Earticle

Local governments are recently developing local characters by using tangible and intangible resources representing their region in order to invigorate and promote local tourism. Local characters as well as a variety of character images act as a representative means of promotion. The present study is intended to suggest the application of color code technology to local characters in order to maximize visual effects of the existing local characters. The study will start with an introduction of current development situation of local characters and their application cases, and then suggest practical ways to take advantage of local character images based on the features of color codes and the cases of use.

As an important business model in the era of network economy, electronic commerce has played an increasingly important role in the development of the world economy. However, when the enterprise carry out the e-commerce strategy, it is often difficult to put corporate social responsibility in an important position. In this paper, we make an empirical analysis to test whether corporate social responsibility will affect the enterprise performance. Through questionnaire survey of the small and medium enterprises in Beijing City, the result shows that corporate social responsibility behavior has a direct positive impact on the corporate performance. Therefore, facing the challenge of internet, SMEs should pay more attention to the construction of enterprise ethics, enhancing the internal value of enterprise by strengthening corporate social responsibility.

The root plays an important role in the ecosystem of plants. In order to solve the problem that to measure the root is difficult, this article proposes the three dimensional morphology model of plant root based on spatial geometry structure and morphology architecture parameters, and realize the three dimensional visualization of root. First, constructing three dimensional display model including root axis growing model, branch geometry model and root axis curve model; then combining topological structure of root, we confirm corresponding pixel, using morphology characteristic parameters outputted by root morphology to conduct the three dimensional reconstruction of root. Finally, we realize the visualization expression of plant root, basing on the VTK simulation software. The result of simulation, for establishing the whole visualization plant growing root further, lays technical foundation.

The scanning format conversion method has been developed rapidly. The traditional TV used interlaced scanning format to compensate motion artifacts. The converting process of interlaced signal into a progressive one is called scanning format conversion. Due to recently developed progressive devices, all interlaced scanned contents must be converted into progressive format. The directional information is widely used for scanning format conversion. In this paper, we assess and compare performances by varying widow size. The performances are evaluated in PSNR, MSE, and SSIM metrics.

In this paper, aiming at the shortcomings of the traditional histogram enhancement method and defect, a kind of image enhancement algorithm is put forward based on digital image complexity. Experimental results show that this method has advantages compared with traditional image enhancement algorithms, mainly reflected in the results obtained by using the improved image enhancement algorithms, the corresponding SNR and MSSIM index are higher than the original. In the paper, SNR and MSSIM index is proved best combination, which are high reflects that the similarity of after-image and the reference image and the image is more suitable to the human eye.

Because the task scheduling problem is np-complete problem, it is hard to find a deterministic algorithm to solve the problem of task scheduling in the cloud computing platform. Therefore this paper presents a task scheduling mechanism based on simulated annealing algorithm. The algorithm is a modern heuristic algorithm and overcome the shortcoming of the local optimum search method. The algorithm uses a greedy algorithm to generate the initial value, and heat to a sufficiently high temperature and according to certain rules to generate a new value. If the new value is better than the original value or at a certain probability can be accepted, then replace the original value with the new value until cool. Experiments proved the feasibility and effectiveness of the algorithm. Compared with traditional algorithms, this task scheduling mechanism not only meets the needs of users and improves the performance of the system.

Water from the Selangor river basin is the main source of supply for the federal capital of Kuala Lumpur and the various districts of Selangor State located in the centre of Peninsular Malaysia since 2000. As this region is the most populated area in the country, its rapid economic development and population growth have caused concern over the adequacy of the quantity and quality of water abstracted from the Selangor basin, both at present and in the future. A recent prolonged drought has caused a one-month water rationing in the Kuala Lumpur and adjacent areas which basically has seriously affected the everyday life of the people and the industrial and agricultural sectors. A rainfall drought analysis is therefore required for assessing the severity of the drought events in the study area. In this study, L-moments have been used to compute the rainfall quantile values for 9 probabilities, 6 durations, 12 starting months for the 2 regions across the Selangor basin. The choice of the Pearson Type III and Wakeby distributions for fitting the Selangor rainfall data is presented. Quantile values are expressed as a percentage of mean rainfall of the particular duration and presented as drought indication maps. Rainfall of specific return period can be calculated easily using these maps and the mean rainfall for the particular station. The return period (severity) of a historical rainfall event from the station can be known when the magnitude of the historical event is compared with that of the rainfall event of a particular return period. This helps in monitoring and management of droughts.

Biomass and coal co-pyrolysis is one of most important reactions in the co-combustion and co-gasification of them. In order to study the interaction of biomass and coal in the co-pyrolysis process, thermo gravimetric experiments of them under different mixing modes were make. The mixed modes of biomass and coal include uniformly mix and stratified layout (coal in the upper) and stratified layout (biomass in the upper). The experimental results show that: the temperature of co-pyrolysis is lower than that of coal pyroly sis separately; the co-pyrolysis reaction velocity would be accelerated or debased, that depends on the biomass components and the mixing modes; the co-pyrolysis reaction velocity of coal and sawdust would be accelerated under the condition of uniformly mix; the others would be debased. The experimental results show also that: the reaction velocities of biomasses and coal co-pyrolysis always are less than those of separately pyrolysis. This study provides the important reference and theoretical basis for biomass and coal co-combustion and co-gasification.

It has been deemed as an effective tool of forecasting performance improvement to combine different component forecasting models. However, current nonlinear combining models are not able to meet the requirement of high forecasting accuracy in practice. To tackle this challenge, this paper constructs a hybrid, named genetic programming and least squared estimation based nonlinear combining method (GPLSE-NC), of a standard genetic programming (GP) algorithm and the least square estimation (LSE) method, based on which a new nonlinear combined forecasting model is proposed. To verify the feasibility of the proposed model, based on the container throughput data of Shanghai Port from January 2004 to November 2015, 4 different forecasting models are constructed and compared with the proposed GPLSE-NC combining model in terms of three forecasting performance evaluation criteria. The empirical results show significant superiority of the GPLSE-NC model over its rivals, which reveals that the proposed model has a great potential to be a powerful nonlinearly combine forecasting approach.