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 |
Head tremor in cervical dystonia: Quantifying severity with computer vision
لرزش سر در دیستونی دهانه رحم: کمی کردن شدت با دید کامپیوتری-2022 Background: Head tremor (HT) is a common feature of cervical dystonia (CD), usually quantified by subjective
observation. Technological developments offer alternatives for measuring HT severity that are objective and
amenable to automation.
Objectives: Our objectives were to develop CMOR (Computational Motor Objective Rater; a computer vision-
based software system) to quantify oscillatory and directional aspects of HT from video recordings during a
clinical examination and to test its convergent validity with clinical rating scales.
Methods: For 93 participants with isolated CD and HT enrolled by the Dystonia Coalition, we analyzed video
recordings from an examination segment in which participants were instructed to let their head drift to its most
comfortable dystonic position. We evaluated peak power, frequency, and directional dominance, and used
Spearman’s correlation to measure the agreement between CMOR and clinical ratings.
Results: Power averaged 0.90 (SD 1.80) deg2/Hz, and peak frequency 1.95 (SD 0.94) Hz. The dominant HT axis
was pitch (antero/retrocollis) for 50%, roll (laterocollis) for 6%, and yaw (torticollis) for 44% of participants.
One-sided t-tests showed substantial contributions from the secondary (t = 18.17, p < 0.0001) and tertiary (t =
12.89, p < 0.0001) HT axes. CMOR’s HT severity measure positively correlated with the HT item on the Toronto
Western Spasmodic Torticollis Rating Scale-2 (Spearman’s rho = 0.54, p < 0.001).
Conclusions: We demonstrate a new objective method to measure HT severity that requires only conventional
video recordings, quantifies the complexities of HT in CD, and exhibits convergent validity with clinical severity
ratings. keywords: لرزش سر | ویدیو | بینایی کامپیوتر | درجه بندی شدت | TWSTRS | Head tremor | Video | Computer vision | Severity rating | TWSTRS |
مقاله انگلیسی |
2 |
Human perception of color differences using computer vision system measurements of raw pork loin
درک انسان از تفاوتهای رنگی با استفاده از اندازهگیریهای سیستم بینایی کامپیوتری گوشت خوک خام-2022 In the food industry, product color plays an important role in influencing consumer choices. Yet, there remains
little research on the human ability to perceive differences in product color; therefore, preference testing is
subjective rather than based on quantitative colors. Using a de-centralized computer-aided systematic discrim-
ination testing method, we ascertain consumers’ ability to discern between systematically varied colors. As a case
study, the colors represent the color variability of fresh pork as measured by a computer vision system. Our
results indicate that a total color difference (ΔE) of approximately 1 is discriminable by consumers. Furthermore,
we ascertain that a change in color along the b*-axis (yellowness) in CIELAB color space is most discernable,
followed by the a*-axis (redness) and then the L*-axis (lightness). As developed, our web-based discrimination
testing approach allows for large scale evaluation of human color perception, while these quantitative findings
on meat color discrimination are of value for future research on consumer preferences of meat color and beyond. keywords: تست تبعیض | تست مثلث | ترجیح رنگ | ظاهر غذا | رنگ گوشت | Discrimination testing | Triange test | Color preference | Food appearance | Meat color |
مقاله انگلیسی |
3 |
Performance analysis of machine learning algorithm of detection and classification of brain tumor using computer vision
تحلیل عملکرد الگوریتم یادگیری ماشین تشخیص و طبقه بندی تومور مغزی با استفاده از بینایی کامپیوتر-2022 Brain tumor is one of the undesirables, uncontrolled growth of cells in all age groups. Classification of tumors
depends no its origin and degree of its aggressiveness, it also helps the physician for proper diagnosis and
treatment plan. This research demonstrates the analysis of various state-of-art techniques in Machine Learning
such as Logistic, Multilayer Perceptron, Decision Tree, Naive Bayes classifier and Support Vector Machine for
classification of tumors as Benign and Malignant and the Discreet wavelet transform for feature extraction on the
synthetic data that is available data on the internet source OASIS and ADNI. The research also reveals that the
Logistic Regression and the Multilayer Perceptron gives the highest accuracy of 90%. It mimics the human
reasoning that learns, memorizes and is capable of reasoning and performing parallel computations. In future
many more AI techniques can be trained to classify the multimodal MRI Brain scan to more than two classes of
tumors. keywords: هوش مصنوعی | ام آر آی | رگرسیون لجستیک | پرسپترون چند لایه | Artificial Intelligence | MRI | Logistic regression | OASIS | Multilayer Perceptron |
مقاله انگلیسی |
4 |
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 |
5 |
Quantum Error Correction at the Threshold: If technologists dont get beyond it, quantum computers will never be big
تصحیح خطای کوانتومی در آستانه: اگر تکنولوژیست ها از آن فراتر نروند، کامپیوترهای کوانتومی هرگز بزرگ نخواهند شد-2022 Dates chIseleD into an
ancient tombstone have more
in common with the data in
your phone or laptop than you may
realize. They both involve conventional,
classical information, carried by hardware that is relatively immune to errors.
The situation inside a quantum computer
is far different: The information itself has
its own idiosyncratic properties, and
compared with standard digital
microelectronics, state-of-the-art
quantum-computer hardware is more
than a billion trillion times as likely to
suffer a fault. This tremendous susceptibility to errors is the single biggest problem holding back quantum computing
from realizing its great promise.
Fortunately, an approach known as
quantum error correction (QEC) can
remedy this problem, at least in principle. A mature body of theory built up
over the past quarter century now provides a solid theoretical foundation, and
experimentalists have demonstrated
dozens of proof-of-principle examples
of QEC. But these experiments still have
not reached the level of quality and
sophistication needed to reduce the
overall error rate in a system.
keywords: |
مقاله انگلیسی |
6 |
فعل و انفعالات فیکساسیون متقاطع جهت ها، پیشنهاد کدگشایی سطح بالا به پایین در حافظه کاری بصری
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 12 - تعداد صفحات فایل doc فارسی: 37 کدگذاری حسی (چگونگی برانگیختن پاسخ های حسی توسط محرک ها) به پیشرفت از ویژگی های سطح پایین به سطح بالا معروف است. کمتر به فهم و درک کدگشایی (چگونه پاسخ ها منجر به ادراک می شوند) پرداخته شده است اما اغلب فرض می شود که از سلسله مراتب مشابهی پیروی می کند. بر این اساس، کدگشایی جهت باید در مناطق سطح پایین مانند V1، بدون فعل و انفعالات فیکساسیون متقابل رخ دهد. با این حال، در مطالعه ی Ding, Cueva, Tsodyks, and Qian (2017) شواهدی برخلاف این فرض ارائه شد و آنها پیشنهاد کردند که کدگشایی بصری اغلب از سلسله مراتبی از سطح بالا به سطح پایین در حافظه کاری پیروی می کند، که در آن محدودیتهای سطح از بالاتر به پایینتر ، تعامل بین ویژگیهای سطح پایینتر را معرفی میکنند. دو جهت در سویه مخالف فیکساسیون، هم مربوط به کار هستند و هم حافظه کاری می و باید با یکدیگر تعامل داشته باشند. در واقع فعل و انفعالات فیکساسیون متقابل پیش بینی شده (دفعه و همبستگی) بین جهت ها را پیدا کرده. کارآزماییها و تجزیه و تحلیلهای کنترلی، توضیحات جایگزین مانند گزارش سوگیری و انطباق در سراسر کارآزماییها را در جهت مشابه فیکساسیون، رد کردند. علاوه بر این، دادهها را با استفاده از چارچوب کدگشایی بیزی سطح بالا به پایین گذشتهنگر شرح دادیم.
کلیدواژه ها: کدگشایی بصری | سوگیری ادراکی | نویز حافظه | گذشته نگر بیزی |
مقاله ترجمه شده |
7 |
LoRaWAN-Based IoT System Implementation for Long-Range Outdoor Air Quality Monitoring
پیاده سازی سیستم اینترنت اشیاء مبتنی بر LoRaWAN برای نظارت بر کیفیت هوای خارج از منزل در محدوده بلند-2022 This study proposes a smart long-range (LoRa) sensing node to timely collect the air quality in-
formation and update it on the cloud. The developed long-range wide area network (LoRaWAN)-
based Internet of Things (IoT) air quality monitoring system (AQMS), hereafter called LoRaWAN-
IoT-AQMS, was deployed in an outdoor environment to validate its reliability and effectiveness.
The system is composed of multiple sensors (NO2, SO2, CO2, CO, PM2.5, temperature, and hu-
midity), Arduino microcontroller, LoRa shield, LoRaWAN gateway, and The Thing Network
(TTN) IoT platform. The LoRaWAN-IoT-AQMS is a standalone system powered continuously by a
rechargeable battery with a photovoltaic solar panel via a solar charger shield for sustainable
operation. Our system simultaneously gathers the considered air quality information by using the
smart sensing unit. Then, the system transmits the information through the gateway to the TTN
platform, which is integrated with the ThingSpeak IoT server. This action updates the collected
data and displays these data on a developed Web-based dashboard and a Graphical User Interface
(GUI) that uses the Virtuino mobile application. Thus, the displayed information can be easily
accessed by users via their smartphones. The results obtained by the developed LoRaWAN-IoT-
AQMS are validated by comparing them with experimental results based on the high-
technology Aeroqual air quality monitoring devices. Our system can reliably monitor various
air quality indicators and efficiently transmit the information in real time over the Internet. keywords: پایش کیفیت هوا | Air quality monitoring | Iot lora lorawan | TTN ThingSpeak Virtuino |
مقاله انگلیسی |
8 |
The applications of Internet of Things in the automotive industry: A review of the batteries, fuel cells, and engines
کاربردهای اینترنت اشیا در صنعت خودرو: مروری بر باتری ها، سلول های سوختی و موتورها-2022 The current advances in the integration of devices through the internet of things (IoT) have
encouraged researchers to focus on the applications of IoT in the automotive industry. Although
different achievements in the in-vehicle network analysis and traffic management have been
already reviewed, a comprehensive study to bring together the main applications of the IoT in the
automotive industry is required. Internal combustion engines (ICEs) are established as the most
common prime-mover for cars, however, with the depleting fossil-fuel resources, the interest in
the usage of fuel cells and batteries has increased. In this regard, the main goal of the current
study is to evaluate the application of IoT in batteries, fuel cells, and ICEs. This paper is also
centralized on different types of IoT applications and combines them with empirical articles such
as Random Location Detection, Vehicle Theft Prevention, Observation of vehicle performance,
and industrial management of vehicles. As an output of this comprehensive review, different
usages of the IoT in the automotive sector will be clarified. Also, this article can be considered as a
basis for advancing the recent implementation of the IoT in the fuel cell, battery, and ICE
domains.
keywords: اینترنت اشیا (IoT) | باتری | سلول سوختی | موتور احتراق داخلی (ICE) | Internet of Things (IoT) | Battery | Fuel cell | Internal combustion engine (ICE) |
مقاله انگلیسی |
9 |
A solution for water management and leakage detection problems using IoTs based approach
راه حلی برای مشکلات مدیریت آب و تشخیص نشت با استفاده از رویکرد مبتنی بر اینترنت اشیا-2022 Water management, distribution, and consumption are not visualized in real time in conventional
systems; this delays the leakage detection process. Nowadays, an increase in the development of
smart water- meter trials and demand management requires higher spatial and temporal de-
cisions. This paper proposes a solution for the water management and distribution problem. The
solution is based on the IoT technology. First, a prototype abstracting the water distribution
network (WDN) is developed. Second, sensors are installed on the network to capture the targeted
physical quantities such as water pH level, turbidity, and flow rates. Third, sensor network is
established to send the readings to Firebase platform. Fourth, an IoT testbed architecture is
proposed to comprehensively interface all the IoT modules. Leakage detection scenarios are
conducted to sense and warn admins and users to fix it. Application of the proposed system to
smart homes would enable monitoring of water quality, measurement of consumption, and
detection of leakage. Moreover, it provides an awareness highlight to users about consumption,
and a monitoring platform for both users and admins for leakage detection. keywords: اینترنت اشیا | مدیریت آب | تشخیص نشتی | IOT | Water management | Leakage detection |
مقاله انگلیسی |
10 |
A survey on security in internet of things with a focus on the impact of emerging technologies
بررسی امنیت در اینترنت اشیا با تمرکز بر تاثیر فناوری های نوظهور-2022 Internet of Things (IoT) have opened the door to a world of unlimited possibilities for imple-
mentations in varied sectors in society, but it also has many challenges. One of those challenges is
security and privacy. IoT devices are more susceptible to security threats and attacks. Due to
constraints of the IoT devices such as area, power, memory, etc., there is a lack of security so-
lutions that are compatible with IoT devices and applications, which is leading this world of
securely connected things to the “internet of insecure things.” A promising solution to this
problem is going beyond the standard or classical techniques to implementing the security so-
lutions in the hardware of the IoT device. The integration of emerging technologies in IoT net-
works, such as machine learning, blockchain, fog/edge/cloud computing, and quantum
computing have added more vulnerable points in the network. This paper introduces a
comprehensive study on IoT security threats and solutions. Additionally, this survey outlines how
emerging technologies such as machine learning and blockchain are integrated in IoT, challenges
resulted from this integration, and potential solutions to these challenges. The paper utilizes the
4-layer IoT architecture as a reference to identify security issues with corresponding solutions. keywords: اینترنت اشیا | امنیت | فراگیری ماشین | بلاک چین | تهدیدها | راه حل های امنیتی | IoT | Security | Machine learning | Blockchain | Threats | Security solutions |
مقاله انگلیسی |