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Parkinson's Disease Detection Using CNN Architectures withTransfer Learning

Parkinson's Disease Detection Using CNN Architectures withTr...

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2021 IEEE international conference on Innovative computing, Intelligent Communication and Smart electrical Systems, ICSES 2021

作者： Jahan, Nusrat Nesa, Arifatun Layek, Md. Abu Jagannath University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665435215

Nowadays the most common and incurable neurological disorder disease is Parkinson's disease (PD). This incurable disease is growing terribly. This study determines PD patients on the basis of fine motor symptoms using sketching. We proposed a system where we use spiral and wave sketching that can identify either the sketch is from a PD patient or not. Our experiment was done on a dataset consisting PD patient and Healthy (without PD) control group. We applied a deep learning approach Convolutional Neural Network (CNN) to determine PD infected patients and healthy (without PD) control group. We experimented on two CNN models-Inception v3 and ResNet50, with transfer learning method. The proposed system achieved 96.67% accuracy on the Inception-v3 model with spiral sketching. © 2021 IEEE.

关键词： Convolutional neural networks

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Target Tracking for High-Speed Railway Catenary Based on Correlation Filtering Algorithm 5th

Target Tracking for High-Speed Railway Catenary Based on Cor...

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5th international conference on electrical engineering and Information Technologies for Rail Transportation, EITRT 2021

作者： Liu, Keyan Jia, Limin Qin, Yong Wang, Zhipeng Tong, Lei Geng, Yixuan State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

ISBN: (纸本)9789811699085

With the increase in railway operating mileage, the pressure on railway inspections has also increased significantly. The realization of automated inspections along the railway can not only improve work efficiency, but also save manpower and material resources. The catenary is an important component of the train power system, and it is necessary to study the automatic inspection technology of the catenary. This paper proposes to use a tracking algorithm based on correlation filtering to track the catenary. Considering to meet real-time requirements, the ECO-HC algorithm based on manual features is adopted. The experimental results show that the ECO-HC algorithm basically realizes the tracking of the catenary and the algorithm speed reaches 57 fps, which meets the real-time requirements;the comparison between the ECO-HC algorithm and the classic tracking algorithm based on correlation filtering proves the superiority of the ECO-HC algorithm. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Railroads

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Time Series Fusion Model for Predicting Electric power tools and equipment

Time Series Fusion Model for Predicting Electric power tools...

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Robotics, Intelligent control and Artificial Intelligence (RICAI), international conference on

作者： Liang Xue Xinghong Ling Lei Yang Yang Yang Computing Science and Artificial Intelligence College Suzhou City University Suzhou China College of Computer Science and Software Engineering Hohai University Nanjing China Suzhou Key Lab of Multi-Modal Data Fusion and Intelligent Healthcare Suzhou City University Suzhou China

ISBN: (数字)9798331541699

ISBN: (纸本)9798331541705

To effectively address the issue of inadequate accuracy and timeliness in industrial data classification, this paper proposes a fusion classification model based on time series (DT-RF-MLP) for loss prediction of electrical work equipment. Firstly, data information is extracted from the dataset and features are constructed based on the data information to enhance the diversity of data features. Secondly, redundant and highly correlated features are removed by quantifying the correlation degree between the features to simplify the model inputs. On this basis, a fusion classification model is constructed and comparative experiments are conducted with a single model to validate the advantages of the fusion model in terms of prediction performance. The experimental results demonstrate that the model markedly enhances prediction accuracy while concurrently reducing the duration of the model run.

关键词： Accuracy Correlation Service robots Time series analysis Predictive models Feature extraction Data models Power systems Decision trees Random forests

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Earlier Stage Identification of Bone Cancer with Regularized ELM

Earlier Stage Identification of Bone Cancer with Regularized...

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international conference on ent computing and control Systems (ICICCS)

作者： S. Murugesan Neelam Sharma N. Jayalakshmi Kumud Pant Amit Chauhan Purnendu Bikash Acharjee Kavaraipettai R.M.D Engineering College Tiruvallur Tamilnadu India Department of Physical Education Lovely Professional University Punjab India PSNA College of Engineering and Technology Dindigul Tamilnadu India Department of Biotechnology Graphic Era Deemed to be University Dehradun Uttrakhand India Department of Life Sciences CHRIST (Deemed to be University) Bengaluru Karnataka India Computer Science CHRIST University Pune Maharashtra India

A major focus of current research in the field of image processing is the application of such methods to the field of medical imaging. While dealing with biological issues like fractures, canoers, ulcers, etc., image processing facilitated pinpointing the precise cause and tailoring a remedy. In the field of tumor identification, medical imaging has set a new standard by overcoming a number of challenges. Medical imaging is the practice of generating images of the human body for diagnostic or exploratory purposes. Because of its high image quality, MRI is the method of choice for detecting tumors. This research study proposes the integration of RLM to detect tumors and presents an automatic bone cancer detection system to assist oncologists in making early diagnosis of bone malignancies, which in turn allows patients to receive treatment as soon as possible. This research work also proposes to detect bone tumors by using a combination of the RELM based M3 filtering, Canny Edge segmentation, and the Enhanced Harris corner approach. When compared to other models like CNN, ELM, and RNN, the suggested technique achieves an accuracy of around 97.55%.

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A Case Study of the Implementation Difficulties in the Pilot Low Cost Concentrating Solar Power Systems Deployment in Sub-Saharan Africa

A Case Study of the Implementation Difficulties in the Pilot...

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international conference on Contemporary computing and Informatics (IC3I)

作者： Sankar Babu Potluri Garima Goswami Annu Yadav P G. Ravivarman P. Gajendran S. A. Tiwaskar Department of EEE S V R Engineering College Nandyal India Department of EE Teerthankar Mahaveer University Moradabad India School of COMPUTER Science and Applications IIMT University Meerut India Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Coimbatore India Computer Engineering Vishwakarma Institute of Information Technology Pune Maharashtra India

Among those most important resources for a particular country's expansion and expansion was electrical power. According to the most recent sustainability the growth paper, the continent continues to have a significant electrical power deficit. sunlight concentration appears to be a viable solution to make up the difference. This is due to the fact the majority of focusing solar energy plant elements are easily accessible and reasonably priced on their African marketplace, and authorized locals can construct the structures. Within Africa south of the Sahara, steer 50 nm-concentrating solar energy plants are being put into operation with promising outcomes that might be grew and utilized to generate large amounts of electrical power. One notable challenge was identified during an evaluation of a prototype focusing photovoltaic plant within the channel-region: the monitoring system's inability to lower the daily costs required to operate the monitoring control structure and enhance the numerous special machines focusing conduct. This essay emphasizes the current energy landscape and African study of concentrated sunlight is currently progressing. To demonstrate current study strategy about the development of inexpensive monitoring devices in regards to mathematical difficulty, energy use, and special machine alignment precision, the article also provides an in-depth examination of the most recent solar monitoring structures for essential receiver networks.

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Security in the World of Internet of Things (IoT): Overcoming Challenges

Security in the World of Internet of Things (IoT): Overcomin...

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Advance computing and Innovative Technologies in engineering (ICACITE), international conference on

作者： Venkat Tulasi Krishna Gannavaram Sravya Desu Venkata Rohith Jujjuru Sri Vatsa Venkata Tejaswi Renikunta Arun Kumar Gajula Ganta Raghotham Reddy School of Electrical Computer and Energy Engineering Arizona State University Tempe USA School of Computing and Augmented Intelligence Arizona State University Tempe USA Department of Electronics and Communication Engineering Kakatiya Institute of Technology and Science Warangal India

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

Internet of Things (IoT) is turning out to be more prominent in our everyday existence, with smart home appliances and industrial control systems serving as examples. But the proliferation of IoT devices and internet connectivity increased the potential of security breaches. Botnet attacks, injection attacks, Domain Name Systems (DNS) spoofing attacks, firmware assaults, zero-day attacks, brute- force attacks, and cryptographic attacks may be used against IoT devices. These assaults may result in the loss of data, illegal access, and even physical damage to infrastructure and people. There are various potential courses of action. Machine Learning subpart of Artificial Intelligence have the capacity for finding and prevent dangers in real time. With blockchain technology, an IoT network can have a secure and unbreakable a record of every exchange and data transfers. Hardware-based security techniques, such as secure boot and trusted execution environments, may protect IoT devices against attacks that seek to compromise the underlying hardware or firmware. Standardizing security procedures may ensure that all devices can work together safely and achieve a given degree of security. The use of privacy-enhancing technology, IoT data may be kept confidential and sensitive information disguised.

关键词： Data privacy Protocols Technology Smart homes Turning Real-time systems Internet of Things Security Domain Name System Microprogramming

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Designing Earthquake Monitoring System Using Earthquake Catcher Network 9

Designing Earthquake Monitoring System Using Earthquake Catc...

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9th international conference on Computer, control, Informatics and Its Applications: Digital Transformation Towards Sustainable Society for Post Covid-19 Recovery, IC3INA 2022

作者： Suhud, Ridwan Hanif, Muhammad Putratama, Christoporus Deo Prakoso, Kevin Yuwono, Bramantio Prihatmanto, Ary Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Indonesia

ISBN: (纸本)9781450397919

The earthquake monitoring system is a system that provides the latest earthquake information detected by seismic sensors ECN based on an accelerometer which has been developed independently in previous studies. This study uses ECN sensors to process and analyze peak ground acceleration (PGA), earthquake intensity, and visualization acceleration graphs in three axes (x, y, z) through the visualization on the website. This research includes sending ECN sensor data to the message broker server and then taking data (consume) to the database server and processing and analyzing data from the database into helpful information for users. The system design results are a prototype of a web-based application that displays the latest news on the state of the earthquake in the form of peak ground acceleration and earthquake intensity, as well as visualization through maps from the sensor location. © 2022 ACM.

关键词： Visualization

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Blockchain-Based Power Internet of Things Data Access control Mechanism 9th

Blockchain-Based Power Internet of Things Data Access Contro...

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9th international conference on Signal and Information Processing, Network and Computers, ICSINC 2021

作者： Wang, Xinyan Jia, Zheng Wang, Qi Li, Dong Zhang, Jing Chen, Xin Yan, Han State Grid Henan Information and Telecommunication Company Zhengzhou450052 China Beijing JingAn YunXin Science and Technology Ltd. Beijing China

ISBN: (纸本)9789811947742

In order to solve the problem of low security in the data access of the Power Internet of Things (PIOT), we design a blockchain-based PIOT data access control model. In this model, cloud servers and blockchain nodes cooperate with each other to optimize the existing data access control mechanism, so as to realize the secure storage of power terminal data in the PIOT. To solve the low efficiency of PIOT data access problem, based on the access control model of this article, a blockchain-based PIOT data access control mechanism is proposed. In terms of search efficiency, we use power terminal data indexing mechanism and query mechanism to improve the efficiency of data search. In terms of security, index encryption and decryption algorithms are used to improve the security of data access. In terms of performance analysis indicators, the performance of the proposed algorithm is analyzed from the three dimensions of system solution throughput, index generation time, and search time, which verifies that the proposed algorithm in this paper improves the security and availability of data access control. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Access control

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MSIF-Net: Multi-branch Semantic Information Fusion Network for automatic Bare Soil Detection in High-Resolution Remote Sensing Images

MSIF-Net: Multi-branch Semantic Information Fusion Network f...

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international conference on Cybernetics, Robotics and control (CRC)

作者： Junqi Zhao Lifu Chen Yawu Liu Yuchen Jin Haoda Chen Zhenhuan Fang School of Electrical & Information Engineering Changsha University of Science&Technology Changsha China

Bare soil erosion dust plays a significant role in the formation of haze weather, occupying an important position in the source of air particulates. Accurate monitoring of bare soil is an urgent need for environmental governance. High-resolution remote sensing images, rich in semantic information, are beneficial for the extraction of bare soil, but they are easily influenced by similar bare soil and background conditions. To address this, this paper proposes a Multi-branch Semantic Information Fusion Network (MSIF-Net) framework for the automatic detection of bare soil in high-resolution remote sensing images. MSIF-Net consists of encoding and decoding parts. The encoding part uses ResNet101 for preliminary feature extraction and outputs four levels of features. The highest-level feature is input into the constructed Dense attention-based Atrous Spatial Pyramid (DASP) module for in-depth extraction of multi-scale features. The medium and low-level features are input into the Multi-branch Detail Information Extraction (MDIE) module, fully utilizing the semantic and detail information of different branches to enhance feature extraction and refinement of local features. In the decoding part, the processed features of different resolutions are input into the constructed Multi-element Flow Alignment (MFA) module, which uses multi-branch stepwise decoding. Shallow spatial information guides the deep semantic information to achieve more flexible feature alignment and improve edge segmentation effects. Experiments on 2 m resolution remote sensing images obtained by the China-Brazil Earth Resources Satellite demonstrate that MSIF-Net has significant advantages over networks like U-Net, DeepLabV3+, MF2AM, and BuildFormer. Its Pixel Accuracy and Intersection over Union reached 93.84% and 85.32%, respectively, enabling high-precision automatic extraction of bare soil.

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Design and Analysis of a Low Power UWB Transmitter Using Second Derivative Gaussian Pulse

Design and Analysis of a Low Power UWB Transmitter Using Sec...

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Intelligent and Innovative Technologies in computing, electrical and Electronics (IITCEE), international conference

作者： Md Aminul Islam Md Ariful Ahmed Safwan Jasir Anirban Ahmed Pratyay Department of Electrical Electronic and Communication Engineering (EECE) Military Institute of Science and Technology (MIST) Mirpur Cantonment Dhaka Bangladesh

A low-power ultra-wideband (UWB) transmitter is proposed with the basic building blocks having an oscillator, modulator, and pulse generator using 90-nm CMOS technology in Cadence Virtuoso using a smaller number of transistors and passive elements. Frequency is generated using a ring oscillator with a common-gate switching nMOS to vary the delay. Different frequency is generated by varying the control voltage from 1V to 5V generating a 5.6 GHz to 7.0 GHz carrier wave. Moreover, a different range of frequency generation is also proposed with different capacitor values with the ring oscillator. BPSK modulation technique is implemented for its higher efficiency over other techniques. A very compact high-frequency BPSK design is proposed for the modulation circuit. Then, a Gaussian second-order pulse is generated with a 140ps pulse width. Gaussian pulse with varying widths can also be generated using the proposed model. The maximum sizing used for the transistors does not exceed 2 µm. The simulation results show the better performance of the transmitter in case of noise, efficiency, and BER over the other existing UWB transmitters.

关键词： Ring oscillators Frequency modulation Power demand Transmitters Radar tracking Binary phase shift keying Transistors

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