Monitoring river microplastics is a challenging task since it is a time-consuming and high-cost process. The use of a physical model to have a better understanding of river microplastics' behaviors can complement the challenging monitoring process. However, there have been very limited studies on modeling river microplastics. In this study, therefore, we evaluated the applicability of one commonly used river water quality model, i.e., the Water Quality Analysis Simulation Program (WASP), in simulating the microplastic concentration in the river environment. We simulated the microplastic concentration in the Anyangcheon stream using the WASP's biochemical oxygen demand (BOD) and suspended solid (SS) variables as possible surrogate variables for the microplastics. Simulation analyses indicate that the SS state variable performs better than the BOD state variable to mimic the observed concentrations of microplastics. This is because of the characteristics of each water quality parameter; the BOD variable, a biochemical indicator, is inappropriate for modeling the behaviors of microplastics, which have generally constant biochemical features. In contrast, the SS variable, which has similar physical behaviors, followed the observed patterns of the microplastic concentrations well. To build a more advanced and accurate model for simulating the microplastic concentration, comprehensive and long-term monitoring studies of the river microplastics under different environmental conditions are needed, and the unit of microplastic concentration should be carefully addressed before its modeling application.
KSCE Journal of Civil and Environmental Engineering Research
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v.30
no.3C
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pp.141-148
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2010
Electrical noises like self potential, burst noises and 60-Hz electrical noises are one of the causes to reduce reliability of electrical resistivity survey. Even the PDC-R (Pseudo DC resisitivity) technique, recently developed, is suffering from the problem of low reliability due to electrical noises. That is, both DC-based and AC-based resistivity technique is subject to reliability problem due to electrical noises embedded in urban geotechnical sites. In this research, a new technique to enhance reliability of the PDC-R technique by minimizing influence of electrical noises was proposed. In addition, an automated procedure was also proposed to facilitate data analysis and interpretation of PDC-R measurements. The proposed technique is composed of two steps: 1. to extract information only related with the input current by means of multiple-filter technique, and 2. to undertake a task to sort out signal information only to show stable and reliable characteristics. This automated procedure was verified by a synthetic harmonic wave including DC shift, burst random noises and 60-Hz electrical noises. Also the procedure was applied to site investigation at urban areas for proving its feasibility and accuracy.
This study conducted in-depth interviews with 5 successful and 6 unsuccessful sales persons and analyzed their activities to further clarify the concepts of learning orientation, performance orientation, working smart, working hard and adaptive selling which have been reported as antecedents of sales persons' performances. We found that successful sales persons had their own distinctive characteristics. First, they regarded their selling activities as a part of their lives, not as a task, and were proud of themselves. Second, they perceived their weaknesses from most of activity areas, voluntarily participated in educational programs, and studied not only their products but also competitive products. Third, successful sales persons conducted customer-oriented activities. They collected data on their customers' personal records, developed customer typology by styles or personalities, and consulted their customers using those data. Fourth, successful sales people carefully prepared their meetings with customers across steps in selling processes and they did their best to develop long term relationship with their customers. These results provide useful implications about objective evaluations on sales persons' customer orientations and adaptive selling abilities, and also clarify the concepts of 'working smart' and 'adaptive selling'.
KIPS Transactions on Software and Data Engineering
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v.12
no.11
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pp.481-492
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2023
This study explores how to build a Korean dataset to extract information from text using generative large language models. In modern society, mixed information circulates rapidly, and effectively categorizing and extracting it is crucial to the decision-making process. However, there is still a lack of Korean datasets for training. To overcome this, this study attempts to extract information using text-based zero-shot learning using a generative large language model to build a purposeful Korean dataset. In this study, the language model is instructed to output the desired result through prompt engineering in the form of "system"-"instruction"-"source input"-"output format", and the dataset is built by utilizing the in-context learning characteristics of the language model through input sentences. We validate our approach by comparing the generated dataset with the existing benchmark dataset, and achieve 25.47% higher performance compared to the KLUE-RoBERTa-large model for the relation information extraction task. The results of this study are expected to contribute to AI research by showing the feasibility of extracting knowledge elements from Korean text. Furthermore, this methodology can be utilized for various fields and purposes, and has potential for building various Korean datasets.
Maritime transportation is one of the oldest means of transportation utilized by mankind, and it has significantly contributed to the advancement of civilization by efficiently transporting bulk cargo at a low cost. The study aim to identify the factors influencing the selection of shipping companies in the bulk shipping market and provide insights for improving the competitiveness of shipping-related companies. To achieve this goal, the Analytic Hierarchy Process (AHP) was employed. For the empirical analysis, previous research, interviews, and a pilot test were conducted to identify five top-level factors such as companies, vessels, operations, services, and transaction factors. Each top-level factor has four sub-factors. The results of the analysis, based on 80 valid questionnaires, are as follows: Firstly, in the selection of shipping companies, the priority of factors influencing the choice of shipping companies was as follows: vessel factors were the most important, followed by company, operations, relationship, and service factors. Secondly, when investigating the priority of sub-factors, the availability/appropriateness of vessels was the most crucial factor, followed by company characteristics, financial soundness, and the company's reputation in order. The implications of these findings suggest that shipowners should focus on securing more suitable vessels and enhancing their reputation in response to shippers' demand. Shippers, on the other hand, should consider maintaining a healthy financial structure as a crucial task in securing competitive shipping service providers.
The growth of the live commerce market allows you to conveniently and simply start live commerce anytime, anywhere with a smartphone. The use of smartphone services provides continuous communication and is used while feeling psychological attachment, and it leads to psychological attachment, self-consistency with consumers themselves, and self-identity. This study focuses on the motives and perceptions of consumers using live commerce. In other words, we will examine the relationship with service attachment through the moderating effect of self-efficacy and control focus tendency as consumers' personal and psychological characteristics. In other words, the tendency of regulatory focus, which determines the direction of behavior of consumers according to their motives and goals, affects the service attachment of live commerce. We believe that self-efficacy, which is personal confidence and belief that you can plan and execute on your own for the desired outcome in a given situation or task, will control this relationship. As a result of this research, consumers who highly perceive prevention focus were more likely to avoid negative consequences and pursue safety and obligations. Their attachment to live commerce services was stronger, offsetting their confidence and self-efficacy. When using live commerce services, the more they perceive that information acquisition is beneficial, the higher their belief, and self-efficacy, so service attachment, which is an emotional experience as well as a cognitive experience, is strongly formed for consumers with a preventive focus to avoid safety-seeking and negative consequences. Through the present research results, we believe that it will be helpful in operating strategies and management for companies and small business owners who want to understand the psychological behavior of consumers in using live commerce services.
KIPS Transactions on Software and Data Engineering
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v.12
no.12
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pp.505-518
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2023
3D point cloud semantic segmentation is a computer vision task that involves dividing the point cloud into different objects and regions by predicting the class label of each point. Existing 3D semantic segmentation models have some limitations in performing sufficient fusion of multi-modal features while ensuring both characteristics of 2D visual features extracted from RGB images and 3D geometric features extracted from point cloud. Therefore, in this paper, we propose MMCA-Net, a novel 3D semantic segmentation model using 2D-3D multi-modal features. The proposed model effectively fuses two heterogeneous 2D visual features and 3D geometric features by using an intermediate fusion strategy and a multi-modal cross attention-based fusion operation. Also, the proposed model extracts context-rich 3D geometric features from input point cloud consisting of irregularly distributed points by adopting PTv2 as 3D geometric encoder. In this paper, we conducted both quantitative and qualitative experiments with the benchmark dataset, ScanNetv2 in order to analyze the performance of the proposed model. In terms of the metric mIoU, the proposed model showed a 9.2% performance improvement over the PTv2 model using only 3D geometric features, and a 12.12% performance improvement over the MVPNet model using 2D-3D multi-modal features. As a result, we proved the effectiveness and usefulness of the proposed model.
Volkova Nataliia;Poyasok Tamara;Symonenko Svitlana;Yermak Yuliia;Varina Hanna;Rackovych Anna
International Journal of Computer Science & Network Security
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v.24
no.4
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pp.127-134
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2024
The article highlights the problems of the digitalization of the educational process, which affect the pedagogical cluster and are of a psychological nature. The authors investigate the transformational changes in education in general and the individual beliefs of each subject of the educational process, caused by both the change in the format of learning (distance, mixed), and the use of new technologies (digital, communication). The purpose of the article is to identify the strategic trend of the educational process, which is a synergistic combination of pedagogical methodology and psychological practice and avoiding dialectical opposition of these components of the educational space. At the same time, it should be noted that the introduction of digital technologies in the educational process allows for short-term difficulties, which is a usual phenomenon for innovations in the educational sphere. Consequently, there is a need to differentiate the fundamental problems and temporary shortcomings that are inherent in the new format of learning (pedagogical features). Based on the awareness of this classification, it is necessary to develop psychological techniques that will prevent a negative reaction to the new models of learning and contribute to a painless moral and spiritual adaptation to the realities of the present (psychological characteristics). The methods used in the study are divided into two main groups: general-scientific, which investigates the pedagogical component (synergetic, analysis, structural and typological methods), and general-scientific, which are characterized by psychological direction (dialectics, observation, and comparative analysis). With the help of methods disclosed psychological and pedagogical features of the process of digitalization of education in a mixed learning environment. The result of the study is to develop and carry out methodological constants that will contribute to the synergy for the new pedagogical components (digital technology) and the psychological disposition to their proper use (awareness of the effectiveness of new technologies). So, the digitalization of education has demonstrated its relevance and effectiveness in the pedagogical dimension in the organization of blended and distance learning under the constraints of the COVID-19 pandemic. The task of the psychological cluster is to substantiate the positive aspects of the digitalization of the educational process.
AI is accepted not only in the private sector but also in the defense sector as a cutting-edge technology that must be introduced for the development of national defense. In particular, artificial intelligence has been selected as a key task in defense science and technology innovation, and the importance of data is increasing. As the national defense department shifts from a closed data policy to data sharing and activation, efforts are being made to secure high-quality data necessary for the development of national defense. In particular, we are promoting a review of the business budget system to secure data so that related procedures can be improved to reflect the unique characteristics of AI and big data, and research and development can begin with sufficient large quantities and high-quality data. However, there is a need to establish standardization and quality standards for structured data and unstructured data at the national defense level, but the defense department is still proposing standardization and quality standards for structured data, so this needs to be supplemented. In this paper, we propose an unstructured data set standard format for defense unstructured data sets, which are most needed in defense artificial intelligence, and based on this, we propose a standardization method for defense unstructured data sets.
Journal of the Korea Institute of Building Construction
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v.24
no.1
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pp.67-75
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2024
In the context of Korean residential heating systems, Ondol pipelines are a prevalent choice. However, the maintenance of these pipelines becomes a complex task once they are embedded within concrete structures. As time progresses, the accumulation of sludge, corrosive oxides, and microorganisms on the inner surfaces of these pipelines diminishes their heating efficiency. In extreme scenarios, this accumulation can induce corrosion and scale formation, compromising the system's integrity. Consequently, this research introduces an ultrasonic generation system tailored for the upkeep of Ondol pipelines, with the objective of empirically assessing its practicality. This investigation delineates three variants of ultrasonic generating apparatuses: those employing surface vibration, external generation, and internal generation techniques. To emulate the presence of contaminants within the pipelines, substances in powder, slurry, and liquid forms were employed. The efficacy of the cleaning process post-ultrasonic wave application was scrutinized over time, with image analysis methodologies being utilized to evaluate the outcomes. The findings indicate that ultrasonic waves, whether generated externally or internally, exert a beneficial effect on the cleanliness of the pipelines. Given the inherent characteristics of Ondol pipelines, external generation proves impractical, thereby rendering internal generation a more viable solution for pipeline maintenance. It is anticipated that future endeavors will pave the way for innovative maintenance strategies for Ondol pipelines, particularly through the advancement of internal generation technologies for pipeline applications.
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