This study presents the results obtained after using a discrete event simulation (DES) model for an emergency department (ED) network in a region of Istanbul under earthquake risk. For this aim the first step was to c...
详细信息
ISBN:
(纸本)9789813146969
This study presents the results obtained after using a discrete event simulation (DES) model for an emergency department (ED) network in a region of Istanbul under earthquake risk. For this aim the first step was to create a DES model of the network including five public hospital EDs using AnyLogic simulation software c. This model was used to create earthquake related scenarios. Then, a design of experiments (DOE) was conducted in order to examine the effect of the main factors on the performance measures (PMs) of patient average length of stay (LOS) in the ED and utilization of resources. A generalized full factorial design was performed where these simulated model factors were (1) the rate of estimated casualties depending on the earthquake magnitude and earthquake time, (2) routing probabilities of patients from the regions to the EDs inside the network and (3) percentage of patient arrivals with respect to the triage level. The experiments were sorted according to the first and third factors. Each PM was analyzed independently. On conclusion, a multi criteria analysis was conducted for each ED in order to show their preparedness capability for a major earthquake.
This paper presents an integrated fuzzy method for the evaluation of jobs in a furniture company in Turkey. Job evaluation provides to build up a sustainable pay structure on the basis of relative values of the jobs. ...
详细信息
ISBN:
(纸本)9789813146969
This paper presents an integrated fuzzy method for the evaluation of jobs in a furniture company in Turkey. Job evaluation provides to build up a sustainable pay structure on the basis of relative values of the jobs. The job evaluation problem can be considered as multi-criteria decision making problem. Multi-criteria decision making techniques, Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods are used for the evaluation. The paper addresses the evaluation of jobs in fuzzy environment to prevent the deviations of managerial assessments. The fuzzy AHP method (FAHP) is used for pair-wise comparisons. More stable weights were obtained with FAHP and then, by introducing these weights in the fuzzy TOPSIS method for a real world problem including 141 different blue collar jobs in the company has been considered. The relative worth of various levels of job factors have been calculated numerically. Finally, a ranking of jobs was obtained.
Resource sharing (RS) is an important method in inter-organizational supply chain collaboration (SCC). However, it is still an under-explored area in research of SCC compared to other subjects (e.g. coordinating contr...
详细信息
ISBN:
(纸本)9789813146969
Resource sharing (RS) is an important method in inter-organizational supply chain collaboration (SCC). However, it is still an under-explored area in research of SCC compared to other subjects (e.g. coordinating contract and information sharing). The aim of this paper is to examine the feasibility of applying RS model in the manufacturing stage of garment supply chain and to determine the suitable type of garment for RS in production. Eight scenarios of RS were designed. Discrete-event simulation was used for running experiment of each scenario. The comparison of different scenarios shows that garment manufacturers could get great benefits by applying RS model.
This study proposes a Cluster-Based Sales Forecasting (CBSF) model for fast fashion (FF) using linguistic and numerical variables. Data are clustered according to the EM algorithm and sales are predicted using extreme...
详细信息
ISBN:
(纸本)9789813146969
This study proposes a Cluster-Based Sales Forecasting (CBSF) model for fast fashion (FF) using linguistic and numerical variables. Data are clustered according to the EM algorithm and sales are predicted using extreme learning machines (ELM). The model employs recent real data from a European online FF brand. Results indicate that ELM yields more accurate forecasts than other typical data mining (DM) techniques when applied to CBSF. It also demonstrates that incorporating relevant linguistic variables into the forecasting system and a greater volume of historical data even if from different families, result in improved forecasting. These evidences confirm the relevance of big data to the FF industry.
Assessment and management of risks in the aviation sector is a difficult problem. Risk management is the part of the overall management activities of the aviation sector which includes whole activities that provides c...
详细信息
ISBN:
(纸本)9789813146969
Assessment and management of risks in the aviation sector is a difficult problem. Risk management is the part of the overall management activities of the aviation sector which includes whole activities that provides completely secure manner with standards and applications. There are many variables and uncertainties that affect aviation risk process. In this study we have implemented multi criteria-decision making techniques, fuzzy Analytic Network Process (ANP) and fuzzy Analytic Hierarchy Process (AHP) for evaluation of airport safety risk criteria and the results of both algorithms are compared.
Resolution principle proposed originally by Robinson in 1965 has dominated automated deduction for over three decades while the current most successful automated deduction systems are based on resolution. In this pape...
详细信息
ISBN:
(纸本)9789813146969
Resolution principle proposed originally by Robinson in 1965 has dominated automated deduction for over three decades while the current most successful automated deduction systems are based on resolution. In this paper, we consider a generalization of the standard resolution principle and their variation since then, it is proposed as a multi-ary, dynamic, contradiction separation based inference rule for automated deduction, where the existing resolution rule and its variations are its special cases. The key concepts and some conclusions are briefly outlined in this short paper.
Inspired by recent successes of deep learning in computer vision, we propose a novel application of deep convolutional neural networks to facial expression recognition, in particular smile recognition. A smile recogni...
详细信息
ISBN:
(纸本)9789813146969
Inspired by recent successes of deep learning in computer vision, we propose a novel application of deep convolutional neural networks to facial expression recognition, in particular smile recognition. A smile recognition test accuracy of 99.45% is achieved for the Denver Intensity of Spontaneous Facial Action (DISFA) database, significantly outperforming existing approaches based on hand-crafted features with accuracies ranging from 65.55% to 79.67%. The novelty of this approach includes a comprehensive model selection of the architecture parameters, allowing to find an appropriate architecture for each expression such as smile. This is feasible because all experiments were run on a Tesla K40c GPU, allowing a speedup of factor 10 over traditional computations on a CPU.
Evaluation of the regional opening competitiveness can help the regional government to take measures to improve the internationalization level, but needs to cope with the problem of comprehensive evaluation of the mul...
详细信息
ISBN:
(纸本)9789813146969
Evaluation of the regional opening competitiveness can help the regional government to take measures to improve the internationalization level, but needs to cope with the problem of comprehensive evaluation of the multiple indicators. In this paper we generated a new hybrid method that mixed the merits of Grey Incidence Analysis (GIA) and Principal Component Analysis (PCA) to overcome the disadvantages of each other. The satisfactory application effect in the opening competitiveness evaluation of the western regions of China suggests that it's suitable for the multiple indicators comprehensive evaluation.
Traffic sign recognition is a significant part in advanced driving assistance system. In this paper, a semi-supervised spectral cluster ensemble model is designed for traffic sign recognition, and the spectral model i...
详细信息
ISBN:
(纸本)9789813146969
Traffic sign recognition is a significant part in advanced driving assistance system. In this paper, a semi-supervised spectral cluster ensemble model is designed for traffic sign recognition, and the spectral model is based on pairwise constraints. Then, the inference of the proposed model is illustrated in detail and the corresponding algorithm is stated step by step. At last, real datasets are selected for experiment and the experimental results show that the proposed algorithm can work well.
暂无评论