• Journal of Biosystems Engineering
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• v.31 no.5 s.118
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• pp.389-394
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• 2006

The characteristic of moisture absorption of granular fertilizer was measured at several different opening sizes on the top cover of a hopper in a humid weather. The size of the opening was to represent the degree of looseness of sealing of the top cover of the hopper. The application distribution was characterized by the scattering distance of granular fertilizer with different degree of moisture absorption in a pneumatic granular fertilizer applicator. The moisture absorption rates were 12.92 and 12.26 mg of moisture an hour for one gram of each granular fertilizers of NPK 22-12-12 and 21-17-17, respectively. The moisture absorption increased linearly as the opening size increased. The median value of the scattering distance distribution decreased with time of absorption, however, it decreased very slowly after three hours of absorption.

• Journal of Oriental Neuropsychiatry
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• v.15 no.1
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• pp.9-25
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• 2004

Behavioral characteristics of Attention Deficit Hyperactivity Disorder(ADHD) is one of the most common mental disorders among children.child psyachiatry. Inattention, Hyperactivity that is done by hyperkinesis or minimal brain dysfunction is major sypmton in ADHD, But etiology and pathological facor of ADHD is very much or unkown.. We brought to about a Study on the Oriental - medical pathologic Understanding about Inattention, Hyperactivity symptom in ADHD within Don yui bo gam Book are as follows. 1. Oriental medical pathologic concepts about Inattention, Hyperactivity are continuous with process of Yang Qi(陽氣), an unbalance of qi(氣) and shen ming(神明), excess of seven emotions(七情), pathology of Huo(火). 2. Immanent factors in inattention, Hyperactivity are improper diet, overtiredness and seven emotions, are continuous with pathological process of the heart, liver, gall bladder, spleen, stomach, kidneys. 3. In oriental medicine, considered as a child's qi of shao yang, dynamic physiological feature, excess and want of yin and yang, organs and bowels, immanently imbalance in growth rather than a child's mental disorder 4. Inattention, looseness in ADHD-PI type are continuous with forgetfulness, improper overtiredness, shortage of qi, the interior heat syndrome due to yin deficiency within Don yui bo gam Book 5. Hyperactivity, impulsive actions in ADHD-C type are continuous with sudden palpitation, severe palpitation, delirium, fidgeting due to deficiency, fidgetiness, hyperactivity of huo due to yin deficiency, fever, febrile disease with accumulation of blood.

• Fashion & Textile Research Journal
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• v.10 no.3
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• pp.329-334
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• 2008

The purpose of this research is to develop the design, pattern and size system of brief as a measurement garment in order to obtain more precise silhouettes and sizes of the body in 3D measurements. The results of this research are as follows: First, nylon/lycra materials which elasticity is equivalent to 18%(wale) and 27%(course), were selected as a material for briefs to minimize possible error in measurement and deformation of body shape caused by looseness or tightness in its measured parts. And T-back style design was selected, of which briefs neither deform human body nor cause overlapping or excessive tightness when was put on the measurement garment over it. Second, different darts for men and women were adopted into the pattern in consideration for the shape of hip. Third, the waist band of briefs was located between the waistline and abdominal girth line so that it didn't interfere with measurement, and using a wide band of 40mm minimized the tightness of the human body. In addition, the stitch lines and sewing procedure were simplified to minimize the deformation of body shape resulting from inseams and stitch lines. Finally, for the size of briefs, 6 cm intervals were set on the basis of the waist girth and 8 kinds for men and 6 kinds for women were selected in descending order of appearance rate by the interval sections. English T meaning T-back design and numbers representing the waist girth were marked in parallel for the name of size.

• Tunnel and Underground Space
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• v.20 no.5
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• pp.360-368
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• 2010

The paper presents a case study from a surface mine where the controlled augmentation of throw and drop of the blasted muck piles was warranted to spread the muck piles on the lower berm of the bench. While the augmentation of throw increased the lateral spread and the looseness of the broken muck, the augmentation of drop significantly lowered the muck pile height for easy excavation by the excavators. In this light, the present paper highlights and discusses some pertinent changes in the blast design parameters for such specialized application of cast blasting in a surface mine, where a sandstone bench, with average height of 22-24 m was to be made amenable for excavation by 10 m3 rope shovels, which possessed maximum digging capability of up to 14 m. The results of tailoring the blast design parameters for augmentation of throw and drop are compared with the baseline blasts which were earlier practiced on the same bench by dividing the full height of the bench in 2-slices; upper slice (10-14 m high) and lower slice (12-15 m high). Results of fragment size, its distribution and total cycle time of excavator (shovel) are presented, and discussed.

• Smart Structures and Systems
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• v.29 no.6
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• pp.757-766
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• 2022

To train deep learning algorithms, a sufficient number of data are required. However, in most engineering systems, the acquisition of fault data is difficult or sometimes not feasible, while normal data are secured. The dearth of data is one of the major challenges to developing deep learning models, and fault diagnosis in particular cannot be made in the absence of fault data. With this context, this paper proposes an anomaly detection methodology for rotating machines using only normal data with self-labeling. Since only normal data are used for anomaly detection, a self-labeling method is used to generate a new labeled dataset. The overall procedure includes the following three steps: (1) transformation of normal data to self-labeled data based on a pretext task, (2) training the convolutional neural networks (CNN), and (3) anomaly detection using defined anomaly score based on the softmax output of the trained CNN. The softmax value of the abnormal sample shows different behavior from the normal softmax values. To verify the proposed method, four case studies were conducted, on the Case Western Reserve University (CWRU) bearing dataset, IEEE PHM 2012 data challenge dataset, PHMAP 2021 data challenge dataset, and laboratory bearing testbed; and the results were compared to those of existing machine learning and deep learning methods. The results showed that the proposed algorithm could detect faults in the bearing testbed and compressor with over 99.7% accuracy. In particular, it was possible to detect not only bearing faults but also structural faults such as unbalance and belt looseness with very high accuracy. Compared with the existing GAN, the autoencoder-based anomaly detection algorithm, the proposed method showed high anomaly detection performance.

• Korean Journal of Culture and Social Issue
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• v.22 no.4
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• pp.643-674
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• 2016

The purpose of present study is to discover the meaning of the Eogul(억울) which is known as a emotion from perceived unfairness. Even though Eogul has been mentioned as a cause of the Hwabyung in Korean culture there were few studies about it. Researchers designed two studies to provide clear understanding for this concept. In study 1, researchers conducted an open-ended questionnaire for 44 participants to deduce the cultural contexts and the whole experience on Eogul. Data were analyzed with grounded theory, the results were cross-checked by different evaluators. According to the analysis, Eogul is not only the negative feelings from the perceived unfairness, but also the motivations and behaviors to resolve the feelings. Especially, what makes Eogul culture-bounded could be related display rules on expressing emotions. We conducted study 2 to clarify the cultural attributes of Eogul in Korean culture. Variables that explain cultural differences were chosen and 123 participants were surveyed with them including the items developed for measuring Eogul. Cultural meanings and implications of Eogul were discussed with the results.

• Smart Structures and Systems
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• v.32 no.1
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• pp.23-35
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• 2023

Steel bolted joint is an important part of steel structure, and its damage directly affects the bearing capacity and durability of steel structure. Currently, the existing research mainly focuses on the identification of corroded bolts and corroded bolts respectively, and there are few studies on multiple states. A detection framework of corroded and loosened bolts is proposed in this study, and the innovations can be summarized as follows: (i) Vision Transformer (ViT) is introduced to replace the third and fourth C3 module of you-only-look-once version 5s (YOLOv5s) algorithm, which increases the attention weights of feature channels and the feature extraction capability. (ii) Three states of the steel bolts are considered, including corroded bolt, bolt missing and clean bolt. (iii) Line segment detector (LSD) is introduced for bolt rotation angle calculation, which realizes bolt looseness detection. The improved YOLOv5s model was validated on the dataset, and the mean average precision (mAP) was increased from 0.902 to 0.952. In terms of a lab-scale joint, the performance of the LSD algorithm and the Hough transform was compared from different perspective angles. The error value of bolt loosening angle of the LSD algorithm is controlled within 1.09%, less than 8.91% of the Hough transform. Furthermore, the proposed framework was applied to fullscale joints of a steel bridge in China. Synthetic images of loosened bolts were successfully identified and the multiple states were well detected. Therefore, the proposed framework can be alternative of monitoring steel bolted joints for management department.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.130-139
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• 2024

Artificial intelligence models are being used to detect facility anomalies using physics data such as vibration, current, and temperature for predictive maintenance in the manufacturing industry. Since the types of facility anomalies, such as facility defects and failures, anomaly detection methods using autoencoder-based unsupervised learning models have been mainly applied. Normal or abnormal facility conditions can be effectively classified using the reconstruction error of the autoencoder, but there is a limit to identifying facility anomalies specifically. When facility anomalies such as unbalance, misalignment, and looseness occur, the facility vibration frequency shows a pattern different from the normal state in a specific frequency range. This paper presents an N-segmentation anomaly detection method that performs anomaly detection by dividing the entire vibration frequency range into N regions. Experiments on nine kinds of anomaly data with different frequencies and amplitudes using vibration data from a compressor showed better performance when N-segmentation was applied. The proposed method helps materialize them after detecting facility anomalies.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.57-76
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• 2017

Recently, consumer needs are diversifying as information technologies are evolving rapidly. A lot of IT devices such as smart phones and tablet PCs are launching following the trend of information technology. While IT devices focused on the technical advance and improvement a few years ago, the situation is changed now. There is no difference in functional aspects, so companies are trying to differentiate IT devices in terms of appearance design. Consumers also consider design as being a more important factor in the decision-making of smart phones. Smart phones have become a fashion items, revealing consumers' own characteristics and personality. As the design and appearance of the smartphone become important things, it is necessary to examine consumer values from the design and appearance of IT devices. Furthermore, it is crucial to clarify the mechanisms of consumers' design evaluation and develop the design evaluation model based on the mechanism. Since the influence of design gets continuously strong, various and many studies related to design were carried out. These studies can classify three main streams. The first stream focuses on the role of design from the perspective of marketing and communication. The second one is the studies to find out an effective and appealing design from the perspective of industrial design. The last one is to examine the consumer values created by a product design, which means consumers' perception or feeling when they look and feel it. These numerous studies somewhat have dealt with consumer values, but they do not include product attributes, or do not cover the whole process and mechanism from product attributes to consumer values. In this study, we try to develop the holistic design evaluation model based on consumer values based on three-step approach from product attributes, perceived attributes, to consumer values. Product attributes means the real and physical characteristics each smart phone has. They consist of bezel, length, width, thickness, weight and curvature. Perceived attributes are derived from consumers' perception on product attributes. We consider perceived size of device, perceived size of display, perceived thickness, perceived weight, perceived bezel (top - bottom / left - right side), perceived curvature of edge, perceived curvature of back side, gap of each part, perceived gloss and perceived screen ratio. They are factorized into six clusters named as 'Size,' 'Slimness,' 'No-Frame,' 'Roundness,' 'Screen Ratio,' and 'Looseness.' We conducted qualitative research to find out consumer values, which are categorized into two: look and feel values. We identified the values named as 'Silhouette,' 'Neatness,' 'Attractiveness,' 'Polishing,' 'Innovativeness,' 'Professionalism,' 'Intellectualness,' 'Individuality,' and 'Distinctiveness' in terms of look values. Also, we identifies 'Stability,' 'Comfortableness,' 'Grip,' 'Solidity,' 'Non-fragility,' and 'Smoothness' in terms of feel values. They are factorized into five key values: 'Sleek Value,' 'Professional Value,' 'Unique Value,' 'Comfortable Value,' and 'Solid Value.' Finally, we developed the holistic design evaluation model by analyzing each relationship from product attributes, perceived attributes, to consumer values. This study has several theoretical and practical contributions. First, we found consumer values in terms of design evaluation and implicit chain relationship from the objective and physical characteristics to the subjective and mental evaluation. That is, the model explains the mechanism of design evaluation in consumer minds. Second, we suggest a general design evaluation process from product attributes, perceived attributes to consumer values. It is an adaptable methodology not only smart phone but also other IT products. Practically, this model can support the decision-making when companies initiative new product development. It can help product designers focus on their capacities with limited resources. Moreover, if its model combined with machine learning collecting consumers' purchasing data, most preferred values, sales data, etc., it will be able to evolve intelligent design decision support system.