• Title/Summary/Keyword: Temporal cost

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First Principles Computational Study of Surface Reactions Toward Design Concepts of High Functional Electrocatalysts for Oxygen Reduction Reaction in a Fuel Cell System

  • Hwang, Jeemin;Noh, Seunghyo;Kang, Joonhee;Han, Byungchan
    • Journal of Surface Science and Engineering
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    • v.50 no.1
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    • pp.1-9
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    • 2017
  • Design of novel materials in renewable energy systems plays a key role in powering transportation vehicles and portable electronics. This review introduces the research work of first principles-based computational design for the materials over the last decade to accomplish the goal with less financial and temporal cost beyond the conventional approach, especially, focusing on electrocatalyst toward a proton exchange membrane fuel cell (PEMFC). It is proposed that the new method combined with experimental validation, can provide fundamental descriptors and mechanical understanding for optimal efficiency control of a whole system. Advancing these methods can even realize a computational platform of the materials genome, which can substantially reduce the time period from discovery to commercialization into markets of new materials.

Gait analysis methods and walking pattern of hemiplegic patients after stroke (뇌졸중환자의 보행분석방법과 보행특성)

  • Han, Jin-Tae;Bae, Sung-Soo
    • PNF and Movement
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    • v.5 no.1
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    • pp.37-47
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    • 2007
  • Objective : A large proportion of stroke survivors have to deal with problems in gait. Proper evaluation of gait must be undertaken to understand the sensorimotor impairment underlying locomotor disorders post stroke. Methods : The characteristics of gait pattern with post stroke are reviewed in this paper. In particular, temporal distance parameters, kimematics, kinetics, as well as energy cost, EMG are focused. Results : The technology for gait analysis is moving rapidly. The techniques of 3D kinematic and kinetic analysis can provide a detailed biomechanical description of normal and pathological gait. This article reviews gait analysis method and characteristics of post stroke. Finally current method of gait analysis can provide further insight to understand paretic gait and therapeutic direction.

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Hierarchical buffering scheme for supporting effective routing scheme in bidirectional MIN (Bidirectional MIN에서 효율적인 라우팅을 지원하기 위한 계층적 버퍼링 기법)

  • 장창수;김성천
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.10
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    • pp.12-19
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    • 1996
  • Many recent supercomputers employ a kind of switch-based multistage interconnection network architectrues (MINs) for constructing scalabel parallel compters. This paper proposed a new routing method, hybrid wormhole and virtual-cut through routing (HWCR) for the prevention of rapid performance degradation comming from a conflict in links usage at hot traffic situation. This HWCR through (VCT) for the fast removing temporal stagger, result in seamless flow of packet stream. When the blocked link is removed, wormhole routing is resumed. The HWCR method adopted a hierachical buffer scheme for improving the network performance and reducing the cost in BMINs. We could get optimum buffer size and communicatin latency through the computer simulation based on proposed HWCR, and the results were compared to those using wormhole and VCT.

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Recent Trends of Hyperspectral Imaging Technology (초분광 이미징 기술동향)

  • Lee, M.S.;Kim, K.S.;Min, G.;Son, D.H.;Kim, J.E.;Kim, S.C.
    • Electronics and Telecommunications Trends
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    • v.34 no.1
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    • pp.86-97
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    • 2019
  • Over the past 30 years, significant developments have been made in hyperspectral imaging (HSI) technologies that can provide end users with rich spectral, spatial, and temporal information. Owing to the advances in miniaturization, cost reduction, real-time processing, and analytical methods, HSI technologies have a wide range of applications from remote-sensing to healthcare, military, and the environment. In this study, we focus on the latest trends of HSI technologies, analytical methods, and their applications. In particular, improved machine learning techniques, such as deep learning, allows the full use of HSI technologies in classification, clustering, and spectral mixture algorithms. Finally, we describe the status of HSI technology development for skin diagnostics.

A Structured Overlay Network Scheme Based on Multiple Different Time Intervals

  • Kawakami, Tomoya
    • Journal of Information Processing Systems
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    • v.16 no.6
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    • pp.1447-1458
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    • 2020
  • This paper describes a structured overlay network scheme based on multiple different time intervals. Many types of data (e.g., sensor data) can be requested at specific time intervals that depend on the user and the system. These queries are referred to as "interval queries." A method for constructing an overlay network that efficiently processes interval queries based on multiple different time intervals is proposed herein. The proposed method assumes a ring topology and assigns nodes to a keyspace based on one-dimensional time information. To reduce the number of forwarded messages for queries, each node constructs shortcut links for each interval that users tend to request. This study confirmed that the proposed method reduces the number of messages needed to process interval queries. The contributions of this study include the clarification of interval queries with specific time intervals; establishment of a structured overlay network scheme based on multiple different time intervals; and experimental verification of the scheme in terms of communication load, delay, and maintenance cost.

Taxi-demand forecasting using dynamic spatiotemporal analysis

  • Gangrade, Akshata;Pratyush, Pawel;Hajela, Gaurav
    • ETRI Journal
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    • v.44 no.4
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    • pp.624-640
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    • 2022
  • Taxi-demand forecasting and hotspot prediction can be critical in reducing response times and designing a cost effective online taxi-booking model. Taxi demand in a region can be predicted by considering the past demand accumulated in that region over a span of time. However, other covariates-like neighborhood influence, sociodemographic parameters, and point-of-interest data-may also influence the spatiotemporal variation of demand. To study the effects of these covariates, in this paper, we propose three models that consider different covariates in order to select a set of independent variables. These models predict taxi demand in spatial units for a given temporal resolution using linear and ensemble regression. We eventually combine the characteristics (covariates) of each of these models to propose a robust forecasting framework which we call the combined covariates model (CCM). Experimental results show that the CCM performs better than the other models proposed in this paper.

A Study on Multiple Modalities for Face Anti-Spoofing (얼굴 스푸핑 방지를 위한 다중 양식에 관한 연구)

  • Wu, Chenmou;Lee, Hyo Jong
    • Annual Conference of KIPS
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    • 2021.11a
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    • pp.651-654
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    • 2021
  • Face anti-spoofing (FAS) techniques play a significant role in the defense of facial recognition systems against spoofing attacks. Existing FAS methods achieve the great performance depending on annotated additional modalities. However, labeling these high-cost modalities need a lot of manpower, device resources and time. In this work, we proposed to use self-transforming modalities instead the annotated modalities. Three different modalities based on frequency domain and temporal domain are applied and analyzed. Intuitive visualization analysis shows the advantages of each modality. Comprehensive experiments in both the CNN-based and transformer-based architecture with various modalities combination demonstrate that self-transforming modalities improve the vanilla network a lot. The codes are available at https://github.com/chenmou0410/FAS-Challenge2021.

A Study on the Effect of Experience-specificity and Uncertainty on Choice in Experiential Products -From Transaction Cost Perspective- (경험재 거래의 경험특유성, 불확실성이 선택에 주는 영향에 관한 연구 -거래비용적 관점에서-)

  • Jeong, Yun-Hee;Park, JI-Yeon
    • Journal of Convergence for Information Technology
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    • v.9 no.4
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    • pp.152-159
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    • 2019
  • The purpose of this study is to investigate the effect of transaction characteristics on transaction cost and choice intention by applying transaction cost theory to experiential product. Experience-specificity, transaction uncertainty, and personal uncertainty are proposed to reflect the characteristics of experiential products, and the effects of these variables on transaction costs and transaction costs are assumed to have an influence on the choice intention. The results of this study are summarized as follows. First, experience-specificity(site, physical equipment, knowledge skill, temporal), transactional uncertainty(product-, process-), personal uncertainty (preference-, and situation-) have a significant positive effect on transaction cost. Second, transaction costs (search, comparison, examination, negotiation, payment, delivery) have a significant negative effect on the choice intention of the experiential product. The results of this study show that the increase of transaction costs can reduce the choice of experiential products and the strategic consideration of experience specificity, transaction uncertainty and individual uncertainty are required to reduce transaction costs. In addition, experiential products lacked access from a transactional and cost-based point of view, and this study contributes theoretically by compensating for the lack.

Monitoring Onion Growth using UAV NDVI and Meteorological Factors

  • Na, Sang-Il;Park, Chan-Won;So, Kyu-Ho;Park, Jae-Moon;Lee, Kyung-Do
    • Korean Journal of Soil Science and Fertilizer
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    • v.50 no.4
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    • pp.306-317
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    • 2017
  • Unmanned aerial vehicles (UAVs) became popular platforms for the collection of remotely sensed data in the last years. This study deals with the monitoring of multi-temporal onion growth with very high resolution by means of low-cost equipment. The concept of the monitoring was estimation of multi-temporal onion growth using normalized difference vegetation index (NDVI) and meteorological factors. For this study, UAV imagery was taken on the Changnyeong, Hapcheon and Muan regions eight times from early February to late June during the onion growing season. In precision agriculture frequent remote sensing on such scales during the vegetation period provided important spatial information on the crop status. Meanwhile, four plant growth parameters, plant height (P.H.), leaf number (L.N.), plant diameter (P.D.) and fresh weight (F.W.) were measured for about three hundred plants (twenty plants per plot) for each field campaign. Three meteorological factors included average temperature, rainfall and irradiation over an entire onion growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, $NDVI_{UAV}$ and rainfall in the model explain 88% and 68% of the P.H. and F.W. with a root mean square error (RMSE) of 7.29 cm and 59.47 g, respectively. And $NDVI_{UAV}$ in the model explain 43% of the L.N. with a RMSE of 0.96. These lead to the result that the characteristics of variations in onion growth according to $NDVI_{UAV}$ and other meteorological factors were well reflected in the model.

Design and Implementation of IEEE 802.11i MAC Layer (IEEE 802.11i MAC Layer 설계 및 구현)

  • Hong, Chang-Ki;Jeong, Yong-Jin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.8A
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    • pp.640-647
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    • 2009
  • IEEE 802.11i is an amendment to the original IEEE 802.11/b,a,g standard specifying security mechanism by stipulating RSNA for tighter security. The RSNA uses TKIP(Temporal Key Integrity Protocol) and CCMP(Counter with CBC-MAC Protocol) instead of old-fashioned WEP(Wired Equivalent Privacy) for data encryption. This paper describes a design of a communication security engine for IEEE 802.11i MAC layer. The design includes WEP and TKIP modules based on the RC4 encryption algorithm, and CCMP module based on the AES encryption algorism. The WEP module suffices for compatibility with the IEEE 802.11 b,a,g MAC layer. The CCMP module has about 816.7Mbps throughput at 134MHz, hence it satisfies maximum 600Mbps data rate described in the IEEE 802.11n specifications. We propose a pipelined AES-CCMP cipher core architecture, which has lower hardware cost than existing AES cores, because CBC mode and CTR mode operate at the same time.