Knife sharpness is one of multiple factors involved in musculoskeletal disorders in industrial meat cutting. The aim of this study was to objectively evaluate, in real working situations, how knife ...sharpness changed over a working day cutting meat, and to analyse the impact of sharpening, steeling and meat-cutting activities on these variations. Twenty-two meat-cutting workers from three different companies participated in the study. The methods included measurements of knife sharpness in relation to real work situations and consideration of the way meat-cutting and sharpening operations were organised. Results showed that the type of meat-cutting activities, the steeling strategy adopted by the worker, including the types of tool used, and the overall organisation of the sharpening task all had a significant influence on how knife sharpness evolved over a 2-h period and over an entire working day. To improve MSD prevention, sharpening and steeling operations should not be considered as independent activities, but taken into account as a continuity of working actions. Appropriate assessment of knife sharpness by meat cutters affects how they organise meat-cutting and sharpening tasks.
•Different factors of the real work situation influence knife sharpness (KSE).•Sharpening and steeling should be considered as a continuity for KSE evolution.•Two steeling tool strategy were identified and significantly influence KSE.•KSE can be lower after maintenance operations than before.•KSE assessment can guide the work organisation of meat-cutters and sharpeners.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Video deblurring is a challenging task because only input blurry sequences are available. To further constrain the optimization process, existing methods explore various additional information, e.g., ...events, depth, and sharpness prior. However, they consume large computational costs or generate unpleasant visual results due to the insufficient exploitation of spatio-temporal information. In this work, we propose a novel spatio-temporal sharpness map learned by a prior-based generation network implicitly. The proposed generation network blends both spatial and temporal sharpness priors in a blurry sequence, while few extra parameters are added. We show that the proposed map has better spatial continuity and guidance for video deblurring than the previous methods. Furthermore, different from the simply concatenation in the previous work, we allow the sharpness map to accommodate to more effective video deblurring via a dual-stream network. Specifically, the network is decomposed by two branches, namely the inter-frame and intra-frame reconstructions. The inter-frame reconstruction obtains the sharp patches of consecutive frames from the sharpness map to restore textures well. Meanwhile, the intra-frame branch is responsible for recovering structures of the latent frame, where a novel histogram statistical method is developed to quantify and count textures in the features under the modulation of the sharpness map. Quantitative and qualitative experiments successfully validate the effectiveness of our proposed method.
Recently, many new results of sharpness assessment for digital images have been achieved, which help to select valuable images from massive images with ragged quality. However, remote sensing images ...encompass a wide range of scenes with diverse characteristics, and their acquisition is often influenced by blurs and noises. Many commonly used sharpness assessment methods based on uniform metrics face challenges in ensuring both subjective and objective impartiality when applied to remote sensing images. Therefore, a novel method for assessing the sharpness of remote sensing images based on a deep multibranch network considering scene features is proposed. In the method, a multitask module (MTM), comprising scene classification and sharpness assessment tasks, is proposed to comprehensively consider the potential impact of diverse scene characteristics on the assessment of sharpness. The accuracy of sharpness assessment is improved by sharing features that reflect the correlation between the scene and sharpness. To overcome the issue of imbalanced task predictions during the joint training of multiple tasks, a total loss function using gradient balance strategy is designed. In addition, the improved attention module (IAM) and the feature fusion module (FFM) are used to better utilize feature information at different scales. Experimental results obtained from datasets demonstrated that the proposed method can outperform the existing comparable methods and achieve satisfactory results, proving its feasibility and effectiveness.
Maximizing separation sharpness is critical for the design and operation of hydrocyclones but remains difficult to achieve. This work presents a numerical study on the relationship between separation ...performance and the characteristics of axial velocity wave zone to understand the reasons for the limited separation sharpness. The results showed that this zone is featured as an inherent transition region, with extensive secondary vortices formed between inner and outer spiral flows. The presence of this zone adversely affects the fluid-solid momentum transfer, causing prolonged residence time and accumulation of intermediate-sized particles. The separation sharpness shows a strong dependence on the characteristics of axial velocity wave zone, which are further controlled by geometric parameters. Increasing the symmetry of flow field and optimizing the spatial distribution of this zone can help increase the separation sharpness while its size shows little effect.
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•Two-fluid model and Lagrangian particle tracking method are used.•The flow field characteristics of axial velocity wave zone are studied.•Limited separation sharpness is attributed to the presence of this zone.•Dependence of separation sharpness on the characteristics of this zone is assessed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
We present a space–time fractional Allen–Cahn phase-field model that describes the transport of the fluid mixture of two immiscible fluid phases. The space and time fractional order parameters ...control the sharpness and the decay behavior of the interface via a seamless transition of the parameters. Although they are shown to provide more accurate description of anomalous diffusion processes and sharper interfaces than traditional integer-order phase-field models do, fractional models yield numerical methods with dense stiffness matrices. Consequently, the resulting numerical schemes have significantly increased computational work and memory requirement. We develop a lossless fast numerical method for the accurate and efficient numerical simulation of the space–time fractional phase-field model. Numerical experiments shows the utility of the fractional phase-field model and the corresponding fast numerical method.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
In this paper, two metrics for measuring image sharpness are presented and used for an autofocus (AF) application. Both measures exploit reorganized discrete cosine transform (DCT) representation. ...The first metric is a focus measure, which involves optimal high- and middle-frequency coefficients to evaluate relative sharpness. It is robust to noise while remaining sensitive to the best focus position. A psychometric function-based metric is introduced to quantify the focus measure. The second metric is a no-reference blurriness metric, which is used to measure absolute blurriness. It first constructs multiscale DCT edge maps using directional energy information and then determines image blurriness by combining change information in edge structures with image contrast. This metric gives predictions that are closely correlated with subjective perceived scores and shows performance comparable with that of state-of-the-art methods, especially for noisy images. For noisy situations, the two metrics are adjusted adaptively according to the estimated noise level. To prevent the introduction of extra computational load, an efficient noise-level estimation algorithm based on median absolute deviation is presented. This algorithm exploits only the available reorganized DCT coefficients. With the focus and blurriness measures, an AF method for which the two metrics play an important role was developed. Because of their high-quality performance, the realized AF function is able to locate the best focus position swiftly and reliably.
Sharpness is an important determinant in visual assessment of image quality. The human visual system is able to effortlessly detect blur and evaluate sharpness of visual images, but the underlying ...mechanism is not fully understood. Existing blur/sharpness evaluation algorithms are mostly based on edge width, local gradient, or energy reduction of global/local high frequency content. Here we understand the subject from a different perspective, where sharpness is identified as strong local phase coherence (LPC) near distinctive image features evaluated in the complex wavelet transform domain. Previous LPC computation is restricted to be applied to complex coefficients spread in three consecutive dyadic scales in the scale-space. Here we propose a flexible framework that allows for LPC computation in arbitrary fractional scales. We then develop a new sharpness assessment algorithm without referencing the original image. We use four subject-rated publicly available image databases to test the proposed algorithm, which demonstrates competitive performance when compared with state-of-the-art algorithms.
VLF radio amplitude and phase measurements are used to find the height and sharpness of the D region of the ionosphere at a mid to high geomagnetic dip latitude of ~52.5°. The two paths used are both ...from the 23.4 kHz transmitter, DHO, in north Germany with the first path being northward and mainly over the sea along the west coast of Denmark over a range of ~320–425 km, and the second, also mainly all‐sea, to a single fixed recording receiver at Eskdalemuir in Scotland (~750 km). From plots of the measured amplitudes and phases versus distance for the first of these paths compared with calculations using the U.S. Navy code, ModeFinder, the Wait height and sharpness parameters of the D region at midday in summer 2015 are found to be H′ = 72.8 ± 0.2 km and β = 0.345 ± 0.015 km−1 at a solar zenith angle ~33°. From phase and amplitude measurements at other times of day on the second path, the daytime changes in H′ and β as functions of solar zenith angle are determined from shortly after dawn to shortly before dusk. Comparisons are also made between the modal ModeFinder calculations and wave hop calculations, with both giving similar results. The parameters found here should be useful in understanding energy inputs to the D region from the radiation belts, solar flares, or transient luminous events. The midday values may be sufficiently precise to be useful for monitoring climate change.
Key Points
Ionospheric lower D region electron density height profiles measured midsummer at a mid to high geomagnetic dip latitude of 52.5°
Midday D region height and sharpness measured as 72.8 ± 0.2 per km and 0.345 ± 0.015 per km defining the electron density height profile
New technique has higher accuracy and higher latitude giving improved baseline for D region radio propagation and particle precipitation
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
The tremendous explosion of image-, video-, and audio-enabled mobile devices, such as tablets and smart-phones in recent years, has led to an associated dramatic increase in the volume of captured ...and distributed multimedia content. In particular, the number of digital photographs being captured annually is approaching 100 billion in just the U.S. These pictures are increasingly being acquired by inexperienced, casual users under highly diverse conditions leading to a plethora of distortions, including blur induced by camera shake. In order to be able to automatically detect, correct, or cull images impaired by shake-induced blur, it is necessary to develop distortion models specific to and suitable for assessing the sharpness of camera-shaken images. Toward this goal, we have developed a no-reference framework for automatically predicting the perceptual quality of camera-shaken images based on their spectral statistics. Two kinds of features are defined that capture blur induced by camera shake. One is a directional feature, which measures the variation of the image spectrum across orientations. The second feature captures the shape, area, and orientation of the spectral contours of camera shaken images. We demonstrate the performance of an algorithm derived from these features on new and existing databases of images distorted by camera shake.
We explore a no-reference sharpness assessment model for predicting the perceptual sharpness of ultrahigh-definition (UHD) videos through analysis of visual resolution variation in terms of viewing ...geometry and scene characteristics. The quality and sharpness of UHD videos are influenced by viewer perception of the spatial resolution afforded by the UHD display, which depends on viewing geometry parameters including display resolution, display size, and viewing distance. In addition, viewers may perceive different degrees of quality and sharpness according to the statistical behavior of the visual signals, such as the motion, texture, and edge, which vary over both spatial and temporal domains. The model also accounts for the resolution variation associated with fixation and foveal regions, which is another important factor affecting the sharpness prediction of UHD video over the spatial domain and which is caused by the nonuniform distribution of the photoreceptors. We calculate the transition of the visually salient statistical characteristics resulting from changing the display's screen size and resolution. Moreover, we calculated the temporal variation in sharpness over consecutive frames in order to evaluate the temporal sharpness perception of UHD video. We verify that the proposed model outperforms other sharpness models in both spatial and temporal sharpness assessments.
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