bluuebunny/crossref_metadata_2025 huggingface dataset:
Biotransformation studies on bioactive compounds: 25 years of interesting research at the ICCBS
Authors: Siddiqui Mahwish , Wahab Atia-tul- , Choudhary M. Iqbal , Rahman Atta-ur-
Published: May 2023

Biotransformation of natural, synthetic, and semi-synthetic compounds has emerged as a frontier branch of chemical sciences that is progressively being applied in numerous fields. In the present review, we have summarized our biotransformation studies on bioactive compounds from 1997 to 2022. Various microbial and plant cell cultures were used for biocatalytic structural transformations. We present here an overview of biotransformation of 53 compounds belonging to various classes of natural, synthetic, and semi-synthetic compounds, published in several leading journals. The structures of the resulting metabolites have been elucidated by detailed spectroscopic studies. Oxidation, reduction, dehydrogenation, chlorination, aromatization, methylation, demethylation, rearrangements, etc. were the main reactions that occurred during the biotransformation processes. Many of the biotransformed products exhibited interesting biological activities. Structural transformations in some cases have also led to improved pharmacokinetic profiles. This review is aimed to provide a focused account of extensive work carried out in our laboratories in this field, as well as the immense potential of biocatalytic transformations in organic chemistry.
The increasing presence of the internet in the lives of patients and doctors: threat or opportunity?
Authors: Anamika FNU , Goel Ashish , Aggarwal Amitesh , Gupta Ramansh Bandhu
Published: May 2023

The conventional sharing of information and education between doctor and patient is no longer what it used to be prior to Dr. Google’s entry into the mix with voluminous data, not only transforming but often threatening the patient-doctor relationship. While patients no longer seek basic information from their physicians since they’ve already consulted Dr. Google, the wise physician accepts that patients are now more aware, more involved in their own care, and more empowered with information. The good old doctor who knew everything is now more a myth that exists largely in folklore. While doctors may be well versed in a variety of fields, they have often narrowed down their areas of specialisation, while they continue to apply what they learn from their daily encounters with patients, establishing a stronger relationship over time. The challenge arises when a patient, having consulted Dr. Google, starts to question their doctor with the little knowledge gained from the internet. Biased opinions based on prior knowledge, have lately placed the doctor-patient relationship in jeopardy.
Kisah Al-Qur’an dan Ayat-ayat yang Memiliki Kemiripan Susunan Kata: Sebuah Tinjauan Sintaksis Arab
Authors: Holilulloh Andi , Huda M. Nurul
Published: May 2023

The method of understanding the story of the Quran using a historical approach is that in several verses it has experienced deadlocks in the editorials of similar verses. Thus, a stylistic approach that focuses on the analysis of Arabic syntax is needed to understand these verses. This study aims to answer questions about the interpretation of stories in the verses of the Quran that have the same word order. The method used in this study is content analysis with a stylistic approach at the syntactic level. The primary data sources used are stories in the verses of the Quran that have similar wording, while the secondary sources used are related and relevant to the research topic. The results of this study indicate that the verses of the Quran with similar wording do not always refer to the same events. One element of the story can be described in various versions according to the intent and purpose of the story. This article can contribute to understanding the story in the verses of the Quran. Apart from the historical approach, a stylistic approach can also be helpful, especially at the level of Arabic syntax.
Effect of a Mobile App–Based Urinary Incontinence Self-Management Intervention Among Pregnant Women in China: Pragmatic Randomized Controlled Trial
Authors: Chen Ling , Zhang Danli , Li Tiantian , Liu Sha , Hua Jie , Cai Wenzhi
Published: May 2023

Background

Urinary incontinence (UI) is a highly prevalent health concern commonly observed during and after pregnancy that can substantially impact women’s physical and psychological well-being and quality of life. Owing to its numerous advantages, mobile health may be a promising solution; however, it is unclear whether the app-based intervention can effectively improve UI symptoms during and after pregnancy.

Objective

This study aimed to evaluate the effectiveness of the Urinary Incontinence for Women (UIW) app–based intervention for UI symptom improvement among pregnant women in China.

Methods

Singleton pregnant women without incontinence before pregnancy who were aged ≥18 years and between 24 and 28 weeks of gestation were recruited from a tertiary public hospital in China and were randomly allocated (1:1) to either an experimental group (n=63) or a control group (n=63). The experimental group received the UIW app intervention and oral pelvic floor muscle training (PFMT) instructions, whereas the control group received oral PFMT instructions alone. Neither the participants nor the researchers were blinded to the intervention. The primary outcome was UI severity. The secondary outcomes included quality of life, self-efficacy with PFMT, and knowledge of UI. All data were collected at baseline, 2 months after randomization, and 6 weeks post partum through electronic questionnaires or by checking the electronic medical record system. Data analysis followed the intention-to-treat principle. A linear mixed model was used to examine the intervention effect on primary and secondary outcomes.

Results

Participants in the experimental and control groups were comparable at baseline. Of the 126 overall participants, 117 (92.9%) and 103 (81.7%) women completed follow-up visits at 2 months after randomization and 6 weeks after delivery, respectively. A statistically significant difference in UI symptom severity was observed between the experimental group and control group (2 months after randomization: mean difference −2.86, 95% CI −4.09 to −1.64, P<.001; 6 weeks post partum: mean difference −2.68, 95% CI −3.87 to −1.49, P<.001). For the secondary outcomes, a statistically significant intervention effect on the quality of life, self-efficacy, and UI knowledge was found at the 2-month follow-up (all P<.05) and 6 weeks post partum (all P<.001).

Conclusions

The app-based UI self-management intervention (UIW) effectively improved UI symptom severity, quality of life, self-efficacy with PFMT, and knowledge of UI during the late pregnancy and early postnatal periods. Larger multicenter studies with a longer postpartum follow-up are required to further extend these findings.

Trial Registration

Chinese Clinical Trial Registry ChiCTR1800016171; http://www.chictr.org.cn/showproj.aspx?proj=27455

International Registered Report Identifier (IRRID)

RR2-10.2196/22771
Using a Virtual Reality Tool to Provide Primary Prevention Training in the Construction Field Following a Periodic Medical Visit: Cross-Sectional Study (Preprint)
Authors: Chamot Sylvain , Mahieu Isabelle , Delzard Marion , Leroy Léa , Marhic Gwen , Gignon Maxime
Published: May 2023

BACKGROUND

The construction field is highly concerned with the risk of work-related accidents, and training employees is difficult due to their small numbers in most companies.

OBJECTIVE

This study aimed to study the impact of a virtual reality (VR) training tool following a periodic occupational health medical visit on the feeling of personal effectiveness in preventing occupational risks related to co-activity on a construction site.

METHODS

We conducted a cross-sectional study with employees who had a periodic medical visit between April 1, 2022, and October 13, 2022, in a French occupational health service specializing in the construction field (Services Médicaux Interentreprises Bâtiment Travaux Publics [SMIBTP]). The employees were divided into 2 groups according to the training received: a medical visit alone or coupled with a session with a VR tool. We compared the scores for a “feeling of self-efficacy in occupational risk prevention” using the Fisher exact test.

RESULTS

Of the 588 employees included, 210 had a medical visit alone, and 378 had a medical visit coupled with VR training. Training with the VR tool was associated with an increased “feeling of self-efficacy in occupational risk prevention.” The employees who benefited from the training reported a willingness to apply the advice given on prevention to a greater extent than those who did not, and they believed that risks on the worksite could be reduced using this tool.

CONCLUSIONS

Using VR training as a complement to periodic medical visits in an occupational health service improves the feeling of personal effectiveness in occupational risk prevention at the end of the training. If this trend is confirmed over a longer period of time, it could be an easily accessible prevention lever for employees in the future.
Impact of Virtual-Reality-Guided Mindfulness on Focus Prior to High-Fidelity Simulation Debrief (Preprint)
Authors: Weingart Brett , Burnett Garrett , Hojsak Stephanie , Katz Daniel
Published: May 2023

BACKGROUND

High-fidelity simulation (HFS) is commonly used to train anesthesiology residents in how to perform in high-stress situations. Previous studies have shown physiologic stress responses during HFS may enhance performance during subsequent high-intensity scenarios, however this level of stress may hinder focus and knowledge retention during a post-HFS debrief session. Currently, the optimal mindset to maximize learning during the debrief is unknown and the ideal modality to create this mindset after a stress-inducing session has not been determined.

OBJECTIVE

This study aims to examine changes in focus and anxiety in anesthesia PGY-2 residents participating in HFS. Participants completed a guided mindfulness exercise session prior to simulation debriefing, either with or without virtual reality (VR) supplementation. We hypothesized that the mindfulness exercise with VR would lead to a larger increase in focus and decrease in anxiety than compared to the mindfulness exercise without VR.

METHODS

26 anesthesiology PGY-2 residents completed twice-weekly HFS sessions over 8 weeks. Immediately after the HFS session and before a standardized debrief, they completed a 5-minute mindfulness exercise guided by a consumer-grade EEG headband. Half of the residents wore a VR headset and meditated in a virtual forest environment, while the other half meditated with their eyes closed. Immediately before and after meditating, they completed a brief anxiety and focus questionnaire, then participated in a standardized debrief on the HFS session. Changes in focus and anxiety after meditating (self-reported) were compared between the two groups, as well as composite EEG scores between the two groups.

RESULTS

Analysis showed no significant differences between two groups regarding baseline anxiety levels or composite EEG scores prior to investigation. There were no significant differences between the groups’ increase in focus (VR group 4.8, Control 8.1, P = .62) and reduction in anxiety (VR group -16.4, Control -21.1, P = .39) after meditating. However, regardless of VR supplementation, meditation reduced anxiety levels by about 19% (P < .001) across all participants. Focus levels did not change after meditation.

CONCLUSIONS

The addition of VR had no effect on the quality of meditation or on changing the resident’s mental state. Meditation led to reduced anxiety levels across all groups, suggesting that meditation of any form is useful before HFS debrief in reducing stress, but the addition of VR may be unnecessary.
Digital Certificate System for Verification & Validation of Educational Certificates using Block chain Technology
Authors: Patole Nisha
Published: May 2023

Abstract: With the proliferation of mobile devices in recent years, there is a tendency to move almost all real-world activities to the cyber world. Although this makes our daily life easier, it violates many security rules due to the anonymous nature of the Internet. Phishing attacks are the easiest way to get sensitive information from innocent users. Phishers aim to obtain sensitive information such as usernames, passwords, and bank account information. Cybersecurity professionals are looking for reliable and consistent detection methods to detect phishing websites. This project deals with machine learning technology to detect phishing URLs by extracting and analyzing various features of legitimate and phishing URLs. Decision trees, random forests, and support vector machine algorithms are used to identify phishing websites in a two-step process of first visualizing and extracting features of URLs using python libraries and then training them into a model using Gradient Classifier Algorithm to predict real-time phishing websites.
The Intelligent Vehicle Number Plate Recognition System based on Arduino
Authors: Boronov Erkinbek , Wei Prof. Wei
Published: May 2023

Abstract: The thesis proposes the development of The Intelligent Vehicle Number Plate Recognition System (IVNPRS) using the Arduino platform. The system uses image processing techniques to automatically detect and recognize vehicle number plates, and it includes a camera module, an image processing unit, and an Arduino microcontroller. The proposed system has practical applications such as security monitoring, automatic toll collection, and traffic monitoring. The thesis discusses the different components of the system, image processing techniques used, and evaluates its performance by measuring accuracy, speed, and robustness under different lighting and weather conditions. The experimental results suggest that the VNPRS has the potential to improve vehicular traffic and safety in various locations.
Face Authenticated Personal Virtual Assistant
Authors: Reddy P. Nishanth , Kumar M. Sampath , Srinivas B. , Prasad G.
Published: May 2023

Abstract: In these days the technology has been increased rapidly. More number people are using the internet to make things simple. Our project is about virtual personal assistant (VPA). There are some Virtualassistants like Siri, Alexa, Cortana, google assistant etc. Virtual assistant takes commands or questions from user and perform the tasks according to The commands virtually or through the internet. Our virtual personal assistant had a features Like search engine, open apps, set timer, send email, send WhatsApp messages, navigation etc. The virtual personal assistant takes an input through voice (via microphone) and process the input and gives the output through systems speaker.But in our VPA it takes a voice input and give the voice output and it also displays an output on the screen.
Securing Smart Devices on Blockchain
Authors: V Mrs. Kamala
Published: May 2023

Abstract: A smart device uses information technology to integrate and manage physical, social, and business infrastructures data in order to provide better services to its dwellers while ensuring efficient and optimal utilization of available resources. With the proliferation of technologies such as Internet of Things (IoT), cloud computing, and interconnected networks, for securing smart devices, they can deliver a lot of innovative solutions. Despite a number of potential benefits, digital disruption poses many challenges related to information security and privacy. Here, this project proposes a security framework that integrates the blockchain technology with smart devices to provide security to smart devices.
Third Vision for Blinds
Authors: Kamal Rohan
Published: May 2023

Abstract: This paper introduces a third vision system designed to assist visually impaired individuals in detecting obstacles and dangers during walking, as well as identifying the world around them. The proposed solution acts as an artificial vision and alarm unit, consisting of three sensors (ultrasonic, water, and heat flame), and a microcontroller (Arduino Uno R3) to process sensor signals into short pulses for the Arduino pins to activate buzzers and LED bulbs. Our project aims to provide an affordable and lightweight smart stick suitable for most blind people, making it accessible to all segments of society and their families in need.
Aspect-Based Sentiment Analysis on Flipkart Data
Authors: Uttam Yeramalla
Published: May 2023

Abstract: This research In this paper, an Aspect-Based Sentiment Assessment (ABSA) model using the The Long Short-Term Memory (LSTM) network for analyzing info on Flipkart sentiment The suggested model seeks to identify and extract certain elements of a product or service, as well as to characterise their related sentiment polarity as positive, negative, or neutral. On a Flipkart dataset that is open to the public, experiments were run to assess the effectiveness of the suggested model. The LSTMbased ABSA model surpasses other baseline models, according to the results, achieving an accuracy of above 90%. The suggested approach is also capable of locating and extracting the key features of a good or service that influence consumers' opinions. This research provides a valuable contribution to the field of sentiment analysis on Flipkart data, and has significant practical implications for Flipkart companies seeking to improve customer satisfaction and loyalty
Identifying Fake News via Machine Learning and Web Scrapping
Authors: Rathi Devanshu
Published: May 2023

Abstract: After digitalization, the increase in use of social media has led the flow of information among the social network users unchecked. The news is immediately transported to social networks, where it is quickly read, marked with opinions (on Facebook), and shared (on Twitter and Facebook) without being verified as accurate or false numerous times. In the modern world, fake news is an issue that has grown difficult to detect. Its impact on the judgement of commonfolk is noticeable, society has witnessed numerous events where the rampant flow of unverified news had affected the society as a whole. The sharing of fake news has become a major issue to the society. Our project aims to aid in reduction of e-crimes like use of social media for sharing of fake content. This will be achieved by training the machine to identify text based fake content. Using this the time for work of filtering out the fake content will be reduced by great lengths whilst helping the mass to get verified and credible news.
Phishing Website Detector using ML
Authors: Jadhav Sairaj
Published: May 2023

Abstract: With the proliferation of mobile devices in recent years, there is a tendency to move almost all real-world activities to the cyber world. Although this makes our daily life easier, it violates many security rules due to the anonymous nature of the Internet. Phishing attacks are the easiest way to get sensitive information from innocent users. Phishers aim to obtain sensitive information such as usernames, passwords, and bank account information. Cybersecurity professionals are looking for reliable and consistent detection methods to detect phishing websites. This project deals with machine learning technology to detect phishing URLs by extracting and analyzing various features of legitimate and phishing URLs. Decision trees, random forests, and support vector machine algorithms are used to identify phishing websites in a two-step process of first visualizing and extracting features of URLs using python libraries and then training them into a model using Gradient Classifier Algorithm to predict real-time phishing websites
Traffic Noise Pollution Modelling and Noise Reduction Asphalt Pavement
Authors: B Baseena
Published: May 2023

Abstract: Noise pollution leads to the lack of concentration of people, as a result, they will be finding longer time for completing the work than that which would be done in a quiet environment and in addition they feel more tired in the noisy area. Road traffic is a complete system which wide comprises of varieties of road user, vehicle and environment interact the congestion of road intersections is due to the motorization from and increase in single occupancy vehicle. This study is carried out to understand the noise traffic pattern of Ottapalam city. So proper planning of the road should be done and proper laws should be available. A study area consisting of two locations, a busy urban street of Ottapalam city, with high population density was selected for the study to determine the impact of the noise pollution at residential zone.
Fraud Detection and Analysis for Insurance Claim Using Machine Learning
Authors: Patil Vaishnavi
Published: May 2023

Abstract: Insurance fraud is an illegal conduct that is done on purpose in order to profit financially. This iscurrently the most serious issue that numerous insurance companies throughout the world are facing. The majority of the time, one or more gaps in the investigation of false claims has been identified as the primary factor. As a result, the requirement to use computer tools to stop fraud activitiesincreased. Providing customers with a dependable and stable environment while significantly lowering fraud claims. We demonstrated the results of our research by automating the evaluation of insurance claims using a variety of data methodologies, where the detection of erroneous claims would be done automatically using Data Analytics and Machine Learning techniques.
Research Paper on ATM Based on Face Recognitions System
Authors: Khaple Prof. Arunadevi
Published: May 2023

Abstract: Automated Teller Machines are widely used nowadays by people. But it’s hard to carry their ATM card everywhere, people may forget to have their ATM card or forget their PIN number. The ATM card may get damaged and users can have a situation where they can’tget access to their money. In our proposal, use of biometrics for authentication instead of PIN and ATM card is encouraged. Here, The Face ID is preferred to high priority, as the combination of these biometrics proved to be the best among the identification and verification techniques. The implementation of ATM machines comes with the issue of being accessed by illegitimate users with valid authentication code. The users are verified by comparing the image taken in front of the ATM machine, to the images which are present in the. If the user is legitimate the new image is used to train the model for further accuracy. Thissystem uses open CV to process the image being obtained and Hear Cascade Classifier to detect the faces in the image. The face recognitions done using Local Binary Pattern.
Review Paper on Anti-Theft Autonomous Delivery Robot for Food and E-Commerce
Authors: Choudhary Shivansh , Tiwari Mansi
Published: May 2023

Abstract: The ongoing development of artificial intelligence and machine learning is enabling robots to become more observant. This advancement allows robots to be utilized in situations where humans may not have control. One example is the use of delivery robots for "last mile" delivery services. These robots can be remotely controlled by an operator in cases where they encounter obstacles. Delivery robots have various applications such as room service, package delivery, food delivery, and hospital deliveries. A research study focused on developing an algorithm that enables autonomous path generation using a GPSbased coordinate system. The algorithm allows the robot to create its own path between its current position and the destination using GPS co-ordinates.
Drug Supply Chain Using Blockchain Technology
Authors: Pawar Pranali
Published: May 2023

Abstract: Developing a supply chain in the healthcare sector is quite challenging since a compromised supply chain could risk a patient's life. Lack of transparency, difficulty tracking items, distribution of out-of-date products, a lack of confidence, a lack of safety and security, and many other problems are dealt with in the healthcare industry. Numerous of these issues can be resolved using blockchain technology. The necessity to increase transparency and traceability in the supply chain has arisen as a result of growing concern over drug safety. The use of an efficient, traceable, and transparent supply chain with blockchain technology can also help avoid drug counterfeiting.
Interpreting Cardiovascular Disease using Random Forest and Explainable AI
Authors: Dabir Aishwarya
Published: May 2023

Abstract: These days, artificial intelligence and machine learning in trendy have proven terrific performances in lots of obligations, from image processing to natural language processing, specifically with the advent of machine learning in conjunction with studies development, they've encroached upon many specific fields and disciplines. a number of them require excessive degree of duty and as a result transparency, as an instance the clinical region studies into Explainable Artificial Intelligence (XAI) has been increasing in current years as a response to the need for extended transparency and believe in AI. that is especially crucial as AI is utilized in sensitive domain names with societal, moral, and safety implications reasons for system choices and predictions are as a consequence had to justify their reliability. This requires extra interpretability, which frequently approach we need to understand the mechanism underlying the algorithms. by means of applying the same categorization to interpretability in clinical research, it is hoped that (1) clinicians and practitioners can in the end method those strategies with caution, (2) insights into interpretability could be born with greater issues for scientific practices, and (3) initiatives to push ahead statistics-based totally, mathematically- and technically-grounded scientific schooling is recommended.
Smart Pet Monitoring and Parenting System
Authors: Kale Vaishnavi , Malaiya Misha , Bagwan Umer , Kamthe Prof. M. A.
Published: May 2023

bstract: Pets bear regular and controlled quantities of food for their good health. Since Internet of things ( IoT) have come to our lives, we've developed colorful smart services utilizing IoT. Basic services of the smart pet monitoring and feeding systemare Remote feeding, remote ruled spontaneous defecation, CCTV indulgence and Smart phone APP that can give the control information of the below services. Introductory armature and system executions are acquainted with the details of services. spontaneous pet affluents can set the time and quantum of food in advance with precise scales, tallying to the pets need. It also records and cover via the Internet of effects( IoT). The robust robot can maneuver around the house and can cover one's pet utilizing the authority of the internet of effects. A smartphone app was aimed to interact with your pet via a live videotape feed. The lattice of the robot is digitally fabricated as several corridor were created utilizing 3D printing and ray slice. The engine consists of an ultrasonic detector, a camera to descry the motion of the canine correlate precious feeding geste across multitudinousaffluents if present-day, and allows a pet proprietor to ever acclimate parameters of the confluent or view the pet through a camera
Credit Risk Analysis Using Naive Bayes in Machine Learning
Authors: Gade Prof. S.P.
Published: May 2023

Abstract: A method of data analysis called machine learning automates the creation of analytical models. It is an area of artificial intelligence based on the idea that robots can learn from data, recognise patterns, and form opinions with little help from people. One of the most important and difficult tasks facing banks is the evaluation of credit risk. To prevent financial loss, accuracy is crucial in the classification of credit data. Lending money to people who need it is a major operation in the banking sector. The depositor bank receives the interest earned by the main borrowers in order to repay the principal borrowed from them. Financial risk management is increasingly focusing on credit risk analysis. The ability to estimate credit risk, monitor it, trust the model, and process loans well are essential for decision-making and transparency. In this study, we develop binary classifiers based on machine learning and deep learning models on actual data to forecast the likelihood of loan default. In the aforementioned research, we examine various methods for credit risk analysis that are used to the assessment of credit risk datasets.
Review on Different Defluoridation Techniques
Authors: Dhorabe Prashant
Published: May 2023

Abstract: Water is basic need for life. It is used in every household activity. With increasing population, the demand of water is increased. In addition to problem of limited quantity of water, its quality is also main concern. One of main concern is about fluoride present in water. Defluoridation involves removal of fluoride present in water. Consuming fluoride has both advantageous and disadvantageous effects on human body and animals that is why it is known as 'double -edged sword ‘. Excessive consumption of fluoride causes fluorosis. It is major health problem in India. Various techniques are studied to remove fluoride bur still the problem is not been solved. The purpose of this paper is to review the techniques or methods available for fluoride removal from water.
Automatic Face Recognition and Detection for Criminal Identification Using Machine Learning
Authors: Nikam Prof. R. A.
Published: May 2023

Abstract: With the use of machine learning technologies, discovering connections and patterns among various types of data has gotten much easier. Finding out what kind of crime might happen given the location where it has previously occurred is the main goal of this research. We have created a model utilizing the machine learning concept using a training set of data that has been cleaned up and transformed. In contemporary civilization, criminal activity is growing dramatically. Effectively identifying criminals to stop crime is the police's principal challenge, but there aren't enough policemen to go around. There are numerous technical approaches to apprehend criminals, yet many of them are ineffective. In this project, a face detection and recognition system for criminal identification is created using a machine learning algorithm. This system will be able to instantly differentiate the 3D faces of criminals and recognize their faces. This system's one-shot learning method only requires a single image of the criminal to identify him. The objective is to identify the criminal from a distance, extract the criminal's information from the database, and notify the police personnel of the location where the criminal was being observed by a camera.
Smart Trolley Using RFID
Authors: Mhatre Prof. Manisha
Published: May 2023

Abstract: People's living standards have improved as a result of modern technologies. As a result, there was a large crowd at the mall. To control the huge crowd, we must streamline the billing procedure. A smart shopping system based on RFID is used to accomplish this. Once each item in a smart shopping cart has been read thoroughly, the bill is generated and displayed. after the last A bill is printed. The customer pays the money using the pre-charged cards that the shopping complex has provided. The objective is to reduce time consumption. It makes use of RFID technology, which can scan a large number of things and help save both customers' and the mall's valuable time.
Brain Tumor Detection
Authors: Saraswat Birendra Kumar , Vaibhav Vibhanshu , Pal Promise , Singh Avneesh kr , Tiwari Navneet
Published: May 2023

Abstract: Accurate detection of brain tumors plays a critical role in diagnosis, treatment planning, and patient outcomes. In this study, we propose a novel deep learning-based approach for brain tumor detection using multimodal magnetic resonance imaging (MRI) data. The proposed model combines convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to efficiently analyze both structural and functional information from T1-weighted, T2-weighted and diffusion-weighted MRI scans. By exploiting the complementary nature of multimodality imaging, our model achieves improved sensitivity and specificity in tumor detection compared to single-modality approaches. Furthermore, we introduce a data augmentation technique to alleviate the limited availability of labeled data. The performance of our model was evaluated on a large dataset of brain MRI scans, achieving a high accuracy of 92.3% and an area under the curve (AUC) of 0.95. Our results demonstrate the potential of deep learning and multimodal imaging to improve brain tumor detection and highlight its clinical relevance in improving early diagnosis and treatment planning
Cryptographic Technique for Communication System
Authors: Koshy Mr. Aditya Sam
Published: May 2023

Abstract: The Cryptography is gotten from a Greek word which implies the craft of ensuring data by changing it into a muddled organization and unreadable format. It is a mix of arithmetic and software engineering. The dynamite growth of the Internet has made an expanded familiarity with intrigue uncertainty issues. Even though security is the measure worries over the internet, numerous applications have been created and structured without considering fundamental destinations of data security that is confidentiality, authentication, and protection. As our day by day exercises become increasingly more dependent upon data networks, the significance of an understanding of such security issues and trouble will also increase. To forestall some undesirable clients or individuals to gain admittance to the data, cryptography is required. .This paper introduces a new hybrid security cipher by combining the three most important Ciphers such as Gronsfeld Cipher , Polybius Cipher and Vigenere Cipher.
Advancements in AI for Brain Tumor Detection and Classification
Authors: Bhushan Badal , Agarwal Priyanshu
Published: May 2023

Abstract: This research paper explores the development of artificial intelligence (AI) in brain tumor detection and classification from 2010 to the present. It examines the significance of brain tumors, the role of MRI in their analysis, and the motivation behind utilizing AI in this context. The objectives and methodology of the research are outlined. The paper discusses various AI techniques, such as machine learning and deep learning, as well as supervised, unsupervised, and semi-supervised learning approaches. The importance of feature extraction and selection is highlighted, and a comparison is made between traditional methods and AI-based approaches. The evolution of AI techniques in brain tumor detection and classification is examined, including notable research papers and their contributions. The impact of AI algorithms on accuracy, efficiency, and clinical applications is analyzed. The paper concludes with a discussion of challenges, future directions, and the potential integration of emerging technologies.
Surveillance Robot for Landmine Detection
Authors: Kumar Dr. Vijay , Srivastav Alok , Arya Divyansh , Chauhan Pranjal Singh , Chaudhary Prashant , Chaudhary Prerna
Published: May 2023

Abstract: Landmine detection robots are intended to cover as much of the landmine field as possible in order to detect landmines.The encountered landmines, along with the scanned and residual territory, are represented with millimetre precision on an interactive map. This study offers a prototype model of a land mine detecting robot that is strong while being affordable in cost and easy to handle. Graphic user interface is created for mapping landmines, displaying scanned and remaining areas, PID tweaking, and camera alignment.The emphasis is on controlling the differential drive robot in auto, semi-auto, and manual modes. The image processing technology is used to determine the precise position of the robot, which offers live reckoning feedback to the robot's dead reckoning servo control. A metal detector is a sensor that is used to detect landminesThe GUI, or graphical user interface, for the remote terminal computer essentially controls the robot.The procedure is simple, yet effective in achieving the intended results.The method is basic but strong and understandable in order to get the desired goals.
Easy Health Care Web Project
Authors: Tomer Mr. Praveen , Kushwaha Ramesh , Kumar Sachin , Kumar Rohit
Published: May 2023

Abstract: Welcome to the future of Easy HealthCare, This Easy HealthCare web project is designed to provide users with simple and intuitive platform to access basic healthcare service online. Then platform aims to connect patients with medical professions and facilities in their area, providing access to healthcare service that are convenient and accessible. affordable, The website will feature a user-friendly interface that allows users to easily navigate through different sections of the platform. User can search for healthcare services and professionals in their disease. They can also view profiles of medical professionals, read patient reviews and book appointment online. In this website admin have all the responsibility to manage the user and doctor authentication and also check the education and profession of the doctor. Overall, this easy healthcare web project is designed to provide users with simple and convenient way to access healthcare services and information online, improving overall health outcomes and promoting wellness in the community.
Design and Modelling of Automated Moisture & Temperature Sensing Umbrella Mechanism
Authors: Sharma Labhansh , Shrimal Devesh , Garg Mukul , Rangrej Muskan , Tripathi Naval , Pandey Nikhil
Published: May 2023

Abstract: The significance of rainfall as a crucial natural resource for various crop cultivations cannot be overstated; however, its excessive occurrence or manifestation in unfavourable climatic conditions can prove fatal by causing crop decay. The principal aim of this research endeavour is to safeguard crops against such aberrant weather circumstances. The proposed solution addresses a major predicament in the realm of agriculture, offering protection against unwanted precipitation or extreme heat through the implementation of an umbrella-like structure. This model encompasses the designated area, employing a mechanism comprising nuts, bolts, motors, gears, and sensors to facilitate the opening and closing of the umbrella in response to rain and temperature variations. The automated functionality of this system holds the potential to deliver optimal crop protection.
Caravan Music Player
Authors: Muqtadir Abdul
Published: May 2023

Abstract: The purpose of this research paper is to provide an overview of a web-based music player, called the "Caravan Music Player," which is built on WordPress and PHP. The Caravan Music Player offers users the ability to purchase music albums, listen to music, and create custom playlists. The research paper details the features and functionality of the Caravan Music Player, including its user interface, payment processing system, and media player. Additionally, the research paper explores the technical aspects of the Caravan Music Player, such as the architecture, database design, and security measures implemented in the website. The paper concludes by discussing the potential impact of the Caravan Music Player on the music industry and the broader technology landscape, as well as identifying opportunities for future research and development of the platform. Overall, this research paper provides a comprehensive overview of the Caravan Music Player and its potential as a platform for music consumption and discovery.
FORM-based Document Understanding Sequential Model
Authors: Dalave Mr. Chetan , Lodh Mrs. Anushka , Bandal Mrs. Monika , Awalekar Mrs. Priyanka , Babanne Mrs. Vanita
Published: May 2023

Abstract: Image recognition and optical character recognition technologies have become an integral part of our daily lives due to the ever-increasing power of computing and the ubiquity of scanning devices. Sequence modeling has performed state-of-theart on natural. Language and document comprehension tasks. However, this is the challenge of properly serializing tokens into form-like documents in practice due to the variety of layout patterns. We propose FormNet, a structure-aware layout model that reduces most serialization of forms. Form-based documents with the help of the OCR, we can search and recognize the text in documents and can easily convert them into human-readable text. It motivates us to make life simple to read the data which is unstructured as we convert it into a structured and simple format so that it becomes easy to read vast textual data.
E-Voting System Using Blockchain
Authors: Singh Suraj
Published: May 2023

Abstract: The introduction of online voting has revolutionized the electoral process, providing a secure and convenient way for people to cast their votes without having to be physically present at polling stations. However, traditional online voting systems are still susceptible to security and integrity issues, such as hacking and tampering. Blockchain technology provides a solution to these problems by offering a decentralized and immutable ledger that can ensure the security and transparency of online voting. In this paper, we propose an online voting system using blockchain technology, which is designed to provide a secure and transparent voting process.
Disease Prediction Using Machine Learning Algorithms
Authors: Kumar Harshit , Kumar Kapil , Sharma Ishan , Srivastava Dr. Prabhat Kumar
Published: May 2023

bstract: The objective of this project is to develop a machine learning model that can predict the disease of a patient based on their symptoms. While data mining has been successfully applied in many areas, such as market analysis and e-commerce, the medical field still lacks powerful analytical tools to uncover hidden relationships and trends in data. Medical data contains a wealth of information, but this knowledge is often not effectively utilized. Machine learning is a field of study that involves developing algorithms that can improve automatically through experience and data. These algorithms use training data to build a model that can make predictions or decisions without being explicitly programmed. In this project, techniques such as association rule mining, classification, and clustering will be used to explore various general health problems. Classification is a crucial problem in data mining, and decision trees are a popular classifier used to create class models. The ID3 Decision Tree algorithm is commonly used for information classification. However, this algorithm can be inaccurate, so techniques such as entropy-based cross-validation and partitioning will be used to improve the accuracy of the model. Finally, the results will be compared to determine the best model. Introduction I would like to begin by highlighting the indispensability of computers in our lives. Computers are integral components in virtually every aspect of our lives today, comprising various hardware and software components. Software, which is a collection of programs designed to perform specific tasks, is an essential component of computer systems. However, software development is a complex process that involves a team of professionals, as denoted by the term "project." The term "project" is an acronym for Planning, Resource, Operating, Joint effort, Engineering, Cooperation, and Technique. Planning involves conceptualizing and identifying the necessary steps to accomplish the project. Resource refers to addressing the financial aspects and acquiring the resources required for the project. Operating entails the systematic procedure for carrying out the project tasks. Joint effort relates to the collaborative effort of individuals working towards achieving the project goals. Engineering signifies the importance of having well-educated professionals in the project team to produce optimal results. Co-operation is essential for the success and timely completion of the project. Finally, technique denotes the importance of utilizing suitable methodologies to achieve project objectives. To conclude, software development is a crucial process that requires a project-based approach that involves planning, resource acquisition, operating procedures, joint effort, engineering, cooperation, and technique. This approach ensures successful completion of software development projects.
Hoof Trimming as a Major Issue in Cattle Farming… Indian Scenario
Authors: Chaudhari Divyam Sudhakar , Jadhav Sarvesh Rajendra , Late Kalpesh Suresh , Lohokare Abhishek Santosh , Patil Sandip Subhashrao
Published: May 2023

Abstract: India has the largest number for cattle farming about 302.79 million, and as the part of managing the cattle health Hoof cutting is the major issue when it comes to taking care of cattle. Improper cutting of hoof can lead to harm to the cattle and it may sometimes turn into severe disease, in this case cattle may be prone to lameness. The cutting of hoof is done by traditional way by using tools like chisel, grinder, pincer etc. these tools have their own specific applications, but still it is used to cut hoofs, It is observed that there is no specific tool for cutting hoof of cattle and available tools not having tool Replacement. In literature review, researcher also neglected the issue and it is rarely found the development of new special tool for hoof cutting. So there is scope of working on this tool. Under this project activity, the designed and developed portable hand operated hoof cutter, new developed tool has the various blade settings adjustment which increase versatility of cutter, and it can cut 4”, 6”, and 8” length of hoof by using this cutter. The new developed cutter has 30% more efficiency compared to all the traditional cutting methods. This Project presents the design and fabrication of a hoof cutter for cattle. New Developed hoof cutter is designed to be efficient, safe, and user-friendly. The hoof cutter is fabricated using readily available materials that are easy to source and assemble. The tool is portable and easy to use, making it ideal for use in the field by farmers and veterinarians. The hoof cutter is tested to evaluate its efficiency and safety. The results showed that the hoof cutter is both efficient and safe to use
Musical Therapy through Facial Expression Recognizer using Machine Learning
Authors: Aswal Shruti , Jyothidas Sruthilaya , Shankarakrishnan S , M Prof. Prabhu
Published: May 2023

Abstract: Musical therapy is a type of treatment that uses music to help people improve their physical, emotional, cognitive, and social functioning.It is a non-invasive treatment that has been shown to have beneficial effects on mental health.Facial recognition technology has grown in prominence as a tool for analyzing human emotions and behaviors in recent years. We are investigating the possibility of facial recognition technology in musical therapy.In this project, we propose a novel approach to musical therapy that uses facial recognition technology to create personalized playlists for individuals based on their emotional state. We use a convolutional neural network (CNN) to analyze facial expressions and classify them into different emotional states, such as happiness, sadness, or anger. Based on the emotional state detected, we recommend music that is likely to have a positive effect on the individual's emotional well-being.A voice assistant is also integrated into the system to provide additional support and guidance to the users. The system is designed to be accessible to people of all ages and abilities, including those with disabilities.Our approach has the potential to improve the effectiveness of musical therapy by providing personalized recommendations based on the individual's emotional state. Moreover, our project provides a convenient and accessible platform for individuals to receive musical therapy without the need for in-person visits to a therapist.