• Mass Spectrometry Letters
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• v.15 no.2
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• pp.107-119
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• 2024

We aimed to develop a suitable quantification method for detecting asparagine deamidation and aspartic acid isomerization in peptide mapping using LC-MS. Our assessment of its validity and suitability involved comparing its quantitative findings with those obtained from cation-exchange chromatography and capillary electrophoresis methods. By subjecting trastuzumab to rigorous conditions to induce these modifications, we validated the efficacy of this new analytical method in peptide mapping via LC-MS, evaluating both qualitative and quantitative aspects of asparagine deamidation and aspartic acid isomerization. Our investigation underscored the significance of enzyme selection and the presence of miss-cleaved or non-specific peptides in achieving accurate quantitative results. The experimental results demonstrated a strong correlation with results from cation-exchange chromatography and capillary electrophoresis analyses, confirming the reliability of the LC-MS based peptide mapping approach.

• Geomechanics and Engineering
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• v.38 no.6
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• pp.583-591
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• 2024

To properly simulate the excavation process and evaluate the structural stability of the tunnel, rigorous large deformation analysis method is necessary. This study applies two most widely used numerical approaches capable of modelling and considering the large deformations behavior during excavation process to analyze and evaluate the structural stability of circular tunnel based on tunnel boring machine (TBM) excavation. By comparing and combining the results from two numerical approaches, the deformation of the excavated ground will be analyzed. The stability of the circular tunnel from TBM tunneling was assessed based on the maximum deformation occurred during the excavation process. From the numerical computation it was concluded that although the range of the damage on the ground done during excavation was found to be larger under hard rock condition, maximum deformation within the circular tunnel structure was larger under weak ground conditions and deeper tunnel depths.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.7-14
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• 2011

The numerical analyses were performed to investigate the curling behavior of the post-tensioned prestressed concrete approach slab (PTAS) under environmental loads. A technique to include properly the boundary conditions of one end of PTAS that was connected to the bridge abutment using hinges was proposed for the numerical model. The applicability of a simplified model not having hunches was also investigated. By using the developed models, the curling behavior of PTAS was analyzed when the foundation settlement occurred. The analysis results showed that the maximum tensile stress obtained from the simplified model involving a simplified hinge connection was very closed to that obtained from a rigorous model. When the slab curled up, the maximum tensile stress occurred in the model including no foundation settlement, but when the slab curled down, the maximum stress occurred in the model including partial settlement of the foundation. Therefore, the design of PTAS should be performed considering those maximum tensile stresses.

• International Journal of Control, Automation, and Systems
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• v.2 no.2
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• pp.247-255
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• 2004

The majority of real-world problems encountered by engineers involve simultaneous optimization of competing objectives. In this case instead of single optima, there is a set of alternative trade-offs, generally known as Pareto-optimal solutions. The use of evolutionary algorithms Pareto GA, which was first introduced by Goldberg in 1989, has now become a sort of standard in solving Multiobjective Optimization Problems (MOPs). Though this approach was further developed leading to numerous applications, these applications are based on Pareto ranking and employ the use of the fitness sharing function to maintain diversity. Another scheme for solving MOPs has been presented by J. Nash to solve MOPs originated from Game Theory and Economics. Sefrioui introduced the Nash Genetic Algorithm in 1998. This approach combines genetic algorithms with Nash's idea. Another central achievement of Game Theory is the introduction of an Evolutionary Stable Strategy, introduced by Maynard Smith in 1982. In this paper, we will try to find ESS as a solution of MOPs using our game model based co-evolutionary algorithm. First, we will investigate the validity of our co-evolutionary approach to solve MOPs. That is, we will demonstrate how the evolutionary game can be embodied using co-evolutionary algorithms and also confirm whether it can reach the optimal equilibrium point of a MOP. Second, we will evaluate the effectiveness of our approach, comparing it with other methods through rigorous experiments on several MOPs.

• Asia-Pacific Journal of Business
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• v.13 no.2
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• pp.155-168
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• 2022

Purpose - Although the government and civic groups do not always confront each other over the Me Too movement, the two stakeholders are often conflicted. For example, the two interested parties may have different positions in the gender conflict and be often hostile due to debates over how to institutionalize and distinguish actual harm from innocence. In this situation, the strategies of the two stakeholders for their own ends are inevitably interdependent. This paper is a study on the strategic reciprocity of interested parties in relation to the Me Too Movement, which has recently raised a new discourses in our society. Design/methodology/approach - We derive equilibrium of the reciprocity between civic groups(collectively referred to as the Me Too Movement Headquarters) leading the Me Too Movement and government that must preemptively respond to new social issues, and analyze how changes in some external conditions affect the reactions of the two stakeholders. For this purpose we rely on economic methodology. Findings - In the reciprocity between the two forces, we derive an equilibrium composed of the pair of the government's optimal response level and the civic group's optimal strategy, and further derive the comparative static results according to changes in external conditions. Analysis results are mixed with intuitive results and non-intuitive ones. However, even if the result is not intuitive, rational reasoning is possible as long as it is derived through a rigorous model, and it has several implications. Research implications or Originality - Although this study is a positive approach, it is meaningful as a starting point to explore practical discussion directions and alternatives by adding another new perspective and approach to research in other social science fields with many normative studies.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.134-146
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• 2024

This study introduces and experimentally validates a novel approach that combines Instruction fine-tuning and Low-Rank Adaptation (LoRA) fine-tuning to optimize the performance of Large Language Models (LLMs). These models have become revolutionary tools in natural language processing, showing remarkable performance across diverse application areas. However, optimizing their performance for specific domains necessitates fine-tuning of the base models (FMs), which is often limited by challenges such as data complexity and resource costs. The proposed approach aims to overcome these limitations by enhancing the performance of LLMs, particularly in the analysis precision and efficiency of national Research and Development (R&D) data. The study provides theoretical foundations and technical implementations of Instruction fine-tuning and LoRA fine-tuning. Through rigorous experimental validation, it is demonstrated that the proposed method significantly improves the precision and efficiency of data analysis, outperforming traditional fine-tuning methods. This enhancement is not only beneficial for national R&D data but also suggests potential applicability in various other data-centric domains, such as medical data analysis, financial forecasting, and educational assessments. The findings highlight the method's broad utility and significant contribution to advancing data analysis techniques in specialized knowledge domains, offering new possibilities for leveraging LLMs in complex and resource-intensive tasks. This research underscores the transformative potential of combining Instruction fine-tuning with LoRA fine-tuning to achieve superior performance in diverse applications, paving the way for more efficient and effective utilization of LLMs in both academic and industrial settings.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.27-33
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• 2013

Nowadays, the utilization of renewable energy sources like wind energy is considered one of the most effective means of generating massive amounts of electricity. This is evident in the rapid increase of wind farms all over the world which comprise a huge number of wind turbines. However, the drawback of utilizing wind turbines is that it requires maintenance, which could be a costly operation. To keep the wind turbines in pristine condition so as to reduce downtime, the implementation of CMS (Condition Monitoring System) and FDS (Fault Detection System) is mandatory. The efficiency and accuracy of these systems are crucial in deciding when to carry out a maintenance process. In this paper, a fault detection system based on intelligent clustering method is proposed. Using SCADA data, the clustering model was trained and evaluated for its accuracy through rigorous simulations. Results show that the proposed approach is able to accurately detect the deteriorating condition of a wind turbine as it nears a downtime period.

• Korean Chemical Engineering Research
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• v.49 no.3
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• pp.361-366
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• 2011

By using Monte Carlo simulation method we developed a new molecular simulation software which can be used to predict the thermodynamic properties of organic compounds. Starting from molecular structure and intermolecular potential function, rigorous statistical mechanical principles give a probability distribution for the behavior of a system containing many molecules, which enables us to calculate macroscopic thermodynamic properties of the system. The software developed in this work, cheMC, is based on Windows platform providing with easy access. One can efficiently administrate simulations by using an intuitive interface equipped with visualization tool and chart generation. It is expected that molecular simulations supplement the equation of state approach and will play a more important role in the study of thermodynamic properties.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2470-2491
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• 2018

Web-scale open information extraction (Open IE) plays an important role in NLP tasks like acquiring common-sense knowledge, learning selectional preferences and automatic text understanding. A large number of Open IE approaches have been proposed in the last decade, and the majority of these approaches are based on supervised learning or dependency parsing. In this paper, we present a novel method for web scale open information extraction, which employs cosine distance based on Google word vector as the confidence score of the extraction. The proposed method is a purely unsupervised learning algorithm without requiring any hand-labeled training data or dependency parse features. We also present the mathematically rigorous proof for the new method with Bayes Inference and Artificial Neural Network theory. It turns out that the proposed algorithm is equivalent to Maximum Likelihood Estimation of the joint probability distribution over the elements of the candidate extraction. The proof itself also theoretically suggests a typical usage of word vector for other NLP tasks. Experiments show that the distance-based method leads to further improvements over the newly presented Open IE systems on three benchmark datasets, in terms of effectiveness and efficiency.

• Wind and Structures
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• v.31 no.1
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• pp.15-20
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• 2020

The aircraft industry supports aviation by building aircraft and manufacturing aircraft parts for their maintenance. Fuel economization is one of the biggest concerns in the aircraft industry. The reduction in specific fuel consumption of aircraft can be achieved by a variety of means, simplest and more effective is the one to impose minor modifications in the aircraft main wing or the parts which are exposed to the air flow. This method can lead to a reduction in aerodynamic resistance offered by the air and have a smoother flight. The main objective of this study is to propose geometric design modifications on an existing aircraft wing which acts as a vortex generator and it can reduce the drag and increase lift to drag ratio, leading to lower fuel consumption. The NACA 2412 aircraft wing is modified and designed. Rigorous flow analysis is carried out using computational fluid dynamics based software Ansys Fluent. Results show that saw tooth modification to the main wing shows the best aerodynamic efficiency as compared to other modifications.