| مشخصات مقاله | |
| ترجمه عنوان مقاله | یک سیستم تشخیص خطا مبتنی بر منطق فازی برای اینترنت پزشکی اشیاء نانو |
| عنوان انگلیسی مقاله | A fuzzy-logic-based fault detection system for medical Internet of Nano Things |
| انتشار | مقاله سال 2021 |
| تعداد صفحات مقاله انگلیسی | 9 صفحه |
| هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
| پایگاه داده | نشریه الزویر |
| نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
| مقاله بیس | این مقاله بیس نمیباشد |
| نمایه (index) | Scopus – Master Journals List – JCR |
| نوع مقاله | ISI |
| فرمت مقاله انگلیسی | |
| ایمپکت فاکتور(IF) |
2.947 در سال 2020 |
| شاخص H_index | 36 در سال 2020 |
| شاخص SJR | 0.463 در سال 2020 |
| شناسه ISSN | 1878-7789 |
| شاخص Quartile (چارک) | Q2 در سال 2020 |
| فرضیه | ندارد |
| مدل مفهومی | ندارد |
| پرسشنامه | ندارد |
| متغیر | ندارد |
| رفرنس | دارد |
| رشته های مرتبط | مهندسی کامپیوتر، مهندسی فناوری اطلاعات |
| گرایش های مرتبط | اینترنت و شبکه های گسترده، امنیت اطلاعات، شبکه های کامپیتری |
| نوع ارائه مقاله |
ژورنال |
| مجله | شبکه های ارتباطی نانو – Nano Communication Networks |
| دانشگاه | Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran |
| کلمات کلیدی | اینترنت اشیاء نانو، تشخیص خطا، منطق فازی ،در مطالعه سیلیکونی، آترواسکلروز |
| کلمات کلیدی انگلیسی | Internet of Nano Things – Fault detection – Fuzzy logic – In silico study – Atherosclerosis |
| شناسه دیجیتال – doi |
https://doi.org/10.1016/j.nancom.2021.100366 |
| کد محصول | E15959 |
| وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
| دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
| سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
| فهرست مطالب مقاله: |
| Abstract Keywords Introduction The architecture of medical IoNT Fuzzy-logic-based fault detection In silico study Conclusion CRediT authorship contribution statement Declaration of Competing Interest References |
| بخشی از متن مقاله: |
| Abstract In this paper, a fuzzy-logic-based fault detection system is designed for a medical Internet of Nano Things architecture. The goal of this system is to detect the root cause and severity of the faults occurred in the in-body nanonetwork. Since nanomachines have very limited capabilities, the sampled data from the in-body nanonetwork is sent to cloud servers by means of an on-body micro-gateway. The fuzzy fault detection system was designed based on two well-known methods including Mamdani and Takagi–Sugeno–Kang (TSK) fuzzy systems. The performance of the proposed approach is evaluated on a theoretical model of medical in-body nanonetwork from the literature through in silico study. This nanonetwork includes eleven types of nanomachines which cooperate with each other within the arterial wall and interact with low-density lipoprotein (LDL), drug and signaling molecules in order to prevent the formation and development of Atherosclerosis plaques. Any fault in these nanomachines can highly take negative effect on treatment efficiency. The results of computer simulation and comparative study on 37 atherosclerosis patients demonstrate how the proposed approach could successfully detect the root cause and severity of the faults occurred in the nanonetwork. Introduction Nanotechnology, as a practical approach for miniaturization and construction of very small devices in nanoscale, provides new solutions in different areas including medicine, industry, biology, and military [1,2]. Particularly, medicine has been acquired significant advances with the aid of nanotechnology [3–6]. This recently emerging field is called nanomedicine, in which, nanomachines are able to noninvasively interact with body tissues and perform sensing and manipulation at cellular and molecular levels. A nanomachine is a basic functional unit with limited sensing and actuation abilities [1]. A nanonetwork is defined as a set of interacting nanomachines that exploits communication and cooperation among them to realize new synergic capabilities in contrast to a single nanomachine. Connecting nanonetworks to external networks such as the Internet has been a challenging topic over recent years. This new paradigm is called Internet of Nano Things (IoNT) [7]. Research works on IoNT can be divided into four general categories. The first category contains some articles that provide an overview of the IoNT and present open problems, challenges and future perspectives [8–10]. There still exist many challenges in the context of IoNT such as designing applicable methods for data collection from nanonetworks, optimizing the consumption of energy in micro-gateways, ensuring data privacy and security, developing a middleware layer to connect nanosensor networks to microscale devices and external networks, and creating appropriate service management systems for IoNT. |