• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.283-291
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• 2021

In this paper, we propose the development and application of a software education program for underachievers. The software education program for underachieving students was developed in consideration of the characteristics of learner's suffering from underachievement and the educational effects of software education, and is meaningful in that it proposes a plan to improve the learning gap in distance learning. Learners can acquire digital literacy and learning skills by solving structured tasks in the form of courseware, intelligent tutoring, debugging, and artificial intelligence learning models in educational programs. Based on the effects of software education, such as enhancing logical thinking ability and problem solving ability, this program provides opportunities to solve fusion tasks to underachievers. Based on this, it is expected that it can have a positive effect on the overall academic work.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1387-1391
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• 2017

Cutting power estimation can be used to select appropriate actuators in the design process of machine tools. Therefore, accurate estimation of cutting power is an important part of the design process. In this study, pipe cutting power is first calculated theoretically using the slotting cutting power equation and then verified experimentally. In this case, a pipe cutting machine is used to cut two pipes made of different materials. Power consumptions in the motor during pipe cutting are measured by using the embedded software, Labview, and NI hardware. The slotting cutting power equation can thus be confirmed easily comparing theoretically calculated cutting powers with experimentally measured cutting powers. The pipe materials used in this study are SUS304 and AL6N01. The specific cutting power of AL6N01 material is proposed through our cutting experiment. As a result, this cutting power can be used to design machining tools for AL6N01 material.

• 한국IT서비스학회:학술대회논문집
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• 2008.11a
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• pp.486-489
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• 2008

재난방재시스템은 재난에 대하여 예방, 대비, 대응, 복구 단계별 활동을 지원하기 위한 정보시스템이다. 재난방재시스템은 여러 형태의 재난에 대하여 여러 수준의 다양한 정보자원을 이용해야 하고 여러 임무를 맡고 있는 다양한 인적자원과 다양한 물적 자원을 활용하여 준비하고 빠르게 대응해야 한다. 기존의 재난방재시스템은 통합적인 상황분석이 부족하고, 지역재난상황에 따라 표준행동에 의한 자동적 실시간 임무부여와 실시간 보고의 처리, 재난관리자의 경험적 지식을 활용될 수 있는 정보시스템화는 미흡한 실정이다. 본 연구에서는 주로 국방, 경찰, 보안 분야에 적용되어온 정보융합(Information fusion)기술과 비즈니스 룰(BRMS)의 규칙기반 지능형 기술을 활용하여 여러 수준의 다양한 정보를 종합 분석하여 통합적인 상황정보를 제공하고, 표준행동 요령과 지역 재난관리자의 지식을 활용하여 인적자원과 물적 자원에 대한 대응계획을 제시하여 대응조치를 선택할 수 있도록 하며, 현장 상황에 따른 실시간 임무 부여와 상황 보고를 처리할 수 있는 정보융합기반 지능형 재난방재 프레임워크를 제안한다. 본 연구의 프레임워크는 지역단위 재난방재에 적용을 고려하고 있으며 오픈소스 소프트웨어를 같이 활용하는 프로토타입 구현을 계획하고 있다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.79-84
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• 2023

Apache Spark, which provides the fastest processing speed among recent distributed and parallel processing technologies, provides real-time functions and machine learning functions. Although official documentation guides for these functions are provided, a method for fusion of functions to predict a specific value in real time is not provided. Therefore, in this paper, we conducted a study to predict the value of data in real time by fusion of these functions. The overall configuration is collected by downloading stock price data provided by the Python programming language. And it creates a model of regression analysis through the machine learning function, and predicts the adjusted closing price among the stock price data in real time by fusing the real-time streaming function with the machine learning function.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.9
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• pp.409-418
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• 2015

In order to delivery of the correct information in IoT environment, it is important to deduce collected information according to a user's situation and to create a new information. In this paper, we propose a control access scheme of information through context-aware to protect sensitive information in IoT environment. It focuses on the access rights management to grant access in consideration of the user's situation, and constrains(access control policy) the access of the data stored in network of unauthorized users. To this end, after analysis of the existing research 'CP-ABE-based on context information access control scheme', then include dynamic conditions in the range of status information, finally we propose a access control policy reflecting the extended multi-dimensional context attribute. Proposed in this paper, access control policy considering the dynamic conditions is designed to suit for IoT sensor fusion environment. Therefore, comparing the existing studies, there are advantages it make a possible to ensure the variety and accuracy of data, and to extend the existing context properties.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.929-938
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• 2004

This paper proposes a pose-invariant face recognition method using cylindrical model and stereo camera. We divided this paper into two parts. One is single input image case, the other is stereo input image case. In single input image case, we normalized a face's yaw pose using cylindrical model, and in stereo input image case, we normalized a face's pitch pose using cylindrical model with previously estimated pitch pose angle by the stereo geometry. Also, since we have an advantage that we can utilize two images acquired at the same time, we can increase overall recognition performance by decision-level fusion. Through representative experiments, we achieved an increased recognition rate from 61.43% to 94.76% by the yaw pose transform, and the recognition rate with the proposed method achieves as good as that of the more complicated 3D face model. Also, by using stereo camera system we achieved an increased recognition rate 5.24% more for the case of upper face pose, and 3.34% more by decision-level fusion.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.505-518
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• 2023

3D point cloud semantic segmentation is a computer vision task that involves dividing the point cloud into different objects and regions by predicting the class label of each point. Existing 3D semantic segmentation models have some limitations in performing sufficient fusion of multi-modal features while ensuring both characteristics of 2D visual features extracted from RGB images and 3D geometric features extracted from point cloud. Therefore, in this paper, we propose MMCA-Net, a novel 3D semantic segmentation model using 2D-3D multi-modal features. The proposed model effectively fuses two heterogeneous 2D visual features and 3D geometric features by using an intermediate fusion strategy and a multi-modal cross attention-based fusion operation. Also, the proposed model extracts context-rich 3D geometric features from input point cloud consisting of irregularly distributed points by adopting PTv2 as 3D geometric encoder. In this paper, we conducted both quantitative and qualitative experiments with the benchmark dataset, ScanNetv2 in order to analyze the performance of the proposed model. In terms of the metric mIoU, the proposed model showed a 9.2% performance improvement over the PTv2 model using only 3D geometric features, and a 12.12% performance improvement over the MVPNet model using 2D-3D multi-modal features. As a result, we proved the effectiveness and usefulness of the proposed model.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.5
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• pp.967-972
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• 2020

Most of the experimental tools currently used are applied to experiments in the physical field by utilizing sensors and only MBL that are suitable for specific experiments have been developed. However, There is no experimental design stage using SW fusion, and there is a limit to the application of various chemistry experiments in textbooks, and in the case of Arduino, it is difficult for students to learn and understand language when programming. In this paper, we designed and developed a SW education convergence science experiment apparatus including a learner's active experiment design process, overcoming the shortcomings of the existing microcomputer experiment and the limitations of software education.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.6
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• pp.513-518
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• 2009

Purpose: Integration of the functional information of myocardial perfusion SPECT (MPS) and the morphoanatomical information of coronary CT angiography (CTA) may provide useful additional diagnostic information of the spatial relationship between perfusion defects and coronary stenosis. We studied to know the added value of three dimensional cardiac SPECT/CTA fusion imaging (fusion image) by comparing between fusion image and MPS. Materials and Methods: Forty-eight patients (M:F=26:22, Age: $63.3{\pm}10.4$ years) with a reversible perfusion defect on MPS (adenosine stress/rest SPECT with Tc-99m sestamibi or tetrofosmin) and CTA were included. Fusion images were molded and compared with the findings from the MPS. Invasive coronary angiography served as a reference standard for fusion image and MPS. Results: Total 144 coronary arteries in 48 patients were analyzed; Fusion image yielded the sensitivity, specificity, negative and positive predictive value for the detection of hemodynamically significant stenosis per coronary artery 82.5%, 79.3%, 76.7% and 84.6%, respectively. Respective values for the MPS were 68.8%, 70.7%, 62.1% and 76.4%. And fusion image also could detect more multi-vessel disease. Conclusion: Fused three dimensional volume-rendered SPECT/CTA imaging provides intuitive convincing information about hemodynamic relevant lesion and could improved diagnostic accuracy.

• Journal of the korean Society of Automotive Engineers
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• v.18 no.6
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• pp.63-68
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• 1996

차량의 자동제어는 컴퓨터, 통신, 기계, 계측등의 하드웨어와 자동제어 기술, 통신망 운영, 컴퓨터 운영등의 소프트웨어 기술의 응용을 바탕으로 하는 지능형 차량은 단순히 차량 상호간, 차량과 도로에 설치된 컴퓨터와의 통신으 통한 정보교환 기능과 더불어 운전기능 자체를 스스로 행하는 기능을 포함하고 있다. 지능형 차량 개발은 운전자 인식증진 기술, 사고회피 기술, 피해확산 방지기술, ITS(Intelligent Transport System) 연계 및 관련 Infrastructure 기술, Human-Machine Interface 기술, Sensor Fusion 기술, 레이더 기술 등을 꼽을 수 있다. 이중에서 차량의 지능화를 구현하는 가장 핵심적인 세부 기술은 CCD 카메라, 레이저 레이더, 밀리파 레이더, 생체 센서등을 들 수 있다. 본 원고에서는 위와 같이 차량의 지능화, 특히 차량 거리검지 장치를 구현코자 사용되고 있는 센서의 종류와 응용에 대하여 고찰하고자 한다.