Small and medium-sized enterprises as the main body of Chinese enterprises should be an important driving force for China's economic development. However, the problems of salary management faced by small and medium-sized enterprises are increasingly hindering their own survival and development. Whether it is standing on the position of the enterprise or the workers, the pay problem is that they are more concerned about the problem, while the remuneration is also an indispensable modern means of competition and incentives. Salary management is not only indispensable content of enterprise human resources, but also the establishment of modern enterprise system, and optimization of the allocation of social resources requirements. Enterprise salary management operation flexibility or not, directly affect the production and operation management, which will affect the long-term development of enterprises. This paper analyzes the problems of salary management in small and medium-sized enterprises (SMEs), such as unreasonable pay system, lack of forward-looking management system, and so on, and analyzes and discusses their own countermeasures.

Machine analysis of detection of the face is an active research topic in Human-Computer Interaction today. Most of the existing studies show that discovering the portion and scale of the face region is difficult due to significant illumination variation, noise and appearance variation in unconstrained scenarios. To overcome these problems, we present a method based on Extended Semi-Local Binary Patterns. For each frame, an aggregation of the pixel values over a neighborhood is considered and a local binary pattern is obtained. From these a binary code is obtained for each pixel and then histogram features is computed. Adaboost algorithm is used to learn and classify these discriminative features with the help of exemplar face and non-face signature of the images for detecting the location of face region in the frame. This Extended Semi Local Binary Pattern is sturdy to variations in illumination and noisy images. The developed methods are deployed on the real time YouTube video face databases and found to exhibit significant performance improvement owing to the novel features when compared to the existing techniques.

Sustainable ocean tourism is required to establish a balance between the environmental, economic, social and cultural aspects of ocean tourism development. Sustainable ocean tourism also contributes to local and national economies, enhancing the quality of social life and protecting the ecology. Sustainable ocean tourism expands the positive contribution of tourism to biodiversity conservation and poverty reduction and aims to attain the common goals of sustainable developments for ocean tourism. Sustainable ocean tourism is possible due to the roles of regulators and private and government institutions. Government policies, regulations and guidelines play vital roles towards achieving the sustainability of ocean tourism. However, the role of institutions also cannot be ignored, which provide support in the innovation of technologies and the implementation of policies. The paper targets to investigate the roles of regulations, policies and institutions in the sustainability of ocean tourism. A primary online survey on the perception of tourism experts was conducted for this study using Google Forms. The tourism experts were invited from all over the world to participate in the survey. The study received a total of 33 responses, out of which only 30 valid responses were considered. Using the Tobit regression model, the study found that, while regulations in India relative to foreign countries significantly boost the sustainability of ocean tourism, government policies and public institutions in India relative to foreign countries remain insignificant in predicting the sustainability of ocean tourism. Therefore, government policies and public institutions in India need to be revised and reformulated to make them important drivers of the sustainability of ocean tourism.

This article explored mineral resources and their relation to structural settings in the Central Eastern Desert (CED) of Egypt. Integration of remote sensing (RS) with aeromagnetic (AMG) data was conducted to generate a mineral predictive map. Several image transformation and enhancement techniques were performed to Landsat Operational Land Imager (OLI) and Shuttle Radar Topography Mission (SRTM) data. Using band ratios and oriented principal component analysis (PCA) on OLI data allowed delineating hydrothermal alteration zones (HAZs) and highlighted structural discontinuity. Moreover, processing of the AMG using Standard Euler deconvolution and residual magnetic anomalies successfully revealed the subsurface structural features. Zones of hydrothermal alteration and surface/subsurface geologic structural density maps were combined through GIS technique. The results showed a mineral predictive map that ranked from very low to very high probability. Field validation allowed verifying the prepared map and revealed several mineralized sites including talc, talc-schist, gold mines and quartz veins associated with hematite. Overall, integration of RS and AMG data is a powerful technique in revealing areas of potential mineralization involved with hydrothermal processes.

Black Death is a virosis caused by the Tomato Spotted Wilt Virus (TSWV), transmitted by thrips, and represents a complex problem since weed hosts for thrips vectors and the virus is accentuated as virus reservoir and vector sustenance. The objective was to generate, from a list of weeds that act as hosts for the four vector thrips species in the horticultural belt of La Plata, a relative risk categorization as an epidemiological component. Between 2000 and 2003, three sites were selected within the horticultural belt of La Plata (Buenos Aires, Argentina) where flowers of 21 weed hosts of Frankliniella occidentalis, Frankliniella schultzei, Frankliniella gemina and Thrips tabaci were sampled monthly (60 in total). For analysis, the sampling results were grouped into three annual seasons, corresponding to the phenology of greenhouse crops in the region. For the four thrips vectors, the abundance of adult thrips and the presence of their larvae were considered using an unsupervised hierarchical cluster analysis and the DGC multivariate mean comparison test to obtain the number of significant groups. From this base grouping, three risk groups (RG) were defined as a source of inoculum for these vectors: high (H), medium (M) and low (L) according to the status of the reproductive host (RH). The groups that emerged were: (H): RH of F occidentalis, (M): RH of F. schultzei and T. tabaci, and (L): RH of F. gemina or non-vector thrips. Periodic survey and early flowering suppression of nine weed species categorized as high risk is proposed. This implies the continuous monitoring of three weed species, to which other companion weeds are added according to the growing season.

Ride-hailing or private hire has taken the Singapore transport network by storm in the past few years. Singapore has had more than three revisions of its ride-hailing regulation in the six years since the arrival of the disruptive technology. Often quoted in the list of cities with commendable public transport policy, Singapore still manages to find a viable and significant position for ride-hailing. Cities from around the world are all searching for a model of regulation for ride-hailing that can be elevated as a benchmark. Singapore, to a large extent, has formulated a successful model based on current market parameters and, more importantly, an adaptive one that evolves constantly with the constantly disruptive technology. The experts and regulators of the Singapore transport sector were interviewed in depth, tapping into their opinions and technocratic commentaries on the city-state’s Point-to-Point, or P2P, sector regulation. The data were analyzed using the three-element model of social practice theory as an alternative to conventional behavioral studies, thereby eliminating bias on the commuters and rather shifting focus to the practice. Content analysis utilizing QDA is executed for categorization through fine-level inductive matrix coding to elaborate upon the policy derivatives of the Singapore model. The unique addition of the research to ride-hailing policy is the comprehension of the commonalities and patterns across industrial and technological disruption, practice and policy irrespective of sectoral variations, thanks to the utilization of social practice theory. The first-of-its-kind policy exercise in the sector can be repeated for any city, which is a direct testament to the simplicity and exhaustivity of the methodology, benefiting both operators and investors through equitable policy formulation.