Reliable text-to-CAD generation remains challenging because syntactically valid programs may fail during geometric execution or produce inaccurate geometric models. Existing approaches often treat geometric execution primarily as a post-generation va...
Classification and regression are the major applications of machine learning algorithms which are widely used to solve problems in numerous domains of engineering and computer science. Different classifiers based on the optimization of the decision t...
This paper theoretically explores the impact of the incentive preferences of executives (i.e., short-term incentives and long-term incentives) on corporate social responsibility (CSR) decisions (i.e., institutional CSR and technical CSR). Further, th...
Background and Objectives: Increased and unstructured digital exposure has raised growing concerns about its potential impact on children’s cognitive and behavioral development. Executive functions (EFs)—encompassing attention, working me...
Shot execution in cricket batting is reliant on intricate movement patterns of crucial body segments. When there is a substantial amount of batting movement data available, supervised machine learning can be used to classify when a batting shot execu...
13 February 2024
Aim: Utilizing the subjective experience of nurse executives who have supervised nurses during a major disaster in a hospital setting, this study aims to describe the subjective experience of nurse executives (NE) who have supervised nurses’ re...
22 June 2021
Academic achievement has been linked to executive functions. However, it is necessary to clarify the different predictive role that executive functions have on general and specific academic achievement and to determine the most predictive executive f...
In this paper, we apply machine learning models to execute certain short-option strategies on the S&P500. In particular, we formulate and focus on a supervised classification task which decides if a plain short straddle on the S&P500 should b...
As one of the technical elements supporting the blockchain to realize decentralized autonomous organizations, smart contracts are crucial for understanding the inherent properties of blockchain systems through formal research. Most existing formal mo...
Most path planning algorithms used presently in multi-robot systems are based on offline planning. The Timed Enhanced A* (TEA*) algorithm gives the possibility of planning in real time, rather than planning in advance, by using a temporal estimation...
Multi-step task solving with large language models in intelligent electronic systems and interactive environments requires stronger process control and execution reliability. To address local error accumulation during multi-step execution, this paper...
Construction supervision is a key task that can confirm and inspect the project execution and support the creation of successful results. For the efficient performance of construction supervision, collecting various information necessary for the supe...
Physical activities, according to the embodied cognition theory, are an important manifestation of cognitive functions. As a result, in this paper, the Activate Test of Embodied Cognition (ATEC) system is proposed to assess various cognitive measures...
14 February 2020
The extant literature has focused on individuals’ knowledge-sharing behavior and its driving factors, which stimulate the knowledge transmission and exchange in organizations. However, little research has focused on factors that inhibit knowled...
Background/Objectives: The relationship between executive functions, special educational needs (SEN), and learning difficulties in school-aged children is critical for developing effective educational interventions. This study explores the connection...
21 August 2024
Background: Considering regulatory, supervision, and control health policy, an innovative knowledge management model is proposed for the Colombian health system, which is recognized as a complex system. Methods: A model is constructed through a compa...
Benefiting from the advancement of deep neural networks (DNNs), detecting objects from drone-view images has achieved great success in recent years. It is a very challenging task to deploy such DNN-based detectors on drones in real-life applications...
Currently, a rapid digital revolution is occurring in the building industry due to the need to solve chronic challenges such as low productivity, inconsistent execution quality, and difficulty in controlling costs and schedules. Construction supervis...
Ensuring trust, security, and privacy among all participating parties in the process of sharing supervision data is crucial for engineering quality and safety. However, the current centralized architecture platforms that are commonly used for enginee...
30 June 2020
(1) Background: Foreign body aspiration (FBA) is a significant public health concern among the pediatric population, and fatalities are dramatic for families. It typically involves organic foreign bodies (mainly food) aspirated by children under thre...
Semi-supervised classification is one of the core methods to deal with incomplete tag information without manual intervention, which has been widely used in various real problems for its excellent performance. However, the existing algorithms need to...
Rehabilitation exoskeletons require supervisory control that can preserve globally safe operating modes while executing local therapeutic behaviors reactively. Pure Finite-State Machine (FSM) implementations provide explicit mode supervision but beco...
Large language model (LLM)-based financial agents use market information to generate trading actions together with textual reasoning. However, the resulting executable position transition may conflict with its supporting analysis, while the effect of...
Machine learning-based indoor localization used to suffer from the collection, construction, and maintenance of labeled training databases for practical implementation. Semi-supervised learning methods have been developed as efficient indoor localiza...
With Industry 5.0, human–robot collaboration has become the center of attention. This has introduced new challenges, where workspaces become highly dynamic, leading to safety concerns for robots and especially for humans. This makes it importan...
Large language model agents are increasingly used to analyze data, generate code, and execute operations in data-engineering environments. However, successful technical execution does not guarantee that an operation is authorized or that its results...
This letter presents the capabilities of a command line tool created to assess the quality of segmented digital images. The executable source code, called AssesSeg, was written in Python 2.7 using open source libraries. AssesSeg (University of Almeri...
Autonomous grounded vehicle-based social assistance/service robot parking in an indoor environment is an exciting challenge in urban cities. There are few efficient methods for parking multi-robot/agent teams in an unknown indoor environment. The pri...
An eco-labeling scheme is a method of environmental performance certification that is beneficial for reducing negative environmental impacts and promoting green consumption. Many types of research studies have shown its effectiveness. However, to the...
This paper describes a supervisor system for monitoring the operation of automated agricultural vehicles. The system analyses all of the information provided by the sensors and subsystems on the vehicles in real time and notifies the user when a fail...
Background/Objectives: Correct supervision during the performance of resistance exercises is imperative to the correct execution of these exercises. This study presents a proposal for the use of Morisita–Horn similarity indices in modelling wit...
Recent advances in large language models, tool-using agents, and financial machine learning are shifting financial automation from isolated prediction tasks to integrated decision systems that can perceive information, reason over objectives, and gen...
Affective Image Stylization (AIS) converts an emotional intent into executable artistic visual styles. Existing methods are often limited to discrete label settings and provide limited interpretability of how target emotions are realized. We propose...
The issue of corporate rent-seeking, which stems from the misuse of authority, remains a critical concern for the international community. Drawing on agency theory and resource dependence theory, this study explores the relationship between corporate...
Airfield ground lighting is safety-critical electrical infrastructure and requires reliable inspection. We benchmarked lamp detection, colour assignment and embedded execution using 59 GoPro HERO 8 recordings acquired through scientific cooperation w...
Green innovation has become an important support to promote the strategic goals of peak carbon dioxide emission and high-quality economic development. This paper systematically examines whether internal control can effectively drive enterprise green...
In recent years, with the deepening research on exoskeletons for children with cerebral palsy, increasing evidence has highlighted their unique characteristics. Unlike adult exoskeletons, pediatric exoskeletons cannot be simply realized by scaling do...
This narrative review aims to highlight and analyze the supervision of precision robotic surgical interventions. These are autonomous, closed-loop procedures, assisted by images and managed by intelligent digital tools. These administered procedures...
Current System-on-Chips (SoCs) execute applications with task dependency that compete for shared resources such as buses, memories, and accelerators. In such a structure, the arbitration policy becomes a critical part of the system to guarantee acces...
Contemporary enterprise IT operations are largely implemented on Shannon–Turing computing models in which programs execute read–compute–write cycles over data structures, while governance—fault handling, configuration control,...
Supervised activity recognition algorithms require labeled data to train classification models. Labeling an activity can be performed trough observation, in controlled conditions, or thru self-labeling. The two first approaches are intrusive, which m...
12 January 2021
This study focuses on the development of executive functions in preschool children during a series of science activities. A longitudinal play-based learning intervention was designed and implemented following the design of an educational experiment....
Conventional vehicle character recognition methods often treat detection and recognition as separate processes, resulting in limited feature interaction and potential error propagation. To address this issue, this paper proposes a structure-aware sel...
The use of Riemannian geometry decoding algorithms in classifying electroencephalography-based motor-imagery brain–computer interfaces (BCIs) trials is relatively new and promises to outperform the current state-of-the-art methods by overcoming...
Nanoindentation was utilized as a non-destructive technique to identify Portland Cement hydration phases. Artificial Intelligence (AI) and semi-supervised Machine Learning (ML) were used for knowledge gain on the effect of carbon nanotubes to nanomec...
UUVs (unmanned underwater vehicles) perform tasks in the marine environment under direction from a commander through a mother ship control system. In cases where communication is available, a UUV task re-planning system was designed to ensure task co...
Over the last decade, supervised denoising models, trained on extensive datasets, have exhibited remarkable performance in image denoising, owing to their superior denoising effects. However, these models exhibit limited flexibility and manifest vary...
Sparse matrix–vector multiplication (SpMV) is a fundamental kernel in high-performance computing (HPC) whose efficiency depends heavily on the storage format across central processing unit (CPU) and graphics processing unit (GPU) platforms. Con...
Geospatial foundation models (GeoFMs) offer broad generalisation across Earth observation (EO) tasks, particularly under data-limited conditions. However, their large model size and computational requirements remain major barriers to deployment on re...
One of Indonesia’s sustainability targets is achieving full energy transitions and net zero emissions by 2060 or sooner. Thus, significant strides and massive investments are being made to revolutionise the development and delivery of infrastru...
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