• Journal of the Korean association of regional geographers
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• v.19 no.2
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• pp.246-258
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• 2013

The relocation of the public institutions such as the provincial government attracts much attentions since it results in substantial regional economic impacts. In this context this paper analyzes the effects of relocation of Gyeongsangbuk-Do provincial government from Daegu city to Gyeongsangbuk-Do, which is scheduled for 2014, on Daegyeong economic region. Based on the interregional input-output model and I-O data which were provided by the Bank of Korea, this paper examines the multiplier effects of the relocation in terms of production, value added, and employment on Daegyeong economic region and other regions, except for the construction effects of the provincial capital. According to the analysis, the relocation is expected to reduce the production by 290million won, value added by 709million won, and employment by 571 persons in Daegyeong economic region. Also, the relocation turns out to decrease the production by 1,179million won and value added by 123million won of other regions. This paper discusses some policy implications of the analysis.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.1 s.13
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• pp.53-63
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• 1999

For the close range digital photogrammetry, multi-step procedures should be embodied in an integrated system. However, it is hard to construct an Integrated system through conventional procedural processing. Using Object Oriented Programming(OOP), photogrammetric processings can be classified with corresponding subjects and it is easy to construct an integrated system lot digital photogrammetry as well as to add the newly developed classes. In this study, the equation of 3-dimensional mathematic model is developed to make an immediate calibration of the CCD camera, the focus distance of which varies according to the distance of the object. Classes for the input and output of images are also generated to carry out the close range digital photogrammetric procedures by OOP. Image matching, coordinate transformation, dirct linear transformation and bundle adjustment are performed by producing classes corresponding to each part of data processing. The bundle adjustment, which adds the principle coordinate and focal length term to the non-photogrammetric CCD camera, is found to increase usability of the CCD camera and the accuracy of object positioning. In conclusion, classes and their hierarchies in the digital photogrammetry are designed to manage multi-step procedures using OOP and close range digital photogrammetric process is implemented using CCD camera in an integrated System.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.139-146
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• 2002

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input-output pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless these algorithms can learn the optimal policy if the agent can visit every state-action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem, we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL) as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state space effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. In this paper we use the AMMQL algorithn as a learning method for dynamic positioning of the robot soccer agent, and implement a robot soccer agent system called Cogitoniks.

• Journal of Korean Society of Transportation
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• v.25 no.3
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• pp.55-63
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• 2007

This paper analyzes the relative efficiency of Korea's logistics industry with the DEA-ANP model from 2003 to 2005. To measure the efficiency, this paper used the numbers of employees, fixed assets. total capital. and operating costs as input factors and sales amounts and net incomes as output factors. The average efficiency score of the entire logistics industry is 0.175, so most logistics companies in Korea should improve their current inefficiencies. The industry with the highest efficiency score is marine transportation. with an average three-year efficiency score of 0.3692. In terms of sales and high efficiency. most of the highest-ranked companies belong to the marine transportation industry, so marine transportation has the most influence on raising the efficiency score of Korea's logistics industry. To improve the inefficiency of inputs that exists overall in the logistics industry it is necessary to control excessive numbers of employees. To improve the amount of sales, it is necessary to make a policy of satisfying various logistics demands, continuous investments, and attracting foreign logistics demand: such things will help strengthen the international competitiveness of Korea's logistics industry.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.31-43
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• 2017

This study was aimed at analyzing the operational efficiency of DPAs(the delivery and pickup agents), which serve as sub-terminals in parcel delivery services, using CCR/BCC models in DEA. The input variables included the number of employees, and the amount of equipment and the operating expenses. The output variable was revenue value. The efficiency for the period from 2014 to 2016 was analyzed. The results revealed that the operational efficiency improved in 2016, compared with 2014, in both CCR and BCC models. According to the benchmarking analysis, DMU 1 and DMU 7 showed higher efficiency in 2016. The inefficiency analysis based on the BCC model showed increased efficiency of all factors in 2016 when compared with 2014. The Malmquist productivity index (MPI) dropped slightly as a result of technical changes and indicated a declining technical efficiency in all DMUs. This study suggests the need for government-led systematic improvement and support for DPAs by providing current insight into the parcel delivery industry and analyzing DPAs' operational efficiency in Korea for the first time. This research performed efficiency analysis of DPAs located in new town of paju and gimpo cities. In future research, comparative study on efficiency analysis including new town, old town area, and other cities are needed.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.6
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• pp.97-104
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• 2010

In this paper, ICT (in circuit tester) inspection system and inspection algorithm is proposed and detects whether inferiority exists or not in the mounted device on the flexible PCB in cell phones or mobile display devices. The system is composed of PD (pin-driver) and GGM (ground guarding method). The structural characteristics of these flexible PCB are analyzed, which is needed to input or output the test signal. Test signal to investigate the characteristics of passive components is generated using modified circuit diagram and proposed inspection algorithm. PM (pin-map) is decided on the basis of circuit diagram and has the information about the kind of test signal to be applied and the pad number for the test signal to be connected. PD is designed to load a proper test signal for a specific pad and is adjusted according to PM so that the reconstructed circuit has minimum node and mash. The proposed ICT inspection system is realized using PD and GGM. Using the system, an experiment for each passive component is done to investigate the measurement accuracy of the developed system and an experiment for real flexible PCB model is done to verity the effectiveness of the system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.18-31
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• 2002

In this study, we introduce a concept of advanced neurofuzzy polynomial networks(ANFPN), a hybrid modeling architecture combining neurofuzzy networks(NFN) and polynomial neural networks(PNN). These networks are highly nonlinear rule-based models. The development of the ANFPN dwells on the technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks and genetic algorithms. NFN contributes to the formation of the premise part of the rule-based structure of the ANFPN. The consequence part of the ANFPN is designed using PNN. At the premise part of the ANFPN, NFN uses both the simplified fuzzy inference and error back-propagation learning rule. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. As the consequence structure of ANFPN, PNN is a flexible network architecture whose structure(topology) is developed through learning. In particular, the number of layers and nodes of the PNN are not fixed in advance but is generated in a dynamic way. In this study, we introduce two kinds of ANFPN architectures, namely the basic and the modified one. Here the basic and the modified architecture depend on the number of input variables and the order of polynomial in each layer of PNN structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the ANFPN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed ANFPN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• Journal of Technology Innovation
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• v.21 no.1
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• pp.59-83
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• 2013

Recently, the importance of the health care industry is increasing due to the rapid changes in the population structure caused by decreasing in fertility rate and aging population. Therefore expansion of government investment in R&D of the health care industry is needed as the demand of health care is increasing. This study attempts to examine the economic impacts of national research and development for the health care industry using an inter-industry analysis. Specifically, the study investigates production-inducing effect, value added inducing effect, and employment-inducing effect of the health care industry based on demand-driven model. These analyses pay particular and close attention to the health care industry by taking it as exogenous rather than endogenous. Here we present results. First, the production-inducing effect and value added inducing effect was high in common real estate and business services and finance and insurance sector. Second, employment-inducing effect of the health care industry showed the highest levels in wholesale and retail sector, followed by the real estate and business services, agriculture sector. Third, the actual 2009 health care industry-related national R&D investment embracing on the production-inducing effect and value added inducing effect. The health care industry R&D induces the production of 4,932 billion won and the value added of 2163 billion won.

• The Journal of Engineering Geology
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• v.15 no.1
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• pp.67-76
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• 2005

This paper presents the application of a neural network for prediction of the unconfined compressive strength from physical properties and schmidt hardness number on rock samples. To investigate the suitability of this approach, the results of analysis using a neural network are compared to predictions obtained by statistical relations. The data sets containing 55 rock sample records which are composed of sandstone and shale were assembled in Daegu area. They were used to learn the neural network model with the back-propagation teaming algorithm. The rock characteristics as the teaming input of the neural network are: schmidt hardness number, specific gravity, absorption, porosity, p-wave velocity and S-wave velocity, while the corresponding unconfined compressive strength value functions as the teaming output of the neural network. A data set containing 45 test results was used to train the networks with the back-propagation teaming algorithm. Another data set of 10 test results was used to validate the generalization and prediction capabilities of the neural network.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.299-336
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• 2017

The purpose of this study is to identify the differential effects of transformational leadership and organizational justice on psychological contract breach and work engagement, and to suggest practical implications. To this purpose, this study theoretically references equity theory which recognizes the relationship between organizational input and output, social exchange theory which explains the exchange relationship between members and organization, and job demand-resource (JD-R) model that combines job demands and job resources. A empirical study was conducted on 277 employees at 18 companies of diverse industries including manufacturing, distribution, and finance, and to eliminate the common method bias problem, the dependent variable was measured using peer evaluation. The results of this study showed that: 1) both transformational leadership and organizational justice had a significant positive effect on work engagement and significant negative effect on psychological contract breach; and 2) psychological contract breach played a partial mediating role in the relationship between transformational leadership and work engagement as well as between organizational justice and work engagement. Therefore, this study suggests that, as organizational justice has stronger influence on work engagement and psychological contract breach than transformational leadership, organizations should not only train its leaders but also guarantee fairness.