Deployment optimization for target perpetual coverage in energy harvesting wireless sensor network

Energy limitation of traditional Wireless Sensor Networks(WSNs)greatly confines the network lifetime due to generating and processing massive sensing data with a limited battery.The energy harvesting WSN is a novel network architecture to address the limitation of traditional WSN.However,existing coverage and deployment schemes neglect the environmental correlation of sensor nodes and external energy with respect to physical space.Comprehensively considering the spatial correlation of the environment and the uneven distribution of energy in energy harvesting WSN,we investigate how to deploy a collection of sensor nodes to save the deployment cost while ensuring the target perpetual coverage.The Confident Information Coverage(CIC)model is adopted to formulate the CIC Minimum Deployment Cost Target Perpetual Coverage(CICMTP)problem to minimize the deployed sensor nodes.As the CICMTP is NP-hard,we devise two approximation algorithms named Local Greedy Threshold Algorithm based on CIC(LGTA-CIC)and Overall Greedy Search Algorithm based on CIC(OGSA-CIC).The LGTA-CIC has a low time complexity and the OGSA-CIC has a better approximation rate.Extensive simulation results demonstrate that the OGSA-CIC is able to achieve lower deployment cost and the performance of the proposed algorithms outperforms GRNP,TPNP and EENP algorithms.

Coverage and Factors Associated with Acceptance and Satisfaction of Seasonal Malaria Chemoprevention in Six Health Zones in Benin

Introduction: Seasonal malaria chemoprevention (SMC) was adopted in 2019 in two health zones in Benin where malaria transmission is very high. Positive results led to the extension of the intervention to other zones with additional financial support. Annual SMC campaigns from 2021 to 2023 were carried out in all six health zones in the Atacora and Alibori departments. In five years of implementation, various approaches have been developed on the basis of a communication plan facilitating buy-in and acceptance by all stakeholders. The aim of this study was to assess the effective coverage and acceptance of the SMC by their beneficiary populations in 2023. Methods: It was a cross-sectional study with an analytical focus. Data collection took place from November 30 to December 13, 2023. The study population consisted of children under 5 years of age residing in the departments of Atacora and Alibori in northern Benin. A total of 3573 children under 5 years of age were included in the study, and their parents or guardians were interviewed. Results: During the 2023 campaign, 87.7% of targets were reached by SMC administration and 100.00% of children had received at least one dose of SMC by the fourth visit. Effective therapeutic coverage of SMC was 70.55%, with 99.60% in BNK, 69.40% in KGS, 16.20% in MK, 56.10% in 2KP, 92.40% in NBT and 89.60% in TMC. This coverage was statistically related to child and respondent ages (p Conclusion: SMC is a strategy accepted by the population, and the main reasons for non-participation in SMC were dominated by the absence of mothers or babysitters when the agents visited.

Models to Simulate Effective Coverage of Fire Station Based on Real-Time Travel Times

In recent years,frequent fire disasters have led to enormous damage in China.Effective firefighting rescues can minimize the losses caused by fires.During the rescue processes,the travel time of fire trucks can be severely affected by traffic conditions,changing the effective coverage of fire stations.However,it is still challenging to determine the effective coverage of fire stations considering dynamic traffic conditions.This paper addresses this issue by combining the traveling time calculationmodelwith the effective coverage simulationmodel.In addition,it proposes a new index of total effective coverage area(TECA)based on the time-weighted average of the effective coverage area(ECA)to evaluate the urban fire services.It also selects China as the case study to validate the feasibility of the models,a fire station(FS-JX)in Changsha.FS-JX station and its surrounding 9,117 fire risk points are selected as the fire service supply and demand points,respectively.A total of 196 simulation scenarios throughout a consecutiveweek are analyzed.Eventually,1,933,815 sets of valid sample data are obtained.The results showed that the TECA of FS-JX is 3.27 km^(2),which is far below the standard requirement of 7.00 km^(2) due to the traffic conditions.The visualization results showed that three rivers around FS-JX interrupt the continuity of its effective coverage.The proposed method can provide data support to optimize the locations of fire stations by accurately and dynamically determining the effective coverage of fire stations.

Detecting the distribution of and public attitudes to charismatic alien species based on media coverage

Charismatic species are often reported by the media,providing information for detecting population status and public perception.To identify the number and distribution of free-living Black Swan(Cygnus atratus),a charismatic alien species in Chinese mainland and to detect the public and the media attitudes to the species,we analyzed the reports and emotional tendency from media coverage in 2000-2022 using manual reading,crawler extraction and latent Dirichlet allocation.A total of 6654 Black Swans were reported at 711 sites,including 147 individuals at 30 nature reserves.Successful breeding was reported at one-fourth of the total sites,including five nature reserves.The proportion of positive emotional tendency to Black Swans was overwhelming in the reports and was higher than that to alien species in general,suggesting that the public and the media are unaware of the risk of biological invasion.Effective management of invasive species requires the media clarifies the invasion risk of charismatic alien species.Promoting the unity between the harmfulness of abstract concept of alien species and the charisma of a specific alien species among the public help effective management.

Distributed collaborative complete coverage path planning based on hybrid strategy

Collaborative coverage path planning(CCPP) refers to obtaining the shortest paths passing over all places except obstacles in a certain area or space. A multi-unmanned aerial vehicle(UAV) collaborative CCPP algorithm is proposed for the urban rescue search or military search in outdoor environment.Due to flexible control of small UAVs, it can be considered that all UAVs fly at the same altitude, that is, they perform search tasks on a two-dimensional plane. Based on the agents’ motion characteristics and environmental information, a mathematical model of CCPP problem is established. The minimum time for UAVs to complete the CCPP is the objective function, and complete coverage constraint, no-fly constraint, collision avoidance constraint, and communication constraint are considered. Four motion strategies and two communication strategies are designed. Then a distributed CCPP algorithm is designed based on hybrid strategies. Simulation results compared with patternbased genetic algorithm(PBGA) and random search method show that the proposed method has stronger real-time performance and better scalability and can complete the complete CCPP task more efficiently and stably.

Modern Corrosion Mapping of Storage Tank Bottoms--Notable Advancements in Critical Zone Coverage,Inspection Efficiency and Data Integrity

Every day,an NDT(Non-Destructive Testing)report will govern key decisions and inform inspection strategies that could affect the flow of millions of dollars which ultimately affects local environments and potential risk to life.There is a direct correlation between report quality and equipment capability.The more able the equipment is-in terms of efficient data gathering,signal to noise ratio,positioning,and coverage-the more actionable the report is.This results in optimal maintenance and repair strategies providing the report is clear and well presented.Furthermore,when considering tank floor storage inspection it is essential that asset owners have total confidence in inspection findings and the ensuing reports.Tank floor inspection equipment must not only be efficient and highly capable,but data sets should be traceable and integrity maintained throughout.Corrosion mapping of large surface areas such as storage tank bottoms is an inherently arduous and time-consuming process.MFL(magnetic flux leakage)based tank bottom scanners present a well-established and highly rated method for inspection.There are many benefits of using modern MFL technology to generate actionable reports.Chief among these includes efficiency of coverage while gaining valuable information regarding defect location,severity,surface origin and the extent of coverage.More recent advancements in modern MFL tank bottom scanners afford the ability to scan and record data sets at areas of the tank bottom which were previously classed as dead zones or areas not scanned due to physical restraints.An example of this includes scanning the CZ(critical zone)which is the area close to the annular to shell junction weld.Inclusion of these additional dead zones increases overall inspection coverage,quality and traceability.Inspection of the CZ areas allows engineers to quickly determine the integrity of arguably the most important area of the tank bottom.Herein we discuss notable developments in CZ coverage,inspection efficiency and data integrity that combines to deliver an actionable report.The asset owner can interrogate this report to develop pertinent and accurate maintenance and repair strategies.

Cluster sampling methodology to evaluate immunization coverage

BACKGROUND Immunization is a key component of primary health care and an indisputable human right.Vaccines are critical to the prevention and control of infectious disease outbreaks.The coronavirus disease 2019(COVID-19)pandemic and associated disruptions over the past two years have strained the health systems,with many children missing out on essential childhood vaccines.AIM To evaluate the immunization coverage among 12-23-month-old children in the rural areas of Community Health Centre(CHC)Dighal and to determine the factors influencing the existing immunization coverage.METHODS A coverage evaluation survey was conducted according to the 30-cluster sampling technique,which is the standard methodology for such surveys devised by World Health Organization.A total of 300 children aged 12-23 months were included,whose immunization details were noted from their immunization cards.RESULTS Full immunization rate was noted in 86.7%of the children,with partial and non-immunized children accounting for 9%and 4.3%respectively.The full immunization dropout rate was 4.2%.The common reasons for partial or non-immunization were family problem including illness of mother,vaccine not being available and child being ill.Place of birth(P=0.014)and availability of immunization card(P<0.001)were significant predictors of the immunization status.Since the study was conducted in 2020/2021,health services were disrupted due to the COVID-19 lockdown.CONCLUSION Due to the coverage being higher than the national average,it was concluded that the immunization coverage was optimal and not affected by the COVID-19 pandemic.

Analysis of Mobile and Internet Network Coverage: Propagation of Electromagnetic Waves and Concept of Digital Divide in Burundi

Mobile and Internet network coverage plays an important role in digital transformation and the exploitation of new services. The evolution of mobile networks from the first generation (1G) to the 5th generation is still a long process. 2G networks have developed the messaging service, which complements the already operational voice service. 2G technology has rapidly progressed to the third generation (3G), incorporating multimedia data transmission techniques. It then progressed to fourth generation (4G) and LTE (Long Term Evolution), increasing the transmission speed to improve 3G. Currently, developed countries have already moved to 5G. In developing countries, including Burundi, a member of the East African Community (ECA) where more than 80% are connected to 2G technologies, 40% are connected to the 3G network and 25% to the 4G network and are not yet connected to the 5G network and then still a process. The objective of this article is to analyze the coverage of 2G, 3G and 4G networks in Burundi. This analysis will make it possible to identify possible deficits in order to reduce the digital divide between connected urban areas and remote rural areas. Furthermore, this analysis will draw the attention of decision-makers to the need to deploy networks and coverage to allow the population to access mobile and Internet services and thus enable the digitalization of the population. Finally, this article shows the level of coverage, the digital divide and an overview of the deployment of base stations (BTS) throughout the country to promote the transformation and digital inclusion of services.

Dynamic Frontier-Led Swarming:Multi-Robot Repeated Coverage in Dynamic Environments

A common assumption of coverage path planning research is a static environment.Such environments require only a single visit to each area to achieve coverage.However,some real-world environments are characterised by the presence of unexpected,dynamic obstacles.They require areas to be revisited periodically to maintain an accurate coverage map,as well as reactive obstacle avoidance.This paper proposes a novel swarmbased control algorithm for multi-robot exploration and repeated coverage in environments with unknown,dynamic obstacles.The algorithm combines two elements:frontier-led swarming for driving exploration by a group of robots,and pheromone-based stigmergy for controlling repeated coverage while avoiding obstacles.We tested the performance of our approach on heterogeneous and homogeneous groups of mobile robots in different environments.We measure both repeated coverage performance and obstacle avoidance ability.Through a series of comparison experiments,we demonstrate that our proposed strategy has superior performance to recently presented multi-robot repeated coverage methodologies.

Energy-Efficient UAVs Coverage Path Planning Approach

Unmanned aerial vehicles(UAVs),commonly known as drones,have drawn significant consideration thanks to their agility,mobility,and flexibility features.They play a crucial role in modern reconnaissance,inspection,intelligence,and surveillance missions.Coverage path planning(CPP)which is one of the crucial aspects that determines an intelligent system’s quality seeks an optimal trajectory to fully cover the region of interest(ROI).However,the flight time of the UAV is limited due to a battery limitation and may not cover the whole region,especially in large region.Therefore,energy consumption is one of the most challenging issues that need to be optimized.In this paper,we propose an energy-efficient coverage path planning algorithm to solve the CPP problem.The objective is to generate a collision-free coverage path that minimizes the overall energy consumption and guarantees covering the whole region.To do so,the flight path is optimized and the number of turns is reduced to minimize the energy consumption.The proposed approach first decomposes the ROI into a set of cells depending on a UAV camera footprint.Then,the coverage path planning problem is formulated,where the exact solution is determined using the CPLEX solver.For small-scale problems,the CPLEX shows a better solution in a reasonable time.However,the CPLEX solver fails to generate the solution within a reasonable time for large-scale problems.Thus,to solve the model for large-scale problems,simulated annealing forCPP is developed.The results show that heuristic approaches yield a better solution for large-scale problems within amuch shorter execution time than the CPLEX solver.Finally,we compare the simulated annealing against the greedy algorithm.The results show that simulated annealing outperforms the greedy algorithm in generating better solution quality.

Region coverage control for multiple stratospheric airships with combined self-/event-triggered mechanism

The region coverage control problem of multiple stratospheric airships system is firstly addressed in this paper.Towards it,we propose a two-layer control framework with the artificial potential field(APF)-based region coverage control law and the adaptive tracking control law.The APF-based region coverage control law ensures the coverage task is achieved until every single stratospheric airship ends up performing station keeping where near the respective global minimum point,in which an innovative solution to the local minimum problem is put forward.The adaptive tracking control law is designed to realize motion control using tracking the desired velocity and angular velocity given by coverage control law,with the consideration of several practical control problems as unknown individual differences and external disturbances.To save resources,the combined self-/event-triggered mechanism designed therein significantly reduces the times of state information transmission and control law calculation.The effectiveness of the proposed control framework is verified through simulations.

Optimization method of linear barrier coverage deployment for multistatic radar

To address the problem of building linear barrier coverage with the location restriction, an optimization method for deploying multistatic radars is proposed, where the location restriction splits the deployment line into two segments. By proving the characteristics of deployment patterns, an optimal deployment sequence consisting of multiple deployment patterns is proposed and exploited to cover each segment. The types and numbers of deployment patterns are determined by an algorithm that combines the integer linear programming(ILP)and exhaustive method(EM). In addition, to reduce the computation amount, a formula is introduced to calculate the upper threshold of receivers’ number in a deployment pattern. Furthermore, since the objective function is non-convex and non-analytic, the overall model is divided into two layers concerning two suboptimization problems. Subsequently, another algorithm that integrates the segments and layers is proposed to determine the deployment parameters, such as the minimum cost, parameters of the optimal deployment sequence, and the location of the split point. Simulation results demonstrate that the proposed method can effectively determine the optimal deployment parameters under the location restriction.

Muti-Fusion Swarm Intelligence Optimization Algorithm in Base Station Coverage Optimization Problems

As millimeter waves will be widely used in the Internet of Things(IoT)and Telematics to provide high bandwidth communication and mass connectivity,the coverage optimization of base stations can effectively improve the quality of communication services.How to optimize the convergence speed of the base station coverage solution is crucial for IoT service providers.This paper proposes the Muti-Fusion Sparrow Search Algorithm(MFSSA)optimize the situation to address the problem of discrete coverage maximization and rapid convergence.Firstly,the initial swarm diversity is enriched using a sine chaotic map,and dynamic adaptive weighting is added to the discoverer location update strategy to improve the global search capability.Diverse swarms have a more remarkable ability to forage for food and avoid predation and are less likely to fall into a“precocious”state.Such a swarm is very suitable for solving NP-hard problems.Secondly,an elite opposition-based learning strategy is added to expand the search range of the algorithm,and a t-distribution-based one-fifth rule is introduced to reduce the probability of falling into a local optimum.This fusion mutation strategy can significantly optimize the adaptability and searchability of the algorithm.Finally,the experimental results show that the MFSSA algorithm can effectively improve the coverage of the deployment scheme in the base station coverage optimization problem,and the convergence speed is better than other algorithms.MFSSA is improved by more than 10%compared to the original algorithm.

Intelligent Deployment Model for Target Coverage in Wireless Sensor Network

Target coverage and continuous connection are the major recital factors for Wireless Sensor Network(WSN).Several previous research works studied various algorithms for target coverage difficulties;however they lacked to focus on improving the network’s life time in terms of energy.This research work mainly focuses on target coverage and area coverage problem in a heterogeneous WSN with increased network lifetime.The dynamic behavior of the target nodes is unpredictable,because the target nodes may move at any time in any direction of the network.Thus,target coverage becomes a major problem in WSN and its applications.To solve the issue,this research work is motivated to design and develop an intelligent model named Distributed Flexible Wheel Chain(DFWC)model for efficient target coverage and area coverage in WSN applications.More number of target nodes is covered by minimum number of sensor nodes that can improve energy efficiency.To be specific,DFWC motivated at obtaining lesser connected target coverage,where every target is available in the monitoring area is covered by a smaller number of sensor nodes.The simulation results show that the proposed DFWC model outperforms the existing models with improved performance.

Thinking Out-of-Box in Addressing Communication and Service Delivery Challenges: Use of a Traditional Communication Method for Improving Immunization Coverage in Remote Rural Hard-to-Reach Areas of India

Sirmaur district in the state of Himachal Pradesh in India is a hard-to-reach area situated in the western Himalayas having an extreme landscape with snow-laden mountains and extensive river systems that makes the delivery of immunization services extremely challenging. Vaccinators needed a long walk through the hilly terrain to reach outreach sites. Community mobilizers were unable to go house to house to inform the caregivers to bring children to the site for vaccination. Caregivers were unaware when the vaccinators arrive at the site. As a result, many children missed vaccination or were not vaccinated timely. Age-appropriate vaccination coverage (according to national immunization schedule) in the Sirmaur district was the lowest in the state. Thinking out-of-box to address the communication barriers with the caregivers, the traditional drum beating was used, for the first time in India, in two blocks of the Sirmaur district (Rajpura and Shillai). The initiative was planned and implemented by the district health system with the support of the local community leaders. An exit interview was conducted to know the reach of the drum beating to caregivers, and a baseline and end line household survey was conducted to know the outcome of the initiative on age-appropriate vaccination coverage. Analysis of exit interviews data indicated a very high reach of a drum beating to the caregivers;more than 97% of caregivers in Rajpura and 100% in Shillai heard drum beating, and almost 95% of caregivers in Rajpura and 98% in Shillai knew the purpose of drum beating. Analysis of immunization data from baseline and end line surveys showed improvement in age-appropriate vaccination coverage for all vaccines in Rajpura (by 2.2% for BCG, 15.3% for Pentavalent 1, 14.9% for Pentavalent 2, 14.1% for Pentavalent 3, and 6.5% for Measles/MR). In Shillai, age-appropriate vaccination coverage improved for Pentavalent 1 (by 3.4%), Pentavalent 2 (by 5%) and Measles/MR (by 1.7%). In addition, dropout rates were reduced in both the blocks, particularly in Rajpura Pentavalent 1 to Measles dropout rate was reduced by 13.5%. Both health workers and community leaders had positive perceptions of the drum beating initiative. However, another important lesson learned from the initiative was that both the access and demand-side barriers need to be addressed for the desired improvement of age-appropriate immunization coverage. In Shillai, there was lower coverage improvement and a reduction in dropout rates attributed to vacant positions of vaccinators that caused an issue with access to immunization services to people.

Universal Health Coverage in Somalia: Charting the Path to Equitable Healthcare Financing and Governance

Somalia is a country facing numerous challenges in achieving universal health coverage (UHC) and ensuring adequate healthcare financing, This article explores the complexities and obstacles that Somalia must overcome in its pursuit of UHC, the paper begins by providing an overview of the current healthcare landscape in Somalia, highlighting the lack of infrastructure, political instability, and limited financial resources that hinder the establishment of a comprehensive and equitable healthcare system. It then examines the role of international aid and non-governmental organizations (NGOs) in filling the healthcare gap, while emphasizing the need for a more sustainable, domestically financed solution. Drawing on a range of data sources and case studies, the article proposes a multi-faceted approach to strengthen healthcare governance, improve resource allocation, and foster local capacity building, the study delves into the unique obstacles that Somalia faces, including a lack of infrastructure, political instability, and limited financial resources, which hinder the establishment of a comprehensive and equitable healthcare system. The paper also examines the role of international aid and non-governmental organizations (NGOs) in filling the healthcare gap, while highlighting the need for a more sustainable, domestically financed solution. The findings underscore the importance of political commitment, international cooperation, and innovative financing mechanisms in advancing towards UHC in Somalia, providing valuable insights for other low resource, conflict affected settings.

Antiviral Therapy Eligibility and Low Treatment Coverage among Hepatitis B Virus Infected Patients in Tanzania

Introduction: Limited access to treatment is a crucial factor contributing to the suboptimal control of hepatitis B virus (HBV) infection, especially in sub-Saharan African countries such as Tanzania. The eligibility for antiviral therapy is typically determined based on the extent of HBV replication and liver damage. However, there is insufficient data available regarding the actual treatment needs and the overall characteristics of HBV-infected individuals in Tanzania. Therefore, the aim of this study is to fill this knowledge gap and provide valuable insights to aid in the planning of treatment programs. Materials and Methods: We conducted a cross-sectional study at Bugando Medical Centre in northwest Tanzania, examining the data of 340 patients who were diagnosed with chronic HBV infection and attending the hepatitis clinic. Data on sociodemographic, clinical, and investigation details were collected through electronic files and subsequently analyzed. The eligibility for HBV antiviral treatment was assessed using the criteria established by the World Health Organization (WHO). Results: Out of the 340 patients included in the study, the majorities were males 252 (74.1%) and had a median age of 36 years. Most patients came from outside of Mwanza city. Twenty-percent had significantly elevated alanine transaminase, and over one-third had high DNA levels (>2000 IU/L). The prevalences of liver cirrhosis and significant liver fibrosis were 15% and 15.3%, respectively. None of the patients were on antiviral therapy for hepatitis B. A total of 64 (18.8%) patients met the criteria for treatment eligibility. Male sex, older age, residing outside Mwanza city, and anemia (all with p Conclusion and Recommendations: The significant number of HBV-infected patients is suitable for antiviral therapy but none of them have initiated the treatment. The significance of these findings is to emphasize the need for enhancing hepatitis B services in Tanzania.

THE OPTIMAL DEDUCTIBLE AND COVERAGE IN INSURANCE CONTRACTS AND EQUILIBRIUM RISK SHARING POLICIES

In this paper, we consider the optimal risk sharing problem between two parties in the insurance business: the insurer and the insured. The risk is allocated between the insurer and the insured by setting a deductible and coverage in the insurance contract. We obtain the optimal deductible and coverage by considering the expected product of the two parties' utilities of terminal wealth according to stochastic optimal control theory. An equilibrium policy is also derived for when there are both a deductible and coverage;this is done by modelling the problem as a stochastic game in a continuous-time framework. A numerical example is provided to illustrate the results of the paper.

Multi-Agent Dynamic Area Coverage Based on Reinforcement Learning with Connected Agents

Dynamic area coverage with small unmanned aerial vehicle(UAV)systems is one of the major research topics due to limited payloads and the difficulty of decentralized decision-making process.Collaborative behavior of a group of UAVs in an unknown environment is another hard problem to be solved.In this paper,we propose a method for decentralized execution of multi-UAVs for dynamic area coverage problems.The proposed decentralized decision-making dynamic area coverage(DDMDAC)method utilizes reinforcement learning(RL)where each UAV is represented by an intelligent agent that learns policies to create collaborative behaviors in partially observable environment.Intelligent agents increase their global observations by gathering information about the environment by connecting with other agents.The connectivity provides a consensus for the decision-making process,while each agent takes decisions.At each step,agents acquire all reachable agents’states,determine the optimum location for maximal area coverage and receive reward using the covered rate on the target area,respectively.The method was tested in a multi-agent actor-critic simulation platform.In the study,it has been considered that each UAV has a certain communication distance as in real applications.The results show that UAVs with limited communication distance can act jointly in the target area and can successfully cover the area without guidance from the central command unit.

Energy Proficient Reduced Coverage Set with Particle Swarm Optimization for Distributed Sensor Network

Retransmission avoidance is an essential need for any type of wireless communication.As retransmissions induce the unnecessary presence of redundant data in every accessible node.As storage capacity is symmetrical to the size of the memory,less storage capacity is experienced due to the restricted size of the respective node.In this proposed work,we have discussed the integration of the Energy Proficient Reduced Coverage Set with Particle Swarm Optimization(PSO).PSO is a metaheuristic global search enhancement technique that promotes the searching of the best nodes in the search space.PSO is integrated with a Reduced Coverage Set,to obtain an optimal path with only high-power transmitting nodes.Energy Proficient Reduced Coverage Set with PSO constructs a set of only best nodes based on the fitness solution,to cover the whole network.The proposed algorithm has experimented with a different number of nodes.Comparison has been made between original and improved algorithm shows that improved algorithm performs better than the existing by reducing the redundant packet transmissions by 18%~40%,thereby increasing the network lifetime.