Self-Powered Dynamic Glazing Based on Nematic Liquid Crystals and Organic Photovoltaic Layers for Smart Window Applications
subject: donor?acceptor bulk heterojunction; dynamic glazing; nematic liquid crystal; organic photovoltaics; smart windows; spatial light modulator
description: 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.
creator: Fall S.; Wang J.; Regrettier T.; Brouckaert N.; Ibraikulov O.A.; Leclerc N.; Lin Y.; Elhaj M.I.; Komitov L.; Lue P.; Zhong Y.; Brinkmann M.; Kaczmarek M.; Heiser T.
source: ACS Applied Materials and Interfaces, Vol-15, No. 3, pp. 4267-4274.
publisher: American Chemical Society
date: 2023-01-01
rights: All Open Access; Green Open Access
relation: ISSN: 19448244; PubMed ID: 36630212
format: Online
language: English
type: Article
coverage: Fall S., Laboratoire des Sciences de lIngieur, de lInformatique et de lImagerie (ICube Research Institute), Universitde Strasbourg, Centre National de la Recherche Scientifique, 23, Rue du Loess, Strasbourg, Cedex 2 67037, France; Wang J., Laboratoire des Sciences de lIngieur, de lInformatique et de lImagerie (ICube Research Institute), Universitde Strasbourg, Centre National de la Recherche Scientifique, 23, Rue du Loess, Strasbourg, Cedex 2 67037, France; Regrettier T., Laboratoire des Sciences de lIngieur, de lInformatique et de lImagerie (ICube Research Institute), Universitde Strasbourg, Centre National de la Recherche Scientifique, 23, Rue du Loess, Strasbourg, Cedex 2 67037, France, Voltec Solar, 1 Rue des Pr, Dinsheim-sur-Bruche, 67190, France; Brouckaert N., Laboratoire des Sciences de lIngieur, de lInformatique et de lImagerie (ICube Research Institute), Universitde Strasbourg, Centre National de la Recherche Scientifique, 23, Rue du Loess, Strasbourg, Cedex 2 67037, France, University of Southampton, Southampton, SO17 1BJ, United Kingdom; Ibraikulov O.A., Laboratoire des Sciences de lIngieur, de lInformatique et de lImagerie (ICube Research Institute), Universitde Strasbourg, Centre National de la Recherche Scientifique, 23, Rue du Loess, Strasbourg, Cedex 2 67037, France; Leclerc N., Institut de Chimie et Proc pour lEnergie, lEnvironnement et la Sant Universitde Strasbourg, Centre National de la Recherche Scientifique, 25, Rue Becquerel, Strasbourg, Cedex 67085, France; Lin Y., Laboratoire des Sciences de lIngieur, de lInformatique et de lImagerie (ICube Research Institute), Universitde Strasbourg, Centre National de la Recherche Scientifique, 23, Rue du Loess, Strasbourg, Cedex 2 67037, France; Elhaj M.I., HighVistec GmbH, Benkenstrasse 254C, Witterswil, CH 4108, Switzerland; Komitov L., HighVistec GmbH, Benkenstrasse 254C, Witterswil, CH 4108, Switzerland, Dept. of Physics, University of Gothenburg, Gothenburg, 41296, Sweden, Department of Chemistry, C…

Customized mask region based convolutional neural networks for un-uniformed shape text detection and text recognition
subject: Deep neural networks; Optical character-recognition; Region based convolutional neural networks; Region of interest; Text detection; Text recognition
description: In image scene, text contains high-level of important information that helps to analyze and consider the particular environment. In this paper, we adapt image mask and original identification of the mask region based convolutional neural networks (R-CNN) to allow recognition at 3 levels such as sequence, holistic and pixel-level semantics. Particularly, pixel and holistic level semantics can be utilized to recognize the texts and define the text shapes, respectively. Precisely, in mask and detection, we segment and recognize both character and word instances. Furthermore, we implement text detection through the outcome of instance segmentation on 2-D feature-space. Also, to tackle and identify the text issues of smaller and blurry texts, we consider text recognition by attention-based of optical character recognition (OCR) model with the mask R-CNN at sequential level. The OCR module is used to estimate character sequence through feature maps of the word instances in sequence to sequence. Finally, we proposed a fine-grained learning technique that trains a more accurate and robust model by learning models from the annotated datasets at the word level. Our proposed approach is evaluated on popular benchmark dataset ICDAR 2013 and ICDAR 2015. 2023 Institute of Advanced Engineering and Science. All rights reserved.
creator: Channegowda R.H.; Karthik P.; Srinivasaiah R.; Shivaraj M.
source: International Journal of Electrical and Computer Engineering, Vol-13, No. 1, pp. 413-424.
publisher: Institute of Advanced Engineering and Science
date: 2023-01-01
rights: All Open Access; Gold Open Access; Green Open Access
relation: ISSN: 20888708
format: Online
language: English
type: Article
coverage: Channegowda R.H., Department of Electronics and Communication Engineering, K S School of Engineering and Management, Ghousia College of Engineering, Visvesvaraya Technological University, Karnataka, India; Karthik P., Department of Electronics and Communication Engineering, K S School of Engineering and Management, Visvesvaraya Technological University, Karnataka, India; Srinivasaiah R., Department of Computer science and Engineering, Christ Deemed to be University, Karnataka, Bengaluru, India; Shivaraj M., Department of Electronics and Communication Engineering, Ghousia College of Engineering, Visvesvaraya Technological University, Ramanagaram, Karnataka, India

An Intelligent Decision Support System to Aid Profit Planning in Manufacturing Companies
subject: Break-Even Analysis; Management Accounting; Market Demand; Multi-product Break Even Point; Profit Planning
description: In order to assure accuracy in profit planning and decision-making, this study uses an intelligent decision support system to investigate an appropriate approach for calculating the "Break-Even" point in multi-product segments while taking into account the implications for contribution margin, demand, and capacity. The research's methodology and findings may be used to propose new projects, grow businesses, and make decisions in processes that focus on many products. Data are used to illustrate the advanced level of break-even analysis and application, and a description of the convenient and system-generated method of computation is given. A mathematical approach has been used based on actual data to show how to determine the break-even point without sacrificing the influencing aspects such as contribution margin, capacity, product mix, and demand for each. The researchers have created a good system application-oriented platform to make it simple to calculate the break-even point, which will be crucial for decision-making and profit planning even with more than 500 SKU (Stock Keeping Unit). This research evaluated the data and created formulas for actual data structure-based analysis. The study's conclusions have a significant influence on those companies that need to determine the true break-even threshold. The challenge area of concern might be the applicability of this activity for other sectors and other countries as this research was centred on the plastic bag industry in Malaysia. Future research can also analyse other important factors like start-up and semi-variable costs as they are not included in the current study. The identified break-even threshold can still be used effectively given the current market demand and the product's capacity. 2023, Ismail Saritas. All rights reserved.
creator: Thasan S.; Rahman A.; Subramanian P.; Williams M.J.
source: International Journal of Intelligent Systems and Applications in Engineering, Vol-11, No. 4s, pp. 345-356.
publisher: Ismail Saritas
date: 2023-01-01
rights: Restricted Access
relation: ISSN: 21476799
format: Online
language: English
type: Article
coverage: Thasan S., Faculty Of Business and Accounting, Linton University College, Malaysia; Rahman A., Faculty of Business and Communications, INTI International University, Malaysia; Subramanian P., School of Business Management, Christ University, Lavasa, Pune, India; Williams M.J., Sri Krishna Arts and Science College, India

An efficient classification of cirrhosis liver disease using hybrid convolutional neural network-capsule network
subject: Adaptive emperor penguin optimization; Deep learning; Imaging modalities; Liver cirrhosis
description: Liver cirrhosis is the diffuse and advanced phase of liver disease. Several morphological methods are used for imaging modalities. But, these modalities are biased and lack in higher detection accuracy. Hence, this work introduces automated cirrhosis liver disease classification using an optimized hybrid deep learning model. In this work, Magnetic Resonance Image (MRI) is considered for the process. Initially, an Extended Guided Filter (EGF) is used for eliminating the noise from input MRI images. Binomial thresholding is used to segment the tumor from the image. Then, Feature Extraction (FE) phase is carried out by Grey Level Co-occurrence Matrix (GLCM) and Gray level Run-length Matrix (GRLM). Finally, a hybrid of two Deep Learning (DL) algorithms Convolutional Neural Network and Capsule Network (HCNN-CN) are integrated to classify the Cirrhosis liver disease. Moreover, for fine tuning the parameters of the neural network, an optimization approach Adaptive Emperor Penguin Optimization (AEPO) is used. The proposed HCNN-CN-AEPO is compared over several approaches and depicted accuracy and sensitivity value of 0.993 and 0.986 on the real time dataset. The experimental results proved that the proposed HCNN-CN-AEPO can exactly diagnose the tumour. 2022 Elsevier Ltd
creator: Shaheen H.; Ravikumar K.; Lakshmipathi Anantha N.; Uma Shankar Kumar A.; Jayapandian N.; Kirubakaran S.
source: Biomedical Signal Processing and Control, Vol-80
publisher: Elsevier Ltd
date: 2023-01-01
rights: Restricted Access
relation: ISSN: 17468094
format: Online
language: English
type: Article
coverage: Shaheen H., Department of Computer Science and Engineering, MVJ College of Engineering, Bangalore, India; Ravikumar K., Dept. Of Cse, Rrase College Of Engg, Chennai Padappai, India; Lakshmipathi Anantha N., CSE Department, Malla Reddy Engineering College, Hyderabad, India; Uma Shankar Kumar A., K.S.R.M. College of Engineering, Andhra Pradesh, Kadapa, India; Jayapandian N., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bangalore, India; Kirubakaran S., Department of Computer Science and Engineering, CMR College of Engineering and Technology, Hyderabad, India

Heteroatom engineered graphene-based electrochemical assay for the quantification of high-risk abused drug oxytocin in edibles and biological samples
subject: Co-doping; Electro-oxidation; Heteroatom; Oxytocin; Synergistic effect
description: The naive detection of scheduled H drug oxytocin is a vital requisite, owing to its deleterious impact on societal affluence prompted by unconstrained usage. Therefore, a reliable, cost-effective, and quick-to-respond analytic technique for this drug is in ample demand. In this work, we report electrochemical detection of oxytocin employing novel nitrogen, phosphorus co-doped coke-derived graphene (NPG) modified electrode. The electro-oxidation behavior of oxytocin was investigated on the NPG modified electrode by square wave stripping voltammetry (SWSV) in 0.1 M phosphate buffer of pH 7. The oxidation peak current was linear in two ranges, spanning from 0.1 nM to 10 nM and 15 nM to 95 nM. The limit of detection at the NPG electrode was calculated to be 40 pM. The practical application of developed sensor for the determination of oxytocin was examined in edible products and body fluids, hence signifying the possibility of having real-time surveillance over its misusage. 2022 Elsevier Ltd
creator: Thomas R.; Balachandran M.
source: Food Chemistry, Vol-400
publisher: Elsevier Ltd
date: 2023-01-01
rights: Restricted Access
relation: ISSN: 3088146; PubMed ID: 36084601; CODEN: FOCHD
format: Online
language: English
type: Article
coverage: Thomas R., Materials Science Research Laboratory, Department of Physics and Electronics, Christ University, Karnataka, Bengaluru, 560029, India; Balachandran M., Materials Science Research Laboratory, Department of Physics and Electronics, Christ University, Karnataka, Bengaluru, 560029, India

Evaluation of physicochemical and biological properties of SnO2 and Fe doped SnO2 nanoparticles
subject: Anticancer; Doping concentration; Green synthesis; Nanoparticles; Structural analysis
description: In recent decades, nanoparticle synthesis has been used for various physical and chemical methods. However, different toxic chemicals are used during this synthesis process to address these concerns, which has multiple effects on environmental toxicity and high cost. To avoid these problems, we need a cost-effective and environmentally friendly approach. In this study, green synthesis was used to make tin oxide (SnO2) and ferrous doped tin oxide (SFO) nanoparticles (NPs) from Morinda citrifolia leaf extracts. The X-ray diffraction patterns of SnO2 and SFO NPs reveal a tetragonal crystalline structure. From the FESEM image of synthesized SnO2 and SFO NPs, their spherical structure and chemical composition were identified by EDX spectrum. Through the DLS spectrum, the hydrodynamic size was observed at 66 and 61 nm for SnO2 and SFO NPs, respectively. In the FTIR spectrum, the OSnO stretching vibration peak arises at (606 & 509 cm?1 for SnO2 NPs) and (613 & 538 cm?1 for SFO NPs). Photoluminescence is used in materials to detect surface defects and impurity levels. The antibacterial activity of the SnO2, SFO NPs, and conventional antibiotics like amoxicillin NPs is effectively inhibited against S. aureus and E. coli bacterial strains. SFO NPs exhibit a higher antibacterial activity as compared to SnO2 and amoxicillin. The anticancer efficacy of increased SFO NPs compared to SnO2 NPs was tested against (MDA-MB-237) human breast cancer cells. These results suggest that Fe ions modified SnO2 NPs could be used in healthcare industrial applications to improve human health. 2022 Elsevier Ltd and Techna Group S.r.l.
creator: Elamin N.Y.; Indumathi T.; Ranjith Kumar E.
source: Ceramics International, Vol-49, No. 2, pp. 2388-2393.
publisher: Elsevier Ltd
date: 2023-01-01
rights: Restricted Access
relation: ISSN: 2728842; CODEN: CINND
format: Online
language: English
type: Article
coverage: Elamin N.Y., Department of Chemistry, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11623, Saudi Arabia, Department of Chemistry, Sudan University of Science and Technology, Khartoum, Sudan; Indumathi T., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Ranjith Kumar E., Department of Physics, KPR Institute of Engineering and Technology, Tamil Nadu, Coimbatore, 641407, India

A facile one-step microwave synthesis of Pt deposited on N & P co-doped graphene intercalated carbon black - An efficient cathode electrocatalyst for PEM fuel cell
subject: Carbon black; Durability; Full cell performance; Graphene; Nitrogen and phosphorous co-doped graphene
description: A facile, single step microwave assisted polyol route for simultaneously depositing platinum as well as co-doping graphene oxide, is herein proposed. However, low durability and full cell performance of Pt/NPG (platinum deposited on nitrogen phosphorous co-doped graphene) was observed due to restacking of graphene layers. This issue was addressed by intercalating CB into the graphene layers as spacers during the synthesis (in-situ addition of spacers - Pt/(NPG + S)). Moreover, to study the influence of spacers, external addition of spacers (ex-situ - Pt/(NPG) + S) were also examined. Results from our study indicate that in-situ addition of spacers- Pt/(NPG + S) enhanced the full cell performance (405 mW cm?2) and exhibited <40% ECSA loss (37.47%), thereby attaining DoE target. Thus, emerging as a durable cathode electrocatalyst (Pt/(NPG + S)) for PEM fuel cells. 2022 Hydrogen Energy Publications LLC
creator: Nair A.S.; Jafri R.I.
source: International Journal of Hydrogen Energy, Vol-48, No. 9, pp. 3653-3664.
publisher: Elsevier Ltd
date: 2023-01-01
rights: Restricted Access
relation: ISSN: 3603199; CODEN: IJHED
format: Online
language: English
type: Article
coverage: Nair A.S., Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore, 560029, India; Jafri R.I., Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore, 560029, India

Normalized Attention Neural Network with Adaptive Feature Recalibration for Detecting the Unusual Activities Using Video Surveillance Camera
subject: adaptive feature recalibration; normalized attention network; surveillance data; unusual activities
description: 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.
creator: Damera V.K.; Vatambeti R.; Mekala M.S.; Pani A.K.; Manjunath C.
source: International Journal of Safety and Security Engineering, Vol-13, No. 1, pp. 51-58.
publisher: International Information and Engineering Technology Association
date: 2023-01-01
rights: All Open Access; Bronze Open Access
relation: ISSN: 20419031
format: Online
language: English
type: Article
coverage: Damera V.K., Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Hyderabad, 500090, India; Vatambeti R., School of Computer Science and Engineering, VIT-AP University, Vijayawada, 522237, India; Mekala M.S., School of Communication Engineering, Yeungnam University, Gyeongsan, 38541, South Korea; Pani A.K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bangalore, 560074, India; Manjunath C., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bangalore, 560074, India

Enhanced electrical properties of CuO:CoO decorated with Sm2O3 nanostructure for high-performance supercapacitor
subject: CuO:CoO; Electrical properties; Energy storage; Nanostructures; Samarium oxide; Super capacitor
description: In the present investigation, we have synthesized samarium (Sm) nanoparticles (NPs) and anchored them onto the surface of CuO:CoO nanostructure (NS) by utilizing a simple chemical precipitation method. Nanostructures (NS) were characterized utilizing powdered X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), scanning electron spectroscopy (SEM), transmission electron spectroscopy (TEM), UVvisible spectroscopy (UVVis), and BrunauerEmmettTeller (BET) studies. Resulting Smx CuO: CoO (x = 1%, 5%, 10%, and 12%) NS were investigated for their anomalous electrical and supercapacitive behavior. NS energy storage performance was experimentally determined using cyclic voltammetry (CV), galvanostatic chargedischarge (GCD), and electrochemical impedance spectroscopy (EIS). Sm10%CuO:CoO exhibited better electrochemical response than other samples and showed a maximum specific capacitance of 283.6F/g at 0.25A/g in KOH electrolyte. However, contrary to our expectation, NS displayed rectifying nature in I-V, intercalative nature in C-V, and polaronic permittivity in all concentrations of Sm2O3 doping as compared with undoped CuO:CoO NS. The outstanding properties of Smx CuO:CoO NS are attributed to the synergy of high charge mobility of Sm NPs, leading to significant variation in dielectric permittivity, currentvoltage (I-V) response, capacitancevoltage (C-V) behavior, with the formation of Sm3+ ionic cluster. The clusters lead to a change in dipole moment creating a strong local electric field. Additionally, a CR2032 type symmetric supercapacitor cell was fabricated using Sm10%CuO:CoO, which exhibited a maximum specific capacitance of 67.4F/g at 0.1A/g. The cell was also subjected to 5000 GCD cycles where it retained 96.3% Coulombic efficiency. Graphical Abstract: [Figure not available: see fulltext.] 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
creator: Adimule V.; Bhat V.S.; Joshi R.; Batakurki S.; Hegde G.; Yallur B.C.
source: Journal of Solid State Electrochemistry, Vol-27, No. 2, pp. 511-529.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2025-01-01
rights: Restricted Access
relation: ISSN: 14328488
format: Online
language: English
type: Article
coverage: Adimule V., Department of Chemistry, Angadi Institute of Technology and Management (AITM), Savagaon Road, Karnataka, Belagavi, 590009, India; Bhat V.S., Centre for Nano-Materials and Displays (CND), B.M.S. College of Engineering, Bull Temple Road, Basavanagudi, Bangalore, 560 019, India; Joshi R., Department of Physics, School of Physical Sciences, Central University of Karnataka, Aland Road, Karnataka, Kadaganchi, Gulbarga, 585311, India; Batakurki S., Department of Chemistry, M. S. Ramaiah University of Applied Sciences, Bangalore, 560054, India; Hegde G., Centre for Adavanced Research and Development (CARD), CHRIST (Deemed to be University), Hosur Rd, Bhavani Nagar, S.G. Palya, Karnataka, Bangalore, 29, India, Department of Chemistry, CHRIST (Deemed to be University), Hosur Rd, Bhavani Nagar, S.G. Palya, Karnataka, Bangalore, 29, India; Yallur B.C., Department of Chemistry, M S Ramaiah Institute of Technology, Karnataka, Bangalore, 560054, India

N-doped graphene quantum dots incorporated cobalt ferrite/graphitic carbon nitride ternary composite for electrochemical overall water splitting
subject: Cobalt ferrite; gCN; HER and OER; N doped graphene quantum dots; Ternary electrocatalyst; Water splitting
description: Multicomponent electrocatalysts containing carbon supports play a crucial role in influencing the hydrogen and oxygen evolution reactions which enhance the total water splitting. Herein, we report a ternary composite with cobalt ferrite, graphitic carbon nitride, and N-doped graphene quantum dots prepared via hydrothermal technique. The purity of the samples is established by carrying out various characterization methods. The intrinsic characteristics of the obtained materials are investigated by employing electrocatalytic processes in an alkaline media toward hydrogen and oxygen evolution reactions. Cobalt ferrite/graphitic carbon nitride/N doped graphene quantum dots electrocatalyst demonstrates a very low overpotential towards hydrogen evolution reaction of 287 mV at a constant 10 mA cm?2 current density in 1.0 M KOH. Tafel slope and Rct values generated are 94 mV dec?1 and 0.86 cm2, respectively. Oxygen evolution reaction studies reveal an overpotential of 445 mV at 10 mA cm?2 with a Tafel slope of 69 mV dec?1. Finally, the cell potential needed for the cobalt ferrite/graphitic carbon nitride/N doped graphene quantum dots electrode to achieve 10 mA cm?2 in total water splitting is only 2.0 V while displaying long-term stability. 2022 Hydrogen Energy Publications LLC
creator: Reghunath B.S.; Rajasekaran S.; Devi K R S.; Pinheiro D.; Jaleel UC J.R.
source: International Journal of Hydrogen Energy, Vol-48, No. 8, pp. 2906-2919.
publisher: Elsevier Ltd
date: 2023-01-01
rights: Restricted Access
relation: ISSN: 3603199; CODEN: IJHED
format: Online
language: English
type: Article
coverage: Reghunath B.S., Department of Chemistry, CHRIST (Deemed to Be University), Karnataka, Bengaluru, 560029, India; Rajasekaran S., Department of Chemistry, CHRIST (Deemed to Be University), Karnataka, Bengaluru, 560029, India; Devi K R S., Department of Chemistry, CHRIST (Deemed to Be University), Karnataka, Bengaluru, 560029, India; Pinheiro D., Department of Chemistry, CHRIST (Deemed to Be University), Karnataka, Bengaluru, 560029, India; Jaleel UC J.R., Department of Chemistry, CHRIST (Deemed to Be University), Karnataka, Bengaluru, 560029, India

Geo-spatial crime density attribution using optimized machine learning algorithms
subject: Crime analysis; Crime density; Kernel density estimation; Newsfeeds
description: Law enforcement agencies use various crime analysis tools. A large amount of crime data has enabled crime analysis. In this paper, the proposed research methodology uses Kernel Density Estimation (KDE) in a Geographical Information System (GIS) to analyze crime-type data. Bangalore and India newsfeeds are considered for experimental purposes. The paper introduces an optimized KDE machine learning algorithm that detects hotspots, estimates a locations crime rate, and identifies point pattern lows and highs. As a result of the experiment, the proposed methodology identified that the bandwidth of the Geographical information system influences the visualization of crime density. The paper also aids in visually determining the appropriate bandwidth for the problem using an optimized KDE algorithm. We had identified a significant correlation between Newsfeed data and Official Government data, both overall Crime and by crime type. The proposed KDE model achieved a predictive performance of 77.49%. 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.
creator: Prathap B.R.
source: International Journal of Information Technology (Singapore), Vol-15, No. 2, pp. 1167-1178.
publisher: Springer Science and Business Media B.V.
date: 2023-01-01
rights: Restricted Access
relation: ISSN: 25112104
format: Online
language: English
type: Article
coverage: Prathap B.R., Department of Computer Science and Engineering, CHRIST (Deemed to Be University), #325(45), Kengeri-Campus, Mysore Road, Karnataka, Bangalore, 560074, India

Deep Learning Inspired Nonlinear Classification Methodology for Handwritten Digits Recognition Using DSR Encoder
subject: Adaptive voting scheme; Batch normalization; DDRNet approach; MaxPooling; SqueezeNet
description: The overlapped handwritten digit classification is a global challenge and a significant measure to assess the network recognition ability ratio. Most efficient models have been designed based on convolutional neural networks (CNN) for effective image classification and digit identification. Subsequently, multiple CNN models have inadequate accuracy because of high degree parameter dimensions that lead to abnormal digit detection error rates and computation complexity. We propose a Deep Digit Recognition Network (DDRNet) based on Deep ConvNets to minimize the number of parameters and features to keep the model light while maximizing the accuracy with an adaptive voting (AV) scheme for digit recognition. The individual digit is identified by CNN, and uncertain digits or strings are identified by Deep Convolutional Network (DCN) with AV scheme through Voting-Weight Conditional Random Field (VWCRF) strategy. These methods originated with the YOLO algorithm. The simulations show that our DDRNet approach achieves an accuracy of 99.4% without error fluctuations, in a stable state with less than 15 epochs contrast with state-of-art approaches. Additionally, specific convolution techniques (SqueezeNet, batch normalization) and image augmentation techniques (dropout, back-propagation, and an optimum learning rate) were examined to assess the system performance based on MNIST dataset (available at: http://yann.lecun.com/exdb/mnist/). 2022, King Fahd University of Petroleum & Minerals.
creator: Singh D.; Bano S.; Samanta D.; Mekala M.S.; Islam S.H.
source: Arabian Journal for Science and Engineering, Vol-48, No. 2, pp. 1385-1397.
publisher: Institute for Ionics
date: 2023-01-01
rights: Restricted Access
relation: ISSN: 2193567X
format: Online
language: English
type: Article
coverage: Singh D., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Bano S., Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Andhra Pradesh, Vaddeswaram, India; Samanta D., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Mekala M.S., Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, 38544, South Korea, RLRC for Autonomous Vehicle Parts and Materials Innovation, Yeungnam University, Gyeongsan, 38544, South Korea; Islam S.H., Department of Computer Science and Engineering, Indian Institute of Information Technology Kalyani, Kalyani, West Bengal, 741235, India

A Multi-Stimuli responsive organic luminogen with aggregation induced emission for the selective detection of Zn2+ ions in solution and solid state
subject: ESIPT; Fluorescence switching; Halochromic; Organic luminogens; Schiff base
description: Organic luminogens capable of excited state intramolecular electron transfer (ESIPT) have drawn prodigious attraction due to their enhanced emission in solid-state. A novel Schiff base molecule, 3,5-dibromo-2-hydroxybenzylidenenicotinohydrazide (DHN) exhibited stimuli-induced reversible fluorescence switching and selective binding propensity towards zinc in aqueous media, and the concentration-dependent studies showed a limit of detection of 9.135 nM. DHN was found to be weakly fluorescent in polar solvents with a quantum yield ranging between 0.0365 and 0.0789 but exhibited a very strong fluorescence in solid state (?exc = 370 nm) due to aggregation induced emission (AIE). The ESIPT fluorophore renders significant reversible halochromic properties in solution and solid-state. In addition, utilizing the solid-state fluorescence, we have prepared PVA-probe green-emitting composite films, which can be used for the on-site detection of Zn2+ in aqueous media. The practical applicability of DHN was proven by detecting Zn2+ in real drug samples. Finally, the ESIPT fluorophore was used for fluorescent imaging of intracellular zinc in the cells acquired from the nervous tissue of rats (N2a). The investigations carried out highlight the versatility of ESIPT Schiff bases used for the development of multi-responsive fluorescent materials for selective sensing of metal ions in both solid and solution states. 2022 Elsevier B.V.
creator: Joy F.; Chaithra K.P.; Nizam A.; Deepti A.; Baby Chakrapani P.S.; Kumar Das A.; Vinod T.P.; Nair Y.
source: Chemical Engineering Journal, Vol-453
publisher: Elsevier B.V.
date: 2023-01-01
rights: Restricted Access
relation: ISSN: 13858947; CODEN: CMEJA
format: Online
language: English
type: Article
coverage: Joy F., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; Chaithra K.P., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; Nizam A., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; Deepti A., Centre for Neuroscience, Department of Biotechnology, Cochin University of Science and Technology, Kochi, 682022, India; Baby Chakrapani P.S., Centre for Neuroscience, Department of Biotechnology, Cochin University of Science and Technology, Kochi, 682022, India; Kumar Das A., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; Vinod T.P., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; Nair Y., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India

Balancing module in evolutionary optimization and Deep Reinforcement Learning for multi-path selection in Software Defined Networks
subject: Balancing module; Crow Search Algorithm; Deep Reinforcement Learning; Software Defined Network; Spider Monkey Optimization
description: Software Defined Network (SDN) has been used in many organizations due to its efficiency in transmission. Machine learning techniques have been applied in SDN to improve its efficiency in resource scheduling. The existing models in SDN have limitations of overfitting, local optima trap and lower efficiency in path selection. This study applied Balancing Module (BM)-Spider Monkey Optimization (SMO)-Crow Search Algorithm (CSA) for multi path selection in SDN to improve its efficiency. The balancing module applies Gaussian distribution to balance between exploration and exploitation in the multi-path selection process. The Balancing module helps to escape local optima trap and increases the convergence rate. Deep Reinforcement learning is applied for resource scheduling in SDN. The Deep reinforcement learning technique uses the reward function to improve the learning performance, and the BM-SMO-CSA technique has 30 J energy consumption, where the existing models: DRL has 40 J energy consumption, and Graph-ACO has 62 J energy consumption. 2022
creator: Praveena H.D.; Srilakshmi V.; Rajini S.; Kolluri R.; Manohar M.
source: Physical Communication, Vol-56
publisher: Elsevier B.V.
date: 2023-01-01
rights: Restricted Access
relation: ISSN: 18744907
format: Online
language: English
type: Article
coverage: Praveena H.D., Department of ECE, Sree Vidyanikethan Engineering College, Andhra Pradesh, Tirupati, 517102, India; Srilakshmi V., Department of Computer Science and Engineering (AI & ML), B V Raju Institute of Technology, Narsapur, India; Rajini S., Department of Information Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, India; Kolluri R., Department of ECE, Narasaraopeta Engineering College, Andhra Pradesh, Guntur, India; Manohar M., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India

Fixed points in n-gonal graphical b-metric spaces under contractive conditions
subject: graphical b-metric space; graphical contraction; N-gonal metric space
description: In this paper, we will define a new metric space called n-gonal graphical b-metric space. We will also prove some fixed point theorems in said metric space and give suitable examples to illustrate our results. These results will help to solve many nonlinear convex models in machine learning and optimization by formulating them in fixed point schemes of optimization. Our paper opens the door for researchers to work in the intersecting area of machine learning and functional analysis in the frame work of n-gonal graphical b-metric space. 2023 World Scientific Publishing Company.
creator: Raza U.; Anwar M.S.; Ali H.; Puneeth V.; Irfan M.; Hussain Z.
source: International Journal of Modern Physics B, Vol-37, No. 4
publisher: World Scientific
date: 2023-01-01
rights: Restricted Access
relation: ISSN: 2179792; CODEN: IJPBE
format: Online
language: English
type: Article
coverage: Raza U., Department of Mathematics, University of Jhang, Jhang, 35200, Pakistan; Anwar M.S., Department of Mathematics, University of Jhang, Jhang, 35200, Pakistan; Ali H., Department of Sciences and Humanities, National University of Computer and Emerging Sciences (FAST), Chiniot, 35400, Pakistan; Puneeth V., Department of Computational Science, Christ (Deemed to Be University), Ghaziabad, 201003, India; Irfan M., Department of Mathematical Sciences, Federal Urdu University of Arts Sciences & Technology, Islamabad, 44000, Pakistan; Hussain Z., Department of Mathematics, University of Baltistan, Skardu, Pakistan

Multigene Genetic Programming Based Prediction of Concrete Fracture Parameters of Unnotched Specimens
subject: Concrete; Fracture Parameters; Multigene Genetic Programming; Notched and Unnotched Specimens
description: This study explores the fracture energy of notched and unnotched concrete specimens subjected to the classical three-point bend test, instantiating a gradational step in the continued development of concrete fracture mechanics. An experimental campaign involving 18 notched test specimens and nine unnotched specimens of three different grades of concrete, an examination of the existing literature models for unnotched specimens, and a novel Multigene Genetic programming (MGGP) based concrete fracture energy model for unnotched specimens are integral to this study. As a salient result, the multiple approaches to quasi-brittle materials adopted in the study, highlighted the criticality of the determination of fracture energy, tensile strength and characteristic length for the crack width study. The failure modes of notched and unnotched specimens were found to be similar. The reported literature has mainly focused on a limited number of fracture energy influencing parameters. Therefore, six impact parameters have been chosen and incorporated into the present study to provide a more acceptable explanation of concrete fracture behaviour. A sensitivity analysis of the parameters and an error analysis of the model undertaken have established the accuracy and robustness of the developed MGGP model. 2023 by the authors. Licensee C.E.J, Tehran, Iran.
creator: Sudhir M.R.; Beulah M.
source: Civil Engineering Journal (Iran), Vol-9, No. 2, pp. 393-410.
publisher: Salehan Institute of Higher Education
date: 2023-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 26766957
format: Online
language: English
type: Article
coverage: Sudhir M.R., Department of Civil Engineering, School of Engineering & Technology, CHRIST (Deemed to be University), Bangalore, India; Beulah M., Department of Civil Engineering, School of Engineering & Technology, CHRIST (Deemed to be University), Bangalore, India

Insight into the effects of waste vegetable oil on self-healing behavior of bitumen binder
subject: Bitumen; Molecular dynamics; Self-healing behavior; Waste vegetable oil
description: The application of waste vegetable oil (WVO) in bitumen has been the subject of research for years, however, the self-healing behavior of WVO modified bitumen (WMB) has not been adequately reported. In this research, molecular dynamics (MD) simulations and laboratory experiments were performed to reveal the effects of WVO on the self-healing behavior of bitumen. Models of base bitumen and WMB were constructed. Further, dynamic calculations were carried out for the self-healing models of base bitumen and WMB both with 10 microcracks. The energy properties, conformation and density of bitumen during the self-healing process were analyzed. Meanwhile, the effects of WVO on the fractional free volume (FFV) of bitumen, the distribution of bitumen components and the mobility of bitumen molecules were investigated. Finally, the modified fatigue-healing-fatigue (FHF) test was conducted to verify the effects of WVO on the self-healing efficiency of bitumen. Results show that Van der Waals forces drive the mobility of bitumen molecules. Along with the disappearance of the central microcrack, the density of the self-healing system gradually increases and finally reaches that of the bulk bitumen. WVO with superior mobility capacity increases the FFV of bitumen and converts asphaltene large aggregated structure into small aggregated structure, which facilitates the mobility of the bitumen during the self-healing process. Thus, the addition of WVO contributes to the self-healing efficiency of the bitumen. The modified FHF test also verified that the self-healing efficiency of bitumen is improved with the presence of WVO. These findings provide further insight into the self-healing behaviors of WMB. 2022
creator: Xu N.; Wang H.; Chen Y.; Hossiney N.; Ma Z.; Wang H.
source: Construction and Building Materials, Vol-363
publisher: Elsevier Ltd
date: 2023-01-01
rights: Restricted Access
relation: ISSN: 9500618; CODEN: CBUME
format: Online
language: English
type: Article
coverage: Xu N., School of Highway, Chang'an University, South Erhuan Middle Section, Shaanxi Province, Xi'an City, 710064, China; Wang H., School of Highway, Chang'an University, South Erhuan Middle Section, Shaanxi Province, Xi'an City, 710064, China; Chen Y., School of Highway, Chang'an University, South Erhuan Middle Section, Shaanxi Province, Xi'an City, 710064, China; Hossiney N., Department of Civil Engineering, CHRIST University, Kumbalgodu, Karnataka, Bengaluru, 560074, India; Ma Z., School of Highway, Chang'an University, South Erhuan Middle Section, Shaanxi Province, Xi'an City, 710064, China; Wang H., School of Highway, Chang'an University, South Erhuan Middle Section, Shaanxi Province, Xi'an City, 710064, China

Open global shadow graph and its zero forcing number
subject: Open global shadow graph; Zero forcing number; Zero forcing set
description: Zero forcing number of a graph is the minimum cardinality of the zero forcing set. A zero forcing set is a set of black vertices of minimum cardinality that can colour the entire graph black using the colour change rule: each vertex of G is coloured either white or black, and vertex v is a black vertex and can force a white neighbour only if it has one white neighbour. In this paper we identify a class of graph where the zero forcing number is equal to the minimum rank of the graph and call it as a new class of graph that is open global shadow graph. Some of the basic properties of open global shadow graph are studied. The zero forcing number of open global shadow graph of a graph with upper and lower bound is obtained. Hence giving the upper and lower bound for the minimum rank of the graph. 2023, Proyecciones. All Rights Reserved.
creator: Raksha M.R.; Dominic C.
source: Proyecciones, Vol-42, No. 1, pp. 33-52.
publisher: Universidad Catolica del Norte
date: 2023-01-01
rights: All Open Access; Gold Open Access; Green Open Access
relation: ISSN: 7160917
format: Online
language: English
type: Article
coverage: Raksha M.R., CHRIST (Deemed to be University), India; Dominic C., CHRIST (Deemed to be University), India

Source-load-variable voltage regulated cascaded DC/DC converter for a DC microgrid system
subject: DC microgrid; DC/DC converter; Photovoltaic system; Voltage lift technique; Voltage regulation
description: Solar energy is available abundantly, the utilization of solar energy is developing rapidly and the photovoltaic based direct current (DC) microgrid system design is under demand but the stability of the DC voltage is of most important issue, as the variation of the output DC voltage is a common problem when the load or source voltage varies, hence a regulated DC output voltage converter is proposed. This paper presents source-load-variable (SLV) voltage regulated cascaded DC/DC converter which is used to obtain regulated output voltage of 203.1 V DC at 0.4 duty ratio with 2% voltage fluctuations for the variation in the input source voltage and 1.5% voltage fluctuations for the variation in load resistance of the nominal value with lower output voltage ripple and without use of sub circuits. A simulation model of SLV voltage regulated cascaded DC/DC converter in LTspice XVII software environment for the assessment of converter performance at different input source voltages and load resistances are verified. 2023 Institute of Advanced Engineering and Science. All rights reserved.
creator: Salyam R.; Margaret V.
source: International Journal of Electrical and Computer Engineering, Vol-13, No. 1, pp. 107-115.
publisher: Institute of Advanced Engineering and Science
date: 2023-01-01
rights: All Open Access; Gold Open Access; Green Open Access
relation: ISSN: 20888708
format: Online
language: English
type: Article
coverage: Salyam R., Department of Electrical and Electronics Engineering, School of Engineering and Technology, Christ University, Bengaluru, India; Margaret V., Department of Electrical and Electronics Engineering, School of Engineering and Technology, Christ University, Bengaluru, India

A facile, green synthesis of carbon quantum dots from Polyalthia longifolia and its application for the selective detection of cadmium
subject: Cadmium sensing; Carbon quantum dots; Fluorescence quenching; Hydrothermal synthesis; Industrial effluents
description: Carbon quantum dots (CQDs) has received world-wide recognition for their outstanding physicochemical properties that have the ability to substitute the semiconductor quantum dots. Herein, we have developed a strategy to determine the presence of Cd2+ using CQDs as a fluorescence probe. The CQDs were synthesized from the leaves of Polyalthia longifolia (a natural source) through a one-step hydrothermal method. The CQDs obtained from Polyalthia longifolia (p-CQDs) was characterized using XRD, TEM, FTIR, Raman Spectroscopy, XPS Studies, UVVisible spectroscopy and PL Spectroscopy. The p-CQDs displayed bright red fluorescence under the UV light, with good water solubility, and appreciable photostability and a quantum yield of 22%. The p-CQDs had a quasi-spherical morphology with an average particle size of 3.33 nm. The p-CQDs showed high selectivity and sensitivity for the detection of Cd2+ with a low limit of detection of 2.4 nM and a wide linear range of 7.3 nM12 ?M. The PL intensity of the p-CQDs showed a quenching effect in presence of Cd2+ and the mechanism of quenching was validated via fluorescence lifetime decay studies. We have also studied the effectiveness of the fluorescent probe developed for Cd2+ sensing in real samples of ground water and industrial effluents. 2022 Elsevier Ltd
creator: Sariga; Ayilliath Kolaprath M.K.; Benny L.; Varghese A.
source: Dyes and Pigments, Vol-210
publisher: Elsevier Ltd
date: 2023-01-01
rights: Restricted Access
relation: ISSN: 1437208; CODEN: DYPID
format: Online
language: English
type: Article
coverage: Sariga, Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Ayilliath Kolaprath M.K., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Benny L., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Varghese A., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India