• ETRI Journal
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• v.34 no.3
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• pp.388-398
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• 2012

Three-dimensional (3D) memories using through-silicon vias (TSVs) will likely be the first commercial applications of 3D integrated circuit technology. A 3D memory yield can be enhanced by vertical redundancy sharing strategies. The methods used to select memory dies to form 3D memories have a great effect on the 3D memory yield. Since previous die-selection methods share redundancies only between neighboring memory dies, the opportunity to achieve significant yield enhancement is limited. In this paper, a novel die-selection method is proposed for multilayer 3D memories that shares redundancies among all of the memory dies by using additional TSVs. The proposed method uses three selection conditions to form a good multi-layer 3D memory. Furthermore, the proposed method considers memory fault characteristics, newly detected faults after bonding, and multiple memory blocks in each memory die. Simulation results show that the proposed method can significantly improve the multilayer 3D memory yield in a variety of situations. The TSV overhead for the proposed method is almost the same as that for the previous methods.

• Korean Journal of Acupuncture
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• v.24 no.3
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• pp.1-8
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• 2007

Objectives : The aim of this study was to show the rationale of point-selection on the methods of acupuncture and moxibustion in the Voice section(in the Naegyeong chapter) of the Donguibogam. Methods : First, We summarized the cause of each disease in the Voice section(in the Naegyeong chapter) of the Donguibogam. Then, We explained the rationale of acupuncture point-selection referring to the cause of disease, physiology of the Oriental medicine, other uses of each acupuncture points In the Donguibogam, character of each acupuncture points, flow of meridian pathways and specific acupuncture points etc. Results and Conclusions : Total 13 acupuncture points were used in the Voice section(in the Naegyeong chapter) of the Donguibogam. Most of acupuncture points were specific acupuncture points. But, some rationale of acupuncture point-selection were explained by the cause of disease, physiology of the Oriental medicine, other uses of each acupuncture points in the Donguibogam, flow of meridian pathways etc.

• Korean Journal of Acupuncture
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• v.24 no.3
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• pp.9-16
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• 2007

Objectives : The aim of this study was to show the rationale of point-selection on the methods of acupuncture and moxibustion in the Resin section(in the Naegyeong chapter) of the Donguibogam. Methods : First, We summarized the cause of each disease in the Resin section(in the Naegyeong chapter) of the Donguibogam Then, We explained the rationale of acupuncture point-selection referring to the cause of disease, physiology of the Oriental medicine, other uses of each acupuncture points in the Donguibogam, character of each acupuncture points, flow of meridian pathways and specific acupuncture points etc. Results and Conclusions : Total 11 acupuncture points were used in the Resin section(in the Naegyeong chapter) of the Donguibogam. Most of acupuncture points were specific acupuncture points. But, some rationale of acupuncture point-selection were explained by the cause of disease, physiology of the Oriental medicine, other uses of each acupuncture points in the Donguibogam, flow of meridian pathways etc.

• Korean Journal of Acupuncture
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• v.26 no.4
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• pp.173-182
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• 2009

Objectives : The aim of this study was to show the rationale of point-selection on the methods of acupuncture and moxibustion in the Essence of life section(in the Naegyeong Chapter) of the Donguibogam. Methods : First, We summarized the cause of each disease in the Essence of life section(in the Naegyeong Chapter) of the Donguibogam. Then, we explained the rationale of acupuncture point-selection referring to the cause of disease, physiology of the Oriental medicine, other uses of each acupuncture points in the Donguibogam, character of each acupuncture points, flow of meridian pathways and specific acupuncture points etc. Results and Conclusions : Total 12 acupuncture points were used in the Essence of life section(in the Naegyeong Chapter) of the Donguibogam. Most of acupuncture points were specific acupuncture points. But, some rationale of acupuncture point-selection were explained by the cause of disease, physiology of the Oriental medicine, other uses of each acupuncture points in the Donguibogam, flow of meridian pathways etc.

• Korean Journal of Acupuncture
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• v.26 no.2
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• pp.165-175
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• 2009

Objectives : The aim of this study was to show the rationale of point-selection on the methods of acupuncture and moxibustion in the Internal Injury section(in the Naegyeong chapter) of the Donguibogam. Methods : First, we summarized the cause of each disease in the Internal Injury section(in the Naegyeong chapter) of the Donguibogam. Then we explained the rationale of acupuncture point-selection referring to the cause of disease, physiology of the oriental medicine, other uses of each acupuncture points in the Donguibogam and other literature, character of each acupuncture points and specific acupuncture points etc. Results and Conclusions : Total 9 acupuncture points were used in the Internal Injury section(in the Naegyeong chapter) of the Donguibogam. Most of rationale of acupuncture point-selection were explained by specific acupuncture points, character of each acupuncture points, physiology of the oriental medicine and flow of meridian pathways etc. Each acupuncture points has practical application of specific diseases.

• Communications for Statistical Applications and Methods
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• v.31 no.4
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• pp.441-457
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• 2024

Semicontinuous data are characterized by a mixture of a point probability mass at zero and a continuous distribution of positive values. This type of data is often modeled using a two-part model where the first part models the probability of dichotomous outcomes -zero or positive- and the second part models the distribution of positive values. Despite the two-part model's popularity, variable selection in this model has not been fully addressed, especially, in high dimensional data. The objective of this study is to investigate variable selection and prediction performance of penalized regression methods in two-part models. The performance of the selected techniques in the two-part model is evaluated via simulation studies. Our findings show that LASSO and ENET tend to select more predictors in the model than SCAD and MCP. Consequently, MCP and SCAD outperform LASSO and ENET for β-specificity, and LASSO and ENET perform better than MCP and SCAD with respect to the mean squared error. We find similar results when applying the penalized regression methods to the prediction of crime incidents using community-based data.

• Earthquakes and Structures
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• v.27 no.3
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• pp.177-189
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• 2024

Accurately predicting the failure modes of reinforced concrete (RC) columns is essential for structural design and assessment. In this study, the challenges of imbalanced datasets and complex feature selection in machine learning (ML) methods were addressed through an optimized ML approach. By combining feature selection and oversampling techniques, the prediction of seismic failure modes in rectangular RC columns was improved. Two feature selection methods were used to identify six input parameters. To tackle class imbalance, the Borderline-SMOTE1 algorithm was employed, enhancing the learning capabilities of the models for minority classes. Eight ML algorithms were trained and fine-tuned using k-fold shuffle split cross-validation and grid search. The results showed that the artificial neural network model achieved 96.77% accuracy, while k-nearest neighbor, support vector machine, and random forest models each achieved 95.16% accuracy. The balanced dataset led to significant improvements, particularly in predicting the flexure-shear failure mode, with accuracy increasing by 6%, recall by 8%, and F1 scores by 7%. The use of the Borderline-SMOTE1 algorithm significantly improved the recognition of samples at failure mode boundaries, enhancing the classification performance of models like k-nearest neighbor and decision tree, which are highly sensitive to data distribution and decision boundaries. This method effectively addressed class imbalance and selected relevant features without requiring complex simulations like traditional methods, proving applicable for discerning failure modes in various concrete members under seismic action.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.471-480
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• 2005

Most questions made for remote examinations on web-based education system use methods of making questions using fixed questions or randomly using item pools or automatically using degree of difficulty. Particularly, automatically selection methods using degree of difficulty is the kernel of a question that objectivity of the first degree of difficulty for questions and an effective questions selection using degree of difficulty and mediateness degree of difficulty based result of examination. This paper is use automatically selection methods for examination on web-based education system. Firstly, we present new question selection algorithms as regards degree of difficulty and distribution between all units. Secondly, we present new algorithms of mediateness degree of difficulty as regards education ability of students for adjust the degree of difficulty. We identified this algorithms is more effective as compared with previously algorithms on web-based education system.

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.149-161
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• 2006

The most important component in decision tree algorithm is the rule for split variable selection. Many earlier algorithms such as CART and C4.5 use greedy search algorithm for variable selection. Recently, many methods were developed to cope with the weakness of greedy search algorithm. Most algorithms have different selection criteria depending on the type of variables: continuous or nominal. However, ordinal type variables are usually treated as continuous ones. This approach did not cause any trouble for the methods using greedy search algorithm. However, it may cause problems for the newer algorithms because they use statistical methods valid for continuous or nominal types only. In this paper, we propose a ordinal variable selection method that uses Cramer-von Mises testing procedure. We performed comparisons among CART, C4.5, QUEST, CRUISE, and the new method. It was shown that the new method has a good variable selection power for ordinal type variables.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.119-125
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• 2021

As the electricity grid systems has been intelligent with the development of ICT technology, power consumption information of users connected to the grid is available to acquired and analyzed for the power utilities. In this paper, the energy theft problem is solved by feature selection methods, which is emerging as the main cause of economic loss in smart grid. The data preprocessing steps of the proposed system consists of five steps. In the feature selection step, features are selected using analysis of variance and mutual information (MI) based method, which are filtering-based feature selection methods. According to the simulation results, the performance of support vector machine classifier is higher than the case of using all the input features of the input data for the case of the MI based feature selection method.