Desired Distance Research Articles

Extending the A Priori Procedure (APP) to Analysis of Variance Models under Normality

The a priori procedure was designed as a pre-data procedure whereby researchers could find the sample sizes necessary to ensure that sample statistics to be obtained are within particular distances of corresponding population parameters with known probabilities. Researchers specify desired precisions (distances of sample statistics from corresponding population parameters) and desired confidences (probabilities of being within desired distances), and this procedure provides necessary sample sizes to meet precision and confidence specifications. Although the a priori procedure has been devised for a variety of experimental paradigms, these have all been simple. The present article constitutes its extension to analysis of variance models. A fortunate side effect of the equations to be proposed is an improvement in efficiency even for a paradigm that fits a previously published article.

Simulated Design and Evaluation of Centralized off Grid Street Light Solar Power System with Backup Generator

In this paper, simulated design and evaluation of centralized off grid street light solar power system with backup generator is presented. The design of the street light solar power system takes into consideration the desired illumination level, the width of road, the coefficient of utilization, the maintenance factor, the desired distance between street light poles, the pole height, the pole space to pole height ratio and the total length of the street. The case study street light is located along IBB Avenue in Uyo, with latitude and longitude of 5.016982, 7.911769 respectively, path length of 2.2 km and daily energy demand of 125.8 kWh/day. The PVSyst simulation results show that the solar fraction is 0.993 which indicates that 99.3 % of the energy demand of the street light is supplied from the solar power while the remaining 0.7% of the energy demand is supplied form the backup generator. The total energy supplied by the generator is 375.7 kWh whereas the total annual energy generated from the PV array is 53739 kWh. The annual total of the energy demand is 46059 kWh while the annual total of the energy supplied to the street light from the solar power system is 46027 kWh. Also, the annual mean of the battery state of charge (SoC) is 80.3 %. Also, it is noted that the month of August alone has about 375.7 kWh energy supply from the backup generator with about 98 liters of fuel. Specifically, in a whole year, the backup generator will be used for only three days in August, namely, on the 13th, 14th and 15th of August, with the maximum supply of 239.8012 kWh occurring on the 14th day of August. Furthermore, the performance ratio (PR) of the system is 48.5%. In all, the results show that the solar power system is able to supply the required energy demand of the case study street light with only 0.7% deficit which is supplied from the backup generator.

Measurement Enhancement of Ultrasonic Sensor using Pelican Optimization Algorithm for Robotic Application

HC-SR04 ultrasonic sensor is one of the famous low-cost sensors. It is measured distance from 2 to 400 cm. It depends on ultrasonic sound waves that are sent by an electronic device to determine the distance of the object, and the reflected sound is converted into an electronic signal. This paper proposed a flowchart of the modern optimization method Pelican Optimization Algorithm (POA) to enhance the distance measurement of ultrasonic sensor kind HC-SR04. In addition, the experimental system designed and interfacing between MATLAB with Ardunio is implemented to easily save the measured and desired distances and enter these distances into the POA as pelicans. The error comparison between two methods implemented, one method called the classical method, and another method is proposed named POA. The results show the minimum distance error between ultrasonic and object in POA is less than the error without POA. The best-measured distance results were achieved and approximately equal to the desired distances. The proposed method of POA for ultrasonic distance sensor enhanced by 99.97%. This sensor accurately detects objects from 2 to 400 cm which can be used in a robotic application.

Multi-environment phenotyping of linseed (Linum usitatissimum L.) germplasm for morphological and seed quality traits to assemble a core collection

Linseed or flax (Linum usitatissimum L.) is one of the most ancient industrial crops domesticated for oilseed and natural fiber. India is one of the two proposed centers of origin of linseed and harbours high genetic diversity. The Indian Council of Agricultural Research-National Bureau of Plant Genetic Resources (ICAR-NBPGR) conserves one of the largest base collections of Linum with around 2800 germplasm accessions at National Genebank, of which 2576 are the unique accessions of cultivated linseed and were characterized for 10 qualitative and 26 quantitative traits and the resultant multi-environment data along with passport information was used to develop a multipurpose core collection. Initially, five different core sets were derived using the core collection assembler tool ‘Core Hunter 3’ by optimization of average genetic distances between each accession and nearest entry in the core (A-NE) and the average distance between each entry and nearest neighbouring entry (E-NE). These five core sets were subjected to different quality evaluation indices to select one set that best represents the maximum genetic diversity and representativeness present in the entire tested collection. The Core collection-4, developed with weightage of E-NE and A-NE in the ratio of 0.7–0.3 was chosen as the best core collection as it exhibited desirable genetic distance, variance difference percentage (VD; 85%), coincidence rate of range (CR; 91.66%) and variable rate of coefficient of variance (VR; 117.76%), which were more than threshold value of VD (80%), CR (80%), and VR (100%) required for an optimally good core collection. Several summary statistics, Kullback-Leibler distance and Shannon Weaver diversity index indicated similar trait distribution patterns among the chosen core set and the entire collection. Correlogram and principal component analysis revealed that trait associations and their magnitude were conserved for most of the traits in the chosen best core collection. The development of this multipurpose core collection is expected to cater to the needs of linseed breeders and germplasm curators to pave the way for expedited access to genetically diverse and agronomically important material for trait introgression.

A novel robust inhibitor of papain-like protease (PLpro) as a COVID-19 drug

Regarding the significance of SARS-CoV-2, scientists have shown considerable interest in developing effective drugs. Inhibitors for PLpro are the primary strategies for locating suitable COVID-19 drugs. Natural compounds comprise the majority of COVID-19 drugs. Due to limitations on the safety of clinical trials in cases of COVID, computational methods are typically utilized for inhibition studies. Whereas papain is highly similar to PLpro and is entirely safe, the current study aimed to examine several plant secondary metabolites to identify the most effective papain inhibitor and validate the results using molecular dynamics and docking. This simulation was conducted identically for PLpro and the optimal inhibitor. The results indicated that the experimental results are comparable to those obtained In-Silico, and the inhibition effects of Chlorogenic acid (CGA) on papain attained in the experiment were validated (IC50=0.54 mM). CGA as an inhibitor was located in the active site of PLpro and papain (total energy −2009410 and −456069 kJ/mol, respectively) at the desired location and distance. The study revealed that CGA and its derivatives are effective PLpro inhibitors against SARS-CoV-2. Communicated by Ramaswamy H. Sarma

Collision-Free Flocking Control for Satellite Cluster With Constrained Spanning Tree Topology and Communication Delay

In this article, a flocking control strategy combining with artificial potential field is developed for collision-free trajectory tracking of satellite cluster with multiple disturbances and communication delay. Considering the link constraints of each satellite, a degree constrained spanning tree is adopted as the communication topology. Furthermore, a topology optimization method based on Prim algorithm and greedy algorithm is investigated to compute the degree radius constrained minimum spanning tree. By using the optimized communication topology, the satellites in cluster can reduce the communication delay and converge to the desired distances more quickly. Finally, the effectiveness and advantages of the proposed method are verified by numerical simulations.

Impact of Magnetic Focusing on the Transport of Energetic Electrons in the Solar Corona

Observations of Type III radio bursts discovered that electron beams with power-law energy spectra are commonly produced during solar flares. The locations of these electron beams are ~ 300 Mm above the particle acceleration region of the photosphere, and the velocities range from 3 to 10 times the local background electron thermal velocity. However, the mechanism that can commonly produce electron beams during the propagation of energetic electrons with power-law energy spectra in the corona remains unclear. In this paper, using kinetic transport theory, we find for the first time that the magnetic focusing effect governs the formation of electron beams over the observational desired distance in the corona. The magnetic focusing effect can sharply increase the bulk velocity of energetic electrons to the observed electron beam velocity within 0.4 solar radii (300 Mm) as they escape from the acceleration region and propagate upward along magnetic field lines. In more rapidly decreasing magnetic fields, energetic electrons with a harder power-law energy spectrum can generate a higher bulk velocity, producing type III radio bursts at a location much closer to the acceleration region. During propagation, the spectral index of the energetic electrons is unchanged.

Parity-Check Matrix Partitioning for Efficient Layered Decoding of QC-LDPC Codes

In this paper, we consider how to partition the parity-check matrices (PCMs) to reduce the hardware complexity and increase decoding throughput for the row layered decoding of quasi-cyclic low-density parity-check (QC-LDPC) codes. First, we formulate the PCM partitioning as an optimization problem, which targets to minimize the maximum column weight of each layer while maintaining a block cyclic shift property among different layers. As a result, we derive all the feasible solutions for the problem and propose a tight lower bound ω <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>LB</i></sub> on the minimum possible maximum column weight to evaluate a solution. Second, we define a metric called layer distance to measure the data dependency between consecutive layers and further illustrate how to identify the solutions with desired layer distance from those achieving the minimum value of ω <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>LB</i></sub> = 1, which is preferred to reduce computation delay. Next, we demonstrate that up-to-now, finding an optimal solution for the optimization problem with polynomial time complexity is unachievable. Therefore, both enumerative and greedy partition algorithms are proposed instead. After that, we modify the quasi-cyclic progressive edge-growth (QC-PEG) algorithm to directly construct PCMs that have a straightforward partition scheme to achieve ω <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>LB</i></sub> or the desired layer distance. Simulation results showed that the constructed codes have better error correction performance and achieve less average number of iterations than the underlying 5G LDPC codes.

Dynamic cyclic fatigue resistance of NiTi instruments in a double-curved stainless steel canal with variable distances of displacement

The present study aimed to measure the number of cycles to fracture (NCF) of different instruments using pecking motion at constant and varying distances of movement at body temperature. This study included 20 files from each brand: ProTaper Universal F2, ProTaper Next X2, and WaveOne Gold Primary (Dentsply Sirona, Maillefer, Ballaigues, Switzerland). Instruments from each brand were divided into two groups (ten files for each group) that experienced constant or variable distances in a stainless-steel artificial double-curved canal in a platform that ensured that the instrument rotated at a stable temperature with a minimum fluctuation of the environment. While running, the platform was programmatically controlled to move at any desired distance of instrument displacement to simulate the clinical pecking motion at variable distances. The files were rotated using proprietary programs. The times to fracture were recorded and then transformed into the number of cycles to fracture (NCF). Data were analyzed using Minitab with proper tests. All fragments were observed under a scanning electron microscope to capture and describe the characteristics of the fracture surface. The WaveOne Gold had the highest NCF, while the ProTaper Universal had the lowest NCF. The manufacturer brands and the modes of displacement of the experimental instrument showed interactive effects. The fracture surface revealed no striation. A new design, material, mode of rotation, and different distances of movement have certain effects on the cyclic fatigue resistance of the instrument.

Design and Implementation of an Energy-Efficient Vehicle Platoon Control Algorithm Using Prescribed Performance and Extremum Seeking Control

Platooning has emerged as a promising approach to enhancing the fuel efficiency of vehicles, but determining the inter-vehicular distance that achieves the minimum consumption remains a challenge. In this article, an algorithm is proposed that employs extremum seeking control integrated with the prescribed performance control technique to find the optimal inter-vehicular distance. The algorithm utilizes the predecessor-following architecture to track the desired distance while minimizing the estimated aerodynamic drag coefficient to seek the optimal value. To estimate the coefficient, an observer is designed. Simulation results are presented to demonstrate the effectiveness of the approach. The proposed algorithm exhibits a significant improvement over existing methods that do not incorporate prescribed performance. Consequently, our scheme provides a valuable contribution to the field of platooning and paves the way for future research directions.

Obstacle avoidance of a wheeled robotic swarm using virtual spring-damper mesh

Swarm robotics, in which groups of robots coordinate to achieve a common goal, has the potential to revolutionize a wide range of industries. However, one of the key challenges in developing effective swarm systems is enabling the robots to navigate around obstacles while maintaining cohesion. In this article, the problem of trajectory tracking for a self-organized swarm of wheeled robots in the shape of a regular polygon operating in an environment with obstacles is addressed. The goal is for the swarm to follow a reference point by the geometric center of the swarm, while avoiding collision with obstacles and maintaining a given distance between neighboring robots and the reference point. To solve this problem, a method based on virtual forces that act on each individual robot in the swarm is proposed. These virtual forces are derived from virtual spring-damper connections acting from the obstacles, adjacent robots, and the reference point. The virtual forces allow the robots to dynamically adjust their trajectories to avoid obstacles and maintain the shape of the swarm. The proposed approach is evaluated through simulation and experiment with a swarm of two-wheeled robots. During the experiment the maximum deviation of inter-robot distances was equal to 0.08 m. With the set limit distance to obstacles equal to 0.2 m, from which virtual forces start to push the robot away from the edge of the obstacle, the shortest distance to obstacles was 0.11 m. The results demonstrate the effectiveness of the method in enabling the swarm to accurately follow the reference point while avoiding obstacles and maintaining the desired distances between robots. Overall, the approach represents a step forward in the development of virtual force-based algorithms for obstacle avoidance in swarm robotics.

A Multistage Framework for Autonomous Robotic Mapping with Targeted Metrics

High-quality maps are pertinent to performing tasks requiring precision interaction with the environment. Current challenges with creating a high-precision map come from the need for both high pose accuracy and scan accuracy, and the goal of reliable autonomous performance of the task. In this paper, we propose a multistage framework to create a high-precision map of an environment which satisfies the targeted resolution and local accuracy by an autonomous mobile robot. The proposed framework consists of three steps. Each step is intended to aid in resolving the challenges faced by conventional approaches. In order to ensure the pose estimation is performed with high accuracy, a globally accurate coarse map of the environment is created using a conventional technique such as simultaneous localization and mapping or structure from motion with bundle adjustment. The high scan accuracy is ensured by planning a path for the robot to revisit the environment while maintaining a desired distance to all occupied regions. Since the map is to be created with targeted metrics, an online path replanning and pose refinement technique is proposed to autonomously achieve the metrics without compromising the pose and scan accuracy. The proposed framework was first validated on the ability to address the current challenges associated with accuracy through parametric studies of the proposed steps. The autonomous capability of the proposed framework was been demonstrated successfully in its use for a practical mission.

Exploring effects of vessels on walrus behaviors using telemetry, automatic identification system data and matching

AbstractArctic marine mammals have had little exposure to vessel traffic and potential associated disturbance, but sea ice loss has increased accessibility of Arctic waters to vessels. Vessel disturbance could influence marine mammal population dynamics by altering behavioral activity budgets that affect energy balance, which in turn can affect birth and death rates. As an initial step in studying these linkages, we conducted the first comprehensive analysis to evaluate the effects of vessel exposure on Pacific walrus (Odobenus rosmarus divergens) behaviors. We obtained &gt;120,000 h of location and behavior (foraging, in‐water not foraging, and hauled out) data from 218 satellite‐tagged walruses and linked them to vessel locations from the marine automatic identification system (AIS). This yielded 206 vessel‐exposed walrus telemetry hours for comparison to unexposed hours, which we used to assess if vessel exposure altered walrus behavior. We developed a filter to account for misclassification of vessel exposure of telemetered walruses. Then we tested for an effect of vessel exposure on walrus behaviors using a combination of exact and propensity score‐based matching to account for confounding covariates, and we conducted statistical power analyses. We did not detect an effect of vessel exposure on walrus behaviors even when statistical power was high (i.e., for foraging walruses), which may have been due to the sample size‐driven need to define vessel presence within a larger than desired distance (15‐km measured radius) around a walrus. Although this study did not determine at what distance vessel exposure affects walrus behaviors, it provided an upper bound on the distance at which the vessels encountered may disturb foraging walruses. When more situation‐specific information is lacking, this distance could be used as a conservative buffer to maintain between vessels and areas of high use by foraging walruses. Studies on behavioral consequences of closer proximities between walruses and vessels are needed, and our assessments of misclassification rates and statistical power can be used for future studies. We demonstrated that analytical approaches such as matching, which are rarely used in wildlife studies, are particularly useful for testing hypotheses with observational data.

Optimization design of autofocusing metasurface for ultrasound wave application

In this paper, two optimized autofocusing metasurfaces (AFMs) with different desired focal distances are designed by using particle swarm optimization (PSO) algorithm. Based on the finite element simulation software COMSOL Multiphysics, the performance of ultrasound transducer (UT) with AFM at different design parameters in Airy distributions ([Formula: see text]) and the bottom thickness ([Formula: see text]) of AFM are simulated and analyzed. Based on the simulation data, the artificial neural network model is trained to describe the complex relationship between the design parameters of AFM and the performance parameters of UT. Then, the multiobjective optimization function for AFM is determined according to the desired performance parameters of UT, including focal position, lateral resolution, longitudinal resolution and absolute sound pressure. In order to obtain AFMs with the desired performance, PSO algorithm is adopted to optimize the design parameters of AFM according to the multiobjective optimization function, and two AFMs are optimized and fabricated. The experimental results well agree with the simulation and optimization results, and the optimized AFMs can achieve the desired performance. The fabricated AFM can be easily integrated with UT, which has great potential applications in wave field modulation underwater, acoustic tweezers, biomedical imaging, industrial nondestructive testing and neural regulation.

A New Topology for Homogeneous Vehicular Platoon under Disturbances

Vehicle platooning has attracted a lot of interest in research in the last decade as it introduced a solution to many problems in traffic flow, safety, fuel economy, and reducing CO2 emissions. As the cost reduction is crucial and necessary to the business’s sector, in this paper, communication cost reduction is achieved via proposing a new topology called Bidirectional Odd Leader (BDOL). The BDOL topology is advantageous in terms of cost compared to the BDL topology due to the BDOL is a relaxation of the BDL topology. The string stability of the dynamical system with the proposed topology is first proven through numerical comparison with BDL topology. Then, the performance of the proposed topology has been evaluated by intensive computer-based simulation. A homogeneous platoon consisting of eight vehicles is created and tested on a straight and curved track, while keeping a small desired inter-vehicle distance. We evaluated the performance of our topology, and tested the string stability in many scenarios. These scenarios include platoon moving on a straight track with or without disturbance, lastly a velocity disturbance produced by a curved track affecting the platoon is also investigated. The results demonstrate the effectiveness of the proposed topology in achieving the intended objectives.

Stabilization of Symmetric Formations

This work proposes a solution to the distance-constrained formation control problem to attain symmetric formations. Utilizing recent results from rigidity theory for symmetric frameworks, we design a gradient-based control strategy that simultaneously drives the agents to the desired inter-agent distances and also a special position characterizing additional symmetry constraints on the graph. We show that for graphs where there exist edges between agents in the same vertex orbit induced by the automorphism group, no additional information exchange links are required. Furthermore, leveraging the symmetry constraints of the system it is possible to solve the formation control problem with fewer edges than standard approaches. In particular, the framework is not required to be minimally infinitesimally rigid in this case. Our results are demonstrated with a numerical example.

Cooperative Adaptive Cruise Control in a Mixed-Autonomy Traffic System: A Hybrid Stochastic Predictive Approach Incorporating Lane Change

This paper presents a stochastic and predictive control design approach for connected and automated vehicles (CAVs) in a mixed-autonomy traffic environment, where CAVs are able to react properly to uncertain maneuvers of human-driven vehicles (HVs). The proposed fully-automated cooperative adaptive cruise control (CACC) design leverages a discrete hybrid stochastic model predictive controller that automatically determines the vehicle's operating mode based on onboard sensors data and information received through vehicle-to-vehicle (V2V) communication. Operating modes include free following, warning, danger, emergency braking, and lane change. Although the controller mainly focuses on maintaining the desired velocity and distance among CAVs, it also allows HVs to perform lane-change maneuvers and merge into the platoon's lane when needed. In response to an HV's position in the lane and its probabilistic behavior, the controller may switch the CAV's operating mode to react accordingly. Considering free-following and emergency-braking modes leads to efficient and safe autonomous driving. Switching between warning, danger, and lane-change modes along with adjusting the steering angle to perform a lane-change maneuver, when needed, robustifies the platoon's performance against unexpected human-driven vehicle maneuvers. Simulation studies are conducted to validate the efficacy of the proposed control design approach. The performance of the proposed control design approach is also compared to a switching control using simulation studies.

Platoon-based collision-free control for connected and automated vehicles at non-signalized intersections

&lt;abstract&gt;&lt;p&gt;This paper proposes a distributed collision-free control scheme for connected and automated vehicles (CAVs) at a non-signalized intersection. We first divide an intersection area into three sections, i.e., the free zone, the platoon zone, and the control zone. In order to enable the following vehicles to track the trajectory of their leading vehicle in the platoon zone and the control zone, as well as to guarantee the desired distance between any two adjacent vehicles, the distributed platoon controllers are designed. In the control zone, each vehicular platoon is taken as a whole to be coordinated via an intersection coordination unit (ICU). To avoid collision between each pair of the conflicting platoons approaching from different directions, a platoon-based coordination strategy is designed by scheduling the arrival time of each leading vehicle of different platoons. Specially, considering traffic efficiency and fuel economy, the optimal control problem of the leading vehicle is formulated subject to the constraint of allowable minimum arrival time, which is derived from coordination with other approaching platoons. The Pontryagin Minimum Principle (PMP) and phase-plane method are applied to find the optimal control sequences. Numerical simulations show the effectiveness of this scheme.&lt;/p&gt;&lt;/abstract&gt;

A Multilayer Graph for Multiagent Formation and Trajectory Tracking Control Based on MPC Algorithm.

This article studies the formation and trajectory tracking control of multiagent systems. We present a novel multilayer graph for the multiagent system to enable extensibility of the interaction network. Based on the multilayer graph, a formation control law by using the potential function approach is developed for autonomous formation, formation maintenance, collision, and obstacle avoidance. When the desired formation is achieved, the barycentric of the formation shape is viewed as a virtual leader, and a model predictive control (MPC) scheme is applied to the virtual leader for tracking a reference trajectory; meanwhile, the agents will maintain the desired angles and distances via the formation control law. By applying the proposed schemes, the tasks of formation maintenance and trajectory tracking in a constrained space are fulfilled. Comprehensive simulation studies under different environmental constraints and trajectories confirm the effectiveness of the proposed approaches in addressing the formation and trajectory tracking problems.

Car-Following Model Optimization and Simulation Based on Cooperative Adaptive Cruise Control

This study aims to improve the desired distance adaptability of the cooperative adaptive cruise control (CACC) during car-following. In this study, the characteristics of the desired distance in different traffic flow states were analyzed. The general functional form of the desired distance in the car-following process was formulated. Then, a car-following platoon was constructed to compare the car-following effect of the platoon under different conditions, using the following speed and the lead vehicle disturbance, as the observed variable and the simulation condition, respectively. The car-following effect of the platoon under different parameters was also compared, based on the improved CACC model. The results show that the improved CACC model exhibited more advantages in car-following efficiency, it can better describe the state of the car-following queue under different traffic flow parameters and car-following behavior conditions, it has a strong anti-interference ability for the fluctuation of the car-following queue and is conducive to further improving the intelligent operation of car-following queue.