bluuebunny/crossref_metadata_2025 huggingface dataset:
Benefits of vacuum-assisted closure therapy over standard treatments for infected and chronic non-healing wounds after kidney transplantation
Authors: Shabunin A. V. , Parfenov I. P. , Drozdov P. A. , Podkosov O. D. , Paklina O. V. , Nesterenko I. V. , Makeev D. A.
Published: April 2021

Objective: to evaluate the effectiveness of vacuum-assisted closure (VAC) therapy in comparison with standard treatments for infected and chronic non-healing wounds after kidney transplantation.Materials and methods. From June 2018 to November 2019, 75 kidney transplants from deceased donors were performed at the Transplantation Ward of Botkin City Clinical Hospital. There were 47 men (62.6%) and 28 women (37.4%). Standard surgical technique was used. Immunosuppressive therapy was carried out according to a three-component scheme with anti-CD25 monoclonal antibody induction (basiliximab) intraoperatively and on day 4. All patients received antibiotic therapy with protected third-generation cephalosporins for 7 days after surgery. Postoperative complications were evaluated according to the Clavien-Dindo classification. Standard methods, including daily dressings using modern dressing materials (group I) and VAC therapy (group II) were used for treating infected and chronic non-healing wounds.Results. 30-day mortality in the postoperative period was zero. Postoperative complications were recorded in 11 patients (14.6%), of which 7 had postoperative wound complications. Group I included 3 patients (1 with aKlebsiella pneumonia-infected wound and 2 with chronic non-healing wounds and no microflora growth). Group 2 had 4 patients (3 with infected wounds (Esherichia coli- 1,Klebsiella pneumonia- 2) and 1 with chronic non-healing wound). Complete cleansing of wound, absence of bacterial growth according to the microbiological examination, and maturation of granulations according to histological examination were considered as the criteria upon which a wound could be sutured in both groups of patients. The average time between the start of treatment and secondary suturing in group 1 patients was 33.11 ± 5.43 (28-37) and 15.01 ± 3.15 (13-17) days in group 1 and group 2 respectively.Conclusion. VAC therapy in patients with wound complications resulting from kidney transplantation, in comparison with standard treatment, can achieve rapid wound cleansing, acute inflammation relief and accelerated maturation of mature granulation tissue, thereby improving treatment outcomes in this category of patients.
A bile duct stent broken during repeat pregnancy in a post-liver transplant patient
Authors: Tarazov P. G. , Polikarpov A. A. , Granov D. A. , Borovik V. V.
Published: April 2021

A young female patient who developed anastomotic biliary stricture following an orthotopic liver transplantation was observed. A self-expandable metallic stent was placed to correct the stricture. At the 8th month of her repeat pregnancy, the stent broke asymptomatically into half. Fortunately, the second childbirth, like the first one, had no complications. Eighteen months later, due to obstruction of fragments by sludge and gallstones, re-stenting was performed with a coated biliary stent. Four years and five months later, recurrent jaundice occurred due to occlusion of the second stent. This was addressed by surgical removal of both stents. Two years after surgery, the bile ducts remain completely patent. We found only two cases in literature on a similar extremely rare biliary stenting complication. It has been suggested that stent deformation may be related to pregnancy. The feasibility of using stenting in benign biliary strictures in some clinical situations is discussed.
Liver steatosis in brain death donors
Authors: Voronov D. V. , Minina M. G. , Chomaev A. K. , Iljinsky I. M. , Tsirulnikova O. M.
Published: April 2021

Aim. To study the frequency of fatty hepatosis in liver biopsies of consecutive brain death donors before cold preservation. Materials and methods. Liver biopsies (before cold preservation) of 300 consecutive donors with brain death were studied. Histological preparations were stained with hematoxylin and eosin, and tricolor Masson staining was performed. Results. The frequency of different degrees of fat hepatosis in men and women did not differ significantly (>0.05). Fat dystrophy of hepatocytes was absent in more than half of the cases (n = 182; 60.7%). A slight degree of fatty degeneration was diagnosed in 57 (19,0%) donors. In total, 239 (79.7%) donor livers were absolutely suitable for transplantation. Moderate degree of steatosis, which is associated with early biliary complications, was detected in 18 (6.0%) cases, and severe degree, which is a contraindication to the use of the organ for transplantation, was detected in 43 (14.3%) cases. Conclusion. Before cold preservation, liver from brain death donors is relatively rarely unsuitable for transplantation.
Valve-sparing operations on the aortic valve and the ascending aorta: radical correction of congenital and acquired heart diseases. Immediate outcomes
Authors: Akopov G. A. , Govorova T. N. , Ivanov A. S.
Published: April 2021

This paper presents the immediate outcomes of valve-sparing operations on the aortic valve and ascending aorta in radical correction of congenital and acquired heart disease. Materials and methods. The study enrolled 50 patients with aortic insufficiency who were operated upon at Shumakov National Medical Research Center of Transplantology and Artificial Organs from 2011 to 2019. The mean age was 48 ± 16 years, 64% of them were men (n = 32). The study included patients with tricuspid (n = 36, 72%) and bicuspid (n = 14, 28%) aortic valves. Aortic valve reimplantation was performed in 32 (64%) patients, aortic root remodeling - in 1 (2%). 17 (34%) patients had no aortic root reconstruction or remodeling. Aortic valve reimplantation was done in 4 (8%) cases in combination with coronary artery bypass grafting, and in 4 (8%) with mitral and tricuspid valve repair. Results. Thirty-day mortality was 0%. In 1 case (2%), a permanent pacemaker was installed due to complete atrioventricular block. There were no neurological and coronary events, and cases of endocarditis. In all patients (100%), aortic valve insufficiency after surgical correction did not exceed grade 1 according to echocardiographic follow-up examination. On aortic valve mean and peak gradients were 8 ± 6 and 15 ± 7 mm Hg, respectively. Findings. Type I and II valve-sparing reconstructive surgery (for bicuspid and tricuspid aortic valves) is an excellent alternative to prosthetic repair with great postoperative outcomes, low valve-associated complications and low mortality.
Corpus de registres différents pour le développement d’un aligneur d’unités polylexicales
Authors: Lemaire Claire , Guilbaud Jean-Philippe
Published: April 2021

Comment trouver des données exprimant les mêmes concepts dans des registres de langue différents ? Après un essai infructueux d’extraction terminologique à partir de corpus comparables spécialisés dans le domaine du médical dans trois langues différentes (anglais, allemand, français), l’idée est d’ajouter pour chaque langue des sous-corpus du registre vulgarisé afin d’y détecter des relations de synonymie. Or ce type de ressources n’existe pas pour l’allemand de spécialité dans le domaine du médical. Nous présentons la constitution d’un corpus de 400 000 mots en allemand dans le domaine de la cancérologie, subdivisé en deux sous-corpus de même taille. À partir d’équivalents en allemand du mot-clé «cancer du sein», nous avons recueilli pour un premier sous-corpus, des textes qui s’adressent à des patientes (et des patients) ou à leurs familles, et pour un second sous-corpus, des textes qui s’adressent à des médecins ou des chercheurs en médecine.
Terminologie orientée vers les connaissances et pratiques traditionnelles
Authors: Moukrim Samira
Published: April 2021

La langue amazighe (berbère) n’est encore vivante et authentique que dans les domaines traditionnels. Or, la société traditionnelle amazighe subit actuellement une mutation très profonde. Les faits anciens se trouvent menacés à cause des processus d’industrialisation et de mondialisation. Avec l’évolution accélérée que connaît la société actuelle, le phénomène de déperdition de cette langue dépasse le rythme naturel et doit en conséquence être considéré comme préoccupant. \\ Sans une politique linguistique qui puisse actualiser l’amazighe pour qu’elle s’adapte à tous les domaines de la communication, notamment techniques et modernes, cette langue risque de disparaître à moyen terme. Dans ce contexte, une orientation de recherche centrée sur le sentiment d’urgence et de sauvetage apparaît primordiale pour sauvegarder les vestiges d’une société en voie de disparition. \\ Dans ce papier, il est question de la construction de terminologies orientées vers les connaissances et pratiques traditionnelles pour sauvegarder une langue à tradition orale, l’amazighe. Nous abordons le travail terminologique dans sa dimension de documentation, de sauvegarde et de revitalisation de la langue. Le corpus d’étude est analysé en exploitant les fonctionnalités offertes par l’outil informatique TXM.
Quel rôle accorder aux adjectifs dans la langue de spécialité ?
Authors: Grcic Simeunovic Larisa , Frleta Tomislav
Published: April 2021

La dénotation des propriétés et des sous-classes par des adjectifs représente un élément important pour la description terminologique. Dans ce travail nous nous interrogeons sur le statut des adjectifs qualificatifs, relationnels et classifieurs dans le domaine spécialisé de la karstologie. La description et l’analyse du corpus spécialisé monolingue nous conduit à en proposer un classement fondé sur les différents emplois des adjectifs. Des critères morphologiques, syntaxiques et sémantiques ont été introduits afin de décrire la relation entre l’adjectif et le nom recteur d’une part, et, d’autre part, de faciliter la distinction entre les emplois prédicatifs et non prédicatifs. Dans bon nombre de cas, les adjectifs donnent lieu a deux interprétations parallèles, qui illustrent le rôle hétérogène des adjectifs en langue de spécialité.
Critères de constitution des entrées à partir d’un corpus historique
Authors: Mabrak Sami
Published: April 2021

Le thème de l’article s’inscrit dans le deuxième axe du programme du colloque, c’est-à-dire, les approches d’extractions terminologiques et d’unités lexicales spécialisées. L’article se penchera plus spécifiquement sur les approches d’extractions d’unités lexicales dans une perspective lexicographique. Le sujet de notre article relève du domaine de la lexicographie et plus précisément de la lexicographie contemporaine. Nous abordons l’une des questions qui concerne la construction de la macrostructure d’un type particulier des dictionnaires, à savoir : le dictionnaire historique. Notre objectif est d’analyser les critères à partir desquels les entrées de ce type de dictionnaires sont constituées. Pour ce faire, nous adoptons une approche analytique et comparative. Quant au corpus de notre étude, nous l’avons constitué à partir de deux dictionnaires historiques déjà compilés et publiés, à savoir : le Dictionnaire historique de la langue française et le Dictionnaire historique de la langue anglaise. Les résultats de cette étude nous permettront de mener une réflexion sur les critères de constitution des entrées du Dictionnaire historique de la langue arabe.
Les routines de topicalisation dans les écrits scientifiques en français
Authors: Yujing Ji , Tutin Agnès
Published: April 2021

Le discours des écrits scientifiques est dialogique. L’auteur des écrits scientifiques présente non seulement des contenus informatifs, mais utilise aussi des éléments métadiscursifs pour évaluer les contenus et interagir avec ses lecteurs. Dans notre étude, nous nous focalisons sur l’aspect interlocutif des écrits scientifiques réalisé à travers des éléments métadiscursifs complexes, les routines de guidage du lecteur comme L’objectif de cet article est d’étudier… Plus précisément, nous examinons un petit ensemble des routines que nous nommons « routines de topicalisation » afin de comprendre comment l’auteur met en relief les idées ou les informations importantes pour ses lecteurs. À partir d’un corpus d’articles de recherches en sciences humaines et sociales, nous appliquons la méthode des « arbres lexico-syntaxiques récurrents » pour extraire des routines. Nous modélisons et analysons ensuite les fonctions rhétoriques et argumentatives des routines de topicalisation.
Un devin de microstructures
Authors: Mangeot Mathieu , Bellynck Valérie
Published: April 2021

Dans cet article, nous présentons un outil pour annoter une ressource non structurée ou semi-structurée, de façon à automatiser l’import de ses données dans un environnement générique facilitant et uniformisant son exploitation. Cet outil s’appuie sur le calcul d’une signature, caractérisant la ressource par des informations comptables sur ses éléments, et sur des heuristiques exploitant les statistiques de la signature pour repérer les entrées et la microstructure de chaque entrée dans le cas d’une ressource lexicale à importer dans la plateforme de bases lexicales Jibiki. Le résultat produit est géré dans iPolex, un entrepôt dédié aux traitements de fichiers de ressources lexicales permettant d’y ajouter des méta-données. La plateforme Jibiki accède à iPoLex pour importer directement des ressources lexicales bien formées et suffisamment renseignées. Le processus d’import ainsi constitué est utilisé pour créer et peupler des bases lexicales dans Jibiki. Les ressources ainsi importées sont ensuite consultables et éditables en ligne.
Les pragmatèmes de salutation du japonais dans une perspective contrastive avec le français
Authors: Ladreyt Alexis
Published: April 2021

Le pragmatème (Mel’čuk 1995), que l’on peut définir comme un sous-type de structure phraséologique ayant une fonction pragmatique spécifique, est un objet d’étude fascinant qui ne cesse d’attiser la curiosité des chercheurs en linguistique. Cette structure phraséologique particulière se caractérise principalement par son ancrage fort à sa situation prototypique d’emploi. Nous faisons ici l’hypothèse que d’une part la notion de pragmatème est tout à fait pertinente pour rendre compte des structures ritualisées du japonais, d’autre part, que la perspective contrastive permet d’apporter de nouveaux éléments typologiques pour circonscrire ce champ notionnel. Dans le cadre de cette communication, nous nous concentrerons sur les pragmatèmes polylexicaux autonomes à noyau verbal, nominal ou adjectival, placés en ouverture ou en clôture de l’interaction et accomplissant l’acte de salutation ou de prise de congés. Nous proposons une typologie du phénomène en prenant en compte la structure de l’interaction en japonais et le matériel linguistique déployé pour réaliser l’acte de salutation.
Analyse et classification d’exemples illustratifs dans le dictionnaire “Cesselin" en utilisant Google Traduction et un dictionnaire UNL-UWs
Authors: Tomokiyo Mutsuko , Mangeot Mathieu , Boitet Christian
Published: April 2021

Savoir si un exemple dans un dictionnaire bilingue est un proverbe, une expression idiomatique, une collocation ou un simple exemple d’utilisation serait très utile aux utilisateurs, mais est rarement indiqué. Dans cet article, nous présentons une classification manuelle et une annotation d’exemples dans un dictionnaire bilingue japonais-français, le « Cesselin » (145000 entrées), dérivées de l’analyse manuelle de 500 entrées, et décrivons les étapes d’automatisation du processus d’annotation. Quant aux proverbes, nous utilisons simplement des dictionnaires de proverbes. Pour les autres cas, notre méthode consiste à comparer la traduction (automatique) en anglais d’un exemple original (japonais) et sa traduction (française) dans le dictionnaire. La comparaison est basée d’abord sur le nombre de lexèmes communs aux deux sorties (anglaises), et deuxièmement sur le nombre de lexèmes synonymes, qui peuvent être trouvés en utilisant un grand dictionnaire UNL-UW. Nous montrons notre procédure de classification en détail et son automatisation future.
Constitution et traitement d’un corpus bilingue d’articles scientifiques
Authors: Kraif Olivier
Published: April 2021

Nous présentons dans cet article un outil dédié à la constitution de corpus parallèles alignés constitués à partir de l’aspiration de sources sur le Web. Nous montrons comment cet outil a permis de constituer un corpus aligné anglais-français pour un type de texte difficile à trouver en version bilingue, à savoir les articles scientifiques. Moyennant l’élaboration de chaînes de traitement basées sur l’écriture d’expressions régulières (dédiées à la définition des urls à aligner et à l’extraction des contenus) nous avons pu constituer, lors d’une première campagne, un corpus parallèle d’environ 4 millions de mots dans chaque langue, formaté en XML-TEI et TMX.
Stability area of a synchronous generator nonlinear model with multiparametric excitation controller
Authors:   Novosibirsk State Technical University, Russian Federation, Chekhonadskikh Alexander
Published: April 2021

We take as the research object the well-known system of nonlinear differential and functional equations that describes a synchronous generator. PIDD2-control was carried out through the excitation block. Effective values of the steady state in relative units and the preliminary settings of suboptimal controllers were obtained earlier using a linearized model. Disturbing surges (spikes and slump) in bus voltages were modeled as line impedance changes. The system stabilization was studied at various surges values and controller parameters by means series of numerical experiments; the calculations were carried out by the methods of Runge-Kutta and Dorman-Prince. The main attention was paid to various transient types, both stabilizing and diverging, as well as a configuration of the stability region boundary in the controller parameters of and a surge magnitude; the paper presents the results for the proportional control parameter are as the most informative. We've identified five types of transients and several important features of the model's behavior near the stabilization area boundary. Thus, the nonlinear model turned out to be unstable to small and stable to bigger perturbations in the unstable area of its linearization. The steady-state oscillations at the boundary have a lower amplitude with increasing of an initial perturbation, etc.
Do Consumers Really Care About Corporate Social Responsibility Messages on Social Media? An Investigation on Turkish Telecommunication Companies
Authors: DİNÇER Mustafa Abdül Metin , YILDIRIM Emre , ARSLAN Yusuf
Published: April 2021

Over the last two decades, corporate social responsibility (CSR) has been regarded as obligatory rather than voluntary. The literature review suggests that these activities provide benefits such as increasing sales, developing the companies' positive image, reducing the costs, protecting the environment, and many other issues. However, it is questionable whether it is valid for all sectors and platforms. In this sense, this study investigates whether the consumers care about companies' CSR messages on social media. From this perspective, an investigation on Turkish telecommunication companies was conducted. The researchers made a qualitative content analysis, and in this regard, the documents of the study were analyzed with qualitative analysis software MAXQDA. According to the obtained results, most consumers do not believe in the sincerity of the cases' CSR activities. Moreover, this insincerity leads to negative credibility in the field. Both of these negative dimensions in the consumers' minds prevent the correct message conveying about CSR activities of the cases.
Online Products Fake Reviews Detection System Using Machine Learning
Authors: Et. al. Deepika Vachane,
Published: April 2021

Nowadays online analyses gotten single indispensable components clients web based shop. Associations plus people utilize data near purchase  correct items then settle on business choices.affect spammers otherwise unscrupulous agents make bogus surveys also elevate  items near  rivalries. To handle this issue, examines have been directed to define successful approaches to recognize the spam surveys. Different spam recognition strategies have been presented in which a large portion of them separates significant highlights from the content or utilized AI proceduresIn this paper, named spam recognition framework, which uses spam highlights for showing review enlightening lists as heterogeneous information structures to configuration spam ID strategy into a gathering of issue. Utilizing the criticalness, us to acquire great results with respect to various measurements on survey informational indexes. The commitment effort remains after people search enquiry show wholly n-no of things similarly as recommendation of the thing.
Implementation of Machine Learning Approaches for Breast Cancer Prediction
Authors: Et. al. Komal Hausalmal ,
Published: April 2021

The grouping of bosom malignant growth has been the subject of enthusiasm for the fields  of  medicinal  services and bioinformatics, in light of the fact that it is the subsequent primary explanation of disease related passings in ladies. Bosom malignancy can be investigated utilizing a biopsy where tissue is wiped out and concentrated under magnifying instrument. The distinguishing proof of issue depends on the capability and experienced of the histopathologists, who will consideration for unusual cells. Be that  as  it  may,  if  the  histopathologist  isn’t  all around prepared or encountered, this may prompt wrong finding. With the ongoing suggestion in picture handling and AI space, there is an enthusiasm for test to build up a solid example acknowledgment based structure to improve the nature of finding. In this work, the picture highlight extraction approach and AI approach is utilized for the grouping of bosom disease utilizing histology pictures into threatening. The preprocessing on the picture is done using histopathological picture after that apply feature extraction and classify the final result using SVM and Naive Bayes Classification techniques.
Voice Based Disease Identification System
Authors: Et. al. Manasi Bendale,
Published: April 2021

Human voice as well as the sound of the body is used as a clinical method to assess the health condition of an individual. The evaluation of the human voice has risen as a critical field of exploration. Speech analysis fundamentally involves the extraction of certain features from voice signals for generation of voice in alluring pertinence by using reasonable techniques. This paper brings up normal ailments that sway understanding voice patterns in proof for driving research that have affirmed voice modifications as demonstrative manifestations in their respective ailments and also the technique by which voice analysis can be done.
Disease Identification System using Image Analysis
Authors: Et. al. Akshay Kapoor,
Published: April 2021

Artificial Intelligence (AI) and Sensor Technologies making a point-of-care delivery possible which was considered impossible. The human body shows early indicators of disease manifestation before actual clinical symptoms appear. These indicators can be picked up by analyzing the optical face image, which can be used for rapid and cost-effective screening of life-threatening health conditions. This article focuses on how health status can be tracked using optical image analytics. Early identification of disease plays a vital role in therapeutics of a patient. In accordance with review of secondary data available in literature, this article proposed a model to rapidly screen the health conditions at point-of-care. The patterns in the optical image have the potential to act as digital disease markers.
Construction of appropriate model for Enrolment Projection of India
Authors: Pajankar Vishal D.
Published: April 2021

There are different models used for enrolment projection in the education system. Of them ARIMA, double exponential, logistic curve method, reconstructive cohort, and regression model, method are commonly used. Every model has its suitability under certain conditions and with prior assumptions. In India, no attempt was made to estimate enrolment except in 1996. The logistic curve method was adopted to estimate enrolment between 1996 – 2001. In the present situation, an attempt has been made to estimate school enrolment for the next years. The present paper discusses fitting the best model for estimating enrolment for the next few years.
Smart Analyzer: Assisting College Management through Machine Learning and Data Analysis
Authors: Et. al. Seema Kedar,
Published: April 2021

This work explores various opportunities to improvise regular tasks done by college faculty viz. Exam Result Analysis, Daily Student Attendance Analysis and Lecture Schedule Storage. Result Analysis becomes a tedious task when handled through traditional pen-paper methods and spreadsheets. This can be simplified by using Classification and Regression techniques. Through Regression, module-wise clarity of subjects can be foretold for students. Classification and Clustering algorithms can help to segregate students in various groups so that additional efforts can be taken for slow learners. It can also be used for classifying modules of a specific subject based on their complexities and course outcomes. The usage of register files for daily student attendance can be improved in a digital approach through Android and Django Framework. Through this approach, attendance can be tracked regularly and lecture (session) wise analysis can be done without the clutter of traditional pen-paper approach. Besides, for storing Lecture schedules and relevant timelines in the Realtime database furnishes additional benefits involving access to multiple users simultaneously. Technologies like Django Framework, Android OS, Realtime Database Systems and Machine Learning algorithms make these tasks simplified and less time-consuming. Data Analysis of Exam Results can be used for classifying student response to the teaching-learning process and can help in strategic outlining for future enhancements. Results of the proposed system consists of graphical representation of analysis done on input data and real time analysis of attendance data.
Stock Market Increase and Decrease using Twitter Sentiment Analysis and ARIMA Model
Authors: Kedar S. V.
Published: April 2021

With centuries and decades, people started evolving and slowly started entering into technology era. Social networks era came before everyone which connected people from far away countries. Such an example of social network are applications like Twitter, Facebook, Instagram, LinkedIn etc. Every application has its own significance. Such an application is Twitter where people tweet regarding their opinion about a topic, a person anything. The tweets regarding company its performance and people’s opinion about the stock is also tweeted. People like to invest in stocks using this data posted of social networking. This data keeps them updated about a company. In this paper, we will be using tweets related to stocks so that we can analyse sentiments of people regarding a particular stock. This sentiment analysis can provide a feedback about the company so that we will be able to understand an increase or decrease with respect to the people or company performance. In later stages, we will be comparing this analysis with ARIMA model which is time series forecasting model. ARIMA takes values of stocks and predicts its future prices based on its algorithm. Using both of these techniques a cumulative result for stock exchange will be obtained. The dataset is the fresh tweets taken from twitter and also the stock data will be imported directly for ARIMA.
Robotic Search and Rescue using Human Detection System
Authors: Et. al. Golande Avinash L,
Published: April 2021

In this Technological advancement period, advanced construction improvements lead the formation of skyscrapers and homes which expanded the dangers of losing life because of natural and manmade catastrophes. In this system, we are proposing a radio-controlled bot that can identify live human beings from which are in the inaccessible region.  Python libraries are used in Raspberry Pi microcontroller having Camera module to catch pictures of objects around it. This paper discusses about the mentioned system. The project takes live image samples and sends it to a network where this images can be accessed through a device. This images can be used for human detection. PIR sensor is used for the detection of human being trapped under debris. Whenever a human is detected the bot will send GPS co-ordinates to the device.
Visual Question Answering using Convolutional Neural Networks
Authors: Et. al. K. P. Moholkar,
Published: April 2021

The ability of a computer system to be able to understand surroundings and elements and to think like a human being to process the information has always been the major point of focus in the field of Computer Science. One of the ways to achieve this artificial intelligence is Visual Question Answering. Visual Question Answering (VQA) is a trained system which can answer the questions associated to a given image in Natural Language. VQA is a generalized system which can be used in any image-based scenario with adequate training on the relevant data. This is achieved with the help of Neural Networks, particularly Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN). In this study, we have compared different approaches of VQA, out of which we are exploring CNN based model. With the continued progress in the field of Computer Vision and Question answering system, Visual Question Answering is becoming the essential system which can handle multiple scenarios with their respective data.
Stock Prediction by using NLP and Deep Learning Approach
Authors: Et. al. Rushali Deshmukh,
Published: April 2021

People have a tendency to analyze existing strategies and so planned new strategies for inventory prediction. We have used Sentiment evaluation and Technical evaluation through NLP and Deep mastering approach. In order to exploit benefits of sentiment analysis on enterprise associated inventory, we have proposed a model that will use the sentiment analysis on twits associated with special sectors that are Information Technology sector, Banking sector, Pharmaceutical sector, Automobile sector, Infrastructure sector which are extracted from twitter. These twits are extracted from twitter for calculating polarity. The rating of sentiment analysis is calculated here by using Natural Language Processing’s method. According to sector we've taken five groups. Top four performer businesses of every sector. Using polarity score we got finalized pinnacle ten groups with great sentiment rating. We then downloaded the CSV facts of historical share charge of top ten organizations that we've selected. Then downloaded CSV records are used to build a CNN version to predict in addition stock movement of these pinnacle ten companies.
Fuzzy Logic Based Environment Control of Operation Theatre
Authors: Et. al. Sakshi Srivastav,
Published: April 2021

It is very critical and important to maintain the appropriate climatic conditions in the operation theatre. In paper, we present an approach to control total environmental conditions for the operation theatre. Generally for environmental control of operation theatre air conditioning system is installed. In operation theatre environmental parameters like humidity, temperature, oxygen and particles etc. have to be controlled precisely. All the environmental parameters are of nonlinear nature hence, difficult to control or model with the help of conventional control systems. Keeping in mind the complexity and nonlinearity of these parameters as fuzzy logic controller (FLC) for controlling all the environment of operation theatre has been designed. For this fuzzy logic control system temperature, micro particles, humidity & oxygen have been taken as input parameters and based on these parameters  speed of AC motor as well as the speed of exhaust motor are controlled. The control system is implemented with the help of different fuzzy rules and their membership functions derived from actual conditions. The performance of the system for control of operation theatre was studied and it has been observed that the result obtained with the fuzzy logic control system provides more effective and economical control. The fuzzy logic control system has been implemented using fuzzy Tech development tool.
Automatic Question Paper Generation using ML: A Review
Authors: Et. al. Kanchan Babaji Dhomse,
Published: April 2021

In any instructive field educational programs, the courses are characterized with learning goals. It is exceptionally challenging for the instructors to create Question Papers with changed questions. There's no standardizing strategy to guarantee quality of question paper. Consequently, there arises a have to be have a framework which can consequently produce it from we entered information inside few seconds. It’s basic to specify tests and exams, it plans understudies in their journey for information, so having a legitimate examination paper & organize is essential. Now the traditional strategy of producing address paper has been manual and it is exceptionally time and cost expending to diminish these things we developed this framework which is able make the programmed address paper and this it can be valuable to numerous instructive establishing.
Block Chain Technology in Supply Chain Management Using Key Generation
Authors: Et. al. Priti Lale,
Published: April 2021

An information system is very important in today's changing world, and therefore choosing the proper system is becoming a very important decision. With the time, the information systems have become more crucial, with multiple problems affecting the supply chain and the continuous writing of performance areas. The principle of chain management aims at chain values. The working of chain management states that chain management enhances the value of the chain by establishing operational units. Traditional manufacturing supply chains bear a lot from additional, costs, delays and information loss due to information middleware’s. Therefore, we propose a blockchain oriented supply chain architecture to reduce intrusion in traditional ones. Current approaches to private-key security include signature schemes based on bio-metrics, index-hidden private key design, and post-quantum block chain schemes. Nevertheless, recovering the lost private key is difficult in all approaches. Here we proposed an optimal key formation procedure using a fitness-based self-adaptive sea lion algorithm for secure information sharing in SCM using block chain.
Face Recognition from Video using Threshold based Clustering
Authors: Et. al. R. P. Dahake,
Published: April 2021

Video processing has gained significant attention due to the rapid growth in video feed collected from a variety of domains. Face recognition and summary generation is gaining attention in the branch of video data processing. The recognition includes face identification from video frames and face authentication. The face authentication is nothing but labelling the faces. Face recognition strategies used in image processing techniques cannot be directly applied to video processing due to bulk data. The video processing techniques face multiple problems such as pose variation, expression variation, illumination variation, camera angles, etc. A lot of research work is done for face authentication in terms of accuracy and efficiency improvement. The second important aspect is the video summarization. Very few works have been done on the video summarization due to its complexity, computational overhead, and lack of appropriate training data. In some of the existing work analysing celebrity video for finding association in name node or face node of video dataset using graphical representation need script or dynamic caption details As well as there can be multiple faces of same person per frame so using K- Means clustering further for recognition purpose needs cluster count initially   considering total person in the video. The proposed system works on video face recognition and summary generation. The system automatically identifies the front and profile faces of users. The similar faces are grouped together using threshold based a fixed-width clustering which is one of the novel approach in face recognition process best of our knowledge and only top k faces are used for authentication. This improves system efficiency. After face authentication, the occurrence count of each user is extracted and a visual co-occurrence graph is generated as a video summarization. The system is tested on the video dataset of multi persons occurring in different videos. Total 20 videos are consider for training and testing containing multiple person in one frame. To evaluate the accuracy of recognition. 80% of faces are correctly identified and authenticated from the video.
Neutrosophic β-Baire Spaces
Authors: Et. al. R.Vijayalakshmi,
Published: April 2021

in this paper the concept of neutrosophic β-Baire spaces are introduced and characterization of neutrosophic β -Baire spaces are studied. Examples are given to illustrate the concepts introduced in this paper.
Radio Mean Labeling Of Paths And Its Total Graph
Authors: Et. al. Meera Saraswathi,
Published: April 2021

A graph labeling problem is an assignment of labels to the vertices or edges (or both) of a graph G satisfying some mathematical condition. Radio Mean Labeling, a vertex-labeling of graphs with non-negative integers has a significant application in the study of problems related to radio channel assignment. The maximum label used in a radio mean labeling is called its span, and the lowest possible span of a radio mean labeling is called the radio mean number of a graph. In this paper, we obtain the radio mean number of paths and total graph of paths.
Neutrosophic e-Continuous Maps and Neutrosophic e-Irresolute Maps
Authors: Et. al. A. Vadivel
Published: April 2021

Aim of this present paper is to introduce and investigate new kind of neutrosophic continuous function called neutrosophic econtinuous maps in neutrosophic topological spaces and also relate with their near continuous maps. Also, a new irresolute map called neutrosophic e-irresolute maps in neutrosophic topological spaces is introduced. Further, discussed about some properties and characterization of neutrosophic e-irresolute maps in neutrosophic topological spaces.
Novel Approach of Existence of Solutions to the Exponential Equation (3m2 + 3) x + (7m2 +1) y = z2
Authors: Et. al. R.Vanajaq,
Published: April 2021

In this manuscript the exponential equation (3m2 + 3) x + (7m2 +1) y = z2 where m Î Z in three variables for the occurrence of solutions belonging to the set  of all integers or the concerned equation has no solution for various alternatives of m is investigated.
Blockchain-based Framework for Online Entrance Examination and Score Card Verification System
Authors: Et. al. Thilagavathi M,
Published: April 2021

Entrance examinations are a means through which universities select prospective students for admission. Most of the entrance exams are conducted using pen-paper in an offline mode where the number of students appearing is also very high. The current entrance examination system with centralized servers to prone to single point of failure and faces threats with respect to leaks in question papers, copying by students during the exam, impersonation, manipulation of the answers, forging the score cards, difficulty in verifying the authenticity and reliability of score cards by the university, etc. To overcome these issues and to conduct entrance exams online in a secure manner and to make the process of verifying the score card easier, a framework based on private blockchain is proposed in this paper.
Simulation of AlGaN MSM detector for investigating the effect varying absorber layer thickness
Authors: Et. al. Harpreet Kaur,
Published: April 2021

For detecting feeble Ultra-Violet (UV) signals it is essential that front-illuminated photodetector (PD) should havethick photo-absorbing layer with thin transparent metal electrodes and antireflective coating (ARC) so as to getmore photocurrent and low dark current.Since detector geometry influences its performance, so it is very important to optimize layer thickness parameters. In proposed work fixed area Al0.5Ga0.5N/AlN/ Sapphire based Metal-Semiconductor-Metal (MSM)PDbased has been analyzed for optimum value of active layer thickness and inter-electrode thickness.In addition to take benefit of large Schottky barrierGold material has beenutilized for electrodes. It has been illustrated in past research studies that with the increase in thickness of AlGaN layer, more incident energy can be absorbed for large EHPs generation which lead to increased responsivity.However, few research papers have related the effect of variations inthickness of active layerwith electron velocity which has significant effect on dark current density, recombination rateand additionally on efficiency.So for further development and widespread implementation of AlGaN/GaN based detectors there is need to study the effect of variation in photo-absorber layer thickness on closely related performance parameters so as to select its optimum value.Current Voltage (IV)-characteristics,recombination rate, current density plots and spectral response have been investigated using Atlas-Silvaco simulation tool.In addition for electrode thickness variation,transmission and absorptionplots are alsoinvestigated. For the proposed MSM structure, it has been observed that dark current density tends to increase

 

beyond the optimum value of thickness of AlGaN layerwith specific absorption coefficient. Good transmission of light with high spectral response can be obtained with optimum value of electrode thickness.These observations can be suitable for improving the detectivity in support of various UV detection applications requiring good sensitivity and high signal to noise ratio.
Additive Manufacturing: Advances in Trends and Technology
Authors: Agrawal Manoj Kumar
Published: April 2021

The latest process involved in the design, development and delivery of products to the end users has been implemented utilizing additive manufacturing (AM) or three-dimensional (3D) printing. This technology provides a great deal of freedom in the production of complicated parts, highly personalized goods and effective waste reduction. The new technological and Industrial revolution, utilizes the incorporation of intelligent fabrication and CAD processes. Via its various advantages, such as time and material savings, rapid prototyping, has enhanced productivity as well as distributed manufacturing processes, where AM actively participates and plays significant role in the industrial advancements. This paper is intended to conduct an analytical review of the latest developments and technological aspects in the AM innovation. This paper also explores the viability of the additive manufacturing mechanism as well as the advantages of the product in global, social and ecological fields. At last, the paper finishes with an outline of AM's potential in technologies, implementations and products developments, which will generate new concepts for AM discovery in the coming years..
Optimize Cryptography Algorithm for Efficient Data Security on Cloud Computing
Authors: Et. al. Dr.M.Buvana,
Published: April 2021

Services in the cloud environment are distributed between all servers and users. Cloud providers have problems with file protection as security is a major problem when processing and transferring information, as the original data type can be viewed, misused and lost. In the cloud computing world, cloud protection is a major concern. A variety of research projects are planned to safeguard the cloud climate. Cryptography is used to address the security problem and to achieve the CIA (confidentiality, honesty and disponibility). The most effective technique for ensuring high data transfer and storage protection is cryptography. There are certain drawbacks in traditional symmetric and asymmetrics. We will introduce a new technique of hybrid data protection and confidentiality to solve this issue. We use the ECC and Blowfish to build a hybrid algorithm in this article. The hybrid scheme output is compared to the current hybrid technique and demonstrates the high safety and confidentiality of the patient data in the proposed method. The hybrid encryption is used to remove both symmetrical and asymmetrical drawbacks.
Reducing Network Energy Consumption using Multidimensional Optimization of LEACH Protocol
Authors: Et. al. Dr.M.Buvana,
Published: April 2021

The optimized LEACH-focused protocol is proposed to make equal network energy usage and outspread the life cycle. In the first place, the threshold function of the cluster head is adjusted and the technique of division of the network area is configured to change reasonably the size of the clusters, taking account of residual energy and node distance. A sleep mechanism is introduced for intra-cluster transmission to balance the power consumption of nodes. And a new Barycenter Node has been introduced to help the head of the cluster fulfill the transmission task and thus prolong the lifespan. We derived a new formula, considering the angle, energy and distance, in multiple-hop communication between clusters to determine the fitting factor of the next hop. The results of simulations display that the remaining total energy of the optimized LEACH is decreased by 32.6% and the network life cycle respectively increases by around 54%.
Breast Cancer Detection Using Deep Belief Network by Applying Feature Extraction on Various Classifiers
Authors: Et. al. Prasath Alias Surendhar S,
Published: April 2021

Among various types of cancer, breast cancer is considered as second largest hazardous diseases that cause death. Initially, small lump like structure grow from breast cells which are considered as malignant lumps. To find the available of malignancy in breast area, several checkups such as self-test and periodic has to be done to reduce the death rate due to breast cancer. But, the classification of breast cancer by medical physicians using available techniques is not sufficient, so it is important to improve the classification technique using neural network. The four important phases namely preprocessing, segmentation, feature extraction, and classification can be done in constructed Deep Belief Network (DBN) whereas preprocessing makes to remove the noise and artifacts of mammogram image and then the glands are enhanced. The preprocessed output is given to fuzzy c-means segmentation process with the help of masking. Again the feature extractors such as Scale Invariant Feature Transform (SIFT) and Speeded up Robust Transform (SURF) made to apply on two types of classifiers such as gradient boosting tree classifier and adaboost classifier. The examination is done interms of parameters such as accuracy, precision, recall and F1 score.
CFD Analysis of Monolithic Heat Exchanger by Using Various Ceramic Materials
Authors: Et. al. S.Elangovan,
Published: April 2021

The main objective of this paper is to increase the heat exchange rate in the monolithic heat exchanger by changing the air passage shape and materials; here we used circular, hexagonal, oval shape for air passage and Al2O3, SiC CrCO3 ceramic materials for our research work. The heat flow rate is analyzed in CFD fluent software and model in done in CATIA software.
FEA Analysis for Scissor Lifting Table
Authors: Et. al. V.Giridharan,
Published: April 2021

The main goal of the project is weight analysis of scissor lifting table in the ware house, the scissor lifting table is a common device for all kind of peoples, we go to do the structural analysis of the scissor lifting table with the various human weights scissor lifting table modelled in Solid works software and structural analysis of human weights 50kg, 75kg, 100kg and 125kg done in ANSYS workbench software Scissor-type systems are frequently used as