• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.1247-1249
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• 1993

In this paper, NUDFET(NonUniformly Doped Field Effect Transistor) is presented as an alternative which offers the possibility of reducing the power necessary to operate switching circuits without a substantial loss in speed. The purpose of this NUDFET is to modify the electric field profile in order to cause carrier velocity saturation to occur at a lower voltage than it would occur in the uniformly doped device of the same channel length. The more MESFET and NUDFET circuits are realized, the more accurate model ins the performance of these devices become required. Analytic model ins was replaced by numerical analysis because of the complexity of device configuration. In this paper, FEM is selected because of simpler local mesh refinement and smaller computer memory than FDM. For accurate analysis, this paper has applied the Scharfetter-Gummel(S-G) Scheme and seven-point Gaussian Quadrature rule to assembly of the finite-element stiffness matrices and right-hand side vector of the semiconductor equations.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.3027-3033
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• 2022

Background: In this study, various types of deep-learning models for predicting in vitro radiosensitivity from gene-expression profiling were compared. Methods: The clonogenic surviving fractions at 2 Gy from previous publications and microarray gene-expression data from the National Cancer Institute-60 cell lines were used to measure the radiosensitivity. Seven different prediction models including three distinct multi-layered perceptrons (MLP), four different convolutional neural networks (CNN) were compared. Folded cross-validation was applied to train and evaluate model performance. The criteria for correct prediction were absolute error < 0.02 or relative error < 10%. The models were compared in terms of prediction accuracy, training time per epoch, training fluctuations, and required calculation resources. Results: The strength of MLP-based models was their fast initial convergence and short training time per epoch. They represented significantly different prediction accuracy depending on the model configuration. The CNN-based models showed relatively high prediction accuracy, low training fluctuations, and a relatively small increase in the memory requirement as the model deepens. Conclusion: Our findings suggest that a CNN-based model with moderate depth would be appropriate when the prediction accuracy is important, and a shallow MLP-based model can be recommended when either the training resources or time are limited.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.47-52
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• 2023

With the growing data size and the increased computing load in machine learning, energy-efficient resource planning in IoT systems is becoming increasingly important. In this paper, we suggest a new resource planning policy for real-time workloads that can be fluctuated over time in IoT systems. To handle such situations, we categorize real-time tasks into fixed tasks and variable tasks, and optimize the resource planning for various workload conditions. Based on this, we initiate the IoT system with the configuration for the fixed tasks, and when variable tasks are activated, we update the resource planning promptly for the situation. Simulation experiments show that the proposed policy saves the processor and memory energy significantly.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.2
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• pp.37-52
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• 2010

The main purpose of this study is to examine how place representation is related to the formation of urban parks in Seoul, which began at the end of the 19th century. In order to grasp place representation, the hypothesis of this study is that most urban parks are undertaken with the idea of monumentality and symbolism or memories of the place itself. Diverse ways of representation through physical or non-physical aspects of symbolism, monumentality, and place memory are summarized as follows. First, in the case of the physical aspects of representation in the parks, monumentality and symbolism are expressed mostly through monuments or statues. In the case that the intention of the park is commemorative, celebrative elements are more actively utilized. In other cases, symbolic sculptures or statues, which are randomly designated by the government, are so often used regardless of the overarching concept of the urban park. In addition, in the case of place memory, monumentality or symbolism are commonly represented through bronze statues or partial remnants of the past. Recently, however, the site in itself has been constructed to coordinate the memories of a certain place into the configuration of the park. Secondly, in relation to the non-physical representation elements, many urban parks tend to reveal monumentality or symbolism through the names they are given. Recently, this tendency has significantly dropped, but some places of parksare frequently denominated in consideration of place memory. In the case of events held in parks, parks which were constructed in the beginning of the park movement, such as Tapgol Park, hold certain events to commemorate certain causes that took place in those days. On the other hand, the main purpose of recently-constructed urban parks relating to place memory is to encourage citizens to participate in events in a variety of ways.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.54-62
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• 2015

Although NAND flash-based SSD (Solid-State Drive) provides superior performance in comparison to HDD (Hard Disk Drive), it has a major drawback in write endurance. As a result, the lifetime of SSD is determined by the workload and thus it becomes a big challenge in current technology trend of such as the shifting from SLC (Single Level Cell) to MLC (Multi Level cell) and even TLC (Triple Level Cell). Most previous studies have dealt with wear-leveling or improving SSD lifetime regarding hardware architecture. In this paper, we propose the optimal configuration of host I/O stack focusing on file system, I/O scheduler, and link power management using JEDEC enterprise workloads in terms of WAF (Write Amplification Factor) which represents the efficiency perspective of SSD life time especially for host write processing into flash memory. Experimental analysis shows that the optimum configuration of I/O stack for the perspective of SSD lifetime is MinPower-Dead-XFS which prolongs the lifetime of SSD approximately 2.6 times in comparison with MaxPower-Cfq-Ext4, the best performance combination. Though the performance was reduced by 13%, this contributions demonstrates a considerable aspect of SSD lifetime in relation to I/O stack optimization.

• Journal of the Mineralogical Society of Korea
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• v.26 no.1
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• pp.19-25
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• 2013

Recent progress in Martian exploration identified hematite as the major candidate for the strong magnetic anomalies observed in Martian lithosphere. In the present study, grain-size dependence of thermoremanent magnetization and low-temperature stability of room-temperature saturation isothermal remanent magnetization (RTSIRM) were monitored using synthetic hematites. For hematite, the antiferromagnetic spin configuration is re-arranged from being perpendicular to the c-axis to be parallel to the c-axis below the Morin transition ($=T_M$). A large fraction of RTSIRM is demagnetized at $T_M$ (= 260 K) during zero-field cooling from 300 K to 10 K. About 37% of the initial RTSIRM is recovered on warming from 10 K to 300 K. Shallow Martian subsurface at 1~2 km depth would experience low-temperature cooling-warming of $T_M$ because average Martian surficial temperature is about 220 K. However in most Martian lithosphere whose temperatures are higher than 260 K, the very stable magnetic memory of hematite could be a contributor to Martian magnetic anomalies.

• Journal of Korea Entertainment Industry Association
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• v.13 no.2
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• pp.79-91
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• 2019

In the entertainment industry, risk management is crucial for securing competitiveness due to the risk of investment. The competitiveness of contents is reinforced when external factors such as industrial environment and internal factors centering on involving mechanism are simultaneously provided. The involving mechanism is a form of cognitive response behavior of the audience and occurs through signal processing of the brain when watching the image contents. The signal processing of the brain related to the contents watching is mainly performed in the working memory area, and in the case of the captivating movie, the information other than the contents transmitted to the audience is blocked to generate a temporary dissociation state. A dissociation state similar to a symptom such as hypnosis or amnesia occurs when the audience's level of involving is high. On the other hand, contents information in which the audience is concentrating his attention is used intensively for constructing future thinking through an episodic buffer while the inflow of external information is relatively blocked or delayed. The spectator's future thinking configuration takes the form of a hypothesis-forming activity and is based on the predictability of the brain. When these hypothesized behaviors correspond to the problem solving simulation of story and predictability which is an evolutionary function of the brain, the audience' s brain is involved in the contents at a high level. In order for the act to be effective, the factors such as the background of the hypothesis, the subject of the hypothesis, the internal information of the person, the type and position and quantity of the hypothesis information, and the hypothesis relevance and type of information are important. Based on these factors, analysis of the Kim Eun Sook Drama 'Goblin' shows that the above elements are operated in a very organic and meaningful way.

• Journal of IKEEE
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• v.16 no.3
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• pp.235-243
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• 2012

In this study, we developed two legged multi-joint robot by using wireless servo motor that was applied by wireless sensor network technology, which is widely used recently, and performed an experiment of walking method of two legged multi-joint robot. We constructed the star network with servo motors which were used at each joint of two-legged robot. And we designed the robot for operation by transmission of joint control signal from main control system or by transmission of the status of each joint to the main control system, so it operates with continuously checking the status of joints at same time. We developed the humanoid robot by using wireless digital servo motor which is different from existing servo motor control system, and controlled it by transmitting the information of angles and speeds of robot joints to the motor(node) as a feedback through main control system after connecting power and setting up the IDs to each joint. We solved noisy problem generated from wire and wire length to connection point of the control device by construction of the wireless network instead of using existing control method of wiring, and also solved problem of poor real time response to gait motion by controlling the position with continuous transmission of control signals to each joint. And we found that the effective control of robot is able by performing the simulation on walking motion in advance with the developed control algorithm which was downloaded into installed memory. Also we performed the stable walking with two-legged robot by attaching pressure sensor to robot sole. And we examined the robot gait operated by application of calculated algorithm on robot movement to each joint. In this study, we studied the method of controlling robot gait motion by using wireless servo motors and measured the torque applied to each joint, and found that the developed wireless servo motor by ZigBee sensor network offers easier control of two legged robot gait and better circuit configuration of it than the existing wired control system could do.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2577-2596
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• 2013

In this paper, we present an Energy-Aware Self-Stabilizing Distributed Clustering protocol based on message-passing model for Ad Hoc networks. The latter does not require any initialization. Starting from an arbitrary configuration, the network converges to a stable state in a finite time. Our contribution is twofold. We firstly give the formal proof that the stabilization is reached after at most n+2 transitions and requires at most $n{\times}log(2n+{\kappa}+3)$ memory space, where n is the number of network nodes and ${\kappa}$ represents the maximum hops number in the clusters. Furthermore, using the OMNeT++ simulator, we perform an evaluation of our approach. Secondly, we propose an adaptation of our solution in the context of Wireless Sensor Networks (WSNs) with energy constraint. We notably show that our protocol can be easily used for constructing clusters according to multiple criteria in the election of cluster-heads, such as nodes' identity, residual energy or degree. We give a comparison under the different election metrics by evaluating their communication cost and energy consumption. Simulation results show that in terms of number of exchanged messages and energy consumption, it is better to use the Highest-ID metric for electing CHs.