• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1001-1004
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• 1993

The Multisensor Fusion Problem (MFP) deals with the methodologies involved in effectively combining together homogeneous or non-homegeneous information obtained from multiple redundant or disparate sensors in order to perform a task more accurately, efficiently, and reliably. The inherent uncertainties in the sensory information are represented using Fuzzy Numbers, -numbers, and the Uncertainty-Reductive Fusion Technique (URFT) is introduced to combine the multiple sensory information into one consensus -number. The MFP is formulated from the Information Theory perspective where sensors are viewed as information sources with a fixed output alphabet and systems are modeled as a network of information processing and processing and propagating channels. The performance of the URFT is compared with other fusion techniques in solving the 3-Sensor Problem.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.45-54
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• 2022

In this study, a multi-objective robust job-shop scheduling (JSS) model was developed. The model considered multi-jobs and multi-machines. The model also considered uncertain processing times for all tasks. Each job was assigned a specific due date and a tardiness penalty to be paid if the job was not delivered on time. If any job was completed early, holding expenses would be assigned. In addition, the model added idling penalties to accommodate the idling of machines while waiting for jobs. The problem assigned was to determine the optimal start times for each task that would minimize the expected penalties. A numerical problem was solved to minimize both the makespan and the total penalties, and a comparison was made between the results. Analysis of the results produced a prescription for optimizing penalties that is important to be accounted for in conjunction with uncertainties in the job-shop scheduling problem (JSSP).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.861-880
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• 2023

Semantic segmentation of road scene is the key technology of autonomous driving, and the improvement of convolutional neural network architecture promotes the improvement of model segmentation performance. The existing convolutional neural network has the simplification of learning knowledge and the complexity of the model. To address this issue, we proposed a road scene semantic segmentation algorithm based on multi-task collaborative learning. Firstly, a depthwise separable convolution atrous spatial pyramid pooling is proposed to reduce model complexity. Secondly, a collaborative learning framework is proposed involved with saliency detection, and the joint loss function is defined using homoscedastic uncertainty to meet the new learning model. Experiments are conducted on the road and nature scenes datasets. The proposed method achieves 70.94% and 64.90% mIoU on Cityscapes and PASCAL VOC 2012 datasets, respectively. Qualitatively, Compared to methods with excellent performance, the method proposed in this paper has significant advantages in the segmentation of fine targets and boundaries.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.115-122
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• 2011

Adaptive arrays suffer from severe performance degradation when there are errors in the steering vector. The DCRCB (doubly constrained robust Capon beamformer) overcomes such a problem, introducing a spherical uncertainty set of the steering vector together with a norm constraint. However, in the standard DCRCB, it is a difficult task to determine the bound for the uncertainty, the radius of the spherical set, such that a near best solution is obtained. A novel beamforming method is presented which has no difficulty of the uncertainty bound setting, employing a recursive search for the steering vector. Though the basic idea of recursive search has been known, the conventional recursive method needs to set a parameter for the termination of the search. The proposed method terminates it by using distances to the signal subspace, without the need for parameter setting. Simulation demonstrates that the proposed method has better performance than the conventional recursive method and than the non-recursive standard DCRCB, even the one with the optimum uncertainty bound.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.609-612
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• 2008

Since most of the industries have adopted automation system, the industrial disaster has been declined sharply. Also automation system has offered many benefits such as productivity and assured quality. However, the construction industry is still relying on man power and because of this there are many victims occurring due to the industrial disaster. Construction industry has to overcome uncertainty of incidents and changing natural surroundings to actualize automation. Therefore, the efficient working plan and intelligent decision making process are needed to run more developed techniques and automations. Specially to decline the rate of industrial accidents occurred in basic construction in earth work, the automation via excavator is necessary and also the development of planning process system is too. This research is to establish Task Planning System to prevent disaster which is used for planning automated earth work.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.8
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• pp.175-183
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• 1996

This paper presents three-dimensional robot task using the vision control method. A minimum of two cameras is required to place points on end dffectors of n degree-of-freedom manipulators relative to other bodies. This is accomplished using a sequential estimation scheme that permits placement of these points in each of the two-dimensional image planes of monitoring cameras. Estimation model is developed based on a model that generalizes known three-axis manipulator kinematics to accommodate unknown relative camera position and orientation, etc. This model uses six uncertainty-of-view parameters estimated by the iteration method.

• Asia pacific journal of information systems
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• v.4 no.2
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• pp.35-61
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• 1994

Accounting information system is the most important and formal subsystem of the total information system of an organization which produces and delivers financial information. An organization has its own contigent characteristics. It is the key to a successful development of accounting information system to select the development mode and information characteristics appropriate for the contigent characteristics. The main purpose of this study is to analyze the relationship between the contigent factors and the development mode of accounting information system. In addition, this study will examine the relationship between the contigent variables and the information characteristics of accounting information system. The research method adopted in this study is the survey. The results show that the environmental uncertainty, organization size, task diversity, task interrelatedness, and management commitment are positively related with the involvement and role of user in the system development process. The aggregate information regarding various departments tends to be produced by an organization under the uncertain environment. The information is reported periodically by a centralized organization. The aggregate information is preferred when tha task for implementation is diversified. The output information is more aggregate and provided more frequently when there exists a high interrelatioship between tasks. The output information is more external and reported more frequently in an organization with the high management commitment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.3
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• pp.8-17
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• 2024

There is a demand for introducing a challenging and innovative R&D system to develop new technologies to generate weapon system requirements. Despite the increasing trend in annual core technology development tasks, the infrastructure expansion, including personnel in research management institutions, is relatively insufficient. This situation continuously exposes difficulties in task planning, selection, execution, and management. Therefore, there is a pressing need for strategies to initiate timely research and development and enhance budget execution efficiency through the streamlining of task agreement schedules. In this study, we propose a strategic model utilizing a flexible workforce model, considering constraints and optimizing workload distribution through resource allocation to minimize bottlenecks for efficient task agreement schedules. Comparative analysis with the existing operational environment confirms that the proposed model can handle an average of 67 more core technology development tasks within the agreement period compared to the baseline. In addition, the risk management analysis, which considered the probabilistic uncertainty of the fluctuating number of core technology research and development projects, confirmed that up to 115 core technology development can be contracted within the year under risk avoidance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.27
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• pp.105-111
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• 1993

Human works shift its roll from physical condition to the system supervisory control task In this paper safety-presentation configuration is discussed instead of well-known fault-warning configuration. Of paticular interest was the personal factor which include the cognitive process. Through a performance between each person information processing(d') and decision process($\beta$) was pointed out to explain the sensitivity of personal cognitive process. Impact of uncertainty effect the supervisor having doubt situations. These facts are released by the use of flat fuzzy number of $\beta$ and its learning rate R.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.160-165
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• 1989

This paper deals with the robust controller design of robotic manipulator to track a desired trajectory in spite of the presence of unmodelled dynamics in cause of nonlinearity and parameter uncertainty. The approach followed in this paper is based on model reference adaptive control technique and convergence on hyperstability theory but it does away with assumption that process is characterized by a linear model remaining time invariant during adaptation process. A computer simulation has been performed to demonstrate the performance of the designed control system in task coordinates for stanford manipulator with payload and disturbances.