A fractional order PID-based sliding mode controller approach for chemical processes by Oscar Camacho, Sebastian Vega, Marco Herrera, Antonio Di Teodoro, Juan J. Gude

Get full text

An optimized deterministic concurrency control approach for geo-distributed transaction processing on permissioned blockchains by Zhibo Han, Zeshun Peng, Gang Wang, Minghe Yu, Xiaohua Li, Yanfeng Zhang, Ge Yu

“…Abstract Concurrency control is crucial for ensuring consistency and isolation in distributed transaction processing. Traditional concurrency control algorithms, such as locking-based protocols, usually suffer from performance degradation due to heavy transaction coordination overheads. …”
Get full text

Predictive Machine Learning Approaches for Supply and Manufacturing Processes Planning in Mass-Customization Products by Shereen Alfayoumi, Amal Elgammal, Neamat El-Tazi

“…Planning in mass-customization supply and manufacturing processes is a complex process that requires continuous planning and optimization to minimize time and cost across a wide variety of choices in large production volumes. …”
Get full text

Highly Parallel Regular Expression Matching Using a Real Processing-in-Memory System by Jeonghyeon Joo, Hyojune Kim, Hyuck Han, Eul Gyu Im, Sooyong Kang

“…Processing-in-Memory (PIM) is an emerging computing paradigm exploiting a cutting-edge memory device (PIM device) that integrates hundreds to thousands of processing units with the memory modules. …”
Get full text

Approach to knowledge management and the development of a multi-agent knowledge representation and processing system by E. I. Zaytsev, E. V. Nurmatova

“…A multi-agent knowledge representation and processing system (MKRPS) comprises a distributed artificial intelligence system designed to solve problems that are difficult or impossible to solve using monolithic systems. …”
Get full text

Design and Evaluation of a Cloud Computing System for Real-Time Measurements in Polarization-Independent Long-Range DAS Based on Coherent Detection by Abdusomad Nur, Almaz Demise, Yonas Muanenda

“…Data handling in DAS remains an open issue, as many applications need continuous monitoring of a volume of samples whose storage and processing in real time require high-capacity memory and computing resources. …”
Get full text

Real-Time Milk Quality Control Using Multi-Spectral Sensing and Edge Computing: Advancing On-Site Detection of Milk Components with XGBoost by Mahmut Durgun

“…This study explores the use of edge computing technologies to enhance the quality control processes in the dairy industry. …”
Get full text

Adjacent Zero Communication Parallel Cloud Computing Method and Its System for N-Body Problem with Short-Range Interaction Domain Decomposition by Dingju Zhu

“…Although parallel computing is used in the existing numerical solutions of N-body problem, tons of communications between N particles render the parallel efficiency extremely low. …”
Get full text

The concept of creating an automated information and computing complex for substantiating projects of programs and plans for the development of arms and means of radiation, chemica... by D. N. Cheshev, A. S. Durnov, S. V. Skoblikov, D. A. Egorushkin

“…The purpose of the research is to create an information and computing complex to support decision-making on improving the armament system of radiation, chemical and biological protection on the basis of modern information computer technologies and methodological support for the justification of programs and development plans of arms and means of radiation, chemical and biological protection. …”
Get full text

Priority-aware task offloading for LEO satellite edge computing network: a multi-agent deep reinforcement learning-based approach by Juan Chen, Jie Zhong, Zongling Wu, Di Tian, Yujie Chen

“…Abstract In the current data-driven era, satellite edge computing (SatEC) emerges as a novel computing paradigm that addresses the coverage limitations of terrestrial networks in remote areas by deploying computational resources on satellite networks. …”
Get full text

Optimizing Machine Learning Models with Data-level Approximate Computing: The Role of Diverse Sampling, Precision Scaling, Quantization and Feature Selection Strategies by Ayad M. Dalloo, Amjad J. Humaidi

“…Efficiency, low-power consumption, and real-time processing in embedded machine learning implementations are critical, particularly for models deployed in environments with large-scale data processing and resource-constrained environments. …”
Get full text

Service-Chain-Driven Communication and Computing Integration Networking: A Case Study of Levee Piping Hazard Inspection via Remote Sensing by Jing Chen, Lyuzhou Gao, Hongquan Sun, Siquan Yang, Zhonggen Wang, Yuting Wan, Kedi Wang

“…In the transmission phase, we adopt the designed multi-path transmission mechanism to promote the efficient data flow across heterogeneous networks. In the computation phase, the proposed SACM algorithm, which is functionally decomposed and implemented as service chains within the proposed network architecture, dynamically processes the retrieved temperature fields to achieve precise hazard identification. …”
Get full text

Prediction of unobserved bifurcation by unsupervised extraction of slowly time-varying system parameter dynamics from time series using reservoir computing by Keita Tokuda, Yuichi Katori

“…IntroductionNonlinear and non-stationary processes are prevalent in various natural and physical phenomena, where system dynamics can change qualitatively due to bifurcation phenomena. …”
Get full text

In‐Sensor Computing‐Based Smart Sensing Architecture Implemented Using a Dual‐Gate Metal‐Oxide Thin‐Film Transistor Technology by Tengteng Lei, Yushen Hu, Xinying Xie, Runxiao Shi, Man Wong

“…Presently proposed is a smart sensor architecture that combines an array of sensing elements with an overlapping array of computing and memory elements, thus emulating an innervated peripheral sensing system (IPSS) capable of local and autonomous neuromorphic in‐sensor data pre‐processing. …”
Get full text

RiverBedDynamics v1.0: a Landlab component for computing two-dimensional sediment transport and river bed evolution by A. D. Monsalve, S. R. Anderson, N. M. Gasparini, E. M. Yager

“…LEMs used in long-term simulations over large watersheds, including some available in the Landlab library, often assume that only erosive processes occur in rivers and that terrain elevation increases solely due to tectonic uplift. …”
Get full text

On-Demand Gait-Synchronous Electrical Cueing in Parkinson's Disease Using Machine Learning and Edge Computing: A Pilot Study by Ardit Dvorani, Constantin Wiesener, Christina Salchow-Hommen, Magdalena Jochner, Lotta Spieker, Matej Skrobot, Hanno Voigt, Andrea Kuhn, Nikolaus Wenger, Thomas Schauer

“…While sensor technology and machine learning offer real-time detection for on-demand cueing, existing systems are limited by the usage of smartphones between the sensor(s) and cueing device(s) for data processing. By avoiding this we aim at improving usability, robustness, and detection delay. …”
Get full text

E-LEARNING AND THE DEVELOPMENT OF INTERCULTURAL COMPETENCE by Meei-Ling Liaw

“…Despite some technical difficulties with the computers, the collaboration between the two groups of students was successful, as can be seen from the positive and complimentary comments from the participants. …”
Get full text

Real-Time Monitoring of Personal Protective Equipment Adherence Using On-Device Artificial Intelligence Models by Yam Horesh, Renana Oz Rokach, Yotam Kolben, Dean Nachman

“…By utilizing a lightweight MobileNetV3 model, we optimized the system for edge computing on a Raspberry Pi 5 single-board computer, enabling rapid image processing without the need for external servers. …”
Get full text

SIR Coverage Analysis in Multi-Cell Downlink Systems With Spatially Correlated Queues by Xiaozhou Zhang, Howard H. Yang, Xiaofang Sun, Gang Zhu, Tony Q. S. Quek, Zhangdui Zhong

“…The locations of the former are modeled by a Neyman-Scott process and those of the latter are modeled as a residual hole process. …”
Get full text

Optimizing casting process using a combination of small data machine learning and phase-field simulations by Xiaolong Pei, Jiaqi Pei, Hua Hou, Yuhong Zhao

Get full text