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Analysis of Challenges Experienced by Students with Online Classes During the COVID-19 Pandemic
In the current context of the COVID-19 pandemic, due to restrictions in mobility and the closure of schools, people had to shift to work from home. India has the worlds second-largest pool of internet users, yet half its population lacks internet access or knowledge to use digital services. The shift to online mediums for education has exposed the stark digital divide in the education system. The digitization of education proved to be a significant challenge for students who lacked the devices, internet facility, and infrastructure to support the online mode of education or lacked the training to use these devices. These challenges raise concerns about the effectiveness of the future of education, as teachers and students find it challenging to communicate, connect, and assess meaningful learning. This study was conducted at one of the universities in India using a purposive sampling method to understand the challenges faced by the students during the online study and their satisfaction level. This paper aims to draw insight from the survey into the concerns raised by students from different backgrounds while learning from their homes and the decline in the effectiveness of education. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Ar-HGSO: Autoregressive-Henry Gas Sailfish Optimization enabled deep learning model for diabetic retinopathy detection and severity level classification
Diabetic Retinopathy (DR) is one the most important problems of diabetics and it directs to the main cause of blindness. When proper treatment is afforded for DR patients, almost 90% of patients are protected from visual damage. DR does not produce any symptoms at the initial phase of the disease, thus various physical assessments, namely pupil dilation, visual acuity test, and so on are needed for DR disease detection. It is more complex to detect the DR during manual testing, because of the variations and complications of DR. The early detection and appropriate treatment assist to prevent vision loss for DR patients. Thus, it is very indispensable to categorize the levels and severity of DR for recommendation of essential treatment. In this paper, Autoregressive-Henry Gas Sailfish Optimization (Ar-HGSO)-based deep learning technique is proposed for DR detection and severity level classification of DR and Macular Edema (ME) based on color fundus images. The segmentation process is more essential for proper detection and classification process, which segments the image into various subgroups. The Deep Learning approach is utilized for effective identification of DR and severity classification of DR and ME. Moreover, the deep learning technique is trained by the designed Ar-HGSO scheme for obtaining better performance. The performance of the devised technique is evaluated using the IDRID dataset and DDR dataset. The introduced Ar-HGSO-based deep learning approach obtained better performance than other existing DR detection and classification techniques with regards to testing accuracy, sensitivity, and specificity of 0.9142, 0.9254, and 0.9142 using the IDRID dataset. 2022 Elsevier Ltd -
FACVO-DNFN: Deep learning-based feature fusion and Distributed Denial of Service attack detection in cloud computing
Cloud computing offers a broad range of resource pools for conserving a huge quantity of information. Due to the intrusion of attackers, the information that exists in the cloud is threatened. Distributed Denial of Service (DDoS) attack is the main reason for attacks in the cloud. In this study, a Fractional Anti Corona Virus Optimization-based Deep Neuro-Fuzzy Network (FACVO-based DNFN) is devised for detecting DDoS in the cloud. The production of log files, feature fusion, data augmentation, and DDoS attack detection is the processing stages involved in this phase of the DDoS attack detection process. The feature fusion is carried out by RV coefficient and Deep Quantum Neural Network (Deep QNN), and the data augmentation is performed. Then, the Anti Corona Virus Optimization (ACVO) method and Fractional Calculus (FC) are both incorporated to create the FACVO algorithm. The DNFN is trained by the created FACVO algorithm, which identifies the DDoS attack. The proposed approach achieved testing accuracy, TPR, TNR, and precision values of 0.9304, 0.9088, 0.9293, and 0.8745 for using the NSL-KDD dataset without attack, and 0.9200, 0.8991, 0.9015, and 0.8648 for using the BoT-IoT dataset without attack. 2022 Elsevier B.V. -
Movie Success Prediction from Movie Trailer Engagement and Sentiment Analysis
The diverse movie industry faces many challenges in the promotion of the product across different demographics. Movie trailer engagements provide valuable information about how the audience perceives the movie. This information can be used to predict the success of the upcoming movie before it gets released. The previous research works were mainly concentrating on Hindi language movies to predict success. The current research paper includes the success prediction of movies other than Hindi. This paper aims to analyze various Machine Learning models performance and select the best performing model to predict movie success. The developed model can efficiently classify successful and unsuccessful movies. For the current research, the data is collected from various sources through web scrapping and API calls in Sacnilk, The Movie Database (TMDB), YouTube, and Twitter. Different machine learning classification models such as Random Forest, Logistic Regression, KNN, and Gaussian Nae Bayes are tested to develop the best-performing prediction model. This research can help moviemakers to understand the popularity of the movie among the viewers and decide on an efficient promotional strategy to make the movie more successful. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Tailoring the properties of tin dioxide thin films by spray pyrolysis technique
Nanostructured transparent conducting SnO2 thin films have been grown on glass substrates via an environmentally benign chemical route viz spray pyrolysis. All samples were grown for various concentrations of precursor solution with the substrate kept at 350 C maintaining a spray rate of 10 mL/min. The characterizations revealed orthorhombic crystal structure with preferential growth in (112) plane for all samples. Ellipsometric analysis confirmed the good quality of the films. The sample prepared at 0.2 M concentration of precursor solution showed average transmission of 60% in the visible region with maximum conductivity of 24.86 S/cm. As synthesized samples exhibited overall Photoluminescence (PL) emission colours of green, greenish white and bluish white depending on the intensities of excitonic and oxygen vacancy defect level emissions. 2021 Elsevier B.V. -
P type copper doped tin oxide thin films and p-n homojunction diodes based on them
P-type copper doped tin oxide (SnO2:Cu) thin films were prepared by chemical spray pyrolysis method on glass substrates for different doping concentrations. Their structural, optical, surface morphological, elemental and electrical studies were investigated. We fabricated two transparent homojunction diodes using optimized sample of SnO2:Cu which are p- SnO2:Cu/n-SnO2 and p-SnO2:Cu/n- SnO2:F.These diodes are reported for the first time by this method. 2021 Elsevier B.V. -
Augmented intelligent water drops optimisation model for virtual machine placement in cloud environment
Virtual machine placement in cloud computing is to allocate the virtual machines (VMs) (user request) to suitable physical machines (PMs) so that the wastage of resources is reduced. Allocation of appropriate VMs to suitable and effective PMs will lead the service provider to be a better competitor with more available resources for affording a greater number of VMs simultaneously which in turn reflects with the growth in the economy. In this research work, an augmented intelligent water drop (IWD) algorithm is used for effectively placing VMs. The preliminary goal of this proposed work is to reduce the overall resource utilisation by packing the VMs to appropriate PMs effectively. The proposed IWD model is tested under the standard simulation process as it is given in the literature. Performance of IWD is compared with the existing techniques first fit decreasing, least loaded and ant colony optimisation algorithm. Performance analysis shows the significance of the proposed method over existing techniques. The Institution of Engineering and Technology 2020. -
An enhanced network intrusion detection system for malicious crawler detection and security event correlations in ubiquitous banking infrastructure
Purpose: In the recent era, banking infrastructure constructs various remotely handled platforms for users. However, the security risk toward the banking sector has also elevated, as it is visible from the rising number of reported attacks against these security systems. Intelligence shows that cyberattacks of the crawlers are increasing. Malicious crawlers can crawl the Web pages, crack the passwords and reap the private data of the users. Besides, intrusion detection systems in a dynamic environment provide more false positives. The purpose of this research paper is to propose an efficient methodology to sense the attacks for creating low levels of false positives. Design/methodology/approach: In this research, the authors have developed an efficient approach for malicious crawler detection and correlated the security alerts. The behavioral features of the crawlers are examined for the recognition of the malicious crawlers, and a novel methodology is proposed to improvise the bank user portal security. The authors have compared various machine learning strategies including Bayesian network, support sector machine (SVM) and decision tree. Findings: This proposed work stretches in various aspects. Initially, the outcomes are stated for the mixture of different kinds of log files. Then, distinct sites of various log files are selected for the construction of the acceptable data sets. Session identification, attribute extraction, session labeling and classification were held. Moreover, this approach clustered the meta-alerts into higher level meta-alerts for fusing multistages of attacks and the various types of attacks. Originality/value: This methodology used incremental clustering techniques and analyzed the probability of existing topologies in SVM classifiers for more deterministic classification. It also enhanced the taxonomy for various domains. 2021, Emerald Publishing Limited. -
Serendipitous detection of an intense X-ray flare in the weak-line T Tauri star KM Ori with SRG/eROSITA
Weak-line T Tauri stars (WTTS) exhibit X-ray flares, likely resulting from magnetic reconnection that heats the stellar plasma to very high temperatures. These flares are difficult to identify through targeted observations. Here, we report the serendipitous detection of the brightest X-ray flaring state of the WTTS KM Ori in the eROSITA DR1 survey. Observations from SRG/eROSITA, Chandra X-ray Observatory, and XMM-Newton are analysed to assess the X-ray properties of KM Ori, thereby establishing its flaring state at the eROSITA epoch. The long-term (1999-2020) X-ray light curve generated for the Chandra observations confirmed that eROSITA captured the source at its highest X-ray flaring state recorded to date. Multi-instrument observations support the X-ray flaring state of the source, with time-averaged X-ray luminosity reaching at the eROSITA epoch, marking it the brightest and possibly the longest flare observed so far. Such intense X-ray flares have been detected only in a few WTTS. The X-ray spectral analysis unveils the presence of multiple thermal plasma components at all epochs. The notably high luminosity , energy (erg), and the elevated emission measures of the thermal components in the eROSITA epoch indicate a superflare/megaflare state of KM Ori. Additionally, the H line equivalent width of from our optical spectral analysis, combined with the lack of infrared excess in the spectral energy distribution, were used to re-confirm the WTTS (thin disc/disc-less) classification of the source. The long-duration flare of KM Ori observed by eROSITA indicates the possibility of a slow-rise top-flat flare. The detection demonstrates the potential of eROSITA to uncover such rare, transient events, thereby providing new insights into the X-ray activity of WTTS. The Author(s), 2025. Published by Cambridge University Press on behalf of Astronomical Society of Australia. -
Long-term Optical and ?-Ray Variability of the Blazar PKS 1222+216
The ?-ray emission from flat-spectrum radio quasars (FSRQs) is thought to be dominated by the inverse Compton scattering of the external sources of photon fields, e.g., accretion disk, broad-line region (BLR), and torus. FSRQs show strong optical emission lines and hence can be a useful probe of the variability in BLR output, which is the reprocessed disk emission. We study the connection between the optical continuum, H? line, and ?-ray emissions from the FSRQ PKS 1222+216, using long-term (?2011-2018) optical spectroscopic data from Steward Observatory and ?-ray observations from Fermi Large Area Telescope (LAT). We measured the continuum (F C,opt) and H? (F H? ) fluxes by performing a systematic analysis of the 6029-6452 optical spectra. We observed stronger variability in F C,opt than F H? , an inverse correlation between the H? equivalent width and F C,opt, and a redder-when-brighter trend. Using discrete cross-correlation analysis, we found a positive correlation (DCF ? 0.5) between the F ??ray>100 MeV and F C,opt (6024-6092 light curves with a time lag consistent with zero at the 2? level. We found no correlation between the F ??ray>100 MeV and F H? light curves, probably dismissing the disk contribution to the optical and ?-ray variability. The observed strong variability in the Fermi-LAT flux and F ??ray>100 MeV ? F C,opt correlation could be due to the changes in the particle acceleration at various epochs. We derived the optical-to-?-ray spectral energy distributions during the ?-ray flaring and quiescent epochs that show a dominant disk component with no variability. Our study suggests that the ?-ray emission zone is likely located at the edge of the BLR or in the radiation field of the torus. 2022. The Author(s). Published by the American Astronomical Society. -
Soft excess in AGN with relativistic X-ray reflection
The soft X-ray excess, emission below (Formula presented.) 2keV over the X-ray power-law, is a marked spectral component in the X-ray spectra of many Seyfert1 galaxies. We investigate if the observed soft X-ray excess in a sample of Seyfert1s is in accordance with the prediction of the relativistic reflection model by analyzing the XMM-Newton and NuSTAR spectra. The fractional difference in the soft excess (SE) obtained from the blurred reflection emission predicted (from NuSTAR) and the observed (from XMM-Newton) luminosities show that the reflection model underestimates the SE emission in our sample. The results point to alternative models (for example, warm Comptonization) to explain the soft X-ray excess in AGN. 2023 Wiley-VCH GmbH. -
Analysis of the Performance of a 5-Level Modular Multilevel Inverter for a Solar Grid-Connected System
The main purpose of a multilevel inverter is to combine numerous levels of DC voltage to create a nearly sinusoidal voltage. The synthesized output waveform has more stages as the number of levels rises, creating a staircase ripple which resembles the preferred waveform. As the number of voltage levels rises, the output waves harmonic distortion diminishes and eventually approaches zero. In particular, the performance analysis of a five-level inverter with variable loads is highlighted in this paper. This topology has fewer devices than traditional multilevel inverters for the same five output levels, which makes it more affordable due to lesser driver circuits. The proposed modular five level topology is simulated using both high frequencies switching pulse width modulation and basic frequency switching modulation techniques. The output voltage, current waveform, and total harmonic distortion are examined and compared using simulink to confirm the viability of the modular multilevel inverter topology. 2024, TUBITAK. All rights reserved. -
Development of effective charging station for EVs using multiport converter and photovoltaic cell integration
The adoption of electric vehicles (EVs) is increasing rapidly as a response to the urgent need to reduce greenhouse gas emissions and dependence on fossil fuels. However, the deployment of a reliable and cost-effective EV charging infrastructure remains a challenge. To address this challenge, this paper proposes the development of an effective charging station using multiport converter and photovoltaic cell integration. A promising approach in the transportation sector is an efficient charging station with multiport converter and photovoltaic cell integration. A multiport converter, photovoltaic cells, a battery energy storage system, and an electric vehicle charging port constitute the proposed charging station. The power flow between the photovoltaic cells, the battery energy storage system, and the electric vehicle charging port is controlled by the multiport converter. The excess energy generated by the photovoltaic cells is stored in the battery energy storage system. The proposed charging station is designed and analysed using MATLAB/Simulink. The simulation results show that the proposed charging station is capable of providing an electric vehicle a reliable and consistent power supply. In contrast to conventional charging stations, the proposed charging station is also capable of offering a faster charging rate. 2024 Nova Science Publishers, Inc. All rights reserved. -
Analysis of the Effectiveness of a Two-Stage Three-Phase Grid-Connected Inverter for Photovoltaic Applications
This paper proposes a two-stage three-phase grid-connected inverter for photovoltaic applications. The proposed inverter topology consists of a DC-DC boost converter and a three-phase grid-connected inverter. The DC-DC boost converter is used to boost the low voltage DC output of the PV array to a high voltage DC level that is suitable for feeding into the grid-connected inverter. The three-phase grid-connected inverter is used to convert the high voltage DC output of the boost converter into a three-phase AC output that is synchronized with the grid voltage. The proposed inverter topology offers several advantages over traditional single-stage inverters. Firstly, the DC-DC boost converter allows for the use of a smaller, more efficient inverter in the second stage, reducing the overall cost of the system. Secondly, the use of a boost converter allows for the maximum power point tracking of the PV array, which can increase the overall efficiency of the system. The proposed inverter topology offers improved control of the grid current, reducing the impact of the PV system on the grid. The proposed topology has been simulated using MATLAB/Simulink and the results show that the system is capable of delivering a high-quality three-phase AC output with low harmonic distortion. The Author(s). Publisher: University of Tehran Press. -
Enhancing power conversion efficiency in five-level multilevel inverters using reduced switch topology
This paper presents extensive research on improving the power conversion efficiency of five-level multilevel inverters (MLIs) by utilizing a reduced switch topology. MLIs have received an abundance of focus because of their ability to generate high-quality output waveforms and have better harmonic outcomes than traditional two-level inverters. The high number of switches in MLIs, on the other hand, can result in increased power losses and lower overall efficiency. In this paper, a novel reduced switch topology for five-level MLIs, which is having five switches is proposed with the aim of minimizing power losses while preserving superior performance due to lesser number of switches. To achieve efficient power conversion, the proposed topology employs advanced pulse width modulation control strategies and optimized switching patterns. The simulation results show that the minimized switch topology improves the power conversion efficiency of the five-level MLI, resulting in lower losses and better overall system performance. The total harmonic distortion (THD) value of the output current has been reduced to 7.12% and the efficiency has been achieved to 96.92%. The findings of this investigation help to advance MLI technology, allowing for more efficient and reliable power conversion in a variety of applications such as renewable energy systems, electric vehicles, and industrial drives. 2024, Institute of Advanced Engineering and Science. All rights reserved. -
Investigation on window opening behavior in naturally ventilated hostels of warm and humid climate
A window is an inevitable element of a naturally ventilated building, and its usage improves indoor environmental conditions. Various research has presented window opening behavior models, stating that it may vary with region, climate, season, building type and many more environmental and non-environmental factors. Major studies in India relied on survey data and were not focused on continuous monitoring. Limited occupants behavior studies have been reported in warm and humid climatic zones, specifically in hostel buildings. Also, a realistic description of occupants window opening behavior is require for more accurate evaluation of building performance using energy simulation. Therefore, there is a need to study the window opening behavior to predict the indoor environment more accurately by using energy simulation tools. In this context, a one-year field research involving questionnaire survey, physical observation, and monitoring was conducted in different hostel buildings in Tiruchirappalli, India. Logistic models were developed to predict the window state in hostel buildings in warm and humid region based on physical observational and long-term monitoring data. It is found that window use is influenced by season, time of the day, weekdays, floor level, buildings orientation, user type, and gender. Results also showed that insects and animal menace (snakes, squirrels, lizards, mosquitoes etc.) impede window opening behavior. The study also presented a logistic model for window opening behavior based on outdoor environment conditions for simulation modeling. 2022 Elsevier B.V. -
Fabrication of NiO nanoparticles modified with carboxymethyl cellulose and D-carvone for enhanced antimicrobial, antioxidant and anti-cancer activities
Colon cancer is a deadly disease while pathogens such as Klebsiella pneumoniae (K. pneumoniae), Shigella dysenteriae (S. dysenteriae), Bacillus subtilis (B. subtilis), Staphylococcus aureus (S. aureus), and Candida albicans (C. albicans) are serious threat to the human health due to their persistent nature and resistant to conventional drugs. This study aims to develop NiO nanoparticles via single one pot chemical approach and to modifying them with natural molecules carboxymethyl cellulose and D-carvone to enhance antioxidant, anticancer and antibacterial activity. The NiO and NiO-CMC-Dcar exhibit fcc structure confirmed by XRD. The band gap values were found be 4.15 eV for NiO and 4.23 eV for NiO-CMC-Dcar nanocomposite. DLS study confirmed that the mean particles diameter of NiO and NiO-CMC-Dcar were 154.1 nm and 130.3 nm respectively. The TEM and SEM analysis confirmed that both NiO and NiO-CMC-Dcar samples were roughly spherical. PL emission spectra of NiO-CMC- Dcar nanoparticles at 426 nm and 506 nm indicate the electronic structural modification due to incorporation of CMC and Dcar molecules in to NiO materials. The green emission observed at 506 nm is due to oxygen vacancy that can be correlated to production of more reactive oxygen species (ROS) to kill microorganism. The experimental results show that the NiO-CMC- Dcar nanoparticles exhibit enhanced antimicrobial, anticancer and antioxidant activity when compared to NiO alone. 2024 Elsevier B.V. -
Self-Powered Dynamic Glazing Based on Nematic Liquid Crystals and Organic Photovoltaic Layers for Smart Window Applications
Dynamic windows allow monitoring of in-door solar radiation and thus improve user comfort and energy efficiency in buildings and vehicles. Existing technologies are, however, hampered by limitations in switching speed, energy efficiency, user control, or production costs. Here, we introduce a new concept for self-powered switchable glazing that combines a nematic liquid crystal, as an electro-optic active layer, with an organic photovoltaic material. The latter aligns the liquid crystal molecules and generates, under illumination, an electric field that changes the molecular orientation and thereby the device transmittance in the visible and near-infrared region. Small-area devices can be switched from clear to dark in hundreds of milliseconds without an external power supply. The drop in transmittance can be adjusted using a variable resistor and is shown to be reversible and stable for more than 5 h. First solution-processed large-area (15 cm2) devices are presented, and prospects for smart window applications are discussed. 2023 American Chemical Society. -
Hindu nationalism and media violence in news discourses in India
The mainstream media and communication discourses in India in the present times engender media violence embedded in the dominant productions of Hinduism together with aspirations for neoliberal development. The media violence engenders indigenous forms of racism and colonialism. This article attempts to examine the nature of these productions through critical theories of postcoloniality and decolonial approaches put into conversation with theories of journalism. Through the examination of the instances of selective silencing of journalistic voices, and erasures embedded within the journalistic practices, this article argues for critical theories of press freedom. The productions of racial superiority and internal colonialism in India only begin to make sense when read together with the interplays of religion, class, caste, and global reach of the privileged sections of Indian society, namely the civil society. Against the backdrop of the historical role of the press in India in freedom struggle against colonial rule, the history of press censorship after independence, the civil society voices that are amplified in the neoliberal restructuring of news media, and the Dalit movements that expose the Brahminical dominance in the imaginary of the Indian culture, the meanings of race and coloniality in India unfold. 2020 National Communication Association.