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Culinary Fusion:Vegetable Recognition Recipe Generation 4

Culinary Fusion:Vegetable Recognition Recipe Generation

引用

4th IEEE International Conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Kanchi, Lohitha Lakshmi Vishnu, Kanduri Purna Venkata Siva Sai Vara Eswar, Kasarabada Bharath Harshitha, Lakkakula Sai Eswar, Maddineni Vasireddy Venkatadri Institute of Technology Department of Computer Science and Engineering Guntur India

ISBN: (纸本)9798350360165

The presented paper aims to propose a novel way to implement advanced deep learning and natural language processing in vegetable recognition and recipe generation. The proposed work uses the YOLOv8 object detection framework, which is first trained on a very meticulously obtained dataset of 20, 708 images from the website Roboflow, to perform intelligent partitioning into three sets: Finally, the proposed methodology has attained 88% accuracy in predicting different vegetables. On detecting vegetables in any input image, the model uses OpenCV to detect those vegetables from the PALM API. It takes the names of the detected vegetables as prompts along with the preferences selected by the user in terms of the language and the number of recipes and gives the output recipe using the PALM API in the form of five different language translations, Telugu, Malayalam, Hindi, Kannada, and Tamil. The output recipes are also provided in text and audio format to cater to users of all linguistic backgrounds. This results in a holistic system that ensures a hassle-free and user-friendly approach to vegetable recognition, its recipe generation, and, finally, the enrichment of the culinary experience and promotion of cultural diversity, even in the kitchen. © 2024 IEEE.

关键词： Food ingredients

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Airline Customer Reviews Analysis and Booking Completion Prediction using Data Visualization and Machine Learning for British Airways

Airline Customer Reviews Analysis and Booking Completion Pre...

引用

2024 IEEE International Conference on Emerging Technologies in computer science for Interdisciplinary Applications, ICETCS 2024

作者： Manibalan, Baranidharan Angel Arul Jothi, J. Birla Institute of Technology and Science Pilani Department of Computer Science Dubai United Arab Emirates

ISBN: (纸本)9798350372502

This study focuses on analyzing airline customer reviews and predicting booking trends, specifically for British Airways. The objectives include interpreting customer sentiments from reviews, identifying key themes, and examining the relationship between these sentiments and factors like flight duration and service offerings. A significant aspect of this research is developing a predictive model to forecast booking outcomes. Methodologically, the study utilizes the Extra Trees Classifier for feature selection, focusing on 8 primary features, and employs the SMOTE technique for dealing with an unbalanced dataset. The predictive models experimented comprise of Random Forest, Logistic Regression, Naive Bayes, and K-Nearest Neighbors (KNN). The models achieved an accuracy rate of 96%, 94%, 92%, and 94% respectively for booking prediction. The results demonstrate the effectiveness of combining machine learning and text analytics in the airline industry, offering valuable insights for strategic decision-making. © 2024 IEEE.

关键词： Air transportation

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Sentiment Analysis for Citizen Feedback in Smart Cities with XLNet-BiLSTM: Delhi Metro as a Case Study★ 3

Sentiment Analysis for Citizen Feedback in Smart Cities with...

引用

3rd International Symposium on Smart Cities Challenges Technologies and Trends Technologies, SCCTT 2024

作者： Shukla, Vaibhav Kuanr, Dibyalochan Juneja, Shallu Sharma, Ajit K. Department of Computer Science and Engineering Maharaja Agrasen Institute of Technology Delhi India

In recent years, smart cities have increasingly recognized the importance of citizen input in enhancing public services and optimizing urban infrastructure. As urban populations grow and services become more complex, understanding resident sentiments and opinions is crucial for effective governance. Sentiment analysis, a technique rooted in natural language processing (NLP), serves as a powerful tool for gauging public opinion on urban services, particularly public transportation. This paper presents a sentiment analysis framework using an advanced XLNet-Bidirectional Long Short-Term Memory (BiLSTM) model, developed with a custom dataset of citizen reviews related to the Delhi Metro, a key element of India’s public transportation. The dataset was meticulously scraped from various platforms and manually labeled for accuracy. Initially, the model was trained on the IMDb dataset, achieving an impressive accuracy of 93.1%. It was then evaluated on the Delhi Metro dataset, yielding an accuracy of 1.00. However, this high accuracy may indicate overfitting due to the small dataset size, suggesting the findings are exploratory. This study highlights how sentiment analysis can improve decision- making and enhance public transportation services. By analyzing feedback on the Delhi Metro, city planners can identify areas for improvement and address citizen concerns. In conclusion, the paper underscores the potential of advanced sentiment analysis techniques in understanding public opinion and calls for further research with larger, more diverse datasets and refined models to assess citizen sentiment in smart cities comprehensively. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Mass transportation

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SWM-YOLO: A New PCB Surface Defect Detection Algorithm Based on YOLOv8 9

SWM-YOLO: A New PCB Surface Defect Detection Algorithm Based...

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9th International Conference on Intelligent Informatics and BioMedical sciences, ICIIBMS 2024

作者： Yang, Ruijun Zhao, Wen Shanghai Institute of Technology College of computer science and Information Engineering Shanghai China

ISBN: (纸本)9798350363043

Printed circuit boards (PCBs) present significant challenges for defect detection due to their complex structures, small size, and high false positive/negative rates associated with traditional methods. To address these issues, this paper proposes SWM-YOLO, a novel network model based on YOLOv8n. By incorporating Swin Transformer backbone, the model enhances feature extraction capabilities, effectively capturing global contextual information. Furthermore, Mixed Local Channel Attention is integrated into the C2f structure to accurately extract detailed features while preserving overall feature representation. Finally, the Wise-IoU loss function is adopted to improve the model's ability to detect subtle defects. Experimental results on a PCB surface defect dataset demonstrate a 3.2% precision improvement over the baseline YOLOv8n, significantly reducing false positives and negatives in PCB surface defect detection. © 2024 IEEE.

关键词： Image coding

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A Fuzzy Logic-Based Opinion Update Model for Online Social Networks with Influential Social Bots 6

A Fuzzy Logic-Based Opinion Update Model for Online Social N...

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6th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2024

作者： Rout, Rashmi Ranjan Sahana, Sudipta Parimi, Priyanka National Institute of Technology Warangal Department of Computer Science and Engineering Telangana India

ISBN: (纸本)9798350344349

Social media is a platform where people express their opinions through user-generated text. Investigating opinion changes of people based on the influence of legitimate users and bots over time is crucial. The influence of bots on opinion evolution can be different from the influence of individuals in a network since the opinion of bots does not evolve over time, irrespective of the opinion of the rest of the network. This work aims at investigating the influence of social bots on users' opinions by considering the user's bias and interactions with other users and bots over time. A fuzzy logic-based approach is designed for opinion updates, allowing for uncertainty in the opinion. By considering the tweet's sentiment, we develop a neighbor-biased-fuzzy opinion influence model and analyze the effect of bots in social media. Experiments are conducted on the Social-Honeypot Twitter dataset to evaluate the performance of the proposed approach. The change in user opinion in the presence of different bots is analyzed. Further, the shift in public opinion over time due to the influence of bots is predicted. © 2024 IEEE.

关键词： Social networking (online)

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An Automated Recommendation Model for E-Commerce Web Application Using Machine Learning 2

An Automated Recommendation Model for E-Commerce Web Applica...

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2nd International Conference on Recent Trends in Microelectronics, Automation, computing, and Communications Systems, ICMACC 2024

作者： Sheik Abdullah, A. Suseendhar, B. John, Sharon Jefrin, Tanisha School of Computer Science and Engineering Vellore Institute of Technology Chennai Chennai India

ISBN: (纸本)9798350366570

The rapid evolution of the Internet and technological advancements have revolutionized the retail landscape, giving rise to e-commerce as a dominant force in the industry. In response to the increasing demand for online shopping, businesses are compelled to develop innovative, user-friendly web applications to cater to evolving consumer needs. This abstract introduces an innovative e-commerce web application designed to transform the online shopping experience. Leveraging cutting-edge technologies, intuitive user interfaces, and personalized recommendations, our web application aims to enhance convenience, engagement, and customer satisfaction. Through a comparative analysis, we demonstrate that our solution surpasses existing methods. Our e-commerce web application boasts intuitive search and filtering capabilities, empowering users to easily navigate through a vast product catalogue. Moreover, sophisticated recommendation algorithms, driven by machine learning techniques, provide personalized product suggestions based on users' browsing and purchasing history, significantly enhancing the overall shopping experience. The web application ensures seamless performance, even during peak traffic periods and also offers integrated secure payment gateways for customers confidence and peace of mind while completing transactions. By combining advanced technology with user-centric design, this e-commerce web application sets a new standard for online shopping, promising increased convenience, engagement and satisfaction for users. © 2024 IEEE.

关键词： Marketplaces

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Advanced Techniques for Chinese Image Captioning: Investigating Attention Mechanisms Based on Object Detection for Chinese Image Caption Generation 5

Advanced Techniques for Chinese Image Captioning: Investigat...

引用

5th International Conference on Machine Learning and computer Application, ICMLCA 2024

作者： Hua, Yongbin Li, Pei'ang Zeng, Xiangjin Xu, Hong School of Computer Science and Engineering Wuhan Institute of Technology Hubei Wuhan China

ISBN: (纸本)9798331530334

The task of image caption generation aims to automatically produce natural language descriptions that match the content of images, integrating the fields of machine vision and natural language processing, which holds significant theoretical and practical value. Inspired by top-down attention mechanisms, this paper proposes an innovative attention model. Utilizing the output of pretrained object detection networks as prior knowledge for images, the model guides the generation of natural language descriptions. By directly incorporating the results of object detection as attention inputs into the text generation network, the model effectively focuses on key descriptive regions of images, thereby significantly enhancing performance. On public Chinese image captioning datasets, this model demonstrates substantial advantages in metrics such as BLEU-4 and METEOR. © 2024 IEEE.

关键词： Object recognition

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A New Ant Colony Optimization Algorithm for Optimization of Software Reliability 4

A New Ant Colony Optimization Algorithm for Optimization of ...

引用

4th International Conference on Advances in Electrical, computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Narender Malhotra, Sona Dhawan, Sanjeev Manav Rachna Univerity Department of Computer Science and Technology Faridabad India Univeristy Institute of Engineerng and Technology Kurukshetra University Department of Computer Science and Engineering Kurukshetra India

ISBN: (纸本)9798350343670

In the last three to four decades several software reliability model has been planned and developed. They played an important role in making the software reliable. Several software reliability metrics have been identified by the researchers and the performance behavior is shown as per the software metrics. The researchers used several approaches for their proposed software reliability model, and all the approaches are doing well in their specific areas. The problems with the most of the models are that they are confined to their specific domain and do not perform better on different context. However, the selection of a good software reliability model can help in this area. To help in this task, it is very important choose an appropriate failure dataset along with selection of good software reliability model. A metaheuristic approach can be fruitful to find the parameter estimation of the chosen model. This pieces of work considers a classical Goel-Okumoto (G-O) model and some failure datasets. A new ant colony optimization method (NACO) has been used to estimate the parameters of the G-O model. The Mean Value Function (MVF) of G-O model is used to minimize the Root Mean Square Error (RMSE) and to find the goodness of fit. Some software metrics have been identified and the performance has been compared with existing metaheuristic approaches. The proposed approach shows outperform behavior than the current metaheuristic approaches. The comparative analysis is done with the help of MATLAB. © 2024 IEEE.

关键词： ant colony optimization genetic algorithms neighbour-joining ant colony optimization particle swarm optimization

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Tackling Food Wastage and Hunger: Feed the Needy 15

Tackling Food Wastage and Hunger: Feed the Needy

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15th International Conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Arakala, Rishitha Abbadasari, Shravani Begari, Rajeshwari Banoth, Sonabai Bhaskara Rao, P. B V Raju Institute of Technology Computer Science and Engineering Telangana India

ISBN: (纸本)9798350370249

In response to the substantial wastage of food globally, this initiative proposes a solution called 'Feed the Needy.' This charitable application streamlines the redistribution of excess food from various events, such as weddings and corporate parties, to orphanages and old age homes. Users input their information, including name, location, contact number, and the quantity of available food for donation. A non-governmental organization (NGO) verifies the authenticity of the provided details and coordinates the pickup and delivery process. Through this efficient system, surplus food is directed to those in need, mitigating wastage and addressing food insecurity. This application benefits both user and people with hunger. ETEX. © 2024 IEEE.

关键词： charitable application food insecurity Food wastage NGO coordination old age homes orphanages surplus food redistribution wastage reduction

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Swarm Based Searching Method for Effective Sinkhole Attack Detection in Internet of Things 1

Swarm Based Searching Method for Effective Sinkhole Attack D...

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1st International Conference on computing, sciences and Communications, ICCSC 2024

作者： Mona, R. Manoranjitham, R. Karunya Institute of Technology and Sciences Division of Computer Science and Engineering Coimbatore India

ISBN: (数字)9798350353648

ISBN: (纸本)9798350353648

Over the last several decades, the IoT and WSN have seen a fast proliferation, which has resulted in astonishing innovation and integrated possibilities. Since the developments in networking technology and nanodevices, the transition from IPv4 to IPv6 has further increased connection. Due to this change, it becomes easier to connect a greater variety of devices to servers. The growing interconnectedness has resulted in challenges in effectively managing and evaluating the massively generated data across all levels of IoT. Considering the massive IoT devices and their tiny size, the demand of comprehensive security management is especially significant for these devices. In IoT layered design, the network layer is of utmost significance in terms of assuring security. This layer is responsible for storing routing information and carrying out choices that match to specific routing information. Among the several security assaults that are being handled, the sinkhole attack is one that is commonly observed and poses a considerable problem. In this study, the ramifications of the sinkhole attack on IoT are investigated in detail, and the effect of the attack is meticulously analyzed. In addition to this, it introduces a unique mitigation method that is specially built to effectively combat threats of this kind. To conduct comprehensive simulations, the study makes use of MATLAB v9. This has made it possible to evaluate the throughput of the network as well as the End-to-End delay and network lifetime. © 2024 IEEE.

关键词： MATLAB

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