32,970 Results Found

Optimizing the location of physical activity spaces (PAS) to ensure health, equity and efficiency has long been an important issue in urban planning. Given the health benefits of urban green spaces (UGS), taking Gongshu District in Hangzhou as a case...

Physical neighbourhood environments (PNE) can affect the active ageing and physical wellbeing of older residents. This paper examined the PNE objective (PNEO): land use mix entropy, population density, traffic intersection density and distance to fac...

Reusing the tactile knowledge of some previously-explored objects (prior objects) helps us to easily recognize the tactual properties of new objects. In this paper, we enable a robotic arm equipped with multi-modal artificial skin, like humans, to ac...

Object detection is an important process in surveillance system to locate objects and it is considered as major application in computer vision. The Convolution Neural Network (CNN) based models have been developed by many researchers for object detec...

Behind the rapid development of deep learning methods, massive data annotations are indispensable yet quite expensive. Many active learning (AL) and semi-supervised learning (SSL) methods have been proposed to address this problem in image classifica...

In the last few years, there has been a steadily growing interest in autonomous vehicles and robotic systems. While many of these agents are expected to have limited resources, these systems should be able to dynamically interact with other objects i...

Objectives: To determine the feasibility of using the activPAL3^TM activity monitor, and, to describe the activity patterns of residential aged care residents. Design: Cross-sectional. Setting: Randomly selected aged care facilities within 100 km of t...

Although active learning can reduce the effort required to annotate object detection data, many current methods rely on a single selection criterion or combine criteria without accounting for annotation costs or their interactions. This paper present...

This paper aims to study and demonstrate the possibilities of using reinforcement learning for the synthesis of multi-objective controllers for radial actively lubricated hybrid fluid film bearings (ALHBs), which are considered to be complex multi-ph...

Active mapping is an important technique for mobile robots to autonomously explore and recognize indoor environments. View planning, as the core of active mapping, determines the quality of the map and the efficiency of exploration. However, most cur...

Adding to the number of sources of sensory information can be efficacious in enhancing the object detection capability of robots. In the realm of vision-based object detection, in addition to improving the general detection performance, observing obj...

Biologists have discovered a kind of weakly electric fish that identifies its prey by using active electrolocation in virtual darkness. In this study, we built an underwater active electrolocation system platform designed to investigate the biologica...

The active contour model is a comprehensive research technique used for salient object detection. Most active contour models of saliency detection are developed in the context of natural scenes, and their role with synthetic and medical images is not...

In this paper we present a novel unsupervised approach to detecting and segmenting objects as well as their constituent symmetric parts in an image. Traditional unsupervised image segmentation is limited by two obvious deficiencies: the object detect...

A multitude of membrane active peptides exists that divides into subclasses, such as cell penetrating peptides (CPPs) capable to enter eukaryotic cells or antimicrobial peptides (AMPs) able to interact with prokaryotic cell envelops. Peptide membrane...

In this paper, we propose an active robotic 3D reconstruction methodology for achieving full object 3D reconstruction. Existing robotic 3D reconstruction approaches often struggle to cover the entire view space of the object or reconstruct occluded r...

Background: In light of the main challenges recognized as being linked to the operationalization of the active aging concept at the policy level, the present study aimed to understand whether and to what extent Italian regional governments plan to de...

Background/Objectives: Motor difficulties due to developmental coordination disorder seem to exist in adolescence, affecting participation in physical activity. The purposes of the present study were, firstly, to identify motor difficulties and, seco...

The accuracy of data captured by sensors highly impacts the performance of a computer vision system. To derive highly accurate data, the computer vision system must be capable of identifying critical objects and activities in the field of sensors and...

In multi-objective optimization, standard evolutionary algorithms, such as NSGA-II, are computationally expensive, particularly when handling complex constraints. Constraint evaluations, often the bottleneck, require substantial resources. Pre-traine...

Background/Objectives: The mechanisms linking eating attitudes to well-being and physical activity objectives have increasingly attracted the attention of researchers in recent years. This research is particularly significant in the context of the CO...

Generating synthetic data is a promising solution to the challenge of limited training data for industrial deep learning applications. However, training on synthetic data and testing on real-world data creates a sim-to-real domain gap. Research has s...

Object detection systems deployed in industrial environments are often constrained by limited annotation budgets, severe class imbalance, and heterogeneous visual conditions. Active learning (AL) aims to reduce labeling costs by selecting informative...

Object detection (OD) coupled with active learning (AL) has emerged as a powerful synergy in the field of computer vision, harnessing the capabilities of machine learning (ML) to automatically identify and perform image-based objects localisation whi...

The increasing prevalence of upper and lower extremity (ULE) functional deficiencies presents a significant challenge, as it restricts individuals’ ability to perform daily tasks independently. Robotic devices are emerging as assistive devices...

Many researchers have confirmed a correlation between the built environment and physical activity. However, most studies are based on the objective characteristics of the built environment, and seldom involve the residents’ subjective perceptio...

The increasing number of individuals with disabilities—over 61 million adults in the United States alone—underscores the urgent need for technologies that enhance autonomy and independence. Among these individuals, millions rely on wheelc...

With the development of More Electrical Aircraft (MEA), the electrification of secondary power systems in aircraft is becoming more and more common. As the key power conversion device, the dual active bridge (DAB) converter is the power interface for...

Active Distribution Networks (ADNs) rely on the precise coordination of flexible resources to mitigate the stochasticity of high-penetration renewables. However, the hierarchical and partitioned nature of modern ADNs transforms the day-ahead scheduli...

Recognition and classification for construction activities help to monitor and manage construction workers. Deep learning and computer vision technologies have addressed many limitations of traditional manual methods in complex construction environme...

In remote sensing, active learning (AL) is considered to be an effective solution to the problem of producing sufficient classification accuracy with a limited number of training samples. Though this field has been extensively studied, most papers ex...

This study aimed to compare subjective and objective measures of physical activity (PA) in healthcare professionals and assess their adherence to recommended guidelines. A convenience sample of 153 female healthcare professionals (51 nurses, 50 medic...

The built environment plays a critical role in promoting residents’ physical activity, yet the interactive mechanisms between objective environmental factors and subjective perceptions remain insufficiently understood. This study examines three...

Active object recognition (AOR) aims at collecting additional information to improve recognition performance by purposefully adjusting the viewpoint of an agent. How to determine the next best viewpoint of the agent, i.e., viewpoint planning (VP), is...

In the context of the green energy transition, the rapid expansion of flexible resources such as distributed renewable energy, electric vehicles (EVs), and energy storage has significantly impacted the operation of distribution networks. This paper p...

Activation time and discharge time are important criteria for the performance of thermal batteries. In this work a heat transfer analysis is carried out on the working process of thermal batteries. The effects of the thicknesses of heat pellets which...

In recent years, the continuous advancement of deep learning has led to significant progress in object-detection technology for remote-sensing images. However, most current detection methods passively perform detection on the input image without cons...

Due to the serious problems with energy efficiency, carbon emissions, and thermal comfort of rural residences in northern China, an optimization of active and passive heating technologies for rural residences is necessary. In this paper, an optimizat...

The large-scale integration of electric vehicles (EVs) can increase load fluctuations, operating costs, and security risks in active distribution networks (ADNs). To address these challenges, this study proposes a multi-objective optimal scheduling s...

Background and Objectives: Wearable technologies increasingly monitor internal training load in high-performance sport, but their alignment with coach-prescribed physiological objectives remains unclear. This study examined within-athlete association...

Multimodal object detection is currently a research hotspot in computer vision. However, the fusion of visible and infrared modalities inevitably increases computational complexity, making most high-performance detection models difficult to deploy on...

Recently, engineering companies have started to digitise documents in image form to analyse their meaning and extract important content. However, many engineering and contract documents contain different types of components such as texts, tables, and...

Depression is a major contributor to the overall global burden of disease, with high prevalence and relapse rate. Several factors have been considered in order to reduce the depression burden. Among them, physical activity (PA) showed a potential pro...

To efficiently utilize limited resources, this paper proposes a semi-supervised object detection (SSOD) approach based on novel adaptive weighted active learning (AWAL) and orthogonal data augmentation (ODA). An uncertainty sampling framework is appl...

CO₂-enhanced oil recovery (CO₂-EOR) with water-alternating-gas (WAG) injection offers the dual benefit of boosted oil production and CO₂ storage, addressing both energy needs and climate goals. However, designing CO₂-WAG schemes is challenging; maxim...

In object detection, annotation cost and computational efficiency are important factors in iterative model improvement under standard benchmark settings. Active learning (AL) addresses this challenge by selecting informative samples for labeling; how...

Computational fluid dynamics (CFD)-driven optimization of engineering systems is often constrained by high computational cost, particularly when surrogate models must be constructed from limited simulation samples. Although surrogate-assisted multi-o...

In low-shot weakly supervised object detection (LS-WSOD), a small number of strong (instance-level) labels are introduced to a weakly (image-level) annotated dataset, thus balancing annotation costs and model performance. To address issues in LS-WSOD...

Active learning (AL) promises accelerated multi-objective materials discovery, yet acquisition-function choice is often made without matching dataset, budget, and target metric. We retrospectively compared EI-random, EI-cent, EI-maxmin, and EI-prod o...

To address the optimization challenges arising from the large-scale integration of distributed energy resources into active distribution networks, this paper proposes a multi-objective optimization partitioning method that balances system security/st...