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1 |
The physical and mechanical properties for flexible biomass particles using computer vision
خواص فیزیکی و مکانیکی ذرات زیست توده انعطاف پذیر با استفاده از بینایی کامپیوتری-2022 The combustion and fluidization behavior of biomass depend on the physical properties (size, morphology, and
density) and mechanical performances (elastic modulus, Poisson’s ratio, tensile strength and failure strain), but
their quantitative models have rarely been focused in previous researchers. Hence, a static image measurement
for particle physical properties is studied. Combining the uniaxial tension and digital image correlation tech-
nology, the dynamic image measurement method for the mechanical properties is proposed. The results indicate
that the average roundness, rectangularity, and sphericity of present biomass particles are 0.2, 0.4, and 0.16,
respectively. The equivalent diameter and density obey the skewed normal distribution. The tensile strength and
failure stress are sensitive to stretching rate, fiber size and orientation. The distribution intervals of elastic
modulus and Poisson’s ratio are 30–600 MPa and 0.25–0.307, respectively. The stress–strain curves obtained
from imaging experiments agree well with the result of finite element method. This study provides the operating
parameters for the numerical simulation of particles in the fluidized bed and combustor. Furthermore, the
computer vision measurement method can be extended to the investigations of fossil fuels. keywords: ذرات زیست توده | مشخصات فیزیکی | اجرای مکانیکی | تست کشش | آزمایش تصویربرداری | بینایی کامپیوتر | Biomass particle | Physical properties | Mechanical performances | Tensile testing | Imaging experiment | Computer vision |
مقاله انگلیسی |
2 |
The application of computer vision systems in meat science and industry – A review
کاربرد سیستم های بینایی کامپیوتری در علم و صنعت گوشت – مروری-2022 Computer vision systems (CVS) are applied to macro- and microscopic digital photographs captured using digital
cameras, ultrasound scanners, computer tomography, and wide-angle imaging cameras. Diverse image acquisi-
tion devices make it technically feasible to obtain information about both the external features and internal
structures of targeted objects. Attributes measured in CVS can be used to evaluate meat quality. CVS are also used
in research related to assessing the composition of animal carcasses, which might help determine the impact of
cross-breeding or rearing systems on the quality of meat. The results obtained by the CVS technique also
contribute to assessing the impact of technological treatments on the quality of raw and cooked meat. CVS have
many positive attributes including objectivity, non-invasiveness, speed, and low cost of analysis and systems are
under constant development an improvement. The present review covers computer vision system techniques,
stages of measurements, and possibilities for using these to assess carcass and meat quality. keywords: سیستم بینایی کامپیوتری | گوشت | محصولات گوشتی | لاشه | Computer vision system | Meat | Meat products | Carcass |
مقاله انگلیسی |
3 |
Disintegration testing augmented by computer Vision technology
آزمایش تجزیه با فناوری Vision کامپیوتری تقویت شده است-2022 Oral solid dosage forms, specifically immediate release tablets, are prevalent in the pharmaceutical industry.
Disintegration testing is often the first step of commercialization and large-scale production of these dosage
forms. Current disintegration testing in the pharmaceutical industry, according to United States Pharmacopeia
(USP) chapter 〈701〉, only gives information about the duration of the tablet disintegration process. This infor-
mation is subjective, variable, and prone to human error due to manual or physical data collection methods via
the human eye or contact disks. To lessen the data integrity risk associated with this process, efforts have been
made to automate the analysis of the disintegration process using digital lens and other imaging technologies.
This would provide a non-invasive method to quantitatively determine disintegration time through computer
algorithms. The main challenges associated with developing such a system involve visualization of tablet pieces
through cloudy and turbid liquid. The Computer Vision for Disintegration (CVD) system has been developed to
be used along with traditional pharmaceutical disintegration testing devices to monitor tablet pieces and
distinguish them from the surrounding liquid. The software written for CVD utilizes data captured by cameras or
other lenses then uses mobile SSD and CNN, with an OpenCV and FRCNN machine learning model, to analyze
and interpret the data. This technology is capable of consistently identifying tablets with ≥ 99.6% accuracy. Not
only is the data produced by CVD more reliable, but it opens the possibility of a deeper understanding of
disintegration rates and mechanisms in addition to duration. keywords: از هم پاشیدگی | اشکال خوراکی جامد | تست تجزیه | یادگیری ماشین | شبکه های عصبی | Disintegration | Oral Solid Dosage Forms | Disintegration Test | Machine Learning | Neural Networks |
مقاله انگلیسی |
4 |
Digital Twin-driven approach to improving energy efficiency of indoor lighting based on computer vision and dynamic BIM
رویکرد دیجیتال دوقلو برای بهبود بهره وری انرژی در روشنایی داخلی بر اساس بینایی کامپیوتر و BIM پویا-2022 Intelligent lighting systems and surveillance systems have become an important part of intelligent buildings. However, the current intelligent lighting system generally adopts independent sensor control and
does not perform multi-source heterogeneous data fusion with other digital systems. This paper fully
considers the linkage between the lighting system and the surveillance system and proposes a digital
twin lighting (DTL) system that mainly consists of three parts. Firstly, a visualized operation and maintenance (VO&M) platform for a DTL system was established based on dynamic BIM. Secondly, the environment perception, key-frame similarity judgment, and multi-channel key-frame cut and merge
mechanism were utilized to preprocess the video stream of the surveillance system in real-time.
Lastly, pedestrians detected using YOLOv4 and the ambient brightness perceived by the environment
perception mechanism were transmitted to the cloud database and were continuously read by the
VO&M platform. The intent here was to aid timely adaptive adjustment of the digital twin and realistic
lighting through the internet. The effectiveness of the proposed method was verified by experimenting
with a surveillance video stream for 14 days. The key results of the experiments are as follows: (1) the
accuracy rate of intelligent decision control reached 95.15%; (2) energy consumption and electricity costs
were reduced by approximately 79%; and (3) the hardware cost and energy consumption of detection
equipment and the time and cost of operation and maintenance (O&M) were greatly reduced.
keywords: Computer vision | Digital Twin | Dynamic BIM | Energy-efficient buildings | Intelligent lighting control |
مقاله انگلیسی |
5 |
Computer vision-based illumination-robust and multi-point simultaneous structural displacement measuring method
روش اندازه گیری جابجایی ساختاری همزمان با روشنایی مبتنی بر بینایی کامپیوتری-2022 Computer vision-based techniques for structural displacement measurement are rapidly becoming
popular in civil structural engineering. However, most existing computer vision-based displace-
ment measurement methods require man-made targets for object matching or tracking, besides
usually the measurement accuracies are seriously sensitive to the ambient illumination variations.
A computer vision-based illumination robust and multi-point simultaneous measuring method is
proposed for structural displacement measurements. The method consists of two part, one is for
segmenting the beam body from its background, the segmentation is perfectly carried out by fully
convolutional network (FCN) and conditional random field (CRF); another is digital image cor-
relation (DIC)-based displacement measurement. A simply supported beam is built in laboratory.
The accuracy and illumination robustness are verified through three groups of elaborately
designed experiments. Due to the exploitation of FCN and CRF for pixel-wise segmentation,
numbers of locations along with the segmented beam body can be chosen and measured simul-
taneously. It is verified that the method is illumination robust since the displacement measure-
ments are with the smallest fluctuations to the illumination variations. The proposed method does
not require any man-made targets attached on the structure, but because of the exploitation of
DIC in displacement measurement, the regions centered on the measuring points need to have
texture feature. keywords: پایش سلامت سازه | اندازه گیری جابجایی | بینایی کامپیوتر | یادگیری عمیق | تقسیم بندی شی | همبستگی تصویر دیجیتال | Structural health monitoring | Displacement measurement | Computer vision | Deep learning | Object segmentation | Digital image correlation |
مقاله انگلیسی |
6 |
Animal biometric assessment using non-invasive computer vision and machine learning are good predictors of dairy cows age and welfare: The future of automated veterinary support systems
ارزیابی بیومتریک حیوانات با استفاده از بینایی کامپیوتری غیرتهاجمی و یادگیری ماشینی پیشبینیکننده خوبی برای سن و رفاه گاوهای شیری هستند: آینده سیستمهای پشتیبانی خودکار دامپزشکی-2022 Digitally extracted biometrics from visible videos of farm animals could be used to automatically assess animal
welfare, contributing to the future of automated veterinary support systems. This study proposed using non-
invasive video acquisition and biometric analysis of dairy cows in a robotic dairy farm (RDF) located at the
Dookie campus, The University of Melbourne, Australia. Data extracted from dairy cows were used to develop
two machine learning models: a biometrics regression model (Model 1) targeting (i) somatic cell count, (ii)
weight, (iii) rumination, and (iv) feed intake and a classification model (Model 2) mapping features from dairy
cow’s face to predict animal age. Results showed that Model 1 achieved a high correlation coefficient (R = 0.96),
slope (b = 0.96), and performance, and Model 2 had high accuracy (98%), low error (2%), and high performance
without signs of under or overfitting. Models developed in this study can be used in parallel with other models to
assess milk productivity, quality traits, and welfare for RDF and conventional dairy farms. keywords: هوش مصنوعی | فیزیولوژی گاو | ماستیت | بیومتریک حیوانات | سنجش از راه دور برد کوتاه | Artificial intelligence | Cows physiology | Mastitis | Animal biometrics | Short range remote sensing |
مقاله انگلیسی |
7 |
A graphics-based digital twin framework for computer vision-based post-earthquake structural inspection and evaluation using unmanned aerial vehicles
یک چارچوب دیجیتال دوقلوی مبتنی بر گرافیک برای بازرسی و ارزیابی ساختاری پس از زلزله مبتنی بر بینایی کامپیوتری با استفاده از وسایل نقلیه هوایی بدون سرنشین-2022 Rapid structural inspections and evaluations are critical after earthquakes. Computer vision-based methods have attracted the interest of researchers for their potential to be rapid, safe, and objective. To provide an end-to-end solution for computer vision-based post-earthquake inspection and evaluation of a specific as-built structure, the concepts of physics-based graphics model (PBGM) and digital twin (DT) are combined to develop a graphics-based digital twin (GBDT) framework. The GBDT framework comprises a finite element (FE) model and a computer graphics (CG) model whose state is informed by the FE analysis, representing the state of the structure before and after an earthquake. The CG model is first created making use of the FE model and the photographic survey of the structure, yielding the virtual counterpart of the as-built structure quickly and accurately. Then damage modelling approaches are proposed to predict the location and extent of structural and nonstructural damage under seismic loading, from which photographic representation of the predicted damage is realized in the CG model. The effectiveness of the GBDT framework is demonstrated using a five-story reinforced concrete benchmark building through the design and assessment of various UAV (Unmanned Aerial Vehicle) inspection trajectories for post-earthquake scenarios. The results demonstrate that the proposed GBDT framework has significant potential to enable rapid structural inspection and evaluation, ultimately leading to more efficient allocation of scarce resources in a post-earthquake setting.
keywords: بینایی کامپیوتر | مهندسی زلزله | دوقلو دیجیتال | ارزیابی پس از زلزله | دوقلو دیجیتال مبتنی بر گرافیک | مدل گرافیکی مبتنی بر فیزیک | Computer vision | Earthquake engineering | Digital twin | Post-earthquake assessment | Graphics-based digital twin | Physics-based graphics model |
مقاله انگلیسی |
8 |
Quantum Kernels for Real-World Predictions Based on Electronic Health Records
هستههای کوانتومی برای پیشبینیهای دنیای واقعی بر اساس پروندههای سلامت الکترونیکی-2022 Research on near-term quantum machine learning has explored how classical machine learning
algorithms endowed with access to quantum kernels (similarity measures) can outperform their purely
classical counterparts. Although theoretical work has shown a provable advantage on synthetic data sets,
no work done to date has studied empirically whether the quantum advantage is attainable and with what
data. In this article, we report the first systematic investigation of empirical quantum advantage (EQA) in
healthcare and life sciences and propose an end-to-end framework to study EQA. We selected electronic
health records data subsets and created a configuration space of 5–20 features and 200–300 training samples.
For each configuration coordinate, we trained classical support vector machine models based on radial basis
function kernels and quantum models with custom kernels using an IBM quantum computer, making this
one of the largest quantum machine learning experiments to date. We empirically identified regimes where
quantum kernels could provide an advantage and introduced a terrain ruggedness index, a metric to help
quantitatively estimate how the accuracy of a given model will perform. The generalizable framework introduced here represents a key step toward a priori identification of data sets where quantum advantage could
exist.
INDEX TERMS: Artificial intelligence | digital health | electronic health records (EHR) | empirical quantum advantage (EQA) | machine learning | quantum kernels | real-world data | small data sets | support vector machines (SVM). |
مقاله انگلیسی |
9 |
یک اسکریپت Matlab برای آنالیز مورفومتریک رودخانهها، کانالها و درههای روی زمینی، زیرآبی و فرا زمینی
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 29 ویژگی های مورفومتریک نقش مهمی در طبقه بندی و مدل سازی سیستم های رودخانه ای دارند. تمرکز تحقیقات گذشته بر شباهت بین سیستمهای زیرآبی و فرازمینی ناشناخته و سیستمهای رودخانهای رو زمینی است، اما اکنون مطالعات جزئی و دقیق دره و کانال زیرآبی در دریاچهها، مخازن، اقیانوسها و سیستمهای فرازمینی افزایش یافته است. در این مطالعات، اغلب فقط چند ویژگی مورفومتریک (به عنوان مثال، شیب بستر، پهنای کرانه، شعاع خط مرکزی در نوک خم، عمق کرانه) در نظر گرفته می شد، که علت آن فقدان ابزاری کارآمد برای تعیین این ویژگیها بود. در این راستا، یک اسکریپت Matlab ساده برای تعیین مهمترین ویژگیهای مورفومتریک رودخانهها، کانالها و درههای رو زمینی، زیرآبی و فرازمینی ارائه شد. تنها ورودیهای مورد نیاز این اسکریپت ، خاکریز یا تاجهای کناره خاکریز است که تعریف خط مرکزی را بهعنوان مبنای سیستم مرجع خمیده خطی کانال محور امکانپذیر می کند و به محاسبه ویژگیهای پلانفرم (به عنوان مثال، عرض کامل، انحنای تدریجی متغیر، سینوسی) می پردازد. در صورتی که دادههای رقومی ارتفاع بیومتری یا توپوگرافی وجود داشته باشد و قابل تبدیل به سیستم مرجع خمیده خطی کانالمرکز باشند، بنابراین امکان تعیین شیب بستر طولی و ویژگیهای بیشتر مورفومتریک در سطح مقطع های عرضی (به عنوان مثال، عمق کرانه، سطح مقطع، و شیب های کناره ها یا سیلاب ها) فراهم می شود. این اسکریپت به عنوان مثال بر دره زیر آبی در دریاچه کنستانس اجرا شد. این اسکریپت ابزاری کارآمد برای آنالیز مقدار روزافزون مدلهای ارتفاعی دیجیتال (DEMs) در رودخانهها، کانالها و درههای رو زمینی، زیرآبی و فرازمینی است. این اسکریپت به ویژه برای سیستمهای زیر آبی که درک آن ها ضعیف است، مناسب بوده و به درک بزرگترین سیستمهای دره و کانال کمک میکند.
کلمات کلیدی: رانندگی خودکار | محلی سازی سطح لاین | تشخیص لاین | GNSS | GPS | تطبیق نقشه |
مقاله ترجمه شده |
10 |
Timing Constraints Imposed by Classical Digital Control Systems on Photonic Implementations of Measurement-Based Quantum Computing
محدودیت های زمانی اعمال شده توسط سیستم های کنترل دیجیتال کلاسیک بر پیاده سازی فوتونیک محاسبات کوانتومی مبتنی بر اندازه گیری-2022 Most of the architectural research on photonic implementations of measurement-based quantum computing (MBQC) has focused on the quantum resources involved in the problem with the implicit
assumption that these will provide the main constraints on system scaling. However, the “flying-qubit” architecture of photonic MBQC requires specific timing constraints that need to be met by the classical control
system. This classical control includes, for example, the amplification of the signals from single-photon
detectors to voltage levels compatible with digital systems; the implementation of a control system which
converts measurement outcomes into basis settings for measuring subsequent cluster qubits, in accordance
with the quantum algorithm being implemented; and the digital-to-analog converter and amplifier systems
required to set these measurement bases using a fast phase modulator. In this article, we analyze the digital
system needed to implement arbitrary one-qubit rotations and controlled-not gates in discrete-variable
photonic MBQC, in the presence of an ideal cluster state generator, with the main aim of understanding the
timing constraints imposed by the digital logic on the analog system and quantum hardware. We have verified
the design using functional simulations and have used static timing analysis of a Xilinx field-programmable
gate array (7 series) to provide a practical upper bound on the speed at which the adaptive measurement
processing can be performed, in turn constraining the photonic clock rate of the system. The design and
testing system is freely available for use as the basis of analysis of more complex designs, incorporating more
recent proposals for photonic quantum computing. Our work points to the importance of codesigning the
classical control system in tandem with the quantum system in order to meet the challenging specifications
of a photonic quantum computer.
INDEX TERMS: Field-programmable gate array (FPGA) | measurement and feed-forward | measurement based quantum computing (MBQC) | photonic quantum computing | timing analysis. |
مقاله انگلیسی |