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1 |
Intelligent authentication of 5G healthcare devices: A survey
احراز هویت هوشمند دستگاه های مراقبت بهداشتی 5G: یک مرور-2022 The dynamic nature of wireless links and the mobility of devices connected to the Internet of
Things (IoT) over fifth-generation (5G) networks (IoT-5G), on the one hand, empowers pervasive
healthcare applications. On the other hand, it allows eavesdroppers and other illegitimate
actors to access secret information. Due to the poor time efficiency and high computational
complexity of conventional cryptographic methods and the heterogeneous technologies used,
it is easy to compromise the authentication of lightweight wearable and healthcare devices.
Therefore, intelligent authentication, which relies on artificial intelligence (AI), and sufficient
network resources are extremely important for securing healthcare devices connected to IoT-
5G. This survey considers intelligent authentication and includes a comprehensive overview of
intelligent authentication mechanisms for securing IoT-5G devices deployed in the healthcare
domain. First, it presents a detailed, thoughtful, and state-of-the-art review of IoT-5G, healthcare
technologies, tools, applications, research trends, challenges, opportunities, and solutions. We
selected 20 technical articles from those surveyed based on their strong overlaps with IoT,
5G, healthcare, device authentication, and AI. Second, IoT-5G device authentication, radiofrequency fingerprinting, and mutual authentication are reviewed, characterized, clustered,
and classified. Third, the review envisions that AI can be used to integrate the attributes
of the physical layer and 5G networks to empower intelligent healthcare devices. Moreover,
methods for developing intelligent authentication models using AI are presented. Finally, the
future outlook and recommendations are introduced for IoT-5G healthcare applications, and
recommendations for further research are presented as well. The remarkable contributions and
relevance of this survey may assist the research community in understanding the research gaps
and the research opportunities relating to the intelligent authentication of IoT-5G healthcare
devices.
keywords: اینترنت اشیا (IoT) | امنیت اینترنت اشیا | احراز هویت دستگاه | هوش مصنوعی | امنیت مراقبت های بهداشتی | شبکه های 5g | InternetofThings(IoT) | InternetofThingssecurity | Deviceauthentication | Artificialintelligence | Healthcaresecurity | 5Gnetworks |
مقاله انگلیسی |
2 |
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 |
3 |
Computer vision for anatomical analysis of equipment in civil infrastructure projects: Theorizing the development of regression-based deep neural networks
چشم انداز کامپیوتری برای تجزیه و تحلیل آناتومیکی تجهیزات در پروژه های زیرساختی عمرانی: نظریه پردازی توسعه شبکه های عصبی عمیق مبتنی بر رگرسیون-2022 There is high demand for heavy equipment in civil infrastructure projects and their performance is a determinant
of the successful delivery of site operations. Although manufacturers provide equipment performance hand-
books, additional monitoring mechanisms are required to depart from measuring performance on the sole basis
of unit cost for moved materials. Vision-based tracking and pose estimation can facilitate site performance
monitoring. This research develops several regression-based deep neural networks (DNNs) to monitor equipment
with the aim of ensuring safety, productivity, sustainability and quality of equipment operations. Annotated
image libraries are used to train and test several backbone architectures. Experimental results reveal the pre-
cision of DNNs with depthwise separable convolutions and computational efficiency of DNNs with channel
shuffle. This research provides scientific utility by developing a method for equipment pose estimation with the
ability to detect anatomical angles and critical keypoints. The practical utility of this study is the provision of
potentials to influence current practice of articulated machinery monitoring in projects. keywords: هوش مصنوعی (AI) | سیستم های فیزیکی سایبری | معیارهای ارزیابی خطا | طراحی و آزمایش تجربی | تخمین ژست کامل بدن | صنعت و ساخت 4.0 | الگوریتم های یادگیری ماشین | معماری های ستون فقرات شبکه | Artificial intelligence (AI) | Cyber physical systems | Error evaluation metrics | Experimental design and testing | Full body pose estimation | Industry and construction 4.0 | Machine learning algorithms | Network backbone architectures |
مقاله انگلیسی |
4 |
تکنیک ها و کاربردهای توالی یابی RNA تک سلولی در تحقیقات تکوین تخمدان و بیماری های مرتبط
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 23 تخمدان یک ارگان بسیار سازمان یافته متشکل از سلول های زایا و انواع مختلف سلول های سوماتیک است که ارتباطات آنها منجر به تکوین تخمدان و تولید تخمک های عملکردی می شود. تفاوت بین سلول های منفرد ممکن است اثرات عمیقی بر عملکرد تخمدان داشته باشد. تکنیکهای توالییابی RNA تک سلولی، رویکردهای امیدوارکنندهای برای کشف ترکیب انواع سلولی ارگانیسم ها، پویایی رونوشتها یا ترنسکریپتوم، شبکه تنظیمکننده بین ژنها و مسیرهای سیگنالدهی بین انواع سلولها در وضوح تک سلولی هستند. در این مطالعه، ما یک مرور کلی از تکنیکهای توالییابی RNA تک سلولی موجود از جمله Smart-seq2 و Drop-seq و همچنین کاربردهای آنها در تحقیقات بیولوژیکی و بالینی ارائه میکنیم تا درک بهتری از مکانیسمهای مولکولی زیربنای تکوین تخمدان و بیماری های مرتبط با آن ارائه کنیم.
کلیدواژگان: تکوین تخمدانن | توالی یابی RNA تک سلولی | شبکه تنظیمی | بیماری ها |
مقاله ترجمه شده |
5 |
Quantum computing in power systems
محاسبات کوانتومی در سیستم های قدرت-2022 Electric power systems provide the backbone of modern industrial societies. Enabling scalable grid analytics is the keystone to
successfully operating large transmission and distribution systems. However, today’ s power systems are suffering from everincreasing computational burdens in sustaining the expanding communities and deep integration of renewable energy resources,
as well as managing huge volumes of data accordingly. These unprecedented challenges call for transformative analytics to support
the resilient operations of power systems. Recently, the explosive growth of quantum computing techniques has ignited new hopes
of revolutionizing power system computations. Quantum computing harnesses quantum mechanisms to solve traditionally
intractable computational problems, which may lead to ultra-scalable and efficient power grid analytics. This paper reviews the
newly emerging application of quantum computing techniques in power systems. We present a comprehensive overview of existing
quantum-engineered power analytics from different operation perspectives, including static analysis, transient analysis, stochastic
analysis, optimization, stability, and control. We thoroughly discuss the related quantum algorithms, their benefits and limitations,
hardware implementations, and recommended practices. We also review the quantum networking techniques to ensure secure
communication of power systems in the quantum era. Finally, we discuss challenges and future research directions. This paper will
hopefully stimulate increasing attention to the development of quantum-engineered smart grids.
keywords: Quantum computing | power system | variational quantum algorithms | quantum optimization | quantum machine learning | quantum security. |
مقاله انگلیسی |
6 |
Secure firmware Over-The-Air updates for IoT: Survey, challenges, and discussions
به روز رسانی ایمن میان افزار خارج از هوا برای اینترنت اشیا: بررسی، چالش ها و بحث ها-2022 The Internet of Things (IoT) market has shown strong growth in recent years, where many
manufacturers of IoT devices and IoT-related service providers are competing. Time to market
has become essential to be competitive. The faster a competitor develops and integrates his
product, the more likely he is to dominate the market. This competition could lead to critical
security issues due to the lack of testing or the short development time. Moreover, lots of
IoT devices present some vulnerabilities that can be exploited by attackers. They are also
constantly subject to Zero-days, which require quick intervention to maintain the security of
the environments in which they are deployed in. For these purposes, the quick update of the
firmware image of these IoT devices is an effective way to counter most of these attacks. This
document starts by defining the firmware update mechanisms for IoT, and in particular the ones
done Over-The-Air. Then presents a state-of-the-art of the currently proposed solutions, with the
particularity of surveying from the literature, the standardization bodies and from some well known industrial solutions. It also proposes a new classification of the different types of System
on Chip (SoC) present in the marketed IoT devices together with an analysis of the different
challenges and threats related to the OTA update. The objective is to open up the horizon for
future research directions.
keywords: دستگاه های اینترنت اشیا | نرم افزار | به روز رسانی | خارج از هوا | امنیت | حریم خصوصی | بررسی | مرور | چالش ها | تهدیدات | زنجیره اعتماد | IoT devices | Firmware | Updates | Over-The-Air | Security | Privacy | State of the art | Survey | Challenges | Threats | Trust chain |
مقاله انگلیسی |
7 |
Ultrasonic physical layers as building blocks of IoT stacks
لایه های فیزیکی اولتراسونیک به عنوان بلوک های سازنده پشته های اینترنت اشیا-2022 Instrumental, Scientific and Medical (ISM) bands are essential to the transmission of IoT traffic
as most of the physical layers of the Wireless Personal Area Network (WPAN) and Low Power
Wide Area Network (LPWAN) families rely on them. ISM bands, however, are associated with
a myriad of problems responsible for signal degradation and pollution that lead to application
Quality of Service (QoS) issues. In this context, the use of alternative transmission mechanisms
serve as backup to traditional schemes. One of such mechanisms relies on sub-ultrasonic and
ultrasonic signals for the propagation of IoT device traffic. In this paper, we recycle a well
known acoustic modulation scheme intended to be used in legacy Public Switching Telephone
Networks (PSTNs) to support sub-ultrasonic and ultrasonic channels. This scheme becomes the
basic building block of a physical layer that is combined with other well known elements of the
IoT layered architecture. This not only includes a customized link layer but also an adaptation
layer that enables full integration with upper layers.
Keywords: 6LoWPAN | Ultrasound | ITU V.23 | CoAP | CSMA/CA | Layers |
مقاله انگلیسی |
8 |
A conceptual IoT-based early-warning architecture for remote monitoring of COVID-19 patients in wards and at home
یک معماری مفهومی هشدار اولیه مبتنی بر اینترنت اشیا برای نظارت از راه دور بیماران COVID-19 در بخش ها و در خانه-2022 Due to the COVID-19 pandemic, health services around the globe are struggling. An effective system for monitoring patients can improve healthcare delivery by avoiding in-person
contacts, enabling early-detection of severe cases, and remotely assessing patients’ status.
Internet of Things (IoT) technologies have been used for monitoring patients’ health with
wireless wearable sensors in different scenarios and medical conditions, such as noncommunicable and infectious diseases. Combining IoT-related technologies with early-warning
scores (EWS) commonly utilized in infirmaries has the potential to enhance health services delivery significantly. Specifically, the NEWS-2 has been showing remarkable results
in detecting the health deterioration of COVID-19 patients. Although the literature presents
several approaches for remote monitoring, none of these studies proposes a customized,
complete, and integrated architecture that uses an effective early-detection mechanism for
COVID-19 and that is flexible enough to be used in hospital wards and at home. Therefore,
this article’s objective is to present a comprehensive IoT-based conceptual architecture that
addresses the key requirements of scalability, interoperability, network dynamics, context
discovery, reliability, and privacy in the context of remote health monitoring of COVID-19
patients in hospitals and at home. Since remote monitoring of patients at home (essential
during a pandemic) can engender trust issues regarding secure and ethical data collection,
a consent management module was incorporated into our architecture to provide transparency and ensure data privacy. Further, the article details mechanisms for supporting a
configurable and adaptable scoring system embedded in wearable devices to increase usefulness and flexibility for health care professions working with EWS.
keywords: نظارت از راه دور | کووید-۱۹ | اخبار-2 | معماری | رضایت | اینترنت اشیا | Remote monitoring | COVID-19 | NEWS-2 | Architecture | Consent | IoT |
مقاله انگلیسی |
9 |
Autoencoder based Consensus Mechanism for Blockchain-enabled Industrial Internet of Things
مکانیزم اجماع مبتنی بر رمزگذار خودکار برای اینترنت اشیاء صنعتی دارای بلاک چین-2022 Conventional blockchain technologies developed for cryptocurrency applications involve complex consensus algorithms which are not suitable for resource constrained Internet of Things
(IoT) devices. Therefore, several lightweight consensus mechanisms that are suitable for IoT devices have been proposed in recent studies. However, these lightweight consensus mechanisms
do not verify the originality of the data generated by the IoT devices, so false and anomalous
data may pass through and be stored in the ledger for further analysis. In this work to address
the data originality verification problem, we propose an autoencoder (AE)-integrated Chaincode
(CC)-based consensus mechanism in which the AE differentiates normal data from anomalous
data. The AE is invoked through the CC once a transaction is initiated; the result returned from
the AE to the CC is stored in the ledger. We have conducted a case study to train and test
the AE model on the IoTID20 dataset. Also, Minifabric (MF) is used to implement the CC and
illustrate the CC operation that stores only original IoT data. Moreover, the performance has
been shown for the CC in terms of latency and throughput.
keywords: IoT | Autoencoder | Blockchain | Hyperledger | Security |
مقاله انگلیسی |
10 |
Evaluation of corporate requirements for smart manufacturing systems using predictive analytics
ارزیابی الزامات شرکت برای سیستمهای تولید هوشمند با استفاده از تجزیه و تحلیل پیشبینیکننده-2022 Smart manufacturing systems (SMS) are one of the most important applications in the Industry
4.0 era, offering numerous advantages over traditional production systems and rapidly being
used as a performance-enhancing strategy of manufacturing enterprises. A few of the technologies that must be connected to construct an SMS are the Industrial Internet of Things (IIoT),
Big Data, Robotics, Blockchain, 5G Communication, Artificial Intelligence (AI), and many more.
SMS is an innovative and popular manufacturing setup that produces increasingly intelligent
production systems; yet, designers must adapt to business tastes and requirements. This study
employs an analytical and descriptive research technique to identify and assess functional and
non-functional, technological, economic, social, and performance evaluation components that
are essential to SMS evaluation. A predictive analytics framework, which is a key component
of many decision support systems, is used to assess corporate needs as well as proposed and
prioritize SMS services.
keywords: صنعت 4.0 | تجزیه و تحلیل پیش بینی کننده | سیستم های تولید هوشمند | اینترنت اشیاء صنعتی | سیستم پشتیبانی تصمیم | Industry4.0 | Predictive analytics | Smart manufacturing systems | Industrial Internet of Things | Decision support system |
مقاله انگلیسی |