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| 1 | Effects of Ti addition on low carbon hot strips produced by CSP process显示文摘Large quantity of fine Ti(C,N) particles, 15-30 nm in size, were observed in low carbon hot strips added to a small amount of Ti and produced by CSP process. The results showed that the precipitation of Ti(C,N) mostly took place during soaking and hot rolling, which is significantly different from that in the conventional production. These fine Ti carbonitride particles could be very effective on the austenite grain refinement by hindering grain growth of recrystallized austenite. Their precipitation behavior was discussed and compared with that of the steels produced in the conventional production. | Mingzhuo Bai Delu Liu Yanzhi Lou Xinping Mao Liejun Li Xiangdong Huo | 2006 | Journal of University of Science and Technology Beijing2006，13，3： | 4 |
| 2 | Ethnobotanical study on medicinal plants from the Dragon Boat Festival herbal markets of Qianxinan, southwestern Guizhou, China显示文摘Dragon Boat Festival herbal markets in the Qianxinan Buyi and Miao Autonomous Prefecture of southwestern Guizhou have a long well-conserved history.These markets,which are a feature of Buyi and Miao traditional medicines,contain a rich diversity of medicinal plants and traditional medical knowledge.Today,people in southwestern Guizhou still believe that using herbs during the Dragon Boat Festival prevents and can treat disease.In this study,we identified the fresh herbal plants sold at the herbal markets of Xingren City and Zhenfeng County in Qianxinan Buyi and Miao Autonomous Prefecture and quantified their importance.We identified 141 plant species(belonging to 114 genera and 61 families).The plant family with the most species was Asteraceae(14 species).Informants reported that most medicinal plants are herbaceous,with 95.7%of plants used for decoction and 30.5%used for medicinal baths.Medicinal plants are most commonly used to treat rheumatism,injury,and abdominal diseases.The utilization frequency index and relative importance values indicated that Artemisia argyi and Acorus calamus are the most important plants sold at herbal markets during the Dragon Boat Festival.The price of medicinal materials sold in the market may serve as an indicator of the conservation status of species in the region.These findings indicate that the Dragon Boat Festival herbal markets in the Qianxinan Buyi and Miao Autonomous Prefecture fully embodies the characteristics of indigenous ethnomedicine and culture,and also exhibits the diversity of plant resources.We recommend that rare and endangered plants in this region be domesticated and protected. | Wei Gu Xiaojiang Hao Zehuan Wang Jiayu Zhang Liejun Huang Shengji Pei | 2020 | Plant Diversity2020，42，6： | 1 |
| 3 | Tidal energy fluxes and dissipation in the Chesapeake Bay 显示文摘 | Zhong Liejun Li Ming | 2006 | Continental Shelf Research2006，26，6： | 1 |
| 4 | Oscillation criteria for impulsive parabolic boundary value problem with delay显示文摘 | Xilin Fu LieJune Shiau | 2003 | Applied Mathematics and Computation2003，，2： | 1 |
| 5 | Facial expression recognition using improved Support Vector Machine by modifying kernels显示文摘 | W Liejun Q Xizhong Z Taiyi | 2009 | Infor- mation Technology Journal2009，8，4： | 1 |
| 6 | A novel high-strength Al-La-Mg-Mn alloy for selective laser melting显示文摘Developing high-strength Al-(La,Ce)alloys for additive manufacturing(AM)would entail considerable economic benefits.In this work,a novel near-eutectic Al-La alloy containing 5.50 wt.%Mg and 0.60 wt.%Mn was designed and fabricated via selective laser melting(SLM).Submicron Al_(11)La_(3)intermetallics with 3D continuous cellular-dendritic and granular morphologies were observed at the interior and boundary of the melt pool,respectively.Interestingly,these intermetallics are hierarchical and contained numerous Al_(6)Mn and Mg_(2)Si secondary nanoprecipitates.The as-fabricated alloy exhibited a tensile yield strength(YS)of 334 MPa and ultimate tensile strength(UTS)of 588 MPa at room temperature,which is the high-est UTS reported for Al-(La,Ce)alloys with an appreciable failure strain of∼6.4%.The 3D continuous cellular dendritic intermetallic and high Mg content afford significant strengthening and work harden-ing ability.In addition,the hierarchical feature of the intermetallics generated additional microcracks to coordinate the deformation. | Xinkui Zhang Liejun Li Zhi Wang Hanlin Peng Jixiang Gao Zhengwu Peng | 2023 | Journal of Materials Science & Technology2023，，6： | 1 |
| 7 | Facial expression recognition using improved support vector machine by modifying kernels 显示文摘 | Liejun W Xizhong Q Taiyi Z | 2009 | Information Technology Journal2009，8，4： | 1 |
| 8 | Divergent effects of prostaglandin receptor signaling on neuronal survival显示文摘 | Liejun Wu Qian Wang Xibin Liang Katrin Andreasson | 2007 | Neuroscience Letters2007，，3： | 1 |
| 9 | Multiuser MIMO OFDM Based TDD/TDMA for Next Generation Wireless Communication Systems显示文摘 | Lu Zhaogan Rao Yuan Zhang Taiyi Wang Liejun | 2010 | Wireless Personal Communications2010，52，2： | 1 |
| 10 | GRATDet:Smart Contract Vulnerability Detector Based on Graph Representation and Transformer显示文摘Smart contracts have led to more efficient development in finance and healthcare,but vulnerabilities in contracts pose high risks to their future applications.The current vulnerability detection methods for contracts are either based on fixed expert rules,which are inefficient,or rely on simplistic deep learning techniques that do not fully leverage contract semantic information.Therefore,there is ample room for improvement in terms of detection precision.To solve these problems,this paper proposes a vulnerability detector based on deep learning techniques,graph representation,and Transformer,called GRATDet.The method first performs swapping,insertion,and symbolization operations for contract functions,increasing the amount of small sample data.Each line of code is then treated as a basic semantic element,and information such as control and data relationships is extracted to construct a new representation in the form of a Line Graph(LG),which shows more structural features that differ from the serialized presentation of the contract.Finally,the node information and edge information of the graph are jointly learned using an improved Transformer-GP model to extract information globally and locally,and the fused features are used for vulnerability detection.The effectiveness of the method in reentrancy vulnerability detection is verified in experiments,where the F1 score reaches 95.16%,exceeding stateof-the-art methods. | Peng Gong Wenzhong Yang Liejun Wang Fuyuan Wei KeZiErBieKe HaiLaTi Yuanyuan Liao | 2023 | Computers, Materials & Continua2023，76，8： | 0 |
| 11 | The Detection of Fraudulent Smart Contracts Based on ECA-EfficientNet and Data Enhancement显示文摘With the increasing popularity of Ethereum,smart contracts have become a prime target for fraudulent activities such as Ponzi,honeypot,gambling,and phishing schemes.While some researchers have studied intelligent fraud detection,most research has focused on identifying Ponzi contracts,with little attention given to detecting and preventing gambling or phishing contracts.There are three main issues with current research.Firstly,there exists a severe data imbalance between fraudulent and non-fraudulent contracts.Secondly,the existing detection methods rely on diverse raw features that may not generalize well in identifying various classes of fraudulent contracts.Lastly,most prior studies have used contract source code as raw features,but many smart contracts only exist in bytecode.To address these issues,we propose a fraud detection method that utilizes Efficient Channel Attention EfficientNet(ECA-EfficientNet)and data enhancement.Our method begins by converting bytecode into Red Green Blue(RGB)three-channel images and then applying channel exchange data enhancement.We then use the enhanced ECA-EfficientNet approach to classify fraudulent smart contract RGB images.Our proposed method achieves high F1-score and Recall on both publicly available Ponzi datasets and self-built multi-classification datasets that include Ponzi,honeypot,gambling,and phishing smart contracts.The results of the experiments demonstrate that our model outperforms current methods and their variants in Ponzi contract detection.Our research addresses a significant problem in smart contract security and offers an effective and efficient solution for detecting fraudulent contracts. | Xuanchen Zhou Wenzhong Yang Liejun Wang Fuyuan Wei KeZiErBieKe HaiLaTi Yuanyuan Liao | 2023 | Computers, Materials & Continua2023，77，12： | 0 |
| 12 | DFE-GCN: Dual Feature Enhanced Graph Convolutional Network for Controversy Detection显示文摘With the development of social media and the prevalence of mobile devices,an increasing number of people tend to use social media platforms to express their opinions and attitudes,leading to many online controversies.These online controversies can severely threaten social stability,making automatic detection of controversies particularly necessary.Most controversy detection methods currently focus on mining features from text semantics and propagation structures.However,these methods have two drawbacks:1)limited ability to capture structural features and failure to learn deeper structural features,and 2)neglecting the influence of topic information and ineffective utilization of topic features.In light of these phenomena,this paper proposes a social media controversy detection method called Dual Feature Enhanced Graph Convolutional Network(DFE-GCN).This method explores structural information at different scales from global and local perspectives to capture deeper structural features,enhancing the expressive power of structural features.Furthermore,to strengthen the influence of topic information,this paper utilizes attention mechanisms to enhance topic features after each graph convolutional layer,effectively using topic information.We validated our method on two different public datasets,and the experimental results demonstrate that our method achieves state-of-the-art performance compared to baseline methods.On the Weibo and Reddit datasets,the accuracy is improved by 5.92%and 3.32%,respectively,and the F1 score is improved by 1.99%and 2.17%,demonstrating the positive impact of enhanced structural features and topic features on controversy detection. | Chengfei Hua Wenzhong Yang Liejun Wang Fuyuan Wei KeZiErBieKe HaiLaTi Yuanyuan Liao | 2023 | Computers, Materials & Continua2023，77，10： | 0 |
| 13 | MULTI-RESOLUTION LEAST SQUARES SUPPORT VECTOR MACHINES显示文摘The Least Squares Support Vector Machines (LS-SVM) is an improvement to the SVM. Combined the LS-SVM with the Multi-Resolution Analysis (MRA),this letter proposes the Multi-resolution LS-SVM (MLS-SVM).The proposed algorithm has the same theoretical framework as MRA but with better approximation ability.At a fixed scale MLS-SVM is a classical LS-SVM,but MLS-SVM can gradually approximate the target function at different scales.In experiments,the MLS-SVM is used for nonlinear system identification,and achieves better identification accuracy. | Wang Liejun Zhang Taiyi Zhou Yatong | 2007 | Journal of Electronics(China)2007，24，5： | 0 |
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