engineers. -
Exploring the effectiveness of mindfulness-based intervention among college students in India
This study investigated the effectiveness of an eight-week mindfulness-based intervention program on the trait mindfulness, psychological well-being and emotion regulation of college-going students. The experimental group participants were college-going students (N = 40) who enrolled for the intervention, and the participants in the control group (N = 40) were interested in the intervention and considered as a wait-list control group. The experimental group underwent mindfulness-based interventions, which included 1112 sessions, including brief exercises and meditations related to their trait mindfulness, emotion regulation, and psychological well-being. They received 23h of training per week for eight weeks. Repeated Measures of ANOVA together with an independent sample t-test were used to evaluate the effectiveness of this intervention programme. Further, Cohens d was used to calculate the effect size to explain the variance caused by the intervention program in trait mindfulness, emotion regulation, and psychological well-being. The results indicated that students significantly improved in their trait mindfulness, emotion regulation, and psychological well-being after receiving mindfulness training. In conclusion, the application of this eight-week mindfulness-based intervention sheds light on the common psychological issues confronted by college students in India, presenting itself as an advantageous tool for the professionals working in this field and offering positive effects on the overall well-being of college students. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Multivariate statistical optimization of phenolics and antioxidants from nutmeg seeds (Myristica fragrans Houtt)
The present study aimed to optimize the phenolic and antioxidant-rich extract from the nutmeg (Myristica fragrans Houtt) by using a two-factor 26-run central composite design-based response surface methodology tool. The selected parameters were extraction period (2 to 5days), solvent-to-water ratio (v/v) (50100%), and type of solvent (acetone or ethanol). The optimized extract at conditions of 3.14days incubation and 68% (v/v) acetone showed total phenolic content (TPC), total flavonoid content (TFC), and DPPH antioxidant assay as 376.38mg GAE/g DW, 34.40mg QUE/g DW and 842.46mg AAE/g DW, respectively. Among the nineteen (19) compounds identified by the LCMS, myristicin (37.74%) was found to be the highest. Nine (9) alkane-fatty acyl compounds were determined by the GCMS analysis, as well. Additionally, SEM and XRD revealed sheet-like anatomy with the presence of Carbon (C), Oxygen (O) and Potassium (K). The study presented a unique approach to optimizing phenolic-rich antioxidant extracts from nutmeg using response surface methodology, offering valuable insights for more efficient extraction of bioactive compounds with minimal resource waste and potentially enhancing the utilization of nutmeg's nutraceutical properties. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Role of Globalization and Innovation Pattern in Growth of Bank Credit: Evidence From Emerging and Advanced Asia
This study examines the role of globalization and innovation pattern (i.e., innovation by the residents and non-residents) in the growth of domestic bank credit across emerging and advanced Asian economies spanning from 1996 to 2022. The bank credit growth model includes economic growth and real interest rate as important control variables. This study employs Cross Sectional-Autoregressive Distributed Lag (CS-ARDL) as an appropriate baseline method because of the cointegration, endogeneity, and cross-sectional dependency present in the data. The long-run results for emerging Asian economies indicate that globalization exhibits a negative impact on banking credit, contrasting with the positive influence observed in advanced Asian economies due to heightened economic growth and increased credit demand. Residential innovation consistently bolsters banking credit in both sets of economies, albeit with mixed effects stemming from non-resident innovation. The long-run results further indicate the positive (negative) impact of economic growth (real interest rate) on bank credit in emerging and advanced Asian economies. These findings are reliable due to the similar results obtained from using Driscoll-Kraay Robust Standard Errors (DKSEs) as robust method. For policymakers in emerging economies, the imperative policy lies in striking a delicate balance between economic openness and bank credit, while counterparts in advanced economies are poised to bolster bank credit accessibility through foreign innovation while upholding stringent regulatory oversight. 2024 John Wiley & Sons Ltd. -
Rise of Populism in Northeast India: A Case of Assam
A blend of historical and contemporary forces has shaped populism in India. The Congress governments shortcomings (20042014), marked by dynastic politics and corruption, paved the way for the rise of populism, particularly under the Bharatiya Janata Party (BJP), which capitalized on anti?elite sentiment. Narendra Modis leadership, characterized by Hindu nationalism and a development agenda, has significantly altered Indias political landscape. This study focuses on the rise of populism in Northeast India, specifically in Assam, where populist movements and leaders have increasingly influenced the socio?political environment. It explores the socio?economic conditions and identity politics that have driven the growth of populist ideologies, often leading to the marginalization of ethnic minorities. By analyzing key political events, movements, and policies, the research seeks to uncover the root causes of populism in Assam and its impact on democracy, social cohesion, and regional stability. Employing a qualitative methodology that includes political speeches, media analysis, and empirical evidence, the study examines how political leaders in Assam have mobilized regional and ethnic sentiments for electoral gains, further exacerbating ethnic marginalization. The article aims to understand the catalysts and consequences of populist governance in Assam, offering insights into the broader trend of populism in Northeast India and its future trajectory. 2024 by the author(s). -
Role of corporate innovation and uncertainty in determining corporate investment of the firm: does financial constraint, executive risk preference and firm risk-taking ability play any role
Purpose: This paper aims to investigate the relationship between corporate innovation and the firms corporate investment. Further, the authors begin with the assertion that the relationship between corporate innovation and corporate investment is impacted by significantly a) uncertain periods, b) financial constraint, c) executives risk preference and d) firm risk-taking ability. Design/methodology/approach: This study has considered non-financial listed companies (774 firms) for the period spanning from 20102022. The authors use a fixed effect regression model within a panel data framework to examine the relationship between corporate innovation and investment. For robustness, the authors use system generalised methods of moments to investigate the relationship between corporate investment and corporate innovation across all the samples. Findings: This study finds a positive relationship between corporate innovation and corporate investment, which means when the firm tries to make some innovation, it will increase its expenditure on fixed assets. However, the positive relationship between corporate innovation and corporate investment reduces with uncertainty. Additionally, financial constraint plays a significant role in determining this relationship. Executives and firms with high risk-taking ability tend to be more inclined to make investments. Originality/value: The study is unique because it determines the impact of corporate innovation on corporate investment. The current literature is focused on corporate innovation and uncertainties. However, no light has been shed on the relationship between corporate innovation and investment. At the same time, the authors have introduced three more variables which play a significant role in determining the corporate innovation-investment relationship. , Emerald Publishing Limited. -
Exploring evolution, development, and contribution of International Journal of Industrial and Systems Engineering (20052022): a bibliometric study
International Journal of Industrial and Systems Engineering (IJISE) reached its 18th year of publishing in 2023. A comprehensive assessment of 1,096 publications using the bibliometric data analysis technique is performed to understand growth of the journal for the past 18 years. Different indicators like co-occurrence of all keywords, co-authorship, citation and co-citation analysis of authors, countries, and institutions is performed through VOS Viewer software. The findings of the study emphasise contribution of IJISE to knowledge domain. Copyright 2024 Inderscience Enterprises Ltd. -
WORKFORCE DIVERSITY: A SPOTLIGHT ON EMPLOYEE SUSTAINABILITY EXCELLENCE IN INDIA
This research paper explores a crucial yet often underestimated nexus: the relationship between workforce diversity and employee sustainability in the vibrant television media industry. Through an in-depth examination of diverse dimensions such as age, gender, culture, and socio-behavioral factors, it illuminates how these elements intricately influence the long-term viability of employees within this rapidly evolving sector. The paper's standout feature lies in its rigorous statistical analyses, which uncover the nuanced connections between workforce diversity and employee sustainability. By grounding its findings in empirical evidence, the paper transcends mere conjecture, offering a robust framework for comprehending and tackling this pressing issue. Moreover, the spotlight on the Indian media industry brings a unique perspective, given its extraordinary growth trajectory and substantial economic impact. Readers stand to gain invaluable insights into the dynamics of diversity within this context, potentially yielding transferable lessons and strategies for other industries and regions. In its culmination, the paper presents a synthesis of actionable recommendations and conclusive insights, serving as a practical guide for organizations seeking to harness diversity as a catalyst for long-term employee sustainability. With its blend of academic rigor and real-world relevance, this paper is indispensable reading for industry practitioners, policymakers, and scholars alike. 2024 Sciendo. All rights reserved. -
Sensitivity analysis of thermal optimisation within conical gap between the cone and the surface of disk with particle deposition
This work examines the thermal and flow characteristics of TiO2+AgBr+GO/EG trihybrid nanofluid in the conical gap that exists between a disc and a cone. Effect of thermophoresis and particle deposition are examined to perceive the mass dissipation change on the surface. The governing equations of the problem are in the form of partial differential equations which are converted to nonlinear ordinary differential equations by applying proper scaling similarity transformations, and then the resultant equations are approximated numerically by using RKF45 technique. The interesting part of this research is to discuss the impact of various pertinent parameters on three cases namely: (1) rotating cone/disk (2) rotating cone/stationary disk and (3) stationary cone/rotating disk. The flow field, heat and mass transfer rates were analysed using graphical representations. Additionally, sensitivity analysis is performed on derived rate of heat transfer as a response function for input factors for different parameters. From the graph, it is perceived that flow field increases significantly with increase in the values of Reynolds numbers for both cone and disk rotations. Also, it is seen that temperature upsurges significantly for ascendent values of solid volume fraction of nanoparticles. It is also noticed that the sensitivity of the Nusselt number towards n is more for all the values of source/sink and for middle level values of n. Akadiai KiadZrt 2024. -
Nonlinear Dynamics in Distributed Ledger Blockchain and analysis using Statistical Perspective
More and more in healthcare is blockchain technology applied for safe and open data storage. Still, it is understudied how deeply regression analysis combined with nonlinear dynamics into distributed ledger systems performs. This kind of approach may help to increase data transfer efficiency and help storage management in blockchain systems. Data speed and storage efficiency restrictions make current blockchain systems difficult to handle for large amounts of healthcare data. Conventional methods find poor data retrieval and transfer due to the great complexity and nonlinear characteristics of healthcare data. Combining nonlinear dynamics with deep regression analysis, this paper proposes a fresh approach for maximizing data transfer and storage in blockchain systems. Inspired by nonlinear dynamics ideas, a deep regression model aimed at maximizing block storage and forecast data transmission requirements was assessed on a simulated healthcare dataset using a distributed ledger system with 1,000 blocks and a 500 GB total dataset size. Performance criteria covered transmission efficiency and storage consumption. The proposed technique improved data transmission efficiency by thirty percent over current techniques. Another clear improvement was using storage; block size needs fell 25%. The best model, according to numerical research, lowered an average transmission time from 120 to 84 minutes and storage overhead from 200 to 150 GB. 2024, International Publications. All rights reserved. -
IDENTITIES AT THE DINNER TABLE: COMMENSALITY, SELF-PERCEPTION, AND RELATIONSHIPS IN ANNE CHERIANS A GOOD INDIAN WIFE
Food studies is rapidly gaining ground as a multidisciplinary area of research. Within it, literary food studies brings an interdisciplinary perspective as works of literature are viewed through the lens of food that is informed by frameworks and concepts that are rooted in a variety of fields including cultural anthropology, sociology, and more. one such concept that is in focus here is that of commensality that is associated with food and food practices. Commensality, drawing from notions of conviviality, refers to the practice of sharing a table and consuming food together. Deeper meanings of communal identities come to the fore in this social practice, leading it to shape how identities are understood and projected. Commensality can be a complex site of belonging and alienation depending on the context, and this paper seeks to explore the representation of the same in Anne Cherians A Good Indian Wife (2008). Leila, the titular Indian wife in the novel, moves to the US from India after her marriage to Neel and grapples with finding her place in the foreign land. With this displacement comes the endeavor to reaffirm her new identity, which now includes the role of being a wife and the aspect of being an immigrant. Neel also deals with complicated feelings towards the projection of his identity. With food playing a crucial role in the everyday experiences of their lives, commensality becomes a point of enquiry into how they see themselves and how their relationships with each other and themselves evolve through the course of the narrative. 2024 Nayana George. -
RCBAM-CNN: Rebuild Convolution Block Attention Module-based Convolutional Neural Network for Lung Nodule Classification
Lung cancer remains the leading cause of cancer-related deaths worldwide. Pulmonary nodules, indicative of tumor growth, present significant diagnostic challenges due to their varying sizes and shapes. Computed Tomography (CT) is commonly used for lung cancer screening due to its high sensitivity and efficacy in detecting these nodules. However, differentiating between benign and malignant nodules can be difficult due to their overlapping characteristics. To address this challenge, we propose a Rebuild Convolution Block Attention Module-based Convolutional Neural Network (RCBAM-CNN) designed to accurately classify lung nodules from CT scans. The RCBAM-CNN integrates a Rebuild Convolution Block Attention Module (RCBAM), which includes reshaped layers and redefined spatial attention mechanisms to enhance the networks focus on relevant features while minimizing noise. The performance of the proposed method is evaluated using the LIDC-IDRI dataset. Data augmentation techniques, including rotation, rescaling, and both vertical and horizontal flips, are applied to improve the models robustness and generalization. Subsequently, U-Net is employed for precise image segmentation, ensuring accurate delineation of nodule regions. The proposed RCBAM-CNN demonstrates exceptional performance, achieving an accuracy of 99.72%, surpassing existing methods such as adaptive morphology with a Gabor Filter (GF) and Capsule Network-based CNN. This approach represents a significant advancement in lung nodule classification, offering improved diagnostic accuracy and reliability. 2024 River Publishers. -
Damaged Relay Station: EEG Neurofeedback Training in Isolated Bilateral Paramedian Thalamic Infarct
Stroke is a major public health concern and leads to significant disability. Bilateral thalamic infarcts are rare and can result in severe and chronic cognitive and behavioral disturbances - apathy, personality change, executive dysfunctions, and anterograde amnesia. There is a paucity of literature on neuropsychological rehabilitation in patients with bilateral thalamic infarcts. Mr. M., a 51 years old, married male, a mechanical engineer, working as a supervisor was referred for neuropsychological assessment and rehabilitation with the diagnosis of bilateral paramedian thalamic infarct after seven months of stroke. A pre-post comprehensive neuropsychological assessment of his cognition, mood, and behavior was carried out. The patient received 40 sessions of EEG-Neurofeedback Training. The results showed significant improvement in sleep, motivation, and executive functions, however, there was no significant improvement in memory. The case represents the challenges in the memory rehabilitation of patients with bilateral thalamic lesions. 2024 Neurology India, Neurological Society of India. -
Revolutionizing Biodegradable and Sustainable Materials: Exploring the Synergy of Polylactic Acid Blends with Sea Shells
This study explores the mechanical properties of a novel composite material, blending polylactic acid (PLA) with sea shells, through a comprehensive tensile test analysis. The tensile test results offer valuable insights into the materials behavior under axial loading, shedding light on its strength, stiffness, and deformation characteristics. The results suggest that the incorporation of sea shells decrease the tensile strength of 14.55% and increase the modulus of 27.44% for 15 wt% SSP (sea shell powder) into PLA, emphasizing the reinforcing potential of the mineral-rich sea shell particles. However, a potential trade-off between decreased strength and reduced ductility is noted, highlighting the need for a delicate balance in material composition. The study underscores the importance of uniform sea shell particle distribution within the PLA matrix for consistent mechanical performance. These results offer a basis for additional PLA-sea shell blend optimization, directing future efforts to balance strength, flexibility, and other critical attributes for a range of applications, including biomedical devices and sustainable packaging. This investigation opens the door to more sustainable and mechanically strong materials in the field of additive manufacturing by demonstrating the positive synergy between nature-inspired materials and cutting-edge testing techniques. 2024 The Authors. -
We wear multiple hats: Exploratory study of role of special education teachers of public schools in India
The role of special education teachers (SETs) is multifaceted. A gap was recognised in the literature in the lack of studies on the roles and responsibilities of SETs in India and the field realities of carrying out the role. The aim was to explore to what extent the special education teachers fulfil their roles and responsibilities. The following is an exploratory study, using open-ended questions that interviewed 12 SETs from five public schools in Delhi, India. The policy documents shared that the SETs were responsible for direct instruction to special needs students, parentteacher collaboration and documentation, including IEPs for students with special needs. But in practice, there were not any clear-cut boundaries, the SETs played multiple rolesSubject teacher, taking substitution periods, para teachers, these were keeping the SETs away from their core responsibilities. The results of the study demonstrated an undervaluation of the work of SETs and lack of support from the principal and regular teachers. The results concluded with recommendations for policy proposal with regards to defining the role of all stakeholders in an inclusive education school and improvements for the teacher education program. 2024 National Association for Special Educational Needs. -
Unveiling Green Supply Chain Practices: A Bibliometric Analysis and Unfolding Emerging Trends
Supply chain management is a multi-dimensional approach. Growing eco-consciousness has forced businesses to optimize operations and incorporate green practices across all the stages of supply chain in manufacturing and service sectors. Reviewing the past research literature propels us to understand its current and future prospects. Employing a systematic analysis, this research explores the intellectual structure of green supply chain practices and their connection to performance outcomes in various industries. This study covers a systematic literature review, content analysis, and bibliometric analysis on green supply chain management using VosViewer. It utilizes a PRISMA-guided screening method for identification, screening, eligibility and inclusion of literature from the literature available since 1999. The bibliometric analysis reveals key contributors, thematic clusters, prevailing theoretical frameworks, and emerging research trends in the domain of green supply chain management. China, followed by the United States and the United Kingdom, emerged as leading contributors to research in this area, driven by rapid economic growth, heightened environmental concerns, and well-established academic and industrial infrastructures. The study identifies eight thematic clusters within green supply chain management, including the triple bottom line, circular economy, and carbon emissions. The most highly cited papers within these clusters were examined for their methodologies, tools, and key findings, highlighting the prominent theories utilized in this field. Moreover, the research discusses how advanced technologies such as AI, blockchain, and big data analytics are poised to transform supply chains by enhancing decision-making and mitigating risks, thus playing a pivotal role in the future of green supply chain management. Copyright 2024 CA Rajkiran, Shaeril Michel Almeida. -
Employee relations: a comprehensive theory based literature review and future research agenda
This study aims to conduct a systematic and integrative literature review to consolidate the extensive information on employee relations accumulated over the past century, thereby offering new insights into domain-specific phenomena. The research followed a four-phase search strategy in accordance with the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol. The keyword search utilized terms such as 'employee relations,' 'employee relation,' 'employment relation,' and 'employment relations' in the Scopus and Web of Science databases. By employing an integrative approach along with specific inclusionexclusion criteria, the researchers synthesized articles from leading journals in the field of employee relations, categorizing them based on geographical region, article types, prominent authors and their affiliations, and the most cited research articles. In the final stage, the researchers presented new insights through a conceptual framework utilizing the ADO-TCCM approach, which encompasses antecedents, outcomes, theories, context, methodology, mediators, and moderators of employee relations. This study synthesizes findings and reorganizes key themes into innovative frameworks, providing fresh perspectives on various aspects of employee relations. Ultimately, it offers valuable insights into the critical factors that strengthen long-term employee-employer relationships. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.