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The spatial feature is important for scene saliency detection. Scene-based visual saliency detection methods fail to incorporate 3D scene spatial aspects. This paper aims to propose a cube-based method to improve saliency detection through integrating visual and spatial features in 3D scenes.

In the presented approach, a multiscale cube pyramid is used to organize the 3D image scene and mesh model. Each 3D cube in this pyramid represents a space unit similar to a pixel in the image saliency model multiscale image pyramid. In each 3D cube color, intensity and orientation features are extracted from the image and a quantitative concave–convex descriptor is extracted from the 3D space. A Gaussian filter is then used on this pyramid of cubes with an extended center-surround difference introduced to compute the cube-based 3D scene saliency.

The precision-recall rate and receiver operating characteristic curve is used to evaluate the method and other state-of-art methods. The results show that the method used is better than traditional image-based methods, especially for 3D scenes.

This paper presents a method that improves the image-based visual saliency model.

The purpose of this paper is to study the impact of learning effect and demand uncertainty on aggregate production planning (APP), provide practitioners with some important managerial implications for improving production planning and productivity.

Motivated by the background of one labour-intensive manufacturing firm – a mosquito expellant factory – an APP model considering workforce learning effect and demand uncertainty is established. Numerical example and comparison with other two models without considering learning and uncertainty of demand are conducted.

The result shows that taking into account the uncertain demand and learning effect can reduce total production cost and increase flexibility of APP.

Managerial implications are provided for practitioners with four propositions on improving workforce learning effect, i.e. emphasizing employee training, combing individual and organizational learning and reduction of forgetting effect.

This paper has practice value in improving APP in labor-intensive manufacturing.

This paper aims to study the temporal and spatial variation of vegetation and the influence of climate change on vegetation coverage in the Yellow River basin, China. The current study aimed to evaluate the role of a series of government-led environmental control projects in restoring the ecological environment of the Yellow River basin.

This paper uses unary linear regression, Mann–Kendall and wavelet analyses to study the spatial–temporal variations of vegetation and the response to climate changes in the Yellow River, China.

The results showed that for the past 17 years, not only the mean annual increase rate of the Normalized Difference Vegetation Index (NDVI) was 0.0059/a, but the spatial heterogeneity also yields significant results. The vegetation growth in the southeastern region was significantly better than that in the northwestern region. The variation period of the NDVI in the study area significantly shortened, and the most obvious oscillation period was half a year, with two peaks in one year. In addition, there are positive and negative effects of human activities on the change of vegetation cover of the Loess Plateau. The project of transforming cultivated land to forest and grassland promotes the increase of vegetation cover of the Loess plateau. Unfortunately, the regional urbanization and industrialization proliferated, and the overloading of grazing, deforestation, over-reclamation, and the exploitation and development of the energy area in the grassland region led to the reduction of the NDVI. Fortunately, the positive effects outweigh the negative ones.

This paper provides a comprehensive insight to analysis of the vegetation change and the responses of vegetation to climate change, with special reference to make the planning policy of ecological restoration. This paper argues that ecological restoration should be strengthened in areas with annual precipitation less than 450 mm.

The bottleneck of current DNA computing paradigms based on brute‐force search strategy is that initial solution space grows exponentially with problem size, thus only trivial instances of NP‐complete problem can be solved. The purpose of this paper is to present a novel molecular program based on sticker models for solving dominating set problems.

The authors do not synthesize the initial solution pool containing every possible candidate solution as previously reported algorithm. Instead, solutions DNA molecules to the problem of interest are constructed during the course of computation.

It is shown that “exponential explosions” inherent in current DNA computing paradigms may be overcome in this way.

The paper proposes an error‐resistant DNA algorithm based on sticker model for solving minimum dominating problems.

The purpose of this paper is to investigate the relationships among just-in-time (JIT), total quality management (TQM) and production operations performance (POP) based on the survey data from Chinese manufacturing firms, provide managerial implications of effectively implementing JIT and TQM for firms in developing countries.

Questionnaires were collected from 173 Chinese manufacturing firms. Three hypotheses on the relationships among JIT, TQM and POP were first established based on literature review. Empirical study method of structural equation modeling using SPSS and AMOS as data processing tools is employed to test the hypotheses.

The results show that, on one hand, JIT positively influences TQM and POP; on the other hand, although TQM also has positive relationship with POP, the relationship is not significant at a given significant level. Meanwhile, the author survey also shows that JIT and TQM have complementary relationship, i.e., JIT and TQM can benefit each other in a firm.

TQM is a base of implementing JIT, it is valuable to concurrently implement JIT and TQM in manufacturing firms in order to improve the POP.

It is believed that this research reveals new insights about the JIT and TQM implementation in Chinese manufacturing firms; it has practice value for firms to improve the implementation performance of JIT and TQM.