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A novel approach incorporating feature extraction followed by YOLOv7 for quality enhancement of mangoes in Bangladesh 14

A novel approach incorporating feature extraction followed b...

引用

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

作者： Kundu, Debashis Rahaman, Md. Mushfiqur Sakib, Md. Nazmus Abdullah Al Sohan, Md. Faruk Fardaush Mithu, Jannatul Hossain, Afzal Aktar, Nishita American International University- Bangladesh Dept. Management Information Systems Dhaka Bangladesh Daffodil Institute of It Dept. of Computer Science and Engineering Dhaka Bangladesh World University of Bangladesh Dept. of Computer Science and Engineering Dhaka Bangladesh American International University- Bangladesh Dept. of Computer Science Dhaka Bangladesh North South University Dept. of Electrical and Computer Engineering Dhaka Bangladesh Savar Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350335095

Qualitative approach for automated grading and quality assessment of fruits, machine learning techniques are crucial in agricultural applications. Automation enhances a nation's agricultural quality, production, and economic prosperity. Fruit quality grading, particularly the surface fault identification of a fruit, is a crucial indicator in the export market. This is particularly important for mangoes, which are quite well-liked inBangladesh. On the other hand, the physical grading of mangoes is a procedure that is labor-intensive, prone to error, and very subjective. In this paper, we proposed a YOLOv7 integrated Discrete wave transformation computer vision system. The proposed model includes support vector machine (SVM) and decision tree for the classification of high-quality mangoes. The results of the experiments show that the proposed solution obtained 96.25% accuracy when the system was trained and tested using a publicly accessible mango database. © 2023 IEEE.

关键词： Support vector machines

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FedStar Caching: Decision Center Assisted Federated Cooperative Edge Caching 4

FedStar Caching: Decision Center Assisted Federated Cooperat...

引用

4th IEEE International Conference on Human-Machine systems, ICHMS 2024

作者： Gharib, Sirvan Kesargheh, Mohammad Mansour Seyedmohammadi, S. Jamal Hajiakhondi, Zohreh Abouei, Jamshid Plataniotis, Konstantinos N. Yazd University Dept. Of Electrical Engineering Yazd Iran Concordia University Inst. Of Information Systems Engineering Montreal Canada Concordia University Dept. Of Electrical Engineering Montreal Canada University Of Toronto Dept. Of Electrical And Computer Engineering Toronto Canada

ISBN: (纸本)9798350315790

With the explosion of data, Wireless Edge Caching (WEC) has become a promising approach for locally accessing cached contents. Due to the limited storage capacity of local caching devices and the varying preferences of humans for content, it is necessary to predict popular contents. In this article, we will address two distinct objectives: 1) Popularity prediction of the content that should be cached at the edge to effectively utilize edge device memory. 2) Edge devices collaboration for efficient content delivery. Accordingly, we propose an FL-based Star Cooperative Caching (FedStar Caching), utilizing a Star network topology for realizing an efficient cooperation among Femto-cell Access Points (FAPs) using a Decision Center (DC) to enhance power efficiency and delay performance. Considering human sensitivity to privacy, collecting users' data on a central server is not desirable, therefore, we leverage Federated Learning (FL) to alleviate this challenge. Simulation results demonstrate that the proposed method outperforms alternatives in terms of cache efficiency, as well as delay and power consumption. © 2024 IEEE.

关键词： Stars

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Electroencephalographic Biomarkers for Major Depressive Disorder and Alcohol Use Disorder 7

Electroencephalographic Biomarkers for Major Depressive Diso...

引用

7th IEEE International Conference on Electrical, Electronics, and System Engineering, ICEESE 2024

作者： Maidin, Muhammad Nur Aiman Haja Yahya, Norashikin Saad, Mohamad Naufal Mohamad Khan, Danish M. Kamel, Nidal S. Electrical & Electronics Eng. Dept. Universiti Teknologi PETRONAS Perak Malaysia Dept. of Computing & Information Systems Sunway University Selangor Malaysia College of Eng. & Computer Science VinUniversity Hanoi Viet Nam

ISBN: (纸本)9798350367447

Major Depressive Disorder (MDD) and Alcohol Use Disorder (AUD) are common neurological disorders that significantly impact physical health, family life, and work. Accurate diagnosis is essential for early intervention and treatment. However, conventional DSM-based diagnosis is subjective and susceptible to errors due to patient dishonesty or memory lapses. This study introduces a more reliable and objective diagnostic approach using effective connectivity (EC) from EEG recordings of 30 healthy controls, 30 MDD, and 30 AUD patients. EC, calculated via partial directed coherence, was used as input for an SVM model, achieving a peak classification accuracy of 95.3%, with perfect accuracy in the beta and gamma rhythms. These findings underscore EC’s potential as biomarkers for more accurate diagnosis and early intervention in neurological disorders. © 2024 IEEE.

关键词： Electroencephalography

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Fractional Order Ultra-Local Model-Based Sliding-Mode-Assissted Disturbance Observer and Model-Free Control

Fractional Order Ultra-Local Model-Based Sliding-Mode-Assiss...

引用

2024 International Conference Automatics and Informatics, ICAI 2024

作者： Zhang, Liuchang Wang, Haoping Tian, Yang Zhuang, Xincheng Azar, Ahmad Taher Ahmed, Saim Nanjing University of Science and Technology Dept. School of Automation Nanjing China Prince Sultan University Dept. Automated Systems & Soft Computing Lab Riyadh Saudi Arabia Prince Sultan University Dept. College of Computer and Information Sciences Riyadh Saudi Arabia

ISBN: (纸本)9798350353907

This paper puts forward a fractional order sliding-mode-assisted disturbance observer-based model-free control (FO-SAMDOMFC) methodology for fractional order system with disturbance. First, the system dynamic model is rewritten as a fractional order ultra-local model (ULM), and a SMADO is designed to estimate the lumped disturbance term. Then, A closed-loop control law is proposed on the basis of the ULM with the objective of guaranteeing the convergence of the tracking error. Next, a proof of the stability of the closed-loop system is given based on the fractional extension of Lyapunov's direct method. Finally, the simulation compared with other controllers based on MATLAB/Simulink is realized, and the simulation results validate the proposed method. © 2024 IEEE.

关键词： Sliding mode control

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Execution of information Processes Subjected to the Influence of Two Types of Disturbing Effects with Different Probability Characteristics 5

Execution of Information Processes Subjected to the Influenc...

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5th International Conference on Control systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Nachev, Atanas Pavlova, Daniela Zhelezov, Stanimir Kordov, Krasimir Gindev, Panayot University of Library Studies and Information Technologies Sofia Bulgaria University of Library Studies and Information Sofia Bulgaria Konstantin Preslavsky University of Shumen Dept. of Computer Systems and Technologies Shumen Bulgaria Konstantin Preslavsky University of Shumen Dept. of Computer Informatics Shumen Bulgaria

ISBN: (纸本)9798350309126

A specific characteristic of computer and communication networks is their limited ability to directly apply the "classical reliability theory"to determine their reliability. This necessitates the development and use of methods that combine the reliability characteristics of network elements with their functional characteristics. In most cases, this boils down to methods for determining the functional reliability of network structures, i.e., their ability to perform their assigned functions with a specified efficiency. Like the methods of classical reliability theory, these methods also need to possess a high degree of invariance. In this paper a method for solving such a problem is proposed, based on defining the term "information process"and determining the time for its execution, taking into account the reliability of the means implementing it. © 2023 IEEE.

关键词： Reliability theory

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A Secured Technique for Executing Queries over Multidimensional Encrypted Data 1

A Secured Technique for Executing Queries over Multidimensio...

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1st International Conference of Intelligent Methods, systems and Applications, IMSA 2023

作者： Al-Musibe, Norah Saud Hamdi, Hedi Abd El-Aziz, A.A. Jouf University Dept. of Computer Science KSA Saudi Arabia University of Manouba Tunisia Jouf University Dept. of Information Systems KSA Saudi Arabia Cairo University Egypt

ISBN: (纸本)9798350335569

In new computing architectures, data is outsourced and sensitive data becomes vulnerable in various areas. Owners must guarantee that their data are secure from breaches and unauthorized users and available anytime. Various techniques have been proposed to maintain a certain degree of privacy in the database and to allow efficient execution of queries on cloud computing. These methods cannot securely support queries over encrypted data without leaking private data. Therefore, in this paper, a secure technique was proposed for executing queries over encrypted data, and the proposed technique was based on the design of CryptDB. This technique eliminates the limitations of CryptDB to perform server-side computations on cryptographic data of different principles. The proposed technique attempts to overcome CryptDB's limitations by encrypting with different keys in multidimensional mode and running each query on the corresponding data encrypted by the same key. © 2023 IEEE.

关键词： Cryptography

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Exercise and Sedentary Activity Recognition Using Late Fusion: Building Adaptable Uncertain Models 26

Exercise and Sedentary Activity Recognition Using Late Fusio...

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26th International Conference on information Fusion, FUSION 2023

作者： Garcia, Ezequiel Juarez Rodrigues, Victoria R. Fazli, Mehrdad Barnes, Laura E. Napoli, Nicholas J. University of Florida Dept. of Electrical and Computer Engineering GainesvilleFL32611 United States University of Virginia Dept. of Systems and Information Engineering CharlottesvilleVA22903 United States

ISBN: (纸本)9798890344854

Wearable smart devices are capable of capturing a variety of information from their users using a multitude of noninvasive sensing modalities. Using features from the raw measurements of wearable devices, sensor fusion enables us to obtain a holistic picture of the users' context and monitor their activity state with increased accuracy. Human activity recognition using noninvasive sensors allows us to capture the natural behavior of users in their day-to-day lives. This in-the-wild activity recognition, however, poses several key challenges that must be addressed to create effective classification models. The main challenges are class imbalance, uncertainty in classifier decisions, and large feature spaces. To address them, this study further explores a probabilistic sensor fusion method called Naive Adaptive Probabilistic Sensor (NAPS) Fusion. In doing so, we establish the viability of NAPS Fusion for natural human activity recognition using noninvasive sensing modalities. NAPS Fusion handles dimensionality reduction by creating reduced feature sets and mitigates the class imbalance issue through the use of Synthetic Minority Oversampling Technique (SMOTE). Moreover, NAPS Fusion addresses uncertainty in the decisions of classifiers using a Dempster-Shafer theoretic late fusion framework. Our empirical evaluation demonstrates that NAPS Fusion has broad applications beyond its original design for cognitive state detection. It outperforms similar decision level sensor fusion methods (late fusion using averaging, LFA, and late fusion using learned weights, LFL) in the detection of exercise and sedentary activities such as walking, running, lying down, and sitting. We observe improvements of up to 56% in F1 score and up to 59% in precision with NAPS Fusion over the compared methods. © 2023 International Society of information Fusion.

关键词： Wearable sensors

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Clinical Score Estimation for Determining Oro-Facial Dysfunction Severity 23

Clinical Score Estimation for Determining Oro-Facial Dysfunc...

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2023 International Conference on Robotics, Control and Vision Engineering, RCVE 2023

作者： Ipapo, Trassandra Jewelle Del Rosario, Charlize Abu, Patricia Angela Alampay, Raphael Ateneo Laboratory for Intelligent Visual Environment Dept. of Information Systems and Computer Science Ateneo de Manila University Quezon City Philippines

ISBN: (纸本)9798400707742

Stroke and amyotrophic lateral sclerosis manifest symptoms that affect facial motion in patients. Tracking these movements and assessing the severity of the impairment can be achieved with facial alignment technology and classification algorithms. Using the Toronto NeuroFace Dataset consisting of patients and healthy individuals performing clinical examination tasks, this study focuses on score estimation of clinical examinations to determine oro-facial dysfunction severity. Facial landmarks extracted using the 2D FAN were used to determine features under range of motion, speed of motion, and symmetry. Speech language pathologist scores from the dataset were transformed using ordinal encoding, then oversampled using random oversampling. The features and transformed scores were fed into random forest classifier models to predict a score using a scale of 1 to 4 for each feature category. The results show that the proposed method is able to estimate oro-facial dysfunction severity and classify between healthy individuals and patients. The average performance of the model setups are comparable to that of the baseline in terms of accuracy ( © 2023 ACM.

关键词： Score Estimation Face Alignment Oro-facial Dysfunction Ordinal Classification

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Oversampling Facial Motion Features Using the Variational Autoencoder to Estimate Oro-facial Dysfunction Severity 1

Oversampling Facial Motion Features Using the Variational Au...

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1st International Conference on computer Graphics and Image Processing, CGIP 2023

作者： Ipapo, Trassandra Jewelle Del Rosario, Charlize Alampay, Raphael Abu, Patricia Angela Ateneo de Manila University Ateneo Laboratory for Intelligent Visual Environments Dept. of Information Systems and Computer Science Quezon City Philippines

ISBN: (纸本)9798350333183

Class imbalance, which negatively affects classification model performance, is a common problem with machine learning. Various oversampling methods have been developed as potential solutions to compensate for imbalanced data. SMOTE is one of the more common methods employed. However, deep generative models such as the variational autoencoder are showing promise as alternatives to traditional oversampling methods. This study investigated the potential of variational autoencoders in learning the distribution of the minority class and producing new observations of facial motion features extracted from an imbalanced medical dataset as well as to see the effects of oversampling before and after the train-test split. The effectiveness of the variational autoencoder was compared to SMOTE in increasing ordinal classification performance across the metrics of accuracy, accuracy±1, inter-rater reliability, specificity, and sensitivity with no oversampling serving as the baseline. The results show that the variational autoencoder has potential as an oversampling method for facial motion features in the context of oro-facial dysfunction estimation. Oversampling prior to the train-test split was also shown to improve classification performance. © 2023 IEEE.

关键词： Statistical tests

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Development of Augmented Reality-based Dental Surgical Guide System for Clinical Use 13

Development of Augmented Reality-based Dental Surgical Guide...

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13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Fukuda, Yusuke Takebayashi, Akira Yamamoto, Hiroaki Kano, Toru Ibaraki University Dept. Major in Computer and Information Sience Ibaraki Japan Medical Engineering Lab. Saitama Japan Tsuda Dental Clinic Ibaraki Japan Ibaraki University Dept. of Mechanical Systems Engineering Ibaraki Japan

ISBN: (纸本)9798350355079

Surgical guide plates, which are used in dental implant treatments, have some limitations that cause problems for the operator and patient. This study aims to develop an augmented-reality-based surgical guide system to solve these problems and discusses its use in clinical practice. Our surgical guide system achieved a good accuracy in drilling simulations on training typodonts, demonstrating its potential in clinical practice. © 2024 IEEE.

关键词： Dental prostheses

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