• International journal of advanced smart convergence
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• v.12 no.3
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• pp.75-88
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• 2023

In a specific domain, experts have different understanding of domain knowledge or different purpose of constructing ontology. These will lead to multiple different ontologies in the domain. This phenomenon is called the ontology heterogeneity. For research fields that require cross-ontology operations such as knowledge fusion and knowledge reasoning, the ontology heterogeneity has caused certain difficulties for research. In this paper, we propose a novel ontology matching model that combines word embedding and a concatenated continuous bag-of-words model. Our goal is to improve word vectors and distinguish the semantic similarity and descriptive associations. Moreover, we make the most of textual and structural information from the ontology and external resources. We represent the ontology as a graph and use the SimRank algorithm to calculate the structural similarity. Our approach employs a similarity queue to achieve one-to-many matching results which provide a wider range of insights for subsequent mining and analysis. This enhances and refines the methodology used in ontology matching.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.658-660
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• 2021

The work within this study develops an algorithm based on the structural similarity index to assess numerically between reconstructed images with a reference image to separate the homogeneity and heterogeneity for diffuse optical tomography. Global geometry and region of interest assessment have been measured to yield the similarity. The results indicate that the mean of structural similarity index shows potential performance to distinguish between visible and invisible inclusion inside the model. Therefore, the structural similarity index may promise to assist the image assessment for evaluating breast structural information.

• Smart Structures and Systems
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• v.23 no.3
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• pp.279-293
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• 2019

To ensure high quality data being used for data mining or feature extraction in the bridge structural health monitoring (SHM) system, a practical sensor fault diagnosis methodology has been developed based on the similarity of symmetric structure responses. First, the similarity of symmetric response is discussed using field monitoring data from different sensor types. All the sensors are initially paired and sensor faults are then detected pair by pair to achieve the multi-fault diagnosis of sensor systems. To resolve the coupling response issue between structural damage and sensor fault, the similarity for the target zone (where the studied sensor pair is located) is assessed to determine whether the localized structural damage or sensor fault results in the dissimilarity of the studied sensor pair. If the suspected sensor pair is detected with at least one sensor being faulty, field test could be implemented to support the regression analysis based on the monitoring and field test data for sensor fault isolation and reconstruction. Finally, a case study is adopted to demonstrate the effectiveness of the proposed methodology. As a result, Dasarathy's information fusion model is adopted for multi-sensor information fusion. Euclidean distance is selected as the index to assess the similarity. In conclusion, the proposed method is practical for actual engineering which ensures the reliability of further analysis based on monitoring data.

• The Mathematical Education
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• v.50 no.1
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• pp.1-12
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• 2011

It is the aim of this paper to study the target problem solving process in reference to the base problem. We observed closely how students solve the target problem in reference to the base problem. The students couldn't solve the target problem, although they succeed to find the base problem. This comes from failing to discover the structural similarity between the target problem and the base problem. Especially it is important to cognize the proper corresponding of primary components between the base problem and target problem. And there is sometimes a part component of the target problem equivalent to the base problem and the target problem can't be solved without the insight into this fact. Consequently, finding the base problem fail to reach solving the target problem without the insight into their structural similarity. We have to make efforts to have an insight into the structural similarity between the target problem and the base problem to solve the target problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1252-1271
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• 2013

Automatic image annotation has become an increasingly important research topic owing to its key role in image retrieval. Simultaneously, it is highly challenging when facing to large-scale dataset with large variance. Practical approaches generally rely on similarity measures defined over images and multi-label prediction methods. More specifically, those approaches usually 1) leverage similarity measures predefined or learned by optimizing for ranking or annotation, which might be not adaptive enough to datasets; and 2) predict labels separately without taking the correlation of labels into account. In this paper, we propose a method for image annotation through collaborative similarity metric learning from dataset and modeling the label correlation of the dataset. The similarity metric is learned by simultaneously optimizing the 1) image ranking using structural SVM (SSVM), and 2) image annotation using correlated label propagation, with respect to the similarity metric. The learned similarity metric, fully exploiting the available information of datasets, would improve the two collaborative components, ranking and annotation, and sequentially the retrieval system itself. We evaluated the proposed method on Corel5k, Corel30k and EspGame databases. The results for annotation and retrieval show the competitive performance of the proposed method.

• Journal of Educational Research in Mathematics
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• v.25 no.1
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• pp.95-111
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• 2015

The purpose of this study is to analyze cases on teaching solutions exploration of Wythoff's game through using the analogy for the gifted elementary students, to suggest useful teaching methods. Students recognized structural similarity among problems on the basis of relevance of conditions of problems. The discovery of structural similarity improves the ability to solve problems. Although 2 groups-NIM game with surface similarity is not helpful in solving Wythoff's game, Queen's move game with structural similarity makes it easier for students to solve Wythoff's game. Useful teaching methods to find solutions of Wythoff's game through using the analogy are as follow. Encoding process helps students make sense of the game. It is significant to help students realize how many stones are remained and how the location of Queen can be expressed by the ordered pair. Inferring process helps students find a solution of 2 groups-NIM game and Queen's move game. It is necessary to find a winning strategy through reversely solving method. Mapping process helps students discover surface similarity and structural similarity through identifying commonalities between the two games. It is crucial to recognize the relationship among the two games based on the teaching in the Encoding process. Application process encourages students to find a solution of Wythoff's game. It is more important to find a solution by using the structural similarity of the Queen's move game rather than reversely solving method.

• Computers and Concrete
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• v.21 no.4
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• pp.385-397
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• 2018

This study is focused on the investigation for similitude the requirements between prototype and scaled models to determine the structural behavior of concrete load bearing systems. The scaling concept has been utilized in many engineering branches, has been assisted to engineers and scientists for obtain the behavior of the prototype by using scaled model. The scaling can be done for two purposes, either scaling up or scaling down depending upon the application. Because, scaled down models are the experimentation on scaled models is cheaper than huge structures. These models also provide facilities for experimental work. Similarity relationships between systems are created either by field equations of the system or by dimensional analysis. Within this study, similarity relationships were obtained by both methods. The similarity relations obtained are applied to different load bearing systems and it is determined that the similarity relation is a general expression. In this study, as an example, column, frame, cantilever beam and simple beam are chosen and 1/2, 1/5 and 1/10 scales are applied. The results are compared with the analytical results which are obtained by creating of the finite element models with SAP2000 software of different scaled load bearing systems. The analysis results of all systems are examined and it is determined that the scale factors are constant depending on the scale types for different load bearing systems.

• Communications of Mathematical Education
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• v.25 no.1
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• pp.21-45
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• 2011

It is the aim of this paper to find the requisites for the target problem solving process in reference to the base problem and to search the roles of those. Focusing on the structural similarity, analytic activity and comparative activity in stage of similar mathematical problem solving process, we tried to find the roles of them. We observed closely how four students solve the target problem in reference to the base problem. And so we got the following conclusions. The insight of structural similarity prepare the ground appling the solving method of base problem in the process solving the target problem. And we knew that the analytic activity can become the instrument which find out the truth about the guess. Finally the comparative activity can set up the direction of solution of the target problem. Thus we knew that the insight of structural similarity, the analytic activity and the comparative activity are necessary for similar mathematical problem to solve. We think that it requires the efforts to develop the various programs about teaching-learning method focusing on the structural similarity, analytic activity and comparative activity in stage of similar mathematical problem solving process. And we also think that it needs the study to research the roles of other elements for similar mathematical problem solving but to find the roles of the structural similarity, analytic activity and comparative activity.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.1
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• pp.99-109
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• 2007

To realize process-driven management, so many companies have been launching business process managementsystems. Business process is collection of standardized and structured tasks inducing value creation of acompany. Moreover, it is recognized as one of significant intangible business assets to achieve competitiveadvantages. This research introduces a novel approach of workflow process analysis, which has more and moresignificance as process-aware information systems are spreading widely into a lot of companies, In this paper, amethodology of workflow clustering based on process similarity has been proposed. The purpose of workflowclustering is to analyze accumulated process definitions in order to assist design of new processes andimprovement of existing ones. The proposed methodology exploits measures of structural similarity of workflowprocesses.The methodology has been experimented with synthetic process models for illustrating the implicationofworkflow clustering.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.229-234
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• 2014

As association between sensor networks that collect environmental information by using numberous sensor nodes and smartphones that are equipped with various sensors, many applications understanding users' context have been developed to interact users and their environments. Collected data should be stored with XML formatted metadata containing semantic information to share the collected data. In case of distance based clustering schemes, the efficiency of data collection decreases because metadata files are extended and changed as the purpose of each system developer. In this paper, we proposed a clustering scheme considering the structural similarity of metadata to reduce clustering construction time and improve the similarity of metadata among member nodes in a cluster.