Identifying ephemeral gullies from high-resolution images and DEMs using flow-directional detection

Ephemeral gullies,which are widely developed worldwide and threaten farmlands,have aroused a growing concern.Identifying and mapping gullies are generally considered prerequisites of gully erosion assessment.However,ephemeral gully mapping remains a challenge.In this study,we proposed a flow-directional detection for identifying ephemeral gullies from high-resolution images and digital elevation models(DEMs).Ephemeral gullies exhibit clear linear features in high-resolution images.An edge detection operator was initially used to identify linear features from high-resolution images.Then,according to gully erosion mechanism,the flow-directional detection was designed.Edge images obtained from edge detection and flow directions obtained from DEMs were used to implement the flow-directional detection that detects ephemeral gullies along the flow direction.Results from ten study areas in the Loess Plateau of China showed that ranges of precision,recall,and Fmeasure are 6 o.66%-90.47%,65.74%-94.98%,and63.10%-91.93%,respectively.The proposed method is flexible and can be used with various images and DEMs.However,analysis of the effect of DEM resolution and accuracy showed that DEM resolution only demonstrates a minor effect on the detection results.Conversely,DEM accuracy influences the detection result and is more important than the DEM resolution.The worse the vertical accuracy of DEM,the lower the performance of the flow-directional detection will be.This work is beneficial to research related to monitoring gully erosion and assessing soil loss.

Capillary Electrophoretic Determination of Jinggangmycin A in Formulations Using Direct UV Detection

A simple, fast and reliable method was developed for the analysis of jinggangmycin A （validamycin A） in commercial formulations. The running buffer used was acetate buffer （100 mmol/L, pH 4.7） with 15 kV as the applied voltage. The detection was achieved by using direct UV mode at 200 nm and the detection limit was 0.2 μg/mL. Linearity in the concentration range of 5-500 μg/mL was excellent （RE 〉 0.999）. The run-to-run repeatability （n = 3）, as expressed by the relative standard deviation （RSD） for migration times and peak areas were less than 0.5% and 3.0% respectively. The mean recovery ranged from 97.2% to 101.4%.

Scratch Detection Algorithm of Car Surface Based on Directional Color SUSAN Operator

The car surface scratch detection adopts the traditional manual detection with poor efficiency and high missing rate.Because of the gray mark and the background of car surface scratches,the traditional edge detection algorithm cannot meet the needs of car surface scratch detection.Therefore,the directional SUSAN algorithm based on CIELab color space is adopted in this paper.The direction template and the circle template to calculate the color difference of the color image are used in the algorithm which has been converted to the CIELab space.The edges and scratches are eliminated by matching and contrasting the detected image with the edge template.Experimental results show that the algorithm can effectively detect scratches on the surface of cars,improve the detection speed and reduce the undetected rate.

Energy Theft Detection in Smart Grids:Taxonomy,Comparative Analysis,Challenges,and Future Research Directions

Electricity theft is one of the major issues in developing countries which is affecting their economy badly.Especially with the introduction of emerging technologies,this issue became more complicated.Though many new energy theft detection(ETD)techniques have been proposed by utilising different data mining(DM)techniques,state&network(S&N)based techniques,and game theory(GT)techniques.Here,a detailed survey is presented where many state-of-the-art ETD techniques are studied and analysed for their strengths and limitations.Three levels of taxonomy are presented to classify state-of-the-art ETD techniques.Different types and ways of energy theft and their consequences are studied and summarised and different parameters to benchmark the performance of proposed techniques are extracted from literature.The challenges of different ETD techniques and their mitigation are suggested for future work.It is observed that the literature on ETD lacks knowledge management techniques that can be more effective,not only for ETD but also for theft tracking.This can help in the prevention of energy theft,in the future,as well as for ETD.

Grey Relevancy Degree and Improved Eight-Direction Sobel Operator Edge Detection

Edge detection is an important aspect to improve image edge quality in image processing. The purpose of edge detection is to identify the points in digital images with great brightness variation. However, the accuracy of traditional edge detection methods in edge extraction is low. For the actual image, the grey edge is sometimes not very clear, the image also contains noise. The detection result of the traditional Sobel operator is relatively accurate, but the detection result is rough and sensitive to noise. To solve the above problems, this paper proposes an improved eight-direction Sobel operator based on grey relevancy degree, which combines 5 × 5 Sobel operator with a grey relational degree and a new eight-direction grey relevancy method. The results show that this method can detect the useful information of edge more accurately and improve the anti-noise performance. However, the drawback is that the algorithm is not automatic.

Edge detection using directional eigenvalues of potential field gradient tensor data

Edge detection of potential field interpretation is an important task. The traditional edge detection methods have poor ability in outlining weak amplitude anomalies clearly. The resolved edges position is blurred.We purposed new edge detection methods based on directional eigenvalues of potential field gradient tensor for the causative sources. In order to balance strong and weak amplitude anomalies simultaneously,we present one normalization method using different orders of vertical derivatives to improve the new filters. The presented filters were tested on synthetic and real potential field data to verify its feasibility. All of the results have shown that the new edge detection methods can not only display the sources edges precisely and clearly,but also bring out more geological subtle details.

Composite excitation multi-extension direction defect magnetic flux leakage detection technology

In the traditional pipeline magnetic flux leakage(MFL)detection technology,circumferential or axial excitation is mainly used to excite the magnetic field of defects.However,the domestic and foreign pipeline detection devices currently in operation are mainly axial excitation MFL detection tools,in which circumferential cracks can be clearly identified,but the detection sensitivity of axial cracks is not high,thus forming a detection blind zone.Therefore,a composite excitation multi-extension direction defect MFL detection method is proposed,which can realize the simultaneous detection of axial and circumferential defects.On the basis of the electromagnetic theory Maxwell equation and Biot Savart law,a mathematical model of circumferential and axial magnetization is firstly established.Then finite element simulation software is used to establish a model of a new type of magnetic flux leakage detection device,and a simulation analysis of crack detection in multiple extension directions is carried out.Finally,under the conditions of the relationship model between the change rate of leakage magnetic field and external excitation intensity under unsaturated magnetization and the multi-stage coil magnetization model,the sample vehicle towing experiment is carried out.The paper aims to analyze the feasibility and effectiveness of the new magnetic flux leakage detection device for detecting defects in different extension directions.Based on the final experimental results,the new composite excitation multi extension direction leakage magnetic field detector has a good detection effect for defects in the axial and circumferential extension directions.

Direct detection of rpoB and katG gene mutations of Mycobacterium tuberculosis in clinical samples

To study the rpoB and katG gene mutation rate and its markers.MethodsCross-sectional study methods were used to study Tuberculosis. A total of 45 sputum samples were collected from Annapurna Neurological Institute and Allied sciences. Then, acid fast bacilli staining were performed. Positive and negative samples were carried for conventional polymerase chain reaction identification and electrophoresis.ResultsOut of 45 samples, 3 were acid fast bacilli positive and the rest were negative. Male participants were more as compare to female participants and the mutation in rpoB and katG gene was found similar i.e. 6.66% among the total samples.ConclusionsWe can conclude that genetic mutation in Mycobacterium tuberculosis can be identified directly from the clinical samples. However, we have carried this study in less sample size and to validate research on large number of sample is recommended.

Progress and Developmental Direction of Post-harvest Component Detection and Preservation Techniques of Nanfeng Citrus in China

This paper was summarized the research status and the development tendency of post-harvest component detection and preservation techniques of Nanfeng citrus in China, also analyzed the characteristics of various techniques, and proposed the developmental direction of novel techniques for post-harvest component detection and preservation of Nanfeng citrus.

Greater than 200 Gb/s Transmission Using Direct-Detection Optical OFDM Superchannel

In this paper, we propose directdetection optical orthogonal frequency division multiplexing superchannel （DDOOFDMS） and optical multiband receiving method （OMBR） to support a greater than 200 Gb/s data rate and longer distance for direct-detection systems. For the new OMBR, we discuss the optimum carriertosideband power ratio （CSPR） in the cases of backtoback and post transmission. We derive the analytical form for CSPR and theoretically verify it. A low overhead training method for estimating I/Q imbalance is also introduced in order to improve performance and maintain high system throughput. The experiment results show that these proposals enable an unprecedented data rate of 214 Gb/s （190 Gb/s without overhead） per wavelength over an unprecedented distance of 720 km SSMF in greater than 100 Gb/s DDOFDM systems.

Direct-Detected OFDM传输系统中光带通滤波器性能研究

研究了中频结构的DD-OFDM系统.在模拟实验中,10 Gb/s的OFDM信号传输了640 km的标准单模光纤,对其光链路中滤波器带宽和阶数进行调整,分析了接收端OSNR和BER.在BER=10-3条件下,结果表明较高阶的单边带滤波器相对于普通单边带滤波器,接收端OSNR敏感度有1 dB的提高,在滤波器阶数达到8阶时,可以得到滤波器性能的极限.研究了间隔50 GHz的4路DD-OFDM的WDM系统,实现了系统传输640km的标准单模光纤,并均衡4路信道和比较了BER=10-3时各路DD-OFDM需要的OSNR.

Improved Security Detection Strategy for Quantum "Ping-Pong" Protocol and Its Security Analysis

In order to transmit the secure messages,a deterministic secure quantum direct communication protocol,called the "Ping-pong"protocol was proposed by Bostrm and Felbinger [Phys.Rev.Lett.89,187902(2002) ].But the protocol was proved to have many vulnerabilities,and can be attacked by eavesdroppers.To overcome the problem,an improved security detection strategy which inserts the | 0〉,| 1〉,|+〉and |-〉particles into the messages as the decoy particles randomly in the"Ping-pong"protocol is presented.During the security analysis,the method of the entropy theory is introduced,and three detection strategies are compared quantitatively by using the constraint between the information which eavesdroppers can obtain and the interference introduced.Because of the presence of the trap particles |+〉and |-〉,the detection rate will be no less than 25% when Eve attacks the communication.The security analysis result shows that the efficiency of eavesdropping detection in the presented protocol is higher than the other two,so the detection strategy in the protocol can ensure that the "Ping-pong"protocol is more secure.

Study on Dim Target Detection and Discrimination from Sea Clutter

Dim target detection from sea clutter is one of the difficult topics in ocean remote sensing application. By aiming at the shortcoming of false alarms when using track before detect （TBD） based on dynamic programming, a new discrimination method called statistics of direction histogram （SDH） is proposed, which is based on different features of trajectories between the true target and false one. Moreover, a new series of discrimination schemes of SDH and Local Extreme Value method （LEV） are studied and applied to simulate the actually measured radar data. The results show that the given discrimination is effective to reduce false alarms during dim targets detection.

HOUSE CHANGE DETECTION BASED ON DSM OF AERIAL IMAGE IN URBAN AREA

The change of house often brings on the change of DSM in an area over different periods. If we can apply information of the height of houses to reinforce the house change detection, the reliability and efficiency of detection methods will be improved greatly.From this viewpoint, a new approach taking advantage of both height data from an image pair and image data is proposed to detect the house change in urban area and is called 'data fusion technology'.

Active User and Data Detection for Uplink Grant-free NOMA Systems

This paper proposes some low complexity algorithms for active user detection(AUD),channel estimation(CE)and multi-user detection(MUD)in uplink non-orthogonal multiple access(NOMA)systems,including single-carrier and multi-carrier cases.In particular,we first propose a novel algorithm to estimate the active users and the channels for single-carrier based on complex alternating direction method of multipliers(ADMM),where fast decaying feature of non-zero components in sparse signal is considered.More importantly,the reliable estimated information is used for AUD,and the unreliable information will be further handled based on estimated symbol energy and total accurate or approximate number of active users.Then,the proposed algorithm for AUD in single-carrier model can be extended to multi-carrier case by exploiting the block sparse structure.Besides,we propose a low complexity MUD detection algorithm based on alternating minimization to estimate the active users’data,which avoids the Hessian matrix inverse.The convergence and the complexity of proposed algorithms are analyzed and discussed finally.Simulation results show that the proposed algorithms have better performance in terms of AUD,CE and MUD.Moreover,we can detect active users perfectly for multi-carrier NOMA system.

Change Detection Based on DSM and Image Features in Urban Areas

On the basis of stereo image analysis, the change detection of man-made objects in urban areas is introduced. Information of the height of man-made objects can be applied to reinforce their change detection. By comparison between the new and old DSMs, the changed regions are extracted. However, our aim is to detect changes of man-made objects in urban area and further in the potential areas by the means of line-feature matching and gradient direction histogram. The experiments based on the aerial images from Japan have proven that the algorithm is correct and efficient.

Detection of Target Genes in Viable Bacteria and Extracellular DNA Using Loop-Mediated Isothermal Amplification Assay

When the loop-mediated isothermal amplification(LAMP)assay is used for detecting target genes,DNA extraction is unnecessary in many cases.Simple pretreatment(e.g.heating)is enough to obtain rather sensitive responses.Even test samples without any pretreatment can be used as template.This feature suggests that LAMP is superior to PCR in developing point-of-care test strategies.In this study,using Stx1 gene from E.coli as model,we verified that viable cells,dead cells and extracellular DNA could function as template in the LAMP assay.In the incubation at 63℃,viable bacteria in the LAMP reaction mixture lysed completely within 2 min,providing DNA template for nucleic acid amplification.The Stx1 gene in diluted culture medium,spiked tap water,spiked seawater and real seawater all could be detected,with or without the step of DNA extraction.We found that the complex substances in real sample(e.g.natural seawater)exhibited considerable inhibitory effect on the sensitivity of the LAMP assay.These outcomes are meaningful for building a point-of-care strategy by employing the LAMP assay for environmental monitoring,bio-resource surveys,food safety,etc.in particular those based on environmental DNA.

SUCCESSIVE BEAMFORMING,MULTIUSER DETECTION AND DIVERSITY RECEPTION FOR MULTICARRIER DS-CDMA SYSTEM WITH ANTENNA ARRAY

Code-Division Multiple-Access (CDMA) systems are interference limited,and therefore efficient interference management is necessary to enhance the performance of a CDMA system.In this paper,a successive beamforming (spatial filtering),linear decorrelating MultiUser Detection (MUD, temporal filtering) and diversity reception structure for uplink multicarrier Direct Sequence CDMA (DS-CDMA) system with antenna array are proposed.By beamforming,the antenna array suppresses interference according to the distinct array signature.Subsequently,linear decorrelating MUD is ap- plied to separate the signals of different users and eliminate Multiple Access Interference (MAI).Finally, the decorrelated signals at different subcarriers that belong to the same user are combined to achieve frequency diversity.Simulation results show that the proposed structure offers significant Bit Error Rate (BER) performance improvement by successively exploiting the space-time-frequency processing.

Integrate Liveness Detection with Iris Verification to Construct Support Biometric System

The probabilities for the technology to be spoofed are widely acknowledged in biometric verification system. Important efforts have been conducted to study such threats and to develop countermeasures to direct attacks to the biometric verification system to ensure the security of these systems against spoof attacks and reduce this risk, by using another module that is added to the biometric verification system called the “liveness detection” which uses different anatomical properties to distinguish between real and fake traits. Thus, the robustness of the system against direct attacks can be improved through increasing the security level offered to the final user. This paper is an attempt to construct support biometric security system to protect the iris biometric verification system from spoof attacks, through integrating the iris verification system with addition module called liveness detection which composed of two sub-modules (static and dynamic). A test has been performed, for iris verification phase performed on two types of database (MMU DB) for 180 samples and (CASIA DB) for 90 samples, and gave accuracy (99.44%) with FAR of (0.0277) and FRR (0.0055) for MMU DB, and accuracy (97.77%) with FAR of (0.0333) and FRR (0.0222) for CASIA DB.

Direction Detecting System of Indoor Smartphone Users Using BLE in IoT

Indoor organization user activity’s (UA) direction detection monitoring system and also emergency prediction are major challenging tasks in the field of the typical body sensor and indoor fixed sensor networks. In this paper, indoor UA based direction detection monitoring system is achieved by the combination of both the orientation sensor and Bluetooth Low Energy (BLE) in user’s smartphones belonging to the Internet of Things (IoT). The orientation sensor senses the actual orientation of the user and BLE transmits the sensed BLE signals to monitoring system using star topology in IoT. In monitoring system, classification algorithm is used to identify the directions of the smartphone users. The emergency situation of the user is also predicted based on signal variation instantly in real time. The user activity’s signals are captured using LabVIEW toolkit then applied to various classification algorithms such asRF—91.42%, Ibk—90.55%, j48— 85.61%, K*—73.54% are the results obtained. An average of 85% was obtained in all the classifi- cation algorithims indicating the consistency and accuracy in detecting the directions of the users. RF was found to be the best among all the classification algorithms. IoT enabled devices have high demand in near coming future, moreover smartphones users increase day by day, hence implementing and maintaining the above said system would be much easier and cheaper compared to other conventional networks.