• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.4
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• pp.159-164
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• 2023

Solar energy harvesting IoT devices prioritize maximizing the utilization of collected energy due to the periodic recharging nature of solar energy, rather than minimizing energy consumption. Meanwhile, research on edge AI, which performs machine learning near the data source instead of the cloud, is actively conducted for reasons such as data confidentiality and privacy, response time, and cost. One such research area involves performing various audio AI applications using audio data collected from multiple IoT devices in an IoT edge computing environment. However, in most studies, IoT devices only perform sensing data transmission to the edge server, and all processes, including data preprocessing, are performed on the edge server. In this case, it not only leads to overload issues on the edge server but also causes network congestion by transmitting unnecessary data for learning. On the other way, if data preprocessing is delegated to each IoT device to address this issue, it leads to another problem of increased blackout time due to energy shortages in the devices. In this paper, we aim to alleviate the problem of increased blackout time in devices while mitigating issues in server-centric edge AI environments by determining where the data preprocessed based on the energy state of each IoT device. In the proposed method, IoT devices only perform the preprocessing process, which includes sound discrimination and noise removal, and transmit to the server if there is more energy available than the energy threshold required for the basic operation of the device.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.77-82
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• 2024

Recent advancements in artificial intelligence (AI) technology have led to an increase in the implementation of AI applications in mobile environments. However, due to the limited resources in mobile devices compared to desktops and servers, there is growing interest in research aimed at efficiently executing AI workloads on mobile platforms. While most studies focus on offloading to edge or cloud solutions to mitigate computing resource constraints, research on the characteristics of file I/O related to storage access in mobile settings remains underexplored. This paper analyzes file I/O traces generated during the execution of deep learning applications in mobile environments and investigates how they differ from traditional mobile workloads. We anticipate that the findings of this study will be utilized to design future smartphone system software more efficiently, considering the file access characteristics of deep learning.

• 한국지구물리탐사학회:학술대회논문집
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• 2004.06a
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• pp.3-17
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• 2004

Space-borne Earth observation technique is one of the most cost effective and rapidly advancing Earth science research tools today and the potential field and micro-wave radar applications have been leading the discipline. The traditional optical imaging systems including the well known Landsat, NOAA - AVHRR, SPOT, and IKONOS have steadily improved spatial imaging resolution but increasing cloud covers have the major deterrent. The new Earth observation satellites ENVISAT (launched on March 1 2002, specifically for Earth environment observation), ALOS (planned for launching in 2004 - 2005 period and ALOS stands for Advanced Land Observation Satellite), and RADARSAT-II (planned for launching in 2005) all have synthetic aperture radar (SAR) onboard, which all have partial or fully polarimetric imaging capabilities. These new types of polarimetric imaging radars with repeat orbit interferometric capabilities are opening up completely new possibilities in Earth system science research, in addition to the radar altimeter and scatterometer. The main advantage of a SAR system is the all weather imaging capability without Sun light and the newly developed interferometric capabilities, utilizing the phase information in SAR data further extends the observation capabilities of directional surface covers and neotectonic surface displacements. In addition, if one can utilize the newly available multiple frequency polarimetric information, the new generation of space-borne SAR systems is the future research tool for Earth observation and global environmental change monitoring. The potential field strength decreases as a function of the inverse square of the distance between the source and the observation point and geophysicists have traditionally been reluctant to make the potential field observation from any space-borne platforms. However, there have recently been a number of potential field missions such as ASTRID-2, Orsted, CHAMP, GRACE, GOCE. Of course these satellite sensors are most effective for low spatial resolution applications. For similar objects, AMPERE and NPOESS are being planned by the United States and France. The Earth science disciplines which utilize space-borne platforms most are the astronomy and atmospheric science. However in this talk we will focus our discussion on the solid Earth and physical oceanographic applications. The geodynamic applications actively being investigated from various space-borne platforms geological mapping, earthquake and volcano .elated tectonic deformation, generation of p.ecise digital elevation model (DEM), development of multi-temporal differential cross-track SAR interferometry, sea surface wind measurement, tidal flat geomorphology, sea surface wave dynamics, internal waves and high latitude cryogenics including sea ice problems.

• Journal of Information Technology Applications and Management
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• v.21 no.4_spc
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• pp.431-447
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• 2014

Demand of spectrum resource is tremendously increasing and this trend will continue as more IT services such as cloud computing, smart devices, Internet of Things are provided through wireless network. Recent development of spectrum sharing technology has drawn attention to spectrum policy makers as a promising way to overcome the expected spectrum shortage problem. However, technology-based solution to spectrum shortage problem may not be sustainable since the solution affect only one aspect of spectrum sharing ecosystem. To understand the whole picture of spectrum shortage problem, policies to vitalize spectrum sharing ecosystem were proposed based on the analysis of System Dynamics causal map in the previous study. This study compares and analyzes the effect of those proposed vitalization policies by using System Dynamics simulation. Among seven alternative policies, combined application of demand acceleration policy and technology development policy was found to be more effective for better utilization of spectrum. The effect of demand acceleration policy was offset when other policies are applied together except supply acceleration policy which shows better spectrum sharing.

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.91-97
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• 2017

IoT (Internet of Things) systems are based on heterogeneous hardware systems of different types of devices interconnected each other, ranging from miniaturized and low-power wireless sensor node to cloud servers. These IoT systems composed of heterogeneous hardware utilize data sets collected from a particular set of sensors or control designated actuators when needed using open APIs created through abstraction of devices' resources associated to service applications. However, previously existing IoT services have been usually developed based on vertical platforms, whose sharing and exchange of data is limited within each industry domain, for example, healthcare. Such problem is called 'data silo', and considered one of crucial issues to be solved for the success of establishing IoT ecosystems. Also, IoT services may need to dynamically organize their services according to the change of status of connected devices due to their mobility and dynamic network connectivity. We propose a way of dynamically composing IoT services under the concept of WoT (Web of Things) where heterogeneous devices across different industries are fully integrated into the Web. Our approach allows developers to create IoT services or mash them up in an efficient way using Web objects registered into multiple standardized horizontal IoT platforms where their resources are discoverable and accessible. A Web-based service composition tool is developed to evaluate the practical feasibility of our approach under real-world service development.

• ETRI Journal
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• v.30 no.2
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• pp.194-204
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• 2008

The online collection of coarse-grained traffic information, such as the total number of flows, is gaining in importance due to a wide range of applications, such as congestion control and network security. In this paper, we focus on an active queue management scheme called SRED since it estimates the number of active flows and uses the quantity to indicate the level of congestion. However, SRED has several limitations, such as instability in estimating the number of active flows and underestimation of active flows in the presence of non-responsive traffic. We present a Markov model to examine the capability of SRED in estimating the number of flows. We show how the SRED cache hit rate can be used to quantify the number of active flows. We then propose a modified SRED scheme, called hash-based two-level caching (HaTCh), which uses hashing and a two-level caching mechanism to accurately estimate the number of active flows under various workloads. Simulation results indicate that the proposed scheme provides a more accurate estimation of the number of active flows than SRED, stabilizes the estimation with respect to workload fluctuations, and prevents performance degradation by efficiently isolating non-responsive flows.

• Journal of Astronomy and Space Sciences
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• v.24 no.4
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• pp.379-388
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• 2007

Modulation Transfer Function (MTF) of satellite image is an important performance index in satellite image applications. Therefore MTF performance is assessed using satellite image for the ground target during LEOP phase after launch. But the MTF performance assessment using the ground target can be affected by imaging conditions such as cloud and weather. In this paper system requirements and satellite operation for assessing MTF performance of satellite image using stellar sources are proposed. Satellite capability in collecting stellar sources using the satellite which is designed for earth observation and satellite image usefulness for assessing MTF performances were analyzed. The proposed approach will be useful to assess MTF performance of earth observation satellite in lower earth orbit.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1455-1461
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• 2015

Micro Grid is a new concept of electrical grid to solve several problems of Mega-Grid and it is under research and development at the national level around the world. With this background, Micro Grid Common Platform has been developed for interoperability technology of devices-systems in Micro Grid and securing enabler for new market. For supporting business models, Micro Grid Common Platform provides electric power information to Third-Party licensee via Open API function. Licensee, who want to develop electric power application by connecting to Micro Grid Common Platform, needs IDE(Integrated Development Environment) for service development and distribution. The paper proposes a service development tool for developing applications of Micro Grid Common Platform as a PaaS (Platform as a Service).

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.2
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• pp.195-200
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• 2015

It is envisaged that the effect of increasingly stricter air emissions legislation implemented through IMO Annex VI and other local air quality controls, together with favorable financial conditions for the use of natural gas instead of liquid fuel oil as a bunker fuel, will see an increasing number of DF engine and single gas fuel engine applications to LNG carriers and other vessel types. As part of provision for the current international movements in the shipping industry to reduce GHG emission in air, new design concepts using natural gas as an alternative fuel source for propulsion of large commercial vessels, have been developed by shipyards and research institutes. In this study, an explosion analysis for a gas supply machinery room of LNG-fuelled container ship is presented. The gas fuel concept is employed for the high pressure ME-GI where a leakage in the natural gas double supply pipe to the engines is the subject of the present analysis. The consequences of a leak are simulated with computational fluid dynamics (CFD) tools to predict typical leak scenarios, gas cloud sizes and possible explosion pressures. In addition, capacity of the structure which is subject to explosion loads has been assessed.

• Asian Journal of Atmospheric Environment
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• v.4 no.3
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• pp.115-140
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• 2010

Great concerns about atmospheric aerosols are attributed to their multiple roles to atmospheric processes. For example, atmospheric aerosols influence global climate, directly by scattering or absorbing solar radiations and indirectly by serving as cloud condensation nuclei. They also have a significant impact on human health and visibility. Many of these effects depend on the size and composition of atmospheric aerosols, and thus detailed information on the physicochemical properties and the distribution of airborne particles is critical to accurately predict their impact on the Earth's climate as well as human health. A single particle analysis technique, named low-Z particle electron probe X-ray microanalysis (low-Z particle EPMA) that can determine the concentration of low-Z elements such as carbon, nitrogen and oxygen in a microscopic volume has been developed. The capability of quantitative analysis of low-Z elements in individual particle allows the characterization of especially important atmospheric particles such as sulfates, nitrates, ammonium, and carbonaceous particles. Furthermore, the diversity and the complicated heterogeneity of atmospheric particles in chemical compositions can be investigated in detail. In this review, the development and methodology of low-Z particle EPMA for the analysis of atmospheric aerosols are introduced. Also, its typical applications for the characterization of various atmospheric particles, i.e., on the chemical compositions, morphologies, the size segregated distributions, and the origins of Asian dust, urban aerosols, indoor aerosols in underground subway station, and Arctic aerosols, are illustrated.