• Convergence Security Journal
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• v.8 no.4
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• pp.173-181
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• 2008

Recently, Worm epidemic models have been developed in response to the cyber threats posed by worms in order to analyze their propagation and predict their spread. Some of the most important ones involve mathematical model techniques such as Epidemic(SI), KM (Kermack-MeKendrick), Two-Factor and AAWP(Analytical Active Worm Propagation). However, most models have several inherent limitations. For instance, they target worms that employ random scanning in the network such as CodeRed worm and it was able to be applied to the specified threats. Therefore, we propose the probabilistic of worm propagation based on the Markov Chain, which can be applied to cyber threats such as Mass SQL Injection worm. Using the proposed method in this paper, we can predict the occurrence probability and occurrence frequency for each threats in the entire system.

• Smart Structures and Systems
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• v.31 no.2
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• pp.113-130
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• 2023

Hybrid simulation (HS) has attracted community attention in recent years as an efficient and effective experimental technique for structural performance evaluation in size-limited laboratories. Traditional hybrid simulations usually take deterministic properties for their numerical substructures therefore could not account for inherent uncertainties within the engineering structures to provide probabilistic performance assessment. Reliable structural performance evaluation, therefore, calls for stochastic hybrid simulation (SHS) to explicitly account for substructure uncertainties. The experimental design of SHS is explored in this study to account for uncertainties within analytical substructures. Both computational simulation and laboratory experiments are conducted to evaluate the pseudo-random Sobol sequence for the experimental design of SHS. Meta-modeling through polynomial chaos expansion (PCE) is established from a computational simulation of a nonlinear single-degree-of-freedom (SDOF) structure to evaluate the influence of nonlinear behavior and ground motions uncertainties. A series of hybrid simulations are further conducted in the laboratory to validate the findings from computational analysis. It is shown that the Sobol sequence provides a good starting point for the experimental design of stochastic hybrid simulation. However, nonlinear structural behavior involving stiffness and strength degradation could significantly increase the number of hybrid simulations to acquire accurate statistical estimation for the structural response of interests. Compared with the statistical moments calculated directly from hybrid simulations in the laboratory, the meta-model through PCE gives more accurate estimation, therefore, providing a more effective way for uncertainty quantification.

• Steel and Composite Structures
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• v.41 no.6
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• pp.831-850
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• 2021

Surface subsidence caused by mining subsidence has an impact on neighboring structures and utilities. In other words, subsurface voids created by mining or tunneling activities induce soil movement, exposing buildings to physical and/or functional destruction. Soil-structure is evaluated employing probability distribution laws to account for their uncertainty and complexity to estimate structural vulnerability. In this study, to investigate the displacement field and surface settlement profile caused by mining subsidence, on the basis of a Winklersoil model, analytical equations for the moment-rotation response ofsoil during mining induced ground movements are developed. To define the full static moment-rotation response, an equation for the uplift-yield state is constructed and integrated with equations for the uplift- and yield-only conditions. The constructed model's findings reveal that the inverse of the factor of safety (x) has a considerable influence on the moment-rotation curve. The maximal moment-rotation response of the footing is defined by X = 0:6. Despite the use of Winkler model, the computed moment-rotation response results derived from the literature were analyzed through the ELM-SVM hybrid of Extreme Learning Machine (ELM) and Support Vector Machine (SVM). Also, Monte Carlo simulations are used to apply continuous random parameters to assess the transmission of ground motions to structures. Following the findings of RMSE and R2, the results show that the choice of probabilistic laws of input parameters has a substantial impact on the outcome of analysis performed.

• Journal of KIBIM
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• v.7 no.3
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• pp.31-39
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• 2017

BIM is effective to improve the labor productivity of construction participants. From this point of view, it is important to analyze the outcome related with BIM Labor which covers most of the BIM investment costs. This research focuses on BIM RFI which is one of the major task of the BIM labor and analyze the outcomes. In addition, this research was quantitatively analyzed by the standby time and related cost caused by BIM labor, which affect the results of the project participants. To this end, analytical standby queue model was utilized to analyze the labor focusing on micros TASK. 11 projects were selected to analyze the results of BIM labor and RFI that the project participants requested to the BIM labor was collected. Through this, it collected variables for analyzing results, and Finally, we pulled out 4 projects for analysis. In this study, the basic results analysis of RFI processing of the BIM labor, the probabilistic analysis of BIM labor service status, and the economic analysis of BIM labor optimal inputs were performed by using the research model presented. The results of this study can be utilized to formulate the optimal strategy for BIM labor inputs(e.g. number of employees, level, time point, etc.) of the construction phase. Moreover, it can contribute to ensuring the credibility of the BIM ROI results by presenting the cost of BIM services in BIM ROI analysis and the standby cost of project participants.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1148-1161
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• 2017

The success of a business process management system stands or falls on the quality of the business processes. Many experiments therefore have been devoting considerable attention to the modeling and analysis of business processes in process-centered organizations. One of those experiments is to apply the probabilistic theories to the analytical evaluations of business process models in order to improve their qualities. In this paper, we excogitate a conceptual way of applying a probability theory of proportions into modeling business processes. There are three types of routing patterns such as sequential, disjunctive, conjunctive and iterative routing patterns in modeling business processes, into which the proportion theory is applicable. This paper focuses on applying the proportion theory to the disjunctive routing patterns, in particular, and formally named proportional information control net that is the formal representation of a corresponding business process model. In this paper, we propose a conceptual approach to discover a proportional information control net from the enactment event histories of the corresponding business process, and describe the details of a series of procedural frameworks and operational mechanisms formally and graphically supporting the proposed approach. We strongly believe that the conceptual approach with the proportional information control net ought to be very useful to improve the quality of business processes by adapting to the reengineering and redesigning the corresponding business processes.

• Nuclear Engineering and Technology
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• v.42 no.4
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• pp.450-459
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• 2010

The present paper investigates the collapse pressure of cylinders with intermediate thickness subjected to external pressure based on detailed elastic-plastic finite element (FE) analyses. The effect of the initial ovality of the tube on the collapse pressure was explicitly considered in the FE analyses. Based on the present FE results, the analytical yield locus, considering the interaction between the plastic collapse and local instability due to initial ovality, was also proposed. The collapse pressure values based on the proposed yield locus agree well with the present FE results; thus, the validity of the proposed yield locus for the thickness range of interest was verified. Moreover, the partial safety factor concept based on the structural reliability theory was also applied to the proposed collapse pressure estimation model, and, thus, the priority of importance of respective parameter constituting for the collapse of cylinders under external pressure was estimated in this study. From the application of the partial safety factor concept, the yield strength was concluded to be the most sensitive, and the initial ovality of tube was not so effective in the proposed collapse pressure estimation model. The present deterministic and probabilistic results are expected to be utilized in the design and maintenance of cylinders subjected to external pressure with initial ovality, such as the once-through type steam generator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3309-3328
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• 2017

The application of Internet of Things (IoT) in the next generation cellular networks imposes a new characteristic on the data traffic, where a massive number of small packets need to be transmitted. In addition, some emerging IoT-based emergency services require a real-time data delivery within a few milliseconds, referring to as ultra-low latency transmission. However, current techniques cannot provide such a low latency in combination with a mice-flow traffic. In this paper, we propose a dynamic resource reservation schema based on an air-interface slicing scheme in the context of a massive number of sensors with emergency flows. The proposed schema can achieve an air-interface latency of a few milliseconds by means of allowing emergency flows to be transported through a dedicated radio connection with guaranteed network resources. In order to schedule the delay-sensitive flows immediately, dynamic resource updating, silence-probability based collision avoidance, and window-based re-transmission are introduced to combine with the frame-slotted Aloha protocol. To evaluate performance of the proposed schema, a probabilistic model is provided to derive the analytical results, which are compared with the numerical results from Monte-Carlo simulations.

• Journal of Korean Society of Transportation
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• v.21 no.3
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• pp.107-120
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• 2003

Over the decades, a lot of studies have dealt with the traffic characteristics and phenomena at a merging area. However, relatively few analytical techniques have been developed to evaluate the traffic flow at the area and, especially, the ramp merging capacity has rarely been. This study focused on the merging behaviors that were characterized by the relationship between the shoulder lane flow and the on-ramp flow, and modeled these behaviors to determine ramp merge capacity by using gap acceptance theory. In the process of building the model, both an ideal mergence and a forced mergence were considered when ramp-merging vehicles entered the gap provided by the flow of the shoulder lane. In addition, the model for the critical gap was proposed because the critical gap was the most influential factor to determine merging capacity in the developed models. The developed models showed that the merging capacity value was on the increase as the critical gap decreased and the shoulder lane volume increased. This study has a meaning of modeling the merging behaviors including the forced merging type to determine ramp merging capacity more precisely. The findings of this study would help analyze traffic phenomena and understand traffic behaviors at a merging area, and might be applicable to decide the primary parameters of on-ramp control by considering the effects of ramp merging flow.

• Journal of IKEEE
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• v.1 no.1 s.1
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• pp.31-46
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• 1997

In this paper, a parallel Optimal Best-First search Branch-and-Bound(B&B) algorithm(pobs) is designed and evaluated for MIN-based multiprocessor systems. The proposed algorithm decomposes a problem into G subproblems, where each subproblem is processed on a group of P processors. Each processor group uses tile sub-Global Best-First search technique to find a local solution. The local solutions are broadcasted through the network to compute the global solution. This broadcast provides not only the comparison of G local solutions but also the load balancing among the processor groups. A performance analysis is then conducted to estimate the speed-up of the proposed parallel B&B algorithm. The analytical model is developed based on the probabilistic properties of the B&B algorithm. It considers both the computation time and communication overheads to evaluate the realistic performance of the algorithm under the parallel processing environment. In order to validate the proposed evaluation model, the simulation of the parallel B&B algorithm on a MIN-based system is carried out at the same time. The results from both analysis and simulation match closely. It is also shown that the proposed Optimal Best-First search B&B algorithm performs better than other reported schemes with its various advantageous features such as: less subproblem evaluations, prefer load balancing, and limited scope of remote communication.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.426-426
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• 1999

;There are many sources of uncertainty in a typical production and inventory system. There is uncertainty as to how many items customers will demand during the next day, week, month, or year. There is uncertainty about delivery times of the product. Uncertainty exacts a toll from management in a variety of ways. A spurt in a demand or a delay in production may lead to stockouts, with the potential for lost revenue and customer dissatisfaction. Firms typically hold inventory to provide protection against uncertainty. A cushion of inventory on hand allows management to face unexpected demands or delays in delivery with a reduced chance of incurring a stockout. The proposed strategies are used for the design of a probabilistic inventory system. In the traditional approach to the design of an inventory system, the goal is to find the best setting of various inventory control policy parameters such as the re-order level, review period, order quantity, etc. which would minimize the total inventory cost. The goals of the analysis need to be defined, so that robustness becomes an important design criterion. Moreover, one has to conceptualize and identify appropriate noise variables. There are two main goals for the inventory policy design. One is to minimize the average inventory cost and the stockouts. The other is to the variability for the average inventory cost and the stockouts The total average inventory cost is the sum of three components: the ordering cost, the holding cost, and the shortage costs. The shortage costs include the cost of the lost sales, cost of loss of goodwill, cost of customer dissatisfaction, etc. The noise factors for this design problem are identified to be: the mean demand rate and the mean lead time. Both the demand and the lead time are assumed to be normal random variables. Thus robustness for this inventory system is interpreted as insensitivity of the average inventory cost and the stockout to uncontrollable fluctuations in the mean demand rate and mean lead time. To make this inventory system for robustness, the concept of utility theory will be used. Utility theory is an analytical method for making a decision concerning an action to take, given a set of multiple criteria upon which the decision is to be based. Utility theory is appropriate for design having different scale such as demand rate and lead time since utility theory represents different scale across decision making attributes with zero to one ranks, higher preference modeled with a higher rank. Using utility theory, three design strategies, such as distance strategy, response strategy, and priority-based strategy. for the robust inventory system will be developed.loped.