با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
ردیف | عنوان | نوع |
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71 |
Patenting trends in biometric technology of the Big Five patent offices
ثبت اختراعات در فناوری بیومتریک دفاتر ثبت اختراع پنج بزرگ-2021 We examined the overall trends in biometric technology based on patent documents. Using PATSTAT database, we extracted 37,462 patent documents applied at the Big Five patent offices between 1990 and 2016. Latent Dirichlet allocation was applied to their abstracts to observe annual trends by topic. Our results are as follows: Fingerprint-enabled car anti-theft systems have been undergoing rapid technological development since 2014. In response, biometric signal transmitting models are becoming popular owing to concerns about theft of biometric templates. While fingerprint, face, and iris authentication technologies continue to advance, finger vein, voice, and signature authentication technologies are lagging. Use of biometric technologies in financial transactions, server networks, and digital media content security are decreasing as well. A citation analysis discovered key topics and patent applicants: Surprisingly, the quantitative growth rate of topics and the effect on the knowledge network showed an inverse relationship. US firms had the most citations, but fewer backward citations of own work, unlike Japanese companies. We provide practical insights to stakeholders of biometric technology. Keywords: Biometrics | Citation analysis | Latent dirichlet allocation | Patent analysis | echnology trend analysis | Topic modeling |
مقاله انگلیسی |
72 |
Tracking and analysing social interactions in dairy cattle with real-time locating system and machine learning
پیگیری و تجزیه و تحلیل تعاملات اجتماعی در گاوهای شیری با سیستم مکان یابی در زمان واقعی و یادگیری ماشین-2021 There is a need for reliable and efficient methods for monitoring the activity and social behavior in cows, in order to optimize management in modern dairy farms. This research presents an embedded system that could track individual cows using Ultra-wideband technology. At the same time, social interactions between individuals around the feeding area were analyzed with a computer vision module. Detections of the dairy cows’ negative and positive interactions were performed on foreground video stream using a Long-term Recurrent Convolution Networks model. The sensor fusion system was implemented and tested on seven dairy cows during 45 days in an experimental dairy farm. The system performance was evaluated at the feeding area. The real-time locating system based on Ultra-wideband technology reached an accuracy with mean error 0.39 m and standard deviation 0.62 m. The accuracy of detecting the affiliative and agonistic social interactions reached 93.2%. This study demonstrates a potential system for monitoring social interactions between dairy cows.
Keywords: Ultra-wideband | Computer vision | Dairy cows | Social interactions | Machine learning |
مقاله انگلیسی |
73 |
Transcending the silos through project management office: Knowledge transactions, brokerage roles, and enabling factors
فراتر از سیلوها از طریق دفتر مدیریت پروژه: معاملات دانش، نقش کارگزاری، و عوامل توانمند-2021 Organisations often suffer from knowledge flow gaps between operational and strategic management levels,
leaving much knowledge trapped within operations’ boundaries. Prior studies viewed the project management
office (PMO) as a knowledge broker that can enhance the interaction between these levels. However, they take a
single-faceted knowledge brokering perspective that fails to define the specific knowledge brokering roles of the
PMO and offer highly fragmentary evidence on the associated enabling factors. To fill this void, we draw on the
brokerage theory to develop a comprehensive theoretical framework in which we define specific knowledge
brokering roles of the PMO and delineate their enabling factors for facilitating multidirectional knowledge
transactions. We elaborate on three sets of knowledge brokering roles, each of which corresponds to one of three
categories of knowledge transactions. Our model shows how PMOs can broker knowledge trapped in organ-
isational silos by balancing bottom-up experiential learning with top-down deliberate learning while maintaining
horizontal knowledge synchronisation. keywords: شکاف جریان دانش | دفتر مدیریت پروژه | نقش های واسطه گری دانش | Knowledge flow gaps | Project management office | Knowledge brokering roles |
مقاله انگلیسی |
74 |
Consistency matters: Revisiting the structural complexity for supply chain networks
موارد سازگاری: بازبینی پیچیدگی ساختاری برای شبکه های زنجیره تأمین-2021 Modern supply chains are becoming increasingly complex. It is commonly believed that complexity is an impediment to performance, and proactively managing complexity can lead to better supply chain efficiency. However, complexity management has not been well-established and widely implemented in the industry, partly because little effort has been made to develop tools for quantifying the complexity. In this paper, we investigate the structural complexity of supply chain networks and aim to provide a supplement to the complexity measures in the literature. For supply chain networks, it is argued that a proper complexity measure should guarantee the consistency requirement, i.e., the complexity of a network should be higher than the complexity of its subnetwork. This is because the network has more members and interactions and normally incurs higher maintenance cost and imposes higher difficulties of management. With this argument, the contributions are three-fold. Firstly, by visualizing supply chain networks as directed graphs, this paper examines the consistency of six existing complexity measures with rigorous proofs. Unfortunately, only two of them are consistent. We point out that although the consistency check is only valid for unweighted graphs, it still has practical implications because it is prevailing in the literature to represent a large-scale supply chain network as an unweighted graph. Secondly, this paper shows those consistent measures are not suitable in multiple scenarios of supply chain networks because they may generate misleading results. Thirdly, to overcome their limitations, a consistent measure that leads to reasonable conclusions is proposed. Extensive numerical experiments are conducted to verify the usefulness of the proposed measure.© 2021 Elsevier B.V. All rights reserved. Keywords: Structural complexity | Consistency | Supply chain network | Entropy function |
مقاله انگلیسی |
75 |
Asynchrony Between Individual and Government Actions Accounts for Disproportionate Impact of COVID-19 on Vulnerable Communities
ناهمزمانی بین اقدامات فردی و دولتی تاثیر نامتناسب COVID-19 بر جوامع آسیب پذیر-2021 Introduction: Previously estimated effects of social distancing do not account for changes in individual behavior before the implementation of stay-at-home policies or model this behavior in relation to the burden of disease. This study aims to assess the asynchrony between individual behavior
and government stay-at-home orders, quantify the true impact of social distancing using mobility
data, and explore the sociodemographic variables linked to variation in social distancing practices.
Methods: This study was a retrospective investigation that leveraged mobility data to quantify the
time to behavioral change in relation to the initial presence of COVID-19 and the implementation of
government stay-at-home orders. The impact of social distancing that accounts for both individual
behavior and testing data was calculated using generalized mixed models. The role of sociodemographics in accounting for variation in social distancing behavior was modeled using a 10-fold crossvalidated elastic net (linear machine learning model). Analysis was conducted in April‒July 2020.
Results: Across all the 1,124 counties included in this analysis, individuals began to socially distance at a median of 5 days (IQR=38) after 10 cumulative cases of COVID-19 were confirmed in
their state, with state governments taking a median of 15 days (IQR=1219) to enact stay-at-home
orders. Overall, people began social distancing at a median of 12 days (IQR=817) before their
state enacted stay-at-home orders. Of the 16 studies included in the review, 13 exclusively used government dates as a proxy for social distancing behavior, and none accounted for both testing and
mobility. Using government stay-at-home dates as a proxy for social distancing (10.2% decrease in
the number of daily cases) accounted for only 55% of the true impact of the intervention when compared with estimates using mobility (18.6% reduction). Using 10-fold cross-validation, 23 of 43 sociodemographic variables were significantly and independently predictive of variation in individual
social distancing, with delays corresponding to an increase in a county’s proportion of people without a high school diploma and proportion of racial and ethnic minorities.
Conclusions: This retrospective analysis of mobility patterns found that social distancing behavior
occurred well before the onset of government stay-at-home dates. This asynchrony leads to the
underestimation of the impact of social distancing. Sociodemographic characteristics associated
with delays in social distancing can help explain the disproportionate case burden and mortality
among vulnerable communities.
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مقاله انگلیسی |
76 |
Automated Vision-Based Microsurgical Skill Analysis in Neurosurgery Using Deep Learning: Development and Preclinical Validation
تجزیه و تحلیل خودکار مهارتهای میکروجراحی مبتنی بر بینایی در جراحی مغز و اعصاب با استفاده از یادگیری عمیق: توسعه و اعتبار پیش بالینی-2021 - BACKGROUND/OBJECTIVE: Technical skill acquisition
is an essential component of neurosurgical training.
Educational theory suggests that optimal learning and
improvement in performance depends on the provision of
objective feedback. Therefore, the aim of this study was to
develop a vision-based framework based on a novel representation of surgical tool motion and interactions
capable of automated and objective assessment of microsurgical skill.
- METHODS: Videos were obtained from 1 expert, 6 intermediate, and 12 novice surgeons performing arachnoid dissection in a validated clinical model using a standard operating microscope. A mask region convolutional neural network framework was used to segment the tools present within the operative field in a recorded video frame. Tool motion analysis was achieved using novel triangulation metrics. Performance of the framework in classifying skill levels was evaluated using the area under the curve and accuracy. Objective measures of classifying the surgeons skill level were also compared using the ManneWhitney U test, and a value of P < 0.05 was considered statistically significant. - RESULTS: The area under the curve was 0.977 and the accuracy was 84.21%. A number of differences were found, which included experts having a lower median dissector velocity (P [ 0.0004; 190.38 mse1 vs. 116.38 mse1), and a smaller inter-tool tip distance (median 46.78 vs. 75.92; P [ 0.0002) compared with novices. - CONCLUSIONS: Automated and objective analysis of microsurgery is feasible using a mask region convolutional neural network, and a novel tool motion and interaction representation. This may support technical skills training and assessment in neurosurgery. Key words: Artificial intelligence | Computer vision | Convolutional neural network | Mask RCNN | Microsurgery | Motion-analysis | Neurosurgery |
مقاله انگلیسی |
77 |
Time, space and accounting at Nonantola Abbey (1350-1449)
زمان، مکان و حسابداری در صومعه نونانتولا (1350-1449)-2021 Accounting historians have provided several accounts of monastic life and accountings
role in it, considering important settings such as Montecassino and San Pietro abbeys in
Italy and Durham Cathedral Priory in England. Research has shown how their governance
arrangements and common values enabled the Benedictines to manage their monasteries
in an efficient manner which was essential in tackling the misappropriation of resources
by organisational actors, including abbots. Other studies have shed light on the use of
practical and effective accounting practices by the Benedictines to manage their considerable wealth and pursue their spiritual and temporal goals. Nevertheless, this body of
literature is yet to explicitly consider the dimensions of time and space and their relationship with accounting practices. This study begins to address this oversight by analysing
the surviving accounting records of the Benedictine abbey of Nonantola in northern Italy
from 1350 to 1449. In the accounting books of Nonantola Abbey linear and cyclical conceptions of time coexisted and had an impact on the way in which transactions were
reflected in the accounts. At the same time, the abbey was at the centre of a complex
network of accountabilities which included lay accountants, farmers and the lessees of the
abbeys properties. The main characteristic of this system was not the accuracy of the
records in detailing the assets, liabilities, expenses and revenue of the abbey but the
maintenance of a control system to administer an extensive agricultural network and the
identification of the relationships between the abbey and the stakeholders inhabiting its
space.
keywords: بنیاد | زمان | فضا | حسابداری | ابی | Benedictine | Time | Space | Accounting | Abbey |
مقاله انگلیسی |
78 |
A data management framework for strategic urban planning using blue-green infrastructure
یک چارچوب مدیریت داده برای برنامه ریزی شهری استراتژیک با استفاده از زیرساخت های آبی سبز-2021 Spatial planning of Blue-Green Infrastructure (BGI) should ideally be based on well-evaluated and context
specific solutions. One important obstacle to reach this goal relates to adequate provisioning of data to ensure
good governance of BGI, i.e., appropriate planning, design, construction, and maintenance. This study explores
the gap between data availability and implementation of BGI in urban planning authorities in Sweden. A multi
method approach including brainstorming, semi-structured interviews with urban planners and experts on BGI
and Geographical Information System (GIS), and validating workshops were performed to develop a framework
for structured and user-friendly data collection and use. Identified challenges concern data availability, data
management, and GIS knowledge. There is a need to improve the organisation of data management and the skills
of trans-disciplinary cooperation to better understand and interpret different types of data. Moreover, different
strategic goals require different data to ensure efficient planning of BGI. This calls for closer interactions between
development of strategic political goals and data collection. The data management framework consists of three
parts: A) Ideal structure of data management in relation to planning process, data infrastructure and organisa-
tional structure, and B) A generic list of data needed, and C) The development of structures for data gathering
and access. We conclude that it is essential to develop pan-municipal data management systems that bridge
sectors and disciplines to ensure efficient management of the urban environment, and which is able to support
the involvement of citizens to collect and access relevant data. The framework can assist in such development. keywords: زیرساخت آبی سبز | مدیریت اطلاعات | برنامه ریزی فضایی | برنامه ریزی استراتژیک | مدیریت طوفان | انطباق تغییرات اقلیمی | فضاهای سبز شهری | Blue-green infrastructure | Data management | Spatial planning | Strategic planning | Stormwater management | Climate change adaptation | Urban green spaces |
مقاله انگلیسی |
79 |
A knowledge-intensive adaptive business process management framework
چارچوب مدیریت فرآیند تجاری تطبیقی مبتنی بر دانش-2021 Business process management has been the driving force of optimization and operational efficiency for
companies until now, but the digitalization era we have been experiencing requires businesses to be
agile and responsive as well. In order to be a part of this digital transformation, delivering new levels
of automation-fueled agility through digitalization of BPM itself is required. However, the automation
of BPM cannot be achieved by solely focusing on process space and classical planning techniques. It
requires a holistic approach that also captures the social aspects of the business environment, such as
corporate strategies, organization policies, negotiations, and cooperation. For this purpose, we combine
BPM, knowledge-intensive systems and intelligent agent technologies, and yield one consolidated
intelligent business process management framework, namely agileBPM, that governs the entire BPM
life-cycle. Accordingly, agileBPM proposes a modeling methodology to semantically capture the
business interests, enterprise environment and process space in accordance with the agent-oriented
software engineering paradigm. The proposed agent-based process execution environment provides
cognitive capabilities (such as goal-driven planning, norm compliance, knowledge-driven actions, and
dynamic cooperation) on top of the developed business models to support knowledge workers’ multicriteria decision making tasks. The context awareness and exception handling capabilities of the
proposed approach have been presented with experimental studies. Through comparative evaluations,
it is shown that agileBPM is the most comprehensive knowledge-intensive process management
solution.
keywords: مدیریت فرآیند کسب و کار | فرایندهای دانش فشرده | مدل سازی و اجرای فرآیند | انطباق فرآیند | مدیریت فرآیند کسب و کار مبتنی بر عامل | مدیریت فرآیند کسب و کار چابک | Business process management | Knowledge-intensive processes | Process modeling and execution | Process adaptation | Agent-based business process management | Agile business process management |
مقاله انگلیسی |
80 |
Blueberry supply chain: Critical steps impacting fruit quality and application of a boosted regression tree model to predict weight loss
زنجیره تأمین زغال اخته: مراحل مهم تأثیر بر کیفیت میوه و استفاده از مدل درخت رگرسیون تقویت شده برای پیش بینی کاهش وزن-2021 Blueberries have increased in popularity in recent years due to their nutritional benefits and sensory characteristics. However, to preserve quality and extend shelf-life, they need to be maintained at refrigerated temperatures and high relative humidity, conditions that are not routinely met along the supply chain. Poor temperature management leads to quality deterioration, increasing waste/losses along the supply chain. This study examined the impact of each step along the supply chain on the physicochemical quality and shelf-life of blueberries, identifying the most critical steps from field to consumption. The following steps were identified acritical in the blueberry supply chain: shipping to distribution centre (DC) (72 h at 5 ◦C), store display (48 h at15 ◦C), and consumer (48 h at 20 ◦C). Given the economic importance of weight loss and its link to fruit quality and shelf-life, a boosted regression tree (BRT) model was built to predict weight loss using the post-harvest environmental conditions of a simulated supply chain applying different temperature-time scenarios. The model explained 84 % of the variance on the test set and highlighted the interactions of supply chain conditions on weight loss. Keywords: Cold chain | Shelf-life | Machine learning | Biochemical properties | Post-harvest storage |
مقاله انگلیسی |