• Magazine of the Korea Concrete Institute
• /
• v.9 no.1
• /
• pp.105-113
• /
• 1997

The reduction phenomena of concrete compressive strength with the size of cylinders have been very interested in, but till now the adequate. analysis technique is not fixed. Based on the existing research results. the bigger the member size is, the smaller the strengt.h is. However. the real test ~.csults reveal that the wduction rate becomes blunt and there are considerable differences between size offrct law and real results. The punposc. ofthis paper is to propose tho model equat.ion which covers the compressive strength of' cylinder specimens in case of general hight/dialnetcr ratio in terms of the size effect. he effect of maximum aggregate size on the microcrack zone was also studied, and the model equation was proposed by considering the concept of'the characteristic length. These results will also be used to predict the cornprcssivt. stxngth of various sized concrete cores sampled from existing structures.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.47 no.2
• /
• pp.155-167
• /
• 2024

Distribution and logistics industries contribute some of the biggest GDP(gross domestic product) in South Korea and the number of related companies are quarter of the total number of industries in the country. The number of retail tech companies are quickly increased due to the acceleration of the online and untact shopping trend. Furthermore, major distribution and logistics companies try to achieve integrated data management with the fulfillment process. In contrast, small and medium distribution companies still lack of the capacity and ability to develop digital innovation and smartization. Therefore, in this paper, a deep learning-based demand forecasting & recommendation model is proposed to improve business competitiveness. The proposed model is developed based on real sales transaction data to predict future demand for each product. The proposed model consists of six deep learning models, which are MLP(multi-layers perception), CNN(convolution neural network), RNN(recurrent neural network), LSTM(long short term memory), Conv1D-BiLSTM(convolution-long short term memory) for demand forecasting and collaborative filtering for the recommendation. Each model provides the best prediction result for each product and recommendation model can recommend best sales product among companies own sales list as well as competitor's item list. The proposed demand forecasting model is expected to improve the competitiveness of the small and medium-sized distribution and logistics industry.

• Information Systems Review
• /
• v.20 no.4
• /
• pp.43-57
• /
• 2018

We propose network effects upon the investment decision of cloud-based ERP. Using the survey data collected from 82 companies in 2015, we examine whether IT managers have an intention to adopt real options in order to manage the risk of cloud-based ERP investments and how the network effects influence upon the intention to adopt real options. Based on prior literature, we propose a research model with 4 hypotheses. We find partial support of the hypotheses from the empirical analysis: technological risks has a positive impact upon the adoption of real options such as defer, contract, and abandon. In contrast, we find no significant impact of security risks upon real options. We validate positive network effects upon the adoption of real options such as defer, contract, and abandon. This work empirically find that IT managers in Korean middle and small sized firms have an intention to adopt real options when the managers realize economic, technological, and relationship risks and when they expect network effects.

• The Journal of the Acoustical Society of Korea
• /
• v.25 no.7
• /
• pp.312-318
• /
• 2006

The conventional lip-synch system has a two-step process, speech segmentation and recognition. However, the difficulty of speech segmentation procedure and the inaccuracy of training data set due to the segmentation lead to a significant Performance degradation in the system. To cope with that, the connected vowel recognition method using Head-Body-Tail (HBT) model is proposed. The HBT model which is appropriate for handling relatively small sized vocabulary tasks reflects co-articulation effect efficiently. Moreover the 7 vowels are merged into 3 classes having similar lip shape while the system is optimized by employing a class dependent SCHMM structure. Additionally in both end sides of each word which has large variations, 8 components Gaussian mixture model is directly used to improve the ability of representation. Though the proposed method reveals similar performance with respect to the CHMM based on the HBT structure. the number of parameters is reduced by 33.92%. This reduction makes it a computationally efficient method enabling real time operation.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.30 no.2
• /
• pp.147-156
• /
• 2024

The sustainable management and enhancement of marine resources are becoming increasingly important issues worldwide. This study was conducted in response to these challenges, focusing on the development and performance comparison of fish detection and classification models as part of a deep learning-based technique for assessing the effectiveness of marine resource enhancement projects initiated by the Korea Fisheries Resources Agency. The aim was to select the optimal model by training various sizes of YOLOv8-Seg models on a fish image dataset and comparing each performance metric. The dataset used for model construction consisted of 36,749 images and label files of 12 different species of fish, with data diversity enhanced through the application of augmentation techniques during training. When training and validating five different YOLOv8-Seg models under identical conditions, the medium-sized YOLOv8m-Seg model showed high learning efficiency and excellent detection and classification performance, with the shortest training time of 13 h and 12 min, an of 0.933, and an inference speed of 9.6 ms. Considering the balance between each performance metric, this was deemed the most efficient model for meeting real-time processing requirements. The use of such real-time fish detection and classification models could enable effective surveys of marine resource enhancement projects, suggesting the need for ongoing performance improvements and further research.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.1186-1189
• /
• 2005

Focused Ion Beam machining is an attractive approach to produce nano-scale 3D structures. However, like other beam-based manufacturing processes, the redeposition of the sputtered material during the machining deteriorates the geometric accuracy of ion beam machining. In this research a new approach to reduce the geometric error in FIB machining is introduced. The observed redeposition phenomena have been compared with existing theoretical model. Although the redeposition effect has good repeatability the prediction of exact amount of geometric error in ion beam machining is difficult. Therefore, proposed method utilizes process control approach. Developed algorithm measures the redeposition amount after every production cycle and modifies next process plan. The method has been implemented to a real FIB machine and the experimental results demonstrated considerable improvement of five micrometer-sized pocket machining.

• Transactions of the Korean Society of Pressure Vessels and Piping
• /
• v.12 no.1
• /
• pp.11-16
• /
• 2016

Fuel assembly's mechanical characterization test facility (FAMeCT) in KAERI was constructed with upgraded functional features such as increased loading capacity, underwater vibration testing and severe earthquake simulation for extended fuel design guideline. This facility is designed and developed to provide out-pile fuel data for accident analysis model and fuel licensing. Functional tests of FAMeCT were performed to confirm functionality, structural integrity, and validity of newly-built fuel assembly mechanical test facility. Test program includes signal check of data acquisition system, load delivering capacity using real-sized fuel assemblies and a standard loading cylindrical rigid specimen. Fuel assembly's lateral bending test was carried out up to 30 mm of pull-out displacement. Limit case axial compression loading test up to 33 kN was performed to check structural integrity of UCPS (Upper Core Plate Simulator) support frame. Test results show that all test equipment and measurement system have acceptable range of alignment, signal to noise ratio, load carrying capacity limit without loss of integrity. This paper introduces newly constructed fuel assembly's mechanical test facility and summarizes results of functional test for the mechanical test equipment and data acquisition system.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.9
• /
• pp.881-887
• /
• 2015

The hardware-in-the-loop simulation (HILS) of a railway vehicle is crucial for overcoming the limitation of field tests of a railway vehicle. A brake HILS system for a railway vehicle was previously not able to test the performance of a speed-sensing system of a railway vehicle, since wheelset speeds were generated only by computer simulations. In this paper, we present a novel wheelset speed implementation of a brake HILS system for a railway vehicle. Four wheelset speeds of a brake HILS system for a car of a railway vehicle are implemented using four small-sized servomotors, whereas the speed sensors and pole wheels used in the brake HILS system are the actual ones of the railway vehicle. According to the simulated speeds of four wheelsets in the dynamic equations of motion, four servomotors generate wheel speeds in real time, and then the measured wheelset speeds are fed back to the computer simulation model. Moreover, in this paper, we improve the performance of wheelset speed measurement via the T method instead of the M method presently used in the field. The performances of wheelset speed implementation and speed-sensor operation are demonstrated by experimental works using a HILS system.

• Journal of Mechanical Science and Technology
• /
• v.17 no.9
• /
• pp.1268-1275
• /
• 2003

In this paper, a compact 3-DOF mobile microrobot with sub-micron resolution is presented. It has many outstanding features : it is as small as a coin ; its precision is of sub-micrometer resolution on the plane ; it has an unlimited travel range ; and it has simple and compact mechanisms and structures which can be realized at low cost. With the impact actuating mechanism, this system enable both fast coarse motion and highly precise fine motion with a pulse wave input voltage controlled. The 1 -DOF impact actuating mechanism is modeled by taking into consideration the friction between the piezoelectric actuator and base. This modeling technique is extended to simulate the motion of the 3-DOF mobile robot. In addition, experiments are conducted to verify that the simulations accurately represent the real system. The modeling and simulation results will be used to design the model-based controller for the target system. The developed system can be used as a robotic positioning device in the micromanipulation system that determines the position of micro-sized components or particles in a small space, or assemble them in the meso-scale structure.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.1
• /
• pp.20-30
• /
• 2013

An intelligent grid computing architecture is proposed and developed for transient stability constrained total transfer capability evaluation of future smart grid. In the proposed intelligent grid computing architecture, a model of generalized compute nodes with 'able person should do more work' feature is presented and implemented to make full use of each node. A timeout handling strategy called conditional resource preemption is designed to improve the whole system computing performance further. The architecture can intelligently and effectively integrate heterogeneous distributed computing resources around Intranet/Internet and implement the dynamic load balancing. Furthermore, the robustness of the architecture is analyzed and developed as well. The case studies have been carried out on the IEEE New England 39-bus system and a real-sized Chinese power system, and results demonstrate the practicability and effectiveness of the intelligent grid computing architecture.