Differences in Pre-Attentive Processes of Sound Intensity Change Between High- and Low-Sensation Seekers

2017 ◽  
Vol 31 (1) ◽  
pp. 29-37 ◽  
Author(s):  
Siqi He ◽  
Yao Chai ◽  
Jinbo He ◽  
Yongyu Guo ◽  
Risto Näätänen
Keyword(s):  
Change Detection ◽  
Mismatch Negativity ◽  
Sound Intensity ◽  
High Sensitivity ◽  
External Stimulus ◽  
Intensity Change ◽  
The Difference ◽  
Cortical Change

Abstract. High-sensation seekers are prone to search for changing stimuli. Pre-attentive processes reveal the earliest cortical change detection in response to external stimulus changes. This study recorded the mismatch negativity (MMN) to intensity increments and decrements in a repetitive tone in high- and low-sensation seekers. It was found that the MMN amplitude for intensity-decrement deviants was larger in high- than low-sensation seekers. However, with regard to deviant-increment stimulation, the difference between the two groups was not significant. Consequently, the sensitivity of high-sensitivity seekers to pre-attentively detect a decrease in sound intensity is higher than that of low-sensation seekers.

Bruch’s membrane opening-minimum rim width: An alternative OCT biomarker study for multiple sclerosis

2021 ◽  
pp. 112067212199663
Author(s):  
Kemal Turgay Özbilen ◽  
Tuncay Gündüz ◽  
Selva Nur Çukurova Kartal ◽  
Ali Ceyhun Gedik ◽  
Mefküre Eraksoy ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
High Sensitivity ◽  
The Novel ◽  
Bruch's Membrane ◽  
Bruch’S Membrane ◽  
Spectral Domain Oct ◽  
Neuroretinal Rim ◽  
Bruch’S Membrane Opening ◽  
The Difference ◽  
Therapeutic Decision Making

Purpose: Bruch’s membrane opening-minimum rim width (BMO-MRW) and RNFL measured using anatomic positioning system (APS-RNFL) are novel OCT methods and remained unexplored in MS patients. To investigate the novel parameters of spectral-domain OCT as an alternative biomarker in patients with multiple sclerosis (MS). Methods: Retrospective cohort study; participants consisted of relapsing-remitting MS (RRMS) patients and healthy controls (HC). Eyes were classified according to the presence of MS and previous optic neuritis (ON). Measurements of standard peripapillary RNFL (S-RNFL), BMO-MRW, and APS-RNFL were performed. Result: A total of 244 eyes of 122 participants (MS-patients: 63, HC: 59) were included in the study. Fifty-one eyes had a history of previous ON. In almost all measured parameters, neuroretinal rim thicknesses were observed the thinnest in eyes with ON history between all subgroups. S-RNFL and APS-RNFL techniques showed the difference in neuroretinal rim thickness in all three subjects (ON+, ON−, and HC). However, BMO-MRW, on the other hand, could not distinguish between ON(−) patients and HC. The relationship between OCT parameters and EDSS were observed only in eyes with an ON history in all three techniques. A meaningful model with 78% accuracy was obtained by using only the OCT parameters as risk factors. In the ROC analysis, no parameters were found to have acceptable high sensitivity and specificity. BMO-MRW was statistically weaker in every aspect than other RNFL techniques. Conclusion: The novel APS-RNFL technique appears to be a bit more reliable alternative to S-RNFL technique to support therapeutic decision-making in MS. BMO-MRW has not been found as a successful alternative to S-RNFL.

Core-shell Cu@C@ZIF-8 composite: a high-performance electrode material for electrochemical sensing of nitrite with high selectivity and sensitivity

2021 ◽  
Author(s):  
Feng Gao ◽  
Xiaolong Tu ◽  
Yongfang Yu ◽  
Yansha Gao ◽  
Jin Zou ◽  
...  
Keyword(s):  
High Performance ◽  
High Selectivity ◽  
Limit Of Detection ◽  
Metal Organic Framework ◽  
High Sensitivity ◽  
Electrochemical Sensing ◽  
Core Shell ◽  
Zeolitic Imidazolate Framework ◽  
Sensing Platform ◽  
The Difference

Abstract Herein, an efficient electrochemical sensing platform is proposed for selective and sensitive detection of nitrite on the basis of Cu@C@Zeolitic imidazolate framework-8 (Cu@C@ZIF-8) heterostructure. Core-shell Cu@C@ZIF-8 composite was synthesized by pyrolysis of Cu-metal-organic framework@ZIF-8 (Cu-MOF@ZIF-8) in Ar atmosphere on account of the difference of thermal stability between Cu-MOF and ZIF-8. For the sensing system of Cu@C@ZIF-8, ZIF-8 with proper pore size allows nitrite diffuse through the shell, while big molecules cannot, which ensures high selectivity of the sensor. On the other hand, Cu@C as electrocatalyst promotes the oxidation of nitrite, thereby resulting high sensitivity of the sensor. Accordingly, the Cu@C@ZIF-8 based sensor presents excellent performance for nitrite detection, which achieves a wide linear response range of 0.1 µM to 300.0 µM, and a low limit of detection (LOD) of 0.033 µM. In addition, the Cu@C@ZIF-8 sensor possesses excellent stability and reproducibility, and was employed to quantify nitrite in sausage samples with recoveries of 95.45-104.80%.

scholarly journals A Novel Active Contours Model for Environmental Change Detection from Multitemporal Synthetic Aperture Radar Images

2020 ◽  
Vol 12 (11) ◽  
pp. 1746
Author(s):  
Salman Ahmadi ◽  
Saeid Homayouni
Keyword(s):  
Synthetic Aperture Radar ◽  
Change Detection ◽  
Active Contours ◽  
Training Data ◽  
Synthetic Aperture ◽  
Data Sets ◽  
Difference Image ◽  
Proposed Model ◽  
The Difference ◽  
Aperture Radar

In this paper, we propose a novel approach based on the active contours model for change detection from synthetic aperture radar (SAR) images. In order to increase the accuracy of the proposed approach, a new operator was introduced to generate a difference image from the before and after change images. Then, a new model of active contours was developed for accurately detecting changed regions from the difference image. The proposed model extracts the changed areas as a target feature from the difference image based on training data from changed and unchanged regions. In this research, we used the Otsu histogram thresholding method to produce the training data automatically. In addition, the training data were updated in the process of minimizing the energy function of the model. To evaluate the accuracy of the model, we applied the proposed method to three benchmark SAR data sets. The proposed model obtains 84.65%, 87.07%, and 96.26% of the Kappa coefficient for Yellow River Estuary, Bern, and Ottawa sample data sets, respectively. These results demonstrated the effectiveness of the proposed approach compared to other methods. Another advantage of the proposed model is its high speed in comparison to the conventional methods.

scholarly journals SAR Image Change Detection Based on Multi-scale Feature Extraction

2021 ◽  
Vol 10 (4) ◽  
pp. 077-081
Author(s):  
Xiaoqian Yuan ◽  
Chao Chen ◽  
Shan Tian ◽  
Jiandan Zhong
Keyword(s):  
Feature Extraction ◽  
Change Detection ◽  
Speckle Noise ◽  
Kernel Matrix ◽  
Sar Image ◽  
Scale Feature ◽  
Difference Image ◽  
Multi Scale ◽  
Image Change Detection ◽  
The Difference

In order to improve the contrast of the difference image and reduce the interference of the speckle noise in the synthetic aperture radar (SAR) image, this paper proposes a SAR image change detection algorithm based on multi-scale feature extraction. In this paper, a kernel matrix with weights is used to extract features of two original images, and then the logarithmic ratio method is used to obtain the difference images of two images, and the change area of the images are extracted. Then, the different sizes of kernel matrix are used to extract the abstract features of different scales of the difference image. This operation can make the difference image have a higher contrast. Finally, the cumulative weighted average is obtained to obtain the final difference image, which can further suppress the speckle noise in the image.

scholarly journals Object-oriented change detection based on weighted polarimetric scattering differences on POLSAR images

2015 ◽  
Vol XL-7/W4 ◽  
pp. 149-154 ◽  
Author(s):  
X. Shi ◽  
L. Lu ◽  
S. Yang ◽  
G. Huang ◽  
Z. Zhao
Keyword(s):  
Change Detection ◽  
Covariance Matrix ◽  
Polarization State ◽  
Object Oriented ◽  
Detection Accuracy ◽  
Processing Unit ◽  
Processing Technologies ◽  
The Difference ◽  
Sar Imagery ◽  
Reasonable Choice

For wide application of change detection with SAR imagery, current processing technologies and methods are mostly based on pixels. It is difficult for pixel-based technologies to utilize spatial characteristics of images and topological relations of objects. Object-oriented technology takes objects as processing unit, which takes advantage of the shape and texture information of image. It can greatly improve the efficiency and reliability of change detection. Recently, with the development of polarimetric synthetic aperture radar (PolSAR), more backscattering features on different polarization state can be available for usage of object-oriented change detection study. In this paper, the object-oriented strategy will be employed. Considering the fact that the different target or target's state behaves different backscattering characteristics dependent on polarization state, an object-oriented change detection method that based on weighted polarimetric scattering difference of PolSAR images is proposed. The method operates on the objects generated by generalized statistical region merging (GSRM) segmentation processing. The merit of GSRM method is that image segmentation is executed on polarimetric coherence matrix, which takes full advantages of polarimetric backscattering features. And then, the measurement of polarimetric scattering difference is constructed by combining the correlation of covariance matrix and the difference of scattering power. Through analysing the effects of the covariance matrix correlation and the scattering echo power difference on the polarimetric scattering difference, the weighted method is used to balance the influences caused by the two parts, so that more reasonable weights can be chosen to decrease the false alarm rate. The effectiveness of the algorithm that proposed in this letter is tested by detection of the growth of crops with two different temporal radarsat-2 fully PolSAR data. First, objects are produced by GSRM algorithm based on the coherent matrix in the pre-processing. Then, the corresponding patches are extracted in two temporal images to measure the differences of objects. To detect changes of patches, a difference map is created by means of weighted polarization scattering difference. Finally, the result of change detection can be obtained by threshold determining. The experiments show that this approach is feasible and effective, and a reasonable choice of weights can improve the detection accuracy significantly.

scholarly journals Urban Change Detection in TerraSAR Image Using the Difference Method and SAR Coherence Coefficient

2018 ◽  
Vol 11 (3) ◽  
pp. 18-23 ◽  
Author(s):  
Zhang Xuedong ◽  
◽  
Liu Wenxi ◽  
He Shuguang ◽  
◽  
...  
Keyword(s):  
Change Detection ◽  
Difference Method ◽  
Urban Change ◽  
The Difference

scholarly journals Effects of External Acidification on the Blood Acid-Base Status and Ion Concentrations of Lamprey

1988 ◽  
Vol 136 (1) ◽  
pp. 351-361
Author(s):  
LEONA MATTSOFF ◽  
MIKKO NIKINMAA
Keyword(s):  
High Sensitivity ◽  
Co2 Concentration ◽  
Acid Base ◽  
Ion Concentrations ◽  
Ph Response ◽  
Ph Values ◽  
Blood Ph ◽  
Acid Base Status ◽  
The Difference ◽  
K Concentration

We studied the effects of acute external acidification on the acid-base status and plasma and red cell ion concentrations of lampreys. Mortality was observed within 24 h at pH5 and especially at pH4. The main reason for the high sensitivity of lampreys to acid water appears to be the large drop in blood pH: 0.6 and 0.8 units after 24 h at pH5 and pH4, respectively. The drop of plasma pH is much larger than in teleost fishes exposed to similar pH values. The difference in the plasma pH response between lampreys and teleosts probably results from the low buffering capacity of lamprey blood, since red cells cannot participate in buffering extracellular acid loads. Acidification also caused a decrease in both Na+ and C− concentrations and an elevation in K+ concentration of plasma. The drop in plasma Na+ concentration occurred faster than the drop in plasma Cl− concentration which, in turn, coincided with the decrease in total CO2 concentration of the blood.

scholarly journals MRA-SNet: Siamese Networks of Multiscale Residual and Attention for Change Detection in High-Resolution Remote Sensing Images

2021 ◽  
Vol 13 (22) ◽  
pp. 4528
Author(s):  
Xin Yang ◽  
Lei Hu ◽  
Yongmei Zhang ◽  
Yunqing Li
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Change Detection ◽  
Remote Sensing Image ◽  
Image Features ◽  
Remote Sensing Images ◽  
The Rich ◽  
The Difference ◽  
Basic Network ◽  
And Performance

Remote sensing image change detection (CD) is an important task in remote sensing image analysis and is essential for an accurate understanding of changes in the Earth’s surface. The technology of deep learning (DL) is becoming increasingly popular in solving CD tasks for remote sensing images. Most existing CD methods based on DL tend to use ordinary convolutional blocks to extract and compare remote sensing image features, which cannot fully extract the rich features of high-resolution (HR) remote sensing images. In addition, most of the existing methods lack robustness to pseudochange information processing. To overcome the above problems, in this article, we propose a new method, namely MRA-SNet, for CD in remote sensing images. Utilizing the UNet network as the basic network, the method uses the Siamese network to extract the features of bitemporal images in the encoder separately and perform the difference connection to better generate difference maps. Meanwhile, we replace the ordinary convolution blocks with Multi-Res blocks to extract spatial and spectral features of different scales in remote sensing images. Residual connections are used to extract additional detailed features. To better highlight the change region features and suppress the irrelevant region features, we introduced the Attention Gates module before the skip connection between the encoder and the decoder. Experimental results on a public dataset of remote sensing image CD show that our proposed method outperforms other state-of-the-art (SOTA) CD methods in terms of evaluation metrics and performance.

scholarly journals Automatic Change Detection Based on Edge Information Using Two Different Types of Ortho Image

2019 ◽  
Vol 2 ◽  
pp. 1-6
Author(s):  
Akira Sasagawa ◽  
Shuto Sugai ◽  
Mayumi Noguchi
Keyword(s):  
Change Detection ◽  
Conventional Method ◽  
Satellite Image ◽  
Aerial Photo ◽  
Edge Information ◽  
Different Types ◽  
The Difference ◽  
Detection Quality ◽  
Edge Vector ◽  
Robust Result

<p><strong>Abstract.</strong> A new algorithm of automatic change detection for update of base map is presented. In conventional method, using two different types of ortho image, such as aerial photo and satellite image, makes detection quality worse due to the difference of each contrast, brightness, color balance and so on. To obtain robust result against such difference between two images, we introduce edge-vector technique. We applied this method using two ortho images derived from each aerial photo and satellite image. We have tested our method and confirmed a performance of the change detection by the interpretation test. In this paper, the detailed algorithm and the result of interpretation test are reported.</p>

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