A Method Based on Intuitionistic Fuzzy Dependent Aggregation Operators for Supplier Selection

Recently, resolving the decision making problem of evaluation and ranking the potential suppliers have become as a key strategic factor for business firms. In this paper, two new intuitionistic fuzzy aggregation operators are developed: dependent intuitionistic fuzzy ordered weighed averaging (DIFOWA) operator and dependent intuitionistic fuzzy hybrid weighed aggregation (DIFHWA) operator. Some of their main properties are studied. A method based on the DIFHWA operator for intuitionistic fuzzy multiple attribute decision making is presented. Finally, an illustrative example concerning supplier selection is given

Semi-blind source extraction algorithm for fetal electrocardiogram based on generalized autocorrelations and reference signals

AbstractBlind source extraction (BSE) has become one of the promising methods in the field of signal processing and analysis, which only desires to extract “interesting” source signals with specific stochastic property or features so as to save lots of computing time and resources. This paper addresses BSE problem, in which desired source signals have some available reference signals. Based on this prior information, we develop an objective function for extraction of temporally correlated sources. Maximizing this objective function, a semi-blind source extraction fixed-point algorithm is proposed. Simulations on artificial electrocardiograph (ECG) signals and the real-world ECG data demonstrate the better performance of the new algorithm. Moreover, comparisons with existing algorithms further indicate the validity of our new algorithm, and also show its robustness to the estimated error of time delay

Bright Soliton and Bright–Dark Soliton Pair in an Er-Doped Fiber Laser Mode-Locked Based on In2Se3 Saturable Absorber

The output power in ultrafast fiber lasers is usually limited due to the lack of a versatile saturable absorber with high damage threshold and large modulation depth. Here we proposed a more efficient strategy to improve the output energy of erbium-doped fiber laser based on indium selenide (In2Se3) prepared by using the physical vapor deposition (PVD) method. Finally, stable mode-locked bright pulses and triple-wavelength dark–bright pulse pair generation were obtained successfully by adjusting the polarization state. The average output power and pulse energy were 172.4 mW/101 nJ and 171.3 mW/100 nJ, which are significantly improved compared with the previous work. These data demonstrate that the PVD-In2Se3 can be a feasible nonlinear photonic material for high-power fiber lasers, which will pave a fresh avenue for the high-power fiber laser

Development and initial validation of the Career Self-Management scale for Chinese coaches

ObjectiveThe purpose of the study was to develop and initially validate a context-specific scale assessing Career Self-Management for Chinese coaches (Career Self-Management Scale-CC; CSMS-CC).MethodsFirstly, qualitative data obtained from in-depth interview with coaches were contently analyzed to generate potential CSMS-CC items. The content validity of the items was evaluated by a panel of experts. Secondly, the factor structure and item performance of the CSMS-CC were examined using exploratory factor analysis (EFA) and internal consistency reliability of its subscales were evaluated in sample 1 (n = 229, 24.01% females). Thirdly, factor structure of the CSMS-CC was further examined using confirmatory factor analysis (CFA) in sample 2 (n = 295, 32.54% females). Internal consistency reliability was evaluated using Cronbach’ alpha coefficient and composite reliability. Nomological validity was examined using Pearson correlation and structural equation modeling (SEM) by investigating the correlations between CSMS-CC subscales with career success. Finally, measurement invariance and latent mean difference of the CSMS-CC was examined across gender, professional title and coaching class using multiple-group CFA (MGCFA).ResultsBased on the results of the content analysis and content validity evaluation, 18 CSMS-CC items were retained for further analysis. Results of EFA in sample 1 revealed that eight items were problematic and removed. The second round of EFA revealed that three components were retained and labelled as Networking Behavior (4 items), Training Exploration (3 items), and Guanxi Development (3 items). Results of CFA in sample 2 suggested that the 10-item three-correlated-factors model of CSMS-CC demonstrated acceptable model fit to the data, χ2 = 135.01, df = 32, p < 0.01, CFI = 0.91, TLI = 0.90, SRMR = 0.05, RMSEA = 0.092 (90% CI = 0.076–0.108). Composite reliability (ranging from 0.84 to 0.88) and Cronbach’s alpha coefficients (ranging from 0.78 to 0.81) of three subscales were found satisfactory. Nomological validity was supported by the results that total score and subscale scores of the CSMS-CC were significantly associated with internal marketability and external marketability. It was found that the CSMS-CC measurement model was strict invariant across gender, professional title and coaching class. Significant differences on all three subscales across professional title and on Guanxi development across coaching class were revealed.ConclusionResults of this study provided initial support for the psychometric properties of the 10-item CSMS-CC, which suggested that the CSMS-CC could be used for measuring the career self-management of Chinese coaches

Intuitionistic fuzzy generalized probabilistic ordered weighted averaging operator and its application to group decision making

In this paper, we present the intuitionistic fuzzy generalized probabilistic ordered weighted averaging (IFGPOWA) operator. It is a new aggregation operator that uses generalized means in a unified model between the probability and the OWA operator. The main advantage of this new operator is that it is able to deal with probabilities (objective information) and ordered weighted averages (subjective information) in the same formulation. Moreover, it is also able to deal with uncertain environments that can be assessed with intuitionistic fuzzy numbers. Furthermore, it uses generalized means providing a very general formulation that includes a wide range of situations. We study some of its main properties and particular cases such as the generalized intuitionistic fuzzy ordered weighted averaging (GIFOWA) operator and intuitionistic fuzzy probabilistic ordered weighted averaging (IFPOWA) operator. We end the paper by applying the new operator to a group decision making problem concerning the selection of investments. First published online: 26 Jun 201

Geographic concentration of industries in Jiangsu, China: a spatial point pattern analysis using micro-geographic data

Detection of geographic concentration of economic activities at different spatial scales has long been of interest to researchers from spatial economics, regional science and economic geography. Using a unique dataset from the first industrial land use survey of its kind in China, this research is the first effort attempting to explore spatial distribution particularly geographic concentration of industries in China using firm-level data. Distance-based functions and spatial cluster analysis are employed to detect the spatial scales as well as the geographic locations of industrial concentration. The results indicate that four of the five selected industries are in general concentrated in southern Jiangsu at small spatial scales (less than 5 km), while the chemical industry demonstrates an overall spatial dispersion pattern relative to the distribution of all other industries. Most industrial clusters have a radius of less than 2.5 km containing 20–60% of enterprises and 60–86% of employees from each selected industry, with larger clusters showing relatively weaker concentration. This research demonstrates the connections and complementarity of different approaches, complementing previous studies that use distance-based functions with spatial scan statistics

A deterministic small-world network created by edge iterations

Small-world networks are ubiquitous in real-life systems. Most previous models of small-world networks are stochastic. The randomness makes it more difficult to gain a visual understanding on how do different nodes of networks interact with each other and is not appropriate for communication networks that have fixed interconnections. Here we present a model that generates a small-world network in a simple deterministic way. Our model has a discrete exponential degree distribution. We solve the main characteristics of the model.Comment: 9 pages, 1 figure. to appear in Physica

Hydrophobic multiscale cavities for high-performance and self-cleaning surface-enhanced Raman spectroscopy (SERS) sensing

Cavity array, with excellent optical capture capability, has received increasing attention for the surface-enhanced Raman spectroscopy (SERS)-active substrates. Here, we proposed molybdenum disulfide (MoS2) nanocavities growing on pyramid Si (PSi) composed of in situ reduced Au nanoparticles (AuNPs), which can form the multiscale cavities (MSCs), and is facile for the couple of the plasmon. We demonstrated that the PSi/MoS2/Au MSCs can serve as highly sensitive, uniform, and stable SERS substrates for rhodamine 6G (R6G), crystal violet, and adenosine triphosphate detection, benefiting from the synergistic effect of the enhanced light trapping and the effective plasmonic couple. The couple of the plasmon in the MSCs is evidently proved by finite-difference time domain simulation, showing the strong electromagnetic field is located around the cavity wall. Moreover, the excellent hydrophobicity of the PSi/MoS2/AuNPs substrate endows it with the ability for the directional monitoring of organic pollutant in a mixture of oil and water. Finally, we demonstrated the MSCs with outstanding photocatalytic performance could achieve the renewable utilization by self-cleaning, which was attributed to the fast electron transfer and effective light absorption. The proposed PSi/MoS2/AuNPs MSC represents a robust mean using the plasmonic metal/semiconductor heterostructure for high-performance SERS sensors and photodegradation

Determinants of foreign direct investment in the Visegrad group countries after the EU enlargement

Considering the role of foreign direct investment (FDI) inflows in the sustainable development of a country, the main aim of this paper is to identify some macroeconomic factors that positively or negatively influence FDI in Visegrad group countries after the European Union (EU) enlargement in 2004. We employed two types of approaches in our analysis: i) time series and ii) panel data approach. According to the generalized ridge regressions estimated in Bayesian framework, the perceived corruption was a factor that influenced FDI in all the countries. In Poland, Czech Republic and Slovakia corruption came through as a serious obstacle for FDIs since 2005, but this was not the case for Hungary. Even if Hungary is perceived as a country with high influence, foreign investors seem no to care about this fact and are more interested in the quality of human resources and the possibility to increase exports. Our panel approach based on a panel ARDL model identified a significant relationship between FDI, corruption index and labour force with advanced education however this causality was only detected in the long run. According to the Granger causality in panel, the attraction of FDI inflows succeeded in generating changes in total tax rate, but the issues related to corruption were not reduced at an acceptable level for foreign investors in Poland, Slovakia, and the Czech Republic