• Journal of Korean Physical Therapy Science
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• v.1 no.1
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• pp.135-144
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• 1994

The authors studied therapeutic effects and related clinical data retrospectively on a series of 48 consecutive patients with head injury who were referred to physical therapy and occupational therapy, Kosin University Medical Center during 1 year, from March, 1993. through March, 1994. The conclusions were as follows : 1. Average age of the subject patients was 50.6 years, their age remped from 14 to 72 years, and the incidence between male and femele was 1:1.1. 2. In respect to the educational level high school graduates showed the highest incidence 18 (39.1 %) of 46 cases, and in respect to economy level, middle class revealed the highest incidence, 31(64.6 %) in 48 cases. 3. The HBP was the most common cause of spontaneity injury, disclosing 19 cases in 35 patients(54.3%), whereas the main cause of traumatic injury was a traffic accident, 7 cases ( 53.8 %) in 13 patients. 4. As for the region of injury in the cases of spontaneity ICH was 14 persons (40%). In the cases of trauma, hematoma was seen in 6 cases(42.2 %) in 48 total cases ICH was seen in 17 cases (35.4 %) to be the most common region. 5. Among 35 persons, spontaneity CBR was the highest region of injury, 13 cases(37.1 %) ; the side of paralysis in extremities the right side showed higher incidence, 18 cas (1.4 %) as compared to the left, 16 cases(45.7%). In the case of traumatic injury, CBR was the highest region of injury, 4(30.8% )in 13 cases and as for the paralysis side, right side showed higher incidence 7 cases(53.8%) as compared to the left side 5 cases(38.5%). 6. In respect to recurrence, HBP was seen in 5 cases to be the most common cause, and as for the region of injury, CBR was the highest. 7. A period of rehabilitation therapy in the cases of physical therapy the highest term was 1-2 month, 14 persons(29.2%). As for occupational therapy within 2 week-term was the highest, 24 persons(50%). 8. Physical strenth grade M.T in the cases of the upper extrimities before therapy, the low mark(grade 0) was 30 cases(62.5%), compared to the high mark(above grade 3)seen in 1 case(2.1%), And after therapy, the lowest mark(grade 0)was seen in 5 cases(10.4%) where as the high mark(above grade 3)was seen in 29 cases(60.4%). In the case of the lower extremities before therapy, the mark(below grade 1)was 37 cases(77.1 %), while the high mark(above grade 3)was seen n 4 cases(8.4%). And after therapy the low mark(below grade 1)was seen in 5 cases (10.4 %) and the high mark (above grade 3)was seen in 29 cases(60.4 %). 9. Before therapy conigtive function-level evaluation utilized R.L.A.L, the low mark(below level 3)was seen in 9 cases(18.8%), while the high mark(above level 7)was seen in 18 cases(37.5%). And after therapy the low mark (below level 3)was 4 cases(8.3%) and high mark(above level 7)was seen in 38 cases(79%). 10. After rehabilitation therapy, patients who were able to walk independently were 29 persons(60.4%), among which 16 cases(55.2%) depended on cane. The ratio between the cases who were able to walk and unable to walk was 1.5:1.

• Korean Journal of Animal Reproduction
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• v.24 no.4
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• pp.357-364
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• 2000

Members of the glycoprotein family, which includes CG, LH, FSH and TSH, comprise two noncovalently linked $\alpha$- and $\beta$-subunits. Equine chorionic gonadotropin (eCG), known as PMSG, has a number of interesting and unique characteristics since it appears to be a single molecule that possesses both LH- and FSH-like activities in other species than the horse. This dual activity of eCG in heterologous species is of fundamental interest to the study of the structure-function relationships of gonadotropins and their receptors. CG and LH $\beta$ genes are different in primates. In horse, however, a single gene encodes both eCG and eLH $\beta$ -subunits. The subunit mRNA levels seem to be independently regulated and their imbalance may account for differences in the quantities of $\alpha$ - and $\beta$-subunits in the placenta and pituitary. The dual activities of eCG could be separated by removal of the N-linked oligosaccharide on the $\alpha$-subunit Asn 56 or CTP-associated O-linked oligosaccharides. The tethered-eCG was efficiently secreted and showed similar LH-like activity to the dimeric eCG. Interestingly, the FSH-like activity of the tethered-eCG was increased markedly in comparison with the native and wild type eCG. These results also suggest that this molecular can implay particular models of FSH-like activity not LH-like activity in the eCG/indicate that the constructs of tethered molecule will be useful in the study of mutants that affect subunit association and/or secretion. A single-chain analog can also be constructed to include additional hormone-specific bioactive generating potentially efficacious compounds that have only FSH-like activity. The LH/CG receptor (LH/CGR), a membrane glycoprotein that is present on testicular Leydig cells and ovarian theca, granulosa, luteal, and interstitial cells, plays a pivotal role in the regulation of gonadal development and function in males as well as in nonpregnant and pregnant females. The LH/CGR is a member of the family of G protein-coupled receptors and its structure is predicted to of a large extracellular domain connected to a bundle of seven membrane-spanning a-helices. The LH/CGR phosphorylation can be induced with a phorbol ester, but not with a calcium ionophore. The truncated form of LHR also was down-regulated normally in response to hCG stimulation. In contrast, the cell lines expressing LHR-t631 or LHR-628, the two phosphorylation-negative receptor mutant, showed a delay in the early phase of hCG-induced desensitization, a complete loss of PMA-induced desensitization, and an increase in the rate of hCG-induced receptor down-regulation. These results clearly show that residues 632~653 in the C-terminal tail of the LHR are involved in PMA-induced desensitization, hCG-induced desensitization, and hCG-induced down-regulation. Recently, constitutively activating mutations of the receptor have been identified that are associated with familial male-precocious puberty. Cells expressing LHR-D556Y bind hCG with normal affinity, exhibit a 25-fold increase in basal cAMP and respond to hCG with a normal increase in cAMP accumulation. This mutation enhances the internalization of the free and agoinst-occupied receptors ~2- and ~17- fold, respectively. We conclude that the state of activation of the LHR can modulate its basal and/or agonist-stimulated internalization. Since the internalization of hCG is involved in the termination of hCG actions, we suggest that the lack of responsiveness detected in cells expressing LHR-L435R is due to the fast rate of internalization of the bound hCG. This statement is supported by the finding that hCG responsiveness is restored when the cells are lysed and signal transduction is measured in a subcellular fraction (membranes) that cannot internalize the bound hormone.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.12 no.2
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• pp.207-214
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• 2009

Purpose: Childhood obesity can be complicated by hypertension, hyperlipidemia, non-alcoholic fatty liver disease, and diabetes mellitus. The aim of this study was to evaluate the prevalence of obesity and metabolic complications of children and adolescents based on the degree of obesity. Methods: We analyzed the records of 8,880 students who received student health examinations between May 2006 and October 2008 at the Eulji General Hospital. The prevalence of obesity was evaluated by the body mass index and obesity index. A total of 1,076 obese students had blood tests. We analyzed aspartate aminotransferase (AST), alanine aminotransferase (ALT), fasting glucose, total cholesterol, and blood pressure according to the degree of obesity. Results: According to the body mass index, the overall prevalence of obesity was 7.2% (7.8% of male and 6.5% of female students). Based on the obesity index, 12.3% of students (mild: 6.3%, moderate: 5.0%, and severe: 1.0%) were obese. The prevalence of hypercholesterolemia, ALT elevation, and hypertension were increased as a function of the degree of obesity (p<0.05), but hyperglycemia showed no significant differences (p=0.298). The overall prevalence of ALT elevation was 17.7% (mild obese group, 10.4%; moderate obese group, 20.5%; and severe obese group, 46.8%). The prevalence of hypercholesterolemia, hypertension, and hyperglycemia were significantly higher in the elevated ALT group (24.7%, 42.6%, and 5.2%, respectively) compared to the normal ALT group (11.1%, 29.8%, and 2.0%, respectively; p<0.05). Conclusion: Hypercholesterolemia, liver function test abnormalities, and hypertension were associated with the degree of obesity. We should focus our attention on managing obese children and adolescents to prevent metabolic complications.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.33 no.3
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• pp.159-165
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• 1997

This paper presents the optimum dimension of 89 ton class stow-net vessel with stern-fishing. The model of basic design is developed by using the optimization techniques referring to objective function and numerous constraints as follows; speed, fishing quantity, fishing days, catch per unit effort(CPUE), and weight/ratio of main dimensions, etc. Thus, the basic design of stow-net fishing vessel is built up by using the optimization of the design variables called the economic optimization criteria, and the objective function represents the criterion which is cost benefit ratio(CBR). The main conclusions are as follows. 1. S/W for decision of optimum hull size is developed in 89 ton class stow-net fishing vessel which is constructed with optimization of the design variables called the economic optimization criteria. 2. For optimum ship dimensions in 89 ton class stow-net fishing vessel, the hull dimensions can be obtained in the range of L= 27.3m, B = 6.6m, D = 2.80m, Cb = 0.695, T/D = 0.80, $\Delta$(displacement)=281.7ton with 10 knots.

• The Journal of the Petrological Society of Korea
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• v.24 no.3
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• pp.165-180
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• 2015

Jurassic granite from Geochang was analysed with respect to the characteristics of the rock cleavage. The phases of distribution of microcracks were well evidenced from the enlarged photomicrographs(${\times}6.7$) of the thin section. In this study, the length - cumulative frequency diagrams were used for expressing the distribution characteristics of microcrack. The diagrams for the six directions were arranged in the magnitude of density(${\rho}$). These diagrams show an order of H2 < H1 < G2 < G1 < R2 < R1 from the related chart. Among six diagrams, the diagram for hardway 2(H2) occupies the lowermost region on the left. On the contrary, the diagram for rift 1(R1) occupies the uppermost region on the right. Curve patterns of the two diagrams change from uniform to exponential distribution type in accordance with the increased density. The overall distribution characteristics of the diagrams were well evidenced from the magnitude of the exponent(${\lambda}$) and length of line oa related to the exponential straight line. The magnitude of exponent governing the values of slope(${\theta}$) is inversely proportional to the values of microcrack parameters such as number(N), length(L) and density. On the contrary, length of line oa is directly proportional to the values of the above three parameters. Above microcrack parameters related to the order of arrangement of diagrams show an order of hardway(H1 + H2) < grain(G1 + G2) < rift(R1 + R2). The distribution characteristics of progressive variation are found among the six diagrams. The order of arrangement of the diagrams indicates a relative magnitude of the rock cleavage. Meanwhile, the parameters such as slope, exponent, density and length of line oa were arranged in an order of H2 < H1 < G2 < G1 < R2 < R1. The variation curves of a smooth quadratic function are shown from the related chart. From the correlation chart between density and the above parameters, a common regularity following power-law correlation function was derived. Finally, the analysis for the rock cleavage was conducted through the combination between the diagram and microcrack parameter. This type of combination contribute to the progressivity in evaluation for the rock cleavage.

• Korean Journal of Digital Imaging in Medicine
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• v.5 no.1
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• pp.64-77
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• 2002

DR has had an important fact not only in the department of radiology but also in productivity or work efficiency of a whole hospital. The environment of DR has more various parameter than CR, so it is able to supply high quality of medical services. The current environment of radiology department in each hospital has been changed from Film-Screen system to DR through Full-PACS. This hospital which uses Full-PACS became to study the proper condition of CR and DDR and how the image quality of them is expressed among general photographing systems in the DR environment. From this experiment, the image quality of DDR is better than CR under the same exposure condition. And in the DDR system, the score of image which uses AEC is a little higher than the score which doesn't use it. Especially it can be known that the function of AEC of DDR is useful to improve the image quality in the part of skull and chest. (The function of AEC : It is the tool that detects the ionized current of x-ray which goes through objects with using the ion chamber which is in the detector. Also it controls the examination of X-ray when the proper density is reached.) Because the proper degree of density can be represented by this system, the photographing can be taken much easily without consideration of the exposure condition with the thickness of various objects. From the result of this experiment, it can be known that the selection of proper exposure condition plays an important rule to gain good Image Quality. More researches will be necessary about DDR system which has potential ability in the future.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.53-65
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• 2019

Object tracking is one of important steps to achieve video-based surveillance systems. Object tracking is considered as an essential task similar to object detection and recognition. In order to perform object tracking, various machine learning methods (e.g., least-squares, perceptron and support vector machine) can be applied for different designs of tracking systems. In general, generative methods (e.g., principal component analysis) were utilized due to its simplicity and effectiveness. However, the generative methods were only focused on modeling the target object. Due to this limitation, discriminative methods (e.g., binary classification) were adopted to distinguish the target object and the background. Among the machine learning methods for binary classification, total error rate minimization can be used as one of successful machine learning methods for binary classification. The total error rate minimization can achieve a global minimum due to a quadratic approximation to a step function while other methods (e.g., support vector machine) seek local minima using nonlinear functions (e.g., hinge loss function). Due to this quadratic approximation, the total error rate minimization could obtain appropriate properties in solving optimization problems for binary classification. However, this total error rate minimization was based on a batch mode setting. The batch mode setting can be limited to several applications under offline learning. Due to limited computing resources, offline learning could not handle large scale data sets. Compared to offline learning, online learning can update its solution without storing all training samples in learning process. Due to increment of large scale data sets, online learning becomes one of essential properties for various applications. Since object tracking needs to handle data samples in real time, online learning based total error rate minimization methods are necessary to efficiently address object tracking problems. Due to the need of the online learning, an online learning based total error rate minimization method was developed. However, an approximately reweighted technique was developed. Although the approximation technique is utilized, this online version of the total error rate minimization could achieve good performances in biometric applications. However, this method is assumed that the total error rate minimization can be asymptotically achieved when only the number of training samples is infinite. Although there is the assumption to achieve the total error rate minimization, the approximation issue can continuously accumulate learning errors according to increment of training samples. Due to this reason, the approximated online learning solution can then lead a wrong solution. The wrong solution can make significant errors when it is applied to surveillance systems. In this paper, we propose an exactly reweighted technique to recursively update the solution of the total error rate minimization in online learning manner. Compared to the approximately reweighted online total error rate minimization, an exactly reweighted online total error rate minimization is achieved. The proposed exact online learning method based on the total error rate minimization is then applied to object tracking problems. In our object tracking system, particle filtering is adopted. In particle filtering, our observation model is consisted of both generative and discriminative methods to leverage the advantages between generative and discriminative properties. In our experiments, our proposed object tracking system achieves promising performances on 8 public video sequences over competing object tracking systems. The paired t-test is also reported to evaluate its quality of the results. Our proposed online learning method can be extended under the deep learning architecture which can cover the shallow and deep networks. Moreover, online learning methods, that need the exact reweighting process, can use our proposed reweighting technique. In addition to object tracking, the proposed online learning method can be easily applied to object detection and recognition. Therefore, our proposed methods can contribute to online learning community and object tracking, detection and recognition communities.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.127-142
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• 2016

Deep learning model is a kind of neural networks that allows multiple hidden layers. There are various deep learning architectures such as convolutional neural networks, deep belief networks and recurrent neural networks. Those have been applied to fields like computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics where they have been shown to produce state-of-the-art results on various tasks. Among those architectures, convolutional neural networks and recurrent neural networks are classified as the supervised learning model. And in recent years, those supervised learning models have gained more popularity than unsupervised learning models such as deep belief networks, because supervised learning models have shown fashionable applications in such fields mentioned above. Deep learning models can be trained with backpropagation algorithm. Backpropagation is an abbreviation for "backward propagation of errors" and a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent. The method calculates the gradient of an error function with respect to all the weights in the network. The gradient is fed to the optimization method which in turn uses it to update the weights, in an attempt to minimize the error function. Convolutional neural networks use a special architecture which is particularly well-adapted to classify images. Using this architecture makes convolutional networks fast to train. This, in turn, helps us train deep, muti-layer networks, which are very good at classifying images. These days, deep convolutional networks are used in most neural networks for image recognition. Convolutional neural networks use three basic ideas: local receptive fields, shared weights, and pooling. By local receptive fields, we mean that each neuron in the first(or any) hidden layer will be connected to a small region of the input(or previous layer's) neurons. Shared weights mean that we're going to use the same weights and bias for each of the local receptive field. This means that all the neurons in the hidden layer detect exactly the same feature, just at different locations in the input image. In addition to the convolutional layers just described, convolutional neural networks also contain pooling layers. Pooling layers are usually used immediately after convolutional layers. What the pooling layers do is to simplify the information in the output from the convolutional layer. Recent convolutional network architectures have 10 to 20 hidden layers and billions of connections between units. Training deep learning networks has taken weeks several years ago, but thanks to progress in GPU and algorithm enhancement, training time has reduced to several hours. Neural networks with time-varying behavior are known as recurrent neural networks or RNNs. A recurrent neural network is a class of artificial neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. Early RNN models turned out to be very difficult to train, harder even than deep feedforward networks. The reason is the unstable gradient problem such as vanishing gradient and exploding gradient. The gradient can get smaller and smaller as it is propagated back through layers. This makes learning in early layers extremely slow. The problem actually gets worse in RNNs, since gradients aren't just propagated backward through layers, they're propagated backward through time. If the network runs for a long time, that can make the gradient extremely unstable and hard to learn from. It has been possible to incorporate an idea known as long short-term memory units (LSTMs) into RNNs. LSTMs make it much easier to get good results when training RNNs, and many recent papers make use of LSTMs or related ideas.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.161-173
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• 2021

The shipping industry plummeted and was depressed due to the global economic crisis caused by the bankruptcy of Lehman Brothers in the US in 2008. In 2020, the shipping market also suffered from a collapse in the unstable global economic situation due to the COVID-19 pandemic, but unexpectedly, it changed to an upward trend from the end of 2020, and in 2021, it exceeded the market of the boom period of 2008. According to the Clarksons report published in May 2021, the decrease in cargo volume due to the COVID-19 pandemic in 2020 has returned to the pre-corona level by the end of 2020, and the tramper bulk carrier capacity of 103~104% of the Panamax has been in the ports due to congestion. Earnings across the bulker segments have risen to ten-year highs in recent months. In this study, as factors affecting BDI, the capacity and congestion ratio of Cape and Panamax ships on the supply side, iron ore and coal seaborne tonnge on the demand side and Granger causality test, IRF(Impulse Response Function) and FEVD(Forecast Error Variance Decomposition) were performed using VAR model to analyze the impact on BDI by congestion caused by strengthen quarantine at the port due to the COVID-19 pandemic and the loading and discharging operation delay due to the infection of the stevedore, etc and to predict the shipping market after the pandemic. As a result of the Granger causality test of variables and BDI using time series data from January 2016 to July 2021, causality was found in the Fleet and Congestion variables, and as a result of the Impulse Response Function, Congestion variable was found to have significant at both upper and lower limit of the confidence interval. As a result of the Forecast Error Variance Decomposition, Congestion variable showed an explanatory power upto 25% for the change in BDI. If the congestion in ports decreases after With Corona, it is expected that there is down-risk in the shipping market. The COVID-19 pandemic occurred not from economic factors but from an ecological factor by the pandemic is different from the past economic crisis. It is necessary to analyze from a different point of view than the past economic crisis. This study has meaningful to analyze the causality and explanatory power of Congestion factor by pandemic.

• Journal of Yeungnam Medical Science
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• v.22 no.1
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• pp.96-103
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• 2005

The motor recovery mechanism of a 21-year-old male monoparetic patient with cerebral palsy, who had complained of a mild weakness on his right hand since infancy, was examined using functional Magnetic Resonance Imaging (fMRI) and Transcranial Magnetic Stimulation (TMS). The patient showed mild motor impairment on the right hand. MRI located the main lesion on the left precentral knob of the brain. fMRI was performed on this patient as well as 8 control subjects using the Blood Oxygen Level Dependent technique at 1.5 T with a standard head coil. The motor activation task consisted of finger flexionextension exercises at 1 Hz cycles. TMS was carried out using a round coil. The anterior portion of the coil was applied tangentially to the scalp at a 1.0 cm separation. Magnetic stimulation was carried out with the maximal output. The Motor Evoked Potentials (MEPs) from both Abductor Pollicis Brevis muscles (APB) were obtained simultaneously. fMRI revealed that the unaffected (right) primary sensori-motor cortex (SM1), which was centered on precentral knob, was activated by the hand movements of the control subjects as well as by the unaffected (left) hand movements of the patient. However, the affected(right) hand movements of the patient activated the medial portion of the injured precentral knob of the left SM1. The optimal scalp site for the affected (right) APB was located at 1 cm medial to that of the unaffected (left) APB. When the optimal scalp site was stimulated, the MEP characteristics from the affected (right) APB showed a delayed latency, lower amplitude, and a distorted figure compared with that of the unaffected (left) APB. Therefore, the motor function of the affected (right) hand was shown to be reorganized in the medial portion of the injured precentral knob.