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High‑Temperature Deformation Behavior of MnS in 1215MS Steel
Fei‑Ya Huang,Yen‑Hao Frank Su,Jui‑Chao Kuo 대한금속·재료학회 2018 METALS AND MATERIALS International Vol.24 No.6
The effect of manganese sulfide (MnS) inclusions on the machinability of free-cutting steel is based on their morphology,size and distribution. Furthermore, the plasticity of MnS is high during the hot working caused different characterizationof MnS. In this study, the deformation behavior of MnS in 1215MS steel after a thermomechanical process was investigatedat 1323 K. The microstructures of MnS inclusions were characterized by optical microscopy, scanning electronmicroscopy, energy-dispersive spectrometry, and electron backscattering diffraction (EBSD). As the thickness reductionof the inclusions increased from 10 to 70%, their average aspect ratio increased from 1.20 to 2.39. In addition, the deformabilityof MnS inclusions was lower than that of the matrix. The possible slip systems of A, B, C, and D plane traces werē10̄1̄101 , 10̄ 1 [101], (011) 01̄ 1 , and (110) 1̄10 . Furthermore, the EBSD measurements suggested that slip planes inMnS inclusions occur on {110} planes.
Treatment Planning in Smart Medical: A Sustainable Strategy
( Fei Hao ),( Doo-soon Park ),( Sang Yeon Woo ),( Se Dong Min ),( Sewon Park ) 한국정보처리학회 2016 Journal of information processing systems Vol.12 No.4
With the rapid development of both ubiquitous computing and the mobile internet, big data technology is gradually penetrating into various applications, such as smart traffic, smart city, and smart medical. In particular, smart medical, which is one core part of a smart city, is changing the medical structure. Specifically, it is improving treatment planning for various diseases. Since multiple treatment plans generated from smart medical have their own unique treatment costs, pollution effects, side-effects for patients, and so on, determining a sustainable strategy for treatment planning is becoming very critical in smart medical. From the sustainable point of view, this paper first presents a three-dimensional evaluation model for representing the raw medical data and then proposes a sustainable strategy for treatment planning based on the representation model. Finally, a case study on treatment planning for the group of “computer autism” patients is then presented for demonstrating the feasibility and usability of the proposed strategy.
Similarity Evalution between Graphs: A Formal Concept Analysis Approach
Fei Hao,심대수,박두순,서형석 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.5
Many real-world applications information are organized and represented with graph structure which is oftenused for representing various ubiquitous networks, such as World Wide Web, social networks, and proteinproteininteractive networks. In particular, similarity evaluation between graphs is a challenging issue inmany fields such as graph searching, pattern discovery, neuroscience, chemical compounds exploration andso forth. There exist some algorithms which are based on vertices or edges properties, are proposed foraddressing this issue. However, these algorithms do not take both vertices and edges similarities into account. Towards this end, this paper pioneers a novel approach for similarity evaluation between graphs based onformal concept analysis. The feature of this approach is able to characterize the relationships between nodesand further reveal the similarity between graphs. Therefore, the highlight of our approach is to take verticesand edges into account simultaneously. The proposed algorithm is evaluated using a case study for validatingthe effectiveness of the proposed approach on detecting and measuring the similarity between graphs.
Similarity Evaluation between Graphs: A Formal Concept Analysis Approach
( Fei Hao ),( Dae-soo Sim ),( Doo-soon Park ),( Hyung-seok Seo ) 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.5
Many real-world applications information are organized and represented with graph structure which is often used for representing various ubiquitous networks, such as World Wide Web, social networks, and proteinprotein interactive networks. In particular, similarity evaluation between graphs is a challenging issue in many fields such as graph searching, pattern discovery, neuroscience, chemical compounds exploration and so forth. There exist some algorithms which are based on vertices or edges properties, are proposed for addressing this issue. However, these algorithms do not take both vertices and edges similarities into account. Towards this end, this paper pioneers a novel approach for similarity evaluation between graphs based on formal concept analysis. The feature of this approach is able to characterize the relationships between nodes and further reveal the similarity between graphs. Therefore, the highlight of our approach is to take vertices and edges into account simultaneously. The proposed algorithm is evaluated using a case study for validating the effectiveness of the proposed approach on detecting and measuring the similarity between graphs.
Treatment Planning in Smart Medical: A Sustainable Strategy
Hao, Fei,Park, Doo-Soon,Woo, Sang Yeon,Min, Se Dong,Park, Sewon Korea Information Processing Society 2016 Journal of information processing systems Vol.9 No.3
With the rapid development of both ubiquitous computing and the mobile internet, big data technology is gradually penetrating into various applications, such as smart traffic, smart city, and smart medical. In particular, smart medical, which is one core part of a smart city, is changing the medical structure. Specifically, it is improving treatment planning for various diseases. Since multiple treatment plans generated from smart medical have their own unique treatment costs, pollution effects, side-effects for patients, and so on, determining a sustainable strategy for treatment planning is becoming very critical in smart medical. From the sustainable point of view, this paper first presents a three-dimensional evaluation model for representing the raw medical data and then proposes a sustainable strategy for treatment planning based on the representation model. Finally, a case study on treatment planning for the group of "computer autism" patients is then presented for demonstrating the feasibility and usability of the proposed strategy.
Four-Leg Object Recognition for Service Robot Based on Top-hat Transformation
Hao Wu,Guohui Tian,Xinran Wang,Fei Lu 보안공학연구지원센터 2014 International Journal of Control and Automation Vol.7 No.12
A method of object recognition for objects with special topological structure is developed based on top-hat transformation for service robot. The objects with four legs are easily detected and recognized by service robot with laser ranger array by this method. First, the top-hat transformation in one dimension is reviewed, then the recognition strategy of self-adapting threshold for objects with special topological structure is proposed, and the general data process for object recognition and position is proposed and analyzed. Experimental results show that the process of object recognition based on top-hat transformation proposed in this article is an effective and accurate application.
Similarity Evaluation between Graphs: A Formal Concept Analysis Approach
Hao, Fei,Sim, Dae-Soo,Park, Doo-Soon,Seo, Hyung-Seok Korea Information Processing Society 2017 Journal of information processing systems Vol.13 No.5
Many real-world applications information are organized and represented with graph structure which is often used for representing various ubiquitous networks, such as World Wide Web, social networks, and protein-protein interactive networks. In particular, similarity evaluation between graphs is a challenging issue in many fields such as graph searching, pattern discovery, neuroscience, chemical compounds exploration and so forth. There exist some algorithms which are based on vertices or edges properties, are proposed for addressing this issue. However, these algorithms do not take both vertices and edges similarities into account. Towards this end, this paper pioneers a novel approach for similarity evaluation between graphs based on formal concept analysis. The feature of this approach is able to characterize the relationships between nodes and further reveal the similarity between graphs. Therefore, the highlight of our approach is to take vertices and edges into account simultaneously. The proposed algorithm is evaluated using a case study for validating the effectiveness of the proposed approach on detecting and measuring the similarity between graphs.