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Facile fabrication of 3D-?-Fe2O3@2D-g-C3N4 heterojunction composite materials: Effect of iron oxide loading on the electrochemical performance
Designing heterojunction nanocomposites is crucial for optimizing supercapacitor electrodes. This study addresses the challenge by introducing a facile synthesis method for creating 3D-?-Fe2O3@2D-g-C3N4 heterojunctions through a bulk carbon nitride-assisted hydrothermal process. During this process, the growth of ferric oxide particles coincides with the exfoliation and deposition of carbon nitride, leading to simultaneous structural changes in both iron oxide and carbon nitride phases. The resulting composite's properties strongly correlate with the iron oxide loading. Comprehensive characterization using XRD, FTIR, SEM-EDAX, XPS and TEM identified three distinct structures for ?-Fe2O3/g-C3N4 composites based on iron oxide loading: low, medium, and high. The medium-loaded sample demonstrated superior electrochemical performance, attributed to better interfacial contact and the formation of 3D-Fe2O3@2D-g-C3N4 heterojunctions. This composite, with an optimized 22 wt% iron oxide loading, exhibited a maximum specific capacitance of 925.1 Fg?1 at 5 mVs?1 and 498.6 Fg?1 at 6 Ag?1 in charge-discharge analysis, with stable performance over 2000 cycles. Overall, this research presents an enhanced hydrothermal method for facile preparation of effective ?-Fe2O3/g-C3N4 heterojunction materials. 2024 Elsevier B.V. -
Women's empowerment within the tourism industry: Risk assessment and mitigation strategies for solo women travellers
Travelling is essential for maintaining one's happiness and mental wellness. Tourism is a job providing industry and huge contributions to economic growth, and many studies have been undertaken to determine who is attracted to tourism. Surprisingly, women take a major stand in the tourism industry. The purpose of this study is to examinefemale solo travelers' risk assessment and their mitigation strategies by investigating online travel blogs. Therefore, the study aims at assessment of risk such as physical risk, destination-specific risk, and financial risk faced by solo women travellers by considering and analyz- ing online women travellers' blog narratives. These narratives from online travel blogs pertaining to Indian solo female travellers are considered in this study. Hence, this assessment gives an opportunity to know how to stay safe in uncertain situations and also mitigation strategies to stay alert. The result of the study indicates the various risks faced by solo female travel and mitigation strategies for promotion of more female travellers. 2023, IGI Global. All rights reserved. -
Impact of terminal group on azobenzene liquid crystal dimers for photo-responsive optical storage devices
Three new series of photo responsive dimers bearing different terminal functional groups (-CN, -COOEt, -OMe) and variable aliphatic spacers have been synthesized and investigated in detail. The molecular structures of the new materials were proved using different spectroscopic techniques and their liquid crystal self-assembly was characterized using differential scanning calorimetry (DSC), polarized light microscope (POM) and X-ray diffraction (XRD). Moreover, their photo switching behaviour was investigated in details in solution. The results revealed that, almost all members of the dimeric materials are mesomorphic exhibit either nematic or both smectic A and nematic phases. Under UV illumination the materials show interesting photo-switching properties, reaching a photo-stationary state in 40 s and a thermal back-relaxation time of approximately 35 h in solution. Finally, a fabricated device authenticates the potential of the reported materials for optical storage devices. 2023 Elsevier B.V. -
Ionic strength and phase systems influence nanotubular material functionality
We synthesized novel thiacyanine chromonic liquid crystals (CLCs) and structurally characterized using NMR and mass spectrometry. The impact of distinct substitution at the para position of aromatic counter anions, aliphatic counter ion chain length, and varied spacer parity of thiacyanine dyes on CLC formation is investigated. Liquid crystal properties of the synthesized dyes are characterized by polarizing optical microscopy (POM) and X-ray diffraction (XRD) studies. Dyes exhibit nematic (N), lamellar (L?), columnar rectangular (Colr), and columnar oblique (Colob) CLCs at different concentrations in the water. Electronic absorption spectra reveal Scheibe aggregation in all the dyes. Cylicvoltametry studies confirm redox behaviour in TC-1a and TC-5e dyes. Chromonic LCs hybrid nano-materials are synthesized using solgel method. Scanning electron microscopy employed to confirm nano tubular fiber structure of the hybrid nanomaterilals. 2024 Elsevier B.V. -
Sum Signed Graph
A sum signed graph S = (G, f, and#963;) is a signed graph of the underlying graph G where f : V (G) and#8722;and#8594; {1, 2, . . . , | V (G) |} is a bijective function and and#963; : E(G) and#8722;and#8594; {+, and#8722;} is newlinea mapping such that and#963;(uv) = +, whenever f(u) + f(v) and#8804; n and and#963;(uv) = and#8722;, whenever f(u) + f(v) gt n. The minimum number of negative and positive edges among all the sum signed labelings of G is known as rna and rna complement number respectively. The maximum number of positive edges among all the sum signed labelings of G is known as adhika number. The set X and#8838; V (G) is said to be a s - dominating of a signed graph whenever X is a dominating set and there exists exactly s number of negative edges between X and its complement. The minimum cardinality of such a dominating set over all signed graphs of the graph G is called an s - domination number. newlineIn the present study, we initiate the study of a new labeling in signed graphs namely, newlinesum signed labeling. The characteristics of sum signed graphs and the bound of rna number of in terms of the number of vertices in the underlying graph are explored by examining the rna number of different graphs. The properties of signed graphs such as negating and balancing is analyzed. The relation between rna number and rna complement number is established. The connection of sum signed labeling with parity signed labeling and cordial labeling is discussed. The absolute cordial condition for graphs satisfying sum signed labeling is examined. The concept of s - domination was also introduced during this period of study. The s domination in both the positive and negative homogeneous signed graph is investigated for each value of s. The properties of s domination in sum signed graphs are also analyzed. The s - domination number for specifc values of s is investigated for various graphs. The maximum value of s for a graph for which the s - domination will exist is discussed. -
Analytical modeling of reconfigurable transistors
A functionally enhanced transistor is a potential candidate for further advancing electronics and Moore's law beyond the classical scaling. This chapter discusses these kinds of multifunctional transistors called reconfigurable field-effect transistor (RFET) and reconfigurable tunnel field-effect transistor (RTFET). The RFET works on the principle of Schottky barrier tunneling, and the RTFET works on the principle of band-to-band tunneling. Both devices can be configured as an n-type and p-type device based on the biasing. This chapter explains the working and performance comparison of RFET and RTFET in detail with the help of technology computer-aided design (TCAD) simulations. Further, the potential and current models of a single-gated RFET and double-gated RTFET are presented in this chapter. The presented analytical models are compared and verified with TCAD simulations. The potential in the channel regions of RFET and RTFET is modeled by solving a two-dimensional (2D) Poisson's equation. Because the working principle of both devices is different, two different formulas are utilized for modeling the current in the device. The current model for the RFET is developed by integrating Landauer's formula, whereas the current model for RTFET is obtained by integrating band-to-band generation rate over the tunneling volume. The procedure, technique, and assumptions followed to obtain the potential and current models of RFET and RTFET are detailed in this chapter. 2022 selection and editorial matter, Ashish Raman, Deep Shekhar and Naveen Kumar; individual chapters, the contributors. -
An analytical model for a TFET with an n-doped channel operating in accumulation and inversion modes
The tunnel field-effect transistor (TFET) is an ambipolar device that conducts current with the channel in both accumulation and inversion modes. Analytical expressions for the channel potential and current in a TFET with an n-doped channel when operating in the accumulation and inversion modes are proposed herein. The potential model is derived by solving the two-dimensional (2D) Poisson equation using the superposition principle while considering the charges present in the channel due to electron or hole accumulation along with the depletion charges. An expression for the tunneling current corresponding to the maximum tunneling probability is also derived. The tunneling current is obtained by analytically calculating the minimum tunneling length in a TFET when operating in the accumulation or inversion mode. The results of the proposed potential model is compared with technology computer-aided design (TCAD) simulations for TFET with various dimensions, revealing good agreement. The potential and current in an n-type TFET (nTFET) obtained using the proposed models are also analyzed. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Green marketing: Exploring concepts, strategies, and future trends
Green marketing research is becoming more and more well-liked in academia and business. Both companies and customers today recognize the value of eco-friendly products due to increased awareness of how companies respond to various factors contributing to environmental degradation. One should understand the meaning, opportunities, and threats associated with green marketing to harness the benefits of green marketing. This book chapter aims to explore various aspects of green marketing, including its evolution throughout the years, opportunities, threats, the future of green marketing, etc. To sum up, this chapter aims to gain an in-depth understanding of green marketing and how companies could use it to their advantage. Successful implementation will be possible only if associated threats are carefully analyzed and understood. Therefore, a part of this chapter will be dedicated to understanding the threats associated with green marketing strategies. 2023, IGI Global. All rights reserved. -
Harnessing Medical Databases and Data Mining in the Big Data Era: Advancements and Applications in Healthcare
In the contemporary period of Big Data, the healthcare industry is witnessing a transformative paradigm shift, propelled by the convergence of medical databases and data mining technology. This research paper delves into the multifaceted application of this synergy, offering a comprehensive overview of its implications and opportunities. With the exponential growth of healthcare data, the utilisation of medical databases serves as the bedrock for data mining techniques, fostering critical advancements in diagnosis, treatment, and patient care. Through this research, we explore the integration of electronic health records, genomic data, and clinical databases, unveiling new dimensions of predictive analytics, patient profiling, and disease monitoring. Moreover, we assess the ethical and privacy concerns entailed in this data-rich landscape, emphasising the need for robust governance and security measures. Our paper encapsulates the evolving landscape of health care, demonstrating the immense potential and the ethical responsibilities accompanying this groundbreaking merger of technology and medicine in the period of Big Data. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Enhancing Stock Market Trend Prediction Using Explainable Artificial Intelligence and Multi-source Data
Determining the trend of the stock market is a complex task influenced by numerous factors like fundamental variables, company performance, investor behavior, sentiments expressed in social media, etc. Although machine learning models support predicting stock market trends using historical or social media data, reliance on a single data source poses a serious challenge. This study introduces a novel Explainable artificial intelligence (XAI) to address a binary classification problem wherein the objective is to predict the trend of the stock market, utilizing an integration of multiple data sources. The dataset includes trading data, news and Twitter sentiment, and technical indicators. Sentiment analysis and the Natural Language Toolkit are utilized to extract the qualitative information from social media data. Technical indicators, or quantitative characteristics, are therefore generated from trade data. The technical indicators are fused with the stock sentiment features to predict the future stock market trend. Finally, a machine learning model is employed for upward or downward stock trend predictions. The proposed model in this study incorporates XAI to interpret the results. The presented model is evaluated using five bank stocks, and the results are promising, outperforming other models by reporting a mean accuracy of 90.14%. Additionally, the proposed model is explainable, exposing the rationale behind the classifier and furnishing a complete set of interpretations for the attained outcomes. 2024, American Scientific Publishing Group (ASPG). All rights reserved. -
Predicting Stock Market Movements Through Multisource Data Fusion Graphs: An Approach Employing Graph Convolutional Neural Network
The stock market plays an important role in the capital market, and investigating price fluctuations in the stock market has consistently been a prominent subject for researchers. The application of soft computing techniques to predict and categorize stock market movements is a significant research challenge that has gathered considerable attention from researchers. Although several studies highlight the significance of incorporating information from two sources in stock movement prediction, the potential of advanced graphical techniques for modeling and analyzing multi-source data remains an unattended research area. This study aims to address this gap by introducing a novel model that utilizes multi-source data fusion graphs to predict future market movements. The primary challenge involves establishing a model that can effectively gather the relationships among various data sources and employ this understanding to improve prediction performance. Compared to several existing methods relying only on historical data or sentiment data, which show limited predictive power and lack generality, the proposed approach seeks to overcome these limitations. The proposed model integrates various information sources, including historical prices, news data, Twitter data, and technical indicators for predicting future stock market trends. This presented method involves constructing a subgraph map for each data type to capture events from both rising and falling markets. Then, a Gated Recurrent Unit (GRU) is employed to aggregate the subgraph nodes. These aggregated nodes are then integrated with a Graph Convolutional Neural Network (GCNN) to classify the multi-source graph, therefore achieving stock market trend prediction effectively. To further validate its effectiveness, the presented model is applied to Indian stock market data, demonstrating its feasibility in fusing multi-source stock data and establishing its suitability for effectively predicting stock market movements. 2024 Seventh Sense Research Group -
Robust Deep Learning Empowered Real Time Object Detection for Unmanned Aerial Vehicles based Surveillance Applications
Surveillance is a major stream of research in the field of Unmanned Aerial Vehicles (UAV), which focuses on the observation of a person, group of people, buildings, infrastructure, etc. With the integration of real time images and video processing approaches such as machine learning, deep learning, and computer vision, the UAV possesses several advantages such as enhanced safety, cheap, rapid response, and effective coverage facility. In this aspect, this study designs robust deep learning based real time object detection (RDL-RTOD) technique for UAV surveillance applications. The proposed RDL-RTOD technique encompasses a two-stage process namely object detection and objects classification. For detecting objects, YOLO-v2 with ResNet-152 technique is used and generates a bounding box for every object. In addition, the classification of detected objects takes place using optimal kernel extreme learning machine (OKELM). In addition, fruit fly optimization (FFO) algorithm is applied for tuning the weight parameter of the KELM model and thereby boosts the classification performance. A series of simulations were carried out on the benchmark dataset and the results are examined under various aspects. The experimental results highlighted the supremacy of the RDL-RTOD technique over the recent approaches in terms of several performance measures. 2022 River Publishers. -
Sum signed graphs - I
Let G=(V,E) be a simple graph, f: V(G) ? {1, 2, ..., |V(G)|} be a bijective function and ?: E(G) ? {+,-} be a mapping such that ? (uv)=+, whenever f(u)+f(v) ? n and ? (uv)=-, whenever f(u)+f(v)>n. Then, S=(G,f,?) is said to be a sum signed graph. In this paper, we initiate the study of sum signed graphs. Also, we find rna number for some classes of graphs and present some of the characteristics of sum signed graphs. 2020 Author(s). -
Negative Domination inNetworks
We introduce s-domination in signed graphs which is based on the number of negative edges between the dominating set and its complement. The s-domination in both the positive and negative homogeneous signed graph will be studied for each value of s. As a special case, the properties of s-domination in sum signed graphs will be analyzed. The maximum value of s for a graph for which the s-domination exists is identified. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Sum Signed Graphs, Parity Signed Graphs and Cordial Graphs
Signed graphs are graphs with every edge is signed either positive or negative. Given an n vertex graph, the vertices are bijectively labelled from 1 to n. A signed graph is a sum signed graph if and only if every edge is signed negative whenever the sum of the vertex labels exceeds n and every edge is signed positive whenever the sum of the vertex labels does not exceed n. For a parity signed graph, an edge receives a negative sign, if the end vertices are of opposite parity and a positive sign otherwise. Cordial signed graphs are the ones with the difference between the total number of negative edges and the positive ones is at most 1. We discuss the connection between sum signed labeling with parity signed labeling and cordial labeling. The absolute cordial condition for graphs satisfying sum signed labeling will be analyzed 2023, IAENG International Journal of Applied Mathematics.All Rights Reserved. -
SUM SIGNED GRAPHS II
In this paper, the study of sum signed graphs is continued. The balancing and switching nature of the graphs are analyzed. The concept of rna number is revisited and an important relation between the number and its complement is established. 2023, Krasovskii Institute of Mathematics and Mechanics. All rights reserved. -
A study of parenting behaviour and children's well-being in urban India families
The aim of the research is to study parenting behavior and children’s well-being in urban Indian families. Socialization, an important process in parent-child relationship is described as, ”the process by which a child or other novice acquires the knowledge, orientations, and practices that enable him / her to participate effectively and appropriately in the social life of a particular community” (Garret & Baquedano-Lopez, 2002, p. 339). Hence, socialization in the family is of crucial significance as it is the microcosm of society and has critical implications for the social and emotional development of the growing child. Parenting is a crucial process in family socialization. The word ‘parenting’ derives from the Latin verb ‘parere’ which means ‘to bring forth, develop or educate.’ Hoghughi, M. (2004) defines parenting as “purposive activities aimed at ensuring the survival and development of children.” It is of utmost importance to understand the dynamics of the parenting in varied cultures. -
The repercussions of teaching in the digital era: A boon or bane?
Recently, the world has experienced a big change due to the pandemic controlling our lives. The change is also experienced by the education sector. The pandemic has forced the whole system to go digital overnight. Although the learning system has been slowly moving towards digitalisation for a considerable period of time now, the social media platform is taking over the traditional method of learning. The study has 61 respondents and the data is collected through a questionnaire. The paper applies regression analysis with the help of SPSS. The development of digital learning platforms provides an alternative to offline learning. This recent spread of the e-learning environment was fast forwarded in the COVID period. The independent variables of the paper are professional skills and ethical proficiency in online learning. These challenges are evaluated, and their impact is assessed on the learning outcome. The chapter limits its approach to professional and ethical scales by ignoring the other important variables that decide the learning outcome of the students. However, the current body of literature has a very narrow approach to the learning system. So, the chapter inspires us to cover the gap through the proposed framework model for teaching practices in the digital era. The chapter intends to develop the teaching skills and moral conscience of the academicians and ease the learners into the new path of education. The future scope makes it definite for the growing learners to understand the advancement in technology and its repercussion on the skill development process. 2024 River Publishers. All rights reserved. -
KESMR: A Knowledge Enrichment Semantic Model For Recommending Microblogs
In today's world, there's an enormous amount of information available on the Internet. Because of this, it's become really important to come up with better and smarter ways to search for things online. The old-fashioned methods, like just matching certain words or using statistics, don't work so well anymore. They often suggest web pages that are irrelevant. As the Semantic Web keeps getting bigger, it needs algorithms for the best fit. In this paper, a way to measure how different the words used for web search. This helps in suggesting the most relevant web pages. A special algorithm that can change its settings. Our proposed method demonstrates 94% accuracy. 2023 IEEE.