• Journal of Positioning, Navigation, and Timing
• /
• v.13 no.4
• /
• pp.457-466
• /
• 2024

The quasi-zenith satellite system (QZSS) provides sub-meter level augmentation service (SLAS) to improve the positioning accuracy of single-frequency GPS L1 receiver users. The SLAS correction consists of differential GPS information (DGPS) and the corrections are transmitted via quasi-zenith satellites (QZS). The DGPS correction reduces the effect of pseudo-range errors due to satellite orbit, clock and atmospheric delay errors. Thirteen SLAS reference stations in Japan generate the correction data. The performance of the DGPS correction depends on several factors, including location of reference stations, distance between the user and reference station, etc. The long-term performance of the SLAS corrections was evaluated by processing data over a five-year period (2019-2023). The SLAS corrections were applied to GPS observations at the IGS stations in Japan and the positioning accuracy was evaluated. The correlation with the ionospheric activity and the latitude of the SLAS reference stations was also evaluated.

• The Journal of Economics, Marketing and Management
• /
• v.12 no.6
• /
• pp.11-25
• /
• 2024

Purpose: This study investigates the challenges and conflicts arising from complaints in alleyway housing redevelopment projects, aiming to generate actionable insights for improving project outcomes. The purpose of this research is to explore the nature of these complaints, understand their origins, and propose effective administrative strategies for mitigation. Research design, data and methodology: Employing focus group interviews (FGI) as a primary data collection method, this study reviews existing legislative and procedural frameworks to contextualize the complaints within governmental response mechanisms. Results: Initial findings indicate that high resident interest and responsiveness in early project stages lead to fewer complaints. However, the formation of steering committees often triggers significant grievances due to asymmetrical information and unclear project planning. Complaints intensify following the establishment of associations, evolving into legal disputes over rights, legitimacy, and financial aspects, eventually decreasing significantly after the management disposition phase. Conclusions: The study underscores the need for improved communication strategies and transparent administrative practices in managing alleyway housing redevelopment projects. Implementing centralized control mechanisms similar to those in the USA could provide a structured approach to complaint management, significantly reducing project delays and resident dissatisfaction.

• The Journal of Korea Robotics Society
• /
• v.19 no.4
• /
• pp.335-346
• /
• 2024

When people empathize, nonverbal communication such as facial expressions and gestures is more weighted than language. Therefore, in the human-robot interaction (HRI), it is important for robots to recognize and understand facial expression of humans. This is because it helps emotional communication and alleviates the psychological distance between robots and humans. In this paper, we introduce the robot system using facial expression recognition and motion generation models for interaction with human. It recognizes human emotions using POSTER++ based on Vision Transformer (ViT) and generates motions using FLAME that is developed to utilize diffusion model. In our scenario, we first perceive facial expression by POSTER++ and generate appropriate reaction texts using text generation model, Gemini AI. Then, we input the generated reaction text into FLAME to obtain 3D motion data, and the data is used to get arm joint angles that is calculated for Forward Kinematics (FK) and Inverse Kinematics (IK). Focusing on scenarios involving human interaction, we only use the head and arm motors of the humanoid robot, HUMIC. Furthermore, we simulate scenarios to verify that our system can recognize facial expression and show various reaction motions.

• Journal of Intelligence and Information Systems
• /
• v.20 no.4
• /
• pp.1-23
• /
• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of Internet Computing and Services
• /
• v.19 no.1
• /
• pp.37-47
• /
• 2018

The number of capabilities of Internet of Things (IoT) devices will exponentially grow over the next years. These devices may generate a vast amount of time-constrained data. In the context of IoT, data management should act as a layer between the objects and devices generating the data and the applications accessing the data for analysis purposes and services. In addition, most of IoT services will be content-centric rather than host centric to increase the data availability and the efficiency of data delivery. IoT will enable all the communication devices to be interconnected and make the data generated by or associated with devices or objects globally accessible. Also, fog computing keeps data and computation close to end users at the edge of network, and thus provides a new breed of applications and services to end users with low latency, high bandwidth, and geographically distributed. In this paper, we propose Edge-Fog cloud-based Hierarchical Data Delivery ($EFcHD^2$) method that effectively and reliably delivers IoT data to associated with IoT applications with ensuring time sensitivity. The proposed $EFcHD^2$ method stands on basis of fully decentralized hybrid of Edge and Fog compute cloud model, Edge-Fog cloud, and uses information-centric networking and bloom filters. In addition, it stores the replica of IoT data or the pre-processed feature data by edge node in the appropriate locations of Edge-Fog cloud considering the characteristic of IoT data: locality, size, time sensitivity and popularity. Then, the performance of $EFcHD^2$ method is evaluated through an analytical model, and is compared to fog server-based and Content-Centric Networking (CCN)-based data delivery methods.

• The Journal of Society for e-Business Studies
• /
• v.27 no.2
• /
• pp.1-20
• /
• 2022

As the global business environment is rapidly changing due to the 4th industrial revolution, new jobs that did not exist before are emerging. Among them, the job that companies are most interested in is 'Data Scientist'. As information and communication technologies take up most of our lives, data on not only online activities but also offline activities are stored in computers every hour to generate big data. Companies put a lot of effort into discovering new opportunities from such big data. The new job that emerged along with the efforts of these companies is data scientist. The demand for data scientist, a promising job that leads the big data era, is constantly increasing, but its supply is not still enough. Although data analysis technologies and tools that anyone can easily use are introduced, companies still have great difficulty in finding proper experts. One of the main reasons that makes the data scientist's shortage problem serious is the lack of understanding of the data scientist's job. Therefore, in this study, we explore the job competencies of a data scientist by qualitatively analyzing the actual job posting information of the company. This study finds that data scientists need not only the technical and system skills required of software engineers and system analysts in the past, but also business-related and interpersonal skills required of business consultants and project managers. The results of this study are expected to provide basic guidelines to people who are interested in the data scientist profession and to companies that want to hire data scientists.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.6
• /
• pp.2237-2244
• /
• 2013

In this study, physics based K-DRUM(K-water Distributed RUnoff Model) using GIS spatial hydrologic data as input data was developed to account for the temperature variation according to the altitude change considering snow melt and cover. The model was applied for Pakistan Kunhar River Basin($2,500km^2$) to calculate long-term discharge considering snow melt and cover. Time series analysis of the temperature and rainfall data reveals that temperature and rainfall of the river basin differs significantly according to altitude change compared to domestic basin. Thus, applying temperature and altitude lapse rate during generate input data generation. As a result, calculated discharge shows good agreement with observed ones considering snow melt and accumulation characteristic which has the difference of 4,000 meter elevation above sea level. In addition, the simulated discharge strongly showed snow melting effect associated with temperature rise during the summer season.

• Journal of Korea Multimedia Society
• /
• v.11 no.2
• /
• pp.247-256
• /
• 2008

Recently, natural disasters like flooding damages have frequently occurred as to typhoons and local downpours affected by the climate changes. Many researches have actively been studied in analysing runoff models, the verification of their parameters, and the inflow on surfaces in order to lessen the damages. However, much time and effort needs in generating input files of the models in most current researches. Therefore, in this paper we develop a system for generating a simulation input data automatically. This system is connected to the EPA-SWMM based on the spatial data in the UIS systems and consists the simulation module for analysing urban flooding and the SWMM simulator module. Also, we construct a prototype using a range of regular inundation to generate a simulation input file. This system gives advantages showing inundation areas based on the map viewer as well as lessening errors of input data and simulation time.

• Korean Journal of Computational Design and Engineering
• /
• v.15 no.3
• /
• pp.212-221
• /
• 2010

Proposed in the paper is a methodology to generate kinematic template for 3D JIG models. Recently, according to increase of the rate of automatic facility in manufacturing system, the 3D manufacturing and verification research and development have been issued. So, unlike in the past, moving 3D facilities are very various like JIGs, turn table, AS/RS worked in the automated manufacturing industry. Because 3D mesh models are used in these kinds of 3D simulation, users have to define the kinematic information manually. This 3D mesh data doesn't have parametric information and design history of the 3D model unlike the design level data. So, it is lighter than 3D design level data and more efficient to render on the 3D virtual manufacturing environment. But, when user wants to find a common axis located between the links, the parameter information of the model has to reconstruct for defining kinematic construction. It takes a long time and very repetitive to define an axis and makes a joint using 3D mesh data and it is non-intuitive task for user. This paper proposed template model that provides kinematic information of the JIG. This model is kinds of a state diagram to describe a relation between links. So, this model can be used for a kinematic template to the JIG which has a same mechanism. The template model has to be registered in the template library to use in the future, after user made the model of the specific type of the 3D JIG model.