Coverage Analysis for High-Speed Railway Communications with Narrow-Strip-Shaped Cells over Suzuki Fading Channels.

Unlike circular cell coverage in public land mobile communications, narrow-strip-shaped cell coverage should be considered in high-speed railway (HSR) communications. Moreover, for the coverage analysis in HSR communications, most works ignore the effect of small-scale fading, which results in an inaccurate coverage performance evaluation. In this paper, we focus on the coverage analysis for HSR communications with narrow-strip-shaped cells over the Suzuki fading channel, where the composite channel fading includes path loss, lognormal shadowing, and Rayleigh-distributed small-scale fading. Based on the channel model, we first analyze the statistical characteristic of the received signal-to-noise ratio. Then, we derive analytical expressions of the edge coverage probability (ECP) and the percentage of cell coverage area (CCA). To link the edge coverage performance and the average coverage performance of a cell, we express the percentage of CCA as a summation of the ECP and a positive increment. As special cases, we also obtain the coverage performance expressions for the systems without small-scale fading. Through Monte Carlo simulations, the accuracy of the derived expressions is verified. Numerical results also show that the small-scale fading has a strong effect on coverage performance and cannot be ignored. In addition, the effects of key parameters are also discussed.

Performance of Narrow Band Wide Area Networks with Gateway Diversity.

This paper quantifies the coverage area of Low-Power Wide-Area Networks (LPWAN) for Packet Success Rates (PSR) above 85%, where acceptable Quality of Service (QoS) can be achieved. The network consists of battery-operated end-nodes (ENs) and multiple stationary gateways (GWs). We consider asynchronous communication that uses ALOHA-based random channel access. Each transmission from the ENs can be received by multiple GWs. Such spatial diversity results in favorable Signal-to-Noise ratios (SNR). The LoRa modulation is assumed and its specific features, such as IQ inversion, further contribute to decreasing the impact of interference. An increase in the GW density improves network performance, which allows support for a larger density of end-nodes as well as increasing the coverage area. Our simulation results show that a suburban area of up to 1.44 km2 can be covered with five GWs with up to fifty end-nodes with a PSR greater than 86%.

Using Adaptive Sensors for Optimised Target Coverage in Wireless Sensor Networks.

Innovation in wireless communications and microtechnology has progressed day by day, and this has resulted in the creation of wireless sensor networks. This technology is utilised in a variety of settings, including battlefield surveillance, home security, and healthcare monitoring, among others. However, since tiny batteries with very little power are used, this technology has power and target monitoring issues. With the development of various architectures and algorithms, considerable research has been done to address these problems. The adaptive learning automata algorithm (ALAA) is a scheduling machine learning method that is utilised in this study. It offers a time-saving scheduling method. As a result, each sensor node in the network has been outfitted with learning automata, allowing them to choose their appropriate state at any given moment. The sensor is in one of two states: active or sleep. Several experiments were conducted to get the findings of the suggested method. Different parameters are utilised in this experiment to verify the consistency of the method for scheduling the sensor node so that it can cover all of the targets while using less power. The experimental findings indicate that the proposed method is an effective approach to schedule sensor nodes to monitor all targets while using less electricity. Finally, we have benchmarked our technique against the LADSC scheduling algorithm. All of the experimental data collected thus far demonstrate that the suggested method has justified the problem description and achieved the project's aim. Thus, while constructing an actual sensor network, our suggested algorithm may be utilised as a useful technique for scheduling sensor nodes.

Coverage-Balancing User Selection in Mobile Crowd Sensing with Budget Constraint.

Mobile crowd sensing (MCS) is a new computing paradigm for the internet of things, and it is widely accepted as a powerful means to achieve urban-scale sensing and data collection. In the MCS campaign, the smart mobilephone users can detect their surrounding environments with their on-phone sensors and return the sensing data to the MCS organizer. In this paper, we focus on the coverage-balancing user selection (CBUS) problem with a budget constraint. Solving the CBUS problem aims to select a proper subset of users such that their sensing coverage is as large and balancing as possible, yet without violating the budget specified by the MCS campaign. We first propose a novel coverage balance-based sensing utility model, which effectively captures the joint requirement of the MCS requester for coverage area and coverage balance. We then formally define the CBUS problem under the proposed sensing utility model. Because of the NP-hardness of the CBUS problem, we design a heuristic-based algorithm, called MIA, which tactfully employs the maximum independent set model to determine a preliminary subset of users from all the available users and then adjusts this user subset to improve the budget implementation. MIA also includes a fast approach to calculating the area of the union coverage with any complicated boundaries, which is also applicable to any MCS scenarios that are set up with the coverage area-based sensing utility. The extensive numeric experiments show the efficacy of our designs both in coverage balance and in the total coverage area.

Indoor Positioning on Disparate Commercial Smartphones Using Wi-Fi Access Points Coverage Area.

The applications of location-based services require precise location information of a user both indoors and outdoors. Global positioning system's reduced accuracy for indoor environments necessitated the initiation of Indoor Positioning Systems (IPSs). However, the development of an IPS which can determine the user's position with heterogeneous smartphones in the same fashion is a challenging problem. The performance of Wi-Fi fingerprinting-based IPSs is degraded by many factors including shadowing, absorption, and interference caused by obstacles, human mobility, and body loss. Moreover, the use of various smartphones and different orientations of the very same smartphone can limit its positioning accuracy as well. As Wi-Fi fingerprinting is based on Received Signal Strength (RSS) vector, it is prone to dynamic intrinsic limitations of radio propagation, including changes over time, and far away locations having similar RSS vector. This article presents a Wi-Fi fingerprinting approach that exploits Wi-Fi Access Points (APs) coverage area and does not utilize the RSS vector. Using the concepts of APs coverage area uniqueness and coverage area overlap, the proposed approach calculates the user's current position with the help of APs' intersection area. The experimental results demonstrate that the device dependency can be mitigated by making the fingerprinting database with the proposed approach. The experiments performed at a public place proves that positioning accuracy can also be increased because the proposed approach performs well in dynamic environments with human mobility. The impact of human body loss is studied as well.

A Novel Positioning System Based on Coverage Area Pruning in Wireless Sensor Networks.

Wireless sensor networks are commonly applied in environmental monitoring applications. The crucial factor in such applications is to accurately retrieve the location of a monitoring event. Although many technologies have been proposed for target positioning, the devices used in such methods require better computational abilities or special hardware that is unsuitable for sensor networks with limited ability. Therefore, a range-free positioning algorithm, named coverage area pruning positioning system (CAPPS), is proposed in this study. First, the proposed CAPPS approach determines the area that includes the target approximately by using sensor nodes that can detect the target. Next, CAPPS uses sensor nodes that cannot detect the target to prune the area to improve positioning accuracy. The radio coverage variation is evaluated in a practical scenario, and a heuristic mechanism is proposed to reduce false positioning probability. Simulation results show that the size of the positioning area computed by CAPPS is smaller than that computed using distance vector hop, angle of arrival, and received signal strength indicator by approximately 98%, 97%, and 93%, respectively. In the radio variation scenario, the probability of determining an area excluding the target can be reduced from 50%⁻95% to 10%⁻30% by applying the proposed centroid point mechanism.

Identifying habitat modification by Chinese pangolin in subtropical forests of southern China.

The excavation of Chinese pangolin (Manis pentadactyla) is expected to alter habitat heterogeneity and thus affect the functioning and structure of forest ecosystems. In this study, the bioturbation of Chinese pangolin on forest soils in three regions (Heping, Tianjingshan, and Wuqinzhang) across Guangdong province was quantified. Overall, a mean of 2.66 m3·ha-1 and 83.1 m2·ha-1 of burrows and bare mounds, respectively, was excavated by Chinese pangolin; the disturbed soils had significantly lower water content and P, C, available N concentrations, but higher bulk density, pH, and microbial abundance than those undisturbed soils. The unevenness of habitat heterogeneity improvement was mainly ascribed to the stronger soil disturbance caused in resting burrows by pangolins. Patterns of altering habitat heterogeneity were site-specific, with high-intensity soil disturbance occurring most in shrubs, meadows, steep habitats at high elevations, and mountain tops in Heping, while in broad-leaved, coniferous and mixed coniferous and broad-leaved forests away from human settlements in Tianjingshan and upper mountains at high elevations far away from roads and human settlements in Wuqinzhang. Road networks are the main interference for the burrow distribution in Heping and Wuqinzhang and should be programmed.

Mass drug administration in response to vivax malaria resurgence in Anhui Province of Huanghuai Plain, China.

This article summarizes the background, specific conditions, main measures, steps and effects of the implementation of Mass Drug Administration (MDA) to control the local P. vivax malaria epidemic in Anhui Province in central China. Distributing medicines to the designated population quickly controlled the local epidemic of P. vivax. Implementing MDA to control P. vivax ensured the correct selection of medicines, clarification of the targeted population for receipt of medicines, and assurance of a high rate of compliance through government support and health education. These results provide a reference for countries and regions experiencing similar events and planning to implement MDA in malaria control.

Disaster Coverage Predication for the Emerging Tethered Balloon Technology: Capability for Preparedness, Detection, Mitigation, and Response.

OBJECTIVE: A disaster is a consequence of natural hazards and terrorist acts, which have significant potential to disrupt the entire wireless communication infrastructure. Therefore, the essential rescue squads and recovery operations during a catastrophic event will be severely debilitated. To provide efficient communication services, and to reduce casualty mortality and morbidity during the catastrophic events, we proposed the Tethered Balloon technology for disaster preparedness, detection, mitigation, and recovery assessment. METHODS: The proposed Tethered Balloon is applicable to any type of disaster except for storms. The Tethered Balloon is being actively researched and developed as a simple solution to improve the performance of rescues, facilities, and services of emergency medical communication in the disaster area. The most important requirement for rescue and relief teams during or after the disaster is a high quality of service of delivery communication services to save people's lives. RESULTS: Using our proposed technology, we report that the Tethered Balloon has a large disaster coverage area. Therefore, the rescue and research teams are given higher priority, and their performance significantly improved in the particular coverage area. CONCLUSIONS: Tethered Balloon features made it suitable for disaster preparedness, mitigation, and recovery. The performance of rescue and relief teams was effective and efficient before and after the disaster as well as can be continued to coordinate the relief teams until disaster recovery. (Disaster Med Public Health Preparedness. 2018;12:222-231).

Remote estimation of cyanobacterial blooms using the risky grade index (RGI) and coverage area index (CAI): a case study in the Three Gorges Reservoir, China.

Harmful cyanobacterial blooms are exemplified as a major environmental concern due to producing toxin, and have generated a serious threat to public health. Knowledge on the spatial-temporal distribution of cyanobacterial blooms is therefore crucial for public health organizations and environmental agencies. In this study, field data and charge coupled device (CCD) image were collected in Lakes Gaoyang and Hanfeng of the Three Gorges Reservoir (TGR), China. We conducted the risky grade index (RGI) and coverage area index to develop a feasible estimation framework of cyanobacterial blooms. First, the close relationships between CCD reflectance spectral indices and water quality parameters were constructed based on water optical classification. Then, a regional algorithm for the RGI classification was established by density peaks. Finally, our proposed algorithm was applied to investigate dynamics of cyanobacterial blooms in the two lakes from 6-year series of CCD images. Encouraging results demonstrated that satellite remote sensing in conjunction with field observation can aid in the estimation of cyanobacterial blooms in the TGR.