Yu Song, Pengcheng Wu, Dongming Dai, Mingyu Gui, Kunli Zhang^*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4767-4790, 2024, DOI:10.32604/cmc.2024.053506 - 12 September 2024

Abstract The growing prevalence of knowledge reasoning using knowledge graphs (KGs) has substantially improved the accuracy and efficiency of intelligent medical diagnosis. However, current models primarily integrate electronic medical records (EMRs) and KGs into the knowledge reasoning process, ignoring the differing significance of various types of knowledge in EMRs and the diverse data types present in the text. To better integrate EMR text information, we propose a novel intelligent diagnostic model named the Graph ATtention network incorporating Text representation in knowledge reasoning (GATiT), which comprises text representation, subgraph construction, knowledge reasoning, and diagnostic classification. In the… More >

Turki Ali Alghamdi, Saud S. Alotaibi^*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4047-4064, 2024, DOI:10.32604/cmc.2024.052796 - 12 September 2024

Abstract Internet of Things (IoTs) provides better solutions in various fields, namely healthcare, smart transportation, home, etc. Recognizing Denial of Service (DoS) outbreaks in IoT platforms is significant in certifying the accessibility and integrity of IoT systems. Deep learning (DL) models outperform in detecting complex, non-linear relationships, allowing them to effectually severe slight deviations from normal IoT activities that may designate a DoS outbreak. The uninterrupted observation and real-time detection actions of DL participate in accurate and rapid detection, permitting proactive reduction events to be executed, hence securing the IoT network’s safety and functionality. Subsequently, this… More >

Xiwang Guo¹, Liangbo Zhou¹, Zhiwei Zhang^1,*, Liang Qi^2,*, Jiacun Wang³, Shujin Qin⁴, Jinrui Cao⁵

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4475-4496, 2024, DOI:10.32604/cmc.2024.048123 - 12 September 2024

Abstract This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers. A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle time. Based on a product’s AND/OR graph, matrices for task-skill, worker-skill, precedence relationships, and disassembly correlations are developed. A multi-objective discrete chemical reaction optimization algorithm is designed. To enhance solution diversity, improvements are made to four reactions: decomposition, synthesis, intermolecular ineffective collision, and wall invalid collision reaction, completing the evolution of molecular individuals. The established model and improved algorithm are applied to ball More >

Benxin Li^*, Xuanming Chang

Energy Engineering, Vol.121, No.10, pp. 3001-3018, 2024, DOI:10.32604/ee.2024.051332 - 11 September 2024

Abstract The increasingly large number of electric vehicles (EVs) has resulted in a growing concern for EV charging station load prediction for the purpose of comprehensively evaluating the influence of the charging load on distribution networks. To address this issue, an EV charging station load prediction method is proposed in coupled urban transportation and distribution networks. Firstly, a finer dynamic urban transportation network model is formulated considering both nodal and path resistance. Then, a finer EV power consumption model is proposed by considering the influence of traffic congestion and ambient temperature. Thirdly, the Monte Carlo method… More > Graphic Abstract

Jianhua Zhang^1,2, Wen Sun³, Zhijun Li^1,*

Energy Engineering, Vol.121, No.10, pp. 2893-2906, 2024, DOI:10.32604/ee.2024.051093 - 11 September 2024

Abstract Two types of tightly coupled Selective Catalytic Reduction (SCR) mixers were designed in this study, namely Mixer 1 integrated with an SCR catalyst and Mixer 2 arranged separately. Computational Fluid Dynamics (CFD) software was utilized to model the gas flow, spraying, and pyrolysis reaction of the aqueous urea solution in the tightly coupled SCR system. The parameters of gas flow velocity uniformity and ammonia distribution uniformity were simulated and calculated for both Mixer 1 and Mixer 2 in the tightly coupled SCR system to compare their advantages and disadvantages. The simulation results indicated that Mixer… More >

Haibo Wang¹, Hongwei Gao^1,*, Pai Jiang¹, Matthieu De Mari², Panzer Gu³, Yinsheng Liu¹

Journal on Internet of Things, Vol.6, pp. 17-41, 2024, DOI:10.32604/jiot.2024.054791 - 26 August 2024

Abstract In the 6G Internet of Things (IoT) paradigm, unprecedented challenges will be raised to provide massive connectivity, ultra-low latency, and energy efficiency for ultra-dense IoT devices. To address these challenges, we explore the non-orthogonal multiple access (NOMA) based grant-free random access (GFRA) schemes in the cellular uplink to support massive IoT devices with high spectrum efficiency and low access latency. In particular, we focus on optimizing the backoff strategy of each device when transmitting time-sensitive data samples to a multiple-input multiple-output (MIMO)-enabled base station subject to energy constraints. To cope with the dynamic varied channel… More >

Olga Vlasova^*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.9, pp. 2127-2137, 2024, DOI:10.32604/fdmp.2024.051202 - 23 August 2024

Abstract The dynamics of rotating hydrodynamic systems containing phase inclusions are interesting due to the related widespread occurrence in nature and technology. The influence of external force fields on rotating systems can be used to control the dynamics of inclusions of various types. Controlling inclusions is of current interest for space technologies. In low gravity, even a slight vibration effect can lead to the appearance of a force acting on phase inclusions near a solid boundary. When vibrations are applied to multiphase hydrodynamic systems, the oscillating body intensively interacts with the fluid and introduces changes in… More >

Kaiyong Hu^1,2,*, Zhaoyi Chen¹, Yunqing Hu¹, Huan Sun¹, Zhili Sun¹, Tonghua Zou^1,3, Jinghong Ning¹

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.9, pp. 2109-2126, 2024, DOI:10.32604/fdmp.2024.050773 - 23 August 2024

Abstract The current study focuses on spray cooling applied to the heat exchange components of a cooling tower. An optimization of such processes is attempted by assessing different spray flow rates and droplet sizes. For simplicity, the heat exchanger of the cooling tower is modeled as a horizontal round tube and a cooling tower spray cooling model is developed accordingly using a computational fluid dynamics (CFD) software. The study examines the influence of varying spray flow rates and droplet sizes on the heat flow intensity between the liquid layer on the surface of the cylindrical tube… More > Graphic Abstract

Lirong Yin¹, Lei Wang¹, Zhuohang Cai², Siyu Lu^2,*, Ruiyang Wang², Ahmed AlSanad³, Salman A. AlQahtani³, Xiaobing Chen⁴, Zhengtong Yin⁵, Xiaolu Li⁶, Wenfeng Zheng^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 771-786, 2024, DOI:10.32604/cmes.2024.052622 - 20 August 2024

Abstract Recent advancements in natural language processing have given rise to numerous pre-training language models in question-answering systems. However, with the constant evolution of algorithms, data, and computing power, the increasing size and complexity of these models have led to increased training costs and reduced efficiency. This study aims to minimize the inference time of such models while maintaining computational performance. It also proposes a novel Distillation model for PAL-BERT (DPAL-BERT), specifically, employs knowledge distillation, using the PAL-BERT model as the teacher model to train two student models: DPAL-BERT-Bi and DPAL-BERT-C. This research enhances the dataset More >

Ahmad Rahdari^1,6, Ahmad Jalili², Mehdi Esnaashari³, Mehdi Gheisari^1,4,7,8,*, Alisa A. Vorobeva⁵, Zhaoxi Fang¹, Panjun Sun^1,*, Viktoriia M. Korzhuk⁵, Ilya Popov⁵, Zongda Wu¹, Hamid Tahaei¹

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2511-2533, 2024, DOI:10.32604/cmc.2024.052994 - 15 August 2024

Abstract Software-Defined Networking (SDN) represents a significant paradigm shift in network architecture, separating network logic from the underlying forwarding devices to enhance flexibility and centralize deployment. Concurrently, the Internet of Things (IoT) connects numerous devices to the Internet, enabling autonomous interactions with minimal human intervention. However, implementing and managing an SDN-IoT system is inherently complex, particularly for those with limited resources, as the dynamic and distributed nature of IoT infrastructures creates security and privacy challenges during SDN integration. The findings of this study underscore the primary security and privacy challenges across application, control, and data planes.… More >