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ROLE OF SIMULATION IN RAPID PROTOTYPING FOR CONCEPT DEVELOPMENT

NAVAL ENGINEERS JOURNAL 1991年第3期103卷 204-211页

作者： KING, JF BARTON, DE J. Fred King:is the manager of the Advanced Technology Department for Unisys in Reston Virginia. He earned his Ph.D. in mathematics from the University of Houston in 1977. He has been principal investigator of research projects in knowledge engineering pattern recognition and heuristic problem-solving. Efforts include the development of a multi-temporal multispectral classifier for identifying graincrops using LANDSAT satellite imagery data for NASA. Also as a member of the research team for a NCI study with Baylor College of Medicine and NASA he helped develop techniques for detection of carcinoma using multispectral microphotometer scans of lung tissue. He established and became technical director of the AI Laboratory for Ford Aerospace where he developed expert scheduling modeling and knowledge acquisition systems for NASA. Since joining Unisys in 1985 he has led the development of object-oriented programming environments blackboard architectures data fusion techniques using neural networks and intelligent data base systems. Douglas E. Barton:is manager of Logistics Information Systems for Unisys in Reston Virginia. He earned his B.A. degree in computer science from the College of William and Mary in 1978 and did postgraduate work in London as a Drapers Company scholar. Since joining Unisys in 1981 his work has concentrated on program management and software engineering of large scale data base management systems and design and implementation of knowledge-based systems in planning and logistics. As chairman of the Logistics Data Subcommittee of the National Security Industrial Association (NSIA) he led an industry initiative which examined concepts in knowledge-based systems in military logistics. His responsibilities also include evaluation development and tailoring of software engineering standards and procedures for data base and knowledge-based systems. He is currently program manager of the Navigation Information Management System which provides support to the Fleet Ballistic Missile Progr

A valuable technique during concept development is rapid prototyping of software for key design components. This approach is particularly useful when the optimum design approach is not readily apparent or several known alternatives need to be rapidly evaluated. A problem inherent in rapid prototyping is the lack of a "target system" with which to interface. Some alternatives are to develop test driver libraries, integrate the prototype with an existing working simulator, or build one for the specific problem. This paper presents a unique approach to concept development using rapid prototyping for concept development and scenario-based simulation for concept verification. The rapid prototyping environment, derived from artificial intelligence technology, is based on a blackboard architecture. The rapid prototype simulation capability is provided through an object-oriented modeling environment. It is shown how both simulation and blackboard technologies are used collectively to rapidly gain insight into a tenacious problem. A specific example will be discussed where this approach was used to evolve the logic of a mission controller for an autonomous underwater vehicle.

关键词： Military Engineering

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Linked data Crowdsourcing Quality Assessment based on Domain Professionalism

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Journal of Physics: Conference Series 2019年第5期1187卷

作者： Lu Yang Li Huang Zhenzhen Liu School of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Intelligent Information Processing and Real-time Industrial System in Hubei Province Wuhan 430065 China Institute of Big Data Science and Engineering Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Rich-media Knowledge Organization and Service of Digital Publishing Content National Press and Publication Administration Beijing 100038 China

With the rapid development of Internet technology, crowdsourcing, as a flexible, effective and low-cost problem-solving method, has begun to receive more and more attention. The use of crowdsourcing to evaluate the quality of linked data has also become a research hotspot. This paper proposes the concept of Domain Specialization Test (DST), which uses domain professional testing tasks DSTs to evaluate the professionalism of workers, and combines the idea of Mini-batch Gradient Descent (MBGD) to improve the EM algorithm, and the MBEM algorithm is proposed to achieve efficient and accurate evaluation of task results. The experimental results show that the proposed method can screen out the appropriate workers for the linked data crowdsourcing task and improve the accuracy and iteration efficiency of the results.

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Emergency Event Matching using Hierarchical Blocking Method

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Journal of Physics: Conference Series 2019年第5期1187卷

作者： Chang Wen Yu Liu College of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Intelligent Information Processing and Real-time Industrial System in Hubei Province Wuhan 430065 China Institute of Big Data Science and Engineering Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Rich-media Knowledge Organization and Service of Digital Publishing Content National Press and Publication Administration Beijing 100038 China

With the extensive application of the knowledge base (KB), how to complete it is a hot topic on Semantic Web. However, many problems go with the big data, and the event matching is one of these problems, which is finding out the entities referring to the same things in the real world and also the key point in the extending process. To enrich the emergency knowledge base (E-SKB) we constructed before, we need to filter out the news from several web pages and find the same news to avoid data redundancy. In this paper, we proposed a hierarchy blocking method to reduce the times of comparisons and narrow down the scope by extracting the news properties as the blocking keys. The method transforms the event matching problem into a clustering problem. Experimental results show that the proposed method is superior to the existing text clustering algorithm with high precision and less comparison times.

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The instantaneous linear motion information measurement method based on inertial sensors for ships

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AIP Conference Proceedings 2018年第1期1967卷

作者： Xu Yang Jing Huang Chen Gao Wei Quan Ming Li Yanshun Zhang 1School of Instrumentation Science & Optoelectronics Beihang University Beijing 100191 China 2Tianjin Zhong Wei Aerospace Data System Technology Co. Ltd Tianjin 300301 China 3Tianjin Key Laboratory of Intelligent Information Processing in Remote Sensing Tianjin 300100 China 4Military Representative Office Positioned in 699 Factory of PLA Beijing 100039 and China

Ship instantaneous line motion information is the important foundation for ship control, which needs to be measured accurately. For this purpose, an instantaneous line motion measurement method based on inertial sensors is put forward for ships. By introducing a half-fixed coordinate system to realize the separation between instantaneous line motion and ship master movement, the instantaneous line motion acceleration of ships can be obtained with higher accuracy. Then, the digital high-pass filter is applied to suppress the velocity error caused by the low frequency signal such as schuler period. Finally, the instantaneous linear motion displacement of ships can be measured accurately. Simulation experimental results show that the method is reliable and effective, and can realize the precise measurement of velocity and displacement of instantaneous line motion for ships.

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LUneXt: Simple and Efficient U-shaped Network Design for Medical Image Segmentation with Nonlinear Activation

Computing Open

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Computing Open 2024年第2期computing-open卷

作者： Guanghong Deng Bing Yu Wenlong Jing Yong Li Xiaodan Zhao GuangDong Engineering Technology Research Center of UAV Remote Sensing Network Guangzhou iMapCloud Intelligent Technology Co. Ltd. Guangzhou 510095 P. R. China Guangdong Province Engineering Laboratory for Geographic Spatiotemporal Big Data Key Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and Application Guangzhou Institute of Geography Guangdong Academy of Sciences Guangzhou 510070 P. R. China Foshan iMapCloud Intelligent Technology Co. Ltd. Foshan 528251 P. R. China

Medical image segmentation has always been a challenging task. This paper proposes a new LUneXt medical image segmentation model based on the characteristics analysis of medical image data sets and testing of different nonlinear activation units. Both normalized activations for the original negative input image activation have good optimization capabilities for the tokenization module parameters proposed in the original UneXt model. Using different activation coefficients for different foreground and background areas has achieved better results. The experimental results of this paper on the Breast Ultrasound Images (BUSI) data set reached an intersection over union (IoU) value of 62.64%, a Dice value of 76.12%, and a single inference speed of 807.57 ms. The experimental IoU value of the International Skin Imaging Collaboration (ISIC 2018) data set reached 82.95%, and the Dice value reached 90.50%. The single inference speed reached 842.58 ms. The LUneXt model is more robust than other models. While improving model performance, it does not introduce higher computational complexity and does not have a major impact on the processing speed of a single image.

关键词： Image segmentation medical images neural networks activation function

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Design of Command and Dispatch system for Automatic Reading of Meter Images in Substations by UAV Inspection Photos

Computing Open

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Computing Open 2024年第2期computing-open卷

作者： Guanghong Deng Liangpei Lin Baihao Lin Wenlong Jing Xiaodan Zhao Yong Li Rui Yang Shidun Xie Pengfeng Wei GuangDong Engineering Technology Research Center of UAV Remote Sensing Network Guangzhou iMapCloud Intelligent Technology Co. Ltd. Guangzhou 510095 P. R. China Guangdong Province Engineering Laboratory for Geographic Spatiotemporal Big Data Key Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and Application Guangzhou Institute of Geography Guangdong Academy of Sciences Guangzhou 510070 P. R. China Foshan iMapCloud Intelligent Technology Co. Ltd. Foshan 528251 P. R. China

The application of the combination of unmanned aerial vehicles (UAVs) and artificial intelligence is a hot topic in the intelligent inspection of substations, and meter reading is a very challenging task. This paper proposes a method based on the combination of YOLOv6n object detection and Deeplabv3 + image segmentation and performs post-processing on the segmented images to obtain meter readings. First, YOLOv6n is used to detect the meter area of the aerial image and classify the meters. Second, the detected meter images are fed into the image segmentation model. The backbone network of the Deeplabv3 + algorithm is improved by using the MobileNetv3 network, which not only effectively extracts pointers and scales, but also makes the model more lightweight. Third, License Plate Recognition Network (LPRNet) is used to recognize digital meter images. In order to solve the problem of inaccurate pointer meter readings, to begin with, the segmented image is corroded; in addition, the circular dial area is flattened into a rectangular area by concentric circle sampling method. Finally, the meter reading is calculated by the position of the pointer, the scale and the total range of the meter. The post-processing part uses numba to optimize the inference speed. The experimental results show that in two datasets, The mean average precision of 50 (mAP50) accuracy of the YOLOv6n model using this method reached 99.71% and 98.60%, respectively, and the inference speed of a single image was 17.1 ms and 13.2 ms, respectively. The mean intersection over union (mIoU) of the image segmentation model reached 82.00%, 74.73%, 73.50%, 82.26% and 73.20%, respectively, and the single segmentation speed reached 33.7 ms. The LPRNet model has a recognition accuracy of 99.17% and a single image inference speed of 14.7 ms. At the same time, several mainstream object detection and semantic segmentation algorithms are compared. The experimental results show that the method in this paper greatly im

关键词： Object detection image segmentation YOLOv6n Deeplabv3 + meter reading

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Circulating proteins and peripheral artery disease risk: observational and Mendelian randomization analyses

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European Heart Journal Open 2023年第3期3卷 oead056页

作者： Yuan, Shuai Titova, Olga E. Zhang, Ke Chen, Jie Li, Xue Klarin, Derek Åkesson, Agneta Damrauer, Scott M. Larsson, Susanna C. Unit of Cardiovascular and Nutritional Epidemiology Institute of Environmental Medicine Karolinska Institutet Nobels väg 13 Solna Stockholm 171 65 Sweden Unit of Medical Epidemiology Department of Surgical Sciences Uppsala University Uppsala Sweden Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province School of Life Sciences Westlake University Hangzhou China Westlake Intelligent Biomarker Discovery Lab Westlake Laboratory of Life Sciences and Biomedicine Hangzhou China Department of Big Data in Health Science School of Public Health Center of Clinical Big Data and Analytics The Second Affiliated Hospital Zhejiang University School of Medicine Hangzhou China VA Palo Alto Healthcare System 4951 Arroyo Rd Livermore 94550 CA United States Department of Surgery Stanford University School of Medicine Stanford University Palo Alto CA United States Corporal Michael J. Crescenz VA Medical Center Philadelphia PA United States Department of Surgery Department of Genetics Perelman School of Medicine University of Pennsylvania Philadelphia PA United States

Aims We conducted observational and Mendelian randomization (MR) analyses to explore the associations between blood proteins and risk of peripheral artery disease (PAD).;Methods and results The observational cohort analyses included data on 257 proteins estimated in fasting blood samples from 12 136 Swedish adults aged 55–94 years who were followed up for incident PAD via the Swedish Patient Register. Mendelian randomization analyses were undertaken using cis-genetic variants strongly associated with the proteins as instrumental variables and genetic association summary statistic data for PAD from the FinnGen study (11 924 cases and 288 638 controls) and the Million Veteran Program (31 307 cases and 211 753 controls). The observational analysis, including 86 individuals diagnosed with incident PAD during a median follow-up of 6.6-year, identified 13 proteins [trefoil factor two, matrix metalloproteinase-12 (MMP-12), growth differentiation factor 15, V-set and immunoglobulin domain-containing protein two, N-terminal prohormone brain natriuretic peptide, renin, natriuretic peptides B, phosphoprotein associated with glycosphingolipid-enriched microdomains one, C-C motif chemokine 15, P-selectin, urokinase plasminogen activator surface receptor, angiopoietin-2, and C-type lectin domain family five member A] associated with the risk of PAD after multiple testing correction. Mendelian randomization analysis found associations of T-cell surface glycoprotein CD4, MMP-12, secretoglobin family 3A member 2, and ADM with PAD risk. The observational and MR associations for T-cell surface glycoprotein CD4 and MMP-12 were in opposite directions. Conclusion This study identified many circulating proteins in relation to the development of incident PAD. Future studies are needed to verify our findings and assess the predictive and therapeutic values of these proteins in PAD. © The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.

关键词： Cohort Mendelian randomization Protein Peripheral artery disease

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2-D GCANet Applied to Denoise 1-D EEG Signals in Online Remote Teaching Scenarios

Journal of Network Intelligence

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Journal of Network Intelligence 2023年第4期8卷 1289-1302页

作者： Huang, Ting-Qing Wang, Chuan-Sheng Chen, Zhao-Qi Zhang, Fu-Quan Meng, Xiang-Long Grau, Antoni Chen, Yang Huang, Jing-Wei College of Computer and Control Engineering Minjiang University Fuzhou University Town No. 200 Xiyuangong Road Fuzhou China Department of Automatic Control Technical Polytechnic University of Catalonia Autonomous Region of Catalonia Barcelona Spain College of Computer and Big Data Fuzhou University Fuzhou University Town No. 2 Wulong Jiangbei Avenue Fuzhou China Digital Media Art Key Laboratory of Sichuan Province Sichuan Conservatory of Music No. 2 Wannianchang Street Chenghua District Sichuan Province Chengdu City China Fuzhou Technology Innovation Center of intelligent Manufacturing information System Minjiang University Fuzhou University Town NO. 200 Xiyuangong Road Fuzhou China Fujian Province University No. 599 Quanxiu Road Juyuanzhou Ecological Civilization District Fujian Province Fuzhou City China College of Electronic Engineering Shandong University of Science and Technology No. 579 Qianwangang Road Huangdao District Qingdao China School of Mechanical and Automotive Engineering Fujian University of Technology No. 33 Xuefu South Road University New District Fujian Province Fuzhou City China

When EEG signals are used to assess the level of student engagement in online teaching tasks, they are often interfered by noise. It is a challenge to effectively remove these noises. Currently, deep learning methods have been applied to the field of EEG denoising. However, existing methods still have some problems. The denoised signals still have obvious noise residue, or the original EEG signals are damaged, and the model fitting speed is too slow. Image dehazing, as a typical denoising task in the field of image enhancement, has achieved great success in recent years. Therefore, inspired by advanced models in this field, we introduce CNN into EEG denoising tasks. In this paper, we take GCANet, an excellent image enhancement model, as an example. The dilated convolutions and gate fusion subnetworks included in GCANet enable more efficient EEG signal denoising. The results demonstrate that the proposed model effectively reduces noise while preserving essential features. Furthermore, in comparison to other state-of-the-art models, our proposed model exhibits enhanced robustness and faster convergence, as evidenced by achieving lower loss values after five epochs. Its good performance provides a new development idea for the field of EEG denoising. © 2023, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Image enhancement

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HRPGAN: A GAN-based Model to Generate High-resolution Remote Sensing Images

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IOP Conference Series: Earth and Environmental Science 2020年第1期428卷

作者： Hai Sun Ping Wang Yifan Chang Li Qi Hailei Wang Dan Xiao Cheng Zhong Xuelian Wu Wenbo Li Bingyu Sun China Telecom Shanghai Ideal Information Industry (Group) Co. Ltd Shanghai China Department of Airborne Remote Sensing National Disaster Reduction Center of China Beijing China Institute of Technology Innovation Hefei Institute of Physical Science Chinese Academy of Sciences Hefei China The Third Research Institute of the Ministry of Public Security Shanghai China Guizhou Key Laboratory of Economics System Simulation Guizhou University of Finance and Economics Guiyang China Beijing Aerospace Flight Control Center Beijing China Institute of Intelligent Machines Chinese Academy of Sciences Hefei China

Generative adversarial networks (GAN) has been mainly used in the generation of natural images such as MNIST, CIFAR10 as well as Imagenet datasets and achieves satisfying generation results. However, GAN always fails in generating high quality high-resolution remote sensing images because remote sensing images are large in size and have various ground objects. To address this issue, a novel framework called High-Resolution PatchGAN (HRPGAN) is introduced in this paper. The structure of HRPGAN follows PatchGAN, but the batch normalization layers are removed and the ReLU activation is replaced by the SELU activation. In addition, a new loss function consisting of the adversarial loss, perceptual reconstruction loss and regularization loss is used in HRPGAN. Experiment results show that the proposed HRPGAN model generates the more diverse and lifelike images in HR remote sensing generation than Bicubic method and TGAN model.

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Flexible, ultrathin bioelectronic materials and devices for chronically stable neural interfaces

Brain‐X

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Brain‐X 2023年第4期1卷

作者： Lianjie Zhou Zhongyuan Wu Mubai Sun Jaejin Park Mengdi Han Ming Wang Junsheng Yu Zengfeng Di Yongfeng Mei Wubin Bai Xinge Yu Ki Jun Yu Enming Song Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception Institute of Optoelectronics Fudan University Shanghai China Contribution: Investigation Visualization Writing - original draft Institute of Agro-food Technology Jilin Academy of Agricultural Sciences Changchun Jilin China Contribution: Data curation Investigation Functional Bio-integrated Electronics and Energy Management Lab School of Electrical and Electronic Engineering Yonsei University Seoul Korea Department of Biomedical Engineering College of Future Technology Peking University Beijing China Contribution: Resources Validation State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai China State Key Laboratory of Electronic Thin Films and Integrated Devices School of Optoelectronic Science and Engineering University of Electronic Science and Technology of China (UESTC) Chengdu Sichuan China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China Department of Material Science Fudan University Shanghai China Department of Applied Physical Sciences University of North Carolina at Chapel Hill Chapel Hill North Carolina USA Department of Biomedical Engineering City University of Hong Kong Hong Kong SAR China Wubin Bai Xinge Yu Ki Jun Yu and Enming Song. Contribution: Conceptualization Methodology Resources Supervision Writing - review & editing

Advanced technologies that can establish intimate, long-lived functional interfaces with neural systems have attracted increasing interest due to their wide-ranging applications in neuroscience, bioelectronic medicine, and the associated treatment of neurodegenerative diseases. A critical challenge of significance remains in the development of electronic platforms that offer conformal contact with soft brain tissue for the sensing or stimulation of brain activities and chronically stable operation in vivo, at scales that range from cellular-level resolution to macroscopic areas. This review summarizes recent advances in this field, with an emphasis on the use of demonstrated concepts, constituent materials, engineered designs, and system integration to address the current challenges. The article begins with an overview of recent bioelectronic platforms with unique form factors, ranging from filamentary probes to conformal sheets and three-dimensional frameworks for alleviating the mechanical mismatch between interface materials and neural tissues. Next, active interfaces which utilize inorganic/organic semiconductor-enabled devices are reviewed, highlighting various working principles of recording mechanisms including capacitively and conductively coupled sensing enabled by high transistor matrices at high spatiotemporal resolution. The subsequent section presents approaches to biological integration which use active materials for multiplexed addressing, local amplification and multimodal operation with high-channel-count and large-scale electronic systems in a safe fashion that provides multi-decade stable performance in both animal models and human subjects. The advances summarized in this review will guide the future direction of this technology and provide a basis for next-generation chronic neural interfaces with long-lived high-performance operation.

关键词： neural interface flexibility passive electrodes active recording barrier materials chronic stability

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