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Sensing nanomaterials of wearable glucose sensors 认领
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作者 Guanglei Li Dan Wen 《中国化学快报:英文版》 SCIE CAS CSCD 2021年第1期221-228,共8页
The metabolic disorder of glucose in human body will cause diseases such as diabetes and hyperglycemia.Hence the determination of glucose content is very important in clinic diagnosing.In recent years,researchers have... The metabolic disorder of glucose in human body will cause diseases such as diabetes and hyperglycemia.Hence the determination of glucose content is very important in clinic diagnosing.In recent years,researchers have proposed various non-invasive wearable sensors for rapid and real-time glucose monitoring from human body fluids.Unlike those reviews which discussed performances,detection environments or substrates of the wearable glucose sensor,this review focuses on the sensing nanomaterials since they are the key elements of most wearable glucose sensors.The sensing nanomaterials such as carbon,metals,and conductive polymers are summarized in detail.And also the structural characteristics of different sensing nanomaterials and the corresponding wearable glucose sensors are highlighted.Finally,we prospect the future development requirements of sensing nanomaterials for wearable glucose sensors.This review would give some insights to the further development of wearable glucose sensors and the modern medical treatment. 展开更多
关键词 Wearable sensors Glucose detection Sensing nanomaterials Noninvasive detection FLEXIBILITY
A Novel SAR Image Ship Small Targets Detection Method 认领
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作者 Yu Song Min Li +3 位作者 Xiaohua Qiu Weidong Du Yujie He Xiaoxiang Qi 《电脑和通信(英文)》 2021年第2期57-71,共15页
To satisfy practical requirements of high real-time accuracy and low computational complexity of synthetic aperture radar (SAR) image ship small target detection, this paper proposes a small ship target detection meth... To satisfy practical requirements of high real-time accuracy and low computational complexity of synthetic aperture radar (SAR) image ship small target detection, this paper proposes a small ship target detection method based on the improved You Only Look Once Version 3 (YOLOv3). The main contributions of this study are threefold. First, the feature extraction network of the original YOLOV3 algorithm is replaced with the VGG16 network convolution layer. Second, general convolution is transformed into depthwise separable convolution, thereby reducing the computational cost of the algorithm. Third, a residual network structure is introduced into the feature extraction network to reuse the shallow target feature information, which enhances the detailed features of the target and ensures the improvement in accuracy of small target detection performance. To evaluate the performance of the proposed method, many experiments are conducted on public SAR image datasets. For ship targets with complex backgrounds and small ship targets in the SAR image, the effectiveness of the proposed algorithm is verified. Results show that the accuracy and recall rate improved by 5.31% and 2.77%, respectively, compared with the original YOLOV3. Furthermore, the proposed model not only significantly reduces the computational effort, but also improves the detection accuracy of ship small target. 展开更多
关键词 The SAR Images The Neural Network Ship Small Target Target Detection
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Ship detection and classification from optical remote sensing images: A survey 认领
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作者 Bo LI Xiaoyang XIE +1 位作者 Xingxing WEI Wenting TANG 《中国航空学报:英文版》 SCIE EI CAS CSCD 2021年第3期145-163,共19页
Considering the important applications in the military and the civilian domain, ship detection and classification based on optical remote sensing images raise considerable attention in the sea surface remote sensing f... Considering the important applications in the military and the civilian domain, ship detection and classification based on optical remote sensing images raise considerable attention in the sea surface remote sensing filed. This article collects the methods of ship detection and classification for practically testing in optical remote sensing images, and provides their corresponding feature extraction strategies and statistical data. Basic feature extraction strategies and algorithms are analyzed associated with their performance and application in ship detection and classification.Furthermore, publicly available datasets that can be applied as the benchmarks to verify the effectiveness and the objectiveness of ship detection and classification methods are summarized in this paper. Based on the analysis, the remaining problems and future development trends are provided for ship detection and classification methods based on optical remote sensing images. 展开更多
关键词 Optical remote sensing Satellite image Sea target detection Ship classification Ship detection
Research on Adaptive Threshold of Received Signal in Communication System 认领
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作者 Xizheng Ke Xukuan Ji 《光学与光子学期刊(英文)》 2021年第1期1-11,共11页
When the light beam propagates in the atmosphere, the signal will be absorbed and scattered by the gas molecules and water mist in the atmosphere, which will cause the loss of power rate. The complex atmospheric envir... When the light beam propagates in the atmosphere, the signal will be absorbed and scattered by the gas molecules and water mist in the atmosphere, which will cause the loss of power rate. The complex atmospheric environment will produce a variety of adverse effects on the signal. The interference produced by these effects overlaps with each other, which will seriously affect the strength of the received signal. Therefore, how to effectively suppress the atmospheric turbulence effect in the random atmospheric turbulence channel, ensure the normal transmission of the signal in the atmospheric channel, and reduce the bit error rate of the communication system, is very necessary to improve the communication system. When processing the received signal, it is an important step to detect the transmitted signal by comparing the received signal with the threshold. In this paper, based on the atmospheric turbulence distribution model, the adaptive signal decision threshold is obtained through the estimation of high-order cumulant. Monte Carlo method is used to verify the performance of adaptive threshold detection. The simulation results show that the high-order cumulant estimation of atmospheric turbulence parameters can realize the adaptive change of the decision threshold with the channel condition. It is shown that the adaptive threshold detection can effectively restrain atmospheric turbulence, improve the performance of free space optical and improve the communication quality. 展开更多
关键词 Free Space Optical Adaptive Threshold Detection Higller-Order Cumulants
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An Oracle Bone Inscription Detector Based on Multi-Scale Gaussian Kernels 认领
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作者 Guoying Liu Shuanghao Chen +1 位作者 Jing Xiong Qingju Jiao 《应用数学(英文)》 2021年第3期224-239,共16页
The detection of Oracle Bone Inscriptions (OBIs) is one of the most fundamental tasks in the study of Oracle Bone, which aims to locate the positions of OBIs on rubbing images. The existing methods are based on the sc... The detection of Oracle Bone Inscriptions (OBIs) is one of the most fundamental tasks in the study of Oracle Bone, which aims to locate the positions of OBIs on rubbing images. The existing methods are based on the scheme of anchor boxes, involving complex network design and a great number of anchor boxes. In order to overcome the problem, this paper proposes a simpler but more effective OBIs detector by using an anchor-free scheme, where shape-adaptive Gaussian kernels are employed to represent the spatial regions of different OBIs. More specifically, to address the problem of misdetection caused by regional overlapping between some tightly distributed OBIs, the character regions are simultaneously represented by multiscale Gaussian kernels to obtain regions with sharp edges. Besides, based on the kernel predictions of different scales, a novel post-processing pipeline is used to obtain accurate predictions of bounding boxes. Experiments show that our OBIs detector has achieved significant results on the OBIs dataset, which greatly outperforms several mainstream object detectors in both speed and efficiency. Dataset is available at http://jgw.aynu.edu.cn. 展开更多
关键词 Oracle Bone Inscriptions Deep Learning Object Detection Hourglass Network
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Vision-Based On-Road Nighttime Vehicle Detection and Tracking Using Taillight and Headlight Features 认领
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作者 Shahnaj Parvin Liton Jude Rozario Md. Ezharul Islam 《电脑和通信(英文)》 2021年第3期29-53,共25页
An important and challenging aspect of developing an intelligent transportation system is the identification of nighttime vehicles. Most accidents occur at night owing to the absence of night lighting conditions. Vehi... An important and challenging aspect of developing an intelligent transportation system is the identification of nighttime vehicles. Most accidents occur at night owing to the absence of night lighting conditions. Vehicle detection has become a vital subject for research to ensure safety and avoid accidents. New vision-based on-road nighttime vehicle detection and tracking system are suggested in this survey paper using taillight and headlight features. Using computer vision and some image processing techniques, the proposed system can identify vehicles based on taillight and headlight features. For vehicle tracking, a centroid tracking algorithm has been used. Euclidean Distance method has been used for measuring the distances between two neighboring objects and tracks the nearest neighbor. In the proposed system two flexible fixed Region of Interest (ROI) have been used, one is the Headlight ROI, and another is the Taillight ROI that could adapt to different resolutions of the images and videos. The achievement of this research work is that the proposed two ROIs can work simultaneously in a frame to identify oncoming and preceding vehicles at night. The segmentation techniques and double thresholding method have been used to extract the red and white components from the scene to identify the vehicle headlights and taillights. To evaluate the capability of the proposed process, two types of datasets have been used. Experimental findings indicate that the performance of the proposed technique is reliable and effective in distinct nighttime environments for detection and tracking of vehicles. The proposed method has been able to detect and track double lights as well as single light such as motorcycle light and achieved average accuracy and average processing time of vehicle detection about 97.22% and 0.01 s per frame respectively. 展开更多
关键词 Vehicle Detection Double Threshold NIGHTTIME HEADLIGHT TAILLIGHT Vehicle Tracking
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Camera-based Basketball Scoring Detection Using Convolutional Neural Network 认领
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作者 Xu-Bo Fu Shao-Long Yue De-Yun Pan 《国际自动化与计算杂志:英文版》 EI CSCD 2021年第2期266-276,共11页
Recently,deep learning methods have been applied in many real scenarios with the development of convolutional neural networks(CNNs).In this paper,we introduce a camera-based basketball scoring detection(BSD)method wit... Recently,deep learning methods have been applied in many real scenarios with the development of convolutional neural networks(CNNs).In this paper,we introduce a camera-based basketball scoring detection(BSD)method with CNN based object detection and frame difference-based motion detection.In the proposed BSD method,the videos of the basketball court are taken as inputs.Afterwards,the real-time object detection,i.e.,you only look once(YOLO)model,is implemented to locate the position of the basketball hoop.Then,the motion detection based on frame difference is utilized to detect whether there is any object motion in the area of the hoop to determine the basketball scoring condition.The proposed BSD method runs in real-time with satisfactory basketball scoring detection accuracy.Our experiments on the collected real scenario basketball court videos show the accuracy of the proposed BSD method.Furthermore,several intelligent basketball analysis systems based on the proposed method have been installed at multiple basketball courts in Beijing,and they provide good performance. 展开更多
关键词 Computer vision convolutional neural network(CCN) frame difference motion detection object detection real-time system
Improving CAD Hemorrhage Detection in Capsule Endoscopy 认领
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作者 Polydorou Alexios Sergaki Eleftheria +4 位作者 Polydorou Andreas Barbagiannis Christos Vardiambasis Ioannis George Giakos Zervakis Michail 《生物医学工程(英文)》 2021年第3期103-118,共16页
This study explores an automated framework to assist the recognition of hemorrhage traces and bleeding lesions in video streams of small bowel capsule endoscopy (SBCE). The proposed methodology aims to achieve fast im... This study explores an automated framework to assist the recognition of hemorrhage traces and bleeding lesions in video streams of small bowel capsule endoscopy (SBCE). The proposed methodology aims to achieve fast image control (<10 minutes), save valuable time of the physicians, and enable high performance diagnosis. A specialized elimination algorithm excludes all identical consecutive frames by utilizing the difference of gray levels in pixel luminance. An image filtering algorithm is proposed based on an experimentally calculated bleeding index and blood-color chart, which inspects all remaining frames of the footage and identifies pixels that reflect active or potential hemorrhage in color. The bleeding index and blood-color chart are estimated of the chromatic thresholds in RGB and HSV color spaces, and have been extracted after experimenting with more than 3200 training images, derived from 99 videos of a pool of 138 patients. The dataset has been provided by a team of expert gastroenterologist surgeons, who have also evaluated the results. The proposed algorithms are tested on a set of more than 1000 selected frame samples from the entire 39 testing videos, to a prevalence of 50% pathologic frames (balanced dataset). The frame elimination of identical and consecutive frames achieved a reduction of 36% of total frames. The best statistical performance for diagnosis of positive pathological frames from a video stream is achieved by utilizing masks in the HSV color model, with sensitivity up to 99%, precision 94.41% to a prevalence of 50%, accuracy up to 96.1%, FNR 1%, FPR 6.8%. The estimated blood-color chart will be clinically validated and used in feature extraction schemes supporting machine learning ML algorithms to improve the localization potential. 展开更多
关键词 Capsule Endoscopy Small Bowel Bleeding Detection Computer Aided Diagnosis (CAD) Color Models Color Feature
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Development and Evaluation of an Optical Sensing System for Detection of Herbicide Spray Droplets 认领
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作者 Yanbo Huang Wei Ma Daniel Fisher 《物联网(英文)》 2021年第1期1-9,共9页
Real time monitoring of herbicide spray droplet drift is important for crop production management and environmental protection. Existing spray droplet drift detection methods, such as water-sensitive paper and tracers... Real time monitoring of herbicide spray droplet drift is important for crop production management and environmental protection. Existing spray droplet drift detection methods, such as water-sensitive paper and tracers of fluorescence and Rubidium chloride, are time-consuming and laborious, and the accuracies are not high in general. Also, the tracer methods indirectly quantify the spray deposition from the concentration of the tracer and may change the drift characteristics of the sprayed herbicides. In this study, a new optical sensor system was developed to directly detect the spray droplets without the need to add any tracer in the spray liquid. The system was prototyped using a single broadband programmable LED light source and a near infrared sensor containing 6 broadband spectral detectors at 610, 680, 730, 760, 810, and 860 nm to build a detection system for monitoring and analysis of herbicide spray droplet drift. A rotatory structure driven by a stepper motor in the system was created to shift the droplet capture line going under the optical sensor to measure and collect the spectral signals that reflect spray drift droplets along the line. The system prototype was tested for detection of small (Very Fine and Fine), medium (Medium), and large (Coarse) droplets within the droplet classifications of the American Society of Agricultural and Biological Engineers. Laboratory testing results indicated that the system could detect the droplets of different sizes and determine the droplet positions on the droplet capture line with 100% accuracy at the wavelength of 610 nm selected from the 6 bands to detect the droplets. 展开更多
关键词 Near Infrared (NIR) Sensor Spray Drift Droplet Detection Plant Protection
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A Hybrid Intrusion Detection System for Smart Home Security Based on Machine Learning and User Behavior 认领
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作者 Faisal Alghayadh Debatosh Debnath 《物联网(英文)》 2021年第1期10-25,共16页
With technology constantly becoming present in people’s lives, smart homes are increasing in popularity. A smart home system controls lighting, temperature, security camera systems, and appliances. These devices and ... With technology constantly becoming present in people’s lives, smart homes are increasing in popularity. A smart home system controls lighting, temperature, security camera systems, and appliances. These devices and sensors are connected to the internet, and these devices can easily become the target of attacks. To mitigate the risk of using smart home devices, the security and privacy thereof must be artificially smart so they can adapt based on user behavior and environments. The security and privacy systems must accurately analyze all actions and predict future actions to protect the smart home system. We propose a Hybrid Intrusion Detection (HID) system using machine learning algorithms, including random forest, X gboost, decision tree, K -nearest neighbors, and misuse detection technique. 展开更多
关键词 Anomaly Detection Smart Home Systems Behavioral Patterns SECURITY Threats
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Review of Anomaly Detection Systems in Industrial Control Systems Using Deep Feature Learning Approach 认领
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作者 Raogo Kabore Adlès Kouassi +3 位作者 Rodrigue N’goran Olivier Asseu Yvon Kermarrec Philippe Lenca 《工程(英文)(1947-3931)》 2021年第1期30-44,共15页
Industrial Control Systems (ICS) or SCADA networks are increasingly targeted by cyber-attacks as their architectures shifted from proprietary hardware, software and protocols to standard and open sources ones. Further... Industrial Control Systems (ICS) or SCADA networks are increasingly targeted by cyber-attacks as their architectures shifted from proprietary hardware, software and protocols to standard and open sources ones. Furthermore, these systems which used to be isolated are now interconnected to corporate networks and to the Internet. Among the countermeasures to mitigate the threats, anomaly detection systems play an important role as they can help detect even unknown attacks. Deep learning which has gained a great attention in the last few years due to excellent results in image, video and natural language processing is being used for anomaly detection in information security, particularly in SCADA networks. The salient features of the data from SCADA networks are learnt as hierarchical representation using deep architectures, and those learnt features are used to classify the data into normal or anomalous ones. This article is a review of various architectures such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Stacked Autoencoder (SAE), Long Short Term Memory (LSTM), or a combination of those architectures, for anomaly detection purpose in SCADA networks. 展开更多
关键词 ICS SCADA Unsupervised Feature Learning Deep Learning Anomaly Detection
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Magnetic Applications to Subsurface and Groundwater Investigations: A Case Study from Wadi El Assiuti, Egypt 认领
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作者 Ahmed Mohamed Elsayed M. Abu El Ella 《地球科学国际期刊(英文)》 2021年第2期77-101,共25页
Wadi El Assiuti represents a promising area for agricultural development and building new communities far from the overpopulated areas in the Nile Val-ley. An integrated approach of satellite-based data and geophysica... Wadi El Assiuti represents a promising area for agricultural development and building new communities far from the overpopulated areas in the Nile Val-ley. An integrated approach of satellite-based data and geophysical data with borehole data was used for defining the area of interest, the sediment thick-ness, delineating the subsurface structures, and mapping the depth to the basement rocks, and defining the groundwater aquifers. Findings are: 1) Dramatic changes are detected in the anthropogenic activities at the entrance area of the wadi, making stress and heavy exploitation of the groundwater resources. However, the central and northeastern regions show no development;2) Several structural trends in the directions of NNW, NW, NE, and E-W are cutting the basement rocks and sedimentary cover;3) The depth to the basement rocks is increasing eastward from ~2.24 km to ~4.84 km;4) Three groundwater-bearing reservoirs are represented by the shallow Qua-ternary, the fractured limestone, and the deep Nubian sandstone aquifers;5) The deep-seated faults are affecting the area and rising groundwater from the deeper Nubian aquifer along its sub-vertical trend;and 6) The results are in-formative and used to define the suitable sites for water well drilling. 展开更多
关键词 Wadi El Assiuti Aeromagnetic Data Change Detection Structural Trends Sediment Thickness Groundwater Aquifers
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Prognosis and Survival of Nasopharyngeal Cancer in Cameroon 认领
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作者 Jean Paul Engbang Amadou Njifou +4 位作者 Therè se Daphné e Tjomb Maurice Mpessa Louis Richard Njock 《耳鼻喉(英文)》 2021年第1期6-19,共14页
<strong>Background:</strong> Nasopharyngeal carcinoma (NPC) is an entity belonging to up-per aerodigestive tract Cancers. NPC is more widespread in Southern China and South East Asia. In our country, it is... <strong>Background:</strong> Nasopharyngeal carcinoma (NPC) is an entity belonging to up-per aerodigestive tract Cancers. NPC is more widespread in Southern China and South East Asia. In our country, it is the leading cause of head and neck cancers. Its prognosis remains bleak because of the late stage at diagnostic. <strong>Objectives:</strong> The objectives of this study were to determine the prognostic fac-tors and survival rate of patients with nasopharyngeal cancer in six reference hospitals in Cameroon. <strong>Material and Methods:</strong> It was a retrospective analytic study, conducted from January 2009 to December 2018. It was conducted in oncology, surgery and Ear Nose and Throat (ENT) units of six reference hos-pitals. Data from 114 files meeting the inclusion were collected. We have drawn survival curves and determined the different survival probabilities with the help of Kaplan-Meier Method. The different survival curves were compared using the Log-Rank Test (P < 0.05), variables that were statistically associated with the 5% cut off were introduced into the Cox regression model for multivariate analysis, thus allowing us to bring out the prognostic factors significantly associated with survival. <strong>Results:</strong> The mean age at the time of diagnosis of the 114 patients recruited was 45.30 ± 17.14 years. The predominant histological type was the UCNT (Undifferentiated Carcinoma of the NasoPharynx) representing 84.2%. According to the WHO classification, 2 patients were classified as stage I (1.8%), 33 as stage II (28.9%), 42 as stage III (36.8%), 25 as stage IV A (21.9%) and 12 as stage IV B (10.5%). At the end of the survival assessment period, 34 patients were dead and 73 patients (64%) were still alive. The median overall survival was 44 months. The overall survival rates at one, two, three, and four years were 80%;74%;68%;44%, respectively. The prognostic factors associated with poor survival were: late consultation time of more than 12 months, N3 lymph node involvement, 3 and 4 adva 展开更多
关键词 Nasopharyngeal Cancer SURVIVAL Prognostic Factors DETECTION Cameroon
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基于核酸适配体调控噻菁染料聚集体构建铅离子检测方法 认领
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作者 赵晗 于丽佳 +3 位作者 吴志生 张颖琳 张华伟 师晓栋 《食品与机械》 北大核心 2021年第1期73-78,共6页
基于调控噻菁染料(Dye2)的超分子自组装性质及其与核酸适配体(T30695)特异性结合的能力,构建了Pb2+的特异性识别模块。结果表明,当体系中加入Pb2+时,T30695单链形成G-四链体,并将二聚体形式存在的噻菁染料诱导解聚为单体,引起422,445nm... 基于调控噻菁染料(Dye2)的超分子自组装性质及其与核酸适配体(T30695)特异性结合的能力,构建了Pb2+的特异性识别模块。结果表明,当体系中加入Pb2+时,T30695单链形成G-四链体,并将二聚体形式存在的噻菁染料诱导解聚为单体,引起422,445nm处紫外吸收峰变化,仅需通过UV-vis光谱仪便可实现对Pb2+的高选择性、高灵敏度识别。该体系在Pb2+浓度为0.25~10.00μmol/L时具有线性关系(R2=0.992 7),其检出限为0.115μmol/L。 展开更多
关键词 核酸适配体 噻菁染料 铅离子(Ⅱ) G-四链体 检测
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掺粉煤灰水利水电建筑混凝土强度检测方法研究 认领
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作者 刘瑞春 《粉煤灰综合利用》 CAS 2021年第1期108-112,共5页
传统混凝土强度检测方法对声波信号频率的计算存在误差,导致检测结果不准确,为此提出掺粉煤灰水利水电建筑混凝土强度检测方法。采用敲击的方式,使混凝土内部产生声波信号,用传感器记录冲击回波频率,计算冲击回波频率传播速度,并在振幅... 传统混凝土强度检测方法对声波信号频率的计算存在误差,导致检测结果不准确,为此提出掺粉煤灰水利水电建筑混凝土强度检测方法。采用敲击的方式,使混凝土内部产生声波信号,用传感器记录冲击回波频率,计算冲击回波频率传播速度,并在振幅谱频谱中分析出声波频率峰值。测定冲击持续时间,计算冲击回波反射面深度以确定混凝土碳化程度,得出掺粉煤灰水利水电建筑混凝土强度值。试验结果显示:该方法得到的声波信号频率、混凝土强度值与实测最为接近,检测精度高。 展开更多
关键词 掺粉煤灰 水利水电建筑 混凝土强度 检测 声波信号 频率
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数字式地下管网泄漏无损探测研究 认领
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作者 谢芳 姚幸晨 +2 位作者 张婷婷 周敏 徐凯 《信息与电脑》 2021年第2期7-8,共2页
地下管线是城市基础设施的重要组成部分,在进行城市规划、设计、施工和管理过程中,如果没有准确的地下管线信息,就会寸步难行,甚至会造成重大损失。本文利用DSP技术多通道分频段采集埋在地下的自来水管流水声谱,利用智能自适应算法滤除... 地下管线是城市基础设施的重要组成部分,在进行城市规划、设计、施工和管理过程中,如果没有准确的地下管线信息,就会寸步难行,甚至会造成重大损失。本文利用DSP技术多通道分频段采集埋在地下的自来水管流水声谱,利用智能自适应算法滤除马路上的汽车及自然噪声,不仅能够及时获取管道是否泄漏及泄漏点的位置,还能减少试探性挖掘找取漏水点,节约人工量,提高快速判定漏水点的效率,大大减少原查漏方式对交通的影响。 展开更多
关键词 管网 泄漏 探测
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一种多通道酶标仪的研制 认领
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作者 于学龙 郈秀菊 +4 位作者 张素文 李红梅 刘阳 钟华风 李俊起 《生物医学工程研究》 2021年第1期78-82,共5页
基于朗伯比尔定律的酶标分析仪在临床诊断、实验室检测领域有着广泛的应用。本研究给出了采用双单片机控制的酶标仪的实现方法,对光学系统、电路结构、控制软件和机械驱动进行了设计。按照酶标分析仪检定规程对吸光度误差和通道差异进... 基于朗伯比尔定律的酶标分析仪在临床诊断、实验室检测领域有着广泛的应用。本研究给出了采用双单片机控制的酶标仪的实现方法,对光学系统、电路结构、控制软件和机械驱动进行了设计。按照酶标分析仪检定规程对吸光度误差和通道差异进行检验,其结果符合要求。该酶标分析仪基本满足实际使用要求。 展开更多
关键词 酶标分析仪 单片机 检测 酶联免疫吸附法 朗伯比尔定律 滤光片
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风疹IgM抗体检测中即刻法和双质控法的应用 认领
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作者 刘斌 《中国卫生标准管理》 2021年第6期80-82,共3页
目的分析风疹IgM抗体检测中即刻法和双质控法的应用效果,探讨IgM抗体的有效检测方法,旨在为临床提高风疹的诊断率提供参考依据。方法筛选出本科室2018年4月—2020年4月的62例疑似风疹患者,均对其进行IgM抗体检测,根据不同室内质量控制... 目的分析风疹IgM抗体检测中即刻法和双质控法的应用效果,探讨IgM抗体的有效检测方法,旨在为临床提高风疹的诊断率提供参考依据。方法筛选出本科室2018年4月—2020年4月的62例疑似风疹患者,均对其进行IgM抗体检测,根据不同室内质量控制方法将其分为A组与B组,A组应用即刻法,B组应用双质控法,对比两组的室内质控效果。结果旧试剂第5~7次与新试剂第1~2次对应的同一个酶标板试验结果以及旧试剂的第7次与新试剂的4次试验结果均处于可控状态。结论风疹IgM抗体检测中双质控法的应用效果优于即刻法,有助于提高检测结果的准确率,对风疹的临床诊断具有重要意义。 展开更多
关键词 风疹 IGM抗体 检测 酶联免疫吸附试验 即刻法 双质控法 应用
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Clustering-based label estimation for network anomaly detection 认领
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作者 Sunhee Baek Donghwoon Kwon +3 位作者 Sang C.Suh Hyunjoo Kim Ikkyun Kim Jinoh Kim 《数字通信与网络:英文版》 SCIE CSCD 2021年第1期37-44,共8页
A substantial body of work has been done to identify network anomalies using supervised and unsupervised learning techniques with their unique strengths and weaknesses.In this work,we propose a new approach that takes... A substantial body of work has been done to identify network anomalies using supervised and unsupervised learning techniques with their unique strengths and weaknesses.In this work,we propose a new approach that takes advantage of both worlds of unsupervised and supervised learnings.The main objective of the proposed approach is to enable supervised anomaly detection without the provision of the associated labels by users.To this end,we estimate the labels of each connection in the training phase using clustering.The“estimated”labels are then utilized to establish a supervised learning model for the subsequent classification of connections in the testing stage.We set up a new property that defines anomalies in the context of network anomaly detection to improve the quality of estimated labels.Through our extensive experiments with a public dataset(NSL-KDD),we will prove that the proposed method can achieve performance comparable to one with the “original”labels provided in the dataset.We also introduce two heuristic functions that minimize the impact of the randomness of clustering to improve the overall quality of the estimated labels. 展开更多
关键词 Label estimation Network anomaly detection Clustering randomness
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煤矿深部奥灰水地球物理探测方法浅析 认领
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作者 张洁 《山东煤炭科技》 2021年第3期144-146,155,共4页
为更好地探查五矿深部奥灰水富水性,对带压开采区域采用瞬变电磁法(TEM)和可控源音频大地电磁法(CSAMT)两种方法进行了煤矿深部奥灰水探查。通过分析研究,确定可控源音频大地电磁法(CSAMT)在抗干扰能力和工作效率方面更突出一些,更适用... 为更好地探查五矿深部奥灰水富水性,对带压开采区域采用瞬变电磁法(TEM)和可控源音频大地电磁法(CSAMT)两种方法进行了煤矿深部奥灰水探查。通过分析研究,确定可控源音频大地电磁法(CSAMT)在抗干扰能力和工作效率方面更突出一些,更适用于煤矿深部奥灰水探测及水文地质条件评价。 展开更多
关键词 地面电法 奥灰水 探测 瞬变电磁
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