• Smart Structures and Systems
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• v.31 no.3
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• pp.247-257
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• 2023

In structural health monitoring of large-scale structures, optimal sensor placement plays an important role because of the high cost of sensors and their supporting instruments, as well as the burden of data transmission and storage. In this study, a vibration sensor placement algorithm based on deep reinforcement learning (DRL) is proposed, which can effectively solve non-convex, high-dimensional, and discrete combinatorial sensor placement optimization problems. An objective function is constructed to estimate the quality of a specific vibration sensor placement scheme according to the modal assurance criterion (MAC). Using this objective function, a DRL-based algorithm is presented to determine the optimal vibration sensor placement scheme. Subsequently, we transform the sensor optimal placement process into a Markov decision process and employ a DRL-based optimization algorithm to maximize the objective function for optimal sensor placement. To illustrate the applicability of the proposed method, two examples are presented: a 10-story braced frame and a sea-crossing bridge model. A comparison study is also performed with a genetic algorithm and particle swarm algorithm. The proposed DRL-based algorithm can effectively solve the discrete combinatorial optimization problem for vibration sensor placements and can produce superior performance compared with the other two existing methods.

• Journal of the Health Care and Life Science
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• v.9 no.2
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• pp.297-302
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• 2021

As the price of LiDAR developed for autonomous driving has dropped dramatically, LiDAR has begun to be applied in various fields. Typical examples are vacuum cleaner robots, autonomous delivery robots, and autonomous obstacle avoidance drones. LiDAR is becoming the only means of figuring out the location of an object in real time while compensating for the weakness that 2D or 3D cameras are vulnerable to lighting. In this paper, we propose a method to monitor the movement of a patient by installing a 2D lidar in a hospital room. When a patient who needs intensive monitoring due to psychologically unstable, suicidal intention, or psychotic findings is alone in the ward, 2D LiDAR monitors the patient's movement and sends an appropriate alarm to the management room to effectively monitor the patient. devised a way to do it.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.123-131
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• 2016

Process mining in big data environment utilize a number of data were generated from the business process. It generates lots of knowledge and insights regarding implementation and improvement of the process through the event log of the company's enterprise resource planning (ERP) system. In recent years, various research activities engaged with the audit work of company organizations are trying actively by using the maximum strength of the mining process. However, domestic studies on applicable sales auditing system for the process mining are insufficient under big data environment. Therefore, we propose process-mining methods that can be optimally applied to online and traditional auditing system. In advance, we propose continuous monitoring information system that can early detect and prevent the risk under the big data environment by monitoring risk factors in the organizations of enterprise. The scope of the research of this paper is to design a pre-verification system for risk factor via practical examples in sales auditing. Furthermore, realizations of preventive audit, continuous monitoring for high risk, reduction of fraud, and timely action for violation of rules are enhanced by proposed sales auditing system. According to the simulation results, avoidance of financial risks, reduction of audit period, and improvement of audit quality are represented.

• Journal of Korean Society for Quality Management
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• v.32 no.2
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• pp.201-211
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• 2004

Process adjustment is a complimentary tool to process monitoring in process control. Process adjustment directs on maintaining a process output close to a target value by manipulating another controllable variable, by which significant process improvement can be achieved. Therefore, this approach can be applied to the 'Improve' stage of Six Sigma strategy. Though the optimal control rule minimizes process variability in general, it may not properly function when special causes occur in underlying process, resulting in off-target bias and increased variability in the adjusted output process, possibly for long periods. In this paper, we consider a responsive feedback control system and the minimum mean square error control rule. The bias in the adjusted output process is investigated in a general framework, especially focussing on stationary underlying process and the special cause of level shift type. Illustrative examples are employed to illustrate the issues discussed.

• Journal of the Society of Disaster Information
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• v.12 no.1
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• pp.40-46
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• 2016

Nowdays, adjacent loading bringing enormous harm to the existing bridge in engineering construction. In this paper, the influencing mechanism of adjacent loading to pier and Law of displacement of pier is researched through living examples, and the safe influence area has been defined. Research shows that: the main damages to piers is caused by the side loading; lateral displacement index of pier top surface is more conservative than the pier additional stress index; it is secure when the distance of adjacent load is 0.5 times of the height of accumulation or 6m, otherwise it would be very scary, and the monitoring measure is necessary.

• Journal of Korean Society for Quality Management
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• v.28 no.1
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• pp.1-12
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• 2000

Since Black Monday there has been a rash of systems developments which aimed at automating and upgrading the surveillance mechanism of monitoring the many facets of security trading. A more sophisticated mathematical model for detecting abnormal trading activities was created by Davis and Ord of Penn State along with Nobel prize laureates Solow and Modigliani of MIT. They used CAPM(Capital Asset Pricing Model) to explain the movements of stock price and applied an idea of residuals to detect unusual movements. In this paper, their idea is discussed and a new method is proposed, which involves a confidence interval of future observation in linear regression. One of the examples of the stock watch system adopting this statistical method is also presented.

• Structural Monitoring and Maintenance
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• v.5 no.2
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• pp.261-272
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• 2018

The commonly used TMD design method in the project assumes the TMD has pure linearity. However, in real engineering TMD will exhibit nonlinear behaviors. Without considering the nonlinearity of TMD, the control effect of the TMD that is designed by the linear design method, may be worse and even enlarge the structural response. In this paper, based on the previous study results of nonlinear TMD, the improved design method for engineering application is proposed. The linear design method and the improved design method are compared. Taking the best parameter obtained by the improved design method is less than or equal to 90% of that obtained by the original design method as the dividing line. The critical nonlinear coefficient, reaching which value the improved design method needs to be used, is given. Finally, numerical simulations on two engineering examples are conducted to proof the results.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.117-120
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• 1995

The electronencephalogram (EEG) is a complex electrical signal which reflects generalized brain activity. The EEG is utilized in the clinical assesment of many neurological and psychiatric disorders and offers promise for monitoring of patients undergoing operation. This paper describes a technique for quantitative analysis of EEG signals which is based on an eigenspace. Examples of the application approach to simulated and clinical EEG data illustrate the capabilities.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.497-499
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• 2006

There are several types of communication method which is used for the supply of electric power stably. But the communication methods used in KEPCO have weak points in the viewpoint of economy, technology and management. The Satellite communication systems have competitive power in price and technology for national wide utility owing to its wide area coverage and stability. This paper presents various adapted examples of the Power industry using he satellite communication systems.

• Geophysics and Geophysical Exploration
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• v.16 no.4
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• pp.268-274
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• 2013

Continuous seismic observation of volcanic earthquakes related to migration of magma or gas, is one of the most important methods used to monitor active volcanoes. In this review paper, we introduce the characteristics of volcanic earthquakes and their classification based on locations of foci, waveforms, frequencies, lithology, and source mechanisms. We also present some examples of successful warnings of volcanic eruptions and the present status of some observations of volcanic earthquakes in Japan, the United States, Italy, and New Zealand.