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Copyright of Journal of Ordnance Equipment Engineering is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Automobile Technology & Material is the property of Automobile Technology & Material Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Acta Materiae Compositae Sinica is the property of Acta Materiea Compositae Sinica Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Cotton Textile Technology is the property of Cotton Textile Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As the increasing demand for smart photoelectric devices such as smart photovoltaic glass and smart temperature sensors, halide perovskite thermochromic materials are gradually emerging. It is widely focused and studied to apply the perovskite material to smart color-changing semiconductor devices due to its characteristics of quick color response with the temperature and reversible cycle. In this paper, firstly, several common liquid-phase preparation methods for perovskite and perovskite-like single crystal materials are introduced. Secondly, thermochromic phenomena of three-dimensional halide perovskite single crystal material, low-dimensional perovskite-like single crystal material, and other single crystal material are mainly introduced, including different materials showing two different thermochromic mechanisms due to their different structures: structural phase transition represented by low-dimensional perovskite material and lattice expansion represented by double perovskite materials. Thirdly, the advantages and disadvantages of thermochromic properties of different single crystal materials, such as whether they are reversible, are compared, and their development potential in multi-functional applications is introduced. Finally, the current challenges and future development of perovskite thermochromic materials are prospected. [ABSTRACT FROM AUTHOR]

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Piezoelectrics & Acoustooptics is the property of Piezoelectric & Acoustooptic and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives: With the popularity of mobile devices and low‑cost sensors,the universal positioning capability of mobile terminals has become a strong demand. In order to build a universally available cloud positioning system, it is necessary to use various positioning sensors in smart terminals to obtain wireless signals, and search in the positioning database to complete the calculation of the position.Methods: In light of smart phone devices in location based service(LBS) scenarios, we focus on location service for massive smart phone devices and put forward the cloud computing network architecture. The breakthroughs on key engineering technologies such as hierarchical cloud positioning capabilities, low ‑cost access for developers, fault tolerance strategy and distributed positioning services are gained. Results: The testing result shows that cloud positioning system has realized the access processing capability of hundreds of billions of requests per day. Conclusions: Consequently, the system can provide location services for hundreds of millions of users and can be widely used in various location based applications. [ABSTRACT FROM AUTHOR]

This study highlights the recent research progress of an online yield monitoring system for grain combine harvesters in modern agriculture. The current measurements for the online yield monitoring were also summarized into the dynamic weighing, volumetric, impulse, and nuclear radiation measurement. Specifically, the dynamic weighing measurement was used for the weighing sensors to weigh the grain bins, screw conveyors, and elevators. The volumetric measurement mainly used the through-beam photoelectric sensors, diffuse reflection photoelectric sensors, and machine vision to measure the volume of grain on the scraper. More importantly, the volume sensor of the scraper wheel was selected to obtain the flow and volume of grain. The impact-based sensors were also adopted to measure the grain flow at the outlet of the elevator. Two kinds of sensors were included, the piezoelectric and strain impact-based grain flow sensors. Nuclear radiation measurement mostly used gamma and X-ray sensors to measure the grain flow. Other measurements were involved to establish the relationship between machine operating parameters and grain quality, such as the torque, tension, current, and speed sensors. At the same time, the limitations of each measurement were evaluated, in terms of stability and accuracy, feasibility, and versatility during the operation of the grain combine harvester. Furthermore, the grains were also dynamically weighed through the grain tank and the scraper due to inertia under specific conditions, such as the machine vibration, the bumps caused by the uneven ground in the field, the tilting, or the turning of ground, and the emergency brake. Nevertheless, the quality and volume were prone to drastic changes in the grain bins or scrapers using the grain volume measurement. Particularly, the accuracy of yield measurement was relatively low, due mainly to the influence of crop varieties, density, and moisture content. Since a large installation space was required for some yield monitoring, such as the auger weighing of net grain in a screw conveyor, capacitance measurement, and working parameters to determine the yield, the compact design of a combine harvester brought the complicated and labor-intensive modification for the installation of measurement system under the limited room. In addition, the low applicability of nuclear radiation was attributed to the possible radiation hazards for the human body during the production test. At the same time, the mechanical damage to the grain was inevitably caused by the collision of grain and impact plate during the impact measurement. As such, the quality and grade of processed grains were reduced for the germination rate of seed, due to the damaged grain was more prone to mildew during storage. Correspondingly, the yield measurement, sensor installation, and location varied significantly in the different physical and chemical properties of various harvested crops, as well as the different net grain transportation structures. Some suggestions were also proposed for crop yield monitoring during this time. Anyway, the simplest and most convenient installation was preferred to meet the needs of different crop harvesting, such as the integrated, miniaturized, high-precision, and intelligent measurement sensors with the communication interface standard. Consequently, an intelligent system can be expected to develop in the combine harvesters for real-time monitoring, such as crop output, harvester geographic location, and output distribution map. [ABSTRACT FROM AUTHOR]

Copyright of Cotton Textile Technology is the property of Cotton Textile Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the development of intelligent textiles, conductive fibers and various flexible sensors are more and more used in wearable textiles. This paper summarizes the types of conductive fibers, the research status of resistance sensors, capacitance sensors and piczoelectric sensors. The sensitivity. accuracy. comfort of wearing and the application advantages of human wearable sensors are analyzed. The advantages of flexible sensors in terms of flexibility. elasticity. stretch, quick response,lightweight and multifunction are summarized. Finally, it is pointed out that flexible sensors made of conductive fibers or fabrics have high sensitivity and accuracy. and play an important role in the fields of human pulse monitoring, motion monitoring. biomechanical energy collection, etc. They can be widely used in the design of wearable intelligent textiles. [ABSTRACT FROM AUTHOR]

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The fine breeding of livestock and poultry facilities is the frontier of the development of modern animal husbandry. The core of the fine breeding of livestock and poultry facilities lies in the deep integration of the "Internet of Things+" with traditional farming facilities. In recent years, with the withdrawal of more and more individual family-based breeding models, the management methods of livestock and poultry farms in China have gradually moved towards intensification, large scale,and automated facilitation. The traditional family-style livestock and poultry management experience is falling behind and gradually withdrawing from the historical stage. The refined farming of livestock and poultry facilities based on the individual animal management and quality assurance of farmed animals and animal welfare requirements have become the latest development trend of livestock and poultry farming industry. The rapid development of digital and network technology will provide new opportunities for the organic combination of animal husbandry production, animal welfare, information management and sustainable utilization of natural resources. Economic benefit, animal health and welfare, refinement of production process management and product quality are three key factors that affect the sustainable development of animal husbandry. In this paper, based on expounding the importance of the information sensing and the environmental regulation and control of the fine breeding livestock and poultry facilities, a cutting-edge technology of the information sensing and the environmental regulation and control of the livestock and poultry facilities was introduced; problems and challenges to be faced with were analyzed; and it was concluded that the smart sensor technology would become the base driving force for progress of livestock and fine poultry breeding facilities, taking account of the welfare of livestock and animal performance of animal anthropomorphizing intelligent control technology and strategy is facing significant challenges. In the field of pig farming, the core direction is mechanized production mode, which is light simplification, feed hygiene and animal health. In the field of cattle farming, the main direction is the automation of the whole chain of forage and the safety of its enclosure facilities. In the field of milking technology, the frontier of technological innovation is to further improve milking efficiency and quality, milking process, low disturbance milk metering, and cow individual milk production prediction. In the field of poultry production, similar to cattle farming, more attention is paid to the improvement of engineering processes such as bedding, environment and drinking water. Finally the paper put forward suggestions on how to implement the key technologies of fine farming of livestock and poultry facilities in China, with purpose of providing theoretical reference and technical support for the transformation, upgrading sustainable development of livestock and poultry breeding industry.

Copyright of China Textile Leader is the property of China Textile Information Center and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Beijing University of Technology is the property of Journal of Beijing University of Technology, Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to meet the increasing demand for smart clothing, the preparation technology of flexible sensors and their new materials under capacitive, piezoresistive, piezoelectric, inductive and optical fiber sensing mechanisms were introduced aiming to the application of flexible sensors in smart clothing. The research achievements and applications of the flexible sensor combined with textile and clothing at home and abroad in human monitoring, medical care and life entertainment were summarized. The challenges of material durability, structural stability and accuracy of measurement clata faced by flexible sensors in the practical application of textile were pointed out. The production process, data collection and processing capabilities of the flexible sensors were prospected, which provides new directions and new ideas for the innovation and transformation of the textile and apparel industry. [ABSTRACT FROM AUTHOR]

Copyright of China Textile Leader is the property of China Textile Information Center and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the networked war, it is urgent that airborne radar can continuously acquire target information while ensuring the safe survival. Focusing on this problem, in the context of safe transition tasks of multi-airborne cooperative operations, this paper proposes a intelligent sensor management method based on deep reinforcement learning. First, the real-time threat membership is calculated considering the signal radiation and several threat factors. Then, the radar-target assignment problem is modeled in a reinforcement learning framework. The neural network is used to approximate the action-value function, and the parameters are updated according to the temporal-difference algorithm. It can be seen from the simulation that the proposed algorithm improves the task success rate and shortens the time of task completion compared with the traditional scheduling methods. [ABSTRACT FROM AUTHOR]

To solve the problem that the existing step counting algorithms have poor adaptability to different motion states, this paper proposed a step counting algorithm based on self-adaptive threshold. By using the 3 -axis accelerometer sensor in smart bracelet, the proposed algorithm firstly collected the acceleration data when users walked at three frequencies including slow walking, fast walking and running. After five-point filter preprocessing, this algorithm detected peaks and valleys in the self adaptive time window. The n it took the average of the peak mean and valley mean as the upper thresh old, and used the valley mean as the lower threshold. Based on this, the algorithm adopted a dynamic threshold a nalysis to achieve the step counting . Finally, in this algorithm, false steps could also be detected according to the regularity of walking amplitude and frequency . The test shows that the achievable average step counting accuracy of the proposed algorithm is above 91. 88% for different users at three different walking frequencies. [ABSTRACT FROM AUTHOR]

With the continuous improvement of sensor technology and intelligent technology, intelligent proportional directional valve with built-in pressure sensor and temperature sensor are emerging. However, due to the large volume and slow response of the flow sensor, the flow sensor is difficult to be integrated into the proportional valve, so the flow information needs to be obtained indirectly by calculation. The traditional calculation method usually applies the empirical formula to the valve port flow coefficient. However, the proportional directional valve used in this study has a more complicated valve port shape and flow channel, which has a great influence on the valve port flow coefficient, and the traditional method is difficult to be directly applied. Therefore, the pressure sensors and the spool displacement sensor are used in this paper. The flow is calculated using the look-up table method and the flow feedback control is performed. This method can realize the flow dynamic control function of the proportional directional valve, thereby improving the versatility of the proportional directional valve. [ABSTRACT FROM AUTHOR]

To improve the accuracy of human behavior recognition and reduce the complexity of the implementation process, this paper raised a method using the data of acceleration sensor and gyroscoped in smartphone to recognize six kinds of daily basic behaviors. It collected and preprocessed data of acceleration sensor after analyzing the framework of sensor, then it used principal component analysis method combining with existing knowledge to reduce the dimension of the statistical characteristics of the original data. Then it used machine learning algorithm to classify and recognize the behavioral characteristics, which aimed at simplifying the basic behavior recognition process and improving the utilization rate of the data. The experimental result shows that the combination of decision tree and support vector machine classifier is effectual, and the recognition accuracy can be close to 97% . [ABSTRACT FROM AUTHOR]

Copyright of Cotton Textile Technology is the property of Cotton Textile Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Textile Leader is the property of China Textile Information Center and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Clean Coal Technology is the property of Clean Coal Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Mobile crowd sensing (MCS) is the core of mobile computing with the rapid development of wireless sensor networks and the popularity of mobile intelligent devices. The use of crowd sensing can be completed large-scale, complex environment and social awareness tasks, which the task distribution is an important part of this application. In order to solve the problem that the perceived environment is complex, the number of users can not meet the requirements and the quality of the collected data is low, this paper proposed a task distribution mechanism EUC based on social attribute and effective user calculation. According to the task to filter the characteristics of the user, from the user point of view, EUC considered the user’s social, the user’s social network through the relevant information to increase the number of effective users. From the platform point of view, according to the task of receiving and submitting the situation, EUC dynamically adjusted the effective user’s points,thus ensuring the effective number of users of the entire system. Theoretical analysis and experimental results show that the proposed mechanism can improves the task distribution efficiency of the system and improves the quality of the collected data. [ABSTRACT FROM AUTHOR]

Due to the limited of power sensors in smart home devices, how to ensure the identity of sensors and the security of the data transmission is a new challenge to be solved. Based on symmetric polynomial, this paper developed a new solution by using sensor paring table. Firstly, when a sensor sent message to server, the server identified this sensor by the related sensors, and stored the information of the related sensors in the sensor paring table. Then, these related sensors returned the reliability score to the local server. At last, there would be a score for each sensor. When the score was below a certain threshold, the sensor was proved to be abnormal, so as to be cleared timely. This method effectively solves the node identity security problem, and ensures the legitimacy of the access node. [ABSTRACT FROM AUTHOR]

In view of the current university laboratory, traditional management mode exists problems of backward management and low efficiency of management. Especially, the laboratory equipment information management is convenient, there exist safe and efficient problems throughout its life cycle. This paper puts forward to use data mining to obtain all kinds of basic data from the various information management systems, and the use big data, the Internet of things, intelligent sensor, RFID, two-dimensional code, mobile terminal APP new technology to expand the laboratory management system functions by using other auxiliary hardware and software. These measures improve the management level of laboratory equipment, the daily management and maintenance of equipment. Bv information technology, it realizes intelligent management. [ABSTRACT FROM AUTHOR]