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Deep Belief Network-Based User and Entity Behavior Analytics (UEBA) for Web Applications
Machine learning (ML) is currently a crucial tool in the field of cyber security. Through the identification of patterns, the mapping of cybercrime in real time, and the execution of in-depth penetration tests, ML is able to counter cyber threats and strengthen security infrastructure. Security in any organization depends on monitoring and analyzing user actions and behaviors. Due to the fact that it frequently avoids security precautions and does not trigger any alerts or flags, it is much more challenging to detect than traditional malicious network activity. ML is an important and rapidly developing anomaly detection field in order to protect user security and privacy, a wide range of applications, including various social media platforms, have incorporated cutting-edge techniques to detect anomalies. A social network is a platform where various social groups can interact, express themselves, and share pertinent content. By spreading propaganda, unwelcome messages, false information, fake news, and rumours, as well as by posting harmful links, this social network also encourages deviant behavior. In this research, we introduce Deep Belief Network (DBN) with Triple DES, a hybrid approach to anomaly detection in unbalanced classification. The results show that the DBN-TDES model can typically detect anomalous user behaviors that other models in anomaly detection cannot. 2024 World Scientific Publishing Company. -
A framework for national-level prevention initiatives in Indian schools: A risk reduction approach
India's mental health policies predominantly prioritize treatment and rehabilitation. While acknowledging the significance of youth well-being, the initiatives undertaken are fragmented, lacking comprehensive data on reach and utilization. Mounting evidence supports the preventability of mental illnesses, highlighting the cost-effectiveness of prevention initiatives, particularly within school-based programs. This paper aims to delineate a preventive framework centered on schools, employing the six-step OrigAMI (Origins of Adult Mental Illnesses) model. This model targets modifiable risk factors to stop the development of mental illnesses. Each step of this model is dissected and examined within the context of the school environment, elucidating the unique and influential role that educational institutions can undertake in preventive initiatives in India. In the initial step, the paper identifies modifiable risk factors in children and adolescents that can be addressed within the school environment. The second and third steps involve pinpointing the target demographic and utilizing data from comprehensive reviews of mental health initiatives. The fourth and fifth steps delineate the workforce structure, advocating for task shifting to non-specialists, engaging school stakeholders and parents, and establishing a systematic workforce framework. The final step delves into policy implications, exploring the potential to reduce the prevalence of mental illness by focusing on risk factors with a high Population Attributable Fraction. This section also contrasts the proposed approach in terms of expenditure against the current budget allocations. The paper culminates with a recommendation to integrate these preventive programs into existing healthcare policies, positioning schools as central to these prevention efforts. The integration of prevention programs into healthcare policies aims to reduce prevalence rates and alleviate the burden on the healthcare system. 2024 Elsevier GmbH -
Hybrid architecture of Multiwalled carbon nanotubes/nickel sulphide/polypyrrole electrodes for supercapacitor
A hybrid electrode structure consisting of amino functionalised multi-walled carbon nanotube, nickel sulphide, and polypyrrole is successfully synthesized using a two-step synthesis such as hydrothermal and in-situ polymerization method. The resulting MWCNT/NiS/PPy composite exhibits a distinct tube-in-tube morphology with excellent stratification. The combination of different components and the unique structure of the composite contribute to its impressive specific capacitance of 1755 F g?1 at 3 A g?1. The prepared ternary composite enables ample exposure of numerous active sites while improving structural stability, ultimately leading to enhanced energy storage capabilities. They do this by combining the advantages of constituent components, a hierarchical assembly approach, and an integrated composite structure. Furthermore, even after undergoing 10,000 charge-discharge cycles, the supercapacitor retains more than 97% of columbic efficiency. An asymmetric coin cell was fabricated using MWCNT/NiS/PPy//AC device which delivered an energy density and power density of 33.12 Wh Kg?1 and 6750 W kg?1 respectively. These findings highlight the exceptional potential of the fabricated device for future applications in hybrid energy storage systems. 2024 Elsevier Ltd -
A hybrid technique linked FOPID for a nonlinear system based on closed-loop settling time of plant
Wind and hydroelectric systems are more cost-effective and environmentally beneficial. A hybrid technique is proposed for the fractional-order proportional-integral-derivative (FOPID) controller to regulate the wind and hydro system. The proposed hybrid technique combines the feedback-artificial-tree (FAT), and atomic-orbital-search (AOS); together known as FAT-AOS approach. The proposed technique is utilized to decide the optimum controller parameters, and it guarantees system constancy in large disturbances using less computation and overshoot by restraining the parameter variation. The FAT is used to predict the optimum gain parameter of FOPID, and minimizing the system error is accomplished with the AOS approach. The performance metrics are peak time, rise time, settling time, and peak overshoot, are analyzed. The performance of the proposed method is done in the MATLAB platform. The simulation result of proposed approach for the rise time as 0.001 sec, settling time is 0.012 sec, and the overshoot percentage is 0.02 %. By comparing the existing methods, like Ant lion optimizer (ALO), Salp swarm algorithm (SSA), Particle swarm optimization (PSO), the proposed approach rise time and settling time overshoot, is less. The comparison proves that the proposed system delivers improved outcome than existing systems. 2024 -
Comparative Analysis of Digital Business Models
This paper discusses the comparative analysis of different attributes of Google and Facebook business model and their novel features for handling innovative business framework. We have compared Google and Facebook business model on different key attributes and also discussed the statistical analysis of business models using Google business analytics platform. We have argued performance analysis of these models. One important point which we discuss and analyze in this paper is that a business model is not about just building revenue generating machine, but it is indeed more than that. It explores the strategy and business approaches of both the models of revenue generating line of attacks. Our research contributes a considerate understanding of Google and Facebook architectural model and its influence on business framework. Statistical enactment and results are analyzed, precisely when big data and media are applied. This paper also provides better understanding of the digital marketplace for both of the platforms and its earning methodology. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
Partner betrayal trauma and trust: Understanding the impact on attachment style and self-esteem
Dismissal of an individual's emotional experience by their significant others can have a massive impact on the psychological well-being of the individual. Betrayal trauma discusses the prevalent social phenomenon and its short- as well as long-term impacts on an individual. This study focused on betrayal trauma in romantic relationships. It aimed to find its relation with an individual's self-esteem and attachment styles, with trust as a mediating variable. The tools used in the study- were the partner betrayal trauma trust scale, adult attachment scale and self-esteem scale, each of which was a self-report measurement scale circulated among young adults in the Indian population. The study consisted of 140 participants (n = 140) with a mean age of 21.7 and a standard deviation (SD) of 2.05. The participants included 85% female, 16% male, 3% of the participants identified as genderfluid, and 2% of the participants preferred not to mention their gender. The results from the study show that betrayal trauma in romantic relationships is related to an individual's attachment style and self-esteem. A positive significant correlation was found between betrayal trauma, self-esteem and attachment style, which reveals the impact of betrayal trauma on the psychological well-being of an individual. These findings may aid mental health practitioners in helping young adults resolve their relationship crises and enhance their lifestyles in India. 2024 Elsevier Masson SAS -
A Comprehensive Survey on Deep Learning Techniques for Digital Video Forensics
With the help of advancements in connected technologies, social media and networking have made a wide open platform to share information via audio, video, text, etc. Due to the invention of smartphones, video contents are being manipulated day-by-day. Videos contain sensitive or personal information which are forged for one's own self pleasures or threatening for money. Video falsification identification plays a most prominent role in case of digital forensics. This paper aims to provide a comprehensive survey on various problems in video falsification, deep learning models utilised for detecting the forgery. This survey provides a deep understanding of various algorithms implemented by various authors and their advantages, limitations thereby providing an insight for future researchers. 2024 World Scientific Publishing Co. -
Unleashing economic potential: decoding the FDI-economic growth nexus in G-15 economies amidst unique host country traits
This study examined the impacts of ForeignDirectInvestment (FDI) on economic growth across top the five G-15 countries over a period of 33years, while considering the influence of key host country traits, namely macroeconomic stability, financial development, human capital, and trade openness. The selection of these variables was firmly supported by both theoretical foundations and empirical studies that highlight their significant role in shaping the FDIgrowth interconnection. Panel data derived from World Bank Indicators, spanning the period from 1989 to 2021, were analyzed using a feasible generalized least squares method (FGLS), a rigorous approach, including descriptive statistics, correlation analysis, cross-sectional dependence tests, unit root tests, and multiple regression models. By exploring the interconnection between FDI and the characteristics of the host country, this study sheds light on how these factors collectively contributed to economic growth in the G-15 economies. Descriptive statistics indicated a favorable trend in economic growth, with an average of 3.470 and a standard deviation of 4.289. Correlation analysis revealed significant positive relationships between Economic Growth and Gross Capital Formation, Human Capital, and Liquid Liabilities. Conversely, FDI, Inflation, and Trade Openness displayed insignificant positive correlations with Economic Growth. The findings also demonstrated that favorable host country traits magnified the impact of FDI on economic growth. Specifically, increased Financial Development, Human Capital, and Trade Openness enhanced the positive effects of FDI on economic growth. However, Inflation had a dampening effect on the growth factor. Policymakers in G-15 countries should give precedence to developing strong financial markets, promoting trade liberalization, and investing in human capital to optimize the advantages of FDI. This research addresses a critical gap in the literature as limited empirical work has been conducted on the FDIgrowth relationships specific to the G-15 economies, which hold substantial influence in the global investment landscape and showcase remarkable economic growth. By employing rigorous panel data methodology and a long-term dataset, we provides original insights into the interaction between FDI and host country characteristics, contributing to the existing body of knowledge. The Japan Section of the Regional Science Association International 2024. -
Beyond the first bite: understanding how online experience shapes user loyalty in the mobile food app market
In the competitive landscape of mobile food ordering applications (MFOA) in India, the primary focus is enhancing the customer experience to mirror or even exceed their offline meal acquisition experiences. Existing research underscores the pivotal role of a superior online experience in driving business success. Against the backdrop of a dearth of studies addressing online customer experience (OCE), our current research seeks to gain insight into its state and its implications for attitudes and intentions. Specifically, we investigate the impact of OCE on the continued usage intentions (CUI) of new MFOA users. This study not only sheds light on the relationship between OCE and CUI but also presents a fresh configuration of OCE, addressing its varied conceptualization. Furthermore, drawing on data collected from over 400 first-time users of MFOA, our findings reveal that e-satisfaction and e-trust act as full mediators in influencing CUI. Finally, the study also suggests that e-trust mediates the effect of e-satisfaction on the CUI of MFOA users. Our research contributes to our understanding of OCE by specifically highlighting the experiences and outcomes of first-time users of MFOAs. Practitioners should employ strategies including personalized orientation and data gathering, location-based services, in-app messaging, push notifications and gamification techniques to increase OCE and drive CUI. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2024. -
Synthesis of Nanoflowers using Garcinia gummi-gutta Leaf Extract via Green Route for Enhanced Antifungal and Anti-cancerous Activities
Due to its envisaged relevance in nanomedicine and materials research, the bio-engineering of nanoparticles (NPs) is becoming progressively more promising. Compared to physical and chemical processes, green synthesis produces NPs that are less hazardous to the environment. The usage of phytochemicals in Garcinia gummigutta (L.) leaf extract (GGL) in the bio-reduction of GGL-Ag NPs with potential antifungal and anti-cancerous activities was the main focus of the current study. UV-vis spectrophotometry at 442 nm verified the synthesized GGL-Ag NPs. The average diameters of the synthesized GGL-Ag NPs were determined by scanning electron microscopy (SEM and zeta-sizer studies to be 166.69 nm and 148.2 nm, respectively. Energy dispersive X-ray spectroscopy (EDS) and X-ray diffraction (XRD) examinations of the GGL-Ag NPs confirmed the crystalline nature and the elemental constitution of the NPs. Additionally, the synthesized GGL-Ag NPs' FTIR spectra demonstrated the presence of Phyto components acting as capping agents. Zeta potential measurements (-26.2 4.13 mV) authenticated the stability of the synthesized GGL-Ag NPs. Antimicrobial activity testing of the GGL-Ag NPs demonstrated considerable suppression against Candida tropicalis and Candida albicans at a dose of 100 g/ml and 60 g/ml. Additionally, the synthesized GGL-Ag NPs have demonstrated considerable cytotoxic effects on the Hep-G2 cell line. The current study results show that GGL-Ag NPs may be produced at a low cost and with minimal environmental impact for nanobiotechnology and biomedicine usage. 2024, Brawijaya University. All rights reserved. -
Optical design studies for national large optical-IR telescope
A 1012 m class national large optical-IR telescope (NLOT) is envisaged to meet the growing scientific requirements in astronomy and astrophysics. Telescopes of such dimensions can only be made by segmenting the primary mirror, as it eases a more prominent primary mirrors fabrication, transportation, operation, and maintenance process. This paper presents the various optical designs analyzed for NLOT that can be fabricated using the India TMT Optics Fabrication Facility (ITOFF) at the Centre for Research and Education in Science and Technology (CREST) campus. We present the primary mirror segmentation details, its ideal optical performance, and study each designs advantages and technical complexities. Based on the above analysis, we have narrowed it down to an optimal design, and its performance analysis is also discussed. Indian Academy of Sciences 2024. -
Synergistic fabrication, characterization, and prospective optoelectronic applications of DES grafted activated charcoal dispersed PVA films
This study investigates the synthesis, analysis, and utility of films comprising deep eutectic solvent (DES) grafted activated charcoal (AC) within a polyvinyl alcohol (PVA) matrix for optoelectronic device applications. The fabrication process involves the dispersion of DES functionalization AC into the PVA solution, followed by casting onto substrates with controlled drying. Comprehensive characterization encompassing X-ray diffraction (XRD), scanning electron microscopy (SEM), UVvis spectroscopy, Fourier-transform infrared spectroscopy (FTIR), and impedance spectroscopy which discerns the films microstructure, morphology, conductance, band-gap, and optical traits. The DES grafted AC infusion with variable concentration has significantly influenced optical absorbance and reduced the band gap indicating efficient charge mobility. Furthermore, the impedance analysis has revealed the electrical conduction of the film to be 1.8 10?6 ??1 m?1. In summary, the dispersion of DES modified AC in the PVA matrix have converted the insulating PVA to a semiconducting polymeric film with reduced band-gap and increased absorption, which present a propitious avenue for wide array of optoelectronic devices, such as thin film transistors, photovoltaics, LEDs, photodetectors, and many such applications. 2024 The Authors. Polymers for Advanced Technologies published by John Wiley & Sons Ltd. -
Defiance in the Shadows: Flames of Resilience in the Selected North Korean Memoirs
The resilient autobiography focuses on the interpersonal dynamics of life narratives, including the relationships that have exacerbated the hardships described and the ones that have provided the support and strength necessary to overcome them. The selected text for this paper is A Thousand Miles to Freedom: My Escape from North Korea by Eunsun Kim and Sebastien Falletti and In Order to Live: A North Korean Girls Journey to Freedom by Yeonmi Park and Maryanne Vollers. These two texts talk about their catastrophic journey from North Korea because of poverty caused by famine and their migration to China, where they were trafficked and subjected to humiliation and their final escape to South Korea. The memoirs depict the individual?s embodiment of resilience as they narrate their own struggles and victories in overcoming hardship. Resistance to adversity and suffering, as well as the ability to bounce back from painful experiences in one?s own life and in the lives of others, are the hallmarks of resilience. Trauma becomes ingrained in attempts for survival in both memoirs, which illustrate the catastrophic impacts of famine, relocation, and personal loss. One effective approach to enhance resilience is reorganizing and reestablishing control over one's life after a traumatic event. Interpretations and writings of the personal narrative are offered from both the subject?s and an outsider?s points of view. Thus, the life story is formed in a dual sense: autobiographically and biographically. 2024 Sciedu Press. All rights reserved. -
Investigating the dynamics, synchronization and control of chaos within a transformed fractional SamardzijaGreller framework
In this article, in response to the limitations of existing ecological models, we address the critical need for a more comprehensive understanding of predatorprey dynamics by presenting a modified fractional SamardzijaGreller model that incorporates intra- and inter-species competitions within two predator populations. Our model stands out for being more realistic because it considers the natural competition that occurs among and between two predator species when they share a common prey We derived the local stability conditions at equilibrium points using RouthHurwitz conditions for the modified model. With the help of a suitably chosen Lyapunov function, we also obtained the global stability condition for our fractional model. The existence of chaos has been confirmed through Lyapunov exponents and bifurcation in the new system for two distinct sets of initial conditions for different fractional orders. Employing the active control method, we establish conditions for synchronization between these two fractional systems and introduce control functions for chaos management in the modified model. Numerical simulations, utilizing the generalized AdamsBashforthMoulton method, support the theoretical findings across a spectrum of fractional orders ranging from 0 to 1. We demonstrated the adaptability of the active control method for different fractional orders. A fractional order of ? equal to 1 for synchronization shows rapid convergence, but a drop to ? equal to 0.80 causes a substantial slowdown that takes almost six times more number of iterations to complete. Thus, we shed light on how the fractional order of the system plays a pivotal role in determining the speed of synchronization, with lower orders leading to a noticeable delay and higher fractional orders favoring faster synchronization. Our thorough investigation contributes to the understanding of complex ecological systems and offers practical insights into fractional chaos control mechanisms within the context of predatorprey models. 2024 Elsevier Ltd -
Enhancing rainwater harvesting and groundwater recharge efficiency with multi-dimensional LSTM and clonal selection algorithm
Rainwater harvesting stands out as a promising solution to alleviate water scarcity and alleviate pressure on conventional water reservoirs. This work introduces a pioneering strategy to elevate the efficiency of rainwater harvesting systems through the fusion of Multi-Dimensional Long Short-Term Memory (LSTM) networks and the Clonal Selection Algorithm (CSA). The Multi-Dimensional LSTM networks serve to model intricate temporal and spatial rainfall patterns, enabling precise predictions regarding the optimal times and locations for rainwater abundance. This insight is pivotal in refining the design and operation of rainwater harvesting setups. Drawing inspiration from the immune system, the Clonal Selection Algorithm is employed to optimize site selection and resource allocation, ensuring the maximal utilization of harvested rainwater. The adaptability and robustness of CSA prove invaluable in tackling the dynamic nature of rainfall patterns. This research endeavor is dedicated to enhancing groundwater levels and optimizing its sources through the implementation of efficient harvesting techniques. By delving into innovative methodologies, it aims to contribute significantly to sustainable water management practices and ensure a reliable supply of groundwater for various societal needs. The experiments are conducted to study the effectiveness of rainwater harvesting systems, where the proposed method achieves increased efficiency, thereby reducing dependence on conventional water sources and contributing to sustainable water management practices. The proposed CSA-LSTM model demonstrates superior performance compared to ACO-ANN and PSO-BPNN, achieving higher training, testing, and validation accuracies while exhibiting lower training, testing, and validation losses. Additionally, CSA-LSTM showcases excellent site suitability, high resource utilization, and robustness to changes, with a fast response time, emphasizing its potential for efficient and effective applications. 2024 Elsevier B.V. -
Boosting productive capacity in OECD countries: Unveiling the roles of geopolitical risk and globalization
This study examines the intertwined effects of geopolitical risk and globalization on productive capacity (the measure of economic cycles) in 20 Organisation for Economic Cooperation and Development (OECD) countries from 2000 to 2021. The panel threshold regression and Driscoll-Kraay standard error estimations highlight the positive impact of globalization on productive capacity. Still, they are underscored by the negative effect of geopolitical risk. The study also unveils a synergistic relationship, demonstrating that the combined influence of globalization and geopolitical risk can amplify productive capacity under specific conditions. Government effectiveness and innovation have positive effects on productive capacities. These findings underscore the need for balanced policies that leverage global economic integration while ensuring geopolitical stability, and offering nuanced insights to guide strategic decision-making for sustained economic cycles. 2024 Elsevier Inc. -
Social entrepreneurial opportunity recognition among higher education students: scale development and validation
Purpose: This study aims to develop and validate a multidimensional scale to measure the motivating factors that lead to opportunity recognition in social entrepreneurship among higher education institute (HEI) students. Design/methodology/approach: The scale was developed through two phases; in phase 1, semi-structured interviews with social entrepreneurs and aspiring students were conducted to explore themes for item generation. Phase 2 included developing and validating the scale using exploratory (EFA) and confirmatory factor analysis (CFA). The sample included HEI students (n = 300 for EFA, n = 300 for CFA) with either academic background or volunteering experiences in social entrepreneurship. Findings: A 24-item scale is developed in the study, with six factors measuring the motivating factors influencing opportunity recognition in social entrepreneurship: life experiences, social awareness, social inclination, community development, institutional voids and natural option for a meaningful career. Research limitations/implications: The scale facilitates the development of theories and models in social entrepreneurship. The scale also enables policymakers and social entrepreneurship educators to understand the motivating factors that lead to opportunity recognition among students. It would help them to provide target-specific support to students. Originality/value: To the best of the authors knowledge, this study is the first attempt to develop a scale that measures opportunity recognition in social entrepreneurship based on specific motivating factors. The study used the model by Yitshaki and Kropp (2016) as the conceptual framework. This study is the first attempt to triangulate the models findings using a quantitative methodology and through the development of a measurement scale. Besides, the scale adds value to social entrepreneurship research, which lacks empirical research on HEI students. 2024, Emerald Publishing Limited. -
Representation of Cancer in the Digital Space
[No abstract available] -
Synthesis and Characterisation of SrAl2O4: Eu3+ Orange-Red Emitting Nanoparticles
The current study involves the synthesis and characterisation of europium doped strontium aluminate nanophosphors using the solid-state reaction method with varying concentrations of europium. The existence of the SrAl2O4 phase in all samples was verified using X-ray diffraction and FTIR analysis. The lattice parameters as well as phase fractions were determined using Rietveld refinement. Surface morphology was studied using field emission scanning electron microscope. Using the Tauc plot method acquired from the diffuse reflectance spectra, the band gaps of the samples were determined and it was found that the doped samples possess lower band gaps compared to the host. Our findings demonstrate that these nanophosphors exhibiting bright orange-red emission under UV excitation with quantum efficiency 70.68%, can be applied for display and fluorescence imaging. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
Study of nanofluid flow in a stationary cone-disk system with temperature-dependent viscosity and thermal conductivity
The substantial temperature gradient experienced by systems operating at relatively high temperatures significantly impacts the transport characteristics of fluids. Hence, considering temperature-dependent fluid properties is critical for obtaining realistic prediction of fluid behavior and optimizing system performance. The current study focuses on the flow of nanofluids in a stationary cone-disk system (SCDS), taking into account temperature-dependent thermal conductivity and viscosity. The influence of Brownian motion, thermophoresis, and Rosseland radiative flux on the heat transport features are also examined. The Reynolds model for viscosity and Chiam's model for thermal conductivity are employed. The Navier-Stokes equation, the energy equation, the incompressibility condition, and the continuity equation for nanoparticles constitute the governing system. The Lie-group transformations lead the self-similar ordinary differential equations, which are then solved numerically. Multi-variate non-linear regression models for the rate of heat and mass transfers on the disk surface were developed. Our study reveals a notable decrease in the rate of heat and mass transfer when pre-swirl exists in the flow. The significant influence of nanofluid slip mechanisms on the effective temperature and nanofluid volume fraction (NVF) within the system is highlighted. Furthermore, the variable viscosity property enhances the temperature and NVF of the SCDS. 2024 Author(s).