• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.2060-2073
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• 2022

Cloud Computing permits users to access vast amounts of services of computing power in a virtualized environment. Providing secure services is essential. There are several problems to real-world optimization that are dynamic which means they tend to change over time. For these types of issues, the goal is not always to identify one optimum but to keep continuously adapting to the solution according to the change in the environment. The problem of scheduling in Cloud where new tasks keep coming over time is unique in terms of dynamic optimization problems. Until now, there has been a large majority of research made on the application of various Evolutionary Algorithms (EAs) to address the issues of dynamic optimization, with the focus on the maintenance of population diversity to ensure the flexibility for adapting to the changes in the environment. Generally, trust refers to the confidence or assurance in a set of entities that assure the security of data. In this work, a dynamic optimization technique is proposed to find an optimal trust weights in cloud during scheduling.

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.688-700
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• 2022

A composite bionic soft gripper integrated with electromagnets and magneto-active elastomers is designed by combining the structure of the human hand and the snake's behavior of enhancing friction by actively adjusting the scales. A silicon-based polymer containing magnetized hard magnetic particles is proposed as a soft finger, and it can be reversibly bent by adjusting the magnetic field. Experiments show that the length, width, and height of rectangular soft fingers and the volume ratio of neodymium-iron-boron have different effects on bending angle. The flexible fingers with 20 vol% are the most efficient, which can bend to 90° when the magnetic field is 22 mT. The flexible gripper with four fingers can pick up 10.51 g of objects at the magnetic field of 105 mT. In addition, this composite bionic soft gripper has excellent magnetron performance, and it can change surface like snakes and operate like human hands. This research may help develop soft devices for magnetic field control and try to provide new solutions for soft grasping.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3419-3437
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• 2022

Anonymization technology is an important technology for privacy protection in the process of data release. Usually, before publishing data, the data publisher needs to use anonymization technology to anonymize the original data, and then publish the anonymized data. However, for data publishers who do not have or have less anonymized technical knowledge background, how to configure appropriate parameters for data with different characteristics has become a more difficult problem. In response to this problem, this paper adds a historical configuration scheme resource pool on the basis of the traditional anonymization process, and configuration parameters can be automatically recommended through the historical configuration scheme resource pool. On this basis, a privacy model hybrid recommendation algorithm for user satisfaction is formed. The algorithm includes a forward recommendation process and a reverse recommendation process, which can respectively perform data anonymization processing for users with different anonymization technical knowledge backgrounds. The privacy model hybrid recommendation algorithm for user satisfaction described in this paper is suitable for a wider population, providing a simpler, more efficient and automated solution for data anonymization, reducing data processing time and improving the quality of anonymized data, which enhances data protection capabilities.

• Journal of the Korean GEO-environmental Society
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• v.23 no.10
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• pp.21-31
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• 2022

Prospecting ice on Moon requires drilling systems to obtain subsurface samples and measure composition of ice deposits. Landers and rovers need to be equipped with drilling equipment in order to analyze the ice and subsurface resources located at the poles of Moon. These devices must be small, lightweight, low-power, highly efficient and high-performance units in order to function properly under the extreme conditions of the lunar environment. Researchers have developed a prototype drilling apparatus that is able to operate in atmospheric and cold environments. Newly developed drilling system in Korea, which is capable of performing not only sampling but also subsurface investigation, is introduced.

• Smart Structures and Systems
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• v.29 no.6
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• pp.777-783
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• 2022

Even though several deep learning-based methods have been applied in the field of acoustic source localization, the previous works have only been conducted using the two-dimensional representation of the beamforming maps, particularly with the planar array system. While the acoustic sources are more required to be localized in a spherical microphone array system considering that we live and hear in the 3D world, the conventional 2D equirectangular map of the spherical beamforming map is highly vulnerable to the distortion that occurs when the 3D map is projected to the 2D space. In this study, a 3D deep learning approach is proposed to fulfill accurate source localization via distortion-free 3D representation. A target function is first proposed to obtain 3D source distribution maps that can represent multiple sources' positional and strength information. While the proposed target map expands the source localization task into a point-wise prediction task, a PointNet-based deep neural network is developed to precisely estimate the multiple sources' positions and strength information. While the proposed model's localization performance is evaluated, it is shown that the proposed method can achieve improved localization results from both quantitative and qualitative perspectives.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.63-71
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• 2021

This paper propose an development of the unmanned automatic test system for a portable detector using TRIZ Methodology. A new development scheme among of the unmanned automatic test system configurations was obtained after application of the TESE(Trends of Engineering System Evolution) one of the TRIZ methods. Using Pugh matrix drives some improving ideas. The key idea of this unmanned automatic test system scheme is to minimize whole test procedure time of each portable detector and to maximize the amount of portable detectors at once. Between the before and the after configurations of the 3D mechanical model find out improvements. This paper shows that the proposed development scheme improves the test performance efficiency compared to previous scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3970-3990
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• 2021

In view of the problems of insufficient data collection and processing capability of multi-source heterogeneous equipment, and low visibility of equipment status at the ship block construction site. A data collection method for ship block construction equipment based on wireless sensor network (WSN) technology and a data processing method based on edge computing were proposed. Based on the Browser/Server (B/S) architecture and the OneNET platform, an online monitoring system for ship block construction equipment was designed and developed, which realized the visual online monitoring and management of the ship block construction equipment status. Not only that, the feasibility and reliability of the monitoring system were verified by using the intelligent tire frame system as the application object. The research of this project can lay the foundation for the ship block construction equipment management and the ship block intelligent construction, and ultimately improve the quality and efficiency of ship block construction.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.319-331
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• 2022

The latest global COVID-19 pandemic has made the use of facial masks an important aspect of our lives. People are advised to cover their faces in public spaces to discourage illness from spreading. Using these face masks posed a significant concern about the exactness of the face identification method used to search and unlock telephones at the school/office. Many companies have already built the requisite data in-house to incorporate such a scheme, using face recognition as an authentication. Unfortunately, veiled faces hinder the detection and acknowledgment of these facial identity schemes and seek to invalidate the internal data collection. Biometric systems that use the face as authentication cause problems with detection or recognition (face or persons). In this research, a novel model has been developed to detect and recognize faces and persons for authentication using scale invariant features (SIFT) for the whole segmented face with an efficient local binary texture features (DLBP) in region of eyes in the masked face. The Fuzzy C means is utilized to segment the image. These mixed features are trained significantly in a convolution neural network (CNN) model. The main advantage of this model is that can detect and recognizing faces by assigning weights to the selected features aimed to grant or provoke permissions with high accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1209-1223
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• 2022

Blood pressure is one of the key physiological parameters for determining human health, and can prove whether human cardiovascular function is healthy or not. In general, what we call blood pressure refers to arterial blood pressure. Blood pressure fluctuates greatly and, due to the influence of various factors, even varies with each heartbeat. Therefore, achievement of continuous blood pressure measurement is particularly important for more accurate diagnosis. It is difficult to achieve long-term continuous blood pressure monitoring with traditional measurement methods due to the continuous wear of measuring instruments. On the other hand, radar technology is not easily affected by environmental factors and is capable of strong penetration. In this study, by using machine learning, tried to develop a linear blood pressure prediction model using data from a public database. The radar sensor evaluates the measured object, obtains the pulse waveform data, calculates the pulse transmission time, and obtains the blood pressure data through linear model regression analysis. Confirm its availability to facilitate follow-up research, such as integrating other sensors, collecting temperature, heartbeat, respiratory pulse and other data, and seeking medical treatment in time in case of abnormalities.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.163-172
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• 2022

The development of ICT technology has created new channels for product sales and promotion, which not only make information accessible to customers as easy as possible, but also provide consumers with much more absolute and comparative information. Modern consumers are exposed so many shopping channels currently, especially mobile-based channels have grown significantly and have become the center of the market. It is true that mobile shopping has led the growth of overall online shopping with the recent development of mobile devices such as smartphones and related software. The importance of strengthening corporate competitiveness and mobile-based management strategies through on line channels continues to increase. At this point, this study attempted to investigate the influencing factors by focusing on the entire distribution channel and mobile shopping channels. As most of previous studies were focused on Internet shopping malls or specific channels, So the research on mobile channels can be judged to be timely and appropriate. Furthermore, it can be said that mobile shopping channels are now presenting empirical implications. In conclusion, it provides practical implications to examine the management strategy of mobile shopping channels from the perspective of consumer value.