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Cognitive Systems engineering at 40, Part I: Deriving Theory from Practice

Proceedings of the human Factors and Ergonomics Society Annual Meeting 2023年第1期67卷 183 - 186页

作者： Michael F. Rayo Nancy J. Cooke John M. Flach Robert R. Hoffman Philip J. Smith David D. Woods Department of Integrated Systems Engineering The Ohio State University Columbus OH USA Center for Human Artificial Intelligence and Robot Teaming Arizona State University Tempe AZ USA Mile Two Dayton OH USA Institute for Human Machine Cognition Pensacola FL USA

This expert panel is the first of a two-panel series marking the 40th anniversary of “Cognitive Systems engineering: New Wine in New Bottles” by Hollnagel and Woods (1983) and, arguably, the beginning of Cognitive Systems engineering (CSE). These experts were there at (or near) the beginning, devising new methods, expanding and creating new theories, and revealing a new perspective on how complex systems sustain performance and fail. They also wrestled and struggled with these new ideas to propose and implement solutions to improve performance in a number of high-consequence industries. Whether in graduate school or as early-career professionals, they saw the surprises that served as signals that the thinking that brought us to that point would not, alone, be the thinking and doing that would take us further. They will each answer the question, “What ideas and perspectives are important about Cognitive Systems engineering, and why?”

关键词： cognitive systems engineering theory practice

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Learning Medical Subject Headings in PubMed Articles to Enhance Deep Predictions

Learning Medical Subject Headings in PubMed Articles to Enha...

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International Conference on Computational Cybernetics (ICCC)

作者： Zolzaya Dashdorj Zoljargal Jargalsaikhan Stanislav Grigorev Andrey Trufanov Tae-Koo Kang Erdenebaatar Altangerel Computer Science Mongolian University of Science and Technology Ulaanbaatar Mongolia School of Information Technology and Data Science Irkutsk National Research Technical University Irkutsk Russia Department of Human Intelligence and Robot Engineering Sangmyung University Seoul South Korea

ISBN: (数字)9798350350159

ISBN: (纸本)9798350350166

MeSH is a vocabulary of terms used in the life sciences and biomedical fields. A large amount of Medical Subject Headings (MeSH) occur in PubMed articles with different weights. In this research, we analyze a disease-symptom network exploiting MeSH metadata co-occurring in 7 million PubMed articles and configure a deep model in the context of biomedical and health care data. Optimized and efficient data networks are important to compile machine learning models. We optimize the deep model by reducing important features. Our result highlights that the degree of the severity of symptoms associated with a disease improves the accuracy of disease prediction models. The network was well optimized by reducing the number of symptoms. This finding may have important implications in healthcare: healthcare chatbots, clinical significance, practical implications.

关键词： Analytical models Vocabulary Accuracy Biological system modeling Computational modeling Medical services Machine learning

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Improving Vision Transformer with Multi-Task Training

Improving Vision Transformer with Multi-Task Training

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Woo Jin Ahn Geun Yeong Yang Hyun Duck Choi Myo Taeg Lim Tae Koo Kang School of Electrical Engineering Korea University Seoul Korea Department of ICT Convergence System Engineering Chonnam University Gwangju Korea Department of Human Intelligence and Robot Engineering Sangmyung University Cheonan Korea

Self-supervised learning methods have shown excellent performance in improving the performance of existing networks by learning visual representations from large amounts of unlabeled data. In this paper, we propose a end-to-end multi-task self-supervision method for vision transformer. The network is given two task: inpainting, position prediction. Given a masked image, the network predicts the missing pixel information and also predicts the position of the given puzzle patches. Through classification experiment, we demonstrate that the proposed method improves performance of the network compared to the direct supervised learning method.

关键词： Training Visualization Supervised learning Self-supervised learning Transformers Multitasking Control systems

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human robot Interaction: Identifying Resembling Emotions Using Dynamic Body Gestures of robot

Human Robot Interaction: Identifying Resembling Emotions Usi...

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Artificial intelligence (ICAI), International Conference on

作者： Sara Ali Faisal Mehmood Khawaja Fahad Iqbal Yasar Ayaz Muhammad Sajid Muhammad Baber Sial Muhammad Faiq Malik Kashif Javed Department of Robotics and Artificial Intelligence Human Robot Interaction Lab (SINES) Intelligent Field Robotics Lab (NCAI) National University of Sciences and Technology H-12 Islamabad Pakistan Department of Robotics and Artificial Intelligence National University of Sciences and Technology H-12 Islamabad Pakistan School of Automation Science and Electrical Engineering Beihang University Beijing China

Natural social interaction between a human and robot requires perception ability of robot for complex social behaviors and in turn displaying the learnt emotional behavior during interaction. The emotions expressed with body language are one of the key parameters during human-robot Interaction (HRI). This research focuses on extending the concept of affective non-verbal human-robot interaction using full body gestures for closely resembling emotion in absence of intricate facial expressions. The movements of head, torso, legs, and arms are used to link body movements and gestures of a bi-pedal humanoid robot with 28 closely resembling emotions. Variation of speed, frequency, and joint angles of the robot are the key features used for expressing a specific emotion. This research uses Russell's circumplex model to define 8 primary emotional categories which are further grouped into closely associated emotions resembling each other. 33 participants were involved in experimentation to authenticate different emotions using body gestures of robot. Each participant performed 28 trials in which emotions were displayed at random to recognize the state of robot. The results showed an average accuracy of 79.69%. The study authenticates that perceived emotions are highly dependent on body movements, postures, and selected features. This design model can therefore be used for even conveying the closely resembling emotions.

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Natural human Skin‑Inspired Wearable and Breathable Nanofiber‑based Sensors with Excellent Thermal Management Functionality

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Advanced Fiber Materials 2024年第6期6卷 1955-1968页

作者： Peng Wang Xiaodan Li Guifen Sun Guoqing Wang Qing Han Chuizhou Meng Zhonghe Wei Yang Li School of Mechanical Engineering University of JinanJinan 250022China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China State Key Laboratory for Reliability and Intelligence of Electrical Equipment Engineering Research Center of Ministry of Education for Intelligent Rehabilitation Device and Detection TechnologyHebei Key Laboratory of Smart Sensing and Human‑Robot InteractionSchool of Mechanical EngineeringHebei University of TechnologyTianjin 300401China Shandong Provincial Key Laboratory of Network‑Based Intelligent Computing School of Information Science and EngineeringUniversity of JinanJinan 250022China Network Information Center Department of Computer ScienceQilu University of Technology(Shandong Academy of Sciences)Jinan 250353China School of Integrated Circuits Shandong UniversityJinan 250101China

Wearable sensors have been rapidly developed for application in various human monitoring ***,the wearing comfort and thermal properties of these devices have been largely ignored,and these characteristics urgently need to be ***,we develop a wearable and breathable nanofiber-based sensor with excellent thermal management functionality based on passive heat preservation and active Joule heating *** multifunctional device consists of a micropatterned carbon nanotube(CNT)/thermoplastic polyurethane(TPU)nanofiber electrode,a microporous ionic aerogel electrolyte and a microstructured Ag/TPU nanofiber *** to the presence of a supercapacitive sensing mechanism and the appli-cation of microstructuration,the sensor shows excellent sensing performance,with a sensitivity of 24.62 ***,due to the overall porous structure and hydrophobicity of TPU,the sensor shows good breathability(62 mm/s)and water repellency,with a water contact angle of 151.2°.In addition,effective passive heat preservation is achieved by combining CNTs with high solar absorption rates(85%)as the top layer facing the outside,aerogel with a low thermal conductivity(0.063 W m-1 k-1)as the middle layer for thermal insulation,and Ag with a high infrared reflectance rate as the bottom layer facing the *** warming,this material yields a higher temperature than ***,the active Joule heat-ing effect is realized by applying current through the bottom resistive electrode,which can quickly increase the temperature to supply controlled warming on *** proposed wearable and breathable sensor with tunable thermal properties is promising for monitoring and heat therapy applications in cold environments.

关键词： Wearable sensor Breathable Personal thermal management Electrospun nanofibers Joule heating

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Optimal controller design for energy effective path following of car-like mobile robot

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AIP Conference Proceedings 2023年第1期3018卷

作者： Kiwon Yeom Department of Human Intelligence Robot Engineering Sangmyung University 31 Sangmyeongdae-gil Dongnam-gu Cheonan-si Chungcheongnam-do South Korea

The Automated self-driving vehicles not only allow of improved energy saving but also better traffic flow. In particular, with the rapid technological advance of autonomous electric vehicles, technical development of energy efficient vehicle control is becoming progressively important due to the limited battery capacity and power of electric vehicles. In this study, the Model Predictive Controller (MPC) algorithm is used to solve the optimal speed profile of the electric vehicles for minimizing energy consumption in a receding horizon and derived to follow the energy efficient path plan of the mobile vehicle. Finally, computational simulation results show that the proposed controller can successfully navigate and drive toward a final destination with energy efficient manner.

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A Laser-Scribed Wearable Strain Sensing System Powered by an Integrated Rechargeable Thin-Film Zinc-Air Battery for a Long-Time Continuous Healthcare Monitoring

SSRN

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SSRN 2022年

作者： Chen, Xue Hou, Zhanrui Li, Guoxian Yu, Wei Xue, Ye Niu, Guangyu Xin, Mingyang Yang, Li Meng, Chuizhou Guo, Shijie State Key Laboratory of Reliability and Intelligence of Electrical Equipment Key Laboratory of Bioelectromagnetics and Neuroengineering of Hebei Province School of Electrical Engineering Hebei University of Technology Tianjin300130 China State Key Laboratory for Reliability and Intelligence of Electrical Equipment Hebei Key Laboratory of Smart Sensing and Human-Robot Interaction School of Mechanical Engineering Hebei University of Technology Tianjin300401 China State Key Laboratory of Reliability and Intelligence of Electrical Equipment School of Health Sciences and Biomedical Engineering Hebei University of Technology Tianjin300130 China Department of Architecture and Art Hebei University of Technology Tianjin300130 China

Wearable sensors with long cruising times without the need for an external wire-connected power supply are urgently required for a continuous physiological signal monitoring. Herein, we report the design and fabrication of a wearable all-in-one sensing system that integrates a sensitive strain sensor and a rechargeable zinc-air battery on the same laser-induced graphene (LIG) platform. The sensing electrode of the strain sensor, the catalytic air electrode of the zinc-air battery and the interconnection lines between the two are simultaneously fabricated through the same laser-scribing process on polyimide (PI) followed by pattern transfer to a flexible and stretchable polydimethylsiloxane (PDMS) substrate. In the sensor, the conductive porous LIG exhibits a high gauge factor (~27028.1), a wide detection range (~40%) and a well cyclic loading-unloading stability (>20000 cycles). In the zinc-air battery, Co3O4 nanoparticles are in-situ laser-sintered on LIG to form an excellent electrode/electrolyte/air three-phased interfacing structure for a high catalytic performance, and a moisturized tetraethyl ammonium hydroxide (TEAOH)-KOH/polyvinyl alcohol (PVA) gel electrolyte tightly binds the Co3O4 /LIG air electrode and zinc foil electrode together into an integrate thin-film energy device, which provides a high open-circuit voltage (~1.39 V) and a high specific capacity (712 mAh g-1 at 0.2 mA cm-2 ). For a proof-of-concept, an intelligent wristband based on the sensing system was fabricated and worn on the wearer’s wrist for a long-time continuous pulse monitoring of up to 10 h. The health state of the wearer can be depicted upon the acquired pulse waveforms. The developed LIG-based sensing system with a high internal powering capability will be promising in wearable sensing applications. © 2022, The Authors. All rights reserved.

关键词： Graphene

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A study on an integrated system for urban autonomous driving technology and its application

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Journal of Institute of Control, robotics and Systems 2020年第5期26卷 279-294页

作者： Park, Raegeun Yun, Hyeok-Jin Han, Ean-Gyu Kang, Seong-Woo Jeon, Dae-Hyeon Park, Ji-Hoon Jung, Kown-Young Kang, Tae-Koo Department of Human Intelligence and Robot Engineering Sangmyung University Korea Republic of Department of Smart Information and Telecommunication Engineering Sangmyung University Korea Republic of Department of Information Security Engineering Sangmyung University Korea Republic of

Research on autonomous vehicles, such as lane recognition, sign recognition, LiDAR data processing, and avoidance control, continues to expand, and recently, commercially available vehicles were partially supplied with level 3 autonomous driving technology for use in highway environments. However, in urban environments, the application of level 3 technology is limited due to variables such as traffic lights and pedestrians. For this reason, for autonomous driving in urban environments, an integrated system of technologies for responding to many variables, such as road component recognition and obstacle avoidance, is required. However, if each sensor in the integrated system malfunctions or arrives at different judgments based on the same situation, a problem in vehicle control may occur due to exclusive data collision. Therefore, this paper proposes an integrated control system that develops a technology for responding to situations that occur during driving in urban environments, such as lane recognition, traffic light recognition, and obstacle avoidance, and gives priority to each algorithm. Experiments were conducted to confirm the performance of each algorithm and to verify the performance of the integrated system. Experiments were conducted at various sections of K-City (an autonomous driving test city in Korea). This integrated system showed how to appropriately respond to common situations in urban driving while considering many factors such as left turn, right turn, straight driving, and emergency braking. It is expected that the system proposed in this study and the experimental results obtained in K-City can be applied to actual urban environments in order to reflect various adverse conditions, such as road damage, encountered while driving on roads. © ICROS 2020.

关键词： Autonomous vehicles

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A Droplet-Based Multivolume Microfluidic Device for Digital Polymerase Chain Reaction

SSRN

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SSRN 2022年

作者： Wei, Chunyang Yu, Chengzhuang Li, Shanshan Meng, Jiyu Li, Tiejun Cheng, Jingmeng Li, Junwei Hebei Key Laboratory of Robotic Sensing and Human-robot Interactions School of Mechanical Engineering Hebei University of Technology Tianjin300132 China State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300130 China Institute of Biophysics School of Health Sciences and Biomedical Engineering Hebei University of Technology Tianjin300401 China Department of Computer Science and Electrical Engineering Hebei University of Technology Langfang065000 China

Digital PCR plays an essential role in detecting and quantifying nucleic acid targets, while there are still challenges, including reduction of cost, simplification of operations, and system miniaturization. This work proposes a droplet-based multivolume microfluidic device for easy-to-operate and integrated droplet digital PCR (ddPCR). With an elaborate " asymmetrical droplet-splitting" microstructure, we have successfully prepared a small droplet population ( n = 1.5k, Φ = 59.1 ± 2.2 μm) and a large droplet population ( n = 1.5k, Φ = 106.3 ± 3.9 μm) in the same chip for realizing multivolume design, by which the ddPCR chip achieves a dynamic range of over 10^4 for DNA molecule quantification. The chip integrates droplet generation, droplet array self-assembly, droplet dPCR, and fluorescence detection on a single device. The quantitative capability of the ddPCR chip was evaluated by measuring template DNA at concentrations from 20 to 12500 copies/μL. Benefiting from the characteristics of wide dynamic range, easy operation, and miniaturization, our ddPCR device is expected to be used in the applications involving DNA molecule quantification, including diagnosis of genetic disease, single-cell gene expression, and point of care field. © 2022, The Authors. All rights reserved.

关键词： Drops

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Fully Stretchable, Porous Mxene-Graphene Foam Nanocomposites for Energy Harvesting and Self-Powered Sensing

SSRN

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SSRN 2022年

作者： Yang, Li Liu, Chaosai Yuan, Wenjing Meng, Chuizhou Dutta, Ankan Chen, Xue Guo, Langang Niu, Guangyu Cheng, Huanyu State Key Laboratory of Reliability and Intelligence of Electrical Equipment School of Health Sciences and Biomedical Engineering Hebei University of Technology Tianjin300130 China Tianjin Key Laboratory of Materials Laminating Fabrication and Interface Control Technology School of Materials Science & Engineering Hebei University of Technology Tianjin300130 China State Key Laboratory for Reliability and Intelligence of Electrical Equipment Hebei Key Laboratory of Smart Sensing and Human-Robot Interaction School of Mechanical Engineering Hebei University of Technology Tianjin300401 China Department of Engineering Science and Mechanics The Pennsylvania State University University Park 16802 United States State Key Laboratory of Reliability and Intelligence of Electrical Equipment Key Laboratory of Bioelectromagnetics and Neuroengineering of Hebei Province School of Electrical Engineering Hebei University of Technology Tianjin300130 China School of Architecture and Art Hebei University of Technology Tianjin300130 China

The growing demand for intelligent wearable electronic devices has spurred the rapid developments of high-performance deformable power supplies such as triboelectric nanogenerators (TENGs) with high output performance. However, the intrinsically stretchable TENGs especially those prepared with low-cost manufacturing approaches still suffer from poor performance. To address the challenge, this paper presents a fully stretchable TENG consisting of an intrinsically stretchable MXene/silicone elastomer and silver nanowires (Ag NWs)-graphene foam nanocomposite. The intrinsically stretchable TENG exhibits high output performance (voltage, current, and power of 73.6 V, 7.75 μA, and 2.76 W m -2 ), long-term reliability, and stable electrical output under various extreme deformation conditions. In addition to the application on the human skin and clothing for human motion monitoring and detecting the strength training postures, the intrinsically stretchable TENG can also harvest the intermittent mechanical energy from human bodies to charge various energy storage units such as commercial capacitors for driving wearable electronic devices. The resulting systems have been demonstrated in applications from home anti-theft to water resources early warning systems, which provide the proof-of-the-concept demonstrations for the next-generation standalone device platforms. © 2022, The Authors. All rights reserved.

关键词： Nanogenerators

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