Journal of the Korean Institute of Telematics and Electronics S
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v.35S
no.10
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pp.144-155
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1998
The array weights that will maximize the SNR for any type of noise environment are determined by the function of the antenna design configuration and the directions of receiving target and interference signals. The conventional SLCs(sidelobe cancellers) using the SNR maximization perform worst from the saturation of the receiving system of main channel when the main antenna has pattern with high gain at the arrival angle of strong interference. In this paper, the new SLC is accomplished by using two independent antenna architecture. Main antenna is implemented with adaptive nulling, which is used for rejecting high-power interference primarily. Auxiliary antenna is realized with adaptive array for receiving interference signal to be suppressed completely, which has a characteristics of sufficient gain for every direction. The new SLC is implemented with above both antennas. We show that the new SLC, which consists of the adaptive nulling main antenna and the adaptive array auxiliary antenna, is useful in reducing the effect of strong interference like jammer, because the adaptive nulling at main antenna prevents its receiver and signal processor for saturation by strong interference. The proposed SLC has improved SNR over the conventional SLCs. The improved SNR at sidelobe region is typically more than 7 dB for a given test signal. Moreover, it improves the SNR of about 20 dB under strong interference at mainlobe.
Kim Ik-Kyun;Oh Jin-Tae;Jang Jong-Soo;Sohn Sung-Won;Han Ki-Jun
Journal of the Institute of Electronics Engineers of Korea TC
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v.43
no.7
s.349
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pp.93-103
/
2006
Network solutions for protecting against worm attacks that complement partial end system patch deployment is a pressing problem. In the content-based worm filtering, the challenges focus on the detection accuracy and its performance enhancement problem. We present a worm filter architecture using the bloom filter for deployment at high-speed transit points on the Internet, including firewalls and gateways. Content-based packet filtering at multi-gigabit line rates, in general, is a challenging problem due to the signature explosion problem that curtails performance. We show that for worm malware, in particular, buffer overflow worms which comprise a large segment of recent outbreaks, scalable -- accurate, cut-through, and extensible -- filtering performance is feasible. We demonstrate the efficacy of the design by implementing it on an Intel IXP network processor platform with gigabit interfaces. We benchmark the worm filter network appliance on a suite of current/past worms, showing multi-gigabit line speed filtering prowess with minimal footprint on end-to-end network performance.
International Journal of Naval Architecture and Ocean Engineering
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v.10
no.6
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pp.794-802
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2018
The ice resistance series charts for icebreaking ships were developed through a series of systematic model tests in the ice tank of the Korean Research Institute of Ship and Ocean Engineering (KRISO). Spencer's (1992) component-based scaling system for ship-ice model tests was applied to extend the model ship correlations. Beam to draft ratio (B/T), length to beam ratio (L/B), block coefficient ($C_B$) and stem angle (${\alpha}$) were selected as geometric parameters for hull form development. The basic hull form (S1) of twin pod type with B/T of 3.0, L/B of 6.0, $C_B$ of 0.75 and stem angle of $25^{\circ}$ was generated with a modern hull design concept. A total of 13 hulls were designed varying the geometric parameters; B/T of 2.5 and 3.5, L/B of 5.0 and 7.0, $C_B$ from 0.65 to 0.85 in intervals of 0.05, and 5 stem angles from $15^{\circ}$ to $35^{\circ}$. Ice resistance tests were first carried out with the basic hull form in level ice with suitable speed. Four more tests for $C_B$ variations from 0.65 to 0.85 were conducted and two more for beam to draft and length to beam ratios were also performed to study the effect of the geometric parameters on ice resistance. Ice resistance tests were summarized using the volumetric coefficient, $C_V$ ($={\nabla}/L^3$), instead of L/B and $C_B$ variations. Additional model tests were also carried out to account for the effect of the stem angle, ice thickness and ice strength on ice resistance. In order to develop the ice resistance series charts with a minimum number of experiments, the trends of the ice resistance obtained from the experiments were assumed to be similar for other model ship with different geometric parameters. A total of 18 sheets composed of combinations of three different beam to draft ratios and six block coefficients were developed as a parameter of $C_V$ in the low speed regions. Three correction charts were also developed for stem angles, ice thickness and ice strength respectively. The charts were applied to estimate ice resistance for existing icebreaking ships including ARAON, and the results were satisfactory with reasonable accuracy.
The Journal of Korean Institute of Communications and Information Sciences
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v.40
no.2
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pp.397-407
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2015
In this paper, we designed 1 chip IC for 3-axis gyroscope and 3-axis accelerometer used for various IoT/M2M mobile devices such as smartphone, wearable device and etc. We especially focused on analysis of gyroscope noise and proposed new architecture for removing various noise generated by gyroscope MEMS and IC. Gyroscope, accelerometer and geo-magnetic sensors are usually used to detect user motion or to estimate moving distance, direction and relative position. It is very important element to designing a low noise IC because very small amount of noise may be accumulated and affect the estimated position or direction. We made a mathematical model of a gyroscope sensor, analyzed the frequency characteristics of MEMS and circuit, designed a low noise, compact and low power 1 chip 6-axis inertial sensor IC including 3-axis gyroscope and 3-axis accelerometer. As a result, designed IC has 0.01dps/${\sqrt{Hz}}$ of gyroscope sensor noise density.
Park, Jimin;Lee, Jung-Ho;Park, Yong-Sun;Jin, Kyoungsuk;Nam, Ki Tae
Proceedings of the Korean Vacuum Society Conference
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2013.08a
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pp.91-91
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2013
Imagine a world where we could biomanufacture hybrid nanomaterials having atomic-scale resolution over functionality and architecture. Toward this vision, a fundamental challenge in materials science is how to design and synthesize protein-like material that can be fully self-assembled and exhibit information-specific process. In an ongoing effort to extend the fundamental understanding of protein structure to non-natural systems, we have designed a class of short peptides to fold like proteins and assemble into defined nanostructures. In this talk, I will talk about new strategies to drive the self-assembled structures designing sequence of peptide. I will also discuss about the specific interaction between proteins and inorganics that can be used for the development of new hybrid solar energy devices. Splitting water into hydrogen and oxygen is one of the promising pathways for solar to energy convertsion and storage system. The oxygen evolution reaction (OER) has been regarded as a major bottleneck in the overall water splitting process due to the slow transfer rate of four electrons and the high activation energy barrier for O-O bond formation. In nature, there is a water oxidation complex (WOC) in photosystem II (PSII) comprised of the earthabundant elements Mn and Ca. The WOC in photosystem II, in the form of a cubical CaMn4O5 cluster, efficiently catalyzes water oxidation under neutral conditions with extremely low overpotential (~160 mV) and a high TOF number. The cluster is stabilized by a surrounding redox-active peptide ligand, and undergo successive changes in oxidation state by PCET (proton-coupled electron transfer) reaction with the peptide ligand. It is fundamental challenge to achieve a level of structural complexity and functionality that rivals that seen in the cubane Mn4CaO5 cluster and surrounding peptide in nature. In this presentation, I will present a new strategy to mimic the natural photosystem. The approach is based on the atomically defined assembly based on the short redox-active peptide sequences. Additionally, I will show a newly identified manganese based compound that is very close to manganese clusters in photosystem II.
In this paper, we introduce our experience for designing and implementing a media manager in the Integrated Streaming Service Architecture (ISSA) developed by the authors. The media manager is regarded as a necessary module in the ISSA framework for the following reasons. It realizes that from which locations of the media source devices, the media streams are coming. Once it knows where the origin is, the media manager should recognizes what types of stream are. After that, it performs how to chose an appropriate CODEC to handle the recognized input streams efficiently, and what type of media playback device should be selected. In order to do such a job efficiently, the proposed media manager consists of two modules source module and sink module. The major role of a media source module is to make an abstraction for the media streams that are coming from various types of media device. This, in consequence, enables a media manager to consistently handle tlle media streams without considering wherever they come from. On the other hand, the media sink module distributes the input streams to an appropriate media device to playback. One of the remarkable virtues of the proposed media manager is an ability to supporting high value-added database services since it provides an interface between the ISSA and real-time multimedia database. Also, it provides the RTP!RTSP source filter and Winamp gateway modules which allow the flexibility to the system. Moreover, the media manager can adopt any types of new media which in fact will provide scalability to the ISSA.
Journal of the Korea institute for structural maintenance and inspection
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v.23
no.3
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pp.143-149
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2019
In this study, a U-shape composite beam was developed to be effectively used for a steel parking lot which is 8m or lower in height. When the U-shape composite beam was applied to a steel parking lot, essential considerations were story-height and long-span. In addition, due to the mixed structural system with reinforced concrete and steel material, the U-shape composite beam needed to have a structural integrity and reliable performance over demand capacity. The main objective of this study was to investigate the performance of the structure consisting of the reinforced concrete (RC) slab and U-shape beam. A U-shape composite beam generally used at a parking lot served as a control specimen. Four specimens were tested under four-point bending. To calculate theoretical values, strain gauges were attached to rebar, steel plate, and concrete surface in the middle of the specimens. As the results, initial yielding strength of the control specimen occurred at the bottom of the U-shaped steel. After yielding, the specimen reached the maximum strength and the RC slab concrete was finally failed by concrete crush due to compressive stress. The structural performance such as flexural strength and ductility of the specimen with the increased beam depth was significantly improved in comparison with the control specimen. Furthermore, the design of the U-shape composite beam with the consideration of flexural strength and ductility was effective since the structural performance by a negative loading was relatively decreased but the ductile behavior was evidently improved.
Recently, machine learning technology has had a significant impact on society, particularly in the medical, manufacturing, marketing, finance, broadcasting, and agricultural aspects of human lives. In this paper, we study how to apply machine learning techniques to foods, which have the greatest influence on the human survival. In the field of Smart Farm, which integrates the Internet of Things (IoT) technology into agriculture, we focus on optimizing the crop growth environment by monitoring the growth environment in real time. KT Smart Farm Solution 2.0 has adopted machine learning to optimize temperature and humidity in the greenhouse. Most existing smart farm businesses mainly focus on controlling the growth environment and improving productivity. On the other hand, in this study, we are studying how to apply machine learning with respect to harvest time so that we will be able to harvest fruits of the highest quality and ship them at an excellent cost. In order to apply machine learning techniques to the field of smart farms, it is important to acquire abundant voluminous data. Therefore, to apply accurate machine learning technology, it is necessary to continuously collect large data. Therefore, the color, value, internal temperature, and moisture of greenhouse-grown fruits are collected and secured in real time using color, weight, and temperature/humidity sensors. The proposed FPSML provides an architecture that can be used repeatedly for a similar fruit crop. It allows for a more accurate harvest time as massive data is accumulated continuously.
Background: Over the past few decades, various goals have been defined to reduce the mortality of children caused by acute lower respiratory infections (ALRIs) worldwide. However, few spatial studies to date have reported on ALRI deaths. Purpose: We aimed to assess the spatial modeling of mortality from ALRI in children under 5 years of age during 2000-2017 using a global data. Methods: The data on the mortality of children under 5 years old caused by ALRI were initially obtained from the official website of the World Health Organization. The income status of their home countries was also gathered from the Country Income Groups (World Bank Classification) website and divided into 5 categories. After that, in the ArcGIS 10.6 environment, a database was created and the statistical tests and related maps were extracted. The Global Moran's I statistic, Getis-Ord Gi statistic, and geographically weighted regression were used for the analyses. In this study, higher z scores indicated the hot spots, while lower z scores indicated the cold spots. Results: In 2000-2017, child mortality showed a downward trend from 17.6 per 100,000 children to 8.1 and had a clustered pattern. Hot spots were concentrated in Asia in 2000 but shifted toward African countries by 2017. A cold spot that formed in Europe in 2007 showed an ascending trend by 2017. Based on the results of geographically weighted regression test, the regions identified as the hot spots of mortality from ALRI in children under 5 years old were among the middle-income countries (R2=0.01, adjusted R2=8.77). Conclusion: While the total number of child deaths in 2000-2017 has decreased, the number of hot spots has increased among countries. This study also concluded that, during the study period, Central and Western Africa countries became the main new hot spots of deaths from ALRI.
Korean Journal of Construction Engineering and Management
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v.23
no.3
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pp.104-115
/
2022
Safety accidents in the construction industry account for the highest percentage of all industries; and thus, it is encouraged to introduce a virtual reality (VR)-based experiential education system into the basic occupational safety and health training for construction as a way to solve the problem. However, there are some limitations such as a lack of competent workforce, and insufficient content and equipment for VR-based construction safety education. In this background, this study aimed to analyze the difference in learning effect between the CG-based experiential VR education (direct method, type B) and the existing photo-based audiovisual VR education (indirect method, type A), in which a CAMIL (Cognitive & Affective Model of Immersive Learning) theory was used as objective assessment tool. The learning effect of the direct education method (type B) was found to be superior to that of the indirect education method (type A) in terms of all areas in the CAMIL theory. It is expected that the VR-based experiential construction safety education will increase the learning effect of construction workers.
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