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تعداد مقالات یافته شده: 661
ردیف عنوان نوع
1 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
2 The physical and mechanical properties for flexible biomass particles using computer vision
خواص فیزیکی و مکانیکی ذرات زیست توده انعطاف پذیر با استفاده از بینایی کامپیوتری-2022
The combustion and fluidization behavior of biomass depend on the physical properties (size, morphology, and density) and mechanical performances (elastic modulus, Poisson’s ratio, tensile strength and failure strain), but their quantitative models have rarely been focused in previous researchers. Hence, a static image measurement for particle physical properties is studied. Combining the uniaxial tension and digital image correlation tech- nology, the dynamic image measurement method for the mechanical properties is proposed. The results indicate that the average roundness, rectangularity, and sphericity of present biomass particles are 0.2, 0.4, and 0.16, respectively. The equivalent diameter and density obey the skewed normal distribution. The tensile strength and failure stress are sensitive to stretching rate, fiber size and orientation. The distribution intervals of elastic modulus and Poisson’s ratio are 30–600 MPa and 0.25–0.307, respectively. The stress–strain curves obtained from imaging experiments agree well with the result of finite element method. This study provides the operating parameters for the numerical simulation of particles in the fluidized bed and combustor. Furthermore, the computer vision measurement method can be extended to the investigations of fossil fuels.
keywords: ذرات زیست توده | مشخصات فیزیکی | اجرای مکانیکی | تست کشش | آزمایش تصویربرداری | بینایی کامپیوتر | Biomass particle | Physical properties | Mechanical performances | Tensile testing | Imaging experiment | Computer vision
مقاله انگلیسی
3 Image2Triplets: A computer vision-based explicit relationship extraction framework for updating construction activity knowledge graphs
Image2Triplets: چارچوب استخراج رابطه صریح مبتنی بر بینایی ماشین برای به روز رسانی نمودارهای دانش فعالیت های ساخت-2022
Knowledge graph (KG) is an effective tool for knowledge management, particularly in the architecture, engineering and construction (AEC) industry, where knowledge is fragmented and complicated. However, research on KG updates in the industry is scarce, with most current research focusing on text-based KG updates. Considering the superiority of visual data over textual data in terms of accuracy and timeliness, the potential of computer vision technology for explicit relationship extraction in KG updates is yet to be ex- plored. This paper combines zero-shot human-object interaction detection techniques with general KGs to propose a novel framework called Image2Triplets that can extract explicit visual relationships from images to update the construction activity KG. Comprehensive experiments on the images of architectural dec- oration processes have been performed to validate the proposed framework. The results and insights will contribute new knowledge and evidence to human-object interaction detection, KG update and construc- tion informatics from the theoretical perspective. © 2022 Elsevier B.V. All rights reserved.
keywords: یادگیری شات صفر | تشخیص تعامل انسان و شی | بینایی ماشین| استخراج رابطه صریح | نمودار دانش | Zero-shot learning | Human-object interaction detection | Computer vision | Explicit relationship extraction | Knowledge graph
مقاله انگلیسی
4 Human perception of color differences using computer vision system measurements of raw pork loin
درک انسان از تفاوت‌های رنگی با استفاده از اندازه‌گیری‌های سیستم بینایی کامپیوتری گوشت خوک خام-2022
In the food industry, product color plays an important role in influencing consumer choices. Yet, there remains little research on the human ability to perceive differences in product color; therefore, preference testing is subjective rather than based on quantitative colors. Using a de-centralized computer-aided systematic discrim- ination testing method, we ascertain consumers’ ability to discern between systematically varied colors. As a case study, the colors represent the color variability of fresh pork as measured by a computer vision system. Our results indicate that a total color difference (ΔE) of approximately 1 is discriminable by consumers. Furthermore, we ascertain that a change in color along the b*-axis (yellowness) in CIELAB color space is most discernable, followed by the a*-axis (redness) and then the L*-axis (lightness). As developed, our web-based discrimination testing approach allows for large scale evaluation of human color perception, while these quantitative findings on meat color discrimination are of value for future research on consumer preferences of meat color and beyond.
keywords: تست تبعیض | تست مثلث | ترجیح رنگ | ظاهر غذا | رنگ گوشت | Discrimination testing | Triange test | Color preference | Food appearance | Meat color
مقاله انگلیسی
5 Computer vision-based illumination-robust and multi-point simultaneous structural displacement measuring method
روش اندازه گیری جابجایی ساختاری همزمان با روشنایی مبتنی بر بینایی کامپیوتری-2022
Computer vision-based techniques for structural displacement measurement are rapidly becoming popular in civil structural engineering. However, most existing computer vision-based displace- ment measurement methods require man-made targets for object matching or tracking, besides usually the measurement accuracies are seriously sensitive to the ambient illumination variations. A computer vision-based illumination robust and multi-point simultaneous measuring method is proposed for structural displacement measurements. The method consists of two part, one is for segmenting the beam body from its background, the segmentation is perfectly carried out by fully convolutional network (FCN) and conditional random field (CRF); another is digital image cor- relation (DIC)-based displacement measurement. A simply supported beam is built in laboratory. The accuracy and illumination robustness are verified through three groups of elaborately designed experiments. Due to the exploitation of FCN and CRF for pixel-wise segmentation, numbers of locations along with the segmented beam body can be chosen and measured simul- taneously. It is verified that the method is illumination robust since the displacement measure- ments are with the smallest fluctuations to the illumination variations. The proposed method does not require any man-made targets attached on the structure, but because of the exploitation of DIC in displacement measurement, the regions centered on the measuring points need to have texture feature.
keywords: پایش سلامت سازه | اندازه گیری جابجایی | بینایی کامپیوتر | یادگیری عمیق | تقسیم بندی شی | همبستگی تصویر دیجیتال | Structural health monitoring | Displacement measurement | Computer vision | Deep learning | Object segmentation | Digital image correlation
مقاله انگلیسی
6 Computer vision for solid waste sorting: A critical review of academic research
بینایی کامپیوتری برای تفکیک زباله جامد: مروری انتقادی تحقیقات دانشگاهی-2022
Waste sorting is highly recommended for municipal solid waste (MSW) management. Increasingly, computer vision (CV), robotics, and other smart technologies are used for MSW sorting. Particularly, the field of CV- enabled waste sorting is experiencing an unprecedented explosion of academic research. However, little atten- tion has been paid to understanding its evolvement path, status quo, and prospects and challenges ahead. To address the knowledge gap, this paper provides a critical review of academic research that focuses on CV-enabled MSW sorting. Prevalent CV algorithms, in particular their technical rationales and prediction performance, are introduced and compared. The distribution of academic research outputs is also examined from the aspects of waste sources, task objectives, application domains, and dataset accessibility. The review discovers a trend of shifting from traditional machine learning to deep learning algorithms. The robustness of CV for waste sorting is increasingly enhanced owing to the improved computation powers and algorithms. Academic studies were un- evenly distributed in different sectors such as household, commerce and institution, and construction. Too often, researchers reported some preliminary studies using simplified environments and artificially collected data. Future research efforts are encouraged to consider the complexities of real-world scenarios and implement CV in industrial waste sorting practice. This paper also calls for open sharing of waste image datasets for interested researchers to train and evaluate their CV algorithms.
keywords: زباله جامد شهری | تفکیک زباله | بینایی ماشین | تشخیص تصویر | یادگیری ماشین | یادگیری عمیق | Municipal solid waste | Waste sorting | Computer vision | Image recognition | Machine learning | Deep learning
مقاله انگلیسی
7 Towards automatic waste containers management in cities via computer vision: containers localization and geo-positioning in city maps
به سمت مدیریت خودکار ظروف زباله در شهرها از طریق بینایی کامپیوتری: محلی سازی ظروف و موقعیت جغرافیایی در نقشه های شهر-2022
This paper describes the scientific achievements of a collaboration between a research group and the waste management division of a company. While these results might be the basis for several practical or commercial developments, we here focus on a novel scientific contribution: a methodology to automatically generate geo- located waste container maps. It is based on the use of Computer Vision algorithms to detect waste containers and identify their geographic location and dimensions. Algorithms analyze a video sequence and provide an automatic discrimination between images with and without containers. More precisely, two state-of-the-art object detectors based on deep learning techniques have been selected for testing, according to their perfor- mance and to their adaptability to an on-board real-time environment: EfficientDet and YOLOv5. Experimental results indicate that the proposed visual model for waste container detection is able to effectively operate with consistent performance disregarding the container type (organic waste, plastic, glass and paper recycling,…) and the city layout, which has been assessed by evaluating it on eleven different Spanish cities that vary in terms of size, climate, urban layout and containers’ appearance.
keywords: Waste container localization | Deep Learning | Computer Vision | Object detection
مقاله انگلیسی
8 Using social media photos and computer vision to assess cultural ecosystem services and landscape features in urban parks
استفاده از عکس های رسانه های اجتماعی و بینایی کامپیوتری برای ارزیابی خدمات اکوسیستم فرهنگی و ویژگی های چشم انداز در پارک های شهری-2022
Urban parks are important public places that provide an opportunity for city dwellers to interact with nature. In recent years, social media data have become a promising data source for the assessment of cultural ecosystem services (CES) and landscape features in urban parks. However, it is a challenging task to identify and classify the CES and landscape features from social media photos by manual content analysis. In addition, relatively few studies focused on the differences in landscape preferences between tourists and locals in urban parks. In this study, we used geotagged social media photos from Flickr and computer vision methods (scene recognition, image clustering and image labeling) based on the convolutional neural networks (CNN) and the Google Cloud Vision platform to assess the spatial preferences and landscape preferences (cultural ecosystem services and landscape features) of tourists and locals in the urban parks of Brussels. The spatial analysis results showed that the tourists’ photos were spatially concentrated on well-known parks located in the city center while the locals’ photos were rather spatially dispersed across all parks of the city. We identified 10 main landscape themes (corresponding to 4 CES categories and 10 landscape feature categories) from 20 image clusters by automated image analysis on social media photos. We also noticed that tourists paid more attention to the place identity featured by symbolic sculptures and buildings, while locals showed more interest in local species of plants, flowers, insects, birds, and animals. This research contributes to social media-based user preferences analysis and CES assessment, which could provide insights for urban park planning and tourism management.
keywords: داده های رسانه های اجتماعی | خدمات اکوسیستم فرهنگی | ویژگی های چشم انداز | پارک های شهری | بینایی کامپیوتر | Social media data | Cultural ecosystem services | Landscape features | Urban parks | Computer vision
مقاله انگلیسی
9 Quantum Federated Learning With Decentralized Data
یادگیری فدرال کوانتومی با داده های غیرمتمرکز-2022
Variational quantum algorithm (VQA) accesses the centralized data to train the model, and using distributed computing can significantly improve the training overhead; however, the data is privacy sensitive. In this paper, we propose communication-efficient learning of VQA from decentralized data, which is so-called quantumfederated learning(QFL).Motivated by the classical federated learning algorithm, we improve data privacy by aggregating updates from local computation to share model parameters. Here, aiming to find approximate optima in the parameter landscape, we develop an extension of the conventional VQA. Finally, we deploy onthe TensorFlowQuantum processor within variational quantumtensor networks classifiers, approximate quantum optimization for the Ising model, and variational quantum eigensolver for molecular hydrogen. Our algorithm demonstrates model accuracy from decentralized data, which have higher performance on near-term processors. Importantly, QFL may inspire new investigations in the field of secure quantum machine learning.
Index Terms: Quantum algorithm | quantum computing | quantum information | quantum machine learning.
مقاله انگلیسی
10 پیاده سازی یک راه حل حسابداری هزینه هوش تجاری در یک محیط مراقبت های بهداشتی
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 6 - تعداد صفحات فایل doc فارسی: 12
محیط سیستم سلامت در پرتغال یک نگرانی دائمی برای جامعه ما است. با توجه به این موضوع، مانند هر بخش دیگری، منطقه بیمارستان دارای ساختار پیچیده ای است که حجم زیادی از اطلاعات را در خود جای داده است که فرآیند تصمیم گیری را دشوار می کند. با این کار، نیاز به بهبود مدیریت خدمات و منابع موسسات بهداشتی وجود دارد. با در نظر گرفتن این موضوع، راه حل شامل تبدیل سیستم فعلی با کمک سیستم های اطلاعاتی برای پیاده سازی می شود. بنابراین، ایده پیاده‌سازی سیستم‌های اطلاعاتی که از هوش تجاری در بیمارستان‌ها استفاده می‌کنند، مطرح می‌شود، تمرکز این پروژه کمک به مدیران در تحلیل حسابداری تحلیلی است. با مشارکت Centro Hospitalar Universitário do Porto، تصمیم گرفته شد تا استفاده از هوش تجاری را با هدف پیاده سازی یک راه حل تکمیلی برای طرح حسابداری بهای تمام شده موجود، با هدف بهبود کارایی و ارائه ابزارهای جدید مدیریت به مدیران مورد بررسی قرار دهیم.
کلمات کلیدی: حسابداری بهای تمام شده | هوش تجاری | مراقبت های بهداشتی
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