无人机静电喷雾治理开放性粉尘的数值模拟

将静电喷雾技术与无人机技术相结合用于治理开放性粉尘,使用Fluent对粉尘的扩散模型进行数值模拟.模拟得出无人机工作高7m,喷雾压力为0.2MPa时,无人机静电喷雾的平均降尘效率能达到85.87％,并在自然风速为1m/s、空气相对湿度为70％时,局部区域的降尘效率高达95.93％.本文提出的无人机静电喷雾控制开放性粉尘...     

基于六旋翼无人机搭载风速仪的边界层风剖面实测研究

对基于六旋翼无人机搭载风速仪进行边界层风场测量的可行性进行了研究,分析了实测得到的平均风速和风向角、湍流度、阵风因子、湍流积分尺度与功率谱密度等风场特性参数,并与测风塔上固定安装的风速仪测量结果进行比较。结果表明:基于无人机方法所测得的风速风向值经过修正后与测风塔实测值基本一致,两者误差在±3%以内;基于无人机方法所测风速拟合的风剖面精度较高,且与规范规定的B类地貌风剖面接近,其拟合计算的平均地面粗糙度为0.148;基于无人机方法所测得的各项脉动风特性参数与测风塔的实测值较为接近,两者误差控制在±5%以内;湍流度与阵风因子存在指数相关性;基于无人机方法所测得的脉动风速功率谱与测风塔所测脉动风速功率谱基本一致,且与Karman谱有较好的吻合。     

Power Optimized Multiple-UAV Error-Free Network in Cognitive Environment

Many extensive UAV communication networks have used UAV cooperative control. Wireless networking services can be offered using unmanned aerial vehicles (UAVs) as aerial base stations. Not only is coverage maximization, but also better connectivity, a fundamental design challenge that must be solved. The number of applications for unmanned aerial vehicles (UAVs) operating in unlicensed bands is fast expanding as the Internet of Things (IoT) develops. Those bands, however, have become overcrowded as the number of systems that use them grows. Cognitive Radio (CR) and spectrum allocation approaches have emerged as a potential approach for resolving spectrum scarcity in wireless networks, and hence as technological solutions for future generations, from this perspective. As a result, combining CR with UAVs has the potential to give significant benefits for large-scale UAV deployment. The paper examines existing research on the subject of UAV covering and proposes a multi-UAV cognitive-based error-free model for energy-efficient communication. Coverage maximization, power control, and enhanced connection quality are the three steps of the proposed model. To satisfy the desired signal-to-noise ratio, the covering zone efficacy is investigated as a function of the distance among UAVs stationed in a specific geographic region depending on multiple deployment configurations like as rural, suburban, and urban macro deployment scenarios of the ITU-R M.2135 standard (SNR).     

Governance assessment of UAV implementation in Kenyan land administration system

The ‘fit-for-purpose’ (FFP) approach was developed to respond to the challenges that the creation of a sustainable land administration system (LAS) faces. FFP has proved its value in integrating technological innovations such as unmanned aerial vehicles (UAVs) in LAS. Technological innovations need to consider the governance context when being implemented. Understanding the relevance of the FFP approach and acknowledging the importance of the governance context, this research applies the ‘Fit-for-purpose governance assessment framework’ (FGAF). FGAF helps to understand the challenges that the implementation of UAVs can face in the LAS in Kenya. This governance assessment is based on 16 semi-structured in-depth interviews, three one-day workshops with local stakeholders and UAVs pilot studies to test the technology. The findings suggest that there are major and minor challenges concerning different attributes of FFP qualities. The governance context across counties is fragmented with a high degree of uncertainty and uneven capacity conditions. There are overlapping responsibilities and trust issues among the different actors. Participation of private and non-governmental actors is limited. Yet, steps have been taken toward the adoption of innovative approaches. Although financial resources are limited, the diversity of local and international stakeholders can work as a leverage point to support the implementation of UAVs in the mid and long-term.     

基于地面站辅助的无人机自主架线系统

将无人机（unmanned aerial vehicle, UAV）技术用于实现电力线展放正逐步成为电力行业发展的主要趋势,研究无人机自主架线技术能够有效提高作业效率、降低施工成本和保障工人安全。但现阶段无人机架线技术面临的问题主要有：1）大多数无人机依赖人工操控或地面站发布航点控制,智能化水平低,长期作业会给电力工人带来较强负荷;2）无人机缺乏自主避障能力且感知能力不足,电线、电杆等障碍物会对其造成安全隐患。为解决上述问题,首先,构建了无人机自主架线系统的硬件框架和以ROS（robot operating system,机器人操作系统）为基础的模块化软件框架,并在此基础上实现了架线任务规划算法和架线弓检测算法等,使无人机具备稳定的自主架线能力。然后,利用碰撞检测方法构建了无人机碰撞模型,并提出了无人机路径规划算法,同时引入地面站辅助避障策略,以有效提高无人机的安全性。实验结果表明：所设计的无人机自主架线系统的软、硬件框架合理,架线任务规划算法能帮助无人机高效稳定地完成自主架线任务;地面站能够实时监控无人机状态,并在必要时及时辅助无人机避障,最大程度地保证了无人机的安全。所设计系统安全可靠,可满足实际电力架线作业的需求。     

Research on Operation of UAVs in Non-isolated Airspace

In order to explore the safe operation of UAVs in non-segregated airspace, a collision risk model for cylindrical UAVs based on conflict areas was constructed and the risk of conflict between manned and unmanned aerial vehicles was researched. According to the results of risk analysis, a strategy for solving the conflict of aircraft is proposed, and the risk assessment experiment of unmanned aerial vehicle (UAV) in non-isolated airspace conflict is carried out. The results show that under the experimental conditions, large unmanned aerial vehicles equipped with ADS-B, TCAS and other airborne sensing systems will indeed interfere with other aircraft in airspace when they enter non-isolated airspace. Especially when the number of aircraft in airspace is large, the automatic avoidance system of UAV will increase the avoidance time and trigger the safety alarm, but the safety level is still acceptable. This indicates that it is relatively safe for UAVs to enter non-isolated airspace under limited conditions. The results can be used as a reference for the safe operation of unmanned aerial vehicle (UAV) in non-isolated airspace.     

Optimum design of three-dimensional behavioural decentralized controller for UAV formation flight

This article proposes a behavioural decentralized approach that allows an unmanned aerial vehicle (UAV) formation flight to carry out a waypoint-passing mission effectively. The objective of the proposed controller is to make each UAV in the formation fly through predefined waypoints while maintaining its distance from other UAVs. To perform these two tasks, which can conflict with each other, coupled dynamics of UAVs is considered; this combines the dynamics of all the members in the formation. To apply the behavioural decentralized controller on the basis of the coupled dynamics, a feedback linearization technique with a diffeomorphic transfer map is derived for a three-dimensional UAV kinematics model. A behavioural approach in which the control input is decided by the relative weight of each UAV's desired behaviour is considered, so that the UAVs can react promptly in various situations. Optimization techniques of the gain matrices are also performed to improve the performance of the formation flight using eigen-structure analysis and Cholesky decomposition. To verify the performance of the proposed controller, numerical simulation is performed for a waypoint-passing mission of multiple UAVs.     

Barriers to the adoption of new technologies in rural areas: The case of unmanned aerial vehicles for precision agriculture in India

Technological advances can significantly transform agrarian rural areas by increasing productivity and efficiency while reducing labour intensive processes. For instance, the usage of Unmanned Aerial Vehicles (UAVs) can offer flexibility collecting real-time information of the crops enabling farmers to take timely decisions. However, little is known about the barriers to the adoption of such technologies by rural farmers in emerging economies like India. Building on an extensive literature review, focussed group discussions, and field visits, the barriers impacting the adoption are identified and classified into technical, social, behavioural, operational, economic, and implementation categories. The relevance of each barrier and its importance is evaluated using a hybrid multi-criteria framework built on the theory of Fuzzy Delphi and Fuzzy Analytical Hierarchy Process to identify the most crucial barriers to the adoption of UAVs to implement precision agriculture in rural India. The paper suggests new avenues for accelerating technology adoption in rural areas of emerging economies.     

A Secure Communication Protocol for Unmanned Aerial Vehicles

Mavlink is a lightweight and most widely used open-source communication protocol used for Unmanned Aerial Vehicles. Multiple UAVs and autopilot systems support it, and it provides bi-directional communication between the UAV and Ground Control Station. The communications contain critical information about the UAV status and basic control commands sent from GCS to UAV and UAV to GCS. In order to increase the transfer speed and efficiency, the Mavlink does not encrypt the messages. As a result, the protocol is vulnerable to various security attacks such as Eavesdropping, GPS Spoofing, and DDoS. In this study, we tackle the problem and secure the Mavlink communication protocol. By leveraging the Mavlink packet’s vulnerabilities, this research work introduces an experiment in which, first, the Mavlink packets are compromised in terms of security requirements based on our threat model. The results show that the protocol is insecure and the attacks carried out are successful. To overcome Mavlink security, an additional security layer is added to encrypt and secure the protocol. An encryption technique is proposed that makes the communication between the UAV and GCS secure. The results show that the Mavlink packets are encrypted using our technique without affecting the performance and efficiency. The results are validated in terms of transfer speed, performance, and efficiency compared to the literature solutions such as MAVSec and benchmarked with the original Mavlink protocol. Our achieved results have significant improvement over the literature and Mavlink in terms of security.     

Trajectory optimization for unmanned aerial vehicle formation reconfiguration

The results of trajectory optimization to reconfigure unmanned aerial vehicle (UAV) formation in the event of a critical failure are presented. The formation reconfiguration process includes two distinct manoeuvres: an escape manoeuvre for a malfunctioning UAV and a replacement movement for an alternative UAV related to its position. This article deals with both manoeuvres but focuses more on the replacement movement. The trajectory optimization problem of the escape manoeuvre is formulated as a minimum-time problem to reduce the possibility of collisions resulting from a failure, whereas the problem of the replacement movement is formulated as a final-time fixed minimum-fuel problem to secure the durability of the group of UAVs. These problems are solved by means of sequential quadratic programming. To evaluate the performance of the optimization results, fuel consumption for the replacement movement is considered and optimization of a three-phase reference trajectory is performed. The results show that the trajectory optimization reduces the fuel consumption and saves time.     

Efficient UAV Communications: Recent Trends and Challenges

Unmanned Ariel Vehicles (UAVs) are flying objects whose trajectory can be remotely controlled. UAVs have lot of potential applications in the areas of wireless communications, internet of things, security, traffic management, monitoring, and smart surveying. By enabling reliable communication between UAVs and ground nodes, emergency notifications can be efficiently and quickly disseminated to a wider area. UAVs can gather data from remote areas, industrial units, and emergency scenarios without human involvement. UAVs can support ubiquitous connectivity, green communications, and intelligent wireless resource management. To efficiently use UAVs for all these applications, important challenges need to be investigated. In this paper, we first present a detailed classification of UAVs based on factors such as their size, communication range, weight, and flight altitude. We also explain the hardware system configuration and uses of these UAVs. We present a brief overview of recent work done related to three major challenges in UAVs. These challenges include trajectory control, energy efficiency and resource allocation. We also present three open challenges and future opportunities for efficient UAV communications. These include use of learning algorithms for resource allocation and energy efficiency in UAVs, intelligent surfaces-based communications for enhanced reliability in UAVs, and security algorithms to combat malicious attacks against UAVs.     

Technology adoption and household food security among rural households in South Africa: The role of improved maize varieties

This study aimed to assess the impact of adoption of improved maize varieties on household food security among smallholder farmers in KwaZulu-Natal, South Africa. A sample of 415 maize producers was analysed using the propensity score matching method, the treatment effect model and the Tobit selection model. The results were consistent across the models, indicating that improved maize varieties positively increased household food security, and that the impact of adoption differed according to the adoption level and socio-economic characteristics of the farmers. The results showed that an additional 1 ha of land under improved maize varieties increases annual food expenditure per capita levels by over R4000. Female farmers were more likely to adopt improved maize varieties, and spent more to ensure household food security, and benefitted more from adoption, than their male counterparts. The findings suggest that policies that seek to increase the land under improved maize varieties among smallholder farmers, especially female farmers who are the majority of these farmers, can play a significant and positive role in increasing the levels of household food security in South Africa through technological innovations. The study recommends that policy makers should aim to facilitate the dissemination of less costly improved seed varieties, target female farmers, and improve their access to information to improve the adoption of technological innovations and food security among the poor farming households in South Africa.     

Energy Optimization in Multi-UAV-Assisted Edge Data Collection System

In the IoT (Internet of Things) system, the introduction of UAV (Unmanned Aerial Vehicle) as a new data collection platform can solve the problem that IoT devices are unable to transmit data over long distances due to the limitation of their battery energy. However, the unreasonable distribution of UAVs will still lead to the problem of the high total energy consumption of the system. In this work, to deal with the problem, a deployment model of a mobile edge computing (MEC) system based on multi-UAV is proposed. The goal of the model is to minimize the energy consumption of the system in the process of data transmission by optimizing the deployment of UAVs. The DEVIPSK (differential evolution algorithm with variable population size based on a mutation strategy pool initialized by K-Means) is proposed to solve the model. In DEVIPSK, the population is initialized by K-Means to obtain better initial positions of UAVs. Besides, considering the limitation of the fixed mutation strategy in the traditional evolutionary algorithm, a mutation strategy pool is used to update the positions of UAVs. The experimental results show the superiority of the DEVIPSK and provide guidance for the deployment of UAVs in the field of edge data collection in the IoT system.     

Understanding the structure of risk belief systems concerning drone delivery: A network analysis

While e-commerce industries envision drones as a promising solution to the challenges associated with last-mile logistics of product delivery, there is increasing public concern over the risks of these airborne innovations. A growing number of studies seek to gauge the public's risk beliefs about drone delivery and inform policy development before its widespread uptake. Complicating these efforts is the fact that beliefs are interconnected and embedded in a cognitive system. This article argues that public outcomes are not based on atomized and isolated beliefs about risks involved in drone delivery, but instead emerge from the patterns in the relationships among these expressed beliefs. However, little is known about the structural characteristics of risk belief systems related to drone delivery, and the implications for risk communication and management. In an effort to fill this void, we conducted a network analysis of risk beliefs about drone delivery based on nationally representative data (N = 1465). The results revealed structural connections among 11 risk beliefs and explored structural variations in the risk belief system between people with different attitudes toward drone delivery. The simulation results showed that risk-mitigating messages instigated greater changes to the public's risk perceptions when they targeted structurally central, as opposed to peripheral, risk beliefs. The reported evidence adds new insights into how risks about drone delivery are configured in the public consciousness, and provides guidance into how practitioners may mobilize structural leverage to optimize the effectiveness and efficiency of risk communication strategies.     

The Unseeing State: How Ideals of Modernity Have Undermined Innovation in Africa’s Urban Water Systems

In contrast to the European historical experience, Africa’s urban infrastructural systems are characterised by stagnation long before demand has been saturated. Water infrastructures have been stabilised as systems predominantly providing services for elites, with millions of poor people lacking basic services in the cities. What is puzzling is that so little emphasis has been placed on innovation and the adaptation of the colonial technological paradigm to better suit the local and current socio-economic contexts. Based on historical case studies of Kampala and Nairobi, this paper argues that the lack of innovation in African urban water infrastructure can be understood using Pinch and Bijker’s concept of technological closure, and by looking at water technology from its embedded values and ideology. Large-scale water technology became part of African leaders’ strategies to build prosperous nations and cities after decolonisation and the ideological purpose of infrastructure may have been much more important than previously understood. Water technology had reached a state of closure in Europe and then came to represent modernisation and progress in the colonial context. It has continued to serve such a similar symbolic purpose after independence, with old norms essentially being preserved. Recent sector reforms have defined problems predominantly as of economic and institutional nature while state actors have become ‘unseeing’ vis-á-vis controversies within the technological systems themselves. In order to induce socio-technical innovation towards equality in urban infrastructure services, it will be necessary to understand the broader incentive structure that governs the relevant social groups, such as governments, donors, water suppliers and the consumers, as well as power-structures and political accountability.     

Energy Aware Data Collection with Route Planning for 6G Enabled UAV Communication

With technological advancements in 6G and Internet of Things (IoT), the incorporation of Unmanned Aerial Vehicles (UAVs) and cellular networks has become a hot research topic. At present, the proficient evolution of 6G networks allows the UAVs to offer cost-effective and timely solutions for real-time applications such as medicine, tracking, surveillance, etc. Energy efficiency, data collection, and route planning are crucial processes to improve the network communication. These processes are highly difficult owing to high mobility, presence of non-stationary links, dynamic topology, and energy-restricted UAVs. With this motivation, the current research paper presents a novel Energy Aware Data Collection with Routing Planning for 6G-enabled UAV communication (EADCRP-6G) technique. The goal of the proposed EADCRP-6G technique is to conduct energy-efficient cluster-based data collection and optimal route planning for 6G-enabled UAV networks. EADCRP-6G technique deploys Improved Red Deer Algorithm-based Clustering (IRDAC) technique to elect an optimal set of Cluster Heads (CH) and organize these clusters. Besides, Artificial Fish Swarm-based Route Planning (AFSRP) technique is applied to choose an optimum set of routes for UAV communication in 6G networks. In order to validated whether the proposed EADCRP-6G technique enhances the performance, a series of simulations was performed and the outcomes were investigated under different dimensions. The experimental results showcase that the proposed model outperformed all other existing models under different evaluation parameters.     

Technology adoption and the challenges of inclusive participation in economic activities: Evidence from small scale oil palm fruit processors in southwestern Nigeria

The lack of technology adoption has been mentioned as a source of lack of inclusive participation of low income groups in economic activities leading to income disparity in developing countries. The study utilized an input-process-output framework to develop a set of indicators to inform the development of policies and practices to ensure the participation of low income groups in economic activities. The input element consists of technology adoption influencing factors such as socio-economic characteristics and innovating units and institutions that provide support for innovation activities. The process and output elements consist of the level of technology adoption in production processes and productivity measures respectively. Focusing on small-scale oil palm fruit processors in Nigeria, the study revealed that inadequate funding of the input processes lead to inadequate technology adoption in specific unit operations of palm oil production. Utilising selected physicochemical properties of palm oil as indicators of productivity, the samples of palm oil assessed were found to be unsuitable for industrial use and may limit the processors from participating in formal sectors of palm oil production. The study recommends policy levers that will enhance input factors through adequate funding to improve the technological base of the small-scale oil palm fruit processing.     

蜂群无人机编队内无线紫外光协作避让算法

在战场复杂电磁环境下,保证蜂群无人机编队机间飞行安全和编队内可靠通信尤为重要。本文提出一种蜂群无人机编队内无线紫外光协作避让算法,结合无线紫外光覆盖特点设计紫外虚拟围栏避让策略,基于增强矢量场直方图法针对无人机在避让时的运动状态的代价函数进行改进,采用无迹卡尔曼预测器预测邻近无人机的飞行状态。在两种预测场景下的避让仿真中,结果表明,与增强矢量场直方图法进行对比,本文算法的整体运动轨迹平滑,局部避让时无明显抖动,避让路径总长度平均减少3.46%,总耗时平均减小18.94%,验证了蜂群无人机编队内无线紫外光协作避让算法的有效性。     

非洲水电开发及投资研究

非洲大陆水电资源蕴藏量极为丰富,但由于缺乏资金投入和技术支持,非洲的水电资源一直没有得到大规模开发和利用。而电力短缺是阻碍非洲社会经济发展的主要“绊脚石”之一。通过大量的数据分析和统计,对非洲各区域水电开发潜力和开发现状进行了剖析,对主要国家的水电开发规划进行解读,给出了非洲水电投资空间评估;深入分析长期以来中国企业在非洲水电开发的特点,总结中国企业的优势,并为拟在非洲投资水电的中国企业提出注意事项和建议。     

Educational reforms and internationalization of universities: evidence from major regions of the world

Internationalization of universities has become a worldwide phenomenon as global economic integration continues to make its way forcefully into the higher education. The objective of the study is to develop a model for internationalization of universities with the transformation of some promising macroeconomic variables i.e., educational reforms and economic growth in the seven largest regions of the world [namely, East Asia and Pacific (sample 25 countries); Europe and Central Asia (40 countries); Latin America and Caribbean (27 countries); Middle East and North Africa (17 countries); North America (22 countries); South Asia (7 countries) and Sub-Saharan Africa (21 countries)]. The data has been analyzed by panel fixed effect regression from the period of 1990–2011. In addition to transform inputs into output, the study employed eleven indicators of education and five indicators for growth, where the resulting vector is internationalization. The results show the dynamic linkages between educational indicators and economic factors in the selected regions of the World. In East Asia and Pacific region, tertiary and higher education expenditures per student increase the economic factors. Higher education is a powerful driver of long-term growth in Europe and Central Asia. Governments of the state should have to focus on higher education enrolment, as it does not have any significant contribution to increase GDP; gross capital formation and FDI in Latin America and Caribbean region. Higher education enrolment in MENA region significantly increases growth factors on the cost of increase gross national expenditures. Investment in general education and other generic human capital is of the utmost importance in creating an enabling environment for FDI in North America. It is imperative for South Asia to encourage the skill levels and education opportunities for females, in order to maximize the effects of FDI on the female human capital stock and therefore economic growth. Tertiary school enrolment and tertiary expenditures per student identified the importance of tertiary education in Sub-Saharan Africa. The results conclude that educational indicators improve the economic gains, which ultimately reap out the benefit of internationalization.