Browse Items (16481 total)
Sort by:
-
Situating censorship: A study of the politics of state and self in literary translations in Iran /
A nation’s culture flourishes by interacting with other cultures” (Razmjou). Cultural variety not only enriches our knowledge, but also acts as a guide towards the growth of a nation. It gives an insight about the basic human right practices of different cultures. The standard of culture of any particular nation can be gauged through various tools, but importance is given to literature, as it acts as a barometer to measure the cultural growth of the nation. To interpret any culture it is important to understand the beginnings of that particular culture and make an in-depth study of the progress of its civilization. The cultural evolution of any place is continuous and is a combination of many factors like geographic location, weather conditions prevalent, suitable food crops grown, its political policies, religious influences, its history and its present circumstances. The above factors directly or indirectly become responsible to blend and give shape to a culture. -
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. -
Skincare Products as Sources of Mutagenic Exposure to Infants: An Imperative Study Using a Battery of Microbial Bioassays
Infant skin is highly absorptive and sensitive to exposure from external agents (microbes, toxicants, heat, cold, etc.). Many specialized infant skincare products are currently commercially available. Although the manufacturers claim that their products are mild enough to suit the infant skin, these products need to be studied for their safety. Using animal models to examine the safety of the ever-increasing number of skincare products is not economically or logistically feasible. To overcome this problem, we suggest using a battery of microbial bioassays as a robust system for monitoring the mutagenic potential of skincare products. We picked popular infant skincare products from the Indian market and assessed them by using a battery of three microbial mutagenicity bioassays. Most of them showed significant and reproducible mutagenic potential. Our study results raise concerns about regular use of infant products and emphasize the need to enforce strict regulations for the manufacturing and safety assessment of infant products. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature. -
Sliced Bidirectional Gated Recurrent Unit with Sparrow Search Optimizer for Detecting the Attacks in IoT Environment
In an era characterized by pervasive interconnectivity facilitated by the widespread adoption of Internet of Things (IoT) devices across diverse domains, novel cybersecurity challenges have emerged, underscoring the imperative for robust intrusion detection systems. Conventional security frameworks, constrained by their closed-system architecture, struggle to adapt to the dynamic threat landscape marked by the continual emergence of unprecedented attacks. This paper presents a methodology aimed at mitigating the open set recognition (OSR) challenge within IoT-specific Network Intrusion Detection Schemes (NIDS). Leveraging image-based representations of data, our approach focuses on extracting geographical traffic patterns. We observe that the Recurrent Neural Network exhibits suboptimal classification accuracy and lacks parallelizability for attack analysis tasks. Our investigation concludes that the Sparrow Search Optimization Algorithm (SSOA) serves as a foundation for constructing an effective assault classification model. This research contributes significantly to the field of network security by emphasizing the importance and ramifications of meticulous hyperparameter tuning. It represents a critical stride toward developing IDSs capable of effectively navigating the evolving cyber threat landscape. In the experimental analysis of proposed model reached the accuracy and 0.963% respectively. 2024 IEEE. -
Slow Violence in Vikram Chandras Sacred Games: An Ecocritical Reading
This article gives insight into the ways in which enforcement and institutional vigilante activities portrayed in Vikram Chandras Sacred Games foreshadow the urban thicket of garbage dump yards and slum dwellings. The text will be analyzed from an ecocritical perspective to establish aspects of slow violence and its explicit and implicit results. Chandras plotline, regarding several entangled human tragedies against the background of refuse, urges a study of the novel through the lens of waste studies. However, he fails to address the reasons for the characters opinion of Mumbai being uninhabitable and infamous for treating human life as expendable. The novelist also seems to normalize the issues of inequalities in waste management and justifies the anthropocentric utilitarian perception of resources. The depictions of Mumbai gang wars against a disturbingly overlooked state of dilapidated lives and misplaced ideologies mention waste as being both created and ignored. Such representation also compels a close reading of consumerism and criminal aspiration. 2023, University of Zadar. All rights reserved. -
SLV voltage regulated DC/DC converter /
Patent Number: 202141046671, Applicant: Radhika S.
The requirement is to develop a DC/DC converter for DC microgrid and charging electric vehicle batteries. The main issue in the DC microgrid is the voltage regulation and it is necessary to implement a regulated DC/DC converter and this can be achieved by the combination of voltage lift and boost circuit giving a regulated DC output voltage of 203.1V DC at 0.4 duty ratio by using LTspice XVII software.