No. |
Title and Author |
Area |
Country |
Page |
1 |
Detection of Road Signs Using Tensor Flow and Neural Networks
-Abas Rasheed Wani ; Heena Arora
Almost all of the jobs we conduct in today's world have been eased by automation. Vehicles frequently disregard signs posted on the side of the road because they only want to concentrate on driving, which is dangerous for both them and other drivers. The driver should be alerted of this concern in a way that doesn't force them to shift their attention away from the road. In this situation, traffic sign detection and recognition (TSDR) is crucial since it warns the driver of impending signals. Because of this, not only are roads safer, but drivers also experience more comfort while navigating unfamiliar or challenging routes. A common problem is the inability to read the sign. With the use of this software, driver assistance systems (ADAS) will make it simpler for drivers to comprehend traffic signals. We offer a method for detecting and identifying traffic signs that uses image processing to find signs and an ensemble of Convolutional Neural Networks (CNNs) to identify signs. CNNs have a high recognition rate, making them suitable for a variety of computer vision applications. CNNTSR (Traffic Sign Recognition), a crucial element of modern driving assistance systems that increases driver comfort and safety, uses TensorFlow. CNNTSR is implemented using TensorFlow (Traffic Sign Recognition). This article looks at a piece of technology that helps drivers read traffic signs and steer clear of collisions. The feature extractor and the classifier are two factors that affect TSR accuracy.. Although there are several methods, the majority of current algorithms do both feature information extraction tasks using CNN (Convolutional Neural Network). We develop the identification of traffic signs using CNN and TensorFlow. 43 different types of traffic signs will be used in the dataset for training the CNN. 95 percent of the results will be accurate. Read More...
|
Computer Science and Engineering |
India |
1-8 |
2 |
Municipal Waste Segregation Using Densenet
-Mir Zahid Mohammad ; Ms Heena Arora
One of the most difficult issues facing contemporary civilization is the correct management of trash. Municipal Solid Waste (MSW) must be divided into many categories, such as bio, plastic, glass, metal, and paper. The most effective methods up to this point have been neural networks. The present deep learning methods that have been suggested to categorize garbage have been thoroughly summarized in this paper. This article suggests a system for dividing litter into the six categories listed in the benchmark techniques. Convolution neural network was the categorization architecture. These models, which Google has suggested, are based on compound scaling, have an accuracy range of 74% to 84 %, and they have been pretrained on the model. For effective categorization, this study suggests Densenet 201 model adjustment for pictures relevant to particular demographic regions. This kind of model tuning through transfer learning offers a unique classification model that is highly tuned for a specific area. Furthermore, through fine-tuning over region-specific litter photos, it led to improvised classifications. Read More...
|
Computer Science and Engineering |
India |
9-14 |
3 |
Relative Analysis of RC Structures With & Without Base Isolation System for Varied Soil Strata Using SSI Effect
-Shivnarayan Porwal ; Sumit Pahwa; Murtaza Safdari
The structural response is highly influenced by Soil Structure Interaction (SSI) under the effect of seismic forces. In this study the response of the structure with varied conditional parameters of soil flexibility have been studied and the behaviour of the structure under these conditions been identified. Different conditions are considered for the analysis; one is substituting support condition at base by spring of equivalent stiffness parameter for different types of soil considered and second by considering the base isolation system under same effect. For SSI study, types of soil which are considered conventionally are Hard, Medium and Soft Soil. The purpose of this study is to carried out the structural response under severe conditions and find its usability under it. Symmetric space frames resting on isolated footing of configurations 5 bays in x and y direction with G+ 5 storeys is considered with fixed base and flexible base with and without different types of base isolator. The spring model is developed by using stiffness equation along all 6 DOF and elastic continuum model is developed by Finite Element Method using Etabs V18. The RSA is carried out in this study as per IS 1893:2016. For more accuracy in results, the additions of base isolation system is also introduced for severe seismic zone which helps to identify the behaviour of the structure in such conditions using lateral load resisting system. The influence of SSI & base isolation system on various structural parameters i.e. natural time period, base shear, roof displacement, drift and overturning moment are presented. The study reveals that the SSI with the base isolation system significantly effects on the response of the structure. Read More...
|
Structural Engineering |
India |
15-21 |
4 |
Comparative Analysis of RC Structures with The Influence of Infill Walls Using Equivalent Strut Approach
-Gaurav Shrivaiya ; Sumit Pahwa; Murtaza Safdari
RC Buildings are very conventional type of construction in India. While analysing & designing the structure, we only consider structural members like slabs, beams, columns, and footings which carries the load and transfer it to another respectively, while walls are not considered under the design criteria and also their impact on the structural response is neglected. In terms of loading only, the effect of walls is considered. But their influence on RC Structural Frames are shown in their global behaviour when subjected to lateral forces. So it is very vital to study its behaviour on RC frames under severe seismic conditions. The presence of infill walls, results in rise in the structural stiffness; also surges natural frequency of vibration which depends on seismic spectrum. In addition to that, it also reduces the storey drift demands & displacements and increases the storey lateral stiffness when it is subjected to lateral loading. In this study a RSA approach is adopted for RC frames with the help of FEM software. The main purpose of this study contains the effect of varying properties of infill wall using different patterns on RC framed structure under lateral load. The FEM model of infill wall was done in Etabs using equivalent strut method. The main objective of this paper is to recognize the performance of the building with varying infill parameters considered like percentage of openings considered, construction material used for infill walls and the performance of such buildings are compared with buildings without infill in zone V as per Indian Standards. In this study, a G+10 RC building is considered with the square plan area of 400 m2. The main parameters are focused in this study have been done on time period, mass participation, storey drifts, storey displacement & base shear and on its basis the performance can be evaluated. Read More...
|
Structural Engineering |
India |
22-29 |
5 |
Fast Fashion vs. Sustainable Fashion: An Economic Textual Analysis
-Samaira Gupta
This paper explores the economic implications of fast fashion versus sustainable fashion by examining secondary data sources, including academic studies, industry reports, and news articles. Fast fashion is characterized by rapid production cycles, low costs, and affordability, appealing particularly to younger consumers. However, this model contributes to significant environmental degradation and labor exploitation. Sustainable fashion, by contrast, emphasizes environmental preservation, ethical labor practices, and long-term economic sustainability, yet faces challenges in scaling due to higher production costs. Through comparative analysis, this paper aims to identify the economic trade-offs and societal impacts associated with both fast and sustainable fashion. Findings suggest that while fast fashion offers immediate economic benefits, sustainable fashion provides a viable long-term alternative with potential environmental and social advantages. The paper concludes with policy recommendations to balance economic growth with environmental responsibility in the fashion industry. Read More...
|
Economics |
India |
30-32 |
6 |
Analysis Over the Technique to Improve the Mechanical Vibration Absorption System of Light Automobile Vehicles
-Jitendra kumar
We know that the compression springs are used in light automobile vehicles. These springs are fixed vertically over the axle to absorb the vibrations and vertical impacts. But sometimes the impact is applied horizontally or at any angle to the vertical. By this the vertical absorbers are failed to absorb the vibrations and impacts. Here we have required such type absorbers which may absorb the vibrations and impacts at any angle like given fig.(1). Read More...
|
Mechanical Engineering |
India |
33-34 |
7 |
Consumer Behaviour Analysis: Understanding Economic Decision Making Through Big Data
-Sanya Rajpal
Understanding consumer decision-making, particularly during economic fluctuations, is crucial for businesses and policymakers. This research delves into the power of big data analytics to unveil the complexities of consumer behavior in an Indian context. The paper first explores established consumer behavior theories and examines how big data is revolutionizing this field globally. By reviewing existing studies on big data analysis and identifying research gaps, the foundation for this investigation is laid. Next, the methodology section outlines the data collection process. It details the sources of big data, such as social media and online shopping platforms, and explores ethical methods for gathering and processing this information. Statistical tools and machine learning algorithms are proposed as potential analytical techniques, with a focus on ensuring data privacy compliance. The heart of the research lies in the analysis of consumer behavior. The paper investigates techniques for segmenting consumers based on demographics, behavior, and preferences. It explores the factors influencing purchasing decisions, including price sensitivity and brand loyalty. Sentiment analysis of online discussions and reviews will be used to glean deeper insights. These insights are then translated into actionable strategies for economic decision-making. The paper examines how understanding consumer behavior shapes marketing strategies, pricing tactics, and product development. Additionally, policy recommendations are offered for businesses and the government. Challenges faced in big data analysis, such as data quality, biases, and resource constraints, are then addressed. The paper concludes by looking toward the future, identifying trends in consumer behavior analysis and big data technologies. It proposes potential areas for further research on Indian consumer behavior and suggests future directions for businesses and policymakers. This research aims to contribute significantly to understanding economic decision-making in India by leveraging the power of big data. The findings have the potential to inform business practices and government policies, ultimately impacting the economic landscape of the country. Read More...
|
Commerce |
India |
35-40 |
8 |
A Review on Phase Change Materials in Cold Storage Applications
-Mr.C.Selva Kumar ; Dr.K.Chinnarasu; Anisha R; Kaleeswari T; Ratish P
The study reviews the key characteristics of PCMs, such as their high latent heat capacity, thermal stability, and ability to maintain a constant temperature during phase transitions. By integrating PCMs into the design of cold storage systems, researchers and engineers aim to enhance thermal inertia, reduce temperature fluctuations, and mitigate the impact of external temperature variations. Additionally, the study investigates various types of PCMs, including organic, inorganic, and eutectic formulations, assessing their suitability for different cold storage applications. Furthermore, the research examines the impact of PCM-enhanced cold storage on energy efficiency, operational costs, and overall sustainability. Insights into the design considerations, material selection, and practical implementation of PCM-based solutions are discussed, emphasizing the potential for significant improvements in energy consumption and environmental impact. Read More...
|
Agricultural Engineering |
India |
41-44 |
9 |
Survey on Advanced Visibility Restoration and Object Segmentation Techniques in Adverse Weather Conditions
-Saba Attar ; Samiksha More; Snehal Bhujbal; Prof. Y. R. Khalate; Prof. J. H. Shaikh
This paper provides a survey of three state-of-the-art techniques focusing on visibility restoration in diverse weather conditions, optical flow estimation in dense fog, and semi-supervised video object segmentation. The unified approach towards weather visibility restoration, the use of semi-supervised learning for optical flow in foggy environments, and the cyclic mechanism for video object segmentation are explored. These methods are compared in terms of system architecture, datasets, and performance metrics. Through this survey, we aim to provide insights into advancements in these domains, highlighting future trends and areas for improvement. Read More...
|
Advanced computing and Data Science |
India |
45-49 |
10 |
Resume Screening App Using Machine Learning
-Ms Mamta ; Aman Kumar Jha; Dhruv Bhandari; Aditya; Ankit
High velocities are associated with the recruitment processes of current hiring environments, and sifting through large volumes of applications pose challenges. With traditional resume screening being labor-intensive, time- consuming, and prone to human error, it translates into delays in recruitment and failure to identify some candidates that might fit the requirements of a post. This paper outlines an automated resume-screening application aimed at fastening the recruitment process through automatic resume categorization according to professional fields. The proposed system is based on ML and NLP techniques, with the application to be designed to classify, from an uploaded resume, the relevant field of the uploaded resume-for instance, information technology, marketing, finance, healthcare, and more. The application was developed using Python for both the machine learning and user interface components. The development environment was Jupyter Notebook. NLP techniques are used to extract key features from the resume text, and a classification model is trained to predict the most relevant field for each document. It used a dataset with resumes from various fields and obtained a high accuracy rate for the correct indication of the resume's field, thereby proving the correctness and dependability of the system. Read More...
|
Computer Science and Engineering |
India |
50-52 |
11 |
Student Digilocker
-Shravani Jagdish Chaudhari ; Gauri Nitin Sakpal; Yogini Pradip Patil; Dhanashree ramdas Gatkal; Ajit P. Patil
A student DigiLocker abstract is a digital version of a student's key documents that can be stored and accessed through the DigiLocker platform, a cloud-based initiative by the Government of India. It provides students with a secure, digital space to store various educational documents, certificates, and identity proofs. Here's what typically constitutes a student DigiLocker abstract. DigiLocker simplifies document management, making it easy for students to share certified documents with institutions, reducing paperwork and delays. Read More...
|
Information Technology |
India |
53-56 |
12 |
Comparative Analysis on Different Industrial Trusses With Change in Material
-Rahul Patidar ; Sumit Pahwa; Murtaza Safdari
In present study, three different industrial trusses, namely, Howe truss, Pratt truss and Warren truss are designed, and performance of the trusses has been evaluated on the basis of the parameters like maximum compressive force, maximum tensile force, maximum, shear, maximum bending moment under compression and node displacement for each alternative under two different materials, i.e., hot rolled steel and cold forged steel. On the basis of the results, ranking of trusses has been done by a well-known statistical technique, coefficient of variance. Results of the research work show the suitability of hot rolled steel for truss making applications. Results also show that hot rolled steel Warren truss shows the best performance out of the available alternatives while the second-best truss design is CFS-Howe truss. Read More...
|
Structural Engineering |
India |
57-62 |
13 |
Wavelet Transform-Based Fault Identification and Classification in Power Systems
-Sonu Kumar Singh ; Sachindra kumar Verma
Power system faults can lead to significant disruptions, economic losses, and safety hazards. Accurate and timely fault detection and classification are crucial for maintaining system reliability and security. This paper proposes a novel approach utilizing Wavelet Transform (WT) for effective fault detection and classification in power systems. WT, with its ability to provide time-frequency analysis, is well-suited to capture the transient characteristics of fault signals. By decomposing the fault signals into different frequency components, WT enables the extraction of relevant features for fault identification. The proposed method involves applying WT to the post-fault voltage and current signals to obtain wavelet coefficients. These coefficients are then analyzed to identify specific patterns associated with different fault types, such as single-line-to-ground, double-line-to-ground, and three-phase faults. Simulation results demonstrate the effectiveness of the proposed method in accurately detecting and classifying various fault scenarios. Read More...
|
Electrical and Electronics Engineering |
India |
63-67 |
14 |
Performance Analysis of 19-Level Modular Cascaded MLI With Reduced Switch Count
-Anchal Meshram ; Sachindra Kumar Verma
Utility Multi-level inverters are increasing day-by-day in smart power system. With this their topologies are also evolving. The main challenge in designing the high-level inverters is to maintain efficiency and reliability with reduced component counts. Since as the level of output increases, requirement for the switches and other components like capacitor, diodes and sources also increases. This paper presents the cascaded type asymmetrical 19-level inverter with only 12 switches and four DC-sources. Asymmetrical topologies are the one which does not have any symmetry in the design and though the units are cascaded in structure, but they are different in topology. The proposed 19-level inverter is designed in MATLAB. Read More...
|
Electrical Engineering |
India |
68-72 |
15 |
Review on Modular Cascaded Multi-level Inverter Topologies
-Anchal Meshram ; Sachindra Kumar Verma
Multi-Level Inverter (MLI) are the widely adopted power conversion devices in modern power system. They have excellent performance characteristics in medium and high voltage level as well as they have wide range of applications. The conventional topologies of MLI are neutral point, fixed capacitance and cascaded topologies. Among the three types, cascaded has the modular type structure. The conventional topologies have high component requirement as the levels increases. Hence the researchers developed the modified reduced count topologies. This paper presents the literature survey on such topologies in order to achieve high voltage level with better efficiency and low component requirements as compared to conventional MLI topologies. Read More...
|
Electrical Engineering |
India |
73-76 |
16 |
Fault Response Improvement in Power system using ANN controlled DVR
-Sonu Kumar Singh ; Sachindra kumar Verma
This research article proposes an advanced fault response improvement technique for power systems using an Artificial Neural Network (ANN)-controlled Dynamic Voltage Restorer (DVR). The DVR, a versatile FACTS device, is capable of mitigating voltage sags and swells, improving power quality, and enhancing system stability. By integrating an ANN into the DVR control system, the proposed approach aims to significantly enhance the device's response time and accuracy in addressing power quality disturbances. The ANN is trained on a comprehensive dataset of fault scenarios, enabling it to learn optimal control strategies. The effectiveness of the proposed ANN-controlled DVR is evaluated through extensive simulations under various fault conditions. The results demonstrate substantial improvements in voltage recovery time, overshoot, and undershoot, leading to enhanced system reliability and performance. Read More...
|
Electrical and Electronics Engineering |
India |
77-81 |
17 |
Farmtrack
-Sanskruti Somnath Pingle ; Pragati Madhukar Bachhav; Narendra Yogesh Ahire; Rajdeep Sharad Pawar
Agriculture is the backbone of many economies, and farmers play a crucial role in feeding the world's growing population. However, farmers face numerous challenges, including crop diseases, pests, and limited access to information and resources. To address these challenges, we propose the development of a FarmTrack Application for Farmers. The Farm application is designed to support farmers in their daily farming practices. The application uses image processing techniques to detect and diagnose plant diseases, providing farmers with timely advice on crop management and pest control. The application's web interface allows farmers to access a comprehensive FarmTrack, while the android application enables remote monitoring and reporting of crop conditions. The application uses image processing algorithm to analyze images of plants and detect common diseases such as fungal infections, bacterial blights, and viral diseases. The system also provides farmers with real-time monitoring and reporting capabilities, enabling them to track crop conditions and receive timely alerts and advice. The FarmTrack application has the potential to improve the productivity and efficiency of farming practices, while also reducing the use of pesticides and other chemicals. The application is a valuable tool for farmers, researchers, and extension agents seeking to improve crop management and plant disease detection. Read More...
|
Computer Engineering |
India |
82-85 |
18 |
Skin Cancer Classification using Deep Learning and Image Processing
-Akanksha Ashok Godse ; Awatade Sneha Jayram; Dhongade Priyanka Pandharinath; Godse Akanksha Ashok; Desale Dhanshree Deepak
Dermatology often involves complex and time-consuming diagnostic processes, influenced by practitioner expertise. To address this, we propose an automated system for skin disease diagnosis using machine learning. The system processes and enhances skin images, extracts features via Convolutional Neural Networks (CNNs), and classifies them using a softmax classifier. This approach ensures faster and more accurate results compared to traditional methods, making it an effective tool for dermatological diagnosis and a valuable resource for medical education. Read More...
|
Computer Engineering |
India |
86-87 |
19 |
Agribid Tracker
-Riya Dnyaneshwar Bhamare ; Bagul Siddhi Milind; Chothe Siddhi Namadev; Jadhav Anushree Shashank; Rahul Shankar Derle
This application will help farmers to sell their products online to the highest bidder. The work will be a bidding-based system where all the merchants will bid for the product that will be posted online by a particular farmer and then the quality will be verified by the Agent and the bid will start from a certain minimum value [3]. The products will be sold to the merchant who has the highest bid. Once the auction is complete the admin managing the website will send a confirmation email/SMS to the farmer as well the merchant and sharing the contact details of both with each other. Once the contact details are shared the transportation of the products will be discussed between the farmer and the merchant [4]. Read More...
|
Computer Engineering |
India |
88-90 |
20 |
Comparecatalyst: E-commerce Comparison website
-Divyesh Pankaj Deore ; Gayatri Chandrakant Tambe; Mayura Patil
With the dynamics of today's e-commerce, comparing prices and products from different platforms has proven to be very cumbersome for consumers. "Compare Catalyst" is an internet-based solution designed to simplify the comparison process by collecting relevant information about products-from prices, specification, reviews, and images-on different e-commerce websites. This paper discusses the system architecture, data collection methods, user interface design, and backend infrastructure powering "Compare Catalyst." Advanced data scraping, API integrations, and real-time data processing offer seamless and accurate product comparisons through the platform. This innovation enhances the online shopping experience, empowering consumers to make well-informed decisions efficiently. Read More...
|
E-Commerce |
India |
91-93 |
21 |
Quick Basket
-Shruti Pravin Deore ; Suraj Manik More; Anushka Somnath Kale; Gauri Kishor Tingle
This paper introduces Quick Basket, a novel platform designed to revolutionize lost and found services. The platform integrates robust front-end technologies, advanced back-end infrastructure, and efficient dataset management, bridging the gap between traditional and digital services. Key features include a token system, chat functionality, and an admin interface for seamless management. Read More...
|
Computer Engineering |
India |
94-95 |
22 |
Smart Vehicle Towing and Alert System
-Ashwin Rajesh More ; Dhanashri Sunil Patil; Sharvari Atul Thakare ; Mr. P.D.Boraste
The Vehicle Towing Alert System is an advanced solution designed to notify vehicle owners in real time when their vehicle is being towed, particularly in urban settings where illegal or unauthorized towing is a common issue. This system alerts owners through text messages or mobile app notifications, triggered by the towing officer once a vehicle is flagged for towing in restricted parking areas. The system reduces the risk of vehicle theft and towing fines, providing owners with immediate information about where their vehicle is being moved. By directing vehicle owners to nearby government-allotted parking spaces, the system encourages compliance with parking regulations and minimizes the inconvenience of towing. At the core of the Vehicle Towing Alert System is a simple yet efficient process: upon detecting a vehicle in a no-parking zone, the towing officer enters the vehicle number into the system, which retrieves the owner's details from a centralized database. Read More...
|
Diploma in Information Technology |
India |
96-98 |
23 |
AI Healthcare Chatbot System
-Chavan Vaishnavi Hemant ; Sangale Sanskruti Nitin; Sasane Janhvi Vinod; Wagh Pratiksha Dnyaneshwar
Healthcare in India continues to face critical challenges, particularly in rural and underserved regions, where access to quality and affordable medical services remains limited. Factors such as inadequate transportation, high treatment costs, and lack of awareness often lead people to delay seeking medical attention, resulting in worsened health outcomes. To address these pressing issues, the AI Healthcare Bot system provides an innovative and accessible solution. This Python-based chatbot interacts with users through an intuitive interface, offering a range of features, including answering health-related queries, providing precautionary advice, and identifying nearby healthcare facilities such as clinics, hospitals, and doctors. By leveraging advanced technologies like Natural Language Processing (NLP) and Convolutional Neural Networks (CNNs), the system ensures accurate analysis of user inputs and delivers reliable information. The integration of the Google Places API further enhances its capabilities by enabling users to locate healthcare services based on real-time location data. Designed to bridge the gap between users and healthcare providers, the AI Healthcare Bot system is not only a tool for immediate assistance but also a resource for spreading health awareness and supporting informed decision-making. It aims to improve healthcare accessibility, especially in emergencies, while reducing dependency on physical consultations for basic health inquiries. Read More...
|
Computer Engineering |
India |
99-101 |
24 |
Seismic Analysis Of Cable Stayed Bridge Under Moving Loads Using IRC & AASHTO Methods With Different Shapes Of Pylons - A Literature Review
-Shakib Shaikh ; Dr J N Vyas
The Cable Stayed Bridges are one of the modern bridges which were built for the longer spans and for better enhancement of the work in the field of aesthetic appearance and durability, therefore there is a need of study which overcomes the idea about the different possibilities in the structural arrangement in the terms of economy and aesthetical appearance. This study reveals an idea about the behaviour of Cable Stayed bridges with different shapes of pylons under the moving loads with varied code specifications. The previous studies related to response of Cable Stayed Bridge under moving load consideration, wind effect & seismic effect have been studied and the behaviour of Cable Stayed bridge under different condition with varied design prospects have been observed in this study. From these observations, the response of the cable stayed bridge has been easily determined in the assumed appropriate conditions on the basis of its mode shapes and other design parameters like displacement, shear, axial force and bending moment. An effort was made to studied the displacements of the cable stayed bridge deck and pylon under the action of traffic loads & lateral loads which are helpful in limiting the limitations of different shapes of pylon too. From the results it has been observed that the diamond shaped pylons shows better performance for both IRC & AASHTO loading and gives satisfactory results and the values of displacement, forces and moments for AASHTO loading is lesser than the IRC loading. Read More...
|
Structural Engineering |
India |
102-110 |
25 |
Seismic Analysis Of Cable Stayed Bridge Under Moving Loads Using IRC & AASHTO Methods With Different Shapes Of Pylons
-Shakib Shaikh ; Dr J N Vyas
The Cable Stayed Bridge is one of the modern bridges which were built for the longer spans and for better enhancement of the work in the field of aesthetic appearance and durability, therefore there is a need of study which overcomes the idea about the different possibilities in the structural arrangement in the terms of economy and aesthetical appearance. This study reveals an idea about the behaviour of Cable Stayed bridges with different shapes of pylons under the moving loads. The modelling and analysis of bridge has been carried out using SAP 2000 with vehicular interaction as per IRC & AASHTO methods & the effects of moving loads on the bridge has been studied. With the moving load configuration, the bridge has also been analysed for the seismic load as per Indian Standard for Zone III using Elastic Response Spectrum Approach. For the modelling of bridges, the arrangement of self-anchored cable stays has been considered as semi fan type with the constant dimensions of height of pylon and span of bridge. From these results, the behaviour of the cable stayed bridge has been easily determined in the assumed appropriate conditions. A static moving load along with seismic analysis is carried out and various response quantities like Bending moment, Shear force, Displacement, and axial force are represented. An effort was made to evaluated the displacements of the cable stayed bridge deck and pylon under the action of traffic loads & seismic loads which are helpful in limiting the limitations of different shapes of pylon too. From the results it has been observed that the diamond shaped pylons shows better performance for both IRC & AASHTO loading and gives satisfactory results and the values of displacement, forces and moments for AASHTO loading is lesser than the IRC loading. Read More...
|
Structural Engineering |
India |
111-120 |
26 |
Deep Learning based Moon Rock Obstacle Detection for Rover Navigation
-Mr. Krish Bhargava ; Mr. Kunal Rana; Mr. Himanshu Negi; Mr. Nitish Meswal; Ms. Pragati
Safe and autonomous navigation for the lunar rovers will play the most important role in successful lunar exploration missions. Precise detection and avoidance of obstacles, especially rocks, are main challenges for obstacle avoidance systems. This paper proposes a deep learning-based real-time moon rock obstacle detection approach, allowing the rovers to make clear decisions about where to move next over complex lunar terrains and which to avoid. Our approach will employ advanced state-of-the-art semantic segmentation techniques for accurately picking out and segmenting regions of rocks in images taken by cameras mounted on the rover. We train a deep neural network on a diverse collection of lunar images to discern, between rocks and the surrounding lunar surface. The segmented images can be used to generate obstacle maps, which are important for information about path planning and obstacles for the rover. We test our proposed method with a challenging dataset of lunar images, showing that our proposed method efficiently detects rocks under different sizes and shapes under dissimilar lighting conditions. Our experiments show that our approach produces a substantial performance gain over the conventional computer vision techniques and may be employed for safe and efficient navigation of lunar rovers. Read More...
|
Computer Science and Engineering |
India |
121-126 |
27 |
Relative Analysis of High Rise RC Structure with Communication Tower at Altered Location on Roof under Severe Lateral Loading
-Piyush Jaiswal ; Sumit Pahwa; Murtaza Safdari
Basic human needs for living to sustain in various changing environments are one of the main problems in this era of construction world is the problem of vacant and stable land. This lacking urban areas has showed to the vertical! construction magnification of low-rise, medium-rise, tall buildings and even skyscraper. These buildings usually castoff framed structures open to lateral loads beside with vertical loads. In these structures, the horizontal loads from resilient winds and earthquakes are the foremost concerns to keep in mind while designing relatively than the gravitational loads caused by the self-weight of structure. The above factors considered for the analysis might be inversely proportional to each other as the building which is designed for gravitational loads do not withstand for lateral loads and vice versa. In this work, response spectrum analysis been carried out for the effect of lateral loading. Previous researches have been carried out to study the enactment of the location of rooftop tower and there is gap in the study for its better enhancement hence the study related to its better performance and locations is yet to be implemented. The objective of this study helps to determine the optimal position of tower position and to evaluate the performance of multistoried buildings having rooftop communication tower and their response under severe seismic conditions. For optimizing the position different options are considered and tower has been placed at various location for better suitability. For the tower configurations, triangular plan is selected. G+10 buildings without tower and with tower is taken into account and G+6 buildings without tower and with tower along with analyzed in compliance of Indian Code of Practice for seismic resistant design of buildings by using I.S. 1893-2016. The various models are assumed to be fixed at the base and are modeled using software STAAD Pro. Various parameters are computer for the buildings with and without tower and the output of the work compared on the basis of these results. Read More...
|
Structural Engineering |
India |
127-134 |
28 |
Personality Prediction tool for Candidate Assessment
-Ms. Sawant Rani Arun ; Ms. Kawde Aditi Krushna; Ms. Varade Shravani Avinash; Prof. J. P. Patil
This tool will provide a more effective way to shortlist submitted candidate CVs from a large pool of applicants, offering a consistent and fair CV ranking policy that can be legally justified [4]. It is an AI-powered platform where users can upload their resumes or CVs, answer AI-generated questions, and receive a detailed report based on their performance and confidence level [3]. The platform will use facial expression recognition and the ChatGPT API to facilitate a sophisticated evaluation process. The system will rank the CVs based on resume details, AI-generated question-and-answer responses, and the candidate's confidence level [4]. This system will help the HR department easily shortlist candidates according to the CV ranking policy. It will focus not only on qualifications and experience but also on other important aspects required for a particular job position. Ultimately, this system will assist the HR department in selecting the right candidates for specific job profiles, ensuring an expert workforce for the organization [2]. Read More...
|
Computer Engineering |
India |
135-136 |
29 |
Smart Waste Collector Vehicle Tracker and Garbage Bin Level Tracker
-Tejaswini Yogesh Kor ; Patil Manali Sanjiv; Kawale Vaishnavi Sopan; More Bhumika Ravindra; Handge Gaurav Nivrutti
Efficient waste management is a critical challenge for urban areas, exacerbated by increasing population and waste generation. Traditional waste collection methods often suffer from in efficiencies, leading to higher operational costs and environmental impact. The implementation of this smart tracking system aims to reduce fuel consumption, minimize emissions, and improve the overall quality of waste management services, contributing to a more sustainable urban environment. Read More...
|
Computer Engineering |
India |
137-139 |
30 |
Face Recognition based Attendance System
-Sonawane Sahil Vijay ; Shinde Aditya Bapu; Gaykwad Pratiksha Madan; Dagale Rutuja Rangnath; Handge Bhagvat
The face recognition-based attendance system targets the automation of attendance in educational institutions or workplaces. It captures the face of the individual using a camera and then matches it against a pre-enrolled database of faces to record attendance. The process is entirely seamless, with the individual's attendance marked automatically upon recognition, thus offering greater convenience, accuracy, and efficiency relative to traditional methods. Such major components would include face detection, facial feature extraction, face recognition, and a storing database for attendance records. This system is built using popular libraries such as OpenCV, Dlib, and even face recognition to provide real-time tracking while efficiently integrating into existing infrastructure, along with all the standards of security and privacy. It has also been designed to function under any conditions of lighting for large-scale implications without compromising on reliability. Read More...
|
Image Processing |
India |
140-142 |
31 |
Survey on Advanced Text Extraction Techniques Using OCR and Resume-Based Job Recommendation Systems for Sponsorship Platforms
-Tejas Adagale ; Abhishek Dhage; Onkar Shivarkar; Vikramsinh Khalate; Prof. Y. R. Khalate
This review examines cutting-edge research and machine learning techniques that support platforms, along with optical character recognition (OCR) technology for effective text extraction. The main objective of the platform is to bridge the gap between students and organizations, offering a shared space for students to receive assistance and for organizations to identify essential roles and skills. Based on this research, the paper illustrates how OCR, iterative parsing, and hybrid consensus models collaborate to enhance the accuracy of matching students with advocates. Contemporary OCR methods transform physical documents into text formats that can be analyzed through machine learning algorithms. Furthermore, this paper investigates a hybrid strategy that merges collaborative and content-based filtering to strengthen the connection between student activities and required sponsors. This approach holds significant potential for developing platforms that not only harness the project's capabilities but also align learners' skills with the specific demands of institutional support. Read More...
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Advanced computing and Data Science |
India |
143-145 |
32 |
Non Helmet and Number Plate Detection
-Patil Durvesh Sanjay ; Dalal Yadnyesh Sachin; Patil Atharva Sahebrao ; Patil Vishal Suresh
This project focuses on an automated system to detect traffic rule violations, specifically targeting riders without helmets and those breaking traffic signals. The system leverages computer vision and machine learning techniques to identify violations in real-time. It integrates helmet detection, signal monitoring, and Optical Character Recognition (OCR) for number plate extraction. When a violation is detected (e.g., a rider without a helmet breaking a signal), the system captures an image of the vehicle and extracts the number plate details. These details are stored in an Excel file for further processing or enforcement actions. The solution aims to enhance road safety and improve compliance with traffic regulations through non-intrusive, automated monitoring. Read More...
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Computer Science and Engineering |
India |
146-148 |