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AI-driven load forecasting and energy management in smart grids using hybrid deep models
Modern power systems are becoming more complex, and integrating renewable energy sources (RES) calls for sophisticated solutions for accurate load forecasting and efficient energy management. To improve forecast accuracy and operational efficiency in smart grids, the research suggests a hybrid deep learning (DL) structure that blends convolutional neural networks (CNN) with long short-term memory (LSTM) systems. The LSTM element records sequential connections within historical energy usage, while the CNN element extracts geographical features from environmental variables such as temperature, humidity, and solar radiation. A comprehensive preprocessing pipeline comprising data cleaning, normalization, and feature selection ensures high-quality inputs for model training. The proposed LSTM-bCNN model is evaluated using a publicly available dataset, and its performance is benchmarked against traditional and contemporary models including ARIMA, SVM, RF, and standalone LSTM. According to findings from experiments, the mixture model obtains the highest R-squared (R) value, the lowest Mean Absolute Error (MAE), and the Root Mean Squared Error (RMSE), confirming its robustness in capturing complex patterns in energy consumption. This research highlights the possible of hybrid DL models in enabling intelligent, adaptive, and resilient energy management systems (EMS) within next-generation smart grids. 2026 Elsevier B.V. -
The effectiveness of proactive coping intervention for students with learning disabilities
The presence of Learning Disabilities (LD) increases the possibility of psychological distress due to the negative school experiences. Apart from academic difficulties, students with LD are facing social and emotional problems related to their disabilities. If the psychological distress evolves over time without proper management, it may lead to psychosocial maladjustment. Previous research has shown that proactive coping helps minimize stress and maladjustment issues and is a predictor of success in people with LD. In comparison to students without LD, students with LD in Kerala have lower proactive coping and are more maladjusted. Hence, the current study has tailored an intervention to enhance proactive coping for students with LD. The present study followed the quasi-experimental research design to examine the effectiveness of the intervention on students with LD. A total of 200 participants from various schools across Kerala were initially selected using a multistage random sampling method. Subsequently, participants exhibiting the lowest scores in proactive coping were identified, and then 60 of them were randomly assigned to either the experimental or control group for the intervention. Proactive Coping Inventory for Adolescents and Adjustment Inventory for School Students were the tools used in this study. The data collected from the experimental and control groups following the intervention were analysed using Mixed analysis of variance and Repeated Measures of ANOVA. The findings of the study showed that the proactive coping intervention has significantly enhanced the proactive coping and social emotional adjustment of students with LD. Using these proactive coping interventions in remedial instruction will enable the students to develop a healthy coping style that benefits their personal growth. The Author(s) 2025. -
Deposition and characterization of ZnO/CdSe/SnSe ternary thin film based photocatalyst for an enhanced visible light-driven photodegradation of model pollutants
A heterogeneous photocatalytic pathway is a possible approach to global energy and environmental issues. Sol-gel spin coating and physical vapour deposition were used to create a new ternary ZnO/CdSe/SnSe nanocomposite thin film photocatalyst. X-ray diffractometry, energy-dispersive X-ray spectroscopy (EDS), field emission-scanning electron microscopy, UV-Vis, and photoluminescence (PL) spectrophotometers were used to characterize the deposited films. When exposed to solar light, the ternary photocatalyst exhibits high photocatalytic activity in photocatalytic dye degradation processes. it demonstrates excellent visible light absorption, enhanced charge carrier separation, and solar light simulation. It was proposed that the charge in the ternary ZnO/CdSe/SnSe photocatalyst moves in a double type-II and cascade manner between the various components. In this study, ternary thin film heterostructures are synthesized, exhibiting outstanding stability and solar light-induced photocatalytic activity.The thin film composed of ZnO/CdSe/SnSe exhibits a degradation efficiency of 96% when exposed to visible light, and a degradation efficiency of 90% for methylene blue under sunlight within a time period of 150 min. Graphical Abstract: (Figure presented.) The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
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MRSP-Multi Routing Systems and Parameter Explanations to Build the Path in Underwater Sensor Network
The underwater network is currently widely used to locate moving objects beneath the sea, monitor marine security, and detect changes in the sea water. A large number of sensors, as well as a precise methodology, are necessary to detect changes in sea depth. The protocol should be revised in response to environmental and chronological changes. The sensor should have been designed with multiple knowledge to route packets in order to optimise transmissions. Because the node will choose the best route based on the circumstances, especially in an underwater network, the paper MRSP - multi routing systems and parameter validations to create the path in an underwater sensor network is discussed in the multi routing knowledge sensor operations, energy saving systems, redundancy reduction, and so on. All of these measures, combined with secure transmission with trusted neighbour selection, result in safer transmissions and more accurate path selection. 2022 IEEE. -
Factors Influencing Rural Youth Engagement in India: A Comprehensive Analysis
India is currently in a crucial situation where utilizing the potential of its rural youth could greatly influence the countrys overall growth, given its large rural areas and young population. This chapter explores the various factors that affect the involvement of rural youth, such as education, job prospects, infrastructure, technology, and government policies. It also examines the current engagement of rural youth in India, their aspirations for rural development, and the factors influencing their participation. First, the chapter examines the factors that influence rural youth engagement in development activities. It identifies driving factors such as resource access, supportive policies, and community backing, while also addressing hindrances including resource limitations, inadequate infrastructure, and socio-cultural barriers. Second, it identifies proven practices that effectively involve young people in rural settings, including empowerment programs, skill development workshops, and technology integration. These practices provide insights into how rural youth are currently contributing to and benefiting from development initiatives. Finally, the chapter proposes a research framework and instrument designed to assess and enhance youth involvement in various developmental areas. The findings offer valuable recommendations for enhancing youth involvement in rural development and addressing their unmet needs, ultimately contributing to more effective and inclusive development strategies in rural India. Through a synthesis of existing literature and insights from focused group discussions at rural colleges, this work explores the challenges and aspirations of rural youth in India. CAB International 2026. -
Factors Influencing Rural Youth Engagement in India: A Comprehensive Analysis
India is currently in a crucial situation where utilizing the potential of its rural youth could greatly influence the countrys overall growth, given its large rural areas and young population. This chapter explores the various factors that affect the involvement of rural youth, such as education, job prospects, infrastructure, technology, and government policies. It also examines the current engagement of rural youth in India, their aspirations for rural development, and the factors influencing their participation. First, the chapter examines the factors that influence rural youth engagement in development activities. It identifies driving factors such as resource access, supportive policies, and community backing, while also addressing hindrances including resource limitations, inadequate infrastructure, and socio-cultural barriers. Second, it identifies proven practices that effectively involve young people in rural settings, including empowerment programs, skill development workshops, and technology integration. These practices provide insights into how rural youth are currently contributing to and benefiting from development initiatives. Finally, the chapter proposes a research framework and instrument designed to assess and enhance youth involvement in various developmental areas. The findings offer valuable recommendations for enhancing youth involvement in rural development and addressing their unmet needs, ultimately contributing to more effective and inclusive development strategies in rural India. Through a synthesis of existing literature and insights from focused group discussions at rural colleges, this work explores the challenges and aspirations of rural youth in India. CAB International 2026. -
Decision-Making Frameworks for Integrating Motion Control in Business Operations
This chapter includes some strategic plans of how to incorporate motions control technologies in the business to promote efficiency, agility, and to make data- driven decisions. It cogitates about the real- time motion tracking and the focus on optimization in the logistics sphere, production and asset management through automation and smart analytics. The chapter explains how AI, IoT, control algorithms help harmonize the processes of motion with the goals of organizations. They lay emphasis on decision theory, performance measures and on the flexibility of motion systems in dynamic environments. The chapter has shed light on the ability of motion control to become the engine of innovation and competition in the operation of the contemporary enterprise by offering scalable and practical integration models. 2026, IGI Global Scientific Publishing. All rights reserved. -
On Proper Diameter of Certain Classes of Graphs
An edge coloring of a graph is said to be proper edge coloring if no two adjacent edges receive the same color. A graph G is said to be properly connected if there exists a properly edge colored path between every pair of vertices. For a properly connected graph G with a k-edge coloring c, the proper diameter of a graph, pdiamk (G) is the maximum proper distance between any distinct pair of vertices in G. We investigate the proper diameter of various classes of graphs that are 2-colored and provide bounds on the values of pdiam2(G) for these graphs. Palestine Polytechnic University-PPU 2025. -
Dynamics of chaotic waterwheel model with the asymmetric flow within the frame of Caputo fractional operator
The chaotic waterwheel model is a mechanical model that exhibits chaos and is also a practical system that justifies the Lorenz system. The chaotic waterwheel model (or Malkus waterwheel model) is modified with the addition of asymmetric water inflow to the system. The hereditary property of the modified chaotic waterwheel model is analyzed to determine the system's stability and identify the parameter that contributes to the stability We also examine the factor that leads to the bifurcation. We determine the well-posed nature of the modified system. The modified chaotic waterwheel model is defined with the Caputo fractional operator. The existence and uniqueness, boundedness, stability, Lyapunov stability, and numerical simulation are studied for the modified fractional waterwheel model. The bifurcation parameter and Lyapunov exponent are examined to study the chaotic nature of the system with respect to the fractional order. The nature of the system is captured with the help of the efficient numerical approach AdamsBashforthMoulton Method. The numerical approach demonstrates that the chaotic nature of the modified chaotic waterwheel is changed into unstable nature, which could further reduce to the stable case with suitable values of the parameter. This analysis is justified with the help of Lyapunov exponent. We consider irrational order (?,e) in the present work to illustrate the reliability of fractional order. 2023 Elsevier Ltd -
Modified Genesio-Tesi systems with trigonometric functions and the Caputo fractional derivative
The new fractional-order Genesio-Tesi system is introduced, and its boundedness, stability of the equilibrium points, Lyapunov stability, uniqueness of the solution, and bifurcation are all discussed in this paper. Using the efficient predictor-corrector approach, we statistically analyze the Genesio-Tesi system in fractional order. The results effectively conceptualize and visualize the novel fractional order Genesio-Tesi systems that are suggested. When the systems order shifts from integer to fractional, the revolution around the fixed point increases. The chaotic character of the modified Genesio-Tesi system is comparable to that of the original Genesio system. The major changes were made to the Geensio-Tesi system by including the trigonometric functions, keeping the initial conditions and parameter values intact. The system is fractionalised with the help of Caputo fractional operator. In particular, the modified systems nature is more complex, which may aid in signal processing and secure communication. Future research on the modified Genesio-Tesi system can now proceed in light of this finding. This article offers a fresh approach to utilizing and thoroughly researching the Genesio-Tesi systems that have been provided. CSP - Cambridge, UK; I&S - Florida, USA, 2024 -
A computational approach for the generalised GenesioTesi systems using a novel fractional operator
This article presents the novel fractional-order GenesioTesi system, along with discussions of its boundedness, stability of the equilibrium points, Lyapunov stability, uniqueness of the solution and bifurcation. The efficient predictorcorrector approach is employed to quantitatively analyse the GenesioTesi system in fractional order. The findings enable conceptualisation and visualisation of the presented novel fractional-order GenesioTesi systems. The modified systems are proposed for future study on chaos control and applying the same for secure communication. Bifurcation analysis is carried out to see the variation in the systems behaviour from stability to chaos. The results of the bifurcation analysis support the results obtained for the stability of the equilibrium points. The system behaves chaotically since all the equilibrium points are unstable. The findings demonstrate a torus attractor for some of the suggested systems and a chaotic attractor for some of the novel fractional-order GenesioTesi systems. The systems torus attractor changes into a steady state when the order is reduced from integer to fractional. Changing the parameter values for one of the modified systems also shifts the systems behaviour, with the point attractor replacing the torus attractor. The point attractor of one of the systems changes into a steady character when the systems order is reduced from integer to fractional. The behaviour for one modified system is the same for fractional and integer orders. This discovery paves the way for the future study of the modified GenesioTesi system. This article gives a new direction to utilise these proposed GenesioTesi systems and study them extensively. The chaotic behaviour of the modified system can be used for secure communication. The synchronisation and chaos control of the modified system is recommended. 2024, Indian Academy of Sciences. -
Financial inclusion and poverty alleviation: The alternative state-led microfinance model of Kudumbashree in Kerala, India
The study examines the microfinance and microenterprise model of Kudumbashree, the state poverty eradication mission of Kerala, and its impact on poverty alleviation in the state of Kerala in India. Kudumbashree's method of identification of the poor is seen to be superior to the conventional head count ratio as it captures the multidimensional characteristics of poverty leading to lesser chances of exclusion of vulnerable families. The microenterprise-linked microfinance model of Kudumbashree has established itself as an effective model linking the state, community, and financial organizations, differentiating itself from other NABARD-led self-help group (SHG) programmes or the Grameena model of microfinance institutions in the country. The fundamental idea of local economic development on which the microenterprise business is built is, however, not free from limitations. Heavy reliance on local markets for procuring inputs and selling outputs makes the products less competitive, questioning the sustainability of a business-led model in the absence of state subsidy in the longer run. Copyright 2014 Practical Action Publishing. -
Parametrical variation and its effects on characteristics of microstrip rectangular patch antenna
This paper represents a brief description about design of rectangular microstrip patch antenna and its parameter effects in size, efficiency and compactness and parametric analysis in terms of return loss, bandwidth, directivity and gain by using same and different dielectric substrate materials with same and different thickness of rectangular microstrip patch antenna. The important parameters of patch such as L, W, r and h has its own impact in antenna characteristics. This parametrical impact is studied and verified. As thickness of dielectric substrate increases, the gain & directivity of rectangular microstrip patch antenna decreases and bandwidth increases. As r increases, the size of the antenna decreases but when height of dielectric substrate increase antenna size also increases. There will be always a compromise between miniaturization and other antenna characteristics. This antenna is designed for microstrip feed line technique and with center frequency (f0) at 4GHz. The parametric analysis is obtained by comparing the simulated results of rectangular microstrip patch antenna for different cases. The proposed antenna is simulated using HFSS tool at resonance frequency of 4 GHz. 2017 IEEE. -
Comic Memes and Sexist Humor in India: Tools for Reinforcement of Female Body-Image Stereotypes
Memes have been described as communicative and aesthetic practices that serve cultural, social, political purpose on a digital platform. Several studies, in the last decade, have attempted to study this digital aesthetic knowledge production as a powerful tool for political, racial, and gender-related discourses. Most often this knowledge is produced through comic multi-media texts. Many theorists believe that, digital media reinforces inequality, marginalization and such other social issues through the audio-visual-textual medium as much as it establishes the counter-discourses for equality, body activism, racial activism and the like. Speed and lack of censorship can be the cardinal reasons for the popularity of these memes. Among the mass-influencing gender-related memes are those encouraging fat-talk and body-image stereotypes. In the Indian context, 'Tag a Friend' memes is one such widely circulated meme which communicates body-shaming messages through sexist humor. It mainly targets the fat/colored/transgender women. The current study examines these memes using multimodal discourse analysis methodology. The paper attempts to investigate the revival/reproduction potential of color-shaming and body-shaming stereotypes via comic memes through Shiffman's memetic dimensions. The analysis establishes that memes can be a prominent site for the re-production of the problematic ideology of body/color shaming even in the 21st century. AesthetixMS 2021 -
Automated Leaf Disease Detection using a Hybrid CNN-BiLSTM Model for Smart Agriculture
The mitigation of crop losses and the sustainability of agriculture rely on the prompt identification of foliar diseases. In large-scale agriculture, conventional identification methods such as expert eye inspections are inefficient, susceptible to errors, and labour-intensive. A growing number of individuals are seeking automated methods to monitor plant health, given that the majority of Indians are employed in agriculture. This study presents a hybrid DL strategy for leaf disease detection, encompassing preprocessing, segmentation, feature extraction, and model training. Initially, images are processed to enhance their quality and uniformity. The impacted regions of the leaf are subsequently categorised by K-Means clustering. The classification accuracy is improved by utilising several feature extraction methods. The proposed model, CNBiLS, integrates bidirectional LSTM layers with convolutional layers to leverage the spatial and sequential information in image data. When evaluated against contemporary state-of-the-art models, CNBiLS exhibited superior performance, achieving an exceptional 99.84% classification accuracy. This result underscores the model's accuracy in identifying various leaf diseases. Ultimately, CNBiLS offers a precise, scalable, and robust automated system for detecting leaf diseases, equipping farmers with timely information to manage illnesses effectively, so enhancing both the quality and yield of their crops. 2025 IEEE. -
Acidified coconut husk as a potential biosorbent for adsorption of textile dye reactive yellow 160
Coconut husk could be employed as an environment friendly adsorbent for removal of various xenobiotics from the environment, especially the reactive dyes from the polluted waterbodies. In this study the Acidified Coconut Husk(ACH) with 0.1 N Hydrochloric acid was identified as a potentially low-cost biosorbent for the removal of Reactive Yellow 160(RY160) in aqueous solution. Optimization of various parameters such as the effect of agitation at shaker rotor speed of 120 rpm, adsorbent dosage ranging from 0.54%, initial dye concentration (200 to 1000 mg/L) and pH (3 to 11) were conducted and it was found that maximum adsorption percentage of 93% occurred with 4% adsorbent dosage at 200 mg/L initial dye concentration and pH 3 under agitating conditions. Adsorption was confirmed with the changes in FTIR spectrum, XRD and SEM of the ACH before and after adsorption. Adsorption kinetics studies proved a best fit into the pseudo second order kinetics model (R2= 0.9973) indicating chemisorption as the rate-limiting step of the process. Adsorption capacity(qe) of 4.56 mg/g fitted more into Langmuir isotherm model (R2= 0.9884) than Freundlich isotherm (R2= 0.8792) with Qmax value of 35.97 mg/g. Acidified coconut husk is proved as feasible adsorbent for textile dye removal from the aqueous environment. 2026 Taylor & Francis Group, LLC. -
Longitudinal study on noncommunicable diseases using machine learning
This longitudinal case study thoroughly explores the intricate connection between body mass index (BMI) and four key factors: physical health, psychological well-being, lifestyle choices, and the impact of diet on health. Through the analysis of longitudinal data, notable trends emerge, revealing an increase in risk factors for noncommunicable diseases (NCDs) and unhealthy behaviors over time. This highlights the combined impact of these interconnected factors on health outcomes and the risk of developing NCDs like heart disease, diabetes, and cancer. Leveraging machine learning, the study effectively identifies individuals at elevated risk for NCDs and dispels common health misconceptions, underscoring the significance of holistic wellness approaches. Serving as a beacon for the next generation, this study provides insights that contribute to shaping a healthier future. 2025 selection and editorial matter, Arun Kumar Rana, Vishnu Sharma, Sanjeev Kumar Rana, and Vijay Shanker Chaudhary; individual chapters, the contributors. All rights reserved. -
A hybridized semantic trust-based framework for personalized web page recommendation
The World Wide Web is constantly evolving and is the most dynamic information repository in the world that has ever existed. Since the information on the web is changing continuously and owing to the presence of a large number of similar web pages, it is very challenging to retrieve the most relevant information. With a large number of malicious and fake web pages, it is required to retrieve Web Pages that are trustworthy. Personalization of the recommendation of web pages is certainly necessary to estimate the user interests for suggesting web pages as per their choices. Moreover, the Web is tending towards a more organized Semantic Web which primarily requires semantic techniques for recommending the Web Pages. In this paper, a framework for personalized web page recommendation based on a hybridized strategy is proposed. Web Pages are recommended based on the user query by analyzing the Web Usage Data of the users. An array of strategies is intelligently integrated together to achieve an efficient Web Page Recommendation system. Latent Semantic Analysis is applied to the User-Term Matrix and the Term-Frequency Matrix that are built from the Web Usage Information to form a Term Prioritization Vector. Further, techniques like Latent Dirichlet Allocation for Topic-based Segregation of the URLs and Normalized Pointwise Mutual Information strategies are used for recommending web pages based on users queries. The Personalization is achieved by prioritizing the Web pages based on the Prioritization Vector. Also, a unique methodology is incorporated into the system to retrieve trustworthy websites. An overall Accuracy of 0.84 is achieved which is better than the existing strategies. 2018 Informa UK Limited, trading as Taylor & Francis Group. -
A hybrid semantic algorithm for web image retrieval incorporating ontology classification and user-driven query expansion
There is always a need to increase the overall relevance of results in Web search systems. Most existing web search systems are query-driven and give the least preferences to the users needs. Specifically, mining images from the Web are a highly cumbersome task as there are so many homonyms and canonically synonymous terms. An ideal Web image recommendation system must understand the needs of the user. A system that facilitates modeling of homonymous and synonymous ontologies that understands the users need for images is proposed. A Hybrid Semantic Algorithm that computes the semantic similarity using APMI is proposed. The system also classifies the ontologies using SVM and facilitates a homonym lookup directory for classifying the semantically related homonymous ontologies. The users intentions are dynamically captured by presenting images based on the initial OntoPath and recording the user click. Strategic expansion of OntoPath based on the users choice increases the recommendation relevance. An overall accuracy of 95.09% is achieved by the proposed system. 2018, Springer Nature Singapore Pte Ltd.