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作者： Tianqi Yang Ye Gu Yanbin Sun Changbao Wang Haitao Cheng Shengju Li Lan Li College of Science&College of Life Science Jiamusi University School of Data Science and Software Engineering Wuzhou University

This paper analyzes the distribution of plant resources in the test plots, and aims to optimize the allocation of plants and improve the follow-up construction plan for the cold land ecological park. We provide basis and reference for plant species selection and diversification in the construction of cold land urban Greenland plant landscape, and further improve the urban environment. Taking Jiamusi City as an example, the plant species, ecological distribution and utilization of plant resources in Jiamusi City Park were investigated and investigated by sample method and field investigation method. The data were analyzed by the analytic hierarchy process, and the ornamental value of the regional plants was *** to the survey, there are 41 species of plants in the park in Jiamusi City, belonging to 15 families and 35 genera. Their use involves three aspects, such as edible medicinal, and has high application value. As a typical cold city, Jiamusi proposes to consider the concept of ecological balance and sustainable development while considering the ornamental nature of plant resources, to play a role in supporting the image of the city.

关键词： Impact of Garden Plant Resources Allocation on Ecological Landscape in Cold Cities

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Effects of atrazine on the black community land function and role of microbial ecology

Effects of atrazine on the black community land function and...

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作者： Yaosheng Zhang Long Tian Ruixi Ma Yanxiang Wei Jiali Yang YanBin Sun Lan Li College of Science&College of Life Science Jiamusi University School of Data Science and Software Engineering Wuzhou University

By measuring the concentration of atrazine stress and different culture days, the abundance of key genes in soil nitrogen transformation was studied by means of real-time PCR with the increase of atrazine stress time. The abundance of soil nitrogen-fixing function gene(nif-H) increased significantly with the increase of time in the middle and late culture period(15-30 d), indicating that the abundance of soil nitrogen-fixing function gene was promoted;soil ammonia oxidation. The abundance of functional gene(amo A) was reduced at the low concentration of atrazine(0 mg/kg, 20 mg/kg), and then decreased with increasing stress time,while at high concentration of atrazine. Under the treatment of(100mg/kg), with the increase of time, the abundance of soil ammonia oxidation function increased first and then decreased,indicating that the abundance of soil ammonia oxidation function gene was affected in the process of culture. II Based on high-throughput sequencing technology, the results of soil nitrogen fixation and ammonia oxidation community diversity showed that the functional gene diversity of soil samples was affected by the concentration of atrazine and stress *** to the analysis of soil diversity index, nitrogen-fixing functional genes of soil samples treated with atrazine at 0 mg/kg, 20 mg/kg and 100 mg/kg were tested at the late stage(30 d). The diversity index of(nif-H) was higher than the mid-test(15 d). At the beginning of the experiment(0 d), the ammonia functional gene(amo A) diversity index of soil samples treated with atrazine concentrations of 0 mg/kg, 20 mg/kg and 100 mg/kg was higher than that in the middle of the experiment(15d), studies have shown that the nitrogen and ammonia oxidation functional gene diversity is affected under different concentrations of atrazine stress time. The distribution of the nitrogen-fixing gene(nif-H) and the ammonia-oxidizing functional gene(amo A) in the horizontal sample community structure showed that the nit

关键词： Effects of atrazine on the black community land function and role of microbial ecology

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Multi-operator network sharing for massive IoT

arXiv

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arXiv 2020年

作者： Xiao, Yong Krunz, Marwan Shu, Tao School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China Department of Electrical and Computer Engineering the University of Arizona TucsonAZ85721 United States School of Electrical and Data Engineering University of Technology Sydney UltimoNSW2007 Australia Department of Computer Science and Software Engineering Auburn University AuburnAL36849 United States

A recent study predicts that by 2020, up to 50 billion Internet-of-Things (IoT) devices will be connected to the Internet, straining the capacity of the wireless infrastructure, which has already been overloaded with data-hungry mobile applications. How to accommodate the demand for both massivescale IoT devices and high-speed cellular services in the physically limited spectrum without significantly increasing the operational and infrastructure costs is one of the main challenges for operators. In this article, we introduce a new multi-operator network sharing framework that supports the coexistence of IoT and high-speed cellular services. Our framework is based on the radio access network (RAN) sharing architecture recently introduced by 3GPP as a promising solution for operators to improve their resource utilization and reduce system roll-out cost. We evaluate the performance of our proposed framework using real base station location data in the city of Dublin collected from two major operators in Ireland. Numerical results show that our proposed framework can almost double the total number of supported IoT devices and simultaneously coexist with other cellular services. Copyright © 2020, The Authors. All rights reserved.

关键词： Internet of things

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A Framework of Blockchain-Based Security for WBANs

A Framework of Blockchain-Based Security for WBANs

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Smart BlockChain (SmartBlock), International Conference on

作者： Han Deng Xiangwei Meng Jun Guo Erhui Xi Hui Zhao Big Data Development and Research Center Guangzhou College of Technology and Business Guangzhou China School of Computer science and Engineering Hunan University of Science and Technology Xiangtan China School of Software Engineering Quanzhou University of Information Engineering Quanzhou China Guangzhou College of Technology and Business Guangzhou China Educational Information Technology Laboratory Henan University Kaifeng China

Purposed to collect and store human physiological data, WBANs as a telemedicine system play a significant role in sensor networks. The complex network environment presents a formidable challenge to the stability of the system and the security of the database. The traditional centralized architecture is to store the registration data of the sensor node and the patient's physiological data in the hub node. When the hub node is subjected to Denial of Service attacks (DoS) and Distributed Denial of Service attacks (DDoS), there will be a single point of failure, so that the sensor node cannot establish a communication connection with the hub node. In this paper, a cloud server layer architecture based on blockchain technology is proposed for WBNAs to ensure system stability and patient data security. Meanwhile, Ciphertext-Policy Attribute-Based Encryption (CP-ABE) scheme is used to ensure patient physiological data safety.

关键词： Wireless communication Cloud computing Architecture Distributed databases Blockchain Medical services Permission

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Improving Automated GUI Exploration of Android Apps via Static Dependency Analysis

Improving Automated GUI Exploration of Android Apps via Stat...

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International Conference on software Maintenance (ICSM)

作者： Wunan Guo Liwei Shen Ting Su Xin Peng Weiyang Xie School of Computer Science Fudan University Shanghai China Shanghai Key Laboratory of Data Science Fudan University Shanghai China School of Software Engineering East China Normal University Shanghai China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China

ISBN: (数字)9781728156194

ISBN: (纸本)9781728156200

Exploring GUIs of Android apps plays a key role in many important scenarios such as functional testing (e.g., finding crash errors), security analysis (e.g., identifying malicious behav-iors) and competitive analysis (e.g., storyboarding app features). To automate GUI exploration, existing techniques often try to visit as many GUI pages as possible via specific strategies, e.g., random (like Monkey) or heuristic (like Stoat, A 3 E). However, their effectiveness is still unclear and much under-explored. To this end, we conducted the first study in this paper to understand and characterize their limitations by carefully analyzing the coverage reports from a set of real-world, open-source apps. Through this study, we identified three key limitations due to the lack of dependency knowledge during exploration, i.e., widget-page dependency, widget-widget dependency and system-event dependency. To overcome them, we introduce dependency-informed exploration, an automated approach that leverages static dependency analysis to effectively improve GUI exploration performance. Given an app, our approach first constructs a GUI page transition model that captures the dependencies between GUI widgets, and then guides GUI exploration during a depth-first traversal. We realized our approach as a tool named Gesda, and evaluated it on 70 open-source Android apps. The results show Gesda outperforms existing state-of-the-art GUI exploration techniques, i.e., Monkey and Stoat. Additionally, Gesda uncovers 4 previously unknown crashes in 4 apps as a by-product of GUI exploration due to the benefit of dependency knowledge, while Monkey and Stoat have not discovered them.

关键词： software maintenance Tools Computer crashes Security Open source software Graphical user interfaces Testing

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software defect prediction model based on improved deep forest and AutoEncoder by forest 31

Software defect prediction model based on improved deep fore...

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31st International Conference on software engineering and Knowledge engineering, SEKE 2019

作者： Zheng, Wenbo Mo, Shaocong Jin, Xin Qu, Yili Xie, Zefeng Shuai, Jia School of Software Engineering Xi'an Jiaotong University Xi'an710049 China College of Computer Science and Technology Zhejiang University Hangzhou310027 China School of Management Huazhong University of Science and Technology Wuhan430074 China School of Data and Computer Science Sun Yat-Sen University Guangzhou510006 China School of Computer Science and Technology Wuhan University of Technology Wuhan430070 China

ISBN: (纸本)1891706489

software defect prediction is an important way to make full use of software test resources and improve software performance. To deal with the problem that of the shallow machine learning based software defect prediction model can not deeply mine the software tool data, we propose software defect prediction model based on improved deep forest and autoencoder by forest. Firstly, the original input features are transformed by the data augmentation method to enhance the ability of feature expression, and the autoencoder by forest performs the data of dimensionality reduction on the features. Then, we use the improved deep forest algorithm and autoencoder by forest to build software defect prediction model. The experimental results show that the proposed algorithm has higher performance than the original deep forest (gcForest) algorithm and other existing start-of-art algorithms, and has higher performance and efficiency than other deep learning algorithms. © 2019 Knowledge Systems Institute Graduate school. All rights reserved.

关键词： Learning algorithms

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Boundary-Aware context neural network for medical image segmentation

arXiv

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arXiv 2020年

作者： Wang, Ruxin Chen, Shuyuan Ji, Chaojie Fan, Jianping Li, Ye Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China School of Software Engineering University of Science and Technology of China Shenzhen Institutes of Advanced Technology Shenzhen China

Medical image segmentation can provide a reliable basis for further clinical analysis and disease diagnosis. The performance of medical image segmentation has been significantly advanced with the convolutional neural networks (CNNs). However, most existing CNNs-based methods often produce unsatisfactory segmentation mask without accurate object boundaries. This is caused by the limited context information and inadequate discriminative feature maps after consecutive pooling and convolution operations. In that the medical image is characterized by the high intra-class variation, inter-class indistinction and noise, extracting powerful context and aggregating discriminative features for fine-grained segmentation are still challenging today. In this paper, we formulate a boundary-Aware context neural network (BA-Net) for 2D medical image segmentation to capture richer context and preserve fine spatial information. BA-Net adopts encoder-decoder architecture. In each stage of encoder network, pyramid edge extraction module is proposed for obtaining edge information with multiple granularities firstly. Then we design a mini multi-Task learning module for jointly learning to segment object masks and detect lesion boundaries. In particular, a new interactive attention is proposed to bridge two tasks for achieving information complementarity between different tasks, which effectively leverages the boundary information for offering a strong cue to better segmentation prediction. At last, a cross feature fusion module aims to selectively aggregate multi-level features from the whole encoder network. By cascaded three modules, richer context and fine-grain features of each stage are encoded. Extensive experiments on five datasets show that the proposed BA-Net outperforms state-of-The-Art approaches. Copyright © 2020, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Blockchain-based approach for securing spectrum trading in multibeam satellite systems

arXiv

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arXiv 2020年

作者： Li, Feng Lam, Kwok-Yan Jia, Min Zhao, Jun Li, Xiuhua Wang, Li School of Information and Electronic Engineering Zhejiang Gongshang University Hangzhou310018 China School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore School of Electronics and Information Engineering Harbin Institute of Technology Harbin150080 China School of Big Data & Software Engineering Chongqing University Chongqing401331 China College of Marine Electrical Engineering Dalian Maritime University Dalian116026 China

This paper presents a blockchain-based approach for securing spectrum sharing in multi-beam satellite systems. Satellite spectrum is a scarce resource that requires highly efficient management schemes for optimized sharing by network users. However, spectrum sharing is vulnerable to attacks by malicious protocol participants. In order to ensure efficient spectrum management in the face of dishonest satellite users or cyber attackers, it is important for spectrum sharing mechanism to provide transparency and traceability of the trading process so as to enable the system to detect, and hence eliminate, unauthorized access by malicious users. We address these requirements by proposing the use of blockchain which, apart from its ability to provide transparency and traceability, ensures an immutable means for keeping track of user trading reputation. Besides, in order to address the practical constraints of heterogeneous user nodes, we also propose the use of edge computing to support users with limited computing power. In this paper, we propose a blockchain-based spectrum trading framework and, based on which, a multibeam satellite spectrum sharing algorithm for interference pricing and heterogeneous spectrum demands is devised to improve the efficiency of satellite spectrum. By leveraging on the system characteristics of blockchain, a dynamic spectrum sharing mechanism with traceability, openness and transparency for whole trading process is presented. Numerical results are also provided to evaluate the system benefits and spectrum pricing of the proposed mechanism. © 2020, CC BY.

关键词： Blockchain

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Task Offloading for Automatic Speech Recognition in Edge-Cloud Computing Based Mobile Networks

Task Offloading for Automatic Speech Recognition in Edge-Clo...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Shitong Cheng Zhenghui Xu Xiuhua Li Xiongwei Wu Qilin Fan Xiaofei Wang Victor C. M. Leung School of Big Data & Software Engineering Chongqing University Chongqing China Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong SAR China College of Intelligence and Computing Tianjin University Tianjin China College of Computer Science & Software Engineering Shenzhen University Shenzhen China Dept. Electrical and Computer Engineering The University of British Columbia Vancouver Canada

ISBN: (数字)9781728180861

ISBN: (纸本)9781728180878

Explosively increasing multimedia services and applications, e.g., automatic speech recognition (ASR), have aggravated the burden on the cloud server in mobile networks. To address the challenge, mobile edge computing has emerged for partially alleviating the workload of the cloud server and enhancing the quality of service of mobile users. In this paper, we aim to employ the technique of edge-cloud computing to accelerate the processing of ASR tasks generated by users in mobile networks. Particularly, we deploy a convolutional neural network based encoder in each edge server to extract features of the audio data. Based on certain network constraints (i.e., user association and edge servers' storage/computing capacity), we propose a low-complexity and distributed iterative greedy method to address the formulated nonlinear mixed-integer nonconvex optimization problem. Simulation results demonstrate the effectiveness of the proposed scheme on reducing the total delay in the network.

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Electron Donor Coordinated Metal-Organic Framework to Enhance Photoelectrochemical Performance

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Angewandte Chemie 2023年第33期135卷

作者： Weisu Kong Da Zhu Yong Zhang Rengan Luo Prof. Dr. Jing Ma Prof. Jianping Lei Prof. Huangxian Ju State Key Laboratory of Analytical Chemistry for Life Science School of Chemistry and Chemical Engineering Nanjing University Nanjing 210023 China Contribution: Conceptualization (lead) Data curation (lead) Formal analysis (lead) Investigation (lead) Validation (lead) Writing - original draft (lead) Contribution: Data curation (supporting) Formal analysis (equal) Investigation (equal) Key Laboratory of Mesoscopic Chemistry School of Chemistry and Chemical Engineering Nanjing University Nanjing 210023 China Contribution: Formal analysis (lead) Software (lead) Writing - original draft (supporting) Contribution: Data curation (supporting) Formal analysis (supporting) Investigation (supporting) Contribution: Investigation (equal) Software (lead) Supervision (supporting) Contribution: Formal analysis (supporting) Supervision (supporting)

To enhance photoelectrochemical (PEC) performance, additional electron donor/acceptor is generally required to inhibit the electron-hole recombination. However, the enhancement is limited due to the long-distance diffusion. Herein a self-supplying electron strategy is designed for PEC enhancement by coordinating an electron donor 1.4-diazabicyclo[2.2.2]octane (Dabco) in metal–organic framework (MOF). The intrareticular photoelectron transfer mechanism in mixed-ligand MOF (m-MOF) is experimentally revealed and verified by density functional theory calculations. The presence of Dabco efficiently inhibits the electron-hole recombination due to the self-supplying electrons and longer electron lifetime in the framework, and thus leads to 23.2-fold enhancement of photocurrent. As proof of concept, a simple PEC method is constructed with the designed m-MOF to demonstrate its application in sensitive bioanalysis. This work provides a new avenue for improving the PEC performance of nanomaterials.

关键词： Biosensors Electron Donor Intrareticular Photoelectron Transfer Metal-Organic Frameworks Photoelectrochemistry

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