Earticle

With the increasing number of vehicles, society and environmental problems become much more seriously. Aiming at the serious problems, CNG engine, which has better emission performance, has been paid much more attention. However, the CNG engine also has its own disadvantages, such as engine power deterioration, great influence of different mixture ratios of the gas and air on the optimum ignition time of the engine, and so on. Therefore, adaptive control for the air-fuel ratio and ignition timing should be properly adjusted with the consideration of the engine power, economy and emissions. There are two methods of controlling the ignition timing: mechanical and electronic control. In this paper, we develop an adoptive control method based on electronic control. According to the verification, the method can improve the efficiency of the CNG engine. It can be shown the validity of the adoptive method.

The work describing in this paper develops and demonstrates an analog to digital conversion (ADC) technique based an electronic device which is used to detect gas leakage using mechanical sensors at households, industries, vehicles, gas stations etc. where detection of gas leakage is an important issue to avoid any uncertainty. The device consists of a processing section which takes input, processes it and provides output. Corresponding to this output, it starts exhaust fan and light emitting diode (LED) is on, if concentration of gas exceeds a certain level, starts buzzer (alarm), switch off the gas power supply and notifies the consumer by sending an alert message through the monitoring computer. The gas concentration level for a particular operational area will be stored in Matlab “Database Explorer Tool” in order to get an overview of gas status of this area for future analysis such as probability to take accident and so on.

With the continuous expansion of power grid, a large number of transmission lines through forests. Forest fire disasters seriously threaten the safe, economic and stable operation of power grid, so that the demand of discriminating fire risk points in transmission line corridors is getting more and more imperative. In this paper, a Fisher discriminant analysis method was put forward based on multivariate statistical analysis to assess the status of forest fire risk points. Firstly, impact factors on forest fire were defined. Secondly, the correlation between impact factors and the stability of fire risk point was analyzed with the historical material of forest fire. Next, multidimensional variables of the stability of fire risk point were turned into one-dimensional variables by projection method. Finally, the distances between one-dimensional variables were calculated and used to discriminate the status of stability of fire risk points. In a case in Shanxi province, this method has been verified.

Chemical industry is the fundamental strategic industry in national economy and one of pillar industries in China. A wealth of chemical industrial parks has been built one after another in many places, where lots of chemical enterprises are established. In the normal operation of those enterprises, their raw materials or products manufactured, transported and stored are usually featured by flammable, explosive or toxic properties, resulting in frequent occurrence of pollution and personal accidents and causing great threats to surrounding environment. This thesis realizes an integrated information management platform based on currently advanced cloud computing and IOT (The Internet of Things) technologies, so as for integrated management of chemical industrial parks. This thesis designs the architectural structure of said integrated information management platform, expounds the roles and realization approaches of the basic support platform and the business service platform, analyzes the principles and methods for realization of regionally coordinate emergency management operation mechanism based on the information management platform, that of IOT architecture technology and that of RFID and Wireless Sensor Network (WSN), and discusses that the standard unification of heterogeneous data under cloud computing is realized by means of multi-source data integration middleware. The said platform can accomplish the whole-process, real-time and dynamic follow-up and control of chemicals and hazardous materials and also provide effective service for users’ decision-making by mining and analyzing tremendous data of a chemical industrial park with Agent-middleware technology. The information management platform is capable of assessing the safety factors of chemical enterprises at peacetime, giving necessary warning before accidents and offering effective technical support for rescue via expert system, emergency plan system, monitoring system and positioning system. The realization of chemical industrial park integrated information management platform based on cloud computing and IOT technologies will greatly improve the management level of chemical industrial parks, intensify surveillance, achieve information resource sharing and lower the probability of accident occurrence.

The cost of equity capital is the expected rate of return that investors provide equity capital to listed companies, it reflect the protection degree of corporate governance mechanisms to the interests of investors. The more effective corporate governance mechanism is, the lower cost of equity capital is. As a factor of influencing corporate operation as well as governance, uncertainty will change such relationship. In perspective of board monitoring, comparing the results of multiple regression with panel data regression, this paper confirm that the uncertainty is positive correlation to the cost of equity capital, the board monitoring is negative correlation to the latter. More importantly, the relationship between the board monitoring and the cost of equity capital will become less significant when the uncertainty the company facing is increasing, which means that the uncertainty will weaken governance efficiency.

Apply the separation principle of the physical contradictions in TRIZ into the simulation of forest fire smoke and propose a forest fire smoke recognition algorithm based on gray bit-plane(short in FFSGBP) to change the problem of identifying the smoke into the analysis on the bit-plane images. To get eight images of moving smoke, the separation process on smoke moving images is necessary; use high-diagram image (the 7th,the 8th image) to extract contours, and extract the contour of the remaining images in the same position. Superimpose the information extracted, get the smoke model. By adding motion operators to the original image, we could simulate the motion of discrete smoke better, by using mean filter, we could reduce the influence of noise, and it can improve the reliability of the experiments. The results show that compared with the traditional method based on HSI model, the proposed algorithm can achieve the fire smoke detection quickly and obtain the contour model of the smoke inside efficiently and accurately.

With the rapid development of biomass pyrolysis fuel technology, the technology about heating through heat-carrier as an important part of biomass pyrolysis fuel process is also to mature. However, since there is a relatively great temperature difference after carrier heating, the biomass pyrolysis products and oil production rate are affected ultimately. Therefore, this article first introduces several kinds of biomass pyrolysis fuel technology about heating through heat-carrier, and then leads to a design of a fine temperature control device through analysis and comparison to keep the initial temperature difference within ±10 ℃ for the carrier in main reactor so that it can satisfy the temperature demand of biomass pyrolysis and promote the industrialization of biomass pyrolysis fuel.

Although urbanization can promote social and economic development, it can also cause various problems. How to evaluate urbanization performance and development coordination is a key problem for decision makers to find problems caused by urbanization and enhance the efficiency of urbanization performance. This paper introduces a hybrid combined weight method–McKinsey Matrix for evaluating the sustainable of urbanization. The values of development index and coordination index are calculated by combined weight method. The GE matrix can assist in assessing sustainable urbanization performance by locating the urbanization state point. A case study of urbanization in Liaoning in China demonstrates the process of using the evaluation method. The result indicates that the development of urbanization in Liaoning is better. The values of the coordination index between economic, environments, social, public service and livelihood is enhancing conspicuously. The case study reveals that the method is an effective tool in helping policy makers understand the performance and formulate suitable strategies for guiding urbanization towards better sustainability.

ZigBee is a relatively recent rise of short-range wireless communication standard, due to the energy resources ZigBee nodes in the network, computing power and bandwidth are very limited, which determines the ZigBee network protocol stack layers are designed to be energy effectiveness led to the design elements. The primary design goal is to establish a network layer path of energy efficiency, reliable data forwarding mechanism of formation and prolong achieve network lifecycle. Aiming at non-optimal and some nodes may be depleted prematurely because the business is too large battery energy issues ZigBee network routing tree routing algorithm, an improved routing algorithm for ZigBee network tree. Achieve network load balancing, saving overall energy consumption of the network, and maximize the lifetime of the network. Finally, the simulation of energy balance ZigBee tree routing algorithm implementation and simulation results.

In the process of full-scale static loading test of wind turbine blades, the loading forces all had relatively strong coupling effect, which seriously affected the accuracy of the test result. In order to eliminate this effect, firstly, a vertical static loading device for 10MW wind turbine blades was established and the coupling rule of loading force was obtained. Then, a control algorithm was put forward based on fuzzy theory. This algorithm took the error of loading force, error’s change rate as the input variables and the opening degree of proportional valve as the output variable. A control strategy based on this algorithm was constructed. In the end, the static device took the max flapwise of aeroblade5.0-62 wind turbine blade as example to conduct loading test. The result suggested the algorithm in this paper could ensure that the loading forces on five nodes always kept uniform changing and the control errors were respectively less than±2KN, ±2KN,± 2KN,± 2KN and±1KN. When in the 100% phase, the loading force could be finely maintained at the set value. The statistical results showed that the error rates of loading force with control algorithm were smaller than those without control algorithm. The test results verified the feasibility of control strategy applying to full-scale static loading test for wind turbine blades.

The accurate cooling load prediction of ice storage system is the basis and foundation for optimization control. In order to implement the optimal control of ice storage system, the accurate cooling load prediction is very important. This paper proposes that the SVM (support vector machine) combined with rough set is used for the load prediction of ice storage system. The simulation results proved that it opens a new avenue in load forecasting. SVM based on RS method is a promising alternative approach for cooling load prediction in a building.

This study aims at the status quo that theory is divorced from practice in embedded systems teaching process. A new theory teaching method is proposed that using Proteus as hardware simulation environment and Keil as software design environment. With this new method, in the teaching process, the hardware circuit can be simulated by the software environment. The joint use of Proteus and Keil in Embedded System Design Course teaching is clarified by an example of the design of electronic stopwatch which is using GPIO and timer in ARM7. This instance illustrates the flow and application methods about the joint application of Proteus and Keil in embedded system course teaching and practical application detailedly. By this method, it can stimulated students' interest in learning, and enhance the students' understanding of the principles and application of Embedded System Design. Thereby using this method can also improve the embedded system experiment teaching effect.

Based on decode-and-forward (DF) relaying scheme, the exact closed-form expression of the outage probability (OP) for the home mobile-to-mobile (M2M) cooperative networks over N-Nakagami fading channels is derived in this paper. Then the OP performance under different conditions is evaluated through numerical simulations. The numerical simulation results coincide with the theoretical results well, and the accuracy of the theoretical results is verified. The simulation results showed that: the fading coefficient, the number of cascaded components, the relative geometrical gain, and the power-allocation parameter have an important influence on the OP performance.

Because the accuracy of traditional sentiment orientation identification algorithm is not high under Q&A community, this paper proposes a new method based on two-level conditional random field improved by particle swarm optimization algorithm for emotion tendency recognition under Q&A community. The proposed method adopts particle swarm optimization algorithm to train two-level conditional random field model, and applies the trained conditional random field model to recognize emotion orientation of question-answer pairs in Q&A community. Experiments were performed on Yahoo! Answers data set and results show that the proposed two-level conditions random field improved by particle swarm optimization algorithm has a higher precision rate, recall rate and F1 value at the micro average and macro average aspects compared with Hidden Markov Model, Max-Entropy Markov Model, Support Vector Machine and traditional condition random domain model, which prove the proposed two-level conditions random field improved by particle swarm optimization algorithm is a more effective method to recognize emotion orientation of question-answer pairs in Q&A community.

Due to the actual demand of remote medical monitoring system, the overall framework of remote medical monitoring system which based on the Internet of things technology and cloud computing technology is designed. Put forward the application solutions of Android mobile terminal equipment in this system, and discusses the development methods of different types of the Android mobile terminal. First, the overall framework of remote medical monitoring system is introduced. Second, the development of data communication method of Android Bluetooth BLE and HTTP is discussed in detail, which is based on the Android framework. The Internet of Things and cloud computing technologies together to build a remote medical monitoring system. Android mobile terminal development on the medical applications of data processing centers and medical data display applications. Finally, the experimental results show that the system not only runs and transfers data stabilize, but also strong real-time, effective and feasible.

The 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) uplink supports only a single antenna transmission. However, in order to improve the uplink spectrum efficiency, support multiple antenna transmission in LTE-Advanced. Meanwhile, taking into account backwards compatibility for LTE. LTE-Advanced De-Modulation Reference Signal (DMRS) needs to be designed [1]. According to requirement of LTE-Advanced uplink pilot design, introducing orthogonal cover code (OCC) as a supplement, analysis and study of the current problems, proposes a Circular Shift (CS), Group/Sequence Hopping (GSH) and the OCC joint instructions method of pilot design. Finally, simulation and analysis of the performance of this scheme. Results show that this scheme can meet LTE- Advanced demand for pilot design well.

Reflectarray antenna with multiple simultaneous beams is a promising antenna candidate for the multiple beam applications. A comprehensive and systematic study on the design of single-feed multi-beam reflectarray antenna is presented in this paper. The traditional direct design method, called aperture field superposition method, is investigated first. It is demonstrated that although this method can generate a multi-beam pattern, it cannot provide satisfactory performances, mainly because of high side lobe level, gain loss and beam deviation. The iterative Fourier technique is then applied to optimize the performances of the multi-beam reflectarray antenna. The required mask and cost function for multi-beam design and the flow of the iterative Fourier techniques are represented. Finally, a Ku-band four beam reflectarray with a single feed is designed using the iterative Fourier techniques and the radiation performances are analyzed and compared with that of single beam, as reference case, and multiple beam designed by aperture field superposition. The numerical results show that a good four beam performance can be obtained by using the iterative Fourier techniques, which suggests that the iterative Fourier technique is suitable for the design of the multi-beam reflectarray antenna with a single-feed.

Smart home services for users require precise and reliable context information to guarantee credibility. To do this, system should have ability of context-awareness. Most of the context-aware systems have adopted rule-based inference but it did not fulfill users’ demand. To support valuable services in smart home environment, we present the rule-based inference engine which uses user profiles to let the system be aware of users’ context much accurately. Since the physical and logical size of the domain is relatively small, we also introduce inference algorithm optimized for limited size of memory space of the system.

Smart home automation system is increasingly used due to the wide manufacturer brands and various available technologies. From a social point of view, residents are admitted to smart homes for comfort, luxury, improving quality of live, and for providing security against intrusion and burglars. Secondly, home automation is achieved using a single controller, monitoring and the controlling many interconnected appliances such as lights, power plugs, HVAC system, humidity and temperature sensors, gas, smoke and fire detectors, audio, video and home theater as well as security and emergency systems. Smart homes are cheap, low-power, cost effective, efficient, and realize the automation of a variety of domestic appliances using user-friendly interface as remote control or any other handheld devices. Elderly, handicapped patients, and people with disabilities who have problems with locomotion difficulty can benefit from this smart home to totally operate, with high performance, all appliances and devices from anywhere in the house. When a resident is living alone, the ubiquitous access becomes very important and it is realized by using XBee transceivers that maintain RF wireless communication between the remote control and the master control panel board.

Various sensors have been recently integrated in a smart-phone and step detection method based on the acceleration sensor of a smart-phone has been introduced for indoor positioning scheme. Many researchers have put their interests on the study of step detection algorithm based on the acceleration sensor. However, the estimation performances of these methods are not good enough or just suitable for the situation when the position of the smart-phone is fixed in hand because the performance is significantly degraded in other cases. In this paper, a novel step counting algorithm based on the acceleration and the gravity sensors is proposed to enhance the estimation performance regardless of the position of a smart-phone and the motions of a pedestrian likewise walking or running. The effectiveness of the proposed scheme is demonstrated with experiments and the performance of the proposed scheme is compared with those of the conventional schemes. According to the results, the performance of the proposed scheme is enhanced compared to the conventional schemes no matter what the pedestrian is walking or running although the phone is in different places like trouser pocket, shirt pocket and hands.

Due to advancement in cloud computing technology, the research on the outsourced database has been spotlighted. In database outsourcing, because the service provider might be untrusted or compromised, two issues of data security emerge: data confidentiality and data integrity. Many data transformation schemes were widely studied for preserving data confidentiality, but they are vulnerable to data leakage problem because they do not consider data distribution when encrypting original data. Meanwhile, several query authentication schemes were proposed to verity data integrity, but they suffer from transmission overhead of verification data. Motivated by these problems, we propose a privacy-aware query authentication scheme which guarantees the data confidentiality and the query result integrity of sensitive data. To solve the original data leakage problem, our clustering-based data transformation scheme is designed to select anchors based on data distribution. To verify the query result, we propose a query result authentication index that stores an encrypted signature for each anchor, which is a concatenated hash digest of cluster data. A user compares the verification information with the cluster signatures stored in the verification index. Through performance evaluation, we show that our method outperforms the existing method in terms of query processing time and verification data size.

Recently, cognitive radio (CR) technology is broadly applied even to sensor networks. Cognitive radio sensor networks (CRSNs) have been studied and, apparently, sensor nodes equipped with directional antennas achieve higher energy efficiency. This paper proposes a medium access control (MAC) protocol named directional CR-aware MAC (DC-MAC) for CRSNs. To the best of the authors’ knowledge, this is the first work to propose a MAC protocol for CRSNs with directional antennas. The simulation study shows that DC-MAC is more energy efficient than the conventional protocol by 50%–60% for the RMF TR 1001 transceiver and by 20%–50% for the Bluetooth transceiver.

In this paper, we have designed the ontology model to achieve a cost effective livestock farm environment by maintaining safety and quality. The proposed model is built with the situational context aware data by making use of the wireless sensor network (WSN). The concepts of the proposed model are identified after considering all the possibilities with respect to the control services that help to increase the productivity and automation in the livestock farm environment. The health and diet management along with the environmental services are considered as a main service, which is a deniable fact. In addition to these services, uprising and downsizing of stock prices can affect the management behavior in regard to the production services. In order to solve the issue, both the health and diet management plans are monitored and modified automatically with respect to the changes in the stock market. With the proposed ontology model, the information from Internet of Things (IoT) is recomposed as context information, which helps in the understanding of the relationship between the livestock environmental factors.