Real‐time path planning in unknown dynamic environments is a significant challenge for mobile robots. Many researchers have attempted to solve this problem by introducing deep reinforcement learning, which trains agents through interaction with their environments. A method called BOAE‐DDPG, combines the novel bidirectional obstacle avoidance enhancement (BOAE) mechanism deterministic policy gradient (DDPG) algorithm, proposed enhance learning ability of avoidance. Inspired analysis reaction...

Bipedal walking is a challenging task for humanoid robots. In this study, we develop lightweight reinforcement learning method real-time gait planning of the biped robot. We regard bipedal as process in which robot constantly interacts with environment, judges quality control action through state, and then adjusts strategy. A mean-asynchronous advantage actor-critic (M-A3C) algorithm proposed to obtain continuous state space space, directly final without introducing reference gait. use...

According to the World Health Organization and CDC, social distancing is currently one of most effective ways slow transmission COVID-19. However, existing epidemic models do not consider impact on COVID-19 pandemic. In this article, we propose a new method deterministic modeling effects pandemic in low setting. Our model dynamic expressed by single predictive variable that satisfies an integro-differential equation. Once calculated, process agents from normal state, infection state...

In this paper, we propose a digital video watermarking algorithm for H.264. The proposed exploits the specific characteristics of compression standard watermark to be embedded into original is randomly localized. It on foundation that our bases its secureness. H.264 in compressed domain, can detected without presence sequence. blindly extracted by help selected modified coefficient at decoder.

Queuing is a frequent daily activity. However, long waiting lines equate to frustration and potential safety hazards. We present novel, personality-based model of emotional contagion control for simulating crowd queuing. Our integrates the influence individual personalities interpersonal relationships. Through interaction between agents external environment parameters, based on well-known theories in psychology used complete agents’ behavior planning path function. combine epidemiological...

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.

Corona Virus Disease 2019 (COVID-19), due to its extremely high infectivity, has been spreading rapidly around the world and bringing huge influence socioeconomic development as well people's daily life. Taking for example virus transmission that may occur after college students return school, we analyze quantitative of key factors on spread, including crowd density self-protection. One Campus Infection Control Simulation model (CVICS) novel coronavirus is proposed in this paper, fully...

With the continued proliferation of mobile Internet and geo-locating technologies, carpooling as a green transport mode is widely accepted becoming tremendously popular worldwide. In this paper, we focus on service called <i>ride hitching</i> , which typically implemented using publish/subscribe approach. ride hitching service, drivers subscribe orders published by riders continuously receive matching until one picked. The current systems (e.g., Didi Hitch) adopt threshold-based approach to...

Driving Scenario recognition is one fundamental technology of automated driving systems or advanced driver assistance systems. A common practice scenario recog-nition to conduct classification tasks with the data collected by in-vehicle acquisition system simulator. In most existing works, visual were used since relevant information scenarios usually inferable from their appearance. However, non-visual information, e.g. physiological state driver, also provide complementary for task...

Developing and rehearsing crowd evacuation plans in gathering situations can improve efficiency reduce safety accidents. However, pedestrians create resource conflicts with other competing for routes during evacuation. Inspired by cellular automata game theory, this paper proposes a model that integrates theory to solve the among process. In construction, we construct basic using automaton, formulate rule pedestrians' conflict according prisoner's dilemma, integrate update strategy into...

Isolation policies are an effective measure in epidemiological models for the prediction and prevention of infectious diseases. In this paper, we use a multi-agent modeling approach to construct disease model that considers influence isolation policies. The analyzes impact on various stages epidemic from two perspectives: external environment agents behavior. It utilizes multiple variables simulate extent which spread pandemic. Empirical evidence indicates progression is primarily driven by...

The increasing availability of high-resolution satellite imagery has created immense opportunities for various applications. However, processing and analyzing such vast amounts data in a timely accurate manner poses significant challenges. paper presents new image architecture combining edge cloud computing to better identify man-made structures against natural landscapes. By employing lightweight models at the edge, system initially identifies potential from imagery. These identified images...

Recent research on real-time object detectors (e.g., YOLO series) has demonstrated the effectiveness of attention mechanisms for elevating model performance. Nevertheless, existing methods neglect to unifiedly deploy hierarchical construct a more discriminative head which is enriched with useful intermediate features. To tackle this gap, work aims leverage multiple hierarchically enhance triple awareness detection and complementarily learn coordinated representations, resulting in new series...

Assessing muscle activation and monitoring stroke recovery progress are vital aspects of evaluating motor impairment. Surface electromyography, a common tool for measuring activity, has practical limitations clinical implementation fails to capture deep activities, leading challenges in accurately identifying patterns patients. To address these limitations, we introduce an All Muscle Activity Test Evaluation (AMATE) system, combining wearable sensor technology with musculoskeletal model....