• International conference on construction engineering and project management
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• 2017.10a
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• pp.42-51
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• 2017

Due to the high degree of mechanization and the good environmental benefits, the prefabricated buildings are being promoted in China. The construction site layout of the prefabricated buildings has important influence on its safety benefit. However, few scholars have studied the safety problem on it. Firstly, in order to give a follow-up study foreshadowing the characteristics of prefabricated buildings are analyzed, the research assumptions are given and three types of safety buffers are established. And then a mult-objective model for the prefabricated buildings site layout is presented: taking into account the limits of noise, the coverage of the tower crane and the possibility of exceeding boundaries and overlapping, the constraints are and designed established respectively; Based on the improved System Layout Planning (SLP) method, the efficiency\cost\safety interaction matrices among the facilities are also founded for objective function. For the sake of convenience, a hypothetical facility layout case of the prefabricated building is used, the optimal solution of that is obtained in MATLAB with particle swarm algorithm (PSO), which proves the effectiveness of the model presented in this paper.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.

• Korean Chemical Engineering Research
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• v.45 no.3
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• pp.249-257
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• 2007

The periodic square wave (PSW) model was successfully applied to the optimal design of a batch-storage network. The network structure can cover any type of batch production, distribution and inventory system, including recycle streams. Here we extend the coverage of the PSW model to multitasking semi-continuous processes as well as pure continuous and batch processes. In previous solutions obtained using the PSW model, the feedstock composition and product yield were treated as known constants. This constraint is relaxed in the present work, which treats the feedstock composition and product yield as free variables to be optimized. This modification makes it possible to deal with the pooling problem commonly encountered in oil refinery processes. Despite the greater complexity that arises when the feedstock composition and product yield are free variables, the PSW model still gives analytic lot sizing equations. The ability of the proposed method to determine the optimal plant design is demonstrated through the example of a high density polyethylene (HDPE) plant. Based on the analytical optimality results, we propose a practical process optimality measure that can be used for any kind of process. This measure facilitates direct comparison of the performance of multiple processes, and hence is a useful tool for diagnosing the status of process systems. The result that the cost of a process is proportional to the square root of average flow rate is similar to the well-known six-tenths factor rule in plant design.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.393-403
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• 2021

Recently, there is becoming larger interest in the public practice centers equipped with advanced manufacturing equipment of industries that is difficult to have in all vocational high schools for strengthening practical education and technical education tailored to the Fourth Industrial Revolution in vocational high schools. In this study, using spatial optimization approaches, we explored the optimal location sets of the public practice centers of vocational high schools in Seoul for an illustration. For the proposed optimial location methods, P-median Problem (PMP) and Maximal Coverage Location (MCLP) were used because, when the public practice centers located in priority of large vocational high schools based on the number of students, it showed that the result is not minimizing the travel distance and maximizing the demand of the vocational high school students. This study found that the PMP can find the optimal location sets that minimize the travel distance of whole students. In addition, all students can be captured through locating five public practice centers by MCLP. It should be noted that the optimal locations of this study are limited in Seoul. However, the frame of this methodology applied in this study can be utilized to locate the public practice centers in other regions based on the spatial decision making.

• Journal of the Korea Concrete Institute
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• v.24 no.2
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• pp.165-172
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• 2012

In this study, the physical, mechanical, structural, and environmental performances based on field measured data were evaluated to check the suitability of concrete for ecological preservation and cultivation of a hydrophilic environment. More specifically, the study is focused on developing an environmentally friendly functional concrete with river ecology restoration and natural river early formation capabilities. The mechanical performance evaluation results showed that the increase in mix rate of the PVA (Poly Vinyl Alcohol) reinforcement fibers and silica fume caused an increase in the strength. The optimal mix rate was found to be 0.05 volume % PVA fiber and approximately 10% silica fume. The frost resistance evaluation showed that superior performance was gained when 0.05 volume % PVA fiber and 15% silica fume was mixed simultaneously. In the structural performance evaluation, the bending strength was improved by 47.7% compared to plain concrete when mixed with 0.05 volume % PVA fiber. The flexural toughness also saw significant improvement. The environmental monitoring of field performance showed that grasses germinated most rapidly, but the growth of red poppies, a plant that germinates in the spring, was most active with passing of time. Coverage measurements in all of the monitoring locations found favorable coverage of over 95% after 12 weeks. The study results showed that the environmentally friendly functional concrete had outstanding environmental performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.683-690
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• 2006

Reducing power consumption to extend network lifetime is one of the most important challenges in designing wireless sensor networks. One promising approach to conserving system energy is to keep only a minimal number of sensors active and put others into low-powered sleep mode, while the active sensors can maintain a connected covet set for the target area. The problem of computing such minimum working sensor set is NP-hard. In this paper, a centralized Voronoi tessellation (CVT) based approximate algorithm is proposed to construct the near optimal cover set. When sensor's communication radius is at least twice of its sensing radius, the covet set is connected at the same time; In case of sensor's communication radius is smaller than twice of its sensing radius, a connection scheme is proposed to calculate the assistant nodes needed for constructing the connectivity of the cover set. Finally, the performance of the proposed algorithm is evaluated through theoretical analysis and extensive numerical experiments. Experimental results show that the proposed algorithm outperforms the greedy algorithm in terms of the runtime and the size of the constructed connected cover set.

• Economic and Environmental Geology
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• v.51 no.6
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• pp.531-542
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• 2018

Batch sorption experiments were performed to remove the uranium (U) in groundwater by using the bamboo charcoal. For 2 kinds of commercialized bamboo charcoals in Korea, the U removal efficiency at various initial U concentrations in water were investigated and the optimal sorption conditions to apply the bamboo charcoal were determined by the batch experiments with replicate at different pH, temperature, and reaction time conditions. From results of adsorption batch experiments, the U removal efficiency of the bamboo charcoal ranged from 70 % to 97 % and the U removal efficiency for the genuine groundwater of which U concentration was 0.14 mg/L was 84 %. The high U removal efficiency of the bamboo charcoal maintained in a relatively wide range of temperatures ($10{\sim}20^{\circ}C$) and pHs (5 ~ 9), supporting that the usage of the bamboo charcoal is available for U contaminated groundwater without additional treatment process in field. Two typical sorption isotherms were plotted by using the experimental results and the bamboo charcoal for U complied with the Langmuir adsorption property. The maximum adsorption concentration ($q_m:mg/g$) of A type and C type bamboo charcoal in the Langmuir isotherm model were 200.0 mg/g and 16.9 mg/g, respectively. When 2 g of bamboo charcoal was added into 100 mL of U contaminated groundwater (0.04 ~ 10.8 mg/L of initial U concentration), the separation factor ($R_L$) and the surface coverage (${\theta}$) maintained lower than 1, suggesting that the U contaminated groundwater can be cleaned up with a small amount of the bamboo charcoal.

• Korean Journal of Plant Resources
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• v.32 no.4
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• pp.338-343
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• 2019

This study was conducted to nominate optimal ground cover plants eventually enhancing Aronia production in the highland rolling plains. Total number of 17 weed species were observed in Aronia field when no cover plant was applied. Meanwhile, 12, 14, 15 and 16 weed species were observed when kentucky bluegrass, white clover, rattail fescue and ground ivy were used, respectively. Untreated native weed species were 73.6 cm tall before cut, and kentucky bluegrass, white clover, Rattail fescue and ground ivy were 57.5, 36.8, 48.3 and 40.9 cm, respectively. Based on plant height before cut, two shortest plants, white clover and ground ivy, were considered effective as ground cover plants in Aronia field. Coverage at $3^{rd}$ year by cover plants ranged from 85% to 100%. Coverage of uncovered Aronia field by native weed species was 95% while coverage by 4 treatments, kentucky bluegrass, white clover, rattail fescue and ground ivy were 100, 87, 85 and 100%, respectively. Aronia yield per plant at $3^{rd}$ year was 1,916 g with white clover cover followed by 1,770 g with Rattail fescue, 1,766 g with ground ivy, 1,098 g without cover plants and 931 g with Kentucky Bluegrass. Out results indicated that ground ivy was the best among all treatments based on 3 criteria, (1) short plant architecture, (2) rapid ground covering and (3) better weed control. In addition, ground ivy cover appeared to secure better yield.

• Fire Science and Engineering
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• v.31 no.3
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• pp.137-143
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• 2017

A sufficient number of ambulances are critical for preventing delayed vehicle dispatch for emergency patients. This study presents effective methodologies for evaluating the effects of ambulance quantities on availability. The statistical properties of the emergency requests and responses were analyzed for a city in Korea. The inter-request times were modeled by statistical distributions. The ambulance dispatch was modeled using simulation, reflecting the shared dispatch among the city districts. The simulation results revealed that the existing ambulance quantity could successfully meet the majority of the requests, but more vehicles were desirable for improvement. The locations of the additional vehicles were determined efficiently by simulations with a greedy approach. The simulations with added vehicles showed a significantly better coverage of the emergency calls. This research can help design improved emergency vehicle operations, and help save lives.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1311-1327
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• 2016

We propose a multi-state model for analyzing semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the 'illness-death model', which composes three states, such as 'healthy', 'diseased', and 'dead'. The state of 'diseased' can be considered as an intermediate event. Two more states are added into the illness-death model to describe missing events caused by a loss of follow-up before the end of the study. One of them is a state of 'LTF', representing a lost-to-follow-up, and the other is an unobservable state that represents the intermediate event experienced after LTF occurred. Given covariates, we employ the Cox proportional hazards model with a normal frailty and construct a full likelihood to estimate transition intensities between states in the multi-state model. Marginalization of the full likelihood is completed using the adaptive Gaussian quadrature, and the optimal solution of the regression parameters is achieved through the iterative Newton-Raphson algorithm. Simulation studies are carried out to investigate the finite-sample performance of the proposed estimation procedure in terms of the empirical coverage probability of the true regression parameter. Our proposed method is also illustrated with the dataset adapted from Helmer et al. (2001).