Grouped random parameters Poisson-Lindley model with spatial effects addressing crashes at intersections: Insights from visual environment features and spatiotemporal instability

Spatiotemporal instability analysis of injury severities in truck-involved and non-truck-involved crashes

Introduction Urban green spaces (UGSs) play a dual role in high-density cities: they are crucial for biodiversity conservation and serve as key venues for promoting residents’ health. However, the benefits gained by people in these settings depend less on objectively measured biodiversity and more on their subjective perception of it. Visual cues, which account for over 80% of sensory input, significantly shape this perception. Methods This study explores the interrelationships among measured plant diversity, perceived plant diversity, and visual landscape characteristics in UGSs, so that to develop a predictive model for perceived diversity using the other two variables. Based on a case study of nine representative parks in Shanghai, the research compared measured plant diversity—using four indices (arbor, shrub, herbaceous, and community diversity)—with perceived plant diversity and evaluated the influence of visual landscape features. Results Results showed a significant mismatch between measured and perceived diversity. Furthermore, visual characteristics were more effective than measured biodiversity in predicting perceived plant diversity. These findings offer practical, short-term design strategies for enhancing perceived biodiversity in urban parks—complementing longer-term ecological measures aimed at increasing actual biodiversity. Discussion This study advances the understanding of how objective biodiversity, human perception, and visual environment interact, and supports the design of nature-based solutions that benefit both human well-being and biodiversity conservation.

With the development of the Shanghai International Shipping Center, the diversity of vehicle types on the highways and arterial roads near Yangshan port is continually increasing. Within such a container port corridor, large container trucks are primarily utilized for mainline transportation. Their larger size and significant inertia would increase psychological pressure on sedan drivers, and elevate their behavior risk. To investigate the effects of container trucks on drivers’ visual characteristics and driving behavior as well as to predict driving risk, firstly, this research conducted field tests in four scenarios surrounding the port. Visual characteristics and behavior data of sedan drivers were collected. Secondly, a “Visual‐behavior” chain model was established. The relationship between drivers’ visual characteristics, driving behavior, and driving risk was illustrated from the perspective of time‐series behavior patterns. Thirdly, three driving risk prediction models were built with Autoregressive Integrated Moving Average (ARIMA), Long Short‐Term Memory (LSTM), and ARIMA‐LSTM. The results indicate that the ARIMA‐LSTM model shows the most effective prediction performance. This research provides a field‐data comparative analysis of the driving risks influenced by a high proportion of container trucks. The findings contribute to understanding the unique mixed traffic visual environment around large‐scale container ports.

We present a variety of new visual features in extension to the TED-LIUM corpus. We re-aligned the original TED talk audio transcriptions with official TED.com videos. By utilizing state-of-the-art models for face and facial landmarks detection, optical character recognition, object detection and classification, we extract four new visual features that can be used for Large-Vocabulary Continuous Speech Recognition (LVCSR) systems, including facial images, landmarks, text, and objects in the scenes. The facial images and landmarks can be used in combination with audio for audio-visual acoustic modeling where the visual modality provides robust features in adverse acoustic environments. The contextual information, i.e. extracted text and detected objects in the scene can be used as prior knowledge to create contextual language models. Experimental results showed the efficacy of using visual features on top of acoustic features for speech recognition in overlapping speech scenarios.

Evidence that visual perception is subject to various forms of induced blindness has been taken to suggest that observers do not build a complete, spatio-topic representation of their visual environment. Instead, it has been suggested that induced blindness and other phenomena related to selective processing are indicative of capacity limits acting at one or more levels in the visual system. Capacity limits in visual attention have traditionally been studied using static arrays of elements from which an observer must detect a target defined by a certain visual feature or combination of features. In the current study, we use a visual search paradigm, with accuracy as the dependent variable, to examine capacity limits for different visual features undergoing change over time. Stimuli used in these experiments were gabor gratings placed in a circular ring around a central fixation point. In Experiment 1, detectability of a single changing target was measured under conditions where the type of change (size, speed, color), the magnitude of change, the set size and distractor homogeneity were all systematically varied. Psychometric function slopes were calculated for different experimental conditions and 'change thresholds' extracted from these slopes were used in Experiment 2, in which multiple supra-threshold changes were made, simultaneously, either to a single or to two or three different stimulus elements. Together, these experiments examined the interactive effects on processing capacity of changing different stimulus features one at a time and changing several (which are distributed either within a single object or across objects) simultaneously.

Decision letter: Visual and motor signatures of locomotion dynamically shape a population code for feature detection in Drosophila

For Digital Media Art, Max is a high-quality visual programming language with the features of visualization and modularization. The processing of the digital signal in Max can achieve a variety of effects. The related operations include numerical operations, numerical mapping, numerical automatic generation, and conditional branch programming, etc. In the process of artistic creation, information such as audio, video and motion can be input, processed, and output. This article summarizes some basic techniques from the above aspects, aiming to promote the communications in art and other fields, and to some extent inspire the transformation of relevant art education.

Caudate nucleus reactivity predicts perceptual learning rate for visual feature conjunctions

It seems reasonable to assume that pigeons use visual features in the landscape for orientation when they are homing over familiar terrain. Experimental evidence to prove or disprove this possibility is, however, difficult to obtain. Here, we link the problem with the observation that deflections of initial orientation caused by clock-shift are often smaller than predicted on a pure sun compass basis. We substantiate the hypothesis that consistently reduced deflections and increased angular scatter occur only when pigeons are released in familiar areas where a remembered pattern of landscape features can conflict with the position of the sun. Repeated releases of the same individuals under clock-shift, or elimination of non-visual navigational clues (odours), appear to strengthen the conflicting influence of familiar visual landmarks. Accelerated returns of birds allowed to preview the surrounding familiar scenery before release also support the conclusion that the visual environment is included in the homing system of pigeons. The landscape, however, not only helps home-finding, if it is familiar, but may also have a distracting influence that contributes to the great variability of initial orientation patterns.

Delineation of natural landscape units for Puerto Rico

Vision-assisted technologies in industrial manual operation such as augmented reality (AR) are increasingly popular. They require high positioning accuracy and robustness to operate normally. However, narrow spaces, moving hands, or tools may occlude or obscure local visual features of operation environments and thus affect the positioning accuracy and robustness of operating position. The resultant misguidance may even cause misoperation of operators. This paper proposes a marker-less monocular vision point positioning method for vision-assisted manual operation in industrial environments. The proposed method can accurately and robustly locate the target point of operation using constraint minimization method even if the target area has no corresponding visual features in the case of occlusion and improper illumination. The proposed method has three phases: intersection generation, intersection optimization, and target point solving. In the intersection generation phase, a certain number of intersections of epipolar lines are generated as candidate target points using fundamental matrices. Here, the solving constraint is converted from point-to-line to point-to-points. In the intersection optimization phase, the intersections are optimized to two different sets through the iterative linear fitting and geometric mean absolute error methods. Here, the solving constraint is further converted from point-to-points to point-to-point sets. In the target point solving phase, the target point is solved as a constrained minimization problem based on the distribution constraint of the two intersection sets. Here, the solving constraint is finally converted from point-to-point sets to point-to-point, and the unique optimal solution is obtained as the target point. The experimental results show that this method has a better accuracy and robustness than the traditional homography matrix method for the practical industrial operation scenes.

Road traffic is the primary source of unwanted outdoor noise caused by human activity. It has been linked to a range of adverse outcomes, from short-term effects, such as sleep disturbance and reduced cognitive performance, to long-term chronic diseases. The pathways by which noise exposure impacts health and well-being extend beyond the physiological act of hearing, as the auditory perception is highly subjective, personal, and context-dependent. Yet, noise control regulatory frameworks typically limit their scope to reducing exposure, thereby neglecting key characteristics of the acoustic environments and situational aspects. Beyond noise levels, spectral content, temporal dynamics, noise source composition, and several non-acoustic modifiers can jointly determine the perceptual and physiological burden of environmental noise. This thesis addresses road traffic noise as a component of the broader environmental noise context, investigating the interplay between its measurable acoustic features, geospatial and contextual information, and the perceptual, behavioral, and physiological responses of individuals and the community. Firstly, vehicle noise was characterized using psychoacoustic indicators, which are objective metrics that better resemble the human auditory experience. These indicators were found to vary systematically with driving speed and temperature and to produce distinctive acoustic signatures for different vehicle classes. Used as features in an audio-only vehicle classifier, psychoacoustic indicators enabled 91% accuracy, offering a potential shift toward a vehicle classification based on how vehicles “sound like” rather than visual characteristics. Second, longitudinal field studies showed that community acceptance of large infrastructural road-noise interventions (noise barriers and road resurfacing with low-noise asphalt) depends less on the eventual noise levels than on situational factors such as trust in the road authorities and expectations. Third, an immersive laboratory experiment combining auralized tire-road noise with virtual-reality streetscapes demonstrated that lower speed limits, quieter and well-maintained pavements, and, to a lesser extent, green infrastructure, reduce not only self-reported noise annoyance but the involuntary physiological stress response, as measured by biomarkers. Finally, a dataset of geolocated soundwalks collected through a citizen science initiative was used to explore the impact of the physical environment on the subjective soundscape assessments. Indicators of anthropogenic activity, presence of nature and land use, and traffic infrastructure proved to explain, to a modest extent, the variance in pleasantness and eventfulness in everyday settings. A prototype geospatial model based solely on these variables shows potential for scalability and replicability, offering a practical tool to guide large-scale soundscape interventions.

Purpose. The purpose of this study is to examine the role of colour in the visual image design of cities in Shandong Province based on the analysis of regional characteristics. Methodology. The study is based on the analysis of collected representative graphic materials from selected cities in Shandong Province using the visual sampling method, which allowed obtaining real visual information about the city. The manual colour extraction method is used to extract the dominant colour in the selected image material from a colour recognition website, record its HEX CODE and name it. Finally, the ‘The main theme’ colours of 10 cities in Shandong Province were extracted using colour analysis. Based on their art historical analysis, which includes an analysis of colour trends, cultural background, and urban development orientation, their spatial colour characteristics and visual images were highlighted to form a system of colour representation with narrativity and locality. Results. The study of urban colour characteristics based on regional aspects demonstrates the diversity of urban colours in Shandong Province and explains the importance of colour in urban development. The colour types of cities in Shandong Province are classified and four categories of urban colour system are distinguished: Coastal freshness, Ecologically wilderness type, Cultural warmth type and Comprehensive type. Each type also presents colour structure and visual characteristics that are closely related to the natural geography and cultural background of the local urban area. The results of the study indicate that regional environment and urban characteristics are inextricably linked in the urban colour system. Scientific novelty. Based on regional aspects, the study proposes for the first time a method for classifying the visual image of urban colours based on geographical environment, history and humanities, and urban functions. Compared with previous studies focusing on the colour of individual urban regions, considerable attention is paid to the visual correlation between the colour structure and the overall unity of urban space, which highlights the aesthetic value and systematic role of the urban colour system. Practical relevance. The research results provide a clear classification basis and methodological support for the design of urban visual image and related urban colour research. The proposed classification of urban colour systems can provide designers with effective design guidelines for their visual practice in different cities. In addition, the research contributes to the formation of a more holistic visual space of the city, the enhancement of public identity, and the enhancement of regional content communication to create a more accurate and vivid image of the city.

We propose a new approach to the visualization design and communication process, literate visualization, based upon and extending, Donald Knuth's idea of literate programming. It integrates the process of writing data visualization code with description of the design choices that led to the implementation (design exposition). We develop a model of design exposition characterised by four visualization designer architypes: the evaluator, the autonomist, the didacticist and the rationalist. The model is used to justify the key characteristics of literate visualization: 'notebook' documents that integrate live coding input, rendered output and textual narrative; low cost of authoring textual narrative; guidelines to encourage structured visualization design and its documentation. We propose narrative schemas for structuring and validating a wide range of visualization design approaches and models, and branching narratives for capturing alternative designs and design views. We describe a new open source literate visualization environment, litvis, based on a declarative interface to Vega and Vega-Lite through the functional programming language Elm combined with markdown for formatted narrative. We informally assess the approach, its implementation and potential by considering three examples spanning a range of design abstractions: new visualization idioms; validation though visualization algebra; and feminist data visualization. We argue that the rich documentation of the design process provided by literate visualization offers the potential to improve the validity of visualization design and so benefit both academic visualization and visualization practice.

Bayesian classification and inference of occupant visual preferences in daylit perimeter private offices