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Prompt Palate: A Prompt-Based Restaurant Recommendation System with Scheduling and Chatbot Integration 8

Prompt Palate: A Prompt-Based Restaurant Recommendation Syst...

引用

8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Vidula, N.A. Babu, T.Hemanth Kiran, V. Gopi Balakrishnan, Roshni M. Bhaskaran, Sreebha Amrita School of Computing Amrita Vishwa Vidyapeetham Dept.of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9798331505462

In today's fast-paced world, individuals often find themselves craving a culinary adventure but struggle to decide on the perfect restaurant to satisfy their desires. Traditional restaurant search platforms typically offer rigid filters such as location, cuisine, and price range, limiting users' ability to explore options tailored to their specific cravings or preferences. We introduce Prompt Palate, a novel prompt-based restaurant recommendation system that uses natural language processing (NLP) techniques to address this challenge. Prompt Palate allows users to input their culinary desires via human-like prompts whose details and preferences are extracted through NLP algorithms. Moreover, the integration of a chatbot interface enhances user engagement and provides additional information about recommended restaurants. Users can engage in interactive conversations with the chatbot to learn more about menu offerings, ambiance, and special features of preferred restaurants. Additionally, the chatbot facilitates food ordering directly from the recommended restaurants, streamlining the dining or home delivery experience. To ensure a seamless and uncrowded dining experience, we incorporate intelligent scheduling algorithms for efficient table management, staff allocation, and delivery coordination. These algorithms optimize resource allocation, minimize wait times, and prevent overcrowding, thereby enhancing customer satisfaction. © 2024 IEEE.

关键词： Resource allocation

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Megan - A Sports Chatbot using OpenAI APIs and Django Framework with Python 9

Megan - A Sports Chatbot using OpenAI APIs and Django Framew...

引用

9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Priya, M. Yagnasri Kamble, Samrudhi S. Shendre, Sanjivani P. Sridhar, Swetha Aiswariya Milan, K. Amrita Vishwa Vidyapeetham Amrita School of Computing Dept.of Computer Science And Engineering Bengaluru India

ISBN: (纸本)9798350394474

The knowledge of the fundamentals of sports is limited and unorganized. A sports chatbot is a conversational agent which provides optimized responses to the user's questions. A sports chatbot has been designed to provide in-depth knowledge of the rules and regulations involved. This chatbot covers three sports- Football, Cricket, and Table Tennis. The chatbot proposed in this paper is capable of answering questions related to the rules of Football, Cricket, and Table Tennis, basic greetings, and also employs word censoring to curb inappropriate content. This simulation has been implemented in Python programming language, the user interface is incorporated using the Django web framework and the database has been handled using MySQL. © 2024 IEEE.

关键词： Python

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CyberEdPlay-An IQ Calculator for Predicting Mental Health 3

CyberEdPlay-An IQ Calculator for Predicting Mental Health

引用

3rd Odisha International Conference on Electrical Power engineering, Communication and Computing Technology, ODICON 2024

作者： Kumaran, U. Gurupriya, M. Adhitya Vardhan, A. Sree, Chittem.Bhavya Geethika, Ganugapati Sai Amrita School of Computing Dept.of Computer Science and Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798350354379

The human brain plays a vital role as a command center for the human nervous system. It takes control of our every action and thought and arranges everything as a central unit by taking sensory input and giving muscle output. Although with its natural ability, some kids need some extra help with their brains. The two main features, memory tests, and IQ tests are incorporated into the application to help the kids to train their brains efficiently, this application not only can be used by kids but can also be used by people of any age to train their brains. additionally, we have included a feature to calculate the age of mental health based on IQ and to increase cognitive thinking. The safety features are been added in the login section where the user has to log in using a secured email and create a strong password, thus the user also needs to verify the email id for authentication purposes. © 2024 IEEE.

关键词： Authentication

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Live Transcription and Closed Caption 15

Live Transcription and Closed Caption

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

作者： Jaswanth, Pasupuleti Priya, Chakravaram Hari Thota, Krithin Khanna, Manju Amrita Vishwa Vidhyapeetham Amrita School of Computing Dept.of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350370249

This innovative study proposes a novel tool targeted at addressing communication issues for people with hearing impairments. This improvement focuses on smart glasses with real-time captioning for improved *** main components are a powerful microphone array, a cloud computing platform driven by Raspberry pi zero w, and an advanced Automatic Speech Recognition (ASR) system. These components work together to enable the smart glasses to detect spoken language, process it using cloud-based algorithms, and display accurate captions in real time inside the wearer's field of *** primary purpose is to improve communication accessibility for those with hearing impairments by providing timely, accurate, and prominently displayed captions. Beyond personal relationships, the impact extends to a variety of settings, including educational institutions, workplaces, and public spaces, where good communication is essential for involvement. © 2024 IEEE.

关键词： Accessibility Technology Automatic Speech Recognition Hearing Impairments Real-Time Captioning Smart Glasses

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Twitter Bot For Consumer Feedback Analysis 5

Twitter Bot For Consumer Feedback Analysis

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5th IEEE International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2023

作者： Dwivedi, Ashish Sharma, Santosh Mishra, Abhinav Sahu, Ashutosh Gupta, Himanshu United Institute Of Technology Dept.Of Computer Science & Engineering Prayagraj India

ISBN: (纸本)9798350330861

This research presents the development of a Twitter bot for consumer feedback analysis using natural language processing (NLP) techniques. The bot is designed to collect and analyze tweets related to specific products or services, and provide businesses with real-time insights on consumer sentiment and feedback. The bot uses a combination of NLP techniques, including sentiment analysis, topic modeling, and keyword extraction, to identify trends and insights from the tweets. The resulting analysis can be used by businesses to improve their products or services, as well as their customer engagement strategies. The paper also discusses the challenges and opportunities associated with developing and deploying such a bot, including ethical considerations related to privacy and data protection. © 2023 IEEE.

关键词： Sentiment analysis

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Secure and Proficient Provable Data Procurity with Privacy Protection in Cloud Storage

Secure and Proficient Provable Data Procurity with Privacy P...

引用

2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Kumar, C.Siva Vasantha, Lebaku Siroshini, Pacha Jagruthi, Pullaiahgari Pavithra, Nellore Supriya, Thumati Sree Vidyanikethan Engineering College Dept.of Computer Science and Systems Engineering Tirupati India

ISBN: (纸本)9798350348217

Cloud technology is the distribution of physical servers in such processors, memory, networks, connectivity, applications, statistics, as well as smartness only via Online platform so,in addition to allow greater innovative technology, better versatile facilities, plus scalable *** this mechanism, the data owner's maintenance and storage costs can be reduced. Simultaneously, when the data owner loses procurity and physical authority over the data, a security threat arises. As a result, data inspection is required to ensure data integrity over a *** concern is now difficult for information owners because data authority must have been validated thereby preserving confidentiality. In the process of labelling these issues, this paradigm provides secure data acquisition as well as efficient privacy-preserving ***, it now supports multipleownership, data complexities, also an unit identification. A majority intriguing aspect for the process in which examiner will validate ownership of data having little maintenance cost. The system demonstrates that a malware platform will present evidence that is adequate to carry third-party auditors authentication of the user. The scheme's security is analysed and demonstrated at this system to protect data privacy from third-party public auditing while making it impossible for cloud service providers avoids saving the necessary blocks to ignore the *** proposed scheme's best intriguing feature is that it supports all of its crucial elements, such as blocking-free validation, security, process monitoring, as well as information behaviour. © 2023 IEEE.

关键词： Cloud storage

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Ensemble Model Classifier in Hybrid CNN to Predict Diabetic Foot Ulcers 15

Ensemble Model Classifier in Hybrid CNN to Predict Diabetic ...

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

作者： Athira, Anil Jyothi Varshepally, Anjana Manogna, Akula Sridhar, Alakunta Vivek, D. B V Raju Institute of Technology Dept.of Computer Science Engineering Medak Telangana Narsapur India

ISBN: (纸本)9798350370249

Diabetes arises due to decrease in the level of sufficient insulin produced in the human body. The prevalent issue faced by the individuals suffering from diabetes is Diabetic foot ulcer (DFU). Diabetic Feet affected around 1-4% individuals within 6.1% of diabetic population in 2023 globally. In this developing world, computer vision technologies are playing a vital role even in the field of medicine, particularly it can be beneficial in detecting and monitoring diabetes, along with its difficulties such as foot ulcers. Various models in computer vision are used for detecting the foot ulcers by image processing. Here the proposed novel hybrid model detects and monitors the diabetic foot ulcer in a proficient way. The proposed model is a combination of multiple neural network frameworks including EfficientNet as a Convolutional neural network architecture along with InceptionNet, Stacked Sparse Autoencoder (SSAE) and Sparrow Search Optimization (SSO). Every framework helps in performing different tasks in contribution for an efficient and accurate output. By analyzing diabetic foot images, EfficientNet brings out the information related to visual features and Inception-ResNet-v2 is able to capture the specific features as well as patterns from the images. Stacked Sparse Autoencoder (SSAE) can learn about the features in detail. Sparrow Search Optimization (SSO) is an optimization algorithm which can make the models work together optimally moreover, can eliminate unnecessary parameters which results in less memory requirement and makes the model smaller. The proposed model can improve the detection and management of Diabetic Foot ulcers and is expected to be 2 percentage higher than any existing models. © 2024 IEEE.

关键词： Convolutional Neural Network (CNN) Diabetic Foot Ulcer (DFU) Digital image processing Frameworks Telemedicine application

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Towards Comprehensive Breast Cancer Detection: Fusion of Dense Layer Model Features 15

Towards Comprehensive Breast Cancer Detection: Fusion of Den...

引用

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

作者： Kumar, Gadawalsa Kishor Muduli, Debendra Rath, Kshirabdi Tanaya Ray, Durbar Sundar Sharma, Santosh Kumar C.V Raman Global University Computer Science dept.of Engineering Odisha Bhubaneswar India

ISBN: (纸本)9798350370249

For an early diagnosis and successful treatment, ultrasonography image analysis is essential for identifying breast cancer. In this discipline, deep learning has become a powerful tool that has demonstrated notable success in several medical imaging tasks,regarding the identification of cancer in the breast. In order to achieve accurate identification, our suggested model combines characteristics from three pre-trained Convolutional Neural Network (CNN) models: DenseNet201, DenseNet169, and DenseNet121. In this study, we use ImageNet weights and ultrasound image datasets to evaluate these models' performance. After extensive testing, our model reached 94.57% accuracy, which is astounding. The model's performance was evaluated through the use of confusion matrices and metrics such as precision & F1-score, which we determined using the Adam optimizer. The efficacy of deep learning-based techniques in identifying breast cancer from ultrasound pictures is highlighted by this study. It illustrates makes major contributions to medical analysis and helps discover breast cancers early. © 2024 IEEE.

关键词： Breast Cancer Deep learning DenseNet121 DenseNet169 DenseNet201 Machine learning Medical imaging ultrasound imaging

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Face Recognition Using openCV- use case on student attendance system 15

Face Recognition Using openCV- use case on student attendanc...

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

作者： Kamalapur, Anjan Kumar Srikanth, Begari Yadav, Asari Shivadeep Yashwanth, Bachhanaboni Duraivelu, Vivek B V Raju Institute of Technology Dept.of Computer Science Engineering Telangana Narsapur502313 India

ISBN: (纸本)9798350370249

This is a modern approach to student attendance management using face recognition technology, powered by advanced techniques including Convolutional Neural Network (CNN) and Haar Cascade frontalface default algorithm. By leveraging OpenCV and these cutting-edge face recognition methods, the system offers a reliable and efficient solution for tracking attendance in educational institutions. Real-time face detection and recognition, support for multiple face recognition, and smooth interaction with current attendance management systems are some of the key characteristics. Additionally, the system incorporates deep learning algorithms to enhance its accuracy and robustness in identifying students' faces. Through practical implementation, the project demonstrates the effectiveness of using OpenCV and deep learning for automated student attendance management. By providing accurate and efficient attendance tracking, while improving operational efficiency in educational settings, this innovative solution marks a significant advancement in modernizing attendance management practices. © 2024 IEEE.

关键词： Convolutional Neural Network (CNN) Deep Learning Face Detection Haar Cascade Open CV

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An Ensemble Technique to Analyse Mental Health of Workforce in the Corporate Sector 7

An Ensemble Technique to Analyse Mental Health of Workforce ...

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7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Lohia, Abhinav Ranjith, Abhinav Sachdeva, Abhinav Bhat, Aruna Delhi Technological University Dept.of Computer Science and Engineering New Delhi India

ISBN: (纸本)9798350397253

The modern world is filled with stress, worry, and pressure, among other things. People can't perform at their highest level as a result, which lowers economic production and raises stress levels. This study examines the working conditions for employees physical and emotional wellbeing. It is examined whether a patient should be treated of his mental illness or not according to the values obtained in the dataset such as self-employment, previous mental health conditions in the employee's family, whether the organisation is providing advantageous life benefits, is the employee currently undergoing any treatment for mental condition etc by applying various Machine Learning techniques. The 'Open Sourcing Mental Illness (OSMI) Mental Health dataset' was used in this study. This data is used to train the proposed model using several techniques, such as Linear Regression, KNN, Decision Trees and Random Forest to find the factors each person is targeted for. Ensemble Technique is applied for increasing the accuracy of the results. The main purpose of this data analysis is to raise general awareness of workplace issues connected to mental health, which will assist to decrease the number of persons who experience mental diseases. This gives an approximate idea of how employees in both the technical as well as non-technical organisations are impacted. Whether or not mental health is taken into account and whether a person needs any medical assistance or not. © 2023 IEEE.

关键词： Decision trees

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