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تعداد مقالات یافته شده: 3391
ردیف عنوان نوع
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 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
3 Development of an Undergraduate Quantum Engineering Degree
توسعه یک مدرک کارشناسی مهندسی کوانتوم-2022
Quantum computing, communications, sensing, and simulations are radically transformative technologies, with great potential to impact industries and economies. Worldwide, national governments, industries, and universities are moving to create a new class of workforce—the Quantum Engineers. Demand for such engineers is predicted to be in the tens of thousands within a five-year timescale, far exceeding the rate at which the world’s universities can produce Ph.D. graduates in the discipline. How best to train this next generation of engineers is currently a matter of debate. Quantum mechanics—long a pillar of traditional physics undergraduate degrees—must now be merged with traditional engineering offerings. This article discusses the history, development, and the first year of operation of the world’s first undergraduate degree in quantum engineering to be grown out of an engineering curriculum. The main purpose of this article is to inform the wider discussion, now being held by many institutions worldwide, on how best to formally educate the Quantum Engineer.
INDEX TERMS: Degree | education | engineering | quantum | undergraduate.
مقاله انگلیسی
4 DQRA: Deep Quantum Routing Agent for Entanglement Routing in Quantum Networks
DQRA: عامل مسیریابی کوانتومی عمیق برای مسیریابی درهم تنیده در شبکه های کوانتومی-2022
Quantum routing plays a key role in the development of the next-generation network system. In particular, an entangled routing path can be constructed with the help of quantum entanglement and swapping among particles (e.g., photons) associated with nodes in the network. From another side of computing, machine learning has achieved numerous breakthrough successes in various application domains, including networking. Despite its advantages and capabilities, machine learning is not as much utilized in quantum networking as in other areas. To bridge this gap, in this article, we propose a novel quantum routing model for quantum networks that employs machine learning architectures to construct the routing path for the maximum number of demands (source–destination pairs) within a time window. Specifically, we present a deep reinforcement routing scheme that is called Deep Quantum Routing Agent (DQRA). In short, DQRA utilizes an empirically designed deep neural network that observes the current network states to accommodate the network’s demands, which are then connected by a qubit-preserved shortest path algorithm. The training process of DQRA is guided by a reward function that aims toward maximizing the number of accommodated requests in each routing window. Our experiment study shows that, on average, DQRA is able to maintain a rate of successfully routed requests at above 80% in a qubit-limited grid network and approximately 60% in extreme conditions, i.e., each node can be repeater exactly once in a window. Furthermore, we show that the model complexity and the computational time of DQRA are polynomial in terms of the sizes of the quantum networks.
INDEX TERMS: Deep learning | deep reinforcement learning (DRL) | machine learning | next-generation network | quantum network routing | quantum networks.
مقاله انگلیسی
5 Moving towards intelligent telemedicine: Computer vision measurement of human movement
حرکت به سمت پزشکی از راه دور هوشمند: اندازه گیری بینایی کامپیوتری حرکت انسان-2022
Background: Telemedicine video consultations are rapidly increasing globally, accelerated by the COVID- 19 pandemic. This presents opportunities to use computer vision technologies to augment clinician visual judgement because video cameras are so ubiquitous in personal devices and new techniques, such as DeepLabCut (DLC) can precisely measure human movement from smartphone videos. However, the accuracy of DLC to track human movements in videos obtained from laptop cameras, which have a much lower FPS, has never been investigated; this is a critical gap because patients use laptops for most telemedicine consultations. Objectives: To determine the validity and reliability of DLC applied to laptop videos to measure finger tapping, a validated test of human movement. Method: Sixteen adults completed finger-tapping tests at 0.5 Hz, 1 Hz, 2 Hz, 3 Hz and at maximal speed. Hand movements were recorded simultaneously by a laptop camera at 30 frames per second (FPS) and by Optotrak, a 3D motion analysis system at 250 FPS. Eight DLC neural network architectures (ResNet50, ResNet101, ResNet152, MobileNetV1, MobileNetV2, EfficientNetB0, EfficientNetB3, EfficientNetB6) were applied to the laptop video and extracted movement features were compared to the ground truth Optotrak motion tracking. Results: Over 96% (529/552) of DLC measures were within +∕−0.5 Hz of the Optotrak measures. At tapping frequencies >4 Hz, there was progressive decline in accuracy, attributed to motion blur associated with the laptop camera’s low FPS. Computer vision methods hold potential for moving us towards intelligent telemedicine by providing human movement analysis during consultations. However, further developments are required to accurately measure the fastest movements.
keywords: پزشکی از راه دور | ضربه زدن با انگشت | موتور کنترل | کامپیوتری | Telemedicine | DeepLabCut | Finger tapping | Motor control | Computer vision
مقاله انگلیسی
6 A robust structural vibration recognition system based on computer vision
یک سیستم قوی تشخیص ارتعاش ساختاری بر اساس بینایی کامپیوتری-2022
Vibration-based structural health monitoring (SHM) systems are useful tools for assessing structural safety performance quantitatively. When employing traditional contact sensors, achieving high-resolution spatial measurements for large-scale structures is challenging, and fixed contact sensors may also lose dependability when the lifetime of the host structure is surpassed. Researchers have paid close attention to computer vision because it is noncontact, saves time and effort, is inexpensive, and has high efficiency in giving visual perception. In advanced noncontact measurements, digital cameras can capture the vibration information of structures remotely and swiftly. Thus, this work studies a system for recognizing structural vibration. The system ensures acquiring high-quality structural vibration signals by the following: 1) Establishing a novel image preprocessing, which includes visual partitioning measurement and image enhancement techniques; 2) initial recognition of structural vibration using phase-based optical flow estimation (POFE), which introduces 2-D Gabor wavelets to extract the independent phase information of the image to track the natural texture targets on the surface of the structure; 3) extracting the practical vibration information of the structure using mode decomposition to remove the complex environment of the camera vibration and other noises; 4) employing phase-based motion magnification (PMM) techniques to magnify small vibration signals, and then recognizing the complete information on the vibration time range of the structure. The research results of the laboratory experiments and field testing conducted under three different cases reveal that the system can recognize structural vibration in complicated environments.
keywords: Computer vision | Phase | Motion estimation | Motion magnification | Mode decomposition | Structural vibration
مقاله انگلیسی
7 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
8 Enabling Pulse-Level Programming, Compilation, and Execution in XACC
فعال کردن برنامه نویسی، کامپایل و اجرا در سطح پالس در XACC-2022
Noisy gate-model quantum processing units (QPUs) are currently available from vendors over the cloud, and digital quantum programming approaches exist to run low-depth circuits on physical hardware. These digital representations are ultimately lowered to pulse-level instructions by vendor quantum control systems to affect unitary evolution representative of the submitted digital circuit. Vendors are beginning to open this pulse-level control system to the public via specified interfaces. Robust programming methodologies, software frameworks, and backend simulation technologies for this analog model of quantum computation will prove critical to advancing pulse-level control research and development. Prototypical use cases for this include error mitigation, optimal pulse control, and physics-inspired pulse construction. Here we present an extension to the XACC quantum-classical software framework that enables pulse-level programming for superconducting, gate-model quantum computers, and a novel, general, and extensible pulse-level simulation backend for XACC that scales on classical compute clusters via MPI. Our work enables custom backend Hamiltonian definitions and gate-level compilation to available pulses with a focus on performance and scalability. We end with a demonstration of this capability, and show how to use XACC for pertinent pulse-level programming tasks.
Index Terms: Quantum computing | quantum programming models | quantum control | quantum simulation
مقاله انگلیسی
9 A survey on adversarial attacks in computer vision: Taxonomy, visualization and future directions
بررسی حملات خصمانه در بینایی کامپیوتر: طبقه بندی، تجسم و جهت گیری های آینده-2022
Deep learning has been widely applied in various fields such as computer vision, natural language pro- cessing, and data mining. Although deep learning has achieved significant success in solving complex problems, it has been shown that deep neural networks are vulnerable to adversarial attacks, result- ing in models that fail to perform their tasks properly, which limits the application of deep learning in security-critical areas. In this paper, we first review some of the classical and latest representative adversarial attacks based on a reasonable taxonomy of adversarial attacks. Then, we construct a knowl- edge graph based on the citation relationship relying on the software VOSviewer, visualize and analyze the subject development in this field based on the information of 5923 articles from Scopus. In the end, possible research directions for the development about adversarial attacks are proposed based on the trends deduced by keywords detection analysis. All the data used for visualization are available at: https://github.com/NanyunLengmu/Adversarial- Attack- Visualization .
keywords: یادگیری عمیق | حمله خصمانه | حمله جعبه سیاه | حمله به جعبه سفید | نیرومندی | تجزیه و تحلیل تجسم | Deep learning | Adversarial attack | Black-box attack | White-box attack | Robustness | Visualization analysis
مقاله انگلیسی
10 Equivalence Checking of Quantum Circuits With the ZX-Calculus
بررسی هم ارزی مدارهای کوانتومی با ZX-calculus-2022
As state-of-the-art quantum computers are capable of running increasingly complex algorithms, the need for automated methods to design and test potential applications rises. Equivalence checking of quantum circuits is an important, yet hardly automated, task in the development of the quantum software stack. Recently, new methods have been proposed that tackle this problem from widely different perspectives. One of them is based on the ZX-calculus, a graphical rewriting system for quantum computing. However, the power and capability of this equivalence checking method has barely been explored. The aim of this work is to evaluate the ZX-calculus as a tool for equivalence checking of quantum circuits. To this end, it is demonstrated how the ZX-calculus based approach for equivalence checking can be expanded in order to verify the results of compilation flows and optimizations on quantum circuits. It is also shown that the ZX-calculus based method is not complete—especially for quantum circuits with ancillary qubits. In order to properly evaluate the proposed method, we conduct a detailed case study by comparing it to two other state-of-the-art methods for equivalence checking: one based on path-sums and another based on decision diagrams. The proposed methods have been integrated into the publicly available QCEC tool (https://github.com/cda-tum/qcec) which is part of the Munich Quantum Toolkit (MQT).
Index Terms: Quantum computing | formal verification | quantum circuit.
مقاله انگلیسی
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