Contour Size Research Articles

Anthropomorphic modular gripper finger actuated by antagonistic wire and shape-memory alloy (SMA) springs

Abstract. The traditional underactuated grippers can only passively adapt to the contour of the object, and the passive contact process may lead to the object slipping, affecting the stability of the grasping process. In this paper, an anthropomorphic modular gripper finger actuated by antagonistic wire and shape-memory alloy (SMA) springs, which can actively control the grasping morphology according to the characteristics of the objects to be grasped, is proposed. The wire drive simulates the flexor muscle, and the SMA and reset springs simulate the extensor muscles of the finger, which antagonistically control the grasping morphology of the finger. It is more in line with the grasping characteristics of the human hand. According to the moment equilibrium principle of the finger joints, the deformation model of the gripper is established, the influence of the wire tension and the equivalent stiffness of the finger joints on the grasping morphology is analyzed, and the theoretical joint angle results are verified by the Adams simulation; finally, the experimental system of the gripper is constructed, and the verification of the deformation morphology of the single finger and the gripper's enveloping–grasping experiments is completed. The results show that according to the contour size of the object, by actively controlling the wire force of the gripper and the equivalent stiffness of the interphalangeal joints, the enveloping–grasping action of different objects can be completed and the stable grasping of objects of different shapes and sizes can be realized.

Influence of thermal denaturation on whey protein isolates in combination with chitosan for fabricating Pickering emulsions: a comparison study.

Composite natural emulsifiers such as whey protein isolate (WPI) and chitosan (CS) are commonly used in Pickering emulsions to address the effect of thermal deformation of proteins before complexation with CS and heating after complexation. In this study, the properties of WPI and CS composites were investigated by complexing CS with either unmodified WPI or thermally denatured WPI (DWPI). Three types of composite particles were prepared, WPI-CS, DWPI-CS, and D(WPI-CS). Atomic force microscopy revealed that the composite particles formed larger aggregates with increased contour size and surface roughness compared to CS and WPI, whereas the interfacial tension decreased, indicating improved emulsifying abilities. Fourier-transform infrared analysis revealed differences in the hydrogen bonds between CS and WPI/DWPI. All three composite particles formed stable emulsions with droplet sizes of 20.00 ± 0.15, 27.80 ± 0.35, and 16.77 ± 0.51 μm, respectively. Thermal stability experiments revealed that the curcumin emulsion stabilized with WPI-CS and DWPI-CS exhibited relatively better thermal stability than that stabilized with D(WPI-CS). In vitro experiments results indicated that the bioaccessibility of the curcumin emulsion stabilized with WPI-CS was 61.18 ± 0.16%, significantly higher than that of the emulsions prepared with the other two composite particles (p < 0.05). This study will enable the customized design of WPI composite-based Pickering emulsions for application in the food and nutrition industries.

Contour Neurovascular System for endovascular embolization of cerebral aneurysms: a multicenter cohort study of 10 European neurovascular centers

BackgroundIntrasaccular devices have become increasingly popular in the treatment of cerebral aneurysms, particularly at the bifurcation. Here we evaluate the Contour Neurovascular System, an intrasaccular device for the endovascular treatment...

Apple Fruit Edge Detection Model Using a Rough Set and Convolutional Neural Network.

Accurately and effectively detecting the growth position and contour size of apple fruits is crucial for achieving intelligent picking and yield predictions. Thus, an effective fruit edge detection algorithm is necessary. In this study, a fusion edge detection model (RED) based on a convolutional neural network and rough sets was proposed. The Faster-RCNN was used to segment multiple apple images into a single apple image for edge detection, greatly reducing the surrounding noise of the target. Moreover, the K-means clustering algorithm was used to segment the target of a single apple image for further noise reduction. Considering the influence of illumination, complex backgrounds and dense occlusions, rough set was applied to obtain the edge image of the target for the upper and lower approximation images, and the results were compared with those of relevant algorithms in this field. The experimental results showed that the RED model in this paper had high accuracy and robustness, and its detection accuracy and stability were significantly improved compared to those of traditional operators, especially under the influence of illumination and complex backgrounds. The RED model is expected to provide a promising basis for intelligent fruit picking and yield prediction.

Clinical Feasibility of Artificial Intelligence-Based Autosegmentation of the Left Anterior Descending Artery in Radiotherapy for Breast Cancer

Abstract Introduction Breast cancer is a prevalent global disease, and radiotherapy plays a crucial role in its treatment. However, radiotherapy may lead to cardiac complications, particularly in patients receiving left-sided radiotherapy who may experience increased risks due to toxicity in the left anterior descending (LAD) artery. The manual contouring of the LAD artery is time-consuming and subject to variability. This study aimed to provide an overview of artificial intelligence (AI) based LAD artery contouring, assess its feasibility, and identify its limitations. Objectives The primary objectives were to evaluate the feasibility of AI-based LAD artery contouring, compare different approaches, and quantify properties impacting accuracy. The secondary objective was to recommend algorithms with greater accuracy. Materials and Methods A (noncontrast) computed tomography dataset of nine patients with breast cancer was used to analyze the features and behavior of the LAD artery. The functioning of different AI models used for autosegmentation was studied, and the LAD artery imaging features were identified and quantified using the widely used AI models. Additionally, an algorithm to reliably compute interpatient variability in the LAD artery contours was proposed. Results A lack of distinctive features, diminutive contour size (∼5 pixels on average), and inconsistent position of the LAD artery were observed. The interpatient variability in the LAD artery contours was five to seven times the average size of the contours. The dataset also had a high standard deviation of 28.9 and skewed data distribution. Conclusions The results indicated that the variable path of the LAD artery and high interpatient variability were the primary reasons for the inability of AI algorithms to have a concordance. Further, the small contour size amplified model inaccuracy. For higher autosegmentation accuracy, an anatomical landmark–based approach is necessary to capture surrounding structures that affect the path of the LAD artery.

A layerwise geometric error compensation procedure for additive manufacturing

PurposeThe purpose of this paper is to provide a new procedure for in-plane compensation of geometric errors that often appear in the layers deposited by an additive manufacturing (AM) process when building a part, regardless of the complexity of the layer geometry.Design/methodology/approachThe procedure is based on comparing the real layer contours to the nominal ones extracted from the STL model of the part. Considering alignment and form deviations, the compensation algorithm generates new compensated contours that match the nominal ones as closely as possible. To assess the compensation effectiveness, two case studies were analysed. In the first case, the parts were not manufactured, but the distortions were simulated using a predictive model. In the second example, the test part was actually manufactured, and the distortions were measured on a coordinate measuring machine.FindingsThe geometric deviations detected in both case studies, as evaluated by various quality indicators, reduced significantly after applying the compensation procedure, meaning that the compensated and nominal contours were better matched both in shape and size.Research limitations/implicationsAlthough large contours showed deviations close to zero, dimensional overcompensation was observed when applied to small contours. The compensation procedure could be enhanced if the applied compensation factor took into account the contour size of the analysed layer and other geometric parameters that could have an influence.Originality/valueThe presented method of compensation is applicable to layers of any shape obtained in any AM process.

Magnetostrictive-based multimodal tactile sensors for object recognition

Tactile perception of the human hand plays a critical role in everyday object recognition. The development of multimodal tactile sensors that can sense stimuli with high sensitivity and low cost is important for intelligent perception. In this article, a multimodal tactile sensor attached on a mechanical hand is studied, which consists of a magnetostrictive tactile sensor, a temperature sensor, and a flex sensor. By applying multimodal tactile sensors to a robotic hand to grasp objects, the output voltage of the magnetotactictive tractile tactile sensor can be used for object shape and softness recognition. The bending angle of the knuckles can be obtained by the flex sensor for object contour size recognition, while the temperature distribution of objects can be obtained through temperature sensors. In order to improve the accuracy, a 1-D convolutional neural network-extreme learning machine (CNN-ELM) pattern recognition model based on the combination of 1-D CNN and ELM is presented, with the accuracy of 97.14% for 21 objects. This multimodal tactile sensor has promising applications in the field of tactile intelligence and humanoid robotics.

Design and Analysis of Modular Gripper Finger Actuated by Antagonistic Wire and Shape Memory Alloy Springs

The traditional underactuated grippers can only passively adapt to the shape contour of the object to complete the envelope or grasping action. In this paper, a wire and shape memory alloy (SMA) spring‐based differential drive gripper finger are proposed, which can actively control the grasping morphology according to the objects to be grasped, and are more in line with the grasping characteristics of the human hand. The wire simulates the flexor muscle, and the SMA and reset springs simulate the extensor muscle of the finger, which together control the finger morphology. According to the principle of moment equilibrium, the static mechanical model of the gripper is established, and the influence of the wire driving force and the equivalent stiffness of the finger joints on the grasping morphology are analysed, and the theoretical grasping force is verified by ADAMS simulation. A comparative analysis of the grasping force between the non‐active and active morphology control is presented. Finally, the experimental system of the gripper is constructed, and the verification of the deformation morphology of the single finger and the gripper’s grasping experiments is completed. The results show that according to the contour size of the object, by actively controlling the wire force of the gripper and the equivalent stiffness of the joints, the enveloping or grasping action for different objects can be completed. In addition, the grasping force of the finger can be improved by actively controlling the grasping morphology.

Efficient multi-branch dynamic fusion network for super-resolution of industrial component image

This work aims to promote the application of a high-performance super-resolution (SR) method in industry. Considering the lack of industrial datasets to evaluate performance, an industrial image SR dataset called WCI110 is first established, comprising 110 typical welding component images with 2040 × 1524 pixels. Subsequently, a parallel fusion structure of CNN and Transformer (FPFCT) is designed to achieve a high-quality reconstruction of component images. This model mainly contains the flexible parallel fusion (FPF) block and dynamic edge attention (DEA) network. The irreparable information loss caused by the inheritable sampling imperfection of CNN and Transformer can be effectively avoided by the parallel fusion structure in FPF block, while the contour features of multi-scale targets can be dynamically enhanced by DEA modules. The results show that the performance of FPFCT is higher than most advanced SR methods based on CNN, Transformer, or hybrid of CNN and Transformer. The images reconstructed by FPFCT are shown to help find and locate defects more effectively than other methods because its reconstructed target is closer to ground truth in terms of contour sharpness and size. Moreover, FPFCT achieves a remarkable advance in model parameters and time consumption, with a drop of more than 37.5 % in model parameters compared to the state-of-the-art SwinIR, and a reduction of more than 48.9 % in single-image delay time during reconstruction. The high efficiency of FPFCT makes it a promising image preprocessing tool for industrial images.

Evolution of Increased Volcanic Activity in Arjuno-Welirang Based on LST Analysis of Landsat 8 Satellite Imagery Using GEE Cloud Computing

Typically, monitoring the volcanic activity of a volcano is carried out using volcanic seismic methods. However, this method is technically less flexible. Volcano seismic data is not freely available. Access to these data centers must be authorized by the data authority. Therefore, it is necessary to use other methods as an alternative. The alternative method used in this study is remote sensing using the Landsat 8 satellite sensors. Landsat 8 satellite imagery data can be freely accessed and easily downloaded. Landsat 8 image analysis is implemented with Google Earth Engine (GEE). GEE is a remote sensing image analysis programming tool with a cloud computing platform. The GEE programming implementation is open source. With GEE, the evolution of Arjuno-Welirang volcanic activity can be monitored accurately. The use of GEE with a cloud computing platform also makes it easier to process large remote sensing data because the downloaded file's size is unlimited. GEE has successfully conducted an LST analysis on Landsat 8 satellite imagery of the Arjuno-Welirang complex area in the 2016-2021 range. The LST calculation is performed by adding the surface emissivity correction obtained based on the NDVI value. According to the results of the LST calculations that have been obtained, the surface temperature in the Arjuna Welirang Crater area experienced the highest increase in 2018, reaching 33.94 oC, with a larger contour size of thermal distribution image than the others. This increase in thermal based volcanic activity is in accordance with the increase in seismic activity monitored by the VSI (Volcanological Survey of Indonesia).

ANTERIOR AESTHETIC REHABILITATION WITH GINGIVECTOMY AND COMPOSITE RESIN VENEERS

The advancement of surgical procedures for gingival repair and restorative treatments for anterior teeth, which stand out in the scientific community, has been fundamentally influenced by the pursuit of aesthetics. The purpose of the current study is to describe the clinical behaviour of a patient who has small teeth and a gummy smile. The goal was to use a clinical case to illustrate how anterior cosmetic rehabilitation, which includes gingivectomy and composite resin veneers, can be accomplished. The restoration of anterior teeth involves using better shades, colours, opacities, translucency, and anatomical onformation, while treatments that combine dentistry and periodontics are capable of producing good results, enabling normalisation of the gums, correcting their deformities, and restoring the interdental grooves and papillae. Periodontal surgery called a gingivectomy involves removing extra gum tissue. The purpose of the procedure is to change the tooth’s contour, which generates an increase in the clinical crown, providing a smile with adequate protection and support for the oral environment. Resin veneers or direct restoration on anterior teeth are the dental remodelling treatment that guarantees longevity and satisfactory results, in addition to being minimally invasive. The adhesive systems and composite resins available are of high quality, do not impose aesthetic limits, and allow a natural effect determined by the excellence and technical knowledge of the operator. The plan accomplishment allowed reaching the aesthetic principles and establishing a better contour shape and size, both of the gingival tissue and of the anterior teeth. Thus, the procedure was always performed prioritising the demands and satisfaction of the patient, generating excellent clinical results. This research is duly authorized by Opinion: 6.275.546 CEP/CONEP.

Assessment of the effect of accelerated ultraviolet aging on mini‐PV modules encapsulated with different poly(ethylene‐co‐vinyl acetate) formulations

AbstractOne of the hindering issues for the long‐term reliability of the photovoltaic (PV) modules is the degradation of poly(ethylene‐co‐vinyl acetate) (PEVA)—a popular encapsulant material. As a globally accepted practice, PEVA is required to have the vinyl acetate (VA) content between 28–33% by weight for encapsulation application in the PV modules. Recent studies have indicated stability improvements in the bare encapsulant layer when the VA content is reduced up to 18%. However, effect of UV aging on the PEVA films encapsulated using these VA contents have not been studied at the module level. Therefore, in this work, we have fabricated mini‐modules containing PEVA films that contain 18, 24 or 33% VA content and have subsequently been subjected to UV aging (1000 hours at 340 nm wavelength and 65C). The assessment of the durability at both the mini‐module and materials level has been made using various characterization techniques such as current–voltage characteristics, adhesion strength measurement, fluorescence imaging and spectra, FTIR, Raman spectra, volume resistivity and TGA. YI for the free‐standing films of PEVA18, PEVA24 and PEVA33 after 1000 hours of UV aging was slightly less than the YI values for the corresponding laminated films of PEVAs in mini‐PV modules after similar hours of aging. This work shows for the first time that increasing the VA content in PEVA increases the fluorescence intensity and contour size in the encapsulated polymer after UV aging. FTIR analysis indicates deacetylation of PEVA33 which resulted in discoloration (increased ΔYI) and has adversely affected the adhesion strength and power output after UV aging. Compared to PEVA33, the modules containing PEVA18 and PEVA24 are resilient against UV aging for all the properties. Hence, this study recommends using PEVA with 24% VA content as an encapsulant as it presents best combination of the adhesion strength and the environmental stability.

Research on Scheme Design and Structure Optimization of High Speed and High Precision Vehicle Contour Detection Platform

To improve road traffic safety and reduce the incidence of unauthorized vehicle modifications, overloading, and oversizing, this study proposed a detection platform structure to support the quick measurement of key dimensions and high-precision reconstruction of local features using the automotive contour size system. Using CAE technology, static and dynamic characteristic analysis was performed on the platform structure, and optimization design was conducted on the column frame and gantry frame separately. The optimized column frame's first-order modal frequency increased by 243% from 5.16 Hz to 17.65 Hz, with an average optimization ratio of 187% for the first six modal frequencies. For the optimized gantry frame, the average optimization ratio of the key node displacement exceeded 46%, with the first-order modal frequency increasing by 13% from 36.43 Hz to 41.33 Hz, and an average optimization ratio of 21% for the first six modal frequencies. Ultimately, the optimized detection platform's key nodes achieved an average optimization ratio of nearly 60%, with the first-order modal frequency increasing by 240% from 5.16 Hz to 17.57 Hz and an average optimization ratio of 185% for the first six modal frequencies. The optimized platform structure provides robust support for the high-speed and high-precision vehicle contour detection system's implementation.

Wave velocity measurement in the through-thickness direction of the anisotropic material plate with ultrasonic polar scan

Ultrasonic polar scan (UPS) records the amplitude in transmission for a wide range of incidence angles, providing a UPS image with characteristic contours reflecting the acoustic parameters of the material. This study focused on a newly developed wave velocity measurement of the DD6 single-crystal material plate by analyzing the UPS image to realize the ultrasonic thickness measurement of the DD6 single-crystal material plate accordingly. Firstly, considering transducer contour size compensation, the UPS images are obtained by numerical simulation on the DD6 single-crystal material plates with different crystal orientations. Secondly, the fitting equations are obtained by analyzing the UPS images to calculate wave velocity in the thickness direction. Finally, a 5-joint UPS scanner is designed to validate the accuracy of wave velocity simulation results experimentally, and it indicates a good agreement with conventional ultrasonic velocity measurement. The measurement results demonstrated that the UPS method could evaluate the wave velocity in the through-thickness direction of the DD6 single-crystal material plate with high precision.

Three dimensional reconstruction and measurement of underwater spent fuel assemblies

It is an important work to measure the dimensions of underwater spent fuel assemblies in the nuclear power industry during the overhaul, to judging whether the spent fuel assemblies can continue to be used. In this paper, a three dimensional reconstruction method for underwater spent fuel assemblies of nuclear reactor based on linear structured light is proposed, and the topography and size measurement was carried out based on the reconstructed 3D model. Multiple linear structured light sensors are used to obtain contour size data, and the shape data of the whole spent fuel assembly can be collected by one-dimensional scanning motion. In this paper, we also presented a corrected model to correct the measurement error introduced by lead-glass and water is corrected. Then, we set up an underwater measurement system for spent fuel assembly based on this method. Finally, an underwater measurement experiment is carried out to verify the 3D reconstruction ability and measurement ability of the system, and the measurement error is less than ±0.05 mm.

A study on the compressive mechanical properties of 316L diamond lattice structures manufactured by laser powder bed fusion based on actual relative density

Lattice structure design is a novel structural lightweight method and has many advantages, but some researches ignored the effects of the factors studied on actual relative density and skipped actual relative density to discuss the effects on mechanical properties. In this paper, the effects of process parameters and geometrical parameters on the compressive mechanical properties of 316L diamond lattice structures manufactured by laser powder bed fusion were investigated on the basis of actual relative density. The results show that the actual relative density (28.0 % → 25.4 %) and the compressive strength in the building direction (55.7 ± 1.3 MPa → 42.0 ± 1.5 MPa) decrease as the hatch spacing (0.05 mm → 0.09 mm) increases, and they conform to the parabolic function relationship better than the Gibson-Ashby relationship, but the opposite in the XY direction. The actual relative densities and compressive strength inevitably conform to the Gibson-Ashby relationship regardless of the nominal relative densities and cell sizes, and the modulus (857 ± 54 MPa → 1019 ± 51 MPa) increases with the increasing of strut diameter (0.54 mm → 3.21 mm). The compressive strength could decrease slightly with the increasing of contour size (10 mm → 30 mm), while the modulus (964 MPa → 682 MPa) decreases rapidly. To sum up, the process parameters and geometrical parameters could affect the actual relative density significantly, and the actual relative density is the key to correctly analyze the effects of various parameters. The conclusions of this work are helpful to optimize the manufacturing process of lattice structures and design geometrical parameters according to the required performance.

Physical Survey of Thermally Heated Non-Newtonian Jeffrey Fluid in a Ciliated Conduit Having Heated Compressing and Expanding Walls

An analytical study is reported that highlights the physical aspects for a heated non-Newtonian Jeffrey liquid in a duct possessing sinusoidally moving ciliated walls. A comprehensive and specific convection analysis is conveyed for this ciliated elliptic duct problem by considering the viscous dissipation effects. The dimensional mathematical problem under consideration is transformed into its dimensionless form by means of appropriate and useful transformations. Then, velocity and temperature equations are exactly evaluated with given boundary conditions. The velocity profile is integrated over the elliptic cross-section and exact mathematical solution is obtained for the pressure gradient. Moreover, the distinct physical flow properties combined with the convection heat transfer phenomenon are discussed in detail through graphical outcomes. The illustrative streamline description shows an enhancing closed contour size with increasing Q (dimensionless flow rate).

Design of flexible dual‐band antenna and metamaterial structure for wearable body area network

To adapt to the application of wireless body area network (WBAN), a wearable flexible dual-band antenna is developed, which has a compact size of 17 × 29 × 0.15 mm3 and a better bandwidth of 61.2% and 43.1% at 2.4 and 5.8 GHz, respectively. The dual-band characteristic is achieved by slotting technique without changing the contour size. A dual-band metamaterial structure (MS) is designed to improve radiation performance and reduce the specific absorption rate (SAR) of the proposed antenna. To verify the validity of the MS, we build two simulation human models. The forward gain of the antenna is increased and the SAR is significantly decreased when adding the MS between antenna and human skin. The antenna is designed and fabricated on a flexible substrate, and its performance is verified for both flat and curved configurations. To examine its performance as a wearable antenna, it is measured on a human body. The measurements show an excellent agreement with the simulations. Good performances of designed antenna make it potential to application of the miniaturized wearable devices.

Topological Friction and Relaxation Dynamics of Spatially Confined Catenated Polymers.

We study catenated ring polymers confined inside channels and slits with Langevin dynamics simulations and address how the contour position and size of the interlocked or physically linked region evolve with time. We show that the catenation constraints generate a drag, or topological friction, that couples the contour motion of the interlocked regions. Notably, the coupling strength decreases as the interlocking is made tighter, but also shorter, by confinement. Though the coupling strength differs for channel and slit confinement, the data outline a single universal curve when plotted against the size of the linked region. Finally, we study how the relaxation kinetics changes after one of the rings is cut open and conclude that considering interlocked circular polymers is key for isolating the manifestations of topological friction. The results ought to be relevant for linked biomolecules in experimental or biological confining conditions.

Tunable Knot Segregation in Copolyelectrolyte Rings Carrying a Neutral Segment.

We use Langevin dynamics simulations to study the knotting properties of copolyelectrolyte rings carrying neutral segments. We show that by solely tuning the relative length of the neutral and charged blocks, one can achieve different combinations of knot contour position and size. Strikingly, the latter is shown to vary nonmonotonically with the length of the neutral segment; at the same time, the knot switches from being pinned at the block's edge to becoming trapped inside it. Model calculations relate both effects to the competition between two adversarial mechanisms: the energy gain of localizing one or more of the knot's essential crossings on the neutral segment and the entropic cost of such localization. Tuning the length of the neutral segment sets the balance between the two mechanisms and hence the number of localized essential crossings, which in turn modulates the knot's size. This general principle ought to be useful in more complex systems, such as multiblock copolyelectrolytes, to achieve a more granular control of topological constraints.