Movement In Environment Research Articles

Why frequent traffic accidents at highway tunnel exit? – An experimental analysis of the slack effect

This study analyzes the causes of frequent traffic accidents at the exit areas of highway tunnels. Vehicle experiments were conducted to collect data on the light environment, vehicle speed, and driver eye movement. The distribution patterns of the illumination, vehicle speed, and gaze location occupancy were analyzed, and highway tunnels of different lengths were compared. The tunnel exit area is divided into the transition, exit, and departure zones. It was observed that there was an obvious white-hole effect at the exit zone, with drastic changes in the light environment. The presence of abnormal acceleration behavior in the transition zone and decreased attention in the departure zone demonstrate the existence of psychological and physiological slack in drivers. Additionally, the tunnel length positively correlates to the slack effect, which is stronger in extra-long tunnels than in the short and medium tunnels. Multiple control scenarios were established and driving simulation experiments were conducted to further analyze the impact of the slack effect on the traffic safety. The experimental results demonstrated that the slack effect of the extra-long tunnels exhibited an evident lag which was still present after leaving the tunnel exit. The average vehicle speed and trajectory offset were larger and more discrete in the post-tunnel zone than on an ordinary open road. The speed of the curve in the post-tunnel zone is 5.1 % higher than that of the curve in the ordinary road, and the maximum trajectory offset is 54.3 % higher. Thus, this study reveals the slack effect at tunnel exits and explains the abnormal phenomenon of relatively good traffic environments but high traffic accident rates in the transition and departure zones of tunnel exits. These results present considerable practical significance for the safe operation of highway tunnels, particularly extra-long tunnels.

A High-Performance, Secure Custom Electronics Circuit for Biopotential Measurement and Processing

Purpose: In this paper, we propose a secure wearable and portable device aiming to (i) monitor physical activity in medical and clinical rehabilitation, (ii) evaluate the subject's movements in sports environments, and (iii) monitor wellness indicators. Materials and Methods: The innovative low-power custom circuit can acquire, pre-process, digitalize, and transmit EMG signals to a Raspberry PI4 device via a low-energy Bluetooth module. The Raspberry PI4 is a hub that sends data to a cloud-based system for remote monitoring and processing. The best cybersecurity practices have been implemented: firewall, anti-DDoS and SELinux. Results: We have assessed the system's vulnerability before and after the system's hardening. SELinux makes the system safer and prevents unauthorized access to patients' data health by tampering with the devices. Conclusion: Adopting IoT systems in telemedicine requires greater attention to cybersecurity. It is necessary to implement security mechanisms to guarantee the privacy of patient's health data.

How Learners’ Visuospatial Ability and Different Ways of Changing the Perspective Influence Learning About Movements in Desktop and Immersive Virtual Reality Environments

Virtual reality (VR) applications are developing rapidly, becoming more and more affordable, and offer various advantages for learning contexts. Dynamic visualizations are generally suitable for depicting continuous processes (e.g., different movement patterns), and particularly dynamic virtual 3D-objects can provide different perspectives on the movements. The present study investigated through a low immersive (desktop “VR”, Study 1) and a high immersive virtual environment (immersive VR; Study 2) the effectiveness of different interaction formats to view 3D-objects from different perspectives. Participants controlled either the orientation of the 3D-objects (Study 1, mouse interaction; Study 2, hand interaction via VR controllers) or their viewpoint in relation to the 3D-objects (Study 1, camera position; Study 2, position of participants’ own body). Additionally, the moderating influence of learners’ visuospatial ability was addressed. Dependent variables were pictorial recognition (easy, medium, difficult), factual knowledge, presence, and motion sickness. Results showed that higher-visuospatial-ability learners outperformed lower-visuospatial-ability learners. In Study 1, higher-visuospatial-ability learners showed higher recognition performance (difficult items) by controlling the camera position, whereas lower-visuospatial-ability learners suffered from this interaction format. In Study 2, higher-visuospatial-ability learners achieved better recognition performance (easy items) by controlling the 3D-models, whereas lower-visuospatial-ability learners tended to profit from moving around the 3D-objects (medium items). The immersive VR yielded more presence and higher motion sickness. This study clearly shows that different interaction formats to view 3D-objects from multiple perspectives in Desktop-VR are not transferable on a one-to-one basis into immersive VR. The results and implications for the design of virtual learning environments are discussed.

Design and analysis of grid mooring system for gravity net cage with a comprehensive optimization method

The design of gravity net cage mooring systems is a complex endeavor, which is critical for preventing major accidents caused by mooring system failures. A comprehensive optimization method is proposed to enhance the reliability and performance of the net cage mooring system by integrating static and dynamic phases. The proposed method initiates static simulations based on the catenary theory to refine the initial range of parameters. This preparatory step ensures the subsequent dynamic analysis is carried out based on feasible initial conditions with the lumped mass method. The dynamic simulation captures the complex interactions and behavior of the mooring systems under various environmental conditions. The multi-objective optimization provides feasible solutions with simultaneous consideration of both processes. Three different scenarios are optimized with the forces and motions compared after the time domain analysis, resulting in a satisfactory set of solutions. The results show that variations in the angle of the mooring line of the net cage primarily impact the net cage's movement and volume in different environments.

35‐3: Modeling Eye Movement and Reflection in Virtual Environments for Eye Tracking

Eye movement tracking plays a pivotal role in use interaction within Virtual Reality (VR) environments. Our research focuses on an advanced eye movement simulation using virtual environment for eye tracking training and eye tracking precision evaluating platform. We developed a real‐eye model, enhanced light refraction and corneal reflections under infrared LED light with eye rotation. Our study also customized screen,light source and cameras placement to capture eye images more faithfully. We also presents a noval testing methology and equipments of spatial accuracy testing of the eye‐tracking systems. The proposed proprietary eye‐tracking test system designed to recreate scenarios of human gaze and provide true values for eye gaze directions. Overall, the integration of Pupil Center Corneal Reflection (PCCR) based dataset generation and testing platform mark a significant advancement, enabling huge database, precise groudtruth training and accurate results testing.

Понятие «средство индивидуальной мобильности»

For a long time, one of the controversial issues in the legal literature is the generic name of the entire set of technical devices equipped with an electric motor and providing an increase in the speed of movement in an urban environment. The authors of publications devoted to the topic under consideration use a wide variety of phrases. In the article, based on the analysis of judicial practice and subordinate regulations, the author of the article develops his own version of this concept. An adjustment of the current legislation is proposed.

Investigation of infectious droplet dispersion in a hospital examination room cooled by split-type air conditioner

The novel coronavirus (SARS-CoV-2) outbreak has spread worldwide, and the World Health Organization (WHO) declared a global pandemic in March 2020. The transmission mechanism of SARS-CoV-2 in indoor environments has begun to be investigated in all aspects. In this regard, many numerical studies on social distancing and the protection of surgical masks against infection risk have neglected the evaporation of the particles. Meanwhile, a 1.83 m (6 feet) social distancing rule has been recommended to reduce the infection risk. However, it should be noted that most of the studies were conducted in static air conditions. Air movement in indoor environments is chaotic, and it is not easy to track all droplets in a ventilated room experimentally. Computational Fluid Dynamics (CFD) enables the tracking of all particles in a ventilated environment. This study numerically investigated the airborne transmission of infectious droplets in a hospital examination room cooled by a split-type air conditioner with the CFD method. Different inlet velocities (1, 2, 3 m/s) were considered and investigated separately. Besides, the hospital examination room is a model of one of the Bursa Uludag University Hospital examination rooms. The patient, doctor, and some furniture are modeled in the room. Particle diameters considered ranged from 2 to 2000 μm. The evaporation of the droplets is not neglected, and the predictions of particle tracks are shown. As a result, locations with a high infection risk were identified, and the findings that could guide the design/redesign of the hospital examination rooms were evaluated.

Sosialisasi Pemanfaatan Tanaman sebagai Obat dan Kosmetika

The utilization of plants as medicine and cosmetics is essentially plants with medicinal properties that are grown on yard land managed by families. These plants are planted in order to fulfill the family's need for traditional medicines that can be made and grown at home. The benefits are to fulfill the need to overcome health problems traditionally (medicine). The crops are planted in order to fulfill the family's need for traditional medicines that can be made and grown at home. The benefits are to fulfill the need to overcome health problems traditionally (medicine). Therefore, it is very important to carry out a planting movement in the surrounding environment not only at home, for example in the school. In this community service research, one of them aims to carry out a planting and utilization movement in the women's dormitory environment. This can also increase the interaction of students with nature and its utilization can provide a preventive benefit in overcoming health problems in the school environment. The results of the assistance of community service activities regarding the partnership program on planting and utilization assistance. Medicinal and cosmetic plants at MAN 3 Mataram, showed significant results in several things such as students being able to plant and utilize medicinal and cosmetic plants in the environment.

Experiences of children with congenital Zika syndrome while using motorized mobility: a qualitative study using the photovoice method

Aim The congenital Zika Syndrome (CZS) often leads to severe motor impairment in affected children, making independent walking unlikely. Early introduction of motorized mobility through ride-on cars has been recommended for young children with severe motor impairment, enabling independent movement in various environments. This study aims to explore mothers’ perceptions of their children’s experiences while using ride-on cars at home and in the community, focusing on children with CZS. Methods This is a qualitative and descriptive study design using the Photovoice method. Four mothers of children with CZS, participating in the ‘Go Zika Go’ intervention project, were included. The research involved the following six steps: 1) Presentation of guide questions and Photovoice training; 2) Participants capturing photos; 3) Individual interviews to contextualize the photos; 4) Transcription and data analysis using thematic analysis principles; 5) Validation of analyses by mothers; and 6) Exhibition of photos to the community. Results The mothers and researchers selected the 21 most relevant photographs, which revealed five main themes related to the use of motorized ride-on cars: 1) Experiences of participation; 2) Independence in mobility; 3) Characteristics of mobility devices; 4) Family support; and 5) Accessibility of the environment. Conclusion The narratives provided by participants, along with photographs depicting the daily lives of children with CZS, shed light on aspects of functionality, autonomy, and participation. The use of these devices contributes to overall equity, breaking down social and cultural barriers and enabling children with disabilities to be seen as equals by their peers.

Introducing a New Method for Studying the Effects of Movement Synchrony in Virtual Reality.

This study introduces a new method to create virtual reality (VR) environments for studying synchrony in human body movements and their prosocial effects. Previous studies have shown the positive effects of synchrony, but more controlled and ecologically valid paradigms are needed to explore these effects deeper and translate them to the therapeutic domain. A total of 82 healthy subjects participated in this study. They performed simple periodic hand movements in a virtual environment with a virtual character (VC) mimicking them. We used inverse kinematics (IKs) to create character movements. The VCs mimic the participants after a short delay in the synchronous group and after a great delay in the nonsynchronous group. The subjective feeling of synchrony and social closeness was measured using a set of rating questionnaires. The participants in the synchronous group reported more synchrony than the nonsynchronous group. The degree of social closeness between the two groups was not significantly different; however, there was a significant positive correlation between the reported degree of synchrony and social closeness within each group. Using a simple VR environment in which body movements are simulated by IKs can engender the feeling of synchrony and exert its prosocial effects.

Does recognizability of connected and automated vehicles (CAVs) platoons affect drivers’ behavior and safety?

Platoons of connected and automated Vehicles (CAVs) comprising both passenger cars and trucks are expected to appear on highways in the coming years. Though prior studies explored driver behaviors in the presence of CAV platoons, it remains unknown whether it is necessary for a traditional vehicle’s driver to recognize CAV platoons in a mixed traffic environment for safe maneuvering. This study aims to test the hypothesis that drivers behave differently when interacting with recognizable CAV platoons compared to interacting with non-recognizable CAV platoons. A driving simulator experiment was conducted featuring four merging and diverging scenarios. Participants were informed beforehand that blue-colored vehicles driving with short gaps would be CAV platoons. However, they also encountered CAV platoons consisting of several vehicles with different colors (not blue). The blue-colored platoon was considered as recognizable CAV platoons and the latter as non-recognizable CAV platoons. Performance indicators including speed, maximum acceleration and deceleration, standard deviation (SD) of speed and acceleration, and time-to-collision (TTC) were considered to examine drivers’ behavior. The generalized estimating equation (GEE) approach was applied to evaluate the effect of recognizability and demographic characteristics on driver performance. The GEE results revealed significant improvement in drivers’ behavior in the presence of recognizable CAV platoons. The merging SD of speed and acceleration were around 32% and 29% lower, respectively in the presence of recognizable CAV platoons. The merging TTC was around 20% higher in the presence of recognizable CAV platoons. Although no significant main effect of recognizability was found for diverging maneuvers, a noteworthy result was that male drivers had around 37% higher diverging TTC than female drivers in the presence of recognizable CAV platoons. The findings also suggested significant effects of gender, age, driving experience, and education on driver performance while merging, as well as effect of gender and prior crash involvement on driver performance while diverging. These findings provide valuable insights to transportation planning authorities in determining the potential need for making CAV platoons recognizable and developing associated guidelines for safer traffic movements in mixed traffic environments.

Macroeconomic Environment and Stock Price Movement in Nigeria: An Evaluation of Fama’s Model of Efficient Market

The study examined the link between macroeconomic environmental dynamics and stock price movements in Nigeria using Fama’s model of efficient market approach. The macroeconomic climate posed issues for Nigerian stock markets. The buying power of local currency occasionally impacted unfavourable changes in the majority of macroeconomic variables. In this study, an ex post facto research design was used. The study looked at certain macroeconomic variables and the evolution of Nigerian stock prices between 1985 and 2021. To test the hypothesis, quantile regression estimates of the Fama-French three-factor coefficient were derived. The findings showed that the interest rate and stock price movement have a negative and negligible association. Additionally, a strong and positive correlation was observed between the exchange rate and changes in stock prices. It was recommended that in order to promote stock market activity and, by extension, enhance stock prices in Nigeria, a suitable monetary policy and a sufficient amount of money supply must be implemented. Also, well-diversified portfolios that mirror the entire market portfolio should be recommended to investors to protect themselves against stock price volatility. This would serve as a guide to protect them against shocks resulting from the macroeconomic environment.

Obstacle shape determination by mobile robot sensor system using GP2Y0A (Sharp) type IR distance sensors

PURPOSE. When organizing a mobile robot (MR) movement in a non-deterministic environment, the SLAM problem arises, which includes the detection of an obstacle presence by the MR sensor system, the distance to the obstacle and its shape. To solve this problem, an infrared (IR) analog distance sensor is often used, the information flow from which is relatively small and can be processed in real time using low-performance microcontrollers. However, such a sensor can only detect an obstacle and determine а distance to a certain point on its surface. The goal is to develop a method for determining both а distance to an obstacle and its shape. When setting up experiments on the use of an analog sensor of the GP2Y0A (SHARP) type, a problem was revealed associated with the occurrence of not only fluctuation noise in а data communication channel, but also artifacts – anomalous signal values appear with random periodicity. It is necessary to determine the source of such interference, propose a method for estimating its parameters and a way to minimize its influence. METHODS. To determine the shape of an obstacle, a differential method is proposed based on the use of several readings of a scanning IR distance sensor. As an indicator of the “noisiness” of the channel, it is proposed to use the number of sensor signal values that exceed the average signal value by 1σ, 2σ, 3σ, 4σ and 5σ. The use of standard methods for filtering abnormal values of a sensor signal leads to significant delays in a response of the MR control system. This is unacceptable, because at the executive level of a control system it is required to provide a "hard" real-time mode. RESULTS. The article presents the results of experiments showing the conditions for applying the differential method for determining a shape of an obstacle, the source of anomalous signal values is identified and a method for minimizing them is proposed. A method for increasing the practical use range of a nonlinear IR sensor conversion function is also proposed. CONCLUSION. The number and magnitude of abnormal values depend on a communication channel length. When using analog sensors, it is necessary to convert an output signal into digital form using analog-to-digital converters (ADCs) in an integrated design, structurally bringing the ADC as close as possible to the signal source.

Development of a Hand-Fan-Shaped Arm and a Model Predictive Controller for Leg Crossing, Walking, and One-Legged Balancing of a Wheeled-Bipedal Jumping Robot

Bipedal walking robots are advancing research by performing challenging human-like movements in complex environments. Particularly, wheeled-bipedal robots are used in many indoor environments by overcoming the speed and maneuverability limitations of bipedal walking robots without wheels. However, when both wheels lose contact with the ground, maintaining lateral balance becomes challenging, and there is an increased risk of toppling over. Furthermore, utilizing robotic arms similar to human arms, in addition to wheel-based balance, could enable more precise and stable control. In this paper, we develop a wheeled-bipedal robot that is able to jump and drive while also being able to cross its legs and balance on one leg (the OLEBOT). The OLEBOT is designed with a hand-fan-shaped end-effector capable of generating compensatory torque. By tilting the hand-fan-shaped end-effector in the opposite direction, OLEBOT achieves pitch control and single-leg balance. In jumping scenario, it imitates the arm movements of a person performing stationary high jumps, while utilizing a cam-based leg joint system to boost jump height. In addition, this paper develops a control architecture based on model predictive control (MPC) to ensure stable posture in driving, jumping, and one-legged balancing scenarios for OLEBOT. Finally, the experimental results demonstrate that OLEBOT is capable of maintaining a stable posture using a wheeled-bipedal system and achieving balance in a one-legged stance.

Cerebral palsy-affected individuals' brain-computer interface for wheelchair movement in an indoor environment using mental tasks

The technique of measuring brain signals or activities by placing electrodes on the scalp of human beings is called Electroencephalogram (EEG). Brain-computer interface (BCI) is a technique to capture brain signals and translate them into control signals to run external devices. With the combination of these two techniques, we can create BCI using brain signals. Methods: In this study, the author considered conducting two types of methods offline and online both in the indoor environment using the Fast Fourier Transform (FFT) technique with Feed Forward Neural Network trained with Bat optimization algorithm (FFNNBOA). The study was carried out on two different age groups between 30 to 45 years and 46 to 60 years with four different tasks. Based on the execution of the four different tasks concerning two different age groups, the accuracy obtained during classification is 94.35 % and 93.76 % for offline and online modes. Results: The results it is observed that the classification accuracy for the age group belonging 46 to 60 is comparably higher than that of the conventional classification model. The offline and online tests were conducted for both age groups persons and obtained the recognizing accuracy of 95 %, 93.25 %, and 93.75 %, 91.75 % for the two modes. This study confirms that the performances of the subjects belonging to age groups 30 to 45 are higher than the age groups belonging to 46 to 60 in terms of classification, offline, and online mode. Finally, this study also identified that subject S4 from the 30 to 45 age group showed 100 % accuracy in both offline and online signal acquisition.

Indoor view graph: A model to capture route and configurational information

This paper presents a graph model that simultaneously stores route and configurational information about indoor spaces. Existing indoor information models either capture route information to compute shortest paths and to generate route descriptions (i.e., answering how-to-get-to questions), or they store configurational information about objects and places and their spatial relationships to enable spatial querying and inference (i.e., answering where-questions). Consequently, multiple representations of an indoor environment must be stored in information systems to address the various information needs of their users. In this paper, we propose a graph that can capture both configurational and route information in a unified manner. The graph is the dual representation of connected lines of sight, or views. Views can represent continuous movement in an indoor environment, and at the same time, the visible configurational information of each view can be explicitly captured. In this paper, we discuss the conceptual design of the model and an automatic approach to derive the view graph from floorplans. Finally, we demonstrate the capabilities of our model in performing different tasks such as calculating shortest paths, generating route descriptions, and deriving place graphs.

Exposure to Sublethal Concentrations of Lead (Pb) Affects Ecologically Relevant Behaviors in House Sparrows (Passer domesticus)

Global contamination of environments with lead (Pb) poses threats to many ecosystems and populations. While exposure to Pb is toxic at high concentrations, recent literature has shown that lower concentrations can also cause sublethal, deleterious effects. However, there remains relatively little causal investigation of how exposure to lower concentrations of environmental Pb affects ecologically important behaviors. Behaviors often represent first-line responses of an organism and its internal physiological, molecular, and genetic responses to a changing environment. Hence, better understanding how behaviors are influenced by pollutants such as Pb generates crucial information on how species are coping with the effects of pollution more broadly. To better understand the effects of sublethal Pb on behavior, we chronically exposed adult wild-caught, captive house sparrows (Passer domesticus) to Pb-exposed drinking water and quantified a suite of behavioral outcomes: takeoff flight performance, activity in a novel environment, and in-hand struggling and breathing rate while being handled by an experimenter. Compared to controls (un-exposed drinking water), sparrows exposed to environmentally relevant concentrations of Pb exhibited decreases in takeoff flight performance and reduced movements in a novel environment following 9–10 weeks of exposure. We interpret this suite of results to be consistent with Pb influencing fundamental neuro-muscular abilities, making it more difficult for exposed birds to mount faster movements and activities. It is likely that suppression of takeoff flight and reduced movements would increase the predation risk of similar birds in the wild; hence, we also conclude that the effects we observed could influence fitness outcomes for individuals and populations altering ecological interactions within more naturalistic settings.

P‐4.27: Modeling Eye Movement and Reflection in Virtual Environments for Eye Tracking

P‐4.27: Modeling Eye Movement and Reflection in Virtual Environments for Eye Tracking

A Unified Environmental Network for Pedestrian Trajectory Prediction

Accurately predicting pedestrian movements in complex environments is challenging due to social interactions, scene constraints, and pedestrians' multimodal behaviors. Sequential models like long short-term memory fail to effectively integrate scene features to make predicted trajectories comply with scene constraints due to disparate feature modalities of scene and trajectory. Though existing convolution neural network (CNN) models can extract scene features, they are ineffective in mapping these features into scene constraints for pedestrians and struggle to model pedestrian interactions due to the loss of target pedestrian information. To address these issues, we propose a unified environmental network based on CNN for pedestrian trajectory prediction. We introduce a polar-based method to reflect the distance and direction relationship between any position in the environment and the target pedestrian. This enables us to simultaneously model scene constraints and pedestrian social interactions in the form of feature maps. Additionally, we capture essential local features in the feature map, characterizing potential multimodal movements of pedestrians at each time step to prevent redundant predicted trajectories. We verify the performance of our proposed model on four trajectory prediction datasets, encompassing both short-term and long-term predictions. The experimental results demonstrate the superiority of our approach over existing methods.

Intelligent driving model considering vehicular dynamics and heterogeneous road environments

ABSTRACT Understanding vehicles’ movement in complex environments becomes cruical with the fast development of connected automated vehicles (CAVs). Current microscopic traffic flow models lack consideration for vehicle dynamics and complex road topologies. This study develops a model addressing these issues, retrieving vehicles’ maneuvers and predicting vehicles’ two-dimensional motion. It introduces a two-dimensional intelligent driving model utilizing steering angle and acceleration as control inputs. Intricate road topologies are represented with potential fields and a virtual boundary to capture the heterogeneous environment’s complexity. A driving potential field model is also developed for off-ramp areas. Model parameters are optimized with the dynamic time warping (DTW) and particle swarm optimization (PSO) algorithm. Furthermore, model predictive control (MPC) enhances the realism of the model’s output. Field validation results demonstrate that the proposed models can accurately describe vehicles’ two-dimensional movement in intricate environments, offering valuable support for research on heterogeneous traffic flows for CAVs and CVs.