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Summary: Fifth generation cellular networks have high data rates and connectivity demands. The relaying approaches are widely used in cellular networks to improve coverage, user throughput, and capacity at low cost. The increasing data requirements of the mobile network increase energy consumption. Energy efficiency‐based approaches also impact network coverage and throughput. Therefore, developing an energy‐efficient network with optimal coverage and throughput is considered a challenging issue. It can be resolved with optimal deployment of Base Station (BS), Relay Station (RS), and minimizing power consumption. In this research, a joint clustering‐based deployment technique is proposed for BS–RS deployment by considering the network throughput and coverage ratio. After enabling optimal BS–RS deployment, the network traffic is estimated with an On‐demand real‐time traffic estimation framework (ODTE). It estimates user association values using Beacon frames. In addition, the Relay Assisted Base station Power Scheduling (RABPS) approach to minimize power consumption is included. Based on Erlang's probability, the RABPS algorithm is enhanced with sleep mode activation during off‐peak hours. The proposed 5G network ensures uninterrupted connectivity and energy efficiency with varying time slots of power scheduling. The throughput performance of the clustering‐based approach is increased with a coverage ratio of 88%. The simulation results show the superiority of the proposed 5G BS–RS deployment and power scheduling in terms of throughput, coverage ratio, and power consumption. [ABSTRACT FROM AUTHOR]

Abstract Time series classification (TSC) has attracted considerable attention from the data mining community over the past decades. One of the effective ways to handle this task is to find discriminative subsequences in time series to train a classifier. Obviously, how to measure the discriminative power of subsequences and find the optimal combination of subsequences is crucial to the accuracy of TSC. In this paper, we introduce a new method, CRMI, to find high-quality discriminative subsequences for multi-class time series classification (MC-TSC). Different from existing methods, there are two significant innovations in the work. At first, we propose a novel measure, named coverage ratio, to evaluate the discriminative power of a subsequence based on a coverage matrix which is figured out by the clustering technique. Second, a heuristic algorithm based on mutual information (MI) is proposed to find the optimal combination of subsequence candidates. The calculation of MI is also based on the coverage matrix. Extensive experiments were conducted on 54 UCR time series datasets with at least 3 categories, and the results show that (1) the proposed algorithm achieves the highest average accuracy and outperforms most of the existing shapelet-based TSC algorithms; (2) compared with existing methods, the proposed algorithm performs better on datasets with a large number of categories.

Introduction: With the increase in non-tariff measures (NTMs) in recent years, understanding their impact on trade policies and agricultural exports is of utmost importance for countries like Sri Lanka, where the proliferation of NTMs has posed substantial impediments to its mango export industry. However, studying NTMs can be challenging due to their complex nature, diverse range, and limited information availability. Methods: This research aims to investigate the significant effect of NTMs on Sri Lankan mango exports, identify the pivotal drivers influencing mango exports, and analyze the performance of mango exports in Sri Lanka. This study utilized a panel dataset of 16 importing countries spanning the period from 2000 to 2021. The primary focus was on examining NTM-related challenges and obstacles faced by the mango export industry in Sri Lanka. The identification and quantification of these obstacles were achieved through a multifaceted approach in which assessment of NTM-related rejections, both domestic and overseas, evaluation of NTM incidences using frequency and coverage ratio measures, and the deployment of various gravity model equations to quantify the effect of NTMs were taken into consideration. Probit, Ordinary Least Square, Random Effects, and Poisson Pseudo Maximum Likelihood estimation techniques were utilized for data analysis. Results: The findings indicate a significant inverse correlation between the increase in the total count of NTMs and Sri Lankan mango exports if the country aims to export more mangoes to relevant markets, while Sanitary and Phytosanitary Measures (SPS), Technical Barriers to Trade (TBT), and Pre-shipment Inspection (PSI) contributed to increased mango exports. Among other explanatory variables, the GDP of both importing and exporting countries had a positive influence on Sri Lankan mango exports. Surprisingly, the distance to the importing country had no significant effect, though it shows a negative sign. Discussion: This study provides valuable insights into the impact of NTMs on Sri Lankan mango exports. It highlights the considerable influence of NTMs on the overall fresh fruit export sector. We recommend proactively aligning internal quality testing regulations with the standards required by destination countries to promote future expansion. [ABSTRACT FROM AUTHOR]

The objective of this work is to improve the existing Wireless Sensor Network coverage optimization method. The pigeon-inspired optimization algorithm was first evaluated, and its shortcomings were noted. The pigeon-inspired optimization method was then enhanced with the good point set, Yin-Yang optimization algorithm, and opposition-based learning. To test the improved algorithm, five representative standard functions were chosen: sphere function (f1), Rosenbrock function (f2), Levy function (f3), Schwefel function (f4), and Levy function N.13 (f5). The algorithm's speed of convergence may be determined by the first two functions, which are unimodal. The final three functions, which are multimodal, can extract several local optimal values from the local optimum. In comparison with other known algorithms, the improved Yin-Yang PIO algorithm showed the highest optimization accuracy and stability. Three sets of experiments were performed to optimize the WSN coverage with different parameters. The first series of experiments suggest that Yin-Yang PIO has the best optimization effect, with a coverage rate of 99.51% (10.22% higher with PIO and 6.41% higher compared with PSO). The second and third series of experiments show that Yin-Yang PIO significantly increased the WSN coverage ratio, up to 99.9%. The algorithm can be applied to optimize WSN coverage in various environments. Future research can extend the research scope to include other optimization problems in IoT. [ABSTRACT FROM AUTHOR]

IntroductionWith the increase in non-tariff measures (NTMs) in recent years, understanding their impact on trade policies and agricultural exports is of utmost importance for countries like Sri Lanka, where the proliferation of NTMs has posed substantial impediments to its mango export industry. However, studying NTMs can be challenging due to their complex nature, diverse range, and limited information availability.MethodsThis research aims to investigate the significant effect of NTMs on Sri Lankan mango exports, identify the pivotal drivers influencing mango exports, and analyze the performance of mango exports in Sri Lanka. This study utilized a panel dataset of 16 importing countries spanning the period from 2000 to 2021. The primary focus was on examining NTM-related challenges and obstacles faced by the mango export industry in Sri Lanka. The identification and quantification of these obstacles were achieved through a multifaceted approach in which assessment of NTM-related rejections, both domestic and overseas, evaluation of NTM incidences using frequency and coverage ratio measures, and the deployment of various gravity model equations to quantify the effect of NTMs were taken into consideration. Probit, Ordinary Least Square, Random Effects, and Poisson Pseudo Maximum Likelihood estimation techniques were utilized for data analysis.ResultsThe findings indicate a significant inverse correlation between the increase in the total count of NTMs and Sri Lankan mango exports if the country aims to export more mangoes to relevant markets, while Sanitary and Phytosanitary Measures (SPS), Technical Barriers to Trade (TBT), and Pre-shipment Inspection (PSI) contributed to increased mango exports. Among other explanatory variables, the GDP of both importing and exporting countries had a positive influence on Sri Lankan mango exports. Surprisingly, the distance to the importing country had no significant effect, though it shows a negative sign.DiscussionThis study provides valuable insights into the impact of NTMs on Sri Lankan mango exports. It highlights the considerable influence of NTMs on the overall fresh fruit export sector. We recommend proactively aligning internal quality testing regulations with the standards required by destination countries to promote future expansion.

Global Competitiveness Index, high technology exports and coverage ratio variables were used in the study. The effects of high technology exports on the Global Competitiveness Index and coverage ratio, and the effects of the Global Competitiveness Index on the coverage ratio were analysed. Positive effects of the analyses were observed. It is also assumed that the coverage ratio is one of the most important criteria of foreign trade performance. In the study, it is seen that the Global Competitiveness Index plays an intermediary role in the effect of technology exports on the coverage ratio. Therefore, the increase in the share of technology exports in total trade affects the coverage ratio through the partial effect of the Global Competitiveness level. Therefore, it is assumed that the technological infrastructure and competitiveness of countries will play a key role in improving foreign trade performance.

Low trading costs, more significant consumer markets, and favourable economic ties between China and Pakistan provide a strong rationale for bilateral trade. Both countries have signed several bilateral trade agreements to boost mutual trade since 1963. The agreement that marked the beginning of a new era of cooperation between two trading partners and paved the way for free trade agreements was the Early Harvest Program (EHP), implemented in 2006. The first China-Pakistan Free Trade Agreement (CPFTA) was signed in November 2006 and became operational in 2007. CPFTA aimed to remove tariff and non-tariff barriers, enhance the comparative value of exports, and increase exportable surplus mainly through technical and financial cooperation. The paper critically evaluates the impact of tariff and non-tariff barriers on Pakistan’s key exports in the pre- and post-CPFTA period. Further, the study quantifies the impact of non-tariff barriers using quantitative techniques of restrictiveness index, converge ratio, and frequency index with 4-digit H.S. code industry-level data. The analysis reveals that China imposed a relatively high tariff rate on Pakistan's top five exports compared to China's other FTA partner countries. The results about the effect of non-tariff barriers (NTBs) show that exports related to cereals, edible fruits, and textile sectors are highly covered under Sanitary and Phytosanitary (SPS) and technical barriers to trade (TBT) despite FTA. Our findings have substantial implications for sustained trade ties between China and Pakistan.

Low trading costs, more significant consumer markets, and favourable economic ties between China and Pakistan provide a strong rationale for bilateral trade. Both countries have signed several bilateral trade agreements to boost mutual trade since 1963. The agreement that marked the beginning of a new era of cooperation between two trading partners and paved the way for free trade agreements was the Early Harvest Program (EHP), implemented in 2006. The first China-Pakistan Free Trade Agreement (CPFTA) was signed in November 2006 and became operational in 2007. CPFTA aimed to remove tariff and non-tariff barriers, enhance the comparative value of exports, and increase exportable surplus mainly through technical and financial cooperation. The paper critically evaluates the impact of tariff and non-tariff barriers on Pakistan’s key exports in the pre- and post-CPFTA period. Further, the study quantifies the impact of non-tariff barriers using quantitative techniques of restrictiveness index, converge ratio, and frequency index with 4-digit H.S. code industry-level data. The analysis reveals that China imposed a relatively high tariff rate on Pakistan's top five exports compared to China's other FTA partner countries. The results about the effect of non-tariff barriers (NTBs) show that exports related to cereals, edible fruits, and textile sectors are highly covered under Sanitary and Phytosanitary (SPS) and technical barriers to trade (TBT) despite FTA. Our findings have substantial implications for sustained trade ties between China and Pakistan.

The frog model is a system of interacting random walks. Initially, there is one particle at each vertex of a connected graph. All particles are inactive at time zero, except for the one which is placed at the root of the graph, which is active. At each instant of time, each active particle may die with probability 1 - p . Once an active particle survives, it jumps on one of its nearest vertices, chosen with uniform probability, performing a discrete time simple symmetric random walk (SRW). Up to the time it dies, it activates all inactive particles it hits along its way. From the moment they are activated, every such particle starts to walk, performing exactly the same dynamics, independent of everything else. In this paper, we consider the n - complete graph (a finite graph with each pair of vertices linked by an edge). We study the limit in n of the coverage ratio, that is, the proportion of visited vertices by some active particle up to the end of the process, after all active particles have died. [ABSTRACT FROM AUTHOR]

The deployment of base stations (BSs) is an extremely important matter in an internet of things (IoT) system. When a BS location is poorly deployed, it will cause the overall coverage of sensor devices (SDs) to decrease. Hence, the more BSs are required to increase the number of covered SDs in IoT systems. It leads to a higher deployment budget of BSs. However, BSs cannot be deployed everywhere in real environments. Taking the SDs positions and BSs candidate locations into account, we design an efficient and novel BSs deployment strategy to maximize the number of covered SDs and to reduce the deployment budget of BSs in IoT systems. We employ the Intuitionistic Fuzzy Sets (IFS) to make an adjustment decision for determining suitable BSs deployment positions from the BS candidate locations. Simulation results demonstrate that our proposed IFS BS deployment strategy achieves a higher coverage ratio of SDs and a favorable deployment budget of BSs in IoT systems. [ABSTRACT FROM AUTHOR]

Global Competitiveness Index, high technology exports and coverage ratio variables were used in the study. The effects of high technology exports on the Global Competitiveness Index and coverage ratio, and the effects of the Global Competitiveness Index on the coverage ratio were analysed. Positive effects of the analyses were observed. It is also assumed that the coverage ratio is one of the most important criteria of foreign trade performance. In the study, it is seen that the Global Competitiveness Index plays an intermediary role in the effect of technology exports on the coverage ratio. Therefore, the increase in the share of technology exports in total trade affects the coverage ratio through the partial effect of the Global Competitiveness level. Therefore, it is assumed that the technological infrastructure and competitiveness of countries will play a key role in improving foreign trade performance. [ABSTRACT FROM AUTHOR]

In the article, a study of the impact of the Russian-Ukrainian war on processes in Ukraine's foreign trade has been conducted. The work performed is based on the wide use of indicators, methods and techniques of economic and statistical analysis. An analysis of changes in the regional and commodity structures of export was carried out, some aspects of the financial results of foreign trade were also considered. It has been established that in the regions of hostilities and those close to them, namely in 10 regions and the city of Kyiv, which in 2021 accounted for 73.2% of Ukraine's commodity exports, in 2022 external supplies of goods decreased by 23.9 billion USD, which is an 89.0% decrease in Ukraine as a whole, and in the Donetsk and Luhansk regions such activity has practically stopped.The analysis also showed significant changes in the commodity structure of exports. Since the mentioned regions were leaders in the export of mineral products, products of chemical and related industries, and non-precious metals and products from them, the decrease in their share in total exports from 47.7% in 2021 to 34.8% affected on the dynamics of the structure of export of goods - the share of agro-food products increased from 40.7% in 2021 to 53.0% in 2022. For the first time in the modern history of Ukraine, agro-food products make up only half of its exports. The analysis emphasizes the extreme dependence of Ukraine's export activity on the operation of transport, especially sea transport. The blockade of seaports disrupted supplies to countries in Asia and Africa, while the use of rail and road transport increased exports to EU countries from $26.8 billion. and in 2021 up to 27.9 billion dollars, which, of course, should lead to certain changes in the trade policy, the directions of export flows, the structure of transportation by various modes of transport. The financial results of foreign trade in goods were analyzed, where it was established that as a result of military operations, the balance from trade in non-precious metals decreased and agro-food products became the main source of obtaining an active balance. The conclusions present recommendations regarding the growth of exports of agro-food products in particular, which will allow maintaining at a certain level both the amount of foreign exchange earnings and the active balance. The financial results of foreign trade in goods were analyzed, where it was established that as a result of military operations, the balance from trade in non-precious metals decreased and agro-food products became the main source of obtaining an active balance. The conclusions present recommendations regarding the growth of exports of agro-food products in particular, which will allow maintaining at a certain level both the amount of foreign exchange earnings and the active balance. [ABSTRACT FROM AUTHOR]

One of the most important challenges for heterogeneous wireless sensor networks (HWSNs) is adequate network coverage and connectivity. Aiming at this problem, this paper proposes an improved wild horse optimizer algorithm (IWHO). Firstly, the population's variety is increased by using the SPM chaotic mapping at initialization; secondly, the WHO and Golden Sine Algorithm (Golden-SA) are hybridized to improve the WHO's accuracy and arrive at faster convergence; Thirdly, the IWHO can escape from a local optimum and broaden the search space by using opposition-based learning and the Cauchy variation strategy. The results indicate that the IWHO has the best capacity for optimization by contrasting the simulation tests with seven algorithms on 23 test functions. Finally, three sets of coverage optimization experiments in different simulated environments are designed to test the effectiveness of this algorithm. The validation results demonstrate that the IWHO can achieve better and more effective sensor connectivity and coverage ratio compared to that of several algorithms. After optimization, the HWSN's coverage and connectivity ratio attained 98.51% and 20.04%, and after adding obstacles, 97.79% and 17.44%, respectively. [ABSTRACT FROM AUTHOR]

IntroductionAutonomous underwater vehicles (AUVs) are required to thoroughly scan designated areas during underwater missions. They typically follow a zig-zag trajectory to achieve full coverage. However, effective coverage can be challenging in complex environments due to the accumulation and drift of navigation errors. Possible solutions include surfacing for satellite positioning or underwater acoustic positioning using transponders on other vehicles. Nevertheless, surfacing or active acoustics can compromise stealth during reconnaissance missions in hostile areas by revealing the vehicle’s location.MethodsWe propose calibration and planning strategies based on error models and acoustic positioning to address this challenge. Acoustic markers are deployed via surface ships to minimize navigation errors while maintaining stealth. And a new path planning method using a traceless Kalman filter and acoustic localization is proposed to achieve full-area coverage of AUVs. By analyzing the statistics of accumulated sensor errors, we optimize the positions of acoustic markers to communicate with AUVs and achieve better coverage. AUV trajectory concealment is achieved during detection by randomizing the USV navigation trajectory and irregularizing the locations of acoustic marker.ResultsThe proposed method enables the cumulative determination of the absolute position of a target with low localization error in a side-scan sonar-based search task. Simulations based on large-scale maps demonstrate the effectiveness and robustness of the proposed algorithm.DiscussionSolving the problem of accumulating underwater localization errors based on inertial navigation by error modeling and acoustic calibration is a typical way. In this paper, we have implemented a method to solve the localization error in a search scenario where stealth is considered.

This study analyzes the impact of Non-tariff Measures (NTMs) on the direction of Agricultural and Processed Food exports (APFE) after the establishment of WTO. The countries have been classified into three groups viz Developed, Developing and LDC countries, to assess the impact of NTMs on the direction of export. An increasing trend was observed for the agricultural and processed food export to Developed Countries for selective years in terms of export value. But in terms of percentage share, a decreasing trend has been observed. There is no difference has been seen in the percentage share and value of agriculture trade to developing countries. It has been recognized that there is an increasing trend presented for LDC for all the selective years compared to the base period in value terms and it has also been noted that the percentage share of APF export to LDC has been increasing during the period. To analyze the impact of Non-Tariff Measures (NTMs) on the Direction of India's exports, particularly in agriculture and food products, the prevalence of NTMs in trade is calculated by the way of incidence indicators viz. the coverage Ratio (CR), the Frequency Index (FI), and the Prevalence Score (PS). The data for all the indicators have been collected from the UNCTAD-TRAINS database for all the sectors and the agricultural sector. The countries those rank declined in 2022 compared to the year 1995 in terms of the import value of agricultural and processed food from India, these countries have the highest level of coverage ratio, frequency index, and prevalence score. It is confirmed that the nexus between NTMs and India's agricultural and processed food exports in the case of India after establishment of WTO. [ABSTRACT FROM AUTHOR]

• UAV Downwash flow impacts the spray structure and droplet deposition uniformity. • Drone flight altitude defines the downwash flow impact on canopy and drift potential. • Drone flight speed increases the propagation of droplet deposition. • Nozzle position under the propeller should be selected by care. • Spray issued by air induction nozzle has much higher resistance against the downwash flow impact of the propeller compare to XR type. Delivering pesticides in the agricultural field has been a venturing advancement in the past decades with the aim of target spraying. Agricultural drones have been introduced as useful assets for target spraying, however, the turbulent downwash flow generated by the drone blades accelerates the atomization process that attributes to the drift potential. In this experimental study, the effect of downwash flow on an air induction nozzle is compared to that of a conventional flat fan XR nozzle under various drone operating conditions to evaluate the best working condition. The test was carried out in an indoor facility in which the effect of environmental parameters can be minimized. The 2D patternation of the droplet deposition known as coverage ratio was evaluated using water-sensitive papers with the change of operating conditions, including nozzle type, drone speed, flying height, and blade rotational speed. As the drone flight speed, height, rotational speed, and nozzle position changed, alterations in droplet size and coverage uniformity were observed along with propagation in the drift effect. In addition, the coverage ratio of the AI nozzle was higher than that of the XR nozzle. [ABSTRACT FROM AUTHOR]

The root-knot nematodes (genus Meloidogyne) are important plant parasites causing substantial agricultural losses. The Meloidogyne incognita group (MIG) of species, most of which are obligatory apomicts (mitotic parthenogens), are extremely polyphagous and important problems for global agriculture. While understanding the genomic basis for their variable success on different crops could benefit future agriculture, analyses of their genomes are challenging due to complex evolutionary histories that may incorporate hybridization, ploidy changes, and chromosomal fragmentation. Here, we sequence 19 genomes, representing five species of key root-knot nematodes collected from different geographic origins. We show that a hybrid origin that predated speciation within the MIG has resulted in each species possessing two divergent genomic copies. Additionally, the apomictic MIG species are hypotriploids, with a proportion of one genome present in a second copy. The hypotriploid proportion varies among species. The evolutionary history of the MIG genomes is revealed to be very dynamic, with noncrossover recombination both homogenizing the genomic copies, and acting as a mechanism for generating divergence between species. Interestingly, the automictic MIG species M. floridensis differs from the apomict species in that it has become homozygous throughout much of its genome.

Objectives : After investigation of types, characteristics, and domestic and overseas installation cases of floating photovoltaic power plants (FPVs), both power generation capacity and coverage ratio of the FPVs were analyzed, and the major environmental issues impacting on water quality and aquatic ecosystem were reviewed. Methods : Both information and data of the FPVs extracted from existing literature and provided by the FPVs installation companies were statistically analyzed. Results and Discussion : FPVs divided into three types such as pontoon type, frame type, and solar tracking type are installed in various ways by country and region. As of the second half of 2018, the global power generation capacity of FPVs is 1.3 GWp, and FPVs have been intensively installed in China, Japan, Korea, Taiwan, and UK. While the pontoon type has been mainly installed in other countries except Korea, the frame type was mainly installed in Korea. Among various water resources, FPVs installed in agricultural water resources have various power generation capacity and coverage ratio whereas FPVs installed in industrial, rainwater storage, and other water resources have relatively high power generation capacity and coverage ratio. Compared to FPVs installed in other water resources, FPVs installed in drinking water resources have relatively low power generation capacity and coverage ratio. After reviewing the major environmental issues related to FPVs (i.e., leaching of hazardous substances, deterioration of water quality and aquatic ecosystem, changes in water temperature and illumination, and disturbance of aquatic ecosystem), the impacts of the FPVs on water environment are found to be insignificant, and the positive effects (i.e., mitigation of green tide and restoration of the aquatic ecosystem) are confirmed. Conclusions : Although the impacts of the FPVs on water environment (water quality and aquatic ecosystem) are found to be insignificant, additional experiments reflecting extreme conditions and long-term continuous monitoring of water quality and aquatic ecosystem in terms of coverage ratio, array and type of FPVs are required.

Derivatives markets show that their structure is always characterized by periods of strong price fluctuations. This is true regardless of the underlying asset of the futures contracts considered, whether they are commodities, interest rates, exchange rates, shares, stock market indices, etc. By locking in future prices, the primary objective of these markets is to limit the risks faced by operators. This article proposes a new method of optimizing the coverage ratio by futures contracts to minimize price variance and thus apply this new technique to reduce the risk associated with Brent price volatility for the period from January 2010 to December 2020. The variance minimization model of Ederington's (1979) is the first and most widely used coverage model and the one that dominates the literature on this area which helps to find the optimal coverage ratio, and is also the objective function in our particle assay optimization algorithm in MATLAB and we will better interpret our results with statistical analysis and lastly, we will evaluate the effectiveness of the coverage model. [ABSTRACT FROM AUTHOR]

This paper presents both experimental measurements and three-dimensional (3D) numerical simulations of turbulent flow in open channels with simulated partial ice-covers. The experiments were conducted with a particle image velocimetry system while the simulations were performed with five eddy-viscosity and second-moment closure turbulence models. Four coverage ratios based on the channel width were examined in each case: a reference fully open channel and 25%, 50% and 75% partially covered channels. The results showed that the influence of the partial ice-covers and secondary currents near the sidewall dramatically altered the distributions of the mean velocity, Reynolds stresses and turbulence production across the channel. Based on the 3D simulations, it was shown that the modifications to the turbulence quantities were largely influenced by strong counter-rotating secondary circulations in the core of the partially covered channels and eight smaller secondary cells at the corners. The core secondary circulations interact with adjacent corner cells to form a dynamic link between the open water and ice-covered sections of the channel. [ABSTRACT FROM AUTHOR]

One of the most important challenges for heterogeneous wireless sensor networks (HWSNs) is adequate network coverage and connectivity. Aiming at this problem, this paper proposes an improved wild horse optimizer algorithm (IWHO). Firstly, the population’s variety is increased by using the SPM chaotic mapping at initialization; secondly, the WHO and Golden Sine Algorithm (Golden-SA) are hybridized to improve the WHO’s accuracy and arrive at faster convergence; Thirdly, the IWHO can escape from a local optimum and broaden the search space by using opposition-based learning and the Cauchy variation strategy. The results indicate that the IWHO has the best capacity for optimization by contrasting the simulation tests with seven algorithms on 23 test functions. Finally, three sets of coverage optimization experiments in different simulated environments are designed to test the effectiveness of this algorithm. The validation results demonstrate that the IWHO can achieve better and more effective sensor connectivity and coverage ratio compared to that of several algorithms. After optimization, the HWSN’s coverage and connectivity ratio attained 98.51% and 20.04%, and after adding obstacles, 97.79% and 17.44%, respectively.

Wireless Sensor Network (WSN) is widely used for collecting the information from the target region by deploying the sensor nodes in that region. In WSNs, energy saving is the prime task which depends upon the number of Cluster Heads (CH) and on their selection techniques. Thus, in order to optimize the energy consumption of the clusters, we are proposing an Energy-efficient technique for selection of Optimum Number of Cluster Head and Grid Head (EOCGS) which extends the network lifetime. Here, firstly we give the expression of optimum number of clusters, then propose a new technique for selecting the optimum number of CHs in an energy efficient manner. For saving the energy of the CHs, the concept of Grid Head (GH) is being added in an efficient way, which works in dynamic mode. When the number of CHs are greater than threshold limit, then few of the CHs work as GHs and they are selected by using the proposed fitness function that depends on residual energy, Euclidean distances, and location of the grid-centroid of CHs. We have depicted that the proposed work saves the network energy efficiently, extends the network lifetime and coverage as compared to similar clustering algorithms e.g., LEACH, TL-LEACH, R-LEACH, RCH-LEACH, UCRA-GSO & CCA-GWO. It also stabilizes the cluster formation in the network. [ABSTRACT FROM AUTHOR]

In the existing work of unmanned aerial vehicle base station (UAV-BS) deployment, where serving radius (SR) is fixed regardless of resource waste and overlapping interference, dynamic tunability of SR has not been considered. In this letter, a dynamic tunable model where SR can be properly adjusted is proposed, based on which a semi-progressive offloading deployment scheme devoted to UAV number and overlapping interference optimization is raised. Specifically, UAV is deployed around macro base stations (MBSs), where a certain proportion (γ) of the ground terminals (GTs) are covered first with the principle of minimum overlap and maximum coverage, then through tunability of SR, the rest GTs are covered without increasing UAV number. Moreover, the base station expands its SR to cover the closest uncovered GT through fine adjustment of power (MBS) or antenna down-tilt (UAV), after which surrounding UAVs are also adjusted to reduce overlapping interference. The results show our proposed scheme reduces 17.26% UAV quantity compared with the cluster method and decreases 71.75% interference compared with the core-set method. [ABSTRACT FROM AUTHOR]

A series of experiments were conducted beneath simulated partial ice covers to investigate the turbulent flow behaviour using a particle image velocimetry system. The velocity data were used to assess predictive capabilities of some bed shear stress models developed for open channels. Specifically, the abilities of the Ludwieg–Tillmann, quadratic stress law and Prandtl's seventh power law techniques to estimate the bed shear stress were compared to estimates from the logarithmic law technique. The ice coverage ratios considered were 0% (representing open water condition), 25%, 50% and 75%. Increasing ice coverage ratio to 50% and 75% increased the freestream velocity by approximately 8%. The dynamic role of secondary flow caused prevalence of the dip phenomenon under open water conditions and increased level of large-scale anisotropy. The present results depict easy adoption of the quadratic and Prandtl's seventh power laws to partial ice-covered flows. [ABSTRACT FROM AUTHOR]

This paper reports the water-flume experimental results of the vortex-induced vibration (VIV) of a circular cylinder partially covered with marine biofouling with various coverage ratios. The elastically mounted cylinder model is partially covered with real moss, which extends from the bottom to top at uniform intervals. The two-degree-of-freedom (2-DOF) vibration and the wake characteristics of the roughed cylinder were monitored with two laser displacement sensors and a particle image velocimetry, respectively. The VIV response was examined in the reduced velocity range of 1.29–11.32, and the coverage ratio (C R) ranging from 0 % to 60 % with an increment of 15 %. The experimental results indicate that the maximum cross-flow amplitude of the roughed cylinder decreases in comparison with the smooth cylinder, suggesting the vibration suppression. Nevertheless, the lock-in region is significantly widened with the attachment of moss. The roughed cylinder with coverage ratio of 30 % exhibits the widest lock-in region. The shift of response from the initial branch to the lower branch is related to the jump of phase difference from 0° to 180°. Compared to the smooth cylinder, the jump of φ shift to occur at a higher U r for roughed cylinders. As C R increases, more vortices are shed from the roughed cylinder, contributing to the occurrence of 2P (two pairs of vortices are alternately shed from two sides per cycle) and 2T (three vortices are shed from each side of the cylinder per cycle) modes. The shift of vibration branch is also associated with the evolution of vortex shedding pattern. • Vibration of a cylinder partially covered with real moss is experimentally studied. • The lock-in region of cross-flow response is widened with the attachment of moss. • The shift of vibration branch is related to the evolution of vortex shedding pattern. • The vortex shedding is sensitive to both coverage ratio and reduced velocity. [ABSTRACT FROM AUTHOR]

This study aims to analyze the impact of Non tariff measures using sanitary and phytosanitary policy (SPS) and technical trade barriers (TBTs) on fishery exports of Indonesia and its trading partner countries such as China, South Korea, Vietnam, Canada, Russia and the European Union in period of 2007 to 2016. SPS and TBT are measured using inventory approach in the form of coverage ratio. In addition, this study uses a gravity model and panel data regression method. The results of this study indicate that the variables GDP of exporting country and GDP of importing country have a positive and significant effect on Indonesian fishery exports. Distance and SPS have a negative and significant effect on Indonesian fishery exports, while TBT has no effect on Indonesian fishery exports. Keywords: Export, SPS and TBT, Fishery Export, Coverage Ratio JEL Classification: F10, F130

In recent years singular spectrum analysis (SSA) has been used as a powerful technique to analyze time series, including theoretical developments and application to many practical problems. However, no inclusive theoretical approach has been discussed regarding the construction of confidence intervals for forecasts. Due to the prominent role of prediction intervals in evaluating the accuracy of forecasts in time series analysis, in this paper, we consider the topic of constructing prediction intervals for SSA. Namely, we revise the existing approaches for the vector SSA forecasting method and propose a new median‐based alternative to this algorithm where the mean in the diagonal averaging step of the SSA algorithm is replaced by the median. The results from the existing and proposed approaches are compared by considering Monte Carlo simulations and real data applications. [ABSTRACT FROM AUTHOR]

Due to the low efficiency of thermoelectric generators (TEGs), many scholars have focused on the structural optimization of TEGs rather than on the optimization of the layout of thermoelectric modules. We aimed to investigate the effect of module layout on the output power of an automotive exhaust thermoelectric power generation system. The module spacing and module coverage ratio were compared under different working conditions based on a numerical simulation. The results show that, under high-temperature conditions, when the module spacing expands from 5 mm to 35 mm, the output power growth rate of modules of different sizes ranges between 8% and 9%. Moreover, under low-temperature conditions, a high coverage ratio of modules will not increase the total output power but, instead, make it decline. In fact, choosing a larger-size module can improve the temperature uniformity, thereby increasing the output power of the automotive thermoelectric power generation system. Hence, the present study has verified that, under different working conditions, different module layouts and module coverage ratios have an impact on the output power of the thermoelectric power generation system, which sheds new light on the improvement of automotive thermoelectric power generation systems.

The orthogonal frequency division multiple access (OFDMA)-based cooperative multicast (CM) technology realizing the intra-cooperation of multicast group (MG) has improved the performance in throughput and coverage. In the MG scenario, users are uniformly distributed. Due to the small effective transmission range of relay user (RU), the cooperation is hindered, which limits the performance of CM. Therefore, non-orthogonal multiple access (NOMA)-based two MGs joint cooperative opportunistic multicast scheme (termed as COM-NOMA) is proposed. In COM-NOMA scheme, two MGs are served as one quasi-MG. First, on the same frequency band, base station (BS) opportunistically multicasts the superposition signal, which is formed by two MGs' signals, to the users with good channel conditions in the two MGs using NOMA way. Second, some successfully receiving users are selected as RUs. The superposition signal is forwarded to the other users by Device-to-Device multicast way. Then, according to the coverage ratio of BS and the decode condition of NOMA, the signal to interference and noise ratio threshold for RU selection is given. Finally, the spectral efficiency of COM-NOMA is analyzed and the approximate expression of system coverage ratio is derived. The simulation results show that, spectral efficiency at unit transmit power (spectral efficiency per watt) and system coverage ratio is improved in comparison with other OFDMA-based CM schemes.

Li, C.-Y.; Weng, W.-K.; Shih, R.-S.; Yang, C.-K., and Lo, J.-S., 2019. Enhancing wave energy harvesting with a submerged crescent-shaped plate. Journal of Coastal Research, 35(5), 985–995. Coconut Creek (Florida), ISSN 0749-0208. Wave energy converters (WECs) are devices that capture energy from waves, which is usually dictated by wave conditions. In this study, a rectangular wave farm with generic point absorber WECs was placed behind a submerged crescent-shaped plate to investigate whether the plate increases the amount of captured energy. A numerical model that describes the wave field around the plate, based on the boundary element method, was developed and validated with experimental results. When waves move past the plate, the combined effects of shoaling, refraction, and diffraction cause waves behind the plate to increase in height. Two parameters, the dimensionless energy extraction coefficient and the buoy coverage ratio, were investigated using long- and short-period waves with the aim of enhancing energy harvesting behind the submerged crescent-shaped plate. The results suggest that increasing the energy extraction coefficient and coverage ratio do not ensure increased harvesting efficiency; rather, these parameters may cause changes in the nearby wave field because of greater wave reflection and diffraction. A dimensionless energy extraction coefficient of 1.0 and a buoy coverage ratio of 0.1 were proposed as optimal parameters for all wave periods under the conditions of this study. In this rectangular wave farm, most energy was captured in the area closest to the submerged plate (30% of the total wave farm), and a lower buoy coverage ratio caused less wave reflection and diffraction in the wave field around the plate. [ABSTRACT FROM AUTHOR]

Abstract An EAST Articulated Maintenance Arm (EAMA), upgraded based on an articulated inspection arm (AIA), which was successfully operated in Tore Supra in 2008, was developed for the purpose of the inspection and maintenance of damaged internal components during plasma discharges without breaking the East Advanced Superconducting Tokamak (EAST) ultra-high vacuum condition. However, the coupling structure and high redundancy of the EAMA, due to the requirement of coverage ratio and the limitation of the EAST environment, produces a limited accuracy in positioning control. Therefore, the optimal design of the geometric parameters plays a vital role in the EAMA's performance. In this paper, the main characteristics of the EAMA system are investigated to formulate the optimization into a multi-objective problem. Furthermore, an approach based on the Monte Carlo method, integrated with a dedicated collision detection algorithm in the EAST environment, is elaborated on, which is utilized to calculate the collision-free workspace of the EAMA. With the knowledge of the workspace, the coverage ratio is obtained by a progressive meshing technique. Finally, several groups of geometric parameters are sampled to calculate the corresponding value of the objective functions, and the optimized combination of the geometric parameters is obtained by comparing the results. [ABSTRACT FROM AUTHOR]

Highlights • A Quadrigeminal Scheme of Event Reporting Scalar Premier Selection is presented. • Scalar premier in each virtual sub-region acts as messenger for communication. • Proposed method minimizes the number of cameras actuated. • Amount of redundant data transmission is minimized. • Higher coverage ratio is obtained for the proposed method. Abstract In this article, we have proposed a novel quadrigeminal scheme for selecting event-reporting scalar premiers that inform the prevailing event information to their corresponding camera sensors while contributing maximal event area coverage along with minimal redundant data transmission. In this work, we have divided the monitored region into a number of sub-regions. Subsequently, each sub-region is further divided into smaller sub-regions. In each of the larger sub-regions, four scalar premiers are chosen in such a way that a single scalar premier exists in one smaller sub-region. Subsequently, the cameras are activated by matching their scalar premier ids with each other based on descending order of their total scalar premier count values. The efficiency of the proposed scheme has been verified by experimental investigation and comparative assessment against three well known existing algorithms. The least camera actuation, improved coverage ratio along with reduced values of event-loss ratio, redundancy ratio and energy expenditure obtained from the experimentation affirm the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The energy utilization of green cellular networking or cellular network infrastructure has become a popular research domain due to the economic concern of network operators and global climate change. Also, due to the growth of wireless networks, the authors are attracted to finding novel relay station (RS) deployment techniques to support high user density and high data rate services by reducing energy consumption and operating costs of different network elements. The location of RSs greatly influences how far a cell can be covered. Therefore, the deployment RS plays a major role in widening the cell's coverage radius. To solve these challenges and to realize greener network designs by maximizing power consumption with QoS assurance, a novel traffic-based power consumption minimization and node deployment for the LTE green cellular networks is proposed. Also, key performance indicators (KPIs) are required to monitor and improve network performance. KPIs control the accomplished resource utilization and the quality of services. The research work comprises RS deployment, traffic estimation, and power allocation. Power losses, communication delays, increased implementation costs, and decreased throughput are the effects of an inappropriate RS deployment. Therefore, this research introduces the transmission area-based relay stations deployment scheme (TARSD) with multiobjective functions maximization of coverage area, minimization of the overlapping area and the minimization of power consumption cost. Traffic estimation helps to identify future capacity requirements and enables improved planning and decision-making. The deployment scheme of a cellular network relies on network traffic estimation. Nash traffic entropy learning algorithm (NTEL) is used to estimate traffic, and based on the estimated eNB switching ON/OFF is performed to minimize power consumption. Inter cell interference (ICI) can impact the performance of the LTE network. Several power allocation schemes can be used to improve system performance to achieve the optimal trade-off between interference and signal-to-noise ratio (SINR). Because of its good performance and efficacy in improving the mutual information between a channel's input and output, the enhanced low complexity water-filling (ELCWF) has been widely employed in power allocation with its increment and decrement properties. This research studies the statistical behaviour of a Received Signal Strength Indicator (RSSI), Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ) and Signal to Interference noise Ratio (SINR). Also, statistical analysis of cost versus coverage performance is examined. Under the 7th simulation run, the proposed method yields the best coverage of 88.81 and 98.74%, respectively. In the experimental scenario, for the proposed model, the deployment cost for BS and RS are 27 and 13 units, the average throughput per user is 9.74 Mbps, and the coverage ratio is 97% under the BS candidate location of 20, respectively. In the power allocation stage, if the number of users is 50, the proposed model yields a power consumption of 0.2 W, throughput of 23.4 Mbps, delay of 15 ms and SINR of 20.12 dB, respectively. [ABSTRACT FROM AUTHOR]

Both the shape and distribution of embedded plasmon nanoparticles within the absorption layer are crucial factors affecting the optical properties of solar cells significantly. Herein, by employing a finite element method (FEM), we proposed a perovskite solar cell (PSC) by introducing a layer of position-randomly-distributed (PRD) ellipsoidal Ag nanoparticles in the CH 3 NH 3 PbI 3 thin film as they provide prototype nanoparticles encountered in experiments. The corresponding absorption spectra and photocurrent were calculated and optimized as a function of both their eccentricity and coverage, which are elucidated well in terms of their EM distributions. The maximum photocurrent is revealed to reach 22.68 mA/cm2, which is 1.18 times larger than that of planar reference. The present work is believed to be insightful for further boosting the optical efficiency of PSCs and easy of choosing appropriate coverage ratio and eccentricity of the embedded ellipsoidal Ag nanoparticles. • A PSC embedded with PRD ellipsoidal Ag NPs was proposed. • The obtained Jsc is improved 13 % and 5 % by subsequently tuning e and F of the embedded PRD Ag NPs, respectively. • The random distribution of PRD NPs will not destroy the obtained Jsc responses. • The maximum Jsc is shown to reach 22.68 mA/cm2, which is 1.18 times larger than that of planar reference PSC. [ABSTRACT FROM AUTHOR]

Este trabajo predice la volatilidad de la rentabilidad diaria del precio del azúcar, en el período compren­dido entre 1 de junio de 2011 y el 24 de octubre de 2013. Los datos diarios utilizados fueron los precios del azúcar, del etanol y la tasa de cambio de la moneda de Brasil (Real) en dólares. Se usaron modelos multivariados de volatilidad autoregresiva condicional generalizada. A partir de la predicción de los precios del azúcar se calcula la razón de cobertura de mínima varianza. Los resultados muestran, que la razón de cobertura es 0.37, esto significa que, si un productor adverso al riesgo, que tiene la intención de eliminar un porcentaje de la volatilidad de la rentabilidad diaria del mercado mundial del azúcar, y espera vender 25 contratos de azúcar, cada uno de ellos de 50,84 toneladas (1.271 toneladas), el número de contratos optimo tomando cobertura a futuro será 9 y el número de contratos sin tomar cobertura (de contado) será 16. This work predicts the volatility of the daily profitability of sugar prices for the period between 1 of June 2001 and 24th of October 2013. The daily data collected covered sugar, ethanol and the Brazilian Real and USD exchange rate information. The models used were multivariate generalized conditional autoregressive volatility. Parting from the sugar price prediction, the coverage ratio for the minimum variance is calculated. Results show that the coverage ratio is 0.37. This means that in the case of a risk adverse producer that wants to eliminate a percentage of volatility of the world´s sugar market daily profitability, and expects to sell 25 sugar contracts, 50,84 tons each, (1,271 tons), the optimal number of contracts with future cover­age will be 9 and the number of contracts without coverage (spot price) will be 16

In a random deployment or uniform deployment strategy, sensor nodes are scattered randomly or uniformly in the sensing field, respectively. Hence, the coverage ratio cannot be guaranteed. The coverage ratio of uniform deployment, in general, is larger than that of the random deployment strategy. However, a random deployment or uniform deployment strategy may cause unbalanced traffic pattern in wireless sensor networks (WSNs). Therefore, cluster heads (CHs) around the sink have larger loads than those farther away from the sink. That is, CHs close to the sink exhaust their energy earlier. In order to overcome the above problem, we propose a Hexagon-based Intelligent Grouping approacH in WSNs (called HIGH). The coverage, energy consumption and data routing issues are well investigated and taken into consideration in the proposed HIGH scheme. The simulation results validate our theoretical analysis and show that the proposed HIGH scheme achieves a satisfactory coverage ratio, balances the energy consumption among sensor nodes, and extends network lifetime significantly.