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MobileNetV3-Based Fine-Tuned Facial Emotion Recognition with Targeted Class Balancing
Facial emotion recognition (FER) is a pillar of affective computing and augmented human computer interaction, but has been stymied by the problem of class imbalance and lack of prevalence of subtle emotional differences. This paper presents a lightweight FER framework based on the MobileNetV3 architecture with a fine-tuned and weighted dataset that applies class balance and class weighting as strategies that optimized the three-class classification of three discrete emotions Angry, Happy, and Sad. The characteristics of the dataset were assembled comprising a total of 7,305 labelled facial images, based on the KDEF, Kaggle, and Face Expression Dataset hence inheriting the heterogeneity of subjects and imaging conditions. The pre-processing of all of the images carried out as the RGB input and after resizing (224 x 224 pixels) a massive data augmentation done to encourage generalization. Transfer learning in the training pipeline is done through progressive unfreezing and the weight of the loss on the minority classes (Angry and Sad) are boosted to improve the performance of detection. The achieved model resulted in an accuracy of 87% on the test set, and had equal accuracy in preciseness, recall, and F1-scores over all emotion types. Extended error analysis revealed that the majority of cases that were misclassified fell between the categories Angry and Sad because they were mistaken due to combining visual cues. Even then, the performance showed stability despite the variable lighting as well as in variable positional context. In Comparison, MobileNetV3 outperforms state-of-art-lightweight models with respect to accuracy and computation of similar computational complexity. 2025 IEEE. -
Edufusion: Integrating Artificial Intelligence With Teaching Practices to Enhance Learning Experiences
The present research explores the influence of artificial intelligence (AI) on traditional teaching methods in the education sector. Through a comprehensive review of existing literature and empirical studies, the present research aims to elucidate the transformative potential of AI technologies in reshaping pedagogical practices and enhancing learning outcomes. The study aims to provide the integrated perspective on the ever changing dynamics influenced by the incorporation of AI in the current education system through a meticulously conducted questionnaire- based investigation involving a diverse pool of huge participants, primarily students from the region of Delhi NCR. 2025 by IGI Global Scientific Publishing. -
SMOTE-Based Sampling for Addressing Class Imbalance
Various real-world applications, including as text categorization, categorization of gender in facial recognition for medical evaluation, fraud detection, and satellites analysis of images for oil-spill monitoring, are frequently plagued by imbalanced data. The majority class is commonly the primary focus of machine learning algorithms, with the minority samples being ignored or classified in a secondary manner. Nevertheless, despite their rarity, these minority samples are very important. When it comes to classification tasks, the issue of class imbalancewhere one class is underrepresented relative to anotherpresents a significant barrier. Specialized approaches including SMOTE, ADASYN, and cost-sensitive voting classifiers have been developed to address this problem. The minority class is oversampled in these methods, synthetic samples are created adaptively, and different prices are placed on misclassification mistakes in order to solve the issue of class imbalance. As a result, rigorous assessment utilizing pertinent metrics and cost considerations are required. The efficacy of these strategies, however, depends on dataset features and problem-specific factors. Class imbalance is still a hot topic for study, and there has been constant innovation in novel methods that are adapted to certain dataset characteristics and application fields. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Financing for SDGs in India in Post Pandemic era - Challenges & Way forward
In 2015, a resolution known as Agenda 2030 was passed by United Nations General Assembly in which seventeen goals for Sustainable Development were laid down for global dignity, peace and prosperity. The post- pandemic era became full of uncertainties in pursuing those Sustainable Development Goals (SDGs) and its implementation became a challenge especially for the developing economies like India. The country is facing a tremendous gap in arranging for resources to meet the climatic changes and attaining the SDGs. India requires 170 billion dollars per year from 2015-2030 to fulfill the Sustainable Development Goals as per the estimation done by National Determined Contribution, a body setup after Paris agreement 2015 to monitor the efforts of the country towards reducing national emissions and adapting to climate change. There is a huge concern amongst the various agencies on exploring the ways to fill this financing gap especially after the economic slowdown seen in the post pandemic era. This research paper analyses the challenges imposed by the COVID 19 pandemic on financing for SDGs and also explores the options to mitigate them. The articles and research papers related to SDG financing are reviewed by the researchers to arrive at the above mentioned statements. This paper is an attempt to draw the attention of worldwide authorities towards this grim situation as sustainable finance is far from reality in India and requires immediate up scaling. The Electrochemical Society -
CSR as an agent of financial stability: A use case of banking industry
The study was undertaken to examine the importance of corporate social responsibility (CSR) as an agent to improve the firm's performance and financial stability by enhancing goodwill and competitive advantage in the Indian banking industry. In the study, it has been hypothesized that CSR expenses have a positive relationship with financial stability. A correlation study has also been undertaken to determine any relationship among these variables, followed by a dependency regression test to show the levels of dependency of financial stability on CSR expenses and the Granger Causality test to find their causal relationship. The study has revealed a significant relationship between the financial stability variables and CSR expenses, and the Granger Causality level supports the findings. 2021 Ecological Society of India. All rights reserved. -
Personalized Medicine Recommendation Through Genomics AI
Every individual is genetically different. This highlights the importance of exploring the possibility of personalized medicine tailored for each persons unique genetic profile. Due to this genetic variability, people have varied responses to the same medication. Thus, it is all the more necessary to withdraw from traditional medication and adopt personalized medicine. Using genomic data analysis techniques, healthcare specialists will be able to distinguish the minute genetic differences to produce unique therapies for each patient. This paper traverses the development of an algorithm to integrate the patients genomic data with his medical history. Personalized treatment can be recommended based on the inferences using genomic AI. These insights derived from the algorithm can be scrutinized by decision support systems. This step ensures the reliability of the prescribed personalized treatment and confidence of patients on the medication. Each time the model predicts medication compositions and dosages using genomic data, it becomes more accurate improving therapeutic results. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
An effective face recognition system based on Cloud based IoT with a deep learning model
As of late, the Internet of Things (IoT) innovation has been utilized in applications, for example, transportation, medical care, video observation, and so on. The quick appropriation and development of IoT in these segments are producing an enormous measure of information. For instance, IoT gadgets, for example, cameras produce various pictures when utilized in medical clinic reconnaissance sees. Here, face acknowledgement is one of the most significant instruments that can be utilized for clinic affirmations, enthusiastic discovery, and identification of patients, location of fake gadgets. patient, and test clinic models. Programmed and shrewd face acknowledgement frameworks are profoundly precise in an overseen climate; notwithstanding, they are less exact in an unmanaged climate. Additionally, frameworks must keep on running on numerous occasions in different applications, for example, insightful wellbeing. This work presents a tree-based profound framework for programmed face acknowledgement in a cloud climate. The inside and out pattern have been proposed to cost less for the PC without focusing on unwavering quality. In the model, the additional size is isolated into a few sections, and a stick is made for each part. The tree is characterized by its branch area and stature. The branches are spoken to by a leftover capacity, which comprises of a twofold layer, a stack game plan, and a non-direct capacity. The proposed technique is assessed in an assortment of generally accessible information bases. An examination of the method is likewise finished with top to bottom craftsmanship models for the eye to eye connection. The aftereffects of the tests indicated that the example was considered to have accomplished a precision of 98.65%, 99.19%, and 95.84%. 2020 -
BEYOND SCREENS: A PSYCHO-THERAPEUTIC INTERVENTION FOR ADOLESCENTS SUFFERING FROM INTERNET GAMING ADDICTION
The Diagnostic and Statistical Manual of Mental Disorders (DSM 5) has now included Internet Gaming disorder in section III as the condition that warrants more clinical research. Internet or Online gaming has become one of the most popular sources of entertainment among children and adolescents, representing the fastest-growing segment leading to hazards as well. Thus, there is a requirement for a psycho-therapeutic intervention module to help in overall psychological well-being of the adolescents suffering from Internet Gaming Disorder (IGD). A total of 8 adolescents suffering from IGD were treated with scientifically prepared psycho-therapeutic module in total of 12 group sessions. The eclectic approach to treatment is proven to be effective for adolescents yielding significant improvement in the clinical condition and promotes wise engagement in gaming. (2023). All Rights Reserved. -
Investigating Personalized Learning Paths to Address Educational Disparities Using Advanced Artificial Intelligence Systems
This innovative study reimagines the role of Natural Language Processing (NLP) in individualized education by highlighting the critical need to incorporate cultural subtleties. While natural language processing (NLP) offers great potential for improving classroom instruction, current research frequently fails to account for the complex issues caused by cultural variation. This research fills a significant need by providing a novel framework for the detection and incorporation of cultural subtleties into individualized learning programs. Further research into common biases is driving the development of natural language processing models with greater cultural sensitivity and awareness, such as gender bias in Named Entity Recognition (NER) and sentiment bias in cultural preferences. In order to correct past biases and promote gender neutrality in educational content, the research makes use of an adaptive NER algorithm and a diverse training dataset. Similarly, to guarantee nuanced and fair sentiment evaluations, the study suggests regularly evaluating and retraining sentiment algorithms with datasets that represent multiple cultures. A Cultural Relevance Score of 0.9, Adaptive Content Embedding vectors [0.3, 0.6, -0.2.], and an impressive Cosine Similarity of 0.85 are some of the evaluation measures that highlight the effectiveness of the research. These measurements show encouraging gains, which confirms that the research might help make schools more welcoming and sensitive to different cultures. The research has the potential to revolutionize individualized education by making it more accessible and engagingfor students from all backgrounds. 2024 IEEE. -
Liability of Artificial Intelligence System: A Bibliometric Study of Current and Emerging Trends (20112024)
The Integration of Artificial intelligence across the various sector such as Transportation as Autonomous vehicle, Business, education and healthcare has introduced the remarkable efficiencies such as data interpretation, data analysis, predictive analysis and Advance decision making, however it also purposed the unprecedented Legal issues. The Artificial intelligence system has become autonomous and obtained the capability of self decision making from the data. These advances of the AI system challenged the various aspect of Legal framework such as Insurance policy, intellectual property in AI and the Liability in case fault. The question of liability has become pressing concern because the Black box nature of AI and the involvement of various stakeholder complicated the assignment of legal responsibility in case of Failure. The present study aimed to investigate the research landscape including the knowledge, emerging area and the trends available in the literature on the Artificial intelligence liability. This research adopted the Bibliometric analysis methodology using the R software Biblioshiny Package, the analysis conducted on Liability focused studies related to artificial intelligence from timespan of 2011-2024. A total 154 document were obtained from the scientific databased SCOPUS and Web of Science after rigorous manual review of keywords Liability and Artificial intelligence in Title and abstract. This study employed the several analyses on the data including growth of research area, leading document, distribution of studies by the author, leading county, collaboration network, trend topic and factorial analysis. The finding indicates a notable increase in the number of publication form 2011-2024 focusing the healthcare sector. The emerging research area includes the area such as insurance, product liability, civil liability, strict liability of artificial intelligence. The study underscored the AI rule, regulation framework underdeveloped which require the further study in relation of legal liability. Finally, the findings suggest that the increasing focus on liability framework will foster the trustworthy AI and better regulating policies. 2025, National Institute of Science Communication and Policy Research. All rights reserved. -
Level Up or Log Out? Exploring the Multifaceted Effects of Internet Gaming on Youths Life: Emotional Intelligence, Coping Behavior, Aggression, Procrastination & Quality of Life
Emotional Intelligence, coping mechanisms, aggression, procrastination, the quality of life are the psychological factors of students well-being examined in this study, which also emphasizes the multifaceted impacts of online gaming on youths. It reveals subtle discrepancies in results through analysis of variance involving gamers and non-gamers. Concerns continue to exist regarding the potential adverse effects of gaming despite its extensive implementation among college students. The findings indicate that individuals who engage in gaming demonstrate diminished levels of emotional intelligence, as evidenced by challenges in proficiently comprehending and regulating emotions. Moreover, excessive discontentment and procrastination result from the tendency of gamers to utilize fewer adaptive coping mechanisms when confronted with stressors. These results highlight the complex relationship between internet gaming and quality of life, which indicates that gamers generally encounter less favorable consequences than those who do not engage in gaming. By illuminating these inconsistencies, the study enhances the comprehension of the varied impacts of online gaming on young adults lives. This highlights the criticality of developing adaptive coping mechanisms and fostering positive gaming behaviors to minimize negative consequences. The research highlights the necessity for interventions that target the well-being of young gamers, with implications that transcend the realm of academia and the real world. Furthermore, it emphasizes the substantial societal ramifications associated with the increasing prevalence of online gaming and its influence on young individuals. This study provides novel perspectives on the intricate nature of online gaming and its consequential effects on diverse facets of the student experience. 2025 RESTORATIVE JUSTICE FOR ALL. -
Free Speech in the Age of Algorithms: Regulating Online Hate in India, Canada, and the United Kingdom
Online hate has increased while public conversation has expanded due to digital connectivity. This contrasts the laws governing hate speech online in the UK, Canada, and India. Canada strikes a compromise between equality and expression, India permits modest limits but issues with uneven enforcement, and the UK makes threatening or nasty online behavior illegal. Uncertain definitions, inconsistent enforcement, algorithmic dissemination, and the possibility of excessive censoring are some of the main obstacles. A harm- reduction model based on rights is put forth. 2026 by IGI Global Scientific Publishing. All rights reserved. -
A bibliometric analysis of compact city for sustainable urban development
This work provides a detailed bibliometric review of compact city literature for sustainable urbanism from 1983 to 2023. The compact city concept has received considerable attention as a possible approach towards solving sustainable city issues. Hence, based on the documents obtained from the Scopus database, we studied the research topics and authors, as well as the thematic development of this topic. The research used the bibliometric approach of citation analysis, keyword cooccurrence, and thematic evolution mapping. Research indicates that there is an Increased research productivity over the recent past especially in the last two decades. Among developed countries, China has become one of the most active participants in the provision of new knowledge. The thematic focus has shifted from pure and applied to complex themes like sustainability, GIS and urban design. The current trends show increasing concern about sustainability, development, and the 15-minute city model. The proposed analysis also reveals the unequal Within the group of countries, citation rates vary significantly, and the scope of methodological approaches is insufficient. In summary, this review finds that although compact city research has evolved to a certain extent, typological models are still lacking context sensitivity; international cooperation remains rather limited; and finally, many long-term outcomes have not been adequately investigated in order to unleash the full potential of compact cities as a global model of sustainable urban development. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). -
Role of AI tools in evaluating brand performance
The way organizations monitor and control brand performance has been significantly changed by the digital environment. Even though they are useful, traditional measurements frequently miss real-time changes in the market. AI-powered solutions are becoming essential resources in order to tackle this, providing a more precise and up-to-date view of brand health. This chapter explores how artificial intelligence (AI) is transforming brand performance evaluation. It does so by examining important metrics, analytics techniques, and particular AI solutions that are revolutionizing the market. Artificial intelligence (AI) enables organizations to make data-driven decisions with previously unheard-of speed and precision, from assessing brand awareness and consumer loyalty to forecasting future trends. In today's quickly changing digital landscape, marketers, analysts, and company executives can obtain a competitive advantage by comprehending how AI tools can improve brand performance evaluation. 2025, IGI Global Scientific Publishing. All rights reserved. -
Analysing Young Adults Preferences for AI-Generated and Human-Created Art in India: A Comparative Study Using the Mixed Method Approach
Artificial intelligence (AI) has emerged as a transformative tool in creating art, blending computational precision with creative processes. This study explores the appeal of AI-generated art compared to human-created physical and digital art among young adults in India, particularly focusing on visual art students. Additionally, the research addresses critical questions regarding the aesthetic appreciation and criticism of AI-generated art, its impact on human creativity, and its challenges to traditional art and its future. The research employed a mixed-method approach to understand preferences, motivations, and perceptions regarding these two art forms. The Art Reception Survey (ARS) was utilised to measure individuals engagement with visual aesthetics and their preferences. The qualitative approach using Multimodal Critical Discourse Analysis (MCDA) enabled deeper analysis, which helped examine how meaning, perceptions, and visual cues must have shaped their responses. The findings indicate a strong preference for original works involving creative thought processes and artistic skills-factors that lean towards a preference for traditional artwork. The findings suggest that despite rapid advancements in AI, people still significantly value human effort and creativity. The participants also acknowledged that blending both art forms can open new avenues of opportunity for the artists. The study suggests that traditional art will likely remain highly valued and argues that AI should not be seen in opposition to conventional art but as complementary tools for artistic innovation. While human-created art remains strongly appreciated, embracing AI would be the way forward, as outright rejection may not always be feasible or beneficial. 2025, Iquz Galaxy Publisher. All rights reserved. -
Applications of artificial intelligence in Echo Global Logistics
Echo Global Logistics is a premier provider of business process outsourcing, using technology to meet its clients logistics and transportation needs. They deliver substantial transportation savings to clients while providing top-tier service, thanks to state-of-the-art web-based technologies, dedicated service teams, and significant purchasing power. The most significant business risk in 2023 will be supply chain interruptions, which can impact cash flow, growth, and shareholder value. Echo Global Logistics has introduced an innovative self-service website called Echo Ship, designed for shippers of less-than-truckload (LTL) shipments. Echo Ship simplifies LTL shipping with excellent visibility, outstanding functionality, and a quick, user-friendly design. Logistics is evolving at Echo Global Logistics, with patented technology incorporating the latest developments in the most flexible and reliable transport management system (TMS) currently available. This TMS is developed using Artificial Intelligence (AI), machine learning, and complex load-matching algorithms. Echos unique software is user-friendly, adaptable, and highly scalable, addressing the evolving needs of carriers and shippers regarding transportation management, enabling customers to move their goods swiftly, securely, and affordably. A transportation management company leverages AI to provide supply chain solutions that optimize transportation and logistics needs. The list of services also encompasses executive dashboard presentations, rate negotiation, transportation procurement, shipment execution and tracking, carrier management, carrier selection, reporting, compliance, and comprehensive shipment reports, Over the next five years, supply chain companies anticipate a twofold increase in the use of machine automation in their operations. Similarly, there is a projected 40% compound annual growth rate (CAGR) over the next seven years, going from $1.67 billion in 2018 to $12.44 billion in 2024. Supply chain executives are often time-constrained, making it challenging to attend numerous meetings for solution implementation. Actionable insights from integrated AI tools can remove bottlenecks and unlock real-time value. This is vital because supply chain businesses require more action rather than excessive analysis. This chapter delves into the AI and supply chain practices at Echo Global Logistics, illustrating how AI-based solutions reduce costs, enhance supply chains, boost productivity, and improve service quality. It aims to determine whether the company can transform its products and services, creating new value propositions for Echo Global Logistics customers with the aid of AI. 2024 by Elsevier Inc. All rights reserved, including those for text and data mining, AI training, and similar technologies. -
Green Innovation for Sustainable Development
In recent years, organisations have notably taken up Green Innovation for sustainable development to maintain the customer base and keep the natural environment safe. Consumers are aware of the current environmental issues, such as global warming and the consequence of environmental pollution. As a result, organisations are demanding to craft green strategies and embryonic to advance holistic methods towards maximising shareholders' values. This paper attempts to provide valuable insights into the going green concepts and their association with the value creation in the automobile industry regarding the e-vehicle by examining the effects of green innovations in Mahindra Electric Mobility Limited, India towards the launching of Mahindra e2oPlus on the Reva platform. Furthermore, the authors analyse the performance of this innovation on the organisational financial performance with the help of event study methodology. 2022 IET Conference Proceedings. All rights reserved. -
Design of a Multi Camera Enabled Scrutinizing Framework for Smart Cities
This research paper presents a multi-camera surveillance system tailored for the demands of smart cities. By integrating edge computing, the system decentralizes processing, reducing latency and alleviating network bandwidth strain. The architecture includes layers for data collection, edge processing, centralized storage, AI-driven analysis, synchronization, and user visualization. Cameras capture and preprocess data locally to identify anomalies and minimize unnecessary transmission. AI algorithms handle tasks like object tracking, behavior analysis, and event detection with precision. Synchronization ensures seamless temporal alignment across video streams for accurate event reconstruction. User-friendly dashboards provide actionable insights for urban planning and public safety. By leveraging edge computing, AI, and robust synchronization, this system addresses scalability, latency, and privacy concerns, offering enhanced safety, optimized traffic flow, and better urban planning. 2025 IEEE. -
Strategic Integration of HR, Organizational Management, Big Data, IoT, and AI: A Comprehensive Framework for Future-Ready Enterprises
This exploration paper proposes a comprehensive frame aimed at fostering unborn-ready enterprises through the strategic integration of Human coffers(HR), Organizational Management, Big Data, the Internet of Things (IoT), and Artificial Intelligence(AI). By synthesizing these critical factors, the frame seeks to optimize organizational effectiveness, enhance decision-making processes, and acclimatize proactively to evolving request dynamics. Through a methodical review of being literature and empirical substantiation, the paper delineates the interconnectedness of these rudiments and elucidates their collaborative impact on organizational performance and dexterity. likewise, it explores perpetration strategies and implicit challenges associated with espousing such an intertwined approach. This paper not only contributes to the theoretical understanding of strategic operation but also provides practical perceptivity for directors and directors seeking to navigate the complications of the contemporary business geography and place their associations for sustained success in a decreasingly digitized and competitive terrain. 2024 IEEE. -
ASSESSMENT OF WATER QUALITY IMPACTS ON CROP PRODUCTIVITY IN SALINE SOILS: INTEGRATING HYDRO CHEMICAL ANALYSIS AND CROP PERFORMANCE
This study aims to address the effect of water quality on crop productivity on saline soils. Water quality parameters to be studied include salinity level, pH, oxygen concentration, nutrient, and heavy metal level. The study will particularly focus on irrigation water sources that are situated in regions characterised by saline soils. Moreover, there are intended growth experiments for the evaluation of various specific crops such as rice, wheat or maize with different levels of water quality. The study will incorporate sophisticated analytical tools including ion chromatography, atomic absorption spectroscopy (AAS), and electric field mapping (EMI) to shed light on the current water quality and soil conditions of the selected area. The experiments that we plan to conduct will involve studying the growth parameters, yield, water use efficiency and the percentage of uptake of nutrients under several water quality scenarios. The data collected in this work will ascertain the link between the values of water quality parameters, soil salinity extent and productivity of crops and will provide the basis for the creation of innovative saline soil agriculture irrigation management practices. 2024, Scibulcom Ltd.. All rights reserved.