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Exploring Social Network Usage and Well-Being Among College Students
Social media plays a significant role in bringing the world together with just a click. However, social media addiction is rapidly increasing, especially among the youth, which affects their mental health and well-being. Instagram is one of the social media sites that is used mainly by students. Due to increasing exposure to Instagram, including the short videos, called Reels, today's students consume the content at an alarming rate, thus becoming addicted to it. College students tend to relentlessly use Instagram, without considering the time and energy wastage or addressing its impact on their mental health and well-being. The present study aimed to (1) explore the relationship between Instagram usage and mental well-being among college students in India, and (2) examine whether Instagram usage serves as a meaningful predictor of students mental well-being. The findings reveal a significant negative correlation (r=?0.332, p<.001) between Instagram usage and students well-being, indicating that higher Instagram use is associated with lower levels of mental well-being among college students. Further, a simple linear regression analysis confirmed that Instagram usage is a significant predictor of well-being (F(1, 154)=19.099, p<.001), explaining a meaningful portion of the variance. The results highlight the need for educators, parents and other stakeholders to recognise the influence of social media, especially Instagram, on students mental health and well-being and develop strategies to promote healthier usage patterns. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Role of breakup distress on perceived academic performance and psychosocial functioning among University students
Emerging adult students often experience romantic relationship dissolutions, which is a normative yet distressing experience for them. The present study examines perceived academic performance and psychosocial functioning among university students who have had a broken romantic relationship in Indian context. The study employed a mixed-method explanatory sequential design including quantitative and qualitative data analysis. Researchers administered questionnaire to 104 students who are studying in Universities and had breakup incidence. Questionnaire included items on breakup distress scale, perceived academic performance, concentration, and quality of life focusing mental wellbeing and social relationship. Researchers selected survey and interview participants through word-of-mouth approach. Findings revealed that girls had high positive correlation between break distress and academic performance than boys. The narrative thematic analysis of qualitative data revealed three main themes and five sub-themes explaining the nuances of breakup and listed coping mechanisms used by the Indian youths to spring back from breakup distress. Future research may focus on how the early breakup incidents affect their post marriage relationship and life satisfaction. 2026 RESTORATIVE JUSTICE FOR ALL. -
Pre-Service and In-Service Teachers Perceptions of Using Virtual Reality Tools in Teaching
This paper explores pre-service and in-service teachers perceptions of virtual reality (VR) technology as a teaching and learning tool in the classroom in India. The study aimed to answer four research questions, including the adoption rate of VR technology among teachers, their confidence levels in teaching using VR technologies compared to digital technologies, attitudes towards using VR technology, and the usefulness of different uses of VR technology. The survey conducted among 102 teachers found limited adoption of VR technology, lower confidence levels in using it, but willingness to use it in the future. The paper recommends providing adequate training and support to increase teachers confidence in using VR technology in their teaching practices. The study also suggests that strategies to promote VR technology should consider gender differences in attitudes towards it. Overall, the research concludes that teachers view VR technology as having potential benefits for learning and teaching across various uses. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
A Comprehensive Review on Fault Data Injection in Smart Grid
Nowadays, power generation at the utility side and transfer to the demand side have been controlled by the smart grid. Day-by-day entire power distribution process has moved in multiple directions and connects more residential and industrial sectors. Due to these phenomena, more monitoring, and security processes have been adopted in smart grid to control fault data injection, cyber-attack, and physical side attackers in smart grids. This research study analyzes the fault data injection in smart grid with respect to the malicious data, signal, and connectivity process. As a part of this research study, a survey has been done on various techniques to control the faults in smart grid. The analysis carried out in this study is very helpful to identify and determine the suitable method to control the fault in smart grid. Along with these, a countermeasure against the FDI is also summarized on the cyber-attack and physical attack. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Synthesis, Green Photoluminescence and Studies of Nonlinear Optical Spatial Self Phase Modulation Effect in 2D Ga2Te3 Nanosheets
The liquid-phase exfoliation (LPE) technique has been employed to prepare two-dimensional (2D) gallium telluride (Ga2Te3) nanosheets with an average thickness of ?2.4 nm and linear optical properties, including UV-visible absorption and photoluminescence (PL) emission characteristics of the sample in the green wavelength region are reported. The third-order nonlinear optical (NLO) responses of the colloidal suspension of 2D Ga2Te3 are determined at 532 and 632 nm wavelengths by a spatial self-phase modulation (SSPM) experiment. The value of the third-order NLO refraction coefficient (n2e) and effective susceptibility for monolayer (?(3)Mono) 2D Ga2Te3 under 532 (632) nm continuous wave (CW) excitation is extracted to be 2.60 10-7 (0.32 10-7) cm2/W and 1.12 10-9 (1.37 10-10) e.s.u., respectively. The origin of the observed SSPM patterns under 532 nm excitation was elucidated theoretically. Finally, the correlation of ?(3)Mono with the mobility of charge carriers for a vast number of 2D materials is utilized to establish the origin of the observed NLO effect under 532 nm pump laser radiation in the 2D Ga2Te3. Additionally, NLO absorption coefficients of 2D Ga2Te3 have been extracted using the femtosecond Z-scan technique at 800 nm. We observed a switching behavior (saturable to threephoton absorption) in the nonlinear absorption mechanism with different input peak intensities. The highest three-photon absorption coefficient of ?1.68 cm3/GW2 was observed for a 350 GW/cm2 peak intensity. We believe that such reports of interesting linear and NLO properties of this newly synthesized 2D material can be utilized in the future for a wide number of optoelectronic applications. 2023 American Chemical Society. -
Data Mining Approaches forHealthcare Decision Support Systems
Data mining is a user-friendly approach to locating previously unknown or hidden information in data. The employment of data mining technologies in the healthcare system may result in the finding of relevant data. Data mining is used in healthcare medicine to construct learning models that predict a patients condition. Data mining technologies have the potential to benefit all stakeholders in the healthcare industry. For example, data mining may aid health providers in detecting theft and fraud, medical organizations in making customer service management decisions, physicians in discovering effective therapies and best practices, and customers in obtaining suitable and less expensive healthcare. Contemporary systems, due to their complexity and size, are unable to control and analyze the huge amounts of data generated by healthcare operations. Data mining is a technique and mechanism for converting a large amount of data into useful information. The fundamental purpose of this research is to look at what makes clinical data mining unique, to give an overview of existing clinical decision support systems, to identify and select the most common data mining algorithms used in modern Health and Demographic Surveillance System (HDSS), and to compare different data mining algorithms. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A novel approach using steganography and cryptography in business intelligence
In the information technology community, communication is a vital issue. And image transfer creates a major role in the communication of data through various insecure channels. Security concerns may forestall the direct sharing of information and how these different gatherings cooperatively direct data mining without penetrating information security presents a challenge. Cryptography includes changing over a message text into an unintelligible figure and steganography inserts message into a spread media and shroud its reality. Both these plans are successfully actualized in images. To facilitate a safer transfer of image, many cryptosystems have been proposed for the image encryption scheme. This chapter proposes an innovative image encryption method that is quicker than the current researches. The secret key is encrypted using an asymmetric cryptographic algorithm and it is embedded in the ciphered image using the LSB technique. Statistical analysis of the proposed approach shows that the researcher's approach is faster and has optimal accuracy. 2021, IGI Global. -
A new combinational technique in image steganography
Internet is used for exchanging information. Sometimes it is needed to transmit confidential data via internet. Here the authors use image steganography to pass confidential data within a cover image. To construct the algorithm, they take the combinational help of particle swarm optimization (PSO), bi-orthogonal wavelet transform (BWT), and genetic algorithm (GA). They use PSO to take the enhanced version of cover image. They use BWT to choose the selective sub bands of cover image and we utilize GA to select a particular stego image among a set of stego images. Thus, an innovative technique of image steganography has been made to transmit confidential data via cover image generating stego image. This combinational approach of image steganography is quite safe for confidential data transmission and makes it hard for the attackers to retrieve the confidential data. 2021 IGI Global. All rights reserved. -
Steganography using Improved LSB Approach and Asymmetric Cryptography
Steganography deals with the craft of obscuring private data inside a spread media. In confidential data communication security is a vital issue. In this paper, we use a two-layer security. At first, data encryption is achieved by the method of RSA algorithm of asymmetric cryptography, and later the ciphered data is hidden into host image by an innovative embedding technique. To hide our ciphered data into host image, we modify the existing LSB technique and use a mapping function that ensures a secure and confidential image steganography resulting in a stego image. Here cryptography is blended with steganography and provides two level security in the confidential data transmission over the internet. 2020 IEEE. -
The Linkage Between the Determinants of Sustainable Growth and Energy-Efficient Consumption to Sustainable Development: A Cross-Country Analysis
The research explores the determinants of sustainable development, highlighting the impact of sustainable growth and energy-efficient consumption. Furthermore, individually analyzing the factors influencing sustainable development, sustainable growth and energy-efficient consumption. Using secondary data sources for 19 variables, the study analyzed it for the G20 nations excluding the European Union. Nevertheless, the findings conclude that a positive relationship between sustainable growth and energy-efficient consumption contributes to sustainable development. Including macroeconomic, spatial and socio-economic variables as control variables enhances the studys findings by unravelling a unique perspective and relationship between these variables on sustainable development. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
A Survey on Adaptive Authentication Using Machine Learning Techniques
Adaptive authentication is a reliable technique to dynamically select the best mechanisms among multiple modalities to authenticate a user based on the users risk profile generated using behavior and context-based information. Websites or enterprise applications enabled with adaptive authentication will have a more robust security system as analyzing the large volume of the user, device, and browser data in real time generates a risk score that decides the appropriate level of security. Though a significant amount of research is being carried out on adaptive authentication, no single model is suitable for a global attack. This paper provides a structured (extensive) survey of current adaptive authentication techniques available in the literature to identify the challenges which demand future research. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
An Architecture for Risk-Based Authentication System in a Multi-Server Environment
Identity authentication, a vital part of any application access, is also one way for imposters to gain access to an application using various fingerprint authentication technologies. Therefore, because of the lack of security in the authentication architecture, this paper proposes an architecture for a risk-based authentication system using a machine learning model in a multi-server environment. Since the recent study mainly focuses on the multi-server environment and adaptive authentication independently, very little work has been proposed using a multi-server environment for adaptive authentication. The study aims to estimate risk for the user during the initial login process and when the user's data is extracted enough for prediction in a multi-server environment. 2023 IEEE. -
Risk-Based Authentication System Using Hierarchical Sub-Feature-Based Model-(HSFBM)
Password-based authentication system recently has been more secure as risk-based authentication system (RBA) is indentured. The RBA system monitors the parameters extracted during the user login process, and based on the proposed model, the system raises a multi-factor authentication to the user. As the vulnerability has increased concerning passwords, fingerprints easy access to any web application may result in a security flow. Several best practices have addressed these issues, but the security threats have been challenging during the initial login sessions. Hence, this paper proposes a novel method for an effective risk identification method during the initial login phase using a hierarchical sub-feature-based model for different categories of users in an RBA system. The FAR is comparatively better in our proposed model, with minimal re-authentication requests for the user. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Urban coastal resilience - An assessment
Increase in the urban area leads to the increase of impervious surfaces which is stressing urban watershed balance resulting in issues like urban flooding in cities around the world. Coastal urban areas experience the pressures of a higher water table which contributes to the rising urban flooding issues of the area. Urban resilience as a concept was developed in cities across the world which includes multiple strategies to cope with the impacts of climate change in cities by integrating engineering and ecological measures. Urban resilience for urban flooding aims to achieve the water balance of an area by balancing the increase of impervious surfaces using ample green and grey infrastructure. This paper aims to understand and evaluate the effectiveness of urban resilience measures implemented in coastal cities worldwide. 2023 Author(s). -
Synthesis and characterization of cyclopentadithiophene and thienothiophene-based polymers for organic thin-film transistors and solar cells /
Macromolecular Research, Vol.26, Issue 10, pp. 1-8, ISSN: 1598-5032 -
Privacy Risk Prediction from Social Media Metadata using Feature Selection Approaches
Millions of new people sign up to online social networks (OSNs) every year, which contributes to the growing spread of Personally Identifiable Information. This often ends up occurring unconsciously, either due to the low stakes involved or because the user doesn't understand or underestimates what can go wrong. This trend indicates the need for a trustworthy means to quantify the privacy danger of sharing information online. The volume of OSN data can simply be too staggering for any degree of meaningful manual review, given both the time and man-hours this would entail. This research presents a two-step, unsupervised, and efficient method to estimate privacy risks at the post level. The first step involves using the most advanced reasoning-based Large Language Model, Gemini 2.5 Pro, to generate a comprehensive 'vulnerability score', which is used as a reference for model training. The next step involves comparing the two most used machine learning feature selection techniques, Recursive Feature Elimination (RFE) and Correlation-Based Selection, to select the best features for predicting this score from metadata alone. The results indicate that Correlation-Based Selection produces better results for both the regression and classification-based models, and the top-performing regression model achieves an R-squared of 0.86. Through this, a practical and scalable method to identify privacy-sensitive content effectively on large datasets has been presented in this study. 2025 IEEE. -
Effects of suction-injection-combination (SIC) on the onset of Rayleigh-Benard magnetoconvection in a micropolar fluid
The effects of suction-injection-combination (SIC) and magnetic field on the linear stability analysis of Rayleigh-Benard convection in a horizontal layer of an Boussinesq micropolar fluid is studied using a Rayleigh-Ritz techinque. The eigenvalues are obtained for free-free, rigid-free and rigid-rigid velocity boundary combinations with isothermal and adiabatic temperature conditions on the spin-vanishing boundaries. The eigenvalues are also obtained for lower rigid isothermal and upper free adiabatic boundaries with vanishing spin. The influence of various micropolar fluid parameters on the onset of convection has been analysed. It is found that the effect of Prandtl number on the stability of the system is dependent on the SIC being pro-gravity or anti-gravity. A similar Pe-sensitivity is found in respect of the critical wave number. It is observed that the micropolar fluid layer heated from below is more stable compared to the classical fluid layer. 2003 Elsevier Science Ltd. All rights reserved. -
Effect of Imposed Time-Periodic Gravity Modulation and Electric Field on the Onset of Rayleigh-Benard Convection in a Couple Stress Fluid
International Journal of Mathematical Sciences and Engineering Applications, Vol-6 (6), pp. 421-435. ISSN-0973-9424 -
Three-Component Convection in a Vertically Oscillating Oldroyd-B Fluid With Cross Effects
This paper sheds light on the impact of vertical oscillations (or gravity modulation) on triple-diffusive convection in a viscoelastic fluid using the Oldroyd-B model, in the presence of cross effects. Cross effects can significantly impact three-component convective systems, despite having small magnitudes. When the cross terms, indicating coupled molecular cross-diffusion of the mixture components, are included in the equations governing heat and species transport, then a deviation from the usual three-component convection process is observed. An analytical solution has been found using linear and nonlinear analysis. The conditions for the onset of convection have been obtained using the linear analysis, which is based on the perturbation technique and the Venezian method. In nonlinear analysis, the expressions for Nusselt and Sherwood numbers, which quantify the rate of heat and mass transport respectively, are obtained by deriving the Lorenz model. It has been found that the onset of convection and heat and mass transport can be controlled by choosing the appropriate values of the parameters. 2022, The Author(s), under exclusive licence to Springer Nature B.V. -
Convection in a horizontal layer of water with three diffusing components
Triple diffusive convection in water is modelled with properties like density, specific heat, thermal conductivity, thermal diffusivity and thermal expansion, modified in the presence of salts. The GinzburgLandau equation is derived to study heat and mass transports of different combinations of salts in water. A table is prepared documenting the actual values of thermophysical properties of water with different salts and the critical Rayleigh number is calculated. This information is used in the estimation of Nusselt and Sherwood numbers and their relative magnitudes are commented upon. A detailed study on different single, double and triple diffusive systems is done and comparison is made of the results. The local nonlinear stability analysis made via a GinzburgLandau model mimics many properties of the original governing equations, namely, Hamiltonian character and a bounded solution. 2020, Springer Nature Switzerland AG.