• Journal of the Korean Geophysical Society
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• v.4 no.3
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• pp.175-182
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• 2001

We consider the problem of determining smoothing parameters of Gibbs priors for Bayesian methods used in the medical imaging application of emission tomographic reconstruction. We address a simple smoothing prior (membrane) whose global hyperparameter (the smoothing parameter) controls the bias/variance tradeoff of the solution. We base our maximum-likelihood (ML) estimates of hyperparameters on observed training data, and argue the motivation for this approach. Good results are obtained with a simple ML estimate of the smoothing parameter for the membrane prior.

• The Journal of Engineering Research
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• v.4 no.1
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• pp.47-54
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• 2002

We consider the problem of determining smoothing parameters of Gibbs priors for Bayesian methods used in the medical imaging application of emission tomographic reconstruction. We address a simple smoothing prior (membrane) whose global hyperparameter (the smoothing parameter) controls the bias/variance tradeoff of the solution. We base our maximum-likelihood(ML) estimates of hyperparameters on observed training data, and argue the motivation for this approach. Good results are obtained with a simple ML estimate of the smoothing parameter for the membrane prior.

• Mineral and Industry
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• v.26
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• pp.22-31
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• 2013

KIGAM and MRAM (Mineral Resources Authority of Mongolia) performed joint researches on geological survey of Dulaankhaikhan W-Mo occurrences areas in southeastern part of Khangai region. XRD results of tungsten containing quartz vein sample show that tungsten minerals are wolframite, hubnerite and ferberiteore. $WO_3$ grade of samples obtained in Silurian Khotont formation is 0.11-4.43% and that of samples obtained in Permian Delgerkhan complex is 137-3844 ppm. Average total $R_2O_3$ of samples obtained in survey area is 473 ppm which is 2.5 times larger than that of Earth's crust. The highest total $R_2O_3$ is 1326 ppm. Factor analysis results show that two areas of high tungsten contents have similar correlations with tungsten, and therefore we conclude that these two areas have the similar origin of mineralization.

• Journal of KIISE:Databases
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• v.27 no.2
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• pp.227-237
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• 2000

A Web database System is a large-scaled multimedia application system that has multimedia processing facilities and cooperates with relational/Object-Oriented DBMS. Conventional hypertext modeling methods and DB gateway have limitations for Web database because of their restricted versatile presentation abilities and inefficient concurrency control caused by bottleneck in cooperation processing. Thus, we suggest a Dynamic Navigation Model & Virtual Graph Structure. The Dynamic Navigation Model supports implicit query processing and dynamic creation of navigation spaces, and introduce node-link creation rule considering navigation styles. We propose a mapping methodology between the suggested hypertext model and the relational data model, and suggest a dynamic allocation scheduling technique for query processing server based on weighted value. We show that the proposed technique enhances the retrieval performance of Web database systems in processing complex queries concurrently.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.1
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• pp.35-42
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• 2010

Guest operating systems running over the virtual machines share a variety of resources. Since CPU is allocated in a time division manner it consequently leads them to having the unknown physical time. It is not regarded as a serious problem in the server virtualization fields. However, it becomes critical in embedded systems because it prevents guest OS from executing real time tasks when it does not occupy CPU. In this paper we propose a hypercall to register a timer service to notify the timer request related real time. It enables hypervisor to schedule a virtual machine which has real time tasks to execute, and allows guest OS to take CPU on time to support real time. The following experiment shows its implementation on Xen-Arm and para-virtualized Linux. We also analyze the real time performance with response time of test application and frames per second of Mplayer.

• Composites Research
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• v.32 no.5
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• pp.216-221
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• 2019

Piecewise integrated composite (PIC) beam has different stacking sequences for several regions with respect to their superior load-resisting capabilities. On the interest of current research is to improve bending characteristics of PIC beam, with assigning specific stacking sequence to a specific region with the help of machine learning techniques. 240 elements of from the FE model were chosen to be reference points. Preliminary FE analysis revealed triaxialities at those regularly distributed reference points to obtain learning data creation of machine learning. Triaxiality values catagorise the type of loading i.e. tension, compression or shear. Machine learning model was formulated by learning data as well as hyperparameters and proper load fidelity was suggested by tuned values of hyperparameters, however, comparatively higher nonlinearity intensive region, such as side face of the beam showed poor load fidelity. Therefore, irregular distribution of reference points, i.e., dense reference points were distributed in the severe changes of loading, on the contrary, coarse distribution for rare changes of loading, was prepared for machine learning model. FE model with irregularly distributed reference points showed better load fidelity compared to the results from the model with regular distribution of reference points.

• FLOWER RESEARCH JOURNAL
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• v.18 no.4
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• pp.225-230
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• 2010

This study was conducted to increase the income of cactus farm by selecting cheaper and better media than the peat moss using for Gymnocalycium mihanovichii 'Huhong'. We cultivated Gymnocalycium mihanovichii 'Huhong' on 10 kinds of media (peat moss, culture medium, coco peat, sphagnum moss, hydro ton, hydro cray, hydro bal, hugato, vermiculite, perlite) and analyzed media's physiochemical factors and growth, betacyanin. The results were as follows: In case of media's physical condition planting Gymnocalycium mihanovichii 'Huhong' after 90 days, an approximate value with peat moss is culture medium and coco peat. Also, coco peat has no change in chemical media. The rate of growth and development is high in Coco peat while overall culture medium and coco peat was seen lower growth. The level of betacyanin in subirrigation is higher than overhead irrigation. Meanwhile, hugato among 10 kinds of media has high value in both of overhead irrigation and bottom watering. Thus, culture medium and coco peat is proper for alternation of peat moss due to similar value with peat moss. And coco peat is favorable to media, growth condition, pigment.

• Clean Technology
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• v.23 no.3
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• pp.270-278
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• 2017

This study introduces a method to easily fabricate highly monodisperse pectin hydrogel microfibers in a microfluidic device by using partial gelation. The hydrodynamic parameters between the pectin aqueous solution and the calcium ions containing oil solution are precisely controlled to form a stable elongation flow of the pectin aqueous solution, and partial gelation of the pectin aqueous solution is performed by the chelating of the calcium ions at the interface between the two phases. The partially gelled pectin aqueous solution is phase-separated from the oil solution in an aqueous calcium chloride solution outside the microfluidic device and is completely gelled to produce monodisperse pectin hydrogel microfibers. The thickness of the pectin hydrogel microfiber is controlled in a reproducible manner by controlling the volumetric flow rate of the initially injected pectin aqueous solution. The pectin hydrogel microfibers were 200 to 500 micrometers in diameter and had a coefficient of variation below 5% under all thickness conditions, indicating that the pectin hydrogel microfibers produced by partial gelation are highly monodisperse. In addition, biomaterials can be immobilized to the pectin hydrogel microfibers produced by a single process, demonstrating the possibility that our pectin hydrogel microfiber can be used as carriers for biomaterials or tissue engineering.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.127-135
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• 2023

This research paper explores the application of FinBERT, a variational BERT-based model pre-trained on financial domain, for sentiment analysis in the financial domain while focusing on the process of identifying suitable training data and hyperparameters. Our goal is to offer a comprehensive guide on effectively utilizing the FinBERT model for accurate sentiment analysis by employing various datasets and fine-tuning hyperparameters. We outline the architecture and workflow of the proposed approach for fine-tuning the FinBERT model in this study, emphasizing the performance of various datasets and hyperparameters for sentiment analysis tasks. Additionally, we verify the reliability of GPT-3 as a suitable annotator by using it for sentiment labeling tasks. Our results show that the fine-tuned FinBERT model excels across a range of datasets and that the optimal combination is a learning rate of 5e-5 and a batch size of 64, which perform consistently well across all datasets. Furthermore, based on the significant performance improvement of the FinBERT model with our Twitter data in general domain compared to our news data in general domain, we also express uncertainty about the model being further pre-trained only on financial news data. We simplify the complex process of determining the optimal approach to the FinBERT model and provide guidelines for selecting additional training datasets and hyperparameters within the fine-tuning process of financial sentiment analysis models.

• The KIPS Transactions:PartA
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• v.9A no.3
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• pp.333-340
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• 2002

Embedding is a mapping an interconnection network G to another interconnection network H. If a network G can be embedded to another network H, algorithms developed on G can be simulated on H. In this paper, we first propose a method to embed between Hierarchical Cubic Network HCN(n, n) and Hierarchical Folded-hypercube Network HFN(n, n). HCN(n, n) and HFN(n, n) are graph topologies having desirable properties of hypercube while improving the network cost, defined as degree${\times}$diameter, of Hypercube. We prove that HCN(n, n) can be embedded into HFN(n, n) with dilation 3 and congestion 2, and the average dilation is less than 2. HFN(n, n) can be embedded into HCN(n, n) with dilation 0 (n), but the average dilation is less than 2. Finally, we analyze the fault tolerance of HCN(n, n) and prove that HCN(n, n) is maximally fault tolerant.