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  • 1
    Publication Date: 2018-07-18
    Description: The precisely perception of key customer requirements (CRs) is critically important for customer collaborative product innovation (CCPI) design. A novel approach is proposed based on the Kano model, interval 2-tuple linguistic representation model, and prospect theory. First of all, a Kano model is constructed to preliminarily screen the relatively important product function attributes. For the uncertain and vague information of CRs, an interval 2-tuple linguistic representation model is proposed to determine the weight of CRs. Then, the comprehensive prospects value is utilized for sorting the innovative programs based on the prospect theory. Finally, a numerical example is given to verify the scientific and validity of the proposed method.
    Print ISSN: 1024-123X
    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
    Published by Hindawi
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  • 2
    Publication Date: 2015-01-01
    Description: The degeneration mechanism of viscoelastic food material in specific processing mode affects the formulation of food material processing technology. On the other hand, it determines the taste of food in the chewing process. The viscoelastic food material was taken as the research object, and experimental data were obtained through stress relaxation experiments and strain relaxation experiments of texture analyzer material. Based on Maxwell model and Kelvin model, describing small deformation of the nonlinear viscoelastic constitutive model, building a composite model was proposed. By making analysis and comparison between constructed composite model and Maxwell model and Kelvin model, it was verified that the constructed composite model can be better described as the mechanical behavior of viscoelastic food material under the mode of compressed chewing, which is also providing a more precise theoretical model for the processing and development of viscoelastic food material.
    Print ISSN: 1024-123X
    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
    Published by Hindawi
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  • 3
    Publication Date: 2014-01-01
    Description: Test task scheduling problem (TTSP) is a typical combinational optimization scheduling problem. This paper proposes a variable neighborhood MOEA/D (VNM) to solve the multiobjective TTSP. Two minimization objectives, the maximal completion time (makespan) and the mean workload, are considered together. In order to make solutions obtained more close to the real Pareto Front, variable neighborhood strategy is adopted. Variable neighborhood approach is proposed to render the crossover span reasonable. Additionally, because the search space of the TTSP is so large that many duplicate solutions and local optima will exist, the Starting Mutation is applied to prevent solutions from becoming trapped in local optima. It is proved that the solutions got by VNM can converge to the global optimum by using Markov Chain and Transition Matrix, respectively. The experiments of comparisons of VNM, MOEA/D, and CNSGA (chaotic nondominated sorting genetic algorithm) indicate that VNM performs better than the MOEA/D and the CNSGA in solving the TTSP. The results demonstrate that proposed algorithm VNM is an efficient approach to solve the multiobjective TTSP.
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    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
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  • 4
    Publication Date: 2016-01-01
    Description: Considering the lack of the research on the relationship between HR flexibility and scheduling effect, a resource-competency matrix-based method was proposed in order to reveal the quantitative relationship between them. Meanwhile, a job shop scheduling model with HR flexibility was established and the improved genetic algorithm was used to solve the model. A case analysis demonstrated significant impact of HR flexibility on the scheduling effect, which provided valuable guidance for building flexible manufacturing systems.
    Print ISSN: 1058-9244
    Electronic ISSN: 1875-919X
    Topics: Computer Science , Media Resources and Communication Sciences, Journalism
    Published by Hindawi
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  • 5
    Publication Date: 2014-01-01
    Description: Chaotic maps play an important role in improving evolutionary algorithms (EAs) for avoiding the local optima and speeding up the convergence. However, different chaotic maps in different phases have different effects on EAs. This paper focuses on exploring the effects of chaotic maps and giving comprehensive guidance for improving multiobjective evolutionary algorithms (MOEAs) by series of experiments. NSGA-II algorithm, a representative of MOEAs using the nondominated sorting and elitist strategy, is taken as the framework to study the effect of chaotic maps. Ten chaotic maps are applied in MOEAs in three phases, that is, initial population, crossover, and mutation operator. Multiobjective problems (MOPs) adopted are ZDT series problems to show the generality. Since the scale of some sequences generated by chaotic maps is changed to fit for MOPs, the correctness of scaling transformation of chaotic sequences is proved by measuring the largest Lyapunov exponent. The convergence metricγand diversity metric Δ are chosen to evaluate the performance of new algorithms with chaos. The results of experiments demonstrate that chaotic maps can improve the performance of MOEAs, especially in solving problems with convex and piecewise Pareto front. In addition, cat map has the best performance in solving problems with local optima.
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    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
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  • 6
    Publication Date: 2013-01-01
    Description: The material function of liquid materials for packaging plays an important role in analysis of its mechanical behavior. The mechanical behavior of material affects the packaging process in many aspects, such as selection of packaging materials and preparation of packaging method. Therefore, research on the material function of the liquid material is very helpful to guide the packaging process and look into how the packaging quality and efficiency are affected by the mechanical properties of material. This paper established the material function for the starch solution under shear process. With the relaxation test of the starch solution specimens, theG(t)function and dumping function were established and verified. Based on the memory function of starch solution, the material function of starch solution was constructed and approved to be efficiently predict the mechanical behavior during the shear process. Therefore, such material function can be used to guide the operation on the shear flow.
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    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
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  • 7
    Publication Date: 2014-01-01
    Description: Test task scheduling problem (TTSP) is a complex optimization problem and has many local optima. In this paper, a hybrid chaotic multiobjective evolutionary algorithm based on decomposition (CMOEA/D) is presented to avoid becoming trapped in local optima and to obtain high quality solutions. First, we propose an improving integrated encoding scheme (IES) to increase the efficiency. Then ten chaotic maps are applied into the multiobjective evolutionary algorithm based on decomposition (MOEA/D) in three phases, that is, initial population and crossover and mutation operators. To identify a good approach for hybrid MOEA/D and chaos and indicate the effectiveness of the improving IES several experiments are performed. The Pareto front and the statistical results demonstrate that different chaotic maps in different phases have different effects for solving the TTSP especially the circle map and ICMIC map. The similarity degree of distribution between chaotic maps and the problem is a very essential factor for the application of chaotic maps. In addition, the experiments of comparisons of CMOEA/D and variable neighborhood MOEA/D (VNM) indicate that our algorithm has the best performance in solving the TTSP.
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    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
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  • 8
    Publication Date: 2013-01-01
    Description: Based on the preview optimal simple artificial neural network driver model (POSANN), a new driver model, considering jerky dynamics and the tracing error between the real track and the planned path, is established. In this paper, the modeling for the driver-vehicle system is firstly described, and the relationship between weighting coefficients of driver model and system parameters is examined through test data. Secondly, the corresponding road test results are presented in order to verify the vehicle model and obtain the information on drive model and vehicle parameters. Finally, the simulations are carried out via CarSim. Simulation results indicate that the jerky dynamics need to be considered and the proposed new driver model can achieve a better path-following performance compared with the POSANN driver model.
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    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
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  • 9
    Publication Date: 2014-01-01
    Description: Objectives. To evaluate the predictive characteristics of KL-6 and CC16 for bronchopulmonary dysplasia (BPD) in preterm infants, either independently or in combination.Study Design. This prospective cohort study was performed from 2011 to 2013 with preterm neonates of gestational age ≤32 weeks and birth weight ≤1500 g. Serum KL-6 and CC16 levels were determined 7 and 14 days after birth.Results. Seventy-three preterm infants were studied. BPD was identified in 24 of these infants. After adjusting for potential confounders, serum KL-6 concentrations were found to be elevated in BPD infants at both time points relative to non-BPD infants, while serum CC16 concentrations were lower at 14 days. At both 7 d and 14 d of life the predictive power of KL-6 levels exceeded that of CC16 (area under receiver operating characteristic curve: at 7 d, 0.91 cf. 0.73,P=0.02; at 14 d, 0.95 cf. 0.85,P=0.05). The combination of these markers enhanced the sensitivity further.Conclusions. Serum KL-6 levels higher than 79.26 ng/mL at 14 days postpartum in preterm infants predict the occurrence of BPD. CC16 was less predictive than KL-6 at this time point, but KL-6 and CC16 together enhanced the prediction.
    Print ISSN: 0278-0240
    Electronic ISSN: 1875-8630
    Topics: Biology , Chemistry and Pharmacology
    Published by Hindawi
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  • 10
    Publication Date: 2019-09-16
    Description: Thyroid cancers are the most common malignancy of the endocrine system; however, there is no reliable blood biomarkers for thyroid cancer diagnosis and even for aggressive and nonaggressive thyroid cancers as well as benign nodule discrimination. The present study is aimed at evaluating whether circulating microRNA (miRNA) can differentiate aggressive and nonaggressive thyroid cancer from benign thyroid nodules. In this study, we performed a multiphase, case-control study to screen serum miRNA expression profile in 100 patients with papillary thyroid cancer (PTC), 15 patients with aggressive medullary thyroid carcinoma (MTC), 91 patients with benign nodules, and 89 healthy controls using TaqMan low-density array followed by extensive reverse transcription quantitative real-time PCR validation. The results showed that the serum levels of miR-222-3p, miR-17-5p, and miR-451a were markedly increased, while miR-146a-5p, miR-132-3p, and miR-183-3p were significantly decreased in the PTC and benign nodule groups compared with the control group. There was no difference in the miRNA expression profile between the PTC group and the benign nodule group. Nevertheless, the serum levels of miR-222-3p and miR-17-5p were significantly increased in the MTC group than the benign nodule and control group. Moreover, receiver operating characteristic curve analyses demonstrated that the 2 miRNAs and their panel can accurately discriminate MTC from the benign nodule group and healthy controls. These findings indicated that the altered circulating miRNAs may discriminate PTC and benign thyroid nodules from controls, and serum miR-222-3p and miR-17-5p have the potential to serve as auxiliary tools for diagnosing more aggressive thyroid carcinomas, such as MTC.
    Print ISSN: 0278-0240
    Electronic ISSN: 1875-8630
    Topics: Biology , Chemistry and Pharmacology
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