• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.1-6
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• 2022

This paper presents a regionalized time slotted channel hopping (TSCH) slotframe-based aerial data collection using wake-up radio. The proposed scheme aims to minimize the delay and energy consumption when an unmanned aerial vehicle (UAV) collects data from sensor devices in the large-scale service area. To this end, the proposed scheme divides the service area into multiple regions, and determines the TSCH slotframe length for each region according to the number of cells required by sensor devices in each region. Then, it allocates the cells dedicated for data transmission to the TSCH slotframe using the ID of each sensor device. For energy-efficient data collection, the sensor devices use a wake-up radio. Specifically, the sensor devices use a wake-up radio to activate a network interface only in the cells allocated for beacon reception and data transmission. The simulation results showed that the proposed scheme exhibited better performance in terms of delay and energy consumption compared to the existing scheme.

• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.89-97
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• 2022

Recently, various problems such as reduced productivity, insufficient inflow of skilled manpower, reduced quality, and concerns about increasing safety accidents have appeared in the domestic construction industry. Stakeholder of construction project are considering the Off-Site Construction (OSC) method rather than the conventional on-site construction as an alternative. Despite the importance of decision making in the early stage of the adoption of OSC, there is a lack of methodologies for rational decision making. In this study, a decision making system has been developed to derive the final construction cost score by deriving the project characteristics, selecting the construction difficulty index, and developing a cost model for each construction method alternatives to calculate the standard construction cost. Using this system, the OSC method can be effectively evaluated in terms of its feasibility in the early stage of construction

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.5
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• pp.73-79
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• 2021

This study was carried out to analyze the properties of the gel propellant and spray characteristics according to the addition of fine particles. The multi-hole diameter was 0.4 mm to induce a high shear rate, and a kerosene gel propellant was prepared using 5 wt% of the Thixatrol ST and SUS304 of 100 nm. The experiment was conducted by fixing the supply pressure in the axial direction to 0.7 MPa and adjusting the supply pressure in the radial direction from 0.7 MPa to 2.1 MPa. Due to the addition of fine particles, pressure vibration during spraying, a small TMR(Total Momentum Ratio) of up to 0.19, and a phenomenon that the spraying angle rapidly increased to more than 70 degrees occurred.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.127-132
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• 2022

As the IoT technology is more developed, it is more important for the accuracy of IoT data. Since the IoT data supports a different formats and protocols, it is often happened that the IoT system is failed or the incorrect data is generated with the unreliable IoT devices(sensor, actuator). Because the abnormality of IoT device or the user situation is not detected correctly, this problem makes the user to be unsatisfied with the IoT system. This study proposes the decision methodology of IoT data consistency whether the IoT data is generated in normal range or not by using the mathematical functions('gradient descent function' and 'linear regression function'). It may be concluded that the gradient function method is suitable for the IoT data which the 'increasing velocity' is related with the next generated pattern(eg. sensor devices), the linear regression function method is suitable for the IoT data which the 'the difference from linear regression function' is related with the next generated pattern in case the data has a linear pattern(eg. water meter, electric meter).

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.143-150
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• 2021

In the recent power industry, a change is taking place from manual meter reading to remote meter reading using AMI(Advanced Metering Infrastructure). If such the power data generated from the AMI is recorded on the blockchain, integrity is guaranteed by preventing forgery and tampering. As data sharing becomes transparent, new business can be created. However, Ethereum blockchain is not suitable for processing large amounts of transactions due to the limitation of processing speed. As a solution to overcome such the limitation, various On/Off-Chain methods are being investigated. In this paper, we propose a interface server using data sharding as a solution for storing large amounts of power data in Etherium blockchain environments. Experimental results show that our power-data processing system with sharding method lessen the data omission rate to 0% that occurs when the transactions are transmitted to Ethereum and enhance the processing speed approximately 9 times.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.359-364
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• 2021

Recently, research on predictive systems using deep learning and machine learning of artificial intelligence is being actively conducted. Due to the development of artificial intelligence, the role of the investment manager is being replaced by artificial intelligence, and due to the higher rate of return than the investment manager, algorithmic trading using artificial intelligence is becoming more common. Algorithmic trading excludes human emotions and trades mechanically according to conditions, so it comes out higher than human trading yields when approached in the long term. The deep learning technique of artificial intelligence learns past time series data and predicts the future, so it learns like a human and can respond to changing strategies. In particular, the LSTM technique is used to predict the future by increasing the weight of recent data by remembering or forgetting part of past data. fbprophet, an artificial intelligence algorithm recently developed by Facebook, boasts high prediction accuracy and is used to predict stock prices and cryptocurrency prices. Therefore, this study intends to establish a sound investment culture by providing a new algorithm for automatic cryptocurrency trading by analyzing the actual value and difference using fbprophet and presenting conditions for accurate prediction.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.25-31
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• 2022

This study aims to investigate the degree of influence of LMS on online classes conducted after COVID-19 at C University in Gyeongsangnam-do, and to examine the relationship between overall class satisfaction and LMS satisfaction variables. C University started the project to construct 'Next-generation Smart LMS' and operated it from the first semester of 2021. As a result of conducting a survey about overall class satisfaction and LMS satisfaction consisting of five variables with 140 learners who have experienced online classes at C University. The learners showed high satisfaction not only in overall classes but also LMS. As a result of regression analysis of LMS satisfaction and overall class satisfaction, it was found that the functional convenience of LMS and interaction with instructors had a significant effect on overall class satisfaction. This study has limitations in that it was conducted only at one college and a limited number of variables were measured.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.5
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• pp.77-88
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• 2022

This study aims to understand the relationship between the distribution of fish species in the two water ecosystems and the habitat factors according to the survey period targeting Gwanggyo Lake Park in the city. There are studies on the appearance and distribution of species by applying eDNA to freshwater ecosystems. However, in the domestic, streams are the target, and studies on the relationship between species distribution and habitat environment in two water environments are lacking. We conducted to analyze the species list and relationship with habitat factors using eDNA research in May and October at 21 points in Gwanggyo Lake Park, Suwon City, which were connected to lakes and streams. As a result, there was no species difference in the water environment according to the survey period. However, the total number of reads during the spawning season(May) was 3,126,482, which was more than double that after the spawning season(October). Tolerant species appeared in Woncheon Lake with a slow or stagnant flow, but there was no significant correlation between species and habitat factors depending on the survey period. On the other hand, intermediate and sensitive species appeared in the Woncheon stream with high flow. There was a significant correlation between the low temperature during the spawning season and the high dissolved oxygen content after the spawning season(P<0.001, Tem.: 20.7±2.6℃, DO: 8.6±1.7). It is expected that environmental DNA will be used to survey species and suggest monitoring methods according to the survey period.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.117-122
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• 2022

In this study, Electromagnetic Induction Power Generation (EMG) is a structure consisting of a stator and a permanent magnet rotor, and is a method that enables power generation by using the kinetic energy of the human arm. Among them, the axial flux permanent magnet (AFPM) technique is a method that can act sensitively to the kinetic energy of the arm at a slow speed of the human body, and has a simple structure and can be designed and manufactured with an ultra-small size. Under the conditions of size of ø46×11mm, rotation speed of 7Hz (420rpm), output voltage 0.4VAC, output current 4.5mA, and output power 30mW were measured and analyzed the same as the target specification. Therefore, the purpose of this study is to study the power generation of the pendulum applying the AFPM (Axial Flux Permanent Magnet) technique to charge power to smart devices with kinetic energy of the human body.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.5
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• pp.67-77
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• 2022

Recently, the trend in structural analysis and design is moving towards the development of reliable system. The reliability-based method defines various limit states related to usability and failure, thereby enabling multiple levels of design according to the importance of a structure. Meanwhile, an actual structure is composed of a set of several elements, and particularly, a frame type is composed of a system in which the members are connected each other. At this time, the actual connection between members is in a semi-rigid condition, not in complete rigid or hinged. This semi-rigid is found in several structures, especially in agricultural facilities designed with lightweight materials. In this study, a system reliability analysis technique for frame structure was established, and applied to an analysis of the semi-rigid connection. Various conditions of correlation were applied to reflect the connectivity between members, and through this, the limitations of existing structural analysis method and the behavioral characteristics of structure were analyzed. The failure probability of the frame member component and the overall structure system was significantly different in consideration of the semi-rigid connection. In addition, it was evaluated that the behavior of structure can be more accurately analyzed if the correlation according to the position of members in a system is further investigated.