• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.491-499
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• 2021

The purpose of this study was to examine the moderating effect of attitude toward green brand on green brand positioning and repurchase intention of environmentally friendly products, product knowledge on attitude toward green brand and the effect of green product knowledge on green repurchase intention. This study uses a structural equation approach with a sample size of 175 and uses an eight-point Likert scale. The data collection technique used purposive sampling. The criteria for respondents are to use environmentally friendly cosmetic products and the respondents live in Central Java and have consumed more than two times. Online sampling using google form. Data were analyzed using statistical software AMOS 22. The results showed that green brand positioning has a significant effect on repurchase intention. Attitude toward green brand has a positive effect in mediating the relationship between green brand positioning and repurchase intention. Similarly, green brand knowledge has a positive effect on attitudes, although green knowledge has no positive effect on repurchase intention. Product positioning in the minds of consumers is important in shaping attitudes. It is important for companies to continue to develop environmentally friendly products so that product positioning can be distinguished from competitors' products.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.411-413
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• 2010

The wireless AP positioning system is under active progress regarding research and commercialization due to its merit of being able to overcome the representing demerits of existing GPS positioning, which are signal distortion and poor signal reception. This system's feature is to collect AP information distributed throughout the real world, store it on database, and execute positioning by comparing with searched AP information. The positioning process uses collected data, whereas comparison of database data uses the fingerprinting method. The fingerprinting method is a probabilistic modeling method that acquires as much of the data collected from one location upon database composition, to store the value's average value and use it in positioning. Yet, using the average value may contain the probability of errors. Such errors are fatal weaknesses for services based on the background of accurate positioning. This paper deals with the characteristics and problems of the previously used wireless AP positioning system, and proposes measures of using AP information for outdoor positioning in order to solve the aforementioned problems.

• Journal of Positioning, Navigation, and Timing
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• v.2 no.2
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• pp.131-137
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• 2013

In this study, positioning results that combined the code observation information of GPS and GLONASS navigation satellites were analyzed. Especially, the distribution of GLONASS satellites observed in Korea and the combined GPS/GLONASS positioning results were presented. The GNSS data received at two reference stations (GRAS in Europe and KOHG in Goheung, Korea) during a day were processed, and the mean value and root mean square (RMS) value of the position error were calculated. The analysis results indicated that the combined GPS/GLONASS positioning did not show significantly improved performance compared to the GPS-only positioning. This could be due to the inter-system hardware bias for GPS/GLONASS receivers, the selection of transformation parameters between reference coordinate systems, the selection of a confidence level for error analysis, or the number of visible satellites at a specific time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.641-642
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• 2018

Currently, the performance of positioning technology based on radio wave fingerprint is greatly influenced by the selection of data comparison algorithm. In this case, the accuracy of the indoor positioning can be greatly improved by the data expansion technique necessary for the learning structure. In this paper, we discuss the importance of learning structure that can be applied to actual positioning through classification and extension of learning data to construct learning structure based on Wi-Fi radio fingerprint.

• Journal of information and communication convergence engineering
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• v.16 no.2
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• pp.114-124
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• 2018

This paper illustrates a vision-based vehicle positioning method at an intersection to support the C-ITS. It removes the minor shadow that causes the merging problem by simply eliminating the fractional parts of a quotient image. In order to separate the occlusion, it firstly performs the distance transform to analyze the contents of the single foreground object to find seeds, each of which represents one vehicle. Then, it applies the watershed to find the natural border of two cars. In addition, a general vehicle model and the corresponding space estimation method are proposed. For performance evaluation, the corresponding ground truth data are read and compared with the vision-based detected data. In addition, two criteria, IOU and DEER, are defined to measure the accuracy of the extracted data. The evaluation result shows that the average value of IOU is 0.65 with the hit ratio of 97%. It also shows that the average value of DEER is 0.0467, which means the positioning error is 32.7 centimeters.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.4
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• pp.285-294
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• 2018

In this study, we implemented the data quality monitoring algorithm which is the previous step for real-time Global Navigation Satellite System (GNSS) correction generation and compared Global Positioning System (GPS) and BeiDou System (BDS). Signal Quality Monitoring (SQM), Data QM, and Measurement QM (MQM) that are well known in Ground Based Augmentation System (GBAS) were used for quality monitoring. SQM and Carrier Acceleration Ramp Step Test (CARST) of MQM result were divided by satellite elevation angle and analyzed. The data which are judged as abnormal are removed and presented as Root Mean Square (RMS), standard deviation, average, maximum, and minimum value.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.527-539
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• 2023

In the positioning algorithm of two-dimensional planar sensor array, the estimation error of time difference-ofarrival (TDOA) algorithm is difficult to avoid. Thus, how to achieve accurate positioning is a key problem of the positioning technology based on planar array. In this paper, a method of sensor reliability discrimination is proposed, which is the foundation for selecting positioning sensors with small error and excellent performance, simplifying algorithm, and improving positioning accuracy. Then, a positioning model is established. The estimation characteristics of the least square method are fully utilized to calculate and fuse the positioning results, and the non-uniform weighting method is used to correct the weighting factors. It effectively handles the decreased positioning accuracy due to measurement errors, and ensures that the algorithm performance is improved significantly. Finally, the characteristics of the improved algorithm are compared with those of other algorithms. The experiment data demonstrate that the algorithm is better than the standard least square method and can improve the positioning accuracy effectively, which is suitable for vibration detection with large noise interference.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.456-457
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• 2021

Recently, in order to more accurately provide indoor location-based services, technologies using Wi-Fi fingerprints and deep learning are being studied. Among the deep learning models, an RNN model that can store information from the past can store continuous movements in indoor positioning, thereby reducing positioning errors. When using an RNN model for indoor positioning, the collected training data must be continuous sequential data. However, the Wi-Fi fingerprint data collected to determine specific location information cannot be used as training data for an RNN model because only RSSI for a specific location is recorded. This paper proposes a region clustering technique for sequential input data generation of RNN models based on Wi-Fi fingerprint data.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.2
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• pp.53-58
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• 2003

It is very important to measure linear cycle plane positioning accuracy of NC lathe as it effects all other parts of machines machined by them in industries. If the plane positioning accuracy of NC lathe is bad, the dimension accuracy and the change-ability of works will be bad in the assembly of machine parts. In this paper, computer software systems are organized to measure linear cycle plane positioning displacement of ATC(Automatic tool changer) on zx plane of NC lathe using two linear scales. And each sets of error data obtained from the test is descriptions to plots and the results of linear cycle plane positioning errors are expressed as nutriments by computer treatment.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.1
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• pp.35-41
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• 2017

Precise Point Positioning (PPP) method is based on dual-frequency data of Global Navigation Satellite Systems (GNSS). The recent multi-constellations GNSS (multi-GNSS) enable us to bring great opportunities for enhanced precise positioning, navigation, and timing. In the paper, the multi-GNSS PPP with a combination of four systems (GPS, GLONASS, Galileo, and BeiDou) is analyzed to evaluate the improvement on positioning accuracy and convergence time. GNSS observations obtained from DAEJ reference station in South Korea are processed with both the multi-GNSS PPP and the GPS-only PPP. The performance of multi-GNSS PPP is not dramatically improved when compared to that of GPS only PPP. Its performance could be affected by the orbit errors of BeiDou geostationary satellites. However, multi-GNSS PPP can significantly improve the convergence speed of GPS-only PPP in terms of position accuracy.