• The Journal of Korean Society for Radiation Therapy
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• v.25 no.1
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• pp.1-8
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• 2013

Purpose: A selection of proper energy in treatment planning is very important because of having different dose distribution in body as photon energy. In generally, the low energy photon has been used in intensity-modulated radiation therapy (IMRT) for head and neck (H&N) cancer. The aim of this study was to evaluate the effect of partially used high energy photon at posterior oblique fields on IMRT plan for H&N cancer. Materials and Methods: The study was carried out on 10 patients (nasopharyngeal cancer 5, tonsilar cancer 5) treated with IMRT in Seoul National University Bundang Hospital. CT images were acquired 3 mm of thickness in the same condition and the treatment plan was performed by Eclipse (Ver.7.1, Varian, Palo Alto, USA). Two plans were generated under same planing objectives, dose volume constraints, and eight fields setting: (1) The low energy plan (LEP) created using 6 MV beam alone, (2) the partially used high energy plan (PHEP) created partially using 15 MV beam at two posterior oblique fields with deeper penetration depths, while 6 MV beam was used at the rest of fields. The plans for LEP and PHEP were compared in terms of coverage, conformity index (CI) and homogeneity index (HI) for planning target volume (PTV). For organs at risk (OARs), $D_{mean}$ and $D_{50%}$ were analyzed on both parotid glands and $D_{max}$, $D_{1%}$ for spinal cord were analyzed. Integral dose (ID) and total monitor unit (MU) were compared as addition parameters. For the comparing dose to normal tissue of posterior neck, the posterior-normal tissue volume (P-NTV) was set on the patients respectively. The $D_{mean}$, $V_{20Gy}$ and $V_{25Gy}$ for P-NTV were evaluated by using dose volume histogram (DVH). Results: The dose distributions were similar with regard to coverage, CI and HI for PTV between the LEP and PHEP. No evident difference was observed in the spinal cord. However, the $D_{mean}$, $D_{50%}$ for both parotid gland were slightly reduced by 0.6%, 0.7% in PHEP. The ID was reduced by 1.1% in PHEP, and total MU for PHEP was 1.8% lower than that for LEP. In the P-NTV, the $D_{mean}$, $V_{20Gy}$ and $V_{25Gy}$ of the PHEP were 1.6%, 1.8% and 2.9% lower than those of LEP. Conclusion: Dose to some OARs and a normal tissue, total monitor unit were reduced in IMRT plan with partially used high energy photon. Although these reduction are unclear how have a clinical benefit to patient, application of the partially used high energy photon could improve the overall plan quality of IMRT for head and neck cancer.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• Sleep Medicine and Psychophysiology
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• v.3 no.2
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• pp.32-42
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• 1996

Objectives : Upper airway resistance syndrome(UARS) is a sleep-related breathing disorder characterized by abnormal negative intrathoracic pressure during sleep. Abnormally increased negative intrathoracic pressure results in microarousal and sleep fragmentation which underlay UARS-associated complaints of daytime fatigue and sleepiness. Although daytime dysfunction in patients with UARS is comparable to that of sleep apnea syndrome, UARS has been relatively unnoticed in clinical setting. That is why UARS is apt to be excluded in diagnosing of sleep-related breathing disorders since its respiratory disturbance index and arterial oxygen saturation are within normal limits. The current study presents a summary of clinical and polysomnographic characteristics found in patients with UARS. The present study aims (1) to explore characteristics of patients diagnosed with UARS, (2) to characterize the polysomnographic findings of UARS patients, and (3) to enhance the understanding of UARS through those clinical and laboratory characteristics. Methods : This was a retrospective study of 20 UARS patients (male 15, female 5) and 30 obstructive sleep apnea (OSA) patients (male 21, female 9) at the Stanford Sleep Disorders Clinic. We diagnosed patients as having UARS when they met critenia, RDI < 5 characteristic findings of an elevated esophageal pressure($<-10\;cmH_2O$), frequent arousals secondary to an elevated esophageal pressure, and symptoms of daytime fatigue and sleepiness. We used polysomnographic value, which is standardized by Williams et al(1974), as normal control. Statiotical test were done with student t-tests. Results : (1) Mean age of UARS was $41.0\;{\pm}\;14.8$ years and OSA was $50.9\;{\pm}\;12.0$ years. UARS subject was significantly younger than OSA subject (p<0.05). (2) The total score of Epworth Sleepiness Scale (ESS) was UARS $9.7\;{\pm}\;6.3$ and OSAS $11.2\;{\pm}\;6.3$. There was no significant difference between two groups. (3) The mean body mass index was UARS $28.1\;{\pm}\;5.7\;kg/m^2$ and OSAS $32.9\;{\pm}\;7.0\;kg/m^2$. UARS had significantly lower meen body man index than OSAS subjects (p<0.05). (4) The polysomnographic parameters of UARS were not significantly different from those of OSA except RDI(p<0.001), $SaO_2$ (p<0.001) and slow wave sleep latency (p<0.05). (5) Compared with normal control, Total sleep time in UARS subjects was significantly shorter (p<0.001), sleep efficiency index was significantly lower (p<0.001), total awakening percentage was significantly higher (p<0.001), and sleep stage 1 (p<0.001) were significantly higher. (6) OSA patients showed poor sleep quality and distinct abnormal sleep architectures compared with normal control. Conclusions : Conclusions from the above results are as follows : (1) UARS patients were younger and had lower body mass index when umpared with OSA patients. (2) The quality of sleep and sleep architectures of the UARS and OSA patients are significantly different from those of normal control. (3) ESS scores and awakening frequencies of UARS are similar with those of OSA, suggesting that daytime dysfunction of UARS patients may be comparable to those of OSA patients. (4) The RDI and the $SaO_2$ which are important indicators in diagnosing sleep-related breathing disorders, of UARS subjects are close to normal value. (5) According to the the above results, we unclude that despite the absence of $SaO_2$ drops and the absence of an elevated number of apnea and hypopnea, subjects developed clinical complaints which were associated with laborious breathing, elevated Pes nadir, and frequently snoring. (6) Accordingly, we suggest including LIARS in the differential diagnosis list when sleep related breathing disorder is suspected clinically and overnight polysomnographic findings except snoring and frequent microarousal are within normal limits.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Tuberculosis and Respiratory Diseases
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• v.44 no.6
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• pp.1318-1325
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• 1997

Background : Since the late 1960s, mechanical ventilation has been accomplished primarily using volume controlled ventilation(VCV). While VCV allows a set tidal volume to be guaranteed, VCV could bring about excessive airway pressures that may be lead to barotrauma in the patients with acute lung injury. With the increment of knowledge related to ventilator-induced lung injury, pressure controlled ventilation(PCV) has been frequently applied to these patients. But, PCV has a disadvantage of variable tidal volume delivery as pulmonary impedance changes. Since the concept of combining the positive attributes of VCV and PCV(dual control ventilation, DCV) was described firstly in 1992, a few DCV modes were introduced. Pressure-regulated volume control(PRVC) mode, a kind of DCV, is pressure-limited, time-cycled ventilation that uses tidal volume as a feedback control for continuously adjusting the pressure limit However, no clinical studies were published on the efficacy of PRVC until now. 'This investigation studied the efficacy of PRVC in the patients with unstable respiratory mechanics. Methods : The subjects were 8 mechanically ventilated patients(M : F=6 : 2, $56{\pm}26$ years) who showed unstable respiratory mechanics, which was defined by the coefficients of variation of peak inspiratory pressure for 15 minutes greater than 10% under VCV, or the coefficients of variation of tidal volume greater than 10% under PCV. The study was consisited of 3 modes application with VCV, PCV and PRVC for 15 minutes by random order. To obtain same tidal volume, inspiratory pressure setting was adjusted in PCV. Respiratory parameters were measured by pulmonary monitor(CP-100 pulmonary monitor, Bicore, Irvine, CA, USA). Results : 1) Mean tidal volumes($V_T$) in each mode were not different(VCV, $431{\pm}102ml$ ; PCV, $417{\pm}99ml$ ; PRVC, $414{\pm}97ml$) 2) The coefficient of variation(CV) of $V_T$ were $5.2{\pm}3.9%$ in VCV, $15.2{\pm}7.5%$ in PCV and $19.3{\pm}10.0%$ in PRVC. The CV of $V_T$ in PCV and PRVC were significantly greater than that in VCV(p<0.01). 3) Mean peak inspiratory pressure(PIP) in VCV($31.0{\pm}6.9cm$ $H_2O$) was higher than PIP in PCV($26.0{\pm}6.5cm$ $H_2O$) or PRVC($27.0{\pm}6.4cm$ $H_2O$)(p<0.05). 4) The CV of PIP were $13.9{\pm}3.7%$ in VCV, $4.9{\pm}2.6%$ in PVC and $12.2{\pm}7.0%$ in PRVC. The CV of PIP in VCV and PRVC were greater than that in PCV(p<0.01). Conclusions : Because of wide fluctuations of VT and PIP, PRVC mode did not seem to have advantages compared to VCV or PCV in the patients with unstable respiratory mechanics.

• The Korean Journal of Nuclear Medicine Technology
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• v.24 no.1
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• pp.27-32
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• 2020

Purpose Glomerular Filtration Rate(GFR) is an important indicator for evaluating renal function and monitoring the progress of renal disease. Currently, the method of measuring GFR in clinical trials by using serum creatinine value and ^99mTc-DTPA(diethylenetriamine pentaacetic acid) renal dynamic scan is still useful. After the Gates method of formula was announced, when ^99mTc-DTPA Renal dynamic scan is taken, it is applied the GFR is measured using a gamma camera. The purpose of this paper is to measure the GFR by applying the Gates method of formula. It is according to effect activity and matrix size that is related in the GFR. Materials and Methods Data from 5 adult patients (patient age = 62 ± 5, 3 males, 2 females) who had been examined ^99mTc-DTPA Renal dynamic scan were analyzed. A dynamic image was obtained for 21 minutes after instantaneous injection of ^99mTc-DTPA 15 mCi into the patient's vein. To evaluate the glomerular filtration rate according to changes in activity and matrix size, total counts were measured after setting regions of interest in both kidneys and tissues in 2-3 minutes. The distance from detector to the table was maintained at 30cm, and the capacity of the pre-syringe (PR) was set to 15, 20, 25, 30 mCi, and each the capacity of post-syringe (PO) was 1, 5, 10, 15 mCi is set to evaluate the activity change. And then, each matrix size was changed to 32 × 32, 64 × 64, 128 × 128, 256 × 256, 512 × 512, and 1024 × 1024 to compare and to evaluate the values. Results As the activity increased in matrix size, the difference in GFR gradually decreased from 52.95% at the maximum to 16.67% at the minimum. The GFR value according to the change of matrix size was similar to 2.4%, 0.2%, 0.2% of difference when changing from 128 to 256, 256 to 512, and 512 to 1024, but 54.3% of difference when changing from 32 to 64 and 39.43% of difference when changing from 64 to 128. Finally, based on the presently used protocol, 256 × 256, PR 15 mCi and PO 1 mCi, the GFR value was the largest difference with 82% in PR 15 mCi and PO 1 mCi. conditions, and at the least difference is 0.2% in the conditions of PR 30 mCi and PO 15 mCi. Conclusion Through this paper, it was confirmed that when measuring the GFR using the gate method in the ^99mTc-DTPA renal dynamic scan. The GFR was affected by activity and matrix size changes. Therefore, it is considered that when taking the ^99mTc-DTPA renal dynamic scan, is should be careful by applying appropriate parameters when calculating GFR in the every hospital.