• Title/Summary/Keyword: Science Channel

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Distribution Channel Model for Hotel Revenue Management: Lessons from Hoteliers and E-Intermediaries

  • IBRAHIM, Niko;PUTRA, Panca O. Hadi;HANDAYANI, Putu Wuri
    • Journal of Distribution Science
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    • v.20 no.2
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    • pp.19-29
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    • 2022
  • Purpose: Understanding the distribution channel is a foundational element of successful hotel revenue management. This study aims to assess hotel distribution network partnerships and develops a model that can be utilized to ensure hoteliers are not becoming increasingly reliant on a single channel, optimize their market exposure, and maximize their portion of the overall worth of the network. Research design, data and methodology: This study utilizes a grounded theory approach to form a theoretical model by analyzing and examining the current practice of hotel distribution management through interviews with 15 stakeholders in Indonesia, such as hoteliers, online travel agents, wholesalers, and connectivity managers. Results: Based on data analysis, we describe hotel distribution elements, revenue team, managed channels, and channel prioritization for a different type of hotel. Finally, we propose a distribution channel model that comprises hotel teams, customer types, indirect channels, and direct channels. Conclusions: The model contributes to the literature by exploring the options of distribution channels for various hotel types to support hotel revenue management practice. By utilizing our model, practitioners can have a complete picture regarding the strategic choice of the channel by considering their hotel capacity and market target.

Multi-channel Long Short-Term Memory with Domain Knowledge for Context Awareness and User Intention

  • Cho, Dan-Bi;Lee, Hyun-Young;Kang, Seung-Shik
    • Journal of Information Processing Systems
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    • v.17 no.5
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    • pp.867-878
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    • 2021
  • In context awareness and user intention tasks, dataset construction is expensive because specific domain data are required. Although pretraining with a large corpus can effectively resolve the issue of lack of data, it ignores domain knowledge. Herein, we concentrate on data domain knowledge while addressing data scarcity and accordingly propose a multi-channel long short-term memory (LSTM). Because multi-channel LSTM integrates pretrained vectors such as task and general knowledge, it effectively prevents catastrophic forgetting between vectors of task and general knowledge to represent the context as a set of features. To evaluate the proposed model with reference to the baseline model, which is a single-channel LSTM, we performed two tasks: voice phishing with context awareness and movie review sentiment classification. The results verified that multi-channel LSTM outperforms single-channel LSTM in both tasks. We further experimented on different multi-channel LSTMs depending on the domain and data size of general knowledge in the model and confirmed that the effect of multi-channel LSTM integrating the two types of knowledge from downstream task data and raw data to overcome the lack of data.

Large eddy simulation on the turbulent mixing phenomena in 3×3 bare tight lattice rod bundle using spectral element method

  • Ju, Haoran;Wang, Mingjun;Wang, Yingjie;Zhao, Minfu;Tian, Wenxi;Liu, Tiancai;Su, G.H.;Qiu, Suizheng
    • Nuclear Engineering and Technology
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    • v.52 no.9
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    • pp.1945-1954
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    • 2020
  • Subchannel code is one of the effective simulation tools for thermal-hydraulic analysis in nuclear reactor core. In order to reduce the computational cost and improve the calculation efficiency, empirical correlation of turbulent mixing coefficient is employed to calculate the lateral mixing velocity between adjacent subchannels. However, correlations utilized currently are often fitted from data achieved in central channel of fuel assembly, which would simply neglect the wall effects. In this paper, the CFD approach based on spectral element method is employed to predict turbulent mixing phenomena through gaps in 3 × 3 bare tight lattice rod bundle and investigate the flow pulsation through gaps in different positions. Re = 5000,10000,20500 and P/D = 1.03 and 1.06 have been covered in the simulation cases. With a well verified mesh, lateral velocities at gap center between corner channel and wall channel (W-Co), wall channel and wall channel (W-W), wall channel and center channel (W-C) as well as center channel and center channel (C-C) are collected and compared with each other. The obvious turbulent mixing distributions are presented in the different channels of rod bundle. The peak frequency values at W-Co channel could have about 40%-50% reduction comparing with the C-C channel value and the turbulent mixing coefficient β could decrease around 25%. corrections for β should be performed in subchannel code at wall channel and corner channel for a reasonable prediction result. A preliminary analysis on fluctuation at channel gap has also performed. Eddy cascade should be considered carefully in detailed analysis for fluctuating in rod bundle.

Assessing Interactions Among Omnichannel Attributes, Customer Perceptions, Customer Experience, Channel Selection

  • NGUYEN, Hai Ninh;NGUYEN, Anh Duc
    • Journal of Distribution Science
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    • v.20 no.3
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    • pp.1-11
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    • 2022
  • Purpose: This study aims at understanding the impacts of three omnichannel attributes (channel transparency, channel uniformity, channel convenience) and four customer perceptions (perceived innovativeness, perceived personalization, perceived risk, perceived credibility) on customer experience and channel selection decision. Research design and methodology: A quantitative online survey with 356 shoppers was executed. The partial least squares linear structural model (PLS-SEM) and Smart PLS were adopted to analyze the collected data and test the proposed hypotheses. Results: The research findings indicate four dominant results: (i) The customers' channel selection is directly determined by customer experience; perceived innovativeness; perceived personalization; perceived risk; and perceived credibility; and (ii) among these, the perceived risk shows negative impact on the customer's experience and customers' channel selection whereas others reveal the positive status; (iii) The customer experience represents the most decisive impact on the channel selection, then perceived personalization, perceived credibility, perceived innovativeness, and perceived risk. (iv) Three proposed channel attributes (transparency, uniformity, convenience) significantly influence the overall customer experience. Conclusions: This research adds to the body of knowledge in omnichannel retailing, customer experience, and customer channel selection. Furthermore, this research provides omnichannel retailers with practical implications for improving customer channel selection.

Property-based Design of Ion-Channel-Targeted Library

  • Ahn, Ji-Young;Nam, Ky-Youb;Chang, Byung-Ha;Yoon, Jeong-Hyeok;Cho, Seung-Joo;Koh, Hun-Yeong;No, Kyoung-Tai
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2005.09a
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    • pp.134-138
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    • 2005
  • The design of ion channel targeted library is a valuable methodology that can aid in the selection and prioritization of potential ion channel-likeness for ion-channel-targeted bio-screening from large commercial available chemical pool. The differences of property profiling between the 93 ion-channel active compounds from MDDR and CMC database and the ACDSC compounds were classified by suitable descriptors calculated with preADME software. Through the PCA, clustering, and similarity analysis, the compounds capable of ion channel activity were defined in ACDSC compounds pool. The designed library showed a tendency to follow the property profile of ion-channel active compounds and can be implemented with great time and economical efficiencies of ligand-based drug design or virtual high throughput screening from an enormous small molecule space.

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Selection of Three (E)UV Channels for Solar Satellite Missions by Deep Learning

  • Lim, Daye;Moon, Yong-Jae;Park, Eunsu;Lee, Jin-Yi
    • The Bulletin of The Korean Astronomical Society
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    • v.46 no.1
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    • pp.42.2-43
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    • 2021
  • We address a question of what are three main channels that can best translate other channels in ultraviolet (UV) and extreme UV (EUV) observations. For this, we compare the image translations among the nine channels of the Atmospheric Imaging Assembly on the Solar Dynamics Observatory using a deep learning model based on conditional generative adversarial networks. In this study, we develop 170 deep learning models: 72 models for single-channel input, 56 models for double-channel input, and 42 models for triple-channel input. All models have a single-channel output. Then we evaluate the model results by pixel-to-pixel correlation coefficients (CCs) within the solar disk. Major results from this study are as follows. First, the model with 131 Å shows the best performance (average CC = 0.84) among single-channel models. Second, the model with 131 and 1600 Å shows the best translation (average CC = 0.95) among double-channel models. Third, among the triple-channel models with the highest average CC (0.97), the model with 131, 1600, and 304 Å is suggested in that the minimum CC (0.96) is the highest. Interestingly they are representative coronal, photospheric, and chromospheric lines, respectively. Our results may be used as a secondary perspective in addition to primary scientific purposes in selecting a few channels of an UV/EUV imaging instrument for future solar satellite missions.

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A Unified Channel Thermal Noise Model for Short Channel MOS Transistors

  • Yu, Sang Dae
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.13 no.3
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    • pp.213-223
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    • 2013
  • A unified channel thermal noise model valid in all operation regions is presented for short channel MOS transistors. It is based on smooth interpolation between weak and strong inversion models and consistent physical model including velocity saturation, channel length modulation, and carrier heating. From testing for noise benchmark and comparing with published noise data, it is shown that the proposed noise model could be useful in simulating the MOSFET channel thermal noise in all operation regions.

The Growth and Change of Korean Cosmetics Market in Distribution Structure

  • YOON, Sang-Hyeon;SONG, Sang-Yeon;KANG, Myung-Soo
    • Journal of Distribution Science
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    • v.18 no.1
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    • pp.5-13
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    • 2020
  • Purpose: The purpose of this study is to examine the growth and change process of Korean cosmetic market that has grown more than three times since 2000. It also examined how the growth and decline of the cosmetics brands are related to the change of the cosmetic distribution structure. Research methodology: This study tried to classify the change of the Korean cosmetics market into four stages based on the market sales information. It analyzed the sales information of Korean cosmetic companies and the relationship with the sales of the brands by distribution channel. Results: One-brand store channel had played a leading role in the market growth, and multi-brand stores have grown and a number of brands also grew through that channel since 2013. Since 2016, multi-brand stores have continued to grow and have dominated the market beyond one-brand store channel. Conclusions: The changes in sales of domestic cosmetics companies have been classified based on the distribution channel type in four stages: the emergence of one-brand store, the growth of one-brand store channel, the growth of multi-brand store channel, and the decline of one-brand store channel. In conclusion, multi-brand store channels have recently grown in the Korean cosmetics market, and this trend is expected to continue.

Load Aware Automatic Channel Switching for Software-Defined Enterprise WLANs

  • Han, Yunong;Yang, Kun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.11
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    • pp.5223-5242
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    • 2017
  • In the last decade, the 2.4 GHz band of IEEE 802.11 WLANs has become heavily congested due to the explosive increase in demand of Wi-Fi connectivity. With the current deployment of enterprise WLANs, channel switching mechanism continues to exhibit inefficiencies because it cannot adapt to real-time channel condition and the inability to support seamless channel switching. Software Defined Networking (SDN) as an emerging architecture is promising to introduce flexibility and programmability for wireless network management. Leveraging SDN to existing enterprise WLANs, channel switching method can be improved significantly. This paper presents a software-defined enterprise WLAN framework with a load aware automatic channel switching solution, which utilizes AP load and channel interference factor (CIF) to provide seamless channel switching. Two automatic channel switching algorithms named Single Switch (SS) and Double Switch (DS) are proposed to improve the overall user experience and the experience of users with highest traffic load respectively. Experiment results demonstrate that our solution can efficiently improve user experience in terms of jitter, transmission delay and network throughout when compared to the conventional channel switching mechanism.

Frequency Domain Channel Estimation for MIMO SC-FDMA Systems with CDM Pilots

  • Kim, Hyun-Myung;Kim, Dongsik;Kim, Tae-Kyoung;Im, Gi-Hong
    • Journal of Communications and Networks
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    • v.16 no.4
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    • pp.447-457
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    • 2014
  • In this paper, we investigate the frequency domain channel estimation for multiple-input multiple-output (MIMO) single-carrier frequency-division multiple-access (SC-FDMA) systems. In MIMO SC-FDMA, code-division multiplexed (CDM) pilots such as cyclic-shifted Zadoff-Chu sequences have been adopted for channel estimation. However, most frequency domain channel estimation schemes were developed based on frequency-division multiplexing of pilots. We first develop a channel estimation error model by using CDM pilots, and then analyze the mean-square error (MSE) of various minimum MSE (MMSE) frequency domain channel estimation techniques. We show that the cascaded one-dimensional robust MMSE (C1D-RMMSE) technique is complexity-efficient, but it suffers from performance degradation due to the channel correlation mismatch when compared to the two-dimensional MMSE (2D-MMSE) technique. To improve the performance of C1D-RMMSE, we design a robust iterative channel estimation (RITCE) with a frequency replacement (FR) algorithm. After deriving the MSE of iterative channel estimation, we optimize the FR algorithm in terms of the MSE. Then, a low-complexity adaptation method is proposed for practical MIMO SC-FDMA systems, wherein FR is performed according to the reliability of the data estimates. Simulation results show that the proposed RITCE technique effectively improves the performance of C1D-RMMSE, thus providing a better performance-complexity tradeoff than 2D-MMSE.