• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.16-22
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• 2024

Robotic grasping in unstructured environments poses a significant challenge, demanding precise estimation of gripping positions for diverse and unknown objects. Generative Grasping Convolution Neural Network (GG-CNN) can estimate the position and direction that can be gripped by a robot gripper for an unknown object based on a three-dimensional depth map. Since GG-CNN uses only a depth map as an input, the precision of the depth map is the most critical factor affecting the result. To address the challenge of depth map precision, we integrate the Segment Anything Model renowned for its robust zero-shot performance across various segmentation tasks. We adjust the components corresponding to the segmented areas in the depth map aligned through external calibration. The proposed method was validated on the Cornell dataset and SurgicalKit dataset. Quantitative analysis compared to existing methods showed a 49.8% improvement with the dataset including surgical instruments. The results highlight the practical importance of our approach, especially in scenarios involving thin and metallic objects.

• Biomolecules & Therapeutics
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• v.32 no.4
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• pp.451-459
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• 2024

Apoptosis signal-regulating kinase 1 (ASK1) is an upstream signaling molecule in oxidative stress-induced responses. Because oxidative stress is involved in asthma pathogenesis, ASK1 gene deficiency was investigated in animal models of allergic asthma. However, there is no study to investigate whether ASK1 inhibitors could be applied for asthma to date. Selonsertib, a potent and selective ASK1 inhibitor, was applied to BALB/c mice of an ovalbumin (OVA)-induced allergic asthma model. Selonsertib suppressed antigen-induced degranulation of RBL-2H3 mast cells in a concentration-dependent manner. The administration of selonsertib both before OVA sensitization and OVA challenge significantly reduced airway hyperresponsiveness, and suppressed eosinophil numbers and inflammatory cytokine levels in the bronchoalveolar lavage fluid. Histopathologic examination elucidated less inflammatory responses and reduced mucin-producing cells around the peribronchial regions of the lungs. Selonsertib also suppressed the IgE levels in serum and the protein levels of IL-13 in the bronchoalveolar lavage fluid. These results suggest that selonsertib may ameliorate allergic asthma by suppressing immune responses and be applicable to allergic asthma.

• The Journal of Korean Academic Society of Nursing Education
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• v.11 no.2
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• pp.127-134
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• 2005

Purpose: The purpose of the study was to develop a cooperative clinical nursing education model in response to the challenge to provide quality clinical instruction for nursing students. Method: A hypothesized model was developed based on literature review and Cho's partnership model of preservice teacher. Final model was refined with cooperative committee meetings, workshop and post clinical education meetings. Results: A Cooperative clinical nursing education model was developed with three phases(collaboration, planning, redefinition of major roles) and ten constructs(organization of cooperative committee, goal setting, partnership contract, planning objectives, and operating manual). Conclusion: The Cooperative clinical nursing education model support the need for continued collaborative partnership between nursing college and hospitals to foster quality clinical instruction.

• Journal of KIBIM
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• v.7 no.3
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• pp.40-48
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• 2017

It only takes one failed project to wipe out an entire year's profit, when the projects are not managed efficiently. Additionally, escalating costs of materials and a competitive local construction market make subcontractors a challenge. Subcontractors have finite resources that should be allocated simultaneously across many projects in a dynamic manner. Significant scheduling problems are posed by concurrent multi-projects with limited resources. The objective of this thesis is to identify the effect of productivity changes on the total cost resulting from shifting crews across projects using a descriptive model. To effectively achieve the objective, this study has developed a descriptive cost model for a subcontractor with multi-resources and multi-projects. The model was designed for a subcontractor to use as a decision-making tool for resources allocation and scheduling. The model identified several factors affecting productivity. Moreover, when the model was tested using hypothetical data, it produced some effective combinations of resource allocation with associated total costs. Furthermore, a subcontractor minimizes total costs by balancing overtime costs, tardiness penalties, and incentive bonus, while satisfying available processing time constraints.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.8
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• pp.821-827
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• 2014

Many researches on the usage of shared spectrum have continuously been carried out to solve the recent frequency shortage problem and to use efficiently the spectrum without interference. Also, exponential mobile data growth and the solutions needed to address this challenge are parallel key objectives addressed in many countries. Spectrum policy innovation to meet this challenge is the ASA/LSA (Authorized Shared Access/Licensed Shared Access), which is the best access model to employ the small cell technology to meet this mobile traffic growth. Because 3.5 GHz bands is considered as the ASA/LSA frequency, in this paper, we propose the SAM(Spectrum Access Model) in 3~4 GHz bands to estimate the available ASA/LSA bands and to open more free spectrum. These results are utilized as the data to develop the SAM for the small cell and the open frequency in future.

• Journal of The Korean Association of Information Education
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• v.19 no.1
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• pp.21-30
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• 2015

Information and knowledge society in the 21st century computer education is very important. Computer programming education in computer education is very important. There are very few teaching and learning model of computer programming education. In this paper, we develop a self-regulated learning model for students to be self-regulated learning. In this study, we propose self-regulated learning elements, a self-regulated learning steps and self-regulated learning modele. Self-regulated learning elements are task level, generalized level, and efficiency level. Self-regulated learning phases are problem understanding, design, and coding, testing, and maintenance. Self-regulated learning models are to copy, to modify, create, and to challenge. The results of this study are as follows. At Correlations between learning elements and achievement, generalized level, and efficiency level are higher than the task level. At Correlations between learning and achievement, Understanding and design stages are higher than the other stages. At Correlations between learning model and achievement, to transform, to create, and to challenge are higher than to copy.

• Journal of Korea Multimedia Society
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• v.7 no.4
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• pp.484-495
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• 2004

In this paper appears that in this extremely attractive and growing services segment, academics, as well as practitioners, would benefit from investigating the relationships among the players' loyalty, word of mouth and flow, and the impacts of several other key game-related constructs on consumer behavioral intentions. A conceptual framework is proposed and a structural equation model is developed. This paper develops the exploratory LISREL model for identifying the factors affecting the players' loyalty for some specific brand of online games. The concept of flow, feedback, challenge, etc, are all introduced into the model, as the independent variables affecting the loyalty directly and indirectly. Statistical results show that depending upon the types of games, the configuration of structural equation model is a little different from each other, but overall results are very much intuitive in that challenge positively enforces flow, and flow strengthens loyalty. Other interesting results concerning game development strategy are also provided. It is hoped that this result might provide the useful guidelines for developing the successful online game contents. With a better understanding of the players' behavioral intentions, online game developers should be able to make adjustments in their development and marketing plans, providing them with a sustainable advantage over their competition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.5
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• pp.533-539
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• 2019

This study proposes a malware classification model that can handle arbitrary length input data using the Microsoft Malware Classification Challenge dataset. We are based on imaging existing data from malware. The proposed model generates a lot of images when malware data is large, and generates a small image of small data. The generated image is learned as time series data by Dynamic RNN. The output value of the RNN is classified into malware by using only the highest weighted output by applying the Attention technique, and learning the RNN output value by Residual CNN again. Experiments on the proposed model showed a Micro-average F1 score of 92% in the validation data set. Experimental results show that the performance of a model capable of learning and classifying arbitrary length data can be verified without special feature extraction and dimension reduction.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.65-70
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• 2018

Wireless data broadcasting system that can support any number of clients is the effective alternative for the challenge of scalability in ubiquitous computing in IoT environment. In the system, it is important to evaluate quickly the performance parameter, the access time that means how quickly the client access desired data items. In this paper, we derive the mathematical model for the access time in the wireless data broadcast system adopting two-tier indexing scheme. The derived model enables to evaluate the access time without the complicated simulation. In order to evaluate the model, we compare the access time by the model with the access time by the simulation.

• Journal of the military operations research society of Korea
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• v.25 no.2
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• pp.44-61
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• 1999

Cost estimation has posed a significant challenge to estimators, planners, and managers in both government and military. Considerable historical evidence shows that accurate cost estimation has been difficult to achieve across a wide range of projects, including weapon systems. This paper introduces new cost estimating concept, CAIV(Cost As an Independent Variable) and a cost estimating case study using PRICE model, computer aided parametric estimating models(CAPE) for K1 tank cost estimate. CAIV concept is to set realistic but aggressive cost objectives easily in each acquisition program and to achieve cost, schedule, and performance objectives considering various managing risks with a project manager and industry teams. The Price model is one of computer aided cost estimating models and widely used in U.S. defense system analysis as a tool for CAIV. We analyze theories, inputs, outputs of the PRICE model and present a case study for K1 tank to estimate costs in requirement and concept phase, program and budgeting phase, and life cycle phase. Finally we obtain results that the Price model can be used in various phases of PPBEES depending upon available data and time.