• Journal of the Korean Applied Science and Technology
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• v.36 no.4
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• pp.1143-1152
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• 2019

In order to study the solubilization of aniline by cationic surfactants (DTAB, TTAB and CTAB), the solubilization constant (K_s) and thermodynamic functions were measured and calculated by using the UV-Vis method. The solubilization constants of aniline with the change of temperature were measured, and the effects of addition of ionic salts and organics on the solubilization constants were investigated. These effects of additives and temperature changes were compared and analyzed for each type of surfactant, and the solubilization of aniline was analyzed microscopically by comparing and evaluating the thermodynamic functions obtained from the solubilization constants. As a result, the Gibbs free energy and enthalpy changes were both negative and the entropy changes were positive within the measured range for the solubilization of aniline by cationic surfactants. The solubilization constant value decreased with increasing temperature and increased with increasing carbon chain length of the surfactant. As the concentration of ionic salts increased, the Gibbs free energy change increased at first and then decreased. In n-butanol solution, the Gibbs free energy change tended to increase continuously with increasing the concentration of n-butanol.

• Journal of the korean academy of Pediatric Dentistry
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• v.41 no.4
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• pp.283-291
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• 2014

Patients with extreme anxiety who are unable to cope with dental treatment under non-pharmacological behavioral management method may require sedation, or other forms pharmacological behavioral management method. The aim of this retrospective study was to investigate the effect of concomitant administration of 0.1 mg/kg intramuscular midazolam with or without sevoflurane insufflation sedation on sedation depth and cardiopulmonary function in pediatric patients. We analysed the records of anesthesia on patients who received dental treatment under deep sedation using sevoflurane insufflation from January 2013 to March 2014. Thirty-six children, aged 3 to 6 years, undergoing dental treatment were sedated using either sevoflurane insufflation alone (Group S, n = 18) or a combination of intramuscular injection of 0.1 mg/kg midazolam plus sevoflurane insufflation (Group SM, n = 18). Upon comparison, the average entropy value of group SM was lower than that of group S, but there were no statistically significant difference between the two groups (p > 0.05). The average heart rate and mean arterial pressure of group SM were higher than those of group S (p < 0.05). Concomitant intramuscular injection of 0.1 mg/kg midazolam with sevoflurane insufflation sedation is not sufficient to enhance the quality of sedation.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.165-172
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• 2010

In clinical data minig, choosing the optimal subset of features is such important, not only to reduce the computational complexity but also to improve the usefulness of the model constructed from the given data. Moreover the threshold values (i.e., cut-off points) of selected features are used in a clinical decision criteria of experts for differential diagnosis of diseases. In this paper, we propose a fuzzy discretization approach, which is evaluated by measuring the degree of separation of redundant attribute values in overlapping region, based on spatial distribution of data with continuous attributes. The weighted average of the redundant attribute values is then used to determine the threshold value for each feature and rough set theory is utilized to select a subset of relevant features from the overall features. To verify the validity of the proposed method, we compared experimental results, which applied to classification problem using 668 patients with a chief complaint of dyspnea, based on three discretization methods (i.e., equal-width, equal-frequency, and entropy-based) and proposed discretization method. From the experimental results, we confirm that the discretization methods with fuzzy partition give better results in two evaluation measures, average classification accuracy and G-mean, than those with hard partition.

• Journal of the Korean Chemical Society
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• v.31 no.5
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• pp.413-418
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• 1987

Rates of the reaction for p-nitro benzyl chloride, benzyl chloride and p-methyl benzyl chloride with pyridine in methanol solvent have been measured by an electric conductivity method at 40$^{\circ}$C and 50$^{\circ}$C under various pressures (1∼2000bar). Pseudo first-order rate constants and second-order rate constants were determined. Rates of these reactions were increased in the order p-NO$_2$ < p-H < p-CH$_3$ and increased with temperature, pressure and concentration of pyridine. From those rate constants, the activation parameters were evaluated. The activation volume and the activation compressibility coefficient are both negative values, but the activation enthalpy is positive and the activation entropy is large negative value. From the evaluation of the ground state and transition state which was resulted from substituents and pressure, it was found that this reaction proceeds through S$_N$2 reaction, and S$_N$2 fashion is slightly disappeared as pressure increases.

• Applied Chemistry for Engineering
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• v.8 no.6
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• pp.1041-1047
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• 1997

The influence of $\omega$-phenylalkylammonium salt on the critical micelle concentration (CMC) of SDS has been examined using the electric conductivity method. CMC of SDS exhibited the tendency to decrease with the length of alkyl group of additives. The effect of temperature on CMC of SDS in additive solutions has been observed in the range of $18^{\circ}C-50^{\circ}C$. The free energy(${\Delta}G_m^{\circ}$) for the micellization of SDS is negative and the entropy(${\Delta}S_m^{\circ}$) is a large positive value. The enthalpy(ΔHm0is positive in low temperature($18^{\circ}C$) and negative in high temperature($>25^{\circ}C$). In the prensence of organic additives, the micellization of SDS was considered as a spontaneous process and to involve a phase transition. The values of ΔGm0has shown the tendency to increase but the values of ${\Delta}S_m^{\circ}$ and ${\Delta}H_m^{\circ}$ to decrease with the length of alklyl group of additive salts. The changes in ${\Delta}\kappa$(difference of specific conductivity) with increasing mole ratio of additives in the mixed solutions indicated the formation of mixed micelles between SDS and additives. The effect of the length of alkyl chain on the micellization of SDS demonstrated the penetration of organic additives into the palisade layer of the SDS micelle.

• Applied Chemistry for Engineering
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• v.25 no.4
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• pp.430-436
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• 2014

Allura Red (AR) is a water-soluble harmful tar-based food colorant (FD & C Red 40). Batch adsorption studies were performed for the removal of AR using bituminous coal based granular activated carbon as adsorbent by varying the operation parameters such as adsorbent dosage, initial concentration, contact time and temperature. Experimental equilibrium adsorption data were analyzed by Langmuir, Freundlich and Temkin isotherms. The equilibrium process was described well by Freundlich isotherm. From determined separation factor ($R_L$), adsorption of AR by granular activated carbon could be employed as effective treatment method. Temkin parameter, B was determined to 1.62~3.288 J/mol indicating a physical adsorption process. By estimation of adsorption rate experimental data, the value of intraparticle diffusion rate constant ($k_m$) increased with the increasing adsorption temperature. The adsorption process were found to confirm to the pseudo second order model with good correlation. Thermodynamic parameters like change of free energy, enthalpy, and entropy were also calculated to predict the nature adsorption in the temperature range of 298~318 K. The negative Gibbs free energy change (${\Delta}G$ = -2.16~-6.55 kJ/mol) and the positive enthalpy change (${\Delta}H$ = + 23.29 kJ/mol) indicated the spontaneous and endothermic nature of the adsorption process, respectively.

• Journal of the Korean Chemical Society
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• v.18 no.5
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• pp.320-328
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• 1974

It is unable to derive the standard emf ($E^{\circ}$) of the cell at high pressure from the conventional method. However, when the concept of the complete equilibrium constant($K{\circ})$) is available to the conventional Nernst equation, it is possible to get the standard emf of the cell at high pressure(complete Nernst equation). Moreover, the other thermodynamic properties, such as the net change of solvation number(k), the compressibility of solvent(${\beta}$), ionization constant(K), the standard free energy change(${\Delta}G^{\circ}$), the standard enthalpy change(${\Delta}H^{\circ}$) and the standard entropy change (${\Delta}S^{\circ}$) of the cell reaction at equilibrium state have been also obtained. In this experiment, the emf of the cell; 12.5 % Cd(Hg)│$CdSO_4(3.105{\times}10^{-3}M),\;Hg_2SO_4│Hg$ have bee measured at temperature from 20 to $35^{\circ}C$ and at pressures from 1 to 2500 atms. The emf of the cell increased with increasing pressure at constant temperature, and did with increasing temperature at constant pressure. The net change of solvation number(k) of the cell reaction was 41.96 at $25^{\circ}C$, and kept constant value with pressure, while, K and ${\Delta}S^{\circ}$ increased with pressure, but whereas ${\Delta}G^{\circ}$ and ${\Delta}H^{\circ}$ decreased. Since the standard emf of the cell at high pressure can be calculated from the complete Nernst equation, the theory of chemical equilibrium could be developed with at high pressure as well as at the atmosphere.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2C
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• pp.181-188
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• 2007

This paper proposed a watermark embedding/extracting method using CABAC(Context-based Adaptive Binary Arithmetic Coding) which is the entropy encoder for the main profile of MPEG-4 Part 10 H.264/AVC. This algorithm selects the blocks and the coefficients in a block on the bases of the contexts extracted from the relationship to the adjacent blocks and coefficients. A watermark bit is embedded without any modification of coefficient or with replacing the LSB(Least Significant Bit) of the coefficient with a watermark bit by considering both the absolute value of the selected coefficient and the watermark bit. Therefore, it makes it hard for an attacker to find out the watermarked locations. By selecting a few coefficients near the DC coefficient according to the contexts, this algorithm satisfies the robustness requirement. From the results from experiments with various kinds and various strengths of attacks the maximum error ratio of the extracted watermark was 5.02% in maximum, which makes certain that the proposed algorithm has very high level of robustness. Because it embeds the watermark during the context modeling and binarization process of CABAC, the additional amount of calculation for locating and selecting the coefficients to embed watermark is very small. Consequently, it is highly expected that it is very useful in the application area that the video must be compressed right after acquisition.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.444-453
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• 2003

Recently, a great interest of bio-technology(BT) is concentrated and the image analysis technique for electrophoresis gels is highly requested to analyze genetic information or to look for some new bio-activation materials. For this purpose, the location and quantity of each band in a lane should be measured. In most of existing techniques, the approach of peak searching in a profile of a lane is used. But this peak is improper as the representative of a band, because its location does not correspond to that of the brightest pixel or the center of gravity. Also, it is improper to measure band quantity in most of these approaches because various enhancement processes are commonly applied to original images to extract peaks easily. In this paper, we adopt an approach to measure accumulated brightness as a band quantity in each band region, which Is extracted by not using any process of changing relative brightness, and the gravity center of the region is calculated as a band location. Actually, we first extract lanes with an entropy-based threshold calculated on a gel-image histogram. And then, three other methods are proposed and applied to extract bands. In the MER method, peaks and valleys are searched on a vertical search line by which each lane is bisected. And the minimum enclosing rectangle of each band is set between successive two valleys. On the other hand, in the RG-1 method, each band is extracted by using region growing with a peak as a seed, separating overlapped neighbor bands. In the RG-2 method, peaks and valleys are searched on two vertical lines by which each lane is trisected, and the left and right peaks nay be paired up if they seem to belong to the same band, and then each band region is grown up with a peak or both peaks if exist. To compare above three methods, we have measured the location and amount of bands. As a result, the average errors in band location of MER, RG-1, and RG-2 were 6%, 3%, and 1%, respectively, when the lane length is normalized to a unit value. And the average errors in band amount were 8%, 5%, and 2%, respectively, when the sum of band amount is normalized to a unit value. In conclusion, RG-2 was shown to be more reliable in the accuracy of measuring the location and amount of bands.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.