bluuebunny/crossref_metadata_2025 huggingface dataset:
Recognition and Classification of Handwritten Urdu Numerals Using Deep Learning Techniques
Authors: Bhatti Aamna , Arif Ameera , Khalid Waqar , Khan Baber , Ali Ahmad , Khalid Shehzad , Rehman Atiq ur
Published: January 2023

Urdu is a complex language as it is an amalgam of many South Asian and East Asian languages; hence, its character recognition is a huge and difficult task. It is a bidirectional language with its numerals written from left to right while script is written in opposite direction which induces complexities in the recognition process. This paper presents the recognition and classification of a novel Urdu numeral dataset using convolutional neural network (CNN) and its variants. We propose custom CNN model to extract features which are used by Softmax activation function and support vector machine (SVM) classifier. We compare it with GoogLeNet and the residual network (ResNet) in terms of performance. Our proposed CNN gives an accuracy of 98.41% with the Softmax classifier and 99.0% with the SVM classifier. For GoogLeNet, we achieve an accuracy of 95.61% and 96.4% on ResNet. Moreover, we develop datasets for handwritten Urdu numbers and numbers of Pakistani currency to incorporate real-life problems. Our models achieve best accuracies as compared to previous models in the literature for optical character recognition (OCR).
3D Digital Image Correlation Analysis of Local Deformation Field of Different Endodontic Calcium Silicate Cements
Authors: Nikitović Ana , Pešić Dragana , Kolak Veljko , Lalović Marija , Milošević Miloš , Trajković Isaak , Melih Irena
Published: January 2023

The objective was to compare the strain of three calcium silicate cements using an optical system based on the 3D digital image correlation method (3D-DIC). Dentine disks from 30 upper premolars were sectioned transversely to obtain 2 mm-thick sections and enlarged with a 4 mm diameter bur. An additional 30 samples were made in Teflon molds (4 × 2 mm). Dentine discs and Teflon molds were divided into three groups with ten samples each and then filled with MTA+ (Cerkamed), Biodentine (Septodont) and Well-Root PT (Vericom). The strain was determined using the 3D-DIC method in two zones: the peripheral and central zones. Data were analyzed using ANOVA with Scheffe’s post hoc test, a paired t-test and Pearson correlation (α = 0.05). Analysis showed that there were significant differences in the values of deformation between all tested materials in both zones. Comparing the strain in both zones, there were significant differences between zones in the Biodentin and Well-Root PT group on dentine discs, and in the Biodentine and MTA group on Teflon discs. Comparing the strain measured on different disc types, the higher values were found on Teflon. All the examined calcium silicate-based cements showed deformation after initial setting. The highest strain was recorded for Biodentine and the lowest was for Well-Root PT.
Experimental and Numerical Studies of Vertical Stresses Beneath the Circular Footings on Sand
Authors: Keskin Mehmet Salih , Bildik Selçuk , Laman Mustafa
Published: January 2023

This paper presents experimental and numerical studies of the vertical stress distribution beneath the centerline of circular footings resting on sand. Vertical stress values due to circular load in medium-dense sand were measured using soil stress transducers. Reduced-scale laboratory model tests were carried out in a square-shaped test box, and vertical stresses were measured at the centerline of the circular footing at different depths of the sand. In order to determine the effect of footing width on vertical stress distribution, laboratory experiments were performed on circular footings of different diameters. In addition, a series of finite element analyses was carried out on the test model to validate the findings of the experimental study. In the numerical analysis, the sand was modeled as a non-linear elastoplastic material. The analyses were performed using the finite element method with two-dimensional axisymmetric and three-dimensional conditions. The results obtained from laboratory model tests and numerical analysis were compared with the vertical stress values obtained from the theoretical solution in the literature. Vertical stress distribution in horizontal planes at any depth from the footing base shows the same characteristic form in all methods. However, some differences were observed between experimental, numerical, and theoretical results and were discussed.
Evaluation of Materials and Structures with a Multistatic Ultra-Wideband Impulse Radar: A Concept Validation
Authors: Gaigals Gatis , Maliks Romans , Aristov Vladimir , Savelis Rolands , Simanovics Janis , Lobanovs Eduards , Egliens Haralds , Laksis Dans , Greitans Kristaps Maris , Greitans Modris
Published: January 2023

This document describes the results of the study contributing to the methods and tools applicable in plastic waste sorting systems that exploit the multistatic ultra-wideband impulse radar enforced with a deep learning signal processing back-end. The novelty of the research is the use of synthetic data for the development of a trained neural network before real data are available, and the use of a multistatic radar for the improvement of the training data set. The study results are described in multiple publications; the current paper shows the applicability of the described approach. The main results are as follows: a monostatic impulse radar can be used for the determination of material properties, such as thickness, dielectric permittivity, and losses, with limited accuracy; multistatic radar configuration increases the accuracy of the material property estimation; an open source finite difference time domain simulator can be used to simulate electromagnetic wave propagation in dielectric structures in order to generate synthetic data for development of optimized artificial neuron network structures used for the estimation of dielectric material properties, and the developed network can successfully be used for multistatic radar data processing.
EFCMF: A Multimodal Robustness Enhancement Framework for Fine-Grained Recognition
Authors: Zou Rongping , Zhu Bin , Chen Yi , Xie Bo , Shao Bin
Published: January 2023

Fine-grained recognition has many applications in many fields and aims to identify targets from subcategories. This is a highly challenging task due to the minor differences between subcategories. Both modal missing and adversarial sample attacks are easily encountered in fine-grained recognition tasks based on multimodal data. These situations can easily lead to the model needing to be fixed. An Enhanced Framework for the Complementarity of Multimodal Features (EFCMF) is proposed in this study to solve this problem. The model’s learning of multimodal data complementarity is enhanced by randomly deactivating modal features in the constructed multimodal fine-grained recognition model. The results show that the model gains the ability to handle modal missing without additional training of the model and can achieve 91.14% and 99.31% accuracy on Birds and Flowers datasets. The average accuracy of EFCMF on the two datasets is 52.85%, which is 27.13% higher than that of Bi-modal PMA when facing four adversarial example attacks, namely FGSM, BIM, PGD and C&W. In the face of missing modal cases, the average accuracy of EFCMF is 76.33% on both datasets respectively, which is 32.63% higher than that of Bi-modal PMA. Compared with existing methods, EFCMF is robust in the face of modal missing and adversarial example attacks in multimodal fine-grained recognition tasks. The source code is available at https://github.com/RPZ97/EFCMF (accessed on 8 January 2023).
Development of Novel Semi-Stranded Windings for High Speed Electrical Machines Enabled by Additive Manufacturing
Authors: Selema Ahmed , Ibrahim Mohamed N. , Sergeant Peter
Published: January 2023

Recent advances in electrical machines and energy storage technologies make electric vehicles (EVs) feasible replacements to conventional internal combustion engines. One of the main challenges of high speed electrical machines is providing maximum output power with minimum energy losses, weight, and volume. At high frequency operation, the conductors of AC electrical machines can suffer from skin and proximity effects. This results in high AC losses in the machine windings and can eventually lead to machine failure. In this paper, a novel design for a semi-stranded coil is proposed to limit these undesirable effects. Enabled by additive manufacturing (AM) technology, this sophisticated design is 3D printed using ultralight aluminum alloy. Finally, the AC performance of this coil is measured and compared with conventional single-strand copper coil at different frequency levels. It is found that the proposed design can effectively limit the eddy current losses in the high frequency domain.
Marital Status of Never Married with Rey Auditory Verbal Learning Test Cognition Performance Is Associated with Mild Cognitive Impairment
Authors: Parra Bautista Yohn Jairo , Messeha Samia S. , Theran Carlos , Aló Richard , Yedjou Clement , Adankai Victor , Babatunde Samuel ,   on behalf of the Alzheimer’s Disease Prediction of Longitudinal Evolution (TADPOLE)
Published: January 2023

A small number of robust studies have explored the association between cognitive tests and marital status levels of mild cognitive impairment (MCI) patients using the TADPOLE dataset. Rey Auditory Verbal Learning Test (RAVLT) cognition performance combined with marital status levels is associated with increased odds of MCI than either RAVLT in isolation. The cross-sectional association between RAVLT performance in immediate response, learning, forgetting, and perception of forgetting with marital status and MCI was evaluated using TADPOLE data. We included participants with MCI and normal cognition in our study. Based on our logistic regression model, four RAVLT subgroups are associated with MCI (low and high response performance, immediate response with learning, immediate response with learning and forgetting, immediate response with learning, forgetting, and perception of forgetting). We adjusted models for sex, age, race, marital status, education, ethnicity, APOE4 genotype, hippocampus, whole brain, ventricles, and ICV. A mean age of 77/67 years was observed in the sample (n = 6560), 44% of participants were females, and 58% had mild cognitive impairment. Subgroups whose ages are 61 to 70 (OR 0.26, 95% CI 0.15–0.45) and older (OR 0.07, 95% CI 0.04–0.12), as well as race: black/African American (OR 0.13, 95% CI 0.03–0.52), multiple races (OR 0.05, 95% CI 0.01–0.24), and never married (OR 0.2, 95% CI 0.12–0.34) were negatively associated with immediate response and forgetting subgroup tests. There is a need for studies that evaluate other cognitive tests in the TADPOLE dataset with missing data as a predictive tool that aligns with the factors associated with MCI.
Seismic Assessment and Structural Retrofitting of the Day-Hospital Building “G. Pascale Foundation”
Authors: Pisapia Alessandro , Piluso Vincenzo , Montuori Rosario , Nastri Elide , Frattolillo Ciro
Published: January 2023

This work aims to provide an effective structural solution, minimizing the discomfort during the works’ execution, for how to retrofit the Day-Hospital building of the National Cancer Institute “G. Pascale Foundation” in Naples. The structural vulnerability has been preliminarily evaluated for this scope, using linear static and dynamic analyses according to code provisions. The performance index in terms of peak ground acceleration (PGA), both for the life safety (SLV) limit state and the operational (SLO) limit state, has been evaluated. A seismic assessment has been performed by finite element (FE) analyses using the SAP2000 computer program, post-processor VIS15 and plugin SPF. Two main solutions have been proposed to improve the structural performance of the existing building. The first one is based on increasing the thickness of the existing reinforced concrete (RC) cores. The second solution is characterized by strengthening the RC cores using steel plates, steel strips and angles. A comparison of the proposed interventions is provided herein from the technological and financial standpoints.
Teflon Coating and Anti-Escape Ring Improve Trapping Efficiency of the Longhorn Beetle, Monochamus alternatus
Authors: Dong Yifan , Xie Ping , Zheng Kaiwen , Gu Yutong , Fan Jianting
Published: January 2023

The longhorn beetle Monochamus alternatus is an important conifer stem-boring pest and the main vector in Asia of the invasive pine wood nematode Bursaphelenchus xylophilus, which causes a devastating pine disease. Field experiments were carried out to evaluate the effect of coating black panel traps with different concentrations of an anti-adhesive material, Teflon, on Monochamus captures. Tests were also conducted to look at the possible decrease in the Teflon effect with exposure duration as well as the effect of the implementation of an anti-escape ring on the trap. The three tested Teflon concentrations significantly improved the captures of M. alternatus with regard to those with uncoated traps. The beetle captures increased by 108.3% in traps coated with a 4x Teflon dilution, but no significant differences in captures were observed when the traps were coated with either a Teflon stock solution or a 8x dilution. The trapping efficiency gradually decreased with the duration of exposure of the coated traps. No significant difference was observed after one year of exposure, but the trapping efficiency significantly decreased by 36.6% after 2 years and by 72.0% after 3 years. Two-year old, coated traps equipped with an anti-escape ring were nearly three times more efficient than those without an anti-escape ring, but the captures were still lower than those obtained with newly coated traps. The present study provides valuable information for the future development of environmentally friendly prevention methods. Attractants combined with Teflon coating and an anti-escape ring could significantly improve the trapping efficiency of M. alternatus adults, which may allow for the reduction of the population density of M. alternatus and transmission probability of pine wilt disease.
The Impact of Munsell Neutral Grey Backgrounds on Tsavorite’s Color and Study on the Evaluation Method of Color Gem Cutting
Authors: Ma Yuanmeng , Guo Ying
Published: January 2023

Tsavorite’s color is not only affected by its internal components, but also by external factors. This paper studies the neutral grey background and cutting on the impact on color. Under a 6504K fluorescent lamp, by changing the Munsell neutral gray backgrounds from N9.5 to N3, we discovered that N9.5 was the best background for tsavorite color grading. In this paper, the feasibility of taking color by photography is studied. The regression models R2 between the photogrammetry (PM) and the colorimeter (CM) were above 86.99% for all of the color parameters (L*, a*, b, C, and h*), allowing the PM data to be used to predict the CM color values. Photographs were taken before and after the cutting to document the color shift. Comparing the L* and C* before and after cutting, the color concentration score was 100–90 if both L* and C* were optimized, 80–70 if only one parameter was optimized, and 70–60 if neither was. The value of ΔL* in the color histogram serves as a measure of the gemstone’s color scintillation; the greater the value of ΔL*, the stronger the scintillation.
Synthesis and Properties of Octet NiCr Alloy Lattices Obtained by the Pack Cementation Process
Authors: Zhao Peng , Huang Deqing , Zhang Hongmei , Chen Weiwei , Zhang Yongfu
Published: January 2023

NiCr alloys with different components were obtained by pack chromation and homogenization heat treatment of octet Ni lattice. The microstructure, alloy composition, microhardness and quasi-static compression properties of the NiCr lattice were tested. The results showed that after homogenization heat treatment, the NiCr alloy lattice had an austenitic structure with uniform composition. Compared with the pure nickel lattice, the microhardness, compressive strength, elastic modulus and energy absorption of the NiCr lattice increased with the increase of chromium content. The microhardness, specific strength, specific modulus and specific energy absorption of the Ni-45Cr alloy were 363 HV, 11.1 MP/(g/cm3), 1169.1 MP/(g/cm3) and 10 J/g, respectively, which were attributed to the solid solution strengthening provided by chromium and the increase in density. NiCr alloy lattices have high strength and toughness and may have potential applications in high-temperature filters or heat exchangers.
Intelligent Whistling System of Rail Train Based on YOLOv4 and U-Net
Authors: Wang Kai , Zhang Zhonghang , Cai Chaozhi , Ren Jianhua , Zhang Nan
Published: January 2023

The whistle of the rail train is usually directly controlled by the driver. However, in long-distance transportation, there is a risk of traffic accidents due to driver fatigue or distraction. In addition, the noise pollution of the train whistle has also been criticized. In order to solve the above two problems, an intelligent whistling system for railway trains based on deep learning is proposed. The system judges whether to whistle and intelligently adjusts the volume of the whistle according to the road conditions of the train. The system consists of a road condition sensing module and a whistling decision module. The former includes the target detection model based on YOLOv4 and the semantic segmentation model based on U-Net, which can extract the key information of the road conditions ahead; the latter is to carry out logical analysis of the data after the intelligent recognition and processing and make the whistling decision. Based on the train-running data set, the intelligent whistle system model is tested. The results of this research show that the whistling accuracy of the model on the test set is 99.22%, the average volume error is 1.91 dB/time, and the Frames Per Second (FPS) is 18.7 f/s. Therefore, the intelligent whistle system model proposed in this paper has high reliability and is suitable for further development and application in actual scenes.
Experimental Evaluation of the Influence of the Diameter of the Outlet Nozzle Bore of a Gas Injector on Its Flow Characteristic
Authors: Szpica Dariusz , Toczko Bogusław , Borawski Andrzej , Mieczkowski Grzegorz
Published: January 2023

Despite the growing share of electrically powered vehicles, internal combustion engines are still one of the primary sources of propulsion in transportation. One way to decarbonize engines is to use alternative fuels, where liquefied petroleum gas (LPG) accounts for a large share. Popular car gas systems are LPG indirect vapor phase injection systems, in which the low-pressure gas-phase injector is the actuator. The purpose of the research and analysis presented in this paper is to determine the flow characteristics of three injectors that are structurally different depending on the diameter of the outlet nozzle bore. The tests are conducted, which is new, with pulsed operation of the injector, which, as it turned out, helps explain the discrepancies found. The obtained characteristics are fitted with a polynomial of the second degree, obtaining high-quality indices. In the group of three tested injectors, the average values of volumetric flow rate decreases relative to the maximum by 19.6 and 35.8%. Differences in opening times of 29.3 and 36.6%, respectively, are cited as one of the main reasons for this. Closing times are similar to each other. In addition, the injector with the highest volumetric flow rate and the shortest opening time obtains 1.8 and 9.94% lower average cycle pressures measured at the outlet of the injector nozzle. The differences in opening times and average cycle pressures are considered as possible reasons for the differences in flow characteristics. The obtained characteristics are applicable to engine conversions and calculations.
Comparative Study of Dispersion Curves for LAMB Waves Using Analytical Solutions and Semi-Analytical Methods
Authors: Galán-Pinilla Carlos A. , E-Quiroga Jabid , Peña-Ballesteros Dario Y. , Acosta-Minoli César A. , González-Estrada Octavio Andrés
Published: January 2023

Lamb wave dispersion curves are useful for optimizing the inspection scanning distance that can be covered with good sensitivity in many current applications. However, one of the main problems concerning this calculation lies in selecting a numerical method that is computationally accurate and efficient. In this paper, Lamb waves dispersion curves are generated by the Scaled Boundary Finite Element Method, and by the Rayleigh–Lamb equation. For the semi-analytical case, waveguide cross-section discretization was performed using isoparametric elements and high-order spectral elements. The semi-analytical formulations lead to an eigenvalue problem that can be solved efficiently by calculating the couples of wavenumbers and frequencies that guarantee the wave mode propagation, the basis for generating the dispersion curves. These are compared with those obtained from the analytical solution for the symmetric and antisymmetric modes; in both cases, homogeneous plates of constant thickness are considered. The numerical results show good agreement when using a low number of isoparametric elements, or a single spectral element with shape functions of the order of six for computing the dispersion curves and wave structure. The calculation is given with low computational effort, and the relative variation with respect to the analytical reference values is less than 2%.
A Novel Three-Phase Switched-Capacitor Five-Level Multilevel Inverter with Reduced Components and Self-Balancing Ability
Authors: Jena Kasinath , Kumar Dhananjay , Janardhan Kavali , Kumar B. Hemanth , Singh Arvind R. , Nikolovski Srete , Bajaj Mohit
Published: January 2023

This paper proposes a step-up 3-Ф switched-capacitor multilevel inverter topology with minimal switch count and voltage stresses. The proposed topology is designed to provide five distinct output voltage levels from a single isolated dc source, making it suitable for medium and low-voltage applications. Each leg of the proposed topology contains four switches, one power diode, and a capacitor. The switching signals are also generated using a staircase universal modulation method. As a result, the proposed topology will operate at both low and high switching frequencies. To highlight the proposed topology’s advantages, a comparison of three-phase topologies wasperformed in terms of the switching components, voltage stress, component count per level factor, and cost function withthe recent literature. The topology achieved an efficiency of about 96.7% with dynamic loading, and 75% of the switches experienced half of the peak output voltage (VDC), whereas the remaining switches experienced peak output voltage (2VDC) as voltage stress. The MATLAB/Simulink environment was used to simulate the proposed topology, and a laboratory prototype was also built to verify the inverter’s theoretical justifications and real-time performance.
Retinex-Based Relighting for Night Photography
Authors: Oishi Sou , Fukushima Norishige
Published: January 2023

The lighting up of buildings is one form of entertainment that makes a city more colorful, and photographers sometimes change this lighting using photo-editing applications. This paper proposes a method for automatically performing such changes that follows the Retinex theory. Retinex theory indicates that the complex scenes caught by the human visual system are affected by surrounding colors, and Retinex-based image processing uses these characteristics to generate images. Our proposed method follows this approach. First, we propose a method for extracting a relighting saliency map using Retinex with edge-preserving filtering. Second, we propose a sampling method to specify the lighting area. Finally, we composite the additional light to match the human visual perception. Experimental results show that the proposed sampling method is successful in keeping the illuminated points in bright locations and equally spaced apart. In addition, the proposed various diffusion methods can enhance nighttime skyline photographs with various expressions. Finally, we can add in a new light by considering Retinex theory to represent the perceptual color.
Reinforcement Learning for Autonomous Underwater Vehicles via Data-Informed Domain Randomization
Authors: Lu Wenjie , Cheng Kai , Hu Manman
Published: January 2023

Autonomous Underwater Vehicles (AUVs) or underwater vehicle-manipulator systems often have large model uncertainties from degenerated or damaged thrusters, varying payloads, disturbances from currents, etc. Other constraints, such as input dead zones and saturations, make the feedback controllers difficult to tune online. Model-free Reinforcement Learning (RL) has been applied to control AUVs, but most results were validated through numerical simulations. The trained controllers often perform unsatisfactorily on real AUVs; this is because the distributions of the AUV dynamics in numerical simulations and those of real AUVs are mismatched. This paper presents a model-free RL via Data-informed Domain Randomization (DDR) for controlling AUVs, where the mismatches between the trajectory data from numerical simulations and the real AUV were minimized by adjusting the parameters in the simulated AUVs. The DDR strategy extends the existing adaptive domain randomization technique by aggregating an input network to learn mappings between control signals across domains, enabling the controller to adapt to sudden changes in dynamics. The proposed RL via DDR was tested on the problems of AUV pose regulation through extensive numerical simulations and experiments in a lab tank with an underwater positioning system. These results have demonstrated the effectiveness of RL-DDR for transferring trained controllers to AUVs with different dynamics.
Combining the Non-Surgical Treatment with Extracts of Croton Lechleri and Myrciaria Dubia to Solve Gingival Cleft
Authors: Monterubbianesi Riccardo , Sarri Stefano , Memè Lucia , Orsini Giovanna , Sparabombe Scilla
Published: January 2023

Nowadays, the “pink” aesthetic possesses a significant role in the success of a dental treatment. Extended or small recessions should be solved to achieve harmony between tooth and gingival tissue. Gingival cleft (GC) is a condition that can lead to unpleasant gingival recession in the anterior area. The etiology of GC is still not clear and is often resolved using surgical treatments that, although minimal, are still interventions which can cause risks and discomfort to the patient. Therefore, this case report aims to propose a non-invasive treatment for GC, consisting of a combination of a non-surgical technique with herbal extracts therapy. A non-smoker, healthy patient was subjected to professional oral hygiene treatment supported by Croton Lechleri resin application and at-home supplementation with natural vitamin C (Myrciaria Dubia). The patient entirely followed the instructions and, after 12 months, the GC almost disappeared. In spite of its limitations, since further clinical cases are needed, the proposed non-surgical periodontal technique combined with herbal extracts therapy can represent a promising way to solve or at least reduce GC, before considering surgical treatment.
Rapid Detection of Tea Polyphenols in Fresh Tea Leaves Based on Fusion of Visible/Short-Wave and Long-Wave near Infrared Spectroscopy and Its Device Development
Authors: Xu Jinchai , Qu Fangfang , Shen Bihe , Huang Zhenxiong , Li Xiaoli , Weng Haiyong , Ye Dapeng , Wu Renye
Published: January 2023

Tea polyphenols are considered as an important indicator of tea quality. Rapid detection of tea polyphenol content plays a valuable role for tea breeding and quality inspection during tea production. In this work, a portable rapid non-destructive detection device of tea polyphenols in fresh tea leaves was developed, which integrated the fusion technology of visible/short-wave (400–1050 nm) and long-wave (1000–1650 nm) near-infrared spectroscopy (Vis/NIR). Experimental results indicated that the spectra within the overlapping region (1000–1050 nm) were assembled by applying the spectral data fusing method. Followed by spectral data preprocessing with the Savitzky–Golay smoothing (SG) method, least squares support vector regression (LS–SVR) models were established for detecting the tea polyphenol content of fresh tea leaves. Based on the fused Vis/NIR spectra (dual-band), the correlation coefficient of calibration (RC), root mean square error of calibration (RMSEC), correlation coefficient of prediction (RP), root mean square error of prediction (RMSEP), and residual predictive deviation (RPD) reached 0.976, 0.679%, 0.893, 0.897%, and 2.230, respectively, which were better than the visible/short-wave or long-wave near infrared spectral data (single-band). The sensitive spectral wavebands of tea polyphenols extracted using the random frog (RF) algorithm were distributed in 402–448 nm, 555–600 nm, 810–1042 nm, 1056–1103 nm, 1219–1323 nm, 1406–1416 nm, and 1499–1511 nm. This demonstrated that the prediction of tea polyphenol content using fused spectral data combined with the LS–SVR model depended on various functional groups such as auxochromes, chromogenic groups, and hydrogen-containing groups. The proposed device is capable of non-destructive detection of tea polyphenol content in fresh tea leaves, which can provide effective technical support for tea breeding and tea leaf quality control.
Performance Analysis of Hybrid Kinematic Mechanism for Fusion Reactor Maintenance
Authors: Qin Guodong , Wu Huapeng , Li Changyang , Ji Aihong , Budden Stuart
Published: January 2023

The hybrid kinematic mechanism (HKM) as an alternative remote handling subsystem of the Demonstration Fusion Power Plant (DEMO) breeding blanket (BB) is undergoing extensive theoretical analysis and feasibility verification. In this paper, the forward and inverse kinematic models of the HKM are derived by combining the Newtonian iterative method and the analytical method. Cartesian space trajectory planning is designed based on the trajectories of the HKM lifting of inboard and outboard BBs. The continuous smooth inverse kinematic solutions in the HKM joint space are obtained based on the polynomial interpolation method. For the characteristics of the HKM piston thread driving, the end-effector position error caused by the degradation of the spherical joint into a universal joint is analyzed and calculated. During the lifting of the left inboard BB, there is a maximum absolute error ∆P = 3.1 mm, and as the error continues to expand to the bottom of the BB it causes a risk of collision. Combining the overall effects of driving control, rigid–flexible coupling, etc., on position accuracy, an open-loop variable parameter error compensation plan based on the Levenberg–Marquardt (LM) nonlinear damping least-squares algorithm is proposed and validated in this paper. The simulation results show that the maximum absolute error after compensation is less than 1 mm as the mesh density increases, and the absolute position accuracy can be further improved by local mesh encryption. This study verifies the feasibility of the HKM as a BB remote handling subsystem and provides an option for high-precision control of the HKM.
Influence of Variotropy on the Change in Concrete Strength under the Impact of Wet–Dry Cycles
Authors: Beskopylny Alexey N. , Stel’makh Sergey A. , Shcherban’ Evgenii M. , Mailyan Levon R. , Meskhi Besarion , Chernil’nik Andrei , El’shaeva Diana , Pogrebnyak Anastasia
Published: January 2023

One of the most dangerous types of cyclic effects, especially inherent in several regions in the world, is the alternating impact of wetting and drying on concrete and reinforced concrete structures. In the current scientific literature and practice, there is not enough fundamental and applied information about the resistance to wetting and drying of variotropic concretes obtained by centrifugal compaction methods. The purpose of the study was to investigate the effect of various technological, compositional, and other factors on the final resistance of variotropic concrete to alternating cycles of moistening and drying. For this, special methods for testing concrete samples were used in the work. It has been established that after strength gain as a result of hydration, there is a tendency for strength loss due to concrete wear. An acidic medium has the most negative effect on the strength characteristics of concretes made using various technologies, compared with neutral and alkaline media. The loss of strength of concrete when moistened in an acidic medium was greater than in alkaline and especially neutral media. The vibrocentrifuged concrete turned out to be the most resistant to the impact of an aggressive environment and the cycles of moistening and drying, compared to the centrifuged and vibrated concrete. The drop in strength was up to 7% less compared to centrifuged concrete and up to 17% less than vibrated concrete.
Stroke-Based Autoencoders: Self-Supervised Learners for Efficient Zero-Shot Chinese Character Recognition
Authors: Chen Zongze , Yang Wenxia , Li Xin
Published: January 2023

Chinese characters carry a wealth of morphological and semantic information; therefore, zero-shot Chinese character recognition with the morphology of Chinese characters has drawn significant attention. The previous methods are mainly based on radical-level decomposition or stroke-level decomposition, which usually cannot capture adequately the structural and spatial information of Chinese characters. In this paper, we develop a stroke-based autoencoder (SAE), to model the sophisticated morphology of Chinese characters with a self-supervised method. Following its canonical writing order, we first represent a Chinese character as a series of stroke images with a fixed writing order, and then our SAE model is trained to reconstruct this stroke image sequence. This pre-trained SAE model can predict the stroke image series for unseen characters, as long as their strokes or radicals are in the training set. We have designed two contrasting SAE architectures on different forms of stroke images. One is fine-tuned on existing stroke-based method for zero-shot recognition of handwritten Chinese characters, and the other is applied to enrich the Chinese word embeddings from their morphological features. The experimental results validate that after pre-training, our SAE architecture outperforms other existing methods in zero-shot recognition and enhances the representation of Chinese characters with their abundant morphological and semantic information.
Dynamic Scheduling and Optimization of AGV in Factory Logistics Systems Based on Digital Twin
Authors: Wu Shiqing , Xiang Wenting , Li Weidong , Chen Long , Wu Chenrui
Published: January 2023

At present, discrete workshops demand higher transportation efficiency, but the traditional scheduling strategy of the logistics systems can no longer meet the requirements. In a transportation system with multiple automated guided vehicles (multi-AGVs), AGV path conflicts directly affect the efficiency and coordination of the whole system. At the same time, the uncertainty of the number and speed of AGVs will lead to excessive cost. To solve these problems, an AGVs Multi-Objective Dynamic Scheduling (AMODS) method is proposed which is based on the digital twin of the workshop. The digital twin of the workshop is built in the virtual space, and a two-way exchange and real-time control framework based on dynamic data is established. The digital twin system is adopted to exchange data in real time, create a real-time updated dynamic task list, determine the number of AGVs and the speed of AGVs under different working conditions, and effectively improve the efficiency of the logistics system. Compared with the traditional scheduling strategy, this paper is of practical significance for the scheduling of the discrete workshop logistics systems to improve the production efficiency, utilization rate of resources, and dynamic response capability.
Automated Classification of Urinary Cells: Using Convolutional Neural Network Pre-trained on Lung Cells
Authors: Teramoto Atsushi , Michiba Ayano , Kiriyama Yuka , Sakurai Eiko , Shiroki Ryoichi , Tsukamoto Tetsuya
Published: January 2023

Urine cytology, which is based on the examination of cellular images obtained from urine, is widely used for the diagnosis of bladder cancer. However, the diagnosis is sometimes difficult in highly heterogeneous carcinomas exhibiting weak cellular atypia. In this study, we propose a new deep learning method that utilizes image information from another organ for the automated classification of urinary cells. We first extracted 3137 images from 291 lung cytology specimens obtained from lung biopsies and trained a classification process for benign and malignant cells using VGG-16, a convolutional neural network (CNN). Subsequently, 1380 images were extracted from 123 urine cytology specimens and used to fine-tune the CNN that was pre-trained with lung cells. To confirm the effectiveness of the proposed method, we introduced three different CNN training methods and compared their classification performances. The evaluation results showed that the classification accuracy of the fine-tuned CNN based on the proposed method was 98.8% regarding sensitivity and 98.2% for specificity of malignant cells, which were higher than those of the CNN trained with only lung cells or only urinary cells. The evaluation results showed that urinary cells could be automatically classified with a high accuracy rate. These results suggest the possibility of building a versatile deep-learning model using cells from different organs.
A Machine-Learning-Based Approach to Predict Deforestation Related to Oil Palm: Conceptual Framework and Experimental Evaluation
Authors: Sboui Tarek , Saidi Salwa , Lakti Ahmed
Published: January 2023

Deforestation is recognized as an issue that has negative effects on the ecosystem. Predicting deforestation and defining the causes of deforestation is an important process that could help monitor and prevent deforestation. Deforestation prediction has been boosted by recent advances in geospatial technologies and applications, especially remote sensing technologies and machine learning techniques. This paper highlights the issue of predicting deforestation related to oil palm, which has not been focused on in existing research studies. The paper proposes an approach that aims to enhance the prediction of deforestation related to oil palm plantations and palm oil production. The proposed approach is based on a conceptual framework and an assessment of a set of criteria related to such deforestation. The criteria are assessed and validated based on a sensitivity analysis. The framework is based on machine learning and image processing techniques. It consists of three main steps, which are data preparation, model training, and validation. The framework is implemented in a case study in the Aceh province of Indonesia to show the feasibility of our proposed approach in predicting deforestation related to oil palm. The implementation of the proposed approach shows an acceptable accuracy for predicting deforestation.
A Multi-Attention Approach Using BERT and Stacked Bidirectional LSTM for Improved Dialogue State Tracking
Authors: Khan Muhammad Asif , Huang Yi , Feng Junlan , Prasad Bhuyan Kaibalya , Ali Zafar , Ullah Irfan , Kefalas Pavlos
Published: January 2023

The modern digital world and associated innovative and state-of-the-art applications that characterize its presence, render the current digital age a captivating era for many worldwide. These innovations include dialogue systems, such as Apple’s Siri, Google Now, and Microsoft’s Cortana, that stay on the personal devices of users and assist them in their daily activities. These systems track the intentions of users by analyzing their speech, context by looking at their previous turns, and several other external details, and respond or act in the form of speech output. For these systems to work efficiently, a dialogue state tracking (DST) module is required to infer the current state of the dialogue in a conversation by processing previous states up to the current state. However, developing a DST module that tracks and exploit dialogue states effectively and accurately is challenging. The notable challenges that warrant immediate attention include scalability, handling the unseen slot-value pairs during training, and retraining the model with changes in the domain ontology. In this article, we present a new end-to-end framework by combining BERT, Stacked Bidirectional LSTM (BiLSTM), and a multiple attention mechanism to formalize DST as a classification problem and address the aforementioned issues. The BERT-based module encodes the user’s and system’s utterances. The Stacked BiLSTM extracts the contextual features and multiple attention mechanisms to calculate the attention between its hidden states and the utterance embeddings. We experimentally evaluated our method against the current approaches over a variety of datasets. The results indicate a significant overall improvement. The proposed model is scalable in terms of sharing the parameters and it considers the unseen instances during training.
Constant and Intermittent Contact with the Volatile Organic Compounds of Serendipita indica Alleviate Salt Stress In Vitro Ocimum basilicum L.
Authors: Fraj Hassiba , Werbrouck Stefaan P. O.
Published: January 2023

Serendipita indica is a plant growth-promoting fungus. It is a natural soil dweller that can colonize the roots of a wide range of plants, including cultivated crops. S. indica has been reported to improve plant nutrient uptake and increase stress tolerance when inoculated into the soil. The present study was undertaken to study the effect of volatile organic compounds (VOCs) of S. indica on salt-stressed Ocimum basilicum ‘Fin vert’ in vitro, either in a culture vessel with a semi-solid medium or via a modified temporary immersion bioreactor system (SETIS). For all salt concentrations, VOCs of S. indica significantly improved plant growth in both semi-solid medium and SETIS bioreactors. This resulted in heavier and taller plants, more shoots per plant, and longer roots. This was even observed for the control without salt. At 9 g/L NaCl, plants with Serendipita were able to give longer roots than those without (1.2 cm vs. 0.0 and 1.7 cm vs. 1.7 cm) in the semi-solid medium and SETIS, respectively. Nevertheless, the VOCs were not able to make the plant salt tolerant to this high concentration. The increase in total phenolic and flavonoid content and radical scavenging suggest that the antioxidant defense system is triggered by the S. indica VOCs. In the semi-solid system, without VOCs, 1 g/L NaCl led to an increase in total chlorophyll content (TCC) and a significant decrease in TCC was further measured only at 6 g/L NaCl or more. However, when VOCs were added, the bleaching effect of the salt was partially restored, even at 6 and 9 g/L NaCl. A significant decrease in TCC was also measured in the SETIS system at 6 g/L NaCl or more and treatment with VOC did not make any difference. An exception was 9 g/L, where the VOC-treated plants produced more than three times more chlorophyll than the non-treated plants. These findings will encourage the application of Serendipita indica for stress reduction. In addition, the proposed original adaptation of a temporary immersion system will be instrumental to investigate stress reduction associated with volatile compounds and better understand their mechanism of action.
Antimicrobial Coatings: Reviewing Options for Healthcare Applications
Authors: Jose Ajay , Gizdavic-Nikolaidis Marija , Swift Simon
Published: January 2023

Many publications report coatings that exhibit antimicrobial potency applicable to high-touch surfaces and desirable for healthcare settings to contribute to reductions in the occurrence of Hospital Acquired Infections (HAI). In this review, the importance of surface contamination and the transmission of microbes is addressed. The standard strategy to tackle fomites is to implement proper disinfection and cleaning practices and periodically monitor the environment’s cleanliness. However, the probability of recontamination of cleaned surfaces is high. Therefore, an additional first line of defense against pathogen transmission and subsequent infection is the antimicrobial surface that can eliminate or at least repel pathogens, introducing a barrier to the spread of infection. It is a simple concept, but formulating a durable, antimicrobial coating with broad-spectrum antimicrobial and antifouling activities has proven challenging. The challenges and progress made in developing such material are reviewed.
Computation of the Attenuated Backscattering Coefficient by the Backscattering Lidar Signal Simulator (BLISS) in the Framework of the CALIOP/CALIPSO Observations
Authors: Szczap Frédéric , Alkasem Alain , Shcherbakov Valery , Schmisser Roseline , Blanc Jérome , Mioche Guillaume , Gour Yahya , Cornet Céline , Banson Sandra , Bray Edouard
Published: January 2023

This paper presents the Backscattering Lidar Signal Simulator (BLISS), an end-to-end lidar simulator developed by the Centre National d’Etudes Spatiales (CNES). We computed the constant multiple-scattering (MS) coefficient of BLISS with a Monte Carlo (MC) code in the framework of CALIOP/CALIPSO observations for different homogeneous and plane-parallel stratocumulus and cirrus cloud geophysical scenes. The MS coefficient varies from 0.46 to 0.63. Then we evaluated the Level 1 products of BLISS. Above and in-cloud relative difference between the attenuated backscattering coefficient vertical profile simulated by BLISS and by the MC code is smaller than 0.5% under single-scattering regime and smaller than 10% (30% if optical depth of cirrus is large) under multiple-scattering regime, thus confirming the robustness of BLISS.
Biofiltration of Waste Gas Containing Cyclohexanol, Cyclohexanone and Butanol
Authors: Tabernacka Agnieszka
Published: January 2023

The aim of the study was to determine the efficiency of a biofilter treating waste gas containing a mixture of cyclohexanol (CHXOH), cyclohexanone (CHXO) and butanol (BL) and to assess the impact of the process parameters on the microorganisms and their enzymatic activities. The biofilter was packed with compost made from green waste mixed with compost made from municipal wastes and polyethylene carriers with immobilized biomass of bacteria. A linear correlation between pollutant loading rate and biofilter elimination capacity was obtained. At a hydraulic load of the biofilter bed of 127.3 m3/(m3 × h), the average elimination capacities were 14.6 g CHXOH/(m3 × h), 3.6 g CHXO/(m3 × h) and 3.8 g BL/(m3 × h). The microbiological and enzymatic analyses of the biofilter bed indicated that high loading rates of pollutants can have significant effects on microbial growth and enzymatic activity.