• Economic and Environmental Geology
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• v.28 no.2
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• pp.155-164
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• 1995

The kriging model, one of the geostatistical models, has been used to evaluate the deep-sea manganese nodule deposits until now. The distribution of the manganese nodule deposits estimated by the model shows the smooth surface as well as much difference from the actual distribution. Subsequently, it estimates the deposit distribution roughly in terms of the limited data of surveyed zone. Therefore, this paper presents the interpretation methodology of the deep-sea manganese nodule deposit distribution by using the fractal model to overcome the problems caused by the geostatistical model. Also, the manganese nodule distributions are interpreted by using the manganese nodule data sampled in the GH82-4 zone, west longitude $165^{\circ}40^{\prime}-169^{\circ}00^{\prime}$, and south latitude $0^{\circ}00^{\prime}-2^{\circ}40^{\prime}$ neighboring Nova-Canton Trough in the Pacific Ocean which was surveyed by the Geological Survey of Japan in 1982.

• Geomechanics and Engineering
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• v.17 no.2
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• pp.215-225
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• 2019

The mechanical behavior of rock is essential to estimate the capacity and long-term stability of $CO_2$ storage in deep saline aquifers. As the depth of reservoir increases, the pressure and temperature that applied on the rock increase. To answer the question of how the confining pressure and temperature influence the mechanical behavior of reservoir rock, triaxial compression experiments were carried out on brine-saturated sandstone at elevated temperature. The triaxial compressive strength of brine-saturated sandstone was observed to decrease with increasing testing temperature, and the temperature weakening effect in strength enhanced with the increase of confining pressure. Sandstone specimens showed single fracture failures under triaxial compression. Three typical regions around the main fracture were identified: fracture band, damaged zone and undamaged zone. A function was proposed to describe the evolution of acoustic emission count under loading. Finally, the mechanism of elevated temperature causing the reduction of strength of brine-saturated sandstone was discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.670-673
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• 2020

Recent advances in artificial intelligence have allowed for easier sentiment analysis (e.g. positive or negative forecast) of documents such as a finance reports. In this paper, we investigate a method to apply text mining techniques to extract in the financial report using deep learning, and propose an accounting model for the effects of sentiment values in financial information. For sentiment analysis with keyword detection in the financial report, we suggest the input layer with extracted keywords, hidden layers by learned weights, and the output layer in terms of sentiment scores. Our approaches can help more effective strategy for potential investors as a professional guideline using sentiment values.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.315-318
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• 2006

This paper concerns about coupled dynamic analysis of the deep-seabed mining system in launching operation. The dynamic behavior of mining system consisting of lifting pipe, buffer station, flexible conduit and self-propelled miner is simulated in time domain. The launching operation is divided into four critical phases: (1) deployment of miner and flexible conduit, (2) deployment of lifting pipe, flexible conduit and miner, (3) touch-down of miner, (4) final launching. The dynamic responses of sub-systems - miner, flexible conduit, buffer and lifting pipe - are analyzed in each launching phase. According to the changing periods of forced excitation at the top, the dynamic responses of sub-systems are diverse in their characteristics. It has been shown that the total integrated responses of sub-systems are strongly affected by the design parameters. Especially, the principal dimensions of flexible conduit seem to be significant in determining of the global response. Based on the simulation results, safe operation conditions are investigated.

• Geomechanics and Engineering
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• v.22 no.4
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• pp.349-359
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• 2020

Quantification of the influence of the fracture of thick magmatic rock (TMR) on the behavior of its overlying strata is a prerequisite to the understanding of the deformation behavior of the earth's surface in deep mining. A three-dimensional numerical model of a special geological mining condition of overlying TMR was developed to investigate the overburden movement and fracture law, and compare the influence of the occurrence horizon of TMR. The research results show that the movement of overlying rock was greatly affected by the TMR. Before the fracture of TMR, the TMR had shielding and controlling effects on the overlying strata, the maximum vertical and horizontal displacement values of overlying strata were 0.68 m and 0.062 m. After the fracture, the vertical and horizontal displacements suddenly increased to 3.06 m and 0.105 m, with an increase of 350% and 69.4%, respectively, and the higher the occurrence of TMR, the smaller the settlement of the overlying strata, but the wider the settlement span, the smaller the corresponding deformation value of the basin edge (the more difficult the surface to crack). These results are of tremendous importance for the control of rock strata and the revealing of surface deformation mechanism under TMR mining conditions in mines.

• Computers and Concrete
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• v.25 no.2
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• pp.145-154
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• 2020

For the influence of the propagation law of stress wave at the coal-rock interface during the pre-blasting of the top coal in top coal mining, the ANSYS-LS/DYNA fluid-solid coupling algorithm was used to numerical calculation and the life-death element method was used to simulate the propagation of explosion cracks. The equation of the crushing zone and the fracturing zone were derived. The results were calculated and showed that the crushing radius is 14.6 cm and the fracturing radius is 35.8 cm. With the increase of the angles between the borehole and the coal-rock interface, the vibration velocity of the coal particles and the rock particles at the interface decreases gradually, and the transmission coefficient of the stress wave from the coal mass into the rock mass decreases gradually. When the angle between the borehole and the coal-rock interface is 0°, the overall crushing degree is about 11% and up to the largest. With the increase of the distance from the charge to the coal-rock interface, the stress wave transmission coefficient and the crushing degree of the coal-rock are gradually decreased. At the distance of 50 cm, the crushing degree of the coal-rock reached the maximum of approximately 12.3%.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.19-22
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• 2022

In this work, we studied consumers' attractiveness/usefulness perceptions (CAUP) of online commerce product photos when exposed to alternative dark/light user interface (UI) modes. We analyzed time-series EEG data from 31 individuals and performed neuroscience mining (NSM) to ascertain (a) how the CAUP of products differs among UI modes; and (b) which deep learning model provides the most accurate assessment of such neuroscience mining (NSM) business difficulties. The dark UI style increased the CAUP of the products displayed and was predicted with the greatest accuracy using a unique EEG power spectra separated wave brainwave 2D-ConvLSTM model. Then, using relative importance analysis, we used this model to determine the most relevant power spectra. Our findings are considered to contribute to the discovery of objective truths about online customers' reactions to various user interface modes used by various online marketplaces that cannot be uncovered through more traditional research approaches like as surveys.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2361-2376
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• 2023

The electrocardiogram (ECG) signal is commonly used to screen and diagnose cardiovascular diseases. In recent years, deep neural networks have been regarded as an effective way for automatic ECG disease diagnosis. The convolutional neural network is widely used for ECG signal extraction because it can obtain different levels of information. However, most previous studies adopt single scale convolution filters to extract ECG signal features, ignoring the complementarity between ECG signal features of different scales. In the paper, we propose a dual-scale network with convolution filters of different sizes for 12-lead ECG classification. Our model can extract and fuse ECG signal features of different scales. In addition, different spatial and time periods of the feature map obtained from the 12-lead ECG may have different contributions to ECG classification. Therefore, we add a spatial-temporal attention to each scale sub-network to emphasize the representative local spatial and temporal features. Our approach is evaluated on PTB-XL dataset and achieves 0.9307, 0.8152, and 89.11 on macro-averaged ROC-AUC score, a maximum F1 score, and mean accuracy, respectively. The experiment results have proven that our approach outperforms the baselines.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.44-55
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• 2024

High-utility itemset mining (HUIM) is a dominant technology that enables enterprises to make real-time decisions, including supply chain management, customer segmentation, and business analytics. However, classical support value-driven Apriori solutions are confined and unable to meet real-time enterprise demands, especially for large amounts of input data. This study introduces a groundbreaking model for top-N high utility itemset mining in real-time enterprise applications. Unlike traditional Apriori-based solutions, the proposed convolutional sequential embedding metrics-driven cosine-similarity-based multilayer perception learning model leverages global and contextual features, including semantic attributes, for enhanced top-N recommendations over sequential transactions. The MATLAB-based simulations of the model on diverse datasets, demonstrated an impressive precision (0.5632), mean absolute error (MAE) (0.7610), hit rate (HR)@K (0.5720), and normalized discounted cumulative gain (NDCG)@K (0.4268). The average MAE across different datasets and latent dimensions was 0.608. Additionally, the model achieved remarkable cumulative accuracy and precision of 97.94% and 97.04% in performance, respectively, surpassing existing state-of-the-art models. This affirms the robustness and effectiveness of the proposed model in real-time enterprise scenarios.

• Geomechanics and Engineering
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• v.3 no.2
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• pp.109-116
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• 2011

This note presents an analytical solution for the determination of the shape factor of a flush bottom piezometer in a uniform, isotropic, and incompressible deep soil deposit. The deduced shape factor is compared to published values obtained by approximate methods. Depending on the selected value, the difference may reach 11%.