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An improved non-dominated sorting genetic algorithm Ⅱ（NSGA-Ⅱ）for solving the large-scale optimization problem of trajectory planning in the strategic stage is designed. Under the framework of the classic NSGA-Ⅱ，an adaptive crossover operator and an adaptive mutation operator are used to accelerate the convergence speed of the algorithm and improve the quality of the solution，and an evaluation index to measure the pros and cons of the Pareto solution set is given. Considering the introduction of large-scale fourdimensional trajectories inevitably increases the complexity of the problem，this paper proposes an effective strategic conflict resolution model，which aims to minimize the number of potential conflicts and the cost of conflict resolution. Using 1 472 flights during peak hours of China’s air-route network for example verification，the proposed algorithm is compared with the classic NSGA-Ⅱ algorithm and MOEA/D. The experimental results show that the improved NSGA-Ⅱ algorithm has a better optimization effect，can effectively resolve the conflicts between aircraft and produce less trajectory amendment costs. [ABSTRACT FROM AUTHOR]

SM9-IBS is an industry standard for identity-based signature (IBS) algorithms issued by China in 2016. Although the IBS algorithms can be reduce the complexity of management of user keys, they have the problem of key revocation. In addition, the existing technologies are not fully applicable to SM9-IBS due to its special algebraic structure of users’ secret keys. Therefore, this paper proposes an efficient revocable SM9 identity-based signature (shorted as CS-SM9-RIBS) algorithm, which can quickly revoke and update the user’s signature authority. The algorithm introduces a complete subtree, which is used by the key generation center (KGC) generates temporary signature keys for each legitimate user, so that only the signature generated by this key can pass the signature verification. In terms of security, the new algorithm is proven to be existentially unforgeable under adaptive chosen message and identity attacks in the random oracle model. In terms of efficiency, when the number of users in the system is large and the number of revoked users is small in the key update stage, the time cost of the KGC to update the user’s signature key is much smaller than Boneh et al. ’s update technology. [ABSTRACT FROM AUTHOR]

High-clearance plant protection machine plays an important role in the large-scale chemical fertilizer spraying machinery in China. The wheels of high-clearance plant protection machine must be driven along the ridge during the working process. However, the driver's vision is blocked by corn plants, which is easy to cause corn seedlings damaged by tires. In view of the serious phenomenon of seedling injury during the operation of high-clearance plant protection machine, a method of real-time extraction of navigation line between the corn rows based on a dynamic Region of Interest (ROI) was proposed in this paper. According to the different growing periods of corn, the videos were collected when the average height of corn plant was 30, 50 and 70 cm under different light conditions. Through reducing the influence of light by pixel normalization, segmenting the image of corn and background by green image processing algorithm and the maximum class square error method, the images were enhanced and removed by morphological processing. Firstly, the collected image was divided into 10 image bands, and each image band was processed by vertical projection method to locate the center lines between crop rows in the first frame of the video. The approximate position of the static ROI was determined and marked based on the perspective principle of camera and geometric information of the corn seedling belts. It took 473.7 ms to divide the static ROI, which does not affect the real-time performance of navigation since the determined of static ROI was prior to the navigation operation. Secondly, the static ROI was applied in the second frame of video, in which the navigation line between the corn rows was obtained by sub-regional feature points clustering algorithm. According to the geometric information of navigation line and ROI, the ROI was updated and optimized. Then the updated ROI was applied to the navigation line extraction of the next video frame. 225 consecutive videos were selected to divide the ROI manually, and the dynamic ROI obtained by proposed method was compared with the artificial ROI. The pixel deviation between the artificial ROI and the ROI was about 10 pixels, which shown that the algorithm had good convergence and met the requirements of navigation accuracy. Finally, a comparative experiment of artificial navigation line extraction and the algorithm in this paper by randomly selecting 100 frames of image. The results showed that the algorithm proposed by this paper could automatically obtain the dynamic ROI, the average error of navigation line extraction between manual and algorithm in this paper was 1.157°, and the accuracy rate of corn seedling belt recognitionwas 96%, and the average processing time of a real-time image with a resolution of 1 920 pixels×1 080 pixels was 97.56 ms. July 16, 2019, the navigation experiment was carried out in corn field, and the heading angle was used as the input signal of the automatic steering control system. The results showed that the wheels of high-clearance plant protection machine walked along the corn rows, and the wheel angle floated up and down at 0°. The algorithm proposed in this paper can meet the accuracy and real-time requirements of the automatic walking for high-clearance plant protection machine in corn. [ABSTRACT FROM AUTHOR]

Pomegranates are one of the economic fruits in China. The timely detection of pomegranate diseases and the corresponding preventive measures are important to increase crop yields and reduce economic losses. To tackle the issues that traditional edge detection operators usually resulted in low accuracy of the detection of pomegranate diseases and its contour, low anti-noise capability, and created false edges, this study presented an improved Prewitt operator with an adaptive threshold. Firstly, in the image pre-processing stage, the pending image was enhanced by high-frequency emphasize filter, and the high-frequency component, which represented to the details of the pomegranate sample in the image, was increased by the filter. On the contrary, the low-frequency component, which represented to the background of the pomegranate sample, was attenuated to facilitate the following image processing. Since the most original images contained the Gaussian noise, bilateral filtering was used to process the noise present in the image. The weighted average of the brightness values of adjacent pixels was used to represent the intensity of a pixel. The weighted average method was used based on Gaussian distribution. The weight calculation took into account both the Euclidean distance between the pixels and the radiation difference in the pixel range domain to better maintain edge feature information. Secondly, a fifth-order convolutional mask was proposed. The weights of the elements in the mask were set according to the properties of the Gaussian noise probability distribution to reduce the effect of noise on the algorithm. The weight of the central element of the convolutional mask was increased so that the edge information of the image had higher contrast. In terms of gradient calculation, eight direction templates were used to perform the convolutional operation of the image, then the gradient values of each direction were calculated. After that, the corresponding gradient values were obtained, and the gradient values of eight directions were combined into eight groups according to the rule of orthogonality. As a result, there was 90 degrees difference between each group of gradients. Then calculated the L2 norm of each set of gradients, and used the largest value of L2 norm as the gradient of the current pixel. It was shown that it was only necessary to calculate the convolutions in half the direction due to the convolutional results in opposite directions were inverse to each other. The gradients of the rest of the direction could be obtained by its symmetric property. The adaptive threshold was implemented through the minimum error method to decrease the probability of false detection and prune irrelevant details. The mean and variance of the target and background were calculated, meanwhile, the minimum error objective function was obtained according to the principle of the minimum error classification. The value that minimizes the objective function was taken as the optimal threshold. To demonstrate the effectiveness of the method in this paper, 607 test images were manually collected as samples in the natural environment from different angles and different illumination conditions. To further reduce the interference of light changes and suppress background noise, the pending images were converted into grayscale images. Therefore, the algorithm was tested using the converted grayscale images. The experimental results showed that the algorithm proposed in this study achieved a better definition at the edge of the lesion. Compared with the traditional edge detection operator, it achieved a higher recognition accuracy and lower running time. The peak signal to noise ratio of the obtained image was higher, and the obtained edge was complete and accurate. The algorithm proposed in this paper could quickly and accurately detect the area of pomegranate lesions, providing a fundamental reference for the future prevention of pomegranate diseases. [ABSTRACT FROM AUTHOR]

This paper presents a hierarchical PageRank algorithm, which is convenient for parallel calculation, is proposed to calculate the importance of urban train stations in China, and the probability of inverse order coefficients is introduced. It is used to measure the difference between the PageRank ranking of urban train stations and the urban GDP ranking. The smaller the reverse order coefficient, the smaller the difference between the two rankings. Specific data experiments show that the inverse coefficient between the PageRank ranking of urban train stations and the urban GDP ranking is less than 0.5, which indicates that PageRank ranking It is similar to the city GDP ranking, which proves that the PageRank value of the city train station calculated by the hierarchical PageRank algorithm represents its importance [ABSTRACT FROM AUTHOR]

Tomato has become the most cultivated and consumed vegetable crop in the world, and China has become one of the largest producers and consumers of tomatoes in the world. The pectin content in cell wall of tomato during ripening is closely related to fruit hardness, which is one of the important indicators to determine the maturity and reflect the quality of tomato. The requirement of tomato maturity classification and evaluation promotes the development of non-destructive, fast and accurate detection methods of tomato hardness.Hyperspectral imaging integrates spectroscopy and imaging technology in an analysis system, which transfers tomato maturity assessment from subjective, manual classification and measurement methods. Hyperspectral imaging has been widely used in the rapid acquisition of information to classify, detect or identify the quality of various fruits. A novel method for tomato hardness detection based on hyperspectral imaging and modified interval Random Frog was proposed in this paper. Firstly, hyperspectral images of 120 tomato samples in different mature periods were captured by hyperspectral imaging system covering near-infrared region (865.11nm-1 711.71nm). And the hardness data of tomato was obtained by texture analyzer. Secondly, the spectral data were pretreated by multiplicative scatter correction (MSC) and normalized preprocessing to eliminate noise and improve signal-to-noise ratio. The validity of the characteristic wavelength plays a crucial role in the prediction performance of the model. Therefore, we need an effective method to extract the effective wavelength to improve the accuracy of the model. Interval random frog (iRF) algorithm considers all possible spectral wavelengths and ranks all the wavelengths based on selected probability. But one of the disadvantages of this method is large number of iterations and slow convergence. In view of above disadvantages, the traditional iRF algorithm was optimized in terms of constructing initial variable subset method. A modified interval Random Frog (miRF)was proposed to extract the characteristic wavelength effectively. Finally, a prediction model was developed based on partial least squares regression (PLSR) method to detect tomato hardness. The results indicated that the convergence efficiency and accuracy of miRF has a significantly improvement compared with the iRF method. The iRF has selected 100 feature bands, accounting for 40.65% of the full band, and its runtime was 32.1min. miRF has selected 47 feature bands, accounting for 19.1% of the full band, and its runtime was 1.6 min. It can be seen that miRF greatly reduces the running time of the algorithm. The characteristic wavelengths selected by iRF and miRF methods were mainly distributed in 1 582 nm-1 655 nm, followed by 1 160 nm-1 190 nm and 1 353 nm-1 383 nm, indicating that above regions were sensitive bands to tomato hardness. In order to prove the effectiveness of the proposed algorithm, the results of miRF-PLSR were compared with those of iRF-PLSR and SPA-PLSR. The prediction set correlation coefficients (RP) of the SPA-PLSR model and the iRF-PLSR model were 0.803 9 and 0.936 6 respectively. And the RP of miRF-PLSR model was 0.968 5. The root mean square error (RMSEP) of the SPA-PLSR model and the iRF-PLSR model were 0.007 7 kg/mm2 and 0.004 4 kg/mm2respectively. And the RMSEP of miRF-PLSR model was 0.004 0 kg/mm2. The experiments results show that the miRF-PLSR model has the best prediction results in all models. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the lack of accurate and efficient off-topic detection algorithm for the current English composition teaching system in China, this paper proposed an off-topic detection algorithm based on LDA and word2vec. The algorithm used LDA to model the documents and trained it with word2vec, with obtained semantic relation between document’s topic and words, calculated the probability weighted sum of each topic and its feature words in the document. Finally, by setting reasonable threshold, it selected the off-topic essays. According to the different F values for the different number of topics in the document, it determined the optimum number of topics in the experiment. The experimental results show that, compared to traditional vector space model, the proposed method can detect more off-topic essays with higher accuracy, and the F value is above 89%, which realizes the intelligent processing of off-topic essays detection, and may applies effectively in English essays teaching. [ABSTRACT FROM AUTHOR]

Technological developments and changes in relative prices lead to changes in the entire production structure. It is not easy to inversely derive the causes of changes from given changes of input-output coefficient matrix. RAS algorithm is a method to update and levelling typical input-out table. The paper attempts to expand this algorithm for the analysis model of changes in the industrial structure, and to decompose the input coefficient changes into column-specific, row-specific and cell-specific changes without setting industrial structure changes by demand-driven or supply-driven in advance. After that, quantitative analysis about changes in the industrial structure and the reasons of them in China is done in this paper. We find that while industrial structure in China is developing sophisticatedly, labor-intensive industries grow in a high rate, which reflects imbalanced regional development of Chinese economy, and the effect of internalization from industrial upgrading into regional industrial transfer. [ABSTRACT FROM AUTHOR]

With the development of Internet, aquaculture information is increasing rapidly in decade years in both internet and the Internet of Things (IoT). Now users are confronted with the information overload, and most of the information has not been effectively utilized. In order to select requested resource for specific users from ubiquitous resource, an aquaculture recommender system was built in this paper. Several IoTs had been deployed in many provinces of China, like Beijing, Jiangsu and Shandong. What's more, an IoT platform was established to collect IoT environment information in real time and crawl aquaculture information from Internet. In this research, item based collaborative filtering algorithm was combined with Web usage mining to generate recommendation. Web usage mining technology processed Web logs in host server and analyzed browsing behavior of users to establish user preference model. Furthermore, item based collaborative filtering used collective intelligence to recommend items that was similar with the items user prefers. The producers of this research were as follows. First, an aquaculture household interest questionnaire was designed after field research with aquaculture households. The questionnaire included user basic investigation, pond basic investigation and user interest investigation. Second, users rated the items in the questionnaire according to their interests. These items included aquaculture technology, fish disease prevention knowledge, government policies, pond production information, disease warning information, weather information, information output prediction and fault information etc. So that user tendency was initialized through the questionnaire and system registration. Third, further user interest could be collected in the form of Web logs. Web logs recorded user browsing behavior, such as user name, IP, access date and time and visited pages. User browsing behavior indicated user interests. To a certain extent, the longer time user browsers a page, the more interest user have. This technology was called Web usage mining. After user initial model and Web usage mining, the user-item rating matrix was calculated. Fourth, item-based collaborative filtering calculated the similarity between two items. The methods of similarity calculation mainly included Pearson similarity, cosine similarity, general modified cosine similarity and improved modified cosine similarity. Considering different user rating behaviors, some users would rate much higher or lower score than the average. So improved modified cosine similarity method was used to reduce the impact of user rating behavior. Using this method, all ratings of one user would be divided by highest rating, and the new user-item rating matrix was obtained. Fifth, the prediction rating from users to items was produced based on item similarity. The recommendation system pushed the items with highest prediction rating to the corresponding users using the top neighborhood method. Finally, this research was evaluated by mean absolute error. Results showed that when recommend items were more than 4, MAE of improved modified cosine method were the least in all methods. So that, the improved modified cosine method (IMCM) was chosen to calculate item similarity. In conclusion, the cold start problem of recommender system could be solved by initial user interest like user registration and questionnaire investigation. And the IMCM method improves the accuracy by reducing impact of user behavior. The aquaculture system recommends precisely according to user interest from both Internet and Internet of Things (IoT), such as trading information, farming technology, government policies and Internet of Things data. There are further works to do in the future. Context aware can be taken into consideration to improve recommendation precision, such as time, location and fault information in pond. Time presents the different production season of aquatic products; location presents where the pond is; and the fault information presents the abnormal status of IoT in pond. [ABSTRACT FROM AUTHOR]

As to the applied range and optimization of grey forecast model, according to the principle that grey GM(1,1) model's parameters are grey and adjustable, the connotation model and parameter packet formulas of GM(1,1, β) were put forward in this paper, and some properties of the model and model's optimization algorithm was analyzed. The results show that the objective valuing region of parameter a of GM(1,1, β) model is (-∞+ ∞), and the objective valuing region of parameter a of GM(1,1) model is (- 2,+2), the objective valuing region of parameter a is determined by the background value coefficient, and it has nothing with raw data sequence; GM(1,1, β) grey differential equation completely suits for the homogeneous exponential function series. Finally, the example of simulating and forecasting the per capita income of urban dwellers in China shows that the grey differential equation GM(1,1, β) is valid. [ABSTRACT FROM AUTHOR]

In view of the situations that the locations of high-speed rail terminals in some cities are far from the city centers, this paper put forward an approach to design feeder bus lines considering two aspects of demands. One is recent demand for transporting high-speed rail passengers between city centers and rail terminals; the other is long-term demand for directly connecting the bus system in city centers and the bus system in the emerging city unit around rail terminals. The optimization model for selecting the bus lines was built based on the two aspects of demands and then the related solution ant-colony algorithm was designed. The case of designing the feeder bus lines for anting rail terminals on Shanghai-Nanjing intercity railway was used to illustrate the model and the algorithm. The index showed the optimized feeder bus lines have the characters of quick and reliable service quality and good potential for the transition to express lines in the future. [ABSTRACT FROM AUTHOR]

Based on the origin-destination-based Frank-Wolfe algorithm proposed by Anthony Chen (2002) which means the shortest-path of all OD pairs with the same origin was searched in the algorithm at one time and the link flow was updated by using one-OD-at-a-time flow update strategy, the initialization, linear search and shortest path search of ODBFW algorithm was improved in this paper, and the improved ODBFW algorithm was proposed. The improved ODBFW algorithm was used for Sioux Falls network which was common used in international similar researches and the road network of Zhucheng City, Shandong Province, China to compare the feasibility, efficiency and stability of the standard FW algorithm, ODBFW algorithm and improved ODBFW algorithm. The results indicated that the improved ODBFW algorithm has more efficiency and stability than standard FW algorithm. The time used for the improved ODBFW algorithm to reach convergence is nearly 15% less than the time used for the original algorithm in small road network, and is nearly 5% less than that in large road network. [ABSTRACT FROM AUTHOR]