• The Journal of the Acoustical Society of Korea
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• v.25 no.2
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• pp.96-100
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• 2006

Kim et al. Proposed Normalized Confidence Measure (NCM) [1-2] and it was successfully used for rejecting mis-recognized words in isolated word recognition. However their experiments were performed on the fixed word speech recognition. In this Paper we apply NCM to the domain of vocabulary independent speech recognition (VISP) and shows the rejection Performance of NCM in VISP. Specialty we Propose vector quantization (VQ) based method for overcoming the problem of unseen triphones. It is because NCM uses the statistics of triphone confidence in the case of triphone-based normalization. According to speech recognition experiments Phone-based normalization method shows better results than RLJC[3] and also triphone-based normalization approach. This results are different with those of Kim et al [1-2]. Concludingly the Phone-based normalization shows robust Performance in VISP domain.

• The Journal of the Acoustical Society of Korea
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• v.27 no.1
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• pp.40-46
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• 2008

Weak target detection and localization in the presence of loud surface ship noise is a critical problem for matched field processing (MFP) in shallow water. For stationary sources, each signal component of received signal can be separated and interference can be suppressed using eigen space analysis schemes. However, source motion, in realistic cases, causes spreading of signal energies in their subspace. In this case, eigenvalues of target and interfere signal components are mixed and hard to be separated with usual phone space eigenvector decomposition (EVD) approaches. Our technique is based on mode space and utilizes the difference in their physical characteristics of surface and submerged sources. Performing EVD for modal cross spectral density matrix, interference components in the mode amplitude subspace can be classified and eliminated. This technique is demonstrated with synthetic data, and results are discussed.

• Convergence Security Journal
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• v.24 no.2
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• pp.189-200
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• 2024

In recent years, the development of defense technology has become digital with the introduction of advanced assets such as drones equipped with artificial intelligence. These assets are integrated with modern information technologies such as industrial IoT, artificial intelligence, and cloud computing to promote innovation in the defense domain. However, the convergence of the technology is increasing the possibility of transfer of cyber threats, which is emerging as a problem of increasing the vulnerability of defense assets. While the current cybersecurity methodologies focus on the vulnerability of a single asset, interworking of various military assets is necessary to perform the mission. Therefore, this paper recognizes these problems and presents a mission-based asset management and evaluation methodology. It aims to strengthen cyber security in the defense sector by identifying assets that are important for mission execution and analyzing vulnerabilities in terms of cyber security. In this paper, we propose a method of classifying mission dependencies through linkage analysis between functions and assets to perform a mission, and identifying and classifying assets that affect the mission. In addition, a case study of identifying key assets was conducted through an attack scenario.

• Smart Media Journal
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• v.12 no.11
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• pp.198-210
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• 2023

After COVID-19, team's collaborations are conducted online using whiteboard tools as remote working increases. In order to understand the problems of the convergence process using online whiteboard tools, an observation study comparing online and offline collaboration and a focus group interview were conducted. In addition, a questionnaire was conducted to confirm the found problem, and a solution idea was proposed. through in-depth interviews, we validate the proposed ideas. The convergence process of collaboration using online whiteboard tools had problems ; "excessive amount of information", "shift of view", "role of facilitator". To solve the problems, we proposed the idea of classifying each stage of the collaboration process, providing a navigator, and facilitator request system window. This paper proposed an idea that can effectively help the convergence process directly related to decision-making during the online collaboration process through analysis of advantages and problems of online and offline collaboration.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.226-234
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• 2024

The frequent handover problem and playing ping-pong effects in 5G (5th Generation) ultra-dense networking cannot be effectively resolved by the conventional handover decision methods, which rely on the handover thresholds and measurement reports. For instance, millimetre-wave LANs, broadband remote association techniques, and 5G/6G organizations are instances of group of people yet to come frameworks that request greater security, lower idleness, and dependable principles and correspondence limit. One of the critical parts of 5G and 6G innovation is believed to be successful blockage the board. With further developed help quality, it empowers administrator to run many systems administration recreations on a solitary association. To guarantee load adjusting, forestall network cut disappointment, and give substitute cuts in case of blockage or cut frustration, a modern pursuing choices framework to deal with showing up network information is require. Our goal is to balance the strain on BSs while optimizing the value of the information that is transferred from satellites to BSs. Nevertheless, due to their irregular flight characteristic, some satellites frequently cannot establish a connection with Base Stations (BSs), which further complicates the joint satellite-BS connection and channel allocation. SF redistribution techniques based on Deep Reinforcement Learning (DRL) have been devised, taking into account the randomness of the data received by the terminal. In order to predict the best capacity improvements in the wireless instruments of 5G and 6G IoT networks, a hybrid algorithm for deep learning is being used in this study. To control the level of congestion within a 5G/6G network, the suggested approach is put into effect to a training set. With 0.933 accuracy and 0.067 miss rate, the suggested method produced encouraging results.

• The Mathematical Education
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• v.63 no.2
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• pp.209-231
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• 2024

The education sector is undergoing significant changes due to the Fourth Industrial Revolution and the advancement of artificial intelligence. Particularly, the importance of education based on artificial intelligence is being emphasized. Accordingly, the purpose of this study is to develop a statistics education program using deep learning prediction in high school mathematics and to examine the impact of such statistically problem-solvingcentered statistics education programs on high school students' statistical literacy and computational thinking. To achieve this goal, a statistics education program using deep learning prediction applicable to high school mathematics was developed. The analysis revealed that students' understanding of context improved through experiencing how data was generated and collected. Additionally, they enhanced their comprehension of data variability while exploring and analyzing various datasets. Moreover, they demonstrated the ability to critically analyze data during the process of validating its reliability. In order to analyze the impact of the statistics education program on high school students' computational thinking, a paired sample t-test was conducted, confirming a statistically significant difference in computational thinking between before and after classes (t=-11.657, p<0.001).

• Information Systems Review
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• v.19 no.1
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• pp.49-74
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• 2017

The development of smart devices has affected employees' working environments and their lives. However, using smart devices is causing employees to experience technostress. This study aims to investigate the effects of technostress in using smart devices on usage intention in an organization. Moreover, the study investigates the effect of employees' stress-coping methods on the intention to use smart devices. This study posits familiarity, use innovativeness, role ambiguity, system vulnerability, technological limitation, and ubiquity as the antecedents of technostress. Data collected from 317 users who have experience in using smart devices in organizations are empirically tested against a research model using the PLS graph. Analysis results show that role ambiguity, system vulnerability, and technological limitation significantly influence technostress. Moreover, users take up emotion-focused coping behaviors because of technostress. Emotion-focused coping behaviors affect usage intention in organizations. However, technostress and problem-focused coping behaviors do not directly affect usage intention in organizations.

• Clinical Endoscopy
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• v.56 no.2
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• pp.194-202
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• 2023

Background/Aims: Endoscopic therapy for neoplastic Barrett's esophagus (BE) has become the standard of care over the past two decades. In clinical practice, we regularly encounter patients who fail to achieve complete squamous epithelialization of the esophagus. Although the therapeutic strategies in the individual stages of BE, dysplasia, and esophageal adenocarcinoma are well studied and largely standardized, the problem of inadequate healing after endoscopic therapy is only marginally considered. This study aimed to shed light on the variables influencing inadequate wound healing after endoscopic therapy and the effect of bile acid sequestrants (BAS) on healing. Methods: Retrospective analysis of endoscopically treated neoplastic BE in a single referral center. Results: In 12.1% out of 627 patients, insufficient healing was present 8 to 12 weeks after previous endoscopic therapy. The average follow-up duration was 38.8±18.4 months. Complete healing was achieved in 13 patients already after intensifying proton pump inhibitor therapy. Out of 48 patients under BAS, 29 patients (60.4%) showed complete healing. An additional eight patients (16.7%) improved, but only partial healing was achieved. Eleven (22.9%) patients showed no response to BAS augmented therapy. Conclusions: In cases of insufficient healing even under exhaustion of proton pump inhibitors, treatment with BAS can be an option as an ultimate healing attempt.

• Tunnel and Underground Space
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• v.34 no.2
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• pp.127-142
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• 2024

The robustness of a numerical method means that its computational performance is maintained under various modeling conditions. New numerical methods or codes need to be assessed for robustness through benchmark testing. The TOUGH-FLAC modeling approach has been applied to various fields such as subsurface carbon dioxide storage, geological disposal of spent nuclear fuel, and geothermal development both domestically and internationally, and the modeling validity has been examined by comparing the results with experimental measurements and other numerical codes. In the present study, a benchmark test of the TOUGH-FLAC approach was performed based on a coupled thermal-hydro-mechanical behavior problem with an analytical solution. The analytical solution is related to the temperature, pore water pressure, and mechanical behavior of a fully saturated porous medium that is subjected to a point heat source. The robustness of the TOUGH-FLAC approach was evaluated by comparing the analytical solution with the results of numerical simulation. Additionally, the effects of thermal-hydro-mechanical coupling terms, fluid phase change, and timestep on the computation of coupled behavior were investigated.

• Structural Engineering and Mechanics
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• v.90 no.3
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• pp.219-232
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• 2024

In current study, for the first time, Nonlinear Bending of a skew microplate made of a laminated composite strengthened with graphene nanosheets is investigated. A mixture of mechanical and thermal stresses is applied to the plate, and the reaction is analyzed using the First Shear Deformation Theory (FSDT). Since different percentages of graphene sheets are included in the multilayer structure of the composite, the characteristics of the composite are functionally graded throughout its thickness. Halpin-Tsai models are used to characterize mechanical qualities, whereas Schapery models are used to characterize thermal properties. The microplate's non-linear strain is first calculated by calculating the plate shear deformation and using the Green-Lagrange tensor and von Karman assumptions. Then the elements of the Couple and Cauchy stress tensors using the Modified Coupled Stress Theory (MCST) are derived. Next, using the Hamilton Principle, the microplate's governing equations and associated boundary conditions are calculated. The nonlinear differential equations are linearized by utilizing auxiliary variables in the nonlinear solution by applying the Frechet approach. The linearized equations are rectified via an iterative loop to precisely solve the problem. For this, the Differential Quadrature Method (DQM) is utilized, and the outcomes are shown for the basic support boundary condition. To ascertain the maximum values of microplate deflection for a range of circumstances-such as skew angles, volume fractions, configurations, temperatures, and length scales-a parametric analysis is carried out. To shed light on how the microplate behaves in these various circumstances, the resulting results are analyzed.