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Internet of things-based virtual private social networks on a text messaging strategy on mobile platforms
A virtual private social network (VPSN) allows a device to communicate securely with a network via the internet. Confidential data may be sent more securely thanks to the encrypted connection; it allows the user to operate remotely and prevents unauthorised parties from listening in. A mobile messaging platform is a text-enabled mailbox on the web. They enable companies and organisations to communicate with clients via text message. Social networking organisations may now use compute resources as a utility instead of creating and managing their computer infrastructures thanks to cloud computing (CC). An example of how a distributed sensor-actor environment might be used in a sociology-technical network is shown in this paper. The results are obtained as regular media access actively is 85.7%, security services in IoT is 85.37%, text attackers is 83.6%, loss of information is 82.8%, and blocking text messages is 91.48%. Copyright 2024 Inderscience Enterprises Ltd. -
Internet of Things: Immersive Healthcare Technologies
Internet of Things (IoT) can be defined as a system that consists of a group of things where information is exchanged with the help of the internet, sensors, and devices. The boom of IoT is mainly because of the factor that it does not require human influence and can take place independently in utilizing digital information from physical devices. The main concern is how the integration of these technologies creates unique applications for the ease of human life. This chapter discusses various technologies of IoT in healthcare and their numerous applications in medical field. It also introduces the involvement of augmented reality that is acquiring a new dimension in the Internet of Things. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Internet of things: Service-oriented architecture opportunities and challenges
Internet of Things is now a subject that is increasingly growing on both the job and modern devices. It is a concept that maybe not just get the potential to influence how we live but in addition how we work. Intelligent systems in IoT machines in many cases are used by various events; consequently, simultaneous information collection and processing are often anticipated. Such a characteristic that is exclusive of systems has imposed brand new challenges towards the designs of efficient data collection processes. This article is to be discussing various layers in Internet of things. Those layers are sensing layer, network layer, service layer and application layer. Various data processing techniques are integrated along with data filtering and data conversion. Protocol transformation is also feeling the major challenges faced by enterprises wanting to shift to the style in brand new technology. Springer Nature Singapore Pte Ltd. 2020. -
Interparental Conflict and Young Adult Romantic Relationships: A Systematic Review
In the last two decades, researchers have been progressively investigating the impact of interparental conflict (IPC) on young adults romantic relationships. This systematic review aimed to synthesize literature on IPC and romantic relationship outcomes among young adults and highlight mechanisms found in this link. Following the PRISMA protocol, 3232 studies were identified using Boolean searches on ProQuest, PubMed, EBSCOhost, Jstor, Cochrane, and Google Scholar, and 17 met the eligibility criteria. To be included, in addition to having IPC and romantic relationship outcomes as variables, studies had to be quantitative in design, have a mean sample age of 1825, include only participants in romantic relationships at the time of the study, and be published in English with full text available. The review found that IPC is associated with negative conflict management, both perpetration and victimization of aggression, worse communication, negative conflict behaviors, and poor relationship quality. Other outcomes like relationship satisfaction, commitment, as well as mediator variables in the link between IPC and young adult romantic relationship outcomes, such as attitudes towards marriage and conflict attributions, yielded varied results. Several shortcomings in the methodology of the reviewed articles, such as the research sample and measures, were discovered. To deal with the impact of IPC on offsprings romantic relationships, preventive interventions should be designed and evaluated, and more research with different variables and study designs, with more men, other ethnicities, and more representative sample frames are needed to detect crucial mediators and obtain reliable and generalizable results. The Author(s) 2022. -
Interpenetrated Robust Metal-Organic Framework with Urea-Functionality-Decked Pores for Selective and Ultrasensitive Detection of Antibiotics and Oxo-anions
Conjoining the benefits of structural diversity and deliberate implantation of task-specific sites inside the porous channels, metal-organic frameworks (MOFs) not only ensure environmental remediation via acute detection of organic as well as inorganic pollutants but also rationalize structure-performance synergies to devise smarter materials with advanced performances. Herein, we report a urea-functionality-grafted Co(II)-framework (UMOF) based on a mixed ligand approach. The 3-fold interpenetrated and [Co2(COO)4N4] building unit-containing structure exhibits high stability and free-carboxamide-site-decorated microporous channels. Assimilation of high-density hydrogen-bond donor groups plus the ?-electron-rich aromatic ligand benefits the UMOF acting as a selective fluoro-sensor for three noxious antibiotics through remarkable quenching, including nitrofurazone (NFT, Ksv: 3.2 104 M-1), nitrofurantoin (NFZ, Ksv: 3.0 104 M-1), and sulfamethazine (SMZ, Ksv: 3.3 104 M-1) with ppb level limits of detection (LODs, NFT: 110.42, NFZ: 97.89, and SMZ: 78.77). The mechanistic insight of luminescence quenching is supported from density functional theory calculations, which endorse the electron-transfer route via portraying variation in the energy levels of the urea group-affixed linker by individual organo-toxins, besides verifying analyte-linker noncovalent interactions. The framework further demonstrates highly discriminative turn-off detection of oxo-anions with extreme low LODs (Cr2O72-: 73.35; CrO42-: 189; and MnO4-: 49.96 ppb). Of note is the reusability of the UMOF toward multicyclic sensing of all the organic and inorganic analytes besides their fast-responsive detection, where variable magnitudes of energy-transfer contributions unequivocally authenticate the turn-off event. 2023 American Chemical Society. -
Interplay between personality and attitude towards emotions with creative self concept among young adults
Creative self-concept, intimately intertwined with the personality traits and plays a pivotal role in shaping individuals behavioral tendencies. Personality traits are largely responsible to influence how people perceive and navigate their creative abilities and self-expression. Moreover, attitudes towards emotions are another key facet of ones psychological landscape, impacting their inclination to perceive, process, and manage emotional experiences. Keeping this view, the present research attempts to explore the interconnectedness of creative self-concept, personality traits, and attitudes towards emotions among young adults, as well as focuses on exploring the predictors of creative self concept. For this purpose participants consisted of 200 young adults with a mean age of 21.20 years. Statistical outcomes revealed that creative self concept is a significant positive correlate of openness, conscientiousness, extraversion, agreeableness, attitude towards sadness, and attitude towards fear. Additionally, stepwise multiple regression analysis confirmed that openness (R2 = 27%), neuroticism (R2 = 2%) and attitude towards sadness (R2 = 2%) emerged as the significant predictors of creative self concept. Findings from the current research concludes that for young adults to have self-perception in the realm of creativity, personality traits and attitude towards emotions are significant contributing factors. By recognizing and employing these connections, individuals, educators, counselors, and practitioners can contribute to the cultivation of creativity and personal development. The Author(s) 2024. -
Interplay of financial inclusion and economic growth in emerging economies
This study delves into the complex link between financial inclusionboth traditional and digitaland economic growth across emerging economies from 1990 to 2022, using Dynamic Simulated ARDL and Driscoll-Kraay Standard Error techniques. Key findings highlight that traditional financial inclusion correlates positively with economic growth, whereas digital financial inclusion presents obstacles. Additionally, fiscal, monetary, and trade policies play vital roles: fiscal policies in Brazil, Colombia, and Mexico focus on infrastructure, social programs, and tax reforms, respectively, to spur growth. Monetary policies include Brazil's inflation targeting, Turkey's interest rate adjustments, and India's MUDRA scheme, which promotes entrepreneurship. Trade policies, such as Chile's Free Trade Agreements and Mexico's participation in NAFTA, improve market access and economic resilience, while Egypt and Saudi Arabia focus on foreign direct investment and economic diversification. The study emphasizes coordinated policy efforts for sustained growth, advocating for financial inclusion supported by robust regulations and government investments in critical areas like infrastructure and healthcare. Central banks contribute by maintaining price stability and credit access, while strategic trade agreements and export diversification enhance economic resilience. The focus of the study on emerging economies and macro-level insights calls for further research at the micro-level to refine these results. By maintaining policy coherence and regular evaluations, these strategies aim to foster inclusive, long-term economic growth. 2025 The Author(s) -
Interplay of financial inclusion and economic growth in emerging economies
This study delves into the complex link between financial inclusionboth traditional and digitaland economic growth across emerging economies from 1990 to 2022, using Dynamic Simulated ARDL and Driscoll-Kraay Standard Error techniques. Key findings highlight that traditional financial inclusion correlates positively with economic growth, whereas digital financial inclusion presents obstacles. Additionally, fiscal, monetary, and trade policies play vital roles: fiscal policies in Brazil, Colombia, and Mexico focus on infrastructure, social programs, and tax reforms, respectively, to spur growth. Monetary policies include Brazil's inflation targeting, Turkey's interest rate adjustments, and India's MUDRA scheme, which promotes entrepreneurship. Trade policies, such as Chile's Free Trade Agreements and Mexico's participation in NAFTA, improve market access and economic resilience, while Egypt and Saudi Arabia focus on foreign direct investment and economic diversification. The study emphasizes coordinated policy efforts for sustained growth, advocating for financial inclusion supported by robust regulations and government investments in critical areas like infrastructure and healthcare. Central banks contribute by maintaining price stability and credit access, while strategic trade agreements and export diversification enhance economic resilience. The focus of the study on emerging economies and macro-level insights calls for further research at the micro-level to refine these results. By maintaining policy coherence and regular evaluations, these strategies aim to foster inclusive, long-term economic growth. 2025 The Author(s) -
Interpretable Breast Cancer Risk Stratification Using Statistical Feature Engineering on Thermal Images
This research solves the black box problem of AI implementation in imaging by introducing a transparent, statistically grounded approach to breast cancer risk stratification via infrared thermography without compromising performance. Using the public DMR-IR dataset, statistical feature engineering was applied to training data by extracting first- and second-order statistical features. After ensuring non-normality with a Shapiro-Wilk test, feature significance was established with the Mann-Whitney U test. LASSO regularization selected the five most predictive features: mean, standard deviation, kurtosis, correlation, and energy. To counteract class imbalance, SMOTE was applied, and two machine learning modelslogistic regression and random forest (classifier)were trained on the balanced data and then evaluated on an unseen test dataset. Reporting an AUC of 0.98 over logistic regressions 0.96 reflects stringent statistical feature engineering and great generalization, creating a strong and interpretable model for breast cancer diagnosis in thermal images, and instills more clinical confidence in AI-based diagnostic systems. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Interpretable Deep Learning for Multiclass Psychological Disorder Classification Using CNN and TCAV Using fMRI
In this paper a 3D convolutional neural network model is presented that has been improved with squeeze-and-excitation blocks and residual blocks to categorize functional MRI data across healthy controls, schizophrenia, and attention deficit hyperactivity disorder classes. A post hoc explainability framework was applied to concept activation vectors based on mean activation for each class and testing using TCAV. The merging of CAV and TCAV for fMRI data was to improve transparency by providing an interpretable model. This helps in understanding the prediction sensitivity of the models. Concept vectors are defined through the extraction and analysis of intermediate activations from the CNN-SE model. These vectors are then used to calculate the TCAV scores, which indicate the degree to which each brain region influences the model output. The precision of the deep learning model was up to 79%. Similarity matrices indicate the degree of overlap and correlate with the model's results. Visualizations such as activation heat maps and glass brain overlays based on the AAL atlas further support the interpretability of the model, making it more transparent and suitable for clinical applications. Variations in activation between classes can be observed using a visual feature plot. This framework allows mapping model predictions to interpretable neuroanatomical regions and identifies classspecific dependencies on particular brain networks. 2025 IEEE. -
Interpreting Scope of Predictive Analytics in Advanced Driving Assistant System
Distracted driving, caused by various factors such as human emotions or reading distracting messages on the roadside, has become a leading cause of traffic accidents today. Ensuring the safety of both individuals and vehicles while minimizing maintenance costs poses a significant challenge for the automotive industry. Fortunately, recent advancements in machine learning offer a potential solution. One promising method is the further development of Advanced Driver Assistance Systems (ADAS), for which machine learning serves as an ideal solution. The proposed model develops an advanced predictive learning enabled driving assistance system with prediction capabilities like traffic light behavior and parking availability detection. The model gave an optimum accuracy of 98.2% with 50 epochs count and the validation loss retains a constant value of 0.3 over epochs. 2023 IEEE. -
Interpreting the Evidence on Life Cycle to Improve Educational Outcomes of Students Based on Generalized ARC-GRU Approach
Research on the effects of teachers' fatigue on students' learning has been significantly less common than research on the effects of teachers' fatigue on teachers' own performance. Therefore, the purpose of this research is to see if teachers' emotional weariness has any bearing on their students' performance in the classroom. Consideration is given to a student's grades and their impressions of whether or not the system receive assistance from teachers, as well as to the student's general outlook on school, confidence in their own abilities, and faith in the availability of faculty support. Data preparation, feature extraction, and model training are the first steps in the proposed approach. Indicators of the quality of the education being provided are eliminated (by outlier removal and feature scaling). k-mean clustering approach is a technique of clustering which is commonly used in feature extraction. Following feature extraction, GARCH-GRU models are trained. The proposed approach is superior to two popular alternatives, ARCH and GRU. Using the provided method, the system were able to achieve a maximum accuracy of 97.07%. 2024 IEEE. -
Interrogating Populist Tendencies within the Left Rhetoric in Kerala
After the disintegration of the Soviet Union, there has been an increasing shift from class-based politics to politics based on mobilising "people" within the left-wing political praxis and rhetoric. Such tendencies are visible even within the left rhetoric in Kerala. In the particular context of Kerala, this process is enmeshed with sub-nationalist sentiments and concerns around vikasanam (development). It is possible that this tendency can metamorphose into different directions, depending on the tactical priorities of the left in Kerala. 2022 Economic and Political Weekly. All rights reserved. -
Intersecting Barriers: Gender, Religion and the Political Under-representation of Muslim Women in Local Governance in Bihar
Womens reservation policies have substantially expanded female political participation in India, yet the representation of Muslim women continues to remain disproportionately low across levels of governance. Drawing on detailed administrative data from the 2016 and 2021 Panchayat elections in Bihar, this study examines the institutional, structural and behavioural mechanisms that shape Muslim womens political inclusion. Using a supply-side framework, the analysis formalizes two key determinants of contest entry, past co-ethnic competitiveness and demographic potential, and shows how these factors jointly influence womens decisions to contest elections. The results highlight the central role of institutional design and strategic expectations in shaping minority womens political agency, even in communities where demographic conditions appear favourable for political representation. 2026 Lokniti, Centre For The Study Of Developing Societies -
Intersecting queer rights and legislative theatre in India: advocacy narrative of power, justice and expression
Queer activism and Legislative Theatre (LT) converge in myriad ways at their intersection, influencing and shaping each other. The present work investigates how LT can help to identify queer marginalisation in the fissured legal paradigm of India. It explores how LT can address the hegemonic silencing of the queer from an advocacy perspective. Our conviction is that the LT challenges the entrenched power structures against a queer-inclusive democratic space, offers a blueprint to advance queer dialogue, and coalition-building for legislation and policy discussions. It is the time when such a potent artistic activism must shape the public discourse. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
Intersection of AI and business intelligence in data-driven decision-making
In today's rapidly evolving business landscape, organizations are inundated with vast amounts of data, making it increasingly challenging to extract meaningful insights and make informed decisions. The traditional business intelligence (BI) approach must often address the complexity and speed required for effective decision-making in this data-rich environment. As a result, many businesses need help to leverage their data to drive sustainable growth and remain competitive. Intersection of AI and Business Intelligence in Data-Driven Decision-Making presents a transformative solution to this pressing challenge. By exploring the convergence of artificial intelligence (AI) and BI, our book provides a comprehensive framework for leveraging AI-powered BI to revolutionize data analysis, predictive modeling, and decision-making processes. Readers will gain valuable insights into practical applications, emerging trends, and ethical considerations, inspiring and exciting them about the potential of AI in driving business success. Through in-depth discussions, case studies, and best practices, this book equips professionals, researchers, and students with the knowledge and tools needed to navigate the complexities of AI-powered business intelligence. Whether you're looking to predict trends, analyze consumer behavior, or optimize supply chains, this book offers actionable strategies and techniques for implementing AI-powered BI solutions in your organization. 2024 by IGI Global. All rights reserved. -
Interval-Valued Fuzzy Trees and Cycles
Interval-valued fuzzy tree (IVFT) and interval-valued fuzzy cycle (IVFC) are defined in this chapter. We characterize interval-valued fuzzy trees. We also prove that if G is an IVFG whose underlying crisp graph is not a tree then G is an IVFT if and only if G contains only ? strong arcs and weak arcs. It is shown that an IVFG G whose underlying crisp graph is a cycle is an IVFC if and only if G has at least two ? strong arcs. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Interventions for the improvement of social skills in autism spectrum disorder in India: A systematic review
Background: The increasing prevalence of Autism Spectrum Disorders (ASD) in India is in a gaping contrast with the existing interventions in India. Though several interventions have proved their efficiency in foreign countries, such studies within India are scarce. Aims: This review attempts to systematically examine the different intervention practices that include improvement of social skills in ASD that is practiced in India as revealed through published literature on the same. Methods: Studies published from 2000 to 2020 were selected for the study. Evidence is presented for nine treatment categories: Behavior-based interventions, Developmental Interventions, TEACHH approach, Parent-mediated Interventions, speech-based Interventions, electronics-based interventions, augmentative and alternative communication, play-based interventions and Yoga-based interventions. These studies were drawn from databases Ebsco, Proquest, PubMed, MEDLINE, science direct and Google Scholar. Though a definitive conclusion cannot be drawn without a meta-analysis, the available evidence is gathered and evaluated in the present review. Results: The review has proved to be a reliable summary of the interventions that include improvement of social skills in ASD that is practiced in India. Conclusions: Parent-mediated interventions may be more appropriate for the resource-poor settings of India, when developmental interventions may be more appropriate for the resourcerich settings of India. The scarcity of published literature on the topic in India is also a significant factor that highlighted itself through the research. 2021, Indian Association for Child and Adolescent Mental Health. All rights reserved. -
Interventions to help students find a deeper purpose during their academic journey
This comprehensive exploration delves deeply into academic interventions aimed at guiding students toward a more profound sense of purpose throughout their educational journeys. It emphasizes that education offers a unique opportunity for students to discover their passions, interests, and aspirations beyond textbooks and exams. The interventions discussed, including mentorship, career counseling, experiential learning, and self-discovery exercises, are meticulously designed to empower students to recognize their distinct strengths and interests. These interventions not only aim to facilitate academic excellence but also enable students to pursue careers aligned with their core values and aspirations. The exploration scrutinizes effective strategies, programs, and support mechanisms, addressing challenges students face when making career choices, and culminates in recommendations for educators, career counselors, and policymakers interested in enriching students' educational experiences and fostering purpose-driven learners. 2024, IGI Global. -
Into the Dark World of User Experience: A Cognitive Walkthrough Study
In this age of AI, the unison of man and machine is going to be more prominent than ever, thus creating a need to understand the underlying framework that is adopted by app designers and developers from a psychological point of view. Research on the various benefits and harmful effects of user experience design and furthermore developing interventions and regulations to moderate the use of dark strategies in digital tools is the need of the hour. This paper calls for an ethical consideration of designing the experience of users by looking at the unethical practices that exist currently. The purpose of the study was to understand the cognitive, behavioural and affective experience of dark patterns in end users. There is a scarcity in the scientific literature with regard to dark patterns. This paper adopts the methodology of user cognitive walkthrough with 6 participants whose transcripts were analysed using thematic network analyses. The results are presented in the form of a thematic network. A few examples of the themes found are the experience of manipulation in users, rebellious attitudes, and automatic or habitual responses. These findings provide a basis for an in-depth understanding of dark patterns in user experience and provide themes that will help future researchers and designers develop ethical and more enriching user experiences for users. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.