Earticle

It is addressed that the point stabilization of the full-actuated autonomous underwater vehicle (AUV). The system model is established in polar coordinates and the designing methods of kinematic controller are obtained. The polar coordinates are applied to avoid Brockett’s conditions. The kinematic controller is extended to dynamic controller based on Lyapunov methods and backstepping techniques. The controller is designed to ensure that the full-actuated AUV asymptotically converges to the target point. Simulations show the effectiveness of the proposed method.

This paper introduces our design and implementation of an E-commerce system. One of the most distinguished features of this system is that an Internet TV system is integrated in the E-commerce system. In addition to the salient features for E-commerce such as price comparison, guarantee of the product quality, comments of other buyers, and so on, this system streams out a sequence of video contents just like home-shopping TV channels do. Our design and implementation details are discussed in this paper.

The calculation of general electricity prices on industry has great significance in cost control, energy conservation and emission reduction, as well as high efficiency management of electricity for the key electric power customers. Traditional solution has specific defections in time-consuming, convenience, and readout, however, the fee charging terminal has provided a more reasonable solution in interaction interface and abundant parameters settings with high efficiency.

Ice and Snow Art Landscape is unique urban landscape form in cold region. It is also artistic form reflecting the regional characteristics and cultural connotations as the symbol of the city. It has the important meaning for urban tourism industry and related industries. The construction of Urban Ice and Snow Art Landscape Information Database is an important channel promoting the development of Urban Ice and Snow Art. The research is based on modern network information technology, taking Urban Ice and Snow Art Landscape as research object. It puts forward on idea constructing Urban Ice and Snow Art Landscape Information Database, and design system architecture in the background using the technology of database, front design using DW, including Data Dictionary, E-R model, SQL, PHP and WEB publish. The development and Application of Urban Ice and Snow Art Landscape Information Database, is very necessary for the great-leap-forward development of Urban Ice and Snow Art Landscape.

It is a general practice to evaluate food taste based on sensory tests, however, this test method’s disadvantage is that a lot of cost and time is required and significant deviation is taken place depending on each evaluator as well. Food taste evaluation by utilizing SNS-based big data for supplementing this disadvantage is considered to be a new challenge and innovative method. The objective of this study is to suggest a system that evaluates and recommends the level of domestic food taste by not only clustering food preference using k-means algorithm after sorting out food-related tweet contents from typical twitter of SNS, followed by scoring taste adjectives being mainly used in daily life by using rough set and selecting food-related adjectives among the scored adjectives, but also exploring the level of salty, sour, savory, bitter and sweet tastes through perception map.

In order to realize rapid extended manufacturing, isomerism data integration method of enterprise resource, based on multi-dimension ontology, is proposed. Enterprise resource classified model is introduced, and process of integration and sharing of enterprise resources is analyzed. Besides, construction method of application view dimension enterprise resource ontology, life cycle dimension enterprise resource ontology and polymerization degree dimension enterprise resource ontology are discussed. Further more, entity relation diagram of enterprise resource integration is introduced, and generating and parsing mechanism of XML file about application view enterprise resources ontology is also stated. The mentioned method can resolve problems, such as enterprise resource isomerism data integration, operating authority control, and state information real-time tracking.

Data Mining is a popular knowledge discovery technique. In data mining decision trees are of the simple and powerful decision making models. One of the limitations in decision trees is towards the data source which they tackle. If data sources which are given as input to decision tree are of imbalance nature then the efficiency of decision tree drops drastically, we propose a decision tree structure which uses discrete haar wavelet transformation technique along with a filter. In this paper, we propose a novel method WT Tree based on above strategy. Extensive experiments, using C4.5 decision tree as base classifier, show that the performance measures of our method is comparable to state-of-the-art methods.

This paper presents fuzzy classification strategy for the hole-filling that can classify the incomplete mass point clouds and improve the precision. The irregular model is complex object that some part is smooth and some parts are irregular including sharp features. Therefore, we put kNN and curvature of mass point clouds to fuzzy inference system to divide the type of the hole of mass point clouds and the output of FIS can determine which part of point clouds belong to. For different kind holes, corresponding algorithm is given. Point clouds in the smooth area are reconstructed by implicit directly and ones in other regions of thin or sharp area are reconstructed by attach points. This method is simpler than those complex methods used on the whole point clouds directly. The experiment results show that classification can save much time and surface reconstruction is very fine.

Group mobile robot path planning is a multi-objective optimization problem, as the requirement of obstacle avoidance, traditional robot path planning optimization method has the problem of algorithm complexity, large search space and low efficiency, it is difficult to obtain the optimal solution. In order to improve the efficiency and the positioning accuracy of group robot path planning, we put forward a group mobile robot path planning method based on variable dimension artificial bee colony algorithm. Firstly, we take robot working environment to model, then taking group robot path network as nectar source, the ultimate goal of path planning is to find minimal path network, to find an optimal swarm robot moving path network which avoids obstacles through the mutual cooperation between bees. Simulation experiment results show that the path planning method based on variable dimension artificial bee colony algorithm improves the efficiency of swarm robot path planning, it can find optimal solution of swarm robot path planning during the shortest time, and it can avoid obstacles safely, it provides basis to group robot task coordination.

Purpose: Purpose of this descriptive research is to examine internet use and sleep related influencing factors of university students and to prepare for the basic data to develop nursing intervention which could be helpful to sleep management which is a major factor of university student’s health management. Method: Study subjects were targeting 228 university students and the correlation between internet addiction disorder and sleep quality, excessive daytime sleepiness (EDS), insomnia was analyzed using Pearson‘s Correlation and logistic regression analysis was conducted with the variables which are predicted to affect the excessive daytime sleepiness(EDS) and insomnia like gender, internet addiction disorder and sleep aspect. Results: Sleep quality, excessive daytime sleepiness (EDS), insomnia and internet addiction disorder showed significant correlation. Logistic regression result identified the influencing factor of excessive daytime sleepiness (EDS) and insomnia as internet addiction disorder and it increases excessive daytime sleepiness (EDS) risk by 1.033(OR 1.033, 95%CI 1.07-1.059) and insomnia risk by 1.022 (OR 1.022, 95%CI 1.002-1.042).

In this paper,we made a research for soybean straw hemicellulose rapid detection by establishing a quantitative analysis model based on near-infrared spectroscopy. At first,146 samples were collected from varieties of soybean straws are gathered in different areas of Heilongjiang province, then made chemical testing of components and spectral scanning to soybean straw, the 140 samples were classified to two groups, in which 100 samples were chosen as calibration set and the remaining 40 samples were chosen as verification set. Wavelet transform was used to deal with the noise spectrum, selected DBN wavelet, Haar wavelet and Symlet wavelet in different layers under penalty threshold, Bridge-massart threshold, and default global threshold for spectral signal decomposition and reconstruction, compared with other traditional noise reduction methods,Symlet2-2 layer decomposition wavelet basis for hemicellulose spectral processing possessed better effect with the determination coefficient of validation set rising from 0.462524 to 0.6314158 after processing.

This study was carried out to address the ever severer white pollution issue in the cotton fields of arid areas and to primarily stop the increase of film residuals in cotton fields. The feasibility of replacing plastic films with liquid mulch in combination with drip irrigation was evaluated. A bucket experiment was conducted to investigate the effects of liquid mulch on the transpiration rate and water use efficiency (WUE) of drip-irrigated cottons. A total of 5 treatments were set up: liquid mulch (1900 kg/hm2) coupled with drip irrigation (LFD1), liquid mulch (2200 kg/hm2) coupled with drip irrigation (LFD2), liquid mulch (2500 kg/hm2) coupled with drip irrigation (LFD3), plastic film coupled with drip irrigation (PFD) and drip irrigation without mulch (NFD or control). The results showed that in the bud stage, the peak value of cotton leaf transpiration rate in LFD3 was 0.95 mmol•m-2•s-1 (or 21.99%) higher than that in control but 0.39 mmol•m-2•s-1 (or 6.89%) lower than that in PFD. The WUE in LFD3 was the highest in any cotton growth stage among the treatments. The peak value of WUE in the seedling and bud stages was 16.90% and 15.03%, respectively higher in LFD3 than in control. When used at an appropriate dosage, liquid mulch can lower the transpiration rate and significantly raise the WUE of drip-irrigated cottons, thus paving the way towards high yields. In addition, liquid mulch has no negative effects on the soil environment and thus is of important research value and good application prospect in light of drip-irrigated cottons in arid areas.

Most analyses in pedagogy have been based on surveys, while in many other research areas like cognitive science and psychology, data-driven research has made significant progress based on large-scale data automatically generated and archived. Recently in pedagogy, learning achievement data has been archived, and EduData is one of such data sets provided by Korean ministry of education. Many data driven analysis algorithms can be applied to such data. As a first data-driven analysis to EduData, we applied the linear regression model to check which factors are effective to Korean student’s learning achievement. Finally, we proposed a model to predict degree of achievement. Experimental results show the performance of our models.

The traditional K-Means clustering is sensitive to random selection of initial cluster centroids, easily into the local optimal solution. In this paper, an efficient aggregation algorithm which combined with Artificial bee colony and K-Means algorithm is proposed to apply to the diagnosis of liver function. The algorithm reduced the dependence on the initial cluster centroids and the probability to be trapped by local optimal solution, thus assigning data points to their appropriate cluster more efficient. The experimental results show that algorithm proposed in this paper is superior to the K-Means clustering in diagnosis of liver function.

Recently, harmful algae (e.g., red tide) has damaged human and marine ecosystems. To address this, a response system should be developed to quickly cope with these ocean disasters. However, it is difficult to simultaneously monitor the vast ocean areas. Here, a marine disaster detection system can be developed through a convergence between the satellite-based ocean color remote sensing and the marine sensor network. The system architecture is divided into two steps: first, the system detects ocean anomalies in real-time using the satellite-based techniques, and secondly, the detected disaster information is transferred to the ships via the marine sensor networks. In this paper, we only focused on the first step and the second step is reserved for future work. Although the polar orbit satellite-based ocean color sensor platforms (e.g., MODIS, MERIS, and SeaWifs) can be used to simultaneously monitor the vast ocean areas, they are unsuitable for capturing subtle changes on a geographically equivalent area. On the other hand, the Geostationary Ocean Color Imager (GOCI), the world’s first ocean color remote sensor platform operated on a geostationary orbit, receives ocean color data around the Northeast Asia region every hour, eight times a day. Therefore, GOCI can be more effectively utilized to observe subtle changes and to detect anomalies in ocean environments in real-time. In this paper, we attempted to build a system to monitor marine disasters by detecting ocean anomalies using the ocean color data derived from GOCI. This system directly compares the test spectrum vectors (i.e. anomaly candidates) to a predefined reference spectrum vector (i.e. a target anomaly) through the cosine similarity. The experimental result showed that the proposed system could efficiently detect the disasters (e.g., the red tide) on the ocean environments.

With the continuous development of information, wireless network has become an integral part of people’s everyday lives. With the explosive growth of data in wireless network, the interferences and competition for resources are more and more serious, especially in the intensive network scenarios. Power control can effectively reduce the interference to improve throughput, save energy and prolong the service life of equipment. This paper proposes a power optimization strategy for Femtocell base station in LTE-A, a two-tier network. It plans the problem into Stackelberg Game, as Stackelberg Game model well describes the user behaviors, making it an effective analysis tool. Then this paper researches the Stackelberg equilibrium and obtains the optimal power distribution and optimal power pricing method. Based on it, a distributed non-uniform pricing algorithm, DNP, is proposed for Femtocell base station deployment. It realizes the distributed deployment with low complexity and less information interaction, and also shows a good performance through simulation, thus having a guiding significance for the power control scheme of Femtocell base station deployment.

It is an inevitable trend for business associations to participate in social governance and provide social services. But at present, the ability of business associations to provide services is not strong, and their social credibility is not high. Thus it is urgent to improve the governance capacity of them. On the basis of literature review and expert interview, this paper builds up a concept model and puts forward hypotheses. Research result from the analysis of 172 valid questionnaires shows that resources access ability and six other factors would influence the governance capacity of business associations in China. The research result attempts to provide reference for the Chinese government and business associations to take corresponding measures to improve the effectiveness of governance.

Recently, the evolution of ubiquitous computing has brought a breakthrough in network access and web based services including the agricultural field, which is integral to human living. In a ubiquitous vertical farm environment, context aware services display the context information in selecting the appropriate web service by identifying the state of the user and its surroundings. In this web enabled environment, establishing a context aware system for the vertical farm without the understanding of domains gets complicated especially when shaping with the avails. The semantic web should enable users to locate, select, compose and monitor web-based services automatically. For a successful execution of such services in semantic web, the service needs to be grounded with the corresponding WSDL. To resolve these issues, our work includes the development of an OWL-S based ontology model to define the relationship between the domains and add classes needed for the model in every aspect of the service oriented system. Compared with any other semantic web service, OWL-S is more suitable for the Vertical Farming System in the ubiquitous computing.

Tourism resource is fundamental to the development, promotion and marketing of tourism scenic areas. It is also a key concern of research on the development of the tourism industry. In this paper, factors that influence the analysis of tourism resource are discussed and analyzed. A multi-factor performance evaluation model of tourism resource of tourism scenic area is proposed based on grey system analysis. Firstly, tourism resources of tourism scenic area are categorized into social factors, economic factors, environmental factors, resource factors, historic factors, scientific and technological factors, regional factors and management and service factors. Secondly, evaluation indicators of different categories are standardized to have unified scale. Thirdly, on the basis of grey system analysis, grey clustering coefficients of tourism resource of tourism scenic area are computed and the performance of tourism resources are evaluated according to coefficients. Last but not least, the evaluation model of tourism resource of tourism scenic area is verified through a case study.

To examine the optical properties of aerosols and Asian dust, continuous monitoring has been performed at more than 20 lidar stations in the Asian Dust Network (AD-Net). Dual wavelengths depolarization lidar has been applied since 2010 at the Daejeon station (127.34E, 36.33N) in South Korea. This lidar system consists mainly of high power Nd:Yag laser, 300 mm telescope, and optical spectrometer with vertical and parallel depolarization channels at the two wavelengths of 532 nm and 1064 nm. For the analysis of aerosols and Asian dust, backscatter coefficients and depolarization ratios were retrieved with the assumption of the mixing condition of aerosols and molecules. The ratio of backscattering coefficient and depolarization ratio between the 532 nm and 1064 nm were then achieved. To know the spatial and temporal variation of Asian Dust, the results of the depolarization ratios and the backscatter coefficients measured at Daejeon station were analyzed and compared with the results measured from other lidar stations in the AD-Net.

The calculation of risk regionalization of meteorological calamities, usually determines the weight factors involved in the calculation by a subjective evaluation and objective calculation method, and the information should be more accurate or perfect. As the determination of the weight factors of meteorological disasters have limitations by subjective evaluation method and the objective calculation method, since the acquisition of information with multiple dimensions, has uncertainty. We propose a calculation method of meteorological disaster risk zoning of a rough set theory with GIS technology, and use this technology to evaluate the division of spatial unit and spatial factors index. The spatial unit of conditional attributes and decision attributes determine the weight of influence factors based on meteorological disasters. We can also determine the regionalization of the risk of meteorological calamities based on GIS spatial technology. The result indicated that the application of rough sets theory, combined with GIS technology can fully describe the relationship of spatial data though the information is still incomplete and uncertain. Moreover, it can be better to solve the practical problems in the calculation of meteorological disaster risk zoning.

In Malaysia, many researchers focus on developing speaker independent systems for training or articulation therapy or to assist language learners to learn about Malay Language or Bahasa Malaysia. Accuracy, noise robustness and processing time are concerns when developing speech therapy systems. In this study, a Malay word pronunciation test application was developed using the first 3 format and fundamental frequencies in an effort to improve pronunciation in Malay. This application was developed using Matlab and uses a vowel recognition algorithm classified using MLP classification technique. The application was developed and tested on UUM undergraduate students. For vowel classification, when fundamental frequency was added, 3-format feature vowel classification rate increased by 1.55% for male gender and 1.48% for female. When combined both genders, a more significant improvement of 1.71% was seen. The developed pronunciation application test results showed that the pronunciation application can assist in testing and improving their Malay word pronunciation. It was also observed that, vowel /i/, /e/, /o/ and /u/ are often mispronounced due to pronunciation habits.

Based on the needs of the Regional Scientific and Technological Innovation Platform, innovations evaluation system was established by AHP. In order to simulate the experts’ experiences and thinking, we used the improved BP neural network model. After training by putting in actual data, the improved BP neural network model was put in use to evaluate and manage the innovations created by the Regional Scientific and Technological Innovation Platform.

In the field of multi-spectral temperature measurement, the high-temperature blackbody furnace is applied to calibrate the multi-spectral pyrometer (MSP). The material of the blackbody furnace is graphite and its melting point is 3000℃. As a result, the MSP is not able to be calibrated above 3000℃ (non-source temperature) and the measurement range of MSP is limited to lower than 3000℃. Currently, the needs of the temperature measurement above 3000 ℃ are gradually increasing. To solve the problem above, the non-source temperature calibration method based on curve similarity principle (NCCSP) is proposed. The core idea of the NCCSP is that the mathematical model is formed based on curve similarity of the MSP output and the power function and then the derivative fitting which can control the curve trend well is applied to obtain model parameters to achieve the purpose that apply the calibration data below 3000 ℃ to predict the calibration data above 3000 ℃. The NCCSP is significance to expand multi-spectral pyrometer measurement range and supplement multispectral temperature measurement theory. The working-wavelength number of MSP is from a few to hundreds, under which the NCCSP is more accurate needs to be further researched. Therefore, in this paper, the impacts on the NCCSP accuracy of the working-wavelength selection are researched. Combine with Planck's law by theoretical simulation method to get the working-wavelength selection basis.

Co-creation refers to when diverse stakeholders in a community utilize IT to communicate and cooperate in a manner that allows all participants to create new value. To effectively utilize co-creation for regional innovation, knowledge storage is necessary to allow users to solve problems that arise in the community. Therefore, in this study, a knowledge-storage model was developed to systematically store cases of regional innovation and community problem solving, to effectively retrieve the cases required by users, and to utilize co-creation. To this end, a literature review and expert interviews were carried out to analyze user requirements, and the concept, functions, architecture, data structures, and attributes of co-creation knowledge storage were defined. In addition, the processes through which knowledge storage was utilized for regional innovation were presented as a scenario. This study’s contributions include the accumulation of research data related to co-creation knowledge storage for regional innovation and new case-based follow-up studies related to knowledge storage. This study also contributes to practical work by presenting the possibility of local governments or institutions establishing and utilizing knowledge storage to solve problems in regional innovation.

Manufacturing enterprise is the core to enhance country or regional competitive advantage; meanwhile it’s the main source of environment pollution. According to configuration theory, only optimal structure can guarantee the realization of strategic target. Therefore, manufacturing enterprise network structure dimension (centrality, transparency, disparity, and complementarity) is confirmed in this paper, and its influencing mechanism on its ecological performance is discovered based on data collection from typical manufacturing enterprise network by regression analysis method. From the research result we can see that efficiency and innovation oriented manufacturing enterprise network ecological performance has different relation with network structure. Efficiency-oriented network should improve its centrality, transparency and complementarity to increase its ecological performance; while for innovation-oriented network, it should keep medium transparency and comparatively higher level disparity to realize ecological development, and the complementarity also should be improved to get higher ecological performance in long run.

This study was purposed to verify the effect of repeated exposure and role to play in simulation-based education on hospital emergency care. 144 nursing students, at Y University in Daegu, Korea, had participated in this non-equivalent control group quasi-experimental study. All participants had 6 time simulation-based educations on hospital emergency care. The experimental group (n=65) had experience as a leader but the control group (n=79) didn’t have. Data were collected from October 01 to December 23 in 2014 regarding problem solving, critical thinking, satisfaction of simulation, performance evaluations by evaluator and students themselves on simulation-based education. It was analyzed with two sample t-test and repeated measured ANOVA using PASW Statistics (SPSS) 21.0 program. Satisfaction (t=0.257, p=.798), self-evaluation (t=-1.650, p=.102), and performance (t=0.147, p=.883) scores between two groups were not significantly different after the educations. Performance scores were significantly increased by the number of the simulation-exposure (F=412.724, p<.001), but not significantly different by the leader experience (F=1.246, p=.266). This study would support that repeated simulation-exposures improved the performance level on hospital emergency care regardless of role of simulation settings.

In order to satisfy the functional request of medical laser detector, the system theory of laser medical detector is analyzed. The gradual correction method is used in the design of laser transmitting and receiving optical system. The variable beam lens system is adopted in the transmitting system, and the Galileo telescope system is used in the receiving system. The software Zemax is used to simulate and macro language ZPL to write program, and the spot diagram and the structure chart of the transmitting and receiving optical system are get. In this design, the transmitting and receiving optical system is non-coaxial. There is a certain distance between two optical axes. So in order to ensure the two coaxial, splitting prisms are used to connect the transmitter optical system and the receiving optical system, forming combined optical system.