• Journal of KIISE
• /
• v.42 no.5
• /
• pp.591-600
• /
• 2015

SLA (Service Level Agreement) is an essential factor that must be guaranteed to provide a reliable and consistent service to user in cloud computing environment. Especially, a contract between user and service provider with SLA is important in an environment using a cloud service brokerage. The cloud computing is classified into IaaS, PaaS, and SaaS according to IT resources of the various cloud service. The existing SLA is difficult to reflect the quality factors of service, because it only considers factors about the physical Network environment and have no methodological approach. In this paper, we suggested a method to specify the quality characteristics of software and proposed a mechanism and structure that can exchange SLA specification between the service provider and consumer. We defined a meta-model for the SLA specification in the SaaS level, and quality requirements of the SaaS were described by the proposed specification language. Through case studies, we verified proposed specification language that can present a variety of software quality factors. By using the UDDI-based mediation process and architecture to interchange this specification, it is stored in the repository of quality specifications and exchanged during service binding time.

• Korean Chemical Engineering Research
• /
• v.57 no.5
• /
• pp.628-636
• /
• 2019

In various industrial processes, piping serves as a link between unit processes and is an essential installation for internal flow. Therefore, the optimum design of the piping system is very important in terms of safety and cost, which requires the estimation of the pressure drop, flow rate, pipe size, etc. in the piping system. In this study, we developed a software that determines pressure drop, flow rate, and pipe size when any two of these design variables are known. We categorized the flows into single phase, homogeneous two phase, and separated two phase flows, and applied suitable calculation models accordingly. We also constructed a system library for the calculation of the pipe material, relative roughness, fluid property, and friction coefficients to minimize user input. We further created a costing library according to the piping material for the calculation of the investment cost of the pipe per unit length. We implemented all these functions in an integrated environment using a graphical user interface for user convenience, and C # programming language. Finally, we verified the accuracy of the software using literature data and examples from an industrial process with obtained deviations of 1% and 8.8% for the single phase and two-phase models.

• KIPS Transactions on Software and Data Engineering
• /
• v.8 no.5
• /
• pp.193-204
• /
• 2019

The explosion of data due to the improvement of sensor technology and computing performance has become the basis for analyzing the situation in the industrial fields, and various attempts to detect events based on such data are increasing recently. In particular, sound signals collected from sensors are used as important information to classify events in various application fields as an advantage of efficiently collecting field information at a relatively low cost. However, the performance of sound-event classification in the field cannot be guaranteed if noise can not be removed. That is, in order to implement a system that can be practically applied, robust performance should be guaranteed even in various noise conditions. In this study, we propose a system that can classify the sound event after generating the enhanced sound signal based on the deep learning algorithm. Especially, to remove noise from the sound signal itself, the enhanced sound data against the noise is generated using SEGAN applied to the GAN with a VAE technique. Then, an end-to-end based sound-event classification system is designed to classify the sound events using the enhanced sound signal as input data of CNN structure without a data conversion process. The performance of the proposed method was verified experimentally using sound data obtained from the industrial field, and the f1 score of 99.29% (railway industry) and 97.80% (livestock industry) was confirmed.

• Journal of The Korean Association of Information Education
• /
• v.23 no.2
• /
• pp.131-139
• /
• 2019

From 2019, software education has become a required subject for all elementary school students. However, many teachers are still unfamiliar with how the classes should be instructed. So this paper presented the meaning, detailed competencies and achievement standard in order to help in the collection, analysis and representation of data among the computational thinking that are key to software education. And it also suggested the applicability of the classes. The full course of the paper is summarized as follows. First, existing studies have summarized the meaning, detail and achievement standard of data related competencies. Based on this, a preliminary investigation was instructed. Pilot study carried out both FGI and closed questions at the same time. This was done in response to the survey's questionnaire reflecting the opinions of experts. Second, the results of the questionnaire generated as a result of the above were verified for validity, stability, and reliability among the PhD, PhD courses, software education teachers, and software education workers. Third, I developed and applied the five lessons as a class objective as 'Choosing collection method-Select the collection method according to the problem situation.', 'Searching for meaning of data-Understand what the analyzed data mean..', 'Using various expression methods-Use a variety of expression tools.' using the backward design model to integrate education, class, and assessment. As a result, the detailed competencies of data collection, analysis, and representation and achievement standard were presented. This may help in setting specific and specific criteria for what direction classes are recommended when planning data-related classes in elementary schools.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.49 no.8
• /
• pp.671-680
• /
• 2021

This paper deals with the contents of designing and producing reconnaissance hardware and software, and verifying the functions after being installed on the CanSat platform and ground stations. The main reconnaissance mission is largely composed of two things: terrain search that renders the surrounding terrain in 3D using radar, GPS, and IMU sensors, and real-time detection of major objects through optical camera image analysis. In addition, data analysis efficiency was improved through GUI software to enhance the completeness of the CanSat system. Specifically, software that can check terrain information and object detection information in real time at the ground station was produced, and mission failure was prevented through abnormal packet exception processing and system initialization functions. Communication through LTE and AWS server was used as the main channel, and ZigBee was used as the auxiliary channel. The completed CanSat was tested for air fall using a rocket launch method and a drone mount method. In experimental results, the terrain search and object detection performance was excellent, and all the results were processed in real-time and then successfully displayed on the ground station software.

• Therapeutic Science for Rehabilitation
• /
• v.11 no.3
• /
• pp.51-64
• /
• 2022

Objective : The purpose of this study is to establish the domain for assessment of feeding disorder with cerebral palsy. In addition, it is to develop item on feeding assessment for feeding disorder on children with cerebral palsy Methods : Factors to be included in the assessment of feeding disorders in children with cerebral palsy based on the ICF classification criteria constituted the assessment domain through literature review. Results : Assessment items of feeding disorders in children with cerebral palsy were categorized into 6 domains. These were systematized through expert advice, and through the first and second Delphi surveys, nine middle categories, 32 sub-categories, and 76 items were confirmed. Conclusions : The results of this study are useful for occupational therapists who want to check the current feeding function and activity level during therapeutic interventions for children with cerebral palsy who have feeding disorders.

• Journal of the Korea Computer Graphics Society
• /
• v.29 no.5
• /
• pp.11-20
• /
• 2023

In this paper, we propose a novel deep learning-based motion reconstruction approach that facilitates the generation of full-body motions, including finger motions, while also enabling the online adjustment of motion generation delays. The proposed method combines the Vive Tracker with a deep learning method to achieve more accurate motion reconstruction while effectively mitigating foot skating issues through the use of an Inverse Kinematics (IK) solver. The proposed method utilizes a trained AutoEncoder to reconstruct character body motions using tracker data in real-time while offering the flexibility to adjust motion generation delays as needed. To generate hand motions suitable for the reconstructed body motion, we employ a Fully Connected Network (FCN). By combining the reconstructed body motion from the AutoEncoder with the hand motions generated by the FCN, we can generate full-body motions of characters that include hand movements. In order to alleviate foot skating issues in motions generated by deep learning-based methods, we use an IK solver. By setting the trackers located near the character's feet as end-effectors for the IK solver, our method precisely controls and corrects the character's foot movements, thereby enhancing the overall accuracy of the generated motions. Through experiments, we validate the accuracy of motion generation in the proposed deep learning-based motion reconstruction scheme, as well as the ability to adjust latency based on user input. Additionally, we assess the correction performance by comparing motions with the IK solver applied to those without it, focusing particularly on how it addresses the foot skating issue in the generated full-body motions.

• Journal of the Institute of Convergence Signal Processing
• /
• v.24 no.4
• /
• pp.205-212
• /
• 2023

Among cardiac diseases, arrhythmias can lead to serious complications such as stroke, heart attack, and heart failure if left untreated, so continuous and accurate ECG monitoring is crucial for clinical care. However, the accurate interpretation of electrocardiogram (ECG) data is entirely dependent on medical doctors, which requires additional time and cost. Therefore, this paper proposes an arrhythmia recognition module for the purpose of developing a medical platform through the analysis of abnormal pulse waveforms based on Lifelogs. The proposed method is to convert ECG data into image format instead of time series data, apply visual pattern recognition technology, and then detect arrhythmia using CNN model. In order to validate the arrhythmia classification of the CNN model by image type conversion of ECG data proposed in this paper, the MIT-BIH arrhythmia dataset was used, and the result showed an accuracy of 97%.

• Radiation Oncology Journal
• /
• v.21 no.1
• /
• pp.100-106
• /
• 2003

Purpose : To develop a patients' setup verification tool (PSVT) to verify the alignment of the machine and the target isocenters, and the reproduclbility of patients' setup for three dimensional conformal radiotherapy (3DCRT) and intensity modulated radiotherapy (IMRT). The utilization of this system is evaluated through phantom and patient case studies. Materials and methods : We developed and clinically tested a new method for patients' setup verification, using digitally reconstructed radiography (DRR), simulation, porial and digital images. The PSVT system was networked to a Pentium PC for the transmission of the acquired images to the PC for analysis. To verify the alignment of the machine and target isocenters, orthogonal pairs of simulation images were used as verification images. Errors in the isocenter alignment were measured by comparing the verification images with DRR of CT Images. Orthogonal films were taken of all the patients once a week. These verification films were compared with the DRR were used for the treatment setup. By performing this procedure every treatment, using humanoid phantom and patient cases, the errors of localization can be analyzed, with adjustments made from the translation. The reproducibility of the patients' setup was verified using portal and digital images. Results : The PSVT system was developed to verify the alignment of the machine and the target isocenters, and the reproducibility of the patients' setup for 3DCRT and IMRT. The results show that the localization errors are 0.8$\pm$0.2 mm (AP) and 1.0$\pm$0.3 mm (Lateral) in the cases relating to the brain and 1.1$\pm$0.5 mm (AP) and 1.0$\pm$0.6 mm (Lateral) in the cases relating to the pelvis. The reproducibility of the patients' setup was verified by visualization, using real-time image acquisition, leading to the practical utilization of our software Conclusions : A PSVT system was developed for the verification of the alignment between machine and the target isocenters, and the reproduclbility of the patients' setup in 3DCRT and IMRT. With adjustment of the completed GUI-based algorithm, and a good quality DRR image, our software may be used for clinical applications.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.05a
• /
• pp.747-750
• /
• 2008

JPEG(Joint Photographic Expert Group)은 손실 압축 기법을 사용하여 데이터 양을 20:1 이상으로 현저히 줄이면서도 원 영상과 거의 유사한 영상을 복원할 수 있도록 해주기 때문에, 요즘 디지털 카메라 및 휴대폰 등 영상을 저장할 매 대부분 Exif(Exchangeable image file format)로 JPEG 압축형식을 널리 사용하고 있다. 본 논문은 JPEG 베이스라인 모드로 압축되어진 영상의 디코딩 단계에서 필요한 비계층형 헤더를 파싱하는 모듈의 기능을 소프트웨어로 모델링하고 VHDL을 이용하여 회로를 합성하고 동작을 검증하였다. 설계 결과 Xilinx xc3s1000 fg676-4 환경에서 154.488MHz의 동작속도를 나타내었고, JPEG 디코더의 고속 데이터 처리에 적응 가능하다.