Small Ground Research Articles

Development of Action-Intention Indicator for Sidewalk Vehicles

Many small ground vehicles that travel on sidewalks, such as electric wheelchairs, are equipped with a differential-wheeled mechanism to turn precisely on the spot and accurately control their trajectory. Conventional ground vehicles operating on public roads have action indicator devices such as blinkers and brake lights, which are effective in preventing collisions during operations. However, similar blinkers may not be suitable for sidewalk navigation because the differential-wheeled mechanism allows a neutral turn without considering the surroundings. In this study, we developed a new action-intention indicator for future differential-wheeled mobile robots that employs RGB light-emitting diode strip lights to express various colors and complex blinking patterns. Sensitivity evaluation experiments were conducted with approximately 50 subjects to determine the optimal colors and blinking patterns for a differential-wheeled mobile robot. Additionally, reaction-time acquisition experiments were conducted to confirm the effectiveness of the proposed intention-display device for mobile robots. Finally, we evaluated whether the determined blinking patterns exhibited appropriate power consumption.

Evolutionary divergence of body size and wing and leg structure in relation to foraging mode in Darwin’s Galapagos finches

Abstract The wings, legs, and tail in Darwin’s finches show many clear adaptations to different types of locomotion used during foraging. We use size scaling to analyse how various characters vary with body mass to clarify dimensional relationships. The selective advantage of a character is judged in terms of energy savings. The wing aspect ratio (4.6–4.9) is very low, so the energy costs for flight are high. Low body mass, low wing loading, and short arm wings in the warbler finch, small tree finch, and small ground finch promote agility and manoeuvrability among vegetation, along with short wings in the warbler finch. Evolution towards a shorter arm wing seems to be favoured in the smaller finch species. Long legs, long toes, and long curved claws are adaptations for climbing/clinging locomotion without tail support (woodpecker finch, small and large tree finches, cactus finch but having short legs). Selection for longer legs seems to act towards a lengthening of the tarsometatarsus. The climbing technique in the woodpecker finch is described. We discuss how the diversification in the beaks relates to the locomotion organs.

Soft Airflow Sensors With Artificial Hair Structures and Printed Ionogel Channels for Wind Gust Detection for Small Uncrewed Vehicles

This article describes the design of a soft airflow sensor capable of detecting the direction and the magnitude of airflow, taking advantage of an additive manufacturing technique for rapid prototyping. The sensor consists of an artificial hair structure and conductive ionogel channels. The artificial hair, made by 3-D printing, is designed to maximize the moments at the base caused by the airflows applied to the hair structure. The ionogel channels are directly printed on a flexible printed circuit board and then embedded in an elastomeric layer. A compact readout circuit is prepared to acquire the impedance information from the sensing channels. The sensor shows reliable and repeatable responses to unidirectional airflows ranging from 6 to 13 m/s. A clear relationship between the applied loads and the sensor outputs is observed. We also demonstrate the performance and the application of the proposed airflow sensor by installing it on a small uncrewed ground vehicle that achieves stable operation through the detection of atmospheric disturbances.

Age effects in Darwin’s finches: older males build more concealed nests in areas with more heterospecific singing neighbors

Nesting success tends to increase with age in birds, in part because older birds select more concealed nest sites based on experience and/or an assessment of prevailing predation risk. In general, greater plant diversity is associated with more biodiversity and more vegetation cover. Here, we ask if older Darwin’s finch males nest in areas with greater vegetation cover and if these nest sites also have greater avian species diversity assessed using song. We compared patterns in Darwin’s Small Tree Finch (Camarhynchus parvulus) and Darwin’s Small Ground Finch (Geospiza fuliginosa) as males build the nest in both systems. We measured vegetation cover, nesting height, and con- vs. heterospecific songs per minute at 55 nests (22 C. parvulus, 33 G. fuliginosa). As expected, in both species, older males built nests in areas with more vegetation cover and these nests had less predation. A novel finding is that nests of older males also had more heterospecific singing neighbors. Future research could test whether older males outcompete younger males for access to preferred nest sites that are more concealed and sustain a greater local biodiversity. The findings also raise questions about the ontogenetic and fitness consequences of different acoustical experiences for developing nestlings inside the nest.

Wideband Dual-Polarized Endfire Phased Array Antenna With Small Ground Clearance for 5G mmWave Mobile Terminals

A dual-polarized end-fire phased array antenna is presented for 5G mmWave mobile terminal applications. The antenna element combines a pair of top-hat dipoles with an open slot in two substrate layers. The dipole is excited by an open-ended substrate integrated waveguide (SIW) for vertical polarization, and the slot is coupled by a bent stripline for horizontal polarization. Both radiators can provide wide bandwidth, and share a small ground clearance of merely 1.6 mm. A 1 × 4 phased array is designed with an element spacing of 6 mm. Decoupling vias and decoupling slots are added between elements to improve port isolation. The simulated and measured overlapped bandwidth of the two polarizations are 21.4% and 14.6%, respectively. The isolation between any two ports is higher than 18 dB. The measured scanning beams of both polarizations are capable of covering ±42° within 3-dB gain variation.

Remotely Administered Psychoacoustic Test for sUAS Noise to Gauge Feasibility of Remote UAM Noise Study

The National Aeronautics and Space Administration (NASA) remotely administered a psychoacoustic test in fall of 2022 as the first of two phases of a cooperative Urban Air Mobility (UAM) vehicle noise human response study. This first phase, described here, was a Feasibility Test to compare human subject responses with a previous in-person psychoacoustic test that found an annoyance response difference between small Uncrewed Aerial System (sUAS) noise and ground vehicle noise. This paper discusses the Feasibility Test online layout, sound calibration method, software development, stimuli selection, test subject recruitment, and test administration. Test performance is measured through comparison of annoyance response data with the previous in-person test. The test also investigated whether a contextual cue to test subjects influenced their annoyance response. Response differences between test subjects in geographically distinct areas are analyzed. Administrative challenges that were encountered during the test are discussed, and improvements to administering subsequent remote tests are recommended.

Sentinel-1 Interferometry and UAV Aerial Survey for Mapping Coseismic Ruptures: Mts. Sibillini vs. Mt. Etna Volcano

The survey and structural analysis of surface coseismic ruptures are essential tools for characterizing seismogenic structures. In this work, a procedure to survey coseismic ruptures using satellite interferometric synthetic aperture radar (InSAR) data, directing the survey using Unmanned Aerial Vehicles (UAV), is proposed together with a field validation of the results. The Sentinel-1 A/B Interferometric Wide (IW) Swath TOPSAR mode offers the possibility of acquiring images with a short revisit time. This huge amount of open data is extremely useful for geohazards monitoring, such as for earthquakes. Interferograms show the deformation field associated with earthquakes. Phase discontinuities appearing on wrapped interferograms or loss-of-coherence areas could represent small ground displacements associated with the fault’s ruptures. Low-altitude flight platforms such as UAV permit the acquisition of high resolution images and generate 3D spatial geolocalized clouds of data with centimeter-level accuracy. The generated topography maps and orthomosaic images are the direct products of this technology, allowing the possibility of analyzing geological structures from many viewpoints. We present two case studies. The first one is relative to the 2016 central Italian earthquakes, astride which the InSAR outcomes highlighted quite accurately the field displacement of extensional faults in the Mt. Vettore–M. Bove area. Here, the geological effect of the earthquake is represented by more than 35 km of ground ruptures with a complex pattern composed by subparallel and overlapping synthetic and antithetic fault splays. The second case is relative to the Mt. Etna earthquake of 26 December 2018, following which several ground ruptures were detected. The analysis of the unwrapped phase and the application of edge detector filtering and other discontinuity enhancers allowed the identification of a complex pattern of ground ruptures. In the Pennisi and Fiandaca areas different generation of ruptures can be distinguished, while previously unknown ruptures pertaining to the Acireale and Ragalna faults can be identify and analyzed.

Simulated seasonal oceanographic changes and their implication for the small pelagic fisheries in the Java Sea, Indonesia

Small pelagic fisheries in the Java Sea (JS) contributes to about 26.6% of the total marine fisheries resources, where their spatial-temporal variation is controlled by seasonal oceanographic changes. This study aims to investigate a relationship between seasonal reversal circulation and number of light-fishing vessels (VBD) dispersion that capture small pelagic fishes, using multi-datasets from a regional ocean circulation model, satellite-derived datasets, and pelagic fish landing datasets between 2010 and 2020. The model demonstrates that main axis of eastward (westward) monsoon current that brings warmer and fresher (cooler and saltier) water, confines much closer along the northern Java (southern Kalimantan) during the northwest (southeast) monsoon period. These changes are followed unprecedentedly by southward (northward) shift of VBD and high abundance of euryhaline (stenohaline) fish species. This new evidence implies that reversal monsoon current and surface component of Makassar Throughflow play a significant role on delineating potential small pelagic fishing ground and fish productions.

A CSAR 3D Imaging Method Suitable for Edge Computation

Due to the large amount of CSAR echo data carried by UAVs, either the original echo data need to be transmitted to the ground for processing or post-processing must be implemented after the flight. Therefore, it is difficult to use edge computing power such as a UAV onboard computer to implement image processing. The commonly used back projection (BP) algorithm and corresponding improved imaging algorithms require a large amount of computation and have slow imaging speed, which further limits the realization of CSAR 3D imaging on edge nodes. To improve the speed of CSAR 3D imaging, this paper proposes a CSAR 3D imaging method suitable for edge computation. Firstly, the improved Crazy Climber algorithm extracts sine track ridges that represent the amplitude changes in the range-compressed echo. Secondly, two-dimensional (2D) profiles of CSAR with different heights are obtained via inverse Radon transform (IRT). Thirdly, the Hough transform is used to extract the intersection points of the defocused circle along the heights in the X and Y directions. Finally, 3D point cloud extraction is completed through voting screening. In this paper, image detection methods such as ridge extraction, IRT, and Hough transform replace the phase compensation processing of the traditional BP 3D imaging method, which significantly reduces the time of CSAR 3D imaging. The correctness and effectiveness of the proposed method are verified by the 3D imaging results for the simulated data of ideal targets and X-band CSAR outfield flight raw data carried by a small rotor unmanned aerial vehicle (SRUAV). The proposed method provides a new direction for the fast 3D imaging of edge nodes, such as aircraft and small ground terminals. The image can be directly transmitted, which can improve the information transmission efficiency of the Internet of Things (IoT).

Generalized Stereo Matching Method Based on Iterative Optimization of Hierarchical Graph Structure Consistency Cost for Urban 3D Reconstruction

Generalized stereo matching faces the radiation difference and small ground feature difference brought by different satellites and different time phases, while the texture-less and disparity discontinuity phenomenon seriously affects the correspondence between matching points. To address the above problems, a novel generalized stereo matching method based on the iterative optimization of hierarchical graph structure consistency cost is proposed for urban 3D scene reconstruction. First, the self-similarity of images is used to construct k-nearest neighbor graphs. The left-view and right-view graph structures are mapped to the same neighborhood, and the graph structure consistency (GSC) cost is proposed to evaluate the similarity of the graph structures. Then, cross-scale cost aggregation is used to adaptively weight and combine multi-scale GSC costs. Next, object-based iterative optimization is proposed to optimize outliers in pixel-wise matching and mismatches in disparity discontinuity regions. The visibility term and the disparity discontinuity term are iterated to continuously detect occlusions and optimize the boundary disparity. Finally, fractal net evolution is used to optimize the disparity map. This paper verifies the effectiveness of the proposed method on a public US3D dataset and a self-made dataset, and compares it with state-of-the-art stereo matching methods.

Darwin’s finches in human-altered environments sing common song types and are more aggressive

Human-altered landscapes may act as an environmental filter benefiting species or individuals with specific sets of capacities or behaviors. Yet the effects of human activity on culturally transmitted traits in animals are still poorly understood. Combining song recordings and simulated territory intrusions, we investigated whether songs (a cultural trait) and aggressiveness (a personality trait) in small ground finches (Geospiza fuliginosa) differed along a gradient of human activity levels (high-low-high) spanning two habitats with contrasting levels of rainfall (arid lowlands, humid highlands). We found that more common syllable types were more prevalent in arid lowland sites and at sites with high human activity. The number of syllables per song, song duration, song tempo and song rhythmicity did not differ across habitats or levels of human activity. During simulated territorial intrusions, small ground finches living in areas with higher levels of human activity and in the arid lowlands (regardless of human activity) showed the strongest aggressive response compared to those living in areas with lower levels of human activity or in the humid highlands. Thus, prevalence of aggression and syllable commonness correlated with each other across sites. Our results support the idea that resource distribution and human-impacted environments may select jointly for specific behavioral phenotypes such as aggression as well as common cultural traits.

Assessment of the effect of contemporary climate warming on the small ground squirrel fleas population dynamics in Northwestern region of Caspian Depression

The dominant zonal rodent species in the steppes and semi-deserts of the Caspian Lowland is the small ground squirrel Spermophilus pygmaeus (Pallas, 1778). Flea species, which are its specific ectoparasites, play a significant role in the occurrence of plague epizootics in this area. The impact of global climate warming on the population dynamics of the fleas of the small ground squirrel in the northern deserts on the territory of the Caspian Lowland is discussed in this article. The literature sources and extensive archival materials were used for the analysis. The Ilmen-Pridelta landscape region (southwest of the Astrakhan Region), which is most fully characterized through the necessary quantitative indicators, was chosen as a model territory. The data of the annual spring-summer registration of indices of the flea abundance in wool and at the entrances of the burrows of the small ground squirrel, as well as his abundance rates (number of specimens per 1 ha), average monthly air temperature values reported by meteorological stations in Astrakhan over the past 70 years were statistically processed. The article reveals the mechanism of the influence of contemporary climate warming on the dynamics of the number of fleas of the small ground squirrel in the territory of the Caspian Lowland over the period of 1950-2021.

Seasonal changes in blood rheology in little ground squirrels.

The annual cycle of small ground squirrels (Spermophilus pygmaeus) consists of 2 periods: wakefulness (spring-autumn) and hibernation (winter). During the active period, ground squirrels breed (spring), accumulate fat reserves (summer) and prepare for hibernation (autumn). We suppose that the rheological properties of blood and the deformability of erythrocytes can change in different seasons of the animal's wakefulness period to adequately provide tissues with oxygen. The aim of this study was to identify possible adaptive changes in erythrocyte deformability and erythrocyte indices in ground squirrels during their active period. The deformability of erythrocytes was studied by ektacytometry in an osmotic gradient. It was found that in spring, after the arousal of ground squirrels, erythrocytes have the highest deformability (El_max), hydration (O_hyper), water permeability (El_min) and osmotic stability (∆O). In summer, compared with spring, the deformability of erythrocytes decreases, and the average volume of erythrocytes (MCV) also decreases. In autumn, before hibernation, the integral deformability of erythrocytes, their hydration, as well as the range of osmotic stability of erythrocytes increases relative to the summer period. In summer and autumn, in contrast to spring, the average concentration of hemoglobin in the erythrocyte (MCHC) increases. At low shear stress (1 Pa) in summer and autumn, osmoscan becomes a pronounced polymodal form, indicating a change in the viscoelastic properties of ground squirrel erythrocyte membranes. Thus, for the first time, we discovered seasonal variability in the deformability of ground squirrel erythrocytes, which is consistent with the spring-summer activity of animals and preparation for hibernation.

Ground Fault Detection of Small Resistance Grounding System Based on Improved Phase Current Abrupt Variable Method

When a high fault resistance happens in a small resistance ground system, the protection device is simple to be unsuccessful to manage. By analyzing the characteristics of positive, negative currents in the additional state of fault, it is found that the fault detection method constructed only by the phase current increment relationship has risk of misoperation, but relationship among the magnitude of phase current increment can directly reflect the phase of the ground fault. At the same time, the phase location among the fault phase voltage and the current of the unhealthy part and non-fault line is different. Therefore, a ground fault protection method based on the correlation between the phase current increment ratio and the different phase angles of fault phase voltage and current is proposed. We choose the phase with the big phase current mutation as the grounding phase, and affect the fault part by the phase difference between the fault phase voltage and the current of the line. This eliminates the risk of protection maloperation only using the relationship between the size of current increment and protection sensitivity in case of high resistance fault. It can be used for fault phase selection, location, and multi-level protection. The correctness of the way is certificated by simulation.

Characteristics and Applicability of Line Selection of Non-solidly Grounding Fault in Paralleling Double-Circuit Distribution Lines on Different Buses

To improve power supply capacity and save land resources, a large number of single-circuit distribution lines have been transformed into double-circuit distribution lines. The influence of their complex coupling relationship on the characteristics of non-solidly grounding faults and the applicability of existing line selection methods are not yet clear. An equivalent model of small grounding fault in double-circuit line from different buses is established, and the influence of the line-to-line coupling on the fault characteristics of the grounding system and the applicability of the line selection methods are analyzed by it. The results show that: for the system with a grounding fault, the line-to-line coupling does not affect its zero-sequence voltage and current characteristics, and the existing line selection methods are still applicable; for the system without a grounding fault, the double-circuit line shows the characteristics of the faulty line, and the existing line selection methods are no longer applicable. Simulation is used to verify the results.

Seismic Source Characterization From GNSS Data Using Deep Learning

AbstractThe detection of deformation in Global Navigation Satellite System (GNSS) time series associated with (a)seismic events down to a low magnitude is still a challenging issue. The presence of a considerable amount of noise in the data makes it difficult to reveal patterns of small ground deformation. Traditional analyses and methodologies are able to effectively retrieve the deformation associated with medium to large magnitude events. However, the automatic detection and characterization of such events is still a complex task, because traditionally employed methods often separate the time series analysis from the source characterization. Here we propose a first end‐to‐end framework to characterize seismic sources using geodetic data by means of deep learning, which can be an efficient alternative to the traditional workflow, possibly overcoming its performance. We exploit three different geodetic data representations in order to leverage the intrinsic spatio‐temporal structure of the GNSS noise and the target signal associated with (slow) earthquake deformation. We employ time series, images, and image time series to account for the temporal, spatial, and spatio‐temporal domain, respectively. Thereafter, we design and develop a specific deep learning model for each dataset. We analyze the performance of the tested models both on synthetic and real data from North Japan, showing that image time series of geodetic deformation can be an effective data representation to embed the spatio‐temporal evolution, with the associated deep learning method outperforming the other two. Therefore, jointly accounting for the spatial and temporal evolution may be the key to effectively detect and characterize fast or slow earthquakes.

UAV Thermal Imaging for Unexploded Ordnance Detection by Using Deep Learning

A few promising solutions for thermal imaging Unexploded Ordnance (UXO) detection were proposed after the start of the military conflict in Ukraine in 2014. At the same time, most of the landmine clearance protocols and practices are based on old, 20th-century technologies. More than 60 countries worldwide are still affected by explosive remnants of war, and new areas are contaminated almost every day. To date, no automated solutions exist for surface UXO detection by using thermal imaging. One of the reasons is also that there are no publicly available data. This research bridges both gaps by introducing an automated UXO detection method, and by publishing thermal imaging data. During a project in Bosnia and Herzegovina in 2019, an organisation, Norwegian People’s Aid, collected data about unexploded ordnances and made them available for this research. Thermal images with a size of 720 × 480 pixels were collected by using an Unmanned Aerial Vehicle at a height of 3 m, thus achieving a very small Ground Sampling Distance (GSD). One of the goals of our research was also to verify if the explosive war remnants’ detection accuracy could be improved further by using Convolutional Neural Networks (CNN). We have experimented with various existing modern CNN architectures for object identification, whereat the YOLOv5 model was selected as the most promising for retraining. An eleven-class object detection problem was solved primarily in this study. Our data were annotated semi-manually. Five versions of the YOLOv5 model, fine-tuned with a grid-search, were trained end-to-end on randomly selected 640 training and 80 validation images from our dataset. The trained models were verified on the remaining 88 images from our dataset. Objects from each of the eleven classes were identified with more than 90% probability, whereat the Mean Average Precision (mAP) at a 0.5 threshold was 99.5%, and the mAP at thresholds from 0.5 to 0.95 was 87.0% up to 90.5%, depending on the model’s complexity. Our results are comparable to the state-of-the-art, whereat these object detection methods have been tested on other similar small datasets with thermal images. Our study is one of the few in the field of Automated UXO detection by using thermal images, and the first that solves the problem of identifying more than one class of objects. On the other hand, publicly available thermal images with a relatively small GSD will enable and stimulate the development of new detection algorithms, where our method and results can serve as a baseline. Only really accurate automatic UXO detection solutions will help to solve one of the least explored worldwide life-threatening problems.

Towards Generating Realistic Wrist Pulse Signals Using Enhanced One Dimensional Wasserstein GAN.

For the past several years, there has been an increasing focus on deep learning methods applied into computational pulse diagnosis. However, one factor restraining its development lies in the small wrist pulse dataset, due to privacy risks or lengthy experiments cost. In this study, for the first time, we address the challenging by presenting a novel one-dimension generative adversarial networks (GAN) for generating wrist pulse signals, which manages to learn a mapping strategy from a random noise space to the original wrist pulse data distribution automatically. Concretely, Wasserstein GAN with gradient penalty (WGAN-GP) is employed to alleviate the mode collapse problem of vanilla GANs, which could be able to further enhance the performance of the generated pulse data. We compared our proposed model performance with several typical GAN models, including vanilla GAN, deep convolutional GAN (DCGAN) and Wasserstein GAN (WGAN). To verify the feasibility of the proposed algorithm, we trained our model with a dataset of real recorded wrist pulse signals. In conducted experiments, qualitative visual inspection and several quantitative metrics, such as maximum mean deviation (MMD), sliced Wasserstein distance (SWD) and percent root mean square difference (PRD), are examined to measure performance comprehensively. Overall, WGAN-GP achieves the best performance and quantitative results show that the above three metrics can be as low as 0.2325, 0.0112 and 5.8748, respectively. The positive results support that generating wrist pulse data from a small ground truth is possible. Consequently, our proposed WGAN-GP model offers a potential innovative solution to address data scarcity challenge for researchers working with computational pulse diagnosis, which are expected to improve the performance of pulse diagnosis algorithms in the future.

Preparation of CaCO3/Al(OH)3 Composites via Heterogeneous Nucleation.

As one of the most widely used inorganic fine powder fillers, calcium carbonate is cheap. However, considering its poor light transmittance, it is not suitable to be added to resin matrix composites that require high light transmittance. Aluminum hydroxide has good light transmission and flame retardancy, but it is more expensive than calcium carbonate. CaCO3/Al(OH)3 composites with a core-shell structure that showed a trend toward the performance of aluminum hydroxide not only improved the surface properties of CaCO3, but also increased the added value of CaCO3. In the present paper, CaCO3/Al(OH)3 composites were successfully prepared in sodium aluminate solution via heterogeneous nucleation. Four types of calcium sources, including calcite-type precipitated calcium carbonate, vaterite-type precipitated calcium carbonate, ground calcium carbonate with two different particle sizes as the precursors and supersaturated sodium aluminate solution as the substrate, have been deeply investigated in terms of their influence on the preparation of CaCO3/Al(OH)3 composites. Results showed that the calcium carbonate precursor greatly affected the formation of CaCO3/Al(OH)3 composites. Both the precipitated calcium carbonate and the small particle ground calcium carbonate are likely to undergo anti-causticization and a complexation reaction with it to generate 3CaO·Al2O3·6H2O and 3CaO·Al2O3·CaCO3·11H2O, which go against the coating of calcium carbonate with aluminum hydroxide. Within the experimental range, the use of ground calcium carbonate with a particle size of 400-500 mesh is more suitable as a precursor for the preparation of core-shell CaCO3/Al(OH)3 composites.

Fault transient feature extraction method of 66kV transmission line based on improved wavelet threshold and CEEMDAN-FME

In the 66kV transmission line, the compensation effect of the arc suppression coil, so the amplitude of fault zero sequence current is weak after the occurrence of single-phase grounding responsibility. The fault characteristics are not obvious, and there is environmental noise interference during fault signal acquisition, which further increases the difficulty of ground fault feature extraction. To solve the above problems, a fault transient feature extraction method of 66kV transmission line is proposed, based on improved wavelet threshold and Complete Ensemble Empirical Mode Decomposition with adaptive noise (CEEMDAN) - Fuzzy measure entropy (FME). The characteristics of single-phase grounding transient fault in small current grounding system are analyzed. The transient fault signal was preprocessed by an improved wavelet threshold method, and the transient fault characteristics were extracted accurately by CEEMDAN-FME processing. The proposed method has good anti-noise performance through the simulation comparison and verification of denoising processing and transient feature extraction by MATLAB. It can effectively extract fault features when the interference degree is significant.