A Comprehensive Detection Approach of Nmap: Principles, Rules and Experiments

2020 ◽  
Author(s):  
Si Liao ◽  
Chenming Zhou ◽  
Yonghui Zhao ◽  
Zhiyu Zhang ◽  
Chengwei Zhang ◽  
...  
Keyword(s):  
Detection Approach

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

Associations between collectivism and perception of social threat: a signal detection approach

2019 ◽  
Author(s):  
Tuong-Van Vu ◽  
Catrin Finkenauer ◽  
Lydia Krabbendam
Keyword(s):  
Signal Detection ◽  
Response Bias ◽  
Social Adjustment ◽  
Emotional Expressions ◽  
Social Threat ◽  
Threat Detection ◽  
Perceptual Sensitivity ◽  
Detection Approach ◽  
Self Construal ◽  
The Individual

Collectivistic orientation, which entails interdependent self-construal and concern for interpersonal harmony and social adjustment, has been suggested to be associated with detecting emotional expressions that signal social threat than individualistic orientation, which entails independent self-construal. The present research tested if this detection is a result of enhanced perceptual sensitivity or of response bias. We used country as proxy of individualism and collectivism (Country IC), measured IC of individuals with a questionnaire (Individual IC) and manipulated IC with culture priming (Situational IC). Dutch participants in the Netherlands (n = 143) and Chinese participants in China (n = 151) performed a social threat detection task where they had to categorize ambiguous facial expressions as “angry” or “not angry”. As the stimuli varied in degrees of scowling and frequency of presentation, we were able to measure the participants' perceptual sensitivity and response bias following the principles of the Signal Detection Theory. On the Country IC level, the results indicated that individualism-representative Dutch participants had higher perceptual sensitivity than collectivism-representative Chinese participants; whereas, Chinese participants were more biased towards categorizing a scowling face as “angry” than the Dutch (i.e. stronger liberal bias). In both groups, collectivism on the Individual IC was associated with a bias towards recognizing a scowling face as “not angry” (i.e. stronger conservative bias). Culture priming (Situational IC) affected neither perceptual sensitivity nor response bias. Our data suggested that cultural differences were in the form of behavioral tendency and IC entails multiple constructs linked to different outcomes in social threat detection.

Detection Approach of DDoS Attacks Based on Conditional Random Fields

2011 ◽  
Vol 22 (8) ◽  
pp. 1897-1910 ◽  
Author(s):  
Yun LIU ◽  
Zhi-Ping CAI ◽  
Ping ZHONG ◽  
Jian-Ping YIN ◽  
Jie-Ren CHENG
Keyword(s):  
Random Fields ◽  
Conditional Random Fields ◽  
Ddos Attacks ◽  
Detection Approach

A Constant False Alarm Rate-(CFAR) Based Change Detection Approach to Helicopter Diagnostics

2008 ◽  
Author(s):  
Kenneth Ranney ◽  
Hiralal Khatri ◽  
Jerry Silvious ◽  
Kwok Tom ◽  
Romeo del Rosario
Keyword(s):  
Change Detection ◽  
False Alarm ◽  
False Alarm Rate ◽  
Constant False Alarm Rate ◽  
Detection Approach

scholarly journals Cloud Detection Based on High Resolution Stereo Pairs of the Geostationary Meteosat Images

2020 ◽  
Vol 12 (3) ◽  
pp. 371 ◽  
Author(s):  
Sahar Dehnavi ◽  
Yasser Maghsoudi ◽  
Klemen Zakšek ◽  
Mohammad Javad Valadan Zoej ◽  
Gunther Seckmeyer ◽  
...  
Keyword(s):  
High Resolution ◽  
Matched Filter ◽  
Stereo Pair ◽  
Cloud Detection ◽  
Operating Characteristics ◽  
Detection Techniques ◽  
Infrared Imager ◽  
Detection Approach ◽  
Considerable Impact ◽  
Image Pairs

Due to the considerable impact of clouds on the energy balance in the atmosphere and on the earth surface, they are of great importance for various applications in meteorology or remote sensing. An important aspect of the cloud research studies is the detection of cloudy pixels from the processing of satellite images. In this research, we investigated a stereographic method on a new set of Meteosat images, namely the combination of the high resolution visible (HRV) channel of the Meteosat-8 Indian Ocean Data Coverage (IODC) as a stereo pair with the HRV channel of the Meteosat Second Generation (MSG) Meteosat-10 image at 0° E. In addition, an approach based on the outputs from stereo analysis was proposed to detect cloudy pixels. This approach is introduced with a 2D-scatterplot based on the parallax value and the minimum intersection distance. The mentioned scatterplot was applied to determine/detect cloudy pixels in various image subsets with different amounts of cloud cover. Apart from the general advantage of the applied stereography method, which only depends on geometric relationships, the cloud detection results are also improved because: (1) The stereo pair is the HRV bands of the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) sensor, with the highest spatial resolution available from the Meteosat geostationary platform; and (2) the time difference between the image pairs is nearly 5 s, which improves the matching results and also decreases the effect of cloud movements. In order to prove this improvement, the results of this stereo-based approach were compared with three different reflectance-based target detection techniques, including the adaptive coherent estimator (ACE), constrained energy minimization (CEM), and matched filter (MF). The comparison of the receiver operating characteristics (ROC) detection curves and the area under these curves (AUC) showed better detection results with the proposed method. The AUC value was 0.79, 0.90, 0.90, and 0.93 respectively for ACE, CEM, MF, and the proposed stereo-based detection approach. The results of this research shall enable a more realistic modelling of down-welling solar irradiance in the future.

scholarly journals Bridge Damage Detection Approach Using a Roving Camera Technique

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1246 ◽  
Author(s):  
Darragh Lydon ◽  
Myra Lydon ◽  
Rolands Kromanis ◽  
Chuan-Zhi Dong ◽  
Necati Catbas ◽  
...  
Keyword(s):  
Low Cost ◽  
Normal Operation ◽  
Laboratory Model ◽  
Traffic Patterns ◽  
Operational Conditions ◽  
Bridge Model ◽  
Detection Approach ◽  
Bridge Damage ◽  
Computer Vision Technology ◽  
Climate Events

Increasing extreme climate events, intensifying traffic patterns and long-term underinvestment have led to the escalated deterioration of bridges within our road and rail transport networks. Structural Health Monitoring (SHM) systems provide a means of objectively capturing and quantifying deterioration under operational conditions. Computer vision technology has gained considerable attention in the field of SHM due to its ability to obtain displacement data using non-contact methods at long distances. Additionally, it provides a low cost, rapid instrumentation solution with low interference to the normal operation of structures. However, even in the case of a medium span bridge, the need for many cameras to capture the global response can be cost-prohibitive. This research proposes a roving camera technique to capture a complete derivation of the response of a laboratory model bridge under live loading, in order to identify bridge damage. Displacement is identified as a suitable damage indicator, and two methods are used to assess the magnitude of the change in global displacement under changing boundary conditions in the laboratory bridge model. From this study, it is established that either approach could detect damage in the simulation model, providing an SHM solution that negates the requirement for complex sensor installations.

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