• Journal of Biosystems Engineering
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• v.37 no.3
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• pp.177-183
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• 2012

Purpose: In near infrared spectroscopy, interactance configuration of a light source and a spectrometer probe can provide more information regarding fruit internal attributes, compared to reflectance and transmittance configuration. However, there is no through study on the parameters of interactance measurement setup. The objective of this study was to investigate the effect of the parameters on the estimation of soluble solids content (SSC) and firmness of muskmelons. Methods: Melon samples were taken from greenhouses at three different harvesting seasons. The prediction models were developed at three distances of 2, 5, and 8 cm between the light source and the spectrometer probe, three measurement points of 2, 3, and 6 evenly distributed on each sample, and different number of fruit samples for calibration models. The performance of the models was compared. Results: In the test at the three distances, the best results were found at a 5 cm distance. The coefficient of determination ($R_{cv}{^2}$) values of the cross-validation were 0.717 (standard error of prediction, SEP=$1.16^{\circ}Brix$) and 0.504 (SEP=4.31 N) for the estimation of SSC and firmness, respectively. The minimum measurement point required to fully represent the spectral characteristics of each fruit sample was 3. The highest $R_{cv}{^2}$ values were 0.736 (SEP=$0.87^{\circ}Brix$) and 0.644 (SEP=4.16 N) for the estimation of SSC and firmness, respectively. The performance of the models began to be saturated when 60 fruit samples were used for developing calibration models. The highest $R_{cv}{^2}$ of 0.713 (SEP=$0.88^{\circ}Brix$) and 0.750 (SEP=3.30 N) for the estimation of SSC and firmness, respectively, were achieved. Conclusions: The performance of the prediction models was quite different according to the condition of interactance measurement setup. In designing a fruit grading machine with interactance configuration, the parameters for interactance measurement setup should be chosen carefully.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.89-99
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• 2020

In this study, we tried to produce moving-image works through sentiment analysis of music. First, Google natural language API was used for the sentiment analysis of lyrics, then the result was applied to the image visualization rules. In prior engineering researches, text-based sentiment analysis has been conducted to understand users' emotions and attitudes by analyzing users' comments and reviews in social media. In this study, the data was used as a material for the creation of artworks so that it could be used for aesthetic expressions. From the machine's point of view, emotions are substituted with numbers, so there is a limit to normalization and standardization. Therefore, we tried to overcome these limitations by linking the results of sentiment analysis of lyrics data with the rules of formative elements in visual arts. This study aims to transform existing traditional art works such as literature, music, painting, and dance to a new form of arts based on the viewpoint of the machine, while reflecting the current era in which artificial intelligence even attempts to create artworks that are advanced mental products of human beings. In addition, it is expected that it will be expanded to an educational platform that facilitates creative activities, psychological analysis, and communication for people with developmental disabilities who have difficulty expressing emotions.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.237-246
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• 2020

this paper, a data modeling method based on decision-making conditions is proposed for making combat and battlefield management systems to be intelligent, which are also a decision-making support system. A picture of a robot seeing and perceiving like humans and arriving a point it wanted can be understood and be felt in body. However, we can't find an example of implementing a decision-making which is the most important element in human cognitive action. Although the agent arrives at a designated office instead of human, it doesn't support a decision of whether raising the market price is appropriate or doing a counter-attack is smart. After we reviewed a current situation and problem in control & command of military, in order to collect a big data for making a machine staff's advice to be possible, we propose a data modeling prototype based on decision-making conditions as a method to change a current control & command system. In addition, a decision-making tree method is applied as an example of the decision making that the reformed control & command system equipped with the proposed data modeling will do. This paper can contribute in giving us an insight of how a future AI decision-making staff approaches to us.

• Archives of Reconstructive Microsurgery
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• v.19 no.1
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• pp.12-20
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• 2010

Purpose: Industrial punch accidents involving fingers cause segmental injuries to tendons and neurovascular bundles. Although multiple-level segmental amputations are not replanted to regain function, most patients with an amputated finger want to undergo replantation for cosmetic as much as functional reason. The authors describe four cases of digital amputation by an industrial punch that involved the reinstatement of the amputated finger involving a joint and neurovascular bundle. Amputated segments were replanted to restore amputated surfaces and distal segments. Methods: A single institution retrospective review was performed. Inclusion criteria of punch injuries requiring replantation were applied to patients of all demographic background. Injury extent (size, tissue involvement), operative intervention, pre- and postoperative hand function were recorded. Result: Four cases of amputations were treated at our institute from 2004 to 2008 from industrial punch machine injury. Average patient age was 32.5 years (25~39 years) and there were three males and one female. Sizes of amputated segments ranged from $1.0{\times}1.0{\times}1.2\;cm^3$ to $3{\times}1.5{\times}1.6\;cm^3$. Tenorrhaphy was conducted after fixing fractured bone of the amputated segments with K-wire. Proximal and distal arteries and veins were repaired using the through & through method. The average follow-up period was thirteen months (2~26 months), and all replanted cases survived. Osteomyelitis occurred in one case, skin grafting after debridement was performed in two cases. Because joints were damaged in all four cases, active ranges of motion were much limited. However, a secondary tendon graft enhanced digit function in two cases. The two-point discrimination test showed normal values for both static and dynamic tests for three cases and 9 mm and 15 mm by dynamic and static testing, respectively, in one case. Conclusion: Though amputations from industrial punch machines are technically challenging to replant, our experience has shown it to be a valid therapy. In cases involving punch machine injury, if an amputated segment is available, the authors recommend that replantation be considered for preservation of finger length, joint mobility, and overall functional recovery of the hand.

• Tunnel and Underground Space
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• v.21 no.3
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• pp.151-163
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• 2011

The LCM test is one of the most powerful and reliable methods for designing the disc cutter and for predicting the TBM (Tunnel Boring Machine) performance. It has an advantage to predict the actual load on disc cutter from the laboratory test on the real-size large rock samples, however, it also has a disadvantage to transport and/or prepare the large rock samples and to need an extra cost for experiment. Moreover it is not easy to execute the test for jointed rock mass, and sometimes the design model estimated from the test can not be applied to the real design of disc cutter. In order to break this critical point, lots of numerical studies have been performed. PFC2D can simulate crack propagation and rock fragmentation effectively, because it is useful in particle flow analysis. Consequently, in this study, the PFC2D has been adopted for numerical analysis on cutting power of disc cutter according to the different angle of joint, the different direction of joint, and the different space of joint with jointed rock mass models. From the numerical analyses, it was concluded that the bigger cutting power of disc cutter was needed for reverse cutting direction to joint rather than for forward direction, and the cutting power of disc cutter was increased with decreasing the dip angle of joint and decreasing the space of joints in reverse cutting direction. The more precise numerical model for disc cutter can be developed from comparison between the numerical results and LCM test results, and the resonable guideline is expected for prediction of TBM performance and disc cutter.

• Journal of Dental Rehabilitation and Applied Science
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• v.30 no.2
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• pp.112-120
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• 2014

Purpose: This study compared the shear bond strength of heat pressed and feldspathic porcelain to metal. Through thermocycling, the clinical aspect of heat pressed porcelain fused metal was estimated. Materials and Methods: 90 non-precious metal specimens were made ($4{\times}4{\times}8 mm$) and divided to three groups. All spicimens were treated and built-up with the porcelain ($4{\times}4{\times}3 mm$) by 2 different methods according to group: Group I: $Inspiration^{(R)}$, Group II: Ivoclar, IPS $Inline^{(R)}PoM$, Group III: GC Initial IQ-One $Body^{(R)}PoM$. The half of each group's specimens were thermocycled. All specimens' shear bond strength were measured by Instron universal testing machine. Exact measuring point was far 1 mm from porcelain/metal interface to the porcelain side. For the statistical analysis, 2-way ANOVA was used. Results: In no-thermocycling specimens, the shear bond strength showed no statistical significance between each group (P > 0.05). In comparison between nothermocycling and thermocycling specimens in each group, the shear bond strength was decreased according to thermocycling, but there was no statistical significance (P > 0.05). In thermocycling specimens, there was no statistical significance between each group (P > 0.05). Conclusion: In feldspathic porcelain and other two types heat pressed porcelain, there was no statistical difference in the shear bond strength of porcelain to metal. The heat pressed porcelain seems to be clinically useful for the aspect of the shear bond strength.

• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.97-107
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• 2013

The latest programming paradigm has been mostly geared toward object-oriented programming and visual programming based on the object-oriented programming. However, object-oriented programming has a more difficult and complicated concept compared with that of existing structural programming technique; thus it has been very difficult to educate students in the IT-related department. This study designed and implemented a Java robot training kit in which the Java virtual machine is built so that it may enhance the desire and motivation of students for learning the object-oriented programming using the training kit which is possible to attach various input and output devices and to control a robot. The developed Java robot training kit is able to communicate with a computer through the USB interface, and it also enables learners to manufacture a robot for education and to practice applied programming because there is a general purpose input and output port inside the kit, through which diverse input and output devices, DC motor, and servo motor can be operated. Accordingly, facing the IT fusion era, the wall between the academic circles and the major becomes lower and the need for introducing education about creative engineering object-oriented programming language is emerging. At this point, the Java robot training kit developed in this study is expected to make a great commitment in this regard.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.527-534
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• 2016

The emergent information society requires the talent for creative thinking based on problem-solving skills and comprehensive thinking rather than simple memorization. Therefore, the Korean curriculum has also changed into the direction of the creative thinking through increasing short-answer questions that can determine the overall thinking of the students. However, their scoring results are a little bit inconsistency because scoring short-answer questions depends on the subjective scoring of human raters. In order to alleviate this point, an automated scoring system using a machine learning has been used as a scoring tool in overseas. Linguistically, Korean and English is totally different in the structure of the sentences. Thus, the automated scoring system used in English cannot be applied to Korean. In this paper, we introduce an automated scoring system for Korean short-answer questions using predictability and unanimity. We also verify the practicality of the automatic scoring system through the correlation coefficient between the results of the automated scoring system and those of human raters. In the experiment of this paper, the proposed system is evaluated for constructed-response items of Korean language, social studies, and science in the National Assessment of Educational Achievement. The analysis was used Pearson correlation coefficients and Kappa coefficient. Results of the experiment had showed a strong positive correlation with all the correlation coefficients at 0.7 or higher. Thus, the scoring results of the proposed scoring system are similar to those of human raters. Therefore, the automated scoring system should be found to be useful as a scoring tool.

• Journal of Digital Convergence
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• v.17 no.8
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• pp.249-255
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• 2019

Type 2 diabetes mellitus(T2DM) is included in metabolic disorders characterized by hyperglycemia, which causes many complications, and requires long-term treatment resulting in massive medical expenses each year. There have been many studies to solve this problem, but the existing studies have not been accurate by learning and predicting the data at specific time point. Thus, this study proposed a model using RNN to increase the accuracy of prediction of T2DM. This work propose a T2DM prediction model based on Korean Genome and Epidemiology study(Ansan, Anseong Korea). We trained all of the data over time to create prediction model of diabetes. To verify the results of the prediction model, we compared the accuracy with the existing machine learning methods, LR, k-NN, and SVM. Proposed prediction model accuracy was 0.92 and the AUC was 0.92, which were higher than the other. Therefore predicting the onset of T2DM by using the proposed diabetes prediction model in this study, it could lead to healthier lifestyle and hyperglycemic control resulting in lower risk of diabetes by alerted diabetes occurrence.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.7
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• pp.1015-1026
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• 2019

Objective: The objective of this study was to evaluate three different degrees of white striping (WS) addressing their automatic assessment and customer acceptance. The WS classification was performed based on a computer vision system (CVS), exploring different machine learning (ML) algorithms and the most important image features. Moreover, it was verified by consumer acceptance and purchase intent. Methods: The samples for image analysis were classified by trained specialists, according to severity degrees regarding visual and firmness aspects. Samples were obtained with a digital camera, and 25 features were extracted from these images. ML algorithms were applied aiming to induce a model capable of classifying the samples into three severity degrees. In addition, two sensory analyses were performed: 75 samples properly grilled were used for the first sensory test, and 9 photos for the second. All tests were performed using a 10-cm hybrid hedonic scale (acceptance test) and a 5-point scale (purchase intention). Results: The information gain metric ranked 13 attributes. However, just one type of image feature was not enough to describe the phenomenon. The classification models support vector machine, fuzzy-W, and random forest showed the best results with similar general accuracy (86.4%). The worst performance was obtained by multilayer perceptron (70.9%) with the high error rate in normal (NORM) sample predictions. The sensory analysis of acceptance verified that WS myopathy negatively affects the texture of the broiler breast fillets when grilled and the appearance attribute of the raw samples, which influenced the purchase intention scores of raw samples. Conclusion: The proposed system has proved to be adequate (fast and accurate) for the classification of WS samples. The sensory analysis of acceptance showed that WS myopathy negatively affects the tenderness of the broiler breast fillets when grilled, while the appearance attribute of the raw samples eventually influenced purchase intentions.