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: A RESEARCH ON: FORMULATION AND EVALUATION OF TOOTH POWDER USING HERBAL INGREDIENTS.
Author Name(s): Waghmare Jagdish Atmaram, Gaikwad Dipak Bhaskar, Sonwane Abhishek Ashok, Ghuge Aashwini Raosaheb
Published Paper ID: - IJCRT2406226
Register Paper ID - 263335
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2406226 and DOI :
Author Country : Indian Author, India, 414204 , Patoda, 414204 , | Research Area: Pharmacy All Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2406226 Published Paper PDF: download.php?file=IJCRT2406226 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2406226.pdf
Title: A RESEARCH ON: FORMULATION AND EVALUATION OF TOOTH POWDER USING HERBAL INGREDIENTS.
DOI (Digital Object Identifier) :
Pubished in Volume: 12 | Issue: 6 | Year: June 2024
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Pharmacy All
Author type: Indian Author
Pubished in Volume: 12
Issue: 6
Pages: c81-c99
Year: June 2024
Downloads: 17
E-ISSN Number: 2320-2882
Dentifrices are the product which is used to maintain the oral hygiene such as Freshness of mouth and to avoid tooth decay. The oral hygiene can be maintained throughout the day by using various dentifrices prepared by herbal and synthetic ingredients. This work was carried out to prepare Tooth powder which can be used as a tool for proper oral hygiene and to overcome the side effect of the conventional Tooth powder prepared by synthetic ingredients. Dentifrices are important in our daily life to maintain good oral health and hygiene. Gingivitis, plaque, Periodontal diseases are the crucial problems related to tooth. These major issues are due to poor oral hygiene and negligence in good caring of tooth. This negligence encourages plaque formation on teeth, by causing inflammation of gum tissues which ultimately leads to gingivitis and tooth loss. Most of the synthetic preparations of dentifrices, such as toothpowder and toothpaste cause side effects such as gum irritation, burning sensation and inflammation due to usage of chemicals. In this study an attempt is made to dispense an alternative to the users by formulating herbal toothpowder using Clove, Ginger, Amla, Neem Bark, Accacia Bark, Mentha Leaf, Rock Salts, Cinnamon Powder, Guava Tree Leaf and Alum. In the present work, the herbal toothpowder was formulated and standardized by analysing necessary evaluation parameters such as organoleptic, physical and phytochemical evaluation of herbal toothpowder.
Licence: creative commons attribution 4.0
Herbal, Accacia Bark, Cinnamon, Synthetic, Oral hygiene
Paper Title: Varieties of English Spoken in the World
Author Name(s): Dr. Pavan Kumar
Published Paper ID: - IJCRT2406225
Register Paper ID - 263378
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2406225 and DOI :
Author Country : Indian Author, India, 505115 , OLDPALVANCHA, 505115 , | Research Area: Languages Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2406225 Published Paper PDF: download.php?file=IJCRT2406225 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2406225.pdf
Title: VARIETIES OF ENGLISH SPOKEN IN THE WORLD
DOI (Digital Object Identifier) :
Pubished in Volume: 12 | Issue: 6 | Year: June 2024
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Languages
Author type: Indian Author
Pubished in Volume: 12
Issue: 6
Pages: c73-c80
Year: June 2024
Downloads: 14
E-ISSN Number: 2320-2882
A few centuries ago, the English language consisted of a collection of dialects spoken mainly by monolinguals within the shores of a small island. However, English serves many purposes throughout the world now-a-days. At the beginning there was only one variety of English existed that is the native variety. There are so many varieties of English worldwide. Even within the native land of English i.e. the British Isles, one can find so many variants of English. It is not an exaggeration to state that English is a language- the language on which the Sun does not set, whose users never sleep (Quirk, 1985:1).
Licence: creative commons attribution 4.0
Varieties, British Isle, Native, England, Received Pronunciation.
Paper Title: State-of-the-Art in Road Accident Analysis: A Review of Machine Learning-Based Approaches and Challenges
Author Name(s): Mohd Saifuddin, Mrs. Dipti Ranjan Tiwari
Published Paper ID: - IJCRT2406224
Register Paper ID - 263132
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2406224 and DOI :
Author Country : Indian Author, India, - , -, - , | Research Area: Science and Technology Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2406224 Published Paper PDF: download.php?file=IJCRT2406224 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2406224.pdf
Title: STATE-OF-THE-ART IN ROAD ACCIDENT ANALYSIS: A REVIEW OF MACHINE LEARNING-BASED APPROACHES AND CHALLENGES
DOI (Digital Object Identifier) :
Pubished in Volume: 12 | Issue: 6 | Year: June 2024
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Science and Technology
Author type: Indian Author
Pubished in Volume: 12
Issue: 6
Pages: c68-c72
Year: June 2024
Downloads: 17
E-ISSN Number: 2320-2882
Road accidents remain a significant public health concern worldwide, leading to loss of lives, injuries, and economic losses. To address this issue, researchers have increasingly turned to machine learning techniques for analyzing road accident data to understand contributing factors, predict accident occurrences, and propose preventive measures. This paper provides a comprehensive review of the state-of-the-art machine learning-based approaches for road accident analysis. We systematically categorize and summarize the various machine learning methods employed in accident detection, severity prediction, causality analysis, and risk assessment. Additionally, we discuss the challenges associated with these approaches, including data availability, feature selection, model interpretability, and scalability. By highlighting the recent advancements, limitations, and future directions in road accident analysis using machine learning, this review aims to provide insights for researchers, policymakers, and practitioners working in the field of road safety.
Licence: creative commons attribution 4.0
Road accidents, public health, severity prediction, road safety, machine learning.
Paper Title: Comparative Analysis Of Sleep Cycle In Males And Females
Author Name(s): Mohammad Muazzam Saeid, Khyati Jaiswal, Mahima Verma
Published Paper ID: - IJCRT2406223
Register Paper ID - 263388
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2406223 and DOI :
Author Country : Indian Author, India, 201310 , Greater Noida, 201310 , | Research Area: Health Science All Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2406223 Published Paper PDF: download.php?file=IJCRT2406223 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2406223.pdf
Title: COMPARATIVE ANALYSIS OF SLEEP CYCLE IN MALES AND FEMALES
DOI (Digital Object Identifier) :
Pubished in Volume: 12 | Issue: 6 | Year: June 2024
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Health Science All
Author type: Indian Author
Pubished in Volume: 12
Issue: 6
Pages: c64-c67
Year: June 2024
Downloads: 7
E-ISSN Number: 2320-2882
Background: Sleep is essential for health but gender differences might impact the sleep patterns. Extensive study has revealed physiological and behavioral differences in sleep cycles between men and women including duration, phases and rhythms. Community actions are critical for increasing awareness and teaching about gender-specific sleep requirements. Creating comfortable sleeping conditions and managing stress are also critical. Communities that promote sleep awareness can empower individuals to priorities their sleep health, hence enhancing overall quality of life. Objectives: To study the difference between the sleep cycles of males and females along with the factors affecting it. To make people aware about the importance and benefits of adequate sleep and measures to maintain regular sleep cycles. Methodology: 400 participants were taken for the data collection. Global Sleep Assessment Questionnaire (GSAQ) which contained 11 questions regarding sleep experiences of an individual was used. Patients were prescribed with various relaxation techniques and recommendations to improve their sleeping habits. For the very purpose data has been collected from January 2024 to April 2024. Results: The analysis of the GSAQ Score showed that sleep cycle of Males is more disturbed than that of Females. The average score of males was 7.3 while as in females it was 6.65. Conclusion: The study concluded that on gender differences in sleep patterns, with males experiencing more interrupted sleep cycles than females. This highlights the importance of targeted therapies to improve sleep quality, particularly among men. Community sleep awareness projects can empower people to priorities their sleep health, resulting in a higher quality of life overall.
Licence: creative commons attribution 4.0
Sleep Cycle, Global Sleep Assessment Questionnaire, Sleep Quality, Sleep Disorder, Health
Paper Title: Smart Blind Stick Using Machine Learning
Author Name(s): Niyati Hariharno, Anshika Shrivastava, Reshama Verma, Prof. Sourabh Yadav
Published Paper ID: - IJCRT2406222
Register Paper ID - 263259
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2406222 and DOI :
Author Country : Indian Author, India, 495001 , Bilaspur, 495001 , | Research Area: Science and Technology Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2406222 Published Paper PDF: download.php?file=IJCRT2406222 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2406222.pdf
Title: SMART BLIND STICK USING MACHINE LEARNING
DOI (Digital Object Identifier) :
Pubished in Volume: 12 | Issue: 6 | Year: June 2024
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Science and Technology
Author type: Indian Author
Pubished in Volume: 12
Issue: 6
Pages: c56-c63
Year: June 2024
Downloads: 10
E-ISSN Number: 2320-2882
Eye sight plays a major role in collecting most of the information from the real world and that information will be processed by brain. Many people around the world are blind or not able to see clearly or recognisation the objects properly. Visually impaired people suffer inconveniences in their daily and social life with respect to challenges during commuting. This condition leads to the loss of the valuable sense of vision. The need for assistive devices was and will be continuous. There is a wide range of navigation systems and tools existing for visually impaired individuals. The blind person truly requires an aid in identifying objects. Smart Blind Stick is an interactive device which mainly aims at helping the blind to navigate easily and in a safer manner. In a normal day to day situation a blind person waves the blind stick ahead of them in order to check for any objects or obstacles. The smart stick helps them in this by detecting if any obstacle is blocking the path being taken by the subject. The device detects the obstacle with the help of a camera attached to the front of the stick. On detection of the obstacle, it is identified and appropriate instructions are provided to the user. The instructions to the blind person are sent over earphones. Thus, the stick provides a safer and a better navigation experience for the visually challenged.
Licence: creative commons attribution 4.0
Object detection, Machine Learning, IoT, Raspberry pi, pi Camera, YOLO algorithm.
Paper Title: Niosomes In Skin Cancer
Author Name(s): Yogesh Hanumant Shendage, Shivani Bandu Rathod
Published Paper ID: - IJCRT2406221
Register Paper ID - 263166
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2406221 and DOI :
Author Country : Indian Author, India, 413520 , Almala, 413520 , | Research Area: Pharmacy All Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2406221 Published Paper PDF: download.php?file=IJCRT2406221 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2406221.pdf
Title: NIOSOMES IN SKIN CANCER
DOI (Digital Object Identifier) :
Pubished in Volume: 12 | Issue: 6 | Year: June 2024
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Pharmacy All
Author type: Indian Author
Pubished in Volume: 12
Issue: 6
Pages: c41-c55
Year: June 2024
Downloads: 22
E-ISSN Number: 2320-2882
The prevalence of skin diseases, particularly skin cancer, presents a global health challenge an increasing impact on the economy and workforce. Melanoma, arising from dysfunctional melanocytes, is the most aggressive form of skin cancer, in constrast non-melanoma skin cancers (NMSC) like squamous cell carcinoma (SCC) and basal cell carcinoma (BCC) account for the majority of cases. The incidence of NMSC has risen significantly, with men being at higher risk due to genetic, phenotypic, and environmental factors. Advances in polymeric micro/nano carrier-based therapies offer promising avenues for skin cancer management, including drug and gene delivery, and combination therapies. These innovative approaches hold the potential for overcoming current treatment limitations and advancing both research and clinical applications in the field. Nisosomes can be important nanomolecules For the cancer management and drug delivery. In this review, we are discussing the nisosomes as a nanocarrirer for drug delivery in skin cancer.
Licence: creative commons attribution 4.0
Skin cancer, niosomes, drug carrier, nanocarrier, cancer treatment
Paper Title: MANUFACTURING OF CYCLOIDAL GEAR BOX FOR SPEED REDUCTION
Author Name(s): SAHIL S. BEDAKE, ROHIT S. DHAKANE, SHASHANK S. GAWALI, JAGANNATH C. GHOLAP, PANKAJ L. FIRKE
Published Paper ID: - IJCRT2406220
Register Paper ID - 263387
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2406220 and DOI :
Author Country : Indian Author, India, 411033 , PUNE, 411033 , | Research Area: Science and Technology Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2406220 Published Paper PDF: download.php?file=IJCRT2406220 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2406220.pdf
Title: MANUFACTURING OF CYCLOIDAL GEAR BOX FOR SPEED REDUCTION
DOI (Digital Object Identifier) :
Pubished in Volume: 12 | Issue: 6 | Year: June 2024
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Science and Technology
Author type: Indian Author
Pubished in Volume: 12
Issue: 6
Pages: c28-c40
Year: June 2024
Downloads: 7
E-ISSN Number: 2320-2882
This project details the design, development, and evaluation of a prototype cycloidal gearbox. Cycloidal gear systems are known for their high torque transmission, compact size, and low noise levels. The main goal of this study is to create a functional prototype to demonstrate the feasibility and effectiveness of cycloidal gearboxes for various applications. The project starts with a comprehensive literature review to understand the principles, benefits, and challenges associated with cycloidal gearing. Utilizing this information, a thorough design process is conducted, including CAD modeling and finite element analysis (FEA) for optimization. Special focus is placed on the design of the cycloid disk and pins to ensure efficient power transmission and minimal wear. After the design phase, the prototype is manufactured using precision machining techniques. Rigorous testing is performed to evaluate its performance characteristics, including torque transmission efficiency, speed variability, and noise levels. Comparative analyses with conventional gear systems are conducted to highlight the unique advantages of the cycloidal design. The findings of this project contribute to the advancement of cycloidal gearbox technology, offering valuable insights into their practical implementation and performance capabilities. Additionally, the prototype serves as a foundation for further research and development in the field of mechanical power transmission systems
Licence: creative commons attribution 4.0
Cycloidal Gearbox, Speed Reduction, Cycloidal Gearing System, Gear Design, High Torque Transmission, Gearbox Manufacturing, CAD Modeling, Cycloid Disk, Precision Machining, Power Transmission Efficiency, Gearbox Optimization, Gearbox Testing, Noise Reduction, Comparative Analysis, Mechanical Power Transmission.
Paper Title: Predictive Sales Analytics for Variable Timeframes using Multiple Machine Learning Models
Author Name(s): Rushikesh Shinde, Rafe Shamsi, Pratham Nanaware, Savita Lohiya
Published Paper ID: - IJCRT2406219
Register Paper ID - 262860
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2406219 and DOI :
Author Country : Indian Author, India, 400706 , Navi Mumbai, 400706 , | Research Area: Science and Technology Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2406219 Published Paper PDF: download.php?file=IJCRT2406219 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2406219.pdf
Title: PREDICTIVE SALES ANALYTICS FOR VARIABLE TIMEFRAMES USING MULTIPLE MACHINE LEARNING MODELS
DOI (Digital Object Identifier) :
Pubished in Volume: 12 | Issue: 6 | Year: June 2024
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Science and Technology
Author type: Indian Author
Pubished in Volume: 12
Issue: 6
Pages: c20-c27
Year: June 2024
Downloads: 20
E-ISSN Number: 2320-2882
Predicting future sales accurately is crucial for businesses to optimize inventory management, plan marketing strategies, and enhance overall profitability. In this paper, we propose a comprehensive analysis of predictive sales analytics for variable timeframes utilizing machine learning models, specifically XGBoost, Linear Regression, Random Forest, and Long Short-Term Memory (LSTM) networks. Through empirical evaluation and comparative analysis, we demonstrate the efficacy of XGBoost in forecasting sales for different timeframes, namely daily, weekly, and monthly. Our findings highlight the superior performance of XGBoost in terms of accuracy and robustness, making it an ideal choice for businesses seeking reliable sales predictions across diverse temporal scales.
Licence: creative commons attribution 4.0
Predictive analytics, Sales forecasting, XGBoost, Random Forest, Linear Regression, LSTM, Variable timeframes, Streamlit.
Paper Title: Review of Image Processing Approaches for Accident Detection and Impact Evaluation in Intelligent Transportation Systems
Author Name(s): Sraddha Singh, Peeyush Kumar Pathak
Published Paper ID: - IJCRT2406218
Register Paper ID - 263412
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2406218 and DOI :
Author Country : Indian Author, India, - , -, - , | Research Area: Science and Technology Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2406218 Published Paper PDF: download.php?file=IJCRT2406218 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2406218.pdf
Title: REVIEW OF IMAGE PROCESSING APPROACHES FOR ACCIDENT DETECTION AND IMPACT EVALUATION IN INTELLIGENT TRANSPORTATION SYSTEMS
DOI (Digital Object Identifier) :
Pubished in Volume: 12 | Issue: 6 | Year: June 2024
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Science and Technology
Author type: Indian Author
Pubished in Volume: 12
Issue: 6
Pages: c15-c19
Year: June 2024
Downloads: 6
E-ISSN Number: 2320-2882
The rapid advancement of intelligent transportation systems (ITS) has necessitated the development of efficient and accurate methods for accident detection and impact evaluation. This review paper examines the latest image processing approaches utilized in the detection and analysis of traffic accidents. We explore a variety of techniques, including machine learning algorithms, deep learning models, and traditional computer vision methods, assessing their effectiveness in real-time accident detection, severity estimation, and post-accident analysis. The paper discusses the strengths and limitations of each approach, highlighting key innovations and their practical applications within ITS. Additionally, the review addresses the integration of image processing with other sensor technologies, such as LiDAR and radar, to enhance the reliability and accuracy of accident analysis. Current challenges, including data quality, computational demands, and implementation in diverse traffic environments, are also considered. Finally, we outline potential future research directions aimed at improving the robustness and scalability of image processing techniques for comprehensive accident impact evaluation. This review serves as a valuable resource for researchers and practitioners seeking to advance the field of traffic accident analysis through image processing innovations.
Licence: creative commons attribution 4.0
accident detection, impact evaluation, image processing, machine learning (ML).
Paper Title: Review of Deep Learning Models for COVID-19 Detection from Chest X-ray Images: Current Trends and Future Perspectives
Author Name(s): Bilal Mirza, Mrs. Dipti Ranjan Tiwari
Published Paper ID: - IJCRT2406217
Register Paper ID - 263130
Publisher Journal Name: IJPUBLICATION, IJCRT
DOI Member ID: 10.6084/m9.doi.one.IJCRT2406217 and DOI :
Author Country : Indian Author, India, - , -, - , | Research Area: Science and Technology Published Paper URL: http://ijcrt.org/viewfull.php?&p_id=IJCRT2406217 Published Paper PDF: download.php?file=IJCRT2406217 Published Paper PDF: http://www.ijcrt.org/papers/IJCRT2406217.pdf
Title: REVIEW OF DEEP LEARNING MODELS FOR COVID-19 DETECTION FROM CHEST X-RAY IMAGES: CURRENT TRENDS AND FUTURE PERSPECTIVES
DOI (Digital Object Identifier) :
Pubished in Volume: 12 | Issue: 6 | Year: June 2024
Publisher Name : IJCRT | www.ijcrt.org | ISSN : 2320-2882
Subject Area: Science and Technology
Author type: Indian Author
Pubished in Volume: 12
Issue: 6
Pages: c10-c14
Year: June 2024
Downloads: 8
E-ISSN Number: 2320-2882
The rapid spread of COVID-19 has prompted urgent research efforts to develop effective diagnostic tools for timely identification and management of the disease. Chest X-ray imaging has emerged as a valuable modality for detecting COVID-19 pneumonia, offering a non-invasive and widely available means of screening and diagnosis. Deep learning models, particularly convolutional neural networks (CNNs), have shown promising results in automated detection of COVID-19 from chest X-ray images. This review paper provides a comprehensive overview of the current trends and future perspectives in the application of deep learning models for COVID-19 detection from chest X-ray images. We systematically analyze the literature to highlight the evolution of deep learning techniques, the performance of different CNN architectures, and the challenges and limitations encountered in COVID-19 diagnosis. Additionally, we discuss emerging trends, such as transfer learning, ensemble methods, and multimodal approaches, and their potential impact on improving the accuracy and reliability of COVID-19 detection. By synthesizing existing research findings and identifying areas for future exploration, this review aims to provide valuable insights for researchers, clinicians, and policymakers involved in combating the COVID-19 pandemic through advanced diagnostic strategies.
Licence: creative commons attribution 4.0
COVID-19, convolutional neural networks (CNN), Chest X-ray, Deep learning.