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A Multi-Modal Approach to Digital Document Stream Segmentation for Title Insurance Domain
In the twenty-first century, storing and managing digital documents has become commonplace for all corporate and public sectors around the world. Physical documents are scanned in batches and stored in a digital archive as a heterogeneous document stream, referred to as a digital package. To make Robotic Process Automation (RPA) easier, it's necessary to automatically segment the document stream into a subset of independent, coherent multi-page documents by detecting the appropriate document boundary. It's a common requirement of a TI company's Automated Document Management Systems (ADMS), where business operations are automated using RPA and the goal is to extract information from digital documents with minimal user intervention. The current study proposes, evaluates, and compares a multi-modal binary classification network incorporating text and picture aspects of digital document pages to state-of-the-art baseline methodologies. Image and textual features are extracted simultaneously from the input document image by passing them through Visual Geometry Group 16 - Convolutional Neural Network (VGG16-CNN) and pre-trained Bidirectional Encoder Representations from Transformers (Legal-BERT {}_{base} ) model through transfer learning respectively. Both features are finally fused and passed through a fully connected layer of Multi Layered Perceptron (MLP) to obtain the binary classification of the pages as the First Page (FP) and Other Page (OP). Real-time document image streams from production business process archive were obtained from a reputed Title Insurance (TI) company for the study. The obtained F_{1} score of 97.37% and 97.15% are significantly higher than the accuracies of the considered two baseline models and well above the expected Straight Through Pass (STP) threshold defined by the process admin. 2013 IEEE. -
Kernel granulometric texture analysis and light res-aspp-unet classification for covid-19 detection
This research article proposes an automatic frame work for detecting COVID -19 at the early stage using chest X-ray image. It is an undeniable fact that coronovirus is a serious disease but the early detection of the virus present in human bodies can save lives. In recent times, there are somany research solutions that have been presented for early detection, but there is still a lack in need of right and even rich technology for its early detection. The proposed deep learning model analysis the pixels of every image and adjudges the presence of virus. The classifier is designed in such a way so that, it automatically detects the virus present in lungs using chest image. This approach uses an image texture analysis technique called granulometric mathematical model. Selected features are heuristically processed for optimization using novel multi scaling deep learning called light weight residual-atrous spatial pyramid pooling (LightRES-ASPP-Unet) Unet model. The proposed deep LightRES-ASPPUnet technique has a higher level of contracting solution by extracting major level of image features. Moreover, the corona virus has been detected using high resolution output. In the framework, atrous spatial pyramid pooling (ASPP) method is employed at its bottom level for incorporating the deep multi scale features in to the discriminative mode. The architectural working starts from the selecting the features from the image using granulometric mathematical model and the selected features are optimized using LightRESASPP- Unet. ASPP in the analysis of images has performed better than the existing Unet model. The proposed algorithm has achieved 99.6% of accuracy in detecting the virus at its early stage. 2022 Tech Science Press. All rights reserved. -
Numerical simulation of JeffreyHamel flow of nanofluid in the presence of gyrotactic microorganisms
The nonlinear differential equations play a prominent role in mathematically describing many phenomena that occur in our world. A similar set of equations appear in this paper that govern the nanofluid flow between two non-parallel walls in the presence of gyrotactic microorganisms that are responsible for bioconvection. These microorganisms ensure the safety of the appliance by avoiding the accumulation of nanoparticles and the movement of these nanoparticles within the fluid experiences major slip mechanisms as discussed by Buongiorno. Further, the orientation of the channel is described by the parameter ? and based on this parameter, the channel is said to be converging if (Formula presented.) and the channel is diverging if (Formula presented.). The case when (Formula presented.) corresponds to a channel with parallel walls, hence this case is ignored. Following these assumptions, the set of governing equations thus formed are made dimensionless and further solved by the Differential Transformation Method (DTM) and the outcomes are discussed through graphs. The analysis is performed for both converging and diverging orientations of the channel. The results indicate that the temperature and the concentration profiles increase with the increase in Brownian motion parameters in both divergent and convergent channels. Meanwhile, the increase in Reynolds number decreases the temperature of the nanofluid. Through the simulation, it was observed that the heat flow is taking place along the isothermal planes in the case of the diverging channel but it was uniform in the domain of the converging channel. 2021 Informa UK Limited, trading as Taylor & Francis Group. -
What Numbers Never Revealed: Tracing Dalit Christian Modernity Through Malayalam Literature
Kerala has a long-standing history of Christianity as well as conversions. Conversions can be dated back to the fifteenth and sixteenth centuries, which saw a large number of slave caste conversions. For the slave castes of KeralaPulayas and ParayasChristianity offered a salvation from the circle of pollution. Scriptures provided the slave castes new vistas of knowledge which they encultured to form a counter discourse against the public sphere set up by the dominant castes. The public sphere of the Malayalee psyche was formed by the ideas of caste pollution, which restricted the slave castes from accessing the social space. A new Dalit perspective on the religious consciousness of the converted Christians will show the role of the Bible, Original Sin, and Repentance on their daily lives. Dalit Christian literature becomes the primary source where Christianity metamorphoses into an oppositional force in resisting oppression as well as in creating a social space with agency. 2022 Indian Institute of Management, Ahmedabad. -
Thermal optimisation through multilayer convective flow of CuO- MWCNT hybrid nanofluid in a composite porous annulus
The present article deals with the analysis of the three-layer convective flow of immiscible nanofluids in a composite porous annulus. Water and kerosene are chosen as base fluids due to their immiscible property that leads to the formation of a non-physical boundary separation and thus forming a multi-layer flow. In this model, the hybrid nanofluid is formed by suspending copper oxide (CuO) and multi walled carbon nanotubes (MWCNTs) in water which is sandwiched between layers of nanofluid formed by suspending CuO in kerosene leading to two boundary separations that give rise to the interface regions. Such a flow finds applications in the field of solar reactors, electronic cooling, etc. The model based on the above assumptions is in the form of a system of ordinary differential equations that are solved using the differential transformation method. The solutions are found to be in agreement with the existing literature and the results of this study are interpreted graphically. It is to be noted that the interfacial region in the multilayer nanofluid flow helps in maintaining the system at an optimum temperature which helps to cool down the systems. Further, the increase in the Eckert number increases the heat conduction of the nanofluid and pressure enhances the flow speed of the nanofluid. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
White LED Light-Mediated Eosin Y-Photocatalyzed One-Pot Synthesis of Novel 1,2,4-Triazol-3-Amines By Sequential Addition
Abstract: A facile and proficient, eco-friendly multicomponent synthesis of 12 novel biologically essential 1,2,4-triazol-3-amines via the sequential addition of substituted phenacyl bromide, aromatic aldehyde, hydrazinecarbothioamide, and urea under white LED with eosin Y as a photocatalyst has been developed. The intrinsic advantages are methodology is cost-effective, non-toxic, generates a high yield of product, is column chromatography free and does not need the use of a specific instrument. Surprisingly, our methodology uses moderate conditions and can count the tolerance of a wide variety of electron-donating and electron-withdrawing groups. The analysis and early conclusions give more value and context for the future development of organic synthesis using photocatalysts. Graphical Abstract: [Figure not available: see fulltext.] 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Linking non-financial motivators of women entrepreneurs with entrepreneurial satisfaction: A cluster analysis
Women entrepreneurs confronted with several obstacles while managing their business houses and dealt firmly developing successful ventures over time. The long term sustainability of their business reflects their entrepreneurial skills. The existence of certain forces empowered entrepreneurial drive of women entrepreneurs leading to their satisfaction and engagement in their ventures. The present investigation evaluated the antecedents of women's entrepreneurial satisfaction by examining 405 women entrepreneur participants using confirmatory factor analysis and cluster analysis techniques. This study comprises only micro and small businesses of women. The non-monetary determinants emerged out as the significant determinants of satisfaction of women entrepreneurs. The results revealed four clusters of women entrepreneurs based on motivational theory such as micro-achievers, entrepreneurial team, liberal and socialist feminism and optimism. The results also indicated that the clusters of women entrepreneurs' respond distinctively towards various dimensions of entrepreneurial satisfaction, i.e., quality of married life, overall venture satisfaction, achieved innovation, achieved freedom, team orientation, achieved recognition and identity and achieved employee trust. 2022 Inderscience Enterprises Ltd. -
A post covid machine learning approach in teaching and learning methodology to alleviate drawbacks of the e-whiteboards
Deep learning has paved the way for critical and revolutionary applications in almost every field of life in general. Ranging from engineering to healthcare, machine learning and deep learning has left its mark as the state-of-the-art technology application which holds the epitome of a reasonable high benchmarked solution. Incorporating neural network architectures into applications has become a common part of any software development process. In this paper, we perform a comparative analysis on the different transfer learning approaches in the domain of hand-written digit recognition. We use two performance measures, loss and accuracy. We later visualize the different results for the training and validation datasets and reach to a unison conclusion. This paper aims to target the drawbacks of the electronic whiteboard with simultaneous focus on the suitable model selection procedure for the digit recognition problem. 2021 Tamkang University. All Rights Reserved. -
Dynamics of fractional model of biological pest control in tea plants with beddingtondeangelis functional response
In this study, we depicted the spread of pests in tea plants and their control by biological enemies in the frame of a fractional-order model, and its dynamics are surveyed in terms of boundedness, uniqueness, and the existence of the solutions. To reduce the harm to the tea plant, a harvesting term is introduced into the equation that estimates the growth of tea leaves. We analyzed various points of equilibrium of the projected model and derived the conditions for the stability of these equilibrium points. The complex nature is examined by changing the values of various parameters and fractional derivatives. Numerical computations are conducted to strengthen the theoretical findings. 2021 by the authors. Licensee MDPI, Basel, Switzerland. -
Iodine promoted synthesis of pyrido[2?,1?:2,3]imidazo[4,5-c]quinoline derivatives via oxidative decarboxylation of phenylacetic acid
An unprecedented and efficient molecular iodine promoted domino protocol for the synthesis of N polycyclic pyrido[2?,1?:2,3]imidazo[4,5-c]quinolines were reported from phenylacetic acid and 2-(imidazoheteroaryl)anilines. This methodology was also extended for the preparation of benzo[4?,5?]thiazolo [2?,3?:2,3]imidazo[4,5-c]isoquinolines in good yields. However, this protocol proceeds via a sequential decarboxylation of phenylacetic acid with I2/DMSO system followed by Pictet-Spengler cyclization in good yields. 2022 Taylor & Francis Group, LLC. -
Mediating role of teacher confidence between support system and satisfaction
Online education in India has witnessed a shift due to the ongoing pandemic, compelling the Indian education sector to adapt to new advancements. The study's main purpose has been to find the relationship between the support systems of institutions, teachers support and students, leading to instructors' satisfaction. It further analyses the mediating role of educators' confidence in linking support systems and leading to teachers' satisfaction. The sample for our research consisted of 129 teachers from Higher Educational Institutions (HEIs). We found that there is a significant relationship between support systems and teacher satisfaction. Among the three support systems, institutions support had a significant influence. On the other hand, teachers' confidence had a partially mediating effect on their satisfaction, even though they could translate to higher effectiveness in online teaching. Further, this study inferred that educational institutions are quick to adapt to online teaching due to the ongoing pandemic. Copyright 2022 Inderscience Enterprises Ltd. -
Visible Light Mediated Organophotoredox-Catalyzed One-Pot Domino Synthesis of Novel 6,7 Disubstituted 1H-Pyrroles
The development of environmentally benign protocols to synthesize novel N-heterocycles is vital in the field of synthetic organic chemistry. We herein report a successful one-pot domino synthesis of novel 6,7 disubstituted 1H-pyrroles using substituted phenacyl bromide, barbituric acid/Meldrums acid, aromatic amines catalysed by 5mol% Fluorescein in presence of visible light. This procedure is a useful and adaptable method for the synthesis of pyrroles since it is compatible with a wide range of sensitive functional groups, does not require column chromatography purification. During the reaction, Fluorescein may catalyse the formation of enamine leading to amino alcohol which subsequently undergoes dehydration to give 6,7 disubstituted 1H-pyrroles. All the synthesized derivatives were obtained in 9095% yields and were characterized by 1H, 13C NMR and HRMS (ESI) analysis. Graphical Abstract: [Figure not available: see fulltext.] 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Improved dhoa-fuzzy based load scheduling in iot cloud environment
Internet of things (IoT) has been significantly raised owing to the development of broadband access network, machine learning (ML), big data analytics (BDA), cloud computing (CC), and so on. The development of IoT technologies has resulted in a massive quantity of data due to the existence of several people linking through distinct physical components, indicating the status of the CC environment. In the IoT, load scheduling is realistic technique in distinct data center to guarantee the network suitability by falling the computer hardware and software catastrophe and with right utilize of resource. The ideal load balancer improves many factors of Quality of Service (QoS) like resource performance, scalability, response time, error tolerance, and efficiency. The scholar is assumed as load scheduling a vital problem in IoT environment. There are many techniques accessible to load scheduling in IoT environments.With this motivation, this paper presents an improved deer hunting optimization algorithm with Type II fuzzy logic (IDHOA-T2F) model for load scheduling in IoT environment. The goal of the IDHOA-T2F is to diminish the energy utilization of integrated circuit of IoT node and enhance the load scheduling in IoT environments. The IDHOA technique is derived by integrating the concepts of Nelder Mead (NM) with the DHOA. The proposed model also synthesized the T2L based on fuzzy logic (FL) systems to counterbalance the load distribution. The proposed model finds useful to improve the efficiency of IoT system. For validating the enhanced load scheduling performance of the IDHOA-T2F technique, a series of simulations take place to highlight the improved performance. The experimental outcomes demonstrate the capable outcome of the IDHOA-T2F technique over the recent techniques. 2022 Tech Science Press. All rights reserved. -
Development and evaluation of the bootstrap resampling technique based statistical prediction model for Covid-19 real time data : A data driven approach
The objective of the article is to develop earlyR package based novel coronavirus disease (COVID-19) forecasting model. The reported COVID-19 serial interval data is applied for obtaining maximum likelihood value of the reproduction number (R0) using maximum likelihood approach and projections package is applied for getting trajectories of epidemic curve. The minimum, median, mean and maximum projected value of R0 with 95% confidence interval (CI) is obtained by using bootstrap resampling strategy and the predicted cumulative probable count of new cases is also presented with different quantile. To validate the results with real scenario, the past COVID-19 data is considered. The % error rate ranges from -7.91% to 21.27% for the developed model for the five Indian States. 2022 Taru Publications. -
Improved dragonfly optimizer for intrusion detection using deep clustering CNN-PSO classifier
With the rapid growth of internet based services and the data generated on these services are attracted by the attackers to intrude the networking services and information. Based on the characteristics of these intruders, many researchers attempted to aim to detect the intrusion with the help of automating process. Since, the large volume of data is generated and transferred through network, the security and performance are remained an issue. IDS (Intrusion Detection System) was developed to detect and prevent the intruders and secure the network systems. The performance and loss are still an issue because of the features space grows while detecting the intruders. In this paper, deep clustering based CNN have been used to detect the intruders with the help of Meta heuristic algorithms for feature selection and preprocessing. The proposed system includes three phases such as preprocessing, feature selection and classification. In the first phase, KDD dataset is preprocessed by using Binning normalization and Eigen-PCA based discretization method. In second phase, feature selection is performed by using Information Gain based Dragonfly Optimizer (IGDFO). Finally, Deep clustering based Convolutional Neural Network (CCNN) classifier optimized with Particle Swarm Optimization (PSO) identifies intrusion attacks efficiently. The clustering loss and network loss can be reduced with the optimization algorithm. We evaluate the proposed IDS model with the NSL-KDD dataset in terms of evaluation metrics. The experimental results show that proposed system achieves better performance compared with the existing system in terms of accuracy, precision, recall, f-measure and false detection rate. 2022 Tech Science Press. All rights reserved. -
A versatile approach based on convolutional neural networks for early identification of diseases in tomato plants
Agriculture is one of the primary occupations in many countries. Tomatoes are grown by many farmers in countries where the water resource is available in abundance. Improper methods of cultivation and failure to identify the diseases when it is in the nascent stage results in the reduction of crop yield thus affecting the outcome of cultivation. This paper proposes a novel method of early identification of diseases in tomato plants by making use of convolutional neural networks (CNN) and image processing. Dataset from an open repository was considered for training and testing and the algorithm was capable of identifying nine different varieties of diseases that affect the tomato plant at its early stages. The images of tomato leaves were fed for identification through processing and classification. An optimum model was developed by analyzing various architectures of CNN including the VGG, ResNet, Inception, Xception, MobileNet and DenseNet. The performance of each of these architectures was compared and various metrics like the accuracy, loss, precision, recall and area under the curve (AUC) were analyzed. 2022 World Scientific Publishing Company. -
A novel optimised method for speckle reduction in medical ultrasound images
The advancement of medical imaging techniques evolving from X-ray to PET images and the medical image analysis helped medical experts to detect, diagnose and offer treatments for complex disorders and deadly diseases in the human body. Among the various modalities used, Ultrasound imaging is the most widely accepted modality because of its affordability, non-invasive nature and various other features. But the presence of speckle noise in ultrasound image lowers the image quality and reduces diagnostic value. This article states an improved hybrid speckle noise reduction method, a combined application of Kuan and non-local means filters. In this method, Kuan filter is used to sharpen the edges and thereafter the speckle noise elimination is done by using the non-local means. In addition, the performance of the proposed hybrid filter and its design parameters are optimised by using a meta-heuristic called grey wolf optimiser. The performance of hybrid method is evaluated by analysing a chosen set of well-known post filtering methods used for speckle reduction with given ultrasound B-mode images. The comparison of test results using remarkable performance metrics and computation time demonstrate that the hybrid method can be used as the efficient speckle reduction method for image analysis. Copyright 2022 Inderscience Enterprises Ltd. -
Removal of cadmium heavy metal ion using recycled black toner powder
The presence of heavy metal ions in the industrial effluents is considered as a major threat to humans and to the ecosystem. Among the available various types of heavy metal ions, cadmium is widely used in many industrial applications and is also considered as the hazardous heavy metal ion even in low level of concentration. In this present work, an attempt has been made to utilize the recycled black toner powder as a low cost adsorption material in the removal of toxic cadmium heavy metal ion. Batch adsorption technique was used for the removal of cadmium heavy metal ion. The experiments were conducted by varying the pH values from 3, 5 and 7, contact time from 15, 30, 45, 60 and 75 min and the dosage of the adsorbent from 2, 4, 6 and 8 g/L. Experimental results shows that the cadmium heavy metal ions were effectively removed for pH value of 5 and increasing the adsorbent dosage doesn't aid in increasing the adsorption rate. Rapid adsorption of cadmium heavy metal ions was observed only during the first 30 min of contact time and it reached equilibrium after contact time of 45 min. 2021 -
Self-esteem and self-efficacy among HIV-positive adolescents: an intervention study
Introduction: The aim of the present study was to understand the impact of comprehensive intervention program on self-esteem and self-efficacy among human immunodeficiency virus (HIV)-positive adolescents. Material and methods: Participants of the research were perinatally HIV-infected adolescent boys and girls, currently living in HIV care and support center. The study adopts a quasi-experimental non-equivalent control group design. Sample consisted of 97 adolescents (47 boys and 50 girls). Self-esteem was assessed using Morris Rosenbergs (1965) self-esteem scale, and self-efficacy was assessed using general self-efficacy scale (GSE) (1995) by Ralf Schwarzer & Matthias Jerusalem. It was hypothesized that there would be a significant improvement in the level of self-esteem and self-efficacy among participants of experimental group and no such improvement would be noticed in control group. Group intervention was conducted for experimental group focusing on four domains physical, cognitive, affective, and social, for 44 hours spread over 6 months. Comprehensive intervention was implemented through innovative expressive strategies. Participants were assessed pre and post-intervention. Results were analyzed using correlated t-test for self-esteem and Wilcoxon signed-rank test for self-efficacy scores. Results: There is a significant improvement in the level of self-esteem (t = 21.154; p < 0.001) and self-efficacy (z = 6.036; p < 0.001) post-intervention in the experimental group, and no such improvement was observed on both the variables in control group. Conclusions: The current study reveal that post-intervention there is a significant improvement in the level of self-esteem and self-efficacy among HIV-positive adolescents. 2022 Termedia Publishing House Ltd.. All rights reserved. -
Evaluating the usability of mhealth applications on type 2 diabetes mellitus using various mcdm models
The recent developments in the IT world have brought several changes in the medical industry. This research work focuses on few mHealth applications that work on the management of type 2 diabetes mellitus (T2DM) by the patients on their own. Looking into the present doctor-to?patient ratio in our country (1:1700 as per a Times of India report in 2021), it is very essential to develop self?management mHealth applications. Thus, there is a need to ensure simple and user-friendly mHealth applications to improve customer satisfaction. The goal of this study is to assess and appraise the usability and effectiveness of existing T2DM?focused mHealth applications. TOP? SIS, VIKOR, and PROMETHEE II are three multi?criteria decision?making (MCDM) approaches considered in the proposed work for the evaluation of the usability of five existing T2DM mHealth applications, which include Glucose Buddy, mySugr, Diabetes: M, Blood Glucose Tracker, and OneTouch Reveal. The methodology used in the research work is a questionnaire?based evaluation that focuses on certain attributes and sub?attributes, identified based on the features of mHealth applications. CRITIC methodology is used for obtaining the attribute weights, which give the pri-ority of the attributes. The resulting analysis signifies our proposed research by ranking the mHealth applications based on usability and customer satisfaction. 2021 by the authors. Licensee MDPI, Basel, Switzerland.