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).
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1 |
On the Logical Error Rate of Sparse Quantum Codes
در مورد میزان خطای منطقی کدهای کوانتومی پراکنده-2022 The quantum paradigm presents a phenomenon known as degeneracy that can potentially
improve the performance of quantum error correcting codes. However, the effects of this mechanism are
sometimes ignored when evaluating the performance of sparse quantum codes and the logical error rate is
not always correctly reported. In this article, we discuss previously existing methods to compute the logical
error rate and we present an efficient coset-based method inspired by classical coding strategies to estimate
degenerate errors and distinguish them from logical errors. Additionally, we show that the proposed method
presents a computational advantage for the family of Calderbank–Shor–Steane codes. We use this method
to prove that degenerate errors are frequent in a specific family of sparse quantum codes, which stresses
the importance of accurately reporting their performance. Our results also reveal that the modified decoding
strategies proposed in the literature are an important tool to improve the performance of sparse quantum
codes.
INDEX TERMS: Iterative decoding | quantum error correction (QEC) | quantum low density generator matrix codes | quantum low-density parity check (QLDPC) codes. |
مقاله انگلیسی |
2 |
برهم کنش متقابل جهت گیری ها نشاندهنده رمز گشایی سطح بالا به پایین در حافظه کار بصری است
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 12 - تعداد صفحات فایل doc فارسی: 41 کدگذاری حسی ( چگونه محرکها واکنشهای حسی را برمیانگیزد ) به پیشرفت از ویژگیهای سطح پایین به سطح بالا مشهور است .
رمزگشایی ( چگونه پاسخها منجر به ادراک میشود ) کمتر درک میشود اما اغلب فرض میشود که از همان سلسلهمراتب پیروی میکند .
بر این اساس ، رمز گشایی جهت گیری باید در نواحی سطح پایین مانند V۱ ، بدون برهم کنش متقابل رخ دهد .
با این حال , یک مطالعه , دینگ ,کوا , تی سودیکس , و کان ( 2017 ) شواهدی در برابر این فرض ارائه دادند و پیشنهاد کردند که رمزگشایی بصری اغلب ممکن است از سلسلهمراتب سطح بالا به پایین در حافظه کاری پیروی کند , که در آن محدودیتهای سطح به پایین تعامل بین ویژگیهای سطح پایینتر را ایجاد میکند . اگر دو جهت گیری در جهت مخالف تثبیت هر دو عملی هستند و حافظه فعال را وارد میکنند , پس باید با هم تعامل داشته باشند. ما در واقع هم برهم کنش متقابل پیشبینیشده ( تنفر و همبستگی ) بین جهت گیری ها را پیدا کردیم .
آزمایشها کنترل و تجزیه و تحلیلهای کنترلی , توضیحات دیگری همچون تعصب گزارش دهی و انطباق در سراسر آزمایشها در همان سمت تثبیت را رد کردند . به علاوه , ما دادهها را با استفاده از چارچوب رمزگشایی Bayesian سطح پایین به سطح پایین توضیح دادیم .
واژه های کاربردی: کدگشایی بصری | جانبداری | سر و صدا | بیزین گذشته نگر |
مقاله ترجمه شده |
3 |
Toward a Union-Find Decoder for Quantum LDPC Codes
به سمت رمزگشای Union-Find برای کدهای LDPC کوانتومی-2022 Quantum LDPC codes are a promising direction
for low overhead quantum computing. In this paper, we propose
a generalization of the Union-Find decoder as a decoder for
quantum LDPC codes. We prove that this decoder corrects all
errors with weight up to Anα for some A, α > 0, where
n is the code length, for different classes of quantum LDPC
codes such as toric codes and hyperbolic codes in any dimension
D ≥ 3 and quantum expander codes. To prove this result,
we introduce a notion of covering radius which measures the
spread of an error from its syndrome. We believe this notion
could find application beyond the decoding problem. We also
perform numerical simulations, which show that our Union-Find
decoder outperforms the belief propagation decoder in the low
error rate regime in the case of a quantum LDPC code with
length 3600.
keywords: Quantum computing | error correction | decoding. |
مقاله انگلیسی |
4 |
Corporate accounting information disclosure based on FPGA and neural network
افشای اطلاعات حسابداری شرکت بر اساس FPGA و شبکه عصبی-2021 Corporate accounting information is a measure of the company’s accounting and external reporting systems. It is
routinely disclosed, which is quantitative data on its financial position and performance audit. The corporate
accounting information system contains confidential information that needs to be secured. The consequences of
unauthorized access are data loss from identity theft issues. To solve the problem, encrypt and decrypt the
sensitive corporate accounting information and product the data using the proposed algorithm Neural Network
(NN) and Field Programmable Gate Array (FPGA) is used to classify the corporate accounting information
authorized person and unauthorized person. When one authorized user accesses the corporate account infor-
mation, it generates the secret critical process. The proposed algorithm unauthorized person cannot access the
information is not allowed for stealing. Encryption is the process of converting to something as random and
meaningless as direct text data. Decryption is the process of restoring the ciphertext plaintext. keywords: اطلاعات حسابداری شرکت | شبکه عصبی (NN) | fpga | فرد مجاز | شخص غیر مجاز | رمزگذاری | رمزگشایی | Corporate accounting information | Neural network (NN) | FPGA | Authorized person | Unauthorized person | Encryption | Decryption |
مقاله انگلیسی |
5 |
A Tokenless Cancellable Scheme for Multimodal Biometric Systems
طرح غیر قابل لغو برای سیستم های بیومتریک چند حالته-2021 Biometric template protection (BTP) is an open problem for biometric identity management systems. Cancellable biometrics is commonly designed to protect biometric templates with two input factors i.e., biometrics and a token used in template replacement. However, the token is often required to be kept secretly; otherwise, the protected template could be vulnerable to several security attacks and breaches of privacy. In this paper, we propose a tokenless cancellable biometrics scheme called Multimodal Extended Feature Vector (M•EFV) Hashing that employs an improved XOR encryption/decryption notion to operate on the transformation key. We stress on multimodal biometrics where the real-valued face and fingerprint vectors are fused and embedded into a binarized cancellable template. Specifically, M•EFV hashing consists of three stages of transformation: 1) normalization and bio- metric fusion; 2) randomization and binarization; and 3) cancellable template generation. To evaluate the proposed scheme, several benchmarking datasets, i.e., FVC2002, FVC2004 for fingerprint and LFW for face are used in experiments. The verification performance is vali- dated by employing the FVC matching protocol. Various attacks are simulated and analysed in the worst-case scenario. Lastly, unlinkability and revocability properties are examined experimentally.© 2021 Elsevier Ltd. All rights reserved. Keywords: Feature-level Fusion | Multimodal Biometrics | Tokenless Cancellable Biometrics | Privacy and security | XOR encryption/decryption |
مقاله انگلیسی |
6 |
A knowledge-based Digital Shadow for machining industry in a Digital Twin perspective
یک سایه دیجیتال مبتنی بر دانش برای صنعت ماشینکاری در یک چشم انداز دیجیتال دوتایی-2021 This paper addresses the problems of data management and analytics for decision-aid by proposing a new vision
of Digital Shadow (DS) which would be considered as the core component of a future Digital Twin. Knowledge
generated by experts and artificial intelligence, is transformed into formal business rules and integrated into the
DS to enable the characterization of the real behavior of the physical system throughout its operation stage. This
behavior model is continuously enriched by direct or derived learning, in order to improve the digital twin. The
proposed DS relies on data analytics (based on unsupervised learning) and on a knowledge inference engine. It
enables the incidents to be detected and it is also able to decipher its operational context. An example of this
application in the aeronautic machining industry is provided to stress both the feasibility of the proposition and
its potential impact on shop floor performance. keywords: سایه دیجیتال | دوقلو | داده ها و مدیریت دانش | ماشینکاری | Digital shadow | Digital twin | Data and knowledge management | Machining |
مقاله انگلیسی |
7 |
Quantum recurrent encoder–decoder neural network for performance trend prediction of rotating machinery
شبکه عصبی رمزگذار- رمزگذار مکرر کوانتومی برای پیش بینی روند عملکرد ماشین های چرخشی-2020 Traditional neural networks generally neglect the primary and secondary relationships of input information
and process the information indiscriminately, which leads to their bad nonlinear approximation
capacity and low generalization ability. As a result, traditional neural networks always show poor
prediction accuracy in the performance degradation trend prediction of rotating machinery (RM).
In view of this, a novel neural network called quantum recurrent encoder–decoder neural network
(QREDNN) is proposed in this paper. In QREDNN, the attention mechanism is used to simultaneously
reconstruct encoder and decoder of QREDNN, so that QREDNN can fully excavate and pay attention
to important information but suppress the interference of redundant information to obtain better
nonlinear approximation capacity. On the other hand, the quantum neuron is used to construct a
new quantum gated recurrent unit (QGRU) in which activation values and weights are represented
by quantum rotation matrices. The QGRU can traverse the solution space more finely and has a lot
of multiple attractors, so it can replace the traditional recurrent unit of the encoder and decoder
and enhance the generalization ability and response speed of QREDNN. Moreover, the Levenberg–
Marquardt (LM) algorithm is introduced to improve the update speeds of the rotation angles of
quantum rotation matrices and the attention parameters of QREDNN. Based on the superiorities of
QREDNN, a new performance trend prediction method for RM is proposed, in which the denoised
fuzzy entropy (DFE) of vibration acceleration signal of RM is input into QREDNN as the performance
degradation feature for predicting the performance degradation trend of RM. The examples of
predicting the performance trend of rolling bearings demonstrate the effectiveness of our proposed
method. Keywords: Quantum recurrent encoder–decoder | neural network (QREDNN) | Artificial intelligence | Attention mechanism | Quantum neuron | Performance trend prediction | Rotating machinery |
مقاله انگلیسی |
8 |
Deciphering the recreational use of urban parks: Experiments using multi-source big data for all Chinese cities
رمزگشایی استفاده تفریحی از پارک های شهری: آزمایش هایی با استفاده از داده های بزرگ چند منبع برای همه شهرهای چین-2020 China’s rapid urbanization process has accentuated the disparity between the demand for and supply of
its park recreational services. Estimations of park use and an understanding of the factors that influence it
are critical for increasing these services. However, the data traditionally used to quantify park use are
often subjective as well as costly and laborious to procure. This paper assessed the use of parks through
an analysis of check-in data obtained from the Weibo social media platform for 13,759 parks located in all
287 cities at prefecture level and above across China. We investigated how park attributes, accessibility,
and the socioeconomic environment affected the number and density of park check-ins. We used multiple
linear regression models to analyze the factors influencing check-ins for park visits. The results
showed that in all the cities, the influence of external factors on the number and density of check-in visits,
notably the densities of points of interest (POIs) and bus stops around the parks was significantly positive,
with the density of POIs being the most influential factor. Conversely, park attributes, which included the
park service area and the landscape shape index (LSI), negatively influenced park use. The density of POIs
and bus stops located around the park positively influenced the density of the recreational use of urban
parks in cities within all administrative tiers, whereas the impact of park service areas was negative in all
of them. Finally, the factors with the greatest influence varied according to the administrative tiers of the
cities. These findings provide valuable inputs for increasing the efficiency of park use and improving
recreational services according to the characteristics of different cities. Keywords: Weibo check-ins | Park attributes | Regression models | Park usage | China |
مقاله انگلیسی |
9 |
Decoding earth’s plate tectonic history using sparse geochemical data
رمزگشایی تاریخ زمین ساختی صفحه با استفاده از داده های نادر ژئوشیمیایی-2020 Accurately mapping plate boundary types and locations through time is essential for understanding the
evolution of the plate-mantle system and the exchange of material between the solid Earth and surface
environments. However, the complexity of the Earth system and the cryptic nature of the geological
record make it difficult to discriminate tectonic environments through deep time. Here we present a new
method for identifying tectonic paleo-environments on Earth through a data mining approach using
global geochemical data. We first fingerprint a variety of present-day tectonic environments utilising up
to 136 geochemical data attributes in any available combination. A total of 38301 geochemical analyses
from basalts aged from 5e0 Ma together with a well-established plate reconstruction model are used to
construct a suite of discriminatory models for the first order tectonic environments of subduction and
mid-ocean ridge as distinct from intraplate hotspot oceanic environments, identifying 41, 35, and 39 key
discriminatory geochemical attributes, respectively. After training and validation, our model is applied to
a global geochemical database of 1547 basalt samples of unknown tectonic origin aged between 1000
e410 Ma, a relatively ill-constrained period of Earth’s evolution following the breakup of the Rodinia
supercontinent, producing 56 unique global tectonic environment predictions throughout the Neoproterozoic
and Early Paleozoic. Predictions are used to discriminate between three alternative published
Rodinia configuration models, identifying the model demonstrating the closest spatio-temporal consistency
with the basalt record, and emphasizing the importance of integrating geochemical data into
plate reconstructions. Our approach offers an extensible framework for constructing full-plate, deeptime
reconstructions capable of assimilating a broad range of geochemical and geological observations,
enabling next generation Earth system models.. Keywords: Plate tectonics | Geochemistry | Geodynamics | Supercontinents | Rodinia | Big data |
مقاله انگلیسی |
10 |
A network view on brain regions involved in experts’ object and pattern recognition: Implications for the neural mechanisms of skilled visual perception
نمای شبکه در مورد مناطق مغز درگیر در تشخیص موضوع و الگوی متخصصان: پیامدهای مکانیسم های عصبی درک بصری ماهر-2019 Skilled visual object and pattern recognition form the basis of many everyday behaviours. The game of chess has
often been used as a model case for studying how long-term experience aides in perceiving objects and their
spatio-functional interrelations. Earlier research revealed two brain regions, posterior middle temporal gyrus
(pMTG) and collateral sulcus (CoS), to be linked to chess experts’ superior object and pattern recognition, respectively.
Here we elucidated the brain networks these two expertise-related regions are embedded in, employing
resting-state functional connectivity analysis and meta-analytic connectivity modelling with the
BrainMap database. pMTG was preferentially connected with dorsal visual stream areas and a parieto-prefrontal
network for action planning, while CoS was preferentially connected with posterior medial cortex and hippocampus,
linked to scene perception, perspective-taking and navigation. Functional profiling using BrainMap
meta-data revealed that pMTG was linked to semantic processing as well as inhibition and attention, while CoS
was linked to face and shape perception as well as passive viewing. Our findings suggest that pMTG subserves
skilled object recognition by mediating the link between object identity and object affordances, while CoS
subserves skilled pattern recognition by linking the position of individual objects with typical spatio-functional
layouts of their environment stored in memory. Keywords: Skilled perception | Chess expertise | Functional connectivity | Resting-state fMRI | MACM | Functional decoding |
مقاله انگلیسی |