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检索条件"机构=Dept. of Information Engineering and Computer Science and Mathematics"

共 8635 条记录，以下是231-240 订阅

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Simplifying Structure and Pattern in Complex Social Networks Using Graph Isomorphism 14

Simplifying Structure and Pattern in Complex Social Networks...

引用

14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Arunakumari, B.N. Kshama, S.B. Swasti, S. Sameeksha, B.H. Puri, Sonia Rubini, P.A. Bms Institute of Technology and Management Dept. of Computer Science and Engineering Bengaluru India Bms Institute of Technology and Management Dept. of Information Science and Engineering Bengaluru India

ISBN: (纸本)9798350335095

In recent years, networks have grown in size and complexity, traditional network testing methods have become time-consuming and inefficient. As a result, there is a need for more efficient and reliable network testing methods. One important topic in the field of network testing is graph pattern matching. Network analysis relies on graph pattern matching. The paper discusses the use of graph isomorphism for network testing. This paper also gives an overview of recent advances in isomorphism testing, which determines if two networks are structurally identical despite potential labeling discrepancies between them. The combination of isomorphism and pattern matching in network analysis is used to identify equivalent structures in different networks. This approach is used to identify and compare common patterns in complex network structures, such as those found in social networks. © 2023 IEEE.

关键词： Pattern matching

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Sarcasm Detection in Libyan Arabic Dialects Using Natural Language Processing Techniques 4

Sarcasm Detection in Libyan Arabic Dialects Using Natural La...

引用

4th IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and computer engineering, MI-STA 2024

作者： Alakrot, Azalden Dogman, Aboagela Ammer, Fathi Yefren College of Medical Technology Dept. of Information Technology Yefren Libya Libyan Academy for Postgraduate Studies Dept. of Electrical and Computer Engineering Al Zentan Libya University of Zawia Dept. of Computer Science Azawia Libya

ISBN: (纸本)9798350372632

Sarcasm is often used to convey the opposite of what is actually said (positive words, negative meaning). It is a type of humor that relies on the listener or reader to understand the intended meaning of the words. Sarcasm can be difficult to detect in written text, especially on social media platforms where people often use abbreviated language and emojis to convey their messages. The sarcasm detection can be a crucial role in refining Automated Sentiment (SA). In order to enhance the effectiveness of data-driven approaches for customer service and product development. Furthermore, the existing research on sarcasm detection in Arabic is limited. Also, there is a noticeable absence of studies in particular, the sarcasm detection in Libyan Arabic dialects. This study utilizes a data-set of 5082 collected from Facebook platform, labeled by team annotators experienced in the Libyan dialects as (sarcastic or non-sarcastic), and extracting some lexical and syntactic features which used to training Support Vector Machine (SVM) model. The results show commendable performance with an accuracy of 79.15%, precision of 79.3%, recall of 79.7%, and an F1 score of 79.5%. © 2024 IEEE.

关键词： Support vector machines

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Deep Learning-Based Image Analysis for Detecting Nutrient Deficiencies of Tomato Plants 5

Deep Learning-Based Image Analysis for Detecting Nutrient De...

引用

5th International Conference on Advancements in Computing, ICAC 2023

作者： Nirasha Jayasiri, K.C. Chandrasiri, Sanjeevi Rupasinghe, Shalini Karunanayake, K.O. Rivindu Uthayachandran, Abineshh Zihara, M.I. Fathima Sri Lanka Institute of Information Technology Dept. of Computer Science and Software Engineering Sri Lanka

ISBN: (纸本)9798350358131

Tomato is one of the most popular crops worldwide. The success of a tomato crop is highly dependent on the health of the plants. Nutrient deficiency surveillance is typically conducted through visual inspections, which can be challenging for inexperienced farmers and home gardeners to work accurately. There is a growing need for a quick, reliable, and accurate nutrient deficiency identification system to address this issue. The proposed method is based on image processing and deep learning technologies that are highly effective for image classification tasks. Two models were trained using a dataset collected from tomato plants in Sri Lanka and evaluated using Mask Region-based Convolutional Neural Network (Mask R-CNN) and, You Only Look Once (YOLO) for deficiency classification, and results obtained 92% and 98% accuracy, respectively. Deficiency dispersion level expressed as a percentage using Mask R-CNN and followed by image processing techniques. Overall, this proposed system offers a convenient and accessible tool for farmers and home gardeners to monitor and maintain the health of their tomato plants, enabling them to achieve optimal yields and ensure profitable returns. © 2023 IEEE.

关键词： Object detection

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Design of QR Code Tracking Car based on Monocular Vision

Design of QR Code Tracking Car based on Monocular Vision

引用

2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Shen, RuiBing Chang, Chih-Yung Hu, ZhiJie Wu, Shih-Jung Hou, Di Xi'an Eurasia University School of Information Engineering Xi'an China Dept. of Computer Science and Information Engineering Tamkang University Taiwan Xi'an ShiYou University Dept. of Electronic Engineering China

ISBN: (纸本)9798350324174

This paper designs an automatic tracking car that uses machine vision technology to realize QR code recognition. The car uses the MSP430F5529 chip as the main controller. It uses the OpenMV camera as the image acquisition sensor and the OpenCV library to process the acquired images. It can locate the target of the QR code by monoculture visual positioning technology. The car can obtain the distance between it and the leading vehicle, and compare the actual distance with the expected distance. The main controller can control the motor operation according to the distance deviation obtained, aiming to realize the automatic following function of the car. © 2023 IEEE.

关键词： Controllers

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Foreign Exchange Market Analysis based on Novel Grey Wolf based Extreme Learning Machine Predictor 4

Foreign Exchange Market Analysis based on Novel Grey Wolf ba...

引用

4th International Conference on Emerging Systems and Intelligent Computing, ESIC 2024

作者： Dash, Swaty Sahu, Pradip Kumar Mishra, Debahuti Veer Surendra Sai University of Technology Burla Dept. of Information Technology Odisha Sambalpur India University Dept. of Computer Science & Engineering Odisha Bhubaneswar India

ISBN: (纸本)9798350349856

Foreign exchange trading basically bridges a gap between buyer and seller to transact at a set of prices of the currencies to make profit out of it by the traders and investors. In this paper, foreign exchange predictive models are explored based on basic Extreme Learning Machine (ELM) along with optimized version of ELM. Initially, this work tried to obtain the best optimized ELM network based upon the four nature-inspired optimization methodologies such as;particle swarm, ant colony, moth flame and grey wolf optimization (GWO). From this phase, it has been observed that the ELM network optimized with GWO outperforms rest of other experimented optimized ELM networks with respect to error graphs and performance metrics. In order to evaluate the performance, the ELM-GWO currency exchange predictor, the recognition performance metrics such as;EVS, MAE, MSE and R2 Score are computed, the error graphs are obtained and the average computational time taken are compared. © 2024 IEEE.

关键词： Ant colony optimization

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An Effective Prediction of Rainfall Using Machine Learning Technique 5

An Effective Prediction of Rainfall Using Machine Learning T...

引用

5th IEEE International Conference on Electrical, computer and Communication Technologies, ICECCT 2023

作者： Rana, Nisha Guru Prasad, M. Sharma, Ashutosh Pratap, M.S. Anand Kumar, M. Aditya Pai, H. Dept. of Computer Science and Engineering Rishikesh India Graphic Era Deemed University Dept. Computer Science and Engineering Dehradun India Rishikesh India School of Computing and Information Technology Reva University Bengaluru India Dept. of Computer Application Dehradun India Dept. of Computer Science and Engg. Dehradun India

ISBN: (纸本)9781665493604

Climatic information such as temperature, humidity, and precipitation are useful for agriculturists, businesses, researchers, and the government. Estimating precipitation is a major factor that affects the environment and is one of the most important aspects of meteorological science. In this study, factual approaches and machine learning methods are used to estimate and forecast meteorological parameters for the government. Estimating precipitation is a major factor that affects the environment and is one of the most important aspects of meteorological science. Approaches are used to forecast and estimate precipitation. Daily observations were used as part of the experiment. Validation of results using real-world data is used to check the accuracy of forecasting model experimentation. The experimental results show that distribution, correlation, line-plots, and neural networks perform well for forecasting meteorological characteristics and have the best classification accuracy when compared to other types of machine learning methods for precipitation forecasting. © 2023 IEEE.

关键词： Machine learning

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Analyzing Voice Quality with Multi-Dimensional Voice Program for Disease Determination 6

Analyzing Voice Quality with Multi-Dimensional Voice Program...

引用

6th International Symposium on computer, Consumer and Control, IS3C 2023

作者： Liza, Rahmi Tsung, Chen-Kun National Chin-Yi University of Technology dept. Computer Science and Information Engineering Taichung Taiwan

ISBN: (纸本)9798350301953

Multi-Dimensional Voice Program (MDVP) parameters are very popular among physicians/clinicians to detect vocal pathologies and analyze various diseases of the vocal cords. In this paper, voice pathologies are automatically detected using the parameters of the MDVP. However, MDVP is commercial software, so this work is trying to build MDVP using Python to extract MDVP parameters useful for various experiments, automatic detection of sound pathologies, and automatic classification of voice recognition. This study evaluates MDVP parameters and applies the XGBoost model as a classification method to analyze and classify diseases. This work considers three sample data, polyps, nodules, and Reinke edema, popular in clinical vocal cords diseases, from Saarbruecken Voice Database (SVD) for data testing and training. Test results demonstrate the excellent ability of MDVP's parameter extraction to identify healthy voices and obtain accurate classification results to discriminate between healthy voices and pathological voices. The best overall accuracy is 98% using the XGBoost classifier. © 2023 IEEE.

关键词： Classification (of information)

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Instance Segmentation based Object Detection with Enhanced Path Aggregation Network

Instance Segmentation based Object Detection with Enhanced P...

引用

2023 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2023

作者： Onthoni, Ade Indra Sahoo, Prasan Kumar Dept. of Computer Science and Information Engineering Chang Gung University Guishan Taoyuan33302 Taiwan

ISBN: (纸本)9798350348071

Multi-scale networks rely heavily on the aggregation process to aggregate feature information into other feature maps. However, it has disadvantages in aggregating information, where the localization information becomes inconsistent. An Enhancing Path Aggregation Network through concatenation and attention mechanism is proposed here to improve the aggregation path for generating the feature maps in multi-scale network. This approach helps to keep information consistently during the process of aggregation. The proposed model is evaluated using the COCO dataset, which achieves significant improvements on several metrics. © 2023 IEEE.

关键词： Object detection

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Multicarrier Waveforms for Moon-to-Earth RF Transmission 10

Multicarrier Waveforms for Moon-to-Earth RF Transmission

引用

10th IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2023

作者： Rahman, Talha Faizur Marojevic, Vuk Sacchi, Claudio Mississippi State University Dept. of Electrical and Computer Engineering Mississippi StateMS United States University of Trento Dept. of Information Engineering and Computer Science Trento Italy

ISBN: (纸本)9781665456906

More than 50 years after the last Apollo mission, the race to the Moon has started again. In the framework of new missions, it will be of paramount importance to establish a reliable communication link between the vehicles (or astronauts) present on the Moon's surface and an Earth station. Alternative choices consider radio-frequency (RF), optical, and hybrid optical-RF solutions. In this paper, we focus on the RF transmission case. Recent works evidenced how diversity is required to face multipath fading issues due to the reflection of electromagnetic rays on the Lunar surface. For this reason, suitable waveforms, which are robust against multi path distortion should be considered. In this work, we propose multicarrier Orthogonal Frequency Division Multiplexing (OFDM), Single-Carrier OFDM (SC-OFDM), and Constant-Envelope OFDM (CE-OFDM). The comparative results will be discussed in order to select the best solution to cope with the various tradeoffs between link performance, spectral efficiency, and computational complexity. © 2023 IEEE.

关键词： 5G mobile communication systems

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Unlocking Efficiency in Agricultural Supply Chains: A Secure and Transparent Approach through Blockchain Technology

Unlocking Efficiency in Agricultural Supply Chains: A Secure...

引用

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

作者： Lohith, J.J. Shreya, S. Hamsa Priya, J.L. B.M.S. College of Engineering Dept. of Computer Science and Engineering Bangalore India D.S.C.E Dept. of Information Science and Engineering Bangalore India B.M.S. College of Engineering Dept. of Electronics and Telecommunications Bangalore India

ISBN: (纸本)9798350372502

Supply Chain Management (SCM) involves orchestrating various processes that extend from acquiring raw materials to delivering finished products to end consumers. The key objectives of a proposed supply chain in agriculture, emphasizes information-driven processes, cost reduction, and customer impact. It creates a versatile system capable of managing the supply chain for diverse commodities within a country, while also addressing the crucial need for increased transparency and traceability in data throughout the chain of activities. In our proposed approach to agricultural supply chain management (SCM), the focus is on creating a secure, transparent, and traceable SCM. To achieve this, we leverage cutting-edge technologies like the Ethereum blockchain and the Interplanetary File System (IPFS). The resulting software is a Decentralized Application (DApp) that orchestrates a series of activities within the agricultural industry, using cryptocurrencies to establish a seamless and efficient supply chain management system. This software platform is fortified by the secure algorithms of blockchain, providing an added layer of reliability. Additionally, our application incorporates transparency and traceability, ensuring user-friendly functionality and making it more accessible for users. © 2024 IEEE.

关键词： Blockchain

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