• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.3
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• pp.29-38
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• 2006

Recent advances in wireless communication technology promotes many researches related to sensor network and brings several proposals to fit into various types of sensor network communication. The research direction for sensor network is divided into the method to maximize an energy efficiency and security researches that has not been remarkable so far. To maximize an energy efficiency, the methods to support data aggregation and cluster-head selection algorithm are proposed. To strengthen the security, the methods to support encryption techniques and manage a secret key that is applicable to sensor network are proposed, In. However, the combined method to satisfy both energy efficiency and security is in the shell. This paper is devoted to design the protocol that combines an efficient clustering protocol with key management algorithm that is fit into various types of sensor network communication. This protocol may be applied to sensor network systems that deal with sensitive data.

• Advances in nano research
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• v.10 no.1
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• pp.77-90
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• 2021

In the present study, novel chitosan coated magnetic magnetite (Fe3O4) nanoparticles were successfully biosynthesized from mushroom, Agaricus campestris, extract. The obtained bio-nanocomposite material was used to investigate ultra-fast and highly efficient for removal of Ni2+ ions in a fixed-bed column. Chitosan was treated as polyelectrolyte complex with Fe3O4 nanoparticles and a Fungal Bio-Nanocomposite Material (FBNM) was derived. The FBNM was characterized by using X-Ray Diffractometer (XRD), Scanning Electron Microscopy-Energy Dispersive X-Ray Spectroscopy (SEM-EDS), Fourier Transform Infrared spectra (FTIR) and Thermogravimetric Analysis (TGA) techniques and under varied experimental conditions. The influence of some important operating conditions including pH, flow rate and initial Ni2+ concentration on the uptake of Ni2+ solution was also optimized using a synthetic water sample. A Central Composite Design (CCD) combined with Response Surface Modeling (RSM) was carried out to maximize Ni2+ removal using FBNM for adsorption process. A regression model was derived using CCD to predict the responses and analysis of variance (ANOVA) and lack of fit test was used to check model adequacy. It was observed that the quadratic model, which was controlled and proposed, was originated from experimental design data. The FBNM maximum adsorption capacity was determined as 59.8 mg g-1. Finally, developed method was applied to soft drinks to determine Ni2+ levels. Reusability of FBNM was tested, and the adsorption and desorption capacities were not affected after eight cycles. The paper suggests that the FBNM is a promising recyclable nanoadsorbent for the removal of Ni2+ from various soft drinks.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.3
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• pp.67-75
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• 2010

Network reprogramming is a technology that allows several sensor nodes deployed in sensor field to be repaired remotely. Unlike general communication in sensor network where small amount of data is transferred, network reprogramming requires reliable transfer of large amount of data. The existing network reprogramming techniques suffers high cost and large energy consumption to recover data loss in node communication. In this paper, a cluster based network reporgramming scheme is proposed for sensor network. It divides sensor field into several clusters and chooses a cluster header in charge of data relay to minimize duplicated transmission and unnecessary competition. It increases reliability by effective error recovery through status table.

• Transactions of the Korean hydrogen and new energy society
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• v.11 no.1
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• pp.43-49
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• 2000

The heat transportation from a complex of industry to a rural area needs more efficient method because the distance between them is usually more than 10km. Conventional heat transportation using steam or hot water via pipe line has limits in transportation distance (about 3~5 km) because of the heat loss and frictional loss in the pipe line. Metal hydride can absorb or discharge hydrogen through exothermic or endothermic reaction. After releasing hydrogen from metal hydride by means of the waste heat from industry, we can transport this hydrogen to urban area via pipe line. In urban areas, other metal alloy reacts with this hydrogen to form metal hydride and produces heat for heating. Cool heat is also obtained if it is possible to use metal hydride with low reaction temperature. Therefore, metal hydride can be used as a media for transportation and storage of heat. $MmNi_{4.5}Al_{0.5}Zr_{0.003}$, $LaNi_5$, $Zr_{0.9}Ti_{0.1}Cr_{0.6}Fe_{1.4}$, $MmNi_{4.7}Al_{0.1}Fe_{0.1}V_{0.1}$ alloys were selected for this purpose and the properties of those metal hydrides were discussed. The design and control techniques were proposed and discussed for this heat transportation system using metal hydride.

• Journal of Microbiology and Biotechnology
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• v.24 no.1
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• pp.59-69
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• 2014

One of the major challenges in metabolic engineering for enhanced synthesis of value-added chemicals is to design and develop new strains that can be translated into well-controlled fermentation processes using bioreactors. The aim of this study was to assess the influence of various fed-batch strategies in the performance of metabolically engineered Pseudomonas putida strains, ${\Delta}gcd$ and ${\Delta}gcd-pgl$, for improving production of medium-chain-length polyhydroxyalkanoates (mcl-PHAs) using glucose as the only carbon source. First we developed a fed-batch process that comprised an initial phase of biomass accumulation based on an exponential feeding carbon-limited strategy. For the mcl-PHA accumulation stage, three induction techniques were tested under nitrogen limitation. The substrate-pulse feeding was more efficient than the constant-feeding approach to promote the accumulation of the desirable product. Nonetheless, the most efficient approach for maximum PHA synthesis was the application of a dissolved-oxygen-stat feeding strategy (DO-stat), where P. putida ${\Delta}gcd$ mutant strain showed a final PHA content and specific PHA productivity of 67% and $0.83g{\cdot}l^{-1}{\cdot}h^{-1}$, respectively. To our knowledge, this mcl-PHA titer is the highest value that has been ever reported using glucose as the sole carbon and energy source. Our results also highlighted the effect of different fed-batch strategies upon the extent of realization of the intended metabolic modification of the mutant strains.

• Advances in nano research
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• v.16 no.6
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• pp.623-638
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• 2024

This study investigates the thermal post-buckling behavior of concrete eccentric annular sector plates reinforced with graphene oxide powders (GOPs). Employing the minimum total potential energy principle, the plates' stability and response under thermal loads are analyzed. The Haber-Schaim foundation model is utilized to account for the support conditions, while the transform differential quadrature method (TDQM) is applied to solve the governing differential equations efficiently. The integration of GOPs significantly enhances the mechanical properties and stability of the plates, making them suitable for advanced engineering applications. Numerical results demonstrate the critical thermal loads and post-buckling paths, providing valuable insights into the design and optimization of such reinforced structures. This study presents a machine learning algorithm designed to predict complex engineering phenomena using datasets derived from presented mathematical modeling. By leveraging advanced data analytics and machine learning techniques, the algorithm effectively captures and learns intricate patterns from the mathematical models, providing accurate and efficient predictions. The methodology involves generating comprehensive datasets from mathematical simulations, which are then used to train the machine learning model. The trained model is capable of predicting various engineering outcomes, such as stress, strain, and thermal responses, with high precision. This approach significantly reduces the computational time and resources required for traditional simulations, enabling rapid and reliable analysis. This comprehensive approach offers a robust framework for predicting the thermal post-buckling behavior of reinforced concrete plates, contributing to the development of resilient and efficient structural components in civil engineering.

• International Journal of Advanced Culture Technology
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• v.8 no.1
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• pp.207-212
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• 2020

The human centric lighting (HCL) control is a major focus point of the smart lighting system design to provide energy efficient and people mood rhythmic motivation lighting in smart buildings. This paper proposes the HCL control using indoor surveillance camera to improve the human motivation and well-beings in the indoor environments like residential and industrial buildings. In this proposed approach, the indoor surveillance camera video streams are used to predict the day lights and occupancy, occupancy specific emotional features predictions using the advanced computer vision techniques, and this human centric features are transmitted to the smart building light management system. The smart building light management system connected with internet of things (IoT) featured lighting devices and controls the light illumination of the objective human specific lighting devices. The proposed concept experimental model implemented using RGB LED lighting devices connected with IoT features open-source controller in the network along with networked video surveillance solution. The experiment results are verified with custom made automatic lighting control demon application integrated with OpenCV framework based computer vision methods to predict the human centric features and based on the estimated features the lighting illumination level and colors are controlled automatically. The experiment results received from the demon system are analyzed and used for the real-time development of a lighting system control strategy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.3
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• pp.39-55
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• 1992

In this research, a Three Level Decomposition technique has been developed for configuration design optimization of truss structures. In the first level, as design variables, behavior variables are used and the strain energy has been treated as the cost function to be maximized so that the truss structure can absorb maximum energy. For design constraint of the optimal design problem, allowable stress, buckling stress, and displacement under multi-loading conditions are considered. In the second level, design problem is formulated using the cross-sectional area as the design variable and the weight of the truss structure as the cost function. As for the design constraint, the equilibrium equation with the optimal displacement obtained in the first level is used. In the third level, the nodal point coordinates of the truss structure are used as coordinating variable and the weight has been taken as the cost function. An advantage of the Three Level Decomposition technique is that the first and second level design problems are simple because they are linear programming problems. Moreover, the method is efficient because it is not necessary to carry out time consuming structural analysis and techniques for sensitivity analysis during the design optimization process. By treating the nodal point coordinates as design variables, the third level becomes unconstrained optimal design problems which is easier to solve. Moreover, by using different convergence criteria at each level of design problem, improved convergence can be obtained. The proposed technique has been tested using four different truss structures to yield almost identical optimum designs in the literature with efficient convergence rate regardless of constraint types and configuration of truss structures.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.1-12
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• 2010

Recently, processor performance has been improved dramatically. Unfortunately, as the process technology scales down, energy consumption in a processor increases significantly whereas the processor performance continues to improve. Moreover, peak temperature in the processor increases dramatically due to the increased power density, resulting in serious thermal problem. For this reason, performance, energy consumption and thermal problem should be considered together when designing up-to-date processors. This paper proposes three modified filter cache schemes to alleviate the thermal problem in the filter cache, which is one of the most energy-efficient design techniques in the hierarchical memory systems : Bypass Filter Cache (BFC), Duplicated Filter Cache (DFC) and Partitioned Filter Cache (PFC). BFC scheme enables the direct access to the L1 cache when the temperature on the filter cache exceeds the threshold, leading to reduced temperature on the filter cache. DFC scheme lowers temperature on the filter cache by appending an additional filter cache to the existing filter cache. The filter cache for PFC scheme is composed of two half-size filter caches to lower the temperature on the filter cache by reducing the access frequency. According to our simulations using Wattch and Hotspot, the proposed partitioned filter cache shows the lowest peak temperature on the filter cache, leading to higher reliability in the processor.

• Journal of the Korean Society for Railway
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• v.13 no.2
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• pp.173-178
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• 2010

Electric railroad systems consist of supply system of electric power and electric locomotive. The electric locomotive is adapted to high speed driving and mass transportation due to obtaining high traction force. The electric locomotive is operated by motor blocks and traction motors. Train speed is controlled by suppling power from motor blocks to traction motors according to reference speed. Speed control of the electric locomotive is efficient by spending minimum energy between motor blocks and traction motors. Recently, induction motors have been used than DC and synchronized motors as traction motors. Speed control of induction motors are used by vector control techniques. In this paper, speed of the induction motor is controlled by using the vector control technique. Control system model is presented by using Simulink. Pulse is controlled by PI and hysteresis controller. IGBT inverter is used for real-time control and system performance is demonstrated by simulating the induction motor which has 210[kW] on the output power.