Bo Cao^1,*, Qinghua Xing², Longyue Li², Huaixi Xing¹, Zhanfu Song¹

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1251-1275, 2024, DOI:10.32604/cmc.2024.052842

Abstract As a core part of battlefield situational awareness, air target intention recognition plays an important role in modern air operations. Aiming at the problems of insufficient feature extraction and misclassification in intention recognition, this paper designs an air target intention recognition method (KGTLIR) based on Knowledge Graph and Deep Learning. Firstly, the intention recognition model based on Deep Learning is constructed to mine the temporal relationship of intention features using dilated causal convolution and the spatial relationship of intention features using a graph attention mechanism. Meanwhile, the accuracy, recall, and F1-score after iteration are introduced More >

Nisreen Innab¹, Ahmed Abdelgader Fadol Osman², Mohammed Awad Mohammed Ataelfadiel², Marwan Abu-Zanona^3,*, Bassam Mohammad Elzaghmouri⁴, Farah H. Zawaideh⁵, Mouiad Fadeil Alawneh⁶

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1325-1345, 2024, DOI:10.32604/cmc.2024.051778

Abstract Phishing, an Internet fraud where individuals are deceived into revealing critical personal and account information, poses a significant risk to both consumers and web-based institutions. Data indicates a persistent rise in phishing attacks. Moreover, these fraudulent schemes are progressively becoming more intricate, thereby rendering them more challenging to identify. Hence, it is imperative to utilize sophisticated algorithms to address this issue. Machine learning is a highly effective approach for identifying and uncovering these harmful behaviors. Machine learning (ML) approaches can identify common characteristics in most phishing assaults. In this paper, we propose an ensemble approach… More >

Shiming Lin^1,2,3, Ling Ye², Yijie Zhuang¹, Lingyun Lu^2,*, Shaoqiu Zheng^2,*, Chenxi Huang¹, Ng Yin Kwee⁴

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 299-317, 2024, DOI:10.32604/cmc.2024.051379

Abstract In recent years, with the continuous development of deep learning and knowledge graph reasoning methods, more and more researchers have shown great interest in improving knowledge graph reasoning methods by inferring missing facts through reasoning. By searching paths on the knowledge graph and making fact and link predictions based on these paths, deep learning-based Reinforcement Learning (RL) agents can demonstrate good performance and interpretability. Therefore, deep reinforcement learning-based knowledge reasoning methods have rapidly emerged in recent years and have become a hot research topic. However, even in a small and fixed knowledge graph reasoning action… More >

Phi-Hung Nguyen^*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1655-1675, 2024, DOI:10.32604/cmc.2024.050713

Abstract This study aims to establish an expert consensus and enhance the efficacy of decision-making processes by integrating Spherical Fuzzy Sets (SFSs) and Z-Numbers (SFZs). A novel group expert consensus technique, the PHI model, is developed to address the inherent limitations of both SFSs and the traditional Delphi technique, particularly in uncertain, complex scenarios. In such contexts, the accuracy of expert knowledge and the confidence in their judgments are pivotal considerations. This study provides the fundamental operational principles and aggregation operators associated with SFSs and Z-numbers, encompassing weighted geometric and arithmetic operators alongside fully developed operators… More >

Jiarui Zhang¹, Dan Liu^2,*, Kan Cao², Ping Xiong², Xiaotong Ji³, Yanze Xu¹, Yunfei Mu¹

Energy Engineering, Vol.121, No.8, pp. 2065-2083, 2024, DOI:10.32604/ee.2024.050342

Abstract The system performance of grid-connected photovoltaic (PV) has a serious impact on the grid stability. To improve the control performance and shorten the convergence time, a predefined-time controller based on backstepping technology and dynamic surface control is formulated for the inverter in the grid-connected photovoltaic. The time-varying tuning functions are introduced into state-tracking errors to realize the predefined-time control effect. To address the “computational explosion problem” in the design process of backstepping control, dynamic surface control is adopted to avoid the analytical calculations of virtual control. The disturbances of the PV system are estimated and More >

Chia-Nan Wang, Thuy-Duong Thi Pham^*, Nhat-Luong Nhieu

Energy Engineering, Vol.121, No.8, pp. 2039-2064, 2024, DOI:10.32604/ee.2024.050224

Abstract Geothermal energy is considered a renewable, environmentally friendly, especially carbon-free, sustainable energy source that can solve the problem of climate change. In general, countries with geothermal energy resources are the ones going through the ring of fire. Therefore, not every country is lucky enough to own this resource. As a country with 117 active volcanoes and within the world’s ring of fire, it is a country whose geothermal resources are estimated to be about 40% of the world’s geothermal energy potential. However, the percentage used compared to the geothermal potential is too small. Therefore, this… More >

Xujing Zhang¹, Hatem Abushammala², Debora Puglia³, Binbao Lu¹, Pengwu Xu¹, Weijun Yang^1,*, Piming Ma¹

Journal of Renewable Materials, Vol.12, No.5, pp. 895-908, 2024, DOI:10.32604/jrm.2024.049810

Abstract Fluorescent nanomaterials have attracted much attention, due to their unique luminescent properties and promising applications in biomedical areas. In this study, lignin based fluorescent nanoparticles (LFNP) with high yield (up to 32.4%) were prepared from lignin nanoparticles (LNP) by one-pot hydrothermal method with ethylenediamine (EDA) and citric acid. Morphology and chemical structure of LFNP were investigated by SEM, FT-IR, and zeta potential, and it was found that the structure of LFNP changed with the increase of citric acid addition. LFNP showed the highest fluorescence intensity under UV excitation at wavelengths of 375–385 nm, with emission More > Graphic Abstract

Retno Asih^1,*, Haniffudin Nurdiansah², Mochamad Zainuri¹, Deni S. Khaerudini^3,4, Angelinus T. Setiawan⁴, A. Y. Dias⁴, Pudji Untoro^4,5, Ahmad Sholih¹, Darminto^1,*

Journal of Renewable Materials, Vol.12, No.5, pp. 969-979, 2024, DOI:10.32604/jrm.2024.049097

Abstract Biomass has become of recent interest as a raw material for ‘green’ graphenic carbon (GC) since it promotes an environmentally friendly approach. Here, we investigate a single pyrolysis route to synthesize GC from coconut shells which provides a simple method and can produce a high yield, thus being convenient for large-scale production. The pyrolysis involves a stepped holding process at 350°C for 1 h and at 650°C or 900°C for 3 h. The GC sample resulted at the 900°C pyrolysis has a thinner sheet, a less porous structure, a higher C/O ratio, and an enhanced More > Graphic Abstract

DIMITRA P. VAGELI^1,2,*, PANAGIOTIS G. DOUKAS³, KERASIA GOUPOU², ANTONIOS D. BENOS², KYRIAKI ASTARA^2,4, KONSTANTINA ZACHAROULI², SOTIRIS SOTIRIOU⁵, MARIA IOANNOU²

Oncology Research, Vol.32, No.8, pp. 1239-1256, 2024, DOI:10.32604/or.2024.052130

Abstract Glioblastoma multiforme (GBM) is an aggressive primary brain tumor characterized by extensive heterogeneity and vascular proliferation. Hypoxic conditions in the tissue microenvironment are considered a pivotal player leading tumor progression. Specifically, hypoxia is known to activate inducible factors, such as hypoxia-inducible factor 1alpha (HIF-1α), which in turn can stimulate tumor neo-angiogenesis through activation of various downward mediators, such as the vascular endothelial growth factor (VEGF). Here, we aimed to explore the role of HIF-1α/VEGF immunophenotypes alone and in combination with other prognostic markers or clinical and image analysis data, as potential biomarkers of GBM prognosis… More >

ANA S. CVETANOVIC^1,2,*, MATTEO LAMBERTINI^3,4, KEVIN PUNIE⁵, GORANA G. MATOVINA BRKO⁶, NIKOLA D. ZIVKOVIC^7,8, MAJA J. POPOVIC^6,9, MARIJANA M. MILOVIC KOVACEVIC¹⁰, LAZAR S. POPOVIC^6,9

Oncology Research, Vol.32, No.8, pp. 1309-1322, 2024, DOI:10.32604/or.2024.049743

Abstract Oncofertility is an extremely significant topic that is increasingly being discussed owing to increased evidence indicating that fertility preservation does not affect the treatment outcomes of patients with cancer but significantly contributes to preserving life quality. The effect of chemotherapy can range from minimal effects to complete ovarian atrophy. Limited data are available on the effects of monoclonal antibodies and targeted therapies on the ovaries and fertility. Temporary ovarian suppression by administering a gonadotropin-releasing hormone agonist (GnRHa) during chemotherapy decreases the gonadotoxic effect of chemotherapy, thereby diminishing the chance of developing premature ovarian insufficiency (POI).… More > Graphic Abstract