Profit-Driven Adaptive Moving Targets Search with UAV Swarms

This paper presents a novel distributed algorithm for a moving targets search with a team of cooperative unmanned aerial vehicles (UAVs). UAVs sense targets using on-board sensors and the information can be shared with teammates within a communication range. Based on local and shared information, the UAV swarm tries to maximize its average observation rate on targets. Unlike traditional approaches that treat the impact from different sources separately, our framework characterizes the impact of moving targets and collaborating UAVs on the moving decision for each UAV with a unified metric called observation profit. Based on this metric, we develop a profit-driven adaptive moving targets search algorithm for a swarm of UAVs. The simulation results validate the effectiveness of our framework in terms of both observation rate and its adaptiveness.

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Assessment of the uncertainty of snowpack simulations based on variance decomposition

Geoscientific Model Development Discussions ◽

10.5194/gmdd-8-2807-2015 ◽

2015 ◽

Vol 8 (3) ◽

pp. 2807-2845 ◽

Cited By ~ 5

Author(s):

T. Sauter ◽

F. Obleitner

Keyword(s):

Measurement Errors ◽

Surface Energy Balance ◽

Global Sensitivity Analysis ◽

State Of The Art ◽

High Arctic ◽

Limited Attention ◽

Sensitivity Pattern ◽

Simulation Results ◽

The Impact ◽

Different Sources

Abstract. State of the art numerical snow models essentially rely on observational data for initialization, forcing, parametrization and validation. Such data are available in increasing amount, but the inherent propagation of related uncertainties on the simulation results has received rather limited attention so far. Depending on their complexity, even small errors can have a profound effect on simulations, which dilutes our confidence in the results. This paper quantifies the fractional contributions of some archetypical measurement uncertainties on key simulation results in a high Arctic environment. The contribution of individual factors on the model variance, either alone or by interaction, is decomposed using Global Sensitivity Analysis. The work focuses on the temporal evolution of the fractional contribution of different sources on the model uncertainty, which provides a more detailed understanding of the model's sensitivity pattern. The decompositions demonstrate, that the impact of measurement errors on calculated snow depth and the surface energy balance components varies significantly throughout the year. Some factors show episodically strong impacts, although there overall mean contribution is low while others constantly affect the results. However, these results are not yet to be generalized imposing the need to further investigate the issue for e.g. other glaciological and meteorological settings.

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Searching and Tracking an Unknown Number of Targets: A Learning-Based Method Enhanced with Maps Merging

Sensors ◽

10.3390/s21041076 ◽

2021 ◽

Vol 21 (4) ◽

pp. 1076

Author(s):

Peng Yan ◽

Tao Jia ◽

Chengchao Bai

Keyword(s):

Moving Targets ◽

Search Region ◽

Area Of Interest ◽

Markov Decision ◽

Simulation Results ◽

Average Observation ◽

High Flexibility ◽

Multiple Moving Targets ◽

Partially Observable ◽

Multi Uav

Unmanned aerial vehicles (UAVs) have been widely used in search and rescue (SAR) missions due to their high flexibility. A key problem in SAR missions is to search and track moving targets in an area of interest. In this paper, we focus on the problem of Cooperative Multi-UAV Observation of Multiple Moving Targets (CMUOMMT). In contrast to the existing literature, we not only optimize the average observation rate of the discovered targets, but we also emphasize the fairness of the observation of the discovered targets and the continuous exploration of the undiscovered targets, under the assumption that the total number of targets is unknown. To achieve this objective, a deep reinforcement learning (DRL)-based method is proposed under the Partially Observable Markov Decision Process (POMDP) framework, where each UAV maintains four observation history maps, and maps from different UAVs within a communication range can be merged to enhance UAVs’ awareness of the environment. A deep convolutional neural network (CNN) is used to process the merged maps and generate the control commands to UAVs. The simulation results show that our policy can enable UAVs to balance between giving the discovered targets a fair observation and exploring the search region compared with other methods.

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Role of chromium (III) in the nutrition of pigs and cattle

Agricultural science and practice ◽

10.15407/agrisp3.02.056 ◽

2016 ◽

Vol 3 (2) ◽

pp. 56-62

Author(s):

R. Iskra ◽

V. Vlizlo ◽

R. Fedoruk

Keyword(s):

Growth And Development ◽

Reproductive Function ◽

Metabolic Effect ◽

Considerable Part ◽

Cultural Medium ◽

Milk Performance ◽

Chromium Compounds ◽

The Impact ◽

Different Sources

The results of our studies and the data of modern literature regarding the biological role of Cr(III) compounds in conditions of their application in the nutrition for pigs and cattle are discussed. The metabolic impact of Cr(III), coming from different sources – mineral and organic compounds, obtained by chemical synthesis or a nanotechnological method (chromium citrate), as well as in the form of biocomplexes from the cultural medium of Saccharomyces cerevisiae yeasts was analyzed. The metabolic connection between the impact of Cr(III) and the biosynthesis of some hormones – insulin, cortisol – as well as the sensitivity of some tissues and organs to the effect of chromium compounds was studied. A considerable part of the review material was dedicated to the metabolic effect of Cr(III) compounds on the reproductive function of pigs and cattle and their impact on the viability of the offspring and gametes of animals. The data about the stimulating effect of Cr(III) on the growth and development of the organism of piglets and calves, meat and milk performance of these species of animals are discussed. The relevance of dosing Cr(III) in the nutrition of pigs and cattle is highlighted.

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A New Narrative?

10.1093/oso/9780198813453.003.0002 ◽

2018 ◽

Author(s):

Natalia Nowakowska

Keyword(s):

Master Narratives ◽

European Context ◽

Early Signs ◽

Research Findings ◽

New Research ◽

The Impact ◽

Different Sources

Our three existing master narratives of the early Reformation in Poland are all over a century old and mutually contradictory, drawing on different sources to serve differing confessional and national/ist agendas. This chapter offers a fresh narrative of the impact of Lutheranism on the Polish composite monarchy to c.1540, synthesizing these older accounts and updating them with new research findings. This is a narrative in three parts: early signs (1517–24), the great Reformation year (1525), and aftershocks (1526–40). The chapter discusses the challenges of measuring ‘Lutheran’ sentiment, sets these Polish-Prussian events clearly in their comparative European context, and considers what implications they might have for that bigger, familiar tale. It stresses the precocity of Sigismund I’s monarchy, which saw the most far-reaching urban and violent Reformation in 1520s Europe (Danzig), a peasant Reformation rising, and Christendom’s first territorial-princely Reformation, in Ducal Prussia.

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Measuring Hydrometeors Using a Precipitation Microphysical Characteristics Sensor: Sampling Effect of Different Bin Sizes on Drop Size Distribution Parameters

Advances in Meteorology ◽

10.1155/2018/9727345 ◽

2018 ◽

Vol 2018 ◽

pp. 1-15 ◽

Cited By ~ 3

Author(s):

Xichuan Liu ◽

Taichang Gao ◽

Yuntao Hu ◽

Xiaojian Shu

Keyword(s):

Drop Size ◽

Rain Rate ◽

Monte Carlo Model ◽

Rain Gauge ◽

Sampling Schemes ◽

Distribution Parameters ◽

Optimum Sampling ◽

Simulation Results ◽

The Impact ◽

Good Agreement

In order to improve the measurement of precipitation microphysical characteristics sensor (PMCS), the sampling process of raindrops by PMCS based on a particle-by-particle Monte-Carlo model was simulated to discuss the effect of different bin sizes on DSD measurement, and the optimum sampling bin sizes for PMCS were proposed based on the simulation results. The simulation results of five sampling schemes of bin sizes in four rain-rate categories show that the raw capture DSD has a significant fluctuation variation influenced by the capture probability, whereas the appropriate sampling bin size and width can reduce the impact of variation of raindrop number on DSD shape. A field measurement of a PMCS, an OTT PARSIVEL disdrometer, and a tipping bucket rain Gauge shows that the rain-rate and rainfall accumulations have good consistencies between PMCS, OTT, and Gauge; the DSD obtained by PMCS and OTT has a good agreement; the probability of N0, μ, and Λ shows that there is a good agreement between the Gamma parameters of PMCS and OTT; the fitted μ-Λ and Z-R relationship measured by PMCS is close to that measured by OTT, which validates the performance of PMCS on rain-rate, rainfall accumulation, and DSD related parameters.

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A New Method to Determine the Impact of Individual Field Quantities on Cycle-to-Cycle Variations in a Spark-Ignited Gas Engine

Energies ◽

10.3390/en14144136 ◽

2021 ◽

Vol 14 (14) ◽

pp. 4136

Author(s):

Clemens Gößnitzer ◽

Shawn Givler

Keyword(s):

Kinetic Energy ◽

Flow Field ◽

Turbulent Kinetic Energy ◽

Negative Impact ◽

Operating Conditions ◽

Engine Operation ◽

Gas Engine ◽

Cycle Simulation ◽

Simulation Results ◽

The Impact

Cycle-to-cycle variations (CCV) in spark-ignited (SI) engines impose performance limitations and in the extreme limit can lead to very strong, potentially damaging cycles. Thus, CCV force sub-optimal engine operating conditions. A deeper understanding of CCV is key to enabling control strategies, improving engine design and reducing the negative impact of CCV on engine operation. This paper presents a new simulation strategy which allows investigation of the impact of individual physical quantities (e.g., flow field or turbulence quantities) on CCV separately. As a first step, multi-cycle unsteady Reynolds-averaged Navier–Stokes (uRANS) computational fluid dynamics (CFD) simulations of a spark-ignited natural gas engine are performed. For each cycle, simulation results just prior to each spark timing are taken. Next, simulation results from different cycles are combined: one quantity, e.g., the flow field, is extracted from a snapshot of one given cycle, and all other quantities are taken from a snapshot from a different cycle. Such a combination yields a new snapshot. With the combined snapshot, the simulation is continued until the end of combustion. The results obtained with combined snapshots show that the velocity field seems to have the highest impact on CCV. Turbulence intensity, quantified by the turbulent kinetic energy and turbulent kinetic energy dissipation rate, has a similar value for all snapshots. Thus, their impact on CCV is small compared to the flow field. This novel methodology is very flexible and allows investigation of the sources of CCV which have been difficult to investigate in the past.

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Revisiting rating scale development for rater-mediated language performance assessments: Modelling construct and contextual choices made by scale developers

Language Testing ◽

10.1177/0265532221994052 ◽

2021 ◽

pp. 026553222199405

Author(s):

Ute Knoch ◽

Bart Deygers ◽

Apichat Khamboonruang

Keyword(s):

Scale Development ◽

Rating Scale ◽

Language Assessment ◽

Performance Assessments ◽

Language Performance ◽

Scale Development And Validation ◽

Post Test ◽

Development And Validation ◽

The Impact ◽

Different Sources

Rating scale development in the field of language assessment is often considered in dichotomous ways: It is assumed to be guided either by expert intuition or by drawing on performance data. Even though quite a few authors have argued that rating scale development is rarely so easily classifiable, this dyadic view has dominated language testing research for over a decade. In this paper we refine the dominant model of rating scale development by drawing on a corpus of 36 studies identified in a systematic review. We present a model showing the different sources of scale construct in the corpus. In the discussion, we argue that rating scale designers, just like test developers more broadly, need to start by determining the purpose of the test, the relevant policies that guide test development and score use, and the intended score use when considering the design choices available to them. These include considering the impact of such sources on the generalizability of the scores, the precision of the post-test predictions that can be made about test takers’ future performances and scoring reliability. The most important contributions of the model are that it gives rating scale developers a framework to consider prior to starting scale development and validation activities.

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Efficient Operative Cost Reduction in Distribution Grids Considering the Optimal Placement and Sizing of D-STATCOMs Using a Discrete-Continuous VSA

Applied Sciences ◽

10.3390/app11052175 ◽

2021 ◽

Vol 11 (5) ◽

pp. 2175

Author(s):

Oscar Danilo Montoya ◽

Walter Gil-González ◽

Jesus C. Hernández

Keyword(s):

Objective Function ◽

Reactive Power ◽

Programming Model ◽

Search Algorithm ◽

Solution Space ◽

Distribution Networks ◽

Optimal Placement ◽

Mixed Integer ◽

Solution Vector ◽

The Impact

The problem of reactive power compensation in electric distribution networks is addressed in this research paper from the point of view of the combinatorial optimization using a new discrete-continuous version of the vortex search algorithm (DCVSA). To explore and exploit the solution space, a discrete-continuous codification of the solution vector is proposed, where the discrete part determines the nodes where the distribution static compensator (D-STATCOM) will be installed, and the continuous part of the codification determines the optimal sizes of the D-STATCOMs. The main advantage of such codification is that the mixed-integer nonlinear programming model (MINLP) that represents the problem of optimal placement and sizing of the D-STATCOMs in distribution networks only requires a classical power flow method to evaluate the objective function, which implies that it can be implemented in any programming language. The objective function is the total costs of the grid power losses and the annualized investment costs in D-STATCOMs. In addition, to include the impact of the daily load variations, the active and reactive power demand curves are included in the optimization model. Numerical results in two radial test feeders with 33 and 69 buses demonstrate that the proposed DCVSA can solve the MINLP model with best results when compared with the MINLP solvers available in the GAMS software. All the simulations are implemented in MATLAB software using its programming environment.

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Effects of Technological Progress from Different Sources on Haze Pollution in China

Sustainability ◽

10.3390/su13052730 ◽

2021 ◽

Vol 13 (5) ◽

pp. 2730

Author(s):

Yuan Zhao ◽

Tian Zhang ◽

Ting Wu ◽

Shujing Xu ◽

Shuwang Yang

Keyword(s):

Technological Progress ◽

Generalized Method Of Moments ◽

National Level ◽

Inhibitory Effect ◽

Dynamic Panel Model ◽

Independent Innovation ◽

Haze Pollution ◽

Technology Introduction ◽

The Impact ◽

Different Sources

Technological progress has always been regarded as an important factor affecting haze pollution. A large number of academic studies have focused on the effect of technological progress on haze pollution, but there are few discussions on the effects of technological progress from different sources. In view of this, a dynamic panel model is constructed, and a systematic generalized method of moments (GMM) method is applied to empirically test the overall impact of technological progress from different sources on haze pollution and the regional heterogeneity of the impact. The results show that the overall and regional impact of technological progress from different sources on haze pollution is entirely different. Among them, for the whole country, independent innovation has a significant inhibitory effect on haze pollution, and technology introduction has aggravated haze pollution to a certain extent. At the regional level, all types of technological progress in the east can effectively reduce haze, the central region having haze reduction results consistent with the overall national level, and in the west, independent innovation and direct introduction can effectively reduce haze, while reverse technology spillover is ineffective. Therefore, policy recommendations such as improving the ability of independent innovation, improving the quality of technology introduction, and coordinating regional technology against haze are put forward.

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A Dicode Signaling Scheme for Capacitively Coupled Interface

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.497.296 ◽

2011 ◽

Vol 497 ◽

pp. 296-305

Author(s):

Yasushi Yuminaka ◽

Kyohei Kawano

Keyword(s):

Partial Response ◽

Data Transmission ◽

High Speed ◽

Circuit Simulation ◽

Frequency Bandwidth ◽

Capacitively Coupled ◽

Limited Frequency ◽

Simulation Results ◽

Response Coding ◽

The Impact

In this paper, we present a bandwidth-efficient partial-response signaling scheme for capacitivelycoupled chip-to-chip data transmission to increase data rate. Partial-response coding is knownas a technique that allows high-speed transmission while using a limited frequency bandwidth, by allowingcontrolled intersymbol interference (ISI). Analysis and circuit simulation results are presentedto show the impact of duobinary (1+D) and dicode (1-D) partial-response signaling for capacitivelycoupled interface.

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