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Computer vision-based classification of concrete spall severity using metaheuristic-optimized Extreme Gradient Boosting Machine and Deep Convolutional Neural Network
طبقه بندی مبتنی بر بینایی کامپیوتری شدت پاشش بتن با استفاده از ماشین تقویت کننده گرادیان قویا بهینه شده فراابتکاری و شبکه عصبی پیچیده عمیق-2022 This paper presents alternative solutions for classifying concrete spall severity based on computer vision ap-
proaches. Extreme Gradient Boosting Machine (XGBoost) and Deep Convolutional Neural Network (DCNN) are
employed for categorizing image samples into two classes: shallow spall and deep spall. To delineate the
properties of a concrete surface subject to spall, texture descriptors including local binary pattern, center sym-
metric local binary pattern, local ternary pattern, and attractive repulsive center symmetric local binary pattern
(ARCS-LBP) are employed as feature extraction methods. In addition, the prediction performance of XGBoost is
enhanced by Aquila optimizer metaheuristic. Meanwhile, DCNN is capable of performing image classification
directly without the need for texture descriptors. Experimental results with a dataset containing real-world
concrete surface images and 20 independent model evaluations point out that the XGBoost optimized by the
Aquila metaheuristic and used with ARCS-LBP has achieved an outstanding classification performance with a
classification accuracy rate of roughly 99%. keywords: شدت ریزش بتن | دستگاه افزایش گرادیان | الگوی باینری محلی | فراماسونری | یادگیری عمیق | Concrete spall severity | Gradient boosting machine | Local binary pattern | Metaheuristic | Deep learning |
مقاله انگلیسی |
2 |
Trustworthy authorization method for security in Industrial Internet of Things
روش مجوز معتبر برای امنیت در اینترنت اشیا صنعتی-2021 Industrial Internet of Things (IIoT) realizes machine-to-machine communication and human–computer inter- action (HCI) through communication network, which makes industrial production automatic and intelligent. Security is critical in IIoT because of the interconnection of intelligent industrial equipment. In IIoT environment, legitimate human–computer interaction can only be performed by authorized professionals, and unauthorized access is not tolerated. In this paper, a reliable authentication method based on biological information is proposed. Specifically, the complete local binary pattern (CLPB) and the statistical local binary pattern (SLPB) are introduced to describe the local vein texture characteristics. Meanwhile, the contrast energy and frequency domain information are regarded as auxiliary information to interpret the finger vein. The distance between the features of the registration image and the test image is used to recognize the finger vein image, so as to realize identity authentication. The experiments are carried out on SDUMLA-FV database and FV-USM database, and results show that the presented method has achieved high recognition accuracy. Keywords: Industrial Internet of Things (IIoT) | Human–computer interaction (HCI) | Biometric recognition | Comprehensive texture | Security system |
مقاله انگلیسی |
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Optimizing the electrical conductivity of polyacrylonitrile/polyaniline with nickel nanoparticles for the enhanced electrostimulation of Schwann cells proliferation
بهینه سازی رسانایی الکتریکی پلی اکریلونیتریل/پلی آنیلین با نانوذرات نیکل برای تحریک الکتریکی افزایش یافته تکثیر سلول های شوان-2021 Tissue engineering scaffolds made of biocompatible polymers are promising alternatives for nerve reparation. For this application, cell proliferation will be speeded up by electrostimulation, which required
electrically-conductive materials. Here, a biomimicking scaffold with optimized conductivity was developed from electrospun polyacrylonitrile/electrically-conductive polyaniline (PAN/PANI) nanofibers
doped with Ni nanoparticles. PAN/PANI/Ni was biocompatible for Schwann cells and exhibited a suitable
tensile strength and wettability for cell proliferation. When compared with unmodified PAN/PANI, the
electrical conductivity of PAN/PANI/Ni was 6.4 fold higher. Without electrostimulation, PAN/PANI and
PAN/PANI/Ni exhibited similar Schwann cells’ proliferation rates. Upon electrostimulation at
100 mV cm1 for one hour per day over five days, PAN/PANI/Ni accelerated Schwann cells’ proliferation
2.1 times compared to PAN/PANI. These results demonstrate the importance of expanding the electrical
conductivity of the tissue engineering scaffold to ensure optimal electrostimulation of nerve cell growth.
Additionally, this study describes a straightforward approach to modulate the electrical conductivity of
polymeric materials via the addition of Ni nanoparticles that can be applied to different biomimicking
scaffolds for nerve healing.
Keywords: Nerve tissue engineering | Electrospinning | PAN/PANI | Ni nanoparticles | Schwann cells |
مقاله انگلیسی |
4 |
Sustainable chitosan-based electrical responsive scaffolds for tissue engineering applications
داربست های پاسخگو الکتریکی مبتنی بر کیتوزان پایدار برای کاربردهای مهندسی بافت-2021 Electroconductive biomaterials have potential in the regeneration of electrically active biological tissues (neural,
orthopedic, cardiac). The aim of this study was to develop an electroconductive scaffold using natural and/or
sustainable materials. A composite scaffold made of chitosan, a compound of natural origin, and with incorporated with graphitic carbon obtained from cork (natural and sustainable source) as an electroconductive filler,
was prepared. Chitosan (Ch) scaffolds with different concentration of pyrolyzed cork (PC) were prepared and
fully characterized. An electroconductivity of 5.5 × 10−5 S/cm, i.e. in the range of cardiac tissues, was obtained.
FTIR and XPS analysis did not show the presence of chemical bonds between the two components. Despite
this, the composite scaffold showed higher thermal stability; moreover, their mechanical strength was significantly higher than for the pure chitosan. The biocompatibility of Ch-PC composite scaffolds has been verified
by SH-SY5Y neuroblastoma cell viability assay. This study shows that a sustainable composite made with chitosan
and an innovative electroconductive filler has potential application in tissue engineering.
Keywords: Conductive polymers | Chitosan | Tissue engineering | Graphitic carbon | Natural sources |
مقاله انگلیسی |
5 |
3D-printable conductive materials for tissue engineering and biomedical applications
مواد رسانای قابل چاپ سه بعدی برای مهندسی بافت و کاربردهای زیست پزشکی-2021 Many patients that undergo autografting suffer from donor site morbidity and risk of immune rejection. Tissue
engineering is receiving considerable attention as engineered tissues could help overcome the drawbacks of
autografts and achieve better performance on tissue repair, replacement and regeneration. Conductivity is one of
the desired properties of engineered scaffolds and tissue constructs as bioelectricity plays an important role in the
native physiological environment. Hence, conductive materials have been extensively used in the making of
biosensors, tissue engineering scaffolds and drug delivery systems to elicit electrically-mediated signals, thus
mimicking the natural cellular environment. Conductive polymers, carbon-based materials, and metal nanoparticles are the main categories of conductive materials used. Ionic liquids, especially biocompatible ionic
liquids, is currently being explored as a competitive filler composite to greatly improve the conductivity of
polymers with little to zero cytotoxicity. The effects of electrical stimulation on cell alignment, migration,
proliferation, and differentiation as well as detailed properties of different types of conductive materials are
briefly yet succinctly reviewed. Furthermore, 3D printing of conductive scaffolds and hydrogels, and their corresponding biomedical applications are also discussed.
Keywords: Conductive biomaterials | Bioprinting | Tissue engineering | Ionic liquids | Electrical stimulation |
مقاله انگلیسی |
6 |
آرایش مولکولی تخمدان بالغ انسان
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 14 سلول های عملکردی تخمدان برای باروری انسان ضروری هستند. در تخمدان بالغ، انواع مختلف سلول ها هموستاز تخمدان را تضمین می کند، تولید هورمونی را امکان پذیر می کند و از بلوغ تخمک حمایت می کند. تخمدان یک اندام پیچیده و بسیار پویا است که از انواع زیادی سلولتشکیل شده است که بسیاری از آنها هنوز مشخص نشدهاند. استفاده از فنآوریهای توالییابی RNA تک سلولی بر روی بافت تخمدان انسان منجر به آغاز کشف نشانه های مولکولی سلولهای موجود در تخمدان شده است و تغییرات چشمگیر در بیان ژن در طول رشد و رگرسیون فولیکولی را نشان داده است. این دانش در نهایت بینش هایی را در مورد باروری زنان و بیماری های تولید مثلی مرتبط ارائه می دهد و بهینه سازی مدل های بیماری مبتنی بر انسان و پروتکل های گامتوژنز در شرایط آزمایشگاهی را امکان پذیر می کند.
کلید واژه ها: انسان | تخمدان بالغ | ردیابی رونویسی | توالی یابی تک سلولی | فولیکولوژنز. |
مقاله ترجمه شده |
7 |
In-field automatic detection of maize tassels using computer vision
تشخیص خودکار کاکل ذرت با استفاده از بینایی ماشین-2021 The heading stage of maize is an important period during its growth and development and indicates the beginning of its pollination. In this regard, an automated method for maize tassel detection is highly important to monitor maize growth. However, the recognition of maize heading stage mainly relies on visual evaluation. This method presents some limitations, such as expensive and subjective. This work proposed a novel method for automatic tassel detection. In the proposed algorithm, a color attenuation prior model was used to model the scene depth of saturation graph to remove image saturation. An Itti visual attention detection algorithm was used to detect the area of interest. Texture features and vegetation indices were used to develop a classification model to eliminate false positives. Pictures were captured using a commercial camera for two years to verify the stability of the proposed algorithm. Three indices were calculated to quantitatively assess and rate the algorithms. Experimental results show that the proposed method outperforms other existing methods, and its recall, precision, and F1 measure values are 86.30%, 91.44%, and 88.36%, respectively. Results indicate that the proposed method can effectively detect maize tassels in field images and remain stable with time.© 2020 China Agricultural University. Production and hosting by Elsevier B.V. on behalf of KeAi. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Keywords: Maize tassel detection | Texture feature | Vegetation index | Saliency based |
مقاله انگلیسی |
8 |
Vision based prediction of surface roughness for end milling
پیش بینی مبتنی بر دید از زبری سطح برای فرز نهایی-2021 Measurement of surface roughness helps to assess the machined component’s functionality. In the past three decades, several scientists have contributed to the computation of surface roughness. This research article deals with two distinct methods for prediction of surface roughness employing the surface pro- filometer and machine vision for AISI 1040 steel specimens prepared by varying cutting parameters of end milling viz. feed rates, speed and cutting depth. Using a surface profilometer, the surface roughness parameters are evaluated. At the other hand, the texture features were extracted using a Gray Level Co- occurrence Matrix Algorithm (GLCM) and a computer vision system. Correlations are formed among characteristics of machined surface and the texture feature such as contrast, entropy, energy, and homogeneity. The comparable findings revealed a maximum relative error of —8% using contrast and energy, — 11% using entropy and —10% using homogeneity.© 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Materials, Processing & Characterization. Keywords: Surface roughness parameter | Gray Level Co-occurrence Matrix (GLCM) | Texture feature | Machine vision system | Linear regression |
مقاله انگلیسی |
9 |
Electro-conductive carbon nanofibers containing ferrous sulfate for bone tissue engineering
Electro-conductive carbon nanofibers containing ferrous sulfate for bone tissue engineering-2021 The application of electroactive scaffolds can be promising for bone tissue engineering applications. In the
current paper, we aimed to fabricate an electro-conductive scaffold based on carbon nanofibers (CNFs) containing ferrous sulfate. FeSO4⋅7H2O salt with different concentrations 5, 10, and 15 wt%, were blended with
polyacrylonitrile (PAN) polymer as the precursor and converted to Fe2O3/CNFs nanocomposite by electrospinning and heat treatment. The characterization was conducted using SEM, EDX, XRD, FTIR, and Raman
methods. The results showed that the incorporation of Fe salt induces no adverse effect on the nanofibers
morphology. EDX analysis confirmed that the Fe ions are uniformly dispersed throughout the CNF mat. FTIR
spectroscopy showed the interaction of Fe salt with PAN polymer. Raman spectroscopy showed that the incorporation of FeSO4⋅7H2O reduced the ID/IG ratio, indicating more ordered carbon in the synthesized nanocomposite. Electrical resistance measurement depicted that, although the incorporation of ferrous sulfate
reduced the electrical conductivity, the conductive is suitable for electrical stimulation. The in vitro studies
revealed that the prepared nanocomposites were cytocompatible and only negligible toxicity (less than 10%)
induced by CNFs/Fe2O3 fabricated from PAN FeSO4⋅7H2O 15%. Although various nanofibrous composite
fabricated with Fe NPs have been evaluated for tissue engineering applications, CNFs exhibited promising
properties, such as excellent mechanical strength, biocompatibility, and electrical conductivity. These results
showed that the fabricated nanocomposites could be applied as the bone tissue engineering scaffold.
Keywords: Bone tissue engineering | Electrospinning | Carbon nanofiber | Ferrous sulfate |
مقاله انگلیسی |
10 |
The biometric recognition system based on near-infrared finger vein image
سیستم تشخیص بیومتریک بر اساس تصویر رگ انگشت نزدیک مادون قرمز-2021 It is a difficult task to extract vein features accurately since the finger-vein images captured by near infrared light are always poor in quality. This paper proposes a novel finger vein feature representation scheme based on pyramid histograms of oriented gradients and local phase quantization. As the vein networks consist of abundant texture and orientation features, a texture feature description operator at various scales is employed on the finger vein image to reduce the effects of geometric deformation occurred image acquisition due to the different posture and position of fingers. To solve the adverse effects of image blurring caused by uneven illumination, local phase quantization is then introduced to extract vein features. Finally, the above mentioned extracted two kinds of texture characteristics of vein image are fused at feature level by concatenated histograms to obtain accurate vein feature named pyramid local phase quantization histogram (PLPQ). In this way, we encode the vein image in- formation not only in frequency domain but also among different orientations and scales. We perform rigorous experiments on two publicly available databases named FV-USM and MMCBUN, and the results of the experiments reveal that proposed fusion system can make promising improvement of finger vein recognition performance. Keywords: Finger texture | Finger vein recognition | Pyramid histogram of oriented gradients | Local phase quantization |
مقاله انگلیسی |