Earticle

Bovine mastitis is one of the common diseases in the dairy industry, and is also caused by the loss in the dairy industry. Timely and effective detection of bovine mastitis has important significance. By monitoring the milk conductivity values and other parameters, is to automate the monitoring cow health, is the basis of the prevention of bovine mastitis infection. This design is based single-chip microcomputer processing core control sensor measurement unit, data transmission unit, display and control unit, online monitoring system to achieve real-time data collection, transmission, display and other control functions. For monitoring the conductivity values were piecewise linear model of the relationship between the conductivity and the feedback voltage power function curve model comparison with simulation experiment. Simulation results show that the conductivity measurement piecewise linear model is a better, fitter factor, the average relative error is 2.31% lower, measuring range is 0.7 ms / cm-11.7ms / cm. The error of measuring the overall system is of relative low ratio, but the accuracy is higher, and better meets the needs of real-time monitoring, for cow health management and prevention of bovine mastitis or other diseases provide effective technical means.

As computer networks become an essential part of our daily life, therefore, protecting the resources from unauthorized users come forward with more challenging and complicated task for the researchers. From the last few decades, many number of password-based authentication schemes have been adopted in multi-server environment to protect the resources from any adversary means. Recently, Li et al. has proposed a dynamic-id based remote user authentication scheme and claimed that their scheme can provide more security than existing schemes and is suitable for practical applications. But, in this paper, we have shown that their scheme is not too much secured as they have claimed and it can suffer from stolen smart card attack, user impersonate attack and lack of some important features of smart card as well. To overcome these security flaws, we have further proposed an improved anonymous authentication scheme.

Aiming at the current situation of remote data monitoring, the study uses the sensor network to realize automation of remote data monitoring. This monitoring system is developed by Internet of Things technology, software technology, network evaluation technology and so on. The system has the characteristics of data real-time processing, visualization, and alarm on abnormal occasion, and has the ability to monitor data remotely and automatically.

During the process of aircraft landing, the control manners of carrier-based aircraft are always used to study. This is one of the important ways to avoid pilot-aircraft adverse coupling. In order to keep the accuracy of landing, this paper presents an improved asymmetric variable universe adaptive landing fuzzy controller with Safe Flight Area during approach for carrier-based aircraft. By means of universe-conversion factors and contraction–expansion factors, universe of discourse can be modified online, and fuzzy rules can reproduce automatically to adapt to the modified universe of discourse. The model simulation results indicate the better performance of the new method in comparison with the traditional controller with more accuracy and practicability.

The operation of microgrid is an important research topic due to its high efficiency of energy consumption and various types of energy source. Demand response (DR) programs can be applied to operate microgrid efficiently and economically. This paper deals with an optimal operation a microgrid in grid-connected operation mode. DR programs based on time of use (TOU) program and emergency demand response program (EDRP) are applied in this paper. Mixed integer linear programming is used to the end of simulation. Through the simulation results, the effectiveness of the DR programs based on TOU and EDRP to the microgrid operation are shown.

Big Data era is changing people’s way of thinking and working, urban residential landscape industry needs to absorb the production methods development outcomes of big data techniques. People need to build landscape environment like which more suitable for their material and spiritual life based on big data. In this paper, the urban residential landscape information database system architecture has been designed, focusing on the data source analysis, conceptual design, logical design and physical design. And further to the database techniques, such as data dictionary, ER model, SQL, and Web publishing platform, network applications techniques were introduced. Development and application of urban residential landscape database is a significant way to expand urban landscape environment construction.

This paper presents user privacy framework for web-of-objects based smart home services to control the release of personally identifiable information (PII) in smart home environment. The ubiquity of smart home enables smart home users and third parties to access home devices and data from any location at any time. The ubiquitous and pervasiveness improves the user comfort level, but also makes user PIIs highly prone to leakage. We propose Smart Home Web of Object User Privacy (SWOPR) architecture to protect and control the release of user PIIs according to the user consent. We suggest an architecture that integrates the RESTful framework, ISO/IEC-29101, and XACML/Ontology; the integration is not supported in existing systems. The SWOPR introduces Smart Home Web of Objects Privacy Controller (SWOPC) and Privacy Processor (SWOPP) nodes. SWOPC controls the process of collection of PIIs from users to the release of his PIIs to others. SWOPP provides PIIs processing functions such as anonymization and encryption under the control of SWOPC. The proposed privacy framework architecture is simple, lightweight and has high performance. We also present service scenarios to acquire the user PIIs, consents and release of PIIs to others.

This thesis focuses on the problems of high-temperature furnace motor in term of rotary shaft over length as well as deformation tendency under high-temperature condition, and therefore the thesis conducts design optimization upon rotary shaft of a motor that is applied in high-temperature furnace regarding its mechanical property and thermal-stress distribution. First, it establishes a full-scale 3D model of the shaft-fan system, then it analyzes its mechanical properties such as rigidity and stiffness under the high-temperature environment, which bases on reasonable assumed conditions and the boundary conditions, where hence the thesis puts forwards an optimized dimension design solution for the motor rotary shaft. And then the thesis analyzes and calculates the shaft-fan system to improve the motor shaft size from the angle of thermal stress and thermal deformation consideration and the special characteristics of such motor working under high-temperature environment. And the improved motor shaft size is verified as reasonable. The thesis analysis can be the designing references for cooling system applied in the high-temperature furnace motor.

Service-Oriented Architecture (SOA) constructs applications by publishing services in an open network environment. In network environment individual service changes highly dynamically, it is required the system based on services to adapt to this change. But the current service management in network environment doesn’t have a good, unified management mode, management mechanism, service and quality control system, and lacks of theoretical foundation to express formal service system. In this paper, a service management framework is designed. A mechanism and method based on strategy and dynamic network environment service management are proposed. The method can effectively solve the problem of dynamic service management in network environment, and is widely used in dynamic service management based on Web services.

In wireless sensor network, determine the position of the node position or events is very important to its surveillance activities, however, in the traditional wireless sensor network, are using two-dimensional spatial positioning technology, aiming at this problem, this article will wireless sensor network (WSN) 2 d algorithm is extended to 3 d space, analyzes the main factors affecting the positioning accuracy of wireless sensor network. In order to further improve the stability and precision of the algorithm, by introducing the Newton's method, gives the quasi-newton three-dimensional node localization hybrid localization algorithm. The simulation analysis shows that the proposed hybrid algorithm can under the same conditions with high positioning accuracy and stability, at the same time the CRLB are obtained. The simulation results show that the proposed algorithm can get g Latin American community, simulation analysis of the localization method is effective

Blackboard system is a network platform that is widely used by Universities and Colleges both at home and abroad. Its role is to broaden students' learning time, space and to assist the students' learning in their class hours and also after their class. Based on the data of a questionnaire on local college students’ attitude and behavior on the e-learning platform of Blackboard, this thesis presents a generalization and analysis the characteristic of students’ e-learning behavior by addressing their three behaviors: Information retrieval and processing behavior, social interaction behavior, and problems solving behavior. The behavioral characteristics of students’ application of Blackboard were analyzed in detail. The results showed that: overall, there is no great gender difference in the three aspects, but there are significant differences in different grades. Finally, according to the results of the questionnaire and statistical analysis, several suggestions and advices of curriculum construction based on Blackboard were put forward.

Bayesian calibration has been used to transform the prior distributions of unknown inputs inherited in a building energy simulation model into the trustworthy posterior distributions. It obtains the posterior distributions using a joint distribution composed of a likelihood function and prior distributions of unknown inputs in the Bayesian paradigm. In other words, it provides higher benefits in terms of a stochastic approach than the deterministic calibration and the feasibility of their calibrated results was sufficiently discussed. However, challenging issues in Bayesian calibration still remains as follows: (1) inappropriate selection of prior distributions, (2) truncated sample dataset of the likelihood functions. The aforementioned issues can increase the risks of Bayesian calibration. This paper aims to inform the risks of Bayesian calibration associated with the aforementioned issues through a reference case study. For this study, the Gaussian Process (GP) emulator, which can be regarded as a meta-model of Building Performance Simulation (BPS) tools, was used to reduce the simulation run-time. Bayesian calibration using the GP emulator was implemented with what-if scenarios considering the aforementioned issues. And then the validated models were used for a stochastic retrofit analysis of glazing systems. With the results of the estimated posterior distributions, validation, and stochastic retrofit, this paper presents Bayesian calibration issues regarding the selection of prior distributions and sample dataset of the likelihood functions.

Firstly, we applied the X-ray non-destructive testing technology to detect wood defects for getting the images. After graying the images, we calculated their GLCMS(Gray Level Co-occurrence Matrixes), then we normalized GLCMS to obtain the joint probabilities of GLCMS. The feature vectors of images, which included 13 eigenvalues of images were calculated and extracted by the joint probability of GLCMS. The fuzzy BP neural network(abbreviated as FBP) was designed by combining fuzzy mathematics and BP neural network . And the FBP neural network was regarded as the membership function of feature vectors, the outputs of the network was regarded as the degree of membership to the feature vectors in each category. We use the maximum degree of membership method for the pattern recognition of feature vectors, so the automatic identification and classification for feature vectors were achieved , and then the automatic identification of wood defects was realized. By simulated study and training many times, the results shown that the average recognition success rate of the network was more than 90%, and some FBP networks had an extremely high recognition success rate to training samples and test samples.

Soil nutrient monitoring system is to master the nutrient status of the bare ground, and quickly extract the information of farmland nutrient. Because of having a significant impact on the crop, the soil nutrient monitoring is important. For the lack of monitoring soil nutrient monitoring currently, combined with “3S” technology, spatial database technology, computer network technology and modern agricultural information technology as the basis, using WebGIS Service standard spatial database engine, the soil nutrient monitoring system based on soil nutrient information of Yangling was scientifically constructed. It achieved soil nutrient management from the large-scale, made the monitoring process towards standardization, improved management efficiency and scientific level, and provided technical support for farmland quality decisions.

In this study, a 3D model was constructed using Continuous Panoramic Image and accuracy analysis of 3D modeling data was performed. The way for 3D modeling using images and SketchUp greatly reduced the time and the coordinates of the target object were effectively collected in panoramic images. Accuracy analysis of the modeling result was performed by comparing coordinates with the total station. As a result of the accuracy evaluation of the 3D model, the horizontal and vertical deviations were 0.06m and 0.128m, respectively. Our results suggest that it is possible to reduce the operation time by 30% compared to modeling using existing laser scanner; also, panorama images can be used in various content businesses. The proposed method of 3D modeling reported in this study greatly reduces effort and time and can contribute to 3D modeling and other relevant areas.

In order to solve the data missing problem caused by sensor faults during the waste gas monitoring in animal building, a method for missing data recovery was presented based on support vector machine (SVM) combined with genetic algorithm (GA). Multiple factors that influence monitoring values of the waste gas in animal building such as temporal, spatial and environmental, were considered to established a SVM regression prediction model to estimate the missing data of the waste gas monitoring. Meanwhile, to obtain better prediction accuracy, model parameters were optimized by the GA. The data processing of the ammonia (NH3) concentration was taken as an example; monitoring data of 3 days were randomly selected in a farm to test the presented model in this paper. It is shown that there was a very little error between the estimated data and the monitoring data, the maximal relative error was 6.99 % (percent), and the average relative error was 2.15 % (percent). It is an effective method for missing data recovery and a practical way of data processing for waste gas monitoring in animal building.

Multi-agent systems fit nicely into domains that are naturally distributed and require artificial intelligence technology. The autonomous network-based information services integration architecture has been designed to satisfy the multiservice utilization in rapidly changing environments. However, the increase in the total number of user requests and changes lead to the unbalancing load in the system and the overload in the locality. This paper proposes a new strategy to solve such problem. Autonomous load distribution can be achieved through the integrated access method, which reduces the total load of the system for the number of Pull-MAs sent to the system decrease. In addition, the information structure of integrated service area is effective to improve the ratio of the satisfaction of Pull-MAs with joint request on one node. As a result, the homogeneous distribution of the separated services requests and correlated services requests is guaranteed autonomously. The simulation witnesses the success of the proposed mechanism.

With the rapid development of the IoT market many institutions are researching and developing various integrated IOT service platforms. Among them the development of IoT based tracking system requires a platform environment that can check in real time the target-oriented logistics movement status in industrial sites and social environments and manage resources. Previous related researches studied about particular single object tracking and about establishing a linkage process, but there were no studies about systems using Multiple Tracking System that target a variety of objects to establish a total task process such as for materials, personnel, and operations and process management. The study developed an efficient target-oriented smart integrated multiple tracking system that looks up object location based on real time and guarantees the accuracy and reliability of logistics location and resource management by combining the function of multiple tracking system.

Directed at the key problem about the heat transfer between heat pipes and piles found in the ground source heat pump system (GSHP), a new finite element method is adopted in this paper to provide a finite element scheme for piles and U-bent tubes.And then a calculation on the term of heat transfer between the pile and the U-bent tube through the point integration method is made.Then the value of the convective heat transfer coefficient h will be determined through the definition of the Nussellt number. Finally three illustrative examples are given in this paper to verify the rationality of our format. The model proposed in this paper has broken through the restrictions of the traditional analytical solutions, making it able to be applied widely in various projects.

This study tested eighty children with the tasks of vocabulary and reading skills (word reading and reading comprehension) and their mothers responded to home questionnaires regarding children’s use of smart device at home. The purposes of this study were about how 5-year old children used smart devices at home and how their use of smart devices at home was related to children’s vocabulary and reading skills. Results were as follows: First, 77.2% of children used smart device at home. Second, the often use of communication applications by children was associated with vocabulary, and vocabulary was related to word reading and reading comprehension. According to mediation analysis, the use of communication applications contributed to word reading and reading comprehension by the mediation of vocabulary among Korean children.

The design of an automatic voltage regulator (AVR) microcontroller-based distributed DC power supply is presented. The system includes a photovoltaic (PV) power generation, commercial hardware drive power system, and a battery booster circuit. A software control technology is used for storage battery charging and discharging. The PID control algorithm is used to control AVR microcontroller to achieve maximum power point tracking (MPPT) and to improve system stability. In addition to the traditional battery power, the system can make full use of solar system for energy sustainability. Experiment results show that the proposed system outperforms the traditional system with respect to the function of track, monitor and fine-tune for system steady state.