Browse Items (16488 total)
Sort by:
-
A Study on Graph Colouring with Distance Constraints
In this dissertation, we have studied the variations of graph colouring based on distance constraints. For a given set T of non-negative integers including zero and a positive integer k, the L(T,1)-colouring of a graph G = (V,E) is a function c : V(G) and#8594; newline{0,1,2,...,k} such that |c(u)and#8722;c(v)| and#8712;/ T if the distance between u and v is 1 and |c(u)and#8722; newlinec(v)| and#8805; 1 whenever u and v are at distance 2. The L(T,1)-span, and#955;T,1(G) is the smallest positive integer k such that G admits an L(T,1)-Colouring. We have determined the newlineL(T,1)-span for some classes of graphs for set T whose elements are arranged in arithmetic progression. Further, for any general set T , we have found the bound for L(T,1)- span of a few classes of graphs. We use Python programming to colour certain classes of graphs concerning L(T,1)-colouring and fnd the value of L(T,1)-span. Next, we have explored equitable fractional open neighbourhood colouring, which is an extension of a specifc variation of L(h,k)-Colouring for h = 0 and k = 1. For a newlinepositive integer p, equitable fractional open neighbourhood colouring of a graph G is an newlineassignment of positive integers to the vertices of G such that for each vertex v and#8712;V(G), vertices of N(v) receives at least l1p|N(v)|m distinct colours and N(v) can be partitioned into k-classes V1,V2,...Vk such that ||Vi|and#8722; |Vj|| and#8804; 1 for every i and#824;= j and 1 and#8804; k and#8804; n. The minimum number of colours required to colour G such that it admits equitable fractional open neighbourhood colouring for a fxed p is called the equitable fractional open neighbourhood chromatic number, and#967;eq onc newlinep (G). We have studied some properties of equitable fractional open neighbourhood colouring and explored some classes of graphs which admit equitable fractional open neighbourhood colouring with land#8710;(pG)m colours. Further, we have introduced and examined a variation of perfect graphs, and#967;onc-perfect graphs, with respect to equitable fractional open neighbourhood colouring for the special case of p = 1. -
VERTEX COLOURING OF FINITE NETWORKS WITH RESPECT TO AVERAGE DISTANCE
For a finite network, represented as a graph G = (V, E) with average distance (G), the average distance colouring of G is a function c from V to the set of non-negative integers, such that for any v ? V, |c(v) ? c(u)| ? 1 for all u ? V such that d(u, v) ? ??. In this paper, we find the average distance colouring number of some special types of networks and present a greedy algorithm to colour any graph with average distance colouring constraint. 2025, Diogenes Co. Ltd.. All rights reserved. -
Unveiling the Impact of Adverse Childhood Experiences on Adult Criminal Behavior: A Qualitative Enquiry
This qualitative study explored how adverse childhood experiences contribute to criminal behavior among 20 male prisoners (aged 2040) in Kerala. Using semi-structured interviews, thematic analysis revealed seven key themes: family dysfunction, emotional struggle, abuse, economic struggle, peer pressure, coping mechanisms, and sensation seeking. Findings showed that family dysfunction creates baseline trauma, fostering emotional voids and maladaptive coping. The study emphasizes the interconnectedness of multiple adversities in shaping criminality. It highlights the need for early interventions addressing trauma, emotional dysregulation, and unhealthy coping patterns through supportive networks to prevent criminal behavior later in life. 2025 Taylor & Francis Group, LLC. -
AI tools for enhancing student engagement
Artificial Intelligence (AI) is revolutionizing the learning environment with adaptive technologies that offer new possibilities to engage, support, and empower learners. Throughout this chapter, we examine how AI technologies are transforming student engagement from the past to enable more personalized, responsive, and inclusive learning environments. From intelligent tutoring systems and adaptive learning systems to chatbots, game- based learning, and predictive analytics, AI offers teachers more and more tools to make behavioral, cognitive, and emotional connections with learners. Based on actual case studies of K- 12 and higher education, including DreamBox Learning and Civitas Learning, the chapter discusses real- world success with respectful consideration of the ethical, technical, and social issues of AI deployment. Issues from data privacy through algorithmic bias and student agency protection are discussed in detail. In the future, the chapter discusses briefly trends such as affective computing, AI- powered AR/VR environments, and human- AI collaboration construction for education's future. Rather than recommending AI as a replacement for teachers, the chapter argues for an equitable partnership-where AI as a system itself can be an effective collaborator to human teachers, enhancing their capacity to create rich learning environments. In the end, the chapter is appealing for an intentional, ethical, and equitable stance in adopting AI, so technology can be used in the name of education not only by facilitating engagement, but also in safeguarding human dignity, equity, and creativity. 2026, IGI Global Scientific Publishing. All rights reserved. -
AI and Multimedia Integration for Smart Mining and Renewable Energy Sustainability
This chapter focuses on how Artificial Intelligence (AI) and multimedia technologies are used to encourage sustainable smart mining and renewable energy optimization. AI boosts the accuracy in planning energy, smart grid use and supporting the management of demand, which saves money. The use of AI, predictive maintenance, geospatial analytics, and real- time monitoring in mining ensures optimisation of resource extraction and insignificant impacts on the environment. The research is powered by the international case studies and the initiatives of the private sector and points out the transformational impact AI can and is making in the sphere of operational efficiencies and sustainable industrial development in the spheres of energy and mining industries. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Global policies and legal frameworks for sustainable internet of vehicles
The Operational vehicles utilize vehicular networks which work through Internet of Vehicles to reach better safety results and enhanced traffic outcomes and environmental benefits in real-time conditions. Multiple barriers restrict implementation worldwide because different jurisdictions maintain different rules about privacy regulations and security standards along with sustainability boundaries. This paper examines the EU GDPR alongside the California CCPA along with the Indian FAME scheme and new data protection laws and Singapore Smart Mobility 2030 and Germany's EU Aligned frameworks. Different governance standards prevent organizational systems from integrating with each other resulting in difficulties during deployment procedures. The proposal establishes environmentally friendly and accessible IoV systems while meeting transport environment regulatory standards through combined implementation of privacy-by-design principles and cybersecurity protocols and standardized protocols. 2025, IGI Global Scientific Publishing. All rights reserved. -
Navigating the complex terrain of medical big data: A synthesis of data security and legal frameworks
This paper will focus on medical big data, in terms of the detail of legal frameworks of medical big data in terms of the significance of data breach incidents such as the Anthem as well as WannaCry ransomware attacks as key focal points for urgent need in toughen data security compliance with legal and ethical norms. Amongst key regulations, we analyze HIPAA, GDPR along with an impending India regulation Digital Personal Data Protection Act that will hold similar strict non-compliance penalties. Issues such as privacy, informed consent and algorithmic bias in healthcare data-managed are also covered. It helps support the usage of current technologies like blockchain and zero trust architecture to enhance data authenticity and trust. Finally, a harmonized legal, technical and ethical approach is proposed to improve global healthcare systems in view of mitigating security threats and assuring the secure, ethical use of medical big data for the best possible global healthcare outcomes. 2025, IGI Global Scientific Publishing. -
Impact of Homophily on Patient Empowerment: A Study of Online Patient Support Groups
Internet facility has led to emergence of patient support groups. These have gained prominence as these fulfils important benefits to patients. One such benefit is patient empowerment. These online groups provide opportunity to patients to interact with similar ailments and predicaments and who can understand the pain and discomfort felt by the patient. This provides validation for the patient and patients experiences. How does this homophily impacts patient empowerment? This question has been explored in this study. The methodology is based on an online survey of patients visiting such online platforms. In all 701 patients provided the data. Independent variable (homophily) and dependent variable (patient empowerment) have been measured using a 7-point Likert scale. Findings provide that both are weakly correlated, but this correlation is significant. Regression analysis led to a regression model that is fit statistically. This provides basis to encourage patients to visit online support groups. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Gucchi (Morchella esculenta)
This chapter focuses on Morchella esculenta as a nutraceutical and functional food, its habit, habitat, general characteristics, availability, biologically active compounds present and pharmacological and medicinal value. Mushrooms are spore-bearing fleshy fruiting bodies of fungus often present above the ground. Greeks and Romans included mushrooms in their diet. Romans considered mushrooms as the food of supernatural beings, despite the Chinese contemplating them as the elixir of the human being. Functional foods that are prepared from morel mushrooms are of high medicinal properties. The production of M. esculenta worldwide is 1.5 million tonnes of fresh weight and 150 tonnes of dry weight. India and Pakistan are the major morel-producing countries and each country has about 50 tonnes of dry morels. The pharmacological properties of Morchella species show its use in Chinese traditional medicine since 2, 000 years and in Malaysia and Japan to cure several diseases. 2023 Deepu Pandita and Anu Pandita. -
Hybrid Convolutional Neural Network and Extreme Learning Machine for Kidney Stone Detection
When it comes to diagnosing structural abnormalities including cysts, stones, cancer, congenital malformations, swelling, blocking of urine flow, etc., ultrasound imaging plays a key role in the medical sector. Kidney detection is tough due to the presence of speckle noise and low contrast in ultrasound pictures. This study presents the design and implementation of a system for extracting kidney structures from ultrasound pictures for use in medical procedures such as punctures. To begin, a restored input image is used as a starting point. After that, a Gabor filter is used to lessen the impact of the speckle noise and refine the final image. Improving image quality with histogram equalization. Cell segmentation and area based segmentation were chosen as the two segmentation methods to compare in this investigation. When extracting renal regions, the region-based segmentation is applied to obtain optimal results. Finally, this study refines the segmentation and clip off just the kidney area and training the model by using CNN-ELM model. This method produces an accuracy of about 98.5%, which outperforms CNN and ELM models. 2023 IEEE. -
Phishing attack detection using Machine Learning
Phishing is a type of digital assault, which adversely affects people where the client is coordinated to counterfeit sites and hoodwinked to screen their touchy and private data which integrates watchwords of records, monetary data, ATM pin-card data, etc. Recently safeguarding touchy records, it's fragile to cover yourself from malware or web phishing. AI is an investigation of information examination and logical investigation of calculations has demonstrated outcomes. Contradicting phishing sprinters with remarkable perception and felonious outcomes comparable as care shops, and custom against phishing approaches. This paper examines the association of Machine Literacy routes in identifying phishing assaults and records their advantages and drawbacks. There are countless Machine Learning calculations that have been dug to proclaim the relevant decision that act as against phishing apparatuses. We made a phishing section framework that extracts capacities that are expected to descry phishing. We likewise utilize numeric outline, as well as an overall investigation of customary Machine Learning methodologies comparable as Decision Tree, Random Forest, Multi-layer Perceptron's, XG Boost Classifier, SVM, Light BGM Classifier, Cat Boost Classifier, and covering grounded highlights choice, which contains the metadata of URLs and assists with deciding if a site is licit or not. 2022 The Authors -
An Enhanced Pathfinder Algorithm for Optimal Integration of Solar Photovoltaics and Rapid Charging Stations in Low-Voltage Radial Feeders
Most low-voltage (LV) feeders have large distribution losses, poor voltage profiles, and inadequate voltage stability margins owing to their radial construction and high R/X ratio branches, and they may not be able to handle substantial solar photovoltaics (SPVs) and EV penetration. Thus, optimal integration of SPVs and rapid charging stations (RCSs) can solve this problem. This paper offers an extended pathfinder algorithm (EPFA) with guiding elements and three followers' life lifestyle procedures based on animal foraging, exploitation, and killing. First, the EV load penetration was used to evaluate the LV feeder performance. Subsequently, the required RCSs and SPVs were appropriately integrated to match the EV load penetration and optimise feeder performance. An Indian 85-bus real-time system was used for simulations. The losses and GHG emissions increased by 150% and 80%, respectively, without the SPVs and RCS for zero-to-full EV load penetration. RCSs allocation alone reduced the losses by 40.1%, whereas simultaneous SPVs and RCSs allocation reduced the losses by 66%. However, the GHG emissions decreased by 13.7% and 54.33%, respectively. This study shows that SPVs and RCS can enhance the LV feeder performance both technically and environmentally. In contrast, EPFA outperformed the other algorithms in terms of the global solution and convergence time. The Author(s). -
Dynamic optimal network reconfiguration under photovoltaic generation and electric vehicle fleet load variability using self-adaptive butterfly optimization algorithm
Currently, electrical distribution networks (EDNs) have used modern technologies to operate and serve many types of consumers such as renewable energy, energy storage systems, electric vehicles, and demand response programs. Due to the variability and unpredictability of these technologies, all these technologies have brought various challenges to the operation and control of EDNs. In this case, in order to operate effectively, it is inevitable that effective power redistribution is required in the entire network. In this paper, a multi-objective based dynamic optimal network reconfiguration (DONR) problem is formulated using power loss and voltage deviation index considering the hourly variation of load, photovoltaic (PV) power, and electric vehicle (EV) fleet load in the network. This paper introduces recently introduced meta-heuristic butterfly optimization algorithm (BOA) and it's improve variant of self-adaptive method (SABOA) for solving the DONR problem. The simulation study of IEEE 33-bus EDN under different conditions has proved the effectiveness of DONR, and its adoptability for real-time applications. In addition, by comparing different performance indicators (such as mean, standard deviation, variance, and average calculation time) of 50 independently run simulations, the efficiency of SABOA can be evaluated compared with other heuristic methods (HMs). Comparative studies show that SABOA is better than PSO, TLBO, CSA and FPA in the frequent occurrence of global optimal values. 2021 Walter de Gruyter GmbH, Berlin/Boston 2021. -
Self-adaptive Butterfly Optimization for Simultaneous Optimal Integration of Electric Vehicle Fleets and Renewable Distribution Generation
Fuel prices and environmental concerns have prompted an increase in the use of electric vehicle (EV) technology in recent years. Charging stations (CSs) are a great way to support this shift to sustainability. This has increased the demand for EV charging on electrical distribution networks (EDNs). However, optimal EV charging stations along with renewable energy sources (RES) integration can maintain EDN performance. This paper proposes a novel hybrid approach based on self-adaptive butterfly optimization algorithm (SABOA) for optimal integration of EV CSs and RES problems under various EV load growth scenarios. A multi-objective function is created from distribution losses, GHG emissions, and VSI. The ideal locations for CSs and RES are found using SABOA while minimizing the proposed multi-objective function. The simulation results on IEEE 33-bus EDN validate the suggested technique's superiority in terms of global optima. This type of hybrid strategy is required for optimal real-time integration of EV CSs and RES, taking into account emerging high EV load penetrations. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Butterfly Optimization Algorithm-Based Optimal Sizing and Integration of Photovoltaic System in Multi-lateral Distribution Network for Interoperability
In this paper, a new and simple nature-inspired meta-heuristic search algorithm, namely butterfly optimization algorithm (BOA), is proposed for solving the optimal location and sizing of solar photovoltaic (SPV) system. An objective function for distribution loss minimization is formulated and minimized via optimally allocating the SPV system on themain feeder. At the first stage, the computational efficiency of BOA is compared with various other similar works and highlights its superiority in terms of global solution. In thesecond stage, the interoperability requirement of SPV system while determining the location and size of SPV system among multiple laterals in a distribution system is solved without compromises in radiality constraint. Various case studies on standard IEEE 33-bus system have shown the effectiveness of proposed concept of interline-photovoltaic (I-PV) system in improving the distribution system performance in terms of reduced losses and improved voltage profile via redistributing the feeder power flows effectively. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Caste, Cricket, and Community Fraternal Intersections in Blue Star
[No abstract available] -
Experimental Study on Warm Mix Asphalt Binders with a Focus on Rheological Performance
Warm mix asphalt (WMA) mixtures have been increasingly used in road construction due to their energy saving and environmental protect benefits. However, unsuitable additives were often adopted due to their variability and it often led to poorer quality of asphalt pavements. In this study, nine asphalt samples from two categories of warm mix additives, including six organic and three chemical additives, were prepared. The rotational viscosity test, temperature sweep test, linear amplitude sweep test (LAS), and bending beam rheometer (BBR) test were employed to comprehensively evaluate the effect of warm mix additives on the viscosity-reduction effect, high-temperature performance, fatigue resistance, and low-temperature performance of WMA, respectively. The results showed that the viscosity- reduction effect of organic additives was more significant compared to chemical additives. Besides, organic additives were generally favorable to the high-temperature and fatigue resistance of asphalt binders, but their effects on the low-temperature performance of asphalt binders were highly variable. Chemical additives had a limited effect on the high-temperature and fatigue resistance of asphalt binders. Meanwhile, the chemical additives have a marginally positive and stable impact on the low-temperature performance of asphalt binders. The findings provided a comprehensive basis for the selection and application of warm mix additives. The Author(s), under exclusive licence to Chinese Society of Pavement Engineering 2025. -
A study of consumers' attitude towards online private label brands using the Tri - Component model
Online private label products seem to be a promising and profitable deal for the Indian online retailers. The purpose of this paper was to understand the consumers' attitude and buying behaviour towards online private label brands. For this purpose, we empirically tested a model comprising of variables such as cognitive, affective, behavioural, purchase intention, and actual buying behaviour. Data were gathered by using a schedule. A sample of 400 respondents was gathered, and the hypotheses were tested by performing structural equation modelling. The findings highlighted that the cognitive, affective, and behavioural factors of attitude influenced each other strongly as well as the purchase intention. In addition, the results obtained revealed that purchase intention led to the buying of online private label brands. It is expected that the findings of this study will enable the marketers of online private label brands to be more informed about the consumers' attitude formation process. Furthermore, it will help them to understand the areas related to private label brands, which need their attention. 1964-2018 Associated Management Consultants.