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تعداد مقالات یافته شده: 542
ردیف عنوان نوع
1 Deep convolutional neural networks-based Hardware–Software on-chip system for computer vision application
سیستم سخت‌افزار-نرم‌افزار روی تراشه مبتنی بر شبکه‌های عصبی عمیق برای کاربرد بینایی ماشین-2022
Embedded vision systems are the best solutions for high-performance and lightning-fast inspection tasks. As everyday life evolves, it becomes almost imperative to harness artificial intelligence (AI) in vision applications that make these systems intelligent and able to make decisions close to or similar to humans. In this context, the AI’s integration on embedded systems poses many challenges, given that its performance depends on data volume and quality they assimilate to learn and improve. This returns to the energy consumption and cost constraints of the FPGA-SoC that have limited processing, memory, and communication capacity. Despite this, the AI algorithm implementation on embedded systems can drastically reduce energy consumption and processing times, while reducing the costs and risks associated with data transmission. Therefore, its efficiency and reliability always depend on the designed prototypes. Within this range, this work proposes two different designs for the Traffic Sign Recognition (TSR) application based on the convolutional neural network (CNN) model, followed by three implantations on PYNQ-Z1. Firstly, we propose to implement the CNN-based TSR application on the PYNQ-Z1 processor. Considering its runtime result of around 3.55 s, there is room for improvement using programmable logic (PL) and processing system (PS) in a hybrid architecture. Therefore, we propose a streaming architecture, in which the CNN layers will be accelerated to provide a hardware accelerator for each layer where direct memory access (DMA) interface is used. Thus, we noticed efficient power consumption, decreased hardware cost, and execution time optimization of 2.13 s, but, there was still room for design optimizations. Finally, we propose a second co-design, in which the CNN will be accelerated to be a single computation engine where BRAM interface is used. The implementation results prove that our proposed embedded TSR design achieves the best performances compared to the first proposed architectures, in terms of execution time of about 0.03 s, computation roof of about 36.6 GFLOPS, and bandwidth roof of about 3.2 GByte/s.
keywords: CNN | FPGA | Acceleration | Co-design | PYNQ-Z1
مقاله انگلیسی
2 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
3 PortiK: A computer vision based solution for real-time automatic solid waste characterization – Application to an aluminium stream
PortiK: یک راه حل مبتنی بر بینایی کامپیوتری برای شناسایی خودکار زباله جامد در زمان واقعی - کاربرد در جریان آلومینیوم-2022
In Material Recovery Facilities (MRFs), recyclable municipal solid waste is turned into a precious commodity. However, effective recycling relies on effective waste sorting, which is still a challenge to sustainable develop- ment of our society. To help the operations improve and optimise their process, this paper describes PortiK, a solution for automatic waste analysis. Based on image analysis and object recognition, it allows for continuous, real-time, non-intrusive measurements of mass composition of waste streams. The end-to-end solution is detailed with all the steps necessary for the system to operate, from hardware specifications and data collection to su- pervisory information obtained by deep learning and statistical analysis. The overall system was tested and validated in an operational environment in a material recovery facility. PortiK monitored an aluminium can stream to estimate its purity. Aluminium cans were detected with 91.2% precision and 90.3% recall, respectively, resulting in an underestimation of the number of cans by less than 1%. Regarding contaminants (i.e. other types of waste), precision and recall were 80.2% and 78.4%, respectively, giving an 2.2% underestimation. Based on five sample analyses where pieces of waste were counted and weighed per batch, the detection results were used to estimate purity and its confidence level. The estimation error was calculated to be within ±7% after 5 minutes of monitoring and ±5% after 8 hours. These results have demon- strated the feasibility and the relevance of the proposed solution for online quality control of aluminium can stream.
keywords: امکانات بازیابی مواد | شناسایی مواد زائد جامد | یادگیری عمیق | شبکه عصبی عمیق | بینایی کامپیوتر | Material recovery facilities | MRF | Solid waste characterization | Deep-learning | Deep neural network | Computer vision
مقاله انگلیسی
4 Post-Quantum Blockchain-Based Data Sharing for IoT Service Providers
به اشتراک گذاری داده های مبتنی بر بلاک چین پسا کوانتومی برای ارائه دهندگان خدمات اینترنت اشیا-2022
Quantum technologies have made significant advances and are likely to lead to important security challenges and threats to networks in the near future. On the other hand, sharing the huge amount of data from the Internet of Things (IoT) in the context of data as a service could provide new revenue streams for infrastructure providers and service providers. However, post-quantum computing exposes the entire data sharing ecosystem to a new set of security risks. In this article, we propose a novel blockchain-based system for data sharing in the post-quantum era. The proposed system facilitates data sharing among multiple organizations while meeting compliance and regulatory requirements via private blockchain. We implemented the proposed architecture and information flow using three blockchain networks (namely Hyperledger Fabric, Ethereum, and Quorum) and selected NTRU as our quantum resistant security algorithm (QRSA) to compare the parallelization performance of Toom-Cook’s and Karatsuba’s computation methods. Experimental results show that parallel computation has a positive impact when the security level of QRSAs is lowered, and the transaction time savings is almost 50 percent in favor of Quorum. Finally, we outline the main challenges and potential solutions.
مقاله انگلیسی
5 Publish–Subscribe approaches for the IoT and the cloud: Functional and performance evaluation of open-source systems
رویکردهای انتشار – اشتراک برای اینترنت اشیا و ابر: ارزیابی عملکرد و کارایی سیستم‌های منبع باز-2022
Publish–Subscribe systems facilitate the communication between services or applications. A typical system comprises the publisher, the subscriber, and the broker but, may also feature message queues, databases, clusters, or federations of brokers, apply message delivery policies, communication protocols, security services, and a streaming API. Not all these features are supported by all systems or, others may be optional. As a result, there is no common ground for the comparison of Publish–Subscribe systems. This paper presents a critical survey and taxonomy of Publish–Subscribe systems, of their design features and technologies. The concepts of message queuing, publish–subscribe systems, and publish–subscribe protocols for the cloud and the IoT are discussed and clarified. The respective evaluation is about seven state-of-the-art open-source systems namely, Apache Kafka, RabbitMQ, Orion-LD, Scorpio, Stellio, Pushpin, and Faye. For the sake of fair comparison, a minimum set of common features is identified in all systems. All systems are evaluated and compared in terms of functionality and performance under real-case scenarios.
keywords: صف پیام | انتشار – اشتراک | معیارها | ارزیابی | Message queue | Publish–subscribe | Benchmarks | Evaluation
مقاله انگلیسی
6 A Quantum-Inspired Classifier for Early Web Bot Detection
یک طبقه بندی الهام گرفته از کوانتومی برای تشخیص زودهنگام ربات وب-2022
This paper introduces a novel approach, inspired by the principles of Quantum Computing, to address web bot detection in terms of real-time classification of an incoming data stream of HTTP request headers, in order to ensure the shortest decision time with the highest accuracy. The proposed approach exploits the analogy between the intrinsic correlation of two or more particles and the dependence of each HTTP request on the preceding ones. Starting from the a-posteriori probability of each request to belong to a particular class, it is possible to assign a Qubit state representing a combination of the aforementioned probabilities for all available observations of the time series. By leveraging the underlying mathematical details of superposition and entanglement on specific subsequences, it is possible to devise a measure of membership to each class, thus enabling the system to take a reliable decision when a sufficient level of confidence is met or to continue with additional observations. The results reported in this paper objectively show the effectiveness of our quantum-inspired algorithm which outperforms other state-of-the-art approaches, including our own one based on the Sequential Probability Ratio Test.
Index Terms— Quantum-inspired computing | bot detection | sequential classification | early decision | multinomial classification | multivariate sequence classification.
مقاله انگلیسی
7 The myth of workforce reduction efficiency: The performativity of accounting language
اسطوره کاهش بهره وری نیروی کار: عملکرد زبان حسابداری-2021
This paper draws on Austin’s conceptualization of performativity to show how the accounting strategies implemented before a workforce reduction can contribute to performing the myth of workforce reduction efficiency. To address this issue, we use both quantitative and qualitative methods. First, through quantitative analyses on a sample of 117 workforce reductions announced by 101 French listed firms from 2007 to 2012, we shed light how, by not taking accounting strategies into account in their models, prior mainstream studies may have conveyed false knowledge about improved performances after the operation and performed the workforce reduction efficiency supported by economic theories. Second, through a case study, we provide an in-depth illustration of the performativity effect of these accounting strategies and more precisely of downward earnings management, which can be considered a calculation act that contributes to performing the myth of the efficiency of these operations. Overall, this paper contributes to the workforce reduction literature by providing a critical illustration of how accounting numbers construct efficiency through the performative role given to earnings management. It also con- tributes to the critical accounting project by notably participating in the debate on the use of quantitative and mixed research methodologies in the critical accounting project.
keywords: کاهش نیروی کار | حسابداری انتقادی | مدیریت درآمد | افتخار | زبان حسابداری | Workforce reductions | Critical accounting | Earnings management | Performativity | Accounting language
مقاله انگلیسی
8 A multi-objective robust optimization model for upstream hydrocarbon supply chain
یک مدل بهینه سازی قوی چند هدفه برای زنجیره تأمین هیدروکربن بالادست-2021
The hydrocarbon supply chain (HCSC) is a significant part of the world’s energy sector. The energy market has experienced erratic behavior over the last few years results in financial risks such as exceeding certain limits of the budget or not achieving the desired levels of cash in-flow, i.e., revenue. In this work, robust optimization and multi-objective mathematical programming are used to develop a model that eliminates or at least mitigates the impact of uncertain market behavior. Robust optimization provides tactical plans that are feasible and robust over market scenarios. The model assesses the trade-offs between alternatives and guides the decision-maker towards the effective management of the HCSC. The economic objectives are to minimize total cost and maximize revenue, while the non-economic objective is to minimize the depletion rate. The model considers the environmental aspect by limiting the emission of CO2 and the sustainability aspect by reducing the depletion rate of natural resources. Uncertain behavior of the oil market is modeled on scenario representation. A case study based on real data from Saudi Arabia HCSC is provided to demonstrate the model’s practicality, and a sensitivity analysis is conducted to provide some managerial insights. The results indicate that Saudi Arabia can cover its entire expenditure, break-evenpoint, by producing oil at 7.18 MMbbld and gas at 3,543.48 MMcftd. Besides, the robust approach provides a preferred plan with the highest cash inflow and the lowest sustainability over other approaches, e.g., deterministic, stochastic, and risk-based. The differences show that the robust model increases oil production to compensate for the variability of the scenario.
KEYWORDS: Hydrocarbon supply chain | Multi-objective optimization | Robust optimization | Scenario-Based Optimization | Tactical planning
مقاله انگلیسی
9 Linking biodiversity into national economic accounting
پیوند تنوع زیستی به حسابداری اقتصادی ملی-2021
Biodiversity underpins the supply of ecosystem services essential for well-being and economic development, yet biodiversity loss continues at a substantial rate. Linking biodiversity indicators with national economic accounts provides a means of mainstreaming biodiversity into economic planning and monitoring processes. Here we examine the various strategies for biodiversity indicators to be linked into national economic accounts, specif- ically the System of Environmental-Economic Accounts Experimental Ecosystem Accounting (SEEA EEA) framework. We present what has been achieved in practice, using various case studies from across the world. These case studies demonstrate the potential of economic accounting as an integrating, mainstreaming frame- work that explicitly considers biodiversity. With the right indicators for the different components of biodiversity and scales of biological organisation, this can directly support more holistic economic planning approaches. This will be a significant step forward from relying on the traditional indicators of national economic accounts to guide national planning. It is also essential if society’s objectives for biodiversity and sustainable development are to be met.
keywords: سیستم حسابداری اقتصادی محیط زیست | رادیو | تنوع زیستی | خدمات محیط زیستی | توسعه پایدار | System of environmental economic accounting | SEEA-EEA | Biodiversity | Ecosystem services | Sustainable development
مقاله انگلیسی
10 Sourcing under competition: The implications of supplier capital constraint and supply chain co-opetition
تأمین منابع تحت رقابت: پیامدهای محدودیت سرمایه تأمین کننده و رقابت همزمان زنجیره تأمین-2021
This paper investigates a manufacturer’s strategic sourcing and supplier financing strategies under downstream horizontal competition and co-opetition. When the manufacturer and the rival engage in a simultaneous-move game, we show that the manufacturer should always exclusively source from and offer finance to a cost-advantageous supplier if the latter is severely capital- constrained. If the supplier is moderately capital-constrained, however, the manufacturer’s preferred sourcing strategy depends on the type of the backup supplier, which leads to a horizontal competition or co-opetition structure. We also examine the robustness of the results by studying the sequential-move game.
Keywords: Supply chain finance | Financing supplier | Dual sourcing | Co-opetition
مقاله انگلیسی
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