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13th International Electrical Engineering Congress, iEECON 2025

作者： Tokampang, Sudarat Apirattanon, Nattapong Sisuk, Noppadon Kaewpoonsuk, Anucha Naresuan University Faculty of Science Deparment of Physics Phitsanulok Thailand Phibunsongkhram Rajabhat University Program of Computer Engineering Faculty of Industrial Technology Phitsanulok Thailand

ISBN: (纸本)9798331543952

This article presents a method for indirectly measuring the moisture content of paddy using a cylindrical capacitive sensor combined with Charge Integrator Circuits. The moisture measurement device operates based on the principle of the dielectric constant of paddy, which changes according to the moisture content within them. The system consists of a moisture detection section utilizing a cylindrical capacitor, a signal generator operating at a frequency of 500 Hz with a microcontroller, a signal conditioning circuit converting the signal to voltage, and a processing unit. Testing was conducted with paddy at five different moisture levels, demonstrating the ability to accurately determine the moisture content of the rice. When compared to the commercially available PM-450TH moisture meter, the results showed a linear response across the measurement range, with an R2 value of 0.9824 and an average error of 2.6%. This technology has the potential for further development and application to other types of seeds in the future. © 2025 IEEE.

关键词： charge integrator circuits cylindrical capacitive sensors paddy moisture

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Fake Reviews Detection Using Deep Learning: A Survey.

Fake Reviews Detection Using Deep Learning: A Survey.

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Intelligent Methods, Systems, and Applications (IMSA)

作者： Yasmeen Abdelmohsen Khaled Wassif Nagy Ramadan Department of Information Systems and Technology Faculty of Graduate Studies for Statistical Research Cairo University Giza Egypt Department of Computer Science Faculty of Computers and Artificial Intelligence Cairo University Giza Egypt

ISBN: (数字)9798350362633

ISBN: (纸本)9798350362640

Online shopping and e-commerce platforms are increasingly plagued by fake reviews, which undermine consumer trust and distort purchasing decisions. This survey addresses the critical need for effective detection mechanisms by exploring the application of deep learning techniques in identifying fake reviews. It carefully examines both supervised and unsupervised deep learning models, presenting their use cases, the features they prioritize, and their effectiveness in different scenarios. Key contributions of this survey include a comprehensive review of current methodologies, a critical comparison of their practical applications, and a discussion on the challenges of implementing these models. Furthermore, the survey identifies promising future research directions aimed at enhancing the accuracy and reliability of fake review detection systems. By synthesizing insights across various studies, this paper contributes significantly to the academic and practical understanding of deep learning's potential to combat the issue of fake reviews in digital commerce.

关键词： Deep learning Surveys Accuracy Reviews Training data Market research Classification algorithms

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Prediction of DHF (Dengue Hemorrhagic Fever) Severity Using Random Forest, KNN, Decision Tree and Naïve Bayes 7

Prediction of DHF (Dengue Hemorrhagic Fever) Severity Using ...

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7th IEEE International Conference on information technology and Digital Applications, ICITDA 2022

作者： Pohan, Husni Iskandar Suparta, Wayan Heryadi, Yaya Wibowo, Antoni Lukas Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Institut Teknologi Nasional Yogyakarta Department of Electrical Engineering Yogyakarta55281 Indonesia Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta12930 Indonesia

ISBN: (数字)9781665461368

ISBN: (纸本)9781665461368

Dengue Hemorrhagic Fever is an acute viral infectious disease caused by the dengue virus. Transmitted through the bite of Aedes Mosquitoes and divided into 4 severity. Severity 1 and 2 are characterized by a decrease in platelet levels below normal and there is a change in hemoconcentration, while Severity 3 and 4 are included in Dengue Shock Syndrome (DSS). The purpose of the study was to classify the severity of dengue, based on age, gender, platelets, body temperature, bleeding, and also doctor's recommendation. The advancement of information technology is the reason for the development of medical science, especially with artificial intelligence. Abundant medical data becomes a source that can be processed in improving the quality of medical information. The method chosen is Random Forest, kNN, Decision Tree and Naïve Bayes. The dataset used is the medical records of all DHF patients for 30 months in the period Jan 2019 to June 2021, at the Nadhifa Al Ghiffari Clinic in Bojongsoang District, Bandung Regency. © 2022 IEEE.

关键词： Decision trees

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Design and Implementation of IoT-Based Smart Fuel Monitoring System

Design and Implementation of IoT-Based Smart Fuel Monitoring...

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International Colloquium on Signal Processing & Its Applications, CSPA

作者： Islam Mohamedalfatih Ahmed Abdalmaged Safaa Najah Saud Al-Humairi Asmaa Mahfoudh Hezam Al-Hakimi Aparna Kumari School of Graduate Studies Management and Science University Shah Alam Selangor Malaysia Faculty of Information Sciences and Engineering Management and Science University Shah Alam Selangor Malaysia Department of Computer Science and Engineering Institute of Technology Nirma University Ahmedabad India

ISBN: (数字)9798331522193

ISBN: (纸本)9798331522209

The fast growth of the 'Internet of Things' (IoT) has impacted on several sectors, including fuel management. This paper describes the design, fabrication, and implementation of an IoT-based smart fuel monitoring system to improve the effectiveness of using fuel resources while minimizing losses and optimizing processes. A Rasp berry Pi controller with various sensors tracks essential parameters such as fuel level, temperature, pressure, pH, and gas levels. The system also provides for processing and presenting the collected data through a mobile application and a website, making it possible to manage the system further from the users via remote control. The system was tested using two fuel types, Benzene and Diesel, and it was effective in fuel parameters management. Results established that the pressure of Benzene was reasonably constant, and it was about 14.8 psi after reaching equilibrium. In contrast, the pressure returned to 14.7 psi value for Diesel, which was its initial value. The temperature readings were constant throughout the experiment, with the benzene temperature being higher than Diesel. The system also differentiated between pH levels, keeping Benzene at 6.9 while Diesel at around 7. These results prove the capabilities and efficiency of this system in anomaly detection, fuel adulteration, and fuel theft prevention, thus solving modern solutions in fuel management.

关键词： Temperature sensors Temperature measurement PI control Process control Real-time systems Temperature control Fuels Internet of Things Monitoring Intelligent sensors

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Survey of Online Exam Proctoring Model to Detect Cheating Behavior based on Face Recognition

Survey of Online Exam Proctoring Model to Detect Cheating Be...

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International Conference on Systems and Informatics (ICSAI)

作者： Sucianna Ghadati Rabiha Iman Herwidiana Kartowisastro Reina Setiawan Widodo Budiharto Computer Science Department BINUS Graduate Program – Computer Science. Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Computer Science. Computer Engineering Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Computer Science. Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665474498

Exams are an important component of any educational program, including online education. In any test, there is a possibility of cheating, so its detection and prevention is important. This study aims to conduct an in-depth study of the online exam monitoring model approach based on facial recognition used to detect cheating. Based on the inclusion and exclusion criteria designed, 13 selected studies were obtained. From these studies, we conducted further analysis regarding the Face Detection Method, Face Recognition Method, Initial Feature, Behavior Analysis and Evaluation Metrics used in each study so as to provide answers to research questions. the most frequently used Face detection method was Viola-Jones with a presentation of 20%, then CNN and MTCNN with a total presentation of 21%. The most widely used face recognition method in selected studies is CNN and metrics Accuracy is one of the most frequently used evaluations with a percentage of 33%. While the features that are usually used to detect cheating during online exams include facial motion and head pose which occupies the first position. The second is eye movement, then multiple faces gaze estimation and facial expression is in third place. Other features that also play a role in analyzing cheating behavior are mouth detection, facial vector, landmark location, gesture and posture.

关键词： Measurement Analytical models Face recognition Mouth Estimation Feature extraction Behavioral sciences

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Metric-Based Resolvability of Quartz Structure

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computers, Materials & Continua 2022年第4期71卷 2053-2071页

作者： Muhammad Imran Ali Ahmad Muhammad Azeem Kashif Elahi Department of Mathematical Sciences United Arab Emirates UniversityAl AinUnited Arab Emirates College of Computer Science&Information Technology Jazan University JazanSaudi Arabia Department of Aerospace Engineering Faculty of EngineeringUniversiti Putra MalaysiaMalaysia Deanship of E-learning and Information Technology Jazan UniversityJazanSaudi Arabia

Silica has three major varieties of crystalline. Quartz is the main andabundant ingredient in the crust of our earth. While other varieties are formedby the heating of quartz. Silica quartz is a rich chemical structure containingenormous properties. Any chemical network or structure can be transformedinto a graph, where atoms become vertices and the bonds are converted toedges, between vertices. This makes a complex network easy to visualize towork on it. There are many concepts to work on chemical structures in termsof graph theory but the resolvability parameters of a graph are quite advanceand applicable topic. Resolvability parameters of a graph is a way to getting agraph into unique form, like each vertex or edge has a unique identification bymeans of some selected vertices, which depends on the distance of vertices andits pattern in a particular graph. We have dealt some resolvability parametersof SiO2 quartz. We computed the resolving set for quartz structure and itsvariants, wherein we proved that all the variants of resolvability parameters ofquartz structures are constant and do not depend on the order of the graph.

关键词： Quartz polycyclic aromatic hydrocarbon related structure metric dimension metric or distance-based resolvability parameters

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HiRes: Hierarchical Feature Optimization and Rescorer for Automatic ICD Coding

HiRes: Hierarchical Feature Optimization and Rescorer for Au...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Liang, Zhenpeng Guan, Hongjiao Lu, Wenpeng Peng, Xueping Xu, Bing Yang, Muyun Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Qilu University of Technology Shandong Academy of Sciences Jinan China Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan China Australian Artificial Intelligence Institute University of Technology Sydney Sydney Australia Faculty of Computing Harbin Institute of Technology Harbin China

ISBN: (纸本)9798350368741

The International Classification of Diseases (ICD) coding assigns standardized codes to diseases. Automating this process enhances the efficiency and accuracy of clinical records processing. However, current methods struggle with noisy and lengthy clinical texts, making it difficult to ensure the reliability of feature extraction. Furthermore, they typically make separate binary predictions for each code, overlooking the dependencies between them. To address these issues, we propose a novel model called Hierarchical Feature Optimization and Rescorer (HiRes). We employ a cascaded convolution architecture to mitigate noise and enhance feature representation. Additionally, a masked autoencoder-based rescorer is introduced to capture ICD code interdependencies, refining initial predictions for improved accuracy. The model also considers the inconsistencies in code representations. Experiments on the MIMIC datasets demonstrate the effectiveness of our model. © 2025 IEEE.

关键词： automatic ICD coding cascaded convolutional network multi-label classification

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The Optimal Shape of the Surface Hardening Head Obtained by Numerical Modeling 15

The Optimal Shape of the Surface Hardening Head Obtained by ...

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15th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2023

作者： Novac, Mihaela Cornelia Codrean, Marius Gordan, Mircea Codrean, Mihaela Oproescu, Mihai Novac, Ovidiu Constantin Slovac, Francisc University of Oradea Electrical Engineering and Information Technology Faculty Department of Electrical Engineering Oradea Romania National Geothermal Research Center Technology Transfer Center NGRC-TTC University of Oradea Oradea Romania Computers and Electrical Engineering University of Pitesti Faculty of Electronics Communication and Computer Science Department of Elecytronics Pitesti Romania University of Oradea Electrical Engineering and Information Technology Faculty Department of Computers and Information Technology Oradea Romania

ISBN: (纸本)9798350321388

This paper presents some aspects of the numerical modeling performed in order to study the process of induction heating applied to a workpiece, using Flux 2D and FEMM (Finite Element Method Magnetics), two software tools specifically designed for electromagnetic simulations. The paper presents a significant technical finding regarding the optimal shape of the surface hardening head. Various shapes of the inductor were analyzed, focusing on solving the eddy current problem using the commercial program FEMM. The induction heating process was numerically simulated using the FLUX 2D program for a semi-finished punch made of OLC 45 steel, specifically for hot surface heat treatment. The simulations were conducted utilizing the program's simulation capabilities. © 2023 IEEE.

关键词： Induction heating

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PyVerDetector: A Chrome Extension Detecting the Python Version of Stack Overflow Code Snippets

PyVerDetector: A Chrome Extension Detecting the Python Versi...

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IEEE/ACM International Conference on program Comprehension (ICPC)

作者： Shiyu Yang Tetsuya Kanda Davide Pizzolotto Daniel M. German Yoshiki Higo Graduate School of Information Science and Technology Osaka University Osaka Japan Department of Computer Science University of Victoria Victoria Canada

Over the years, Stack Overflow (SO) has accumulated numerous code snippets, with developers going to SO for problem solutions and code references. However, in the case of the Python programming language, Python 3 is not necessarily backward compatible with Python 2. The major implication of this versioning problem is that code written in Python 2 may not be interpreted by Python 3 without modifications. This issue may affect the usability of Python code snippets on SO. We investigate how many Python code snippets on SO suffer from version compatibility issues, and find that about 10% of the snippets exhibit this problem. Moreover, of the code snippets that are interpretable only by Python 2 or Python 3, less than 17% are tagged with the Python *** this paper, we present a Chrome extension called PyVerDetector. This extension allows the user to select a given version of Python and verifies whether the code snippets on a given SO question are compatible with the user’s selected Python version, providing error messages if not. The tool parses snippets and can determine versioning errors due to differences in syntax and also provides the user with a list of Python versions capable of interpreting each code snippet.

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Using compression tables to improve HiveQL Performance with Spark A Case study on NVMe Storage Devices

Using compression tables to improve HiveQL Performance with ...

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International computer science and Engineering Conference (ICSEC)

作者： Youppadee Intasorn Kritwara Rattanaopas Yanapat Chuchuen Computer Science Program Faculty of Science and Technology Songkhla Rajabhat University Songkhla Thailand Information Technology Program Faculty of Science and Technology Songkhla Rajabhat University Songkhla Thailand

ISBN: (纸本)9781665462730

Query language execution is widely used in big data. The SQL standard is the major query language. Big data has a lot of SQL-like tools, for example: Spark-SQL, Hive, Drill, and Presto. This paper focused on Hive with the Spark engine. To increase Hive’s query performance in a case study, NVMe Solid State Devices, we proposed the compressed Parquet file including SNAPPY, gzip, and Zstandard (zstd). Query workloads use TPC-H benchmark. Thus, this compression codec can reduce the main transaction table of TPC-H benchmark by 56%, and some queries have lower CPU usage than Text file. However, the Hive on Spark engine with our proposed compression codecs for Parquet files has lower CPU usage than Text file in some TPC-H queries. Thus, NVMe storage with the Parquet file compression codec is more efficient than text files for improving query performance on the Spark engine.

关键词： Performance evaluation Structured Query Language Codecs Solid state drives Big Data Benchmark testing Virtual machining

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