In reality, the quality of an image is generally affected by haze. To obtain a well-quality image, removing haze is a hot issue on theory and application. This paper proposes a new algorithm to remove haze of hazy images. In the algorithm, first, the ambient illumination is estimated by a logarithmic guide filtering that can reserve the characteristics of the bright source areas and improve the dark source areas of the hazy image. Second, to overcome the defect of dark channel prior (DCP) and the over-brightness of the bright channel prior (BCP), two models with two parameters are introduced to improve the DCP and BCP, called multi-channel prior method. At the same time, a self-adaptive method is presented to compute the values of the two parameters. At last, based on the multi-channel prior, a self-adaptive method is proposed to compute the transmission mapping value. Further, four classes hazy images are employed to test the proposed method. The experimental results carried out on the public databases demonstrate that the proposed algorithm can outperform the current state-of-the-arts, including more effective defogging, clearer visibility and richer details.

Purpose: This paper aims to propose a novel nature-inspired optimization algorithm, called whirlpool algorithm (WA), which imitates the physical phenomenon of whirlpool. Design/methodology/approach: The idea of this algorithm stems from the fact that the whirlpool has a descent direction and a vertex. Findings: WA is tested with two types of models: 29 typical mathematical optimization models and three engineering problems (tension/compression spring design, welded-beam design, pressure vessel design). Originality/value: The results shown that the WA is vying compared to the state-of-art algorithms likewise conservative approaches.

Captured images are usually influenced by fog or haze. In reality, image dehazing is challenging. This paper proposes a modified artificial multiple-exposure image fusion (AMEF) algorithm to remove the haze from an image. In the algorithm, first, an adaptive gamma -correction transform with the mean and standard deviation values of each component of a hazy image is utilized to verify the intensities. Second, the homomorphic filtering algorithm is introduced into the Gaussian pyramid and Laplacian pyramid to compute the exposed accessible images. Last, a modified Laplacian filter method is presented to calculate the contrast of the exposed accessible images. Further, extensive experimental results demonstrate that the proposed algorithm has superior performance compared with that of some state-of-the-art methods, including higher contrast, richer details and a better visual effect in the dehazed image.

Purpose: Understanding the antecedents of patient safety culture among medical staff is essential if hospital managers are to promote explicit patient safety policies and strategies. The factors that influence patient safety culture have received little attention. The authors aim to investigate the antecedents of patient safety culture (safety climate) in relation to medical staff to develop a comprehensive approach to improve patient safety and the quality of medical care in China.Design/methodology/approach: The Chinese version of the Safety Attitudes Questionnaire (CSAQ) was used to examine the attitudes toward patient safety among physicians and nurses. This medical staff was asked to submit the intra-organizational online survey via email. A total of 1780 questionnaires were issued. The final useable questionnaires were 256, yielding a response rate of 14.38%. One-way analysis of variance (ANOVA) was employed to test if different sex, supervisor/manager, age, working experience, and education result in different perceptions. Confirmatory factor analysis (CFA) was used to verify the structure of the data. Then linear regression with forward selection was performed to obtain the essential dimension(s) that affect the safety culture (safety climate).Findings: The CFA results showed that 26 CSAQ items measured 6 safety-related dimensions. The linear regression results indicated that working conditions, teamwork climate, and job satisfaction had significant positive effects on safety culture (safety climate).Practical implications: Hospital managers should put increased effort into essential elements of patient-oriented safety culture, such as working conditions, teamwork climate, and job satisfaction to develop appropriate avenues to improve the quality of delivered medical services as well as the safety of patients.Originality/value: This study focused on the contribution that the antecedents of patient safety culture (safety climate) make with reference to the perspective of medical staff in a tertiary hospital in China.