ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 7.97 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
IJCRT Journal front page | IJCRT Journal Back Page |
Paper Title: SOME COMMON FIXED POINT RESULTS IN CONE METRIC SPACE
Author Name(s): Preeti Mehta ,, Badrilal Bhati
Published Paper ID: - IJCRT2106006
Register Paper ID - 207683
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2106006 and DOI :
Author Country : Indian Author, India, 313001 , udaipur, 313001 , | Research Area: Mathematics All Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2106006 Published Paper PDF: download.php?file=IJCRT2106006 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2106006.pdf
Title: SOME COMMON FIXED POINT RESULTS IN CONE METRIC SPACE
DOI (Digital Object Identifier) :
Pubished in Volume: 9 | Issue: 6 | Year: June 2021
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Mathematics All
Author type: Indian Author
Pubished in Volume: 9
Issue: 6
Pages: a25-a31
Year: June 2021
Downloads: 1290
E-ISSN Number: 2320-2882
Licence: creative commons attribution 4.0
47H10, 54H25, 54C60, 46B40.
Paper Title: ANTIMICROBIAL POLYHERBAL HAND WASH FORMULATION
Author Name(s): SURWASE VIJAYA BALASO, SAVALE MANASI MAHALING, MURGUDE MANISHA .M, DR. MOHITE SHINIVAS . K, DR. MAGDUM CHANDRAKANT . S
Published Paper ID: - IJCRT2106005
Register Paper ID - 208044
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2106005 and DOI :
Author Country : Indian Author, India, 415404 , SANGLI, 415404 , | Research Area: Pharmacy All Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2106005 Published Paper PDF: download.php?file=IJCRT2106005 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2106005.pdf
Title: ANTIMICROBIAL POLYHERBAL HAND WASH FORMULATION
DOI (Digital Object Identifier) :
Pubished in Volume: 9 | Issue: 6 | Year: June 2021
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Pharmacy All
Author type: Indian Author
Pubished in Volume: 9
Issue: 6
Pages: a21-a24
Year: June 2021
Downloads: 1394
E-ISSN Number: 2320-2882
The aim of present work was to prepare formulations of poyherbal handwash from the metholonic extracts of leaves of Tridax procumbens, Azadirachta indica and lemon juice. Two formulations of hand wash were prepared and the formulations were evaluated for physical properties like appearance, pH and viscosity. The antimicrobial activity of prepared formulations of hand wash was checked against skin pathogens Bacilus subtilus, Staphylococcus aureus, Psuedomonas aeruginosa and Escherichia coli by agar diffusion method. The results revealed that prepared herbal hand wash formulations showed significant zone of inhibition compared with standard antibiotic drug (Amoxicillin). So these plant materials can be used in the preparation of herbal hand wash on commercially scale.
Licence: creative commons attribution 4.0
Ployherbal handwash, Antimicrobial activity, Tridax procumbens and Azadirachta indica.
Paper Title: PLANT DISEASE DETECTION USING DEEP LEARNING: A SURVEY
Author Name(s): Namitha Banu K, Mohamed Rafi
Published Paper ID: - IJCRT2106004
Register Paper ID - 207995
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2106004 and DOI :
Author Country : Indian Author, India, 577004 , Davanagere, 577004 , | Research Area: Science and Technology Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2106004 Published Paper PDF: download.php?file=IJCRT2106004 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2106004.pdf
Title: PLANT DISEASE DETECTION USING DEEP LEARNING: A SURVEY
DOI (Digital Object Identifier) :
Pubished in Volume: 9 | Issue: 6 | Year: June 2021
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Science and Technology
Author type: Indian Author
Pubished in Volume: 9
Issue: 6
Pages: a16-a20
Year: June 2021
Downloads: 1389
E-ISSN Number: 2320-2882
Rapid and accurate identification of plant diseases is essential for sustainable increases in agricultural productivity. Human experts have traditionally been relied upon to diagnose diseases, pests, nutritional shortages, and severe weather abnormalities in plants. This however is costly, time-consuming, and not practicable in some situations. The study of the use of pictorial methods for plant recognition has become a hot topic to address these challenges. We review the recent studies in the field of identifying pesticides and diseases utilizing imaging and machine learning in this paper. We expect this work to serve as a valuable resource for researchers who use image processing techniques to recognize crop pests and disease. In particular, we concentrate on the use of RGB images due to the low cost and high accessibility of RGB cameras. Deep learning instead of superficial classifications using manufactured characteristics has been at the forefront of recent efforts. The accuracy of the recognition on a specific dataset has been recorded by researchers; in some cases, the performance of these systems has deteriorated significantly when assessed on different datasets or under field conditions. However, it was promising to make progress to date. The experimental findings are present in ten CNN leaf disease recognition architectures, showing the accuracy, memory, precisely, specification, F1 score, training duration, and storage specifications. Recommendations are subsequently provided on the most appropriate architectures to be used in both traditional and mobile computing environments. We also explore some outstanding issues to be tackled to establish realistic systems for recognizing automatic plant diseases in field conditions.
Licence: creative commons attribution 4.0
Plant disease detection; Classification; Machine Learning, Convolutional Neural Network.
Paper Title: BIKER STORE AND BLOG SYSTEM
Author Name(s): Mohsin Malgundkar, Prince Patel, Arjun Patel
Published Paper ID: - IJCRT2106003
Register Paper ID - 207840
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2106003 and DOI :
Author Country : Indian Author, India, 400050 , Mumbai, 400050 , | Research Area: Science and Technology Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2106003 Published Paper PDF: download.php?file=IJCRT2106003 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2106003.pdf
Title: BIKER STORE AND BLOG SYSTEM
DOI (Digital Object Identifier) :
Pubished in Volume: 9 | Issue: 6 | Year: June 2021
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Science and Technology
Author type: Indian Author
Pubished in Volume: 9
Issue: 6
Pages: a10-a15
Year: June 2021
Downloads: 1365
E-ISSN Number: 2320-2882
Licence: creative commons attribution 4.0
Buying, Selling, Renting Bike Part, Online Order, Registration
Paper Title: HUMAN EMOTION DETECTION USING IMAGE PROCESSING
Author Name(s): Mansee Dhamal, Suyog Rakh, Sangram Kakade, Sudhir Chaudhari, Dr.Vilas gaikwad
Published Paper ID: - IJCRT2106002
Register Paper ID - 207828
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2106002 and DOI :
Author Country : N, India, - , -, - , | Research Area: Science and Technology Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2106002 Published Paper PDF: download.php?file=IJCRT2106002 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2106002.pdf
Title: HUMAN EMOTION DETECTION USING IMAGE PROCESSING
DOI (Digital Object Identifier) :
Pubished in Volume: 9 | Issue: 6 | Year: June 2021
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Science and Technology
Author type: N
Pubished in Volume: 9
Issue: 6
Pages: a6-a9
Year: June 2021
Downloads: 1389
E-ISSN Number: 2320-2882
In todays world of technology human cannot survive without be- ing techno-freak. Just to get workplace environment friendly we are going to introduce six emotions and positive and negative emotion recognition methods using facial image and the the development of app based on the method. In this project we will use the Deep Learning technology to generate models with emotion based facial expressions to recognized emotions. Inevitebly feelings play an important role not only in our relations with other people but also in the way we use Computers. Affective computing is a domain that focuses on user emotions while he inter- acts with computers and applications. As emotional state of person may influence concentration, task solving and decision making skills, effective computing vision is to make system stable to recognize and influence human emotions in order to enhance productivity and ef- fectiveness of working with computers. We will develop an automated system to recognize six emotions along with positive and negatives in graphs and percentages. Thus, we recognize six emotions such as Angry, Disgust, Fear, Happy, Sad, Surprise. Also classified the calculated emotion recognition scores into pos- itive, negative and neutral emotions. Then we will implement an app that provides the user with six emotions scored and positive and negative emotions
Licence: creative commons attribution 4.0
Image Processing, CNN, LPBH(Local Binary Pattern Histogram), AWS cloud, S3 Bucket, Haar Cascades, Feature Extractions, deep learning, Facial Images.
Paper Title: EVALUATION OF PHYTOCHEMICALS AND ANTIMICROBIAL PROPERTIES OF VEGETABLES
Author Name(s): Deepak Chauhan, Ritu Sharma, Runjhun Mathur, Swati Tyagi, Dr. Abhimanyu Kumar Jha
Published Paper ID: - IJCRT2106001
Register Paper ID - 207604
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2106001 and DOI :
Author Country : Indian Author, India, 201001 , Ghaziabad, 201001 , | Research Area: Humanities All Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2106001 Published Paper PDF: download.php?file=IJCRT2106001 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2106001.pdf
Title: EVALUATION OF PHYTOCHEMICALS AND ANTIMICROBIAL PROPERTIES OF VEGETABLES
DOI (Digital Object Identifier) :
Pubished in Volume: 9 | Issue: 6 | Year: June 2021
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Humanities All
Author type: Indian Author
Pubished in Volume: 9
Issue: 6
Pages: a1-a5
Year: June 2021
Downloads: 1341
E-ISSN Number: 2320-2882
Vegetables contain lots of beneficial phytochemicals and also have antioxidant and antimicrobial properties. Phytochemicals are chemical compounds which are produced by plants, generally help in resistance of fungi, bacteria and plant virus infection. Various phytochemicals found in vegetables are tannins, cardiac glycosides, terpenoids, saponins, phytosterols, alkaloids, flavanoids. Antimicrobial properties of vegetables have been found to be very effective against Escherichia coli, Streptococcus pyogenes, Klebsiella peumoniae, Pseudomonas aeroginosa, Bacillus subtilis which have been examined by disc- diffusion method. This review includes the study on Bottle gourd(Lagenaria siceraria), cucumber( Cucumis sativas), pumpkin( Cucurbita), ridged gourd( Luffa), karella ( Momordica charantia), tinda ( Praecitrullus fistulosus). Vegetables also have therapeutic properties like anti- diabetic, anti- ulcers, anti- inflammatory, anti- oxidant, anti- tumor properties.
Licence: creative commons attribution 4.0
Phytochemicals, antimicrobial activity, antioxidant, flavonoids, alkaloids