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Effects of Standing Time during Pretreatment on the Nitrite Concentration Detected by Spectrophotometric Method
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作者 Yingfei Zeng Juan Hu +2 位作者 Xianglong Bian Qianfeng Xia Tingwei Hu 《Journal of Materials Science and Chemical Engineering》 2024年第2期73-83,共11页
Food safety problems caused by excessive nitrite addition have been frequently reported and the detection of nitrite in food is particularly important. The standing time during the pretreatment of primary sample has a... Food safety problems caused by excessive nitrite addition have been frequently reported and the detection of nitrite in food is particularly important. The standing time during the pretreatment of primary sample has a great influence on the concentration of nitrite tested by spectrophotometric method. In this context, three kinds of food samples are prepared, including canned mustard, canned fish and home-made pickled water. A series of standing times are placed during the sample pretreatments and the corresponding nitrite contents in these samples are detected by spectrophotometric method based on N-ethylenediamine dihydrochloride. This study aims to find out a reasonable standing time during the pretreatment of food sample, providing influence factor for precise detection of nitrite. 展开更多
关键词 Standing Time Spectrophotometric Method Nitrite Detection
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A study of the strong pulses detected from PSR B0656+14 using the Urumqi 25-m radio telescope at 1540 MHz 被引量:2
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作者 Guo-Cun Tao Ali Esamdin +3 位作者 Hui-Dong Hu Mao-Fei Qian Jing Li Na Wang 《Research in Astronomy and Astrophysics》 SCIE CAS CSCD 2012年第12期1649-1654,共6页
We report on the properties of strong pulses from PSR B0656+14 by analyzing the data obtained using the Urumqi 25-m radio telescope at 1540 MHz from August 2007 to September 2010.In 44 h of observational data,a total... We report on the properties of strong pulses from PSR B0656+14 by analyzing the data obtained using the Urumqi 25-m radio telescope at 1540 MHz from August 2007 to September 2010.In 44 h of observational data,a total of 67 pulses with signal-to-noise ratios above a 5σthreshold were detected.The peak flux densities of these pulses are 58 to 194 times that of the average profile,and their pulse energies are 3 to 68 times that of the average pulse.These pulses are clustered around phases about 5-ahead of the peak of the average profile.Compared with the width of the average profile,they are relatively narrow,with the full widths at half-maximum ranging from 0.28 ° to 1.78 °.The distribution of pulse-energies follows a lognormal distribution.These sporadic strong pulses detected from PSR B0656+14 have different characteristics from both typical giant pulses and its regular pulses. 展开更多
关键词 stars:neutron-pulsars-pulsars:individual(B0656+14)Options: Encrypt Page Allow Cookies Remove Scripts Remove Objects 收藏本站首页期刊全文库学位论文库会议论文库学术百科吾喜杂志工具书优先出版注册|登录|我的账户基础科学|工程科技I辑|工程科技II辑|医药卫生科技|信息科技|农业科技|哲学与人文科学|社会科学I辑|社会科学II辑|经济管理高级搜索: 用" stars neutron-pulsars—pulsars "到知网平台检索 点击这里搜索更多...《Research in Astronomy and Astrophysics》 2012年12期 加入收藏 获取最新 A study of the strong pulses detected from PSR B0656+14 using the Urumqi 25-m radio telescope at 1540 MHzAli Esamdin 【摘要】: We report on the properties of strong pulses from PSR B0656+14 by analyzing the data obtained using the Urumqi 25-m radio telescope at 1540 MHz from August 2007 to September 2010.In 44 h of observational data a total of 67 pulses with signal-to-noise ratios above a 5σthreshold were detected.The peak flux densities of these pulses are 58 to 194 times that of the average profile and their pulse energies are 3 to 68 times that of the average pulse.These pulses are clustered around phases about 5-ahead of the peak of the average profile.Compared with the width of the average profile they are relatively narrow with the full widths at half-maximum ranging from 0.28 ° to 1.78 °.The distribution of pulse-energies follows a lognormal distribution.These sporadic strong pulses detected from PSR B0656+14 have different characteristics from both typical giant pulses and its regular pulses.【作者单位】 Xinjiang
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TOPOLOGICAL STRUCTURE OF THE SINGULAR POINTS OF THE THIRD ORDER PHASE LOCKED LOOP EQUATIONS WITH THE CHARACTER OF DETECTED PHASE BEING g(φ)=(1+k)sinφ/(1+kcosφ)
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作者 金均 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 1992年第9期883-889,共7页
In this paper, we study the topological structure of the singular points of the third order phase locked loop equations with the character of detected phase being g(?) =(1+k)sin?/1+kcos?.
关键词 singular point topological structure character of detected phase exponentially asymptotically stable Jordan form
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Quantum Spin Liquid Phase in the Shastry–Sutherland Model Detected by an Improved Level Spectroscopic Method
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作者 Ling Wang Yalei Zhang Anders W.Sandvik 《Chinese Physics Letters》 SCIE EI CAS CSCD 2022年第7期105-116,共12页
We study the spin-1/2 two-dimensional Shastry–Sutherland spin model by exact diagonalization of clusters with periodic boundary conditions, developing an improved level spectroscopic technique using energy gaps betwe... We study the spin-1/2 two-dimensional Shastry–Sutherland spin model by exact diagonalization of clusters with periodic boundary conditions, developing an improved level spectroscopic technique using energy gaps between states with different quantum numbers. The crossing points of some of the relative(composite) gaps have much weaker finite-size drifts than the normally used gaps defined only with respect to the ground state, thus allowing precise determination of quantum critical points even with small clusters. Our results support the picture of a spin liquid phase intervening between the well-known plaquette-singlet and antiferromagnetic ground states, with phase boundaries in almost perfect agreement with a recent density matrix renormalization group study, where much larger cylindrical lattices were used [J. Yang et al., Phys. Rev. B 105, L060409(2022)]. The method of using composite low-energy gaps to reduce scaling corrections has potentially broad applications in numerical studies of quantum critical phenomena. 展开更多
关键词 red SSM Sutherland Model detected by an Improved Level Spectroscopic Method Quantum Spin Liquid Phase in the Shastry Model
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Analysis of Detected Avalanches Using Meteorological Data of Nearby Monitoring Stations in Ischgl, Austria
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作者 Lisa Jobstl Arnold Studeregger +2 位作者 Amulf Wurzer Daniel Stock Richard Koschuh 《Journal of Environmental Science and Engineering(B)》 2014年第2期87-90,共4页
A set of detected avalanches from January to April 2012 on a hillside southeast of lschgl, Austria is given. The avalanches are off-the-cut or caused by blast. The meteorological data of two monitoring stations nearby... A set of detected avalanches from January to April 2012 on a hillside southeast of lschgl, Austria is given. The avalanches are off-the-cut or caused by blast. The meteorological data of two monitoring stations nearby the hillside are taken for analysing the weather situation. The meteorological parameters air temperature, wind intensity and wind speed, relative humidity, precipitation and snow depth are investigated for similarities short before and during an avalanche. The avalanches are grouped into three categories and meteorological characteristics are found for each category. Thereby the avalanche hazard for the observed hillside is better assessed and an infrastructure safety by avalanche control due to concerted avalanche blasts is more effective. The result of the analysis shows three kinds of hazard weather conditions, which increase the avalanche hazard: warm air temperatures cause a settlement of the snow pack, but in the beginning of the process a weakening in the snow pack happens. Rapidly decreasing of the air temperature cause cracks in the snow pack and the combination of fresh snow and strong wind speed leads to accumulation of snow on sheltered slopes. 展开更多
关键词 detected avalanches meteorological weather stations avalanche danger snow pack
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Iron-Mediated Oxidative DNA Damage Detected by Fluorometric Analysis of DNA Unwinding in Isolated Rat Liver Nuclei
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作者 SAURA C.SAHU MELISSA C.WASHINGTON 《Biomedical and Environmental Sciences》 SCIE CAS CSCD 1991年第3期232-241,共10页
Studies were performed to determine the extent of nuclear DNA degradation induced by iron, iron-ascorbate, or iron-bleomycin under aerobic conditions in a model system using isolated rat liver nuclei. The effects of f... Studies were performed to determine the extent of nuclear DNA degradation induced by iron, iron-ascorbate, or iron-bleomycin under aerobic conditions in a model system using isolated rat liver nuclei. The effects of five antioxidants (catalase, superoxide dismutase, dimethyl sulfoxide, glutathione and diallyl sulfide) on this oxidative nuclear damage were also investigated. At the 0.05 level for statistical significance, iron induced concentration-dependent DNA degradation, and this effect was enhanced by ascorbate and bleomycin. The antioxidants catalase, dimethyl sulfoxide, and diallyl sulfide significantly reduced the iron-ascorbate-induced DNA damage, whereas superoxide dismutase and dimethyl sulfoxide significantly reduced iron-bleomycin-induced damage. Glutathione significantly increased the iron-bleomycin-induced DNA damage. These results suggest that the reactive oxygen species generated by iron, iron-ascorbate, and iron-bleomycin are responsible for the DNA strand breaks in isolated rat liver nuclei. 展开更多
关键词 Iron-Mediated Oxidative DNA Damage detected by Fluorometric Analysis of DNA Unwinding in Isolated Rat Liver Nuclei DNA
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Super Large-scaled Bauxite Deposit Detected in Guizhou Province
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《China's Refractories》 CAS 2013年第3期11-11,共1页
Recently, the Bureau of Geology and Mineral Exploration and Development of Guizhou Province detected an about 140 million tons resource in Zheng'an County, 100 million tons of which was bauxite. This is the second de... Recently, the Bureau of Geology and Mineral Exploration and Development of Guizhou Province detected an about 140 million tons resource in Zheng'an County, 100 million tons of which was bauxite. This is the second detected super large-scaled bauxite deposit after the Dazhuyuan bauxite deposit in Wuchuan County. 展开更多
关键词 Super Large-scaled Bauxite Deposit detected in Guizhou Province
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Is every microorganism detected in the intensive care unit a nosocomial infection?Isn’t prevention more important than detection? 被引量:1
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作者 Fatma Yildirim Irem Karaman Mehmet Yildirim 《World Journal of Clinical Cases》 SCIE 2022年第20期7184-7186,共3页
The present letter to the editor is related to the study entitled“Multidrug-resistant organisms in intensive care units and logistic analysis of risk factors.”Not every microorganism grown in samples taken from crit... The present letter to the editor is related to the study entitled“Multidrug-resistant organisms in intensive care units and logistic analysis of risk factors.”Not every microorganism grown in samples taken from critically ill patients can be considered as an infectious agent.Accurate and adequate information about nosocomial infections is essential in introducing effective prevention programs in hospitals.Therefore,the development and implementation of care bundles for frequently used medical devices and invasive treatment devices(e.g.,intravenous catheters and invasive ventilation),adequate staffing not only for physicians,nurses,and other medical staff but also for housekeeping staff,and infection surveillance and motivational feedback are key points of infection prevention in the intensive care unit. 展开更多
关键词 Critical care PREVENTION Intensive care unit Nosocomial infection DETECTION
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Reconstruction of vector static magnetic field by different axial NV centers using continuous wave optically detected magnetic resonance in diamond
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作者 Jian-Feng Ye Zheng Jiao +3 位作者 Kun Ma Zhi-Yong Huang Hai-Jiang Lv Feng-Jian Jiang 《Chinese Physics B》 SCIE EI CAS CSCD 2019年第4期337-341,共5页
We carried out a proof-of-principle demonstration of the reconstruction of a static vector magnetic field involving adjacent three nitrogen-vacancy(NV) sensors with corresponding different NV symmetry axes in a bulk d... We carried out a proof-of-principle demonstration of the reconstruction of a static vector magnetic field involving adjacent three nitrogen-vacancy(NV) sensors with corresponding different NV symmetry axes in a bulk diamond. By means of optical detection of the magnetic resonance(ODMR) techniques, our experiment employs the continuous wave(CW) to monitor resonance frequencies and it extracts the information of the detected field strength and polar angles with respect to each NV frame of reference. Finally, the detected magnetic field relative to a fixed laboratory reference frame was reconstructed from the information acquired by the multi-NV sensor. 展开更多
关键词 DIAMOND defect optical detection magnetic resonance MAGNETOMETER
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Ocular surface heat effects on ocular hemodynamics detected by real-time measuring device
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作者 Ting-Ting Li Guang-Bin Shao +4 位作者 Yu-Long Jiang Jing-Xuan Wang Xin-Rong Zhou Min Ren Long-Qiu Li 《International Journal of Ophthalmology(English edition)》 SCIE CAS 2018年第12期1902-1908,共7页
AIM: To investigate the ocular hemodynamic effects of applying a hot compress to the eye.METHODS: The right eyes of five New Zealand white rabbits, both male and female, were hot-compressed for 18 min. An independentl... AIM: To investigate the ocular hemodynamic effects of applying a hot compress to the eye.METHODS: The right eyes of five New Zealand white rabbits, both male and female, were hot-compressed for 18 min. An independently designed novel ocular contacttype temperature measuring device was used to measure the ocular surface temperature before and after the heating. Relevant retrobulbar hemodynamic parameters such as peak systolic velocity(PSV), end diastolic velocity(EDV), and resistance index(RI) of each of the central retinal artery(CRA), long posterior ciliary artery(LPCA), and ophthalmic artery(OA), as well as the mean velocity(V_m) of the central retinal vein(CRV), were measured using a color Doppler flow imaging(CDFI) technique and expressed as mean values with standard deviation(mean±SD). A statistical analysis was conducted based on a paired t-test and the Wilcoxon signed-rank test. RESULTS: The employed real-time temperature measuring device was able to accurately measure ocular surface temperature during the hot-compress process. The temperature increased after the hot compress was applied. Analysis showed that the PSV and EDV values of the CRA and LPCA significantly increased after the application of the hot compress, as did the V_m of the CRV. There were no significant changes in the EDV of the OA nor the RI of each artery. CONCLUSION: This experiment, which is the first of its kind, confirms that the retrobulbar blood flow velocities can increase upon heating the ocular surface. This simple method may be useful in the future. 展开更多
关键词 ocular hemodynamics ocular surface heating temperature detection device color Doppler flow imaging
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Structural Mechanics Analysis Using an FE-Mesh Adaption to Real, 3D Surface Detected Geometry Data
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作者 Sebastian Katona Michael Koch +1 位作者 Tobias C. Spruegel Sandro Wartzack 《Journal of Mechanics Engineering and Automation》 2015年第7期387-394,共8页
Within today's product development process, various FE-simulations (finite element) for the functional validation of the desired characteristics are made to avoid expensive testing with real components. Those simul... Within today's product development process, various FE-simulations (finite element) for the functional validation of the desired characteristics are made to avoid expensive testing with real components. Those simulations are performed with great effort for discretization, use of simulations conditions, like taking different non-linearities (i.e., material behavior, etc.) into account, to create meaningful results. Despite knowing the effects of deformations occurring during the production processes, always the non-deformed design model of a CAD-system (computer aided design) is used for the FE-simulations. It seems rather doubtful that further refinement of simulation methods makes sense, if the real manufactured geometry of the component is not considered for in the simulation. For an efficient exploit of the potential of simulation methods, an approach has been developed which offers a geometry model for simulation based on the existing CAD-model but with integrated production deviations as soon as a first prototype is at hand by adapting the FE-mesh to the real, 3D surface detected geometry. 展开更多
关键词 FEA (finite element analysis) PREPROCESSING simulation 3D surface detection RE (reverse engineering)
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基于改进Detection Transformer的棉花幼苗与杂草检测模型研究
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作者 冯向萍 杜晨 +3 位作者 李永可 张世豪 舒芹 赵昀杰 《计算机与数字工程》 2024年第7期2176-2182,共7页
基于深度学习的目标检测技术在棉花幼苗与杂草检测领域已取得一定进展。论文提出了基于改进Detection Transformer的棉花幼苗与杂草检测模型,以提高杂草目标检测的准确率和效率。首先,引入了可变形注意力模块替代原始模型中的Transforme... 基于深度学习的目标检测技术在棉花幼苗与杂草检测领域已取得一定进展。论文提出了基于改进Detection Transformer的棉花幼苗与杂草检测模型,以提高杂草目标检测的准确率和效率。首先,引入了可变形注意力模块替代原始模型中的Transformer注意力模块,提高模型对特征图目标形变的处理能力。提出新的降噪训练机制,解决了二分图匹配不稳定问题。提出混合查询选择策略,提高解码器对目标类别和位置信息的利用效率。使用Swin Transformer作为网络主干,提高模型特征提取能力。通过对比原网络,论文提出的模型方法在训练过程中表现出更快的收敛速度,并且在准确率方面提高了6.7%。 展开更多
关键词 目标检测 Detection Transformer 棉花幼苗 杂草检测
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Vector magnetometry in zero bias magnetic field using nitrogen-vacancy ensembles
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作者 Chunxing Li Fa-Zhan Shi +1 位作者 Jingwei Zhou Peng-Fei Wang 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第10期21-29,共9页
The application of the vector magnetometry based on nitrogen-vacancy(NV)ensembles has been widely investigatedin multiple areas.It has the superiority of high sensitivity and high stability in ambient conditions with ... The application of the vector magnetometry based on nitrogen-vacancy(NV)ensembles has been widely investigatedin multiple areas.It has the superiority of high sensitivity and high stability in ambient conditions with microscale spatialresolution.However,a bias magnetic field is necessary to fully separate the resonance lines of optically detected magneticresonance(ODMR)spectrum of NV ensembles.This brings disturbances in samples being detected and limits the rangeof application.Here,we demonstrate a method of vector magnetometry in zero bias magnetic field using NV ensembles.By utilizing the anisotropy property of fluorescence excited from NV centers,we analyzed the ODMR spectrum of NVensembles under various polarized angles of excitation laser in zero bias magnetic field with a quantitative numerical modeland reconstructed the magnetic field vector.The minimum magnetic field modulus that can be resolved accurately is downto~0.64 G theoretically depending on the ODMR spectral line width(1.8 MHz),and~2 G experimentally due to noisesin fluorescence signals and errors in calibration.By using 13C purified and low nitrogen concentration diamond combinedwith improving calibration of unknown parameters,the ODMR spectral line width can be further decreased below 0.5 MHz,corresponding to~0.18 G minimum resolvable magnetic field modulus. 展开更多
关键词 vector magnetometry NV ensembles optically detected magnetic resonance(ODMR) zero bias magnetic field
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IDS-INT:Intrusion detection system using transformer-based transfer learning for imbalanced network traffic 被引量:3
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作者 Farhan Ullah Shamsher Ullah +1 位作者 Gautam Srivastava Jerry Chun-Wei Lin 《Digital Communications and Networks》 SCIE CSCD 2024年第1期190-204,共15页
A network intrusion detection system is critical for cyber security against llegitimate attacks.In terms of feature perspectives,network traffic may include a variety of elements such as attack reference,attack type,a... A network intrusion detection system is critical for cyber security against llegitimate attacks.In terms of feature perspectives,network traffic may include a variety of elements such as attack reference,attack type,a subcategory of attack,host information,malicious scripts,etc.In terms of network perspectives,network traffic may contain an imbalanced number of harmful attacks when compared to normal traffic.It is challenging to identify a specific attack due to complex features and data imbalance issues.To address these issues,this paper proposes an Intrusion Detection System using transformer-based transfer learning for Imbalanced Network Traffic(IDS-INT).IDS-INT uses transformer-based transfer learning to learn feature interactions in both network feature representation and imbalanced data.First,detailed information about each type of attack is gathered from network interaction descriptions,which include network nodes,attack type,reference,host information,etc.Second,the transformer-based transfer learning approach is developed to learn detailed feature representation using their semantic anchors.Third,the Synthetic Minority Oversampling Technique(SMOTE)is implemented to balance abnormal traffic and detect minority attacks.Fourth,the Convolution Neural Network(CNN)model is designed to extract deep features from the balanced network traffic.Finally,the hybrid approach of the CNN-Long Short-Term Memory(CNN-LSTM)model is developed to detect different types of attacks from the deep features.Detailed experiments are conducted to test the proposed approach using three standard datasets,i.e.,UNsWNB15,CIC-IDS2017,and NSL-KDD.An explainable AI approach is implemented to interpret the proposed method and develop a trustable model. 展开更多
关键词 Network intrusion detection Transfer learning Features extraction Imbalance data Explainable AI CYBERSECURITY
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Esophageal cancer screening,early detection and treatment:Current insights and future directions 被引量:3
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作者 Hong-Tao Qu Qing Li +7 位作者 Liang Hao Yan-Jing Ni Wen-Yu Luan Zhe Yang Xiao-Dong Chen Tong-Tong Zhang Yan-Dong Miao Fang Zhang 《World Journal of Gastrointestinal Oncology》 SCIE 2024年第4期1180-1191,共12页
Esophageal cancer ranks among the most prevalent malignant tumors globally,primarily due to its highly aggressive nature and poor survival rates.According to the 2020 global cancer statistics,there were approximately ... Esophageal cancer ranks among the most prevalent malignant tumors globally,primarily due to its highly aggressive nature and poor survival rates.According to the 2020 global cancer statistics,there were approximately 604000 new cases of esophageal cancer,resulting in 544000 deaths.The 5-year survival rate hovers around a mere 15%-25%.Notably,distinct variations exist in the risk factors associated with the two primary histological types,influencing their worldwide incidence and distribution.Squamous cell carcinoma displays a high incidence in specific regions,such as certain areas in China,where it meets the cost-effect-iveness criteria for widespread endoscopy-based early diagnosis within the local population.Conversely,adenocarcinoma(EAC)represents the most common histological subtype of esophageal cancer in Europe and the United States.The role of early diagnosis in cases of EAC originating from Barrett's esophagus(BE)remains a subject of controversy.The effectiveness of early detection for EAC,particularly those arising from BE,continues to be a debated topic.The variations in how early-stage esophageal carcinoma is treated in different regions are largely due to the differing rates of early-stage cancer diagnoses.In areas with higher incidences,such as China and Japan,early diagnosis is more common,which has led to the advancement of endoscopic methods as definitive treatments.These techniques have demonstrated remarkable efficacy with minimal complications while preserving esophageal functionality.Early screening,prompt diagnosis,and timely treatment are key strategies that can significantly lower both the occurrence and death rates associated with esophageal cancer. 展开更多
关键词 Esophageal cancer SCREENING Early detection Treatment Endoscopic mucosal resection Endoscopic submucosal dissection
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A Hybrid Intrusion Detection Method Based on Convolutional Neural Network and AdaBoost 被引量:1
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作者 Wu Zhijun Li Yuqi Yue Meng 《China Communications》 SCIE CSCD 2024年第11期180-189,共10页
To solve the problem of poor detection and limited application range of current intrusion detection methods,this paper attempts to use deep learning neural network technology to study a new type of intrusion detection... To solve the problem of poor detection and limited application range of current intrusion detection methods,this paper attempts to use deep learning neural network technology to study a new type of intrusion detection method.Hence,we proposed an intrusion detection algorithm based on convolutional neural network(CNN)and AdaBoost algorithm.This algorithm uses CNN to extract the characteristics of network traffic data,which is particularly suitable for the analysis of continuous and classified attack data.The AdaBoost algorithm is used to classify network attack data that improved the detection effect of unbalanced data classification.We adopt the UNSW-NB15 dataset to test of this algorithm in the PyCharm environment.The results show that the detection rate of algorithm is99.27%and the false positive rate is lower than 0.98%.Comparative analysis shows that this algorithm has advantages over existing methods in terms of detection rate and false positive rate for small proportion of attack data. 展开更多
关键词 ADABOOST CNN detection rate false positive rate feature extraction intrusion detection
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Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features 被引量:1
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作者 Asifa Mehmood Qureshi Naif Al Mudawi +2 位作者 Mohammed Alonazi Samia Allaoua Chelloug Jeongmin Park 《Computers, Materials & Continua》 SCIE EI 2024年第3期3683-3701,共19页
Road traffic monitoring is an imperative topic widely discussed among researchers.Systems used to monitor traffic frequently rely on cameras mounted on bridges or roadsides.However,aerial images provide the flexibilit... Road traffic monitoring is an imperative topic widely discussed among researchers.Systems used to monitor traffic frequently rely on cameras mounted on bridges or roadsides.However,aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger area.To this end,different models have shown the ability to recognize and track vehicles.However,these methods are not mature enough to produce accurate results in complex road scenes.Therefore,this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image bursts.The extracted frames were converted to grayscale,followed by the application of a georeferencing algorithm to embed coordinate information into the images.The masking technique eliminated irrelevant data and reduced the computational cost of the overall monitoring system.Next,Sobel edge detection combined with Canny edge detection and Hough line transform has been applied for noise reduction.After preprocessing,the blob detection algorithm helped detect the vehicles.Vehicles of varying sizes have been detected by implementing a dynamic thresholding scheme.Detection was done on the first image of every burst.Then,to track vehicles,the model of each vehicle was made to find its matches in the succeeding images using the template matching algorithm.To further improve the tracking accuracy by incorporating motion information,Scale Invariant Feature Transform(SIFT)features have been used to find the best possible match among multiple matches.An accuracy rate of 87%for detection and 80%accuracy for tracking in the A1 Motorway Netherland dataset has been achieved.For the Vehicle Aerial Imaging from Drone(VAID)dataset,an accuracy rate of 86%for detection and 78%accuracy for tracking has been achieved. 展开更多
关键词 Unmanned Aerial Vehicles(UAV) aerial images DATASET object detection object tracking data elimination template matching blob detection SIFT VAID
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Automated Vulnerability Detection of Blockchain Smart Contacts Based on BERT Artificial Intelligent Model 被引量:1
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作者 Feng Yiting Ma Zhaofeng +1 位作者 Duan Pengfei Luo Shoushan 《China Communications》 SCIE CSCD 2024年第7期237-251,共15页
The widespread adoption of blockchain technology has led to the exploration of its numerous applications in various fields.Cryptographic algorithms and smart contracts are critical components of blockchain security.De... The widespread adoption of blockchain technology has led to the exploration of its numerous applications in various fields.Cryptographic algorithms and smart contracts are critical components of blockchain security.Despite the benefits of virtual currency,vulnerabilities in smart contracts have resulted in substantial losses to users.While researchers have identified these vulnerabilities and developed tools for detecting them,the accuracy of these tools is still far from satisfactory,with high false positive and false negative rates.In this paper,we propose a new method for detecting vulnerabilities in smart contracts using the BERT pre-training model,which can quickly and effectively process and detect smart contracts.More specifically,we preprocess and make symbol substitution in the contract,which can make the pre-training model better obtain contract features.We evaluate our method on four datasets and compare its performance with other deep learning models and vulnerability detection tools,demonstrating its superior accuracy. 展开更多
关键词 BERT blockchain smart contract vulnerability detection
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An Intelligent SDN-IoT Enabled Intrusion Detection System for Healthcare Systems Using a Hybrid Deep Learning and Machine Learning Approach 被引量:1
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作者 R Arthi S Krishnaveni Sherali Zeadally 《China Communications》 SCIE CSCD 2024年第10期267-287,共21页
The advent of pandemics such as COVID-19 significantly impacts human behaviour and lives every day.Therefore,it is essential to make medical services connected to internet,available in every remote location during the... The advent of pandemics such as COVID-19 significantly impacts human behaviour and lives every day.Therefore,it is essential to make medical services connected to internet,available in every remote location during these situations.Also,the security issues in the Internet of Medical Things(IoMT)used in these service,make the situation even more critical because cyberattacks on the medical devices might cause treatment delays or clinical failures.Hence,services in the healthcare ecosystem need rapid,uninterrupted,and secure facilities.The solution provided in this research addresses security concerns and services availability for patients with critical health in remote areas.This research aims to develop an intelligent Software Defined Networks(SDNs)enabled secure framework for IoT healthcare ecosystem.We propose a hybrid of machine learning and deep learning techniques(DNN+SVM)to identify network intrusions in the sensor-based healthcare data.In addition,this system can efficiently monitor connected devices and suspicious behaviours.Finally,we evaluate the performance of our proposed framework using various performance metrics based on the healthcare application scenarios.the experimental results show that the proposed approach effectively detects and mitigates attacks in the SDN-enabled IoT networks and performs better that other state-of-art-approaches. 展开更多
关键词 deep neural network healthcare intrusion detection system IOT machine learning software-defined networks
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Potential clinical application of microRNAs in bladder cancer 被引量:1
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作者 Pei Wang Xiaowei Wei +1 位作者 Xiaojun Qu Yefei Zhu 《Journal of Biomedical Research》 CAS CSCD 2024年第4期289-306,共18页
Bladder cancer(BC)is the tenth most prevalent malignancy globally,presenting significant clinical and societal challenges because of its high incidence,rapid progression,and frequent recurrence.Presently,cystoscopy an... Bladder cancer(BC)is the tenth most prevalent malignancy globally,presenting significant clinical and societal challenges because of its high incidence,rapid progression,and frequent recurrence.Presently,cystoscopy and urine cytology serve as the established diagnostic methods for BC.However,their efficacy is limited by their invasive nature and low sensitivity.Therefore,the development of highly specific biomarkers and effective noninvasive detection strategies is imperative for achieving a precise and timely diagnosis of BC,as well as for facilitating an optimal tumor treatment and an improved prognosis.microRNAs(miRNAs),short noncoding RNA molecules spanning around 20–25 nucleotides,are implicated in the regulation of diverse carcinogenic pathways.Substantially altered miRNAs form robust functional regulatory networks that exert a notable influence on the tumorigenesis and progression of BC.Investigations into aberrant miRNAs derived from blood,urine,or extracellular vesicles indicate their potential roles as diagnostic biomarkers and prognostic indicators in BC,enabling miRNAs to monitor the progression and predict the recurrence of the disease.Simultaneously,the investigation centered on miRNA as a potential therapeutic agent presents a novel approach for the treatment of BC.This review comprehensively analyzes biological roles of miRNAs in tumorigenesis and progression,and systematically summarizes their potential as diagnostic and prognostic biomarkers,as well as therapeutic targets for BC.Additionally,we evaluate the progress made in laboratory techniques within this field and discuss the prospects. 展开更多
关键词 bladder cancer MICRORNAS BIOMARKER DIAGNOSIS detection method
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