• Title/Summary/Keyword: data value predictor

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Performance Evaluation of Value Predictor in High Performance Microprocessors (고성능 마이크로프로세서에서 값 예측기의 성능평가)

  • Jeon Byoung-Chan;Kim Hyeock-Jin;RU Dae-Hee
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.2 s.34
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    • pp.87-95
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    • 2005
  • value prediction in high performance micro processors is a technique that exploits Instruction Level Parallelism(ILP) by predicting the outcome of an instruction and by breaking and executing true data dependences. In this paper, the mean Performance improvements by predictor according to a point of time for update of each table as well as prediction accuracy and Prediction rate are measured and assessed by comparison and analysis of value predictor that issues in parallel and run by predicting value, which is for Performance improvements of ILP in micro Processor. For the verification of its validity the SPECint95 benchmark through the simulation is compared by making use of execution driven system.

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Efficient of The Data Value Predictor in Superscalar Processors (슈퍼스칼라 프로세서에서 데이터 값 예측기의 성능효과)

  • 박희룡;전병찬;이상정
    • Proceedings of the IEEK Conference
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    • 2000.06c
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    • pp.55-58
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    • 2000
  • To achieve high performance by exploiting instruction level parallelism(ILP) aggressively in superscalar processors, value prediction is used. Value prediction is a technique that breaks data dependences by predicting the outcome of an instruction and executes speculatively it's data dependent instruction based on the predicted outcome. In this paper, the performance of a hybrid value prediction scheme with dynamic classification mechanism is measured and analyzed by using execution-driven simulator for SPECint95 benchmark set.

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The Influence of Scarcity Message on Customers' Perceived Value, Satisfaction, and Repurchase Intention in the Context of Group-Buying Social Commerce (공동구매형 소셜커머스에서 희소성메시지가 고객의 지각된 가치, 만족, 재구매의도에 미치는 영향)

  • Choi, Sujeong
    • Journal of Information Technology Applications and Management
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    • v.23 no.1
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    • pp.97-117
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    • 2016
  • Drawing on the theoretical framework of customer value-satisfaction-loyalty, this study examines how scarcity message influences customers' value, satisfaction, and loyalty in the context of group-buying social commerce. Previous studies have argued that scarcity message limiting the avilability of products and service is a source of enhancing customer value. In this regard, this study posits scarcity message as a predictor of customer value. Furthermore, this study classifies customer value into two forms (i.e., utilitarian value and hedonic value) and verfies how scarcity message is associated with them. To test the proposed research model and hypotheses, this study performed structural equation modeling (SEM) analyses, using a total of 292 data collected on users who have experience in purchasing products and service through group-buying social commerce sites such as Coupang, Timon, and WeMakePrice. The key results are as follows : First, scarcity message increases utilitarian and hedonic values and further customer satisfaction. Second, utilitarian value increases customer satisfaction and repurchase intention while hedonic value has nothing to do with them. The findings imply that customers seek to maximize utilitarian value through group-buying social commerce. Finally, this study indicates that repuchase intention depends greatly on customer satisfaction.

Position Control of Linear Actuator with Time Delay Using the Smith Predictor

  • Kang, Seung-Won;Park, Gi-sang
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.68.1-68
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    • 2001
  • This paper discusses tracking position control of linear actuator that has a time delay. The time delay happens when the process reads the sensor data and sends the control input to the plant located at a remote site in distributed control system. In this thesis, the time delay between the linear actuator and the discrete PID controller has constant value due to buffer device so the time delay can be modeled by Pade approximation but the large position error of the linear actuator is generated by the time delay. Therefore, the Smith predictor is used for tracking position control of the linear actuator with the time delay in order to minimize the effect of the time delay. The experimental and simulation results show that the ...

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Demand Forecasting for New Service using the Diffusion Model (확산모형 (Diffusion Model)을 이용한 새로운 서비스 수요예측)

  • Kim, Gyeong-Taek;Park, Se-Gwon
    • Journal of Korean Institute of Industrial Engineers
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    • v.13 no.1
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    • pp.25-29
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    • 1987
  • When the historical data are available, the diffusion model, which describes the time pattern of the adoption process of a new product or technology or service, has been used as a reasonable predictor in the telecommunication demand forecasting area. This paper shows that the diffusion model is applicable when the historical data are not available. The model used is in the form of a "logistic" function. The parameters of the function are estimated using the questionnaire and the historical data of reference products. From the questionnaire, an initial and an upper limit long run value of the market share are estimated, and the diffusion time to the upper limit value is determined by the relation between the investment and the utility.

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Export-Import Value Nowcasting Procedure Using Big Data-AIS and Machine Learning Techniques

  • NICKELSON, Jimmy;NOORAENI, Rani;EFLIZA, EFLIZA
    • Asian Journal of Business Environment
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    • v.12 no.3
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    • pp.1-12
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    • 2022
  • Purpose: This study aims to investigate whether AIS data can be used as a supporting indicator or as an initial signal to describe Indonesia's export-import conditions in real-time. Research design, data, and methodology: This study performs several stages of data selection to obtain indicators from AIS that truly reflect export-import activities in Indonesia. Also, investigate the potential of AIS indicators in producing forecasts of the value and volume of Indonesian export-import using conventional statistical methods and machine learning techniques. Results: The six preprocessing stages defined in this study filtered AIS data from 661.8 million messages to 73.5 million messages. Seven predictors were formed from the selected AIS data. The AIS indicator can be used to provide an initial signal about Indonesia's import-export activities. Each export or import activity has its own predictor. Conventional statistical methods and machine learning techniques have the same ability both in forecasting Indonesia's exports and imports. Conclusions: Big data AIS can be used as a supporting indicator as a signal of the condition of export-import values in Indonesia. The right method of building indicators can make the data valuable for the performance of the forecasting model.

A Study on the Effect of Anthropomorphism, Intelligence, and Autonomy of IPAs on Continuous Usage Intention: From the Perspective of Bi-Dimensional Value

  • Ping Wang;Sundong Kwon;Weikeon Zhang
    • Asia pacific journal of information systems
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    • v.32 no.1
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    • pp.125-150
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    • 2022
  • Technology companies launched their intelligent personal assistants (IPAs). IPAs not only provide individuals with a convenient way to interact with technology but also offer them the opportunity to interact with AI in a useful and meaningful form. Therefore, the global IPAs have experienced tremendous growth over the past decade. But maintaining continuous usage intention is still a massive challenge for developers and marketers and previous technology adoption models are not enough to explain continuous usage intention of IPAs. Thus, we adopted the bi-dimensional perspectives of utilitarian and hedonic value in this research model, and investigated how three characteristics of IPAs - anthropomorphism, autonomy, and intelligence - affect utilitarian value and hedonic value, which in turn continuous usage intentions. 227 data were collected from IPA users. The results showed that IPAs' continuous usage intention is significantly determined by both utilitarian and hedonic value, with the hedonic value being more prominent. In addition, the results showed that anthropomorphism and intelligence are the most important antecedents of utilitarian and hedonistic value. The results also illustrated that autonomy is a crucial predictor of utilitarian value rather than hedonistic value. Our work contributes to current research by widening the theoretical understanding of the effect of IPA characteristics on continuous usage intention through bi-dimensional values. Our paper also provides IPAs' developer and marketer guidelines for enhancing continuous usage intention.

Effects of Family Value on Family Adaptation in Family Who has a Child with Cancer (가족 가치관이 암환아 가족의 적응에 미치는 영향)

  • Park In-Sook;Tak Young-Ran;Lee Jung-Aee
    • Child Health Nursing Research
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    • v.7 no.4
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    • pp.494-510
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    • 2001
  • As a family respond to any stressful situation as a whole system, cancer diagnosis of a child, as a serious life event, could be emotional shock to destroy homeostasis of the family system. A family has a resilient capacity to adjust and adapt to stressful events. Previous studies have been focused on family stress and adaptation, but little attention has been given to family value as one of resilient factors. The data for model testing were collected from July 18, 2000 to August 30, 2000 and the analysis included 309 parents of children who are diagnosed as cancer, 18 or less years of age, and treated either hospitalized or at the outpatient clinics. The data analysis utilized SAS 6.12 and LISREL 8 for descriptive statistics, correlation, cluster analysis, factor analysis, and LISREL. The study findings are as follows. 1) Monthly income (γ=-0.28, t=-5.81) was the most important factor to explain family strain along with family support (γ=-0.11, t=-2.43), severity of children's illness (γ=0.26, t=5.22), and family stressor (γ=0.22, t=4.62). All of these factors together explained 40% of variance in family strain. 2) Among general family value, the relationship with the parents (γ=0.28, t=4.89) and relationship with the children (γ=0.20, t=3.60) showed positive effects to family value for cancer children, while relationship with the spouse (γ=-0.19, t=-3.22) and the age of the cancer children (γ=-0.11, t=-2.21) showed negative effects. These predictors together explained 22% of variance in family value for cancer children. 3) Family hardiness was explained mostly by family strain (γ=-0.53, t=-8.65) along with direct negative effects of family persistency and indirect negative effects of severity of children's illness, family stressor, relationship with the spouse, and the children's age. Family value for cancer children was the most important predictor with positive effect (γ=0.44, t=6.76) along with indirect effects of monthly income, relationship with the parents, relationship with the children, support from family and significant others, and confidence with the health professionals. 51% of variance in family hardiness was explained by all of these predictors. 4) The most important predictor for family adaptation was family stressor (γ=-0.50, t=-6.85) with direct and indirect negative effects along with the severity of children's illness (γ=-0.27, t=-5.21). However, family value for cancer children showed compromised total effect (γ=-0.13, t=-1.99) with negative direct effects (γ=-0.28, t=-3.43) and positive indirect effects (γ=0.14, t=3.01). Similarly, confidence with the health professionals also showed compromised total effect (γ=0.09, t=1.99) with positive direct effects and negative indirect effects. Family hardiness showed the biggest positive direct effects while other factors such as monthly income, family stressor, family persistence, support of family and significant others, relationship with the parents, relationship with the children, and relationship with the spouse, and children's age showed indirect effects only. 39% of variance in family adaptation was explained by all of these predictors.

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An Application of Canonical Analysis on the Distribution of Lichens in Mt. Duckyuoo (덕유산 지의식물 분포에 대한 정준분석법의 적용연구)

  • Park, Seung Tai
    • The Korean Journal of Ecology
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    • v.9 no.3
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    • pp.135-147
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    • 1986
  • The simplification and the searching trends of complex data which assumed relationship between predictor variables and object variables are one of primary objective of ecological research. This study was aimed to apply cononical analysis consisting of canonical correlation analysis and canonical variate analysis related to lichen vegetation and several environmental variables which are elevation, height on grond, exposure side and cover values. Data collected from the Duckyoo National Park in August 1985. Lichen species was ranked by eqivocation information theory with cover values. Canonical correlation analysis was applied to one data set both set both environmental variables and lichem family. In order to make two sets of data matrix the scale of position vector ordination was calculated from the vector scalar product for lichen species. Canonical variate analysis was applied to rearranged data which was made by interval class code for environmental variables. The sharpness values was calculated in frequency of cotingency tables and the dispersion profiles of each species in classes of environmental variables was designed to extract component values based on the decomposition of expected frequencies in contingency table. The results of canonical correlation analysis revealed canonical first correlation value 0.815(89%), and second correlation value 0.083(11%). Significance test showed that the hypothesis of joint mutuallity of canonical correlation is accepted (P>0.05). The relation between canonical score of vegetation variables and that of environmental variable indicated linear tendency.

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Boosting green cars retail in Malaysia: The influence of conditional value on consumers behaviour

  • ALGANAD, Amr Mohammed Nasser;ISA, Normalisa Md;FAUZI, Waida Irani Mohd
    • Journal of Distribution Science
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    • v.19 no.7
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    • pp.87-100
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    • 2021
  • Purpose: This paper examined the role of conditional value in the green automotive industry. The relationships of conditional value's four factors, consumers' attitudes and consumers' intention to purchase green cars were investigated. The conditional value was extended by examining the effect of fuel prices. Research design, data, and methodology: This study is quantitatively designed. All variables were measured using a 7-point Likert-scale; 425 questionnaires were collected from the respondents in Malaysia. SmartPLS was utilized to examine the proposed nine hypotheses. Result: The results demonstrate a positive relationship between attitude and intention toward green cars. Additionally, the results of the relationships were as follows: fuel prices was the most significant predictor of Malaysian consumers' attitudes and consumers' intention to purchase green cars, followed by environmental consequences and government policy. However, retail sales promotions did not show a significant effect on both consumers' attitudes and intentions. Conclusion: The study's findings suggest that the Malaysian government should implement an integrated package that includes a fuel pricing policy that restricts the purchase of non-green cars, as well as a set of financial incentives for purchasing green cars. Moreover, it is valuable to conduct public awareness campaigns about the negative consequences of current consumption patterns.