• Journal of Digital Convergence
• /
• v.11 no.10
• /
• pp.419-429
• /
• 2013

The Wireless sensor network(WSN) consisting of a large number of sensors aims to gather data in a variety of environments. The sensor nodes operate on battery of limited power. so, To extend network life time is major goals of research in the WSN. In this paper, we state the key point of a energy consumption with minimum&load balancing. The proposed protocol guarantee balance of number of cluster member nodes using the node memory threshold and optimization of distribution of cluster head using the optimized clustering method. The results show that the proposed protocol could support the load balancing and high energy efficiency by distributing the clusters with a reasonable number of member nodes. The simulation results show that our schme ensure longer life time in WSN as compare with existing schemes such as LEACH and CBLM.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.11C
• /
• pp.871-876
• /
• 2010

Currently the development of powerline communication technology has become possible due to the high-speed communications. But the communication lines used for power line communication, not wires carrying power wiring is because when sending high-frequency wireless communication system unintentionally be influenced. To compensate for these shortcomings by using notch filters to reduce interference has been studied. Wavelet-based OFDM on the other hand by the method has been used to reduce interference. Wavelet-based OFDM has been used in the existing powerline OFDM scheme using FFT instead of the general structure of the CMFB filters to generate a signal. By doing so, subtly signals per frequency band, cut it, is to realize how efficient highways. It brought a deep filter characteristics, a flexible notch filter can be achieved without an external circuit has an advantage. In this paper, Using Wavelet OFDM powerline communication system is designed and presented the results of simulations.

• Journal of Intelligence and Information Systems
• /
• v.10 no.3
• /
• pp.133-146
• /
• 2004

By the development of the network technology, the types and amount of information that users keep in contact with have been dramatically increased. As a result, users are consuming a lot of time and energy to find needed information. On this, this article presents a new methodology that can efficiently manage their information within small cost by using content-based recommendation method and keyword affinity method. By using keyword affinity method, this methodology solves the content-based recommendation method's weak point that the performance is not good within the environment that the preferences of users are rapidly changing and new contents are created continuously and the accuracy level is low until the information of preferences are sufficiently gathered. This article carried out research on the personal e-mail environment where new information is frequently created and disappeared. Also this article assists folder recommendation for the efficient management of e-mail and verified the methodology mentioned above by an experiment to compare the performance of existing folder recommendation methods with the performance of this new method.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.3
• /
• pp.237-246
• /
• 2019

In order to improve the accuracy of the rating prediction of the recommendation model, not only user-item rating data are used but also consider auxiliary information of item such as comments, tags, or descriptions. The traditional approaches use a word-level model of the bag-of-words for the auxiliary information. This model, however, cannot utilize the auxiliary information effectively, which leads to shallow understanding of auxiliary information. Convolution neural network (CNN) can capture and extract feature vector from auxiliary information effectively. Thus, this paper proposes character-level deep-Convolution Neural Network based matrix factorization (Char-DCNN-MF) that integrates deep CNN into matrix factorization for a novel recommendation model. Char-DCNN-MF can deeper understand auxiliary information and further enhance recommendation performance. Experiments are performed on three different real data sets, and the results show that Char-DCNN-MF performs significantly better than other comparative models.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.34 no.6
• /
• pp.393-401
• /
• 2021

In this paper, we proposed a numerical model based on moment-curvature, to evaluate the resistance of reinforced concrete (RC) members subjected to blast loading. To consider the direct shear failure mode, we introduced a dimensionless spring element based on the empirical direct shear stress-slip relation. Based on the dynamic increase factor equations for materials, new dynamic increase factor equations were constructed in terms of the curvature rate for the section which could be directly applied to the moment-curvature relation. Additionally, equivalent bending stiffness was introduced in the plastic hinge region to consider the effect of bond-slip. To verify the validity of the proposed model, a comparative study was conducted against the experimental results, and the superiority of this numerical model was confirmed through comparison with the analytical results of the single-degree of freedom model. Pressure-impulse (P-I) diagrams were produced to evaluate the resistance of members against bending failure and direct shear failure, and additional parametric studies were conducted.

• Journal of Aerospace System Engineering
• /
• v.16 no.5
• /
• pp.70-77
• /
• 2022

This paper proposes database generation and management system for small-pixelized airborne target recognition. The proposed system has five main features: 1) image extraction from in-flight test video frames, 2) automatic image archiving, 3) image data labeling and Meta data annotation, 4) virtual image data generation based on color channel convert conversion and seamless cloning and 5) HOG/LBP-based tiny-pixelized target augmented image data. The proposed framework is Python-based PyQt5 and has an interface that includes OpenCV. Using video files collected from flight tests, an image dataset for airborne target recognition on generates by using the proposed system and system input.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.21-21
• /
• 2021

효과적인 하천의 유지 및 관리를 위해서는 준설과 각종 수리시설물 영향에 의한 하상변화 양상을 파악하는 것이 필수적이다. 일반적으로 하상변화 분석을 위해서는 하도지형, 하상재료, 유사량 등 현장계측자료가 요구되지만, 대하천 주요 지점이나 정기조사가 이루어지는 일부 지점이 아니라면 하상변화 분석을 위한 현장계측자료가 부족한 실정이다. 따라서 하천을 효율적으로 관리하고 운영하기 위해서는 장래 하상변화 양상을 분석하는데 필요한 충분한 공간적 해상도를 가지는 지형정보와 하상재료 및 유사량 계측자료가 필요하며, 이를 기반으로 중기 및 장기 하상변화를 예측하고 그에 따른 하천관리계획을 수립하게 된다. 본 연구에서는 하도지형 현황자료의 공간해상도가 하상변화의 양적 규모 평가에 미치는 영향을 평가해보고자 한다. 현행 낙동강과 같은 대하천 하도의 하상변동 관련된 조사 및 연구 분석에는 500 m 간격을 기준으로 설정된 기준상의 측선 자료를 이용한다. 본 연구방법으로는 기존 측선을 이용하여 산정된 체적하상변동량과 기준 측선 사이 구간에 대해 측정된 보조측선에 대한 지형정보를 함께 활용하여 산정한 체적하상변동량을 비교함으로써, 하도지형자료의 해상도에 따른 체적변동량 산정결과의 차이와 영향을 평가하였다. 비교를 통해 기존 측선기준 하상변동량 산정치가 실체 하상변동량과 큰 차이를 보일 수 있음을 확인하였다. 따라서 효과적인 하천의 유지 및 관리와 계획 수립을 위해서는 보다 높은 공간해상도의 하도지형자료를 기반으로 한 하상변동 평가 및 분석의 정확도 제고가 필요한 것으로 판단된다. 향후 본 연구 성과를 장래의 하상변화조사의 기초자료로 활용시 상기의 문제점(자료 품질, 추정 자료 사용 등)을 해결하여 모의의 정확성과 정밀성을 제고할 수 있을 것으로 기대되는 바이다.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.44 no.1
• /
• pp.40-50
• /
• 2016

A BIM, which is being applied actively to the construction and civil construction industries, is a technology that can maximize efficiency of various sectors from initial planning and design, construction, and maintenance, to demolition; however, it is in the introductory phase in the field of domestic landscaping. In order to introduce and promote BIM in the field of landscape design, this study developed a prototype of a library and template and analyzed the performance of trial application. For the development of a prototype, annotations and types were analyzed from floor plans of existing small parks, and components of landscape template were deduced. Based on this, play facilities, pergola, and benches were madeintofamily and templates, making automatic design possible. In addition, annotations and tags that are often used in landscape design were made, and a 3D view was materialized through visibility/graphic reassignment. As for tables and quantities, boundary stone table, mounding table, summary sheet of quantities, table of contents, and summary sheet of packaging quantities were grouped and connected with floor plans; regarding landscaping trees, classification criteria and name of trees that are suitable for domestic situations were applied. A landscape template was created to enable the library file format(rfa) that can be mounted on a building with BIM programs. As for problems that arose after the trial application of the prepared template, some CAD files could not be imported; also, while writing tables, the basis of calculation could not be made automatically. Regarding this, it is thought that functions of a BIM program and template need improvement.

• Journal of the Korean Vacuum Society
• /
• v.21 no.4
• /
• pp.205-211
• /
• 2012

We investigated the optical and hydrophobic properties of the deposited silver (Ag) zinc oxide (ZnO) nanorods (NRs) on flexible indium tin oxide (ITO) coated polyethylene terephthalate (PET) substrates (i.e., ITO/PET). The ZnO NRs were grown by an electrochemical deposition using a sputtered ZnO seed layer and the Ag was deposited by using a thermal evaporator. For comparison, the same fabrication process was carried out on the bare ITO/PET without ZnO NRAs. Due to the discrete surface of ZnO NRs, the deposited Ag was formed as nano-scale particles, while the Ag became film-like for bare ITO/PET. In order to control the size and amount of Ag particles, the Ag deposition time was changed from 100 to 600 s. When the deposition time was increased, the Ag particles became larger and denser, and the absorptance was increased. This enhanced absorptance may be due to the localized surface plasmon resonance of Ag particles. Furthermore, the relatively high hydrophobicity was observed for the deposited Ag on the ZnO NRs/ITO/PET. These improved optical and surface properties are expected to be useful for flexible photovoltaic and optoelectronic devices.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.26 no.4
• /
• pp.307-326
• /
• 2021

Real-time sea level observations from tide gauges include missing and erroneous values. Classification as abnormal values can be done for the latter by the quality control procedure. Although the 3𝜎 (three standard deviations) rule has been applied in general to eliminate them, it is difficult to apply it to the sea-level data where extreme values can exist due to weather events, etc., or where erroneous values can exist even within the 3𝜎 range. An artificial intelligence model set designed in this study consists of non-annotated recurrent neural networks and ensemble techniques that do not require pre-labeling of the abnormal values. The developed model can identify an erroneous value less than 20 minutes of tide gauge recording an abnormal sea level. The validated model well separates normal and abnormal values during normal times and weather events. It was also confirmed that abnormal values can be detected even in the period of years when the sea level data have not been used for training. The artificial neural network algorithm utilized in this study is not limited to the coastal sea level, and hence it can be extended to the detection model of erroneous values in various oceanic and atmospheric data.