• Title/Summary/Keyword: Size-based selection

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A Study of Smartphone Sustainable Business in the Chinese Market through Conjoint Analysis

  • Junyan YANG;Jun ZHANG
    • The Journal of Industrial Distribution & Business
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    • v.15 no.3
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    • pp.11-20
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    • 2024
  • Purpose: This study focuses on the Chinese smartphone market to estimate product attributes influencing Chinese customers' preference for developing new smartphones through conjoint analysis. Research design, data and methodology: The online questionnaire survey is processed among Chinese potential smartphone customers. Conjoint analysis including traditional conjoint analysis (TCA) and choice-based conjoint analysis (CBCA), is used to analyze the useful data of 500. Results: Results indicate that price is the most important predictor while screen size is the least for Chinese customers' preference whether the method is TCA or CBCA. However, the importance of brand, capacity, CPU, and screen design is different. Moreover, based on each smartphone attribute level's utility, the new products with the best combinations are different compared with both methods. Finally, the predicted market shares of the top 3 products are the same with maximum utility rule model between TCA and CBCA. However, when considering with the new best combined product, they are significantly different. Conclusions: Managers should recognize the differences between TCA and CBCA and select the best method to develop new smartphones for sustainable business in the Chinese competitive market based on the important attributes of price, brand, capacity, CPU, screen design, and size.

A study of bioindicator selection for long-term ecological monitoring

  • Han, Yong-Gu;Kwon, Ohseok;Cho, Youngho
    • Journal of Ecology and Environment
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    • v.38 no.1
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    • pp.119-122
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    • 2015
  • It is very useful and important to see the status and change of necessary parts in a short period through selecting and observing the bioindicator continually to forecast and prepare the future. Especially, living things are so closely related to the environment that the indicator between the environment and living things shows close interrelationship. Also, the indicator related to environment provides information about representative or decisive environmental phenomenon and is used to simplify complicated facts. Considering wide range of background and application including various indicators such as the change-, destruction-, pollution-, and restoration of habitats, climate change, and species diversity, the closest category includes "environmental indicator," "ecological indicator," and "biodiversity indicator." The selection and use of bioindicator is complicated and difficult. The necessary conditions for the indicator selection are flexible and greatly depend on the goals of investigation such as the indicator for biological diversity investigation of specific area, the indicator for habitat destruction, the indicator for climate change, and the indicator for polluted area. It should meet many various conditions to select a good indicator. In this study, eleven selection standards are established based on domestic and overseas studies on bioindicator selection: species with clear classification and ecology, species distributed in geographically widespread area, species that show clear habitat characteristics, species that can provide early warning for a change, species that are easy and economically benefited for the investigation, species that have many independent individual groups and that is not greatly affected by the size of individual groups, species that is thought to represent the response of other species, species that represent the ecology change caused by the pressure of human influence, species for which researches on climate change have been done, species that is easy to observe, appears for a long time and forms a group with many individuals, and species that are important socially, economically, and culturally.

Fast Intra Mode Selection Algorithm Based on Edge Activity in Transform Domain for H.264/AVC Video (변환영역에서의 에지활동도에 기반한 H.264/AVC 고속 인트라모드 선택 방법)

  • Seo, Jae-Sung;Kim, Dong-Hyung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.8C
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    • pp.790-800
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    • 2009
  • For the improvement of coding efficiency, the H.264/AYC standard uses new coding tools such as 1/4-pel-accurate motion estimation, multiple references, intra prediction, loop filter, variable block size etc. Using these coding tools, H.264/AYC has achieved significant improvements from rate-distortion point of view compared to existing standards. However, the encoder complexity was greatly increased due to these coding tools. We focus on the complexity reduction method of intra macroblock mode selection. The proposed algorithm for fast intra mode selection calculates the edge activity in transform domain, and performs fast encoding of intra frame in H.264/AYC through the fast prediction mode selection of intra4x4 and chrominance blocks. Simulation results show that the proposed method saves about 59.76% for QCIF sequences and 65.03% for CIF sequences of total encoding time, while bitrate increase and PSNR decrease are very small.

Development of an Adaptive Neuro-Fuzzy Techniques based PD-Model for the Insulation Condition Monitoring and Diagnosis

  • Kim, Y.J.;Lim, J.S.;Park, D.H.;Cho, K.B.
    • Electrical & Electronic Materials
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    • v.11 no.11
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    • pp.1-8
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    • 1998
  • This paper presents an arificial neuro-fuzzy technique based prtial discharge (PD) pattern classifier to power system application. This may require a complicated analysis method employ -ing an experts system due to very complex progressing discharge form under exter-nal stress. After referring briefly to the developments of artificical neural network based PD measurements, the paper outlines how the introduction of new emerging technology has resulted in the design of a number of PD diagnostic systems for practical applicaton of residual lifetime prediction. The appropriate PD data base structure and selection of learning data size of PD pattern based on fractal dimentsional and 3-D PD-normalization, extraction of relevant characteristic fea-ture of PD recognition are discussed. Some practical aspects encountered with unknown stress in the neuro-fuzzy techniques based real time PD recognition are also addressed.

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A Meta-Analysis of youth leadership related variables: focus on implication of leadership selection by admission officer system (청소년 리더십 관련변인 메타분석: 입학사정관 리더십 전형에의 시사점 도출을 중심으로)

  • Kim, Yee Jee;Lee, Ki Hak
    • Korean Journal of School Psychology
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    • v.8 no.1
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    • pp.43-59
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    • 2011
  • The purposes of this research are: to observe the related variables; to compare the effect size; and make suggestions for leadership selection by admission officer system based on the results from the observation and comparison through meta analysis. The research questions crafted in order to achieve the purpose are as follows. First, what kind of variables were discussed in the previous studies? and can these variables be classified as the categories of the existing studies? Second, how are the effect sizes of the youth leadership related variable groups? Third, how are the effect sizes of sub factors of the related variable groups? The specific results of this research are as follows. First, youth leadership related variables can be classified as demographic, organization-activities, home environment and sociopsychological variables. Second, sociopshycological variable group shows the largest effect size. Third, among the sub factors, self esteems (ES=1.3231) and degree of satisfaction for life (ES=1.1737) show two largest effect sizes. In conclusion, based on the result of the research, this research suggests an alternative for a method to select students through admission counseling leadership selection system.

Application-aware Routing Protocol Selection Scheme in Wireless Mesh Network (무선 메쉬 네트워크에서의 응용 서비스 인지 라우팅 프로토콜 선택 기법)

  • Choi, Hyo-Hyun;Shon, Tae-Shik;Park, Yong-Suk
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.46 no.6
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    • pp.103-110
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    • 2009
  • We propose a novel routing protocol selection scheme based on the application feature in wireless mesh network. Each application has its own feature such as its packet size. For example, text messenger generates short size packets and file transfer application generates long size packets. Routing protocols in wireless mesh network discover the route with different features. Some find shortest hop routes; others find the routes consisting of high bandwidth though they have more hops. The proposed scheme selects the routing protocol by matching the feature of routing protocol and that of application. This paper shows the system that we have developed for supporting mesh routing as well as the proposed scheme and experimental results.

A Hybrid System of Joint Time-Frequency Filtering Methods and Neural Network Techniques for Foreign Exchange Rate Forecasting (환율예측을 위한 신호처리분석 및 인공신경망기법의 통합시스템 구축)

  • 신택수;한인구
    • Journal of Intelligence and Information Systems
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    • v.5 no.1
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    • pp.103-123
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    • 1999
  • Input filtering as a preprocessing method is so much crucial to get good performance in time series forecasting. There are a few preprocessing methods (i.e. ARMA outputs as time domain filters, and Fourier transform or wavelet transform as time-frequency domain filters) for handling time series. Specially, the time-frequency domain filters describe the fractal structure of financial markets better than the time domain filters due to theoretically additional frequency information. Therefore, we, first of all, try to describe and analyze specially some issues on the effectiveness of different filtering methods from viewpoint of the performance of a neural network based forecasting. And then we discuss about neural network model architecture issues, for example, what type of neural network learning architecture is selected for our time series forecasting, and what input size should be applied to a model. In this study an input selection problem is limited to a size selection of the lagged input variables. To solve this problem, we simulate on analyzing and comparing a few neural networks having different model architecture and also use an embedding dimension measure as chaotic time series analysis or nonlinear dynamic analysis to reduce the dimensionality (i.e. the size of time delayed input variables) of the models. Throughout our study, experiments for integration methods of joint time-frequency analysis and neural network techniques are applied to a case study of daily Korean won / U. S dollar exchange returns and finally we suggest an integration framework for future research from our experimental results.

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Antecedent Variables that Influence Personalization in Apparel Products Shopping - Clothing Involvement, Monthly Clothing Expenditures, Additional Expenses - (개인화된 의류상품과 서비스에 대한 소비자 태도에 영향을 미치는 요인)

  • Kim, Yeon-Hee;Lee, Kyu-Hye
    • Journal of the Korean Society of Costume
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    • v.58 no.4
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    • pp.58-71
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    • 2008
  • The demand for personalized products and service of apparel product has increased dramatically. In order to acquire a personalized apparel product, consumers may have to sacrifice more expense or time. The purpose of this study was to investigate various personalization strategies in apparel business and to identify antecedents that influence the process. Clothing involvement and two price related variables (clothing expense and willingness to pay more) were included in the study as antecedents. Four personalization strategies were included in the study: design selection, size customization, in-store service and promotion personalization. For an empirical study, a conceptual model was designed and research questionnaire was developed. A measure of personalization of apparel shopping was developed based on existing scale items of prior research and a pilot study. Data from 766 men and women in their twenties to forties were used for statistical analysis. Structural Equation Modeling was used for the data analysis. Results indicated that the conceptual model was a good fit to data. Structural paths indicated that there was significant influence of clothing involvement on design selection and sales promotion personalization strategies. Involved consumers spent more on chothing products and were likely to pay more on personalized products and services. Monthly clothing expense influenced size customization significantly. It also had negative influence on service related personalization strategies. Consumers were willing to pay more when it comes to product related personalization strategies such as design and size but not necessarily to service related strategies. This study was an attempt to provide an in-depth and synthesized approach on consumer attitudes toward personalization of apparel products.

Heterogeneity-aware Energy-efficient Clustering (HEC) Technique for WSNs

  • Sharma, Sukhwinder;Bansal, Rakesh Kumar;Bansal, Savina
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.4
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    • pp.1866-1888
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    • 2017
  • Efficient energy consumption in WSN is one of the key design issues for improving network stability period. In this paper, we propose a new Heterogeneity-aware Energy-efficient Clustering (HEC) technique which considers two types of heterogeneity - network lifetime and of sensor nodes. Selection of cluster head nodes is done based on the three network lifetime phases: only advanced nodes are allowed to become cluster heads in the initial phase; in the second active phase all nodes are allowed to participate in cluster head selection process with equal probability, and in the last dying out phase, clustering is relaxed by allowing direct transmission. Simulation-based performance analysis of the proposed technique as compared to other relevant techniques shows that HEC achieves longer stable region, improved throughput, and better energy dissipation owing to judicious consumption of additional energy of advanced nodes. On an average, the improvement observed for stability period over LEACH, SEP, FAIR and HEC- with SEP protocols is around 65%, 30%, 15% and 17% respectively. Further, the scalability of proposed technique is tested by varying the field size and number of sensing nodes. The results obtained are found to be quite optimistic. The impact of energy heterogeneity has also been assessed and it is found to improve the stability period though only upto a certain extent.

Early Selection of Double Flowers Based on Cotyledon Shape in Cut Stock (Matthiola incana L.) Flowers

  • Irani, Sepideh Famil;Arab, Mostafa
    • Horticultural Science & Technology
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    • v.35 no.2
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    • pp.265-275
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    • 2017
  • Selection of double-flowered plants at the seedling stage is one of the main purposes of stock breeding programs. Eight stock cultivars of Matthiola incana L. named 'Nobel', 'Cinderella', 'Pacific', 'Avalanche', 'Midblue', 'Lavender', 'Goddess' and 'Esfahan', with different percentage of double-flowered plants were used for examining the relationship with three morphological types of cotyledons. The results of a chi-square test indicated that in heart-shaped (HC) and cup-shaped cotyledon (CC) populations, the number of plants with double flowers was much more than that of single flowers and CC seedlings rarely produced single flowers. Therefore, increasing the number of CC seedlings can improve the percentage of double flowers. The highest and lowest numbers of CC seedling were observed in high double and single flower cultivars, respectively. Single flower cultivars showed the maximum count of dumbbell-shaped cotyledons. Chromosome pairing of these cultivars was evaluated using the squash technique. Aneuploid cells were found in 'Nobel' and 'Goddess' cultivars, which showed the highest percentage of CC seedling. Based on morphological measurements, the highest value of inflorescence size was observed in the seedlings with cup-shaped cotyledons.