• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7549-7554
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• 2015

The aim of this study was to develop gastric retentive bi-layered tablet using floating drug delivery technique. Metformin was selected as a model drug due to its narrow absorption window as well as very highly water solubility. These properties of metformin led to be difficult controlling the drug release. The bi-layered tablet was prepared with bi-layered compression machine to minimize interference between floating part and controlling part. The tablet weight, appearance and hardness were evaluated after compression process. The times of 'time to floating' and 'Floating duration' were tested for floating ability and drug release study was also carried out to understand drug release behavior. Furthermore, the drug release of bi-layered tablet was compared with marketed metformin tablet with sustained release pattern (Glucopharge XR$^{(R)}$).The floating ability and drug release behaviors were well controlled by changing amounts of $NaHCO_3$ (floating substance) and hydroxypropyl methylcellulose (HPMC; release control material). Bi-layered tablet had 13s of time to float, over 10h of floating duration and very similar drug release behavior compared with Glucopharge XR$^{(R)}$($f_2$: 89.6). Consequently, the bi-layered tablet with floating ability was successfully prepared and these properties can maximize the efficacy of metformin.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.1-10
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• 2010

This study is about what process and methodology could make UI designer be able to achieve the interface which considers user's mental model through implementing corporate line-up model, when people design an interface between product of multi-function printer and user. The most important concern of UI designers who are dealing with an interface between product and user is how they can make product system image match user's mental model so that users can utilize products without any confusion and discomfort. If concept model which designers bring up and mental model which users expect and recognize could be of one accord, then users can feel ease of use toward products. The understanding and observation for user behavior and use pattern is prerequisite to develop user-centered interface between product and user. However, UI designers do design interface from their own perspective and assumption in many business areas, and users do not react as designers assumed and intended in many cases or examples. This study is to find inappropriate system images against users' mental model on basic function of multi-function printer, and the relationship of system image and user's mental model is diagramed to build up a hypothesis. The hypothesis from this study is validated through evaluation of domestic and international users. In addition, two suggestions to improve usability problems revealed from user test are proposed. The optimal solution is designed based on the result of user evaluation and consideration of many user environments, and then it is implemented to line-up product. In conclusion, this study considers how UI designers can create system image which is close to user's mental model.

• Journal of Food Hygiene and Safety
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• v.28 no.3
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• pp.217-221
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• 2013

This study developed predictive models for the kinetic behavior of Staphylococcus aureus on processed cheeses. Mozzarella slice cheese and cheddar slice cheese were inoculated with 0.1 ml of a S. aureus strain mixture (ATCC13565, ATCC14458, ATCC23235, ATCC27664, and NCCP10826). The inoculated samples were then stored at $4^{\circ}C$ (1440 h), $15^{\circ}C$ (288 h), $25^{\circ}C$ (72 h), and $30^{\circ}C$ (48 h), and the growth of all bacteria and of S. aureus were enumerated on tryptic soy agar and mannitol salt agar, respectively. The Baranyi model was fitted to the growth data of S. aureus to calculate growth rate (${\mu}_{max}$; ${\log}CFU{\cdot}g^{-1}{\cdot}h^{-1}$), lag phase duration (LPD; h), lower asymptote (log CFU/g), and upper asymptote (log CFU/g). The growth parameters were further analyzed using the square root model as a function of temperature. The model performance was validated with observed data, and the root mean square error (RMSE) was calculated. At $4^{\circ}C$, S. aureus cell growth was not observed on either processed cheese, but S. aureus growth on the mozzarella and cheddar cheeses was observed at $15^{\circ}C$, $25^{\circ}C$, and $30^{\circ}C$. The ${\mu}_{max}$ values increased, but LPD values decreased as storage temperature increased. In addition, the developed models showed acceptable performance (RMSE = 0.3500-0.5344). This result indicates that the developed kinetic model should be useful in describing the growth pattern of S. aureus in processed cheeses.

• Journal of Navigation and Port Research
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• v.31 no.3 s.119
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• pp.271-279
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• 2007

Ship structures are basically an assembly of plate elements and estimation load-carrying capacity or the ultimate strength is one of the most important criterion for estimated safety assessment and rational design on the ship structure. Also, Structural elements making up ship plated structures do not work separately against external load. One of the critical collapse events of a ship structure is the occurrence of overall buckling and plastic collapse of deck or bottom structure subjected to longitudinal bending. So, the deck and the bottom plates are reinforced by a number af longitudinal stiffeners to increase their strength and load-carrying capacity. For a rational design avoiding such a sudden collapse, it is very important to know the buckling and plastic behaviour or collapse pattern of the stiffened plate under axial compression. In this present study, to investigate effect af modeling range, the finite element method are used and their results are compared varying the analysis ranges. When making the FEA model, six types of structural modeling are adopted varying the cross section of stiffener. In the present paper, a series of FEM elastoplastic large deflection analyses is performed on a stiffened plate with fiat-bar, angle-bar and tee-bar stiffeners. When the applied axial loading, the influences of cross-sectional geometries on collapse behaviour are discussed. The purpose of the present study is examined to numerically calculate the characteristics of buckling and ultimate strength behavior according to the analysis method of ship's stiffened plate subject to axial loading.

• Journal of the Korean Chemical Society
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• v.64 no.5
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• pp.249-258
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• 2020

The potential use of egg shell and calcined egg shell as adsorbent was evaluated and compared to remove Cd²⁺ from aqueous solution. The samples were characterized using Thermogravimetry and Differential Thermal Analysis (TG/DTA), Scanning Electron Microscope (SEM), X-ray Diffractometer (XRD), Energy Dispersive X-ray Spectrometer (EDX) and BET Surface Analyzer. The batch-type adsorption experiment was conducted by varying diverse variables such as contact time, pH, initial Cd²⁺ concentrations and adsorbent dosage. The results showed that, under the initial Cd²⁺ concentrations ranged from 25 to 200 mg g^-1, the removal efficiencies of Cd²⁺ by egg shell powder (ESP) were decreased steadily from 96.72% to 22.89% with increase in the initial Cd²⁺ concentration at 2.5 g of dosage and 8 h of contact time. However, on the contrary to this, calcined egg shell powder (CESP) showed removal efficiencies above 99% regardless of initial Cd²⁺ concentration. The difference in the adsorption behavior of Cd²⁺ may be explained due to the different pH values of ESP and CESP in solution. Cd²⁺ seems to be efficiently removed from aqueous solution by using the CESP with a basicity nature of around pH 12. It was also observed that an optimum dosage of ESP and CESP for nearly complete removal of Cd²⁺ from aqueous solution is approximately 5.0 g and 1.0 g, respectively. Consequently, Cd²⁺ is more favorably adsorbed on CESP than ESP in the studied conditions. Adsorption data were applied by the pseudo-first-order and pseudo-second-order kinetics models and Freundlich and Langmuir isotherm models, respectively. With regard to adsorption kinetics tests, the pseudo-second-order kinetics was more suitable for ESP and CESP. The adsorption pattern of Cd²⁺ by ESP was better fitted to Langmuir isotherm model. However, by contrast with ESP, CESP was described by Freundlich isotherm model well.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.77-87
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• 2021

With the development of the Internet and personal computers, various and complex attacks begin to emerge. As the attacks become more complex, signature-based detection become difficult. It leads to the research on behavior-based log anomaly detection. Recent work utilizes deep learning to learn the order and it shows good performance. Despite its good performance, it does not provide any explanation for prediction. The lack of explanation can occur difficulty of finding contamination of data or the vulnerability of the model itself. As a result, the users lose their reliability of the model. To address this problem, this work proposes an explainable log anomaly detection system. In this study, log parsing is the first to proceed. Afterward, sequential rules are extracted by Bayesian posterior probability. As a result, the "If condition then results, post-probability" type rule set is extracted. If the sample is matched to the ruleset, it is normal, otherwise, it is an anomaly. We utilize HDFS datasets for the experiment, resulting in F1score 92.7% in test dataset.

• Journal of the Korean Geotechnical Society
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• v.22 no.6
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• pp.71-82
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• 2006

One of the most popular pre-reinforcement methods of tunnel heading in cohesionless soils would be the fore-polling of grouted pipes, known as RPUM (reinforced protective umbrella method) or UAM (umbrella arch method). This technique allows safe excavation even in poor ground conditions by creating longitudinal arch parallel to the tunnel axis as the tunnel advances. Some previous studies on the reinforcing effects have been performed using numerical methods and/or laboratory-based small scale model tests. The complexity of boundary conditions imposes difficulties in representing the tunnelling procedure in laboratory tests and theoretical approaches. Full-scale study to identify reinforcing effects of the tunnel heading has rarely been carried out so far. In this study, a large scale model testing for a tunnel in granular soils was performed. Reinforcing patterns considered are four cases, Non-Reinforced, Crown-Reinforced, Crown & Face-Reinforced, and Face-Reinforced. The behavior of ground and pipes as reinforcing member were fully measured as the surcharge pressure applied. The influences of reinforcing pattern, pipe length, and face reinforcement were investigated in terms of stress and displacement. It is revealed that only the Face-Reinforced has decreased sufficiently both vertical settlement in tunnel heading and horizontal displacement on the face. Vertical stresses along the tunnel axis were concentrated in tunnel heading from the test results, so the heading should be reinforced before tunnel advancing. Most of maximum axial forces and bending moments for Crown-reinforced were measured at 0.75D from the face. Also it should be recommended that the minimum length of the pipe is more than l.0D for crown reinforcement.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Journal of the Korea Concrete Institute
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• v.19 no.4
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• pp.515-525
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• 2007

In this investigation, results of laboratory tests on four reinforced concrete flat plate interior connections with elongated rectangular column support which has been used widely in tall residential buildings are presented. The purpose of this study is to evaluate an effect of column aspect ratio (${\beta}_c={c_1}/{c_2}$=side length ratio of column section in the direction of lateral loading $(c_1)$ to the direction of perpendicular to $c_1$) on the hysteretic behavior under earthquake type loading. The aspect ratio of column section was taken as $0.5{\sim}3\;(c_1/c_2=1/2,\;1/1,\;2/1,\;3/1)$ and the column perimeter was held constant at 1200mm in order to achieve nominal vertical shear strength $(V_c)$ uniformly. Other design parameters such as flexural reinforcement ratio $(\rho)$ of the slab and concrete strength$(f_{ck})$ was kept constant as ${\rho}=1.0%$ and $f_{ck}=40MPa$, respectively. Gravity shear load $(V_g)$ was applied by 30 percent of nominal vertical shear strength $(0.3V_o)$ of the specimen. Experimental observations on punching failure pattern, peak lateral-load and story drift ratio at punching failure, stiffness degradation and energy dissipation in the hysteresis loop, and steel and concrete strain distributions near the column support were examined and discussed in accordance with different column aspect ratio. Eccentric shear stress model of ACI 318-05 was evaluated with experimental results. A fraction of transferring moment by shear and flexure in the design code was analyzed based on the test results.

• Korean Chemical Engineering Research
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• v.50 no.6
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• pp.980-987
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• 2012

Nonpoint source pollution causes leaks and overtopping, depending on the state of the sewer network as well as aggravates the pollution load of the aqueous water system as it is introduced into the sewer by wash-off. According, the need for efficient sewer monitoring system which can manage the sewage flowrate, water quality, inflow/infiltration and overflow has increased for sewer maintenance and the prevention of environmental pollution. However, the sewer monitoring is not easy since the sewer network is built in underground with the complex nature of its structure and connections. Sewer decontamination mechanism as well as pipe network monitoring and fault diagnosis of water network system on system analysis proposed in this study. First, the pollution removal pattern and behavior of contaminants in the sewer pipe network is analyzed by using sewer process simulation program, stormwater & wastewater management model for expert (XP-SWMM). Second, the sewer network fault diagnosis was performed using the multivariate statistical monitoring to monitor water quality in the sewer and detect the sewer leakage and burst. Sewer decontamination mechanism analysis with static and dynamic state system results showed that loads of total nitrogen (TN) and total phosphorous (TP) during rainfall are greatly increased than non-rainfall, which will aggravate the pollution load of the water system. Accordingly, the sewer outflow in pipe network is analyzed due to the increased flow and inflow of pollutant concentration caused by rainfall. The proposed sewer network monitoring and fault diagnosis technique can be used effectively for the nonpoint source pollution management of the urban watershed as well as continuous monitoring system.