Soto, Laia Barrufet de;White, Glenn J.;Pearson, Chris;Serjeant, Stephen;Lim, Tanya;Matsuhara, Hideo;Oi, Nagisa;Karouzos, Marios;AKARI-NEP Team
Publications of The Korean Astronomical Society
/
v.32
no.1
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pp.271-273
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2017
The AKARI North Ecliptic Pole Deep Field is a natural location to accomplish deep extragalactic surveys. It is supported by comprehensive ancillary data extending from radio to X-ray wavelengths, which have been used to classify radio sources as radio-loud and radio-quiet objects and to create a catalogue of Active Galactic Nuclei (AGN). This has been achieved by using a radio-optical classification and colour-colour diagrams rather than the more usual way based on spectroscopy Furthermore, we explore whether this technique can be extended by using a far-Infrared (FIR) colour-colour diagram which has been used to identify 268 high redshift candidates.
Visible channel calibration method using deep convective clouds (DCCs) is developed. The method has advantages that visible radiance is not sensitive to cloud optical thickness (COT) for deep convective clouds because visible radiance no longer increases when COT exceeds 100. Therefore, once DCCs are chosen appropriately, and then cloud optical properties can be assumed without operational ancillary data for the specification of cloud conditions in radiative transfer model. In this study, it is investigated whether IR measurements can be used for the selection of DCC targets. To construct appropriate threshold value for the selection of DCCs, the statistics of cloud optical properties are collected with MODIS measurements. When MODIS brightness temperature (TB) at 11 ${\mu}$ m is restricted to be less than 190 K, it is shown that more than 85% of selected pixels show COT ${\geq}$ 100. Moreover, effective radius ($r_e$) distribution shows a sharp peak around 20 ${\mu}m$. Based on those MODIS observations, cloud optical properties are assumed as COT = 200 and $r_e$ = 20 ${\mu}m$ for the simulation of MODIS visible (0.646 ${\mu}m$) band radiances over DCC targets.
Park, Se-Joon;Lim, Jung-Yeol;Yoon, Seok-Am;Cha, In-Su
Journal of the Korean Solar Energy Society
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v.28
no.3
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pp.15-20
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2008
Building-integrated photovoltaics(BIPV) are increasingly incorporated into new domestic and industrial buildings as a principal or ancillary source of electrical power, and are one of the fastest growing segments of the photovoltaic industry. This paper presents design, operational features analysis, and PCS(Power Conditioning System) of grid-connected 30kW BIPV set up on the library of Dongshin University. For a sustainable photovoltaics system in this area, the data of the BIPV system are collected and analyzed by monitoring system using LabView. PCS of the grid-connected BIPV system, also, is designed for optimal operation with characteristics suggested in this paper.
Lee, Si Young;Jin, Young Gyu;Kim, Sun Kyo;Yoon, Yong Tae
Journal of Electrical Engineering and Technology
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v.9
no.3
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pp.1089-1095
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2014
Innumerable microgrids would be operated independently by individual operators in a future smart grid. This kind of decentralized power system requires entirely different operation scheme in the actual power system and electricity market operation. Especially, frequency regulation is very important for successive energy trade in this multi-microgrid circumstance. This paper presents an optimal energy and reserve market participation strategy and operation strategy of energy storage system (ESS) by a microgrid operator (MGO). For definite evaluation of the proposed strategy, we postulate that the MGO should participate in the Power Exchange for Frequency Control (PXFC) market, which was devised by Maria Ilic and her coworkers and is suitable to the decentralized operation circumstances. In particular, optimal reserve capacity of the frequency control market and optimal market participation ratio of ESS between frequency control market and energy market are derived theoretically and evaluated by simulations utilizing Nordic Pool Elspot price data.
The MSC is a remote sensing instrument with very high performance that is to be installed on KOMPSAT2 satellite. The MSC consists of EOS (Electro-Optic Subsystem), PMU (Payload Management Unit) and PDTS (Payload Data Transmission Subsystem). PMU controls and monitors all the other payload units by sending commands and collecting telemetry. PMU is in charge of interfacing between payload system and satellite bus system. PMU gets commands from ground-station via OBC (On-Board Computer) that is a main controller of the satellite bus system and sends telemetry to the ground-station via OBC. There is a processor module, called SBC (Single Board Computer) in the PMU. The SBC is a main controller of the MSC system. The main roles of the SBC are payload mission management, command validation and execution, telemetry collection and monitoring, ancillary data handling, event reporting, power control of payload sub-units and communication with these units. Intel's 80486DX2 processor has been used for the SBC. Due to the fact that the SBC plays important roles for imaging mission execution and handles a lot of control data that is required for payload operation, it is required to make analysis of the CPU load when it is in maximum operation mode. In this paper, the analysis and measurement results of the SBC throughput in the maximum operation mode.
Variability of sea surface temperature (SST) in the Japan/East Sea (JES) was studied using complex empirical orthogonal function (CEOF) analysis. Two daily data sets were analyzed: (1) New Generation 0.05o-gridded SST from Tohoku University, Japan (July 2002-July 2006), and (2) 0.25o-gridded SST from the Japan Meteorological Agency (October 1993-November 2006). Linkages with wind stress curl were revealed using 6-h 1o-gridded surface zonal and meridional winds from ancillary data of the Sea- WiFS Project, a special National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) product (1998-2005). SST anomalies (SSTA) were obtained by removing the seasonal signal, estimated as the leading mode of the CEOF decomposition of the original SST. Leading CEOF modes of residual SSTA obtained from both data sets were consistent with each other and were characterized by annual, semiannual, and quasi-biennial time scales estimated with 95% statistical significance. The Semiannual Mode lagged 2 months behind the increased occurrence of the anticyclonic (AC) wind stress curl over the JES. Links to dynamic processes were investigated by numerical simulations using an oceanic model. The suggested dynamic forcings of SSTA are the inflow of subtropical water into the JES through the Korea Strait, divergence in the surface layer induced by Ekman suction, meridional shifts of the Subarctic Front in the western JES, AC eddy formation, and wind-driven strengthening/weakening of large-scale currents. Events of west-east SSTA movement were identified in July-September. The SSTA moved from the northeastern JES towards the continental coast along the path of the westward branch of the Tsushima Current at a speed consistent with the advective scale.
Kim, Ji Won;Lee, You Min;Han, Shawn;Kim, Kyeongtaek
Journal of Korean Society of Industrial and Systems Engineering
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v.44
no.3
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pp.98-105
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2021
The sensory stimulation of a cosmetic product has been deemed to be an ancillary aspect until a decade ago. That point of view has drastically changed on different levels in just a decade. Nowadays cosmetic formulators should unavoidably meet the needs of consumers who want sensory satisfaction, although they do not have much time for new product development. The selection of new products from candidate products largely depend on the panel of human sensory experts. As new product development cycle time decreases, the formulators wanted to find systematic tools that are required to filter candidate products into a short list. Traditional statistical analysis on most physical property tests for the products including tribology tests and rheology tests, do not give any sound foundation for filtering candidate products. In this paper, we suggest a deep learning-based analysis method to identify hand cream products by raw electric signals from tribological sliding test. We compare the result of the deep learning-based method using raw data as input with the results of several machine learning-based analysis methods using manually extracted features as input. Among them, ResNet that is a deep learning model proved to be the best method to identify hand cream used in the test. According to our search in the scientific reported papers, this is the first attempt for predicting test cosmetic product with only raw time-series friction data without any manual feature extraction. Automatic product identification capability without manually extracted features can be used to narrow down the list of the newly developed candidate products.
The major objective of this research is to identify those hospital characteristics that best explain cost variation among hospitals and to formulate linear models that can predict hospital costs. Specific emphasis is placed on hospital output, that is, the identification of diagnosis related patient groups (DRGs) which are medically meaningful and demonstrate similar patterns of hospital resource consumption. A casemix index is developed based on the DRGs identified. Considering the common problems encountered in previous hospital cost research, the following study requirements are estab-lished for fulfilling the objectives of this research: 1. Selection of hospitals that exercise similar medical and fiscal practices. 2. Identification of an appropriate data collection mechanism in which demographic and medical characteristics of individual patients as well as accurate and comparable cost information can be derived. 3. Development of a patient classification system in which all the patients treated in hospitals are able to be split into mutually exclusive categories with consistent and stable patterns of resource consumption. 4. Development of a cost finding mechanism through which patient groups' costs can be made comparable across hospitals. A data set of Medicare patients prepared by the Social Security Administration was selected for the study analysis. The data set contained 27,229 record abstracts of Medicare patients discharged from all but one short-term general hospital in Connecticut during the period from January 1, 1971, to December 31, 1972. Each record abstract contained demographic and diagnostic information, as well as charges for specific medical services received. The 'AUT-OGRP System' was used to generate 198 DRGs in which the entire range of Medicare patients were split into mutually exclusive categories, each of which shows a consistent and stable pattern of resource consumption. The 'Departmental Method' was used to generate cost information for the groups of Medicare patients that would be comparable across hospitals. To fulfill the study objectives, an extensive analysis was conducted in the following areas: 1. Analysis of DRGs: in which the level of resource use of each DRG was determined, the length of stay or death rate of each DRG in relation to resource use was characterized, and underlying patterns of the relationships among DRG costs were explained. 2. Exploration of resource use profiles of hospitals; in which the magnitude of differences in the resource uses or death rates incurred in the treatment of Medicare patients among the study hospitals was explored. 3. Casemix analysis; in which four types of casemix-related indices were generated, and the significance of these indices in the explanation of hospital costs was examined. 4. Formulation of linear models to predict hospital costs of Medicare patients; in which nine independent variables (i. e., casemix index, hospital size, complexity of service, teaching activity, location, casemix-adjusted death. rate index, occupancy rate, and casemix-adjusted length of stay index) were used for determining factors in hospital costs. Results from the study analysis indicated that: 1. The system of 198 DRGs for Medicare patient classification was demonstrated not only as a strong tool for determining the pattern of hospital resource utilization of Medicare patients, but also for categorizing patients by their severity of illness. 2. The wei틴fed mean total case cost (TOTC) of the study hospitals for Medicare patients during the study years was $11,27.02 with a standard deviation of $117.20. The hospital with the highest average TOTC ($1538.15) was 2.08 times more expensive than the hospital with the lowest average TOTC ($743.45). The weighted mean per diem total cost (DTOC) of the study hospitals for Medicare patients during the sutdy years was $107.98 with a standard deviation of $15.18. The hospital with the highest average DTOC ($147.23) was 1.87 times more expensive than the hospital with the lowest average DTOC ($78.49). 3. The linear models for each of the six types of hospital costs were formulated using the casemix index and the eight other hospital variables as the determinants. These models explained variance to the extent of 68.7 percent of total case cost (TOTC), 63.5 percent of room and board cost (RMC), 66.2 percent of total ancillary service cost (TANC), 66.3 percent of per diem total cost (DTOC), 56.9 percent of per diem room and board cost (DRMC), and 65.5 percent of per diem ancillary service cost (DTANC). The casemix index alone explained approximately one half of interhospital cost variation: 59.1 percent for TOTC and 44.3 percent for DTOC. Thsee results demonstrate that the casemix index is the most importand determinant of interhospital cost variation Future research and policy implications in regard to the results of this study is envisioned in the following three areas: 1. Utilization of casemix related indices in the Medicare data systems. 2. Refinement of data for hospital cost evaluation. 3. Development of a system for reimbursement and cost control in hospitals.
To address the requirements of gap analysis for species protection, as well as the needs of state and federal agencies for detailed digital land cover, a 43-class map at the vegetation alliance level was created for the state of Kansas using multi-temporal Thematic Mapper imagery. The mapping approach included the use of three-date multi-seasonal imagery, a two-stage classification approach that first masked out cropland areas using unsupervised classification and then mapped natural vegetation with supervised classification, visualization techniques utilizing a map of small multiples and field experts, and extensive use of ancillary data in post-hoc processing. Accuracy assessment was conducted at three levels of generalization (Anderson Level I, vegetation formation, and vegetation alliance) and three cross-tabulation approaches. Overall accuracy ranged from 51.7% to 89.4%, depending on level of generalization, while accuracy figures for individual alliance classes varied by area covered and level of sampling.
Background: The purpose of this study was to identify factors inhibiting access of people with disability to health check-ups as well as identify pertinent solutions for improvement. Methods: Twenty-three people with disability older than the age of 19 who took respective health check-ups within the last 3 years were selected as participants. For the data collection, the 1:1 intensive interview was used. The data were analyzed by the grounded theory by Corbin and Strauss. Results: The results comprised nine categories, 23 subcategories, and 179 concepts. The central phenomenon was 'failure to obtain check-ups.' Causal conditions were observed as a 'lack of communication method,' 'physical difficulties,' and 'staff unfamiliar with people with disability,' Interventional conditions comprised 'physical accessibility,' 'staffs' competency,' and 'assistant manpower.' The active strategy was included 'to investigate the professional medical institution,' 'to find the medical institution of convenient traffic accessibility,' 'to overcome communication difficulties through equipment,' and 'to overcome linguistic barriers through sufficient communication.' Whereas, 'utilization of ancillary equipment,' 'the education of staffs on people with disability,' 'universal design manual,' and 'customized check-ups' were included in the passive strategy. Such processes arose in the contextual conditions of 'lack of expectations for daily lives' and 'lack of government support.' As a consequence, the subjects participated experienced the 'disadvantages,' 'discrimination,' and 'reduced reliability of the health check-ups.' Conclusion: The subjects who participated in this study emphasized 'staffs familiar with people with disability' and 'systems customized for people with disability' are mandatory to secure complete health check-ups for people with disability.
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