scholarly journals A JITTER DETECTION METHOD BASED ON THE INTEGRATION IMAGING MODEL

2020 ◽  
Vol V-3-2020 ◽  
pp. 709-715
Author(s):  
G. Ye ◽  
J. Pan ◽  
Y. Zhu ◽  
S. Jin
Keyword(s):  
Random Error ◽  
Detection Method ◽  
Image Space ◽  
Multispectral Images ◽  
Error Source ◽  
Image Degradation ◽  
Object Space ◽  
Imaging Model ◽  
The Relationship

Abstract. Satellite jitter is a random error source which leads to image degradation. This paper proposes a method to detect the time-variant jitter using multispectral images. In the method, multispectral images are adopted for their large overlap to obtain the parallax map. The imaging process is analyzed in details, and an integration imaging model is constructed, which takes fully into account the time-variant jitter property and builds the relationship between object space with image space. Besides, multispectral images of ZY-3 satellite were used for experiments, and results show that the presented method obtains the jitter curve with the error of amplitude, frequency and phase not more than 0.0591 px, 0.0006 Hz and 0.007 rad, respectively. Results demonstrate the performance of the presented method in jitter detection.

scholarly journals Correspondence Learning for Deep Multi-Modal Recognition and Fraud Detection

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 800
Author(s):  
Jongchan Park ◽  
Min-Hyun Kim ◽  
Dong-Geol Choi
Keyword(s):  
Deep Learning ◽  
Simple Technique ◽  
Detection Method ◽  
Fraud Detection ◽  
Complementary Information ◽  
Multiple Modalities ◽  
Vending Machines ◽  
Emotion Intensity ◽  
The Relationship ◽  
Extract Information

Deep learning-based methods have achieved good performance in various recognition benchmarks mostly by utilizing single modalities. As different modalities contain complementary information to each other, multi-modal based methods are proposed to implicitly utilize them. In this paper, we propose a simple technique, called correspondence learning (CL), which explicitly learns the relationship among multiple modalities. The multiple modalities in the data samples are randomly mixed among different samples. If the modalities are from the same sample (not mixed), then they have positive correspondence, and vice versa. CL is an auxiliary task for the model to predict the correspondence among modalities. The model is expected to extract information from each modality to check correspondence and achieve better representations in multi-modal recognition tasks. In this work, we first validate the proposed method in various multi-modal benchmarks including CMU Multimodal Opinion-Level Sentiment Intensity (CMU-MOSI) and CMU Multimodal Opinion Sentiment and Emotion Intensity (CMU-MOSEI) sentiment analysis datasets. In addition, we propose a fraud detection method using the learned correspondence among modalities. To validate this additional usage, we collect a multi-modal dataset for fraud detection using real-world samples for reverse vending machines.

scholarly journals DENSE 3D POINT CLOUD GENERATION FROM UAV IMAGES FROM IMAGE MATCHING AND GLOBAL OPTIMAZATION

2016 ◽  
Vol XLI-B1 ◽  
pp. 1005-1009 ◽  
Author(s):  
S. Rhee ◽  
T. Kim
Keyword(s):  
Global Optimization ◽  
Image Matching ◽  
Point Clouds ◽  
Image Space ◽  
Object Space ◽  
3D Point Clouds ◽  
Local Point ◽  
Matching Technique ◽  
Uav Images ◽  
Orientation Parameters

3D spatial information from unmanned aerial vehicles (UAV) images is usually provided in the form of 3D point clouds. For various UAV applications, it is important to generate dense 3D point clouds automatically from over the entire extent of UAV images. In this paper, we aim to apply image matching for generation of local point clouds over a pair or group of images and global optimization to combine local point clouds over the whole region of interest. We tried to apply two types of image matching, an object space-based matching technique and an image space-based matching technique, and to compare the performance of the two techniques. The object space-based matching used here sets a list of candidate height values for a fixed horizontal position in the object space. For each height, its corresponding image point is calculated and similarity is measured by grey-level correlation. The image space-based matching used here is a modified relaxation matching. We devised a global optimization scheme for finding optimal pairs (or groups) to apply image matching, defining local match region in image- or object- space, and merging local point clouds into a global one. For optimal pair selection, tiepoints among images were extracted and stereo coverage network was defined by forming a maximum spanning tree using the tiepoints. From experiments, we confirmed that through image matching and global optimization, 3D point clouds were generated successfully. However, results also revealed some limitations. In case of image-based matching results, we observed some blanks in 3D point clouds. In case of object space-based matching results, we observed more blunders than image-based matching ones and noisy local height variations. We suspect these might be due to inaccurate orientation parameters. The work in this paper is still ongoing. We will further test our approach with more precise orientation parameters.

Acousmatic Approaches to the Construction of Image and Space in Sound Art

2015 ◽  
Vol 20 (2) ◽  
pp. 148-159 ◽  
Author(s):  
Peter Batchelor
Keyword(s):  
Current Trend ◽  
Image Space ◽  
Sound Art ◽  
Concert Hall ◽  
Spatial Sound ◽  
Alternative Means ◽  
Acousmatic Music ◽  
Relationship Of ◽  
The Relationship

This article considers ideas of image and space as they apply to acousmatic music and to sound art, establishing overlaps and compatibilities which are perhaps overlooked in the current trend to consider these two genres incompatible. Two issues in particular are considered: compositional (especially mimesis and the construction of image, and what shall be termed ‘ephemeral narrative’) and presentational (in particular multichannel speaker deployment). While exploring several relevant works within this discussion, by way of a case study the article introduces the author’s GRIDs project – a series of four multichannel sound sculptures united in their arrangement in geometric arrays of many (in some cases potentially hundreds of) loudspeakers. These permit, by virtue of being so massively (and geometrically) multichannel, the generation of extremely intricate spatial sound environments – fabricated landscapes – that emerge directly from an acousmatic compositional aesthetic. Owing to their alternative means of presentation and presentation contexts, however, they offer very different experiences from those of acousmatic music encountered in the concert hall. So the latter part of this article explores the various ways in which the listener might engage with constructed image space within these sound sculptures, along with the relationship of the audio content of each with its visual and situational setup – that is, its environment.

scholarly journals CYP450s-Activity Relations of Celastrol to Interact with Triptolide Reveal the Reasons of Hepatotoxicity of Tripterygium wilfordii

Molecules ◽  
2019 ◽  
Vol 24 (11) ◽  
pp. 2162 ◽  
Author(s):  
Chunhuan Jin ◽  
Zijun Wu ◽  
Lili Wang ◽  
Yoshikatsu Kanai ◽  
Xin He
Keyword(s):  
Mitochondrial Membrane ◽  
Detection Method ◽  
Enzyme Inhibitor ◽  
Rat Hepatocytes ◽  
Toxic Effects ◽  
Tripterygium Wilfordii ◽  
Primary Rat Hepatocytes ◽  
Underlying Mechanisms ◽  
The Relationship ◽  
Potential Hepatotoxicity

Celastrol and triptolide, as the two main bio-activity ingredients in Tripterygium wilfordii, have wide anticancer pharmacological potency, as well as anti-inflammatory and immunosuppression effects. However, they have potential hepatotoxicity and underlying mechanisms of them-induced toxicity mediated by hepatic CYP450s have not been well delineated. In the present study, we accessed the toxic effects and possible mechanism of celastrol and triptolide on primary rat hepatocytes. Models of subdued/enhanced activity of CYP450 enzymes in primary rat hepatocytes were also constructed to evaluate the relationship between the two ingredients and CYP450s. LC-MS/MS was used to establish a detection method of the amount of triptolide in rat hepatocytes. As the results, cell viability, biochemical index, and mitochondrial membrane potential indicated that celastrol and triptolide had toxic potencies on hepatocytes. Moreover, the toxic effects were enhanced when the compounds combined with 1-aminobenzotriazole (enzyme inhibitor) while they were mitigated when combined with phenobarbital (an enzyme inducer). Meanwhile, celastrol could affect the amount of triptolide in the cell. We therefore put forward that increase of triptolide in the cell might be one of the main causes of hepatotoxicity caused by Tripterygium wilfordii.

scholarly journals egoDetect: Visual Detection and Exploration of Anomaly in Social Communication Network

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5895
Author(s):  
Jiansu Pu ◽  
Jingwen Zhang ◽  
Hui Shao ◽  
Tingting Zhang ◽  
Yunbo Rao
Keyword(s):  
Social Networks ◽  
Anomaly Detection ◽  
Communication Networks ◽  
Social Communication ◽  
Detection Method ◽  
Detection Methods ◽  
Visualization System ◽  
Egocentric Network ◽  
Unsupervised Anomaly Detection ◽  
The Relationship

The development of the Internet has made social communication increasingly important for maintaining relationships between people. However, advertising and fraud are also growing incredibly fast and seriously affect our daily life, e.g., leading to money and time losses, trash information, and privacy problems. Therefore, it is very important to detect anomalies in social networks. However, existing anomaly detection methods cannot guarantee the correct rate. Besides, due to the lack of labeled data, we also cannot use the detection results directly. In other words, we still need human analysts in the loop to provide enough judgment for decision making. To help experts analyze and explore the results of anomaly detection in social networks more objectively and effectively, we propose a novel visualization system, egoDetect, which can detect the anomalies in social communication networks efficiently. Based on the unsupervised anomaly detection method, the system can detect the anomaly without training and get the overview quickly. Then we explore an ego’s topology and the relationship between egos and alters by designing a novel glyph based on the egocentric network. Besides, it also provides rich interactions for experts to quickly navigate to the interested users for further exploration. We use an actual call dataset provided by an operator to evaluate our system. The result proves that our proposed system is effective in the anomaly detection of social networks.

Mutual noncollinear mapping of object space and visible-image space

2008 ◽  
Vol 75 (3) ◽  
pp. 166
Author(s):  
G. K. Potapova ◽  
M. A. Moskalenko
Keyword(s):  
Image Space ◽  
Visible Image ◽  
Object Space

New Online Detection Method of State of Charge of Car Batteries

2012 ◽  
Vol 253-255 ◽  
pp. 2130-2134 ◽  
Author(s):  
Li Bei ◽  
Zhang Di ◽  
Lu Lu Du
Keyword(s):  
Theoretical Analysis ◽  
Detection Method ◽  
Discharge Rate ◽  
The State ◽  
State Of Charge ◽  
Lead Acid Battery ◽  
Depth Of Discharge ◽  
Environment Temperature ◽  
The Relationship ◽  
Reliable Basis

By theoretical analysis and experiment, this article studied the rebound voltage of lead-acid battery when off-lined. By considering elements as discharge rate, depth of discharge, and environment temperature and so on, we experimented and found the relationship between the rebound voltage and the state of charge (SOC) of battery, which provided reliable basis to estimate the SOC of battery by rebound voltage.

The Current Using Situation of SBS Modified Asphalt in China and a New Method of Monitoring SBS Modifier Dosage

2013 ◽  
Vol 706-708 ◽  
pp. 575-578
Author(s):  
Jia Le Song ◽  
Chang Yong Ye ◽  
Bai Lin Wang ◽  
Zhi Mi Zhou ◽  
Yan Xiao ◽  
...  
Keyword(s):  
Molecular Weight ◽  
High Temperature ◽  
Research Group ◽  
Detection Method ◽  
Microscopic Analysis ◽  
Construction Site ◽  
Modified Asphalt ◽  
Sbs Modified Asphalt ◽  
The Relationship ◽  
Fluorescence Microscopic Analysis

The relationship between the SBS modifier types and asphalt components on the effect of modified asphalt properties was discussed in this paper. Higher block ratio, higher molecular weight and star-like structure of SBS can improve modified asphalt high temperature properties. Colloid content decrease leading the processing easier, result stability decline. Our research group invented a chemical titration combined with fluorescence microscopic analysis detection method monitoring SBS modifier dosage. This method applied in highway construction site, the effect is significant.

Quantification of proteins using enhanced etching of Ag coated Au nanorods by the Cu2+/bicinchoninic acid pair with improved sensitivity

Nanoscale ◽  
2016 ◽  
Vol 8 (2) ◽  
pp. 780-784 ◽  
Author(s):  
Wenqi Liu ◽  
Shuai Hou ◽  
Jiao Yan ◽  
Hui Zhang ◽  
Yinglu Ji ◽  
...  
Keyword(s):  
Protein Oxidation ◽  
Detection Method ◽  
Peak Shift ◽  
Au Nanorods ◽  
Bicinchoninic Acid ◽  
The Relationship

We present an SPR detection method to quantify proteins by building up the relationship between the LSPR peak shift of Au@Ag nanorods and the protein amount via Cu2+/BCA pair bridged protein oxidation and Au@Ag etching.

scholarly journals Analysis of the Effects of Arc Volt–Ampere Characteristics on Different Loads and Detection Methods of Series Arc Faults

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 323 ◽  
Author(s):  
Qiwei Lu ◽  
Zeyu Ye ◽  
Yilei Zhang ◽  
Tao Wang ◽  
Zhixuan Gao
Keyword(s):  
Fault Detection ◽  
Research And Development ◽  
Hardware Implementation ◽  
Detection Method ◽  
Low Cost ◽  
Experimental Methods ◽  
Experimental Results ◽  
National Standard ◽  
Detection Methods ◽  
The Relationship

Owing to the shortcomings of existing series arc fault detection methods, based on a summary of arc volt–ampere characteristics, the change rule of the line current and the relationship between the voltage and current are deeply analyzed and theoretically explained under different loads when series arc faults occur. A series arc fault detection method is proposed, and the software flowchart and principles of the applied hardware implementation are given. Finally, a prototype of an arc fault detection device (AFDD) with a rated voltage of 220 V and a rated current of 40 A is developed. The prototype was tested according to experimental methods provided by the Chinese national standard, GB/T 31143-2014. The experimental results show that the proposed detection method is simple and practical, and can be implemented using a low-cost microprocessor. The proposed method will provide good theoretical guidance in promoting the research and development of an AFDD.

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