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This paper proposes two rigid formation task planning schemes for multi-agent systems to address the problem of maintaining rigid formation task planning under the condition of only obtaining local distance and relative angle information of multi-agent systems. Firstly, a rigid formation planning scheme based on distance and relative angle is proposed to ensure the rigid formation of intelligent agents in unknown relative positions. Secondly, the task planning method of null space projection is used to solve the conflict between formation tasks and obstacle avoidance tasks, ensuring the stability of formation during the movement process. An overall rigid formation planning scheme is proposed that combines distance and relative angle again, and the multi-agent system is considered as a whole for obstacle avoidance during the obstacle avoidance process, ensuring stable rigid formation and the completion of obstacle avoidance tasks. After simulation verification, the two methods proposed in this paper can maintain a rigid formation and complete obstacle avoidance tasks well under the condition of weakening relative position information. Compared with the null space behavior control method that relies on relative position, it weakens the dependence on relative position information.

Copyright of Aero Weaponry is the property of Aero Weaponry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aspect-category-opinion-sentiment (ACOS) quadruples play an essential role in implicit sentiment analysis. Considering the distances between aspects and opinions in sentences, a novel Distance-Extract-Classify- ACOS quadruple extraction method with distance information between aspects and opinions is proposed. Compared with Double-Propagation-ACOS, JET-BERT-ACOS, and Extract-Classify-ACOS quadruple extraction models, the recall and F1 scores of the Distance-Extract-Classify-ACOS quadruple extraction model respectively increase by 2.08%-35.81% and 1.47%-36.7% on the Restaurant-ACOS and Laptop-ACOS datasets. Using the extracted quadruples for implicit sentiment analysis, the performance of the LSTM, GRU, TextCNN, and BERT models significantly outperform these models with original sentences, aspects-opinions pairs, and aspects-categories-opinions triples on Restaurant-ACOS and Laptop-ACOS datasets. [ABSTRACT FROM AUTHOR]

Particle locations determine the whole structure of a granular system, which is crucial to understanding various anomalous behaviors in glasses and amorphous solids. How to accurately determine the coordinates of each particle in such materials within a short time has always been a challenge. In this paper, we use an improved graph convolutional neural network to estimate the particle locations in two-dimensional photoelastic granular materials purely from the knowledge of the distances for each particle, which can be estimated in advance via a distance estimation algorithm. The robustness and effectiveness of our model are verified by testing other granular systems with different disorder degrees, as well as systems with different configurations. In this study, we attempt to provide a new route to the structural information of granular systems irrelevant to dimensionality, compositions, or other material properties. [ABSTRACT FROM AUTHOR]

An ultra-wideband (UWB) positioning system consists of at least three anchors and a tag for the positioning procedure. Via the UWB transceivers mounted on all devices in the system, we can obtain the distance information between each pair of devices and further realize the tag localization. However, the uncertain measurement in the real world may introduce incorrect measurement information, e.g., time, distance, positioning, and so on. Therefore, we intend to incorporate the technique of ensemble learning with UWB positioning to improve its performance. In this paper, we present two methods. The experimental results show that our ideas can be applied to different scenarios and work well. Of note, compared with the existing research in the literature, our first algorithm was more accurate and stable. Further, our second algorithm possessed even better performance than the first. Moreover, we also provide a comprehensive discussion for an ill-advised point, which is often used to evaluate the positioning efficiency in the literature. [ABSTRACT FROM AUTHOR]

Since wireless systems allow for easier access to communication paths than wired systems, it is necessary to improve their dependability against cyberterrorists. To make wireless systems more dependable, additional measures at the lower layer are required, in addition to those at the upper layers. Our proposal uses an integrated terminal-like cellular phone which has multiple radio access technologies (RATs) such as cellular, wireless local area network (LAN), Bluetooth, and an ultra-wide band (UWB). We propose to communicate information encoded by shortened code using multiple RATs. Redundancy by RATs and their error correction capability can simultaneously improve wiretap resistance and attack resistance. A codeword of shortened code is obtained by removing a part of a codeword of popular code. A decoder can improve the error correction capability if the removed part is known. By using shortened codes, the dependability can be further enhanced because the error correction capability between the legitimate receiver and the cyberterrorist can make a difference. To do this, it is necessary to securely share the removed part between the sender and receiver. Our proposal is to securely measure the distance between the sender and receiver using UWB and use it as the removed part. It was confirmed that the secrecy capacity is improved.

Particle locations determine the whole structure of a granular system, which is crucial to understanding various anomalous behaviors in glasses and amorphous solids. How to accurately determine the coordinates of each particle in such materials within a short time has always been a challenge. In this paper, we use an improved graph convolutional neural network to estimate the particle locations in two-dimensional photoelastic granular materials purely from the knowledge of the distances for each particle, which can be estimated in advance via a distance estimation algorithm. The robustness and effectiveness of our model are verified by testing other granular systems with different disorder degrees, as well as systems with different configurations. In this study, we attempt to provide a new route to the structural information of granular systems irrelevant to dimensionality, compositions, or other material properties.

Camera focal length estimation from a single image is of great importance for many computer vision tasks. Unfortunately, previous methods cannot achieve satisfactory accuracy yet. This paper proposes a focal length estimation approach based on distances among four points in the scene of a single image. The issue is cast into a nonlinear optimization by adapting a standard pinhole camera model under the constraints of distance information. Multiple algorithms are employed to solve the optimization, and the best solution is then regarded as the final solution. Experimental results show that our method is able to obtain a more accurate focal length than some state of the art in a single image setting. In addition, we provide some simple application examples and show the intuitive effects of focal length estimation errors. We also demonstrate experimentally that distance information has an improved meaning for the solution of the focal length. [ABSTRACT FROM AUTHOR]

An ultra-wideband (UWB) positioning system consists of at least three anchors and a tag for the positioning procedure. Via the UWB transceivers mounted on all devices in the system, we can obtain the distance information between each pair of devices and further realize the tag localization. However, the uncertain measurement in the real world may introduce incorrect measurement information, e.g., time, distance, positioning, and so on. Therefore, we intend to incorporate the technique of ensemble learning with UWB positioning to improve its performance. In this paper, we present two methods. The experimental results show that our ideas can be applied to different scenarios and work well. Of note, compared with the existing research in the literature, our first algorithm was more accurate and stable. Further, our second algorithm possessed even better performance than the first. Moreover, we also provide a comprehensive discussion for an ill-advised point, which is often used to evaluate the positioning efficiency in the literature.

Copyright of Journal of Data Acquisition & Processing / Shu Ju Cai Ji Yu Chu Li is the property of Editorial Department of Journal of Nanjing University of Aeronautics & Astronautics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Minimally invasive techniques, such as laparoscopy and radiofrequency ablation of tumors, bring important advantages in surgery: by minimizing incisions on the patient's body, they can reduce the hospitalization period and the risk of postoperative complications. Unfortunately, they come with drawbacks for surgeons, who have a restricted vision of the operation area through an indirect access and 2D images provided by a camera inserted in the body. Augmented reality provides an "X-ray vision" of the patient anatomy thanks to the visualization of the internal organs of the patient. In this way, surgeons are free from the task of mentally associating the content from CT images to the operative scene. We present a navigation system that supports surgeons in preoperative and intraoperative phases and an augmented reality system that superimposes virtual organs on the patient's body together with depth and distance information. We implemented a combination of visual and audio cues allowing the surgeon to improve the intervention precision and avoid the risk of damaging anatomical structures. The test scenarios proved the good efficacy and accuracy of the system. Moreover, tests in the operating room suggested some modifications to the tracking system to make it more robust with respect to occlusions. Graphical Abstract Augmented visualization in minimally invasive surgery. [ABSTRACT FROM AUTHOR]

Abstract Delay-tuned auditory neurons of the mustached bat show facilitative responses to a combination of signal elements of a biosonar pulse-echo pair with a specific echo delay. The subcollicular nuclei produce latency-constant phasic on-responding neurons, and the inferior colliculus produces delay-tuned combination-sensitive neurons, designated "FM-FM" neurons. The combination-sensitivity is a facilitated response to the coincidence of the excitatory rebound following glycinergic inhibition to the pulse (1st harmonic) and the short-latency response to the echo (2nd–4th harmonics). The facilitative response of thalamic FM-FM neurons is mediated by glutamate receptors (NMDA and non-NMDA receptors). Different from collicular FM-FM neurons, thalamic ones respond more selectively to pulse-echo pairs than individual signal elements. A number of differences in response properties between collicular and thalamic or cortical FM-FM neurons have been reported. However, differences between thalamic and cortical FM-FM neurons have remained to be studied. Here, we report that GABAergic inhibition controls the duration of burst of spikes of facilitative responses of thalamic FM-FM neurons and sharpens the delay tuning of cortical ones. That is, intra-cortical inhibition sharpens the delay tuning of cortical FM-FM neurons that is potentially broad because of divergent/convergent thalamo-cortical projections. Compared with thalamic neurons, cortical ones tend to show sharper delay tuning, longer response duration, and larger facilitation index. However, those differences are statistically insignificant. Highlights • The facilitative responses of thalamic FM-FM neurons are glutamate-dependent. • The fast and slow components of those responses are non-NMDA- and NMDA-dependent. • The slow component (burst of discharges) produces sharp delay tuning in the thalamus. • Inhibition modulates the duration of the slow component in thalamic FM-FM neurons. • Inhibition modulates the sharpness of delay tuning in cortical FM-FM neurons. [ABSTRACT FROM AUTHOR]

• The matter-element extension model was used to evaluate the effectiveness of eight scenarios on driver behavior. • Including distance information can improve driver safety when passing through a work zone. • It is recommended that the number of warning signs in work zones should be less than three, with two being the ideal number. The continuous growth of automobile ownership and road mileage in China has brought a lot of road maintenance work. The work zone shall be set for road maintenance work. Due to the road characteristics near the work zone, more accidents and a higher accident risk exist. Traffic signs are one of the essential means to ensure traffic safety. The location and number of road work signs (sign level) play a crucial role in driver safety near the work zone. The repeated road work signs can form a warning system to regulate driver behavior. This paper evaluates the effect of the number of warning signs with and without distance information on driver behavior (psychological load and physiological characteristics) near the work zone. The matter-element extension model is used for comprehensive evaluation. The study resulted in several findings. First, adding distance information improves the difficulty and time of visual recognition and enhances driver alertness. On the other hand, too many road signs are not conducive to maintaining driver alertness. Second, distance information on the work signs and the repeated setting of road warning signs add extra burden on the driver and increase driver fatigue. Third, driver's response to the repeated road work signs will gradually become stable; The speed transition under the warning signs Levels 2 and 3 are more stable than that under the warning sign Levels 1 and 4. Finally, the warning sign level shall not be more than 3. If the advanced warning area is short, it is recommended to select a warning sign Level 1. If the advanced warning area is relatively long, it is recommended to choose a warning sign Level 2. Finally, adding distance information will improve the overall effect of the warning scheme. These findings can provide a valuable reference for setting the road work signs near the work zone in practice in China. [ABSTRACT FROM AUTHOR]

Image-guided neurosurgery, or neuronavigation, has been used to visualise the location of a surgical probe by mapping the probe location to pre-operative models of a patient's anatomy. One common limitation of this approach is that it requires the surgeon to divert their attention away from the patient and towards the neuronavigation system. In order to improve this type of application, the authors designed a system that sonifies (i.e. provides audible feedback of) distance information between a surgical probe and the location of the anatomy of interest. A user study (n = 15) was completed to determine the utility of sonified distance information within an existing neuronavigation platform (Intraoperative Brain Imaging System (IBIS) Neuronav). The authors’ results were consistent with the idea that combining auditory distance cues with existing visual information from image-guided surgery systems may result in greater accuracy when locating specified points on a pre-operative scan, thereby potentially reducing the extent of the required surgical openings, as well as potentially increasing the precision of individual surgical tasks. Further, the authors’ results were also consistent with the hypothesis that combining auditory and visual information reduces the perceived difficulty in locating a target location within a three-dimensional volume.

Since the honeybee possesses eusociality, advanced learning, memory ability, and information sharing through the use of various pheromones and sophisticated symbol communication (i.e., the “waggle dance”), this remarkable social animal has been one of the model symbolic animals for biological studies, animal ecology, ethology, and neuroethology. Karl von Frisch discovered the meanings of the waggle dance and called the communication a “dance language.” Subsequent to this discovery, it has been extensively studied how effectively recruits translate the code in the dance to reach the advertised destination and how the waggle dance information conflicts with the information based on their own foraging experience. The dance followers, mostly foragers, detect and interact with the waggle dancer, and are finally recruited to the food source. In this review, we summarize the current state of knowledge on the neural processing underlying this fascinating behavior.

Many wireless sensor network (WSN) applications rely on precise location or distance information. Despite the potentials of WSNs, efficient location prediction is one of the subsisting challenges. This study presents novel prediction algorithms based on a Kriging interpolation technique. Given that each sensor is aware of its location only, the aims of this work are to accurately predict the temperature at uncovered areas and estimate positions of heat sources. By taking few measurements within the field of interest and by using Kriging interpolation to iteratively enhance predictions of temperature and location of heat sources in uncovered regions, the degree of accuracy is significantly improved. Following a range of independent Monte Carlo runs in different experiments, it is shown through a comparative analysis that the proposed algorithm delivers approximately 98% prediction accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A method to decompose a 3D object into simple parts starting from its curve skeleton is described. Branches of the curve skeleton are classified as meaningful and non-meaningful by using the notion of zone of influence of the points where skeleton branches meet. Meaningful branches are associated to subsets of the object, which are obtained by subtracting from the input object suitably expanded versions of the zones of influence, termed overlapping regions. Decision is taken on whether the overlapping regions should be individual decomposition components, or should be assigned to properly selected adjacent object’s subsets. The so obtained object’s decomposition components are subdivided into parts characterized by simple shape through the polygonal approximation of the corresponding skeleton branches. [ABSTRACT FROM AUTHOR]

The distance labeled curve skeleton of a 3D object is used to guide the decomposition of the object into disjoint parts. To this aim, the skeleton is polygonally approximated by taking into account spatial coordinates and distance values of its voxels. The obtained skeleton segments are characterized by the absence of significant changes of curvature. Moreover, along each skeleton segment distance values are constant or show a linearly changing trend. Each segment can be interpreted as the spine of a simple part, which is characterized by the absence of significant curvature changes along its boundary, and by local thickness that is constant or evolves linearly along the part. By using exclusively the spatial coordinates and distance values of the vertices of the spines, quantitative information on shape, size, position and orientation of the corresponding simple parts can be obtained. Alternative decompositions of the object can be computed by selecting different values for the threshold used during polygonal approximation of the skeleton. Some criteria are also discussed for the selection of optimal threshold values originating approximated skeletons having a small number of segments, but still producing decompositions rather well adapting the input object boundary. [ABSTRACT FROM AUTHOR]

Aimed at the tracking drift bought by imaging perspective and distance changes in the tracking process of image-guided target tracking system, a tracking algorithm using the distance information to dynamically change the scale of tracking window of the Mean-Shift algorithm was proposed. Firstly, the target's gray feature model was established according to the selected initial tracking template, and the initial scale of tracking window of Mean-Shift was determined. Then, the window's scale was updated according to the distance information to ensure the tracking window contain the target completely or partially while the tracking system gradually closed to the target. Finally, Bhattacharyya correlation coefficient was used to update the target template nonlinearly after the tracking convergence of each frame. This paper uses the flight video data generated by Vega to simulate the algorithm, and the result shows that it can adapt to the expanding of the goal, and reduce the tracking drift in a large extent. [ABSTRACT FROM AUTHOR]

Abstract: The observations of Type Ia supernovae (SN Ia), Baryon Acoustic Oscillations (BAO) and Cosmic Microwave Background radiation (CMB) provide powerful tools for the measurement of cosmological parameters. One of the most useful information encodes in the distance measured by those probes. In this Letter, we test the coherence of the observational information provided by SN Ia, BAO and CMB experiments. We make two kinds of comparison: the first is the constraints on cosmological parameters of the equation of state parameter (EoS) of dark energy (DE) and matter budget parameter from the latest data by global fitting, and we find the large discrepancy from those different probes. The second comparison is performed among the derived distance information from these observations at certain appointed redshift, the results show that the distance provided by WMAP5 are larger than those from SN Ia and BAO on the whole. [Copyright &y& Elsevier]

Jumping spiders (Salticidae) use exceptional vision, largely mediated by their forward-facing anterior lateral (AL) and anterior medial (AM) eyes, to pounce on prey from a distance. We evaluated depth perception through the use of 'texture density' (depth estimation through surface texture comparisons, with greater distances having higher textural density) in the salticid Trite planiceps. In visual cliff experiments, spiders tended to choose an area with a false 'low drop' over a false 'high drop' with the same texture densities, but showed no preference for either area when presented with substrates with different texture densities at a constant height. This was corroborated when T. planiceps did not avoid jumping over an illusion resembling a trench compared to a no-illusion control pattern. We then selectively occluded both AL and 1 AM eye (monocular treatment), both AL eyes (ALE-occluded binocular treatment) or no eyes (control), and induced spiders to jump across a gap at different heights. Neither control spiders, spiders with binocular cues from the AM eyes or monocular treatment spiders exhibited a height preference. These results suggest that while T. planiceps accurately perceives depth, it does not appear to rely on texture gradients as a depth cue. • We investigated depth perception in jumping spiders (salticids) using texture density. • Salticids lept between islands or walked on floating glass with textured substrates. • Spiders were averse to heights, and gauged depth using monocular cues. • Visual illusions, however, were not perceived as illusory. • Salticids did not appear to use texture density to gauge distance. [ABSTRACT FROM AUTHOR]

In vehicular ad hoc networks (VANets), a precise localization system is a crucial factor for several critical safety applications. The global positioning system (GPS) is commonly used to determine the vehicles' position estimation. However, it has unwanted errors yet that can be worse in some areas, such as urban street canyons and indoor parking lots, making it inaccurate for most critical safety applications. In this work, we present a new position estimation method called cooperative vehicle localization improvement using distance information (CoVaLID), which improves GPS positions of nearby vehicles and minimize their errors through an extended Kalman filter to execute Data Fusion using GPS and distance information. Our solution also uses distance information to assess the position accuracy related to three different aspects: the number of vehicles, vehicle trajectory, and distance information error. For that purpose, we use a weighted average method to put more confidence in distance information given by neighbors closer to the target. We implement and evaluate the performance of CoVaLID using real-world data, as well as discuss the impact of different distance sensors in our proposed solution. Our results clearly show that CoVaLID is capable of reducing the GPS error by 63%, and 53% when compared to the state-of-the-art VANet location improve (VLOCI) algorithm. [ABSTRACT FROM AUTHOR]

Since the honeybee possesses eusociality, advanced learning, memory ability, and information sharing through the use of various pheromones and sophisticated symbol communication (i.e., the "waggle dance"), this remarkable social animal has been one of the model symbolic animals for biological studies, animal ecology, ethology, and neuroethology. Karl von Frisch discovered the meanings of the waggle dance and called the communication a "dance language." Subsequent to this discovery, it has been extensively studied how effectively recruits translate the code in the dance to reach the advertised destination and how the waggle dance information conflicts with the information based on their own foraging experience. The dance followers, mostly foragers, detect and interact with the waggle dancer, and are finally recruited to the food source. In this review, we summarize the current state of knowledge on the neural processing underlying this fascinating behavior. [ABSTRACT FROM AUTHOR]