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نتیجه جستجو - گراف

تعداد مقالات یافته شده: 362
ردیف عنوان نوع
1 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
2 Assessing surface drainage conditions at the street and neighborhood scale: A computer vision and flow direction method applied to lidar data
ارزیابی شرایط زهکشی سطحی در مقیاس خیابان و محله: یک روش دید کامپیوتری و جهت جریان اعمال شده به داده های لیدار-2022
Surface drainage at the neighborhood and street scales plays an important role in conveying stormwater and mitigating urban flooding. Surface drainage at the local scale is often ignored due to the lack of up-to-date fine- scale topographical information. This paper addresses this issue by providing a novel method for evaluating surface drainage at the neighborhood and street scales based on mobile lidar (light detection and ranging) measurements. The developed method derives topographical properties and runoff accumulation by applying a semantic segmentation (SS) model (a computer vision technique) and a flow direction model (a hydrology technique) to lidar data. Fifty lidar images representing 50 street blocks were used to train, validate, and test the SS model. Based on the test dataset, the SS model has 80.3% IoU and 88.5% accuracy. The results suggest that the proposed method can effectively evaluate surface drainage conditions at both the neighborhood and street scales and identify problematic low points that could be susceptible to water ponding. Municipalities and property owners can use this information to take targeted corrective maintenance actions.
keywords: تقسیم بندی معنایی | جهت جریان | لیدار موبایل | زهکشی سطحی | زیرساخت های زهکشی | Semantic segmentation | Flow direction | Mobile lidar | Surface drainage | Drainage infrastructure
مقاله انگلیسی
3 Graph Kernels Encoding Features of All Subgraphs by Quantum Superposition
ویژگی های رمزگزاری هسته های گراف زیرگراف ها با برهم نهی کوانتومی-2022
Graph kernels are often used in bioinformatics and network applications to measure the similarity between graphs; therefore, they may be used to construct efficient graph classifiers. Many graph kernels have been developed thus far, but to the best of our knowledge there is no existing graph kernel that uses some features explicitly extracted from all subgraphs to measure similarity. We propose a novel graph kernel that applies a quantum computer to measure the similarity obtained from all subgraphs by fully exploiting the power of quantum superposition to encode every subgraph into a feature of particular form. For the construction of the quantum kernel, we develop an efficient protocol that clears the index information of the subgraphs encoded in the quantum state. We also prove that the quantum computer requires less query complexity to construct the feature vector than the classical sampler used to approximate the same vector. A detailed numerical simulation of a bioinformatics problem is presented to demonstrate that, in many cases, the proposed quantum kernel achieves better classification accuracy than existing graph kernels.
Index Terms: Quantum computing | machine learning | bioinfomatics.
مقاله انگلیسی
4 The application of computer vision systems in meat science and industry – A review
کاربرد سیستم های بینایی کامپیوتری در علم و صنعت گوشت – مروری-2022
Computer vision systems (CVS) are applied to macro- and microscopic digital photographs captured using digital cameras, ultrasound scanners, computer tomography, and wide-angle imaging cameras. Diverse image acquisi- tion devices make it technically feasible to obtain information about both the external features and internal structures of targeted objects. Attributes measured in CVS can be used to evaluate meat quality. CVS are also used in research related to assessing the composition of animal carcasses, which might help determine the impact of cross-breeding or rearing systems on the quality of meat. The results obtained by the CVS technique also contribute to assessing the impact of technological treatments on the quality of raw and cooked meat. CVS have many positive attributes including objectivity, non-invasiveness, speed, and low cost of analysis and systems are under constant development an improvement. The present review covers computer vision system techniques, stages of measurements, and possibilities for using these to assess carcass and meat quality.
keywords: سیستم بینایی کامپیوتری | گوشت | محصولات گوشتی | لاشه | Computer vision system | Meat | Meat products | Carcass
مقاله انگلیسی
5 Implementing Graph-Theoretic Feature Selection by Quantum Approximate Optimization Algorithm
پیاده سازی انتخاب ویژگی گراف-نظری توسط الگوریتم بهینه سازی تقریبی کوانتومی-2022
Feature selection plays a significant role in computer science; nevertheless, this task is intractable since its search space scales exponentially with the number of dimensions. Motivated by the potential advantages of near-term quantum computing, three graph-theoretic feature selection (GTFS) methods, including minimum cut (MinCut)-based, densest k -subgraph (DkS)-based, and maximal-independent set/minimal vertex cover (MIS/MVC)-based, are investigated in this article, where the original graph-theoretic problems are naturally formulated as the quadratic problems in binary variables and then solved using the quantum approximate optimization algorithm (QAOA). Specifically, three separate graphs are created from the raw feature set, where the vertex set consists of individual features and pairwise measure describes the edge. The corresponding feature subset is generated by deriving a subgraph from the established graph using QAOA. For the above three GTFS approaches, the solving procedure and quantum circuit for the corresponding graph-theoretic problems are formulated with the framework of QAOA. In addition, those proposals could be employed as a local solver and integrated with the Tabu search algorithm for solving large-scale GTFS problems utilizing limited quantum bit resource. Finally, extensive numerical experiments are conducted with 20 publicly available datasets and the results demonstrate that each model is superior to its classical scheme. In addition, the complexity of each model is only O(pn2) even in the worst cases, where p is the number of layers in QAOA and n is the number of features.
Index Terms: Feature selection | graph theory | parameterized quantum circuit | quantum approximation optimization algorithm | quantum computing.
مقاله انگلیسی
6 Model-Predictive Quantum Control via Hamiltonian Learning
مدل-کنترل کوانتومی پیش‌بینی‌کننده از طریق یادگیری همیلتونی-2022
This work proposes an end-to-end framework for the learning-enabled control of closed quantum systems. The proposed learning technique is the first of its kind to utilize a hierarchical design which layers probing control, quantum state tomography, quantum process tomography, and Hamiltonian learning to identify both the internal and control Hamiltonians. Within this context, a novel quantum process tomography algorithm is presented which involves optimization on the unitary group, i.e., the space of unitary operators, to ensure physically meaningful predictions. Our scalable Hamiltonian learning algorithms have low memory requirements and tunable computational complexity. Once the Hamiltonians are learned, we formalize data-driven model-predictive quantum control (MPQC). This technique utilizes the learned model to compute quantum control parameters in a closed-loop simulation. Then, the optimized control input is given to a physical quantum system in an open-loop fashion. Simulations show modelpredictive quantum control to be more efficient than the current state-of-the-art, quantum optimal control, when sequential quadratic programming (SQP) is used to solve each control problem.
INDEX TERMS: Quantum Hamiltonian learning | quantum process tomography | quantum control | quantum consensus | quantum networks | quantum computing
مقاله انگلیسی
7 A graphics-based digital twin framework for computer vision-based post-earthquake structural inspection and evaluation using unmanned aerial vehicles
یک چارچوب دیجیتال دوقلوی مبتنی بر گرافیک برای بازرسی و ارزیابی ساختاری پس از زلزله مبتنی بر بینایی کامپیوتری با استفاده از وسایل نقلیه هوایی بدون سرنشین-2022
Rapid structural inspections and evaluations are critical after earthquakes. Computer vision-based methods have attracted the interest of researchers for their potential to be rapid, safe, and objective. To provide an end-to-end solution for computer vision-based post-earthquake inspection and evaluation of a specific as-built structure, the concepts of physics-based graphics model (PBGM) and digital twin (DT) are combined to develop a graphics-based digital twin (GBDT) framework. The GBDT framework comprises a finite element (FE) model and a computer graphics (CG) model whose state is informed by the FE analysis, representing the state of the structure before and after an earthquake. The CG model is first created making use of the FE model and the photographic survey of the structure, yielding the virtual counterpart of the as-built structure quickly and accurately. Then damage modelling approaches are proposed to predict the location and extent of structural and nonstructural damage under seismic loading, from which photographic representation of the predicted damage is realized in the CG model. The effectiveness of the GBDT framework is demonstrated using a five-story reinforced concrete benchmark building through the design and assessment of various UAV (Unmanned Aerial Vehicle) inspection trajectories for post-earthquake scenarios. The results demonstrate that the proposed GBDT framework has significant potential to enable rapid structural inspection and evaluation, ultimately leading to more efficient allocation of scarce resources in a post-earthquake setting.
keywords: بینایی کامپیوتر | مهندسی زلزله | دوقلو دیجیتال | ارزیابی پس از زلزله | دوقلو دیجیتال مبتنی بر گرافیک | مدل گرافیکی مبتنی بر فیزیک | Computer vision | Earthquake engineering | Digital twin | Post-earthquake assessment | Graphics-based digital twin | Physics-based graphics model
مقاله انگلیسی
8 یک اسکریپت Matlab برای آنالیز مورفومتریک رودخانه‌ها، کانال‌ها و دره‌های روی زمینی، زیرآبی و فرا زمینی
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 29
ویژگی های مورفومتریک نقش مهمی در طبقه بندی و مدل سازی سیستم های رودخانه ای دارند. تمرکز تحقیقات گذشته بر شباهت‌ بین سیستم‌های زیرآبی و فرازمینی ناشناخته و سیستم‌های رودخانه‌ای رو زمینی است، اما اکنون مطالعات جزئی و دقیق دره و کانال زیرآبی در دریاچه‌ها، مخازن، اقیانوس‌ها و سیستم‌های فرازمینی افزایش یافته است. در این مطالعات، اغلب فقط چند ویژگی مورفومتریک (به عنوان مثال، شیب بستر، پهنای کرانه، شعاع خط مرکزی در نوک خم، عمق کرانه‌) در نظر گرفته می شد، که علت آن فقدان ابزاری کارآمد برای تعیین این ویژگی‌ها بود. در این راستا، یک اسکریپت Matlab ساده برای تعیین مهم‌ترین ویژگی‌های مورفومتریک رودخانه‌ها، کانال‌ها و دره‌های رو زمینی، زیرآبی و فرازمینی ارائه شد. تنها ورودی‌های مورد نیاز این اسکریپت ، خاکریز یا تاج‌های کناره خاکریز است که تعریف خط مرکزی را به‌عنوان مبنای سیستم مرجع خمیده خطی کانال محور امکان‌پذیر می‌ کند و به محاسبه ویژگی‌های پلان‌فرم (به عنوان مثال، عرض کامل، انحنای تدریجی متغیر، سینوسی) می پردازد. در صورتی که داده‌های رقومی ارتفاع بیومتری یا توپوگرافی وجود داشته باشد و قابل تبدیل به سیستم مرجع خمیده خطی کانال‌مرکز باشند، بنابراین امکان تعیین شیب بستر طولی و ویژگی‌های بیشتر مورفومتریک در سطح مقطع های عرضی (به عنوان مثال، عمق کرانه، سطح مقطع، و شیب های کناره ها یا سیلاب ها) فراهم می شود. این اسکریپت به عنوان مثال بر دره زیر آبی در دریاچه کنستانس اجرا شد. این اسکریپت ابزاری کارآمد برای آنالیز مقدار روزافزون مدل‌های ارتفاعی دیجیتال (DEMs) در رودخانه‌ها، کانال‌ها و دره‌های رو زمینی، زیرآبی و فرازمینی است. این اسکریپت به ویژه برای سیستم‌های زیر آبی که درک آن ها ضعیف است، مناسب بوده و به درک بزرگترین سیستم‌های دره و کانال کمک می‌کند.
کلمات کلیدی: رانندگی خودکار | محلی سازی سطح لاین | تشخیص لاین | GNSS | GPS | تطبیق نقشه
مقاله ترجمه شده
9 Random Telegraph Noise of a 28-nm Cryogenic MOSFET in the Coulomb Blockade Regime
نویز تصادفی تلگراف یک ماسفت برودتی 28 نانومتری در رژیم بلوک کولن-2022
We observe rich phenomena of two-level random telegraph noise (RTN) from a commercial bulk 28-nm p-MOSFET (PMOS) near threshold at 14 K, where a Coulomb blockade (CB) hump arises from a quantum dot (QD) formed in the channel. Minimum RTN is observed at the CB hump where the high-current RTN level dramatically switches to the low-current level. The gate-voltage dependence of the RTN amplitude and power spectral density match well with the transconductance from the DC transfer curve in the CB hump region. Our work unequivocally captures these QD transport signatures in both current and noise, revealing quantum confinement effects in commercial short-channel PMOS even at 14 K, over 100 times higher than the typical dilution refrigerator temperatures of QD experiments (<100 mK). We envision that our reported RTN characteristics rooted from the QD and a defect trap would be more prominent for smaller technology nodes, where the quantum effect should be carefully examined in cryogenic CMOS circuit designs.
Index Terms: 28-nm CMOS | cryogenic CMOS | random telegraph noise | quantum dot | Coulomb blockade.
مقاله انگلیسی
10 LoRaWAN-Based IoT System Implementation for Long-Range Outdoor Air Quality Monitoring
پیاده سازی سیستم اینترنت اشیاء مبتنی بر LoRaWAN برای نظارت بر کیفیت هوای خارج از منزل در محدوده بلند-2022
This study proposes a smart long-range (LoRa) sensing node to timely collect the air quality in- formation and update it on the cloud. The developed long-range wide area network (LoRaWAN)- based Internet of Things (IoT) air quality monitoring system (AQMS), hereafter called LoRaWAN- IoT-AQMS, was deployed in an outdoor environment to validate its reliability and effectiveness. The system is composed of multiple sensors (NO2, SO2, CO2, CO, PM2.5, temperature, and hu- midity), Arduino microcontroller, LoRa shield, LoRaWAN gateway, and The Thing Network (TTN) IoT platform. The LoRaWAN-IoT-AQMS is a standalone system powered continuously by a rechargeable battery with a photovoltaic solar panel via a solar charger shield for sustainable operation. Our system simultaneously gathers the considered air quality information by using the smart sensing unit. Then, the system transmits the information through the gateway to the TTN platform, which is integrated with the ThingSpeak IoT server. This action updates the collected data and displays these data on a developed Web-based dashboard and a Graphical User Interface (GUI) that uses the Virtuino mobile application. Thus, the displayed information can be easily accessed by users via their smartphones. The results obtained by the developed LoRaWAN-IoT- AQMS are validated by comparing them with experimental results based on the high- technology Aeroqual air quality monitoring devices. Our system can reliably monitor various air quality indicators and efficiently transmit the information in real time over the Internet.
keywords: پایش کیفیت هوا | Air quality monitoring | Iot lora lorawan | TTN ThingSpeak Virtuino
مقاله انگلیسی
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بازدید امروز: 2021 :::::::: بازدید دیروز: 0 :::::::: بازدید کل: 2021 :::::::: افراد آنلاین: 81