• Geomechanics and Engineering
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• v.34 no.5
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• pp.547-559
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• 2023

We evaluated the applicability of machine learning techniques and the Kuz-Ram model for predicting the mean fragmentation size in open-pit mines. The characteristics of the in-situ rock considered here were uniaxial compressive strength, tensile strength, rock factor, and mean in-situ block size. Seventy field datasets that included these characteristics were collected to predict the mean fragmentation size. Deep neural network, support vector machine, and extreme gradient boosting (XGBoost) models were trained using the data. The performance was evaluated using the root mean squared error (RMSE) and the coefficient of determination (r²). The XGBoost model had the smallest RMSE and the highest r² value compared with the other models. Additionally, when analyzing the error rate between the measured and predicted values, XGBoost had the lowest error rate. When the Kuz-Ram model was applied, low accuracy was observed owing to the differences in the characteristics of data used for model development. Consequently, the proposed XGBoost model predicted the mean fragmentation size more accurately than other models. If its performance is improved by securing sufficient data in the future, it will be useful for improving the blasting efficiency at the target site.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.283-286
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• 2001

전통의 자기 디스크 형태 저장 장치로의 접근 지연 시간을 줄이고자, 최근에 서로 네트워크로 연결된 컴퓨터간의 메모리 자원들을 파일을 저장하는 장치로써 활용해 볼 수 있는 가상 장치(Network RamDisk)가 개발되었다. 이 시스템은 메모리 공간을 제공해 주는 서버의 노드들이 패리티 그룹(parity group)을 이루는 일종의 software RAID 시스템으로 한 서버의 노드 crash 에 대해 대응하는 것을 고려하지 않아 제 이의 서버가 노드 crash, 프로세스 crash 혹은 데이터 손실을 발생시키면 완전히 데이터를 잃어버리는, 신뢰성이 낮은 문제점이 있다. 본 논문은 클라이언트가 서버측의 노드 crash를 적절히 감지하고 새로운 서버로 fail over 할 수 있는 여러 가지 기법들을 설계하고 구현하였다. 또한 서버 풀(server pool)이라는 가상의 공간을 따로 관리하여 서버들에 대한 메모리 자원 요구 부하를 균등히 분산 시키는 효과도 얻도록 하였다.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.73-80
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• 2023

The recent growth in the use of mobile devices has contributed to increased computing and storage requirements. Cloud computing has been used over the past decade to cater to computational and storage needs over the internet. However, the use of various mobile applications like Augmented Reality (AR), M2M Communications, V2X Communications, and the Internet of Things (IoT) led to the emergence of mobile cloud computing (MCC). All data from mobile devices is offloaded and computed on the cloud, removing all limitations incorporated with mobile devices. However, delays induced by the location of data centers led to the birth of edge computing technologies. In this paper, we discuss one of the edge computing technologies, i.e., cloudlet. Cloudlet brings the cloud close to the end-user leading to reduced delay and response time. An algorithm is proposed for scheduling tasks on cloudlet by considering VM's load. Simulation results indicate that the proposed algorithm provides 12% and 29% improvement over EMACS and QRR while balancing the load.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.6
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• pp.213-219
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• 2004

This paper describes the developmnet of a web-based boiler controller which can be in parallel operated with an existing boiler controller. The web-based boiler controller mainly consists of RTL8019AS NIC and TS80C32 microcontroller. In order to communicate over the Internet, we need to develop network driver, IP, TCP, UDP, ICMP, and HTTP. For a specific application like web-boiler controller, we have proposed a common global data buffer algorithm to minimize the RAM memory usage. Finally, the correctness and performance of the protocols are tested and verified using CommView and Dummynet. The development is satisfactorily operated only for few hundreds of bytes of RAM usage without sacrificing interoperability between hosts.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3399-3406
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• 2015

NRD(Network RamDisk) is a scheme which allows a system to use the memory of the remote systems just as his own block device via networking. Basically, it consists of a client requesting an NRD access and server providing the NRD. In this paper, we describe the design, implementation and experiment of the block device driver for accessing the NRD in the Linux kernel(2.6) level. First of all, we have analyzed the flow of processing the requests for accessing the block devices in the traditional Linux kernel and figured out the additional functions required for supporting the NRD. Then we have designed and implemented the device diver of NRD client and NRD server for providing these functions. Finally, we have established a NRD server system, and reviewed its functional feasibility by experimenting the requests of NRD access through the NRD device driver implemented on a NRD client.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1251-1254
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• 2003

In this paper, Experience Sensitive Cumulative Neural Network (ESCNN) is introduced, which can cumulate the same or similar experiences. As the same or similar training patterns are cumulated in the network, the system recognize more important information in the training patterns. The functions of forgetting less important informations and attending more important informations resided in the training patterns are surveyed and implemented by simulations. The system behaves well under the noisy circumstances due to its forgetting and/or attending properties, even in 50 percents noisy environments. This paper also describes the creation of the generalized patterns for the input training patterns.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2169-2177
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• 2015

This paper proposes a new pattern matching module to overcome the increased runtime of previous algorithm using RAM, which was designed to overcome cost limitation of hash-based algorithm using CAM (Content Addressable Memory). By adopting Merge FSM algorithm to reduce the number of state, the proposed module contains state block and entry block to use in RAM. In the proposed module, one input string is compared with multiple entry strings simultaneously using entry block. The effectiveness of the proposed pattern matching unit is verified by executing Snort 2.9 rule set. Experimental results show that the number of memory reads has decreased by 15.8%, throughput has increased by 47.1%, while memory usage has increased by 2.6%, when compared to previous methods.

• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.675-696
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• 2023

Terpenoids, also referred to as terpenes, are a large family of naturally occurring chemical compounds present in the essential oils extracted from medicinal plants. In this study, a nondestructive methodology was created by combining ATR-FT-IR (attenuated total reflectance-Fourier transform infrared), and Raman spectroscopy for the terpenoids assessment in medicinal plants essential oils from ten different geographical locations. Partial least squares regression (PLSR) and support vector regression (SVR) were used as machine learning methodologies. However, a deep learning based model called as one-dimensional convolutional neural network (1D CNN) were also developed for models comparison. With a correlation coefficient (R²) of 0.999 and a lowest RMSEP (root mean squared error of prediction) of 0.006% for the prediction datasets, the SVR model created for FT-IR spectral data outperformed both the PLSR and 1 D CNN models. On the other hand, for the classification of essential oils derived from plants collected from various geographical regions, the created SVM (support vector machine) classification model for Raman spectroscopic data obtained an overall classification accuracy of 0.997% which was superior than the FT-IR (0.986%) data. Based on the results we propose that FT-IR spectroscopy, when coupled with the SVR model, has a significant potential for the non-destructive identification of terpenoids in essential oils compared with destructive chemical analysis methods.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.436-437
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• 2018

This paper describes the structure and design of a modular DC/DC converter for connecting DC sources such as battery, solar cell, etc. to DC distribution network. The modular converter structure of IPOS type and the optimal design and implementation of the unit converter cell are discussed.

• ETRI Journal
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• v.27 no.3
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• pp.334-336
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• 2005

We improved the performance of the spectrum-sliced light source for wavelength-division-multiplexed passive optical networks by employing a Fabry-Perot laser diode(FP-LD). We found that the FP-LDs can suppress the intensity noise as significantly as using a gain-saturated semiconductor optical amplifier. The transmission characteristics were measured and analyzed in both conditions with and without employing an FP-LD.