Measurement of reaction time in clinical settings is generally employed to assess cognitive abilities by having a subject perform standard simple tests. In this study, a new method of measuring response time (RT) was developed using a system composed...
With advancements in drone driving technology, drones can now collaborate with trucks to execute tasks. However, existing drone–truck collaborative systems are limited to single-task objectives and lack efficiency in large-scale multi-task scen...
The increasing prevalence of age-related cognitive decline, alongside the aging global population, underscores the urgent need for innovative and effective preventative strategies. While the advantages of combining physical and cognitive exercises ha...
The development of real-time learning assessment tools is hindered by an incomplete understanding of the underlying neural mechanisms. To address this gap, this study aimed to identify the specific neural correlates of implicit learning, a foundation...
(1) Background: Attention is an important cognitive process in daily life. However, limited cognitive resources have been allocated to attention, especially for multiple objects and its mechanism is still unclear. Most of the previous studies have be...
There is a gap in our understanding of how best to apply transcranial direct-current stimulation (tDCS) to enhance learning in complex, realistic, and multifocus tasks such as aviation. Our goal is to assess the effects of tDCS and feedback training...
Cognitive abilities in fish have been widely demonstrated using experimental protocols commonly adopted with mammals and birds. Only a few studies have tested fish in the simultaneous match-to-sample task (sMTS), and mixed evidence regarding their ca...
With the recent advances of deep learning, automatic target recognition (ATR) of synthetic aperture radar (SAR) has achieved superior performance. By not being limited to the target category, the SAR ATR system could benefit from the simultaneous ext...
The purpose of this study was to compare the difference in the accuracy of gait events between young and older adults during metronomic walking by auditory cueing. Additionally, age-specific changes in the gait event accuracy according to additional...
This paper presents a sensor fusion strategy applied for Simultaneous Localization and Mapping (SLAM) in dynamic environments. The designed approach consists of two features: (i) the first one is a fusion module which synthesizes line segments obtain...
This paper proposes a comprehensive Mixed-Integer Linear Programming (MILP) formulation for the simultaneous scheduling of machines and Automated Guided Vehicles (AGVs) within a partitioned Flexible Manufacturing System (FMS). The main objective is t...
17 November 2022
Walking requires attentional resources, and the studies using neuroimage techniques have grown to understand the interaction between cortical activity and motor performance. Previous studies reported a decline in gait performance and changes in the p...
The rapid increase in population aging and associated age-related cognitive decline requires identifying innovative and effective methods to prevent it. To manage this socio-economic challenge, physical, cognitive, and combined stimulations are propo...
For data-driven intelligent manufacturing, many important in-process parameters should be estimated simultaneously to control the machining precision of the parts. However, as two of the most important in-process parameters, there is a lack of multi-...
This study aimed to develop a deep learning-based model to simultaneously perform the objective response (OR) and tumor segmentation for hepatocellular carcinoma (HCC) patients who underwent transarterial chemoembolization (TACE) treatment. A total o...
This paper addresses the challenge of coordinating task allocation and generating collision-free trajectories for a fleet of mobile robots in dynamic environments. Our approach introduces an integrated framework comprising a centralized task allocati...
Various deep learning applications benefit from multi-task learning with multiple regression and classification objectives by taking advantage of the similarities between individual tasks. This can result in improved learning efficiency and predictio...
Visual perception is a critical task for autonomous driving. Understanding the driving environment in real time can assist a vehicle in driving safely. In this study, we proposed a multi-task learning framework for simultaneous traffic object detecti...
Face alignment methods have been actively studied using coordinate and heatmap regression tasks. Although these regression tasks have the same objective for facial landmark detection, each task requires different valid feature maps. Therefore, it is...
Robots with multiple degrees of freedom (DOFs), such as underwater vehicle–manipulator systems (UVMSs), are expected to optimize system performance by exploiting redundancy with various basic tasks while still fulfilling the primary objective....
Classifying and segmenting skin cancer represent pivotal objectives for automated diagnostic systems that utilize dermoscopy images. However, these tasks present significant challenges due to the diverse shape variations of skin lesions and the inher...
Background: Clinical imaging is an important part of health care providing physicians with great assistance in patients treatment. In fact, segmentation and grading of tumors can help doctors assess the severity of the cancer at an early stage and in...
Recent neuroimaging research has suggested that interpreters and non-interpreters elicit different brain activation patterns during simultaneous language translation. However, whether these two groups have different functional connectivity during suc...
The elastic optical network (EON) adopting virtual network function (VNF) is a new type of network, in which the routing, spectrum, and data center allocation are key and challenging problems, and solving these three problems simultaneously can not o...
In everyday life, we recurrently perform two tasks simultaneously, which is called dual-tasking. A common dual task is smartphone use while standing or walking. According to previous studies, this task can compromise postural stability. However, few...
Machine learning with deep neural networks (DNNs) is widely used for human activity recognition (HAR) to automatically learn features, identify and analyze activities, and to produce a consequential outcome in numerous applications. However, learning...
A novel tropical cyclone (TC) size estimation model (TC-SEM) in the western North Pacific was developed based on a convolutional neural network (CNN) using geostationary satellite infrared (IR) images. The proposed TC-SEM was tested using three CNN s...
It is difficult to effectively operate a dual-arm robot using only the information written in a cooking recipe. To cope with this problem, this paper proposes a graph-based approach on bimanual cooking motion planning from a cooking recipe. In our ap...
Area coverage and target tracking are important applications of UAV swarms. However, attempting to perform both tasks simultaneously can be a challenge, particularly under resource constraints. In such scenarios, UAV swarms must collaborate to cover...
A hierarchical mission planning method was proposed to solve a simultaneous attack mission planning problem for multi-unmanned aerial vehicles (UAVs). The method consisted of three phases aiming to decouple and solve the mission planning problem. In...
In this paper, we addressed the problem of controlling the position of a group of unicycle-type robots to follow in formation a time-varying reference avoiding obstacles when needed. We propose a kinematic control scheme that, unlike existing methods...
In public use of a large display, it is a usual phenomenon that multiple users individually participate in respective tasks on a common device. Previous studies have categorized such activity as independent interaction that involves little group enga...
The generation of topographic classification maps or relative heights from aerial or remote sensing images represents a crucial research tool in remote sensing. On the one hand, from auto-driving, three-dimensional city modeling, road design, and res...
In complex environments, users frequently need to manage multiple tasks simultaneously, which poses significant challenges for user interface design. For instance, when driving, users must maintain continuous visual attention on the road ahead while...
The vehicle routing problem with time windows (VRPTW) is a widely studied combinatorial optimization problem in supply chains and logistics within the last decade. Recent research has explored the potential of deep reinforcement learning (DRL) as a p...
As control and execution components within hydraulic systems, hydraulic valves are critical to system efficiency and operational safety. However, existing research primarily focuses on specific valve designs, exhibiting limitations in versatility and...
Falling is a frequent and major clinical problem among older adults, as well as in patients with chronic cerebrovascular diseases (CVD). At present, sequential (mixed) and simultaneously (dual-task) motor-cognitive trainings are the best approaches t...
This dataset was acquired during collaboration and competition tasks performed by sixteen subject pairs (N = 32) of one female and one male under different (face-to-face and online) modalities. The collaborative task corresponds to cooperating to put...
Privacy-preserving task assignment is vital to assign a task to appropriate workers and protect workers’ privacy or task privacy for spatial crowdsourcing (SC). Existing solutions usually require each worker to travel to the task location on pu...
Background/Objectives: Performing cardiopulmonary resuscitation (CPR) is cognitively demanding, often requiring helpers to perform cognitive and manual tasks simultaneously. While the human brain primarily switches between tasks rather than processin...
Suspended solids (SS) composed of micrometer-to-nanometer-scale particles, including silt and organic matter, significantly impact aquatic ecosystems through physicochemical interactions. Accurate monitoring of SS concentration and particle size is c...
Limited by the load capacity of UAVs, it is difficult for an integrated radio frequency (RF) system aboard a single platform to have both wide-area and comprehensive battlefield sensing capabilities. One possible approach to solve this dilemma is to...
Multi-task learning (MTL) is a learning strategy for solving multiple tasks simultaneously while exploiting commonalities and differences between tasks for improved learning efficiency and prediction performance. Despite its potential, there remain s...
Agricultural factories utilize advanced facilities and technologies to cultivate crops in a controlled environment, enhancing operational yields and reducing reliance on natural resources. This is crucial for ensuring a stable supply of agricultural...
Hand gesture recognition and hand pose estimation are two closely correlated tasks. In this paper, we propose a deep-learning based approach which jointly learns an intermediate level shared feature for these two tasks, so that the hand gesture recog...
Gaze convergence of multiuser eye movements during simultaneous collaborative use of a shared system interface has been proposed as an important albeit sparsely explored construct in human-computer interaction literature. Here, we propose a novel ind...
The assembly of large and complex products such as cars, trucks, and white goods typically involves a huge amount of production resources such as workers, pieces of equipment, and layout areas. In this context, multi-manned workstations commonly char...
Previous studies have primarily focused on predicting the remaining useful life (RUL) of tools as an independent process. However, the RUL of a tool is closely related to its wear stage. In light of this, a multi-task joint learning model based on a...
21 November 2022
Several models have tentatively associated improving attention-deficit/hyperactivity disorder (ADHD) symptoms with arousal and external environmental stimulation. In order to further clarify the relationships between ADHD symptoms, arousal, and exter...
Medical images are acquired at different resolutions based on clinical goals or available technology. In general, however, high-resolution images with fine structural details are preferred for visual task analysis. Recognizing this significance, seve...
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