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Deep Learning Based Automated Diagnosis of Skin Diseases Using Dermoscopy

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Computers, Materials & Continua 2022年第5期71卷 3145-3160页

作者： Vatsala Anand Sheifali Gupta Deepika Koundal Shubham Mahajan Amit kant Pandit Atef Zaguia Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjabIndia Department of Systemics School of Computer ScienceUniversity of Petroleum&Energy StudiesDehradunUttrakhandIndia School of Electronics&Communication Shri Mata Vaishno Devi UniversityKatra182320India Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Biomedical image analysis has been exploited considerably by recent technology involvements,carrying about a pattern shift towards‘automation’and‘error free diagnosis’classification methods with markedly improved accurate diagnosis productivity and cost *** paper proposes an automated deep learning model to diagnose skin disease at an early stage by using Dermoscopy *** proposed model has four convolutional layers,two maxpool layers,one fully connected layer and three dense *** the convolutional layers are using the kernel size of 3∗3 whereas the maxpool layer is using the kernel size of 2∗*** dermoscopy images are taken from the HAM10000 *** proposed model is compared with the three different models of ResNet that are ResNet18,ResNet50 and *** models are simulated with 32 batch size and Adadelta *** proposed model has obtained the best accuracy value of 0.96 whereas the ResNet101 model has obtained 0.90,the ResNet50 has obtained 0.89 and the ResNet18 model has obtained value as ***,features obtained from the proposed model are more capable for improving the classification performance of multiple skin disease *** model can be used for early diagnosis of skin disease and can also act as a second opinion tool for dermatologists.

关键词： Dermoscopy images CNN deep learning classification optimizer ResNet diagnosis skin disease

MRMR Based Feature Vector Design for Efficient Citrus Disease Detection

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Computers, Materials & Continua 2022年第9期72卷 4771-4787页

作者： Bobbinpreet Sultan Aljahdali Tripti Sharma Bhawna Goyal Ayush Dogra Shubham Mahajan Amit kant Pandit Department of Electronics&Communication Engineering Chandigarh UniversityMohali140413India Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Ronin Institute Mont ClairNJ07043USA School of Electronics&Communication Engineering Shri Mata Vaishno Devi UniversityKatra182320India

In recent times,the images and videos have emerged as one of the most important information source depicting the real time *** images nowadays serve as input for many applications and replacing the manual methods due to their capabilities of 3D scene representation in 2D *** capabilities of digital images along with utilization of machine learning methodologies are showing promising accuracies in many applications of prediction and pattern *** of the application fields pertains to detection of diseases occurring in the plants,which are destroying the widespread *** the disease detection process was done by a domain expert using manual examination and laboratory *** is a tedious and time consuming process and does not suffice the accuracy *** creates a room for the research in developing automation based methods where the images captured through sensors and cameras will be used for detection of disease and control its *** digital images captured from the field’s forms the dataset which trains the machine learning models to predict the nature of the *** accuracy of these models is greatly affected by the amount of noise and ailments present in the input images,appropriate segmentation methodology,feature vector development and the choice of machine learning *** ensure the high rated performance of the designed system the research is moving in a direction to fine tune each and every stage separately considering their dependencies on subsequent *** the most optimum solution can be obtained by considering the image processing methodologies for improving the quality of image and then applying statistical methods for feature extraction and *** training vector thus developed is capable of presenting the relationship between the feature values and the target *** this article,a highly accurate system model for detecting the diseases occurring in citrus fruits

关键词： Citrus diseases classification feature vector design plant disease detection redundancy reduction

Decline of Japanese encephalitis in Eastern Uttar Pradesh,India,2009-2019

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Asian Pacific Journal of Tropical Medicine 2022年第5期15卷 230-231页

作者： Neha Srivastava Hirawati Deval Nikhat Khan Rajni kant Aparup Das ICMR-Regional Medical Research Centre BRD Medical College CampusGorakhpurUttar Pradesh273013India ICMR-National Institute of Research in Tribal Health Nagpur RoadGarhaJabalpurMadhya Pradesh482003India

Japanese encephalitis(JE),one of the major viral encephalitides,is caused by Flavivirus circulating in rural areas of Asia and Western Pacific regions[1]and is a neglected tropical viral disease due to its endemicity[2].The culicine mosquitoes,mainly of Culex tritaeniorhynchus and Culex vishnui group,are the vectors of JE virus(JEV)[1].Being a neurologic infection,JE manifests with a set of serious symptoms leading to death in many cases and/or change in behaviour of the patients leading to permanent disability[3].

关键词： encephalitis Eastern neglected

A review on emerging materials with focus on BiI_(3) for room-temperature semiconductor radiation detectors

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Radiation Detection Technology and Methods 2023年第4期7卷 465-483页

作者： Ritu Chaudhari Chhaya Ravi kant Alka Garg Surender Kumar Sharma Department of Applied Sciences and Humanities Indira Gandhi Delhi Technical University for WomenKashmere GateDelhi110006India Gargi College University of DelhiSiri Fort RoadNew Delhi110049India Delhi Skill and Entrepreneurship University New DelhiIndia

Purpose Considerable advances in the fundamental knowledge and applications of radiation science have led to significant progress and development of room-temperature semiconductor radiation detectors(RTSD).The RTSDs technologies are continuously evolving with accelerated research and material engineering in the last *** scientific and technological advancements have led to development of high-performance radiation detectors with high signal-to-noise ratio(SNR),better sensitivity,faster response and higher-resolution with capability of desired room-temperature *** paper is a review on emerging semiconductor radiation detector materials with a deeper insight into the prospective role of Bismuth tri-iodide(BiI_(3))for room-temperature radiation *** An introduction of the state of art of most developed semiconductor materials,i.e.,cadmium telluride(CdTe),mercury iodide(HgI_(2)),lead iodide(PbI_(2)),etc.,and a critical examination of properties,shortcomings and challenges related to their synthesis have been ***-semiconductor composites with desirable properties and their integration into detector devices is also *** sections discuss the role of BiI_(3) as an emerging radiation detector material for room-temperature operation with an in-depth discussion on the role of defects in charge transportation and electrode ***,the current challenges along with the future prospects of these materials for radiation detection to promote continuous innovation and practical applications are also *** The comprehensive review on latest developments in room-temperature radiation detector materials is expected to help establish a technological roadmap for the synthesis,fabrication and commercialization of novel materials for development of efficient radiation detectors.

关键词： Radiation detector Defects Electrical properties Bismuth tri-iodide Semiconductor Toxicity

Deep Learning Based Automated Detection of Diseases from Apple Leaf Images

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Computers, Materials & Continua 2022年第4期71卷 1849-1866页

作者： Swati Singh Isha Gupta Sheifali Gupta Deepika Koundal Sultan Aljahdali Shubham Mahajan Amit kant Pandit Department of Electronics and Communication Engineering University Institute of TechnologyHimachal Pradesh UniversityShimla171005India Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjabIndia Department of Systemics School of Computer ScienceUniversity of Petroleum and Energy StudiesDehradunIndia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia School of Electronics&Communication Shri Mata Vaishno Devi UniversityKatra185320India

In Agriculture Sciences, detection of diseases is one of the mostchallenging tasks. The mis-interpretations of plant diseases often lead towrong pesticide selection, resulting in damage of crops. Hence, the automaticrecognition of the diseases at earlier stages is important as well as economicalfor better quality and quantity of fruits. Computer aided detection (CAD)has proven as a supportive tool for disease detection and classification, thusallowing the identification of diseases and reducing the rate of degradationof fruit quality. In this research work, a model based on convolutional neuralnetwork with 19 convolutional layers has been proposed for effective andaccurate classification of Marsonina Coronaria and Apple Scab diseases fromapple leaves. For this, a database of 50,000 images has been acquired bycollecting images of leaves from apple farms of Himachal Pradesh (H.P)and Uttarakhand (India). An augmentation technique has been performedon the dataset to increase the number of images for increasing the *** performance analysis of the proposed model has been compared with thenew two Convolutional Neural Network (CNN) models having 8 and 9 layersrespectively. The proposed model has also been compared with the standardmachine learning classifiers like support vector machine, k-Nearest Neighbour, Random Forest and Logistic Regression models. From experimentalresults, it has been observed that the proposed model has outperformed theother CNN based models and machine learning models with an accuracy of99.2%.

关键词： Deep learning convolutional neural network apple leaves apple scab support vector machine

Effect of local longitudinal shortening on the transport of luminal contents through small intestine

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Acta Mechanica Sinica 2019年第1期35卷 45-60,I0002页

作者： Ravi kant Avvari Sasi Institute of Technology and Engineering Tadepalligudem 534101India

A theoretical analysis of the rheological fluid flow due to peristalsis is studied. We have applied the classical lubrication theory to predict the near physiological behavior of the intestinal segment, mixing and transport. A parametric study involving the changes in local longitudinal shortening (LLS) magnitude, LLS spacing, fluid viscosity, wavelength of the wave, and occlusion of lumen caused by the wave provided insights into the dynamics of the peristalsis flow of a non-Newtonian fluid. LLS appear to have little significance in modulating the flow patterns that are caused by circular contraction alone. Results also indicate that there exists trade-off between the power requirement for peristalsis at a certain occlusion against the percentage LLS. LLS appear to be more advantageous to perform the peristalsis activity at higher occlusion than lower occlusion. Having mucosal folds in the inner lining of the intestine allows for one more advantage of slowing the transit due to increased friction factor and increase in time for absorption of the nutrients.

关键词： Circular contraction Local longitudinal shortening Lubrication theory

Preventive strategies to innovate Japanese encephalitis control in eastern Uttar Pradesh: Accelerating towards zero incidence

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Asian Pacific Journal of Tropical Medicine 2023年第4期16卷 145-147页

作者： Neha Srivastava Rohit Beniwal Brij Ranjan Misra Umaer Alam Hirawati Deval Rajni kant ICMR-Regional Medical Research Centre GorakhpurUttar PradeshIndia

Japanese Encephalitis(JE)is a zoonotic mosquito-borne viral disease that primarily affects young children under the age of 15[1].Annually,there are more than 50000 clinical cases and JE causes over 10000 fatalities globally[1].In Japan,South Korea,China and Thailand,where it is now under control or almost entirely eradicated,the disease was initially noted to have a high incidence[1].Later,it expanded to Nepal and India,becoming a serious public health issue in rural regions[1].JE is a flavivirus-based neglected tropical disease that is spread by culicine mosquitoes of the Culex(Cx.)tritaeniorhynchus and *** species[2].

关键词： entirely neglected expanded

Process-structure-property relationship for plasma-sprayed iron-based amorphous/crystalline composite coatings

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International Journal of Minerals,Metallurgy and Materials 2022年第1期29卷 144-152页

作者： Abhishek Pathak Biswajyoti Mukherjee Krishna kant Pandey Aminul Islam Pavan Bijalwan Monojit Dutta Atanu Banerjee Anup Kumar Keshri Research and Development Unit Tata SteelJamshedpur 831001India Plasma Spray Coating Laboratory Metallurgical and Materials EngineeringIndian Institute of Technology PatnaBihta 801106India

This study explores the fabrication of Fe-based amorphous/crystalline coating by air plasma spraying and its dependency on the coating parameters(plasma power,primary gas flow rate,powder feed rate,and stand-off distance).X-ray diffraction of the coatings deposited at optimized spray parameters showed the presence of amorphous/crystalline *** deposited at a lower plasma power and highest gas flow rate exhibited better density,hardness,and wear *** coatings demonstrated equally good resistance against the corrosive environment(3.5wt%NaCl solution).Mechanical,wear,and tribological studies indicated that a single process parameter optimization cannot provide good coating performance;instead,all process parameters have a unique role in defining better properties for the coating by con-trolling the in-flight particle temperature and velocity profile,followed by the cooling pattern of molten droplet before impingement on the substrate.

关键词： Fe-based alloys amorphous alloys plasma spray coating mechanical corrosion and wear

Effectiveness of lukewarm water compress on reduction of breast pain and breast engorgement among post-cesarean section mothers

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中西医结合护理杂志(英文) 2023年第3期5卷 167-172页

作者： Soni CHAUHAN Kumari NUTAN Monica AGRAWAL Surya kant TIWARI Nursing Tutor Yatharth Nursing College and Paramedical InstituteChandauliUttar PradeshIndia Institute of Nursing King George’s Medical UniversityLucknowUttar PradeshIndia Professor Cum Vice-Principal M.V.P.Samaj’s Institute of Nursing EducationNashikMaharashtraIndia Department of Obstetrics and Gynecology King George’s Medical UniversityLucknowUttar PradeshIndia

Objective:The study aimed to assess the effectiveness of lukewarm water compress on breast pain and breast engorgement among post-cesarean primiparous *** and Methods:This quasi-experimental posttest-only design was conducted with 60 post-cesarean section primiparous mothers between October 2018 and January 2019.A simple random sampling technique was used to allocate 30 participants to both experimental and control *** experimental group received lukewarm water compress using a sponge cloth for 20 min twice a day on the second,third,and fourth postnatal *** control group received routine hospital *** pain and engorgement were assessed using the Visual Analog Pain Scale and Breast Engorgement Assessment Scale on the third,fourth,and fifth postnatal ***:Significant differences were observed between the experimental and control groups on day 1 and day 3 in terms of breast pain and engorgement scores among post-cesarean section mothers(P0.05).Conclusion:Lukewarm water compress is effective in reducing breast pain and engorgement in post-cesarean primiparous *** research can include randomized controlled trials to evaluate the effectiveness of different therapies in treating breast pain and engorgement.

关键词： Effectiveness lukewarm water compress post-cesarean section postnatal posttest only primiparous