• Smart Structures and Systems
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• v.31 no.5
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• pp.485-500
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• 2023

Machine learning-based structural health monitoring (ML-based SHM) methods are researched extensively in the recent decade due to the availability of advanced information and sensing technology. ML methods are well-known for their pattern recognition capability for complex problems. However, the main obstacle of ML-based SHM is that it often requires pre-collected historical data for model training. In most actual scenarios, damage presence can be detected using the unsupervised learning method through anomaly detection, but to further identify the damage types would require prior knowledge or historical events as references. This creates the cold-start problem, especially for new and unobserved structures. Modal-based methods identify damages based on the changes in the structural global properties but often require dense measurements for accurate results. Therefore, a two-stage hybrid modal-machine learning damage detection scheme is proposed. The first stage detects damage presence using Principal Component Analysis-Frequency Response Function (PCA-FRF) in an unsupervised manner, whereas the second stage further identifies the damage. To solve the cold-start problem, mode shape assessment using the first mode is initiated when no trained model is available yet in the second stage. The damage identified by the modal-based method would be stored for future training. This work highlights the performance of the scheme in alleviating the cold-start issue as it transitions through different phases, starting from zero damage sample available. Results showed that single and multiple damages can be identified at an acceptable accuracy level even when training samples are limited.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.3
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• pp.95-105
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• 2019

In recent years, image processing techniques for detecting road surface damaged spot have been actively researched. Especially, it is mainly used to acquire images through a smart phone or a black box that can be mounted in a vehicle and recognize the road surface damaged region in the image using several algorithms. In addition, in conjunction with the GPS module, the exact damaged location can be obtained. The most important technology is image processing algorithm. Recently, algorithms based on artificial intelligence have been attracting attention as research topics. In this paper, we will also discuss artificial intelligence image processing algorithms. Among them, an object detection method based on an region-based convolution neural networks method is used. To improve the recognition performance of road surface damage objects, 600 road surface damaged images and 1500 general road driving images are added to the learning database. Also, supervised learning using background object recognition method is performed to reduce false alarm and missing rate in road surface damage detection. As a result, we introduce a new method that improves the recognition performance of the algorithm to 8.66% based on average value of mAP through the same test database.

• Journal of Intelligence and Information Systems
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• v.10 no.1
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• pp.65-75
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• 2004

It is notorious that PIN(Personal Identification Number) is used widely for user verification and authentication in networked environment. But, when the user Identification and password are exposed by hacking, we can be damaged monetary damage as well as invasion of privacy. In this paper, we adopt face recognition-based authentication which have nothing to worry what the ID and password will be exposed. Also, we suggest the remote authentication and verification system by considering not only 2-Tier system but also 3-Tier system getting be distributed. In this research, we analyze the face feature data using the SVM(Support Vector Machine) and PCA(Principle Component Analysis), and implement artificial intelligence face recognition module in distributed environment which increase the authentication speed and heightens accuracy by utilizing artificial intelligence techniques.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11B
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• pp.1339-1345
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• 2011

Red tide is a natural phenomenon that change sea color by harmful algal blooms. There have been many studies on red tide due to increasing of red tide damage. However, to automatically classify the red tide algae is not enough. Recognition of red tide algae is difficult because they do not have matching center features for recognizing algae image object. Previously studies are used a few type of red tide algae for classification. In this paper, we proposed the red tide algae recognition method using PCA and roundness of image objects.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.23-29
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• 2011

There have been many studies on red tide due to increasing damage from red tide on fishing and aquaculture industry. However, internal study of automatic red tide image classification is not enough. Recognition of red tide algae is difficult because they do not have matching center features for recognizing algae image object. Previously studies used a few type of red tide algae for image classification. In this paper, we proposed the red tide image recognition method using semantic features of NMF and roundness of image objects.

• Journal of Trauma and Injury
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• v.21 no.1
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• pp.8-14
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• 2008

Iatrogenic ureteral injury is a complication that can occur during a variety of pelvic or abdominal surgeries. The most frequent causes are gynecological ones, followed by colon and vascular surgeries. Management of ureteric injury depends on the time of diagnosis and the severity of organ damage. Injuries diagnosed intraoperatively should be treated immediately. Occasionally, intraoperative ureteral injury is overlooked, and symptoms of the late diagnosis of ureteral injury are usually nonspecific; therefore, the diagnosis is delayed for days or weeks postoperatively. Management of injuries diagnosed postoperatively is more complex. There are differing opinions on whether an initial conservative or immediate operative intervention is the best line of action. Delayed repair is suggested on the grounds that it will reduce inflammation and tissue edema. However, many authors are in favor of early repair, perhaps because tissue planes are easier to find before fibrosis becomes too dense. Ureteral injuries occurring at the level of the pelvic brim should be best managed with an end-to-end anastomosis, preferably around a ureteric stent. More distal injuries also should be ideally managed with an end-to-end anastomosis, after excision of the crushed or compromised segments. However, if the remaining distal segment is short, ureteral reimplantation is the procedure of choice. The Boari flap technique for ureteral reimplantation is invaluable in cases with a short proximal segment. Delayed recognition of iatrogenic ureteral injury may be associated with serious complications, so prompt recognition of ureteral injuries is important. Recognition of the injury before closure is the key to easy, successful, and complications-free repair. Increased awareness of the risk for ureteral damage during certain operative maneuvers is vital to prevent injury, and to decrease the incidence of iatrogenic injury. A sound knowledge of abdominal and pelvic anatomy is the best prevention.

• Smart Structures and Systems
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• v.21 no.4
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• pp.421-433
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• 2018

Carbon fiber reinforced polymer (CFRP) cable has good mechanical properties and corrosion resistance. However, the anchorage of CFRP cable is a big issue due to the anisotropic property of CFRP material. In this article, a high-efficient bonding anchorage with novel configuration is developed for CFRP cables. The acoustic emission (AE) technique is employed to evaluate the performance of anchorage in the fatigue test and post-fatigue ultimate bearing capacity test. The obtained AE signals are analyzed by using a combination of unsupervised K-means clustering and supervised K-nearest neighbor classification (K-NN) for quantifying the performance of the anchorage and damage evolutions. An AE feature vector (including both frequency and energy characteristics of AE signal) for clustering analysis is proposed and the under-sampling approaches are employed to regress the influence of the imbalanced classes distribution in AE dataset for improving clustering quality. The results indicate that four classes exist in AE dataset, which correspond to the shear deformation of potting compound, matrix cracking, fiber-matrix debonding and fiber fracture in CFRP bars. The AE intensity released by the deformation of potting compound is very slight during the whole loading process and no obvious premature damage observed in CFRP bars aroused by anchorage effect at relative low stress level, indicating the anchorage configuration in this study is reliable.

• Structural Monitoring and Maintenance
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• v.1 no.1
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• pp.111-130
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• 2014

The increased use of carbon fiber reinforced polymer (CFRP) in retrofitting reinforced concrete (RC) members has led to the need to develop non-destructive techniques that can monitor and characterize the unique damage mechanisms exhibited by such structural systems. This paper presented the damage characterization results of six CFRP retrofitted RC beam specimens tested in the laboratory and monitored using acoustic emission (AE). The focus of this study was to continuously monitor the change in AE parameters and analyze them both qualitatively and quantitatively, when brittle failure modes such as debonding occur in these beams. Although deterioration of structural integrity was traceable and can be quantified by monitoring the AE data, individual failure mode characteristics could not be identified due to the complexity of the system failure modes. In all, AE was an effective non-destructive monitoring tool that can trace the failure progression in RC beams retrofitted with CFRP. It would be advantageous to isolate signals originating from the CFRP and concrete, leading to a more clear understanding of the progression of the brittle damage mechanism involved in such a structural system. For practical applications, future studies should focus on spectral analysis of AE data from broadband sensors and automated pattern recognition tools to classify and better correlate AE parameters to failure modes observed.

• Smart Structures and Systems
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• v.17 no.2
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• pp.167-194
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• 2016

This paper investigates the Synergetics based Damage Detection Method (SDDM) for frame structures by using surface-bonded PZT (Lead Zirconate Titanate) patches. After analyzing the mechanism of pattern recognition from Synergetics, the operating framework with cooperation-competition-update process of SDDM was proposed. First, the dynamic identification equation of structural conditions was established and the adjoint vector (AV) set of original vector (OV) set was obtained by Generalized Inverse Matrix (GIM).Then, the order parameter equation and its evolution process were deduced through the strict mathematics ratiocination. Moreover, in order to complete online structural condition update feature, the iterative update algorithm was presented. Subsequently, the pathway in which SDDM was realized through the modified Synergetic Neural Network (SNN) was introduced and its assessment indices were confirmed. Finally, the experimental platform with a two-story frame structure was set up. The performances of the proposed methodology were tested for damage identifications by loosening various screw nuts group scenarios. The experiments were conducted in different damage degrees, the disturbance environment and the noisy environment, respectively. The results show the feasibility of SDDM using piezoceramic sensors and actuators, and demonstrate a strong ability of anti-disturbance and anti-noise in frame structure applications. This proposed approach can be extended to the similar structures for damage identification.

• Culinary science and hospitality research
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• v.6 no.2
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• pp.315-330
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• 2000

The development of foodservice franchise is inevitable in the developmental process of domestic foodservice industry and it has been led by some big enterprises and foreign brands, but foodservice franchise of a new and differential form will be rapidly developed. The success of franchise can be resulted under the recognition that franchiser and franchise are in the common fate as the partner. Franchisee must make its best efforts to enhance the unity and value of brand jointly with franchiser. Therefore. franchisee has to make efforts to maintain the quality of commodity and service, not to damage the value of title and follow the guidance and effort of franchiser it chose. Franchiser must have the recognition that the success of franchisee is the key of that of franchiser and give franchisee a reliability in order that it follows the order of franchiser. It must have the consciousness that it can achieve the success through the increase of sales by franchisee and support franchisee with trust not to have the easygoing way of thinking to derive its income of commission from increasing the number of franchisees.