Browse Items (14421 total)
Sort by:
-
Single Port Multimode Reconfigurable UWB-NB Antenna for Cognitive Radio Applications
In this paper, a compact, single port, multimode reconfigurable UWB-NB antenna with a novel feeding network is presented. The proposed antenna consists of a pentagonal-shaped monopole radiator, a beveled-shaped partial defected ground plane with a rectangular slot, and a reconfigurable bypass feeding network. The antenna realizes a wideband frequency range from 2.4 to 18 GHz and four narrow band frequency ranges, 5.3 to 6.8 GHz, 6.0 to 7.6 GHz, 7.2 to 8.8 GHz and 8.4 to 11.4 GHz. The antenna provides an omnidirectional radiation pattern with gain from 2.2 to 6.2 dBi maximum at 12 GHz and voltage standing wave ratio (VSWR) ranges from 1 to 2. The fabricated antenna has an overall dimension of 181.6 mm3. Sensing and tuning ranges of the fabricated antenna shows good agreement with the simulation results. The proposed antenna has an advantage of simple design, low profile, single port excitation and omnidirectional radiation pattern making it suitable for applications such as handheld mobile cognitive radio systems. 2022 SBMO/SBMag -
Single-monomer dual templated MIP based electrochemical sensor for tartrazine and brilliant blue FCF
In this study, a dual-templated molecularly imprinted polymer-based electrochemical sensor was developed for the simultaneous analysis of two food additive dyes, brilliant blue FCF and tartrazine. Using a 3-aminophenyl boronic acid (3-APBA) monomer and the dual templates of brilliant blue FCF (BB) and tartrazine (TZ), the molecularly imprinted polymer (MIP) layer was electropolymerized on the carbon fibre paper (CFP) electrode. By using BB and TZ as template molecules along the electro-polymerization of 3-APBA, then removing both template molecules, the MIP film was generated on the surface of the CFP electrode. Due to the high surface area provided by modification, several complementary binding sites for template molecules are formed on the surface of the MIP sensor during this process of sensor fabrication. On the MIP/CFP electrode, the electrochemical behavior of BB and TZ was assessed. The monomer/template ratio, pH values, and influencing parameters like the electro-polymerization scanning cycles were all optimized. This sensor was applied to detect brilliant blue FCF and tartrazine in beverage and food samples using MIPAPBA/CFP electrode. 2023 -
Single-Stage Bidirectional Three-Level AC/DC LLC Resonant Converter with High Power Factor
The increasing demand for efficient and high-performance power converters in electric vehicle technology and renewable energy integration has brought attention to LLC resonant converters due to their advantages in soft switching, inherent short circuit and open circuit protection, and high efficiency. These converters are particularly well-suited for high-frequency operation, making them ideal for electric vehicle battery charging and other power conversion tasks. However, when integrated with a front-end boost power factor correction (PFC) stage in AC-DC applications, challenges arise in maintaining power balance during transients, leading to voltage fluctuations and potential operational instability. Moreover, light load conditions can result in excessive switching frequencies, causing elevated switching losses and control difficulties. Additionally, traditional LLC resonant converters face limitations related to high voltage stress on switches, which affects device reliability and overall converter performance. To address these issues, researchers have explored the use of multilevel inverters, but they introduce complexity and cost. In this context, this paper proposes a novel single-stage, three-level bidirectional AC-DC LLC-based resonant converter with features like zero voltage switching and duty ratio control for output voltage regulation. The converter achieves a unity displacement power factor naturally through discontinuous conduction mode. Simulation results demonstrate the converter's effectiveness of the proposed topology. The proposed converter offers a promising solution for Electric vehicle chargers, combining unity power factor operation and efficient bidirectional power flow control in a single topology. 2024 IEEE. -
Single-use Plastic Packaging and Food and Beverage industry's take on it
Micro-plastics created by the gradual breakdown of SUP in oceans have recently been consumed by marine organisms, including fish, shellfish, etc. It is causing significant disturbance to marine life. The environment is littered with food packing. Snack food packaging is a great example of a long-standing, aesthetically obnoxious form of pollution. The majority of SUPs, especially perishable products, wind up in landfills within months of purchase.This is due to a rise in on-the-go food and beverage consumption, fueling the proliferation of single-use plastic packaging. The lack of dumpsters in some areas might contribute to an increase in littering. While the majority of food packaging plastics end up in the trash, municipal waste, landfills, and even the seas, a tiny fraction can be recycled. The reason for this is that poor countries have a prevalent culture of human waste. The Electrochemical Society -
Sinking houseboats and swaying home stays: community resilience and local impacts of COVID-19 in managing tourism crisis in Kerala
Purpose: The tourism sector of the state of Kerala in India is highly vulnerable and has been extensively impacted by the global pandemic disaster. This paper aims to analyze the impact of COVID-19 (Corona virus pandemic) on houseboat operators and homestay managers. Design/methodology/approach: This paper indicates a multi-stakeholder assessment method to examine various pandemic disaster facets through a structured discussion with different destination stakeholders. This study examines qualitative data collected through semi-structured interviews from homestay owners, houseboat operators and government designators in Kerala. This study proposes a conceptual community resilience competency framework that could facilitate speedy crisis management responses. In this study, the sample comprises of nine respondents who play a pivotal role in the travel business, comprising the public sector, private sector, NGO's and community leaders. Findings: The qualitative findings identify Indias and the state of Kerala's roles in handling crisis management scenarios over internal strategies and strategy formulation. The results indicate that the supplementary industry practitioners explore tactical and strategic management initiatives to sustain their businesses. The dynamics of stakeholder engagement adopted by the state is given prominence. Originality/value: This study suggests mechanisms to re-establish the brand image and the possible strategies and suggestions that could help in the survival of the Kerala tourism industry in the post-disaster period. The new normal has been substantiated in the study by incorporating strategies and precautionary methods adopted by the homestay and houseboat operators so as to address the guests' safety concerns. 2021, International Tourism Studies Association. -
Siri the Healing Mother: Relational Dynamics Between Mother and Child in a Matrilineal Society
The Siri cult revolves around an oral tradition from Tulunadu in Dakshina Kannada (South Canara), India, featuring a story that unfolds over 15,683 lines. It tells the myth of Siri, a remarkable woman, and her lineage. During the famous Siri Jatre (which means festival), women are possessed by the spirits of Siri and her descendants, such as Abbaga and Daraga. This article explores the ritual space of the Siri cult as a transformative arena for women, where the boundaries between myth and reality blur, allowing for collective healing and psychic reintegration. The ritual performances, particularly during the Siri festival, facilitate a trance-like state in which women embody Siri and her struggles, experiencing emotional release. Through communal participation and embodied identification with Siri, women reclaim their repressed emotions, anxieties, and desires, forging new alternative narratives of motherhood, femininity, and divine womanhood. Importantly, Siris divine presence offers women a symbolic anchora figure who legitimises their grief and challenges male-dominated ideals for women to be obedient, nurturing, and submissive. Taking a psychoanalytical lens, this article examines the ritual space of the Siri cult through the framework of object relations theory to explore the psychic processes. The rituals allow women to externalise their inner conflicts and repressed desires, processing their grief and trauma through symbolic enactment. By situating the Siri cult within a psychoanalytical framework, the study reveals how the myth of Siri functions as a transformative object, allowing women to bridge their individual suffering with communal strength, ultimately achieving a sense of psychic integration and empowerment. 2025 Department of Psychology, University of Allahabad -
Sixth-Generation (6G) Mobile Cloud Security and Privacy Risks for AI System Using High-Performance Computing Implementation
The exchange of information from one person to another is called communication. Telecommunication makes it possible with electronic devices and their tools. The scientist Alexander Graham Bell has invented the basic telephone in 1876 in the USA. Telephones now have the new format in the form of mobile phones, which are the primary media for communicating and transmitting data. We are using 5th-generation mobile network standards. Still, there are some requirements for the users that are believed to be solved in the 6th-generation mobile network standards. By 2030, all of the people would be using 6G. The computing model in the cloud is not dependent on either the location or any specific device that would provide the service. It is an on-demand computational service-oriented mechanism. Combining these two technologies as mobile cloud computing provides customized options with more flexible implementations. Artificial intelligence is being used in devices in many fields. AI can be used in mobile network services (MNS) to provide more reliable and customized services to the users, such as network operation monitoring, network operation management, fraud detection, and reduction in mobile transactions and security to the cyber devices. Combining cloud with AI in mobile network services in the 6th generation would improve human beings' lives, such as zero road accidents, advanced level special health care, and zero crime rates in society. However, the most vital needs for sixth-generation standards are the capability to manage large volumes of records and excessive-statistics-fee connectivity in step with gadgets. The sixth-generation mobile network is under development. This generation has many exciting features. Security is the central issue that needs to be sorted out using appropriate forensic mechanisms. There is a need to approach high-performance computing for improved services to the end-user. Considering three-dimensional research methodologies (technical dimension, organizational dimension, and applications hosted on the cloud) in a high-performance computing environment leads to two different cases such as real-time stream processing and remote desktop connection and performance test. By 'narrowing the targeted worldwide audience with a wide range of experiential opportunities,' this paper is aimed at delivering dynamic and varied resource allocation for reliable and justified on-demand services. 2022 Srinivasa Rao Gundu et al. -
Size effect in market-wide liquidity commonality: Evidence from the indian stock market
Liquidity commonality and the co-movements in trading costs related to such commonality have remarkable implications in market microstructure. Analyzing and identifying such commonality will enable the investor and policy maker to discover evidence regarding the inventory risks and asymmetric information influencing individual securities' liquidity. Thus, this study aims at documenting the liquidity commonality and measuring its extent in the Indian stock market. Employing fourteen liquidity measures attributed to the cost, quantity, time, and multidimensional aspects of liquidity, it empirically proves the existence of co-movements among market-wide liquidity and the individual securities' liquidity. The study also shows the presence of a size effect in liquidity commonality in Indian stock market. It is found that the slope coefficient indicating the interface between market-wide liquidity and individual securities' liquidity generally increases with size. Copyright 2019 Namitha K. Cheriyan, Daniel Lazar. -
Size Tuning, Phase Stabilization, and Anticancer Efficacy of Amorphous Selenium Nanoparticles: Effect of Ion-Pair Interaction, ?OH Functionalization, and Reuse of RTILs as Host Matrix
Se nanoparticles (NPs) of predominantly amorphous phase (?-Se) have been prepared in room-temperature ionic liquids (RTILs). The effects of ion-pair combination and ?OH functionalization of RTILs on the size and phase stability of Se NPs were investigated. The RTILs used were 1-ethyl-3-methyl imidazolium boron tetrafluoride ([EMIM][BF4]), 1-(2-hydroxyethyl)-3-methyl imidazolium boron tetrafluoride ([EOHMIM][BF4]), and 1-ethyl-3-methyl imidazolium methane sulfonate ([EMIM][MS]). The size of Se NPs@[EOHMIM][BF4] was found to be the smallest (?32 nm), followed by Se NPs@[EMIM][BF4] (?57 nm) and Se NPs@[EMIM][MS] (?60 nm), respectively. Interestingly, the stability studies revealed minimal size variations for Se NPs@[EMIM][MS], followed by Se NPs@[EOHMIM][BF4] and Se NPs@[EMIM][BF4], respectively. The observed trends could be correlated with the strength of interionic interactions in the respective RTILs, as well as their packing order (density). Importantly, the RTILs played the role of a solvent, a stabilizer, and an in situ source of reducing species. Pulse radiolysis study revealed imidazolium-originated radical species-driven formation of Se NPs. Further, anticancer efficacy studies demonstrated the role of NP size, wherein Se NPs@[EOHMIM][BF4] exhibited the highest cancer cell killing, followed by Se NPs@[EMIM][BF4] and Se NPs@[EMIM][MS]. Another significant highlight of this work is the reuse of the spent RTILs for the synthesis of the next batch of Se NPs. 2021 American Chemical Society -
Size-dependent analysis of surface wave in irregular fractured porous seabed subjected to fractional-order derivative
This study focuses on the investigation of the dispersive and damping characteristics of surface waves through an irregular boundary of ocean bed composed of a fluid-saturated dual porosity/dual permeability material. The nonlocal fluid-saturated dual porosity/dual permeability layer (NFSDP2L) is confined by a nonlocal viscous liquid layer (NVLL) and a nonlocal viscous sandy substrate (NVSS) having fractional viscoelastic properties. The governing equations for the proposed model are derived using Eringens nonlocal theory. The complex frequency relation is obtained by applying the variable separation technique and enforcing appropriate boundary conditions. By dissociating the frequency relation into real (dispersion equation) and imaginary (attenuation equation) parts, graphs are generated to illustrate the influence of several key parameters., viz. nonlocality, porosity, sandiness, fractional-order, fluctuation, flatness, and position on the fundamental and higher modes of propagating waves. The effects of various parameters are also depicted through the graphical illustration of shear wave speed in NFSDP2L and NVSS. Furthermore, the surface response of shear stress against depth within the layered structure has been graphically illustrated. The validity of our mathematical model has been assessed by examining multiple relevant scenarios. 2025 Taylor & Francis Group, LLC. -
Size-dependent analysis of surface wave in irregular fractured porous seabed subjected to fractional-order derivative
This study focuses on the investigation of the dispersive and damping characteristics of surface waves through an irregular boundary of ocean bed composed of a fluid-saturated dual porosity/dual permeability material. The nonlocal fluid-saturated dual porosity/dual permeability layer (NFSDP2L) is confined by a nonlocal viscous liquid layer (NVLL) and a nonlocal viscous sandy substrate (NVSS) having fractional viscoelastic properties. The governing equations for the proposed model are derived using Eringens nonlocal theory. The complex frequency relation is obtained by applying the variable separation technique and enforcing appropriate boundary conditions. By dissociating the frequency relation into real (dispersion equation) and imaginary (attenuation equation) parts, graphs are generated to illustrate the influence of several key parameters., viz. nonlocality, porosity, sandiness, fractional-order, fluctuation, flatness, and position on the fundamental and higher modes of propagating waves. The effects of various parameters are also depicted through the graphical illustration of shear wave speed in NFSDP2L and NVSS. Furthermore, the surface response of shear stress against depth within the layered structure has been graphically illustrated. The validity of our mathematical model has been assessed by examining multiple relevant scenarios. 2025 Taylor & Francis Group, LLC. -
Size, Value Effects and the Explanatory Power of Pricing Models: Evidence from BSE listed Indian Industries
The firm size and value anomalies are the global-level counterpart for explaining the cross-sectional variations of equity returns. This paper aims to examine the size, value effects and explanatory power of three well-known pricing models - CAPM, three-and five-factor- across and within 15 Indian industries. The study considers all firms listed on Indian largest stock exchange, BSE (Bombay stock exchange), between 1999-2021 by developing portfolios using firm size/value, size/investment and size/profitability risk characteristics. The study employs both univariate and multivariate methods, including time series, GRS statistics, and cross-sectional models within and across industries portfolios. Results indicated that size and value effects exist in almost all industries, presenting that size and value anomalies are the most prominent determinants for industry-level equity returns. In addition, the profitability and investment effects were also investigated; however, the results are mixed from industry to industry. In the case of the explanatory power of pricing models, the five-factor performs much better within and across industry portfolios than other pricing models; however, the models' effectiveness varies by industry. We also reported that investors who seek to allocate funds within and across industries tend to be expected reasonably stable returns and conceivably predictable; the findings of this study contribute to the existing literature on asset pricing and portfolio management in emerging markets. The Author(s) 2022. -
Skewed Food Policies, Distorted Inter-crop Parity, and Nutri-cereal Farmers - An Empirical Analysis
Farmer profitability, cost of food production, and associated issues of nutri-cereals are analysed by leveraging a large database spanning a 35-year period. The skewed food policies being followed in India are highlighted here. An unacceptably high distortion in inter-crop parity was found, which led to loss of profitability, increased costs, and lower prices for the nutri-cereals. The policymakers must take corrective measures in several aspects, including technologies, prices, input provision, processing, storage, and distributional policies to promote the production and consumption of nutri-cereals in India. 2023 Economic and Political Weekly. All rights reserved. -
Skilful Leadership and Management: The Importance of Emotional Intelligence
Emotional intelligence (EI) has become more important in the study of organisational behaviour, particularly in relation to management and effective leadership. EI is the ability to identify, understand, and control ones own emotions as well as those of others. Those with high EI find it easier to navigate complex social interactions, build strong relationships, and resolve conflicts. EI is the ability to recognise, manage, and evaluate emotions. The ability to express ones emotions in a healthy way and to empathise with others is a sign of great emotional intelligence in a leader, and it will enhance both performance and workplace relationships. The study employed a range of machine learning (ML) methods, such as ANN, BRDT, Naive Bayes, and Random Forest, to predict EI based on behaviour credits. ML approaches have become more and more common. The results showed that the BRDT has the accuracy of 98.3 which is higher in all other machine learning models and gives better results. Seven behavioural attributes and seven additional individual attributes made up the prediction dataset. 2024 selection and editorial matter, Prof. (Dr.) Dorota Jelonek, Prof. (Dr.) Narendra Kumar, Prof. (Dr.) Mamta Chahar, Prof. (Dr.) Rusudan Kinkladze and Prof. (Dr.) Lilla Knop; individual chapters, the contributors. -
Skill Enhancement is an Essential Aspect of the Emerging Curriculum to Resolve the Talent Crunch and Foster Entrepreneurship Among Young Graduates
Human capital management is one of the most important aspects of the booming economies in the current scenario. However, a problem faced over the last decade is the lack of skilful employees required by the industries in the changing market trends. The World is rapidly progressing with innovation and technological advancements from time to time. Our young graduates need to gear up and gain momentum to match the ever-changing needs of the new business models. The biggest challenge in many countries is recruiting skilful resources, resulting in a recent Talent crunch and another important problem is a shortage of entrepreneurs. When these issues are discussed, it is very important to bridge the gap and make the path to success clear by transforming human capital into skilful capital, which could be achieved by redesigning the curriculum and tailoring it to integrate academic knowledge with industry interface. This paper is an attempt to highlight the importance of Curriculum design in improving the skills for employability and entrepreneurship among students to bridge the gap between the industry, job seekers and the role of educational institutions in building an individual's employability and growth, as they are the prime sources of skills and knowledge. 2025 selection and editorial matter, Kennedy Andrew Thomas, Joseph Chacko Chennattuserry and Joseph Varghese Kureethara; individual chapters, the contributors. -
Skill sets required to meet a human-centered Industry 5.0: A systematic literature review and bibliometric analysis
The first industrial revolution, known as Industry 1.0, was primarily concerned with mechanical engineering and water and steam. Electric power systems and mass production assembly lines were established during the second industrial revolution (Industry 2.0). The third industrial revolution (Industry 3.0) was defined as automatic manufacturing and the incorporation of electronics, computers, and information technology into manufacturing. The fourth industrial revolution (Industry 4.0) is automating business operations and advancing manufacturing to a level based on connected devices, smart factories, cyberphysical systems (CPS), and the internet of things (IoT), where machines will change how they interact with one another and carry out specific tasks. Industry 5.0, with all modern technologies, is aimed to be a harmonious balance between human and machine interaction, and has an emphasis on sustainable growth. The present study uses an interpretive-qualitative research method to review the skill sets required to meet a human-centered Industry 5.0. 2024, IGI Global. All rights reserved. -
Skin as Script Embodied Archives of Post-headhunting in Longwa, Nagaland
[No abstract available] -
Skin cancer classification using machine learning for dermoscopy image
Skin cancer is highly ambiguous and difficult to identify and cure in the last stage. To increase the survival rate, it is important to recognize the stages of skin cancer for effective treatment. The main aim of the paper is to classify the various stages of skin cancer using dermoscopy images from the data repository of ISIC and PH2. The data is pre -processed with the help of median filter and wiener filter for removing the noise. Segmentation is processed using Watershed and Morphological. After the segmentation, features were extracted using Grey Level Co-occurrence Matrix (GLCM), Color, Geometrical shapes in order to improve the accuracy of dermoscopy image. Finally, the dataset is classified with some popular methods like KNN with 89%, Ensemble with 84% and SVM works better than the other two methods by giving the highest accuracy of 92%. BEIESP. -
Skin cancer prediction using AI: A bibliometric analysis
Skin cancer is a major public health concern globally, with early detection being crucial for successful treatment and management. Artificial intelligence (AI) has emerged as a promising tool for aiding in the early detection of skin cancer [15, 19, 23, 41]. This paper conducts a literature review and bibliometric analysis to explore the current landscape of AI-based skin cancer prediction. This bibliometric analysis systematically examines the landscape of research on skin cancer prediction using AI. The aim of the study is to identify the research trends, keyword contributors, influential authors, and research hotspots [13, 31]. Through this bibliometric analysis, this study offers insights into the evolution of AI-based approaches for skin cancer prediction. By producing and analyzing bibliometric data from relevant scholarly publications, this study provides a comprehensive overview of the current state of research in this domain, informing future directions for advancing skin cancer prediction using AI technologies. 2025 Author(s). -
Skin lesion classification using decision trees and random forest algorithms
Any superficial skin growth that does not resemble the surrounding area is referred to as skin lesion. It can occur in the form of mole, bump, cyst, rash or other changes that can be classified either as primary or secondary lesion. While primary skin lesions correspond to those changes in color or texture, secondary lesions occur as a primary lesion progression. Skin lesion image segmentation and classification at the early stages can help the patients recover through proper medication and treatment. Many algorithms for segmentation and classification are available in the literature but they all fail to extract lesion boundaries perfectly and classify them with more accuracy. To improve the reliability of the skin image segmentation and classification, we propose to use decision trees and random forest algorithms in this works and compare them with different data sets. The proposed method can generate high-resolution feature maps that can help to preserve the spatial details of the image. While tested against the ISIC 2017 and HAM10000 dataset, we found that the proposed method is more accurate as compared to the existing algorithms in this domain and is also very robust to artifacts or hair fibers present in the skin images. 2020, Springer-Verlag GmbH Germany, part of Springer Nature.