• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.40-49
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• 2019

Reinforcement learning has been applied to various problems in robotics. However, it was still hard to train complex robotic manipulation tasks since there is a few models which can be applicable to general tasks. Such general models require a lot of training episodes. In these reasons, deep neural networks which have shown to be good function approximators have not been actively used for robot manipulation task. Recently, some of these challenges are solved by a set of methods, such as Guided Policy Search, which guide or limit search directions while training of a deep neural network based policy model. These frameworks are already applied to a humanoid robot, PR2. However, in robotics, it is not trivial to adjust existing algorithms designed for one robot to another robot. In this paper, we present our implementation of Guided Policy Search to the robotic arms of the Baxter Research Robot. To meet the goals and needs of the project, we build on an existing implementation of Baxter Agent class for the Guided Policy Search algorithm code using the built-in Python interface. This work is expected to play an important role in popularizing robot manipulation reinforcement learning methods on cost-effective robot platforms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2718-2731
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• 2019

Conjunctive keyword search encryption is an important technique for protecting sensitive data that is outsourced to cloud servers. However, the process of searching outsourced data may facilitate the leakage of sensitive data. Thus, an efficient data search approach with high security is critical. To solve this problem, an efficient conjunctive keyword search scheme based on ciphertext-policy attribute-based encryption is proposed for cloud storage environment. This paper proposes an efficient mechanism for removing the secure channel and resisting off-line keyword-guessing attacks. The storage overhead and the computational complexity are regardless of the number of keywords. This scheme is proved adaptively secure based on the decisional bilinear Diffie-Hellman assumption in the standard model. Finally, the results of theoretical analysis and experimental simulation show that the proposed scheme has advantages in security, storage overhead and efficiency, and it is more suitable for practical applications.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.1
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• pp.1-11
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• 2017

Stochastic resource-constrained project scheduling problem is an extension of resource-constrained project scheduling problem such that activity duration has stochastic nature. In real situation where activity duration is not known until the activity is finished, open-loop based static policies such as activity-based policy and priority-based policy will not well cope with duration variability. Then, a dynamic policy based on closed-loop decision making will be regarded as an alternative toward achievement of minimal makespan. In this study, a dynamic policy designed to select activities to start at each decision time point is illustrated. The performance of static and dynamic policies based on variable neighborhood search is evaluated under the discrete-event simulation environment. Experiments with J120 sets in PSPLIB and several probability distributions of activity duration show that the dynamic policy is superior to static policies. Even when the variability is high, the dynamic policy provides stable and good solutions.

• Korean Journal of Health Education and Promotion
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• v.33 no.3
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• pp.109-119
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• 2016

Objectives: To review policy contents which can have a direct impact on health-enhancing physical activity(PA) prevalence in Korea. Methods: The web-search and a literature was undertaken to identify reports and documents related to policy contents of PA. The web-search mainly focused on the web site of the departments and organizations relevant to PA policy and was supplemented by the literature searching. Results: The results of this study are as follows: First, the goal of PA does not match the established number of the Health Plan(HP). Second, the recommended levels of PA is not the same as levels of the year of establishment of the HP. Third, the questions of monitoring tool were inconsistent across years. Conclusions: Therefore, policy contents of physical activity should be improved to ensure accurate PA prevalence in Korea.

• Health Policy and Management
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• v.28 no.2
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• pp.119-127
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• 2018

Background: This study aimed to examine (1) the patterns of online health information search with respect to seeking and scanning, and (2) how online search, along with eHealth literacy, predicts perceived information usefulness in the context of diet and weight control. Methods: Online survey was conducted with 299 adults from the consumer panel recruited for the purpose of quality assessment of the Korean National Health Information Portal in 2016. We conducted paired sample t-test and multiple logistic regression to address the research questions. Data analysis was performed using IBM SPSS Statistics ver. 24.0 (IBM Corp., Armonk, NY, USA) and SAS ver. 9.3 (SAS Institute Inc., Cary, NC, USA). Results: Of the respondents, 38.8% were 'high seek-high scanners,' 35.8% were 'low seek-low scanners,' 13.0% were 'high seek-low scanners,' and 12.4% were 'low seek-high scanners.' eHealth literacy was a significant, positive predictor of online information scanning (odds ratio [OR], 2.46; 95% confidence interval [CI], 1.41-4.29), but not for online information seeking (OR, 1.75; 95% CI, 1.00-3.05). With respect to perceived usefulness of online information seeking, online seeking (OR, 4.90; 95% CI, 2.19-11.00) and eHealth literacy (OR, 2.30; 95% CI, 1.11-4.75) were significant predictors. Perceived usefulness of online scanning had a significant association with online scanning (OR, 2.38; 95% CI, 1.08-5.22), but not with eHealth literacy. Conclusion: To increase the effectiveness of the health policy for online information search and related outcomes in the context of diet and weight control, it is important to develop education programs promoting eHealth literacy.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.1-9
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• 2023

This paper presents an optimal path planning strategy for aerial searching and surveying of a user-designated area using multiple Unmanned Aerial Vehicles (UAVs). The method is designed to deal with a single unseparated polygonal area, regardless of polygonal convexity. By defining the search area into a set of grids, the algorithm enables UAVs to completely search without leaving unsearched space. The presented strategy consists of two main algorithmic steps: cellular decomposition and path planning stages. The cellular decomposition method divides the area to designate a conflict-free subsearch-space to an individual UAV, while accounting the assigned flight velocity, take-off and landing positions. Then, the path planning strategy forms paths based on every point located in end of each grid row. The first waypoint is chosen as the closest point from the vehicle-starting position, and it recursively updates the nearest endpoint set to generate the shortest path. The path planning policy produces four path candidates by alternating the starting point (left or right edge), and the travel direction (vertical or horizontal). The optimal-selection policy is enforced to maximize the search efficiency, which is time dependent; the policy imposes the total path-length and turning number criteria per candidate. The results demonstrate that the proposed cellular decomposition method improves the search-time efficiency. In addition, the candidate selection enhances the algorithmic efficacy toward further mission time-duration reduction. The method shows robustness against both convex and non-convex shaped search area.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.37-42
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• 2015

Although online search engine service provide a convenient means to search for information on the World Wide Web, it also poses a risk of disclosing privacy. Regardless of such risk, most of users are neither aware of their personal information being exposed on search results nor how to redress the issue by requesting removal of information. According to the 2015 parliamentary inspection of government offices, many government agencies were criticized for mishandling of personal information and its leakage on online search engine such as Google. Considering the fact that the personal information leakage via online search engine has drawn the attention at the government level, the online search engine and privacy issue needs to be rectified. This paper, by examining current online search engines, studies the degree of personal information exposure on online search results and its underlying issues. Lastly, based on research result, the paper provides a sound policy and direction to the removal of exposed personal information with respect to search engine service provider and user respectively.

• Journal of Information Technology Services
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• v.12 no.3
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• pp.389-404
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• 2013

Geospatial information, which is one of social overhead capital, is predicted as a core growing industry for the future. The production of geospatial information requires a huge budget, so it is very important objective of the policy for geospatial information to prevent the duplication of geospatial projects. In this paper, we proposed a semantic search system which extracts possible duplication of geospatial projects by using ontology for geospatial project administration. In order to achieve our goal, we suggested how to construct and utilize geospatial project ontology, and designed the architecture and process of the semantic search. Moreover, we showed how the suggested semantic search works with a duplicated projects search scenario. The suggested system enables a nonprofessional can easily search for duplicated projects, therefore we expect that our research contributes to effective and efficient duplication review process for geospatial projects.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.14-28
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• 2015

Numerous research has been conducted using internet search data since the mid-2000s. For example, Google Inc. developed a service predicting influenza patterns using the internet search data. The main objective of this study is to prove the hypothesis that highway traffic indices are similar to the internet search patterns. In order to achieve this objective, a model to predict the number of vehicles entering the expressway and space-mean speed was developed and the goodness-of-fit of the model was assessed. The results revealed several findings. First, it was shown that the Google search traffic was a good predictor for the TCS entering traffic volume model at sites with frequent commute trips, and it had a negative correlation with the TCS entering traffic volume. Second, the Naver search traffic was utilized for the TCS entering traffic volume model at sites with numerous recreational trips, and it was positively correlated with the TCS entering traffic volume. Third, it was uncovered that the VDS speed had a negative relationship with the search traffic on the time series diagram. Lastly, it was concluded that the transfer function noise time series model showed the better goodness-of-fit compared to the other time series model. It is expected that "Big Data" from the internet search data can be extensively applied in the transportation field if the sources of search traffic, time difference and aggregation units are explored in the follow-up studies.

• Korean Journal of Social Welfare
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• v.43
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• pp.299-327
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• 2000

Although economic crisis is allaying in Korea, the more effective unempoyment policies are requried in this present. So in this paper, we analyze the effects of relevant factors, especially job search behaviors of the unempyoed on reemployment and look for implications to the improvement of unemployment policies. Major findings are as follows: First, we find that job search behaviors, especially the effectiveness of job search activity and job search attitude are significantly different between the unemployed and the re-employed. Second, we find that the variables of job search behaviors - the effectiveness of job search activity (number of job offers), job search attitude (reservation wage), positive use of job search methods - significantly affect the re-employment of the unemployed from logistic regression analysis results. These findings' implications are as follows: First, the approach based on search theory may be useful in finding out determinants of re-employment. Second, the effects of job search behaviors on the reemployment and their implications should be actively accepted to policy makers in order to improve the effectiveness of un-employment policies. It meams that the effects of job search behaviors must be carefully considered in making or restructuring unemployment policies and their administrations.