Trajectory Distance Research Articles

Study of Flyrock to Reduce Safe Radius from 500 m to 300 m on Blasting Quarry at PT Vale Indonesia, Sorowako, Luwu Timur, South Sulawesi

Flyrock exceeding the safe radius can cause harm to equipment and humans. In recent years there has been frequent flyrock exceeding 500 m which has caused a significant impact on the environment in addition to several quarries adjacent to the population at a distance of 500 meters. Data collection at PT. Vale Indonesia uses Leica GS and GoPro with an analysis method using Tracker 5.1.5 to observe blasting activities. The estimated maximum flyrock trajectory distance is determined using empirical and dimensional analysis methods. It is done to obtain accurate and precise results on the conditions of the blasting sites. The empirical method is based on the theories of Lundborg (1981) and Richard and Moore (2005), while the dimensional analysis method is based on the theory of Ebrahim Ghasemi (2012). A comparison of the actual flyrock trajectory deviation between the dimensional analysis method of Ebrahim Ghasemi and the empirical method of Richard and Moore shows that Ebrahim Ghasemi’s method is closer to the deviation percentage, which is 7.76%. From the estimated distance, the flyrock closest to the actual flyrock dimension analysis method has a deviation of 4.89m with a factor of safety value against flyrock hazards of 1.5. A trial was conducted based on the dimensional analysis method to determine the appropriate safe radius.

Drilling accuracy evaluation of a mouldable surgical targeting system for minimally invasive access to anatomic targets in the temporal bone.

Minimally invasive cochlear implant surgery using a micro-stereotactic surgical targeting system with on-site moulding of the template aims for a reliable, less experience-dependent access to the inner ear under maximal reduction of trauma to anatomic structures. We present an accuracy evaluation of our system in ex-vivo testing. Eleven drilling experiments were performed on four cadaveric temporal bone specimens. The process involved preoperative imaging after affixing the reference frame to the skull, planning of a safe trajectory preserving relevant anatomical structures, customization of the surgical template, execution of the guided drilling and postoperative imaging for determination of the drilling accuracy. Deviation between the drilled and desired trajectories was measured at different depths. All drilling experiments were successfully performed. Other than purposely sacrificing the chorda tympani in one experiment, no other relevant anatomy, such as facial nerve, chorda tympani, ossicles or external auditory canal were harmed. Deviation between the desired and achieved path was found to be 0.25 ± 0.16mm at skulls' surface and 0.51 ± 0.35mm at the target level. The closest distance of the drilled trajectories' outer circumference to the facial nerve was 0.44mm. We demonstrated the usability for drilling to the middle ear on human cadaveric specimen in a pre-clinical setting. Accuracy proved to be suitable for many applications such as procedures within the field of image-guided neurosurgery. Promising approaches to reach sufficient submillimetre accuracy for CI surgery have been outlined.

AMGB: Trajectory prediction using attention-based mechanism GCN-BiLSTM in IOV

Accurate and reliable prediction of vehicle trajectories is closely related to the path planning of intelligent vehicles and contributes to intelligent transportation safety, especially in dynamic and uncertain scenarios. However, most existing methods have difficulty in accurately capturing vehicle interactions and the dependencies between vehicle multimodal features in dynamic and uncertain driving environments. Thus, we propose a new Attention-based Mechanism GCN-BiLSTM trajectory prediction model (AMGB) which tackles trajectory prediction in dynamic environments from a new perspective of predicting vehicle motion direction and motion distance. Firstly, the Attention-based Time-Frequency domain Graph Convolutional Network (AT-GCN) module learns the dependencies between vehicle multimodal features and extracts coarse-grained features containing directions information of future trajectories. Then the Multi-structure based Bidirectional Long- Short Term Memory network (M-BiLSTM) module can acquire fine-grained features containing future trajectory distance from vehicle interaction information by the memory storage function of BiLSTM. Finally, we apply the attention mechanism to fuse the coarse and fine-grained features to establish the mapping relationship between vehicle multimodal features and interaction behaviors, and future trajectories. The proposed AMGB model is evaluated on the NGSIM dataset, the results confirm that our model outperforms other state-of-the-art models in both short-long term trajectory prediction.

Stepwise Cooperative Trajectory Planning for Multiple BUVs Based on Temporal–Spatial Bezier Curves

Biomimetic underwater vehicles (BUVs) are important instrumentation in applications such as water quality monitoring and underwater detection. In this paper, we study the cooperative trajectory planning problem for multiple BUVs and propose a stepwise trajectory planning algorithm based on temporal-spatial Bezier curves to enable cooperative formations. We introduce the time variable into the three-dimensional (3D) Bezier curve, designing a four-dimensional temporal-spatial Bezier curve. Considering the various physical constraints of the BUV, we obtain a smooth and feasible trajectory using Particle Swarm Optimization (PSO) when taking the shortest trajectory distance as the optimization goal. On this basis, we propose a method to perform cooperative trajectory planning and efficient obstacle avoidance replanning for multiple BUVs by integrating the real-time collision avoidance, real-time detection, and underwater complex terrain constraints. We verify the effectiveness of the proposed cooperative planning method through simulation and comparison.

Comparison of Accuracy of Frameless Stereotactic System (Neuronavigation) Against Frame Based Stereotaxy in Deep Seated Lesion of Brain

Objective: The determination of accuracy of frameless stereotactic system against frame based stereotaxy in deep seated lesion of brain. Study Type: randomized controlled trial. Study Place and Duration: Department of Neurosurgery, Nishtar Hospital Multan from June 2019 to June 2020. Material and methods: A total of 124 patients were included in the study after informed consent and eligible in accord to the inclusion and exclusion criteria. Total participants were 124 (randomized) and were divided into two randomized groups; frame-based stereotaxy group (FB) and stereotaxy group (SG) including 62 patients in each group. The angular deviation and target distance between actual and planned trajectory were the primary outcomes in this study. Independent samples were tested through 2-tailed t-tests for statistical testing. Mann-Whitney U test was performed for non-normally distributed data while for comparison of categorical variables Chi-square or Fisher tests were performed. P-value was 0.05 as a level off statistical significance. SPSS version 23 was used for statistical computations. Results: Trajectory length and distance were 42.32±10.38 mm and 2.43±1.02 mm in FB group, while 43.45±11.65 mm and 2.59±1.06 mm in VG group, and there was no statistically significant difference in these two parameters (p value 0.570 and 0.390, respectively). Trajectory deviation was 1.85±1.28 degree in FB group and 2.63±158 degree in VG group, and the difference was statistically significant (p=0.003). Table-II. Conclusion: Patients in which brain biopsy was done, the Varioguide system can be compared to the gold standard frame-based stereotaxy on the basis of means of trajectory accuracy, complications rate and diagnostic yield.

Development of An Algorithm for Slippage-Induced Motion Artifacts Reduction in Video-Nystagmography

Objectives: The slippage of the video-nystagmography devices causes motion artifacts in the trajectory of the pupil and thus results in distortion in the nystagmus waveform. In this study, the moving average was proposed to reduce slippage-induced motion artifacts from the real-world data obtained in the field.Methods: The dataset consists of an infrared video of positional tests performed on eight patients with a lateral semicircular canal benign paroxysmal positional vertigo. The trajectories of the pupil were obtained from the video with binarization, morphological operation, and elliptical fitting algorithm. The acquired data was observed and the section where the slippage occurred was labeled by an otolaryngologist. The moving average with windows of various lengths was calculated and subtracted from the original signal and evaluated to find the most adequate parameter to reduce the motion artifact.Results: The period of nystagmus in the given data was found to be ranged from 0.01 to 4 seconds. The slippages that appeared in the data can be categorized into fast and slow slippages. The length, distance, and speed of trajectories in the slippage ranges were also measured to find the characteristics of the motion artifact in video-nystagmography data. The shape of the nystagmus waveform was preserved, and the motion artifacts were reduced in both types of slippages when the length of the window in moving average was set to 1 second.Conclusions: The algorithm developed in this study is expected to minimize errors caused by slippage when developing a diagnostic algorithm that can assist clinicians.

A new drought monitoring approach using three-dimensional drought properties based on a dynamic drought detection technique algorithm

Study regionCentral Asia. Study focusIn Central Asia, there is a lack of drought information to help understand the spatiotemporal variability and evolutionary characteristics of droughts. In this study, drought analysis data (i.e., high-resolution Standardized Precipitation Evapotranspiration Index (SPEI) dataset) was utilized in consideration of the meteorological and topographical characteristics of Central Asia and a dynamic drought detection technique (DDDT) algorithm was proposed for extracting three-dimensional(3D) drought events. As a result, it was possible to analyze the spatiotemporal distribution patterns and characteristics of droughts, which are intertwined with spatiotemporal dimensions. The drought events in Central Asia during the period of 1981–2018 were identified and their spatiotemporal distribution patterns and variabilities were characterized using various drought characteristic indicators (drought duration, severity, affected area, intensity, location (latitude and longitude), and the distance and direction of the drought trajectory). Finally, a new approach to monitoring conditional drought in Central Asia was proposed based on a dynamic drought map that includes all 3D-drought properties. New hydrological insights for the regionOur major findings include (i) high-resolution data sets are suitable to interpret the development process and evolutionary characteristics of drought in consideration of the climatic and various topographical characteristics of Central Asia, (ii) most droughts of large and small scale in Central Asia can be quantified by identifying drought events in a three-dimensional concept using a DDDT algorithm, (iii) the direction of the drought trajectory that occurred in the study area during the period of 1981–2018 was often lateral, i.e., east and west, and (iv) in Central Asia at the beginning of 2008, severe drought continued in 2008, although the number of new monthly droughts tended to decrease. As a result of identifying the cause using the dynamic drought map, the number of new droughts that occurred every month in the second half of 2007 tended to increase, which led to the long-term drought in 2008.

Objective Quantitative Analysis of Laryngeal Glottal Gaps using High-Speed Video in Glottal Analysis Tools, a Case-Control Study

Quantitative voice analysis for clinical use has been focused upon for many years. The aim was to test if Glottal Analysis Tools (GAT) could be used, based on High-Speed Video (HSV) to quantify distances between the vocal folds at any place on the vocal folds. The software includes a reproduced computed film of the vocal fold movements online. 20 normal HSV and 30 with insufficient closure in the rear part of the vocal folds (rear glottal gap) were compared in a case-control study. The distance of trajectories was chosen at 50% and 10% from the rear part of the glottis and maximum and minimum distances between the vocal folds were defined during phonation in the 2 groups. It was possible to calculate the absolute data of insufficiency of closure of the vocal folds compared to normal HSV with a statistical difference of p<0,0001. An interesting result was in this material also that functional closure was found in all images in the middle of the vocal folds. In the future quantification of voice disorders should include specific parts of the Glottal Area Waveform (GAW) analyses based on HSV for better differentiation of function and pathology of the vocal folds.

Predicting Visual Differentiability for Unmanned Aerial Vehicle Gestures

Unmanned Aerial Vehicles (UAVs) are increasingly integrated into diverse human interaction domains that require robust human-robot communication systems. Visual communication techniques have shown promise in their ability to communicate concrete information to observers. Such techniques, often described as a UAV ‘gesture,’ may be especially useful in the domain of unmanned aerial flight as they can be integrated as a stand-alone software solution in contrast to light or sound-based systems that often require additional hardware and add weight to a vehicle. Gestures may also be useful in contexts where long distance operation reduces the effectiveness of sound-based communication strategies. As gesture is a visual communication technique, it is critical that gestures are designed to optimize an observer’s ability to visually perceive the shape of a gesture’s motion. Factors such as low visual differentiability between gestures within a set may reduce an observer’s ability to classify the shape of a gestural motion. In this letter, we discuss the results from multiple gesture perception surveys. We also develop and evaluate techniques to predict, in advance, how participants may perceive a UAV gesture. We demonstrate that participant gesture classification accuracy correlates to trajectory distance measures and present a method for evaluating high-differentiabilty gesture sets. This letter will enable gesture designers to create gesture sets that are differentiable with high-confidence.

Effect of Flapping Trajectory and Interfoil Distance on Propulsive Performance of a Tandem Flapping Foil

Abstract In the present research, a 2D simulation of tandem flapping foil following an elliptical trajectory, i.e., altered from a simple flapping trajectory is performed. The purpose of the research is to evaluate the influence of the trajectory motion of the tandem flapping foil on hydrodynamics characteristics and propulsive efficiency. The study is carried out with tandem foil configurations as in such position, both the foils are subjected to the same flow, which allows the flapping foil to enhance the propulsive efficiencies with proper selection of foil position as well as the foil trajectory. The 2D simulation is carried out with NACA 0012 at Re = 1173 by varying Strouhal number (St) between 0.2 and 0.5. The results show that an elliptical motion trajectory pattern and interfoil spacing of 1cm–2cm (where cm is the mean chord length) between the foils would enhance the propulsive efficiency whereas an unfavorable spacing between the foils causes unfavorable wake interaction, which reduces propulsive efficiency as compared to solo flapping foil. When the results of the current numerical investigation of elliptical trajectory are compared to the results of simple trajectory tandem flapping, the current study shows a significant increase in propulsive efficiency. This study gives new insights in the development of biomimetic propulsors, as it strives to improve propulsive efficiency through the usage of wake vortex.

Numerical simulation on spatial steering rule of directional perforation hydraulic fractures in low-permeability reservoir

For purpose of clearing the spatial pattern of hydraulic fracture during directional perforation in low-permeability unconventional reservoirs, RFPA2D-Flow software is used to numerically calculate their spatial steering trajectory and deflection distance. The accuracy of numerical calculation results is verified by theoretical and experimental results. Then the influences of horizontal principal stress difference, perforation length, and azimuth on the hydraulic fractures’ spatial steering trajectory are studied. It is shown by the results that 1) the software can accurately predict the space steering trajectory and deflection distance of directional perforation hydraulic fractures, 2) both deflection distance and spatial steering trajectory of hydraulic fractures are quantitatively evaluation indexes, which are used to evaluate the hydraulic fractures’ spatial steering effects, and 3) under different horizontal principal stress differences, perforation azimuths, and lengths, the same hydraulic fracture’s propagation trajectories are presented. They initiate from the perforation end and gradually deflect along the maximum horizontal principal stress direction and finally represent curved fractures like both wings. With the increase in horizontal principal stress difference, the fractures’ deflection distance decreases. However, it increases with the increase in perforation azimuth and length. Their deflection amplitude increases first and then decreases. Initiation pressure of hydraulic fracture rises with the decrease in perforation length and increase in perforation azimuth and horizontal principal stress difference.

VRE

Managing massive trajectory data from various moving objects has always been a demanding task. A desired trajectory data system should be versatile in its supported query types and distance functions, of low storage cost, and be consistently efficient on processing trajectory data of different properties. Unfortunately, none of the existing systems can meet the above three criteria at the same time. To this end, we propose VRE, a v ersatile, r obust, and e conomical trajectory data system.VRE separates the storage from the processing. In the storage layer, we propose a novel segment-based storage model that takes advantage of the strengths of both point-based and trajectory-based storage models. VRE supports these three storage models and ten storage schemas upon them. With the secondary index, VRE reduces the storage cost up to 3x. In the processing layer, we first propose a two-stage processing framework and a pushdown strategy to alleviate full trajectory transmission cost. Then, we design a unified pruning strategy for five widely used trajectory distance functions and numerous tailored processing algorithms for five advanced queries. Extensive experiments are conducted to verify the design choice and efficiency of VRE, from which we present some key insights that are crucial to both VRE and future trajectory system's design.

A Cloud-Assisted Reliable Trust Computing Scheme for Data Collection in Internet of Things

Large number of Internet of Things (IoT) applications with intelligent sensing devices (ISDs) are combined with cloud computing to collect and process data more efficiently. However, ISDs are vulnerable to various attacks. Compromised devices may maliciously provide unreliable data to the cloud, causing damage to IoT applications. Therefore, it is a critical issue to design an effective mechanism to ensure the security of data collection in cloud computing. In this article, a cloud-assisted reliable trust computing (CRTC) scheme is proposed to identify the trust of ISDs at low cost, providing high-quality data for IoT applications. The CRTC scheme mainly includes the following parts: First, a reliable approach of obtaining the real data of ISDs at a low cost is proposed to identify the trust of ISDs. In the proposed method, ISDs fits the forwarding packets information to form inspection information (II) with a small amount of data and then sends II to inspection nodes, effectively reducing the cost of routing II. Second, an effective method of trust computing is given to evaluate the trustworthiness of ISDs based on the data and II collected by unmanned aerial vehicles (UAV). Then, the aggregators are selected from high-trust ISDs to ensure secure data collection. Third, to obtain more reliable trust at lower cost, a trajectory optimization algorithm for UAV is proposed to collect as much II as possible and reduce the moving distance. Theoretical analysis and experimental results show that the proposed CRTC scheme is superior to previous strategies in terms of the success rate of data collection, the speed of identifying the trust of ISDs, and the UAV's trajectory distance.

Multi-UAV Cooperative Trajectory Planning Based on Many-Objective Evolutionary Algorithm

The trajectory planning of multiple unmanned aerial vehicles (UAVs) is the core of efficient UAV mission execution. Existing studies have mainly transformed this problem into a single-objective optimization problem using a single metric to evaluate multi-UAV trajectory planning methods. However, multi-UAV trajectory planning evolves into a many-objective optimization problem due to the complexity of the demand and the environment. Therefore, a multi-UAV cooperative trajectory planning model based on many-objective optimization is proposed to optimize trajectory distance, trajectory time, trajectory threat, and trajectory coordination distance costs of UAVs. The NSGA-III algorithm, which overcomes the problems of traditional trajectory planning, is used to solve the model. This paper also designs a segmented crossover strategy and introduces dynamic crossover probability in the crossover operator to improve the solving efficiency of the model and accelerate the convergence speed of the algorithm. Experimental results prove the effectiveness of the multi-UAV cooperative trajectory planning algorithm, thereby addressing different actual needs.

Social Force Model Calibration for Preschool Children Evacuations Based on Multiscenario Experiments

The social force model has been widely used in simulating and analyzing pedestrian behavior. Like any agent-based models, the fidelity of the social force model largely relies on its numerical parameters that characterizes pedestrians’ behaviors. While parameters describing normal walking behaviors have been observed and calibrated in field experiments, those describing behaviors under abnormal and urgent circumstances have rarely been studied but are of practical significance in evaluating safety functionality of facilities, particularly those serving children or elders. Specifically aiming at providing a set of social force model parameters characterizing children’s behavior during evacuation, this study conducted evacuation experiments with preschool children under multiple emergency scenarios involving impaired-vision and flame scenarios and benchmarked against a normal scenario. A simulation-calibration framework is developed based on the social force model to calibrate evacuation behavior parameters by minimizing trajectory distance. The numerical approximation results indicate evident parameter disparities of preschool children from adults. This study can improve evacuation strategies and the designing/evaluation process of dedicated facilities layouts such as kindergarten corridors, activity rooms, and playgrounds.

Trajectory Distance Algorithm Based on Segment Transformation Distance

Trajectory Distance Algorithm Based on Segment Transformation Distance

A Robust Reference Path Selection Method for Path Planning Algorithm

In this letter, a general robust reference path selection method (RPSM) that can be integrated into current existing motion planning algorithms is proposed to improve the mobile performance of autonomous patrol robots. The proposed RPSM maintains a dynamic array of path candidates that contains newly found paths, optimal historical paths, and hybrid paths that incorporate local trajectories. All these candidates will be evaluated in a unified criterion, and the best path with the minimal cost will be presented for trajectory tracking, ensuring the consistency and smoothness of the actual motion. Experiments with two different kinds of robots in various scenarios confirm that RPSM enriches the diversity and robustness of reference paths, and improves the execution efficiency by significantly reducing the average actual trajectory distance, orientation change, and total execution time, with an acceptable extra computational cost in comparison to the corresponding original hybrid A* algorithm.

Is Medoid Suitable for Averaging GPS Trajectories?

Averaging GPS trajectories is needed in applications such as clustering and automatic extraction of road segments. Calculating mean for trajectories and other time series data is non-trivial and shown to be an NP-hard problem. medoid has therefore been widely used as a practical alternative and because of its (assumed) better noise tolerance. In this paper, we study the usefulness of the medoid to solve the averaging problem with ten different trajectory-similarity/-distance measures. Our results show that the accuracy of medoid depends mainly on the sample size. Compared to other averaging methods, the performance deteriorates especially when there are only few samples from which the medoid must be selected. Another weakness is that medoid inherits properties such as the sample frequency of the arbitrarily selected sample. The choice of the trajectory distance function becomes less significant. For practical applications, other averaging methods than medoid seem a better alternative for higher accuracy.

Modeling, Trajectory Analysis and Waypoint Guidance System of a Biomimetic Underwater Vehicle Based on the Flapping Performance of Its Propulsion System

The performance of biomimetic underwater vehicles directly depends on the correct design of their propulsion system and its control. These vehicles can attain highly efficient motion, hovering and thrust by properly moving part(s) of their bodies. In this article, a mathematical modeling and waypoint guidance system for a biomimetic autonomous underwater vehicle (BAUV) is proposed. The BAUV achieves sideways and dorsoventral thunniform motion by flapping its caudal fin through a parallel mechanism. Also, an analysis of the vehicle’s design is presented. A thrust analysis was performed based on the novel propulsion system. Furthermore, the vehicle’s kinematics and dynamic models were derived, where hydrodynamic equations were obtained as well. Computed models were validated using simulations where thrust and moment analysis was employed to visualize the vehicle’s performance while swimming. For the path tracking scheme, a waypoint guidance system was designed to correct the vehicle’s direction toward several positions in space. To accurately obtain waypoints, correction over the propeller’s flapping frequency and bias was employed to achieve proper thrust and orientation of the vehicle. The results from numerical simulations showed how by incorporating this novel propulsion strategy, the BAUV improved its performance when diving and maneuvering based on the dorsoventral and/or sideways configuration of its swimming mode. Furthermore, by designing proper strategies to regulate the flapping performance of its caudal fin, the BAUV followed the desired trajectories. The efficiency for the designed strategy was obtained by comparing the vehicle’s traveled distance and ideal scenarios of straight-line trajectories between targets. During simulations, the designed guidance system presented an efficiency of above 80% for navigation tasks.

Stable Isotope Trajectory Analysis (SITA): A new approach to quantify and visualize dynamics in stable isotope studies

AbstractEcologists working with stable isotopes have to deal with complex datasets including temporal and spatial replication, which makes the analysis and the representation of patterns of change challenging, especially at high resolution. Due to the lack of a commonly accepted conceptual framework in stable isotope ecology, the analysis and the graphical representation of stable isotope spatial and temporal dynamics of stable isotope value at the organism or community scale remained in the past often descriptive and qualitative, impeding the quantitative detection of relevant functional patterns. The recent community trajectory analysis (CTA) framework provides more explicit perspectives for the analysis and the visualization of ecological trajectories. Building on CTA, we developed the Stable Isotope Trajectory Analysis (SITA) framework, to analyze the geometric properties of stable isotope trajectories on n‐dimensional (n ≥ 2) spaces of analysis defined analogously to the traditional multivariate spaces (Ω) used in community ecology. This approach provides new perspectives into the quantitative analysis of spatio‐temporal trajectories in stable isotope spaces (Ωδ) and derived structural and functional dynamics (Ωγ space). SITA allows the calculation of a set of trajectory metrics, based on either trajectory distances or directions, and new graphical representation solutions, both easily performable in an R environment. Here, we illustrate the use of our approach by reanalyzing previously published datasets from marine, terrestrial, and freshwater ecosystems. We highlight the insights provided by this new analytic framework at the individual, population, community, and ecosystems levels, and discuss applications, limitations, and development potential.