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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 |
Direct Quantum Communications in the Presence of Realistic Noisy Entanglement
ارتباطات کوانتومی مستقیم در حضور درهم تنیدگی پر سر و صدا واقعی-2022 To realize the Quantum Internet, quantum
communications require pre-shared entanglement among quantum nodes. However, both the generation and the distribution
of the maximally-entangled quantum states are inherently contaminated by quantum decoherence. Conventionally, the quantum
decoherence is mitigated by performing the consecutive steps of
quantum entanglement distillation followed by quantum teleportation. However, this conventional approach imposes a long delay.
To circumvent this impediment, we propose a novel quantum
communication scheme relying on realistic noisy pre-shared
entanglement, which eliminates the sequential steps imposing
delay in the standard approach. More precisely, our proposed
scheme can be viewed as a direct quantum communication
scheme capable of improving the quantum bit error ratio (QBER)
of the logical qubits despite relying on realistic noisy pre-shared
entanglement. Our performance analysis shows that the proposed
scheme offers competitive QBER, yield, and goodput compared
to the existing state-of-the-art quantum communication schemes,
despite requiring fewer quantum gates.
Index Terms: Quantum communication | quantum entanglement | quantum error-correction | quantum stabilizer codes | Quantum Internet. |
مقاله انگلیسی |
3 |
IoTracker: A probabilistic event tracking approach for data-intensive IoT Smart Applications
IoTracker: یک رویکرد ردیابی رویداد احتمالی برای برنامههای هوشمند اینترنت اشیا با داده های فشرده-2022 Smart Applications for cities, industry, farming and healthcare use Internet of Things (IoT)
approaches to improve the general quality. A dependency on smart applications implies that any
misbehavior may impact our society with varying criticality levels, from simple inconveniences
to life-threatening dangers. One critical challenge in this area is to overcome the side effects
caused by data loss due to failures in software, hardware, and communication systems, which
may also affect data logging systems. Event traceability and auditing may be impaired when an
application makes automated decisions and the operating log is incomplete. In an environment
where many events happen automatically, an audit system must understand, validate, and
find the root causes of eventual failures. This paper presents a probabilistic approach to track
sequences of events even in the face of logging data loss using Bayesian networks. The results of
the performance analysis with three smart application scenarios show that this approach is valid
to track events in the face of incomplete data. Also, scenarios modeled with Bayesian subnets
highlight a decreasing complexity due to this divide and conquer strategy that reduces the
number of elements involved. Consequently, the results improve and also reveal the potential
for further advancement.
Keywords: Smart applications | Event tracker | Probabilistic tracker | Bayesian networks |
مقاله انگلیسی |
4 |
Efficient Implementation of Lightweight Hash Functions on GPU and Quantum Computers for IoT Applications
اجرای کارآمد توابع هش سبک در GPU و کامپیوترهای کوانتومی برای کاربردهای اینترنت اشیا-2022 Secure communication is important for Internet of Things (IoT) applications, to avoid cybersecurity attacks. One of the key security aspects is data integrity, which can be protected by employing cryptographic hash functions. Recently, US National Institute of Standards and Technology (NIST)
announced a competition to standardize lightweight hash functions, which can be used in IoT applications.
IoT communication involves various hardware platforms, from low-end microcontrollers to high-end cloud
servers with GPU accelerators. Since many sensor nodes are connected to the gateway devices and cloud
servers, performing high throughput integrity check is important to secure IoT applications. However, this is a
time consuming task even for high-end servers, which may affect the response time in IoT systems. Moreover,
no prior work had evaluated the performance of NIST candidates on contemporary processors like GPU and
quantum computers. In this study, we showed that with carefully crafted implementation techniques, all
the finalist hash function candidates in the NIST standardization competition can achieve high throughput
(up-to 1,000 Gbps) on a RTX 3080 GPU. This research output can be used by IoT gateway devices and cloud
servers to perform data integrity checks at high speed, thus ensuring a timely response. In addition, this is
also the first study that showcase the implementation of NIST lightweight hash functions on a quantum
computer (ProjectQ). Besides securing the communication in IoT, these efficient implementations on a GPU
and quantum computer can be used to evaluate the strength of respective hash functions against brute-force
attack.
INDEX TERMS: Graphics processing units (GPU) | hash function | lightweight cryptography | quantum computer. |
مقاله انگلیسی |
5 |
EP-PQM: Efficient Parametric Probabilistic Quantum Memory With Fewer Qubits and Gates
EP-PQM: حافظه کوانتومی احتمالی پارامتریک کارآمد با کیوبیت ها و گیت های کمتر-2022 Machine learning (ML) classification tasks can be carried out on a quantum computer (QC)
using probabilistic quantum memory (PQM) and its extension, parametric PQM (P-PQM), by calculating
the Hamming distance between an input pattern and a database of r patterns containing z features with
a distinct attributes. For PQM and P-PQM to correctly compute the Hamming distance, the feature must
be encoded using one-hot encoding, which is memory intensive for multiattribute datasets with a > 2. We
can represent multiattribute data more compactly by replacing one-hot encoding with label encoding; both
encodings yield the same Hamming distance. Implementing this replacement on a classical computer is
trivial. However, replacing these encoding schemes on a QC is not straightforward because PQM and P-PQM
operate at the bit level, rather than at the feature level (a feature is represented by a binary string of 0’s and
1’s). We present an enhanced P-PQM, called efficient P-PQM (EP-PQM), that allows label encoding of data
stored in a PQM data structure and reduces the circuit depth of the data storage and retrieval procedures.
We show implementations for an ideal QC and a noisy intermediate-scale quantum (NISQ) device. Our
complexity analysis shows that the EP-PQM approach requires O(z log2(a)) qubits as opposed to O(za)
qubits for P-PQM. EP-PQM also requires fewer gates, reducing gate count from O(rza) to O(rz log2(a)).
For five datasets, we demonstrate that training an ML classification model using EP-PQM requires 48% to
77% fewer qubits than P-PQM for datasets with a > 2. EP-PQM reduces circuit depth in the range of 60% to
96%, depending on the dataset. The depth decreases further with a decomposed circuit, ranging between 94%
and 99%. EP-PQM requires less space; thus, it can train on and classify larger datasets than previous PQM
implementations on NISQ devices. Furthermore, reducing the number of gates speeds up the classification
and reduces the noise associated with deep quantum circuits. Thus, EP-PQM brings us closer to scalable ML
on an NISQ device.
INDEX TERMS: Efficient encoding | label encoding | quantum memory. |
مقاله انگلیسی |
6 |
Digital Twin-driven approach to improving energy efficiency of indoor lighting based on computer vision and dynamic BIM
رویکرد دیجیتال دوقلو برای بهبود بهره وری انرژی در روشنایی داخلی بر اساس بینایی کامپیوتر و BIM پویا-2022 Intelligent lighting systems and surveillance systems have become an important part of intelligent buildings. However, the current intelligent lighting system generally adopts independent sensor control and
does not perform multi-source heterogeneous data fusion with other digital systems. This paper fully
considers the linkage between the lighting system and the surveillance system and proposes a digital
twin lighting (DTL) system that mainly consists of three parts. Firstly, a visualized operation and maintenance (VO&M) platform for a DTL system was established based on dynamic BIM. Secondly, the environment perception, key-frame similarity judgment, and multi-channel key-frame cut and merge
mechanism were utilized to preprocess the video stream of the surveillance system in real-time.
Lastly, pedestrians detected using YOLOv4 and the ambient brightness perceived by the environment
perception mechanism were transmitted to the cloud database and were continuously read by the
VO&M platform. The intent here was to aid timely adaptive adjustment of the digital twin and realistic
lighting through the internet. The effectiveness of the proposed method was verified by experimenting
with a surveillance video stream for 14 days. The key results of the experiments are as follows: (1) the
accuracy rate of intelligent decision control reached 95.15%; (2) energy consumption and electricity costs
were reduced by approximately 79%; and (3) the hardware cost and energy consumption of detection
equipment and the time and cost of operation and maintenance (O&M) were greatly reduced.
keywords: Computer vision | Digital Twin | Dynamic BIM | Energy-efficient buildings | Intelligent lighting control |
مقاله انگلیسی |
7 |
Implementation of Quantum Annealing: A Systematic Review
پیاده سازی آنیل کوانتومی: مروری سیستماتیک-2022 Quantum annealing is a quantum computing approach widely used for optimization and
probabilistic sampling problems. It is an alternative approach designed due to the limitations of gate-based
quantum computing models. The method is observed to have a significant impact on different fields such as
machine learning, graphics, routing, scheduling, computational chemistry, computational biology, security,
portfolio, and others despite the fact that it is relatively new. This research provides a systematic review of
research development trends in the field of quantum annealing and analyzes how it has been implemented
in different problem domains. The results are expected to serve as the basis to identify the opportunities
and challenges of research related to its implementation. The main contribution of this systematic review
is to summarize different implementations of quantum annealing. It is also to analyze the prospect and
opportunities in one of the problem domains with the greatest interest which is machine learning.
INDEX TERMS: Quantum annealing | implementation | review. |
مقاله انگلیسی |
8 |
Layer VQE: A Variational Approach for Combinatorial Optimization on Noisy Quantum Computers
لایه VQE: یک رویکرد متغیر برای بهینه سازی ترکیبی در کامپیوترهای کوانتومی پر سر و صدا-2022 Combinatorial optimization on near-term quantum devices is a promising path to demonstrating quantum advantage. However, the capabilities of these devices are constrained by high noise or
error rates. In this article, inspired by the variational quantum eigensolver (VQE), we propose an iterative
layer VQE (L-VQE) approach. We present a large-scale numerical study, simulating circuits with up to
40 qubits and 352 parameters, that demonstrates the potential of the proposed approach. We evaluate
quantum optimization heuristics on the problem of detecting multiple communities in networks, for which we
introduce a novel qubit-frugal formulation. We numerically compare L-VQE with the quantum approximate
optimization algorithm (QAOA) and demonstrate that QAOA achieves lower approximation ratios while
requiring significantly deeper circuits. We show that L-VQE is more robust to finite sampling errors and has
a higher chance of finding the solution as compared with standard VQE approaches. Our simulation results
show that L-VQE performs well under realistic hardware noise.
INDEX TERMS: Combinatorial optimization | hybrid quantum-classical algorithm | quantum optimization. |
مقاله انگلیسی |
9 |
A systematic review on computer vision-based parking lot management applied on public datasets
مرور سیستماتیک مدیریت پارکینگ مبتنی بر بینایی ماشین اعمال شده بر روی مجموعه داده های عمومی-2022 Computer vision-based parking lot management methods have been extensively researched upon owing to their
flexibility and cost-effectiveness. To evaluate such methods authors often employ publicly available parking lot
image datasets. In this study, we surveyed and compared robust publicly available image datasets specifically
crafted to test computer vision-based methods for parking lot management approaches and consequently
present a systematic and comprehensive review of existing works that employ such datasets. The literature
review identified relevant gaps that require further research, such as the requirement of dataset-independent
approaches and methods suitable for autonomous detection of position of parking spaces. In addition, we have
noticed that several important factors such as the presence of the same cars across consecutive images, have
been neglected in most studies, thereby rendering unrealistic assessment protocols. Furthermore, the analysis
of the datasets also revealed that certain features that should be present when developing new benchmarks,
such as the availability of video sequences and images taken in more diverse conditions, including nighttime
and snow, have not been incorporated.
keywords: Parking lot | Dataset | Benchmark | Machine learning | Image processing |
مقاله انگلیسی |
10 |
Measurement-Induced Boolean Dynamics for Open Quantum Networks
دینامیک بولی ناشی از اندازه گیری برای شبکه های کوانتومی باز-2022 In this paper, we study the recursion corresponding
to the measurement outcomes for open quantum networks
under sequential measurements. Open quantum networks are
networked quantum subsystems (e.g., qubits) with the state evolutions described by a continuous Lindblad master equation. When
measurements are performed sequentially along such continuous
dynamics, the quantum network states undergo probabilistic
jumps and the corresponding measurement outcomes can be
described by a vector of probabilistic Boolean variables. The
induced recursion of the Boolean vectors forms a probabilistic
Boolean network. First of all, we show that the state transition
of the induced Boolean network can be explicitly represented
through a real version of the master equation. Next, when the
open quantum dynamics are relaxing in the sense that they
possess a unique equilibrium as a global attractor, structural
properties including absorbing states, reducibility, and periodicity for the induced Boolean network are direct consequences
of this relaxing property. Particularly, we show that generically,
relaxing quantum dynamics lead to irreducible and aperiodic
chains for the measurement outcomes. Finally, we show that for
quantum consensus networks which are a type of non-relaxing
open quantum network dynamics, the communication classes of
the measurement-induced Boolean networks are encoded in the
quantum Laplacian of the underlying interaction graph.
Index Terms: quantum networks | open quantum systems | quantum measurements | Boolean networks |
مقاله انگلیسی |