• Journal of the Ergonomics Society of Korea
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• v.25 no.1
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• pp.43-49
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• 2006

A laboratory study was conducted to evaluate if two different age groups(young vs. old) had differences in walking velocity and heel contact velocity and, furthermore, if these gait characteristics could adversely influence initial friction demand characteristics(i.e. RCOF) and the likelihood of slip-initiation. Twenty eight(14 younger and 14 older adults) participated in the study. While wearing a safety harness, all participants walked at their preferred gait speed for approximately 20 minutes on the linear walking track(1.5m× 20m) consisting of two floor-mounted forced plates. During subsequent 20 cameras, respectively. The results indicated that older adults walked slower(i.e., slower whole body center-of-mass velocity), exhibited lower heel contact velocity, and produced lower initial friction demand characteristics (i.e. RCOF) in comparison to younger adults. However, ANCOVA indicated that the diferences in heel contact velocity between the two age groups were due to the effects of walking velocity. The bivariate analysis further suggested that walking velocity was correlated to RCOF and heel contact velocity, while heel contact velocity was not found to be correlated to RCOF. In conclusion, could be a better indicator for predicting initial friction demand characteristics(i.e. RCOF) not hel contact velocity.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.789-795
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• 2014

In a demand response (DR) market run by independent system operators (ISOs), load aggregators are important market participants who aggregate small retail customers through various DR programs. A load aggregator can minimize the allocation cost by efficiently allocating its demand response resources (DRRs) considering retail customers' characteristics. However, the uncertain response behaviors of retail customers can influence the allocation strategy of its DRRs, increasing the economic risk of DRR allocation. This paper presents a risk-based DRR allocation method for the load aggregator that takes into account not only the physical characteristics of retail customers but also the risk due to the associated response uncertainties. In the paper, a conditional value-at-risk (CVaR) is applied to deal with the risk due to response uncertainties. Numerical results are presented to illustrate the effectiveness of the proposed method.

• Korean Journal of Human Ecology
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• v.24 no.4
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• pp.587-601
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• 2015

The purposes of this study were to segment outdoor wear market based on consumer knowledge and consumer demand for function/design development, and to examine the differences of demographic characteristics and purchase behavior among the segmented markets. Data were collected using a questionnaire survey. Respondents were adults aged over 20 and who have experiences of purchasing outdoor wear. The survey was made up of the questions on consumer knowledge to outdoor wear, consumer demand for product development, purchase behavior, and demographic characteristics. Frequency analysis, descriptive analysis and chi-squared test were used to conduct the data analysis on 454 questionnaires. The results of this study were as follows. It showed that the consumer knowledge was a little high and the consumer demands for function/design development were high. Six segmented markets based on consumer knowledge and consumer demand for function development were significantly different in terms of gender, income, purchase frequency and total item holdings. Also, six segmented markets based on consumer knowledge and consumer demand for design development were significantly different in terms of age, income, purchase frequency, purchase objective, purchase place and total item holdings. Compared to the segmented markets based on the consumer demands for product development, the gender was the key of the marketing strategies for the segmented markets by the consumer demand for function development while the age was the one in the markets by the consumer demand for design development. After considering all the results, the characteristics of the segmented markets were made out and the marketing strategies were established.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.3
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• pp.35-46
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• 2013

In order to develop an accurate analytical model for domestic electricity demand forecasting, we propose a prediction method of the electric power demand pattern by combining SMO classification techniques and a dimension reduction conceptualized subspace clustering techniques suitable for high-dimensional data cluster analysis. In terms of electricity demand pattern prediction, hourly electricity load patterns and the demographic and geographic characteristics can be analyzed by integrating the wireless load monitoring data as well as sub-regional unit of census information. There are composed of a total of 18 characteristics clusters in the prediction result for the sub-regional demand pattern by using census information and power load of Seoul metropolitan area. The power demand pattern prediction accuracy was approximately 85%.

• Transactions of the Korean hydrogen and new energy society
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• v.33 no.5
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• pp.591-597
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• 2022

Recently, technologies for efficient power grid operation have become important due to climate change. For this reason, predicting power demand using deep learning is being considered, and it is necessary to understand the influence of characteristics of each region, industrial structure, and climate. This study analyzed the power demand of New Jersey in US, with a high urbanization rate and a large service industry, and West Virginia in US, a low urbanization rate and a large coal, energy, and chemical industries. Using recurrent neural network algorithm, the power demand from January 2020 to August 2022 was learned, and the daily and weekly power demand was predicted. In addition, the power grid operation based on the power demand forecast was discussed. Unlike previous studies that have focused on the deep learning algorithm itself, this study analyzes the regional power demand characteristics and deep learning algorithm application, and power grid operation strategy.

• Journal of Technologic Dentistry
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• v.28 no.1
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• pp.177-198
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• 2006

This study purposed to offer basic data for safety education of the dental laboratory technology after the investigation of how much the students in the dept. of dental laboratory technology are aware of the danger of each instrument, equipment or laboratory procedure that they use during laboratory and how much they demand safety education for this. The objects for this study were 423 students who were in the dept. of dental laboratory technology. In this regard, four colleges which have the dept. of dental laboratory technology were randomly selected to do a questionnaire survey. SPSS 12.0 was used to analyze the collected data. The results were as follows: As for satisfaction with their major, the respondents answered Satisfied (59.1%), Average (35.5%) and Dissatisfied (5.4%). In terms of the production process of a partial denture, they considered casting, polishing the casting body, polishing denture and burn out were most dangerous in order. As for the production process of a full denture, what they regarded as the most dangerous in order was polishing denture, deflasking and wax wash. Regarding the laboratory procedures of porcelain material, casting, trimming casting body, polishing porcelain material and burn out were the most dangerous procedures that they perceived. With regard to materials for use, alcohol, polishing, metal and wire were the most dangerous ones they thought. As for the handling characteristics of each material, small towns showed a higher demand for safety of the handling characteristics of alcohol. In terms of school year and sex, juniors and girls had higher scores in the demand for safety of the handling characteristics of acid. Regarding the handling characteristics of each equipment and instrument, all of small towns, juniors and girls showed the highest demand for safety of the handling characteristics of alcohol lamps. With regard to scores in the demand for safety of other characteristics, all of small towns, juniors and girls had the highest demand for safety of emergency treatment. Concerning the demand for safety education by the completion of safety education, in terms of each material, highest was the demand for safety of acid from the group which completed safety education. In regard to equipments and instruments, when it came to the demand for safety of the handling characteristics of casting machine, the educated group's demand for safety of acid was higher. Regarding other characteristics, the group which was not educated gained higher scores in the demand for safety of emergency treatment. 11. In all areas(materials, machines and others), small towns, girls and juniors showed higher scores in the demand for safety. Based on the above results, it was found that when students conduct the laboratory of dental technology, they would think that many materials, instruments or equipments for use are very dangerous. However, safety education was not fully given to them. Regarding the scores in the damned for safety education, the highest was 4.16 and the lowest was 3.43, which suggests that the scores were generally very high. In this regard, it is necessary to continue delivering a systematic safety education of materials, equipments or instruments used during the laboratory of dental technology. Therefore, through the analysis of each material, instruments or facility used in every laboratory and each process, safety accident types and accident risk factors should be investigated to develop educational materials for this. Moreover, it is required to open safety education as a single course of study or insert safety contents of all materials and machines into the class of dental laboratory instrument or dental materials for the purpose of a systematic and thorough safety education to prevent a safety accident during laboratory.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.15-19
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• 2001

This paper describes effectiveness and characteristics of 3 P(point) task analysis as a new Ergonomic and Kansei design method for extracting user demand especially. The key point in 3 P task analysis is to describe the flow of tasks and extract any problems in each task. A solution of a problem means a user demand. 3 P task analysis cal eliminate an oversight of check items by examining the users' information processing level. The suers' information processing level was divided into the following three stages for problem extraction: acquirement of information ---> understanding and judgment ---> operation. Three stages has fourteenth cues such as difficulty of seeing, no emphasis, mapping for extracting problems. To link analysis results to the formulation of a product concept. I added a column on the right side of the table for writing the requirements (user demand) to resolve the problems extracted from each task. The requirements are extracted by using seventh cues. Finally 3 P task analysis was compared with group interview to make the characteristics of 3 P task analysis, especially extracting user demand, clear.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.2
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• pp.403-420
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• 1997

In this paper, we examine the effect of production uncertainty to production control policies. First, we examine two famous production control policies, namely, MRP and JIT from the view point of shop floor control perspective, and analyze the differences between them due to demand fluctuations and activity time variations. Second, we conduct simulation studies on MRP and JIT to draw out the effects of demand fluctuations and activity time variations. Demand fluctuations are further classified into demand lumpiness and demand irregularity. And, activity time variations are further classified into stationary time variations and non-stationary time variations. Experimental results show that, in terms of demand fluctuations, MRP is affected by demand lumpiness, but JIT by demand irregularity. And we also see that both MRP and JIT are influenced by stationary time variation with respect to activity time variations.

• Journal of Korean Society of Rural Planning
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• v.15 no.2
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• pp.97-110
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• 2009

The objective of this research was to develop a rural settlement demand model to analyze the determinants of settlement demand of urban residents. The point aimed at from model development was deriving stated preference of potential consumers towards rural settlement through setting a hypothetical market, and using settlement subsidy as a surrogate variable for price in the demand model. The adequate demand model deducted from hypothetical market data was derived from the basis of Hanemann's utility difference theory. In the rural settlement demand model, willingness to accept was expressed by a function of settlement subsidy. Data utilized in the analysis was collected from surveys of households nationwide. According to inferred results of the demand model, settlement subsidy had a significant influence on increasing demand for rural settlement. A significant common element was found among variables affecting demand increase through demand curve shift. The majority group of those with high rural settlement demand sought agricultural activity as their main motive, due to harsh urban environments aggravated by unstable job market conditions. Subsequently, restriction of income opportunities in rural areas does not produce an entrance barrier for potential rural settlers. Moreover, this argument could be supported by the common trend of those with high rural settlement demand generally tending to have low incomes. Due to such characteristics of concerned groups of rural settlement demand, they tended to react susceptibly to the subsidy provided by the government and local autonomous entities.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.8
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• pp.418-428
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• 2005

In this paper, a new probabilistic generation modeling method which can address the characteristics of changed electricity industry is proposed. The major contribution of this paper can be captured in the development of a probabilistic generation modeling considering generator maintenance outage and in the classification of market demand into multiple demand clusters for the applications to electricity markets. Conventional forced outage rates of generators are conceptually combined with maintenance outage of generators and, consequently, effective outage rates of generators are newly defined in order to properly address the probabilistic characteristic of generation in electricity markets. Then, original market demands are classified into several distinct demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the original demand. We have found that generators have different effective outage rates values at each classified demand cluster, depending on the market situation. From this, therefore, it can be seen that electricity markets can also be classified into several groups which show similar patterns and that the fundamental characteristics of power systems can be more efficiently analyzed in electricity markets perspectives, for this classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.