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1st International Conference on Computational science and technology, ICCST 2022

作者： Renukadevi, B. Ponmalar, A. Deepa, R. Dinesh, P. Rusitha, U. Hemanth, P. Department of Information Technology Sri Sai Ram Engineering College India Department of Artificial Intelligence and Data Science Sri Sai Ram Institute of Technology India Department of Artificial Intelligence and Data Science SRM Valliammai Engineering College India

ISBN: (纸本)9781665476553

In essence, our application is a Smartphone app that facilitates ordering and purchasing of groceries, produce, and other goods. Our app introduces the concept of preserving social distance in tiny supermarkets. Our main goal is to make grocery shopping quick and safe. Through our app, customers can place orders from anywhere, including their homes and offices, and pick up their orders whenever they need to. The Shop Owners can view the orders placed by the consumers through our app, pack those items, and then send the customer a notification. Customers only need to pay the whole cost to select their items from the store. We gain safety and save time waiting in line for purchases thanks to this software. We anticipate that this software will be more helpful for shop owners and customers during the pandemic condition. © 2022 IEEE.

关键词： Sales

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Multi-Blockchain Based data Trading Markets With Novel Pricing Mechanisms

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IEEE/CAA Journal of Automatica Sinica 2023年第12期10卷 2222-2232页

作者： Juanjuan Li Junqing Li Xiao Wang Rui Qin Yong Yuan Fei-Yue Wang IEEE the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao 266590China the School of Artificial Intelligence Anhui UniversityHefei 266114 the Qingdao Academy of Intelligent Industries Qingdao 230031China the School of Mathematics Renmin University of ChinaBeijing 100872China the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 the Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China

In the era of big data,there is an urgent need to establish data trading markets for effectively releasing the tremendous value of the drastically explosive *** security and data pricing,however,are still widely regarded as major challenges in this respect,which motivate this research on the novel multi-blockchain based framework for data trading markets and their associated pricing *** this context,data recording and trading are conducted separately within two separate blockchains:the data blockchain(DChain) and the value blockchain(VChain).This enables the establishment of two-layer data trading markets to manage initial data trading in the primary market and subsequent data resales in the secondary ***,pricing mechanisms are then proposed to protect these markets against strategic trading behaviors and balance the payoffs of both suppliers and ***,in regular data trading on VChain-S2D,two auction models are employed according to the demand scale,for dealing with users’ strategic *** incentive-compatible Vickrey-Clarke-Groves(VCG)model is deployed to the low-demand trading scenario,while the nearly incentive-compatible monopolistic price(MP) model is utilized for the high-demand trading *** temporary data trading on VChain-D2S,a reverse auction mechanism namely two-stage obscure selection(TSOS) is designed to regulate both suppliers’ quoting and users’ valuation ***,experiments are carried out to demonstrate the strength of this research in enhancing data security and trading efficiency.

关键词： Auction data trading markets multi-blockchain pricing mechanisms

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Diagnosis of Plant Infection for Optimised Authomatic Health Monitoring System Using Vision Transformer Models 5

Diagnosis of Plant Infection for Optimised Authomatic Health...

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5th IEEE International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Thapliyal, Nitin Aeri, Manisha Satyarthi, Abhishek Kukreja, Vinay Sharma, Rishabh Graphic Era Hill University Computer Science and Engineering Uttarakhand Dehradun India Artificial Intelligence & Data Science Iimt College of Engineering Uttar Pradesh Greater Noida India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350383522

Mosaic Virus is highly responsible for the crop loss, especially the pepper, which is considered part of food crop, an essential aspect of world's agriculture. This work aims at automating the classification of disease severity level-related the Pepper Leaf Mosaic Virus Disease threshold through vision transformer (ViT) model to ensure a critical job. The classification of the severity is more often accompanied by a fairly significant amount of workload and arbitrariness, resulting in equipment innovation in most of the locations. The work applies ViT-based approaches with sufficient precision to appropriately classify a dataset, which contains 10,800 meticulously selected photographs. The present model obtained a commendable average accuracy of 97.25%, which shows that the model was able to detect even smaller differences between the classes of severity. The operational criteria that include the tale of the precision, recall, and F1-score highlight the model's ability to minimize to Feggsor false Positives with its ability to discriminate cases of viruses at different levels of the spectrum. The more advanced comparison charts made hand methodologies stand at the pinnacle in plant pathology studies. This study is not only beneficial in terms of illuminating the understanding about the Pepper Leaf Mosaic Virus but also gives farmers and researchers a transformative tool that could change the way disease control methods are used. Technologies AI that power ViT model are helping the agriculture industries throughout the world to implement sustainability and resiliency of the systems by providing responses in the right time and place in addressing viral infections. © 2024 IEEE.

关键词： Agricultural Automation Agricultural technology artificial intelligence Automated Diagnosis Crop Health Disease Management Global Food Security Image Classification Machine Learning Pepper Leaf Mosaic Virus Plant Pathology Precision Agriculture Severity Classification Vision Transformer ViT Model

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Automated AI-Powered Fruit Identification Using Convolutional Neural Network

Automated AI-Powered Fruit Identification Using Convolutiona...

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2025 International Conference on Multi-Agent Systems for Collaborative intelligence, ICMSCI 2025

作者： Sai Tejasree, K. Surendran, R. Rajakumar, B. Gomathi, R.M. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India J.N.N Institute of Engineering Department of Artificial Intelligence and Data Science Chennai India School of Computing Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509828

Clever system that can look at pictures of fruits and figure out what kind of fruit each picture shows. AI algorithms like deep learning, which is like giving the Machine learning model a crash course in fruit recognition. This method teaches the ML Model we clearly explained the Model using application's agent using PEAS and the application's task environment using the 6 dimensions by showing it tons of fruit images, so over time, it gets really good at spotting the differences and similarities between, say, a banana and a grape. We also used another technique called pattern recognition, which helps the computer pay attention to specific details like the fruit's color, shape, size and texture. Overcoming multiple obstacles in order to automatically identify the type of fruit from the picture. The variety of images is influencing the color, texture, and shape of many different types of fruits. When it came to fruit picture detection, Convolutional Neural Network (CNN) Algorithm outperformed standard support-vector-machine-based approaches using handcrafted features in terms of accuracy also, it is a lot faster to implement for new fruits. By integrating deep learning and pattern recognition techniques such as Convolutional Neural Network Algorithm we have got the accuracy of 84%, our system efficiently identified different fruit types from images, demonstrating the power and effectiveness of our methods. The goal of our project is to create a tool that can quickly and correctly identify many types of fruits in photos, which could be useful for things like sorting fruits in a grocery store or helping people learn about different fruits by using Convolutional Neural Network Algorithm. This is not just about teaching a computer to recognize fruits;it is about making technology that can understand and interact with the world in a way that is helpful to us. © 2025 IEEE.

关键词： Convolutional neural networks

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Observation points classifier ensemble for high-dimensional imbalanced classification

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CAAI Transactions on intelligence technology 2023年第2期8卷 500-517页

作者： Yulin He Xu Li Philippe Fournier‐Viger Joshua Zhexue Huang Mianjie Li Salman Salloum College of Computer Science&Software Engineering Shenzhen UniversityShenzhenChina Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ) Shenzhen UniversityShenzhenChina Faculty of Information Technology Macao University of Science and TechnologyMacaoChina School of Computing National University of SingaporeSingaporeSingapore

In this paper,an Observation Points Classifier Ensemble(OPCE)algorithm is proposed to deal with High-Dimensional Imbalanced Classification(HDIC)problems based on data processed using the Multi-Dimensional Scaling(MDS)feature extraction ***,dimensionality of the original imbalanced data is reduced using MDS so that distances between any two different samples are preserved as well as ***,a novel OPCE algorithm is applied to classify imbalanced samples by placing optimised observation points in a low-dimensional data ***,optimization of the observation point mappings is carried out to obtain a reliable assessment of the unknown *** experiments have been conducted to evaluate the feasibility,rationality,and effectiveness of the proposed OPCE algorithm using seven benchmark HDIC data *** results show that(1)the OPCE algorithm can be trained faster on low-dimensional imbalanced data than on high-dimensional data;(2)the OPCE algorithm can correctly identify samples as the number of optimised observation points is increased;and(3)statistical analysis reveals that OPCE yields better HDIC performances on the selected data sets in comparison with eight other HDIC *** demonstrates that OPCE is a viable algorithm to deal with HDIC problems.

关键词： classifier ensemble feature transformation high-dimensional data classification imbalanced learning observation point mechanism

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Smart framework for enhancing security of IoT linked devices in Healthcare Systems 5

Smart framework for enhancing security of IoT linked devices...

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5th International Conference on Information Management and Machine intelligence, ICIMMI 2023

作者： Duvey, Anurag Anand Rahi, Pankaj Gowri Ganesh, N.S. Basa, Santi Swarup Dept. of Artificial Intelligence & Data Science Poornima Institute of Engineering and Technology Jaipur India Health Information Technology Management Indian Institute of Health Management Research Bangalore India Dept. of Artificial Intelligence & Data Science Saveetha Engineering College Chennai India Dept. of Computer Science Maharaja Sriram Chandra Bhanja Deo University Odisha Baripada India

ISBN: (纸本)9798400709418

The adoption of blockchain technology is widespread across diverse industries due to its rapid advancement and high level of innovation. The technology in question is widely acknowledged for its ability to adapt and be utilized in diverse domains, thereby enabling the storage of data in interconnected fields through peer-to-peer networks. Blockchain technology demonstrates high performance in the storage of transactions that have minimal digital traces, as well as in situations where there is a need for immutability and transparency. The utilization of blockchain technology can potentially offer advantages in various domains such as supply chain management, the maintenance of dynamic patient authorization for data use, and the verification of patient, provider, or supplier identification in certain situations. The main objective of this research study is to investigate the application of blockchain technology in improving the security of Internet of Things (IoT) systems, particularly in the context of remote patient monitoring and its linked EHR system. This article explores the advantages of incorporating Internet of Things (IoT) devices into the remote patient monitoring practice, as well as the practical challenges that may arise during the installation phase. The proposed concept utilizes sophisticated and effective cryptographic methodologies, particularly the Advanced Encryption Standard (AES) scheme, to guarantee dependable data transmission across networks and safeguarded storage within cloud environments. © 2023 ACM.

关键词： Smart contract

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Disease and Medications Text Visualization Using Scattertext

Disease and Medications Text Visualization Using Scattertext

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2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Rama Krishna, K. Sandhya, Kaipa Praveen Gujjar, J. Devadas, Raghavendra M. Hiremani, Vani Sapna, R. Impact college of Engineering and Applied Sciences Department of Artificial Intelligence and Machine Learning Bengaluru India Impact college of Engineering and applied sciences Department of Data Science Bengaluru India Faculty of Management Studies Bengaluru India Department of Information Technology Manipal India University Pune India

ISBN: (纸本)9798331527495

Before text data can be analysed and visualised, it must be thoroughly cleaned due to its messy nature. data visualizations use the data to tell an engaging and simple-to-read story. That is what the Scattertext tool does. Scatter text allows which terms stand out in your corpora and how their frequency varies across categories. The dataset used in this paper includes reviews of drugs. This dataset offers a useful window into how people discuss their thoughts and experiences using various drugs. The drug names, user ratings, and the actual written reviews are among the details included in the dataset. This dataset consists of drug reviews collected from various sources, hence expressing a wide range of opinions and feelings. Each row in this dataset represents the experience a user had with a given medication and hence allows us to explore those emotions that are associated with any particular set of drugs. Understanding opinion expressed in the review about drugs might go a long way in helping decision-making processes in both healthcare and pharmaceuticals. The scatter plot distinguishes between labelled points and unlabelled ones by using a custom algorithm for Scattertext. By hovering their cursor over the labelled areas done client-side, users can interactively see which terms correspond to which points. © 2025 IEEE.

关键词： data visualization

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Multi-Modal LLM Driven Computer Interface 8

Multi-Modal LLM Driven Computer Interface

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Sowmiya, R. Revathi, P. Ragunath, D. Sindhuja, S. Gokila, P. Kalaivani, T. Sns College of Engineering Department of Artificial Intelligence and Data Science Tamilnadu Coimbatore India Bannari Amman Institute of Technology Department of Computer Science and Engineering Tamilnadu Sathyamangalam India Tamilnadu Coimbatore India Info Institute of Engineering Department of Computer Science and Engineering Tamilnadu Coimbatore India

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376425

This study presents a framework for multimodal models to control and interact with computers: The Multimodal-driven Computer Interface. A decision-making module is used by the framework to determine what actions are acceptable after it processes user input through a variety of modalities, such as speech, text, and gestures, and runs it through a multimodal fusion algorithm. Platform-specific APIs are then used to carry out these operations on the computer. It runs on Linux, Mac, and Windows platforms and is currently integrated with the multimodal LLM. Although the framework shows promising results, there are still issues with adjusting to different user demands and preferences and increasing the accuracy of mouse click position prediction. Potentially revolutionizing human-computer interaction, the Multimodal-driven Computer Interface offers new avenues for accessibility, productivity, and pleasure. © 2024 IEEE.

关键词： Windows operating system

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HUSS:A Heuristic Method for Understanding the Semantic Structure of Spreadsheets

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data intelligence 2023年第3期5卷 537-559页

作者： Xindong Wu Hao Chen Chenyang Bu Shengwei Ji Zan Zhang Victor S.Sheng Key Laboratory of Knowledge Engineering with Big Data(the Ministry of Education of China) Hefei University of TechnologyChinaSchool of Computer Science and Information EngineeringHefei University of TechnologyHefeiChina Research Institute of Artificial Intelligence Zhejiang LabHangzhouChina Department of Computer Science Texas Tech UniversityLubbockTX 79409USA

Spreadsheets contain a lot of valuable data and have many practical *** key technology of these practical applications is how to make machines understand the semantic structure of spreadsheets,e.g.,identifying cell function types and discovering relationships between cell *** existing methods for understanding the semantic structure of spreadsheets do not make use of the semantic information of cells.A few studies do,but they ignore the layout structure information of spreadsheets,which affects the performance of cell function classification and the discovery of different relationship types of cell *** this paper,we propose a Heuristic algorithm for Understanding the Semantic Structure of spreadsheets(HUSS).Specifically,for improving the cell function classification,we propose an error correction mechanism(ECM)based on an existing cell function classification model[11]and the layout features of *** improving the table structure analysis,we propose five types of heuristic rules to extract four different types of cell pairs,based on the cell style and spatial location *** experimental results on five real-world datasets demonstrate that HUSS can effectively understand the semantic structure of spreadsheets and outperforms corresponding baselines.

关键词： Spreadsheet semantic structure Information extraction Heuristics Cell function analysis Table structure analysis

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Recommendations of Smartphone Applications According to Customer Reviews and Capabilities 2

Recommendations of Smartphone Applications According to Cust...

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2nd International Conference on Augmented intelligence and Sustainable Systems, ICAISS 2023

作者： Ramnath, M. Rubavathi, C. Yesubai Ramco Institute of Technology Department of Artificial Intelligence and Data Science Tamil Nadu Rajapalayam India Francis Xavier Engineering College Department of Computer Science and Engineering Tamil Nadu Tirunelveli India

ISBN: (纸本)9798350325799

There are a plethora of new Android portable apps available now. As a result, making sure the apps you install on your mobile device are safe is a daunting undertaking for the average user. This study provides a popular and secure mobile App with a recommendation system to streamline the process. The design focus is on making recommendations for mobile apps by gauging their popularity and potential security issues. To index the apps and save the information in a database, a web crawler is employed. The programs are then sorted into groups according to their popularity and ratings. The suggested Android app provides a list of applications from the Google Play Store along with their respective security ratings whenever a query is executed. How popular an app is and what permissions it requires from the user significantly increase the app's potential security risks. This work aims to create such a recommendation system without sacrificing security or user engagement. © 2023 IEEE.

关键词： Recommender systems

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