scholarly journals Sharpness evaluation of microscopic detection image for micro parts

2022 ◽  
Vol 355 ◽  
pp. 03013
Author(s):  
Xianghui Zhang ◽  
Zhanjiang Yu ◽  
Jinkai Xu ◽  
Huadong Yu
Keyword(s):  
Information Entropy ◽  
Noise Immunity ◽  
Spatial Information ◽  
High Sensitivity ◽  
Image Texture ◽  
Evaluation Function ◽  
Local Variance ◽  
Microscopic Detection ◽  
Micro Parts ◽  
The One

According to the characteristics of micro parts microscopic detection image, including the image texture is similar, the edge information is too little and the gray distribution Range is limited, based on the basic principles of algorithm, analyzes the traditional sharpness evaluation function. Aiming at the defect that the traditional sharpness evaluation function cannot have both high sensitivity and noise immunity, an algorithm based on local variance information entropy is proposed. The method uses the local variance to weight the self-information of each gray level, on the one hand, it makes up for the lack of spatial information of information entropy and avoids misjudgement of sharpness; on the other hand, it can increase the weights of clear region pixels when they participate in the calculation of information, while reducing the weights of background and noise region pixels, thereby improve the function sensitivity. The experimental results show that compared with the traditional sharpness evaluation function, the local variance information entropy function not only has high sensitivity, but also has better noise immunity and is suitable for actual auto-focusing systems.

scholarly journals IIMLP: integrated information-entropy-based method for LncRNA prediction

2021 ◽  
Vol 22 (S3) ◽  
Author(s):  
Junyi Li ◽  
Huinian Li ◽  
Xiao Ye ◽  
Li Zhang ◽  
Qingzhe Xu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Dna Sequences ◽  
Information Entropy ◽  
Area Under The Curve ◽  
Prediction Method ◽  
Machine Learning Algorithms ◽  
Reading Frame ◽  
Non Coding Rna ◽  
The One ◽  
Long Non Coding Rna

Abstract Background The prediction of long non-coding RNA (lncRNA) has attracted great attention from researchers, as more and more evidence indicate that various complex human diseases are closely related to lncRNAs. In the era of bio-med big data, in addition to the prediction of lncRNAs by biological experimental methods, many computational methods based on machine learning have been proposed to make better use of the sequence resources of lncRNAs. Results We developed the lncRNA prediction method by integrating information-entropy-based features and machine learning algorithms. We calculate generalized topological entropy and generate 6 novel features for lncRNA sequences. By employing these 6 features and other features such as open reading frame, we apply supporting vector machine, XGBoost and random forest algorithms to distinguish human lncRNAs. We compare our method with the one which has more K-mer features and results show that our method has higher area under the curve up to 99.7905%. Conclusions We develop an accurate and efficient method which has novel information entropy features to analyze and classify lncRNAs. Our method is also extendable for research on the other functional elements in DNA sequences.

scholarly journals Overview of Popular Techniques of Raman Spectroscopy and Their Potential in the Study of Plant Tissues

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1537
Author(s):  
Aneta Saletnik ◽  
Bogdan Saletnik ◽  
Czesław Puchalski
Keyword(s):  
Raman Spectroscopy ◽  
Cell Walls ◽  
Structural Changes ◽  
Spatial Information ◽  
Technological Development ◽  
Analytical Techniques ◽  
High Sensitivity ◽  
Plant Tissues ◽  
Wide Range ◽  
Identification Technique

Raman spectroscopy is one of the main analytical techniques used in optical metrology. It is a vibration, marker-free technique that provides insight into the structure and composition of tissues and cells at the molecular level. Raman spectroscopy is an outstanding material identification technique. It provides spatial information of vibrations from complex biological samples which renders it a very accurate tool for the analysis of highly complex plant tissues. Raman spectra can be used as a fingerprint tool for a very wide range of compounds. Raman spectroscopy enables all the polymers that build the cell walls of plants to be tracked simultaneously; it facilitates the analysis of both the molecular composition and the molecular structure of cell walls. Due to its high sensitivity to even minute structural changes, this method is used for comparative tests. The introduction of new and improved Raman techniques by scientists as well as the constant technological development of the apparatus has resulted in an increased importance of Raman spectroscopy in the discovery and defining of tissues and the processes taking place in them.

Oil and Methanol Price volatility

2013 ◽  
Vol 03 (08) ◽  
pp. 01-10
Author(s):  
Majid Delavari ◽  
Nadiya Gandali Ali khani ◽  
Esmaeil Naderi
Keyword(s):  
Crude Oil ◽  
Time Series Data ◽  
Price Volatility ◽  
High Sensitivity ◽  
Oil Price ◽  
Series Data ◽  
Cultural Issues ◽  
Crude Oil Price ◽  
Oil Export ◽  
The One

Crude oil as one of the main sources of energy is also the main source of income for members of OPEC. So, the volatility of crude oil price is one of the main economic variables in the world and analysis of the effect of its changes on key economic factors has been always considered as significant. The reason might be the high sensitivity of oil price to political, economic and cultural issues worldwide and consequently its volatility on the one hand, and the high influence of the volatile prices on macroeconomic variables. On the other hand, for different reasons such as oil price volatilities and income from oil export, economic planners and policy makers in Iran have been mainly focused on the promotion of non-oil exports especially during the last few decades. Therefore, methanol as one of the most commonly used petrochemical products has a high potential for production and export of non-oil products in Iran. For this reason, in the present study there was an attempt to examine the relationship between the prices of Iran’s crude oil and methanol using FIGARCH model and based on the weekly time series data related to the research variables. The results of the study showed that the long memory parameter is equal to 0.32 which is meaning the shocks caused by volatility of methanol market and crude oil price to the methanol price were lasting and meaningful and were revealed in the long term.

One-Dimensional Fluorescent Nanosized-Diamond Nanowires with Fluorescent Detection of Vitamin B12

NANO ◽  
2019 ◽  
Vol 14 (07) ◽  
pp. 1950084 ◽  
Author(s):  
Jilong Wang ◽  
Siheng Su ◽  
Jingjing Qiu ◽  
Shiren Wang
Keyword(s):  
Electron Microscopy ◽  
Photoelectron Spectroscopy ◽  
High Sensitivity ◽  
Anodic Aluminum Oxide Template ◽  
Fluorescent Detection ◽  
Dimensional Structure ◽  
Fluorescent Properties ◽  
One Dimensional ◽  
Sensitivity And Selectivity ◽  
The One

In this paper, a novel and facile method to achieve fluorescent nanosized-diamond based nanowire (NW) is reported. One-dimensional (1D) organic NW has received tremendous attention due to its superior chemical functionality and size-, shape-, and material-dependent properties. In addition, nanosized-diamond is comprehensively studied and investigated due to superior tunable fluorescent properties, cost-effectiveness, facile manufacturing and high biocompatibility. Through thermal treatment, sulfur-modified nanosized-diamond was fabricated by mixing oxidized nanosized-diamond and dibenzyl disulfide at 900∘C. Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS) and zeta potential were employed to characterize sulfur-modified nanosized-diamond. After that, porous anodic aluminum oxide template-assisted cathodic electrophoretic deposition method was used to achieve sulfur-modified nanosized-diamond NW. Scanning electron microscopy and transmission electron microscopy were applied to present the one-dimensional structure of the NWs. The optical properties of sulfur nanosized-diamond NW were characterized via ultraviolet-visible spectroscopy and photoluminescence spectroscopy. Finally, the as-synthesized sulfur-modified nanosized-diamond NW-based optical sensor was fabricated to detect vitamin B[Formula: see text] with high sensitivity and selectivity.

scholarly journals Исследование коэффициента диффузии в тонких изделиях из пористых материалов

2019 ◽  
Vol 89 (10) ◽  
pp. 1630
Author(s):  
В.П. Беляев ◽  
С.В. Мищенко ◽  
П.С. Беляев
Keyword(s):  
Mass Transfer ◽  
Porous Media ◽  
Diffusion Coefficient ◽  
Transfer Process ◽  
Noise Immunity ◽  
Measurement Accuracy ◽  
High Sensitivity ◽  
Mass Transfer Process ◽  
Static Characteristic ◽  
Rapid Diffusion

A new method for studying mass transfer process in porous media has been considered, which allows the rapid diffusion coefficient control in thin products without destroying them and without the preliminary calibration of the diffuser concentration meter. The method provides an increase in the measurement accuracy due to the possibility of choosing the measured parameters included in the design expression. Parameters are taking from the segments of converter static characteristic. The converter has high sensitivity and noise immunity.

Chaotic Differential-Evolution-Based Fuzzy Contrast Stretching Method

2018 ◽  
pp. 71-94 ◽  
Author(s):  
Krishna Gopal Dhal ◽  
Sanjoy Das
Keyword(s):  
Differential Evolution ◽  
Objective Function ◽  
Quality Index ◽  
Color Images ◽  
Consumer Electronics ◽  
Grey Level ◽  
Swarm Optimization ◽  
Local Variance ◽  
The One ◽  
Contrast Stretching

This study concentrates to develop one novel parameterized Bi-Histogram Fuzzy Contrast Stretching (BHFCS) method for enhancing the contrast of the grey level as well as color images properly. The parameters of this method have been optimized by employing one modified Chaotic Differential Evolution (CDE) with the combined assistance of Fractal Dimension (FD) and Quality Index based on Local Variance (QILV) as objective function. Experimental results prove that the modified DE gives better result than particle swarm optimization (PSO), genetic algorithm (GA) and traditional DE in this enhancement domain and the used objective function is also very useful to preserve the image's original brightness which is the one of the main criterion of the consumer electronics field.

scholarly journals Highly Sensitive Diode-Based Micro-Pirani Vacuum Sensor with Low Power Consumption

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 188 ◽  
Author(s):  
Debo Wei ◽  
Jianyu Fu ◽  
Ruiwen Liu ◽  
Ying Hou ◽  
Chao Liu ◽  
...  
Keyword(s):  
Power Consumption ◽  
Low Power ◽  
Forward Bias ◽  
High Sensitivity ◽  
Bias Current ◽  
Low Power Consumption ◽  
Sensor Performance ◽  
Sensor Structure ◽  
Vacuum Sensor ◽  
The One

Micro-Pirani vacuum sensors usually operate at hundreds of microwatts, which limits their application in battery-powered sensor systems. This paper reports a diode-based, low power consumption micro-Pirani vacuum sensor that has high sensitivity. Optimizations to the micro-Pirani vacuum sensor were made regarding two aspects. On the one hand, a greater temperature coefficient was obtained without increasing power consumption by taking advantage of series diodes; on the other hand, the sensor structure and geometries were redesigned to enlarge temperature variation. After that, the sensor was fabricated and tested. Test results indicated that the dynamic vacuum pressure range of the sensor was from 10−1 to 104 Pa when the forward bias current was as low as 10 μA with a power consumption of 50 μW. Average sensitivity was up to 90 μV/Pa and the sensitivity of unit power consumption increased to 1.8 V/W/Pa. In addition, the sensor could also work at a greater forward bias current for better sensor performance.

scholarly journals Diagnostic challenges in chronic inflammatory demyelinating polyradiculoneuropathy

Brain ◽  
2020 ◽  
Vol 143 (11) ◽  
pp. 3214-3224
Author(s):  
Filip Eftimov ◽  
Ilse M Lucke ◽  
Luis A Querol ◽  
Yusuf A Rajabally ◽  
Camiel Verhamme
Keyword(s):  
Peripheral Nerves ◽  
Diagnostic Tests ◽  
High Sensitivity ◽  
Nerve Biopsy ◽  
Chronic Inflammatory Demyelinating Polyradiculoneuropathy ◽  
Control Group ◽  
Nerve Ultrasound ◽  
Hand Performance ◽  
The One ◽  
Csf Examination

Abstract Chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) consists of a spectrum of autoimmune diseases of the peripheral nerves, causing weakness and sensory symptoms. Diagnosis often is challenging, because of the heterogeneous presentation and both mis- and underdiagnosis are common. Nerve conduction study (NCS) abnormalities suggestive of demyelination are mandatory to fulfil the diagnostic criteria. On the one hand, performance and interpretation of NCS can be difficult and none of these demyelinating findings are specific for CIDP. On the other hand, not all patients will be detected despite the relatively high sensitivity of NCS abnormalities. The electrodiagnostic criteria can be supplemented with additional diagnostic tests such as CSF examination, MRI, nerve biopsy, and somatosensory evoked potentials. However, the evidence for each of these additional diagnostic tests is limited. Studies are often small without the use of a clinically relevant control group. None of the findings are specific for CIDP, meaning that the results of the diagnostic tests should be carefully interpreted. In this update we will discuss the pitfalls in diagnosing CIDP and the value of newly introduced diagnostic tests such as nerve ultrasound and testing for autoantibodies, which are not yet part of the guidelines.

Development of drawing abilities in a distinct population: Depiction of perceptual principles by three children with congenital total blindness

2003 ◽  
Vol 27 (3) ◽  
pp. 193-200 ◽  
Author(s):  
Amedeo D’Angiulli ◽  
Stefania Maggi
Keyword(s):  
Initial Phase ◽  
Spatial Information ◽  
Vantage Point ◽  
The Other ◽  
Distinct Population ◽  
Congenital Blindness ◽  
Other Hand ◽  
Blind Children ◽  
Total Blindness ◽  
The One

We studied the development of spontaneous tactile drawing in three 12-year-old children with congenital total blindness and with no previous drawing tuition. In a period of 9 months, from an initial phase in which they were taught to draw tangible straight and curve raised lines, the three blind children went on making spontaneous raised outlines representing edges, surfaces of objects, vantage point, and motion. The corpus of drawings produced by these children shows that several aspects of outline pictures can be implemented through touch. The perceptual principles represented in these drawings are comparable to those commonly found in sighted children. On the one hand, this convergence indicates similarities in the way vision and touch mediate the acquisition and the conceptualisation of spatial information from objects and the environment. On the other hand, it reflects the influence of cross-modal plasticity typically associated with early or congenital blindness. This study suggests that drawing development in general does not depend on learning pictorial conventions. Rather it seems driven by natural generativity based on children’s knowledge of space and perceptual principles.

Optimal Sensor and Actuator Configuration for Structural Identification

2001 ◽  
Author(s):  
C. Papadimitriou ◽  
K. Christodoulou ◽  
M. Pavlidou ◽  
S. A. Karamanos
Keyword(s):  
Information Entropy ◽  
Structural Model ◽  
Model Updating ◽  
Cost Effective ◽  
Entropy Measure ◽  
Parameter Estimates ◽  
Discrete Optimization Problem ◽  
Damage Scenarios ◽  
The One ◽  
Theoretical Developments

Abstract A methodology is presented for designing cost-effective optimal sensor and actuator configurations useful for structural model updating and health monitoring purposes. The optimal sensor and actuator configuration is selected such that the resulting measured data are most informative about the condition of the structure. This selection is based on an information entropy measure of the uncertainty in the model parameter estimates obtained using a statistical system identification methodology. The optimal sensor and actuator configuration is selected as the one that minimizes the information entropy. A discrete optimization problem arises which is solved efficiently using genetic algorithms. This study also addresses important issues related to robustness of the optimal sensor and actuator configuration to unavoidable uncertainties in the structural model, as well as issues related to the optimal sensor and actuator configurations designed to monitor multiple damage scenarios. The theoretical developments are illustrated by designing the optimal configuration for a 40-DOF two-dimensional truss structure subjected to an impulse hammer excitation.

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