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Persona-oriented data Protection Impact Assessment for Small Businesses 3rd

Persona-oriented Data Protection Impact Assessment for Small...

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3rd international conference on Society 5.0, 2023

作者： Schneider, Bettina Asprion, Petra Maria Misyura, Ilya Jonkers, Natalie Zaugg, Esther University of Applied Sciences and Arts Northwestern FHNW Switzerland

The European (EU) General data Protection Regulation (GDPR) is applicable since May 2018 and has since posed major challenges for small businesses with limited knowledge and resources. According to Art. 35 of the GDPR, a so-called ‘data Protection Impact Assessment’ (DPIA) is mandatory if a processing of personal data is likely to result in a high risk to the rights and freedoms of natural persons. There is a demand for low-threshold, practical instruments that support the required DPIA. The objective of this research was to develop a new DPIA instrument that meets the needs – as unit of analysis – of non-technology small businesses and complies with the requirements of the EU GDPR. Design Science Research was used as the methodological framework and identified personas were drivers in the development. The result is two variants of instruments that have been carefully evaluated and proven to be valuable. © 2023, EasyChair. All rights reserved.

关键词： Risk assessment

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data Mining of Chinese Language and Literature Education Based on Diversified Constraint Model 3rd

Data Mining of Chinese Language and Literature Education Bas...

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3rd EAI international conference on Application of Big data, Blockchain, and Internet of Things for Education Informatization, BigIoT-EDU 2023

作者： Wei, Xiaolan Nanchang Institute of Science and Technology Jiangxi Nanchang330108 China School of Economics and Management Guilin University of Electronic Technology Guilin541000 China

ISBN: (纸本)9783031631290

China culture. When teaching Chinese language and literature, teachers should vigorously and guide the teaching, so as to effectively enhance students’ learning enthusiasm. All colleges and universities have established their own teaching management information systems, which have greatly improved the level of teaching and management, and accumulated a large amount of teaching and management data. But at present, most of these information systems are on-line transaction processing, lacking the ability of comprehensive analysis and decision-making. data mining technology is produced to solve this problem. If the function of classifying and deep-level analysis of the collected data cannot be provided, the managers cannot understand the relevant information in time in the face of complex situations, and the leaders do not have practical data support in decision-making. As the core component in the field of digital education practice, diversity constraint model understands the structural form of Chinese language and literature education data mining in the field of learning practice with internal psychological mechanism and external behavior structure. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： data mining

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Deep Learning-Based Brain Tumor Segmentation—An Overview 1

引用

3rd international conference on Artificial-Business Analytics, Quantum and Machine Learning: Trends, Perspectives, and Prospects, Com-IT-Con 2023

作者： Kataria, Jyoti Panda, Supriya P. Manav Rachna International Institute of Research and Studies Haryana Faridabad India

ISBN: (数字)9789819748600

ISBN: (纸本)9789819748594

Brain tumor segmentation is a subdivision of study that focuses on creating a precise delineation of brain tumor regions using magnetic resonance imaging (MRI). Nowadays, deep learning (DL) algorithms have shown remarkable growth in addressing a range of computer vision problems like semantic segmentation, image classification, and object detection. Applying DL techniques to electronic health records can yield useful insights that can be used to improve patient risk score systems or identify the onset of a brain tumor. Deep learning techniques can also facilitate the effective processing and balanced assessment of the vast volumes of MRI-based image data. This paper presents an overview of the traditional and deep learning techniques used for brain tumor segmentation (BTS) and brain tumor classification (BTC). Further, a detailed analysis of the existing surveys was carried out to determine the overall impact of each survey. In addition, this study discusses the deep learning-based methods with their respective classification/segmentation, features, pre-processing, and outcomes. Finally, this study not only examines the prior research but identifies potential future research directions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Semantic Segmentation

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Multi-view block Fusion Algorithm for data Mining and Intelligent Sports Training 3

Multi-view block Fusion Algorithm for Data Mining and Intell...

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3rd international conference on Electronics and Sustainable Communication Systems, ICESC 2022

作者： Li, Li Hunan Vocational College of Modern Logistics Hunan Changsha410131 China

ISBN: (数字)9781665479714

ISBN: (纸本)9781665479714

Multi-view block fusion algorithm for data mining and intelligent sports training is designed and implemented in this manuscript. It has excellent performance in the field of ultra-high-speed real-time image processing. The dual-DSP high-speed real-time signal processing system of this system consists of two DSP chips as the core to form a neighborhood image parallel processor, and realizes synchronous parallel operation processing through the division and decomposition of system tasks. With the designed model, the ideas on the block fusion algorithm for data mining and intelligent sports training is then discussed. Under the condition of the same fill factor, the composite aperture array structure can obtain the higher resolution and imaging quality than the typical aperture array structure after image restoration, which is an effective means to obtain very high resolution. This will be further considered to optimize the sport system. The performance is validated by performing a general testing on different datasets. © 2022 IEEE.

关键词： data mining

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Usformer: A Light Neural Network for Left Atrium Segmentation of 3D LGE MRI 31

Usformer: A Light Neural Network for Left Atrium Segmentatio...

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31st European signal processing conference, EUSIPCO 2023

作者： Lin, Hui Lopez Tapia, Santiago Schiffers, Florian Wu, Yunan Yang, Huili Iakovlev, Nikolay Allen, Bradley D. Avery, Ryan Lee, Daniel C. Kim, Daniel Katsaggelos, Aggelos K. Northwestern University United States

ISBN: (纸本)9789464593600

Left atrial fibrosis is an important mediator of atrial fibrillation and atrial myopathy. Late gadolinium-enhancement (LGE) MRI is a proven non-invasive test for the evaluation of left atrial (LA) fibrosis. However, manual segmentation is labor-intensive. Automatic segmentation is challenging due to varying intensities of data acquired by different vendors, low contrast between the LA and surrounding tissues, and complex LA shapes. Current approaches based on 3D networks are computationally expensive and time-consuming due to the large size of 3D LGE MRIs and networks. To address this, most approaches use two-stage methods to first locate the LA center using a down-scaled version of the MRIs and then crop the full-resolution MRIs around the LA center for final segmentation. We propose a light transformer-based model to accurately segment LA volume in one stage, avoiding errors introduced by suboptimal two-stage training. Transposed attention in transformer blocks can capture long-range dependencies among pixels in large 3D volumes without significant computation requirements. Our proposed model achieved a promising dice similarity coefficient of 92.6% in the 2018 Atrial Segmentation Challenge, with only 611k parameters, which is about 1% of the method ranked 3rd in the challenge but with similar performance. © 2023 European signal processing conference, EUSIPCO. All rights reserved.

关键词： Magnetic resonance imaging

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Online Monitoring System Based on Convolutional Neural Networks for Urban Environmental Noise 3rd

Online Monitoring System Based on Convolutional Neural Netwo...

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3rd international conference on Environmental Pollution and Governance, ICEPG 2023

作者： Gu, Haojie Zhang, Wenjuan Huang, Caineng Liao, Tongqing School of Integrated Circuits Anhui University Hefei230601 China KEWELL Technology Co. Ltd. Hefei230088 China

ISBN: (纸本)9783031529009

Noise monitoring is becoming more and more important with the development of the city. In this paper, an online monitoring system for urban environmental noise based on a convolutional neural network is designed and developed which mainly includes a backstage management system and noise acquisition and transmission unit. The central control system uses the FCU1104 IoT gateway which is responsible for data acquisition and the distributed remote modules are used for the data transmission and control signal sending. Modbus RTU, Modbus TCP and SFTP communication protocols are used for data communication for security and stability. A convolutional neural network is used to deal with Fbank features of the audio for acoustic source recognition. And then, the number of CONV layers and the Pooling layer is determined. At last, a one-month data acquisition rate test and accuracy of noise recognition test are carried out. The test results show that the data acquisition rate is 98.585% and the accuracy of noise recognition test is 81.4%. It prove that this system has stable rate of data acquisition and high accuracy of acoustic source recognition. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： data acquisition

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Design of an Automobile Status Monitoring Platform Based on Multi-Sensor data Fusion

Design of an Automobile Status Monitoring Platform Based on ...

引用

signal processing, Communications and Engineering Management conference (ISPCEM), international

作者： Shengjiao Chen Chenyu Hu School of Mechanical and Electronic Engineering Wuhan University of Technology Wuhan China School of Safety Science and Emergency Management Wuhan University of Technology Wuhan China

With the swift progression of the automotive industry, real-time monitoring of vehicular status has become increasingly paramount. Existing monitoring methodologies are, however, constrained by their inherent limitations. This paper presents an automobile status monitoring platform rooted in multi-sensor data fusion. data processing and analysis are executed through a synergistic approach, employing the LSTM model combined with a rule engine. The research discerns that this methodology proficiently extracts pertinent information from abundant sensor data, monitoring the automobile's operational state and potential issues both real-time and with precision. This investigation proffers robust backing for vehicular health management and fault prognosis, demonstrating significant practical relevance.

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Design of communication protocol and data processing algorithm for wireless laser power counting system 3

Design of communication protocol and data processing algorit...

引用

3rd international conference on Mechanical, Electronics, and Electrical and Automation Control, METMS 2023

作者： Shi, Feiyu Zhang, Jinghui Cai, Yihua Li, Linge Fan, Chengyu Key Laboratory of Atmospheric Optics Anhui Institute of Optics and Fine Mechanics HFIPS Chinese Academy of Sciences Hefei230031 China University of Science and Technology of China Hefei230026 China Advanced Laser Technology Laboratory of Anhui Province Hefei230037 China Institute of Material Science and Information Technology of Anhui University Hefei230601 China

ISBN: (纸本)9781510666689

In environments with harsh environments, high electromagnetic interference, and poor data channel quality, wireless laser power meters face the risk of data loss and data bit errors when measuring laser power. The wireless data transmission module works on a free channel using open standards, and is vulnerable to attacks, resulting in data leakage. In view of the above problems, this paper designs the communication data frame format of the PC end and the data acquisition module end for the wireless laser power meter data acquisition system. The TEA data encryption algorithm and the CRC check algorithm based on the look-up table method are added to the data frame. For the voltage noise and abnormal values collected by the data acquisition module, this paper uses a real-Time low-pass filter algorithm to filter out high-frequency noise, and designs a sliding window algorithm to smooth the power curve and remove power abnormal values. The communication protocol and data processing algorithm designed in this paper realize the data verification, error retransmission and data encryption of the wireless laser power counting system, ensure the data reliability and data integrity during the data transmission process, and realize real-Time noise reduction and power curve smoothing. © 2023 SPIE.

关键词： Table lookup

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Stockwell Transform and data Mining based Fault Diagnosis Method to protect Microgrid 3

Stockwell Transform and Data Mining based Fault Diagnosis Me...

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3rd international conference for Emerging Technology, INCET 2022

作者： Kumar Joga, S Ramana Sinha, Pampa Maharana, Manoj Kumar Jena, Chitralekha Mishra, Alok Roy, Ashutosh Kiit Deemed to Be University School of Electrical Engineering Bhubaneswar India

ISBN: (纸本)9781665494991

Increase in industrial and residential loads gives arise to the need of local power generation. The concept of local power generation to local loads in a small area made a new local power grid known as Microgrid. The monitoring and control of Microgrid is the important concern of electrical engineers and power engineering researchers. Current fluctuations are common in Microgrid due to various factors. In literature many methods are there to diagnose the fault occur in Microgrid. Machine Learning techniques are one of the future method to detect and island the fault in Microgrid. signal processing techniques helps to analyze the signal condition for further diagnosis. combination of these two methods for fault diagnosis in Microgrid yields better result compared to other previous methods that present in the literature. In this paper, a Microgrid consisting of PV Distributed Energy Resources (DER) and Wind System with local loads is simulated and all the simulations are carried out in MATLAB Simulink. © 2022 IEEE.

关键词： Failure analysis

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Bit Wise Multipliers Using Symmetric Stackers 3

Bit Wise Multipliers Using Symmetric Stackers

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3rd international conference on Power, Energy, Control and Transmission Systems, ICPECTS 2022

作者： Devi, Ledalla Anjali Sagar, Dubey Ram, Aviti Shiva Phani Vidyadhar, R. Vardhaman College of Enginnering Department of Electronics and Communication Engineering Hyderabad India Vardhaman College of Enginnering Department of Electronics and Communications Engineering Hyderabad India

ISBN: (纸本)9781665462754

All computing units, including the Digital signal processing (DSP) applications, Multiply Accumulate Unit (MAU), and Arithmetic Logic Unit (ALU), require high speed multipliers. The efficiency of data multiplication is a common performance limiter for DSP systems. Therefore, there is a great need right now for multiplier algorithms that are fast and consume less energy. The design of fast and speed efficient multipliers based on symmetric stacking-based binary counters. This study analyses a Wallace tree multiplier using symmetric stacking-based counters as well as traditional counters. In terms of latency and area, the performance is also contrasted. Verilog HDL and Xilinx are used in programming and synthesis. © 2022 IEEE.

关键词： Digital signal processing

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