• 대한수학교육학회지:학교수학
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• 제18권4호
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• pp.749-771
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• 2016

이 논문에서는 우리나라와 미국 수학 교과서에서 다루고 있는 평행사변형이 되기 위한 조건 관련 과제를 과제의 구조, 증명과 추론 유형, 그리고 인지적 노력 수준에 따라 비교 분석하였다. 이를 통해 두 나라 교과서 과제의 공통점과 차이점을 분석하였다. 그 결과는 다음과 같다. 첫째, 과제 구조와 관련하여, 우리나라 교과서에 비해 미국 교과서에 제시된 과제의 구조가 더 다양하다. 둘째, 증명과 추론 유형과 관련하여, 우리나라와 미국 교과서 모두 IC 과제와 DA 과제의 구성 비율이 높으며, 우리나라 교과서에 비해 미국 교과서에 제시된 과제의 유형이 더 다양하다. 셋째, 과제의 인지적 노력 수준과 관련하여, 우리나라와 미국 교과서 모두 PNC 과제와 PWC 과제가 대부분을 차지하며, 우리나라의 경우 미국에 비해 구체적인 알고리즘적 절차를 이용하는 수학 과제를 제시하는 비율이 높다. 차이점을 토대로 우리나라 교과서 재구성에 필요한 다음과 같은 시사점을 얻을 수 있었다. 첫째, 과제의 구조 및 증명과 추론 유형과 관련하여, 구성의 다양성을 높여야 한다. 둘째, 과제의 인지적 노력 수준과 관련하여, PNC 과제에 대한 편중현상을 완화해야 하며, 과제 유형별 인지적 노력 수준에 대한 재고가 필요하다. 셋째, 과제의 주제 또는 소재와 관련하여, 수학 내적, 외적인 상황과의 연결성이 강화된 과제를 도입할 수 있는 방안의 재고가 필요하다.

• Design & Manufacturing
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• 제16권3호
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• pp.1-8
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• 2022

In this study, an artificial neural network(ANN) was constructed to establish the relationship between process condition prameters and the qualities of the injection-molded product in the injection molding process. Six process parmeters were set as input parameter for ANN: melt temperature, mold temperature, injection speed, packing pressure, packing time, and cooling time. As output parameters, the mass, nominal diameter, and height of the injection-molded product were set. Two learning structures were applied to the ANN. The single-task learning, in which all output parameters are learned in correlation with each other, and the multi-task learning structure in which each output parameters is individually learned according to the characteristics, were constructed. As a result of constructing an artificial neural network with two learning structures and evaluating the prediction performance, it was confirmed that the predicted value of the ANN to which the multi-task learning structure was applied had a low RMSE compared with the single-task learning structure. In addition, when comparing the quality specifications of injection molded products with the prediction values of the ANN, it was confirmed that the ANN of the multi-task learning structure satisfies the quality specifications for all of the mass, diameter, and height.

• Imaging Science in Dentistry
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• 제46권4호
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• pp.245-249
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• 2016

Purpose: This study was designed to evaluate differences in the required visibility of anatomic structures according to the diagnostic tasks of implant planning and periapical diagnosis. Materials and Methods: Images of a real skull phantom were acquired under 24 combinations of different exposure conditions in a cone-beam computed tomography scanner (60, 70, 80, 90, 100, and 110 kV and 4, 6, 8, and 10 mA). Five radiologists evaluated the visibility of anatomic structures and the image quality for diagnostic tasks using a 6-point scale. results: The visibility of the periodontal ligament space showed the closest association with the ability to use an image for periapical diagnosis in both jaws. The visibility of the sinus floor and canal wall showed the closest association with the ability to use an image for implant planning. Variations in tube voltage were associated with significant differences in image quality for all diagnostic tasks. However, tube current did not show significant associations with the ability to use an image for implant planning. conclusion: The required visibility of anatomic structures varied depending on the diagnostic task. Tube voltage was a more important exposure parameter for image quality than tube current. Different settings should be used for optimization and image quality evaluation depending on the diagnostic task.

• Wind and Structures
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• 제14권6호
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• pp.517-536
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• 2011

The assessment of wind-induced motion plays an important role in the development and design of the majority of today's structures that push the limits of engineering knowledge. A vital part of the design is the prediction of wind-induced tall building motion and the assessment of its effects on occupant comfort. Little of the research that has led to the development of the various international standards for occupant comfort criteria have considered the effects of the low-frequency motion on task performance and interference with building occupants' daily activities. It has only recently become more widely recognized that it is no longer reasonable to assume that the level of motion that a tall building undergoes in a windstorm will fall below an occupants' level of perception and little is known about how this motion perception could also impact on task performance. Experimental research was conducted to evaluate the performance of individuals engaged in a manual tracking task while subjected to low level vibration in the frequency range of 0.125 Hz-0.50 Hz. The investigations were carried out under narrow-band random vibration with accelerations ranging from 2 milli-g to 30 milli-g (where 1 milli-g = 0.0098 $m/s^2$) and included a control condition. The frequencies and accelerations simulated are representative of the level of motion expected to occur in a tall building (heights in the range of 100 m -350 m) once every few months to once every few years. Performance of the test subjects with and without vibration was determined for 15 separate test conditions and evaluated in terms of time taken to complete a task and accuracy per trial. Overall, the performance under the vibration conditions did not vary significantly from that of the control condition, nor was there a statistically significant degradation or improvement trend in performance ability as a function of increasing frequency or acceleration.

• 한국IT서비스학회지
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• 제12권1호
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• pp.309-321
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• 2013

In current complex nature of management with task-structures, a method to reach the enterprise's informationalization success is not common. To satisfy these various requirement, improving the usability of information technology (IT) is a key factor which defining the level of organizational requirement first. Imposing an IT-solution which has excess service of the organization's previous task-environment, procedure and scope is not effective to SME-level unit, which unit could not have a formal organization structure and task structure. SME level informationalization will be success if each function realizes easier on the task-employee's viewpoint. Achieving this objective, a solution provider or department must reflect their work characteristics of nature which has least level of work performing resistance. It is most useful system for SME level unit, if a provider develops single programs which based on task activities, and each program can configure network-linking.

• 정보화정책
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• 제23권3호
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• pp.84-116
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• 2016

본 연구는 지방정부 정보화 조직의 경쟁력 강화를 위해 업무, 구조, 관계적 역량을 진단하고 조직발전 모델을 제시하는 것을 목적으로 한다. 연구 대상은 한국 17개 광역자치단체의 정보화 부서이며, 조직 변화에 대한 통시적 관찰, 조직 간 비교, 심층 인터뷰 등 다각적 방법으로 지방정부 정보화 조직의 현실적 문제를 담아내고자 하였다. 분석결과, 첫째, 업무 측면의 경우, 새로운 정보통신기술의 도입, 업무 구분 및 조정, 창의적 정책 탐색에서 문제를 보였다. 둘째, 구조 측면에서는 부서 위치 및 명칭, 인력, 공식적 권한, 조직문화 등 공식적 비공식적 원인에 의해 조직 위상이 저하되어 있다. 셋째, 관계측면에서는 전담부서-현업부서 간, 정부 간, 정부-민간 간 관계에서의 주도적인 역할 변화가 필요한 것으로 진단되었다. 이와 같은 조직문제를 개선하기 위해 본 연구는 지방정부와 조직이 처한 상황에 따라 적용할 수 있는 'Relation Model, Resource Model, Curation Model, Creation Model'을 구상하고 이의 실현을 위한 업무, 구조, 관계 역량 강화 전략을 제시하였다.

• Smart Structures and Systems
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• 제31권4호
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• pp.383-392
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• 2023

Post-earthquake building condition assessment is crucial for subsequent rescue and remediation and can be automated by emerging computer vision and deep learning technologies. This study is based on an endeavour for the 2nd International Competition of Structural Health Monitoring (IC-SHM 2021). The task package includes five image segmentation objectives - defects (crack/spall/rebar exposure), structural component, and damage state. The structural component and damage state tasks are identified as the priority that can form actionable decisions. A multi-task Convolutional Neural Network (CNN) is proposed to conduct the two major tasks simultaneously. The rest 3 sub-tasks (spall/crack/rebar exposure) were incorporated as auxiliary tasks. By synchronously learning defect information (spall/crack/rebar exposure), the multi-task CNN model outperforms the counterpart single-task models in recognizing structural components and estimating damage states. Particularly, the pixel-level damage state estimation witnesses a mIoU (mean intersection over union) improvement from 0.5855 to 0.6374. For the defect detection tasks, rebar exposure is omitted due to the extremely biased sample distribution. The segmentations of crack and spall are automated by single-task U-Net but with extra efforts to resample the provided data. The segmentation of small objects (spall and crack) benefits from the resampling method, with a substantial IoU increment of nearly 10%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권11호
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• pp.3638-3657
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• 2022

In urban vehicular edge computing (VEC) environments, one edge server always serves many task requests in its coverage which results in the resource-constrained problem. To resolve the problem and improve system utilization, we first design a general hierarchical resource management framework based on typical VEC network structures. Following the framework, a specific interacting protocol is also designed for our decision algorithm. Secondly, a greedy bidding-based multi-hop task scheduling decision algorithm is proposed to realize effective task scheduling in resource-constrained VEC environments. In this algorithm, the goal of maximizing system utility is modeled as an optimization problem with the constraints of task deadlines and available computing resources. Then, an auction mechanism named greedy bidding is used to match task requests to edge servers in the case of multiple hops to maximize the system utility. Simulation results show that our proposal can maximize the number of tasks served in resource constrained VEC networks and improve the system utility.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권3호
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• pp.353-360
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• 2004

In this paper we describe Task-Based Problem Solving Adapters (TPSAs) for modeling a humam solution (through activity-centered analysis) to a software solution (in form of computer-based artifact). TPSAs are derived from the problem solving pattern or consistent problem solving structures/strategies employed by practitioners while designing solutions to complex problems. The adapters developed by us lead toward human-centeredness in their design and underpinning that help us to address the pragmatic task constraints through a range of technologies like neural networks, fuzzy logic, and genetic algorithms. We also outline an example of applying the TPSAs to develop a working system for assisting sales engineers of an electrical manufacturing firm in preparing indent and monitoring the status of orders in the company.

• Structural Monitoring and Maintenance
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• 제2권3호
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• pp.181-197
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• 2015

Assessing the condition of paint on civil structures is an important but challenging and costly task, in particular when it comes to large and complex structures. Current practices of visual inspection are labour-intensive and time-consuming to perform. In addition, this task usually relies on the experience and subjective judgment of individual inspectors. In this study, hyperspectral imaging and classification techniques are proposed as a method to objectively assess the state of the paint on a civil or other structure. The ultimate objective of the work is to develop a technology that can provide precise and automatic grading of paint condition and assessment of degradation due to age or environmental factors. Towards this goal, we acquired hyperspectral images of steel surfaces located at long (mid-range) and short distances on the Sydney Harbour Bridge with an Acousto-Optics Tunable filter (AOTF) hyperspectral camera (consisting of 21 bands in the visible spectrum). We trained a multi-class Support Vector Machines (SVM) classifier to automatically assess the grading of the paint from hyperspectral signatures. Our results demonstrate that the classifier generates highly accurate assessment of the paint condition in comparison to the judgement of human experts.