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Medical Knowledge Graph:Data Sources,Construction,Reasoning,and Applications

Big Data Mining and Analytics 2023年第2期6卷 201-217页

作者： Xuehong Wu Junwen Duan Yi Pan Min Li Computer Science and Engineering Central South UniversityChangsha 410083China School of Computer Science Hunan First Normal UniversityChangsha 410006China School of Computer Science and Engineering Central South UniversityChangsha 410083China Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518000China

Medical knowledge graphs(MKGs)are the basis for intelligent health care,and they have been in use in a variety of intelligent medical ***,understanding the research and application development of MKGs will be crucial for future relevant research in the biomedical *** this end,we offer an in-depth review of MKG in this *** research begins with the examination of four types of medical information sources,knowledge graph creation methodologies,and six major themes for MKG ***,three popular models of reasoning from the viewpoint of knowledge reasoning are discussed.A reasoning implementation path(RIP)is proposed as a means of expressing the reasoning procedures for *** addition,we explore intelligent medical applications based on RIP and MKG and classify them into nine major ***,we summarize the current state of MKG research based on more than 130 publications and future challenges and opportunities.

关键词： medical knowledge graph knowledge graph construction knowledge reasoning intelligent medical applications intelligent healthcare

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Temperature-triggered liquid metal actuators for fluid manipulation by leveraging phase transition control

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International Journal of Smart and Nano Materials 2024年第4期15卷 730-742页

作者： Hongda Lu Jiayi Yang Mengqing Zhao Qingtian Zhang Jialu Wang Xiangbo Zhou Yipu Guo Liping Gong Zexin Chen Shi-Yang Tang Weihua Li School of Mechanical MaterialsMechatronic and Biomedical EngineeringUniversity of WollongongWollongongAustralia School of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijingP.R.China School of Mechanical and Manufacturing Engineering University of New South WalesSydneyAustralia School of Electronics and Computer Science University of SouthamptonSouthamptonUK

Small-scale pumps for controlling microfluidics have promising applications in drug delivery and chemical *** metal(LM)demonstrates excellent flow pumping performance due to its simple structure and the electrocapillary effect under an electric ***,LM droplets risk escaping from constrained structures,which can lead to pump *** regulation is also a critical parameter in optimizing chemical reactions in fluidic systems,however,integrating it into a compact system remains ***,we develop a temperature-triggered gallium-based actuator(TTGA)by introducing a gallium(Ga)droplet wetted on a copper(Cu)plate as the core element for flow *** Cu plate prevents the Ga droplet from escaping the chamber and significantly increases the flow *** leveraging the electrochemical method to inhibit the supercooling effect of Ga,the TTGA enables activation/deactivation for flow actuation at different *** investigate the impact of electrode position,solution concentration,and applied voltage on TTGA’s pumping *** dynamically tuning the Ga droplet’s temperature to control phase transition,TTGA allows for accurate flow actuation ***,placing Ga and eutectic Ga-indium(EGaIn)droplets in different channels enables the expected flow divergence for fluids with different *** development of TTGA presents new opportunities in microfluidics and biomedical treatment.

关键词： Liquid metal actuators temperature sensation phase transition

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Exploiting Machine Learning and LSTM for Human Activity Recognition: Using Physiological and Biological Sensor Data from Actigraph 25

Exploiting Machine Learning and LSTM for Human Activity Reco...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Oyeleye, Matthew Chen, Tianhua Su, Pan Antoniou, Grigoris School Of Computing And Engineering University Of Huddersfield Department Of Computer Science United Kingdom School Of Control And Computer Engineering North China Electric Power University China

ISBN: (纸本)9798350340266

Human activity recognition involves identifying the daily living activities of an individual through the utilization of sensor attributes and intelligent learning algorithms. The identification of intricate human activities proves to be a labo-rious task, given the inherent difficulty of capturing long-term dependencies and extracting efficient features from unprocessed sensor data. For this purpose, this study aims at recognizing and classifying human activities using physiological and biological sensor data generated by Actigraph, as they can accurately measure moderate-to-vigorous intensity physical which is mostly affected by body composition and also better suited for self-monitoring. We examined the effectiveness of these features by applying prevalent machine learning classifiers and long short-term memory (LSTM) networks on recently publicly available data, which includes accelerometer and heart rate recordings. The results from our experiments showed that LSTM models performed better than conventional ML classifiers with the best result achieving an accuracy of 86.5%. The findings also confirms the significance of the heart rate in accurately classifying and identification of human activity more. © 2024 IEEE.

关键词： Long short-term memory

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Remote sensing image encryption algorithm based on novel hyperchaos and an elliptic curve cryptosystem

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Chinese Physics B 2024年第5期33卷 292-304页

作者：田婧希金松昌张晓强杨绍武史殿习 School of Computer Science National University of Defense TechnologyChangsha 410003China Intelligent Game and Decision Laboratory (IGDL) Beijing 100091China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China

Remote sensing images carry crucial ground information,often involving the spatial distribution and spatiotemporal changes of surface *** safeguard this sensitive data,image encryption technology is *** this paper,a novel Fibonacci sine exponential map is designed,the hyperchaotic performance of which is particularly suitable for image encryption *** encryption algorithm tailored for handling the multi-band attributes of remote sensing images is *** algorithm combines a three-dimensional synchronized scrambled diffusion operation with chaos to efficiently encrypt multiple ***,the keys are processed using an elliptic curve cryptosystem,eliminating the need for an additional channel to transmit the keys,thus enhancing *** results and algorithm analysis demonstrate that the algorithm offers strong security and high efficiency,making it suitable for remote sensing image encryption tasks.

关键词： hyperchaotic system elliptic curve cryptosystem(ECC) 3D synchronous scrambled diffusion remote sensing image unmanned aerial vehicle(UAV)

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Crowd E-Home—A Crowd-Based Collaborative Decoration Platform

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International Journal of Crowd Science 2022年第3期6卷 135-141页

作者： Ge, Rui Sun, Hongbo School of Computer and Control Engineering Yantai University Yantai264005 China

With the rapid development of Chinese urbanization and industrialization level, the Chinese real estate transaction area continues to grow, and the country's decoration industry is expanding. Due to the rapid expansion, the decoration industry has failed to establish a good industry order, and the current decoration industry has many problems, such as opaque information and low industrial efficiency. Traditional and Internet decoration companies have failed to solve these problems effectively. The purpose of this study is to build a new collaborative decoration platform to solve the shortcomings of the decoration industry and promote its healthy development. A crowd-based collaborative decoration platform called Crowd E-home is proposed. Based on the Building Information Modeling (BIM) of houses, the platform constructs collaborative intelligent digital models, which have the characteristics of evolution, coordination, multifaceted, and initiative. These models act as intermediate coordinators to complete the collaborative division of labor. This platform plays a role in matching multiparty transactions among consumers, designers, construction teams, material suppliers, and supervisors to solve the problem of the huge coordination costs of traditional decoration companies. It also breaks the space-time limit of consumer selection during the decoration process, improves the decision-making power of consumers, and meets consumer needs for personalized services. The collaborative concept of the platform and the application of BIM optimize the existing decoration industry chain, which transforms the traditional chain model into a star-shaped decoration closed-loop ecosystem. © The author(s) 2022.

关键词： Decision making

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A Personality Detection Method Based on Semantic and Psycholinguistic of Social Texts 7

A Personality Detection Method Based on Semantic and Psychol...

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7th International Conference on computer Information Science and Application Technology, CISAT 2024

作者： Wang, Chundong Yang, Yuhan Lin, Hao Han, Lu Tianjin University of Technology School of Computer Science and Engineering National Engineering Laboratory for Computer Virus Prevention and Control Technology Tianjin China

ISBN: (纸本)9798350375107

At the intersection of personality psychology, computer science, and linguistics, more and more researchers are paying attention to personality detection based on content analysis of texts on social media. However, existing social text-based personality detection methods rely heavily on pre-trained language models, overlook multi-dimensional sentiment in social texts, and lack of effective feature selection of psycholinguistic features. To address these limitations, we propose a method for Myers-Briggs type indicator (MBTI) personality detection. Our approach extracts and selects high-dimensional psycholinguistic feature, utilizes an optimal intermediate layer output from pre-trained language models for semantic representation, and fuses these features to enhance detection accuracy. The experiment results indicate that our proposed method improves the state-of-art results for MBTI personality traits by 1.65% on average on Kaggle MBTI dataset. © 2024 IEEE.

关键词： Psychoacoustic

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A Crowd Equivalence-Based Massive Member Model Generation Method for Crowd Science Simulations

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International Journal of Crowd Science 2022年第1期6卷 23-33页

作者： Xing, Aoqiang Sun, Hongbo School of Computer and Control Engineering Yantai University Yantai264005 China

Crowd phenomena are widespread in human society, but they cannot be observed easily in the real world, and research on them cannot follow traditional ways. Simulation is one of the most effective means to support studies about crowd phenomena. As modelbased scientific activities, crowd science simulations take extra efforts on member models, which reflect individuals who own characteristics such as heterogeneity, large scale, and multiplicate connections. Unfortunately, collecting enormous members is difficult in reality. How to generate tremendous crowd equivalent member models according to real members is an urgent problem to be solved. A crowd equivalence-based massive member model generation method is proposed. Member model generation is accomplished according to the following steps. The first step is the member metamodel definition, which provides patterns and member model data elements for member model definition. The second step is member model definition, which defines types, quantities, and attributes of member models for member model generation. The third step is crowd network definition and generation, which defines and generates an equivalent large-scale crowd network according to the numerical characteristics of existing networks. On the basis of the structure of the large-scale crowd network, connections among member models are well established and regarded as social relationships among real members. The last step is member model generation. Based on the previous steps, it generates types, attributes, and connections among member models. According to the quality-time model of crowd intelligence level measurement, a crowd-oriented equivalence for crowd networks is derived on the basis of numerical characteristics. A massive member model generation tool is developed according to the proposed method. The member models generated by this tool possess multiplicate connections and attributes, which satisfy the requirements of crowd science simulations well. T

关键词： Data models Numerical models Level measurement Task analysis Standards

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An identification method of dangerous driving behavior in rush hour based on apriori algorithm

Advances in Transportation Studies

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Advances in Transportation Studies 2022年第Special issue期4卷 113-122页

作者： Li, D.H. Sun, J.L. Wu, P. Tao, W. Chen, A. School of Computer and Control Engineering Qiqihar University Qiqihar161000 China

Aiming at the problem of large error and long time of traditional dangerous driving behavior recognition, this paper designs a dangerous driving behavior recognition method based on Apriori algorithm in rush hour. Firstly, the basic coordinate system and the world coordinate system of the camera are established, and the driving behavior images of the driver are collected comprehensively by means of homogeneous matrix transformation. After the grayscale processing of the image, median filtering method is used to suppress the noise in the image, and histogram equalization algorithm is used to enhance the image. Finally, dangerous driving behavior is located by determining the face and hand change characteristics of dangerous driving behavior, and the Apriori algorithm is used to determine the frequent item set of dangerous driving behavior, and the principal component of dangerous driving behavior image is extracted to achieve effective recognition. Experimental results show that the proposed method can keep the recognition error below 2.0%, and its global maximum recognition time is only 0.21s, indicating that the proposed method effectively achieves the design expectation. © 2022, Aracne Editrice. All rights reserved.

关键词： Image enhancement

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COVID-19 Spread Simulation in a Crowd Intelligence Network

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International Journal of Crowd Science 2022年第3期6卷 117-127页

作者： Shan, Linzhi Sun, Hongbo School of Computer and Control Engineering Yantai University Yantai264005 China

In this paper, the Crowd Intelligence Network Model is applied to the simulation of epidemic spread. This model combines the multi-layer coupling network model and the two-stage feedback member model to study the epidemic spread mechanisms under multiple-scene intervention. First, this paper establishes a multi-layer coupled network structure based on the characteristic of Social Network, Information Network, and Monitor Network, namely, the Crowd Intelligence Network structure. Then, based on this structure, the digital-self model, which has a multiple-scene effect and two-stage feedback structure, is designed. It has an emotional state and infection state quantified by using attitude and self-protection levels. This paper uses the attitude level and self-protection level to quantify individual emotions and immune levels, and discusses the impact of individual emotions on epidemic prevention and control. Finally, the availability of the Crowd Intelligence Network Model on the epidemic spread is verified by comparing the simulation trend with the actual spread trend of COVID-19. © The author(s) 2022.

关键词： COVID-19

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Two-Stage Distributionally Robust Optimization Model of Integrated Energy System Considering Flexible Resources 8

Two-Stage Distributionally Robust Optimization Model of Inte...

引用

8th IEEE International Conference on Energy Internet, ICEI 2024

作者： Li, Jie Deng, Dan Li, Yunzhi North China Electric Power University School of Control and Computer Engineering Beijing China

ISBN: (纸本)9798331523558

Due to the intermittent and fluctuating properties of renewable energy, Integrated Energy Systems (IES) face great challenges in terms of secure, economic, and low-carbon operation. To improve the penetration rate of renewable energy and the flexibility of IES, a two-stage distributionally robust optimization model is proposed considering flexible resources. Firstly, a fuzzy set of the total error function is established based on the Wasserstein distance. Then a two-stage distributionally robust optimization model is established within the day-ahead and real-time scales. Finally, the flexible resource model is finely established and the flexibility constraints are considered based on the flexibility demand of IES. The simulation results show that the upward and downward flexibility of IES can be maximally increased by 8 342.3 kW and 8 428.6 kW by means of flexible resources, meanwhile the system economy has not significantly decreased. © 2024 IEEE.

关键词： Clean energy

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