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ردیف | عنوان | نوع |
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1 |
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 |
2 |
In-situ optimization of thermoset composite additive manufacturing via deep learning and computer vision
بهینه سازی درجای تولید افزودنی کامپوزیت ترموست از طریق یادگیری عمیق و بینایی کامپیوتری-2022 With the advent of extrusion additive manufacturing (AM), fabrication of high-performance thermoset com-
posites without the need of tooling has become a reality. However, finding an optimal set of printing parameters
for these thermoset composites during extrusion requires tedious experimentation as composite ink properties
can vary significantly with respect to environmental parameters such as temperature and relative humidity.
Addressing this challenge, this study presents a novel optimization framework that utilizes computer vision and
deep learning (DL) to optimize the calibration and printing processes of thermoset composite AM. Unlike
traditional DL models where printing parameters are determined prior to printing, our proposed framework
dynamically and autonomously adjusts the printing parameters during extrusion. A novel DL integrated extrusion
AM system is developed to determine the optimal printing parameters including print speed, road width, and
layer height for a given composite ink. This closed loop system is consisted of a computer communicating with an
extrusion AM system, a camera to perform in-situ imaging and several high accuracy convolution neural net-
works (CNNs) selecting the ideal process parameters for composite AM. The results show that our proposed
process optimization framework was able to autonomously determine these parameters for a carbon fiber-
composite ink. Consequently, specimens with complex geometries could be fabricated without visible defects
and with maximum fiber alignment and thus enhancing the mechanical performance of the specimen’s com-
posite material. Moreover, our proposed framework minimizes a labor-intensive procedure required to additively
manufacture thermoset composites by optimizing the extrusion process without any user intervention. keywords: یادگیری عمیق | بینایی کامپیوتر | اکستروژن | پرینت سه بعدی کامپوزیت | Deep learning | Computer vision | Extrusion | Composite 3D printing |
مقاله انگلیسی |
3 |
An exploration of local rules to map spawning processes to regular hardware architectures
کاوشی در قوانین محلی برای نگاشت فرآیندهای تخم ریزی به معماری های سخت افزاری معمولی-2022 This thesis presents an exploration of population growth via simulation in software to ascertain if a massively parallel hardware system can manage applications running within.
Task execution happens dynamically and is controlled by the growth mechanism implementing efficient mapping in simulation.
Algorithms that provide population simulation models are often inspired by those
evidenced in biology and in particular those of cellular automata and L-systems. These
algorithms are of particular interest due to their complexity and self-replication and
recent research has shown that it is the refinement of the biological methodology that
has resulted in their complexity. Further to this, adaptation of the design has moved the
algorithm on towards being able to organize and build itself from a single cell. A growth
model is utilized in software systems to provide production of meaningful data. The
development of bio-inspired software is constrained by using contemporary processor
architectures. |
مقاله انگلیسی |
4 |
عوامل تعیین کننده باز بودن کسب و کار در فرآیندهای نوآوری
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 6 - تعداد صفحات فایل doc فارسی: 13 مفهوم نوآوری باز نه تنها به عنوان یک موضوع مطالعه در دانشگاهیان، بلکه به عنوان چارچوبی برای توسعه مدل های جدید مدیریت کسب و کار به اهمیت ویژه ای دست یافته است. این مقاله به بررسی عوامل تعیین کننده یکی از ابعاد نوآوری باز مرتبط با استفاده از دانش خارجی برای توسعه فرآیندهای نوآوری تجاری می پردازد. تجزیه و تحلیل بر اساس ریز داده های توسعه و نوآوری فناوری بررسی EDIT 2015 - 2016 انجام شده توسط آژانس آماری کلمبیا (DANE) انجام شده است. برای این منظور، معیاری که میزان باز بودن شرکت را در رابطه با استفاده از منابع اطلاعاتی خارجی برای توسعه فعالیتهای نوآورانه نشان میدهد، معرفی شده است. متغیرهای مرتبط با قابلیتهای فنآوری شرکت، موانع نوآوری و استراتژی مناسببودن به عنوان عوامل تعیینکننده در نظر گرفته میشوند.
کلیدواژه ها: نوآوری باز | منابع اطلاعاتی | تحقیق و توسعه | استراتژی های مناسب سازی |
مقاله ترجمه شده |
5 |
A holistic approach to health and safety monitoring: Framework and technology perspective
رویکردی جامع برای نظارت بر سلامت و ایمنی: چارچوب و دیدگاه فناوری-2022 Existing H&S monitoring methods are manual, cumbersome, time consuming and issues with
safety compliance and use of PPE remain a concern. With the existing manual H&S processes,
there are significant delays and, in some cases, even failure to report incidences, resulting in no or
slow improvements to safety. This paper proposes a prototype PPE access monitoring system
which combines smart PPE and an indoor/outdoor personnel location monitoring system. The
paper also proposes a generic framework to be used for smart gateway services within a
manufacturing site to augment and enable smart PPE, separating areas of high and low risk. The
prototype automated PPE detection gate presents a practical use of the framework and demon-
strates a suitable method for assessing workforce/visitor PPE compliance. Its secondary function
is to act as a location waypoint system to support other location tracking methods, identified in
the literature and throughout the testing protocol. The system could be further adapted to support
augmented personnel within the Operator 4.0 paradigm to improve site safety, monitoring and
control. keywords: اینترنت اشیا | تجهیزات حفاظت فردی | اپراتور 4.0 | انطباق با PPE | چارچوب | RFID | Internet of things | Personal protective equipment | Operator 4.0 | PPE compliance | Framework | RFID |
مقاله انگلیسی |
6 |
Evaluating computing performance of deep neural network models with different backbones on IoT-based edge and cloud platforms
ارزیابی عملکرد محاسباتی مدلهای شبکه عصبی عمیق با ستون فقرات مختلف در بسترهای لبه و ابری مبتنی بر اینترنت اشیا-2022 This paper focuses on evaluating and predicting the computing performance of different archi-
tectures of deep neural network models (DNNs) in cross-platform and cross-inference frame-
works. We test nearly 30 typical DNN models for image recognition on Google Colab cloud
computing platform and Intel neural compute stick 2 embedded edge computing platform and
record the computational performance metrics i.e. the Top-N accuracy, model complexity,
computational complexity, inference time, memory usage, and so on. We compare and analyze
these performance parameters with the previous workstation equipped with NVIDIA Titan X
Pascal and an embedded system based on NVIDIA Jetson TX1 board to evaluate the inference
efficiency of different DNN models using different inference frameworks. The methods of ANOVA
are adopted to quantify the differences between the models. A combination method of cluster
analysis and regression analysis is proposed to find the similar inference time variation processes
across models, which can be used to predict the inference results of unknown models. These
presented results will contribute to better deployment and application of resource-constrained
DNN models on the heterogeneous high-performance computing platform. keywords: شبکه های عصبی عمیق | سکوهای متقابل | چارچوب های استنتاج متقابل | تشخیص تصویر | Deep neural networks | Cross platforms | Cross-inference frameworks | Image recognition |
مقاله انگلیسی |
7 |
Organizational knowledge in the I4:0 using BPMN: a case study
دانش سازمانی در I4:0 با استفاده از BPMN: مطالعه موردی-2021 expert operators is not transferred quickly and easily to newly arrived operators. This sharing of knowledge could help in the faster
adaptation of humans to workstations and could bring the more agile accommodation of artificial intelligence techniques to allow
the self-learning. The Business Process Management (BPM) is a technique which enables the representation and analysis of
processes, has been already mention in the literature as a useful tool that can facilitate the Knowledge Management. A process
repository can be accomplished with BPM, thus promoting agile and fast knowledge transfer in a context where new skills emerge
and must be quickly taken up. This paper intends to show the development of the working instructions maps, with workers’ tacit
knowledge, using the BPMN 2.0, in a chemical industry. This representation allowed the creation of a knowledge’s repository
which will help the company (in a I4.0 environment) to deal with the most existing workforce rotation, thus preserving most of the
knowledge within the company itself.
© 2019 The Authors. Published by Elsevier B.V.
Keywords: Knowledge Management | Industry 4.0 | Business Process Management | BPMN 2.0 | Organizational Knowledge |
مقاله انگلیسی |
8 |
Knowledge management and humanitarian organisations in the Asia-Pacific: Practices, challenges, and future pathways
مدیریت دانش و سازمان های بشردوستانه در آسیا و اقیانوس آرام: شیوه ها، چالش ها و مسیرهای آینده-2021 While there is growing recognition amongst humanitarians that knowledge sharing and exchange are essential
components of organisational efficiency and effectiveness, knowledge management processes in many human-
itarian organisations are still inadequate. The review of knowledge management and international relations
literature reveals limited research on the institutional memory of humanitarian organisations. This article aims to
start filling this research gap by examining the use of explicit and tacit knowledge transfer in the humanitarian
sector in the Asia-Pacific. It points to the embryonic stage of knowledge management and the reliance on tacit
knowledge management consistent with the early stage of sector professionalization in the region. It reviews and
analyses existing scholarly literature and manuals and draws on fieldwork interviews with key humanitarian
personnel that primarily focus on natural hazards. The findings suggest institutional memory in the humanitarian
sector remains ad hoc with limited long-term capture. There is a broad tendency in the region to rely on tacit
knowledge transfer – interpersonal relationships and informal decision-making – as the dominant knowledge
management practice. This reliance challenges knowledge management at the institutional level and indicates a
weakness in the institutional memory of humanitarian organisations in the region. Our research raises questions
about how to improve knowledge management practices within humanitarian organisations in the Asia-Pacific
with significant implications for the sector more generally. A recalibration of tacit and explicit knowledge
management would build institutional memory in humanitarian organisations. This requires a dual-track
approach with codified documentation of experiences and greater emphasis on an institutional culture of
knowledge sharing. keywords: آسیا و اقیانوسیه | حافظه نهادی | مدیریت بحران | مدیریت دانش | امور بشردوستانه | حکومت | Asia-pacific | Institutional memory | disaster management | Knowledge management | Humanitarian affairs | governance |
مقاله انگلیسی |
9 |
Benefits of and Obstacles to RPA Implementation in Accounting Firms
مزایا و موانع اجرای RPA در شرکت های حسابداری-2021 This paper describes the concept of a novel research planned to be carried out in Polish accounting firms providing accounting
services to micro and small enterprises. The accounting firms consist of around 36,000 active entities providing services to as many
as about 2 million entrepreneurs. The principal objective of this research is to determine the extent of robotic process automation
in Polish accounting firms, as well as to identify the benefits of and obstacles to its implementation. The research is to be structured
into 6 tasks, while the methods to be applied include a literature review, interviews with the owners and accountants working in
accounting firms, survey methods/pen-and-paper personal interview and computer-assisted web interview, as well as raw data
collection and statistical analysis. The results of a preliminary pilot study in two accounting firms are also presented in the paper.
Keywords: Accounting processes management | Robotic Process Automation | accounting firms |
مقاله انگلیسی |
10 |
Dynamic resilience for biological wastewater treatment processes: Interpreting data for process management and the potential for knowledge discovery
انعطاف پذیری پویا برای فرآیندهای تصفیه بیولوژیکی فاضلاب: تفسیر داده ها برای مدیریت فرآیند و پتانسیل برای کشف دانش-2021 Climate change, population growth and increasing regulation are causing wastewater treatment plants to become
increasingly stressed, especially in countries like the UK, where many of these systems date back to the early part
of the 20th century. Understanding resilience dynamics for these ageing wastewater assets represents a funda-
mental step in classifying multi-dimensional water stressors toward preventing severe pollution incidents. This
paper explores the potential of a novel dynamic resilience approach to assess and predict the dynamic resilience
of biological wastewater treatment based on the separation of stressor events (cause) and process stress (effect) to
consider the deviation from reference conditions. The approach presented provides a fundamental link between
(1) conventional activated sludge modelling methodologies, (2) actual biological wastewater process instrument
data (potential for knowledge discovery) and (3) the characterisation of dynamic resilience in wastewater
treatment processes. Results first present the dynamic resilience approach by modelling simulated shock flow
conditions on an activated sludge plant, then incorporates ten years of wastewater process instrument data to
demonstrate the actual dynamic resilience. The aim is to represent the “dynamic resilience” as self-ordering
windows, a visual knowledge base (three dimensional, heat map), which operational staff can easily interpret.
The outcomes presented suggest that such an approach is feasible and has the potential for real-time identifi-
cation of conditions that result in pollution incidents based on actual historical process instrument data
(knowledge discovery). Also, the methods presented could be extended to develop an improved understanding of
wastewater system resilience under a range of future stressor scenarios. keywords: انعطاف پذیری پویا | مدل سازی تاثیر فرآیند | استرس فرایند | مدل سازی پویا | مدل سازی فاضلاب | Dynamic resilience | Process impact modelling | Process stress | Dynamic modelling | Wastewater modelling |
مقاله انگلیسی |