• International conference on construction engineering and project management
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• 2020.12a
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• pp.463-481
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• 2020

Cutter suction dredgers (CSDs) are widely used in various dredging constructions such as channel excavation, wharf construction, and reef construction. During a CSD construction, the main operation is to control the swing speed of cutter to keep the slurry concentration in a proper range. However, the slurry concentration cannot be monitored in real-time, i.e., there is a "time-lag effect" in the log of slurry concentration, making it difficult for operators to make the optimal decision on controlling. Concerning this issue, a solution scheme that using real-time monitored indicators to predict current slurry concentration is proposed in this research. The characteristics of the CSD monitoring data are first studied, and a set of preprocessing methods are presented. Then we put forward the concept of "index class" to select the important indices. Finally, an ensemble learning algorithm is set up to fit the relationship between the slurry concentration and the indices of the index classes. In the experiment, log data over seven days of a practical dredging construction is collected. For comparison, the Deep Neural Network (DNN), Long Short Time Memory (LSTM), Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and the Bayesian Ridge algorithm are tried. The results show that our method has the best performance with an R² of 0.886 and a mean square error (MSE) of 5.538. This research provides an effective way for real-time predicting the slurry concentration of CSDs and can help to improve the stationarity and production efficiency of dredging construction.

• Asia Marketing Journal
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• v.7 no.1
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• pp.43-65
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• 2005

In most leading companies, new product development is one of the most important corporate activities which affects the very existence of them. Therefore, CFT(cross-functional team) is frequently used to utilize knowledge and experiences of its members from various teams. To ensure the successful operation of CFT, various structural assistances, such as committee and Task Force Team, are made which will coordinate smooth interactions among members. Many researches show that the increase of interaction among team members affects the performance. This research is exploratory research intend to show the effects of relational characteristics such as group efficacy and participation on the perceived performance of new product development. This research examines the performance mechanism that lies in between CFT and its members by expanding the understandings on the relationship between interaction and performance in new product development CFT. Results show that the level of interaction affect group efficacy. and group efficacy affect participation. Finally, participation affect perceived performance. However. it shows that the level of interaction and group efficacy do not have direct effect on perceived performance.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.183-192
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• 2023

This study analyzes the performance of flipped learning, an offline class method conducted in a degree-linked work-learning parallel system. Training in the work-study parallel system, which is conducted as part of job competency improvement, has thoroughly adhered to the offline method, but in line with COVID-19, unlike before, it is changing in the direction of using the online method more actively. However, educational methods such as flipped learning are not new because the degree-linked operation is applied to the academic system and education method of universities and is practically the same form as general university education. Therefore, it is necessary to analyze the educational performance and complementary points of flipped learning, which has recently been expanded in the degree-linked work-study parallel system, considering the characteristics of this system, in which classes are held only on weekends. As a result of statistical analysis based on the survey, some of the outcomes of flipped learning have been confirmed, and in order to increase the performances, it is necessary to continuously seek out specific measures to encourage learning and expand communication between instructors and students.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.552-560
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• 2023

Aircraft midair collisions are dangerous events that can cause massive casualties. To prevent this, civil aviation has mandated the installation of TCAS (ACAS), which is becoming more sophisticated with the help of new technologies. However, there are institutional problems in collecting data for TCAS research in Korea, limiting the ability to obtain data for personal research. ADS-B and Mode-S automatic broadcast various information about the flight status of the aircraft. This data also contains information about TCAS RA, which can be used by anyone to find examples of TCAS RA operation. We used the databases of ADS-B Exchange and Opensky-Network to acquire data and visually represent three TCAS RA cases through Python coding. We also identified domestic TCAS cases in the first half of 2023 and analyzed their characteristics to confirm the usefulness of the data.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.958-963
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• 2023

Lately, there has been increasing research on the prediction of motion performance using artificial intelligence for the safe design and operation of ships. However, compared to conventional ships, research on small fishing boats is insufficient. In this paper, we propose a model that estimates the motion response essential for calculating the motion performance of small fishing boats using a deep neural network. Hydrodynamic analysis was conducted on 15 small fishing boats, and a database was established. Environmental conditions and main particulars were applied as input data, and the response amplitude operators were utilized as the output data. The motion response predicted by the trained deep neural network model showed similar trends to the hydrodynamic analysis results. The results showed that the high-frequency motion responses were predicted well with a low error. Based on this study, we plan to extend existing research by incorporating the hull shape characteristics of fishing boats into a deep neural network model.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.4
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• pp.437-445
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• 2023

A space system refers to a network of sensors, ground systems, and space-craft operating in space. The security of space systems relies on information systems and networks that support the design, launch, and operation of space missions. Characteristics of space operations, including command and control (C2) between space-craft (including satellites) and ground communication, also depend on wireless frequency and communication channels. Attackers can potentially engage in malicious activities such as destruction, disruption, and degradation of systems, networks, communication channels, and space operations. These malicious cyber activities include sensor spoofing, system damage, denial of service attacks, jamming of unauthorized commands, and injection of malicious code. Such activities ultimately lead to a decrease in the lifespan and functionality of space systems, and may result in damage to space-craft and, lead to loss of control. The Cybersecurity Adversarial Tactics, Techniques, and Common Knowledge (ATT&CK) matrix, proposed by Massachusetts Institute of Technology Research and Engineering (MITRE), consists of the following stages: Reconnaissance, Resource Development, Initial Access, Execution, Persistence, Privilege Escalation, Defense Evasion, Credential Access, Discovery, Lateral Movement, Collection, Command & Control, Exfiltration, and Impact. This paper identifies cybersecurity activities in space systems and satellite navigation systems through the National Institute of Standards and Technology (NIST)'s standard documents, former U.S. President Trump's executive orders, and presents risk management activities. This paper also explores cybersecurity's tactics attack techniques within the context of space systems (space-craft) by referencing the Sparta ATT&CK Matrix. In this paper, security threats in space systems analyzed, focusing on the cybersecurity attack tactics, techniques, and countermeasures of space-craft presented by Space Attack Research and Tactic Analysis (SPARTA). Through this study, cybersecurity attack tactics, techniques, and countermeasures existing in space-craft are identified, and an understanding of the direction of application in the design and implementation of safe small satellites is provided.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.37-44
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• 2023

As a primary technology of Industry 4.0, human-robot collaboration (HRC) requires additional measures to ensure worker safety. Previous studies on avoiding collisions between collaborative robots and workers mainly detect collisions based on sensors and cameras attached to the robot. This method requires complex algorithms to continuously track robots, people, and objects and has the disadvantage of not being able to respond quickly to changes in the work environment. The present study was conducted to implement a web-based platform that manages collaborative robots by recognizing the emotions of workers - specifically their perception of danger - in the collaborative process. To this end, we developed a web-based application that collects and stores emotion-related brain waves via a wearable device; a deep-learning model that extracts and classifies the characteristics of neutral, positive, and negative emotions; and an Internet-of-things (IoT) interface program that controls motor operation according to classified emotions. We conducted a comparative analysis of our system's performance using a public open dataset and a dataset collected through actual measurement, achieving validation accuracies of 96.8% and 70.7%, respectively.

• The Journal of Korea Robotics Society
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• v.18 no.4
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• pp.444-455
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• 2023

In this report, a specialization plan for wearable robots by mission profile was investigated and analyzed to derive an application plan. The final goal of this study was to derive the operating requirements of wearable robots according to specialized plans, and to conduct a specialized study on wearable robots by mission profile through investigation/analysis of specialized plans for each mission profile. In the study, 1) Research on technology trends related to military wearable robots such as patents and papers, 2) Research/analysis of mission profiles to characterize wearable robots, 3) Analysis of wearable robot specialization plans according to mission profiles, and 4) Requirements for wearable robot operation were derived. In the first time of the study, a survey on technology trends related to wearable robots for soldiers such as patents and papers was completed, and a military consultative body was conducted to derive measures to characterize wearable robots. In addition, a survey was conducted on mission profiles, and the second time study derived Key Performance Parameters (KPP) for operational performance, core performance, and system performance based on scenarios by mission profile. However, it is revealed that the KPP derived from the research results was not covered in this paper because it was judged that more in-depth research was needed prior to disclosure. In order to prepare for future battlefield situations and increase the usability of wearable robots, this study was conducted to characterize wearable robots by considering the characteristics of soldiers' equipment according to mission profiles and to characterize wearable robots by mission profile.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.495-507
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• 2023

The purpose of this study is to identify the current status of legal disputes that occur while firefighters are performing their duties and to suggest efficient response measures. To investigate awareness of legal disputes, a survey was conducted on 3,500 firefighters, and the responses of 505 people who participated in the survey were analyzed. As a research method, frequency analysis and cross-analysis were conducted based on the demographic characteristics of the participants and a survey of firefighters' awareness of the law, and through this, basic statistics and status were analyzed. As a result of the analysis, it was found that firefighters feel a lot of burden, including time and material losses, as well as disadvantages and mental anxiety in the workplace when legal disputes occur while performing their duties. The need for an organizational response in the workplace as an efficient response to this was statistically confirmed. Therefore, based on the results of this study, we propose the permanent establishment and operation of a professional legal support team within each city/provincial fire department headquarters so that firefighters can concentrate on their duties free from legal disputes.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.300-305
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• 2023

This thesis is a study of content development utilizing media outlets to date through digital humans. The trend of global content is that the video content industry, including the character business, is growing. Lil Michela, who was selected as one of the 25 most influential people on the Internet by Time magazine in 2018, Nasua, who appeared in a SK Telecom commercial, and Rosie, who appeared in a Shinhan Bank commercial, are representative. Digital humans, which are driving new content, are computer-generated human characters with various characteristics and are referred to as virtual humans, metahumans, and cyber humans. With the rise of the metaverse after COVID-19, digital humans are being utilized in various forms such as media and marketing as an element of visual content. In the form of media, we can see that the boundaries between the offline and digital worlds are converging, and in the form of marketing, we can see that digital humans connect consumers and products more naturally. In the form of interaction, it is possible to achieve two-way communication through various methods of operation, and through these factors, it is possible to go beyond behavioral communication in the form of memorialization to emotional communication through AI technology. What can be seen through these processes is that through the currently developing digital human production methods and AI functions, not only experts but also non-experts can create quality contents, and new directions of contents will appear, and contents that can provide immediate feedback by bringing consumers and creators closer together have been studied.