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Novel Deep Neural Network Based Stress Detection System
Stress is a state of tension on an emotional or bodily level. Frustration, despair, anxiety, and other mental health problems can all be brought on by Stress. Strain is a side effect of Stress. People can openly share their views and opinions on social media networking sites like Twitter and Facebook, which are highly popular. The COVID 19 pandemic has wreaked havoc on millions of peoples lives all across the world. The public has experienced Stress as a result of the various measures employed to stop the spread of COVID 19, including confinement and social isolation. The current research seeks to develop an unique COVID 19 scenario-based deep neural network-based Stress detection system using tweets related to COVID 19. We use deep learning to create three models. RNN with single LSTM layer, two layers of LSTM with RNN followed by bidirectional LSTM layer is built to detect Stress for the considered dataset. A number of recurrent neural networks are built upon the Keras layers. The optimization algorithm called RMSProp and Sigmoid activation function is used. It is observed that RNN with 2 layers of LSTM outperforms the other deep learning architectures constructed. 2023 American Institute of Physics Inc.. All rights reserved. -
Novel deep eutectic solvent catalysed Single-Pot open flask synthesis of Tetrasubstituted-1H-Pyrroles
Pyrrole and its analogs have garnered immense attention due to their multifaceted biological significance and versatile applications, ranging from medicinal agents to fundamental biological pigments. Despite their prominence, pyrrole synthesis with multiple substituents is complex and calls for innovative approaches to green chemistry. This study delves into synthesizing novel 3,5-dimethyl-1H-pyrroles via multicomponent reactions (MCRs) employing deep eutectic solvents (DES). Due to their eco-friendly nature, these DESs provide a safer substitute for traditional solvents. Specifically, a novel three-component DES (3CDES) was formulated, showcasing promising catalytic activity for multiple cycles with excellent product generation. The synergy between MCR and DES elucidates their combined potential in fostering a sustainable and efficient green synthesis route with the E-factor of 0.1699. 2024 Elsevier B.V. -
Novel carbon nano-onions from paraffinum liquidum for rapid and efficient removal of industrial dye from wastewater
Carbon nano-onions (CNOs) are fascinating zero-dimensional carbon materials owning distinct multi-shell architecture. Their physicochemical properties are highly related to the parent material selected and the synthesis protocol involved. In the present work, we report for the first time novel CNO structures encompassing discrete carbon allotropes, namely, H18 carbon, Rh6 carbon, and n-diamond. These structures were cost-effectively synthesized in gram scale by facile flame pyrolysis of paraffinum liquidum, a highly refined mineral oil. The as-synthesized and chemically refashioned CNOs are quasi-spherical self-assembled mesopores, manifesting remarkable stability and hydrophilicity. The CNO structures exhibit excellent dye adsorption characteristics with high removal capacity of 1397.35mg/g and rapid adsorption kinetics with a minimal adsorbent dosage of 10mg/L, for a low concentration of 20mg/L methylene blue dye. The novel CNOs assure potential implementation in the remediation of low concentration and high volume of dye-contaminated wastewater. Graphical abstract [Figure not available: see fulltext.] 2020, Springer-Verlag GmbH Germany, part of Springer Nature. -
Novel booster control system for fully automotive driverless vehicle /
Patent Number: 201941039882, Applicant: Dr. Debabrata Samanta.
The present disclosure presents a novel electronic booster control system for fully automotive driverless vehicle. The it discloses a system of vacuum booster with an automotive air compressor system which comprises a compression piston, a power transmission component and a power input part with integrated to plurality of sensors , servo controllers and a central control module of the fully automotive driverless vehicle. -
Novel biocompatible zinc oxide nanoparticle synthesis using Quassia indica leaf extract and evaluation of its photocatalytic, antimicrobial, and cytotoxic potentials
Prognostic research points to the necessity and relevance of revamping polluted environments. The toxic effect of textile dyes released into waterbodies can be reduced by the degradation process and alternate methods in nanotechnology are used to lessen the gravity of the situation. Compared with chemical and physical NP synthesis, plant extract-based nanoparticle synthesis is an environmentally friendly alternative method, and the use of waste leaves in this process is an added advantage. Quassia indica zinc oxide nanoparticles (QI-ZnO NPs) were synthesised in the current work employing a simple and cost-effective process using Q. indica leaf extract. The surface plasmon peak was visible in the UV-Vis absorption spectrum of the decreased reaction mixture at 346 nm. The average crystallite size of the QI-ZnO NPs was found to be 16.66 nm. The QI-ZnO NPs were found to have a stable zeta potential of ?28.4 mV. The surface morphology of the optimised QI-ZnO NPs was observed to be hexagonal using field emission scanning electron microscopy and high-resolution transmission electron microscopy. Under UV light irradiation, the photocatalytic degradation of industrial textile dyes Reactive Blue-220, Reactive Yellow-145, Reactive Red-120, and Reactive Blue-222 showed degradation efficiency of 8090%. Antibacterial and antifungal activity was assessed using well diffusion on gram-positive and gram-negative microorganisms. When administered to the A549 and MDA-MB-231 cancer cell lines, QI-ZnO NPs displayed significant anticancer activities. Limited studies in the area of plant extract-based nanoparticle synthesis mark the novelty of this attempt and this trailblazing and pioneering approach using non-toxic QI-ZnO NPs synthesised through green synthesis is futuristic and sustainable helping in effective wastewater treatment. Graphical abstract: [Figure not available: see fulltext.] 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Novel approaches for nonlinear Sine-Gordon equations using two efficient techniques
In this work, we obtained a new functional matrix using Clique-polynomials of complete graphs (Formula presented.) with (Formula presented.) vertices and considered a new approach to solving the SineGordon (SG) equation. The clique polynomial method transforms this equation into a system of algebraic equations. The solution will be drawn with the help of Newton Raphsons method. Also, we employed the q-homotopy analysis transform method (q-HATM), which is the proper collision of the Laplace transform and the q-homotopy analysis method (q-HAM). To witness the reliability and accuracy of the considered schemes, some illustrations of the SG equation and double SG equation are considered. Here, the SG equation is solved easily and elegantly without using discretization or transformation of the equation by using the q-HATM. Also, in q-HATM, the presence of homotopy and axillary parameters allows us to have a large convergence region. The 3D surfaces of acquired solutions are drawn effectively. The tables of error analysis demonstrate the success of these methods. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Novel approach to the analysis of fifth-order weakly nonlocal fractional Schringer equation with Caputo derivative
The main goal of this study is to find solutions for the fractional model of the fifth-order weakly nonlocal Schringer equation incorporating nonlinearity of the parabolic law and external potential using a recent modification of the homotopy analysis method (HAM) called the q-homotopy analysis transform method (q-HATM). A mixture of q-HAM and Laplace transform is the projected solutions procedure. The method contributes approximate and exact (for some special cases) solutions such as the bright soliton, dark soliton, and exponential solutions. The simulation results using Mathematica package software, demonstrate that only a few terms are enough to achieve precise, effective, and reliable approximate solutions. In addition, in terms of plots for varying fractional order, the physical behavior of q-HATM solutions has been depicted and the numerical simulation is also exhibited. The results of q-HATM reveal that the projected method is competitive, reliable, and powerful for studying complex nonlinear models of fractional type. 2021 The Authors -
Novel approach for nonlinear time-fractional Sharma-Tasso-Olever equation using Elzaki transform
In this article, we demonstrated the study of the time-fractional nonlinear Sharma-Tasso-Olever (STO) equation with different initial conditions. The novel technique, which is the mixture of the q-homotopy analysis method and the new integral transform known as Elzaki transform called, q-homotopy analysis Elzaki transform method (q-HAETM) implemented to find the adequate approximated solution of the considered problems. The wave solutions of the STO equation play a vital role in the nonlinear wave model for coastal and harbor designs. The demonstration of the considered scheme is done by carrying out some examples of time-fractional STO equations with different initial approximations. q-HAETM offers us to modulate the range of convergence of the series solution using ?, called the auxiliary parameter or convergence control parameter. By performing appropriate numerical simulations, the effectiveness and reliability of the considered technique are validated. The implementation of the new integral transform called the Elzaki transform along with the reliable analytical technique called the q-homotopy analysis method to examine the time-fractional nonlinear STO equation displays the novelty of the presented work. The obtained findings show that the proposed method is very gratifying and examines the complex nonlinear challenges that arise in science and innovation. 2023 Balikesir University. All rights reserved. -
Novel approach for investigation and synthesis of non linear optical crystal /
Patent Number: 202141040430, Applicant: Ingeniouz.
An amino acid based semiorganic nonlinear optical family single crystal of l-leucinium perchlorate (LLPCl) was grown by the solvent evaporation method at ambient temperature. Good optical quality single crystals up to a size of 6 mm — 5 mm — 3 mm were obtained. The single-crystal XRD analysis shows that the grown crystals have a monoclinic structure. Fourier transform infrared (FTIR) spectral analysis and UVvis spectral studies were also carried out. Micro hardness mechanical studies show that the hardness number (Hv) of a LLPCl single crystal decreases with the load as measured by the Vickers micro hardness method. -
Novel Applications of Graphene and its Derivatives: A Short Review
Graphene, a layered allotropic form of graphitic carbon, has fascinated the scientific world since its discovery. Its unique structural, physical, chemical, mechanical, and electrical properties find application in many areas. Because of its large surface area and its apt electrical property, it is used in electromagnetic interference shielding. With excellent carrier mobility, it is used for sensing purposes. Mechanical strength and elastic properties coupled with its lightweight make graphene a promising material as a supercapacitor. The 2-dimensional structural properties of the graphene layers can be used for the purification treatment of water and gas. The number of research in graphene applications is increasing every day, showing the importance and excellency of graphene properties. This short review provides a comprehensive understanding of graphene's properties and progress in electromagnetic interference shielding, sensors, water treatment, energy production, storage, and conversion applications such as supercapacitors, fuel cells, solar cells and electrocatalysts. 2023 Bentham Science Publishers. -
Novel Anti-Corrosion and Anti-Fouling Coatings and Thin Films
Nanomaterials and nanocomposite materials have been developed as corrosion inhibitors and are the most noble and effective alternatives to traditional organic corrosion inhibitors. Nanomaterials provide reasonably high anticorrosive activity in both aqueous and solution phases. A unified approach to this task is lacking, however, which highlights the role of all disciplines involved in the creation and use of corrosion protection coatings for metals. Fouling is the process of accumulating unwanted material that is mostly non-living and comprised of detritus and organic or inorganic compounds, or organisms, such as tiny viruses up to giant kelps. This book covers both the processes of biofouling and anti(bio)fouling, and the devices that stop the biofouling process. This book provides a missing synopsis by providing an understanding of the anticorrosive and anti-biofouling effects of nanomaterials and nanocomposites under different environments. It features an up-to-date picture of the quality and chemistry of a substrate surface, its proper preparation by conversion treatment, the function of resins and anticorrosive pigments in paints, and novel concepts for corrosion protection. 2024 Scrivener Publishing LLC. -
Novel algorithm for control of a shunt active power filter based on a three-level voltage source inverter
A three-level voltage source inverter is utilized to implement a shunt active power filter. SVPWM technique is used in the control circuit to generate the required gate pulses for the voltage source inverter. Principle of operation and analysis of the control circuit is presented. The proposed control algorithm ensures balance of dc bus voltages. Hence this active power filter is ideally suited for high power drives and transmission systems. The simulation results are presented and analyzed. The THD of load current is reduced to 6.47 % from 28.795 % in steady operation. 2010 Institute of Thermomechanics AS CR. -
Nouveau shoppers buying behavior pattern and perception towards luxury brands
The customer perception towards purchasing luxury brands has various psychological patterns and the behviour towards purchasing such brands differs accordingly. The main objective of the study is to map the nouveau shoppers mind-set towards shopping malls and to analyze the buying behavior pattern and perception towards luxury brand on shopping malls. For this purpose a sample of 130 was collected from the respondents were percentage analysis, descriptive statistics, Kruskall Wallis test and Oneway anova were used as tools to analye the data. The conclusion is that shopping malls have higher potentiality to pull the customers to visit their places but the conversion of making every customers purchasing in the mall is based on various factors of each individual shops. The conversion towards making the consumers purchasing the products can be done to attractive displays and understanding the mindset of modern shoppers towards various products and brand. 2020 Webology Center. -
Notions of beauty, perception and acceptance - How people perceive product advertising /
Beauty has always been an important factor in humanity. It has played a very important role in history, being recorded timeless in various arts. Needless to say it is a very important part of our world, our society and us. Though beauty can be achieved through many means, one of the most popular ways one thinks of achieving it is beauty products. These beauty products have wriggled their ways though our daily lives and have made themselves a staple through their insistent advertising which proclaim that they are the answer to all your beauty related problems. One of their proclamations is that their products help achieve perfection. -
Northeast and its portrayal in broadcast media - A picture beyond terrorism and insurgency /
Northeast India is a rich home of natural beauty and magnificence surrounding the seven sister states of Assam, Arunachal Pradesh, Meghalaya, Manipur, Mizoram, Nagaland, Tripura and the nearby hilly state of Sikkim. In any case it is a bizarre reality that such an inconceivable region of the nation stays inadequately spoken and noticed in the national cognizance. -
Normalized group activations based feature extraction technique using heterogeneous data for Alzheimers disease classification
Several deep learning networks are developed to identify the complex atrophic patterns of Alzheimers disease (AD). Among various activation functions used in deep neural networks, the rectifier linear unit is the most used one. Even though these functions are analyzed individually, group activations and their interpretations are still not explored for neuroimaging analysis. In this study, a unique feature extraction technique based on normalized group activations that can be applied to both structural MRI and resting-state-fMRI (rs-fMRI) is proposed. This method is split into two phases: multi-trait condensed feature extraction networks and regional association networks. The initial phase involves extracting features from various brain regions using different multi-layered convolutional networks. Then, multiple regional association networks with normalized group activations for all the regional pairs are trained and the output of these networks is given as input to a classifier. To provide an unbiased estimate, an automated diagnosis system equipped with the proposed feature extraction is designed and analyzed on multi-cohort Alzheimers Disease Neuroimaging Initiative (ADNI) data to predict multi-stages of AD. This system is also trained/tested on heterogeneous features such as non-transformed features, curvelets, wavelets, shearlets, textures, and scattering operators. Baseline scans of 185 rs-fMRIs and 1442 MRIs from ADNI-1, ADNI-2, and ADNI-GO datasets are used for validation. For MCI (mild cognitive impairment) classifications, there is an increase of 14% in performance. The outcome demonstrates the good discriminatory behaviour of the proposed features and its efficiency on rs-fMRI time-series and MRI data to classify multiple stages of AD. 2024 Vaithianathan et al. -
Normalized Attention Neural Network with Adaptive Feature Recalibration for Detecting the Unusual Activities Using Video Surveillance Camera
Over the past few years, surveillance cameras have become common in many homes and businesses. Many businesses still employ a human monitor of their cameras, despite the fact that this individual is more probable to miss some anomalous occurrences in the video feeds owing to the inherent limitations of human perception. Numerous scholars have investigated surveillance data and offered several strategies for automatically identifying anomalous occurrences. Therefore, it is important to build a model for identifying unusual occurrences in the live stream from the security cameras. Recognizing potentially dangerous situations automatically so that appropriate action may be taken is crucial and can be of great assistance to law enforcement. In this research work, starting with an MRCNN for feature extraction and AFR for fine-tuning, this architecture has a number of key components (AFR). To increase the quality of the features extracted by the MRCNN, the AFR replicas the inter-dependencies among the features to enhance the quality of the low- and high-frequency features extracted. Then, a normalized attention network (NAN) is used to learn the relationships between channels, which used to identify the violence and speeds up the convergence process for training a perfect. Furthermore, the dataset took real-time security camera feeds from a variety of subjects and situations, as opposed to the hand-crafted datasets utilized in prior efforts. We also demonstrate the method's capability of assigning the correct category to each anomaly by classifying normal and abnormal occurrences. The method divided the information gathered into three primary groups: those in need of fire protection, those experiencing theft or violence, and everyone else. The study applied the proposed approach to the UCF-Crime dataset, where it outperformed other models on the same dataset. 2023 WITPress. All rights reserved. -
Nontraditional security: Redefining state-centric outlook /
Jadavpur journal of International Relations, Vol.20, Issue 1, pp.102-124, ISSN: 0973-5984 (Print) 2349-0047 (Online). -
Nontoxic photoluminescent tin oxide nanoparticles for cell imaging: Deep eutectic solvent mediated synthesis, tuning and mechanism
Non-toxic and photoluminescent (PL) tin oxide nanoparticle synthesis in Deep Eutectic Solvents (DESs) is being reported herein. Both radiation (electron beam and ? radiation) and solvothermal methods were employed for the synthesis. An electron beam radiation technique proved to be more appropriate in tuning the size and morphology compared to the solvothermal process. Addition of any external oxido-reductive or stabilizing agent could be avoided by the use of Reline (choline chloride?:?urea; 1?:?2) as the host matrix. Detailed analysis of the PL behaviour of the nanoparticles is another important aspect of this study. The oxygen vacancies and tin interstitials responsible for photoluminescence have been identified from the de-convoluted PL spectra of the nanoparticles. Time dependent PL kinetics depicts PL decay at ?1.2 ns due to near band edge emission and at ?3.15 ns due to defect state emission. The synthetic process has been standardized focusing on the size of the particles by varying all possible experimental parameters such as the temperature, concentration of the precursors, reaction time, dose of irradiation and dose rate. Synthesized nanoparticles have been characterized using XRD, XPS and EDX. TEM images illustrate nanomorphological differences obtained in the two methods. The probable mechanism of synthesis (both radiation and thermal) has been proposed based on the results obtained from transient studies using electron pulses and FTIR experiments. Cytotoxicity data demonstrate that the nanoparticles are suitable for application in biological studies involving cells up to a concentration of 10 ?M. Imaging experiments with these photoluminescent nanoparticles exhibit their ubiquitous distribution including the nucleus of the tumour cells, which signifies potential application of these NPs for targeted drug delivery in cancer chemotherapy. Furthermore, the nanoparticles exhibited excellent antioxidant properties in vitro. The findings herein can open up enormous possibilities for more advanced and dedicated research towards using this cheap and versatile nanomaterial in a variety of biomedical applications. 2021 The Royal Society of Chemistry. -
Nonlocal thermoelastic waves inside nanobeam resonator subject to various loadings
The present article focuses on the new meticulous model based on the postulate of memory-dependent derivatives to analyze the thermo-mechanical interactions inside the nano-beam-based machined resonators. Also, the size effect on dynamic responses of thermoelastic vibrations of homogeneous and isotropic nano-beam is considered. The fundamental expressions are formulated in the frame of non-local generalized thermoelasticity with paired relaxation times by operating the results of Euler-Bernoulli beam theory, non-local effect, and memory-dependent derivative. The proposed model is applied to study the nano-beam-based machined resonator subjected to the ramp-type heating and exponentially decaying time-dependent load. Closed-form solutions of the physical fields are examined by applying the Laplace transform mathematical mechanism. However, the coherence of the new thermal conductivity framework, a collation has been bestowed among the results obtained in the presence or absence of the memory-dependent derivative; also, the size effect is analyzed on the significant parameters of nano-beam such as deflection, temperature, displacement as well as bending moment. Moreover, the prominent influence of the distinct affecting parameters such as constituents of memory-dependent derivative (kernel function and time delay) and ramping time parameter with an applied load on the physical fields have been investigated with the help of quantitative results. 2022 Taylor & Francis Group, LLC.