Multi-task learning is a computationally efficient method to solve multiple tasks in one multi-task model, instead of multiple single-task models. MTL is expected to learn both diverse and shareable visual features from multiple datasets. However, MT...
Traditional evolution algorithms tend to start the search from scratch. However, real-world problems seldom exist in isolation and humans effectively manage and execute multiple tasks at the same time. Inspired by this concept, the paradigm of multi-...
In the process of bridge management, large amounts of domain information are accumulated, such as basic attributes, structural defects, technical conditions, etc. However, the valuable information is not fully utilized, resulting in insufficient know...
With the explosive growth of multimedia services and the continuous emergence of new space tasks, the spatial task scheduling timeliness problem is of great concern. The high computational cost of existing task scheduling methods is not suitable for...
Due to its links to computer science (CS), teaching computational thinking (CT) often involves the handling of algorithms in activities, such as their implementation or analysis. Although there already exists a wide variety of different tasks for var...
In this paper, we propose a centralized task allocation and an alignment technique based on constraint table and alignment rules. For task allocation, a scoring scheme has to be set. The existing time-discounted scoring scheme has two problems; if th...
For many practical systems that are required to perform critical tasks, it is commonly observed that tasks can be performed multiple times within a limited time to improve task success probability. Such property is referred to as time redundancy. Thi...
The multiple unmanned aerial vehicles (UAVs) system is highly sought after in the fields of emergency rescue and intelligent transportation because of its strong perception and extensive coverage. Formulating a reasonable task scheduling scheme is es...
This paper presents an optimization framework for Multi-Robot Task Allocation (MRTA) for a heterogeneous robot fleet operating in dynamic, failure-prone environments. In contrast to traditional MRTA approaches that handle only the initial allocation,...
Mental fatigue is a widely studied topic on account of its serious negative effects. But how the neural mechanism of task switching before and after mental fatigue remains a question. To this end, this study aims to use brain functional network featu...
Life in today’s world is characterized by complexity and rapid change. Twenty-first century skills and especially mathematical understanding are supposed to crucially contribute to meeting the demands of our world since mathematics offers strat...
30 October 2020
A soldier’s occupational physical task requirements are diverse and varied. However, the type of physical training that most effectively improves soldiers’ occupational task requirements has not been studied previously. The purpose of thi...
This paper tackles the problem of resource sharing and dynamic task assignment in a task scheduling architecture designed to enable a persistent, safe, and energy-efficient Intelligent Transportation System (ITS) based on multi-rotor Unmanned Aerial...
In this paper, we address the problem of online dynamic multi-robot task allocation (MRTA) problem. In the existing literature, several works investigated this problem as a multi-objective optimization (MOO) problem and proposed different approaches...
Multi-task learning (MTL) is essential for satellite internet systems requiring simultaneous optimization of beam management, interference mitigation, resource allocation, and traffic prediction. However, existing evaluation methods rely predominantl...
Recent studies have witnessed significant advances in unified multi-weather image restoration, which aims to handle diverse weather degradations within a single model. In this work, we observe that rain, haze, and snow restoration exhibit substantial...
Maintaining balance while performing secondary tasks is essential for daily life. The interplay between motor control and cognitive processes during dual tasks remains equivocal, characterized by mixed findings across studies. This pilot study implem...
With the continuous emergence of intelligent network applications and complex tasks for mobile terminals, the traditional single computing model often fails to meet the greater requirements of computing and network technology, thus promoting the form...
Cluster separation is required to perform multi-class visual statistics tasks and plays an essential role in information processing in visualization. This cognition behavioral study investigated the cluster separation task and the effects of visual c...
Edge computing enables devices with insufficient computing resources to offload their tasks to the edge for computing, to improve the service experience. Some existing work has noticed that the data size of offloaded tasks played a role in resource a...
Semantic communication provides a task-oriented alternative to conventional bit-level transmission. For wireless image transmission, existing systems mainly optimize image reconstruction, while downstream classification is often handled by a separate...
Coded computing is recognized as a promising solution to address the privacy leakage problem and the straggling effect in distributed computing. This technique leverages coding theory to recover computation tasks using results from a subset of worker...
In multirobot task planning, the goal is to meet the multi-objective requirements of the optimal and balanced energy consumption of robots. Thus, this paper introduces the energy penalty strategy into the GA (genetic algorithm) to achieve the optimiz...
Aiming at the problem of UAV swarms with distributed subsets performing cooperative reconnaissance-and-attack tasks on multi-targets in complex and uncertain combat scenarios, a distributed grouping cooperative dynamic task assignment method is propo...
Although Brazilian governmental documents have conceived language teaching from a critical perspective, the recent scenario points to a backlash towards critical perspectives on teaching, which have been socially perceived as indoctrination. Since we...
Fog computing is one of the major components of future 6G networks. It can provide fast computing of different application-related tasks and improve system reliability due to better decision-making. Parallel offloading, in which a task is split into...
Cooperative edge offloading to nearby end devices via Device-to-Device (D2D) links in edge networks with sliced computing resources has mainly been studied for end devices (helper nodes) that are stationary (or follow predetermined mobility paths) an...
In this work, we investigate an energy-aware multi-robot task-allocation (MRTA) problem in a cluster of the robot network that consists of a base station and several clusters of energy-harvesting (EH) robots. It is assumed that there are
In open-ended continuous environments, robots need to learn multiple parameterised control tasks in hierarchical reinforcement learning. We hypothesise that the most complex tasks can be learned more easily by transferring knowledge from simpler task...
Entity resolution aims to identify records that point to the same entity in the real world. In recent years, crowdsourcing approaches have provided new ideas for entity resolution, using human intelligence to bring entity resolution to a higher level...
In contemporary environments, young children are frequently exposed to diverse audiovisual stimuli and often encounter dual-task situations requiring them to process unrelated stimuli simultaneously. Although dual-task conditions impair children&rsqu...
This research demonstrates a novel design of an FPGA-implemented task scheduler for real-time systems that supports both aperiodic and periodic tasks. The periodic tasks are automatically restarted once their period has expired without any need for s...
With the rapid changes in the battlefield situation, the requirement of time for UAV groups to deal with complex tasks is getting higher, which puts forward higher requirements for the dynamic allocation of the UAV group. However, most of the existin...
This study investigates how increasing prompt complexity affects the performance of Large Language Models (LLMs) across multiple Natural Language Processing (NLP) tasks. We introduce an incremental evaluation framework where six tasks—JSON form...
This paper conducts a rigorous game-theoretic analysis on multi-task deep learning, providing mathematical insights into the dynamics and interactions of tasks within these models. Multi-task deep learning has attracted significant attention in recen...
In partially observable adversarial environments, heterogeneous unmanned aerial vehicle (UAV) swarms must generate tasks online from noisy observations while respecting platform capabilities, consumable resources, and structural dependencies among ta...
Including motivational variables such as interest in the cognitive load framework is an ongoing process. Of particular interest is the question of how motivational variables influence the investment of mental effort. In this study, we investigated ho...
Multi-access edge computing (MEC) has emerged as a promising technology to facilitate efficient vehicular applications, such as autonomous driving, path planning and navigation. By offloading tasks from vehicles to MEC servers (MECSs), the MEC system...
In the computer-aided diagnosis of lung cancer, the automatic segmentation of pulmonary nodules and the classification of benign and malignant tumors are two fundamental tasks. However, deep learning models often overlook the potential benefits of ta...
Dynamic task allocation for unmanned aerial vehicles (UAVs) is often constrained by stale and asymmetric information. Variants of the Consensus-Based Bundle Algorithm (CBBA) can waste bandwidth by transmitting every state or bid update without distin...
Multi-robot systems have become integral to a wide range of practical applications, requiring efficient and reliable task allocation to maintain operational performance, particularly in dynamic and unpredictable environments such as disaster response...
Infrared image colorization has gained widespread attention in recent years as an important means of enhancing image visibility and semantic expression. However, existing evaluation methods mostly rely on pixel-level differences or feature distributi...
This study studies the problem of on-orbit maintenance task planning for space-robot clusters. Aiming at the problem of low maintenance efficiency of space-robot cluster task-planning, this study proposes a cluster-task-planning method based on energ...
In order to secure organizational sustainability in a rapidly changing environment, it is necessary to implement a decentralized and flexible work environment. In such work environments, normally individuals are provided with autonomy and independenc...
TASK-3 is a two-pore domain potassium (K2P) channel highly expressed in the hippocampus, cerebellum, and cortex. TASK-3 has been identified as an oncogenic potassium channel and it is overexpressed in different cancer types. For this reason, the deve...
It is difficult for swarm robots to allocate tasks efficiently by self-organization in a dynamic unknown environment. The computational cost of swarm robots will be significantly increased for large-scale tasks, and the unbalanced task allocation of...
Computational models of the basal ganglia (BG) provide a mechanistic account of different phenomena observed during reinforcement learning tasks performed by healthy individuals, as well as by patients with various nervous or mental disorders. The ai...
Task allocation in edge computing refers to the process of distributing tasks among the various nodes in an edge computing network. The main challenges in task allocation include determining the optimal location for each task based on the requirement...
As technological advancements increase exponentially, mobile phones become smarter with machine learning and artificial intelligence algorithms. These advancements have allowed mobile phone users to perform most of their daily routine tasks on mobile...
The interference between software components is increasing in safety-critical domains, such as autonomous driving. Low-criticality (LC) tasks, such as vehicle communication, may control high-criticality (HC) tasks, such as acceleration. In such cases...
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