This document describes a proposed chatbot system for a college that would answer students' questions. It would use natural language understanding and machine learning to analyze student queries and provide responses. The system would have a user-friendly interface so students can ask questions without needing to visit the college in-person. It would aim to respond similarly to how a human would, drawing from a knowledge base of questions and answers. The document outlines the system architecture and methodology, which involves greeting the user, analyzing queries using machine learning, and providing a relevant response from the knowledge base. It aims to develop an accurate question-answering chatbot to help students remotely.
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This document discusses the development of a healthcare chatbot using machine learning. Key points:
1. The chatbot will use machine learning algorithms to understand patient symptoms from conversations in their native language and provide medical advice and health monitoring.
2. Deep learning models like BERT and SQLOVA will be used to train the chatbot's data collection and natural language processing abilities.
3. The proposed system aims to address issues with current healthcare platforms like long wait times for responses from doctors by providing timely answers to common patient questions through the chatbot.
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The document summarizes a research project that aims to develop a banking chatbot using natural language processing (NLP) and machine learning algorithms. The chatbot will be trained on customer query and response data to understand inquiries about account balances, transaction histories, and other banking information. It will use techniques like support vector machine and Naive Bayes classifiers to accurately respond to customer questions in a conversational manner. The researchers conducted a literature review on existing chatbot systems and their limitations in order to inform the methodology for their project, which is designed to provide more personalized responses and handle complex requests through advanced NLP and ML.
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This document describes the development of an interaction-based expert system for restaurant recommendations. It begins with an abstract describing the system's use of chat-based interaction to provide human-like responses and recommendations based on user preferences like cuisine, location, budget and timing. The introduction provides context on similar systems from companies like Zomato and Swiggy and the goal of this system to automate the ordering process through dialogue. It then covers the system design, methodology, user interface, results and conclusions that an expert system using natural language can successfully replace human agents for common tasks like reservations and orders.
The document describes the design of a chatbot using deep learning. It proposes using a neural network with multiple hidden layers to learn and process data for the chatbot. The chatbot is intended to be trained on any file based on the user's needs, making it generalized. It will also have text-to-speech conversion to make it more user-friendly. The chatbot is evaluated and achieved 98.24% accuracy in responding to questions within its training data.
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This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
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The document proposes the development of an AI chatbot named StudyPal that can serve as a virtual tutor for students. StudyPal would use techniques like active recall and mind mapping to teach students curriculum content for their grade and subject without needing an in-person teacher. The goal is for StudyPal to provide individualized attention to effectively communicate concepts to each student. StudyPal would be created using a federated learning model to maintain data privacy and address issues with internet connectivity. The document outlines the proposed design and development process for StudyPal.
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This document discusses the development of a virtual community system called "Unitalk" using cloud technology. The system would allow a college community to share notices, posts, notes, and ask student queries through a web portal connected to the cloud. It would help the college administrator get information on registered students and faculty. The system also proposes a chatbot for easy access to common questions. The chatbot would allow users to ask questions like they would to a human. The document discusses how cloud computing, community clouds, software as a service, and chatbots could enable this virtual community system.
The document discusses AI-based healthcare chatbots and their advantages and limitations. It provides examples of existing chatbots like Youper, Babylon Health, Woebot, and Safedrugbot that provide various healthcare services like monitoring symptoms of depression/anxiety, providing medical consultations, mental health support, and drug safety information. The key advantages of AI healthcare chatbots are that they can provide 24/7 service, personalized care, have low costs, and quick responses. However, limitations include potential inaccuracies in responses, inability to fully diagnose medical conditions, and lack of human empathy in interactions.
HealthCare ChatBot Using Machine LearningIRJET Journal
This document discusses the development of a healthcare chatbot using machine learning. Key points:
1. The chatbot will use machine learning algorithms to understand patient symptoms from conversations in their native language and provide medical advice and health monitoring.
2. Deep learning models like BERT and SQLOVA will be used to train the chatbot's data collection and natural language processing abilities.
3. The proposed system aims to address issues with current healthcare platforms like long wait times for responses from doctors by providing timely answers to common patient questions through the chatbot.
BANKING CHATBOT USING NLP AND MACHINE LEARNING ALGORITHMSIRJET Journal
The document summarizes a research project that aims to develop a banking chatbot using natural language processing (NLP) and machine learning algorithms. The chatbot will be trained on customer query and response data to understand inquiries about account balances, transaction histories, and other banking information. It will use techniques like support vector machine and Naive Bayes classifiers to accurately respond to customer questions in a conversational manner. The researchers conducted a literature review on existing chatbot systems and their limitations in order to inform the methodology for their project, which is designed to provide more personalized responses and handle complex requests through advanced NLP and ML.
IRJET - Interaction based Expert SystemIRJET Journal
This document describes the development of an interaction-based expert system for restaurant recommendations. It begins with an abstract describing the system's use of chat-based interaction to provide human-like responses and recommendations based on user preferences like cuisine, location, budget and timing. The introduction provides context on similar systems from companies like Zomato and Swiggy and the goal of this system to automate the ordering process through dialogue. It then covers the system design, methodology, user interface, results and conclusions that an expert system using natural language can successfully replace human agents for common tasks like reservations and orders.
The document describes the design of a chatbot using deep learning. It proposes using a neural network with multiple hidden layers to learn and process data for the chatbot. The chatbot is intended to be trained on any file based on the user's needs, making it generalized. It will also have text-to-speech conversion to make it more user-friendly. The chatbot is evaluated and achieved 98.24% accuracy in responding to questions within its training data.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
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The document proposes the development of an AI chatbot named StudyPal that can serve as a virtual tutor for students. StudyPal would use techniques like active recall and mind mapping to teach students curriculum content for their grade and subject without needing an in-person teacher. The goal is for StudyPal to provide individualized attention to effectively communicate concepts to each student. StudyPal would be created using a federated learning model to maintain data privacy and address issues with internet connectivity. The document outlines the proposed design and development process for StudyPal.
IRJET- Virtual Community Using Cloud Technology “Unitalk”IRJET Journal
This document discusses the development of a virtual community system called "Unitalk" using cloud technology. The system would allow a college community to share notices, posts, notes, and ask student queries through a web portal connected to the cloud. It would help the college administrator get information on registered students and faculty. The system also proposes a chatbot for easy access to common questions. The chatbot would allow users to ask questions like they would to a human. The document discusses how cloud computing, community clouds, software as a service, and chatbots could enable this virtual community system.
The document discusses AI-based healthcare chatbots and their advantages and limitations. It provides examples of existing chatbots like Youper, Babylon Health, Woebot, and Safedrugbot that provide various healthcare services like monitoring symptoms of depression/anxiety, providing medical consultations, mental health support, and drug safety information. The key advantages of AI healthcare chatbots are that they can provide 24/7 service, personalized care, have low costs, and quick responses. However, limitations include potential inaccuracies in responses, inability to fully diagnose medical conditions, and lack of human empathy in interactions.
COLLEGE ENQUIRY CHATBOT SYSTEM IN JAVASCRIPTIRJET Journal
This document describes the development of a college inquiry chatbot system using HTML, CSS, and JavaScript. The system provides students with information about admission requirements, courses, tuition fees, and more through a conversational chatbot interface. It was tested with various queries and provided accurate responses. Future work could improve the system with voice recognition and integrating it with the college's database. Overall, the chatbot was well-received by students and chatbots can benefit the education sector by providing timely information to students.
IRJET- Cloud based Chat Bot using IoT and ArduinoIRJET Journal
This document describes a cloud-based chatbot using the Internet of Things (IoT) and Arduino. The chatbot can communicate with users via Bluetooth using a mobile app. It tells users the current temperature and humidity and their distance from the robot. It also indicates new message notifications using sound and light. Users can have basic conversations with the robot and get information about it. The chatbot uses IoT and Android technologies and works within a wireless local area network (WLAN). It provides a low-cost way for businesses to improve customer service and interactions through an automated chatbot system.
Providing highly accurate service recommendation for semantic clustering over...IRJET Journal
This document proposes an adaptive recommendation system to provide accurate service recommendations for semantic clustering over big data. It combines item-based collaborative filtering and content-based filtering techniques to address issues like cold starts, sparsity, and scalability. The system first performs clustering to group similar services and reduce data size. It then uses the collaborative filtering approach of finding similar users to the target user and their item ratings to generate recommendations. The content-based filtering technique considers a user's past ratings to recommend related items. Combining these techniques improves accuracy and performance for big data applications. Evaluation of this adaptive recommendation system shows it can provide highly accurate recommendations and address current limitations.
This document discusses detecting spam comments on YouTube videos using machine learning techniques. It analyzes YouTube comments datasets using logistic regression, AdaBoost, decision trees and random forest algorithms. Neural networks achieved the highest accuracy of 91.65% for spam detection, an improvement of around 18% over existing approaches. The document outlines the methodology, including preprocessing, feature selection and extraction, and model building. It discusses the results and screenshots of a developed system for classifying YouTube comments as spam or not spam. In conclusion, machine learning techniques can effectively detect spam comments, though spammers may adapt over time to evade detection.
Situation Alert and Quality of Service using Collaborative Filtering for Web ...IRJET Journal
This document discusses a proposed location-aware collaborative filtering method for web service recommendation to improve quality of service (QoS) prediction accuracy. Existing QoS prediction methods do not adequately consider the personalized influence of users and services or the locations of users and services. The proposed method leverages both user and service locations when selecting similar neighbors and includes an enhanced similarity measurement that accounts for personalized deviations in user and service QoS. Experimental results on a real-world dataset show the proposed approach significantly outperforms previous collaborative filtering methods in QoS prediction accuracy and computational efficiency.
The document describes a proposed voice recognition-based medical assistant system. It would use artificial intelligence techniques like machine learning and natural language processing to diagnose diseases, provide medical advice to patients, and assist doctors. The system would analyze patient data using machine learning algorithms to predict disease risk. It would include a voice-based conversational agent to answer patient questions and a system for virtual consultations between doctors and patients. The goal is to improve healthcare through more personalized, efficient and accurate diagnosis and treatment using these voice and AI-based technologies.
IRJET- Secure Re-Encrypted PHR Shared to Users Efficiently in Cloud ComputingIRJET Journal
This document proposes a Securely Re-Encrypted PHR Shared to Users Efficiently in Cloud Computing (SeSPHR) system. The SeSPHR system aims to securely store and share patients' Personal Health Records (PHRs) with authorized entities in the cloud while preserving privacy. It encrypts PHRs stored on untrusted cloud servers and only allows verified users access using re-encryption keys from a semi-trusted proxy server. The system enforces patient-centric access management of PHR components based on access levels and supports dynamic addition and removal of authorized users. The operation of SeSPHR was analyzed and verified using High-Level Petri Nets, SMT-Lib and Z3 solver. Performance analysis
IRJET- Shopping Mall Experience using Beacon TechnologyIRJET Journal
The document proposes a system that uses beacon technology to track customers in retail shops and provide personalized discounts based on their shopping patterns. Beacons set up in shops would detect customers' locations via Bluetooth signals from their smartphones. This information would be sent to a server to analyze customers' purchase histories and send personalized offers. The system aims to improve customers' shopping experiences and increase retailers' sales by offering targeted discounts to customers based on their identified preferences and shopping behaviors.
Location Privacy Protection Mechanisms using Order-Retrievable Encryption for...IRJET Journal
1) The document proposes a new encryption scheme called Order-Retrievable Encryption (ORE) to protect user location privacy in location-based social networks.
2) ORE allows users to share their exact locations with friends without leaking location information to outside parties. It also enables efficient location queries with low computational and communication costs.
3) An experimental evaluation shows that the proposed privacy-preserving location sharing system using ORE has much lower computational and communication overhead compared to existing solutions.
IDENTIFYING THE DAMAGE ASSESSMENT TWEETS DURING DISASTERIRJET Journal
The document proposes a novel method for identifying damage assessment tweets during disasters using machine learning techniques. The method utilizes lexical, frequency, and syntactic features specific to damage assessment that are weighted using LSTM and TensorFlow algorithms. A random forest classifier is then used to classify tweets. The method was tested on 14 standard disaster datasets and can be applied when labeled training data is limited or specific to other disaster types through training on past datasets.
This document describes a healthcare chatbot that was developed to provide medical information and diagnoses to users. The chatbot uses natural language processing and machine learning to understand users' symptoms and concerns during a conversation. It can then provide diagnoses, treatment recommendations, and allow users to book appointments with doctors if needed. The chatbot was created using Python programming languages and libraries like Flask and works in multiple languages to be accessible to different users. Its goals are to give users accurate medical advice, help schedule appointments efficiently, and reduce contact with doctors when possible during the COVID-19 pandemic.
A Review on the Determinants of a suitable Chatbot Framework- Empirical evide...IRJET Journal
This document reviews and compares two popular chatbot frameworks: RASA and IBM Watson Assistant. It analyzes 30 publications using a systematic review approach to examine the development methodology and areas for improvement of each framework. An extensive comparative analysis is conducted using evaluation models to analyze the performance of each chatbot. The study concludes by discussing why one framework may be preferred over the other and future aspects of each based on data collected from 50 respondents at two companies that provide chatbot services.
1. Coordination across agencies - As threats evolve, the DHS will need to continue strengthening coordination between its various sub-agencies as well as other federal, state, and local partners.
2. Technology and information sharing - Advances in technology and the ability to share timely intelligence across organizations will be vital. The DHS must adapt to emerging technologies.
3. Addressing new and evolving threats - As threats change, the DHS needs flexibility to take on new responsibilities and tackle threats such as cybersecurity that have become more prominent.
Other issues
This document discusses a product analyst advisor software that uses natural language processing techniques like sentiment analysis to analyze customer reviews and sentiments about products. It extracts reviews from various websites about a product being researched and processes the data to provide useful insights. The insights help users easily select the best available option. The system architecture involves scraping live data from websites, using deep learning algorithms to analyze reviews for sentiments, and displaying product insights. It uses BERT for sentiment analysis and frameworks like Django and ReactJS. Web scraping is used to extract review data for analysis and providing recommendations to users.
Streamlining Home Service Website with Virtual Assistant AIIRJET Journal
This document describes a proposed website and mobile application system for booking home services. The system would allow users to book skilled professionals for various household tasks and repairs. It uses technologies like PHP, Laravel, and Bootstrap to provide a user-friendly interface for customers to find local service providers by location, view their costs, and schedule appointments. The system aims to streamline the home service process through a centralized online platform that connects users and providers in a convenient, transparent, and secure manner. It discusses the roles of administrators, service providers, and customers on the system and how their interactions are managed through the technological components.
Finite State Machine Based Evaluation Model For Web Service Reliability Analysisdannyijwest
Today’s world economy demands that both market access and customer service be available anytime and
anywhere. The Web is the only way to supply global economic needs and, due to expand the development of
comprehensive web service, it does so relatively inexpensively. The ability of web service is to provide a
relatively inexpensive way to deploy customer services. As days goes on the business logic of a system
emerges out at a great extent where it has to react to several different competitors under different
situations. Through means of a business logic system we can able to achieve faster communication of
information, rampant change and increasing business complexity
Evaluation of a Framework for Integrated Web ServicesIRJET Journal
This document proposes and evaluates a framework for integrating web services. It begins by discussing how users appreciate simple, on-demand access to affordable software services without needing to install or update applications themselves. The document then presents an argument for a web-based architecture that allows users to access and purchase a wide range of software applications as needed. It evaluates this framework through user surveys and examples of simulation software services to demonstrate how the integrated framework can be implemented. The surveys found that the framework reduced costs, simplified processes, and improved the user experience by combining various online components and software services.
IRJET - E-Assistant: An Interactive Bot for Banking Sector using NLP ProcessIRJET Journal
This document describes a proposed chatbot called E-Assistant that would be used in the banking sector to help customers complete tasks like opening accounts or applying for loans. It would use natural language processing to understand user queries and respond in text, speech, or visual form. The chatbot's architecture includes modules for context recognition, preprocessing text, intent classification, entity extraction, and context reset. The goal is to provide a helpful and user-friendly assistant to guide customers through banking processes.
This document describes a research project that developed a healthcare chatbot to provide medical information and advice to users from their homes. The chatbot uses machine learning algorithms like decision trees and logistic regression trained on medical datasets. It allows users to describe their symptoms and receives a predicted diagnosis along with the probability and potential future symptoms. For emergencies, it recommends expert doctors. The goal is to enable self-diagnosis and determine if hospital visits are needed, saving time. Evaluation showed the chatbot model achieved 95.52% accuracy in identifying illnesses based on symptom inputs. Future work aims to improve the chatbot and add translation features for wider accessibility.
Employment Performance Management Using Machine LearningIRJET Journal
This document discusses using machine learning techniques to analyze employee performance. Specifically, it proposes using a support vector machine (SVM) algorithm to identify employee performance based on factors like quality, timeliness, and cost. The document reviews related literature on using both traditional and data-driven approaches to performance assessment. It then outlines the proposed system for building a software tool to manage employee performance data using SVM. Key steps in the SVM algorithm are described. The document concludes that improving individual performance can boost business results and SVM is effective for differentiating between two groups of data.
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
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1. Coordination across agencies - As threats evolve, the DHS will need to continue strengthening coordination between its various sub-agencies as well as other federal, state, and local partners.
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This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
Solving Linear Differential Equations with Constant CoefficientsIRJET Journal
1) The document discusses methods for finding the solutions to linear differential equations with constant coefficients. It defines such an equation and explains that the complete solution is the combination of the complementary function (C.F.) and particular integral (P.I.).
2) Various methods are presented for determining the C.F. depending on whether the roots of the auxiliary equation are real, imaginary, repeated, etc.
3) Rules are provided for obtaining the P.I. based on the type of function involved (exponential, trigonometric, power, etc.). Examples are worked through to demonstrate the full solution process.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.