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2024 Symposium on Beyond the Canopy: Technologies and Applications of Remote Sensing

作者： Hosingholizade, Ali Erfanifard, Yousef Alavipanah, Seyed Kazem Pirasteh, Saied Garcia Millan, Virginia Dept. of Remote Sensing and GIS Faculty of Geography University of Tehran Tehran Iran Institute of Artificial Intelligence School of Mechanical and Electrical Engineering Shaoxing University China Department of Geotechnics and Geomatics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602105 India Dept. of Computer Science and Programming Languages School of Computer Science and Enginering University of Málaga Málaga Spain

The shape and area of the crown of each tree are among the most influential parameters for identifying and controlling the processes of photosynthesis, respiration, transpiration and its management. In such a way that various physiographic functions, such as carbon dioxide absorption, light energy absorption, oxygen release and transpiration, which are vital for the growth and development of the tree, are done in the crown. In this research, the RGB image of the UAV with a spatial resolution of 2 cm was resampled to three pixel sizes of 10, 30 and 50 cm. Then, each image was classified separately by SVM, ANN and MLC algorithms, which are all part of Ensemble. In the next step, each of the obtained crowns was compared with the digitization of the same crown, and based on the area of the crown obtained from each classification and normalization method, the weight was obtained specifically for the same crown. Finally, by using the weighted majority voting method, classifications were fusioned at the decision level. The results showed that the ANN method gives better results in all pixel sizes compared to MLC and SVM. Also, the combination of different classification methods with the weighted majority voting method based on the weight assigned to the same crown based on each classification method has significantly increased the classification accuracy of the tree crown in all the sizes of the analyzed pixels. © Author(s) 2024.

关键词： Pixels

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Coue Application: User Emotional Reasoning Chain for Enhancing Brand Public Opinion Management 21

Coue Application: User Emotional Reasoning Chain for Enhanci...

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21st International computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2024

作者： Jingwen, Deng Xintao, Ding School of Foreign Languages University of Electronic Science and Technology of China Chengdu China University of Massachusetts Amherst Dept. Electrical and Computer Engineering Boston United States

ISBN: (纸本)9798331519254

This study aims to improve corporate brand public opinion management through user emotional reasoning, focusing on understanding users' psychological states and applying emotion analysis methods. Existing research typically uses end-to-end generative models, fine-tuning small pre-trained language models for emotion analysis. However, these methods lack fine-grained emotional state understanding, resulting in lower sentiment analysis accuracy and limited model interpretability. To address this, the study introduces a novel framework, Co De (Chaln-of-User-Emotlonal), based on large language models. CoDebreaks down emotion analysis into a phased reasoning process with three chains: emotion reasoning, public opinion trend, and response generation. By using background enhancement strategies, the method improves emotional state analysis and sentiment prediction, enabling real-time market sentiment monitoring and reducing brand public opinion crises. © 2024 IEEE.

关键词： Public policy

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Effectiveness of Performance Visualizations for Declarative Model Transformations

Effectiveness of Performance Visualizations for Declarative ...

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IEEE International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT)

作者： Raffaela Groner Matthias Tichy Dept. of Computer Science and Engineering Chalmers | University of Gothenburg Gothenburg Sweden Institute of Software Engineering and Programming Languages Ulm University Ulm Germany

ISBN: (数字)9798331528485

ISBN: (纸本)9798331528492

Several profilers for general-purpose languages like Java offer visualizations to support users in understanding the execution of a program and identifying the causes of a performance issue. Unfortunately, these performance visualizations are difficult to reuse in profilers for declarative model transformations since they cannot display transformation-specific information. For example, a profiler for a declarative model transformation language must provide information on the traversal of the input model since it impacts the performance but is hidden from the developer. Moreover, the respective visualization must scale for input models that consist of several thousand model elements. Hence, we developed performance visualizations for the declarative model transformation language Henshin that provide insights into the transformation execution. Subsequently, we performed a mixed methods study with 18 Henshin novices to evaluate the effectiveness of our visualizations. In our study, the participants tried to improve the execution performance of four transformations by performing a root cause analysis using our visualizations. The results of our study show that depending on the task, between 16 and 18 participants understood the execution of a transformation correctly based on our visualizations. Moreover, between 12 and 18 participants proposed effective optimizations using our visualizations.

关键词： Visualization Root cause analysis Java Color Software Encoding Data mining Optimization

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Developing Enhanced Conversational Agents for Social Virtual Worlds

arXiv

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arXiv 2025年

作者： Griol, David Sanchis, Araceli Molina, José Manuel Callejas, Zoraida Dept. of Computer Science Universidad Carlos III de Madrid Spain Dept. of Languages and Computer Systems University of Granada Spain

In this paper, we present a statistical model for spoken dialog segmentation that decides the current phase of the dialog by means of an automatic classification process. We have applied our proposal to three practical conversational systems acting in different domains. The results of the evaluation show that is possible to attain high accuracy rates in dialog segmentation when using different sources of information to represent the user input. The statistical model developed with human-machine dialog corpora has been applied to human-human conversations and provides a good baseline as well insights in the model limitation. © 2025, CC BY-NC-ND.

关键词： Chatbots

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Home Care Assistance Solution based on a Software Multi-Agents System 24

Home Care Assistance Solution based on a Software Multi-Agen...

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24th International Conference on Control Systems and computer science, CSCS 2023

作者： Rasras, Mohammad Marin, Iuliana Radu, Serban University Politehnica of Bucharest Doctoral School of Automatic Control and Computers Bucharest Romania University Politehnica of Bucharest Dept. of Engineering in Foreign Languages Bucharest Romania University Politehnica of Bucharest Dept. of Computer Science Bucharest Romania

ISBN: (纸本)9798350313390

A smart home allows automated technology to control systems and appliances to assist daily life activities. In the current work, a prototype of a designed smart home health-aware system is presented. Three predefined ruled agents have been used to gather data, communicate between themselves, interpret the data based on several machine learning algorithms to predict abnormality for cardiac conditions. The paper also compares results obtained by running five machine learning algorithms. The agents function in accordance with predefined dataset describing residents ' age, gender, height, weight, systolic and diastolic blood pressure, cholesterol, and glucose levels, smoking and alcohol consumption habits, and lastly, physical activity. Our plan is to simplify ubiquitous health monitoring for smart home's residents. The proposed solution aims to monitor parametric measurements to alert health specialists in case of emergencies. © 2023 IEEE.

关键词： Multi agent systems

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SMART HOME ENVIRONMENT MODELLED WITH A MULTI-AGENT SYSTEM

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical Engineering and computer science 2023年第1期85卷 365-376页

作者： Rasras, Mohammad Marin, Iuliana Radu, Șerban Dept. of Engineering in Foreign Languages University POLITEHNICA of Bucharest Romania Dept. of Computer Science University POLITEHNICA of Bucharest Romania

A smart home can be considered a place of residence that enables the management of appliances and systems to help with day-to-day life by automated technology. In the current paper is described a prototype that simulates a context-aware environment, developed in a designed smart home. The smart home environment has been simulated using three agents and five locations in a house. The context-aware agents behave based on predefined rules designed for daily activities. Our proposal aims to reduce operational cost of running devices. In the future, monitors of health aspects belonging to home residents will sustain their healthy life daily. © 2023, Politechnica University of Bucharest. All rights reserved.

关键词： Multi agent systems

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SMART HOME ENVIRONMENT MODELLED WITH A MULTI-AGENT SYSTEM

arXiv

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arXiv 2023年

关键词： Multi agent systems

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A novel hybrid CNN-KNN ensemble voting classifier for Parkinson’s disease prediction from hand sketching images

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Multimedia Tools and Applications 2024年 1-33页

作者： Saleh, Shawki Ouhmida, Asmae Cherradi, Bouchaib Al-Sarem, Mohammed Hamida, Soufiane Alblwi, Abdulaziz Mahyoob, Mohammad Bouattane, Omar EEIS Laboratory ENSET of Mohammedia Hassan II University of Casablanca Mohammedia Morocco STIE Team CRMEF Casablanca-Settat Provincial Section of El Jadida El Jadida24000 Morocco College of Computer Science and Engineering Taibah University Medina42353 Saudi Arabia 2IACS Laboratory ENSET of Mohammedia Hassan II University of Casablanca Mohammedia Morocco Department of Computer Science Applied College Taibah University Medina Saudi Arabia Dept. of Languages and Translation College of Arts and Humanities Taibah University Medina Saudi Arabia Technical Community College Taiz Yemen

Parkinson's disease is a progressive neurodegenerative disorder that causes significant physical disabilities and reduces the quality of life. This disease is caused by the loss of dopamine-producing cells in the brain. Its symptoms are Speech disorders, muscle rigidity, bradykinesia and tremors that cause involuntary shaking or trembling, typically starting in the hands, fingers, or limbs at rest. In this work, we focused on predicting this disease via the hand tremor, which appears in the speed and pen pressure that vary between healthy and affected people during sketching spiral and waves. To enhance the medical services, improve lifestyle and for early detection of people with Parkinson’s disease, we proposed an ensemble voting classifier that combines the Convolutional Neural Network and K-Nearest Neighbours (KNN) to decide whether or not a person has Parkinson's disease based on predicting spiral and wave sketching separately. Contrary to the traditional Convolutional Neural Network, the proposed architecture offers better flexibility in scenarios where data may be small and imbalanced to avoid overfitting or when capturing the nuanced relationships between data points (by considering their neighbours) can be beneficial. Moreover, the proposed system has been built to automate the extraction of features from images and perform classification. This work represents several approaches, such as image processing, developing Convolutional Neural Networks models, hyper-parameters tuning, transfer learning, feature extraction and developing a hybrid classifier that combines deep learning and machine learning to enhance the performance of the prediction. We have developed six models to predict Parkinson's disease using a Spiral-Wave dataset and provided a detailed explanation and comparison between their performances. Based on these models, we built the hybrid ensemble voting CNN-KNN classifier that reached 96.67% accuracy and 93.33% and 100% sensitivity and precision,

关键词： Feature extraction

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A Logic Study of NL Fuzzy Degree 16

A Logic Study of NL Fuzzy Degree

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16th IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2021

作者： He, Xia Hu, Tingshu Hua, Jie Wang, Chunmei Hong, Long Huaiyin Institute of Technology Dept. of Foreign Languages Huaian China Nanjing University of Posts and Telecommunications Dept. of Computer Science Nanjing China

ISBN: (纸本)9781665405539

Natural language is inherently fuzzy. Medium Logic (ML) reveals that the essence of language fuzziness is the intermediary state of its semantics, and the measuring of Medium Truth Degree (MMTD) is the tool quantifying this intermediary state. From the perspective of part of speech, the fuzziness of language is mainly reflected in three parts of speech: adjectives, verbs and adverbs. This article uses MMTD and establishes a metric function that quantifies the fuzzy degree according to the independence of each part of speech. On this basis, it proposes concepts such as leaf words and word links to establish a method to quantify the fuzzy degree of sentences. © 2021 IEEE.

关键词： Fuzzy systems

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Coue Application: User Emotional Reasoning Chain for Enhancing Brand Public Opinion Management

Coue Application: User Emotional Reasoning Chain for Enhanci...

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International Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： DENG JINGWEN DING XINTAO School of Foreign Languages University of Electronic Science and Technology of China Chengdu China Dept. Electrical and Computer Engineering University of Massachusetts Amherst Boston USA

ISBN: (数字)9798331519254

ISBN: (纸本)9798331519261

关键词： Analytical models Emotion recognition Sentiment analysis Accuracy Large language models Market research Wavelet analysis Cognition Robustness Multilingual

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