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检索条件"任意字段=Scientific Conference on Mechatronics Engineering and Computer Science"

共 38182 条记录，以下是791-800 订阅

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Business Process Management Anomaly Detection Through Semantic Embedding-Integrated Graph Neural Networks 9

Business Process Management Anomaly Detection Through Semant...

引用

9th International conference on computer science and engineering, UBMK 2024

作者： Ayaz, Teoman Berkay Gülce, Ege Hsu, Stanley Özcan, Alper Akbulut, Akhan Akdeniz University Department of Computer Engineering Antalya Turkey R&d Center Next4biz Istanbul Turkey Istanbul Kültür University Dept. of Computer Engineering Istanbul Turkey

ISBN: (纸本)9798350365887

Detecting anomalies in business operations is paramount to maintaining business efficiency and fulfilling operational goals. Anomalies in business processes can pose major threats to a company's operations;therefore, their detection is crucial in business process management (BPM) tools. While several current methodologies predominantly rely on statistical frequency for anomaly detection, it is critical to recognize that infrequency does not inherently mean undesirability. The complexities of business processes, along with the scarcity of labeled data, make successful anomaly detection even more difficult, necessitating novel methodologies and advanced algorithms. This study proposes a novel, fully unsupervised graph neural network architecture integrated with natural language processing capabilities, designed for scalability and applicability to real-world business process logs for anomaly detection. Our methodology employs graph autoencoders with edge-conditioned convolutions in conjunction with sentence transformers to enhance the analytical depth of business process state-to-state relationships by incorporating the semantic meaning of the processes. To validate the efficacy and versatility of our model, we conduct empirical experiments utilizing three distinct real-life logs, demonstrating its applicability in both trace-level and event-level anomaly detection scenarios. © 2024 IEEE.

关键词： Graph neural networks

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A Three-Phase Unfolding-Based PFC Topology with Two Inductors for Electric Vehicles Battery Charging 64

A Three-Phase Unfolding-Based PFC Topology with Two Inductor...

引用

64th IEEE Annual International scientific conference on Power and Electrical engineering of Riga Technical University, RTUCON 2023

作者： Mohseni, Parham Husev, Oleksandr Vinnikov, Dmitri Matiushkin, Oleksandr Kurdkandi, Naser Vosoughi Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia San Diego State University Department of Electrical and Computer Engineering San Diego United States

ISBN: (纸本)9798350317732

This paper introduces a three-phase unfolding-based Power Factor Correction (PFC) rectifier design for electric vehicle charging systems, utilizing two filter inductors. The proposed structure achieves PFC action on the system grid side, similar to conventional three-phase PFC setups, but with only two filter inductors. Furthermore, the PFC functionality on the grid side requires only two current sensors (instead of three in the conventional ones) to measure the currents of the two filter inductors to control the current. This innovative approach results in a PFC-enabled electric vehicle battery charging system with significantly improved power density and reduced cost. To assess the advantages of the proposed design, a comparison is made with the conventional three-phase T-type structure. Theoretical analysis is performed, and simulations are carried to validate the proposed design versus the conventional T-type structure. Additionally, a 3.6kW laboratory prototype of the proposed structure is constructed, and experimental results are presented for idea verification. © 2023 IEEE.

关键词： Charging (batteries)

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Mobile Application Security: Malware Threat and Defenses

Mobile Application Security: Malware Threat and Defenses

引用

International IoT, Electronics and mechatronics conference, IEMTRONICS 2024

作者： Mira, Fahad Department of Computer Science and Technology University of Bedfordshire Bedfordshire United Kingdom

ISBN: (纸本)9789819747795

Regular mobile phones to smart phones are phenomenal because massive leap in capabilities. The abundance of applications available for download and installation is one of the main selling points of smart phones. But it also means that malicious software may be readily distributed to smart phones, allowing hackers to launch a variety of attacks. Effective detection procedures and preventative measures should be taken to deal with this problem. The reasons why cell phones are susceptible to security breaches are initially covered in this article. After then, it shows signs of malicious behavior and virus threats. After that, it takes a look back at the methods currently used to identify and stop malware. It highlights the need for additional research in these areas, as well as the efforts of app developers, app store authorities, and users to protect themselves from this type of malware. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Mobile applications

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Reliable Data Transmission and Efficient Vehicle Path-Planning in Cooperative Vehicular Networks 1

Reliable Data Transmission and Efficient Vehicle Path-Planni...

引用

1st Asian conference on Communication and Networks, ASIANComNet 2024

作者： Habelalmateen, Mohammed I. Abdulsattar, Nejood F. Gangopadhyay, Amit Hadi, Rusul Lsmael Abed, Hassan Mohammed Abbas, Fatima Hashim The Islamic University College of Technical Engineering Department of Computer Technical Engineering Najaf Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq Mohan Babu University Erstwhile Sree Vidyanikethan Engineering College Department of Electronics and Communication Engineering Tirupati India National University of Science and Technology Dhi Qar Iraq Mazaya University College Department of Computer Techniques Engineering DhiQar Iraq Al-Mustaqbal University Medical Laboratories Techniques Department Hillah Iraq

ISBN: (纸本)9798350367003

In recent times, an increased number of vehicles create a traffic congestion problem in urban enrollment. In recent scientific research to normalize the communication issues of the vehicles, unmanned aerial vehicles (UAVs) are embedded with the vehicular communication mainly to control the traffic congestion and insufficient bandwidth utilization of the vehicles. The aerial vehicles are highly flexible and efficient so that they are able to control the vehicles in an efficient manner. But still certain drawbacks are present in the aerial vehicles such as improper localization and ineffective data transmission. To solve these flaws, in this article, reliable data transmission and efficient vehicle path planning in the cooperative communication model (RDTEVP) is developed. The core modules of this model are reliability base network modeling and path planning based routing. Through this process the efficiency of the network is maximized and the data transmission quality is improvised. This model is structured to analyses the device performance are packet delivery ratio, network throughput, energy efficiency, average delay and routing overhead. The term delay and routing overhead are greatly minimized in the RDTEVP when compared with the earlier schemes. © 2024 IEEE.

关键词： Traffic congestion

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Vehicle Assistance System Using Convolutional Neural Networks 11

Vehicle Assistance System Using Convolutional Neural Network...

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11th International scientific conference on computer science, COMSCI 2023

作者： Zemla, Filip Ciganek, Jan Slovak University of Technology in Bratislava Faculty of Electrical Engineering and Information Technology Bratislava Slovakia

ISBN: (纸本)9798350325256

The aim of this paper is to create a safety assistance system for a vehicle that is able to recognize dangerous situations while driving using the front camera. In addition to the detection of these events, the system is able to warn the driver using sound and visual effects to prevent a possible accident. The main principle of the work consists in creating and training a convolutional neural network that will be able to detect a set group of objects in images, videos or camera images captured in real time and to visualize these objects in the created application. © 2023 IEEE.

关键词： Vehicles

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A Comparison of Earthquake Prediction using Machine Learning Algorithms 5

A Comparison of Earthquake Prediction using Machine Learning...

引用

5th International conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Rath, Subashree Gurulakshmi, A.B. Aditya, S. Naik, Vaibhav R Pawar, Amith Karoor, Vikram Computer Science and Engineering New Horizon College of Engineering Bengaluru India Electronics and Communication Engineering New Horizon College of Engineering Bengaluru India

ISBN: (纸本)9798331518097

Predicting earthquakes is one of the most challenging scientific endeavors due to the complex and dynamic nature of Earth's crust and the multitude of factors influencing seismic activity. Earthquake prediction research remains an essential scientific frontier, offering hope for better mitigation strategies and reduced impact in the future. This study examines the prediction of earthquake magnitudes using machine learning models, namely Random Forest Regression, Decision Tree Regression, and Support Vector Regression. Data such as latitude, longitude and depth were used to test and train the models to forecast magnitude. The performance of each model was evaluated using the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). According to the results, the Support Vector Regression model outperforms the others. © 2024 IEEE.

关键词： Prediction models

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Super-resolution reconstruction of remote sensing images based on multi-scale reparameterized pyramids 8

Super-resolution reconstruction of remote sensing images bas...

引用

8th IEEE Information Technology and mechatronics engineering conference, ITOEC 2025

作者： Huang, RuiNan Zheng, GengSheng Wuhan Institute of Technology Hubei Province Key Laboratory of Intelligent Robot Wuhan China Wuhan Institute of Technology School of Computer Science & Engineering Wuhan China

ISBN: (纸本)9798331517915

In order to solve the problems of loss of structural details and insufficient attention to edge information in the existing lightweight remote sensing super-resolution reconstruction methods, a multi-scale reparameterized pyramid network (MRPN) method for remote sensing image super-resolution reconstruction based on multi-scale reparameterized pyramids was proposed. The model is based on the deep residual network structure, and multiple cascading multi-scale reparameterized pyramid modules are designed in the network for feature extraction. In the module, a multi-scale separation convolution and fusion module is designed to help the network refine image information, and the unglobal and global feature expressions are enhanced, and the link-enhanced spatial attention module is used to improve the attention to high-frequency feature information. Finally, the jumping connection method is used to fuse multi-level features to achieve effective spatial information fusion. The model is verified by 2x, 3x and 4x super-resolution reconstruction on the NWPU-RESISC45 dataset and the AID dataset, and the experimental results show that the peak signal-to-noise ratio and structural similarity are improved, and the method has good performance in improving image quality and preserving details. © 2025 IEEE.

关键词： Image enhancement

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A Low-Cost Skiing Motion Capture System Based on Monocular RGB Camera and MINS Fusion 20

A Low-Cost Skiing Motion Capture System Based on Monocular R...

引用

20th IEEE International conference on mechatronics and Automation, ICMA 2023

作者： Zhang, Zibin Cong, Xiaodan Zhang, Xiaoqi Yu, Xilin Lin, Kaihong Guan, Lianwu Harbin Engineering University College of Intelligent Systems Science and Engineering Nantong St. Harbin150001 China Institute of Intelligent Manufacturing Heilongjiang Academy of Sciences Hanshui Rd Harbin150008 China

ISBN: (纸本)9798350320831

Ice and snow sports have entered a rapid development period since the Winter Olympics, and the emergence of indoor simulated skiing machines has driven the indoor skiing market developed in a high-way. However, there are some shortcomings in the use of existing simulated skiing machines: Simulated skiing machines lack a sense of immersion in relatively dry sports. Fortunately, the visual and inertial motion capture technology has developed rapidly, and is used in entertainment, games, film and television widely. Actually, the multi-node based inertial motion capture system makes it inconvenient to wear as many nodes, and monocular human motion capture system is also affected by occlusion. This paper proposes a real-time human body motion capture method by integrating the monocular vision and the inertial sensors. Specifically, the inertial sensors based Micro Inertial Navigation System (MINS) and the RGB cameras based computer vision system are integrated to capture the trajectory and posture of the key nodes (head, arms, trunk, legs, etc.) of skis and skiers in real-time. Moreover, the filtering technology is also utilized to reduce the jitter of visual motion capture data to improve the stability of the overall system. Finally, an indoor human motion capture experiment was conducted to verify the effectiveness of the scheme. The experimental results shown that there is a large error in visual motion capture under occlusion, and the inertial sensor could be integrated to replace the visual motion capture data for more accurate motion capture under occlusion. © 2023 IEEE.

关键词： Inertial navigation systems

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Recent Advancements in Machine Learning and IoT for Health care 15

Recent Advancements in Machine Learning and IoT for Health c...

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15th International conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Vani, K.S. Basavaraju, T.G. Surekha, K.B. Department of Information Science and Engineering Nitte Meenakshi Institute of Technology Karnataka Bangalore India Department of Computer Science and Engineering Government College of Engineering Hassan India Department of Information Science and Engineering BMSIT Bangalore India

ISBN: (纸本)9798331300579

In the current landscape of healthcare, Machine Learning (ML) and the Internet of Things (IoT) are making significant strides. Ongoing research focuses on remote patient monitoring, disease prediction, and diagnostic imaging, utilizing wearable devices and sensors. ML algorithms contribute to drug discovery, personalized medicine, and operational efficiency, predicting equipment failures and optimizing resource allocation. This paper surveys the most recent papers on ML and IoT in health care. This survey of ML and IoT in healthcare highlights diverse applications, from automated diabetes prediction to breast cancer detection. Utilizing wearable devices and sensors, these technologies provide real-time health insights and personalized interventions. Challenges such as data security and limited datasets are identified, prompting the need for future improvements. © Grenze scientific Society, 2024.

关键词： Electronic health record

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An Enhanced Packet Delivery Ratio Improvement Protocol Design over 5G Assisted Wireless Sensor Network Environment 2

An Enhanced Packet Delivery Ratio Improvement Protocol Desig...

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2nd IEEE Global conference on Communications and Information Technologies, GCCIT 2024

作者： Balaji, T.S. Charaan, R.M.Dilip Rajalakshmi, J. Samuthira Pandi, V. Shobana, D. Priya, J. Lakshmi Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Electronics and Communication Engineering Tamilnadu Chennai India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India S.A.Engineering College Department of Cse Tamilnadu Chennai India Chennai Institute of Technology Centre for Advanced Wireless Integrated Technology Tamil Nadu Chennai India Rajalakshmi Engineering College Department of Mechatronics Engineering Tamil Nadu Chennai India Saveetha Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350388916

Sensors are pervasive in modern life, and Wireless Sensor Networks (WSNs) will play an increasingly important role in the years to come. Broadband, energy, coverage, and route optimization resource shortages are WSN's main drawbacks. Optimizing the packet delivery ratio is a crucial aspect of wireless sensor network (WSN) architecture. In order to enhance WSNs over the long term, previous approaches used a secure zone-based routing mechanism. For packet transmission, a new criterion was developed in multi-hop communication. It was built into the routing metric to protect against flooding, message manipulation, and dropping attacks. Congestion in WSN increases and reduces packet delivery ratio, even while energy conservation and attack resilience are accomplished. Our proposed solution, Advanced Path Selection with Traffic Estimation (APSTE), is a new way of routing data packets that takes flow differentiation into account. This should help increase the packet delivery ratio and solve this issue. In order to determine how effective, the suggested method is, it is cross-validated using the standard routing model known as Link Consistency with Path Evaluation (LCPE). In order to improve the WSN's QoS parameters and extend the network's lifespan, the APSTE approach reduces the energy consumption of sensor nodes while maintaining or improving their logical throughput and packet acquisition rates. © 2024 IEEE.

关键词： 5G mobile communication systems

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