• Clinics in Shoulder and Elbow
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• v.25 no.1
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• pp.68-72
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• 2022

Proximal humerus fractures are the third most common fractures, totaling 4% to 5% of all fractures. Here, we present the case of a 39-year-old man with a dislocated four-part fracture of the proximal humerus with a huge bony Bankart lesion. Preoperatively, the bony Bankart lesion of the glenoid was not visualized on computed tomography scans or magnetic resonance imaging because the fracture of the proximal humerus was comminuted, displaced, and complex. It was planned for only the humerus fracture to be treated by open reduction and internal fixation using a locking plate. However, a fractured fragment remained under the scapula after reduction of the dislocated humeral head. This was mistaken for a dislocated bone fragment of the greater tuberosity and repositioning was attempted. After failure, visual confirmation showed that the bone fragment was a piece of the glenoid. After reduction and fixation of this glenoid part with suture anchors, we acquired a well-reduced fluoroscopic image. Given this case of complex proximal humerus fracture, a glenoid fracture such as a bony Bankart lesion should be considered preoperatively and intraoperatively in such cases.

• Progress in Medical Physics
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• v.15 no.2
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• pp.112-119
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• 2004

We tried to build human models based on medical images of live Korean, instead of using standard data of human body structures. Characteristics of mechanical structures of human bodies were obtained from medical images such as CT and MR images. For each constitutional part of mechanical structures CT images were analyzed in terms of gray levels and MR images were analyzed in terms of pulse sequence. Characteristic features of various mechanical structures were extracted from the analyses. Based on the characteristics of each structuring element we peformed image segmentation on CT and MR images. We delineated bones, muscles, ligaments and tendons from CT and MR images using image segmentation or manual drawing. For the image segmentation we compared the edge detection method, region growing method and intensity threshold method and applied an optimal compound of these methods for the best segmentation results. Segmented mechanical structures of the head/neck part were three dimensionally reconstructed.

• Smart Structures and Systems
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• v.16 no.3
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• pp.415-433
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• 2015

Tendon failures in bonded post-tensioned bridges over the last two decades have motivated ongoing investigations on various aspects of unbonded tendons and their monitoring methods. Recent research shows that change of strain distribution in anchor heads can be useful in detecting wire breakage in unbonded construction. Based on this strain variation, this paper develops a damage detection model that enables an automated tendon monitoring system to identify and locate wire breaks. The first part of this paper presents an experimental program conducted to study the strain variation in anchor heads by generating wire breaks using a mechanical device. The program comprised three sets of tests with fully populated 19-strand anchor head and evaluated the levels of strain variation with number of wire breaks in different strands. The sensitivity of strain variation with wire breaks in circumferential and radial directions of anchor head in addition to the axial direction (parallel to the strand) were investigated and the measured axial strains were found to be the most sensitive. The second part of the paper focuses on formulating the wire breakage detection framework. A finite element model of the anchorage assembly was created to demonstrate the algorithm as well as to investigate the asymmetric strain distribution observed in experimental results. In addition, as almost inevitably encountered during tendon stressing, the effects of differential wedge seating on the proposed model have been analyzed. A sensitivity analysis has been performed at the end to assess the robustness of the model with random measurement errors.

• Korean Journal of Applied Biomechanics
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• v.13 no.1
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• pp.155-171
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• 2003

The purpose of this study was to analyze the kinematic variables of over head kick(OHK) in soccer with three dimensional analysis technique and show the kinematic characteristics of it. The 7 subjects were university football player who have been playing football more than 7 years. The OHK was filmed on 16mm video camera(30frame/sec.) kinematic variables were temporal, postures, and COG(center of gravity). The mean values and the standard deviation for each variables were obtained and used as basic factors for examining characteristics of OHK. The results of this analysis were as follows : Temporal variables : The total time elapsed(TE) of OHK was $0.95{\sim}1.14sec$, the 1st phase was 0.35sec., 2nd phase was 0.46sec., and 3rd phase was 0.22sec.. Posture variables : When subjects performed OHK at the impact event, the ankle and knee angle of kicking foot were more extend than supporting foot. but the hip angle of supporting foot were more extend than kirking foot. Moving distance of the center of mass of the both foot. When subject performed OHK at the impact event, the range of distance on mediolateral direction aspect into right left shoulder line, anteroposterior direction aspect was $20.9{\pm}10.5cm$, vertical direction aspect was $92.3{\pm}19.9cm$. Angular velocity : the faster angular velocity of knee ankle on the kicking foot pew form jump position to landing position, the faster velocity of ball became. C. O. G. variables. When subject performed OHK at the impact event, upper part of the body was getting lower, lower part of the body was getting higher.

• Journal of the Korean Wood Science and Technology
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• v.25 no.3
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• pp.50-57
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• 1997

The presence of slime in paper mills is practically universal. Many researches have been performed for many years to resolve the problem caused by the slime in pulp and paper mill. Many papers have been published to show the bacteria is a major cause of paper mill slime. Now that the recycling of the water has been increased and the regulations of a toxic chemical dosage have become more strengthen, the importance of the control of slime in pulp and paper mill recently has been more recognized. Therefore, to produce quality products at the lowest economic and environmental costs, a through study of the microbial ecology and the indentification of troublesome slime-forming bacteria is a quite necessary. The purpose of this paper is to indentify slime~forming bacteria isolated from the papermaking process. The samples were taken from four parts of making fine paper : machine chest, head box, wire part, white water tank. Machine chest showed the most numbers of bacteria, numbering $2.55{\times}10^7$. The different colony types were taken from the 105 dilution plate. Nine bacteria were identified u sing the Biolog system and the vitek system: 6 gram-negative bacteria, 3 gram-positive bacteria. They are Pseudomonas paucimobilis B., Staphylococcus sp., Acinetobacter calcoaceticus., Pseudomonas cepacia, Actinobaci1lus capsulatus, Acidovorax sp., Flavobacterium sp., and Staphylococcus auricularis in addition to one unidentified sp., Among them. Pseudomonas paucimobillis was found in all places where the samples were taken. And, each parts had the different predominant bacteria in it : Pseudomonas paucimobilis B. in machine chest, Acinetobactor calcoaceticus. in Wire Part and Staphylococcus sp. in head box.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.402-409
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• 2019

Patients with dementia or elderly patients who can not move at all by themselves are at a high risk of falls and bedsore due to lack of caregivers. In this paper, to solve this problem, we propose an algorithm to determine the patient's lying postures by discriminating the main body parts such as head, shoulders, and hips based on the pressure intensity sensed at regular intervals. A smart mat with a lattice structure in which a pressure sensor is arranged so that the body part can be discriminated irrespective of the physical characteristics has been implemented. It consists of two modules of $7{\times}7$ array size. Each module consists of 49 FSR-406 sensors and independently senses pressure. For each module, the body part corresponding to the upper body or the lower body is sequentially discriminated by using a pressure distribution such as a cumulative pressure sum using a filter. The proposed algorithm can identify five lying positions by examining the inclusion relationship between body parts belonging to layer-1 such as head, shoulder, and hip area.

• Parasites, Hosts and Diseases
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• v.34 no.3
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• pp.161-168
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• 1996

We observed the morphological characteristics and identified the species of gnathostome larvae obtained from the imported Chinese loaches. The early third-stage larvae ($EL_3$) were collected from viscera of the loaches and a part of them were infected to mice. The advanced third-stage larvae ($AdL_3$) were recovered from the mice at 4 weeks post-infection. both larval worms were fixed loth 10% formalin, cleared in alcohol-glycerin solution, mounted with glycerin-jelly, and observed. A total of 369 $EL_3$ were collected from viscera of 9,493 Chinese loaches. The whole body of $EL_3$ was covered with about 190 transverse rows of minute cuticular spines and $0.624{\;}{\times}{\;}0.101{\;}mm$ in average size. A pair of lips were protruded at the anterior end, and the muscular esophagus and brownish intestine were followed. The characteristic head bulb was provided with 4 rows of hooklets. The average number of hooklets in the respective row was 36.7, 39.5, 41.6 and 44.3 posteriorly $AdL_3$ was $2.660{\;}{\times}{\;}0.346{\;}mm$ in average size, and retained the esophagus (about 0.755 mm length) and cervical sac (about 0.355 mm length). The average number of hooklets in the respective row on the head bulb was 39.0, 41.9, 43.9 and 45.6, posteriorly. On the basis of the morphological characteristics, they were identified as the third-stage larvae of Gnathostomc hispinun.

• The KIPS Transactions:PartC
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• v.14C no.3 s.113
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• pp.277-284
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• 2007

The routing algorithm many used in the wireless sensor network features the clustering method to reduce the amount of data transmission from the energy efficiency perspective. However, the clustering method results in high energy consumption at the cluster head node. Dynamic clustering is a method used to resolve such a problem by distributing energy consumption through the re-selection of the cluster head node. Still, dynamic clustering modifies the cluster structure every time the cluster head node is re-selected, which causes energy consumption. In other words, the dynamic clustering approaches examined in previous studies involve the repetitive processes of cluster head node selection. This consumes a high amount of energy during the set-up process of cluster generation. In order to resolve the energy consumption problem associated with the repetitive set-up, this paper proposes the Round-Robin Cluster Header (RRCH) method that fixes the cluster and selects the head node in a round-robin method The RRCH approach is an energy-efficient method that realizes consistent and balanced energy consumption in each node of a generated cluster to prevent repetitious set-up processes as in the LEACH method. The propriety of the proposed method is substantiated with a simulation experiment.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.23 no.2
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• pp.8-8
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• 1987

This paper describes on the distribution of the vibration and the noise produced on a skipjack pole and line training ship M/S Pusan 403 (243GT, 1,000ps) under the cruising or drifting condition. The vibration and the noise level were measured by use of protable vibration analyzer (B and K 3513) and sound level meter (B and K 2205), and so the vibration level was converted into dB unit. The check points were set through every decks and around important places of the ship. The results obtained can be summarized as follows: 1. The vibration and the noise level 1) On the main deck, both the vibration and the noise level were highest at the vertically above the main engine, whereas the vibration level was the lowest in the bow store and the noise level beneath the bridge. 2) Under cruising condition, the vibration level around the cylinder head of main engine, port side of the engine room, on the shaft tunnel was 80, 67, 65 dB and the noise level 104, 87, 86 dB, respectively. 3) The vibration level on the vertical line passing through the bridge was the highest at the orlop deck with 60 dB and the lowest on the bridge deck with 55 dB, whereas the noise level the highest at the compass deck with 75 dB and the lowest at the orlop deck with 53 dB. 4) The vibration and the noise level on the open decks were the highest with 65 dB and 84 dB on the boat deck, whereas the vibration level was the lowest at the lecture room with 51 dB and the noise level the lowest at the fore castle deck with 57 dB. 5) On the orlop decks, both the vibration and the noise level were the highest at the engine room with 65 dB and 85 dB, and the lowest at bow store with 54 dB and 52 dB, respectively. Comparing with the vibration level and the noise level, the vibration level was higher than the noise level in the bow part and it was contrary in the stern part of the ship. 2. Vibration analysis 1) The vibration displacement and the vibration velocity were the greatest at the cylinder head of main engine with 100μm and 11mm/sec, and were the smallest at the compass deck with 3μm and 0.07mm/sec. They were also attenuated rapidly around the frequency of 100Hz and over. 2) The vibration acceleration was the greatest at the cylinder head with the main frequency of 1KHz and the acceleration of 1.1mm/sec super(2), and the smallest at the compass deck with 30KHz and 0.05mm/sec super(2).

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.23 no.2
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• pp.54-60
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• 1987

This paper describes on the distribution of the vibration and the noise produced on a skipjack pole and line training ship M/S Pusan 403 (243GT, 1,000ps) under the cruising or drifting condition. The vibration and the noise level were measured by use of protable vibration analyzer (B and K 3513) and sound level meter (B and K 2205), and so the vibration level was converted into dB unit. The check points were set through every decks and around important places of the ship. The results obtained can be summarized as follows: 1. The vibration and the noise level 1) On the main deck, both the vibration and the noise level were highest at the vertically above the main engine, whereas the vibration level was the lowest in the bow store and the noise level beneath the bridge. 2) Under cruising condition, the vibration level around the cylinder head of main engine, port side of the engine room, on the shaft tunnel was 80, 67, 65 dB and the noise level 104, 87, 86 dB, respectively. 3) The vibration level on the vertical line passing through the bridge was the highest at the orlop deck with 60 dB and the lowest on the bridge deck with 55 dB, whereas the noise level the highest at the compass deck with 75 dB and the lowest at the orlop deck with 53 dB. 4) The vibration and the noise level on the open decks were the highest with 65 dB and 84 dB on the boat deck, whereas the vibration level was the lowest at the lecture room with 51 dB and the noise level the lowest at the fore castle deck with 57 dB. 5) On the orlop decks, both the vibration and the noise level were the highest at the engine room with 65 dB and 85 dB, and the lowest at bow store with 54 dB and 52 dB, respectively. Comparing with the vibration level and the noise level, the vibration level was higher than the noise level in the bow part and it was contrary in the stern part of the ship. 2. Vibration analysis 1) The vibration displacement and the vibration velocity were the greatest at the cylinder head of main engine with 100$\mu$m and 11mm/sec, and were the smallest at the compass deck with 3$\mu$m and 0.07mm/sec. They were also attenuated rapidly around the frequency of 100Hz and over. 2) The vibration acceleration was the greatest at the cylinder head with the main frequency of 1KHz and the acceleration of 1.1mm/sec super(2), and the smallest at the compass deck with 30KHz and 0.05mm/sec super(2).