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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 Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. 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 Frontiers of Computer Science & Technology is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. 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 Hydrographic Surveying & Charting / Haiyang Cehui is the property of Hydrographic Surveying & Charting Editorial Board 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 Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. 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 Sichuan University (Natural Sciences Division) / Sichuan Daxue Xuebao-Ziran Kexueban is the property of Editorial Department of Journal of Sichuan University Natural Science Edition 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 Sichuan University (Natural Sciences Division) / Sichuan Daxue Xuebao-Ziran Kexueban is the property of Editorial Department of Journal of Sichuan University Natural Science Edition 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.)

Traditional load balancing algorithms can't meet the demand of high concurrent requests and quick calling of public network digital trunk. This paper proposed a dynamic load balancing algorithm based on load feedback for distributed digital trunk to achieve load balancing and increase user capacity. Firstly, this paper established monitoring method and monitoring indexes for static and dynamic load of participating MCPTT server. Then, it used weighted round robin algorithm to allocate participating MCPTT server to users and got complex load parameters by dealing user requests. Finally, it updated the weight of participating MCPTT server based on load feedback to dynamically adjust server load. Simulation results show that the proposed algorithm has better load balancing effect, smaller load balancing degree and lower response delay compared with traditional algorithms and other dynamic feedback algorithms. [ABSTRACT FROM AUTHOR]

Copyright of Application Research of Computers / Jisuanji Yingyong Yanjiu is the property of Application Research of Computers Edition 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 Application Research of Computers / Jisuanji Yingyong Yanjiu is the property of Application Research of Computers Edition 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 Application Research of Computers / Jisuanji Yingyong Yanjiu is the property of Application Research of Computers Edition 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.)

Multi-granularity is one of the important research directions in the field of granular computing. It represents the research of problem solving at two or more different granules and already has become a new computing method to solve complex problems. Rough set theory is a kind of computing tool to solve uncertain problems effectively. As one of the core contents of rough set theory，attribute reduction has been widely studied in the fields of data mining，machine learning，and granular computing. It is a meaningful problem to apply the idea of multi-granularity to attribute reduction. The granulation idea in granular computing theory is used to granulate attributes to form multiple granules. Then we evaluate the significance of attribute granules and the significance of attributes in attribute granules based on discernibility matrix. Finally， a multi-granularity attribute reduction algorithm based on these two significance measures is designed. By selecting attributes from different granules， the reduction results obtained by this algorithm are more representative and different. In order to verify the effectiveness of our proposed method，experiments on six data sets show that the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Changes in behavioral activity are increasingly recognized as a useful indicator of dairy cows’ health and welfare. The classifying of changes in behavioral activity can be useful in early detection and prevention of diseases, and monitoring dairy cows’ behavioral activity helps farmers to take a comprehensive view of the dairy cows’ estrus time. The aim of this study is to automatically measure and distinguish several behavior activities of dairy cows from accelerometer data. The study consists of 2 parts, namely, wireless leg sensor and binary decision-tree algorithm. The wireless leg sensor was designed to collect test data, which integrates microcontroller MSP430F149IMP, tri-axial accelerometer ADXL345, and radio frequency module CC1101 to meet the requirements of accurately collecting data of the acceleration of dairy cows, and long-term reliable transmission of data. The binary decision-tree algorithm was designed to classify the behavior of dairy cows. Firstly, 24 statistical features describing the magnitude, symmetry, steepness, variability, uncertainty and angle of the three-axis acceleration of cow legs were selected. Secondly, the best classification behavior category and optimal threshold of each statistical feature were obtained by constructing ROC(receiver operating characteristic) curve. Then the information gain is used as the selection criterion for the split attribute of the binary decision-tree model. Finally, a optimal binary decision tree classification model is constructed to classify and recognize the dairy cow motion behavior. Compared with the traditional binary decision-tree algorithm, the innovation of the algorithm is as follows: Firstly, the ROC curve principle is used to ensure the classification and threshold of each statistical feature to select the local optimal. Then the information gain is used as the split attribute selection standard, and the binary decision-tree classification model is constructed to realize the overall optimal classification of the behavior characteristics of the dairy cows. The results illustrate that the optimal binary decision-tree algorithm can accurately classify 6 types of biologically relevant behavior: standing (88.59% sensitivity, 83.35% precision, and 85.89% F1 score ), lying (85.59% sensitivity, 86.04% precision, and 86% F1 score), normal walking (73.91% sensitivity, 84.25% precision, and 78.74% F1 score), active walking (75.75% sensitivity, 74.46% precision, and 75.1% F1 score), standing up (67.63% sensitivity, 67.81% precision, and 67.72% F1 score), and lying down (66.96% sensitivity, 65.06% precision, and 65.99% F1 score). The highest sensitivity was 88.59% for standing and the sensitivity was good for all classes of behavior except standing up and lying down. The best precision was achieved for standing, lying, and normal walking. The precision for active walking classification was slightly lower but substantially better than those for standing up and lying down. Standing and lying behavior were classified correctly to a high degree, but were also misclassified as other behavior. Normal walking was mainly misclassified as either standing or active walking (18.79% of the cases). Active walking was misclassified most often as standing or normal walking (18.43% of the cases). Standing up and lying down were mostly confused with each other (15.53% and 14.92% of the cases, respectively). The average sensitivity, the average precision and the average F1 score of the classification are 76.47%, 76.83%, and 76.57% respectively. Compared with the traditional ID3 (iterative dichotomiser 3) decision-tree algorithm, they are increased by 5.71 percentage points, 5.4 percentage points and 5.61 percentage points respectively; they are increased by 7.51 percentage points, 8.02 percentage points and 7.77 percentage points respectively compared with the K-means clustering algorithm, and 6.77 percentage points, 6.72 percentage points and 6. 57 percentage points respectively compared with the support vector machine algorithm. The experimental results show that the optimal binary decision-tree algorithm has the characteristics of simple classification rules and high classification accuracy. This research of the method can provide an effective theoretical support for improving the classification accuracy of dairy cow behavior. [ABSTRACT FROM AUTHOR]

Closed cultivation is a new type of cultivation model, which is widely used in solar greenhouse, and it uses EC as the performance index of the regulation process of nutrient solution. In the study, a dynamic analysis was conducted on the regulation process of closed culture nutrient solution with two-step mixed fertilizer characteristics. PID control algorithm was used to control the regulation process of the nutrient solution, and the effects of 6 factors on control process were analyzed through comparative experiment. The results showed that it was difficult to use a precise model to characterize the fertilizer mixing process, since the output liquid flow rate, the fertilizer concentration and the PID parameters had great influence on the control effect of the two-step mixed fertilizer system. Experiments were carried out to find the effect of different output liquid flow rates, fertilizer concentration and the PID parameters, on PID control model. The results were obtained using the fixed variable method and orthogonal tests, under the target electrical conductivity (EC) of 2.3. The experimental results showed that the time of the system decreased with the decrease of the output liquid flow rate or the increase of the fertilizer concentration. Duration of system oscillation and overshoot amount increased with the decrease of the output liquid flow rate or the increase of the fertilizer concentration. Keeping the fertilizer concentration and the PID parameters (obtained under the condition that the output liquid flow rate was 4 m3/h and the fertilizer concentration was 4 channels) unchanged, and the target EC of 2.3, the duration of system oscillation was changed from 15 s to 125 s while the output liquid flow rate was changed from 10 m3/h to 4 m3/h, and, the stable time was changed from 180 s to 205 s and the overshoot was changed from 1% to 20%. Keeping the output liquid flow rate and the PID parameters (obtained under the condition that the output liquid flow rate was 4 m3/h and the fertilizer concentration was 4 channels) unchanged and the target EC of 2.3, the duration of system oscillation was changed from 40 s to 125 s while the number of the fertilizer opening channel was changed from 1 channel to 4 channels, the stable time was changed from 255 s to 205 s, and the overshoot was changed from 3% to 20%. According to the different executive agencies and environmental factors, it was necessary to adjust the PID parameter of the system to achieve better control effect. The closed cultivation system ran with high efficiency and stability using the adjusted PID parameters. According to the test results and analysis, the optimal output liquid flow rate and the concentration of the fertilizer solution in closed culture system with two-step mixed fertilizer were 6 m3/h and 200 g/L, respectively. Under this condition, the PID control parameters were adjusted, and the stability time of the system was 100 s, the overshoot was 3%, and the duration of oscillation was 25 s. In summary, the nutrient solution of the closed type cultivation system with double mixed fertilizer could be regulated by the PID algorithm to achieve stable and efficient operation, which provided a reference for the regulation. [ABSTRACT FROM AUTHOR]