Browse Items (14421 total)
Sort by:
-
Advanced electrochemical performance of N-Ti3C2/MnO2 MXene as a promising electrode for energy storage
In this study, we demonstrate a simple and efficient two-step synthetic strategy to design a high-performance N-Ti3C2/MnO2 composite for energy storage application. Nitrogen doping alters the electronic structure of electrode materials and enhances pseudocapacitance. N-Ti3C2 serves as a supporting substrate for MnO2, boosting the active surface area by preventing Ti3C2 layer stacking. Benefitting from the collaborative contribution and synergistic interaction within this multicomponent system, N-Ti3C2/MnO2 results in exceptional specific capacitance of 2107.1 Fg?1 at 1 Ag?1. It also exhibits a low internal resistance and maintains a capacitive retention of 94% over 3000 cycles. The asymmetric capacitor also delivers an energy density of 117.1 Whkg?1 at a power density of 1290.1 Wkg?1. This work presents a straightforward method for modifying Ti3C2 through nitrogen doping and the insertion of MnO2 as an interlayer spacer to enhance electrochemical performance. Qatar University and Springer Nature Switzerland AG 2024. -
Revealing the synergistic potential of Ti3C2 MXene/Vanadium sulfide composite for enhancing electrochemical water splitting
The development of advanced materials for sustainable energy solutions is more critical than ever, and efficient electrocatalysts are at the forefront of this research. MXene-based materials have garnered significant focus for their electrocatalytic uses due to their high electrical conductivity, hydrophilicity, and tunable surface chemistry. Here, we highlight the innovative work on Ti3C2/V3S4 composites for efficient hydrogen evolution reaction (HER). The Ti3C2 MXene serves as a conductive matrix, while V3S4, a transition metal sulfide, enhances catalytic activity by providing active sites for HER. Integration of V3S4 into the MXene structure increases the surface area and introduces mesoporous channels that improve electron transfer and electrolyte accessibility. Notably, the composite exhibits an enhancement in surface area (45 m2g-1) and pore diameter (11.6 nm) compared to pristine Ti3C2 MXene. Electrochemical measurements demonstrate that the Ti3C2/V3S4 composite has superior hydrogen evolution activity with a lower overpotential of 188 mV and excellent stability compared to bare Ti3C2 MXene. As the demand for clean energy grows, these findings represent a significant step towards the formulation of top-performing materials for water splitting, positioning MXene-based hybrids as a promising solution in the field of renewable energy. This work is a testament to how material innovations can drive progress in hydrogen production technologies, paving the way for cleaner, greener energy systems. 2025 Hydrogen Energy Publications LLC -
Insights into the synergistic effect of V3S4 decorated Ti3C2 MXene as an electrode for asymmetric supercapacitor
As the globe moves toward sustainable energy options, effectively storing and managing energy becomes increasingly crucial. Advanced energy storage technologies can bridge the gap between energy generation and consumption, ensuring a reliable and stable supply even when renewable sources are intermittent. In this context, the rise of two-dimensional layered Ti3C2 MXene as a promising electrode for supercapacitors is particularly noteworthy, owing to its unique physical, chemical, and electrocatalytic attributes. Despite its potential, the immediate collapse and aggregation of MXene layers pose significant obstacles to their widespread usage in energy storage applications. This study explores advanced energy storage technologies using V3S4 coupled Ti3C2 MXene as electrodes in asymmetric supercapacitors. By combining the unique properties of V3S4 and Ti3C2 MXene, new avenues for improving the performance of supercapacitors are being unlocked. The experimental results indicate that the Ti3C2/V3S4 electrode exhibits an enhanced specific capacitance (Csp) of 1323.7 Fg-1 at a current density of 1 Ag-1, with an outstanding capacitance retention of 90.5 % after 2000 cycles. An assembled asymmetric supercapacitor, Ti3C2/V3S4//activated carbon shows superior energy storage efficiency, achieving a Csp of 258.4 Fg-1 at 2 Ag-1. The device exhibits a high energy density of 60.6 Whkg?1 at a power density of 649.2 Wkg-1, while holding onto a capacitance retention rate of 91.1 % over 10,000 cycles. 2025 Elsevier Ltd -
Digital mental health interventions in India: Addressing challenges and expanding access
[No abstract available] -
Centrality measures-based sensitivity analysis and entropy of nonzero component graphs
The nonzero component graph of a finite-dimensional vector space over a finite field is a graph whose vertices are the nonzero vectors in the vector space, and any two vertices are adjacent if the corresponding linear combination contains a common basis vector. In this paper, we discuss the centrality measures and entropy of the nonzero component graph and also analyze the sensitivity of the graph using the centrality measures. 2025 World Scientific Publishing Company. -
Classifying AI-generated summaries And Human Summaries Based on Statistical Features
In an age where artificial intelligence knows no bounds, it's crucial to know if the textual content is reliable. But, the task of identifying AI-generated content within vast volumes of textual data is a big challenge. The existing studies in feature-based classification only explored prompt-based text responses. This paper explores methods to identify AI-generated summaries using feature-based machine-learning techniques. This study uses the BBC News Summary dataset. The summaries for the dataset are then generated using three of the top-performing summarisation models. Different statistical features like Zipf's Law Score, Flesch Reading Ease Score, and the Gunning Fog Index are used for extracting features for the classification model. The aim is to differentiate AI-generated summaries from human-written summaries. The main part of the study involves extracting the statistical features from the summarized texts, which are then classified using different classification models. Different models like Support Vector Machine (SVM), Random Forest, Decision Tree, and Logistic Regression models are used in the paper. Grid Search is also used to fine-tune SVM for the best results. The right model depends on what the need is. Whether it's accuracy, F1 score, or a mix of both, there are different options to lead you to the truth. The feature-based approach in this paper helps in more explainable classification and can compare how statistical text features are different for human-written summaries and generated summaries. 2024 IEEE. -
Fake News Detection: An Effective Content-Based Approach Using Machine Learning Techniques
Fake news is any information fabricated to mislead readers to spread an idea for certain gains (usually political or financial). In today's world, accessing and sharing information is very fast and almost free. Internet users are growing significantly than ever before. Therefore, online platforms are perfect grounds to spread information to a broader section of society. What could circulate between a relative few can now circulate globally overnight. This advantage also marked the increase in the number of fake news attacks by its users, which is unsuitable for a healthy society. Therefore, there is a need for good algorithms to identify and take down fake information as soon as they appear. This paper aims at solving the problem by automating the process of identifying fake news using its content. Evaluation metrics like the accuracy of correct classification, precision, recall and f1-score assess the performance of the approach. The machine learning approach achieved its best performance with 96.7 percentage accuracy, 96.2 percentage precision, 97.5 percentage recall and 96.9 percentage f1 score on the ISOT dataset. 2022 IEEE. -
A study of CNN models for re-identification of vehicles
Vehicle Re-identification has evolved in recent times. Initially, clicking a single picture of a vehicle or a car was done manually, inviting the workforce to complete a specified task. With the growth in technology, the method and techniques in Vehicle Re-Id also have advanced, transforming from manual to automation. Surveillance cameras were used to capture vehicle images and retrieve information about a specific vehicle. Re-trieving and identifying the images of the vehicle is done using computer vision, the most important branch of computer science and artificial intelligence. Earlier, Vehicle Re-Id implemented a single algorithm on a dataset, making the corresponding result insufficient to determine its effects. This paper proposes a brief survey of multi-modal techniques and methods for vehicle re-identification and fingerprinting. The different attributes of the vehicle are considered for ANPR (Automatic number plate recognition) for identifying the number plate, focusing on the vehicle's details or features as the initial phase of identification, and then the vehicle number plate. 2023 IEEE. -
Improved Computer Vision-based Framework for Electronic Toll Collection
The world is moving towards artificial intelligence and automation because time is the most crucial asset in today's scenario. This paper proposes an automatic vehicle fingerprinting system that avoids long waiting times in toll plazas with the help of computer vision. The number plate recognition and vehicle re-identification focus on this research. Day/night IR cameras are used to get the images of the vehicle and its number plate. The VeRi776 datum, which contains real-world vehicle images, is used to facilitate the research of vehicle re-identification. The proposed framework employs Siamese model architecture to identify the attributes such as color, model, and type of vehicle. The Car License Plate Detection datum is used to evaluate the efficiency of the proposed license plate recognition system. An ensemble of image localization techniques using CNNs and application of the OCR model on the localized snapshot is used to recognize the vehicle's license plate. A combination of license plate recognition and vehicle re-identification techniques is used in the proposed framework to improve the efficiency of identifying vehicles in toll plazas 2022 IEEE. -
Hybrid homomorphic-asymmetric lightweight cryptosystem for securing smart devices: A review
The Internet of Things (IoT) has emerged as a new concept in information and communication technology, and its structure depends on smart device communications. It was evolving as a significant factor of the Internet and made the interconnection of huge devices likely, accumulating huge amounts of information through innovative technologies. Thus, the requirement for IoT security is more significant. Scalable services and applications are susceptible to information leakage and attacks, demanding higher privacy and security. Cryptography is a technique to secure data integrity, confidentiality, authentication, and network access control. Owing to several limitations of IoT devices, the classical cryptographic protocols are not appropriate for all IoT smart devices like smart cities, smart homes and so forth. Consequently, researchers have introduced numerous lightweight cryptographic (LWC) protocols and algorithms for IoT security. Numerous solutions are available in the research field regarding security using cryptographic algorithms in IoT environments; however, such solutions have not attained satisfactory outcomes. So, finding a solution by examining the recent issues is open research. This article investigates the various LWC protocols for IoT devices and provides a reasonable enquiry into existing ubiquitous ciphers. Furthermore, the article appraises various recently presented lightweight (LW) block ciphers and hybrid homomorphic LWC regarding security. In addition, this article assists in comprehending the significance of security features and progression in cryptographic algorithms. Finally, the article reports on the necessary changes and recommends upcoming research focuses. Also, this article assists in realizing the importance of security and progressions in cryptographic algorithms. 2023 John Wiley & Sons, Ltd. -
Bob Dylan: Poet of disruption, dissonance and an aesthetic of dissent
This paper is a brief study of the pivotal figure of folk rock, Bob Dylan. Acclaimed as a songwriter and singer, he was also the poetic voice of the counter culture of the nineteen sixties in America. The counter culture sought to unseat the mainstream establishment that seemed obsessed with war, conservative ideals and religious nationalism. Dylan burst onto this scene 'already a legend' and 'the unwashed phenomenon' (Baez, 1975) projecting the image of the original vagabond and troubadour. A glance at a selection of some of his best known lyrics disabuses one of the notions of his being uninitiated into the discourse of philosophy and literature. He draws freely on and engages with ideas from texts that are sometimes even obscure. The Nobel he was awarded in October 2016 recognized his art for evolving new modes of poetic expression. This paper studies Dylan, the performer and the writer who has masterfully disrupted most accepted literary modes using the dissonance-rich space of Rock music while retaining some of the traditional forms of poetic utterance. AesthetixMS 2016. -
Pink floyd's time: An aural metanarrative exploring time through form, lyric, and musical arrangement
The inability of language to capture the essence of time is a crisis that has been expressed by philosophers starting from St. Augustine to Paul Ricoeur. Appearing on their seminal album, Dark Side of the Moon, Pink Floyd's Time is a profound artistic attempt which transcends this language barrier by using music to bring the listeners to a more direct confrontation with time; doing so by juxtaposing time as calibrated and as experienced through the music and the lyrics, and by making the reader experience time-based affects such as impatience, expectation, monotony, and such. As a direct function of song, time is experienced as musical time in the song, thereby ensuring that the listener's confrontation with time is immersive, with lyrics that describe the nature of experienced and calibrated time working synchronously with the music to complete the image. In the context of its release in 1974, the 6:52 minute song was in engagement with the concept of time as well, in that it was among the pioneering ones which redefined radio broadcast time beyond the standard 3 minutes afforded to popular music tracks, with the commercially preferred listener span in mind. The matter of time thus becomes a multi-layered formal engagement in the song, at the level of lyric, recording, music and listening, thereby making possible an image of time that is polished and rounded. These aural, lyrical and production-based concepts will be addressed and expanded upon to show how Pink Floyd's Time functions as a metanarrative in how it uses and invokes the elements of time to talk about time. AesthetixMS 2020. -
The Dark Side of Personalisation: Biases, Filter Bubble, and Impact on Advertising Effectiveness
This book chapter critically examines the intersection of personalized marketing, algorithmic bias and the need for inclusive marketing. Drawing on real-world examples from the beauty industry, ride-hailing services, food delivery platforms and OTT streaming services, it highlights how personalization reinforces existing biases. The black box models are inherently based on faulty data perpetuating discrimination for minority groups. Although machine learning systems deliver highly accurate, they fail to understand deeply rooted biases. The book chapter advocates for human centered AI, regular audits, serendipitous recommender systems and adoption of ethical and transparent frameworks. By integrating human judgment with AI technologies, marketers can foster inclusive and fair personalized marketing. 2026, IGI Global Scientific Publishing. All rights reserved. -
Navigating the filter bubble: A pill for hyperpersonalization
AI-driven personalization has transformed the digital landscape shaping consumer behavior, active engagement and influencing purchase intention. However, the extensive use of these strategies have led to a filter bubble-a state of intellectual isolation due to hyper-personalisation. Users are confined to information that reinforces their existing beliefs, limiting awareness of alternative products and leading to advertising fatigue. The chapter delves into extensive literature on filter bubble phenomenon to draw parallel implications from political marketing to consumer marketing. It discusses strategies to mitigate the impact of hyper-personalisation. These strategies focus on platform-specific dynamics, audience fragmentation v/s duplication, and leveraging automated serendipity and ideological polarisation to foster diversity and consumer engagement. The chapter articulates the strategic role of social media in offering personalised marketing to consumers. 2025, IGI Global Scientific Publishing. -
Critical concepts of restrained domination in signed graphs
A signed graph ? is a simple undirected graph in which each edge is either positive or negative. Restrained dominating set D in ? is a restrained dominating set of the underlying graph |?| where the subgraph induced by the edges across ?[D: V D] and within V D is balanced. The minimum cardinality of a restrained dominating set of ? is called the restrained domination number, denoted by ?r(?). In this paper, we initiate the study on various critical concepts to investigate the effect of edge removal or edge addition on restrained domination number in signed graphs. 2022 World Scientific Publishing Company. -
Restrained domination in signed graphs
A signed graph ? is a graph with positive or negative signs attatched to each of its edges. A signed graph ? is balanced if each of its cycles has an even number of negative edges. Restrained dominating set D in ? is a restrained dominating set of its underlying graph where the subgraph induced by the edges across ?[D: V\D] and within V\D is balanced. The set D having least cardinality is called minimum restrained dominating set and its cardinality is the restrained domination number of ? denoted by ?r(?). The ability to communicate rapidly within the network is an important application of domination in social networks. The main aim of this paper is to initiate a study on restrained domination in the realm of different classes of signed graphs. 2020 Anisha Jean Mathias et al., published by Sciendo 2020. -
A study on the restrained domination number in diverse families of derived signed graphs
A derived graph is obtained by applying a specific graph operation to a given graph G. A set D of vertices in a signed graph ? is a restrained dominating set of ? if D is a restrained dominating set of the underlying graph |?|, and every cycle formed by the edges connecting D to V \D and those within V \D is balanced. The restrained domination number ?r(?) is the minimum cardinality of a restrained dominating set of ?. In this paper, we establish results on the restrained domination number for derived signed graphs, including line signed graphs, semi-total point signed graphs, semi-total line signed graphs, and total signed graphs and we also examine their structural properties in relation to their restrained domination number. 2025 World Scientific Publishing Company. -
3D-Printed MOFCuO/TiO2 Energy Device for Continuous Self-Charging Power Generation
The electric nanogenerator offers an easy and affordable way to capture energy and operates on the premise of energy conversion. Contact electrification-based tribological energy harvesting through the interaction between tires and road surfaces, represents a highly promising renewable resource with a significant estimated potential. One of the important factors that decides the performance and application of these nanogenerators is the material used for its fabrication. In this work, we introduced a novel energy harvester comprised of defect-engineered Metal Organic Framework (MOF) templated CuO/TiO2 (MCT) based triboelectric layer integrated with a 3D printed substrate for a smart power wheel. The comprehensive properties of the material are revealed by the surface potential, structural, morphological, and electrical studies, which validate MOF as a feasible choice for energy harvesting applications. The MCT-based triboelectric nanogenerators (TENGs) generate a sustainable output of ?1.6V in flexible cantilever mode. The smart power-wheel system successfully showed a ? 400% enhancement in the output performance due to the combined effects of heating and bending. The detailed density functional theory (DFT) insight in Cu/O vacancies synergistically promotes TiO2?CuO charge transfer through flexible Cu+/Cu2+ redox states, facilitates electron mobility, and enhances the overall energy conversion efficiency. Overall, this study broadens the range of functional materials available for 3D printing and promotes the adoption of 3D-printed triboelectric devices in batteryless intelligent applications within smart automobiles. 2026 Wiley-VCH GmbH. -
Strain-induced wave energy harvesting using atomically thin chromiteen
Developing non-corrosive wave energy harvesters is one of the critical technologies required for sustainable energy harvesting. This work studies the effect of surface defects in atomically thin chromiteen for harvesting energy from water waves. An external strain further enhances the surface charge properties of the chromiteen, resulting in higher electrical output in the fabricated flexible nanogenerator (C-FNG) to harvest wave energy. The peak output voltage of the C-FNG device was ?5 V due to the water wave force. The density functional theory (DFT) results indicate the presence of surface defects in the 2D chromiteen, and the applied strain gradient introduced a redistribution of electron density, possibly due to altered bond lengths in the material. The present work provides an atomistic study of energy harvesting in the marine environment to provide power for deep-sea divers, ships, and any other small electronic sensors or marine Internet of Things in remote areas. This journal is The Royal Society of Chemistry, 2025 -
Recyclable layered chromite-based porous film for water cleaning
The oil spillage and pollutants in water bodies are a significant concern in the present time. To address this concern, a porous and superhydrophobic nanocomposite film containing layered natural chromite ores with a polymer was fabricated using a simple solution casting method. The flexible film exhibited a good tensile strength of 1.022 kg mm?2 and self-cleaning properties. It showed an excellent oil adsorption of up to ?268% for castor oil and an adsorption efficiency of ?90% for toxic cationic dyes. The presence of high surface charges on the chromite nanosheets enhanced its adsorbing capability. Furthermore, even after being resynthesized from old used film, the composite film maintained its mechanical strength, hydrophobicity, and adsorbing capabilities. Therefore, we believe that the present work can help in cleaning oil and other pollutants from large water bodies and consequently preserving aquatic life. 2025 The Royal Society of Chemistry.