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Rough Set Based Recipe Clustering Approach 10

Rough Set Based Recipe Clustering Approach

引用

10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Das, Priyanka Mukherjee, Chandrani Gupta, Samiksha Roy, Sayan Shah, Khushi Singh, Shreya Institute of Engineering & Management Dept. of Computer Application and Science Kolkata India

ISBN: (纸本)9798350384369

Online cooking instructions including ingredient lists and cooking methods are now widely available due to the proliferation of recipe sharing websites. Finding novel and complex patterns in such vast, ambiguous categorical data sets is a crucial task. Conventional clustering analysis algorithms frequently fail to address the uncertainty surrounding the exact value of features found in these categorical data sets. Thus to aid in decision-making, rough set based clustering is frequently used. This study aims to identify the optimal clustering feature from the recipe data that will result in the grouping of related food products by applying the rough purity notion. The recipe data has been regarded as a categorical valued information system in this instance, and information theoretic attribute purity is taken into account using the rough purity technique. © 2024 IEEE.

关键词： Food chemistry

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Classification of Foods based on Bijective Soft Set 15

Classification of Foods based on Bijective Soft Set

引用

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

作者： Das, Priyanka Bhattacharya, Rupam Dept. of Computer Application and Science Institute of Engineering & Management Kolkata India

ISBN: (纸本)9798350370249

Cuisine data is typically classified using images of the cuisine, cooking methods, cooking utensils, and, most importantly, ingredients. The vast amount of recipe data available on the internet necessitates the creation of specialised systems for storing, retrieving, and effectively utilising stored knowledge and data. Neural networks based expert systems are steadily being used to classify the cuisine data. But it lacks in dealing the vagueness present in the categorical cuisine data. Also, most of the popular recipes available online are mostly unhealthy. As a result, the Bijective soft set theory has been introduced into this study since it is an intelligent method for developing classification rules from food data and then recognising ambiguity and data reliance. The classification guidelines also address the necessity to select healthy/nutritious meals. The investigation outcomes from using bijective soft set analysis to a set of data samples are presented and appraised in this work. Furthermore, the classification rules derived from this approach provides valuable help for developing food recommendation systems. The accuracy of this classification scheme has got really influenced by application of the bijective soft set when compared to other state-of-the-art classifiers. ©2024 IEEE.

关键词： bijective soft set classification classification rule generation cuisine ingredients

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A Graph Based Approach For Detecting Sybil Node In Online Social Networks 15

A Graph Based Approach For Detecting Sybil Node In Online So...

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

作者： Chandra, Sucheta Das, Priyanka Institute of Engineering & Management Dept. of Computer Application and Science Kolkata India

ISBN: (纸本)9798350370249

Sybil attacks pose a significant threat to the security and integrity of online social networks by allowing malicious actors to create multiple fake identities to manipulate network behavior. The abstract outlines a method for detecting Sybil attacks in online social networks using graph analysis. It involves constructing a graph representation of the network, calculating node centrality measures such as in-degree and out-degree, and setting a degree threshold to identify potentially malicious nodes. Additional parameters like clustering coefficient and community structure are also considered to improve detection accuracy. The proposed approach aims to enhance the security of online social networks by identifying and isolating Sybil identities, thus preserving network integrity and trustworthiness. The authors' firmly assert that employing graph-based theory for Sybil node detection in online social networks stands out as one of the most effective methods. This approach not only offers robustness but also scalability, allowing for efficient detection even in large-scale networks. With its ability to unveil intricate relationships, anomalies, and patterns within the network, graph-based theory emerges as a cornerstone in the fight against Sybil attacks. © 2024 IEEE.

关键词： Cyber attacks

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Detecting Feet's Bending Patterns With Smart Insoles 5

Detecting Feet's Bending Patterns With Smart Insoles

引用

5th IEEE International Conference on Pattern Recognition and Machine Learning, PRML 2024

作者： Zhong, Yuchen Ying, Qijun Cai, Xiaohui dept. of Computer Science and Technology Hefei China dept. of Data Science Hefei China

ISBN: (纸本)9798350355925

Foot bending is a basic component of walking. Although bending is important for foot-ground interaction and ensures the speed and balance of the whole walking cycle, there is still no practical method for recording and analyzing foot bending under everyday scenarios. In this study we propose to use a smart insole, with two embedded Inertial Measurement Units, to acquire the movements of the fore-foot and the hind-foot and deduce the bending, represented by the bending point's position. We use the deep learning approach to estimate the bending position and its changes during different walking patterns. On the dataset containing 8 test subjects and 6 walking patterns, our method can achieve an overall mean absolute error accuracy of 2.58 cm. The smart insole can be with the subject all the day, bring in a new method for continuous foot bending monitoring. © 2024 IEEE.

关键词： Wearable technology

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Designing a Secure Audio / Text Based Captcha Using Neural Network 13

Designing a Secure Audio / Text Based Captcha Using Neural N...

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13th International Conference on Cloud Computing, data science and Engineering, Confluence 2023

作者： Pai, H. Aditya Anandkumar, M. Prasad, M.S. Guru Agarwal, Jyoti Christa, Sharon Dept. of Computer Science and Engineering Dehradun India Dept. of Computer Application Dehradun India

ISBN: (纸本)9781665462631

A CAPTCHA is used to reduce the misuse in the case of rising automated bots or software systems and also to avoid any corruption of the web services. The Captcha is used as solving a turing test problem by the users, before they get access to the software system. The paper discusses about the model that extracts the alphanumeric characters from either of audio or text-based captchas. Finally, the model's performance is found based on different parameters like accuracy level, specificity, precision etc. © 2023 IEEE.

关键词： Web services

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From data to Harvest through Machine Learning based Crop Yield Forecasting 2

From Data to Harvest through Machine Learning based Crop Yie...

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2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： Budarapu, Aadithya Vikram Gaddam, John Hyde Boyedi, Ramu Muthyala, Thoshan Kumer Kathirisetty, Nikhila Dept. of Information Technology Hyderabad India Dept. of Computer Science and Data Science Hyderabad India

ISBN: (纸本)9798350370188

The maintenance and enhancement of dynamic soil characteristics are the primary focus of soil management in agriculture to increase crop productivity. Higher productivity may result from efficient soil control of resources and corrective micronutrient treatments. Using CNN and 'KNN' algorithms, the 'soil land classification and crop prediction system' application was created. In this study, two datasets are used: one to obtain crop prediction and the other for soil land categorization. The kind of soils are trained using CNN ('VGG- 19') algorithm, and the accuracy of the model is calculated. The trained model is then utilized in the Flask web app to forecast the type of soil. Another data set with nitrogen, phosphorus, potassium, pH, and temperature as features and the class type of crop as a label is used to forecast crop production. These two algorithms are used to create the flask website, which accepts inputs such as soil picture, soil type prediction, and land parameter inputs for crop prediction. © 2024 IEEE.

关键词： Soils

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An Intelligent LLM-Powered Personalized Assistant for Digital Banking Using LangGraph and Chain of Thoughts 22

An Intelligent LLM-Powered Personalized Assistant for Digita...

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22nd IEEE International Symposium on Intelligent Systems and Informatics, SISY 2024

作者： Easin, Arafat Md Sourav, Saha Tamas, Orosz Data Science and Engineering Dept. Budapest Hungary Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350385601

Text-based applications and chatbots are increasingly popular for delivering banking services and educational tools, offering convenient and efficient solutions for users. Whereas, personalized assistants have transformed user engagement in the digital banking space by utilizing Large Language Models (LLMs) in conjunction with autonomous agents. This study proposes the development of an intelligent personalized assistant for digital banking, utilizing a multi-agent framework based on the LangGraph and Chain of Thoughts (COT) prompting. While COT guarantees context-aware replies, the LangGraph design maps characteristics to nodes to improve user interactions. The objectives of this system are to enhance task efficiency and elevate the capabilities of digital banking assistants. We present a customizable digital banking system powered by LLM-based models, designed to deliver an interactive and personalized banking experience. The system supports a range of services, including adding money, transferring funds, paying bills, accessing telco services like mobile recharge, managing savings interest rates, DPS schemes, fixed deposits, and answering FAQs related to banking information. Therefore, integrating COT for logical reasoning enhances the effectiveness of multi-agent systems, as each single agent benefits from the structured reasoning process. In addition, LangGraph is employed for structured data management, enabling the assistant to support and accelerate various digital banking processes efficiently. The code implementation of this work is available for public access at: https://***/srv-sh/digital-agent. © 2024 IEEE.

关键词： Information management

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Using Ant Colony Optimised Algorithms for Shortest Path Exploration by Robots 2

Using Ant Colony Optimised Algorithms for Shortest Path Expl...

引用

2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Singh, Aashdeep Dhawan, Sakshi Verma, Jyoti Singh, Gurpreet Kaur, Amanpreet Dept. of Computer Science & Engineering Punjab Rajpura India Dept. of Computer Application Punjab Rajpura India Chitkara University Institute of Engineering & Technology Dept. of Computer Science & Engineering Punjab Rajpura India

ISBN: (纸本)9798350360523

In the realm of robotics and autonomous systems, efficient path planning is a critical aspect for optimizing resource utilization and achieving mission objectives. This study explores the application of Ant Colony Optimized (ACO) algorithms to enhance the efficiency of robots in navigating and exploring unknown environments. Inspired by the foraging behavior of ants, ACO algorithms are employed to find the shortest paths by leveraging pheromone communication and decentralized decision-making. Ant Colony Optimization is then introduced as a bio-inspired solution to address these challenges. The experimental results demonstrate the capability of the ACO algorithm to efficiently explore complex environments, adapt to changes in the surroundings, and converge to optimal paths. Insights gained from these analyses contribute to the refinement of the ACO algorithm for diverse robotic applications. The findings of this research have practical implications for the development of autonomous robots operating in real-world scenarios, such as search and rescue missions, environmental monitoring, and surveillance. This study provides a valuable foundation for the integration of bio-inspired algorithms in robotics, advancing the state-of-the-art in autonomous exploration and path planning. © 2024 IEEE.

关键词： Motion planning

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Enhancing data Security in Mobile Traffic Networks Through Reverse Engineering 4

Enhancing Data Security in Mobile Traffic Networks Through R...

引用

4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Islam, Syed Arif Mohankumar, M. Khatuna Jannat, Umma Karpagam Academy of Higher Education Dept. of Computer Science Coimbatore India Sns College of Technology Dept. of Computer Application Coimbatore India

ISBN: (纸本)9798331529635

This research enhances mobile traffic network security using reverse engineering and encryption. It analyzes vulnerabilities in evolving mobile protocols (GSM, 4G, 5G) and applies encryption schemes like AES and RSA to secure data transmission. The study also explores secure key exchange mechanisms such as Diffie-Hellman (DH) and Elliptic Curve Cryptography (ECC) and evaluates Intrusion Detection Systems (IDS) for threat detection. Tests in a Python-simulated environment confirm the effectiveness of these solutions, providing insights into balancing security and performance in dynamic mobile networks. © 2024 IEEE.

关键词： data Security Encryption Mobile Traffic Networks Reverse Engineering Vulnerability Assessment

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Real-Time Traffic Management System Using YOLOv8 and CNN: A Deep Learning Approach with IoT Integration 1

Real-Time Traffic Management System Using YOLOv8 and CNN: A ...

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1st International Conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Saklani, Sumit Manchanda, Mahesh Sharma, Raman Singh, Devendra Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to be University Dept. of Computer Application Dehradun India

ISBN: (纸本)9798331518578

Traffic management also plays a crucial role in urban planning and development, with pressing challenges related to congestion, safety, and environmental impact. In this study, we proposed a real time traffic control system using YOLOv8 and CNNs combined with Internet of Things (IoT) technologies. As a high-performing object detection model, YOLOv8 is able to accurately and rapidly detect vehicles, pedestrians, and other traffic objects. When combined with CNN based data analytics, the proposed system can successfully monitor traffic flow, discover irregularities, and control the signals dynamically. Creating a cohesive framework for intelligent decision-making IoT integration ensures real-time data acquisition from sensors, cameras and edge devices. IoT framework for a smart urban environment the proposed architecture provides the versatility through scalability, low latency, and adjustment to several urban perspective scenarios. The combination leads to greatly enhanced traffic flow efficiency, accident prevention and environmental impact reduction as experimental results show. With data till October 2023, this study resolves a gap between the developing field of deep learning and the Internet of Things (IoT), that creates to be utilized to connect to advanced town environments. © 2025 IEEE.

关键词： Decision making

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