• Journal of the Korean Society of Safety
• /
• v.20 no.1 s.69
• /
• pp.126-132
• /
• 2005

The purpose of this study is to propose a method to evaluate task complexity using CIFs(Complexity Influencing Factors). We developed a method that CIFs can be used in the evaluation of task complexity using fuzzy linguistic approach. That is, a fuzzy linguistic multi-criteria method to assess task complexity in a specific task situation was proposed. The CIFs luting was assessed in linguistic terms, which are described by fuzzy numbers with triangular and trapezoidal membership function. A fuzzy weighted average algorithm, based on the extension principle, was employed to aggregate these fuzzy numbers. Finally, the method was validated by experimental approach. In the result, it was validated that TCIM(Tink Complexity Index Method) is an efficient method to evaluate task complexity because the correlation coefficient between task performance time and TCI(Task Complexity Index) was 0.699.

• Korean Journal of Applied Biomechanics
• /
• v.23 no.2
• /
• pp.169-177
• /
• 2013

The purpose of this study is to investigate the effect of aging and dual tasking to the postural control during quiet standing. It was hypothesized that the center of pressure (COP) dynamics would be differently affected by aging and characteristics of the task. Total 60 adults (35 young adults and 25 older adults) participated in this study. They conducted two different standing tasks (dual vs. Nondual) twice in a random order. Variability, complexity, coupling and symmetric index from the left, right and overall COPs were measured by various parameters in nonlinear, linear and frequency analyses methods. Results demonstrated that older adults had worse performance in postural control with decreased complexity in overall sway movement, and increased coupling between left and right limb COP movement, even though there was no significant difference in symmetric index. These tendencies are generally clearer in nonlinear measures at the dual task condition. Results implied that older adults had compensatory strategy in dual tasking which results in simple and combined postural movement patterns.

• Physical Therapy Rehabilitation Science
• /
• v.7 no.3
• /
• pp.109-113
• /
• 2018

Objective: The purpose of this study was to investigate the effects of fall experience and task complexity on gait performance in community-dwelling persons with chronic hemiparetic stroke. Design: Cross-sectional study. Methods: Thirty-three persons who had a history of stroke participated in this study. The participants included 18 persons (aged mean 54.0, mean score of 24.6 points on the Montreal Cognitive Assessment, MoCA) with fall experience (faller group) and 15 persons (aged mean 53.7, mean score of 24.7 points on the MoCA) without fall experience (non-faller group) in the previous six months. This study measured balance and gait performance at two different conditions (with/without 70% of water filled in a 200 cc cup). The participants were clinically assessed using the 10-meter walk test (10MWT), 6-minute walk test (6MWT), Berg Balance scale (BBS), Dynamic Gait Index (DGI), and Timed Up-and-Go (TUG) test. Results: After analyzation, persons in the faller group performed significantly better on the 10MWT, 6MWT, BBS, DGI, and the TUG test in the no-cup-carrying condition than those in the cup-carrying condition (p<0.05). The persons in the non-faller group also performed significantly better in all outcome measures with the no-cup-carrying condition than those in the cup-carrying condition (p<0.05). However, there was no interaction between fall experience and task complexity in the two groups. Conclusions: Our results showed that balance and gait performance depended on fall experience and task complexity but fall experience did not interact with task complexity. Clinicians should consider fall prevention and task complexity during therapeutic approaches in persons with hemiparetic stroke.

• Proceedings of the KSR Conference
• /
• 2007.05a
• /
• pp.1204-1208
• /
• 2007

In order to prevent railway accidents due to human errors which have been recognized to be the most important cause in the railway accidents, human errors should have been controlled based on systematical analysis of the human errors, and countermeasures should be derived to reduce human error probability. Among several factors inducing human errors, task load (or task complexity) is representative. In order to reduce the human error, a systematic analysis should be undertaken to evaluate task load. In this study, task load according to task types of railway worker who are a safety critical staff have been quantitatively analyzed based on NASA-TLX(Task Load Index).

• Steel and Composite Structures
• /
• v.24 no.4
• /
• pp.391-397
• /
• 2017

With the increasing application of explosive composite structure in many engineering fields, its interface bonding state detection is more and more significant to avoid catastrophic accidents. However, this task still faces challenges due to the complexity of the bonding interface. In this paper, the concept of nonlinear output frequency response functions (NOFRFs) is introduced to detect the bonding state of explosive composite structure. The NOFRFs can describe the nonlinear characteristics of nonlinear vibrating system. Because of the presence of the bonding interface, explosive composite structure itself is a nonlinear system; when bonding interface of the structure is damaged, its dynamic characteristics show enhanced nonlinear characteristic. Therefore, the NOFRFs-based detection index is proposed as indicator to detect the bonding state of explosive composite pipes. The experimental results verify the effectiveness of the detection approach.

• Nuclear Engineering and Technology
• /
• v.28 no.5
• /
• pp.431-439
• /
• 1996

In the process of simplifying the complex fate of the plant into a binary state, the information loss is inevitable. To minimize the information loss, the quantification of plant safety status has been formulated through the combination of the probability density function arising from the sensor measurement and the membership function representing the expectation of the state of the system. Therefore, in this context, the safety index is introduced in an attempt to quantify the plant status from the perspective of safety. The combination of probability density function and membership function is achieved through the integration of the fuzzy intersection of the two functions, and it often is not a simple task to integrate the fuzzy intersection due to the complexity that is the result of the fuzzy intersection. Therefore, a methodology based on the Algebra of Logic is used to express the fuzzy intersection and the fuzzy union of the arbitrary functions analytically. These exact analytical expressions are then numerically integrated by the application of Monte Carlo method. The benchmark tests for rectangular area and both fuzzy intersection and union of two normal distribution functions have been performed. Lastly, the safety index was determined for the Core Reactivity Control of Yonggwang 3&4 using the presented methodology.

• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.8
• /
• pp.527-534
• /
• 2013

The software is changed according to the changing businesses and the user requirement, it involves increasing complexity and cost. Considering the repetitive changes required for the software, replacement is more efficient than maintenance at some point. In this study, the replacement time was predicted using the service dissatisfaction index and replacement point assessment index by the software group for each task. First, fuzzy inference was used to develop the method and indicator for the user's service level dissatisfaction. Second, the replacement point assessment method was established considering the quality, costs, and new technology of the software. Third, a replacement time prediction technique that used the gap between the user service measurement and replacement point assessment values was proposed. The results of the case study with the business solutions of three organizations, which was conducted to verify the validity of the proposed prediction technique in this study, showed that the service dissatisfaction index decreased by approximately 16% and the replacement point assessment index increased by approximately 9%.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.7
• /
• pp.3714-3732
• /
• 2019

With the rapid development of network, Intrusion Detection System(IDS) plays a more and more important role in network applications. Many data mining algorithms are used to build IDS. However, due to the advent of big data era, massive data are generated. When dealing with large-scale data sets, most data mining algorithms suffer from a high computational burden which makes IDS much less efficient. To build an efficient IDS over big data, we propose a classification algorithm based on data clustering and data reduction. In the training stage, the training data are divided into clusters with similar size by Mini Batch K-Means algorithm, meanwhile, the center of each cluster is used as its index. Then, we select representative instances for each cluster to perform the task of data reduction and use the clusters that consist of representative instances to build a K-Nearest Neighbor(KNN) detection model. In the detection stage, we sort clusters according to the distances between the test sample and cluster indexes, and obtain k nearest clusters where we find k nearest neighbors. Experimental results show that searching neighbors by cluster indexes reduces the computational complexity significantly, and classification with reduced data of representative instances not only improves the efficiency, but also maintains high accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.11
• /
• pp.5229-5252
• /
• 2016

With proliferation of diverse network access technologies, users demands are also increasing and service providers are offering a Quality of Service (QoS) to satisfy their customers. In roaming, a mobile node (MN) traverses number of available networks in the heterogeneous wireless networks environment and a single operator is not capable to fulfill the demands of user. It is crucial task for MN for selecting a best network from the list of networks at any time anywhere. A MN undergoes a network selection situation frequently when it is becoming away from the home network. Multiple Attribute Group Decision (MAGD) method will be one of the best ways for selecting target network in heterogeneous wireless networks (4G). MAGD network selection process is predominantly dependent on two steps, i.e., attribute weight, decision maker's (DM's) weight and aggregation of opinion of DMs. This paper proposes Multi-Attribute Intuitionistic Fuzzy Group Decision Method (MAIFGDM) using TOPSIS for the selection of the suitable candidate network. It is scalable and is able to handle any number of networks with large set of attributes. This is a method of lower complexity and is useful for real time applications. It gives more accurate result because it uses Intuitionistic Fuzzy Sets (IFS) with an additional parameter intuitionistic fuzzy index or hesitant degree. MAIFGDM is simulated in MATLAB for its evaluation. A comparative study of MAIFDGM is also made with TOPSIS and Fuzzy-TOPSIS in respect to decision delay. It is observed that MAIFDGM have low values of decision time in comparison to TOPSIS and Fuzzy-TOPSIS methods.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.1
• /
• pp.81-90
• /
• 2000

Parallel manipulator is suitable for the high precise task because it than has higher stiffness, larger load capacity and more excellent precision, due to the closed-lop structure, than serial manipulator. But the controller design for parallel manipulator is difficult because the parallel manipulator has both the complexity of structure and the interference of actuators. The precision improvement of parallel manipulator using a classical linear control scheme is difficult because the parallel manipulator has the tough nonlinear characteristics. In this paper, firstly, the kinematic analysis of a parallel manipulator used at the experiments is performed so as to show the controllability. The analysis of internal singular configuration of the workspace is performed using the kinematic isotropic index so a sto show the limitation of control performance of a simple linear controller with fixed control gains. Secondly, a control scheme is designed by using an adaptive fuzzy logic controller so that active joints of the parallel manipulator track more precisely the desired input trajectory. This adaptive fuzzy logic controller so that active joints of the parallel manipulator track more precisely the desired input trajectory. This adaptive fuzzy logic controller is often used for the control of nonlinear system because it has both the inference ability and the learning ability. Lastly, the effeciency of designed control scheme is demonstrated by the real-time control experiments with IBM PC interface logic H/W and S/W of my won making. The experimental results was a success.