• Journal of the Society of Naval Architects of Korea
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• v.56 no.6
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• pp.488-496
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• 2019

The estimation of block erection work time at a dock is one of the important factors when establishing or managing the total shipbuilding schedule. In order to predict the work time, it is a natural approach that the existing block erection data would be used to solve the problem. Generally the work time per unit is the product of coefficient value, quantity, and product value. Previously, the work time per unit is determined statistically by unit load data. However, we estimate the work time per unit through work time coefficient value from series ships using machine learning. In machine learning, the outcome depends mainly on how the training data is organized. Therefore, in this study, we use 'Feature Engineering' to determine which one should be used as features, and to check their influence on the result. In order to get the coefficient value of each block, we try to solve this problem through the Ensemble learning methods which is actively used nowadays. Among the many techniques of Ensemble learning, the final model is constructed by Stacking Ensemble techniques, consisting of the existing Ensemble models (Decision Tree, Random Forest, Gradient Boost, Square Loss Gradient Boost, XG Boost), and the accuracy is maximized by selecting three candidates among all models. Finally, the results of this study are verified by the predicted total work time for one ship among the same series.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.3A
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• pp.267-277
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• 2011

Like other wireless network protocols, IEEE 802.15.4 adopts CA (Collision Avoidance)algorithm to avoid the early collision of a new packet by randomizing its first transmission time rather than its immediate delivery. The traditional CA scheme of IEEE 802.15.4, however, selects the random access time from the predetermined range without considering the degree of current congestion. It probably causes either a long delay to settle in the suitable range for the current network load or frequent clashes especially during the long lasting heavy traffic period. This paper proposes an ACA(Adaptive Collision Avoidance) algorithm adapting the initial backoff range to the undergoing collision variations. It also introduces a mathematical model to predict the performance of ACA algorithm added to IEEE 802.15.4. With only small deviations from corresponding simulations, our analytical model shows that ACA technique can improve the throughput of IEEE 802.15.4 by up-to 41% maximally in addition to shortening the packet delays.

• Journal of the Korean Society of Clothing and Textiles
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• v.4 no.1_2
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• pp.25-33
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• 1980

The studies on shrinkage and characteristics of the weft knitted fabrics were investigated under the various dry and wet treating conditions. Various relaxation values were found out according to treating conditions. The characteristics of knitted fabrics such as shrinkage rate, thickness, spirality, elongation and recovery were also measured. The used knitting yams were OE (open-end) cotton and POY (pre-oriented yarn)-DTY (draw textured yam) polyester. The conclusions obtained in this study are as follows. 1. In case of dry relaxation little change of Ks values was seen with increasing time after 48 hours. So it was found that relaxation shrinkage of dry relaxation reached its maximal state in about 48 hours. 2. In case of wet relaxation, higher Ks values were observed, in comparision with those of dry one and higher shrinkage rates were also observed. But when experimental temperature was constant, sudden marked increases in Ks values and shrinkage rates appeared through the initial 4 hours, and after that time little change was seen in them. 3. As Ks value increases, thickness also increased. But thickness showed to some degree stability around Ks value 23. 4. As Ks value increases, spirality values also increased gradually. But little change of spirality values was observed above a certain Ks values (cotton 22.5, polyester 21.5). 5. As Ks value increases, the elongation decreased under a certain load, and the recovery was random.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.3
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• pp.307-313
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• 2009

In general, pyroshock is generated from the actuation of separation devices for several stage, fairing, and satellite separation in the flight of a launch vehicle. During these events, transient vibration phenomenon called pyroshock, which shows large acceleration in the high frequency range, occurs and it can result in the malfunction of electronic components which is equipped inside the launch vehicle or satellite. In this paper, mesh washer isolators made out of SMA were introduced for the isolation of pyroshock. One type of isolator primarily used pseudoelastic characteristics of SMA and the other type of isolator used shape memory effect of SMA. For the study of basic load-displacement relationship of each SMA isolator, compressive loading tests were performed and the results showed the capability of the isolator itself. Pyroshock isolation tests were followed and verified the outstanding isolation performance of isolator. In addition, random vibration tests were also performed and checked the dynamic characteristics of each SMA isolator.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1202-1211
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• 2018

In this paper, induction machine operation efficiency and torque is improved using Machine Learning based Gene Optimization (ML-GO) Technique is introduced. Optimized Genetic Algorithm (OGA) is used to select the optimal induction machine data. In OGA, selection, crossover and mutation process is carried out to find the optimal electrical machine data for induction machine design. Initially, many number of induction machine data are given as input for OGA. Then, fitness value is calculated for all induction machine data to find whether the criterion is satisfied or not through fitness function (i.e., objective function such as starting to full load torque ratio, rotor current, power factor and maximum flux density of stator and rotor teeth). When the criterion is not satisfied, annealed selection approach in OGA is used to move the selection criteria from exploration to exploitation to attain the optimal solution (i.e., efficient machine data). After the selection process, two point crossovers is carried out to select two crossover points within a chromosomes (i.e., design variables) and then swaps two parent's chromosomes for producing two new offspring. Finally, Adaptive Levy Mutation is used in OGA to select any value in random manner and gets mutated to obtain the optimal value. This process gets iterated till finding the optimal value for induction machine design. Experimental evaluation of ML-GO technique is carried out with performance metrics such as torque, rotor current, induction machine operation efficiency and rotor power factor compared to the state-of-the-art works.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.3
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• pp.577-585
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• 2004

System Packet Interface Level 4 Phase(SPI-4.2) is an interface for packet and cell transfer between a physical layer(PHY) device and a link layer device, for aggregate bandwidths of OC-192 ATM and Packet Over Sonet/SDH(POS), as well as 10Gbps Ethernet applications. In this paper, we performs the research for SPI-4.2. Also we analyze the performance of SPI-4.2 interface module after modeling using C programming language. This paper shows that SPI-4.2 interface module with 512-word FIFO depth is able to be adapted for the offered loads to 97％ in random uniform traffic and 94％ in bursty traffic with bursty length 32. SPI-4.2 interface module can experience an performance degradation due to heavy overhead when it massively receives small size packets less than 14-byte. SPI-4.2 interface module is suited for line cards in gigabit/terabit routers, and optical cross-connect switches, and SONET/SDH-based transmission systems.

• Journal of Korean Society of Steel Construction
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• v.19 no.2
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• pp.211-221
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• 2007

A structural reliability analysis of fatigue truck model for fatigue failure of highway steel bridges was performed by applying the Miner's fatigue damage rule expressed as a function of various random variables affecting fatigue damage. Among the variables, the statistical parameters for equivalent moment, impact factor, and loadometer were obtained by analyzing recently measured domestic traffic data, whereas the parameters on fatigue strength, girder distribution factor, and headway factor of the measured data available in the literature were used. The effects of various fatigue truck models, fatigue life, ADTT, fatigue detail category, loadometer, and gross vehicle weight of fatigue truck on the reliability index of fatigue damage were analyzed. It is expected that the analytical results presented herein can be used as a basic background material in the calibration of both fatigue design truck and fatigue load factor of LRFD specification.

• Journal of the Korean Society of Safety
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• v.34 no.5
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• pp.87-94
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• 2019

This study deals with the reliability analysis approach of the temporary structure that can consider the uncertainty in rotational stiffness at the joints of the members, for which the semi-rigid connections are modelled as rotational spring and its coefficient is treated as a random variable following uniform distribution. In addition, this study introduces a computational procedure of the effective length coefficient for more accurate buckling load according to connection conditions of the supporting members attached to the joint. From the results of this study, it can be seen that the failure probability of the joint-hinge model (Case 1) presented in the design standard is higher than that of the practical model (Case 5) considering the rotational stiffness at the joints. This implies that the design standard leads to a conservative design of the temporary structure. The results also confirmed that the failure probability of the vertical member, i.e., the most critical member, can be further reduced when the base connection is provided with a fixed end. The comparative results between FORM, SORM and MCS further demonstrated that FORM can have a high level of numerical efficiency while ensuring the accuracy of the solution, compared with SORM and MCS. Based on these results, the proposed approach can be used as an accurate and efficient reliability analysis method of the three dimensional temporary structure.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.8
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• pp.661-669
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• 2021

A mechanical stiffener has been mainly applied on a PCB to secure fatigue life of a solder joint of an electronic components in spaceborne electronics by minimizing bending displacement of the PCB. However, it causes an increase of mass and volume of the electronics. The high damping PCB implemented by multi-layered viscoelastic tapes of a previous research was effective for assuring the fatigue life of the solder joint, but it also has a limitation to decrease accommodation efficiency for the components on the PCB. In this study, we proposed high damping PCB with a multi-layered superelastic shape memory alloy stiffener for spatialminimized, light-weighted, high-integrated structure design of the electronics. To investigate the basic characteristics of the proposed PCB, a static load test, a free vibration test were performed. Then, the high damping characteristic and the design effectiveness of the PCB were validated through a random vibration test.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.2
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• pp.87-96
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• 2019

Low power issue is one of the most critical problems in the Internet of Things (IoT), which are powered by battery. To solve this problem, various approaches have been presented so far. In this paper, we propose a method to reduce the power consumption by reducing the numbers of accesses into the flash memory consuming a large amount of power for on-chip software execution. Our approach is based on using cooperative logging structure to distribute the sampling overhead in single sensor node to adjacent nodes in case of rare-event applications. The proposed algorithm to identify event occurrence is newly introduced with negative feedback method by observing difference between past data and recent data coming from the sensor. When an event with need of flash access is determined, the proposed approach only allows access to write the sampled data in flash memory. The proposed event detection algorithm (EDA) result in 30% reduction of power consumption compared to the conventional flash write scheme for all cases of event. The sampled data from the sensor is first traced into the random access memory (RAM), and write access to the flash memory is delayed until the page buffer of the on-chip flash memory controller in the micro controller unit (MCU) is full of the numbers of the traced data, thereby reducing the frequency of accessing flash memory. This technique additionally reduces power consumption by 40% compared to flash-write all data. By sharing the sampling information via LoRa channel, the overhead in sampling data is distributed, to reduce the sampling load on each node, so that the 66% reduction of total power consumption is achieved in several IoT edge nodes by removing the sampling operation of duplicated data.