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| 1 | CNN intelligent early warning for apple skin lesion image acquired by infrared video sensors显示文摘Video sensors and agricultural IoT(internet of things) have been widely used in the informationalized orchards.In order to realize intelligent-unattended early warning for disease-pest,this paper presents convolutional neural network(CNN) early warning for apple skin lesion image,which is real-time acquired by infrared video sensor.More specifically,as to skin lesion image,a suite of processing methods is devised to simulate the disturbance of variable orientation and light condition which occurs in orchards.It designs a method to recognize apple pathologic images based on CNN,and formulates a self-adaptive momentum rule to update CNN parameters.For example,a series of experiments are carried out on the recognition of fruit lesion image of apple trees for early warning.The results demonstrate that compared with the shallow learning algorithms and other involved,wellknown deep learning methods,the recognition accuracy of the proposal is up to 96.08%,with a fairly quick convergence,and it also presents satisfying smoothness and stableness after convergence.In addition,statistics on different benchmark datasets prove that it is fairly effective to other image patterns concerned. | 谭文学 Zhao Chunjiang Wu Huarui | 2016 | High Technology Letters2016，22，1： | 3 |
| 2 | Advanced agricultural disease image recognition technologies: A review显示文摘Agricultural disease image recognition has an important role to play in the field of intelli-gent agriculture.Some advanced machine learning methods associated with the develop-ment of artificial intelligence technology in recent years,such as deep learning and transfer learning,have begun to be used for the recognition of agricultural diseases.However,the adoption of these methods continues to face a number of important challenges.This paper looks specifically at deep learning and transfer learning and discusses the recent progress in the use of these advanced technologies for agricultural disease image recognition.Anal-ysis and comparison of these two methods reveals that current agricultural disease data resources make transfer learning the better option.The paper then examines the core issues that require further study for research in this domain to continue to progress,such as the construction of image datasets,the selection of big data auxiliary domains and the optimization of the transfer learning method.Creating image datasets obtained under actual cultivation conditions is found to be especially important for the development of practically viable agricultural disease image recognition systems. | Yuan Yuan Lei Chen Huarui Wu Lin Li | 2022 | Information Processing in Agriculture2022，9，1： | 2 |
| 3 | Revisiting the role of delta-1-pyrroline-5-carboxylate synthetase in drought-tolerant crop breeding显示文摘The delta-1-pyrroline-5-carboxylate synthetase(P5CS)gene exercises a protective function in stressed plants.However,the relationship between proline accumulation caused by P5CS and abiotic stress tolerance in plants is not always clear,as P5CS overexpression has been reported to repress plant growth under normal conditions in several reports.We re-evaluated the role of P5CS in drought-tolerant rice breeding by expressing the AtP5CS1 and feedback-inhibition-removed AtP5CS1(AtP5CS1^(F128A))genes under the regulation of an ABA-inducible promoter to avoid the potential side effects of P5CS overexpression under normal conditions.ABA-inducible AtP5CS1 and AtP5CS1^(F128A) increased seedling growth in a nutrient solution(under osmotic stress)and grain yield in pot plants.However,the evidently deleterious effects of AtP5CS1 on grain quality,tiller number,and grain yield in the field indicated the unsuitability of P5CS for drought-tolerance breeding. | Xuanjun Feng Yue Hu Weixiao Zhang Rongqian Xie Huarui Guan Hao Xiong Li Jia Xuemei Zhang Hanmei Zhou Dan Zheng Ying Wen Qingjun Wang Fengkai Wu Jie Xu Yanli Lu | 2022 | The Crop Journal2022，10，4： | 2 |
| 4 | Non-uniform clustering routing protocol of wheat farmland based on effective energy consumption显示文摘Wireless sensor network(WSN)can achieve real-time data collection and transmission of environment,soil,meteorology,crop physiology and other information in agriculture.The data provided by WSN could be used for decision making and management,which is very important in precision agriculture.Wheat farmland wireless sensor network has the characteristics of wide coverage area,long planting period,inconvenient energy supply,and serious impact of crop environment on wireless signal transmission.Routing protocol is an important method to achieve long-term WSN monitoring by selecting an appropriate path with low energy consumption for data transmission.According to the phenomenon of uneven environment and channel parameters caused by intensive crop growth in farmland,a non-uniform clustering routing protocol based on effective energy consumption(UCEEC)was proposed in this work.The method combined with the characteristics of multi-path fading of farmland environment signals.The idea of image segmentation was introduced.Nodes with high similarity were divided into a cluster area by the dissimilarity between nodes in order to improve the intracluster communication performance.Meanwhile,a multi-hop path selection method between cluster-heads based on the estimation of two-hop effective energy consumption is designed.The energy consumption cost factor is calculated by the effective energy consumption and the average energy consumption within the cluster to achieve the minimum and balance of the overall energy consumption of the network.Simulation results show that,compared with the existing Maximum Residual Energy Based Routing(MREBR)protocol,minimum Energy Consumption Based Routing(MEC)routing protocols,UCEEC improves the energy balance effect between nodes,prolongs the network life cycle,and realizes efficient energy utilization of wireless sensor network data collection in the complex environment of wheat field. | Yisheng Miao Chunjiang Zhao Huarui Wu | 2021 | International Journal of Agricultural and Biological Engineering2021，14，3： | 1 |
| 5 | Plant G proteins interact with endoplasmic reticulum luminal protein receptors to regulate endoplasmic reticulum retrieval显示文摘Maintaining endoplasmic reticulum(ER) homeostasis is essential for the production of biomolecules.ER retrieval, i.e., the retrograde transport of compounds from the Golgi to the ER, is one of the pathways that ensures ER homeostasis. However, the mechanisms underlying the regulation of ER retrieval in plants remain largely unknown. Plant ERD2-like proteins(ERD2 s) were recently suggested to function as ER luminal protein receptors that mediate ER retrieval. Here, we demonstrate that heterotrimeric G protein signaling is involved in ERD2-mediated ER retrieval. We show that ERD2 s interact with the heterotrimeric G protein Ga and Ggsubunits at the Golgi. Silencing of Ga, Gb, or Gg increased the retention of ER luminal proteins. Furthermore,overexpression of Ga, Gb, or Gg caused ER luminal proteins to escape from the ER, as did the co-silencing of ERD2 a and ERD2 b. These results suggest that G proteins interact with ER luminal protein receptors to regulate ER retrieval. | Shanshan Wang Ke Xie Guoyong Xu Huarui Zhou Qiang Guo Jingyi Wu Zengwei Liao Na Liu Yan Wang Yule Liu | 2018 | Journal of Integrative Plant Biology2018，60，7： | 1 |
| 6 | Optimization of energy heterogeneous cluster-head selection in farmland WSN 显示文摘 | Miao Yisheng Yuan Ling Wu Huarui | 2014 | Applied Mechanics and Materials2014，441，： | 1 |
| 7 | An improved method of DV-Hop loca- lization algorithm 显示文摘 | Wu Huarui Gao Ronghua | 2011 | Journal of Computational Information Sys- tems2011，7，7： | 1 |
| 8 | Asymptotic Analysis of Transmission Capacities for Overlaid Spread-Spectrum Wireless Networks显示文摘We study the transmission capacities of two coexisting spread-spectrum wireless networks (a primary network vs. a secondary network) that operate in the same geographic region and share the same spectrum. We defi ne transmission capacity as the product among the density of transmissions, the transmission rate, and the successful transmission probability. The primary (PR) network has a higher priority to access the spectrum without particular considerations for the secondary (SR) network, while the SR network limits its interference to the PR network by carefully controlling the density ofits transmitters. Considering two types of spread-spectrum transmission schemes (FH-CDMA and DS-CDMA) and the channel inversion power control mechanism, we quantify the transmission capacities for these two networks based on asymptotic analysis. Our results show that if the PR network permits a small increase ofits outage probability, the sum transmission capacities of the two networks (i.e., the overall spectrumefficiency per unit area) will be boosted significantly over that of a single network. | Huarui Wu Di Li Changchuan Yin | 2010 | China Communications2010，7，3： | 1 |
| 9 | Irrigation decision model for tomato seedlings based on optimal photosynthetic rate显示文摘Soil moisture is a major environmental factor that influences tomato growth and development.Suitable soil moisture not only increases tomato production but also saves irrigation water.In this study,an irrigation decision model was developed,which called soil moisture regulation model,for optimizing growth of tomato seedlings while saving water.The data used for modeling were collected from a multi-gradient nested experiment,in which temperature,photosynthetic photon flux density(PPFD),carbon dioxide(CO2)concentration and soil moisture were variables and the corresponding photosynthetic rate was measured.Subsequently,a prediction model of tomato photosynthetic rate was constructed using support vector regression(SVR)algorithm.With photosynthetic rate prediction model as fitness function,genetic algorithm(GA)was used to find the optimal soil moisture under each combination of the above environmental factors.Finally,back propagation neural network(BPNN)algorithm was used to establish a decision model of tomato irrigation,which could provide the optimal soil moisture under current environment.For the soil moisture regulation model constructed here,the coefficient of determination was 0.9738,the mean square error of the test set was 1.51×10-5,the slope of the verified straight line was 0.9752,and the intercept was 0.00916.This model demonstrated high precision,which thereby provides a theoretical basis for accurate irrigation control in the greenhouse facility environment. | Xiangbei Wan Bin Li Danyan Chen Xingyue Long Yifei Deng Huarui Wu Jin Hu | 2021 | International Journal of Agricultural and Biological Engineering2021，14，5： | 1 |
| 10 | Layout Optimization for Greenhouse WSN Based on Path Loss Analysis显示文摘When wireless sensor networks (WSN) are deployed in the vegetablegreenhouse with dynamic connectivity and interference environment, it is necessary to increase the node transmit power to ensure the communication quality,which leads to serious network interference. To offset the negative impact, thetransmit power of other nodes must also be increased. The result is that the network becomes worse and worse, and node energy is wasted a lot. Taking intoaccount the irregular connection range in the cucumber greenhouse WSN, wemeasured the transmission characteristics of wireless signals under the 2.4 Ghzoperating frequency. For improving network layout in the greenhouse, a semiempirical prediction model of signal loss is then studied based on the measureddata. Compared with other models, the average relative error of this semi-empiricalsignal loss model is only 2.3%. Finally, by combining the improved networktopology algorithm and tabu search, this paper studies a greenhouse WSN layoutthat can reduce path loss, save energy, and ensure communication quality. Giventhe limitation of node-degree constraint in traditional network layout algorithms,the improved algorithm applies the forwarding constraint to balance network energyconsumption and constructs asymmetric network communication links. Experimentalresults show that this research can realize the energy consumption optimization ofWSN layout in the greenhouse. | Huarui Wu Huaji Zhu Xiao Han Wei Xu | 2021 | Computer Systems Science & Engineering2021，37，4： | 0 |
| 11 | Mn-based MXene with high lithium-ion storage capacity显示文摘3d-transition metal(Fe,Co,Ni,and Mn)-based MXene materials have been predicted to demonstrate exceptional electrochemical performance because of their good electrical conductivity and the presence of metallic atoms with multiple charge states.However,until now,there have been no reports on MXenes based on Fe,Co,Ni,and Mn,due to the lack of 3d-metal-layered precursors.Herein,we successfully synthesized the first 3d-transition metal-based MXenes,Mn_(2)CT_(x) by exfoliating a layered precursor derived from the anti-perovskite bulk Mn3GaC.The as-prepared Mn_(2)CT_(x) MXene nanosheets were employed as anode materials in lithium-ion batteries,which exhibited stable storage capacity of 764.7 mAh·g^(-1) at 0.5 C,placing its storage capacities at an upper-middle level compared with other reported MXene materials as well as other Mn-based anode materials.Overall,this study opens a new avenue for MXene research by synthesizing 3d-transition metal-based MXenes for electrochemical applications. | Yanyan Wu Dongqing Liu Xiaonan Wang Usman Ghani Muhammad Asim Mushtaq Jinfeng Yang Huarui Sun Panagiotis Tsiakaras Xingke Cai | 2024 | Nano Research2024，17，5： | 0 |
| 12 | Cow behavior recognition based on image analysis and activities显示文摘For the rapid and accurate identification of cow reproduction and healthy behavior from mass surveillance video,in this study,400 head of young cows and lactating cows were taken as the research object and analyzed cow behavior from the dairy activity area and milk hall ramp.The method of object recognition based on image entropy was proposed,aiming at the identification of motional cow object behavior against a complex background.Calculating a minimum bounding box and contour mapping were used for the real-time capture of rutting span behavior and hoof or back characteristics.Then,by combining the continuous image characteristics and movement of cows for 7 d,the method could quickly distinguish abnormal behavior of dairy cows from healthy reproduction,improving the accuracy of the identification of characteristics of dairy cows.Cow behavior recognition based on image analysis and activities was proposed to capture abnormal behavior that has harmful effects on healthy reproduction and to improve the accuracy of cow behavior identification.The experimental results showed that,through target detection,classification and recognition,the recognition rates of hoof disease and heat in the reproduction and health of dairy cows were greater than 80%,and the false negative rates of oestrus and hoof disease were 3.28%and 5.32%,respectively.This method can enhance the real-time monitoring of cows,save time and improve the management efficiency of large-scale farming. | Gu Jingqiu Wang Zhihai Gao Ronghua Wu Huarui | 2017 | International Journal of Agricultural and Biological Engineering2017，10，3： | 0 |
| 13 | Reliable and broad-range layer identification of Au-assisted exfoliated large area MoS_(2)and WS_(2)using reflection spectroscopic fingerprints显示文摘The emerging Au-assisted exfoliation technique enables the production of a wealth of large-area and high-quality ultrathin two dimensional(2D)crystals.Fast,damage-free,and reliable determination of the layer number of such 2D films can greatly promote layer-dependent physical studies and device applications.Here,an optical method has been developed for simple,high throughput,and accurate determination of the layer number for Au-assisted exfoliated MoS_(2)and WS_(2)films in a broad thickness range.The method is based on quantitative analysis of layer-dependent white light reflection spectra(WLRS),revealing that the intensity of exciton-induced reflection peaks can be used as a clear indicator for identifying the layer number.The simple yet robust method will facilitate fundamental studies on layer-dependent optical,electrical,and thermal properties and device applications of 2D materials.The technique can also be readily combined with photoluminescence(PL)and Raman spectroscopies to study other layer-dependent physical properties of 2D materials. | Bo Zou Yu Zhou Yan Zhou Yanyan Wu Yang He Xiaonan Wang Jinfeng Yang Lianghui Zhang Yuxiang Chen Shi Zhou Huaixin Guo Huarui Sun | 2022 | Nano Research2022，15，9： | 0 |
| 14 | Intelligent Recommendation and Matching Method for Agricultural Knowledge Based on Context-Aware Models显示文摘The personalized recommendation of the cloud platform for agricultural knowledge and agricultural intelligent service is one of the core technologies for the development of smart agriculture.Revealing the implicit laws and dynamic characteristics of agricultural knowledge demand is a key problem to be solved urgently.In order to enhance the matching ability of knowledge recommendation and service in human-computer interaction of cloud platform,the mechanism of agricultural knowledge intelligent recommendation service integrated with context-aware model was analyzed.By combining context data acquisition,data analysis and matching,and personalized knowledge recommendation,a framework for agricultural knowledge recommendation service is constructed to improve the ability to extract multidimensional information features and predict sequence data.Using the cloud platform for agricultural knowledge and agricultural intelligent service,this research aims to deliver interesting video service content to users in order to solve key problems faced by farmers,including planting technology,disease control,expert advice,etc.Then the knowledge needs of different users can be met and user satisfaction can be improved. | Chang Liu Huarui Wu Huaji Zhu Yisheng Miao Jingqiu Gu Chunjiang Zhao | 2023 | Journal of Beijing Institute of Technology2023，32，3： | 0 |
| 15 | Multi-Task Timing Assignment Algorithm for Intelligent Production of Vegetables in Open Field显示文摘Vegetable production in the open field involves many tasks,such as soil preparation,ridging,and transplanting/sowing.Different tasks require agricultural machinery equipped with different agricultural tools to meet the needs of the operation.Aiming at the coupling multi-task in the intelligent production of vegetables in the open field,the task assignment method for multiple unmanned tractors based on consistency alliance is studied.Firstly,unmanned vegetable production in the open field is abstracted as a multi-task assignment model with constraints of task demand,task sequence,and the distance traveled by an unmanned tractor.The tight time constraints between associated tasks are transformed into time windows.Based on the driving distance of the unmanned tractor and the replacement cost of the tools,an expanded task cost function is innovatively established.The task assignment model of multiple unmanned tractors is optimized by the consensus based bundle algorithm(CBBA)with time windows.Experiments show that the method can effectively solve task conflict in unmanned production and optimize task allocation.A basic model is provided for the cooperative task of multiple unmanned tractors for vegetable production in the open field. | Huarui Wu Huaji Zhu Jingqiu Gu Wei Guo Ning Zhang Xiao Han | 2023 | Journal of Beijing Institute of Technology2023，32，3： | 0 |
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