• Journal of Distribution Science
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• v.21 no.7
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• pp.65-71
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• 2023

Purpose: This study attempted to analyze the impacts of the backward linkage and output multipliers, and investigate the price fluctuation and the price forecast amongst the manufacturing sectors associated with food processing industrial output of Thailand. Research design, data and methodology: The Thailand Input-Output table with a size of 180 x 180 sectors from 2005, 2010, and 2015 was utilized while the secondary data of the time series from January 2002 to December 2021 were processed via a multiplicative model and Box-Jenkins model. Results: The backward linkage analysis indicates that canning and preserving of the meat sector majorly utilized the factors of production from the slaughtering sector; canning and preservation of fish and other seafoods sector largely used those factors from the ocean and coastal fishing sector; and the sugar sector used those of the sugarcane sector. Notably, the output multiplier analysis indicated that output multipliers of those 3 manufacturing sectors were highly increased; meanwhile the price fluctuation continually existed in all forms. Besides, the price forecast suggested that prices of chicken and sugarcane tended to be higher; whereas, the price of shrimp was unstable. Conclusions: Food processing industry contains the favorable components to be one of the industries of the future of Thailand.

• Journal of Power Electronics
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• v.18 no.6
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• pp.1912-1919
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• 2018

The output capacitance of power semiconductor devices is important in determining the switching losses and in the operation of some resonant converter topologies. Thus, it is important to be able to accurately determine the output capacitance of a particular device operating at elevated power levels so that the contribution of the output capacitance discharge to switch-on losses can be determined under these conditions. Power semiconductor switch manufacturers usually measure device output capacitance using small-signal methods that may be insufficient for power switching applications. This paper shows how first principle methods are applied in a novel way to obtain more relevant large signal output capacitances of Gallium-Nitride (GaN) FETs using the drain-source voltage transient during device switch-off numerically. A non-linear capacitance for an increase in voltage is determined with good correlation. Simulations are verified using experimental results from two different devices. It is shown that the large signal output capacitance as a function of the drain-source voltage is higher than the small signal values published in the data sheets for each of the devices. It can also be seen that the loss contribution of the output capacitance discharging in the channel during switch-on correlates well with other methods proposed in the literature, which confirms that the proposed method has merit.

• Solar Energy
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• v.6 no.1
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• pp.37-46
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• 1986

This paper deals with analytical methods for estimating the optimal design parameters of wind turbine from power output curve. Asmussen [5] has been used a linearized power output curve for an analytical expression for the specific output of wind turbine generators, but a nonlinear power output curve is developed to determine the design parameters of optimal wind turbine in this study that has maximum specific output and minimum swept area. Thus, the design results of this research will yield reliabilities in construction of wind turbine system and detailed results are presented for several district in Korea. Although the results presented pertain to a wind turbine system without storage, the design approach is equally applicable to system with storage.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.699-708
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• 2015

In the testing of a software component-based robot system, generating test cases for the system is a time-consuming and difficult task that requires the combining of test data. This paper proposes an adaptive combinatorial testing method which is based on the input/output relationship among components and which automatically generates the test cases for the system. The proposed algorithm first generates an input/output relationship graph in order to analyze the input/output relationship of the system. It then generates the reduced set of test cases according to the analyzed type of input/output relationship. To validate the proposed algorithm some comparisons are given in terms of the time complexity and the number of test cases.

• Journal of Information Technology Applications and Management
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• v.25 no.3
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• pp.17-28
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• 2018

In this paper, an activity-oriented usability model is proposed. The usability model contains two types of characteristics: special-type characteristics of usability and sub-characteristics of usability. Workability, study-ability, and playability are, but do not exhaust, examples of special-type characteristic of usability. They correspond to working, studying, and playing using the software product, respectively. They represent the goal of using and can overlap each other. They are usability too by themselves. Navigate-ability, data-prepare-ability, data-input-ability, response-wait-ability, output-examine-ability, and output-utilize-ability are typical examples of sub-characteristics of usability. They correspond to navigating, preparing data, inputting data, waiting response, examining output, and utilizing the output data, respectively. They are not usability by themselves. They constitute usability together as a group. Assessing is the fundamental and indispensable aspect of quality. Without assessing, the concept of quality has little practical value. Satisfaction, effectiveness, and efficiency are the most typical sub-characteristics of usability in existing quality models, which correspond to the evaluation criteria of usability. In the activity-oriented usability model, however, only the user's satisfaction is included: Satisfaction is regarded as the operational definition of usability in the user's view. As the result, usability can be interpreted as the 'goodness for using, which is evaluated by the user. 'Three fundamental principles regarding software quality models are proposed too in this paper: Principles of Parsimony, Cohesiveness, and Inheritance. Discussions illustrate well that typical existing usability models violate these basic principles. Many authors have tried to define general usability models which can be applied to most kinds of software. The dream of the general and universal usability model, however, may be an illusion. The activity-oriented usability model is expected to serve as a prototype from which specialized usability models can be derived.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.3
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• pp.273-284
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• 2020

The performance of Global Navigation Satellite System (GNSS) chipset and Inertial Measurement Unit (IMU) sensors embedded in smartphones for location-based services (LBS) is limited due to the economic reasons for their mass production. Therefore, it is necessary to efficiently process the output data of the smartphone's embedded sensors in order to derive the optimum navigation values and, as a previous step, output performance of smartphone embedded sensors needs to be verified. This paper analyzes the navigation performance of such devices by processing the raw measurements data output from smartphones. For this, up-to-dated versions of smartphones provided by Samsung (Galaxy s10e) and Xiaomi (Mi 8) are used in the test experiment to compare their performances and characteristics. The GNSS and IMU data are extracted and saved by using an open market application software (Geo++ RINEX Logger & Mobile MATLAB), and then analyzed in post-processing manner. For GNSS chipset, data is extracted from static environments and verified the position, Carrier-to-Noise (C/N₀), Radio Frequency Interference (RFI) performance. For IMU sensor, the validity of navigation and various location-based-services is predicted by extracting, storing and analyzing data in static and dynamic environments.

• Journal of Korean Society on Water Environment
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• v.21 no.1
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• pp.21-28
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• 2005

The training and prediction modeling using an artificial neural network was implemented to predict the turbidity of treated water as well as to estimate the optimized feed concentration of polyaluminium chloride (PACl) in a water treatment plant. The parameters used in the input layers were pH, temperature, turbidity and alkalinity, while those in output layers were PACl and turbidity of treated water. Levenberg-Marquadt method of feedforward back-propagation perceptron in the neural network toolbox of MATLAB program was used in this study. Correlation coefficients of the training data with the measured data were 0.9997 for PACl and 0.6850 for turbidity and those of the testing data with measured data were 0.9140 for PACl and 0.3828 for turbidity, when four parameters at input layer, 12-12 nodes each at both the first and the second hidden layers, and two parameters(PACl and turbidity) at output layer were used. Although the predictability of PACl was improved, compared to that of the previous studies to use the only coagulant dose as output layer, turbidity in treated water could not be predicted well. Acquisition of more data through several years obtained with the advanced on-line measuring system could make the artificial neural network useful and practical in actual water treatment plants.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.2
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• pp.38-44
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• 2003

In this paper, we propose the method in which multimedia data simultaneously transfers to the main memory and the multimedia processor from the network interface card to improve bottleneck of system bus through analysis for architecture of video conference system and input/output model. The proposed method can reduce the number of system bus accesses, bus cycles, data transmission time and compression ratio of video data in the video conference system. We compared the performance between the proposed method and the conventional methods in the multi-party video conference systems. The simulation results showed that the proposed method was reduced the transmission time of multimedia data than the conventional method.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.3
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• pp.154-163
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• 2010

Process monitoring of output variables affecting final performance have been mainly executed in semiconductor manufacturing process. However, even earlier detection of causes of output variation cannot completely prevent yield loss because a number of wafers after detecting them must be re-processed or cast away. Semiconductor manufacturers have put more attention toward monitoring process inputs to prevent yield loss by early detecting change-point of the process. In the paper, we propose the method to efficiently monitor functional input variables in multi-phase semiconductor manufacturing process. Measured input variables in the multi-phase process tend to be of functional structured form. After data pre-processing for these functional input data, change-point analysis is practiced to the pre-processed data set. If process variation occurs, key variables affecting process variation are selected using contribution plot for monitoring efficiency. To evaluate the propriety of proposed monitoring method, we used real data set in semiconductor manufacturing process. The experiment shows that the proposed method has better performance than previous output monitoring method in terms of fault detection and process monitoring.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5A
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• pp.641-647
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• 2008

This paper introduces a new technique that can extract natural frequencies and damping ratios from output-only vibration data. Firstly, the free vibration data is obtained from the cross correlations of the output-only response data using a singular value decomposition process. Secondly, the well-known system identification algorithm is applied to extract the natural frequencies and damping ratios from the extracted free vibration data. Comparing to ERADC technique, the accuracy of the proposed modal parameter identification algorithm has been numerically examined. Furthermore, the practicability of the proposed algorithm has been examined through the output-only acceleration data collected from the Seohae cable-stayed bridge. Using the proposed technique, total 24 modes have been identified for the deck plate motions of the bridge.