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Nine Level Quadra Boost Inverter with Modified Level Shifted Pulse Width Modulation Technique
This research initiatives to introduce a switched capacitor based nine level boost inverter (SC-9LBI) powered by modified level shifted pulse width modulation (PWM) technique. The SC-9LBI equipped with single DC source along with three capacitors and eight controlled switches to develop nine level inverter output voltage. The suggested inverter configuration has the ability of boosting the inverter input voltage into 1:4 ratio. Also, this research involves modified level shifted PWM technique to enhance the quality of inverter output voltage. The effectiveness of the NLMLI is assessed through parameters such as harmonic distortion, peak voltage, and output voltage root mean square value (rms). Simulation studies have been conducted using MATLAB/Simulink to evaluate the proposed inverter's performance. 2024 IEEE. -
NIR properties of Be stars in star clusters in the Magellanic Clouds
Magellanic Clouds are the nearby galaxies which are ideal to study the properties of metal poor stellar population. In this study, we explore the near-IR properties of optically identified classical Be stars in 19 star clusters in the Magellanic Clouds. From an optically identified sample of 835 Be stars we obtained the J, H, K magnitudes of 389 stars from the IRSF MCPS catalog. Among these, 247 stars (36.4%) are found in 9 clusters in the Large Magellanic Cloud and 142 stars (55.5%) in 10 clusters in the Small Magellanic Cloud. After correcting for reddening, we studied their NIR properties in the (HK)0 vs (JH)0 diagram. We identified 14 stars with abnormally large near IR excesses, which were removed from the analysis, there by restricting our study to 355 classical Be stars. We propose an extended area in the near-IR (H-K)0 vs (J-H)0 diagram as the diagnostic location of Classical Be stars in the Magellanic Clouds. We identified 14 stars to have near-IR excess, higher than those seen in classical Be stars. From the analysis based on spectral energy distribution and luminosity estimate, we found that 8 candidate Be stars may be Herbig Ae/Be stars. We identified a new sample of 6 sgB[e] stars, which when added to the sparse existing sample of 15 sgB[e] stars in the Magellanic Clouds can provide insight to understand the evolutionary link between sgB[e] stars and Luminous Blue variables. 2017 Elsevier B.V. -
Nitrogen-doped carbonized polymer dots (CPDs) and their optical and antibacterial characteristics: A short review
Substantial advancements in the field of Carbon Dots (CDs) and their derivatives in recent years can be accredited to their tunable properties. Recently Carbonized Polymer Dots (CPDs) are the emerging form in the CDs family, which possesses a typical polymer/Carbon hybrid structure and properties due to its incomplete carbonization. Alteration of various parameters during the synthesis process suggested that the properties of CPDs depend on temperature and pH. It was found that doping of CPDs using nitrogen enhanced its optical properties, thereby being used as biomarkers. CPDs generally hold a strong green and blue emission, while intense red luminescence was observed doping with nitrogen. Photoluminescence Quantum Yield (PLQY) was also found to increase with the increase in doping and temperature. Doped CPDs find several applications, including bio-imaging, LEDs, etc. In this review, we focus on analyzing the increase in efficiency of CPDs with the process of doping considering optical and antibacterial applications. 2021 by the authors. -
Nitrogen-Oxygen Co-Functionalized Waste Cassava Peel-Derived Carbon Dots for White Led
White light emitting diodes (WLEDs)are most sought after, with the broad spectra ranging from cool to warm white light being skillfully utilized to create various modes of lighting effects. The fabrication of WLEDs is generally sophisticated, involving either multiple components emitting in different regions or single-component phosphors with complex elemental compositions. In the present work, WLEDs utilizing solvent-tuned carbon dots derived from waste cassava peel are reported through a facile one-step microwave-assisted solvothermal method. The carbon dots show evident UV absorption and correspondingly emit broad visible light spectra when dispersed in a dimethylformamide (DMF)-polyvinyl alcohol (PVA)blend, making themselves suitable white lightemitting down conversion materials. The successful transformation of a 400nm UV LED into a WLED with a general colour rendering index (CRI) of 83 and colour correlation temperature (CCT) of 4426 K gives a promising future outlook toward developing eco and economic-friendly WLEDs. 2025 Wiley-VCH GmbH. -
Nitrogen-rich dual linker MOF catalyst for room temperature fixation of CO2 via cyclic carbonate synthesis: DFT assisted mechanistic study
The benign synthesis of a novel Zn based Lewis acid-base bifunctional metal-organic framework (ITH-1) and its room temperature catalytic ability for the chemical fixation of carbon dioxide via cyclic carbonate synthesis is reported herein. ITH-1 is characterized by the presence of mono coordinated pendant imidazole groups throughout the framework inducing Lewis basicity. The synthesized material is crystallized in the monoclinic space group as revealed by the Single Crystal X-ray Diffraction Analysis and possesses a 2 D non-planar interdigitated network wherein the neighbouring sheets are connected via strong hydrogen bonding (1.947 . ITH-1 was characterized thoroughly via various physicochemical analyses such as XRD, FT-IR, Raman, FE-SEM, CHN, ICP, TGA and was found thermally stable up to 300 ?C. The co-existence of accessible and active Lewis acid (Zn) Lewis base (imidazole) moieties rendered ITH-1 the potential to catalyse the cycloaddition of CO2 with propylene oxide under solvent and co-catalyst free conditions (~95% conversion) at moderate temperatures with remarkable reusable performance (over 5 times). ITH-1 manifested excellent CO2 conversion even under room temperature and 1 bar pressure in the presence of a co-catalyst. Density Functional Theory (DFT) calculations utilizing M06 functional were exercised to envisage the mechanism behind the successful CO2 conversion by ITH-1 at room temperature and were found to be in clear agreement with the experimental results. 2022 Elsevier Ltd -
NLP-based Health Care- Hospital Recommendation Systems with Online Text Reviews by Patients Satisfaction
Recent times, these recommendations based on reviews play a vital role in the service industry. The hospital is assessing its quality of service using these surveys or studies posted in online forums. The ongoing pandemic also played a vital role in making the online review more popular. These statistical data and visualization are informative in representing the views of patient satisfaction towards health service. As the size of data is large and it is of varied size and format it is difficult to get consolidated results. The users share their emotions and feelings through this review. So, it is a challenge to assess the emotions of the patients. Sentiment analysis using machine learning makes our work easy in evaluating the scores visually. The reviews are analyzed using natural language processing (NLP), and the sentiment of the studies is analysed as positive, negative, and neutral using polarity ranking, which in turn is converted as the recommendation system based on patient reviews. This paper aims to propose a new method of recommending the hospital based on the sentiment of the previous user review. The thought of the user is collected from the various hospitals. The proposed (Healthcare Recommendation System) HRS system has nearly 0.5 mean absolute error, which states that the proposed HRS system is significantly effective. 2023 IEEE. -
NLP-based personal learning assistant for school education
Computer-based knowledge and computation systems are becoming major sources of leverage for multiple industry segments. Hence, educational systems and learning processes across the world are on the cusp of a major digital transformation. This paper seeks to explore the concept of an artificial intelligence and natural language processing (NLP) based intelligent tutoring system (ITS) in the context of computer education in primary and secondary schools. One of the components of an ITS is a learning assistant, which can enable students to seek assistance as and when they need, wherever they are. As part of this research, a pilot prototype chatbot was developed, to serve as a learning assistant for the subject Scratch (Scratch is a graphical utility used to teach school children the concepts of programming). By the use of an open source natural language understanding (NLU) or NLP library, and a slack-based UI, student queries were input to the chatbot, to get the sought explanation as the answer. Through a two-stage testing process, the chat-bot's NLP extraction and information retrieval performance were evaluated. The testing results showed that the ontology modelling for such a learning assistant was done relatively accurately, and shows its potential to be pursued as a cloud-based solution in future. 2021 Institute of Advanced Engineering and Science. All rights reserved. -
Node Overlapping Detection for Draggable Node-Based Applications
Node-based interfaces are user interfaces that are based on the concept of nodes, which represent individual units of functionality, and edges, which represent the connections between nodes. In a node-based interface, nodes are connected by edges to form a graph, which represents the data flow and relationships between different parts of the system. The Node overlapping detection technique is only for react flow version 11 and higher. Users having previous versions are not able to use that functionality. To detect the overlapping, based on the output of this library, several user-defined functions can be used to resolve to overlap. It will see the single-pixel overlap. Using this library, users can avoid Node and edge overlapping by creating custom edges. It is a simple JavaScript function currently used for reactjs. In the future, if any other script develops a draggable node-based flowsheet-creating feature, the user can use this library accordingly. 2023 IEEE. -
Noise removal feature enhancement and speech recognition techniques for artificial larynx transducer speech
Speech impediments are the state of difficulty for a person to speak comfortably. These impediments make the spoken speech distorted and they are generally categorized as disordered speech. The quality of disordered speech is poor as clarity, intelligibility and naturalness is missing. In most type of disordered speech the voice is natural and produced by the vocal system of the human being. The vocal system includes the organ called as Larynx placed in the upper part of the neck. This organ has the vocal folds that contribute for pitch variation and volume of the speech. This organ will be malfunctioning some time or will be removed because of cancer. In both the case in order to restore speech, an external device called Artificial Larynx Transducer (ALT) is used to produce the sound. It is a small handheld battery operated device and is used for decades to obtain the audible speech for people who lost their speech because of removal of larynx. The quality of speech and its intelligibility of AL speakers have not improved for decades. The reason for poor quality is constant vibration of ALT, direct sound from ALT and pressure offered to produce the vibration. newlineSo in this research the nature of the speech produced from ALT is analyzed, a possible enhancement of the parameter is done and a recognition technique of the spoken word with the help of trained data is done. Here the approach followed to tackle the problem of poor quality in AL speech involves both speech enhancement and recognizer technique development. When it is looked as enhancement problem noise region localization, noise estimation and noise suppression methods were adopted. In the process of parameter enhancement, pitch frequency estimation and improvement is implemented. When it is looked as recognition problem the parameters pitch frequency, formant frequency, glottal excitation, spectral tilt, coefficients are extracted. As formant frequency is a sensitive parameter, its estimation was done using Recurrent Neural network. -
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Non invasive methods of blood glucose measurement: Survey, challenges, scope
Noninvasive body parameters monitoring and disease detection is one of the emerging research area now a days. In this paper a review on Non-invasive methods of blood glucose measurement has been made. A comparative study has been made which describes the methodology incorporated in the published literatures, research challenges and the used tools. This paper also describes about the factors which highly impacts the non-invasive measurement. Finally, a deep learning based noninvasive measurement method compatible with IOT is mentioned. This paper serves as a proper reference for future researchers working in non-invasive blood glucose measurement domain in selecting appropriate non-invasive method algorithm for glucose monitoring non-invasively. 2019 Bharati Vidyapeeth, New Delhi. Copy Right in Bulk will be transferred to IEEE by Bharati Vidyapeeth. -
Non linear thermal radiation effect on Williamson fluid with particle-liquid suspension past a stretching surface
A mathematical analysis of two-phase boundary layer flow and heat transfer of a Williamson fluid with fluid particle suspension over a stretching sheet has been carried out in this paper. The region of temperature jump and nonlinear thermal radiation is considered in the energy transfer process. The principal equations of boundary layer flow and temperature transmission are reformed to a set of non-linear ordinary differential equations under suitable similarity transformations. The transfigured equalities are solved numerically with the help of RKF-45 order method. The effect of influencing parameters on velocity and temperature transfer of fluid is examined and deliberated by plotted graphs and tabulated values. Significances of the mass concentration of dust particle parameter play a key role in controlling flow and thermal behavior of non-Newtonian fluids. Further, the temperature and concern boundary layer girth are declines for increasing values of Williamson parameter. 2017 The Authors -
Non-Alcoholic Fatty Liver Disease Prediction with Feature Optimized XGBoost Model
Non-alcoholic fatty liver disease (NAFLD) is an expanding health threat, posing significant risks for long-term complications. Early detection and intervention are crucial, but traditional diagnostic methods can be expensive and invasive.This study investigates the utilization of machine learning models for predicting liver diseases from various out-sourced datasets..We employed Decision Trees, Random Forests, and Support Vector Machines (SVMs) to predict NAFLD based on various clinical and demographic features. Model performance was evaluated by calculating accuracy, precision,deviation and accuracy-score.All these models achieved promising accuracy levels, ranging from 80% to 90%, showcasing their potential for NAFLD prediction. Among them, XG-Boost demonstrated the highest performance, with an accuracy of 90% and more.This study demonstrates the effectiveness of machine learning models in predicting NAFLD with high accuracy using readily available data. Further research with larger sized and more varied datasets will vindicate these models for real-world application in clinical settings. 2024 IEEE. -
Non-Antibacterial Carbon Nanoparticles and Its Fluorescence Properties
Highly fluorescent carbon nanoparticles are synthesized from corn starch via one-pot hydrothermal method. Upon treatment with the lime juice as the catalyst, carbon nanoparticles are functionalized with potassium, and an improvement in the luminescence behavior is also observed. The synthesized nanoparticles did not exhibit any antibacterial activity against gram-positive (Staphylococcus aureus, Bacillus subtilis) and gram-negative (Pseudomonas fluorescence, E.coli) bacteria. The excellent photoluminescence coupled with non-toxic behaviour of the carbon nanoparticles would be best suited for biomedical applications. The Electrochemical Society -
Non-contact oximeter cum thermometer /
Patent Number: 202241009488, Applicant: Jyothi Thomas.
The invention pertains to the field of Covid-19 Equipment. The invention uses non-contact sensors to measure Sp02 level and human body temperature. The Invention can be classified under the Covid-19 as it includes sensors to identify an infected person. The objective of the invention was to tackle the problem of the detection of an infected Person in crowded places without having contact with devices. The basic idea behind the invention was to check the oxygen level as well as the temperature of a person without having contact with the devices used. -
Non-contact oximeter cum thermometer /
Patent Number: 202241009488, Applicant: Jyothi Thomas.
The invention pertains to the field of Covid-19 Equipment. The invention uses non-contact sensors to measure Sp02 level and human body temperature. The Invention can be classified under the Covid-19 as it includes sensors to identify an infected person. The objective of the invention was to tackle the problem of the detection of an infected Person in crowded places without having contact with devices. The basic idea behind the invention was to check the oxygen level as well as the temperature of a person without having contact with the devices used. -
Non-Contact Vital Prediction Using rPPG Signals
In this paper, we present the clinical significance of various cardiac symptoms with the use of heart rate detection, ongoing monitoring and present emotions. The development of algorithms for remote photoplethysmography has drawn a lot of interest during the past decade (rPPG). As a result, using data gathered from the video feed, we can now precisely follow the heart rate of individuals who are still seated. rPPG algorithms have also been developed, in addition to technique based on hand-crafted characteristics. Deep learning techniques often need a lot of data to train on, but biomedical data frequently lacks real-world examples. The experiment described in this work, we looked at how illumination affected the rPPG signals' SNR. The findings show that the SNR in each RGB channel varies depending on the colour of the light source. Paper describes development in video filtering for recognising the comprehending human face emotions. In our method, emotions are deduced by identifying facial landmarks and analysing their placement. 2023 IEEE. -
Non-destructive classification of diversely stained capsicum annuum seed specimens of different cultivars using near-infrared imaging based optical intensity detection
The non-destructive classification of plant materials using optical inspection techniques has been gaining much recent attention in the field of agriculture research. Among them, a near-infrared (NIR) imaging method called optical coherence tomography (OCT) has become a well-known agricultural inspection tool since the last decade. Here we investigated the non-destructive identification capability of OCT to classify diversely stained (with various staining agents) Capsicum annuum seed specimens of different cultivars. A swept source (SS-OCT) system with a spectral band of 1310 nm was used to image unstained control C. annuum seeds along with diversely stained Capsicum seeds, belonging to different cultivar varieties, such as C. annuum cv. PR Ppareum, C. annuum cv. PR Yeol, and C. annuum cv. Asia Jeombo. The obtained cross-sectional images were further analyzed for the changes in the intensity of back-scattered light (resulting due to dye pigment material and internal morphological variations) using a depth scan profiling technique to identify the difference among each seed category. The graphically acquired depth scan profiling results revealed that the control specimens exhibit less back-scattered light intensity in depth scan profiles when compared to the stained seed specimens. Furthermore, a significant back-scattered light intensity difference among each different cultivar group can be identified as well. Thus, the potential capability of OCT based depth scan profiling technique for non-destructive classification of diversely stained C. annum seed specimens of different cultivars can be sufficiently confirmed through the proposed scheme. Hence, when compared to conventional seed sorting techniques, OCT can offer multipurpose advantages by performing sorting of seeds in respective to the dye staining and provides internal structural images non-destructively. 2018 by the authors. Licensee MDPI, Basel, Switzerland. -
Non-destructive silkworm pupa gender classification with X-ray images using ensemble learning
Sericulture is the process of cultivating silkworms for the production of silk. High-quality production of silk without mixing with low quality is a great challenge faced in the silk production centers. One of the possibilities to overcome this issue is by separating male and female cocoons before extracting silk fibers from the cocoons as male cocoon silk fibers are finer than females. This study proposes a method for the classification of male and female cocoons with the help of X-ray images without destructing the cocoon. The study used popular single hybrid varieties FC1 and FC2 mulberry silkworm cocoons. The shape features of the pupa are considered for the classification process and were obtained without cutting the cocoon. A novel point interpolation method is used for the computation of the width and height of the cocoon. Different dimensionality reduction methods are employed to enhance the performance of the model. The preprocessed features are fed to the powerful ensemble learning method AdaBoost and used logistic regression as the base learner. This model attained a mean accuracy of 96.3% for FC1 and FC2 in cross-validation and 95.3% in FC1 and 95.1% in FC2 for external validation. 2022 The Authors -
Non-enzymatic electrochemical determination of progesterone using carbon nanospheres from onion peels coated on carbon fiber paper
A simple electrochemical sensor was developed by coating Onion peel wastes derived carbon nanospheres on carbon fiber paper (CFP) electrode. Carbon nanospheres (CNS) were prepared from Onion peels utilizing an environmentally benign and cost-effective strategy. In the present investigation, the obtained carbon nanospheres were coated on carbon fiber paper and the modified electrodes were physicochemically characterized by Field emission scanning electron microscopy (FESEM) with energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD) spectroscopy and X-ray photoelectron spectroscopy (XPS) techniques. Electrochemical characterizations of the modified electrodes were done by Cyclic voltammetry (CV) and Electrochemical impedance spectroscopy (EIS). CNS modified CFP electrode was successfully used in the determination of Progesterone, an important steroid hormone at an ultra-nanomolar level with superior detection limit of 0.012 nM. The developed electrochemical sensor was effectively utilized for the determination of Progesterone in pharmaceutical Progesterone injections, human blood serum samples and cow milk samples. 2019 The Electrochemical Society.