Browsing by Author "Hung, Hui-Nien"

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A Bayesian approach for group supplier selections based on the popular process-capability-index C-pk
(2016)
Wu, Chin-Chieh
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Shiau, Jyh-Jen Horng
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Pearn, W. L.
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Hung, Hui-Nien
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統計學研究所
Supplier selection is an important part of supply chain management. In the initial stage of production setting, the decision-maker usually faces the problem of selecting the "best\'\' one(s) from available manufacturing material suppliers. For this purpose, process capability indices (PCIs) are commonly used in the literature to rank the suppliers under selection; and among these PCIs, C-pk could be the most popular one. This problem of selecting the best supplier(s) has received considerable attention in the literature but mainly from the frequentist point of view. In this paper, we tackle the so-called group supplier selection problem via the Bayesian approach, namely selecting a group of suppliers that would include the supplier of the largest C-pk value with a high level of confidence in a Bayesian sense. Based on the observed data and available prior information, we develop a practical procedure for the group supplier selection, which is useful for practitioners operating in-plant applications.
A Comprehensive Analysis of Low-Power Operation for Beacon-Enabled IEEE 802.15.4 Wireless Networks
(2009-11-01)
Huang, Yu-Kai
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Pang, Ai-Chun
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Hung, Hui-Nien
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統計學研究所
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Institute of Statistics
ZigBee, a unique communication standard designed for low-rate wireless personal area networks, has extremely low complexity, cost, and power consumption for wireless connectivity of inexpensive, portable, and moving devices. ZigBee uses the IEEE 802.15.4 standard as its communication protocol for medium access control (MAC) layer and physical (PHY) layer. The IEEE 802.15.4 MAC layer achieves duty-cycle operations by setting two system parameters, macBeaconOrder (BO) and macSuperFrameOrder (SO), to achieve low power consumption for ZigBee devices. This study comprehensively analyzes IEEE 802.15.4 duty-cycle operation. Specifically, a novel analytical model that accommodates a general traffic distribution is developed. An NS-2 based simulation model, which is validated by the developed analytical model is also proposed. Through the experiments conducted by the analytical and simulation models, some important performance-evaluation insights are gained that can be used as guidelines for future low-power ZigBee network deployment.
An adaptive GTS allocation scheme for IEEE 802.15.4
(2008-05-01)
Huang, Yu-Kai
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Pang, Ai-Chun
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Hung, Hui-Nien
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統計學研究所
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Institute of Statistics
IEEE 802.15.4 is a new standard uniquely designed for low-rate wireless personal area networks. It targets ultralow complexity, cost, and power for low-rate wireless connectivity among inexpensive, portable, and moving devices. IEEE 802.15.4 provides a Guaranteed Time Slot (GTS) mechanism to allocate a specific duration within a superframe for time-critical transmissions. This paper proposes an adaptive GTS allocation (AGA) scheme for IEEE 802.15.4, which considers low latency and fairness. The scheme is designed based on the existing IEEE 802.15.4 medium access control protocol, and IEEE 802.15.4 devices can receive this AGA service without any modification. A simulation model and an analytical model are developed to investigate the performance of our AGA scheme. The numerical results show that the proposed scheme significantly outperforms the existing IEEE 802.15.4 implementation.
Deriving the distributions for the numbers of short message arrivals
(2014-03-01)
Hung, Hui-Nien
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Lin, Yi-Bing
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Luo, Chao-Liang
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統計學研究所
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資訊工程學系
In the broadband era, narrowband short message service (SMS) is still the most popular wireless data service. Many studies have been conducted to investigate the performance of SMS based on the arrival rates of short messages. From Chunghwa Telecom's commercial SMS call data records, we observed that even if the SMS arrival rates are the same, the distributions for the number of SMS arrivals per half hour are quite different for various observed days. We further identify that for the SMS traffic in a specific day, there are non-burst and burst periods. This paper investigates the SMS behaviors on weekdays, weekends, and holidays (specifically, new years' days and eves). With the assistance of kernel-based fitting method, we derive the SMS arrival number distributions of various traffic types and observed days. Our approach fits each SMS arrival number distribution by three cubic polynomial functions that can accurately capture the SMS behaviors. On the basis of the SMS arrival number distributions derived from our model, the mobile operators have better understanding about the volumes of short messages in different times and days, which can be used to design more flexible short message charging rates. Copyright (c) 2012 John Wiley & Sons, Ltd.
Deriving the Vehicle Speeds from a Mobile Telecommunications Network
(2013-09-01)
Liou, Ren-Huang
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Lin, Yi-Bing
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Chang, Yu-Long
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Hung, Hui-Nien
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Peng, Nan-Fu
Vehicle speeds are often measured by intelligent transportation systems (ITSs) by utilizing sensors or software solutions. Our previous work proposed the Lin-Chang-Huangfu (LCH) scheme to compute the cell residence times by the standard counter values in mobile telecommunications switches. In this paper, we use mathematical and statistical developments to investigate the accuracy of the LCH scheme by deriving the bias of the cell residence times computed in this scheme. Then, we extend the LCH scheme with some filtering and compensation techniques for vehicle speed estimation and validate our approach with vehicle detector (VD) measurements at National Highway 3, Longtan Township, Taoyuan County, Taiwan. Our study indicates that the LCH scheme is an effective approach to vehicle speed estimation.
Extending the discussion on coverage intervals and statistical coverage intervals
(2006-12-01)
Chen, Lin-An
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Hung, Hui-Nien
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統計學研究所
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Institute of Statistics
Willink ( 2004 Metrologia 41 L5 - 6) is concerned that, in the society of metrology, there is potential for confusion between coverage interval and statistical coverage interval and he makes a precise interpretaion of these two terms. We further clarify that the confidence of a coverage interval is actually a statistical coverage interval.
Maximum average-power (MAP) tests
(2007)
Chen, Lin-An
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Hung, Hui-Nien
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Chen, Chih-Rung
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統計學研究所
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Institute of Statistics
The objective of this article is to propose and study frequentist tests that have maximum average power, averaging with respect to some specified weight function. First, some relationships between these tests, called maximum average-power (MAP) tests, and most powerful or uniformly most powerful tests are presented. Second, the existence of a maximum average-power test for any hypothesis testing problem is shown. Third, an MAP test for any hypothesis testing problem with a simple null hypothesis is constructed, including some interesting classical examples. Fourth, an MAP test for a hypothesis testing problem with a composite null hypothesis is discussed. From any one-parameter exponential family, a commonly used UMPU test is shown to be also an MAP test with respect to a rich class of weight functions. Finally, some remarks are given to conclude the article.
Modeling credit reservation procedure for UMTS online charging system
(2007-11-01)
Son, Sok-Ian
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Hung, Hui-Nien
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Lin, Yi-Bing
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Peng, Nan-Fu
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Jeng, Jeu-Yih
The IP Multimedia Core Network Subsystem (IMS) provides real-time multimedia services for Universal Mobile Telecommunications System (UMTS). Through Recharge Threshold-based Credit Reservation (RTCR) mechanism, prepaid IMS services can be supported by the Online Charging System (OCS) in UMTS. In RTCR, when the remaining amount of prepaid credit is below a threshold, the OCS reminds the user to recharge the prepaid account. It is essential to choose an appropriate recharge threshold to reduce the probability that the in-progress service sessions are forced-terminated. An analytic model is developed to investigate the performance of RTCR for the OCS. Based on our study, the network operator can select the appropriate parameter values for various traffic conditions.
Modeling UMTS power saving with bursty packet data traffic
(2007-12-01)
Yang, Shun-Ren
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Yan, Sheng-Ying
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Hung, Hui-Nien
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統計學研究所
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Institute of Statistics
The universal mobile telecommunications system ( UMTS) utilizes the discontinuous reception ( DRX) mechanism to reduce the power consumption of mobile stations ( MSs). DRX permits an idle MS to power off the radio receiver for a predefined sleep period and then wake up to receive the next paging message. The sleep/ wake- up scheduling of each MS is determined by two DRX parameters: the inactivity timer threshold and the DRX cycle. In the literature, analytic and simulation models have been developed to study the DRX performance mainly for Poisson traffic. In this paper, we propose a novel semi- Markov process to model the UMTS DRX with bursty packet data traffic. The analytic results are validated against simulation experiments. We investigate the effects of the two DRX parameters on output measures including the power saving factor and the mean packet waiting time. Our study provides inactivity timer and DRX cycle value selection guidelines for various packet traffic patterns.
Modeling VolP call holding times for telecommunications
(2007-11-01)
Chen, Whai-En
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Hung, Hui-Nien
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Lin, Yi-Bing
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交大名義發表
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National Chiao Tung University
Voice over IP is one of the most popular applications in broadband access networks. It is anticipated that the characteristics of call holding times (CHTs) for VoIP calls will be quite different from traditional phone calls. This article analyzes the CHTs for mobile VoIP calls based on measured data collected from commercial operation. Previous approaches directly used the Kolmogorov-Smirnov (K-S) test to derive the CHT distributions, which may cause inaccuracy. In this article we propose a new approach to derive the CHT distributions for mobile VoIP calls and other call types. Specifically, our approach uses hazard rate to select an appropriate distribution, and then utilizes the K-S test to validate our selection. We show that. the mobile VoIP CHT distribution can be accurately approximated by a mix of two log-normal distributions. Based on the derived distributions, we compare the mobile VoIP CHTs with those for non-VoIP calls and fixed-network VoIP calls. Our study indicates that the characteristics for mobile VoIP calls are quite different from those of the non-VoIP mobile phone calls and are more close to those of fixed-network phone calls.
Sample size determination for a specific region in multiregional clinical trials with multiple co-primary endpoints
(2017-06-30)
Huang, Wong-Shian
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Hung, Hui-Nien
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Hamasaki, Toshimitsu
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Hsiao, Chin-Fu
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統計學研究所
Recently, multi-regional clinical trials (MRCTs), which incorporate subjects from many countries/ regions around the world under the same protocol, have been widely conducted by many global pharmaceutical companies. The objective of such trials is to accelerate the development process for a drug and shorten the drug's approval time in key markets. Several statistical methods have been purposed for the design and evaluation of MRCTs, as well as for assessing the consistency of treatment effects across all regions with one primary endpoint. However, in some therapeutic areas (e.g., Alzheimer's disease), the clinical efficacy of a new treatment may be characterized by a set of possibly correlated endpoints, known as multiple co-primary endpoints. In this paper, we focus on a specific region and establish three statistical criteria for evaluating consistency between the specific region and overall results in MRCTs with multiple co-primary endpoints. More specifically, two of those criteria are used to assess whether the treatment effect in the region of interest is as large as that of the other regions or of the regions overall, while the other criterion is used to assess the consistency of the treatment effect of the specific region achieving a pre-specified threshold. The sample size required for the region of interest can also be evaluated based on these three criteria.
SEMI-PARAMETRIC INFERENCE FOR COPULA MODELS FOR TRUNCATED DATA
(2011-01-01)
Emura, Takeshi
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Wang, Weijing
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Hung, Hui-Nien
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統計學研究所
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Institute of Statistics
We investigate the dependent relationship between two failure time variables that truncate each other. Chaieb, Rivest, and Abdous (2006) proposed a semi-parametric model under the so-called "semi-survival" Archimedean-copula assumption and discussed estimation of the association parameter, the truncation probability, and the marginal functions. Here the same model assumption is adopted but different inference approaches are proposed. For estimating the association parameter, we extend the conditional likelihood approach (Clayton (1978)) and the two-by-two table approach (Wang (2003)) to dependent truncation data. We further show that the three estimators, including that proposed by Chaieb, Rivest, and Abdous (2006), differ in weights. The likelihood approach provides the formula for a good weight. Large sample properties of the proposed methods are established by applying the functional delta method, which can handle estimating functions that are not in the form of U-statistics. Analytic formulae for the asymptotic variance estimators are provided. Two competing methods are compared via simulations, and applied to the transfusion-related AIDS data.
SensorTalk: An IoT Device Failure Detection and Calibration Mechanism for Smart Farming
(2019-11-01)
Lin, Yi-Bing
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Lin, Yun-Wei
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Lin, Jiun-Yi
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Hung, Hui-Nien
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交大名義發表
In an Internet of Things (IoT) system, it is essential that the data measured from the sensors are accurate so that the produced results are meaningful. For example, in AgriTalk, a smart farm platform for soil cultivation with a large number of sensors, the produced sensor data are used in several Artificial Intelligence (AI) models to provide precise farming for soil microbiome and fertility, disease regulation, irrigation regulation, and pest regulation. It is important that the sensor data are correctly used in AI modeling. Unfortunately, no sensor is perfect. Even for the sensors manufactured from the same factory, they may yield different readings. This paper proposes a solution called SensorTalk to automatically detect potential sensor failures and calibrate the aging sensors semi-automatically. Numerical examples are given to show the calibration tables for temperature and humidity sensors. When the sensors control the actuators, the SensorTalk solution can also detect whether a failure occurs within a detection delay. Both analytic and simulation models are proposed to appropriately select the detection delay so that, when a potential failure occurs, it is detected reasonably early without incurring too many false alarms. Specifically, our selection can limit the false detection probability to be less than 0.7%.
Short-Term Traffic Prediction for Edge Computing-Enhanced Autonomous and Connected Cars
(2019-04-01)
Yang, Shun-Ren
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Su, Yu-Ju
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Chang, Yao-Yuan
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Hung, Hui-Nien
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統計學研究所
Autonomous and connected cars (ACCs), together with edge computing (EC), have been recognized as a promising solution to achieve green intelligent transportation for smart cities. This paper aims to address short-term traffic prediction, a fundamental enabler for the success of ACC applications, under the European Telecommunications Standards Institute multiaccess EC (MEC) architecture that exhibits constraints different from conventional cloud computing. First, a data-centric experiment platform is designed and implemented to facilitate traffic prediction algorithm development. This paper further proposes a novel short-term traffic prediction model that integrates a traffic light model and a vehicle velocity model, considering limited computing resources of MEC servers. We note that the effects of traffic lights are complicated and have not been rigorously examined in most, if not all, of the related work. This work models the queueing time when a driver arrives at a road intersection and faces a red light. Moreover, to forecast the vehicle velocity, we propose a novel low-complexity semiparametric prediction model considering periodic features and spatial/temporal correlations of dynamic road events. The experiment results demonstrate that our vehicle-velocity prediction model achieves almost equivalent accuracy to the well-known Long Short-Term Memory Neural Network model, requiring much lower computational complexity. Our experiment results also confirm that since our integrated model pays attention to the traffic-light effects and the individual driver behavior, it can more effectively capture the real-time changes of traffic conditions.
Statistical inferences based on outliers for gene expression analysis
(2017-08-01)
Lai, Yi-Hsuan
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Chen, Hung-Chia
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Chen, Lin-An
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Chen, Dung-Tsa
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Hung, Hui-Nien
Discovering differential genes through the detection of outliers in samples from disease group subjects is a new and important approach for gene expression analysis. Extending the outlier mean of Chen et al. (2010a), we develop the asymptotic distributions of the outlier least squares estimator (LSE) and the outlier proportion for the linear regression model. An optimal property of the best linear outlier mean acting as an outlier estimator version of the Gauss Markov theorem for the outlier LSE is presented. Power comparisons demonstrate that tests based on outlier estimators are competitive in detecting a shift of the parent tail distribution. An analysis of DNA microarray data from samples of pancreatic breast tumors supports the use of outlier-based methods. (C) 2017 Elsevier B.V. All rights reserved.