A direct interpretation of dynamic images and camera motion for vision guided robotics

Compared to conventional electron sources, the use of a highly coherent field-emission gun (FEG) in TEM improves the information resolution considerably. A direct interpretation of this extra information, however, is hampered since amplitude and phase of the electron wave are scrambled in a complicated way upon transfer from the specimen exit plane through the objective lens towards the image plane. In order to make the additional high-resolution information interpretable, a phase retrieval procedure is applied, which yields the aberration-corrected electron wave from a focal series of HRTEM images (Coene et al, 1992).Kirkland (1984) tackled non-linear image reconstruction using a recursive least-squares formalism in which the electron wave is modified stepwise towards the solution which optimally matches the contrast features in the experimental through-focus series. The original algorithm suffers from two major drawbacks : first, the result depends strongly on the quality of the initial guess of the first step, second, the processing time is impractically high.

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Interpretation of the Contrast of High-Resolution Electron Microscopy Images of Ni4Mo by Means of Simulated Image Maps

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100178896 ◽

1990 ◽

Vol 48 (1) ◽

pp. 28-29

Author(s):

A. Thust ◽

K. Urban

Keyword(s):

Electron Microscopy ◽

High Resolution ◽

Antiphase Boundary ◽

High Resolution Electron Microscopy ◽

Foil Thickness ◽

Order Structure ◽

Simulated Image ◽

Resolution Electron ◽

Fcc Lattice ◽

Direct Interpretation

The alloy of composition Ni4Mo develops, at temperatures below 860 °C, an ordered Dla-structure which is based on the fcc-lattice. This alloy has been widely investigated with respect to its physical properties and its ordering behaviour. High resolution studies are rare and concentrated mainly on its short-range order structure. The aim of the present work was to develop a detailed understanding of image contrast and to apply the results to antiphase-boundary studies in ordered Ni4Mo by means of a JEOL 4000 EX electron microscope.In high-resolution electron microscopy, depending on defocus and foil thickness, a large variety of different images is obtained. Only a few of these allow a direct interpretation concerning the location and the type of the atoms. By computing a through-focus/through-thickness map (TFTT map) before starting experimental work it is possible to determine the proper conditions at which images can be obtained which are closely related to the projected potential.

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Kinematic Analysis of Lower Limb Joint Asymmetry during Gait in People with Multiple Sclerosis

Symmetry ◽

10.3390/sym13040598 ◽

2021 ◽

Vol 13 (4) ◽

pp. 598

Author(s):

Massimiliano Pau ◽

Bruno Leban ◽

Michela Deidda ◽

Federica Putzolu ◽

Micaela Porta ◽

...

Keyword(s):

Multiple Sclerosis ◽

Lower Limb ◽

Sagittal Plane ◽

Cross Sectional Study ◽

Camera Motion ◽

Cross Sectional ◽

Temporal Parameters ◽

Wide Range ◽

Edss Score ◽

Spatio Temporal

The majority of people with Multiple Sclerosis (pwMS), report lower limb motor dysfunctions, which may relevantly affect postural control, gait and a wide range of activities of daily living. While it is quite common to observe a different impact of the disease on the two limbs (i.e., one of them is more affected), less clear are the effects of such asymmetry on gait performance. The present retrospective cross-sectional study aimed to characterize the magnitude of interlimb asymmetry in pwMS, particularly as regards the joint kinematics, using parameters derived from angle-angle diagrams. To this end, we analyzed gait patterns of 101 pwMS (55 women, 46 men, mean age 46.3, average Expanded Disability Status Scale (EDSS) score 3.5, range 1–6.5) and 81 unaffected individuals age- and sex-matched who underwent 3D computerized gait analysis carried out using an eight-camera motion capture system. Spatio-temporal parameters and kinematics in the sagittal plane at hip, knee and ankle joints were considered for the analysis. The angular trends of left and right sides were processed to build synchronized angle–angle diagrams (cyclograms) for each joint, and symmetry was assessed by computing several geometrical features such as area, orientation and Trend Symmetry. Based on cyclogram orientation and Trend Symmetry, the results show that pwMS exhibit significantly greater asymmetry in all three joints with respect to unaffected individuals. In particular, orientation values were as follows: 5.1 of pwMS vs. 1.6 of unaffected individuals at hip joint, 7.0 vs. 1.5 at knee and 6.4 vs. 3.0 at ankle (p < 0.001 in all cases), while for Trend Symmetry we obtained at hip 1.7 of pwMS vs. 0.3 of unaffected individuals, 4.2 vs. 0.5 at knee and 8.5 vs. 1.5 at ankle (p < 0.001 in all cases). Moreover, the same parameters were sensitive enough to discriminate individuals of different disability levels. With few exceptions, all the calculated symmetry parameters were found significantly correlated with the main spatio-temporal parameters of gait and the EDSS score. In particular, large correlations were detected between Trend Symmetry and gait speed (with rho values in the range of –0.58 to –0.63 depending on the considered joint, p < 0.001) and between Trend Symmetry and EDSS score (rho = 0.62 to 0.69, p < 0.001). Such results suggest not only that MS is associated with significantly marked interlimb asymmetry during gait but also that such asymmetry worsens as the disease progresses and that it has a relevant impact on gait performances.

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SMPLIP-Score: predicting ligand binding affinity from simple and interpretable on-the-fly interaction fingerprint pattern descriptors

Journal of Cheminformatics ◽

10.1186/s13321-021-00507-1 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Surendra Kumar ◽

Mi-hyun Kim

Keyword(s):

Ligand Binding ◽

Binding Affinity ◽

Scoring Functions ◽

Binding Affinities ◽

Ligand Interaction ◽

Fingerprint Pattern ◽

Comparable Performance ◽

Direct Interpretation ◽

Benchmark Datasets ◽

Complex Features

AbstractIn drug discovery, rapid and accurate prediction of protein–ligand binding affinities is a pivotal task for lead optimization with acceptable on-target potency as well as pharmacological efficacy. Furthermore, researchers hope for a high correlation between docking score and pose with key interactive residues, although scoring functions as free energy surrogates of protein–ligand complexes have failed to provide collinearity. Recently, various machine learning or deep learning methods have been proposed to overcome the drawbacks of scoring functions. Despite being highly accurate, their featurization process is complex and the meaning of the embedded features cannot directly be interpreted by human recognition without an additional feature analysis. Here, we propose SMPLIP-Score (Substructural Molecular and Protein–Ligand Interaction Pattern Score), a direct interpretable predictor of absolute binding affinity. Our simple featurization embeds the interaction fingerprint pattern on the ligand-binding site environment and molecular fragments of ligands into an input vectorized matrix for learning layers (random forest or deep neural network). Despite their less complex features than other state-of-the-art models, SMPLIP-Score achieved comparable performance, a Pearson’s correlation coefficient up to 0.80, and a root mean square error up to 1.18 in pK units with several benchmark datasets (PDBbind v.2015, Astex Diverse Set, CSAR NRC HiQ, FEP, PDBbind NMR, and CASF-2016). For this model, generality, predictive power, ranking power, and robustness were examined using direct interpretation of feature matrices for specific targets.

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Imperceptible manipulation of lateral camera motion for improved virtual reality applications

ACM Transactions on Graphics ◽

10.1145/3414685.3417773 ◽

2020 ◽

Vol 39 (6) ◽

pp. 1-14

Author(s):

Ana Serrano ◽

Daniel Martin ◽

Diego Gutierrez ◽

Karol Myszkowski ◽

Belen Masia

Keyword(s):

Virtual Reality ◽

Camera Motion

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A Convolutional Neural Network-Based Method for Corn Stand Counting in the Field

Sensors ◽

10.3390/s21020507 ◽

2021 ◽

Vol 21 (2) ◽

pp. 507

Author(s):

Le Wang ◽

Lirong Xiang ◽

Lie Tang ◽

Huanyu Jiang

Keyword(s):

Frame Rate ◽

Flying Height ◽

Battery Life ◽

Growth Stages ◽

Camera Motion ◽

Long Duration ◽

Manual Counting ◽

Detection And Counting ◽

Plant Image ◽

Early Seedling

Accurate corn stand count in the field at early season is of great interest to corn breeders and plant geneticists. However, the commonly used manual counting method is time consuming, laborious, and prone to error. Nowadays, unmanned aerial vehicles (UAV) tend to be a popular base for plant-image-collecting platforms. However, detecting corn stands in the field is a challenging task, primarily because of camera motion, leaf fluttering caused by wind, shadows of plants caused by direct sunlight, and the complex soil background. As for the UAV system, there are mainly two limitations for early seedling detection and counting. First, flying height cannot ensure a high resolution for small objects. It is especially difficult to detect early corn seedlings at around one week after planting, because the plants are small and difficult to differentiate from the background. Second, the battery life and payload of UAV systems cannot support long-duration online counting work. In this research project, we developed an automated, robust, and high-throughput method for corn stand counting based on color images extracted from video clips. A pipeline developed based on the YoloV3 network and Kalman filter was used to count corn seedlings online. The results demonstrate that our method is accurate and reliable for stand counting, achieving an accuracy of over 98% at growth stages V2 and V3 (vegetative stages with two and three visible collars) with an average frame rate of 47 frames per second (FPS). This pipeline can also be mounted easily on manned cart, tractor, or field robotic systems for online corn counting.

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Probability-based diagnostic imaging with corrected weight distribution for damage detection of stiffened composite panel

Structural Health Monitoring ◽

10.1177/14759217211033967 ◽

2021 ◽

pp. 147592172110339

Author(s):

Guoqiang Liu ◽

Binwen Wang ◽

Li Wang ◽

Yu Yang ◽

Xiaguang Wang

Keyword(s):

Distribution Function ◽

Diagnostic Imaging ◽

Weight Distribution ◽

Composite Structures ◽

Damage Identification ◽

Guided Wave ◽

Composite Panel ◽

Damage Localization ◽

Localization Accuracy ◽

Direct Interpretation

Due to no requirement for direct interpretation of the guided wave signal, probability-based diagnostic imaging (PDI) algorithm is especially suitable for damage identification of complex composite structures. However, the weight distribution function of PDI algorithm is relatively inaccurate. It can reduce the damage localization accuracy. In order to improve the damage localization accuracy, an improved PDI algorithm is proposed. In the proposed algorithm, the weight distribution function is corrected by the acquired relative distances from defects to all actuator–sensor pairs and the reduction of the weight distribution areas. The validity of the proposed algorithm is assessed by identifying damages at different locations on a stiffened composite panel. The results show that the proposed algorithm can identify damage of a stiffened composite panel accurately.

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Effect of External Charging on Nanoparticle Formation in a Flame

Materials ◽

10.3390/ma14112891 ◽

2021 ◽

Vol 14 (11) ◽

pp. 2891

Author(s):

Elena Fomenko ◽

Igor Altman ◽

Igor E. Agranovski

Keyword(s):

Negative Ions ◽

Formation Processes ◽

Particle Charge ◽

Mgo Nanoparticles ◽

Nanoparticle Formation ◽

Noticeable Change ◽

Nanoparticle Shape ◽

Positive Ions ◽

Direct Interpretation ◽

Shape Of Nanoparticles

This paper attempts to demonstrate the importance of the nanoparticle charge in the synthesis flame, for the mechanism of their evolution during formation processes. An investigation was made of MgO nanoparticles formed during combustion of magnesium particles. The cubic shape of nanoparticles in an unaffected flame allows for direct interpretation of results on the external flame charging, using a continuous unipolar emission of ions. It was found that the emission of negative ions applied to the flame strongly affects the nanoparticle shape, while the positive ions do not lead to any noticeable change. The demonstrated effect emphasizes the need to take into account all of the phenomena responsible for the particle charge when modeling the nanoparticle formation in flames.

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A Logically Justified Model of Computation I

Fundamenta Informaticae ◽

10.3233/fi-1981-4108 ◽

1981 ◽

Vol 4 (1) ◽

pp. 151-172

Author(s):

Pierangelo Miglioli ◽

Mario Ornaghi

Keyword(s):

Computer Science ◽

Program Synthesis ◽

Completeness Theorem ◽

Point Of View ◽

Program Execution ◽

Computation Model ◽

Clear Explanation ◽

Direct Interpretation ◽

Adequacy Condition ◽

General Explanation

The aim of this paper is to provide a general explanation of the “algorithmic content” of proofs, according to a point of view adequate to computer science. Differently from the more usual attitude of program synthesis, where the “algorithmic content” is captured by translating proofs into standard algorithmic languages, here we propose a “direct” interpretation of “proofs as programs”. To do this, a clear explanation is needed of what is to be meant by “proof-execution”, a concept which must generalize the usual “program-execution”. In the first part of the paper we discuss the general conditions to be satisfied by the executions of proofs and consider, as a first example of proof-execution, Prawitz’s normalization. According to our analysis, simple normalization is not fully adequate to the goals of the theory of programs: so, in the second section we present an execution-procedure based on ideas more oriented to computer science than Prawitz’s. We provide a soundness theorem which states that our executions satisfy an appropriate adequacy condition, and discuss the sense according to which our “proof-algorithms” inherently involve parallelism and non determinism. The Properties of our computation model are analyzed and also a completeness theorem involving a notion of “uniform evaluation” of open formulas is stated. Finally, an “algorithmic completeness” theorem is given, which essentially states that every flow-chart program proved to be totally correct can be simulated by an appropriate “purely logical proof”.

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Intelligent English classroom video clarity improvement based on motion compensation and grid flow

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189528 ◽

2020 ◽

pp. 1-11

Author(s):

Shufang Li ◽

Wang Juan

Keyword(s):

Motion Compensation ◽

Noise Removal ◽

Operating Efficiency ◽

Camera Motion ◽

Video Denoising ◽

Actual Operating ◽

Flow Motion ◽

Pros And Cons ◽

English Classroom ◽

Teaching Video

For the English classroom teaching video denoising algorithm, it is not only necessary to consider whether the noise removal of the output video is thorough, but also to consider the actual operating efficiency and robustness of the algorithm. In the process of the thesis research, after reading a large number of internal and external documents on video denoising algorithms and analyzing the pros and cons of various denoising algorithms, this paper proposes a new video denoising algorithm, which uses the recently proposed grid flow motion model based on camera motion compensation to generate denoised video. Compared with the current advanced video denoising schemes, our method processes noisy frames faster and has good robustness. In addition, this article improves the algorithm framework so that the algorithm can not only deal with offline video denoising, but also deal with online video denoising.

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