bluuebunny/crossref_metadata_2025 huggingface dataset:
Unusual Canine Distemper Virus Infection in Captive Raccoons (Procyon lotor)
Authors: Stancu Adrian Constantin , Voia Octavian Sorin , Boldura Oana Maria , Pasca Sorin Aurelian , Luca Iasmina , Hulea Anca Sofiana , Ivan Oana Roxana , Dragoescu Alina Andreea , Lungu Bianca Cornelia , Hutu Ioan
Published: July 2023

Canine morbillivirus, also known as canine distemper virus (CDV), is the causative agent of canine distemper (CD), which is a serious contagious disease of canines, large felids, and, occasionally, raccoons. This study included seven raccoons from the Timisoara Zoological Garden, Romania. CDV was detected using RT-qPCR on blood samples, but several other exams were also performed—clinical, bacteriological, immunohistochemistry (IHC) and histopathology, toxicological screening, and necropsy—which confirmed CDV infection. Severe digestive disorders (diarrhea and frequent hematemesis) were observed. The necropsy findings included pseudo membranous gastroenteritis, congestion, and pulmonary edema in two raccoons. Immunohistochemistry showed immunolabeled CDV antigenantibodies on the viral nucleocapsid. Histopathology revealed lymphocyte depletion in mesenteric lymphnodes and intranuclear and intracytoplasmic inclusions in the enterocytes of the small intestine. Based on the RT-qPCR assay, laboratory tests, and the lesions observed, it was established that the raccoons were infected with CDV, which was the cause of death in two cases. The results from the necropsy, histology, and immunohistochemistry in the raccoons are comparable with reported CDV lesions in dogs. In conclusion, several exams may be performed to establish the etiology of possible interspecific viral infection, but only very specific exams can identify aCDV infection. Laboratory analyses must be completed by RT-qPCR assay or IHC to establish infection with uncommon viruses in raccoons with high accuracy.
Characteristics and Connectivity Analysis of Hidden Karst in Jurong Pumped Storage Power Station Area, China
Authors: Chen Liqiang , Dong Xiaosong , Miao Kehan , Yang Wenjie , Huang Yong
Published: July 2023

Based on the hidden karst exposed in Jurong Pumped Storage Power Station, combined with the field exploration data, the temporal and spatial development characteristics of hidden karst in the power station area are analyzed using the methods of specific solubility and specific corrosion, water chemical composition analysis, borehole television imaging, tracer test, and water pressure test. The results show that the karst development in the study area can be divided into three periods: pre-Cretaceous, Pleistocene, and modern karst. Karst development is controlled by soluble rock, non-soluble rock, and their combination, and the development direction is basically consistent with the fault strike. Karst caves are mainly distributed below the elevation of 100 m, with different shapes and scales and randomness. Non-soluble rocks and impure carbonate rocks are widely distributed in the study area, and surface karst is not developed. The underground karst caves are filled with red clay, and the rate of groundwater circulation is slow. The existence of geological bodies such as rock veins causes the groundwater levels to have obvious double-layer characteristics, which results in weak connectivity between karst caves. Although the karst in the power station area has a certain hydraulic connection with the surface water outside the area, the hydraulic connection of karst in the power station area is generally weak. The research results provide a scientific basis for the anti-seepage measures of underground powerhouses.
PROPERTIES OF THE MODIFIED SILICA COMPONENT – A PROMISING RAW MATERIAL IN THE PRODUCTION OF AERATED CONCRETE
Authors: Baranov A. , Shanin A. , Akulova M.
Published: July 2023

The scientific article relates to the building materials industry, namely, to the production of autoclaved cellular concrete. The purpose of the study was to reveal the potential possibilities of aerated concrete manufacturing technology. The following are considered as basic processing stages: preparation of the silica component, carried out by an energy-intensive and metal-intensive method - grinding in a ball mill; cutting of the raw mass with the formation of a crust - recyclable waste, the use of which only in the raw mixture does not allow obtaining the maximum technical and economic effect. It is shown that a fundamentally new method of using reverse sludge when grinding quartz sand makes it possible to manufacture a modified silica component. An assessment of its properties was given, which made it possible to reveal the mechanism: increase in sedimentation and aggregative stability; pH shift towards basicity; the presence of an amorphous surface on the particles; increasing the degree of dispersion and the acquisition of the active component in CaO. Changes in the chemical composition of the modified silica component compared to the base component were revealed. Morphological analysis showed the formation of components of the polymineral composition and primary neoplasms of the silicate system. The advantage of obtaining and using a modified silica component is not only in increasing the efficiency of the grinding section, saving binders, improving the parameters of the production process, the prospect of increasing the operational physical and mechanical characteristics of the finished product, but also in the absence of the need for significant changes in technological conversions of existing lines for the production of aerated concrete.
Forestry Professionals and Extension Educators vs. Climate Change: Implications for Cooperative Extension Programming
Authors: Jones Christopher , Lenart Melanie
Published: July 2023

Extension educators seeking to integrate climate science into programming must respect different perceptions on climate change. We surveyed forestland managers and owners, researchers, and Extension educators nationally to compare perceptions about climate change adaptation and mitigation management in forests (n=576). Despite differences in perception that climate change is anthropogenic, we found the professional groups were often statistically similar in supporting or rejecting specific actions and receptive to learning more about a variety of forest adaptation and mitigation practices. Our findings support a role for Extension in addressing climate change and indicate areas of common ground that can minimize contention.
Agricultural Producer Perceptions of Climate Change and Climate Education Needs for the Central Great Plains
Authors: Hibbs Amber , Kahl Daniel , PytlikZillig Lisa , Champion Ben , Monem Tarik , Steffensmeier Timothy , Rice Charles , Hubbard Kenneth
Published: July 2023

The Central Great Plains Climate Education Partnership conducted focus groups throughout Kansas to gain a better understanding of farmer perceptions and attitudes towards climate change education. Results indicate concern about climatic changes, even if producers are unsure that "human caused climate change" is occurring. Participants indicated they would like access to information through Web-based programs that allow them to manipulate variables relevant to their area and situation. Participants prefer locally relevant information and identified Extension agents as trusted educators. The study provided an expanded understanding of agricultural producer perceptions that will be valuable to individuals or organizations providing climate education.
Knowledge, Attitudes, and Commitment Concerning Evidence-Based Prevention Programs: Differences Between Family and Consumer Sciences and 4-H Youth Development Educators
Authors: Perkins Daniel , Chilenski Sarah , Olson Jonathan , Mincemoyer Claudia , Spoth Richard
Published: July 2023

We describe the results of a study designed to assess knowledge, perceptions, and attitudes towards evidence-based and other prevention programs among county Extension educators. We examined differences across educators from Family and Consumer Sciences (FCS) and 4-H Youth Development. Analyses based on a multi-state sample of educators revealed significant differences such that, compared to their 4-H counterparts, FCS educators were more knowledgeable of evidence-based programs and had more favorable perceptions and attitudes towards evidence-based and other pre-packaged prevention programs. These findings suggest that Extension administrators should work to encourage the use of evidence-based and other prevention programs, particularly within 4-H.
Endogenous Intoxication and Formation of Micronuclei in Cells in Pelvic Adhesion in Women
Authors: Керменбаева А.Ж. , Шоонаева Н.Дж. , Молдоканова М.Т.
Published: July 2023

В работе представлены данные оценки эндогенной интоксикации и формирования микроядер в клетках у женщин репродуктивного возраста при развитии спаечного процесса в малом тазу. Показано, что развитие эндогенной интоксикации обусловлено деградацией белков, накоплением в плазме крови среднемолекулярных пептидов и активацией фосфолипазы, а также увеличением количества клеток с микроядрами в буккальном эпителии, отражающим стадию спаечного процесса и генетическую предрасположенность части женщин к образованию спаек при воспалении и оперативных вмешательствах на органах малого таза.

The paper presents data on the assessment of endogenous intoxication and the formation of micronuclei in cells in women of reproductive age with the development of pelvic adhesions. It has been shown that the development of endogenous intoxication is due to the degradation of proteins and the accumulation of medium-molecular peptides in the blood plasma and the activation of phospholipase, as well as an increase in the number of cells with micronuclei in the buccal epithelium, reflecting the stage of the adhesive process and the genetic predisposition of some women to the formation of adhesions during inflammation and surgical interventions in the pelvic organs.
Energy curve and histogram thresholding implementation and evaluation with Aquila Cross-entropy optimization algorithm
Authors: ZARATE-NAVARRO Omar , ROMO-GONZALEZ Ana Eugenia , VILLALOBOS-ALONZO María de los Ángeles , CABRERA-VILLASEÑOR Héctor Ulises
Published: July 2023

This work proposes the implementation of minimum cross-entropy thresholding based on the aquila optimizer (MCE-AO) for the segmentation of base images and support to visually differentiate the different tissues present in the region. As an alternative to segmentation, the energy curve of the images was used, the energy curve has interesting properties, since it considers the spatial contextual information of each image and not only the intensity of the pixel as the histogram does, and in contrast to the histogram, the energy curve seems to be smoother by preserving the valleys and peaks. A comparison was made between the results calculated by the Aquila optimizer algorithm histograms of each image and the energy curve calculated for each image, showing considerable improvements in mean fitness. The quality of the segmented images was evaluated with the PSNR, SSIM and FSIM metrics, with the histogram and the energy curve, and a comparison of each of the results was made, showing improvement in the quality of the images segmented with the energy curve.
The Potential of ChatGPT to Enhance Physics Education in Vietnamese High Schools
Authors: Bruneau Philippe , Wang Jin , Cao Linh , Trương Hana
Published: July 2023

This paper explores the potential of ChatGPT, a natural language model developed by OpenAI, to enhance physics education in Vietnamese high schools. ChatGPT utilizes AI and deep learning technology, employing transformer architectures to process information and generate appropriate outputs. Drawing on the abilities of ChatGPT in Vietnamese physics, we examine the role of ChatGPT in the context of Vietnamese education and its specific application to physics learning and teaching. Additionally, we discuss the integration of student-centered pedagogies and information and communication technologies (ICT) in the Vietnamese physics education landscape.
Sur les contours de la liberté de correspondance des détenus : quand la rétention de courriers et la substitution de motifs ne font pas bon ménage
Authors: Le Moing Rosalie
Published: July 2023

L’existence d’une instruction du Parquet ne constitue pas un motif légal permettant de retenir les correspondances d’un détenu. L’administration est toutefois habilitée à demander au juge administratif une substitution de motifs, afin d’invoquer les deux motifs légaux de restrictions de la liberté de correspondance des détenus. Une telle entreprise est toutefois infructueuse lorsque la rétention des courriers est systématique et a priori, même si elle ne concerne que les courriers adressés à un individu identifié. La décision de l’administration pénitentiaire est dès lors annulée, faute de disposer d’un motif légal.
Le titre exécutoire : une voie amiable de recouvrement pour l’ONIAM face à un assureur défail-lant
Authors: Benard Georgina Vincent
Published: July 2023

Dans le cas d’un assureur défaillant, l’ONIAM peut se substituer à lui. Pour le remboursement des sommes versées, l’organisme public a le choix entre deux voies de droits dans l’exercice de la subrogation : la voie classique de la saisine du juge administratif ou la voie amiable du titre exécutoire. Cet acte juridique constatant une créance, émis par l’ONIAM, dans le cadre de l’article L. 1142-15 du code de la santé publique, est une décision administrative répondant aux règles de la procédure administrative non contentieuse. En revanche, la pénalité civile affligée à l’assureur pour non proposition d’une offre est de la compétence exclusive du juge administratif.
Classification of Mammograms using Attention Learning for Localization of Malignancy
Authors:   Computer Science Engineering, REVA University, Bangalore, India., Nagaraj Manaswini , Prabhakar Vignesh ,   Computer Science Engineering, SRM Institute of Science and Technology, Chennai, India., Thota Sailaja ,   Computer Science Engineering, REVA University, Bangalore, India.
Published: July 2023

Mammography is a specialized medical imaging that uses a low-dose x-ray system to examine the breasts. A mammogram is a mammography exam report that helps in the detection and diagnosis of breast diseases in women at an early stage. This project proposes to classify mammography breast scans into their respective classes and uses attention learning to localize the specific pixels of malignancy using a heat map overlay. The attention learning model is a standard encoder-decoder circuit wherein convolutional neural networks perform the encoding and recurrent neural networks perform the decoding. Convolutional neural networks enable feature extraction from the mammography scans which is thereafter fed into a recurrent neural network that focuses on the region of malignancy based on the weights assigned to the extracted features over a series of iterations during which the weights are continuously adjusted owing to the feedback received from the previous iteration or epoch. Mammography images are equalized, enhanced and augmented before extracting the features and assigning weights to them as a part of the data preprocessing procedures. This procedure would essentially help in tumor localization in case of breast cancers.
BMTC e-pass Application
Authors:   REVA University, India., B Guna Shekar , C Darshan ,   REVA University, India., V Ganesh Horamata B ,   REVA University, India., Mulimani Basavaraddi ,   REVA University, India., R Sarvamangala D ,   REVA University, India.
Published: July 2023

Bengaluru Metropolitan Transport Corporation (BMTC) is a prominent public transport service provider in Bengaluru. It makes commuting favourable and cheap compared to other modes of transport within the city. The organization enhances its services by analyzing passenger demands and providing them the necessary services. BMTC working model is coagulating with information technology in terms of ITS (Intelligent Transport System- Global Positioning System [GPS] enabled buses, electronic ticketing machine [ETM]). In spite of these advancements, it charges its service fares through paper tickets and passes which need to be purchased by paying cash. In the Digital era, technological solutions pave the way for digitizing mechanisms for traditional methods or problems and synchronizing information in real-time. These paper pass which proves to be beneficiary for passengers are being misused by means of transferring, reusing the day pass when there is lack of inspection. We have designed a solution to overcome misuse and also to encourage digital transaction for a cashless economy. The solution is mobile application electronic pass (e-pass).
Effect of Kernel Learning in Unsupervised Learning for Clustering High Dimensional Databases
Authors:   Department of Mathematics, Pondicherry University, Puduchery, India., Kashyap Esha , Kannan S.R. ,   Department of Mathematics, Pondicherry University, Puduchery, India., Last Mark ,   Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Negev, Israel.
Published: July 2023

This paper reviews the effectiveness of kernel learning in unsupervised data analysis using clustering. Cluster analysis is an explorative data analysis tool that assists in discovering hidden patterns or natural grouping and has many effective applications in various disciplines. The unison of kernel learning with the objective of unsupervised clustering algorithms facilitates in recognizing non linear structures in high dimensional data containing outliers with heavy noise. The recent kernel clustering methods considered in this paper are the kernelized versions of K-Means, Fuzzy C-Means, Possibilistic C-Means and Intuitionistic Fuzzy C-Means. Computational complexities in kernel based clustering algorithms are quiet prominent and our objective is to understand the performance gains while using kernels in clustering. Experimental studies of this paper substantiate that kernel based clustering algorithms yields significant improvements over their traditional counterparts.
News Rank: Ranking News Topics based on Social Media Factors
Authors:   REVA University, India., Kulkarni Malathi , Hulipalled Vishwanath. R. ,   REVA University, India.
Published: July 2023

All media sources, particularly the news media have educated the everyday news. These days, internet based media like twitter gives us an immense amount of information that is created by client, which potentially contains news related information. These sources to be helpful we should remove undesirable information and concentrate just the information which is like the news media. Indeed, even though the unwanted information can still exist, so which is vital to give need to its usage. For this prioritization, information must be positioned utilizing three components. First Media Focus(MF) of the Topic which principally centers around both internet based life and news media, Next User Attention(UA) which depends on clients’ interests and User Interaction(UI), which is on how client responds to that specific topic. This is an unsupervised framework News Rank--- which find the news topics which is applicable in both news media and internet based life and after that ranking the news topics utilizing degree of three elements.
Traffic Management using Convolution Neural Network
Authors:   Student, School of computing and Information Technology, REVA University, Bangalore, India., Dhingra Gaurav , S Supreeth ,   Asst. Professor, School of computing and Information Technology, REVA University, Bangalore, India., R Neha K ,   Student, School of computing and Information Technology, REVA University, Bangalore, India., V Amruthashree R ,   Student, School of computing and Information Technology, REVA University, Bangalore, India., D Eshitha ,   Student, School of computing and Information Technology, REVA University, Bangalore, India.
Published: July 2023

Traffic is one of the major problems in most of the metropolitan cities. Classifying the traffic conditions are important for determining traffic control strategies and management. Traffic congestions have negative impact on society, as a lot of time is wasted in it and controlling the congestions is necessary. By classification we can get to know which lane has traffic, from which we can further check the reasons for traffic and to take appropriate decisions to improve the performance. Video on traffic data is suitable source for traffic analysis. In this paper, video surveillance data is used for classification of road traffic using Convolution Neural Network. Convolution Neural Network requires minimal preprocessing when compared to other classification algorithms and is known for its accuracy. The video is classified based on rating of the traffic of its content. The Convolution Neural Network is first trained and then it is evaluated and updated using validation set. Once the model is completely trained it is tested with the testing set. This trained model is capable of processing the live streaming video and classifies each of the frames and gives the rating of the traffic for each lane, which can be helpful for traffic management.
Intrusion Detection System using Deep Neural Network and Regularization of Hyper Parameters with Adam Optimizer
Authors:   Dy Director, DRC, National Intelligence Grid, MHA, Bengaluru, Sekhar R. , Thangavel K. ,   Department of Computer Science, Periyar University, Salem, Tamil Nadu.
Published: July 2023

Intrusion Detection Systems (IDSs) study is unavoidable in the field of network security due to the present target oriented attacks for taking secret data of an organization. Classifying and detecting attacks are highly technical and tedious. In the existing models, the accuracy of intrusion detection in network traffic is different for different algorithms. This paper proposed a better intrusion detection system using Deep Neural Network with regularization of the hyper parameters. Adam optimization is proposed to optimize the weights in the neural network. The proposed system consists of six phases namely data collection, data framing, splitting of data for training and testing, pre-processing/encoding, regularization with Adam Optimizer, training and testing. It produces the better accuracy in detection process than the existing Deep Neural Network model. The bench mark data set NSL_KDD is collected and processed in the suggested system.
Comparative Study of Multiple Machine Learning Algorithms for Students’ Performance Data for Job Placement in University
Authors:   School of Computing and Information Technology, REVA University, Bangalore, India., B Athreya Shetty , Pasha Akram ,   School of Computing and Information Technology, REVA University, Bangalore, India., S Amith Singh ,   School of Computing and Information Technology, REVA University, Bangalore, India., N I Shreyas ,   School of Computing and Information Technology, REVA University, Bangalore, India., Hande Adithya R ,   School of Computing and Information Technology, REVA University, Bangalore, India.
Published: July 2023

In the era of data evolution, many organizations have taken the lead in storing the data in huge data repositories. Analysis of data comes with several challenges since the time the data is captures till the insights are inferred from the data. Accentuating the accuracy of data analysis is of paramount importance as many critical decisions are totally dependent on the outcomes of the analysis. Machine learning has been found as the most effective and most preferred tool in the literature for in-memory data analytics. Universities mostly collect the statistical data related to the students that is only either used quantitatively or sparsely analyzed to gain the insights that could be useful for the authorities to enhance the percentage of placements in campus drives held through early analysis of such data accurately. The work proposed in this paper formulates the problem of predicting the likelihood of a student getting placed in a company as a binary classification problem. Then it makes an effort to train and perform the empirical study of following multiple machine learning algorithms with the placement data; Logistic Regression, Naïve Bayes, Support Vector Machine, K-Nearest Neighbor and Decision Tree. The machine learning classification models are built to predict the probabilities of a student getting placed in a company based on the student’s academic scores, achievements, work experience (internship), and many other relevant features. Such an analysis helps the university authorities to dynamically create plans to enhance the unlikely students to be placed in a company participating in the campus recruitment held in the university. To improve these models and to avoid the models from overfitting to the training data, strategies like K-Fold cross-validation is applied for various values of k. The machine learning models selected are also compared for its efficiency by employing the supervised and unsupervised feature extraction techniques such as PCA and LDA. The Decision Tree model with K as 10 for cross-validation and PCA has outperformed all the other models producing the accuracy of 72.83% with satisfactory support and recall during experimentation. The application focuses on the targeted group of students, to eventually improve the probability of students getting placed during campus recruitment drives held in the university.
A Smart Bot as an Interactive Medical Assistant with Voice-based System using Natural Language Processing
Authors:   CSE Department, SRM Institute of Science and Technology, Chennai, India., Tiwari Aashita , Paul Ahitagnee ,   CSE Department, SRM Institute of Science and Technology, Chennai, India., Suganya P. ,   CSE Department, SRM Institute of Science and Technology, Chennai, India
Published: July 2023

In this fast-moving world, people are ignorant about their health issues and avoid routine check-ups. It is very difficult for users to spend longer time on-line and explore health information. To solve the problem, voice-based application is provided to the user where user can interact with system and get inference of diseases and their remedies by giving the symptoms as input.For processing the given input, the data is normalized by using noun phrase extraction and medical term identifier. For getting more precise result, the system generates relevant questions to the user and accordingly provide remedy for problem. Question is generated by mapping the user input array with question generation matrix. The project is based on a digital medical aid through a smart bot using machine learning and optical character recognition techniques. The user can just talk to the bot and get to know what the possible causes and effects of the particular symptoms are, determine the illness and take appropriate actions. Basically, the purpose of this bot is to act as a friendly healthcare assistant that helps in all the work that people need to take care of their health.
Efficient Face Recognition System for Identifying Lost People
Authors:   School of Computing and Inforrnation Technology, REVA University, Bangalore, India., Balar Bharath Darshan , Kavya D S ,   School of Computing and Inforrnation Technology, REVA University, Bangalore, India, M Chandana ,   School of Computing and Inforrnation Technology, REVA University, Bangalore, India.., E Anush ,   School of Computing and Inforrnation Technology, REVA University, Bangalore, India., Hulipalled Dr. Vishwanath R ,   School of Computing and Inforrnation Technology, REVA University, Bangalore, India.
Published: July 2023

In the world, a countless number of people are missing every day which includes kids, teens, mentally challenged, old-aged people with Alzheimer's, etc. Most of them remain untraced. This paper proposes a system that would help the police and the public by accelerating the process of searching using face recognition. When a person goes missing, the people related to that person or the police can upload the picture of the person which will get stored in the database. When the public encounter a suspicious person, they can capture and upload the picture of that person into our portal. The face recognition model in our system will try to find a match in the database with the help of face encodings. It is performed by comparing the face encodings of the uploaded image to the face encodings of the images in the database. If a match is found, it will be notified to the police and the people related to that person along with the location of where the person is found. The face recognition model that we have used maintains an accuracy of 99.38% on the Labelled Faces in the Wild Benchmark which comprises of 13,000 images [1].
Insights of Mathematics for Big Data
Authors:   REVA University, Bengaluru, India., Kumar D.N.Punith , Pasha Akram ,   REVA University, Bengaluru, India.
Published: July 2023

Computer Science can be considered as one of the extensions made to the pure mathematical sciences that exhibit the design and development of many mathematical models to solve various engineering problems. Data storage and data processing are the two major operations that are primarily focused by any computational model while solving a problem. Mathematical modelling has been helped in producing the various computational models across several problems that are found in the field of computer science. Among many problems that are found in the area of computer science, data science and big data have recently geared up to solve many business oriented problems that are purely based on data analytics to enhance the profit by taking critical business decisions. Data Scientists and mathematicians are found to have a skeptical understanding or too little collaboration either in knowing the mathematical concepts behind big data technologies, or too little knowledge of applications of mathematical concepts in applications of big data, respectively. Therefore, in this paper, an effort is made to bring out the major mathematical concepts that have contributed in fueling the solutions for big data problems. The authors hypothesize that the work proposed in this paper would benefit any data scientist or a mathematician to clearly understand the bridge between the math and its application in big data analytics. The authors identify the mathematical concepts and their roles played while solving various tasks that are encountered in the domains of big data. Further, such an endeavor is expected to open up many opportunities for both mathematicians and big data professionals to work collaboratively, while encouraging and contributing in enhancing interdisciplinary research across many domains of engineering.
Machine Learning Methods For Heart Disease Prediction
Authors:   Department of Computer Science and Information Technology, REVA University, Bangalore, India., O Rashmi.G. , M Ashwinkumar.U. ,   Department of Computer Science and Information Technology, REVA University, Bangalore, India.
Published: July 2023

Machine learning is utilized to empower a program to analyze information, understand correlations and make utilization of bits of knowledge to take care of issues or potentially enhance information and for prediction. The American Heart Association Statistics 2016 Report shows that coronary illness is the main source of death for people, responsible for 1 in every 4 deaths. Machine learning algorithms play a very important role in medical area. We use machine learning to understand, predict, and prevent cardiovascular disease using numeric data. The end goal is to produce an approved machine learning application in healthcare. In an effort to refine the search for a useful and accurate method with the dataset, the results of several algorithms will be compared. The front-runners will be analyzed and used to develop a unique, higher-accuracy method. Machine learning methods inclusive of Logistic Regression, Naïve Bayes, Decision tree(CART). We use ensemble learning for better accuracy which includes algorithms like Random Forest, XGBoost, Extra trees classifier. Also, our work adds to the present literature by giving a far reaching review of machine learning algorithms on sickness prediction tasks. Our goal is to perform predictive analysis with these machine learning algorithms on heart diseases using ensembles like bagging, boosting, stacking. Machine Learning algorithms used and conclude which techniques are effective and efficient. A huge medical datasets are accessible in different data repositories which used in the real world application.
Optimizing Random Forest to Detect Disease in Apple Leaf
Authors:   School of C&IT, REVA University, India., S Kamalalochana. , Guptha Dr. Nirmala ,   School of C&IT, REVA University, India.
Published: July 2023

Green Revolution was introduced in agriculture to meet the food scarcity. Despite the increase of agricultural production, farmers are challenged by infestations. Infestation reduced the crop yield. Traditional method involved manual inspection of plants to identify diseases. With advancement in technology, the infested plant leaves can be captured into images and subjected to processing by computing element. The computing system are being trained to process the image using Machine Learning algorithms to classify the images. Processing the image and detecting with improved accuracy is essential. Random Forest classifier is used to detect the disease in Apple Leaf. The accuracy of prediction by Random Forest can be influenced by configuring its parameters. This Paper talks about the various options that can be applied to optimize Random Forest classifier for improving the accuracy of detecting Apple Leaf disease.
Adaptive Resource Allocation using various Smart Antenna Techniques to maintain better System Performance
Authors:   Research Scholar, Department of ECE, Visvesvaraya Technological University, Belagavi, India., G Shivapanchakshari T , Aravinda H S ,   Department of ECE, JSSATE, Bangalore, India.
Published: July 2023

Smart antennas are capable of offering major contribution in improving system performance of orthogonal frequency division multiplexing (OFDM) systems. The OFDM is an air-link technology required for future wireless communication applications to address the technological challenges in fulfilling users demand. The adaptive resource allocation techniques in OFDM systems using smart antennas is an optimistic approach showing light towards developing various methods to improve spectral efficiency with required quality of service (QoS). However, fully adaptive techniques increase the challenges in designing the physical layer with minimum complexity. Now, the challenge is to investigate the possibility of achieving satisfactory system performance without increasing complexity at MAC layer of next generation OFDM systems. In this paper, methodology of designing a hybrid smart antenna system is proposed to achieve required QoS with minimum system complexity.
Real Time Solution for Prosopagnosia
Authors:   Solution Architect Products, SCS Accenture Bengaluru, Manu Abhilash , S Dr.Aravind H ,   Professor, ECE Department,JSSATE, Bengaluru
Published: July 2023

The paper aims at building a prototype for solving the problem of a rare neurological disorder ‘Prosopagnosia’. It is also called face blindness / facial agnosia. This is a behavioral disorder of face perception that impairs the ability to detect familiar faces, which include one's own face, while other forms of visual processing and intellectual functioning remain intact. The Extensive research has indicated 1 out of 50 people may have this neurological disorder. In order to help the significant number of affected people overcome this difficulty, we have built a prototype which uses a camera to capture the image and an appropriate face recognition code using the Histogram of Oriented Gradients (HOG) approach is implemented for face detection. After detection, SVM classifier is used for classification and the name of the identified person will be displayed. Simultaneously, the conversation is being recorded and text mining is performed to extract the keywords of the conversation. The result is displayed on a suitable interface. The hardware module Raspberry Pi is used as a processor for processing the incoming image and audio data.
AN OBSERVATIONAL STUDY FOR PREVALENCE OF MALNUTRITION AMONG UNDER FIVE YEAR CHILDREN AND ITS ASSOCIATED FACTORS AT URBAN HEALTH TRAINING CENTER, SMS MEDICAL COLLEGE, JAIPUR
Authors: Singh Rathore Sunil , Rathore Monika , Dhamania Madhvi , Meena Sadhna
Published: July 2023

Introduction: Malnutrition is the most widespread condition affecting the health of children [1]. As recent data shows higher malnutrition in children of urban area and little work has been done in this regard hence this study aims to estimate the magnitude and explore the socio-economic determinants of malnutrition among under -ve children of eld practicing area of UHTC. This would help in better understanding of the issue and future planning. Methods: This Community based, cross-sectional, observational study was done at Sushilpura area from July 2021 to October 2022. Total 360 children under ve year of age were assessed for malnutrition and factors associated. Results: There were 46.7% male and 53.3% female. Majorities (83.9%) were Hindus and were nuclear families (68.3%). Only 6.4 percent families were higher socioeconomic status while only 7.2% households were lowest socioeconomic status. Around one fourth subjects were from ST/SC categories. The prevalence of under nutrition was 56.4%. Overall stunting was about 35.3% with 4.2% of severe stunting; moreover about 21.1% had wasting with 5.6% of severe wasting. Sex, religion, caste, family size, socio economic status, livestock in house, ventilation of house, overcrowding were signicant factors associated with malnutrition. Conclusion: under-nutrition is high among children of Sushilpura, an urban dwelling of Jaipur city. One third was stunted and every fth child was wasted too. Low socioeconomic status, less educated parents, poor sanitation, female sex, birth order, lack of exclusive breast feeding, nuclear family, higher number of episodes of acute diarrhea in last one year were important associated factors. Presence of domestic livestock and absence of overcrowding were positive factor for preventing malnutrition.
MANAGEMENT OF CALCULUS ANURIA-OUR EXPERIENCE IN A TERITIARY CARE CENTRE
Authors: Reddy Narendra , S B Siraj , Prakasa Rao B.
Published: July 2023

Introduction : Urinary lithiasis have been a major urological problem. The incidence of calculus renal failure is very high in India. Calculus anuria is a urological emergency and needs early emergency intervention (double J stenting, PCN and dialysis) to manage calculus anuria after which denite treatment of stone can be performed. Methods : The Prospective study is carried out in Government General Hospital, Guntur from January 2021 to June 2022. 30 patients with calculus anuria of all ages and either sex were included in the study. USG KUB, X-ray KUB and CT KUB were taken for size and site of stone in the urinary tract. Urinary diversion procedures like double J stenting or percutaneous nephrostomy were done on emergency basis to relieve the obstruction. After stabilisation of the patient, denite treatment was planned. Results: Among 30 patients who presented with anuria, dialysis was done in 21 patients. Bilateral DJ stenting was done in 21 cases. Unilateral DJ stenting was done in 3 patients with single kidney or single functioning kidney. Unilateral DJ stenting and contralateral PCN for pyonephrosis done in 6 patients. After relief of obstruction and stabilizing patient, denitive treatment of calculi likeURSL, pushback PCNL, PCNL, ureterolithotomy and pyelolithotomy done. Conclusion: Calculus anuria is a urological emergency .Dialysis is required in most of cases. Early intervention with DJ stenting/ PCN is initial treatment of choice. After stabilization, majority of the patients can be managed with endo-urological procedures like ureteroscopicpneumatic/ laser lithotripsy, PCNL.
“EFFICACY OF LOW DOSE CIS-ATRACURIUM AND LOW DOSE ATRACURIUM IN FACILITATING I-GEL INSERTION: A RANDOMIZED COMPARATIVE STUDY”
Authors: Shravya Sarvepalli , Koppad Devaraj , J. Mahanthesha Sharma M.
Published: July 2023

Background And Objective: Cis-atracurium and Atracurium are Non depolarizing muscle relaxants used along with induction agents to overcome the excessive airway reactivity of I-gel insertion and causing relaxation of jaw muscles making insertion of this device easier. Objective of the present study is to evaluate the efcacy of low dose cis-atracurium (26.5 mcg/kg) and low dose atracurium (0.15 mg/kg) in providing adequate muscle relaxation and other satisfactory conditions for I-gel insertion. Methods: 80 ASA grade I/II patients, aged 18-60 years, of either sex scheduled to undergo elective surgeries under general anaesthesia with controlled ventilation will be randomly divided into Group A: atracurium (0.15mg/kg) or Group C: cis-atracurium(26.5mcg/kg). Standard monitors (pulse oximeter, ECG leads, NIBP) will be connected. Baseline vital parameters will be recorded, After administration of respective relaxant and insertion of I-gel following conditions are assessed: Jaw relaxation, ease of insertion, coughing and gagging, patients movements, number of failed attempts. HR, SPO2, MAP monitoring at 1,5,10 minutes to asses post-insertion hemodynamic status. Postoperative complications were assessed (sore throat and bleeding). Results: The groups were similar with respect to age, sex, number of sample, HR, MAP,SPO2, sore throat . Percentage of full jaw relaxation is signicantly better in group A (95%) with p <0.01. Ease of insertion was found to be signicantly easier in Group A (92%) than in group C (57.5%) with p<0.03. In Group A , I-gel was inserted in rst attempt in 92.5% patients were as only 75% in Group C indicating signicant difference p<0.02. In Group A patient movements were almost nil (97.5%) with signicant difference of p(<0.001) when compared to Group C. Group A had lesser coughing and gagging percentage (100%) compared with Group C (72.5%) showing signicant difference among both groups with p<0.001. Conclusion: From the results of our study, we concluded that insertion conditions of I-gel were better with low-dose of atracurium (0.15 mg/kg) than with low dose cis atracurium (26.5 mcg/kg) in terms of ease of insertion, number of attempts, patient movement, coughing and gaging.
ASSOCIATION BETWEEN PLATELET INDICES AND ACUTE CORONARY SYNDROMES IN A
TERTIARY CARE CENTRE – A COMPARATIVE STUDY
Authors: Kumar Saini Rajesh , Mosalpuri Ashok , Gupta Punit , Kumar Sharma Nitesh
Published: July 2023

Introduction: Platelets plays important role in progression of atherosclerosis. Alpha granules and dense granules of
platelet contains many chemokines, cytokines and growth factors. Release of these factors along with interaction with
endothelial cells and leukocytes promotes inflammation and atherosclerosis. There is scope to make better use of the
platelet parameters generated, as patients with larger platelets can easily be identified during routine hematological
analysis and could possibly benefit from timely treatment. The study was undertaken to account the efficacy of platelet
parameters in Acute Coronary Syndromes. The current study was a case control study carried Material And Methods:
out in the Department of Medicine, SRGH Hospital, which is affiliated with Jhalawar Medical College, from February 2022
to December 2022. The purpose of this study was to comparison between the platelet indices in patients with ACS and those with non cardiac chest pain. Approval from Institutional Ethical Committee of the Hospital was taken before the start of the study. A total 200 participants were included among them 100 were cases diagnosed with ACS and 100 controls with those with non cardiac chest pain were included. Data were analyzed in SPSS v- 24. Independent t-test and Chi-square test were applied. Pearson correlation coefficient was calculated. p value <0.05 was considered statistically significant. In the present study, no statistically significant difference in platelets count and pl Observation: ateletcrit (%) were found between both groups. However, a statistically significant high PDW, MPV and P-LCR were found among the cases compare to the controls. In the current study, accuracy of PDW, MPV, P-LCR and plateletcrit to detect ACS was found to be 95.7%, 92.2%, 94.4% and 46.7% respectively. The current study's findings appear to CONCLUSIONS: confirm and substantiate that higher platelet indices such as mean platelet volume (MPV), platelet distribution width (PDW), and platelet large cell ratio (P-LCR) contribute to the prothrombotic state in Acute coronary syndrome (ACS), and that larger platelets may also play a specific role in ACS.
WOMEN EMPOWERMENT IN INDIA
Authors: Kumar Sinha Ranjeet , Ambastha Surabhi
Published: July 2023

The aim of the present study is to determine the factors which affect women empowerment and the issues being faced by
the women. This study reveals the status of women empowerment in India and explained the factors affecting their
current situation.It has been found during study that females in India are not authorized to do some acts and have lower
status as equated to men.Several efforts have been taken by government to endow women at national and global level by
introducing and employing numerous schemes and initiatives. This study tries to hypothesize prospects of women in
numerous areas and initiatives commenced by the Union of India.
REFLECTION OF HINDU AND BUDDHIST PHILOSOPHY IN T.S ELIOT'S 'WASTE LAND.'
Authors: Chahal Paramveer
Published: July 2023

The Indian spiritual thoughts are inundated with enduring values and timeless appeal, which has carved a niche in Eliot's mind. Its universal appeal has the ability to allure all categories of people starting from the illiterate to the elite, from the peasant to the perfectionist, from the writer to the religious preacher with a profound sense of high moral character and ethical living. The soil of Eliot's poetic fervor has been properly prepared with the manure and fertilizer of the Indian religious thought which provides a balanced nutrition to the seedling of The Waste Land. In order to examine how far oriental wisdom influences Eliot's poetic vision and sensibility to give it a universal undertone running parallel with the wisdom of Europe, this study attempts to trace the reflections of Hindu and Buddhist philosophy in Eliot's famous poem The Waste Land. The everlasting ideals and eternal attractiveness of Indian spirituality have left a lasting impression on Eliot. From the ignorant to the elite, from the peasant to the perfectionist, from the writer to the religious preacher with a great sense of high moral character and ethical life, its global appeal has the power to enchant all sorts of people. Eliot's poetic fervour has been dutifully prepared with the manure and fertiliser of Indian religious thinking, which gives the seedling of The Waste Land a nutritious diet. Eliot's relationships with mentors like Irving Babbitt, George Santayana, Charles Rockwell Lanman, and James Haughton, as well as the Oriental Study Centre at Harvard, have been carefully analysed to determine the effect of Indian ideas on Eliot's thinking. Each section of the poem has been examined in order to comprehend how meticulously Eliot depicts the tragic impasse of modern humanity due to spiritual draught and how at each stage Indian thoughts, specifically Buddhism and Hinduism with its Vedic and Upanishadic lore stand as yardstick to restore spiritualism by centralising the moral vision of European Waste Landers, which centres on the Christian intent that formed Eliot's Indian sensibility