As data science advances, automated machine learning (AutoML) gains attention for lowering barriers, saving time, and enhancing efficiency. However, with increasing data dimensionality, AutoML struggles with large-scale feature sets. Effective featur...
With the increasing deployment of multi-robot systems in autonomous applications, efficient task allocation is essential for coordinating multiple robots and improving system performance. To address this challenge, this paper proposes an FPGA-oriente...
In this study, a cooperative robotic system comprising two Selective Compliance Assembly Robot Arm (SCARA) robots was developed and simulated. An algorithm was proposed for the coordination of robots in cooperative tasks, along with a Rapidly explori...
This study evaluated the use of a technology-based self-monitoring of performance (SMP) with differential reinforcement to increase task completion and reduce off-task behavior for three 5th-grade students with disabilities. A concurrent multiple bas...
The new barrier mode in Apache Spark allows for embedding distributed deep learning training as a Spark stage to simplify the distributed training workflow. In Spark, a task in a stage does not depend on any other tasks in the same stage, and hence i...
The task context switch operation, the inter-task synchronization and communication mechanisms, as well as the jitter occurred in treating aperiodic events, are crucial factors in implementing real-time operating systems (RTOS). In practice and liter...
Today, many big data applications require massively parallel tasks to compute complicated mathematical operations. To perform parallel tasks, platforms like CUDA (Compute Unified Device Architecture) and OpenCL (Open Computing Language) are widely us...
Excavator–truck operations, characterized by their repetitive excavation and loading tasks, present a prime candidate for automation. While numerous studies have aimed to automate the earthworks, practical implementations remain scarce. This re...
Robots and artificial intelligence have revolutionized the healthcare sector. Transporting patients within hospitals is critical; however, reducing errors and inefficiencies caused by human intervention and increasing task efficiency are necessary. T...
This paper presents an experimental investigation into the implementation of free-motion tasks on a serial metamorphic manipulator (SMM). Utilizing a previously established task-based optimization methodology, the dynamic performance of the SMM is ev...
Distributed computing technologies allow a wide variety of tasks that use large amounts of data to be solved. Various paradigms and technologies are already widely used, but many of them are lacking when it comes to the optimization of resource usage...
In recent years, systems that monitor and control home environments, based on non-vocal and non-manual interfaces, have been introduced to improve the quality of life of people with mobility difficulties. In this work, we present the reconfigurable i...
The advent of the Internet of Things (IoT) has revolutionised our interaction with the environment, facilitating seamless connections among sensors, actuators, and humans. Efficient task scheduling stands as a cornerstone in maximising resource utili...
Enhancing energy efficiency is one of the main challenges of today’s industrial robotics and manufacturing technology. In this paper a task-related analysis of the energetic performance of a 4-DOF industrial parallel robot is presented, and the...
The widespread applicability of cyber-physical systems (CPS) necessitates efficient schemes to optimize the performance of both computing units and physical plant. Task scheduling (TS) in CPS is of vital importance to enhance resource usage and syste...
The article aims to enhance understanding of how relations, behavior and attitude of the executives and contractors to achieving the objectives by energy supplying companies affect the efficiency of the latter’s overall development. There is offered...
Secure and compact designs of HIGHT block cipher on representative ARM microcontrollers are presented in this paper. We present several optimizations for implementations of the HIGHT block cipher, which exploit different parallel approaches, includin...
Efficient and accurate data entry is essential for ensuring high-quality clinical registries; however, conventional electronic data-capture (EDC) interfaces impose a substantial workload on healthcare professionals. This study compared a wizard-style...
Automating fall risk assessment, in an efficient, non-invasive manner, specifically in the elderly population, serves as an efficient means for implementing wide screening of individuals for fall risk and determining their need for participation in f...
With the explosive growth of data at the edge in the Industrial Internet of Things (IIoT), edge devices are increasingly performing more data processing tasks to alleviate the load on cloud servers. To achieve this goal, Programmable Logic Controller...
Mission scheduling is an essential function of the management control of remote-sensing satellite application systems. With the continuous development of remote-sensing satellite applications, mission scheduling faces significant challenges. Existing...
The need for effective and efficient special education teacher training in evidence-based instructional procedures persists. In this study, behavioral skills training (BST) and coaching were used to train and support a preservice special education te...
In this paper, we present a novel approach to task planning based on an intelligent expert system that makes it possible to obtain a conclusion based on linguistically characterized knowledge. The main goal of the proposed task planning system is to...
There has been a recent surge in publications related to binarized neural networks (BNNs), which use binary values to represent both the weights and activations in deep neural networks (DNNs). Due to the bitwise nature of BNNs, there have been many e...
The ability to predict the maximal performance of an industrial robot executing non-deterministic tasks can improve process productivity through time-based planning and scheduling strategies. These strategies require the configuration and the compari...
The prediction mechanism is very crucial in a smart factory as they widely help in improving the product quality and customer’s experience based on learnings from past trends. The implementation of analytics tools to predict the production and...
Industry 4.0 provides a tremendous potential of data from the work floor. For manufacturing companies, these data can be very useful in order to support assembly operators. In literature, a lot of contributions can be found that present models to des...
Energy limitations remain a key concern in the development of Internet of Medical Things (IoMT) devices since most of them have limited energy sources, mainly from batteries. Therefore, providing a sustainable and autonomous power supply is essential...
In recent decades, machine-learning algorithms have been extensively utilized to tackle various complex tasks. To achieve the high performance and efficiency of these algorithms, various hardware accelerators are used. Typically, these devices are sp...
Space-based systems providing remote sensing, communication, and navigation services are essential to the economy and national defense. Users’ demand for satellites has increased sharply in recent years, but resources such as storage, energy, a...
Cloud computing is a rapidly growing technology that has been implemented in various fields in recent years, such as business, research, industry, and computing. Cloud computing provides different services over the internet, thus eliminating the need...
Within the transition from precision agriculture (task-specific approach) to smart farming (system-specific approach) there is a need to build and evaluate robotic systems that are part of an overall integrated system under a continuous two-way conne...
Task scheduling in the cloud computing paradigm poses a challenge for researchers as the workloads that come onto cloud platforms are dynamic and heterogeneous. Therefore, scheduling these heterogeneous tasks to the appropriate virtual resources is a...
Efficiency is very important for robots when executing multiple tasks, especially for autonomous underwater vehicles (AUVs) with limited endurance. In order to improve efficiency, task-sequencing optimization, which focuses on achieving the optimal e...
Vehicular fog computing (VFC) is an innovative computing paradigm with an exceptional ability to improve the vehicles’ capacity to manage computation-intensive applications with both low latency and energy consumption. Moreover, more and more A...
In recent years, the focus of the smart transportation industry has been shifting towards the research and development of smart cars with autonomous control. Smart cars are considered to be a smart investment, as they promote safe driving while focus...
In modern information technology systems, secure storage and transmission of personal and sensitive data are recognized as important tasks. These requirements are achieved through secure and robust encryption methods. Argon2 is an advanced cryptograp...
Because of the comprehensiveness and urgency of environmental challenges, every stakeholder needs to be engaged in reducing environmental impacts. The healthcare sector has rarely been studied, despite its intense effects on the environment, particul...
Traditional volatile organic compounds (VOCs) detection models separate component identification and concentration prediction, leading to low feature utilization and limited learning in small-sample scenarios. Here, we realize a Residual Fusion Netwo...
Roboticized nursing technology is a significant means to implement efficient elderly care and improve their welfare. Introducing multi-heterogeneous robot systems (MHRS) and sensor networks into a smart home is a promising approach to improve the saf...
The composition of cloud services plays a vital role in optimizing resource allocation, load balancing, task scheduling, and energy management. However, it remains a significant challenge due to the dynamic nature of workloads and the variability in...
One of the most important challenges in modern digital systems, especially regarding autonomous embedded systems, is energy efficiency. This work studies an energy consumption optimization approach on a microcontroller that implements IoT-like applic...
Automating sheet steel visual inspection can improve quality and reduce costs during its production. While many manufacturers still rely on manual or traditional inspection methods, deep learning-based approaches have proven their efficiency. In this...
In underwater environments restricted from human access, many intervention tasks are performed by using robotic systems like underwater manipulators. Commonly, the robotic systems are tele-operated from operating ships; the operation is apt to be ine...
Improving sample efficiency and achieving balanced multi-task performance across different tasks remain important research challenges in reinforcement learning. Yie Ar Kung-Fu is formulated as a multi-task reinforcement learning environment. A task-s...
With the expansion of vehicle-to-everything (V2X) networks and the rising demand for intelligent services, vehicle edge computing encounters heightened requirements for more efficient task offloading. This study proposes a task offloading technique t...
A binary convolutional neural network (BCNN) is a neural network promising to realize analysis of visual imagery in low-cost resource-limited devices. This study presents an efficient inference processor for BCNNs, named TORRES. TORRES performs infer...
Designing an efficient task offloading system is essential in the Industrial Internet of Things (IIoT). Owing to the limited computational capability of IIoT devices, offloading tasks to edge servers enhances computational efficiency. When an edge se...
Small satellite technologies have enhanced the potential and feasibility of geodesic missions through the simplification of design and decreased costs allowing for more frequent launches. On-satellite data acquisition systems can benefit from the imp...
With the increased penetration of cloud computing and virtualization, a plethora of internet of things devices have been deployed globally. As a result, computationally intensive tasks are transmitted from the edge towards the centralized cloud for p...
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