Infrastructure Coverage Research Articles

UAV-aided networks with optimization allocation via artificial bee colony with intellective search

In this paper, we consider a strong global search algorithm which exhibits strong exploration ability in unmanned aerial vehicle (UAV)-aided networks. UAVs in wireless communication have aroused great interest recently due to its low cost and flexibility in providing wireless connectivity in areas without infrastructure coverage. Artificial bee colony algorithm is a powerful approach for such a scene. However, due to its one-dimensional and greedy search strategy, it still suffers slow convergence speed. In the traditional version, three types of bees, including employed bees, onlooker bees, and scouts, are employed and they cooperate with each other to find the best food source position. Though different roles, these three types of bees play, there is no difference of division within the internal of each type of bees. Considering this phenomenon, this paper proposes a modified artificial bee colony algorithm with intellective search and special division (ABCIS) to enhance its performance, where different employed bees and different onlooker bees use different search strategies to search for food sources. Besides, the greedy selection method is also abandoned and the food sources’ positions are updated at each iteration. Under this circumstance, the whole population’s experience is fully utilized to guide bee’s search. Finally, to testify the proposed algorithms’ competitiveness, a series of benchmarks are adopted, and the experimental results demonstrate its superior performance among other state-of-the-art algorithm in UAV-aided networks.

Towards the new era of wastewater treatment of China: Development history, current status, and future directions

Water is essential for the sustainable development of human society. With the largest population and rapid economic development, water usage and treatment in China have grown tremendously in the past decades. In order to prevent water pollution, the standards for wastewater effluent discharge in China have been gradually developed and implemented since 1973. After the rapid development during over 40 years, numerous milestones have been achieved in terms of infrastructure coverage, standard and policy system establishment, and technological innovations. In this article, we reviewed the development history and the current status of the wastewater treatment in China, including the generation of wastewater, the construction of wastewater treatment plants (WWTPs), the overall treatment performance of WWTPs, as well as the developments in effluent discharge standards. In addition, we highlighted the challenges lying ahead in the aspects of influent concentration, sludge disposal and water reclamation. Based on the achievement and foundation built in the past, the new era of wastewater treatment of China is on the way, in which water reclamation, wastewater treatment in rural areas and resource/energy recovery from sludge are becoming the main tasks.

A modified algorithm for computation issues in UAV-enabled wireless communications

Unmanned aerial vehicles (UAVs) in wireless communication have received significant interests recently due to its low cost and flexibility in providing wireless connectivity in areas without infrastructure coverage. In this paper, we optimize the location of UAVs to maximize their coverage areas. We propose a modified artificial bee colony (MABC) incorporating bee number reallocation and a new search equation. In the proposed algorithm, a greater number of bees in the population are assigned to execute local searches near food sources to enhance solution accuracy, and the bees are guided by elite vectors to enable the algorithm to rapidly converge to a potentially globally optimal position. The deployment of UAVs is thus obtained. The experimental results show that the proposed algorithm achieves great improvements over the traditional algorithm.

Optimal charging management and infrastructure planning for free-floating shared electric vehicles

Recently, major car-sharing service providers have begun to include electric vehicles (EVs) in free-floating car-sharing fleets. For these EVs, downtime due to charging, including time spent traveling to and waiting in queues at charging stations in a sparse charging infrastructure network, is a major barrier to sustainable operation. An intuitive solution to overcome this barrier is to increase the number of fast-charging stations in the fleet service area. This paper studies the relationship between fleet vehicle downtime and the number of charging stations by modeling the fleet operations of a major car-sharing service provider. An integer programming model is developed that jointly optimizes charging station allocation, in terms of the number and location of charging stations, and the assignment of EVs to charging stations. Case study results showed that fleet vehicle charging time comprises 72–75% of the total downtime spent on charging trips. This indicates that charging time, as opposed to travel time or waiting time, is the dominant component of total fleet downtime for charging. The study also shows that by adding 5–20 new charging stations reduces total fleet downtime and travel time during charging trips by 2–4% and 26–49%, respectively. Although adding new charging stations to the fleet service area reduces total charging trip travel time significantly, it does not reduce total downtime significantly. Results also show that if the EV battery state of the charge (SOC) threshold—below which a charging trip is initiated—is less than 18%, not all EVs in the car-sharing fleet can be charged using the existing direct current fast chargers (DCFCs) in the fleet’s service area. This implies that adequate charging infrastructure coverage is required to ensure that EVs of a given range can operate in the car-sharing fleet.

Battery versus infrastructure: Tradeoffs between battery capacity and charging infrastructure for plug-in hybrid electric vehicles

Battery systems and charging infrastructures are essential, cost intense, and partly interchangeable building blocks of electric mobility. Although both building blocks are expected to develop favorably in the coming years, their current limitations hinder the adoption of electric vehicles. As their advancement competes for limited resources, it is of interest to quantify the trade-offs between battery capacity and charging infrastructure improvements in order to allocate research and development resources and public spending effectively. In an analysis that utilizes mobility data from a large cohort of regular drivers, we assess the impact of three electric mobility scenario parameters – battery capacity, charging infrastructure coverage, and charging power – on key performance indicators and side effects of electric mobility. The study goes beyond the state-of-the-art in several ways, including the large amount of driving data that serves as input (909 conventional vehicles monitored over two years while traveling over 46.5 million km (28.9 million miles)), the quality of the movement data (profiles based on global positioning systems), and the use of clustering that allows us to assess driver segments separately within one coherent analysis. For 180 battery-infrastructure scenarios, we derive energy consumption and charging behavior of the vehicles, electric reachability of destinations, electric mileage share of hybrid vehicles, and grid impact (electricity demand and time of peaks). Results show that realistic battery capacity improvements dispel concerns about the need for a dense charging infrastructure. We find that only small segments of long-range drivers and vehicles with very limited electric range benefit much from a dense charging network. Moreover, we observe that the benefits of fast charging are small for most driver segments even if charging can take place only at the home location.

Global cardiac surgery: Access to cardiac surgical care around the world

ObjectiveCardiovascular disease is the leading cause of death worldwide, responsible for 17.5 million deaths every year, of which 80% occur in low- and middle-income countries. Some 75% of the world does not have access to cardiac surgery when needed because of lack of infrastructure, human resources, and financial coverage. This study aims to map access to cardiac surgery around the world. MethodsA scoping review was done on access to cardiac surgery for an undifferentiated population. Workforce data were collected from the Cardiothoracic Surgery Network database and used to calculate numbers and ratios of adult and pediatric cardiac surgeons to population. ResultsA total of 12,180 adult cardiac surgeons and 3858 pediatric cardiac surgeons were listed in the Cardiothoracic Surgery Network in August 2017, equaling 1.64 (0-181.82) adult cardiac surgeons and 0.52 (0-25.97) pediatric cardiac surgeons per million population globally. Large disparities existed between regions, ranging from 0.12 adult cardiac surgeons and 0.08 pediatric cardiac surgeons per million population (sub-Saharan Africa) to 11.12 adult cardiac surgeons and 2.08 pediatric cardiac surgeons (North America). Low-income countries possessed 0.04 adult cardiac surgeons and 0.03 pediatric cardiac surgeons per million population, compared with 7.15 adult cardiac surgeons and 1.67 pediatric cardiac surgeons in high-income countries. ConclusionsThis study maps the current global state of access to cardiac surgery. Disparities exist between and within world regions, with a positive correlation between a nation's economic status and access to cardiac surgery. Low early mortality rates in low-resource settings suggest the possibility of high-quality cardiac surgery in low- and middle-income countries. There is the need to increase human and physical resources, while focusing on safety, quality, and efficiency to improve access to cardiac surgery for the 4.5 billion people without.

Task Offloading in UAV-Aided Edge Computing: Bit Allocation and Trajectory Optimization

The deployment of unmanned aerial vehicles (UAVs) in wireless communication systems promises to provide services for devices with limited or without infrastructure coverage. With the emergence of diverse Internet of Things (IoT) applications, there is an ever-increasing demand for computation resources of IoT mobile devices (IMDs) in UAV communication scenarios. Motivated by this, we consider a UAV-aided edge computing scenario and study the task offloading problem between the IMDs and the UAV, aiming to minimize the overall energy consumption for accomplishing the tasks. An alternative optimization algorithm is proposed as our solution, which jointly optimizes task offloading decision-making, bit allocation during transmission, and the UAV trajectory. Numerical results demonstrate the significant energy savings of the proposed scheme.

Use of open mobile mapping tool to assess human mobility traceability in rural offline populations with contrasting malaria dynamics

Infectious disease dynamics are affected by human mobility more powerfully than previously thought, and thus reliable traceability data are essential. In rural riverine settings, lack of infrastructure and dense tree coverage deter the implementation of cutting-edge technology to collect human mobility data. To overcome this challenge, this study proposed the use of a novel open mobile mapping tool, GeoODK. This study consists of a purposive sampling of 33 participants in six villages with contrasting patterns of malaria transmission that demonstrates a feasible approach to map human mobility. The self-reported traceability data allowed the construction of the first human mobility framework in rural riverine villages in the Peruvian Amazon. The mobility spectrum in these areas resulted in travel profiles ranging from 2 hours to 19 days; and distances between 10 to 167 km. Most Importantly, occupational-related mobility profiles with the highest displacements (in terms of time and distance) were observed in commercial, logging, and hunting activities. These data are consistent with malaria transmission studies in the area that show villages in watersheds with higher human movement are concurrently those with greater malaria risk. The approach we describe represents a potential tool to gather critical information that can facilitate malaria control activities.

Indoor Localization Using Multi-operator Public Land Mobile Networks and Support Vector Machine Learning Algorithms

Given Public Land Mobile Networks (PLMN) ubiquitous infrastructure and excellent coverage, they can be used for providing location information for various location-based services, especially in indoor environments. This paper investigates indoor positioning solutions which utilize received signal strength measurements obtained by mobile device from PLMN cells belonging to multiple mobile network operators. Two indoor positioning methods, based on Support Vector Machine learning algorithms and space-partitioning principle, are proposed. The first method utilizes Support Vector Regression (SVR) algorithm, whilst the second one introduces space-partitioning principle and the combined use of Support Vector Classification and SVR algorithms. The proposed techniques are thoroughly investigated in a real indoor environment. In addition, several criteria for choosing relevant cells for the positioning purposes have been explored. Positioning with SVR has demonstrated good results, while utilizing space-partitioning principle has further reduced the average positioning error by 27%. Moreover, the proposed solution has outperformed positioning methods based on k Nearest Neighbours and Artificial Neural Networks, when implemented in the same verification test bed.

Throughput maximization for UAV-enabled full-duplex relay system in 5G communications

In areas without infrastructure coverage, unmanned aerial vehicles (UAVs) have made great progress in wireless communication because of its low cost and flexible connectivity. This paper studies a novel mobile relay system, which can obtain the properties of high-mobility and high-performance by adopting an UAV as a relay node. By assuming that the UAV employs full-duplex (FD) and spectrum-efficient trajectory-based decode-and-forward (DF) relay, we study the throughput maximization problem by jointly optimizing UAV trajectory and source/relay transmission power, subject to the constraints on initial/final location, maximum speed and maximum power of the UAV and information-causality of each node in practical situations. It is revealed that there exists a jointly optimal allocation of trajectory and power for the UAV achieved by alternative and iterative algorithm. Numerical results show that by jointly optimizing the trajectory and power, the proposed two UAV-enabled full-duplex relay models are able to obtain significant throughput gains over the conventional static relay.

Understanding the linkage between electric vehicle charging network coverage and charging opportunity using GPS travel data

Using GPS travel survey data from three metropolitan areas, this paper estimates the relationship between plug-in electric vehicle (PEV) public charging infrastructure coverage and charging opportunity. The former is defined as the percentage of public areas with charging stations installed and the latter represents the drivers probability of accessing a public charger at their trip stops (stop-based) or during at least one stop of their travel day (trip chain-based). Understanding this relationship is important to PEV manufacturers and electric vehicle supply equipment (EVSE) providers, as well as government agencies, for evaluating different levels of EVSE deployment and estimating the impact of its availability on PEV adoption. Heuristic procedures are developed to estimate stop- and trip chain-based charging opportunities. Charging opportunity reflects the visibility of EVSE as the incremental security that charging stations enable, while evaluating the potential of a driver to access EVSE at travel stops or during the day, for different levels of EVSE deployment on the transportation network. The metrics proposed do not assess the probability of completing trips with electric vehicles of a given range. The analysis results indicate that drivers’ trip destinations concentrate in a few popular places and EVSE deployment in these areas could achieve relatively high levels of charging opportunity. This finding is also robust to regional variations.

Optimization approach for a climbing robot with target tracking in WSNs

Climbing robots are being developed for various applications. The confined space requires a compact locomotion system with vertical and overhead climbing ability. To achieve surface transition, Steering geometry Interaction system and static force are used. WSNs ubiquitous infrastructure and excellent coverage, they can be used for providing location information for various location-based services, especially in indoor environments. This structure is designed for a magnetic wall-climbing robot to gradually decrease the magnetic force when it is transiting between perpendicular magnetic surfaces. This paper describes the design process of a magnetic wall climbing robot, which adopts SgI and has the potential to carry materials in a confined space with an energy efficient system model. To resolve the problem of target tracking, it is essential to deploy a system model. Over the last two decades, several researchers have recommended many remote user authentication schemes. Researchers are continuously trying to enhance the security in material handling automation system by introducing several features into their work. A working prototype has been built based on the optimized dimension.

Special issue on amateur drone and UAV communications and networks

The development of the mini-drones, formally called unmanned air vehicles (UAVs) have captured the attention of hobbyists and the investors due to their enormous applications. Drones have endless commercial applications as well due to the irrelatively small size and ability to fly without an on-board pilot such as in agriculture, photography, surveillance, and numerous public services. The use of drones for achieving high speed wireless communication is one of the most significant applications for next generation communication system (5G). Indeed, drone-based communication network offers encouraging solution to provide wireless connectivity for devices without infrastructure coverage due to e.g., severe shadowing by urban or mountainous terrain, or damage to the communication infrastructure caused by natural disasters.

Drone Assisted Vehicular Networks: Architecture, Challenges and Opportunities

This article introduces the DAVN, which provides ubiquitous connections for vehicles by efficiently integrating the communication and networking technologies of drones and connected vehicles. Specifically, we first propose a comprehensive architecture of the DAVN and outline its potential services. By cooperating with vehicles and infrastructures, drones can improve vehicle-to-vehicle connectivity, infrastructure coverage, network information collection ability, and network interworking efficiency. We then present the challenges and research opportunities of DAVNs. In addition, a case study is provided to demonstrate the effectiveness of DAVNs by leveraging our designed simulation platform. Simulation results demonstrate that the performance of vehicular networks can be significantly enhanced with the proposed DAVN architecture.

Cancer control in war-torn Iraq

Before 1980, the Iraqi health system was described by the UN as the best health-care system in the Middle East with respect to its infrastructure, medical expertise and universal health coverage through its free of charge services. The repercussions of the war against Iran (1980–88), followed by the Gulf wars (1990–91 and 2003–11), and the civil war initiated by the Islamic State of Iraq and the Levant (2014–17), resulted in a severe decline in the availability of medical resources, funds, and medical personnel; factors that were exacerbated by an excess of bureaucracy, corruption, and turmoil at a time when the health sector was not considered a priority by the Iraqi Government. In 2017, the International Organization for Migration registered over 3 million internally displaced Iraqis, which added a further burden on the Iraqi Ministry of Health. Much of the focus from high-income countries centers on the aftermath of the second Gulf war in Iraq, but it is important to realise that this country has been in a continuous state of war for about 40 years, claiming the lives of hundreds of thousands of Iraqi citizens in which it is of little surprise that health-care service and provision of the country has suffered. During the Gulf war, Iraq and the surrounding regions were exposed to various weapons, including depleted uranium-tipped ammunitions, which raised a hitherto unresolved debate on the potential carcinogenicity of the weapons. The UN sanctions, undertaken to restrict Saddam Hussein's capacity to manufacture weapons of mass destruction, imposed an embargo on a range of cancer diagnostic and treatment equipment, including linear accelerators, some chemotherapy drugs, radioisotopes, and analgesics, which were blocked on the assumption that they might be converted into chemical weapons. The 2003 Gulf war saw the destruction of 12% of hospitals and public laboratories, while many others were either looted or destroyed. In 2004, David Kerr visited Basra to explore the residual robustness of the health service under the auspices of the British Army, and witnessed the extraordinary pressure that clinical colleagues and health-care professionals were under from sectarian, authoritarian, and criminal organisations to comply with living within dangerous and mysterious circumstances. Unsurprisingly, many senior clinicians had to put the safety of their families first and seek employment elsewhere, which substantially expanded the Iraqi medical diaspora. At such a time, individuals in high-level positions were specifically targeted—eg, Muhammed Alwan, Dean of Mustansiriya Medical College, was mysteriously killed by a car bomb in 2011. Why this hard working, universally acclaimed surgeon was targeted was much speculated on, but no clear motives have been discovered to date.

Determinants of Growth of Micro, Small and Medium Enterprises (MSMEs) in Developing Countries Evidence from Rubaga Division, Kampala District Uganda

The Study examines the determinants of Small and Medium Enterprises (MSMEs) growth in an urban set up area in Uganda. Using a cross sectional survey design comprising of 254 MSMEs operators, we find access to credit by the MSMEs, access to market and the level of managerial skills all positively associated with the growth of small and medium enterprises in the surveyed region. We thus recommend for the need to train enterprise owners, managers and other operators in order to equip them with the relevant skills and knowledge specifically tailored towards impacting various business management practices, enhancing access to financial assistance through fair lending rates and reduced bureaucratic tendencies in the credit market. In addition, the government need to improve the ICT infrastructure coverage to enable MSMEs to utilize the online market base that can enhance sales.

Causes of energy poverty in a cold and resource-rich country: evidence from Kazakhstan

ABSTRACTKazakhstan is an upper-middle-income country and one of the coldest countries in the world with rich energy resources and energy prices considerably lower than in developed countries. This paper presents the first comprehensive overview of household fuel use in Kazakhstan and assesses the causes and extent of energy poverty using the Households Living Conditions Survey dataset of 12,000 households. The results show that there is an overwhelming reliance on coal in Kazakhstan: 40% of all surveyed households use coal for heating, cooking and other needs. In general, liquefied petroleum gas is mainly used for cooking, coal and firewood for heating, while electricity is rarely used for heating. Energy poverty was less prevalent in oil and gas rich regions, due to low gas prices and higher income levels in those regions, while households located in the North Kazakhstan, Central and East Kazakhstan mainly suffer from lack of cleaner fuel options, income poverty, longer and colder winters and consequently energy affordability. Despite low energy prices in Kazakhstan, the results demonstrate that 28% of surveyed households spend more than 10% of their income on energy. Gas and district heating infrastructure coverage and income inequality across its regions contributed the most to energy poverty in Kazakhstan. Energy prices are regulated and indirectly subsidised. Removing energy subsidies alone may worsen energy affordability of households. Offering direct subsidies to cover part of the energy expenditures may not fully solve the problem, but subsidies, interventions for efficient technologies and fuels, dwelling energy-efficiency improvements are necessary.

TCT-395 Cost-effective, Innovative, Indigenous, Population-based and Telemedicine-guided, AMI Strategy for India’s most Populous State

AMI management in India is constrained by lack of infra-structure, ambulance systems and insurance coverage. A STEMI systems of care approach is altogether lacking. As a result, there are considerable delays in presentation and major disparities exist based upon the financial ability to pay.

Resilient Health System As Conceptual Framework for Strengthening Public Health Disaster Risk Management: An African Viewpoint.

Disasters whether natural or man-made, pose major challenge to human health and development in Africa; their impact on the health of individuals and communities are often severe and could hinder attainment of global, regional, and national development goals (1–3). Recent disasters in Africa aptly illustrate the complex interaction between health systems and disasters; a vicious cycle in which weak health systems provide fertile grounds for deterioration of public health and natural hazards into disasters while on the other hand, disasters further decimate already weak health systems (4). The sustained transmission of the 2014/15 Ebola virus disease outbreak in Guinea, Liberia, and Sierra Leone was consistently linked to the weak health systems in these countries (5, 6). The outbreak resulted in the death of several health workers (7), depletion of scarce financial resources, diversion of medical equipment. This in addition to overburdening of already weak health information and supply chain management systems resulted in disruption of health services delivery in these countries (8–10). Other disasters such as the Yellow Fever outbreaks in Angola, Democratic Republic of Congo and Uganda, and ongoing armed conflicts in South Sudan, Central Africa Republic, northeast Nigeria, and other African countries also had similar consequences (11–15). This pattern is not limited to Africa; the fragile pre-disaster health systems in the city of New Orleans in America and the Eastern Visayas Region of the Philippines contributed to the public health consequences of Hurricane Katrina and Haiyan (Yolanda) and constrained timely and effective post-disaster health system recovery efforts (16, 17). The pre-Katrina health system in the city of New Orleans was characterized by low coverage of health insurance and reduced access to health services by the largely poor population of the city (16). Similar challenges such as inadequate health-care infrastructure, staffing, and low coverage of health insurance, which reduced access to health services were also prevalent in the affected areas of the Philippines pre-Hurricane Haiyan (17). The Sendai Framework for Disaster Risk Reduction (SFDRR) and sustainable development goals (SDGs), both of which are landmark United Nations agreements adopted in 2015, recommend scaling up implementation of disaster risk reduction (DRR) strategies as means to improve resilience to disasters globally (18, 19). The SFDRR in contrast to its predecessor, the Hyogo Framework for Action, puts a lot of emphasis on health (20). It proposes resilient health systems as an opportunity for ensuring effective DRR in the health sector (20). The World Health Assembly, through resolution 64.10, urged countries to strengthen disaster risk management (DRM) programs by incorporating them into national health systems (21). The 2008 Ouagadougou declaration on Primary Health Care and the African Regional strategy for DRM in the health sector also advocated for the use of strong health systems as the basis for addressing the health vulnerabilities and inequalities, which are associated with disasters in Africa (22, 23). The foregoing and available literatures (2, 24) make a strong case for the use of resilient health systems as a conceptual framework for public health DRM in Africa. Calls for the use of resilient health system as the basis for public health DRM have intensified lately (25); however, there is paucity of practical guidance, requisite tools, and skills for integration of DRM into longer-term health system programs in public health settings in Africa (26). This often results in parallel implementation of health systems strengthening and public health DRM programs within Ministries of Health and between their Disaster Management counterparts with duplication of efforts and lack of synergy. This article reflects on the nexus between the health system framework and DRM and provides insights into how a resilient health system could be used as a framework to strengthen public health DRM in Africa.

Mobility Analysis for Passive Reservations in Vehicular Cellular Networks Based on Dynamic Programming and Roads Compression

The employment of an appropriate Bandwidth Management Scheme (BMS) is needed in wireless networking, given that the main desire of end-users is to take advantage of satisfactory services, in terms of Quality of Service (QoS), especially when a particular charge is paid to meet the requirement. In this paper the authors are interested in investigating how the continuity of services can be guaranteed in QoS networks, when users move from a cell to another one, under an infrastructure cellular coverage. The only way to face this issue is represented by the employment of in-advance bandwidth reservations, although it leads the system to waste bandwidth resources, since they are not used until the mobile host enters the coverage cell where the passive request has been made. A new scheme for predicting user movements is proposed, taking the advantage of the dynamic programming approach, that is able to reduce the number of possible roads to be considered and thereby increasing/decreasing the accuracy/redundancy of the proposed model. Several simulation runs have been carried out in order to assess the effectiveness of the proposed idea.