Edge Computing to Solve Security Issues for Infectious Disease Intelligence Prevention

2022 ◽  
Vol 22 (3) ◽  
pp. 1-20
Zhihan Lv ◽  
Ranran Lou ◽  
Haibin Lv

Nowadays, with the rapid development of intelligent technology, it is urgent to effectively prevent infectious diseases and ensure people's privacy. The present work constructs the intelligent prevention system of infectious diseases based on edge computing by using the edge computing algorithm, and further deploys and optimizes the privacy information security defense strategy of users in the system, controls the cost, constructs the optimal conditions of the system security defense, and finally analyzes the performance of the model. The results show that the system delay decreases with the increase of power in the downlink. In the analysis of the security performance of personal privacy information, it is found that six different nodes can maintain the optimal strategy when the cost is minimized in the finite time domain and infinite time domain. In comparison with other classical algorithms in the communication field, when the intelligent prevention system of infectious diseases constructed adopts the best defense strategy, it can effectively reduce the consumption of computing resources of edge network equipment, and the prediction accuracy is obviously better than that of other algorithms, reaching 83%. Hence, the results demonstrate that the model constructed can ensure the safety performance and forecast accuracy, and achieve the best defense strategy at low cost, which provides experimental reference for the prevention and detection of infectious diseases in the later period.

2021 ◽  
Vol 6 (1) ◽  
Hee-Gyeong Yi ◽  
Hyeonji Kim ◽  
Junyoung Kwon ◽  
Yeong-Jin Choi ◽  
Jinah Jang ◽  

AbstractRapid development of vaccines and therapeutics is necessary to tackle the emergence of new pathogens and infectious diseases. To speed up the drug discovery process, the conventional development pipeline can be retooled by introducing advanced in vitro models as alternatives to conventional infectious disease models and by employing advanced technology for the production of medicine and cell/drug delivery systems. In this regard, layer-by-layer construction with a 3D bioprinting system or other technologies provides a beneficial method for developing highly biomimetic and reliable in vitro models for infectious disease research. In addition, the high flexibility and versatility of 3D bioprinting offer advantages in the effective production of vaccines, therapeutics, and relevant delivery systems. Herein, we discuss the potential of 3D bioprinting technologies for the control of infectious diseases. We also suggest that 3D bioprinting in infectious disease research and drug development could be a significant platform technology for the rapid and automated production of tissue/organ models and medicines in the near future.

2021 ◽  
Vol 11 (1) ◽  
pp. 1-30
Yunjiang Rao ◽  
Zinan Wang ◽  
Huijuan Wu ◽  
Zengling Ran ◽  
Bing Han

AbstractPhase-sensitive optical time domain reflectometry (Ф-OTDR) is an effective way to detect vibrations and acoustic waves with high sensitivity, by interrogating coherent Rayleigh backscattering light in sensing fiber. In particular, fiber-optic distributed acoustic sensing (DAS) based on the Ф-OTDR with phase demodulation has been extensively studied and widely used in intrusion detection, borehole seismic acquisition, structure health monitoring, etc., in recent years, with superior advantages such as long sensing range, fast response speed, wide sensing bandwidth, low operation cost and long service lifetime. Significant advances in research and development (R&D) of Ф-OTDR have been made since 2014. In this review, we present a historical review of Ф-OTDR and then summarize the recent progress of Ф-OTDR in the Fiber Optics Research Center (FORC) at University of Electronic Science and Technology of China (UESTC), which is the first group to carry out R&D of Ф-OTDR and invent ultra-sensitive DAS (uDAS) seismometer in China which is elected as one of the ten most significant technology advances of PetroChina in 2019. It can be seen that the Ф-OTDR/DAS technology is currently under its rapid development stage and would reach its climax in the next 5 years.

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 929
Guiyun Liu ◽  
Jieyong Chen ◽  
Zhongwei Liang ◽  
Zhimin Peng ◽  
Junqiang Li

With the rapid development of science and technology, the application of wireless sensor networks (WSNs) is more and more widely. It has been widely concerned by scholars. Viruses are one of the main threats to WSNs. In this paper, based on the principle of epidemic dynamics, we build a SEIR propagation model with the mutated virus in WSNs, where E nodes are infectious and cannot be repaired to S nodes or R nodes. Subsequently, the basic reproduction number R0, the local stability and global stability of the system are analyzed. The cost function and Hamiltonian function are constructed by taking the repair ratio of infected nodes and the repair ratio of mutated infected nodes as optimization control variables. Based on the Pontryagin maximum principle, an optimal control strategy is designed to effectively control the spread of the virus and minimize the total cost. The simulation results show that the model has a guiding significance to curb the spread of mutated virus in WSNs.

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 215 ◽  
Yu Yang ◽  
Bichen Che ◽  
Yang Zeng ◽  
Yang Cheng ◽  
Chenyang Li

With the rapid development and widespread applications of Internet of Things (IoT) systems, the corresponding security issues are getting more and more serious. This paper proposes a multistage asymmetric information attack and defense model (MAIAD) for IoT systems. Under the premise of asymmetric information, MAIAD extends the single-stage game model with dynamic and evolutionary game theory. By quantifying the benefits for both the attack and defense, MAIAD can determine the optimal defense strategy for IoT systems. Simulation results show that the model can select the optimal security defense strategy for various IoT systems.

Materials ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2545
Marcin Hoffmann ◽  
Krzysztof Żarkiewicz ◽  
Adam Zieliński ◽  
Szymon Skibicki ◽  
Łukasz Marchewka

Foundation piles that are made by concrete 3D printers constitute a new alternative way of founding buildings constructed using incremental technology. We are currently observing very rapid development of incremental technology for the construction industry. The systems that are used for 3D printing with the application of construction materials make it possible to form permanent formwork for strip foundations, construct load-bearing walls and partition walls, and prefabricate elements, such as stairs, lintels, and ceilings. 3D printing systems do not offer soil reinforcement by making piles. The paper presents the possibility of making concrete foundation piles in laboratory conditions using a concrete 3D printer. The paper shows the tools and procedure for pile pumping. An experiment for measuring pile bearing capacity is described and an example of a pile deployment model under a foundation is described. The results of the tests and analytical calculations have shown that the displacement piles demonstrate less settlement when compared to the analysed shallow foundation. The authors indicate that it is possible to replace the shallow foundation with a series of piles combined with a printed wall without locally widening it. This type of foundation can be used for the foundation of low-rise buildings, such as detached houses. Estimated calculations have shown that the possibility of making foundation piles by a 3D printer will reduce the cost of making foundations by shortening the time of execution of works and reducing the consumption of construction materials.

Aerospace ◽  
2019 ◽  
Vol 6 (5) ◽  
pp. 61 ◽  
Jesus Gonzalez-Llorente ◽  
Aleksander A. Lidtke ◽  
Ken Hatanaka ◽  
Ryo Kawauchi ◽  
Kei-Ichi Okuyama

As small satellites are becoming more widespread for new businesses and applications, the development time, failure rate and cost of the spacecraft must be reduced. One of the systems with the highest cost and the most frequent failure in the satellite is the Electrical Power System (EPS). One approach to achieve rapid development times while reducing the cost and failure rate is using scalable modules. We propose a solar module integrated converter (SMIC) and its verification process as a key component for power generation in EPS. SMIC integrates the solar array, its regulators and the telemetry acquisition unit. This paper details the design and verification process of the SMIC and presents the in-orbit results of 12 SMICs used in Ten-Koh satellite, which was developed in less than 1.5 years. The in-orbit data received since the launch reveal that solar module withstands not only the launching environment of H-IIA rocket but also more than 1500 orbits in LEO. The modular approach allowed the design, implementation and qualification of only one module, followed by manufacturing and integration of 12 subsequent flight units. The approach with the solar module can be followed in other components of the EPS such as battery and power regulators.

Niels Hørbye Christiansen ◽  
Per Erlend Torbergsen Voie ◽  
Jan Høgsberg ◽  
Nils Sødahl

Dynamic analyses of slender marine structures are computationally expensive. Recently it has been shown how a hybrid method which combines FEM models and artificial neural networks (ANN) can be used to reduce the computation time spend on the time domain simulations associated with fatigue analysis of mooring lines by two orders of magnitude. The present study shows how an ANN trained to perform nonlinear dynamic response simulation can be optimized using a method known as optimal brain damage (OBD) and thereby be used to rank the importance of all analysis input. Both the training and the optimization of the ANN are based on one short time domain simulation sequence generated by a FEM model of the structure. This means that it is possible to evaluate the importance of input parameters based on this single simulation only. The method is tested on a numerical model of mooring lines on a floating off-shore installation. It is shown that it is possible to estimate the cost of ignoring one or more input variables in an analysis.


Signatures may be stylish or unconventional and have many personal characteristics that are challenging to reproduce by anyone other than the original author. For this reason, signatures are used and accepted as proof of authorship or consent on personal checks, credit purchases and legal documents. Currently signatures are verified only informally in many environments, but the rapid development of computer technology has stimulated great interest in research on automated signature verification and forgery detection. In this paper, we focus on forgery detection of offline signatures. Although a great deal of work has been done on offline signature verification over the past two decades, the field is not as mature as online verification. Temporal information used in online verification is not available offline and the subtle details necessary for offline verification are embedded at the stroke level and are hard to recover robustly. We approach the offline problem by establishing a local correspondence between a model and a questioned signature. The questioned signature is segmented into consecutive stroke segments that are matched to the stroke segments of the model. The cost of the match is determined by comparing a set of geometric properties of the corresponding substrokes and computing a weighted sum of the property value differences. The least invariant features of the least invariant substrokes are given the biggest weights, thus emphasizing features that are highly writer-dependent. Random forgeries are detected when a good correspondence cannot be found, i.e. the process of making the correspondence yields a high cost. Many simple forgeries can also be identified in this way. The threshold for making these decisions is determined by a Gaussian statistical model. Using the local correspondence between the model and a questioned signature, we perform skilled forgery detection by examining the writer-dependent information embedded at the substroke level and try to capture unballistic motion and tremor information in each stroke segment, rather than as global statistics. Experiments on random, simple and skilled forgery detection are presented.

2010 ◽  
Vol 40-41 ◽  
pp. 156-161 ◽  
Yang Li ◽  
Yan Qiang Li ◽  
Zhi Xue Wang

With the rapid development of automotive ECUs(Electronic Control Unit), the fault diagnosis becomes increasingly complicated. And the link between fault and symptom becomes less obvious. In order to improve the maintenance quality and efficiency, the paper proposes a fault diagnosis approach based on data mining technologies. By making full use of data stream, we firstly extract fault symptom vectors by processing data stream, and then establish a diagnosis decision tree through the ID3 decision tree algorithm, and finally store the link rules between faults and the related symptoms into historical fault database as a foundation for the fault diagnosis. The database provides the basis of trend judgments for a future fault. To verify this approach, an example of diagnosing faults of entertainment ECU is showed. The test result testifies the reliability and validity of this diagnostic method and reduces the cost of ECU diagnosis.

2003 ◽  
Vol 44 (Suppl 1) ◽  
pp. P55
Nils Toft ◽  
Anders R Kristensen ◽  
Erik Jørgensen

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