• Journal of radiological science and technology
• /
• v.45 no.1
• /
• pp.11-17
• /
• 2022

This study was purpose to quantitative assessment of the resolution characteristics by using American college of radiology(ACR) phantom for magnetic resonance imaging (MRI). The MRI equipment was used (Achiva 3.0T MRI, Philips system, Netherlands) and the head/neck matrix shim SENSE head coil were 32 channels(elements) receive MR coil. And the MRI equipment was used (Discovery MR 750, 3.0T MRI, GE medical system, America) and the head/neck matrix shim MC 3003G-32R 32-CH head coil were receive MR coil. As for the modulation transfer function(MTF) comparison result by using ACR magnetic resonance imaging phantom, the MTF value of the ACR standard T2 image in GE equipment is 0.199 when the frequency is 1.0 mm^-1 and the MTF value of the hospital T2 image in Philips equipment is 0.528. It was used efficiently by using a general sequence more than the standard sequence method using the ACR phantom. In addition it is significant that the quantitative quality assurance evaluation method for resolution characteristics was applied mutatis mutandis, and the result values of the physical image characteristics of the 3.0T MRI device were presented.

• Journal of the Semiconductor & Display Technology
• /
• v.20 no.4
• /
• pp.171-176
• /
• 2021

Die-to-wafer (D2W) hybrid bonding in the multilayer semiconductor manufacturing process is one of wafer direct bonding, and various studies are being conducted around the world. A noteworthy point in the current die-to-wafer process is that a lot of voids occur on the bonding surface of the die during bonding. In this study, as a suggested method for removing voids generated during the D2W hybrid bonding process, a flexible mechanism for implementing convex for die bonding to be applied to the bond head is proposed. In addition, modeling of flexible mechanisms, analysis/design/control/evaluation of static/dynamics properties are performed. The proposed system was controlled by capacitive sensor (lion precision, CPL 290), piezo actuator (P-888,91), and dSpace. This flexure mechanism implemented a working range of 200 ㎛, resolution(3σ) of 7.276nm, Inposition(3σ) of 3.503nm, settling time(2%) of 500.133ms by applying a reverse bridge type mechanism and leaf spring guide, and at the same time realized a maximum step difference of 6 ㎛ between die edge and center. The results of this study are applied to the D2W hybrid bonding process and are expected to bring about an effect of increasing semiconductor yield through void removal. In addition, it is expected that it can be utilized as a system that meets the convex variable amount required for each device by adjusting the elongation amount of the piezo actuator coupled to the flexible mechanism in a precise unit.

• Smart Media Journal
• /
• v.12 no.7
• /
• pp.27-42
• /
• 2023

The development of cloud services and IoT technology has radically changed the cloud environment, and has evolved into a new concept called fog computing and F2C (fog-to-cloud). However, as heterogeneous cloud/fog layers are integrated, problems of access control and security management for end users and edge devices may occur. In this paper, an F2C-based IoT smart health monitoring system architecture was designed to operate a medical information service that can quickly respond to medical emergencies. In addition, a role-based service access control technology was proposed to enhance the security of user's personal health information and sensor information during service interoperability. Through simulation, it was shown that role-based access control is achieved by sharing role registration and user role token issuance information through blockchain. End users can receive services from the device with the fastest response time, and by performing service access control according to roles, direct access to data can be minimized and security for personal information can be enhanced.

• Smart Media Journal
• /
• v.12 no.4
• /
• pp.19-26
• /
• 2023

IoT edge services utilizing neuromorphic hardware architectures are suitable for autonomous IoT applications as they perform intelligent processing on the device itself. However, spiking neural networks applied to neuromorphic hardware are difficult for IoT developers to comprehend due to their complex structures and various hyper-parameters. In this paper, we propose a method for generating spiking neural network (SNN) models that satisfy user performance requirements while considering the constraints of neuromorphic hardware. Our proposed method utilizes previously trained models from pre-processed data to find optimal SNN model parameters from profiling data. Comparing our method to a naive search method, both methods satisfy user requirements, but our proposed method shows better performance in terms of runtime. Additionally, even if the constraints of new hardware are not clearly known, the proposed method can provide high scalability by utilizing the profiled data of the hardware.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2020.01a
• /
• pp.143-144
• /
• 2020

4차 산업 시대가 도래하여 빅데이터와 딥러닝 기술은 다양한 분야에서 아주 중요한 기술로 자리 잡고 있으며, 현재 세계 여러 분야에서 이 기술들을 이용하여 일상, 산업 분야에 적용을 시키고자 한다. 국내에서는 스마트 팩토리, 스마트 시티와 같은 분야에 적용하고 있다. 본 논문에서는 스마트 시티에 적용할 수 있는 횡단보도 상황을 인지하여 교통제어에 활용할 수 있는 빅데이터를 생산하거나 효율적인 교통제어에 활용할 수 있도록 Nvidia Jetson TX2와 실시간 객체 감지 기술인 YOLO v3를 이용하여 횡단보도용 상황 인식을 위한 영상인식 장치를 개발하였다. 제안하는 기술들을 이용하여 스마트시티 구축에 활용할 수 있고, 실시간으로 추가적으로 필요한 객체를 감지하여 확장이 용이한 장점이 있다. 또한 구현에서 효율성을 높이기 위하여 에지 컴퓨팅, 스페이스 디텍션과 같은 기술들을 활용하였다.

• Journal of Internet of Things and Convergence
• /
• v.10 no.2
• /
• pp.17-23
• /
• 2024

Losses in domestic water supply due to leaks are very large, such as fractures and defects in pipelines. Therefore, preventive measures to prevent water leakage are necessary. We propose the development of a leakage detection sensor utilizing vibration sensors and present an optimal leakage detection algorithm leveraging artificial intelligence. Vibrational sound data acquired from water pipelines undergo a preprocessing stage using FFT (Fast Fourier Transform), followed by leakage classification using an optimized tree-based boosting algorithm. Applying this method to approximately 260,000 experimental data points from various real-world scenarios resulted in a 97% accuracy, a 4% improvement over existing SVM(Support Vector Machine) methods. The processing speed also increased approximately 80 times, confirming its suitability for edge device applications.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.4
• /
• pp.77-82
• /
• 2024

Recent advancements in artificial intelligence (AI) technology have led to an increase in the implementation of AI applications in mobile environments. However, due to the limited resources in mobile devices compared to desktops and servers, there is growing interest in research aimed at efficiently executing AI workloads on mobile platforms. While most studies focus on offloading to edge or cloud solutions to mitigate computing resource constraints, research on the characteristics of file I/O related to storage access in mobile settings remains underexplored. This paper analyzes file I/O traces generated during the execution of deep learning applications in mobile environments and investigates how they differ from traditional mobile workloads. We anticipate that the findings of this study will be utilized to design future smartphone system software more efficiently, considering the file access characteristics of deep learning.

• Asia-Pacific Journal of Business
• /
• v.15 no.3
• /
• pp.101-120
• /
• 2024

Purpose - The purpose of this study was to examine the influencing factors on the revisit intention of unmanned convenience stores for Chinese consumers who use unmanned convenience stores. The effect of unmanned convenience store characteristics (operation system, store arrangement) on customers' perceived benefits and the effect of perceived benefits (convenience, speed, stability, playability) on revisit intention were verified. In addition, by using untact propensity as a control variable, the purpose of this study was to examine that the characteristics of unmanned convenience stores have a moderating effect on the perceived benefits of customers. Design/methodology/approach - The study collected 201 survey data from unmanned convenience stores in China. In order to analyze the data, Smart PLS was used to carry out empirical analysis. Findings - The results showed that operating systems had a positive impact on convenience, speed, and safety, while store layout had a positive impact on playfulness. Perceived benefits (convenience, safety, and playfulness) had a positive impact on their intention to revisit. Rapidity had a negative impact on the intention to revisit. Contactless tendencies regulate the effect of operating systems on convenience. Research implications or Originality - Unmanned convenience stores are striving to provide high-quality experiences to customers and increase customer satisfaction by utilizing cutting-edge IT technologies in stores such as AI, mobile device payment services, QR codes, and big data technologies. Recently, research on unmanned convenience stores has been active in the service and distribution industry-related fields, but research on the intention to revisit is insufficient. Also, few studies have used untact propensity as a control variable.

• Journal of the Korean Crystal Growth and Crystal Technology
• /
• v.33 no.2
• /
• pp.83-90
• /
• 2023

The β-Ga₂O₃ has the most thermodynamically stable phase, a wide band gap of 4.8~4.9 eV and a high dielectric breakdown voltage of 8MV/cm. Due to such excellent electrical characteristics, this material as a power device material has been attracted much attention. Furthermore, the β-Ga₂O₃ has easy liquid phase growth method unlike materials such as SiC and GaN. However, since the grown pure β-Ga₂O₃ single crystal requires the intentionally controlled doping due to a low conductivity to be applied to a power device, the research on doping in β-Ga₂O₃ single crystal is definitely important. In this study, various source powders of un-doped, Sn 0.05 mol%, Sn 0.1 mol%, Sn 1.5 mol%, Sn 2 mol%, Sn 3 mol%-doped Ga₂O₃ were prepared by adding different mole ratios of SnO₂ powder to Ga₂O₃ powder, and β-Ga₂O₃ single crystals were grown by using an edge-defined Film-fed Growth (EFG) method. The crystal direction, crystal quality, optical, and electrical properties of the grown β-Ga₂O₃ single crystal were analyzed according to the Sn dopant content, and the property variation of β-Ga₂O₃ single crystal according to the Sn doping were extensively investigated.

• Journal of the Korean Crystal Growth and Crystal Technology
• /
• v.34 no.4
• /
• pp.109-116
• /
• 2024

β-Ga₂O₃ is a representative ultra-wide bandgap (UWBG) semiconductor that has attracted much attention for power device applications due to its wide-bandgap of 4.9 eV and high-breakdown voltage of 8 MV/cm. In addition, because solution growth is possible, it has advantages such as fast growth rate and lower production cost compared to SiC and GaN [1-2]. In this study, we have successfully grown Si-doped 10 mm thick Si-doped β-Ga₂O₃ single crystals by the EFG (Edge-defined Film-fed Growth) method. The growth direction and growth principal plane were set to [010] / (010), respectively, and the growth speed was 7~20 mm/h. The as-grown β-Ga₂O₃ single crystal was cut into various crystal planes (001, 100, ${\bar{2}}01$) and off-angles (1^o, 3^o, 4^o), and then surface processed. After processed, the homoepitaxial layer was grown on the epi-ready substrate using the HVPE (Halide vapor phase epitaxy) method. The processed samples and the epi-layer grown samples were analyzed by XRD, AFM, OM, and Etching to compare the surface properties according to the crystal plane and off-angle.