• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.995-1010
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• 2020

In this study, a multivariate analysis model of partial least square regression (PLSR) was developed to predict the moisture content of green peppers using hyperspectral imaging (HSI). In HSI, illumination is essential for high-quality image acquisition and directly affects the analytical performance of the visible near-infrared hyperspectral imaging (VIS/NIR-HSI) system. When green pepper images were acquired using a direct lighting system, the specular reflection from the surface of the objects and their intensities fluctuated with time. The images include artifacts on the surface of the materials, thereby increasing the variability of data and affecting the obtained accuracy by generating false-positive results. Therefore, images without glare on the surface of the green peppers were created using a polarization filter at the front of the camera lens and by exposing the polarizer sheet at the front of the lighting systems simultaneously. The results obtained from the PLSR analysis yielded a high determination coefficient of 0.89 value. The regression coefficients yielded by the best PLSR model were further developed for moisture content mapping in green peppers based on the selected wavelengths. Accordingly, the polarization filter helped achieve an uniform illumination and the removal of gloss and artifact glare from the green pepper images. These results demonstrate that the HSI technique with a polarized lighting system combined with chemometrics can be effectively used for high-throughput prediction of moisture content and image-based visualization.

• Journal of Korean Neurosurgical Society
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• v.64 no.1
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• pp.69-77
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• 2021

Objective : Classification systems for cervical ossification of the posterior longitudinal ligament (OPLL) have traditionally focused on the morphological characteristics of ossification. Although the classification describes many clinical features associated with the shape of the ossification, including the concept of spondylosis seems necessary because of the similarity in age distribution. Methods : Patients diagnosed with OPLL who presented with increase signal intensity (ISI) on magnetic resonance imaging were surgically treated in our department. The patients were divided into two groups (pure versus degenerative) according to the presence of disc degeneration. Results : Of 141 patients enrolled in this study, more than half (61%) were classified into the degenerative group. The pure group showed a profound male predominance, early presentation of myelopathy, and a different predilection for ISI compared to the degenerative group. The mean canal compromise ratio (CC) of the ISI was 47% in the degenerative group versus 61% in the pure group (p<0.0000). On the contrary, the global and segment motions were significantly larger in the degenerative group (p<0.0000 and p=0.003, respectively). The canal diameters and global angles did not differ between groups. Conclusion : Classifying cervical OPLL based on the presence of combined disc degeneration is beneficial for understanding the disorder's behavior. CC appears to be the main factor in the development of myelopathy in the pure group, whereas additional dynamic factors appear to affect its development in the degenerative group.

• Food Science and Industry
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• v.49 no.4
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• pp.64-69
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• 2016

The potentialities of 3D printing technology are discussed from technical and research-oriented perspectives for industrial manufacturing of a variety of food products. Currently, 3D printing technology has advanced to enable us to process or cook innovative foods. However, food-based materials for 3D printing are still limited in terms of eating qualities, nutritional values and functionality as well as industrial production. Therefore, this uprising issue on alternative food processing techniques especially focused on the exploration of new food materials combined with these 3D printing technologies needs to be re-spotlighted, and then solved to pave the way to this innovative and sensational area of investigation with more accessibility. In this review, previous research work and industrial applications conducted by frontier research groups in this field are covered, then to open discussion for future research on the 3D printing of food.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.3
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• pp.29-38
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• 2006

Recent advances in wireless communication technology promotes many researches related to sensor network and brings several proposals to fit into various types of sensor network communication. The research direction for sensor network is divided into the method to maximize an energy efficiency and security researches that has not been remarkable so far. To maximize an energy efficiency, the methods to support data aggregation and cluster-head selection algorithm are proposed. To strengthen the security, the methods to support encryption techniques and manage a secret key that is applicable to sensor network are proposed, In. However, the combined method to satisfy both energy efficiency and security is in the shell. This paper is devoted to design the protocol that combines an efficient clustering protocol with key management algorithm that is fit into various types of sensor network communication. This protocol may be applied to sensor network systems that deal with sensitive data.

• Maritime Security
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• v.1 no.1
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• pp.61-92
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• 2020

This paper attempts to examine the changes in China's naval strategy and to analyze the goal, range, and method of each strategy during the Xi Jinping's era. Since the founding of New China, the People's Liberation of Army Navy(PLAN) has made four changes in the naval strategy. Under Xi Jinping's administration, China's naval strategy is far seas operation combined with near seas active defense. Now, China's naval strateg y is shifting from a defensive to an aggressive one, increasing the proportion of offensive weapon systems and the number of state-of-the-art warships, and the scope of the naval strategy has been specified in the second island chain including the Indian Ocean. With the changes of naval strategy, the PLAN will set a new strategic goal to secure maritime dominance and implement an assertive strategy to actively respond to the intervention and intrusion of external forces. Moreover, the PLAN will also improve its sea-based deterrence force and the maneuver force to block other countries in the long-distance maritime conflict zones. The operation method of China's future naval strateg y will gradually shift from 'interdiction' to 'rapid-response.'

• Structural Engineering and Mechanics
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• v.77 no.1
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• pp.47-56
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• 2021

This paper deals with damage detection using a Gapped Smoothing Method (GSM) combined with deep learning. Convolutional Neural Network (CNN) is a model of deep learning. CNN has an input layer, an output layer, and a number of hidden layers that consist of convolutional layers. The input layer is a tensor with shape (number of images) × (image width) × (image height) × (image depth). An activation function is applied each time to this tensor passing through a hidden layer and the last layer is the fully connected layer. After the fully connected layer, the output layer, which is the final layer, is predicted by CNN. In this paper, a complete machine learning system is introduced. The training data was taken from a Finite Element (FE) model. The input images are the contour plots of curvature gapped smooth damage index. A free-free beam is used as a case study. In the first step, the FE model of the beam was used to generate data. The collected data were then divided into two parts, i.e. 70% for training and 30% for validation. In the second step, the proposed CNN was trained using training data and then validated using available data. Furthermore, a vibration experiment on steel damaged beam in free-free support condition was carried out in the laboratory to test the method. A total number of 15 accelerometers were set up to measure the mode shapes and calculate the curvature gapped smooth of the damaged beam. Two scenarios were introduced with different severities of the damage. The results showed that the trained CNN was successful in detecting the location as well as the severity of the damage in the experimental damaged beam.

• Imaging Science in Dentistry
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• v.51 no.2
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• pp.137-148
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• 2021

Purpose: This study aimed to assess the computer monitors used for analysis and interpretation of digital radiographs within the clinics of the Oral Health Centre of Western Australia. Materials and Methods: In total, 135 computer monitors(3 brands, 6 models) were assessed by analysing the same radiographic image of a combined 13-step aluminium step wedge and the Artinis CDDent 1.0^® (Artinis Medical Systems B.V.^®, Elst, the Netherlands) test object. The number of steps and cylindrical objects observed on each monitor was recorded along with the monitor's make, model, position relative to the researcher's eye level, and proximity to the nearest window. The number of window panels blocked by blinds, the outside weather conditions, and the number of ceiling lights over the surgical suite/cubicle were also recorded. MedCalc^® version 19.2.1 (MedCalc Software Ltd^®, Ostend, Belgium, https://www.medcalc.org; 2020) was used for statistical analyses(Kruskal-Wallis test and stepwise regression analysis). The level of significance was set at P<0.05. Results: Stepwise regression analysis showed that only the monitor brand and proximity of the monitor to a window had a significant impact on the monitor's performance (P<0.05). The Kruskal-Wallis test showed significant differences (P<0.05) in monitor performance for all variables investigated, except for the weather and the clinic in which the monitors were placed. Conclusion: The vast performance variation present between computer monitors implies the need for a review of monitor selection, calibration, and viewing conditions.

• Convergence Security Journal
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• v.20 no.5
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• pp.11-17
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• 2020

With the increase in cases of using Bluetooth devices used in the electric vehicle charging systems, security issues are also raised. Although various technical efforts have beed made to enhance security of bluetooth technology, various attack methods exist. In this paper, we propose an intelligent Bluetooth intrusion detection system based on a well-known machine learning method, Hidden Markov Model, for the purpose of detecting intelligently representative Bluetooth attack methods. The proposed approach combines packet types of H4, which is bluetooth transport layer protocol, and the transport directions of the packet firstly to represent the behavior of current traffic, and uses the temporal deployment of these combined types as the final input features for detecting attacks in real time as well as accurate detection. We construct the experimental environment for the data acquisition and analysis the performance of the proposed system against obtained data set.

• Advances in nano research
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• v.10 no.2
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• pp.151-163
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• 2021

The main target of this study is to investigate nonlinear transient responses of moving polymer nano-size plates fortified by means of Graphene Platelets (GPLs) and resting on a Winkler-Pasternak foundation under a transverse pressure force and a temperature variation. Two graphene spreading forms dispersed through the plate thickness are studied, and the Halpin-Tsai micro-mechanics model is used to obtain the effective Young's modulus. Furthermore, the rule of mixture is employed to calculate the effective mass density and Poisson's ratio. In accordance with the first order shear deformation and von Karman theory for nonlinear systems, the kinematic equations are derived, and then nonlocal strain gradient scheme is used to reflect the effects of nonlocal and strain gradient parameters on small-size objects. Afterwards, a combined approach, kinetic dynamic relaxation method accompanied by Newmark technique, is hired for solving the time-varying equation sets, and Fortran program is developed to generate the numerical results. The accuracy of the current model is verified by comparative studies with available results in the literature. Finally, a parametric study is carried out to explore the effects of GPL's weight fractions and dispersion patterns, edge conditions, softening and hardening factors, the temperature change, the velocity of moving nanoplate and elastic foundation stiffness on the dynamic response of the structure. The result illustrates that the effects of nonlocality and strain gradient parameters are more remarkable in the higher magnitudes of the nanoplate speed.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1424-1436
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• 2020

Although huge progress has been made in current image segmentation work, there are still no efficient segmentation strategies for tree image which is taken from natural environment and contains complex background. To improve those problems, we propose a method for tree image segmentation combining adaptive mean shifting with image abstraction. Our approach perform better than others because it focuses mainly on the background of image and characteristics of the tree itself. First, we abstract the original tree image using bilateral filtering and image pyramid from multiple perspectives, which can reduce the influence of the background and tree canopy gaps on clustering. Spatial location and gray scale features are obtained by step detection and the insertion rule method, respectively. Bandwidths calculated by spatial location and gray scale features are then used to determine the size of the Gaussian kernel function and in the mean shift clustering. Furthermore, the flood fill method is employed to fill the results of clustering and highlight the region of interest. To prove the effectiveness of tree image abstractions on image clustering, we compared different abstraction levels and achieved the optimal clustering results. For our algorithm, the average segmentation accuracy (SA), over-segmentation rate (OR), and under-segmentation rate (UR) of the crown are 91.21%, 3.54%, and 9.85%, respectively. The average values of the trunk are 92.78%, 8.16%, and 7.93%, respectively. Comparing the results of our method experimentally with other popular tree image segmentation methods, our segmentation method get rid of human interaction and shows higher SA. Meanwhile, this work shows a promising application prospect on visual reconstruction and factors measurement of tree.