• Journal of the Optical Society of Korea
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• v.18 no.3
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• pp.274-282
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• 2014

In this study, closely spaced Au nanoparticles which are arranged in nanocluster (heptamer) configurations have been employed to design efficient plasmonic subwavelength devices to function at the telecommunication spectrum (${\lambda}$~1550 nm). Utilizing two kinds of nanoparticles, the optical properties of heptamer clusters composed of Au rod and shell particles that are oriented in triphenylene molecular fashion have been investigated numerically, and the cross-sectional profiles of the scattering and absorption of the optical power have been calculated based on a finite-difference time-domain (FDTD) method. Plasmon hybridization theory has been utilized as a theoretical approach to characterize the features and properties of the adjacent and mutual heptamer clusters. Using these given nanostructures, we designed a complex four-branch ($1{\times}4$) Y-shape splitter that is able to work at the near infrared region (NIR). This splitter divides and transmits the magnetic plasmon mode along the mutual heptamers arrays. Besides, as an important and crucial parameter, we studied the impact of arm spacing (offset distance) on the guiding and dividing of the magnetic plasmon resonance propagation and by calculating the ratio of transported power in both nanorod and nanoshell-based structures. Finally, we have presented the optimal structure, that is the four-branch Y-splitter based on shell heptamers which yields the power ratio of 23.9% at each branch, 4.4 ${\mu}m$ decaying length, and 1450 nm offset distance. These results pave the way toward the use of nanoparticles clusters in molecular fashions in designing various efficient devices that are able to be efficient at NIR.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.50-56
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• 2020

With the rapid development of deep neural network theory and application research, the effect of face detection has been improved. However, due to the complexity of deep neural network calculation and the high complexity of the detection environment, how to detect face quickly and accurately becomes the main problem. This paper is based on the relatively simple model of the MTCNN model, using FDDB (Face Detection Dataset and Benchmark Homepage), LFW (Field Label Face) and FaceScrub public datasets as training samples. At the same time of sorting out and introducing MTCNN(Multi-Task Cascaded Convolutional Neural Network) model, it explores how to improve training speed and Increase performance at the same time. In this paper, the dynamic image pyramid technology is used to replace the traditional image pyramid technology to segment samples, and OHEM (the online hard example mine) function in MTCNN model is deleted in training, so as to improve the training speed.

• Biomolecules & Therapeutics
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• v.30 no.4
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• pp.320-327
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• 2022

Neurodevelopmental disorders are complex conditions that pose difficulty in the modulation of proper motor, sensory and cognitive function due to dysregulated neuronal development. Previous studies have reported that an imbalance in the excitation/inhibition (E/I) in the brain regulated by glutamatergic and/or GABAergic neurotransmission can cause neurodevelopmental and neuropsychiatric behavioral deficits such as autism spectrum disorder (ASD). NMDA acts as an agonist at the NMDA receptor and imitates the action of the glutamate on that receptor. NMDA however, unlike glutamate, only binds to and regulates the NMDA receptor subtypes and not the other glutamate receptors. This study seeks to determine whether NMDA administration in mice i.e., over-activation of the NMDA system would result in long-lasting behavioral deficits in the adolescent mice. Both gender mice were treated with NMDA or saline at early postnatal developmental period with significant synaptogenesis and synaptic maturation. On postnatal day 28, various behavioral experiments were conducted to assess and identify behavioral characteristics. NMDA-treated mice show social deficits, and repetitive behavior in both gender mice at adolescent periods. However, only the male mice but not female mice showed increased locomotor activity. This study implies that neonatal exposure to NMDA may illicit behavioral features similar to ASD. This study also confirms the validity of the E/I imbalance theory of ASD and that NMDA injection can be used as a pharmacologic model for ASD. Future studies may explore the mechanism behind the gender difference in locomotor activity as well as the human relevance and therapeutic significance of the present findings.

• Wind and Structures
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• v.34 no.2
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• pp.185-197
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• 2022

This study aimed to analyze the wind-induced mechanical energy (WME) of a proposed super high-rise and long-span transmission tower-line system (SHLTTS), which, in 2021, is the tallest tower-line system with the longest span. Anew index - the WME, accounting for the wind-induced vibration behavior of the whole system rather than the local part, was first proposed. The occurrence of the maximum WME for a transmission tower, with or without conductors, under synoptic winds, was analyzed, and the corresponding formulae were derived based on stochastic vibration theory. Some calculation data, such as the drag coefficient, dynamic parameters, windshielding areas, mass, calculation point coordinates, mode shape and influence function, derived from wind tunnel testing on reducedscale models and finite element software were used in calculating the maximum WME of the transmission tower under three cases. Then, the influence of conductors, wind speed, gradient wind height and wind yaw angle on WME components and the energy transfer relationship between substructures (transmission tower and conductor) were analyzed. The study showed that the presence of conductors increases the WME of transmission towers and changes the proportion of the mean component (MC), background component (BC) and resonant component (RC) for WME; The RC of WME is more susceptible to the wind speed change. Affected by the gradient wind height, the WME components decrease. With the RC decreasing the fastest and the MC decreasing the slowest; The WME reaches the its maximum value at the wind yaw angle of 30°. Due to the influence of three factors, namely: the long span of the conductors, the gradient wind height and the complex geometrical profile, it is important that the tower-line coupling effect, the potential for fatigue damage and the most unfavorable wind yaw angle should be given particular attention in the wind-resistant design of SHLTTSs

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1229-1244
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• 2017

In recent years, as demand for data-based analytical methodologies increases in various fields, optimization methods have been developed to handle them. In particular, various constraints required for problems in statistics and machine learning can be solved by convex optimization. Alternating direction method of multipliers (ADMM) can effectively deal with linear constraints, and it can be effectively used as a parallel optimization algorithm. ADMM is an approximation algorithm that solves complex original problems by dividing and combining the partial problems that are easier to optimize than original problems. It is useful for optimizing non-smooth or composite objective functions. It is widely used in statistical and machine learning because it can systematically construct algorithms based on dual theory and proximal operator. In this paper, we will examine applications of ADMM algorithm in various fields related to statistics, and focus on two major points: (1) splitting strategy of objective function, and (2) role of the proximal operator in explaining the Lagrangian method and its dual problem. In this case, we introduce methodologies that utilize regularization. Simulation results are presented to demonstrate effectiveness of the lasso.

• Journal of The Korean Association For Science Education
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• v.34 no.6
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• pp.601-611
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• 2014

The purpose of this study is to analyze the Korean science magazine, Science Donga providing scientific facts, phenomenons, and issues with infographic for the readers by time series analysis and to search for the application of infographic on the science education. The criteria for the infographic analysis of Science Donga consisted of three categories such as storytelling type, visual perception, and framework level because infographic presents complex information quickly and clearly by integrating various images, words, and graphics. We found that the articles emphasized by including image about science issue have been published from 1986 to 2014. Particularly, after 2008, the articles including infographic sharply rose. So we set up 2008 as $T_c$(Critical time point). The articles including infographic after 2008 have been more variously distributed and frequently used in storytelling types category such as location, time, number, connection, function, and process based infographic, in visual perception of Gestalt Theory such as proximity, similarity, continuation, and closure than before 2008. Lastly, in framework level category, location, time, number, and process based infographic mainly had total range level but function and connection based infographic changed in the framework level. The three features about storytelling type, visual perception, framework level are important changes to influence $T_c$ in the infographic analysis about Science Donga. Through the results of this study, we analyzed the feature of change on infographic from 1986 to 2014. Thus, we hope that the results suggest a basic criteria for making materials including infographic in science education.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.75-85
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• 2000

In existing models in optimization, the crisp data improve has been used in the objective or constraints to derive the optimal solution, Besides, the subjective environments are eliminated because the complex and uncertain circumstances were regarded as Probable ambiguity, In other words those optimal solutions in the existing models could be the complete satisfactory solutions to the objective functions in the Process of application for industrial engineering methods to minimize risks of decision-making. As a result of those, decision-makers in location Problems couldn't face appropriately with the variation of demand as well as other variables and couldn't Provide the chance of wide selection because of the insufficient information. So under the circumstance. it has been to develop the model for the location and size decision problems of logistics facility in the use of the fuzzy theory in the intention of making the most reasonable decision in the Point of subjective view under ambiguous circumstances, in the foundation of the existing decision-making problems which must satisfy the constraints to optimize the objective function in strictly given conditions in this study. Introducing the Process used in this study after the establishment of a general mixed integer Programming(MIP) model based upon the result of existing studies to decide the location and size simultaneously, a fuzzy mixed integer Programming(FMIP) model has been developed in the use of fuzzy theory. And the general linear Programming software, LINDO 6.01 has been used to simulate, to evaluate the developed model with the examples and to judge of the appropriateness and adaptability of the model(FMIP) in the real world.

• Journal of KIISE:Software and Applications
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• v.28 no.9
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• pp.669-680
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• 2001

Genetic Algorithms are optimization algorithm that mimics biological evolution to solve optimization problems. Genetic algorithms provide an alternative to traditional optimization techniques by using directed random searches to locate optimal solutions in complex fitness landscapes. Hybrid genetic algorithm that is combined with local search called learning can sustain the balance between exploration and exploitation. The genetic traits that each individual in the population learns through evolution are transferred back to the next generation, and when this learning is combined with genetic algorithm we can expect the improvement of the search speed. This paper proposes a genetic algorithm based Cellular Learning with accelerated learning capability for function optimization. Proposed Cellular Learning strategy is based on periodic and convergent behaviors in cellular automata, and on the theory of transmitting to offspring the knowledge and experience that organisms acquire in their lifetime. We compared the search efficiency of Cellular Learning strategy with those of Lamarckian and Baldwin Effect in hybrid genetic algorithm. We showed that the local improvement by cellular learning could enhance the global performance higher by evaluating their performance through the experiment of various test bed functions and also showed that proposed learning strategy could find out the better global optima than conventional method.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.9_10
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• pp.429-440
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• 2008

As embedded system becomes more complex, software development becomes more important in the entire design process. Most embedded applications consist of multi -tasks, that are executed in parallel. So, dataflow model that expresses concurrency naturally is preferred than sequential programming language to develop multitask software. For the execution of multitasking codes, operating system is essential to schedule multi-tasks and to deal with the communication between tasks. But, it is needed to execute multitasking code without as when the target hardware platform cannot execute as or target platforms are candidates of design space exploration, because it is very costly to port as for all candidate platforms of DSE. For this reason, we propose the serialized multitasking code generation technique from dataflow specification. In the proposed technique, a task is specified with dataflow model, and generated as a C code. Code generation consists of two steps: First, a block in a task is generated as a separate function. Second, generated functions are scheduled by a multitasking scheduler that is also generated automatically. To make it easy to write customized scheduler manually, the data structure and information of each task are defined. With the preliminary experiment of DivX player, it is confirmed that the generated code from the proposed framework is efficiently and correctly executed on the target system.

• YAKHAK HOEJI
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• v.3 no.1
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• pp.4-9
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• 1957

Effects of antibioties on micro-organism have been reported by many scientists, such as Krampitz and Werkman, Fisher, Gale and Rodwell, Klimick Cavalito and Bailey, Umbreit, etc. On the mechanism by which penicillin act, Fisher(1947), Platt(1947), and Cavallito, considered that penicillin might act on bacteria by inhibiting with the normal function of SH-group of glutathione in the metabolism of the cell. Resenbrance of penicillin to gultathione in structure and the inactivation of penicillin by cysteine make us approve of the above inhibiting theory of SH-group. Galland (1947) and Schmidt (1947) reported that penicillin inhibited the activity of ribonuclease, Phosphatase, and mononucleotidase. Gale (1948) discovered that the gram positive bacteria had lost the power to uptake glutamic acid by ribonucleic acid in the medium contained penicillin: growth of gram positive organism was inhibited by the results that penicillin inhibited the uptake of amino acid byribonucleic acid, acting on ribonucleic acid of gram positive bacteria. Hotchkiss (1950) cultured S. aureus in the medium contained glucose and amino acids, and studied the effect of penicillin on protein synthesis. Peptide formation in living cells was inhibited by penicillin, while amono acid was utilized as before the addition of penicillin. On the otherhand, Binkley (1951) found penicillin interfered hydrolase of glutath one, and Hans (1950) reported penicillin inhibited the transpeptidation. On the machanism by which streptomycin acts. Cohen (1947) reported steptomycin made a irreversible complex with desoxyribonucleic acid, by the fact that desoxyribonucleic acid formed the precipitates with diguanide group of steptomycin. Zeller (1951) reported, on the other hand, streptomycin inhibited diamine oxidease. Geiger (1947) and Umbreit (1949) reported that steptomycin inhibited condensation of oxaloacetate and pyruvate in E. Coli and Oginsky et al (1949) reported steptomycin inhibited oxaloacetate-pyruvate reaction in Kreb's cycle. On the mechanism by which terramycin acts, Hahn & Wisseman (1951) reported that the formation of adaptive enzyme was inhibited by terramycin in E. Coli cultivated in the medium contained loctose, and that the protein synthesis was inhibited by terramycin. However, effects of antibiotics on amino acid metabolism have not been discussed much in spite of its important role in living cells. Especislly, effects of anitibiotics on higher plants have scarcely been reported. Here, to prove the effect of antibiotics on higher plants, and the mechanism by which, through amino acid metabolism, they promote or inhibit growth of plants, amino acids in bean plants treated with penicillin, streptomycin, and terramycin were analyzed by paper chromatography. And to clarify the antagonis of cysteine (as SH-group) against penicillin, through amino acid metabolism, amino acids in bean plants treated with cystene and penicillin, at the same time, were also analyzed.