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ردیف | عنوان | نوع |
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1 |
Data Mining Strategies for Real-Time Control in New York City
استراتژی داده کاوی برای کنترل زمان واقعی در شهر نیویورک-2105 The Data Mining System (DMS) at New York City Department of Transportation (NYCDOT) mainly consists of four database
systems for traffic and pedestrian/bicycle volumes, crash data, and signal timing plans as well as the Midtown in Motion (MIM)
systems which are used as part of the NYCDOT Intelligent Transportation System (ITS) infrastructure. These database and
control systems are operated by different units at NYCDOT as an independent database or operation system. New York City
experiences heavy traffic volumes, pedestrians and cyclists in each Central Business District (CBD) area and along key arterial
systems. There are consistent and urgent needs in New York City for real-time control to improve mobility and safety for all
users of the street networks, and to provide a timely response and management of random incidents. Therefore, it is necessary to
develop an integrated DMS for effective real-time control and active transportation management (ATM) in New York City.
This paper will present new strategies for New York City suggesting the development of efficient and cost-effective DMS,
involving: 1) use of new technology applications such as tablets and smartphone with Global Positioning System (GPS) and
wireless communication features for data collection and reduction; 2) interface development among existing database and control
systems; and 3) integrated DMS deployment with macroscopic and mesoscopic simulation models in Manhattan. This study
paper also suggests a complete data mining process for real-time control with traditional static data, current real timing data from
loop detectors, microwave sensors, and video cameras, and new real-time data using the GPS data. GPS data, including using taxi
and bus GPS information, and smartphone applications can be obtained in all weather conditions and during anytime of the day.
GPS data and smartphone application in NYCDOT DMS is discussed herein as a new concept.
© 2014 The Authors. Published by Elsevier B.V.
Selection and peer-review under responsibility of Elhadi M. Shakshu
Keywords: Data Mining System (DMS), New York City, real-time control, active transportation management (ATM), GPS data |
مقاله انگلیسی |
2 |
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 |
3 |
Decentralization Using Quantum Blockchain: A Theoretical Analysis
تمرکززدایی با استفاده از بلاک چین کوانتومی: یک تحلیل نظری-2022 Blockchain technology has been prominent recently due to its applications in cryptocurrency. Numerous decentralized blockchain applications have been possible due to blockchains’ nature of
distributed, secured, and peer-to-peer storage. One of its technical pillars is using public-key cryptography
and hash functions, which promise a secure, pseudoanonymous, and distributed storage with nonrepudiation.
This security is believed to be difficult to break with classical computational powers. However, recent
advances in quantum computing have raised the possibility of breaking these algorithms with quantum
computers, thus, threatening the blockchains’ security. Quantum-resistant blockchains are being proposed
as alternatives to resolve this issue. Some propose to replace traditional cryptography with postquantum
cryptography—others base their approaches on quantum computer networks or quantum internets. Nonetheless, a new security infrastructure (e.g., access control/authentication) must be established before any of
these could happen. This article provides a theoretical analysis of the quantum blockchain technologies
that could be used for decentralized identity authentication. We put together a conceptual design for a
quantum blockchain identity framework and give a review of the technical evidence. We investigate its
essential components and feasibility, effectiveness, and limitations. Even though it currently has various
limitations and challenges, we believe a decentralized perspective of quantum applications is noteworthy and
likely.
INDEX TERMS: Blockchains | consensus protocol | decentralized applications | identity management systems | quantum computing | quantum networks. |
مقاله انگلیسی |
4 |
Intelligent context-aware fog node discovery
کشف گره مه آگاه از زمینه هوشمند-2022 Fog computing has been proposed as a mechanism to address certain issues in
cloud computing such as latency, storage, network bandwidth, etc. Fog computing brings the processing, storage, and networking to the edge of the network
near the edge devices, which we called fog consumers. This decreases latency,
network bandwidth, and response time. Discovering the most relevant fog node,
the nearest one to the fog consumers, is a critical challenge that is yet to be addressed by the research. In this study, we present the Intelligent and Distributed
Fog node Discovery mechanism (IDFD) which is an intelligent approach to enable fog consumers to discover appropriate fog nodes in a context-aware manner.
The proposed approach is based on the distributed fog registries between fog consumers and fog nodes that can facilitate the discovery process of fog nodes. In
this study, the KNN, K-d tree, and brute force algorithms are used to discover
fog nodes based on the context-aware criteria of fog nodes and fog consumers.
The proposed framework is simulated using OMNET++, and the performance of
the proposed algorithms is compared based on performance metrics and execution
time. The accuracy and execution time are the major points of consideration in
the selection of an optimal fog search algorithm. The experiment results show
that the KNN and K-d tree algorithms achieve the same accuracy results of 95 %.
However, the K-d tree method takes less time to find the nearest fog nodes than
KNN and brute force. Thus, the K-d tree is selected as the fog search algorithm
in the IDFD to discover the nearest fog nodes very efficiently and quickly.
keywords: Fog node | Discovery | Context-aware | Intelligent | Fog node discovery |
مقاله انگلیسی |
5 |
Deep Reinforcement Learning With Quantum-Inspired Experience Replay
یادگیری تقویتی عمیق با تکرار تجربه کوانتومی-2022 In this article, a novel training paradigm inspired
by quantum computation is proposed for deep reinforcement
learning (DRL) with experience replay. In contrast to the traditional experience replay mechanism in DRL, the proposed DRL
with quantum-inspired experience replay (DRL-QER) adaptively
chooses experiences from the replay buffer according to the
complexity and the replayed times of each experience (also
called transition), to achieve a balance between exploration and
exploitation. In DRL-QER, transitions are first formulated in
quantum representations and then the preparation operation
and depreciation operation are performed on the transitions.
In this process, the preparation operation reflects the relationship between the temporal-difference errors (TD-errors) and the
importance of the experiences, while the depreciation operation is
taken into account to ensure the diversity of the transitions. The
experimental results on Atari 2600 games show that DRL-QER
outperforms state-of-the-art algorithms, such as DRL-PER and
DCRL on most of these games with improved training efficiency
and is also applicable to such memory-based DRL approaches
as double network and dueling network.
Index Terms: Deep reinforcement learning (DRL) | quantum computation | quantum-inspired experience replay (QER) | quantum reinforcement learning. |
مقاله انگلیسی |
6 |
Internet of Things-enabled Passive Contact Tracing in Smart Cities
ردیابی تماس غیرفعال با قابلیت اینترنت اشیا در شهرهای هوشمند-2022 Contact tracing has been proven an essential practice during pandemic outbreaks and is a
critical non-pharmaceutical intervention to reduce mortality rates. While traditional con-
tact tracing approaches are gradually being replaced by peer-to-peer smartphone-based
systems, the new applications tend to ignore the Internet-of-Things (IoT) ecosystem that is
steadily growing in smart city environments. This work presents a contact tracing frame-
work that logs smart space users’ co-existence using IoT devices as reference anchors. The
design is non-intrusive as it relies on passive wireless interactions between each user’s
carried equipment (e.g., smartphone, wearable, proximity card) with an IoT device by uti-
lizing received signal strength indicators (RSSI). The proposed framework can log the iden-
tities for the interacting pair, their estimated distance, and the overlapping time duration.
Also, we propose a machine learning-based infection risk classification method to char-
acterize each interaction that relies on RSSI-based attributes and contact details. Finally,
the proposed contact tracing framework’s performance is evaluated through a real-world
case study of actual wireless interactions between users and IoT devices through Bluetooth
Low Energy advertising. The results demonstrate the system’s capability to accurately cap-
ture contact between mobile users and assess their infection risk provided adequate model
training over time.
© 2021 Elsevier B.V. All rights reserved. keywords: بلوتوث کم انرژی | ردیابی تماس | اینترنت اشیا | طبقه بندی خطر عفونت | Bluetooth Low Energy | Contact Tracing | Internet of Things | Infection Risk Classification |
مقاله انگلیسی |
7 |
Deployment-Ready Quantum Key Distribution Over a Classical Network Infrastructure in Padua
توزیع کلید کوانتومی آماده استقرار بر روی یک زیرساخت شبکه کلاسیک در پادوآ-2022 Current technological progress is driving Quantum
Key Distribution towards a commercial and worldwide scale
expansion. Its capability to deliver secure communication
regardless of the computational power of the attackers will be a
fundamental feature in the next generations of telecommunication
networks. Nevertheless, demonstrations of QKD implementation in a real operating scenario and their coexistence with the
classical telecom infrastructure are of fundamental importance
for reliable exploitation. Here we present a Quantum Key
Distribution application implemented over a classical fiber-based
infrastructure. We exploit a 50 MHz source at 1550 nm, a single 13
km-long fiber cable for both the quantum and the classical channel,
and a simplified receiver scheme with just one single-photon
detector. In this way, we achieve an error rate of approximately
2% and a secret key rate of about 1.7 kbps, thus demonstrating the
feasibility of low-cost and ready-to-use Quantum Key Distribution
systems compatible with standard classical infrastructure.
Index Terms: Classical channel | cryptography | fiber, FPGA | padua | POGNAC | quantum communication | quantum key distribution | qubit4sync | telecommunication. |
مقاله انگلیسی |
8 |
IoT anomaly detection methods and applications: A survey
روش ها و کاربردهای تشخیص ناهنجاری اینترنت اشیا: یک مرور-2022 Ongoing research on anomaly detection for the Internet of Things (IoT) is a rapidly expanding
field. This growth necessitates an examination of application trends and current gaps. The
vast majority of those publications are in areas such as network and infrastructure security,
sensor monitoring, smart home, and smart city applications and are extending into even more
sectors. Recent advancements in the field have increased the necessity to study the many IoT
anomaly detection applications. This paper begins with a summary of the detection methods
and applications, accompanied by a discussion of the categorization of IoT anomaly detection
algorithms. We then discuss the current publications to identify distinct application domains,
examining papers chosen based on our search criteria. The survey considers 64 papers among
recent publications published between January 2019 and July 2021. In recent publications, we
observed a shortage of IoT anomaly detection methodologies, for example, when dealing with
the integration of systems with various sensors, data and concept drifts, and data augmentation
where there is a shortage of Ground Truth data. Finally, we discuss the present such challenges
and offer new perspectives where further research is required.
keywords: Anomaly detection | Internet of Things | IoT | Review | Survey | Applications |
مقاله انگلیسی |
9 |
Design of an Integrated Bell-State Analyzer on a Thin-Film Lithium Niobate Platform
طراحی یک آنالایزر حالت زنگ یکپارچه بر روی بستر نازک لیتیوم نیوبات-2022 Trapped ions are excellent candidates for quantum
computing and quantum networks because of their long coherence
times, ability to generate entangled photons as well as high fidelity
single- and two-qubit gates. To scale up trapped ion quantum
computing, we need a Bell-state analyzer on a reconfigurable platform that can herald high fidelity entanglement between ions. In
this work, we design a photonic Bell-state analyzer on a reconfigurable thin-film lithium niobate platform for polarization-encoded
qubits.We optimize the device to achieve high fidelity entanglement
between two trapped ions and find >99% fidelity. Apart from
that, the directional coupler used in our design can achieve any
polarization-independent power splitting ratio which can have a
rich variety of applications in the integrated photonic technology.
The proposed device can scale up trapped ion quantum computing
as well as other optically active spin qubits, such as color centers
in diamond, quantum dots, and rare-earth ions.
Index Terms: Bell-state analyzer | thin-film lithium niobate | scalable quantum computing | trapped ions | entanglement | polarization qubits | polarization-independent directional coupler. |
مقاله انگلیسی |
10 |
IoT architecture for continuous long term monitoring: Parkinson’s Disease case study
معماری اینترنت اشیا برای نظارت طولانی مدت مداوم: مطالعه موردی بیماری پارکینسون-2022 In recent years, technological advancements and the strengthening of the Internet of Things
concepts have led to significant improvements in the technology infrastructures for remote
monitoring. This includes telemedicine which is the ensemble of technologies and tools involved
in medical services, from consultations, to diagnosis, prescriptions, treatment and patient
monitoring, all done remotely via an Internet connection.
Developing a telemedicine framework capable of monitoring patients over a continuous long-term monitoring window may encounter various issues related to the battery life of the device or the accuracy of the retrieved data. Moreover, it is crucial to develop an IoT architecture that is adaptable to various scenarios and the ongoing changes of the application scenario under analysis. In this work, we present an IoT architecture for continuous long-term monitoring of patients. Furthermore, as a real scenario case study, we adapt our IoT architecture for Parkinson’s Disease management, building up the PDRMA (Parkinson’s disease remote monitoring architecture). Performance analysis for optimal operation with respect to temperature and daily battery life is conducted. Finally, a multi-parameter app for the continuous monitoring of Parkinson’s patients is presented. keywords: IoT | Telemedicine | Continuous long term monitoring | Parkinson’s disease | e-Health |
مقاله انگلیسی |