با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
ردیف | عنوان | نوع |
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71 |
Graph Kernels Encoding Features of All Subgraphs by Quantum Superposition
ویژگی های رمزگزاری هسته های گراف زیرگراف ها با برهم نهی کوانتومی-2022 Graph kernels are often used in bioinformatics and
network applications to measure the similarity between graphs;
therefore, they may be used to construct efficient graph classifiers.
Many graph kernels have been developed thus far, but to the
best of our knowledge there is no existing graph kernel that
uses some features explicitly extracted from all subgraphs to
measure similarity. We propose a novel graph kernel that applies
a quantum computer to measure the similarity obtained from all
subgraphs by fully exploiting the power of quantum superposition
to encode every subgraph into a feature of particular form. For
the construction of the quantum kernel, we develop an efficient
protocol that clears the index information of the subgraphs
encoded in the quantum state. We also prove that the quantum
computer requires less query complexity to construct the feature
vector than the classical sampler used to approximate the same
vector. A detailed numerical simulation of a bioinformatics
problem is presented to demonstrate that, in many cases, the
proposed quantum kernel achieves better classification accuracy
than existing graph kernels.
Index Terms: Quantum computing | machine learning | bioinfomatics. |
مقاله انگلیسی |
72 |
Pork primal cuts recognition method via computer vision
روش تشخیص برش های اولیه گوشت خوک از طریق بینایی کامپیوتری-2022 Pork accounts for more than 33% of global meat consumption and dominates meat consumption in China. With
the improvement of peoples quality of life, people pay more and more attention to the quality of pork. There are
many factors that affect the quality of pork, and the cutting position of pork is also one of them. The quality of
different pork primal cuts varies greatly. Aiming at the difficulty of distinguishing pork primal cuts, this study
proposes a computer vision-based method to identify different pork primal cuts, using images of four different
pork primal cuts (ham, loin, belly, and neck) as the experimental data, the results show that the method proposed
in this paper can identify the original cuts of pork well. It also proves that computer vision technology has the
potential to help people identify pork cuts. keywords: برش های اولیه گوشت خوک | شناسایی برش گوشت خوک | بینایی کامپیوتر | تشخیص برش های اولیه | Pork primal cuts | Identifying pork cut | Computer vision | Primal cuts recognition |
مقاله انگلیسی |
73 |
Grover on KATAN: Quantum Resource Estimation
گروور در کاتان: برآورد منابع کوانتومی-2022 This article presents the cost analysis of mounting Grover’s key search attack on the family of
KATAN block cipher. Several designs of the reversible quantum circuit of KATAN are proposed. Owing
to the National Insitute of Standards and Technology’s (NIST) proposal for postquantum cryptography
standardization, the circuits are designed focusing on minimizing the overall depth. We observe that the
reversible quantum circuits designed using and gates and T-depth one Toffoli gate give more shallow
circuits. Grover oracle for KATAN is designed based on the reversible circuits, which are used further to
mount Grover’s key search attack on KATAN. The designs are implemented using the software framework
ProjectQ, which provides a resource estimation tool to perform an appropriate cost analysis in an automated
way. While estimating the resources, NIST’s depth restrictions are also respected.
INDEX TERMS: Grover’s algorithm | KATAN | postquantum cryptography (PQC) | ProjectQ implementation | quantum cryptanalysis. |
مقاله انگلیسی |
74 |
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 |
75 |
Guesswork of a Quantum Ensemble
حدس و گمان یک گروه کوانتومی-2022 The guesswork of a quantum ensemble quantifies
the minimum number of guesses needed in average to correctly
guess the state of the ensemble, when only one state can be
queried at a time. Here, we derive analytical solutions of the
guesswork problem subject to a finite set of conditions, including
the analytical solution for any qubit ensemble with uniform
probability distribution. As explicit examples, we compute the
guesswork for any qubit regular polygonal and polyhedral
ensemble.
Index Terms: Guesswork | quantum states | quantum measurements | quantum state discrimination. |
مقاله انگلیسی |
76 |
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 |
77 |
Hash Function Based on Controlled Alternate Quantum Walks With Memory (September 2021)
عملکرد هش بر اساس راه رفتن کوانتومی جایگزین کنترل شده با حافظه (سپتامبر 2021)-2022 We propose a Quantum inspired Hash Function using controlled alternate quantum walks with
Memory on cycles (QHFM), where the jth message bit decides whether to run quantum walk with one-step
memory or to run quantum walk with two-step memory at the jth time step, and the hash value is calculated
from the resulting probability distribution of the walker. Numerical simulation shows that the proposed hash
function has near-ideal statistical performance and is at least on a par with the state-of-the-art hash functions
based on quantum walks in terms of sensitivity of hash value to message, diffusion and confusion properties,
uniform distribution property, and collision resistance property; and theoretical analysis indicates that the
time and space complexity of the new scheme are not greater than those of its peers. The good performance
of QHFM suggests that quantum walks that differ not only in coin operators but also in memory lengths can
be combined to build good hash functions, which, in turn, enriches the construction of controlled alternate
quantum walks.
INDEX TERMS: Controlled alternate quantum walks (CAQW) | hash function | quantum walks with memory (QWM) | statistical properties | time and space complexity. |
مقاله انگلیسی |
78 |
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 |
79 |
High-Performance Reservoir Computing With Fluctuations in Linear Networks
محاسبات مخزن با کارایی بالا با نوسانات در شبکه های خطی-2022 Reservoir computing has emerged as a powerful
machine learning paradigm for harvesting nontrivial information
processing out of disordered physical systems driven by sequential inputs. To this end, the system observables must become
nonlinear functions of the input history. We show that encoding
the input to quantum or classical fluctuations of a network of
interacting harmonic oscillators can lead to a high performance
comparable to that of a standard echo state network in several
nonlinear benchmark tasks. This equivalence in performance
holds even with a linear Hamiltonian and a readout linear in the
system observables. Furthermore, we find that the performance of
the network of harmonic oscillators in nonlinear tasks is robust to
errors both in input and reservoir observables caused by external
noise. For any reservoir computing system with a linear readout,
the magnitude of trained weights can either amplify or suppress
noise added to reservoir observables. We use this general result to
explain why the oscillators are robust to noise and why having
precise control over reservoir memory is important for noise
robustness in general. Our results pave the way toward reservoir
computing harnessing fluctuations in disordered linear systems.
Index Terms: Dynamical systems | machine learning | quantum mechanics | recurrent neural networks | reservoir computing | supervised learning. |
مقاله انگلیسی |
80 |
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 |