• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.6
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• pp.115-125
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• 2001

Authentication and access control are essential requirements for the information security of distributed environment. Delegation is process whereby an initiator principal in a distributed environment authorizes another principal to carry out some functions on behalf of the former. Delegation of access rights also increases the availability of services offer safety in distributed environments. A delegation easily provides principal to grant privileges in the single domain with Role-Based Access Control(RBAC). But in the multi-domain, initiators who request delegation may require to limit the access right of their delegates with restrictions that are called delegate restriction to protect the abuse of privilege. In this paper, we propose the delegation view as function of delegation restrictions. Proposed delegation view model not only prevent over-exposure of documents from granting multiple step delegation to document sharing in multi-domain with RBAC infrastructure but also reduce overload of security administrator and communication.

• Journal of Information Technology Services
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• v.20 no.5
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• pp.89-104
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• 2021

Food delivery service combined with IT technology and HMR (Home Meal Replacement) are rapidly growing due to the COVID-19. Recently, the demand for salads along with HMR has increased among office workers in their 20s and 30s who are interested in health and beauty. Freshcode is a food startup with 6 years of experience that started selling salad products through O2O service. Freshcode applied for a patent for a service that collects orders from nearby areas and delivers them on the same day to a designated delivery address 'FCOSPOT' to save shipping costs. In March 2021, in recognition of the growth potential of the regular delivery service, Freshcode received an investment of 6 billion won in Series A. This study may have practical implications to early-stage startups and scale-up stage startups through a longitudinal case study on the growth of a single company. As for the research method, the lean startup methodology and lean canvas were used in the early stage of startup. In particular, the process of the build-measure and learn feedback-loop, which is the core of lean startup methodology, was applied to each major decision-making step. In the scale-up stage after 5 years, the business model canvas was used to schematize the growth as a food online O2O platform to verify continuous innovation. This case study has three main findings. First, the idea of 'FCOSPOT' was successfully implemented through the Lean Startup methodology. Second, Freshcode demonstrated the scalability of the differentiated business model of shared base delivery O2O. Third, a key factor of success was the digital integrated communication operation strategy that maximizes the experience for the created customers.

• Smart Structures and Systems
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• v.29 no.1
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• pp.129-140
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• 2022

The effectiveness of system identification, damage detection, condition assessment and other structural analyses relies heavily on the accuracy and reliability of the measured data in structural health monitoring (SHM) systems. However, data anomalies often occur in SHM systems, leading to inaccurate and untrustworthy analysis results. Therefore, anomalies in the raw data should be detected and cleansed before further analysis. Previous studies on data anomaly detection mainly focused on just single type of data anomaly for denoising or removing outliers, meanwhile, the existing methods of detecting multiple data anomalies are usually time consuming. For these reasons, recognising multiple anomaly patterns for real-time alarm and analysis in field monitoring remains a challenge. Aiming to achieve an efficient and accurate detection for multi-type data anomalies for field SHM, this study proposes a pattern-recognition-based data anomaly detection method that mainly consists of three steps: the feature extraction from the long time-series data samples, the training of a pattern recognition neural network (PRNN) using the features and finally the detection of data anomalies. The feature extraction step remarkably reduces the time cost of the network training, making the detection process very fast. The performance of the proposed method is verified on the basis of the SHM data of two practical long-span bridges. Results indicate that the proposed method recognises multiple data anomalies with very high accuracy and low calculation cost, demonstrating its applicability in field monitoring.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.260-266
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• 2013

This study for establishing specific standards of atrium design aims to discuss design of atrium to consider energy performance according to the types of atrium of office building. In order to evaluate a type and a scale of atrium at the early design stage, modeling details of mass design were set as standards of conceptual design. In the experiment, Project Vasari was used to analyze modeling and energy consumption, based on the LOD 100-step suggested by AIA, because there is no guideline to specify a level of modeling details at each design process. From this analysis, the correlation among a simple-typed atrium and scale and energy load was understood, and the followings are the considerations for designing an atrium. First, the single-sided atrium reduced energy the most, and it was followed by three-sided, two-sided, four-sided and continuous-typed ones. On the whole, they could decrease energy by up to about 15%. Also, the atrium with a wide facade facing in the south was more favorable to reduce energy. Second, planning an atria within 10~30% of the whole building area was more energy efficient. Third, rather than the depth, adjusting the length in designing an atrium could reduce cooling and heating loads by 1.5% per 1m. As explained above, energy performance evaluation considering types and planning elements of atrium helps to assess alternatives in a reasonable way. In particular, considering the use of building needs to be preceded to select a type of atrium, although it is also important to consider its planning elements.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.39-46
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• 2016

This paper describes the third order feedforward delta-sigma modulator with inverter-based integrators and a 1.5bit comparator for the application of audio signal processing. The proposed 3rd-order delta-sigma modulator is multi-bit structure using 1.5 bit comparator instead of operational amplifier. This delta-sigma modulator has high SNR compared with single-bit 4th-order delta-sigma modulator in a low OSR. And it minimizes power consumes and simplified circuit structure using inverter-based integrator and using inverter-based integrator as analogue adder. The modulator was designed with 0.18um CMOS standard process and total chip area is $0.36mm^2$. The measured power cosumption is 28.8uW in a 0.8V analog supply and 66.6uW in a 1.8V digital supply. The measurement result shows that the peak SNDR of 80.7 dB, the ENOB of 13.1bit and the dynamic range of 86.1 dB with an input signal frequency of 2.5kHz, a sampling frequency of 2.56MHz and an oversampling rate of 64. The FOM (Walden) from the measurement result is 269 fJ/step, FOM (Schreier) was calculated as 169.3 dB.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.8-15
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• 2020

A forecasting method using deep learning does not have consistent results due to the differences in the characteristics of the dataset, even though they have the same forecasting models and parameters. For example, the forecasting model X optimized with dataset A would not produce the optimized result with another dataset B. The forecasting model with the characteristics of the dataset needs to be optimized to increase the accuracy of the forecasting model. Therefore, this paper proposes novel optimization steps for outlier removal, dataset classification, and a CNN-LSTM-based hyperparameter tuning process to forecast the daily power usage of a university campus based on the hourly interval. The proposing model produces high forecasting accuracy with a 2% of MAPE with a single power input variable. The proposing model can be used in EMS to suggest improved strategies to users and consequently to improve the power efficiency.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.7
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• pp.46-52
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• 2006

The effects of surface treatment on the hydrogen storage properties of a $Mg_2Ni$ alloy particle were investigated by the microvoltammetric technique, in which a carbon-filament microelectrode was manipulated to make electrical contact with the particle in a KOH aqueous solution. It was found that the hydrogen storage properties of $Mg_2Ni$ at room temperature were improved by the surface treatment with a nickel plating solution. The sodium salts(sodium phosphate and sodium dihydrogen citrate) contained in the nickel plating solution made the alloy form an amorphous-like state, resulting in an improved hydrogen charge/discharge capacity at room temperature as high as about 150[mAh/g] from the original value of 17[mAh/g]. Potential-step experiment was carried out to determine the apparent chemical diffusion coefficient of hydrogen atom($D_{app}$) in the alloy. Since the alloy particle we used here was a dense, conductive sphere, the spherical diffusion model was employed for data analysis. $D_{app}$ was found to vary the order between $10^{-8}{\sim}10^{-9}[cm^2/s]$ over the course of hydrogenation and dehydrogenation process.

• Journal of Microbiology and Biotechnology
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• v.22 no.12
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• pp.1636-1643
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• 2012

Enzymatic pre-bleaching by modification of pulp fibers with xylanases is an attractive approach to reduce the consumption of toxic bleaching chemicals in the paper industry. In this study, an alkaliphilic endoxylanase gene was isolated from metagenomic DNA of a structurally stable thermophilic lignocellulose-degrading microbial consortium using amplification with conserved glycosyl hydrolase family 10 primers and subsequent genome walking. The full-length xylanase showed 78% sequence identity to an endo-${\beta}$-1,4-xylanase of Clostridium phytofermentans and was expressed in a mature form with an N-terminal His6 tag fusion in Escherichia coli. The recombinant xylanase Xyn3F was thermotolerant and alkaliphilic, working optimally at $65-70^{\circ}C$ with an optimal pH at 9-10 and retaining >80% activity at pH 9, $60^{\circ}C$ for 1 h. Xyn3F showed a $V_{max}$ of 2,327 IU/mg and $K_m$ of 3.5 mg/ml on birchwood xylan. Pre-bleaching of industrial eucalyptus pulp with no prior pH adjustment (pH 9) using Xyn3F at 50 IU/g dried pulp led to 4.5-5.1% increase in final pulp brightness and 90.4-102.4% increase in whiteness after a single-step hypochlorite bleaching over the untreated pulp, which allowed at least 20% decrease in hypochlorite consumption to achieve the same final bleaching indices. The alkaliphilic xylanase is promising for application in an environmentally friendly bleaching step of kraft and soda pulps with no requirement for pH adjustment, leading to improved economic feasibility of the process.

• Tunnel and Underground Space
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• v.29 no.3
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• pp.197-213
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• 2019

We simulated the fault reactivation experiment conducted at 'Main Fault' intersecting the low permeability clay formations of Mont Terri Underground Research Laboratory in Switzerland using TOUGH-FLAC simulator. The fluid flow along a fault was modelled with solid elements and governed by Darcy's law with the cubic law in TOUGH2, whereas the mechanical behavior of a single fault was represented by creating interface elements between two separating rock blocks in FLAC3D. We formulate the hydro-mechanical coupling relation of hydraulic aperture to consider the elastic fracture opening and failure-induced dilation for reproducing the abrupt changes in injection flow rate and monitoring pressure at fracture opening pressure. A parametric study was conducted to examine the effects of in-situ stress condition and fault deformation and strength parameters and to find the optimal parameter set to reproduce the field observations. In the best matching simulation, the fracture opening pressure and variations of injection flow rate and monitoring pressure showed good agreement with field experiment results, which suggests the capability of the numerical model to reasonably capture the fracture opening and propagation process. The model overestimated the fault displacement in shear direction and the range of reactivated zone, which was attributed to the progressive shear failures along the fault at high injection pressure. In the field experiment results, however, fracture tensile opening seems the dominant mechanism affecting the hydraulic aperture increase.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.682-691
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• 2005

We present a two-step evolution system that produces controllable virtual creatures in physically simulated 3D environment. Previous evolutionary methods for virtual creatures did not allow any user intervention during evolution process, because they generated a creature's shape, locomotion, and high-level behaviors such as target-following and obstacle avoidance simultaneously by one-time evolution process. In this work, we divide a single system into manageable two sub-systems, and this more likely allowsuser interaction. In the first stage, a body structure and low-level motor controllers of a creature for straight movement are generated by an evolutionary algorithm. Next, a high-level control to follow a given path is achieved by a neural network. The connection weights of the neural network are optimized by a genetic algorithm. The evolved controller could follow any given path fairly well. Moreover, users can choose or abort creatures according to their taste before the entire evolution process is finished. This paper also presents a new sinusoidal controller and a simplified hydrodynamics model for a capped-cylinder, which is the basic body primitive of a creature.