• Smart Structures and Systems
• /
• v.23 no.6
• /
• pp.553-564
• /
• 2019

Modeling of magnetorheological (MR) dampers for cable vibration control to facilitate the design of even more effective and economical systems is still a challenging task. In this study, a parameter-adaptive three-element model is first established for a full-scale MR damper based on laboratory tests. The parameters of the model are represented by a set of empirical formulae in terms of displacement amplitude, voltage input, and excitation frequency. The model is then incorporated into the governing equation of cable-damper system for investigation of open-loop vibration control of stay cables in a cable-stayed bridge. The concept of optimal voltage/current input achieving the maximum damping for the system is put forward and verified. Multi-mode suboptimal and Single-mode optimal open-loop control method is then developed. Important conclusions are drawn on application issues and unique characteristics of open-loop cable vibration control using MR dampers.

• East Asian mathematical journal
• /
• v.35 no.5
• /
• pp.569-587
• /
• 2019

In this paper, we consider a split least-squares characteristic mixed element method for Sobolev equations with a convection term. First, to manipulate both convection term and time derivative term efficiently, we apply a characteristic mixed element method to get the system of equations in the primal unknown and the flux unknown and then get a least-squares minimization problem and a least-squares characteristic mixed element scheme. Finally, we obtain a split least-squares characteristic mixed element scheme for the given problem whose system is uncoupled in the unknowns. We prove the optimal order in $L^2$ and $H^1$ normed spaces for the primal unknown and the suboptimal order in $L^2$ normed space for the flux unknown.

• Journal of Yeungnam Medical Science
• /
• v.36 no.3
• /
• pp.163-182
• /
• 2019

The primary function of intraoperative frozen consultation is to provide an as accurate and prompt diagnosis as possible during surgery and to guide the surgeon in further management. However, the evaluation of frozen section (FS) is sometimes difficult because of suboptimal tissue quality and frozen artifacts compared with routinely processed tissue section. The pathologist responsible for the FS diagnosis requires experience and good judgment. Ovarian tumors are a heterogeneous group of tumors including primary surface epithelial tumors, germ cell tumors and sex cord-stromal tumors, secondary tumors, and other groups of tumors of uncertain histogenesis or nonspecific stroma. Intraoperative FS is a very important and reliable tool that guides the surgical management of ovarian tumors. In this review, the diagnostic key points for the pathologist and the implication of the FS diagnosis on the operator's decisions are discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.3
• /
• pp.1174-1192
• /
• 2021

With the assistance of non-orthogonal multiple access (NOMA), the spectrum efficiency and the number of users in cloud radio access network (CRAN) can be greatly improved. In this paper, the system performance of NOMA-assisted CRAN is investigated. Specially, the outage probability (OP) and ergodic sum rate (ESR), are derived for performance evaluation of the system, respectively. Based on this, by minimizing the OP of the system, a suboptimal power allocation (PA) scheme with closed-form PA coefficients is proposed. Numerical simulations validate the accuracy of the theoretical results, where the derived OP has more accuracy than the existing one. Moreover, the developed PA scheme has superior performance over the conventional fixed PA scheme but has smaller performance loss than the optimal PA scheme using the exhaustive search method.

• Journal of Digestive Cancer Research
• /
• v.12 no.1
• /
• pp.31-37
• /
• 2024

Pancreatic cancer is a highly fatal malignancy with a 5-year survival rate of < 10%. Endoscopic ultrasound (EUS) is a useful noninvasive tool for differential diagnosis of pancreatic malignancy and treatment decision-making. However, the performance of EUS is suboptimal, and its accuracy for differentiating pancreatic malignancy has increased interest in the application of artificial intelligence (AI). Recent studies have reported that EUS-based AI models can facilitate early and more accurate diagnosis than other preexisting methods. This article provides a review of the literature on EUS-based AI studies of pancreatic malignancies.

• ETRI Journal
• /
• v.46 no.1
• /
• pp.137-153
• /
• 2024

This study introduces a new approach in Korean morphological analysis combining dictionary-based techniques with Transformer-based deep learning models. The key innovation is the use of a BERT-based reranking system, significantly enhancing the accuracy of traditional morphological analysis. The method generates multiple suboptimal paths, then employs BERT models for reranking, leveraging their advanced language comprehension. Results show remarkable performance improvements, with the first-stage reranking achieving over 20% improvement in error reduction rate compared with existing models. The second stage, using another BERT variant, further increases this improvement to over 30%. This indicates a significant leap in accuracy, validating the effectiveness of merging dictionary-based analysis with contemporary deep learning. The study suggests future exploration in refined integrations of dictionary and deep learning methods as well as using probabilistic models for enhanced morphological analysis. This hybrid approach sets a new benchmark in the field and offers insights for similar challenges in language processing applications.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2024.05a
• /
• pp.794-797
• /
• 2024

Despite advancements in deep learning, existing semantic segmentation models exhibit suboptimal performance under adverse weather conditions, such as fog or rain, whereas they perform well in clear weather conditions. To address this issue, much of the research has focused on making image or feature-level representations weather-independent. However, disentangling the style and content of images remains a challenge. In this work, we propose a novel fine-tuning method, 'freeze-n-update.' We identify a subset of model parameters that are weather-independent and demonstrate that by freezing these parameters and fine-tuning others, segmentation performance can be significantly improved. Experiments on a test dataset confirm both the effectiveness and practicality of our approach.

• Clinical Endoscopy
• /
• v.57 no.1
• /
• pp.24-35
• /
• 2024

The field of artificial intelligence is rapidly evolving, and there has been an interest in its use to predict the risk of lymph node metastasis in T1 colorectal cancer. Accurately predicting lymph node invasion may result in fewer patients undergoing unnecessary surgeries; conversely, inadequate assessments will result in suboptimal oncological outcomes. This narrative review aims to summarize the current literature on deep learning for predicting the probability of lymph node metastasis in T1 colorectal cancer, highlighting areas of potential application and barriers that may limit its generalizability and clinical utility.

• Tuberculosis and Respiratory Diseases
• /
• v.87 no.3
• /
• pp.302-308
• /
• 2024

In cases where pulmonary tuberculosis (PTB) is not microbiologically diagnosed via sputum specimens, bronchoscopy has been the conventional method to enhance diagnostic rates. Although the additional benefit of bronchoscopy in diagnosing PTB is well-known, its overall effectiveness remains suboptimal. This review introduces several strategies for improving PTB diagnosis via bronchoscopy. First, it discusses how bronchoalveolar lavage or an increased number of bronchial washings can increase specimen abundance. Second, it explores how thin or ultrathin bronchoscopes can achieve specimen acquisition closer to tuberculosis (TB) lesions. Third, it highlights the importance of conducting more sensitive TB-polymerase chain reaction tests on bronchoscopic specimens, including the Xpert MTB/RIF assay and the Xpert MTB/RIF Ultra assay. Finally, it surveys the implementation of endobronchial ultrasound with a guide sheath for tuberculomas, collection of post-bronchoscopy sputum, and reduced use of lidocaine for local anesthesia. A strategic combination of these approaches may enhance the diagnostic rates in PTB patients undergoing bronchoscopy.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.8 no.2
• /
• pp.107-117
• /
• 2013

The main objective of this study lies at examining economic features of IT security investment and comparing alternative mechanisms to achieve optimal provision of IT security resources within a firm. There exists a paucity of economic analysis that provide useful guidelines for making critical decisions regarding the optimal level of provision of IT security and how to share the costs among different users within a firm. As a preliminary study, this study first argues that IT security resources share some unique characteristics of pure public goods, namely nonrivalry of consumption and nonexcludability of benefit. IT security provision problem also suffers from information asymmetry problem with regard to the valuation of an individual user for IT security goods. Then, through an analytical framework, it is shown that the efficient provision condition at the overall firm level is not necessarily satisfied by individual utility maximizing behavior. That is, an individual provision results in a suboptimal solution, especially an underprovision of the IT security good. This problem is mainly due to the nonexcludability property of pure public goods, and is also known as a free-riding problem. The fundamental problem of collective decision-making is to design mechanisms that both induce the revelation of the true information and choose an 'optimal' level of the IT security good within this framework of information asymmetry. This study examines and compares three alternative demand-revealing mechanisms within the IT security resource provision context, namely the Clarke-Groves mechanism, the expected utility maximizing mechanism and the Groves-Ledyard mechanism. The main features of each mechanism are discussed along with its strengths, weaknesses, and different applicability in practice. Finally, the limitations of the study and future research are discussed.