bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimizing infrastructure development through BIM: A comprehensive analysis of lifecycle benefits and applications
Authors: Zhang Yingfei
Published: April 2024

This comprehensive study delves into the multifaceted impacts of Building Information Modeling (BIM) across different phases of infrastructure projects, encompassing project planning and design, construction, as well as operations and maintenance. By offering a granular analysis of BIM's contributions to design efficiency, enhanced collaboration, sustainability considerations, improved project management, risk mitigation, quality control, asset management, lifecycle analysis, and space management and utilization, the paper presents quantifiable evidence of BIM's transformative potential. The findings underscore the substantial benefits of BIM in reducing project timeframes, minimizing material costs, enhancing operational efficiency, and contributing to sustainability goals. Through detailed quantitative analysis, this article illustrates how BIM technology facilitates a more integrated, efficient, and sustainable approach to infrastructure development, challenging traditional practices and fostering a new paradigm in construction and facility management.
Updates on Diagnosis, Clinical Presentation, and Management of Ocular Cicatricial Pemphigoid (OCP): A Systematic Review
Authors: Osman Mirghani Hyder , Alqrid Aedah , Albalawi Hadeel , Alshabab Saud , Aljezany Dana , Alghamdi Hamdan , Aljohani Khalid , Almousa Mohammed , Alshehri Ali , Alahmri Zeyad , Alsaidalani Sara , Alshahrani Abdullah , Alshamrani Salman
Published: April 2024

This study systematically searched literature on the diagnosis, clinical presentation, and management of ocular chronic pain (OCP), including eight studies with 168 patients. The most reliable method of diagnosis was biopsy, with inflammatory markers detected in a small proportion of patients. Some patients had systemic or oral involvement and associated Sjogren's syndrome. Common immune-suppressives were MFF and steroids. Cyclophosphamide is a good choice in severe cases. Methotrexate and Rituximab were used as a maintenance therapy. OCP is characterized by ocular involvement that progresses to fibrosis and scarring. Diagnostic hurdles and inconclusive results make a comprehensive examination and clinical suspicion crucial.
Efektifitas Caring Perawat (Maintaining Belief) Terhadap Penurunan Kecemasan Pre-operasi Appendiktomi
Authors: Suhartini Tini
Published: April 2024

Introduction: Anxiety faced by patients when going to surgery includes fear of pain, fear of physical changes, and fear that the operation will fail and this anxiety can cause delaying or canceling the operation. Anxiety is an emotional response to an assessment that describes a state of worry, anxiety, fear, and restlessness accompanied by various life situations as a disease disorder. In the management of nursing care in preoperative patients who experience anxiety, nursing interventions are needed, one of which is caring. Caring is a behavior or action taken to provide a sense of physical and emotional security to others sincerely. The purpose of caring behavior is to provide physical care by paying attention to emotions while increasing a sense of security by showing concern, feelings of empathy, and love. The nurse's caring attitude towards the client in providing nursing care by caring for the client with sincerity, sincerity, and full of love, both through communication, providing support, and direct action Purpose: This study aims to determine the effectiveness of nurse caring (maintaining belief) given to preoperative appendectomy patients and its effect on reducing anxiety
Methods: The research used was quasi-experimental (quasi-experimental) using two groups of subjects with a control group (Nonequivalent Control Group Design). Measurements were carried out before and after treatment. Using a non-randomized pretest and posttest group design approach. The total population was 52 patients and the entire population was sampled (total sampling) and divided into 2 groups of 26 patients each
Results: In the group of caring nurses (maintaining belief) there was a decrease in anxiety in patients pre-operative appendectomy from heavy to moderate and from moderate to mild. From the results of the Wilcoxon test that on average there is a difference with a p-value (0,000 <0,05). While in the control group there was a slight decrease in anxiety in appendicectomy pre-operative patients from severe to moderate. From the results of the Wilcoxon test that the average is different from the p-value (0,317 <0,05).
Discussion: There is a difference in the average decrease in the anxiety of appendectomy pre-operative patients, both in respondents who do care nurses (maintaining belief) and those who do not, by doing caring nurses (maintaining belief) managed to reduce the anxiety felt by pre-operative appendectomy patients.
Hubungan Dukungan Keluarga Dengan Tingkat Kecemasan Pada Lansia Di Masa Pandemi COVID-19 Di Desa Bojonglarang Kecamatan Cijati Kabupaten Cianjur
Authors: Lestari Yuspia
Published: April 2024

Introduction: During the COVID-19 pandemic elderly experience anxiety levels due to fear of contracting the coronavirus, one of the factors that make the level of elderly anxiety increase is the absence of family support in the elderly. COVID-19 (Corona Virus Disease 2019) is a new disease caused by a virus from the Corona Virus group or a disease caused by virus infection severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) or often called the Corona Virus. COVID-19 can cause respiratory system disorders, ranging from mild flu-like symptoms to lung infections, such as pneumonia. COVID-19, known as the Novel Corona Virus, first occurred in the city of Wuhan, China in December 2019. The Corona Virus began spreading to other countries in January 2020. Meanwhile, Indonesia itself announced COVID-19 cases in March 2020 The spread of COVID-19 is currently the most critical global health disaster that has infected more than 100 countries and caused 6,400 deaths.1 On January 7, 2021, COVID-19 cases continued to grow by 87,640,097 cases, which was ranked the highest number of COVID-19 cases, namely the United States with 21,857,616 cases. Meanwhile, Indonesia ranks 20th out of 220 countries infected with Covid-19 with a total number of cases of 797,723 cases (2).
Methods: The population in this study was 70 with a sample number of 60 taken using purposive sampling. This research is quantitative with the type of design correlation that is research conducted to connect two variables.
Results: The results of the statistical test showed that there was a Mutation of the Relationship between Family Support and Anxiety Levels in the Elderly in Bojonglarang Village, Cijati District, Cianjur Regency in 2021 with the results of a statistical test, the p-value = 0,000 which was < 0,05 so that H0 was rejected and Ha was accepted.
Discussion: The relationship between family support and the level of anxiety in the elderly during the COVID-19 pandemic in Bojonglarang Village, Cijati District, Cianjur Regency in 2021, so that families can provide maximum support to the elderly during the COVID-19 pandemic.
On galaxies of sequences of toeplitz matrix solutions of the Diophantine Equation Xn + Yn = Zn, n ≥ 3
Authors: Mouanda Joachim Moussounda
Published: April 2024

We construct the galaxies of sequences of Toeplitz matrix solutions of the Diophantine equation Xn + Yn = Zn, n ≥ 3, linked to Pythagorean triples.
Attenuation of the hemodynamic response to laryngoscopy and tracheal intubation: A randomized controlled trial
Authors: Bayer Rekha , Faneja Ami , Baria Tushar , Ameen Sneha
Published: April 2024

Background: Fentanyl and lidocaine are two drugs that are often suggested to lower the reaction of the blood flow to laryngoscopy and endotracheal intubation.

Aims and Objectives: The main goal of our study is to find out how the heart and blood vessels react when laryngoscopy and intubation are used. A comparison was made between fentanyl 2 mcg/kg and fentanyl 2 mcg/kg plus 15 mg of paracetamol per kg of body weight. The goal was to find the best and safest ways for these options to reduce stress during laryngoscopy and intubation.

Materials and Methods: The anesthesiology department and the general surgery department at the medical college and hospital that is connected to it worked together on the study. The study included a total of 120 patients, covering a wide age range from 20 to 70 years, and including both males and females. The patients had physical statuses I and II, indicating their overall health. In Group A, patients were given a pre-medication of 0.02 mg/kg of glycopyrrolate and then 2 mg/kg of fentanyl through an intravenous (IV) 90 s before they were intubated. Fentanyl at a dose of 2 mcg/kg was given to patients in Group B 90 s before they were intubated. A dose of 15 mg/kg of paracetamol was also given 10 min before the operation. As a starting point, the medical team wrote down the patient’s heart rate (HR), systolic and diastolic blood pressures, and mean artery pressure before they started intubation.

Results: Large rise in HR was seen in Group A, while Group B’s HR stayed close to the baseline. There was a clear rise in mean blood pressure in both groups after intubation. Group A, on the other hand, saw a rise that was clear and lasted for 6 min, while Group B did not. When compared to IV fentanyl alone, IV fentanyl and paracetamol work better at lowering the changes in blood flow that happen during laryngoscopy and airway intubation.

Conclusion: This finding highlights the potential benefits of combining these two medications for improved patient outcomes. Endotracheal intubation, fentanyl, paracetamol, and laryngoscopy are all important medical terms that are commonly used in health-care settings. These procedures and medications play a crucial role in various medical interventions and treatments. Understanding the significance and proper usage of these terms is essential for health-care professionals to provide effective care to their patients.
Application of augmented reality technology in education in Vietnam: Current situation and solutions
Authors: Quang Nguyen Vinh , Kien Nguyen Hoang , Giang Cao Thi Van , Khanh Ngo Gia
Published: April 2024

Augmented Reality (AR) technology has significant potential and advantages for the teaching and learning process due to its interactive and immersive nature. Within the scope of this topic, the research group focuses on investigating the trends of using augmented reality technology in education to determine the extent and scope of its utilization in teaching at primary and secondary schools in Vietnam. Additionally, the group proposes solutions and directions for development to apply AR in education. The study employs qualitative and quantitative analysis methods, including surveying 678 students and 328 lecturers and teachers from secondary, high school and tertiary institutions nationwide. The survey results indicate that the use of AR technology in Vietnam's primary and secondary education system is still quite limited and not widely implemented, as traditional teaching methods remain predominant. However, considering the potential and benefits that AR technology brings, its application in education can open up a new and promising future for education.
LICITAÇÃO PÚBLICA:UMA ANÁLISE DAS LACUNAS NA LITERATURA E SUA RELEVÂNCIA TEÓRICA E PRÁTICA
Authors: Oliveira Rosimeire Alves de , Sá Rubens de Oliveira , Barbosa Sandra Carla Pereira
Published: April 2024

O estudo das licitações públicas é de extrema relevância tanto teórica quanto prática, dada a importância das contratações governamentais para a economia e para a sociedade como um todo. No entanto, apesar da sua importância, existem lacunas na literatura acadêmica sobre o tema, tanto em termos de abordagens teóricas quanto de análises práticas. Do ponto de vista teórico, as lacunas na literatura podem incluir uma falta de consenso sobre definições e conceitos-chave relacionados às licitações públicas, bem como uma limitada compreensão dos mecanismos subjacentes aos processos licitatórios. Em termos de análises práticas, as lacunas na literatura podem incluir uma falta de estudos empíricos que examinem o funcionamento real dos processos licitatórios, bem como uma escassez de pesquisas que avaliem a eficácia e eficiência das políticas e práticas relacionadas às contratações governamentais. Portanto, é crucial preencher essas lacunas na literatura para promover uma compreensão mais completa e aprofundada das licitações públicas e para informar a formulação de políticas e práticas mais eficazes nessa área. Isso pode envolver a realização de estudos empíricos, o desenvolvimento de teorias mais robustas e a realização de análises comparativas entre diferentes contextos e países. Ao fazer isso, os pesquisadores podem contribuir para melhorar a transparência, a eficiência e a integridade dos processos licitatórios, promovendo assim o desenvolvimento econômico e social de forma mais ampla.
Perbandingan Tingkat Penerimaan Pajak Hotel Dan Pendapatan Asli Daerah (PAD) Di Daerah Kota Malang
Authors: Safitri Dewi , Nabilqodarsa Merindah Dwi
Published: April 2024

Regional Original Income (PAD) is often used as a comparison material between districts/cities in Indonesia. Not only the amount, but also the composition of the amount of regional income apart from balancing funds and other legal regional income is interesting to consider.studied. Generally, PAD revenues are dominated by local taxes. Unfortunately, the types of local taxes are too rigid, making it difficult for districts/cities to innovate in order to increase PAD. To increase PAD, the first step that is needed is to analyze the potential of each region. By using documentsthe output of the Malang City Government between 2018-2022 which is analyzed quantitatively, this paper finds the results that economic development has changed the regional potential. Hotel taxes are a source of income that has high potential as a source of income for the people in Malang City as a tourist. This study aims to determine and analyze hotel tax in Malang city based on the number of hotels, the number of hotel occupancy rates, and the number of tourists on hotel tax revenue in Malang city for the period 2018 – 2022. The method used in this research is descriptive analysis and multiple linear regression analysis. Descriptive analysis is to describe the picture research data consisting of the number of hotels, the number of hotel occupancy rates, and the number of tourists in Malang City from 2018-2022. Meanwhile, multiple linear analysis serves to prove the hypothesis of the effect of the number of hotels, the number hotel occupancy rate, and the number of tourists to hotel tax revenue in Malang City. The results of this study indicate that the number of hotels, the number of tourists and occupancy rates have a significant effect on hotel tax receipts
Hybrid Deep Learning Approach to Emotion-Infused Music Recommendation
Authors:   B.Tech. student, Dept. of CSE Institute of Aeronautical Engineering Hyderabad, India, Rao Dr.C..Madhusudhana
Published: April 2024

Music holds a crucial place in our daily lives, uplifting our spirits and contributing to our overall well-being. However, not all musical genres are suitable for every emotional state, and the vast digital music repositories make it challenging to pinpoint the perfect tune for a specific mood. With the ever-expanding song options, individuals often face confusion when selecting tracks. To address this, a context-aware music recommendation system is introduced, designed to recognize users' current emotions and suggest music that aligns with those feelings. This system takes a comprehensive approach, integrating both context and emotion elements to enhance user preference prediction. The overarching goal is to simplify the music selection process, providing users with a more seamless, intuitive, and enjoyable listening experience. The forthcoming evaluation will delve into performance metrics and research findings, contributing to the ongoing refinement and optimization of this context-sensitive music recommendation strategy. Keywords: Emotion Detection, CNN(Convolutional Neural Network),Video and audio music recommendation
PLANT LEAF DISEASE DETECTION
Authors:   Department of Information Technology VPPCOE&VA, University of Mumbai, Tharkar Rushikesh
Published: April 2024

Plant diseases affect the growth of their respective species, therefore their early identification is very important. Many Machine Learning (ML) models have been employed for the detection and classification of plant diseases but, after the advancements in a subset of ML, that is, Deep Learning (DL), this area of research appears to have great potential in terms of increased accuracy. Many developed/modified DL architectures are implemented along with several visualization techniques to detect and classify the symptoms of plant diseases. Moreover, several performance metrics are used for the evaluation of these architectures/techniques. This review provides a comprehensive explanation of DL models used to visualize various plant diseases. In addition, some research gaps are identified from which to obtain greater transparency for detecting diseases in plants, even before their symptoms appear clearly Keywords: Plant leaf disease detection, leaf disease detection, convolutional neural network, deep learning
Home Automation System Using ESP8266 and Blynk Mobile App
Authors:   Assistant Professor, Department of Electrical Engineering, Bharati Vidyapeeth (Deemed to be University) College of  Engineering, Pune, Ambekar Prof. Rupali
Published: April 2024

The emergence of Internet of Things (IoT) technology has revolutionized various aspects of our lives, including home automation. This abstract introduces a home automation system based on the ESP8266 microcontroller, a versatile and cost-effective solution for IoT projects. The proposed system aims to provide homeowners with remote control and monitoring capabilities over various home appliances and devices through a user-friendly interface. The core components of the system include the ESP8266 microcontroller, which serves as the central processing unit, and sensors/actuators for interaction with the physical environment. The system utilizes Wi-Fi connectivity to establish communication between the ESP8266 module and a designated mobile application or web interface, enabling users to remotely monitor and control connected devices from anywhere with internet access. Keywords: Home-Automation, Energy Efficient, Blynk IOT Platform.
AgroGenius: Advanced Crop Recommendation System using Machine Learning Techniques
Authors:   Associate Professor, Computer Engineering, NHITM, S Dr.. Brinthakumari
Published: April 2024

The agricultural sector faces the pressing challenge of optimizing crop selection to ensure sustainable yield amidst dynamic environmental conditions and evolving market demands. To address this challenge, This paper presents a Crop Recommendation System (CRS) designed to assist farmers in optimizing crop selection. Utilizing machine learning, historical data, soil analysis, weather patterns, and market trends, CRS delivers personalized recommendations. Through user-friendly interfaces accessible via web or mobile platforms, farmers input site-specific information to receive real-time tailored suggestions. Field trials demonstrate CRS's efficacy in enhancing productivity, resource utilization, and sustainability. This system represents a significant advancement in agricultural technology, facilitating informed decision-making and resilience in farming practices. Key Words: Crop recommendation, machine learning, soil, weather, farmer, agriculture, KNN
The AI Revolution: How Artificial Intelligence is Reshaping Marketing Strategies
Authors:   School Of Business, GALGOTIAS  University, Greater Noida, SINGH, ABHINAV
Published: April 2024

This paper explores the transformative impact of Artificial Intelligence (AI) on modern marketing practices. It examines how AI applications are revolutionizing various aspects of marketing, including customer experience, campaign personalization, content creation, and market research. The paper analyzes real- world examples and data to showcase the effectiveness of AI implementation. It also discusses potential challenges and ethical considerations surrounding AI in marketing. Finally, the paper explores the future potential of AI and its role in shaping the marketing landscape of tomorrow.
TRENDS AND PATTERNS IN DIGITAL PAYMENT SYSTEM RESEARCH: A BIBLIOMETRIC OVERVIEW FROM SCOPUS DATABASE
Authors:   DEPARTMENT OF COMMERCE  GURU GHASIDAS VISHWAVIDYALAYA, Venkatraman Prof. Bhuvana
Published: April 2024

In the contemporary technological landscape, digital payment systems have been instrumental in transforming traditional payment methodologies. Globally, with a focus on countries like India, most nations are actively incorporating digital payment systems into their economic frameworks. Given the widespread acceptance and diverse dimensions of digital payment systems, numerous academicians have enriched this field through a variety of research papers, articles, and other form of publications. This research utilizes the SCOPUS database to conduct a bibliometric analysis of publications related to keyword “digital payment system”. The aim of this paper is to achieve a more comprehensive insight into the current trends and patterns in research in this field. The analysis reveals important aspects such as key terms, authors, and collaborative networks present in literature concerning digital payment systems. The results enhance the overall understanding of the academic landscape concerning digital payment systems, providing valuable insights into the evolving trends and patterns influencing research in this area. Key Words: Author, Bibliometric Analysis, Digital Payment System, Publication, SCP, MCP.
Effective Traffic Signal Control System Using Deep Learning
Authors:   ECE, RVRJCCE, INDIA, Sk . Sadik
Published: April 2024

Traffic congestion is becoming a serious problem with a large number of vehicles on the roads. The present traffic system is a timer-based system that operates irrespective of the amount of traffic if there exists an ambulance. So, this Deep Learning project is designed in such a way that the traffic control system is based on vehicle density in a lane and also detecting the ambulance’s lane and let that particular lane pass considering as a first priority. In fact, we use computer vision to have the characteristics of the competing traffic rows at the signals. This is done by a object detection model based on a Deep Learning model called You Only Look Once (YOLO)v8. Then traffic signal phases are optimized according to collected data, mainly queue density and waiting time per vehicle, to enable as much as more vehicles to pass safely with minimum waiting time. Keywords— Object detection, ambulance, YOLOv8, Deep learning
Android Legal Assistance Application: Bridging the Gap in Legal Access
Authors:   Computer Engineering, Sinhgad Institute of Technology and Science, Narhe, Chaware Prasad
Published: April 2024

The Android Legal Assistance Application represents a significant stride towards democratizing access to legal services through technological innovation. In this paper, we provide a thorough analysis of the application’s function- alities, algorithms, and impact. By leveraging the ubiquity of smartphones and advanced algorithms, our application aims to bridge the gap between individuals and legal resources, empowering users to navigate complex legal land- scapes effectively. Through a comprehensive examination, we elucidate how the application addresses the persistent challenge of unequal access to legal resources, particularly for marginalized communities. By providing tailored legal assistance, recommendations, and access to a vast repository of legal documents, our application strives to promote justice and equality. We delve into the core features of the application, including its legal assistance feature, lawyer recommendation system, and extensive legal document library. Moreover, we discuss the system architecture, tools, and technologies employed in the development process. Through advanced algorithms in natural language processing (NLP) and document analysis, our application delivers accurate and contextually appropriate legal guidance to users. We also present empirical results indicating improved accessibility, enhanced user experience, and positive user feed- back. Finally, we outline future prospects for the application, emphasizing the integration of additional legal services, implementation of robust security measures, and refinement of algorithms. Overall, the Android Legal Assistance Application signifies a paradigm shift in legal access, paving the way for a more inclusive and equitable society.
MINUTIA EXTRACTOR AND MINUTIA MATCHER BASED FINGER PRINT RECOGNITION USING DIGITAL IMAGE PROCESSING
Authors:   Research Scholar, Department of Electrical Engineering, JCDMCOE, Sirsa, India, Mahboob Ferheen
Published: April 2024

The MATLAB code presents a user-friendly graphical interface for fingerprint recognition and verification. Through this interface, users can load fingerprint images and execute a series of image processing tasks aimed at enhancing image quality and extracting crucial features. Operations such as histogram equalization, FFT enhancement, binarization, and thinning are available to optimize the fingerprint images for analysis. The system facilitates minutia extraction, identifying significant points like ridge endings and bifurcations, which are fundamental for fingerprint matching. Moreover, it includes functionalities for removing spurious minutiae, thereby improving the accuracy of the recognition process. Users can save and load fingerprint templates, streamlining the storage and retrieval of extracted features for matching purposes. Additionally, the system supports fingerprint matching, allowing users to compare templates and determine their similarity or match percentage. This versatile tool finds applications in biometric authentication systems, forensic analysis, and security domains, where robust fingerprint recognition and verification are imperative. Overall, the MATLAB code provides a comprehensive framework encapsulated within a user-friendly interface, offering researchers and practitioners a valuable resource for fingerprint analysis and biometric authentication. Keywords : Fingerprint recognition, GUI (Graphical User Interface), Security systems, Access control, Forensic analysis, User-friendly
PHISHNET: Multi-Algorithmic Safety Net for Advanced Phishing URL Detection
Authors:   Assistant Professor, Visvesvaraya Technological University, Computer Science, SJB Institute of Technology,    Bangalore, Karnataka, India, M Mrs Anusha
Published: April 2024

Today's generation heavily relies on web technology for various tasks such as banking and communication. However, this also means that users are exposed to numerous security threats, with phishing being one of the most serious and common attacks. Phishing attacks aim to steal sensitive information from users by impersonating a legitimate entity. Attackers use phishing to obtain victims' credentials such as bank account numbers, passwords, or other private information. The victim may not be aware of the website that is phishing. which impersonates a genuine website. Therefore, this paper proposes a system to identify phishing sites using machine learning algorithms. The system utilizes a classifier that is trained on a comprehensive dataset with enriched features. Keywords: Phishing URL Detection, Machine Learning, Websites
Exploring Household Composting as an Effective Solution for Urban Waste Management
Authors:   Dept. of Civil Engineering, VIIT, Pune, Maharashtra, India, Tanawade Dr. Archana
Published: April 2024

Organic wastes are generated from many sources’ compiles, solid waste, food, kitchens wastes, etc. Disposal of solid waste is stinging and widespread problem in both urban and rural areas in many developed and developing countries. Collection and disposal of solid waste is one of the major problems of urban environment in most countries worldwide today. Improper Solid Waste Management causes many environmental problems. Traditional composting methods have been common practices in many rural/sub urban areas and requires more time for complete degradation. Traditional method requires large sites for disposal, which nowadays is not possible, as limited spaces are available in the cities. So, here comes the need to find new techniques such as Home Composting. The research focuses on understanding the effectiveness of household composting as a waste management technique for household garbage. Household composting is an attractive method in which small bins can be used as an alternative to composting sites to a small scale. This technique helps to decompose the organic matter in lesser time than the traditional methods. Addition of compost accelerators in the bins increases the decomposition rate. Simply by home composting, the quantity of waste can be reduced. Key Words: Solid Waste Management, Composting, Compost Accelerators, Home Composting, Household Garbage
Experimental Study on Compressive Strength of the Cement Mortar Cubes with Partial Replacement of Fine Aggregate Using Polyvinyl Chloride (PVC) Plastic
Authors:   M.Tech, Assistant Professor, Department of Civil Engineering,  Sanketika Vidya Parishad Engineering College(SVPEC), .K.M Ms.Jayakumari
Published: April 2024

Mortar is a material that consists of cement and sand with a range of applications in the construction industry. However, the plain mortar materials are usually brittle and often crack and fail more suddenly than reinforced mortar. This experimental study is about the compressive strength of cement mortar stabilised with the use of the polyvinyl chloride (PVC) plastic powder. Generally the compressive strength of cement mortar of mix proportion (1:3) is 33 N/mm² to 53 N/mm² has been obtained after 28 days curing. The cement mortar ratio is 1: 3 respectively. The PVC powder is added along with the sand with percentages of 0%, 2.5%, 5%, 7.5%, 10% respectively. And the water cement ratio is 0.5 with volume. The moulds of 70×70×70 mm size were used for the cube test, and the cubes were tested on the Compressive testing machine to determine the strength of cube for 3, 7, 28 days of time period respectively. The main aim of f this study to determine the compressive strength of cement mortar (1:3) of sand added with PVC powder, Key Words:- Waste Plastic, Polyvinyl Chloride, Compressive Strength, Mortar.
Agriculture eCommerce Website with ML Chatbot
Authors:   Department of Computer Science & Engineering, Raghu Engineering College, Visakhapatnam,India, P Sowjanya
Published: April 2024

The project aims to develop an innovative Agriculture eCommerce platform integrated with a Machine Learning (ML) chatbot to revolutionize the agricultural industry's online marketplace. The proposed system addresses the growing need for efficient access to agricultural products and services while enhancing user engagement through intelligent conversational interfaces. The Agriculture eCommerce site serves as a digital marketplace where farmers, agricultural professionals, and enthusiasts can browse, purchase, and interact with a wide range of agricultural products, equipment, and services. Leveraging ML algorithms, the platform's chatbot offers intuitive conversational interactions, allowing users to inquire about products, receive recommendations, and troubleshoot queries effectively. Through this project, B.Tech students will gain valuable experience in developing a comprehensive eCommerce solution integrated with cutting-edge ML technology. Additionally, the project holds the potential to make a significant impact on the agricultural sector by fostering digital transformation and facilitating access to agricultural resources. Keywords: - Agricultural industry, eCommerce, Machine Learning, Digital experience, User-friendly platform, Chatbot, Farming community.
Real-Time Twitter Trends Analysis Using Latent Dirichlet Allocation and Machine Learning
Authors:   Department of Computer Science And  Engineering  Sharda University, Greater Noida, Kumar Sandeep
Published: April 2024

In today’s world of growing social media usage twitter has become an enormous source of data from public in form of tweets. These tweets can be collect and useful to extract effective meaningful insights ex, public sentiments, choices and opinions about a particular event, product or person, which can prove helpful for business growth, political parties and celebrities to know public choices, sentiments and their reviews over a particular product , person or government decision. But before performing sentiment analysis on tweets data we need to clean and per-process it as tweets data is highly unstructured and noisy for that many methods are there:-data per-processing, stop-words removal, stemming, lemmatization etc. After data cleaning effective meaningful insights can be extracted and sentiment analysis can be performed to extract public opinions and their choices. Twitter data possesses significant power in capturing timely public opinions on a variety of topics, such as preferences for products, political tendencies, and sentiments within the business realm. The extensive user base of this platform provides a wide array of viewpoints, rendering it a valuable resource for comprehending consumer behaviour, political developments, and market outlooks. By employing sentiment analysis, organizations can measure levels of customer contentment, policymakers can evaluate public reception, and corporations can monitor how their brands are perceived to make well-informed decisions. The real-time aspect and high level of user involvement associated with Twitter data render it priceless for shaping strategies related to product innovation, political campaigns, and business expansion efforts. This research paper highlights the power of power BI tool in data visualization of real-time tweets of a user twitter account and builds effective dashboards and also perform sentiment analysis of real-time tweets. Keywords: LDA, Machine Learning, Topic Modelling, Sentiment Analysis, NLP, Social Media.
FAKE PRODUCT DETECTION USING BLOCKCHAIN TECHNOLOGY
Authors:   Student Department Computer Science and Engineering, Angel College Of Engineering and Technology, Tiruppur, TamilNadu, India, V AathishNithin.
Published: April 2024

End consumers face threats to their finances, health, and safety when counterfeit or duplicate goods are manufactured and marketed. Through revenue loss, product defamation, downtime, replacement costs, causing brands to spend money battling counterfeits, compromising partner trust, stealing sales, etc., it also has an adverse effect on the economic growth of original manufacturers and businesses. A block chain-based system that uses barcodes and QR codes to authenticate objects is suggested as a solution to this problem, enhancing security with the SHA-256 algorithm. This technology makes use of a camera scanner to confirm the product's unique code that is kept on an impenetrable block chain, guaranteeing the legitimacy of every item thanks to the cryptographic strength of SHA-256. The consumer is notified if a product's code matches the block chain record after it is scanned; if there are any differences, the manufacturer and the customer are notified about the product's counterfeit status. By giving consumers direct verification capabilities and protecting producers' interests with an opaque, safe, and secure verification system against counterfeit goods, this strategy drastically lowers reliance on merchant promises. Keywords: Block chain, smart contracts, QR (Quick Response) code, anti- counterfeit.
Traffix : Efficient Traffic Control using IoT
Authors:   Student Department Computer Science and Engineering, Angel College Of Engineering and Technology, Tiruppur, TamilNadu, India, Amin Reuel
Published: April 2024

This paper aims to alleviate traffic congestion brought on by antiquated, ineffective traffic management systems that are based on a predefined countdown. Long red light delays are the result of these traditional systems, which have a predefined countdown regardless of the actual traffic on a given road. Our system makes sure that time set for the traffic lights reflects the traffic density in real time, which ensures efficient use of time. In order to do this, we first compute the traffic density, which is ascertained by combining image processing methods along with the use of ultrasonic sensors. The Raspberry Pi then processes this data and then manages the time set for the traffic light. Furthermore, the use of SQL Alchemy ensures that this processed information is stored to the cloud, where it may be utilized in events of sensor failure or system malfunction. Index Terms—Image Processing, Raspberry Pi, Traffic Congestion, Ultrasonic sensors
Earthquake Detection and Alerting system using ANN and IOT
Authors:   Students of the Department of Electronics and Communication Engineering, R.V.R & J.C College of Engineering, K Chethan
Published: April 2024

Earthquakes are one of the deadliest natural disasters. The damage caused by earthquakes is very destructive and the number of deaths are at a very large scale. The National Earthquake Information Centre now detects about 20,000 earthquakes around the globe each year, or approximately 55 per day. Many of the Earth’s earthquake zones coincide with areas of high population density. When a large earthquake occurs in such areas, the results can be catastrophic. The basic parameter to determine an earthquake before it was going to occur is the p wave or primary shock wave which is not destructive to infrastructure because it travels parallel to the propagation of seismic wave. A series of destructive waves that follows p waves are s waves or secondary waves which has a speed of about 60% that of p waves. The movement of the s wave is perpendicular to the direction of propagation of the seismic wave and hence it is extremely risky to infrastructures and cause a lot of damage. This research aims to build an earthquake detection and alerting system using a low-cost accelerometer, ESP32 Wi-Fi module, and ANN algorithm. The input earthquake data is taken by the accelerometer and with the help of the ESP32 Wi-Fi module the data is sent to a system that processes the ANN algorithm with Multi layered perceptron trained with stochastic gradient descent learning algorithm and detects whether an earthquake is going to occur or not and alerts users with ESP32 Wi-Fi module. Key Words: Artificial Neural Networks, ESP32, Accelerometer, Earthquake, Multi-layer perceptron, Sigmoid function, Stochastic Gradient Descent.
BudgetBliss: Predictive Budget Planning using Neural Networks and Socioeconomic Factors
Authors:   Artificial Intelligence &  Data Science  Shah & Anchor Kutchhi Engineering College Mumbai, India, Phadale, Kapil Sanjay
Published: April 2024

BudgetBliss is a transformative web application developed to revolutionize personal finance management through the integration of Artificial Neural Networks. Leveraging a sophisticated architecture, BudgetBliss provides users with a comprehensive platform to effectively plan and manage their income. The development process involved meticulous data collection and preprocessing, followed by the implementation of an Artificial Neural Network model. By analyzing users' spending habits and categorizing income, BudgetBliss offers detailed financial breakdowns tailored to individual needs. This methodology ensures the accuracy and relevance of the insights provided to users. Furthermore, BudgetBliss serves as an inadvertent educational tool, fostering financial literacy as users gain insights into their spending habits and make informed decisions about their money. Additionally, the automation of categorization, analysis of spending habits, and provision of personalized insights significantly reduce financial stress, empowering users to feel in control of their finances and focus on achieving their goals with confidence. In today's fast-paced society, where financial management significantly impacts overall well-being, BudgetBliss addresses the critical need for a system that enhances household financial control. By enabling users to make informed decisions and gain a deeper understanding of their financial landscape, BudgetBliss facilitates a path towards contentment and fulfillment in life. Keywords - Budget planning, Personal finance, Artificial Neural Networks, Financial management, Well-being
ENVIRONMENT DOCTOR SYSTEM
Authors:   IT Department & Mahatma Gandhi Institute of Technology, B Lokesh
Published: April 2024

The degradation of water resources , soil and air pollution has become a common problem. It is necessary to monitor air quality and water quality and keep it under control for a better future and healthy living for all. System uses air sensors to sense presence of harmful gases/compounds in the air and constantly transmit this data to microcontroller. System keeps measuring the parameters of water, such as temperature PH value, turbidity, flow and reports it to the online server over IOT. Also, System also measures the parameters like Soil Moisture , pH, Temperature and Humidity . This system collects data about the air , water and soil quality and determines its purity. It will send us the data about quality from a wireless network. This data will be received by a machine and it will send this data to the server. Next, the data on the server can be displayed to various clients.
THE IMPACT OF ONLINE ADVERTISING ON THE BUYING BEHAVIOR OF CONSUMERS
Authors:   School of Business,  Galgotias University, Y Purushottam,
Published: April 2024

The present research report delves into assessing the influence of online advertising on consumer buying behavior, particularly how it enhances consumer intentions toward products and their purchasing behaviors. The study highlights that consumer purchasing behavior is significantly affected by the image of the product portrayed by advertisers. Conducted in March 2024 in Gautam Budha Nagar, Uttar Pradesh, the research gathered primary data through questionnaires, while secondary data were obtained from the internet. The sample consisted of 50 respondents, comprising individuals from various backgrounds Random sampling method was employed for selecting the participants. As technology advances, marketers increasingly utilize online platforms like websites, blogs, and advertising campaigns to enhance brand visibility. In India, online advertising grows by 25–30% annually, fueled by the country's status as home to the world's largest Facebook population. Rapid digitization has expanded the use of online marketing through various online channels and networking methods, allowing businesses to connect with audiences effectively. India also has the World’s largest Facebook population. The use of online marketing has widened as a result of quick digitization, through websites, networking methods, etc. Internet usage is commonplace. The findings of the research emphasize that online advertising consistently exerts a substantial impact on consumer purchasing trends and behaviors. Additionally, the report underscores the significance of return on investment (ROI) and product quality in influencing consumer buying behavior. Furthermore, the study acknowledges that online celebrity endorsements also play a role, albeit to a lesser extent, in shaping purchasing behavior. Keywords: - Online advertising, Digital Marketing, Customer behaviour, Customer segmentation
Detecting Diabetic Retinopathy using Mobile Net
Authors:   dept of Electronics and Communication Engineering RVR & JC College Of Engineering, Guntur, Sireesha Palagiri
Published: April 2024

Diabetic retinopathy (DR) is a prevalent complication of diabetes mellitus that can lead to This paper presents a novel machine learning approach using TensorFlow for the automated detection and stage classification of diabetic retinopathy from retinal images. The study utilizes a comprehensive dataset of retinal images, which undergo preprocessing steps to enhance image quality and prepare them for analysis. A deep learning model based on convolutional neural networks (CNNs) is developed using TensorFlow, leveraging its efficient computational capabilities and optimization tools. The proposed model using Mobile Net is trained and validated on the retinal image dataset to classify diabetic retinopathy into different stages, ranging from mild to severe. Keywords— Deep Learning, Mobile Net, Diabetic Retinopathy (DR) , Dataset
FACE DETECTION SYSTEM USING CONVOLUTIONAL NEURAL NETWORKS: A REVIEW
Authors:   “Department of Computer Science”  Sipna College of Engineering and Technology Amravati Maharashtra, Desai, Mr. Jai
Published: April 2024

Implementing a facial recognition system can help in identifying or verifying the identity of a person from a digital image. Accurate attendance records are critical to classroom assessment. However, manual attendance tracking can lead to errors, missed students, or duplicate records. The facial recognition attendance system includes facial recognition technology that recognizes and verifies an employee's facial features and automatically records attendance. The facial liveliness detection part is based on CNN, which creates a 3D model of the detected face to distinguish between real and fake images. The attendance system is written in Python and the user interface is designed using the WebView library. The main goal of facial recognition is to identify individuals, either individually or collectively. The number of positive faces may vary depending on the technology used for face recognition. Keywords: Face Recognition Attendance System, CNN Algorithm.
VIDEO MANAGEMENT SYSTEM
Authors:   Computer engineering, Bharat college of Engineering, Waidande Megha
Published: April 2024

Video footage from many cameras can be managed, recorded, stored, and retrieved in real-time with the use of software solutions known as video management systems (VMS). They are extensively utilized for security and monitoring purposes in a variety of industries, including retail, transportation, healthcare, and education. Users of the system can record video, watch live feeds, and examine previously recorded video for analytical or security reasons. Commercial “security systems” are frequently created as a careless monitoring system to recording quality. In such a system, locating and Exporting pertinent video can be difficult and frequently requires extensive human intervention. VMS was intended to deliver the highest level of record quality while allowing easy searching, filtering and exporting of security footage. Keywords : security system, video