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نتیجه جستجو - Actions

تعداد مقالات یافته شده: 1218
ردیف عنوان نوع
51 Big data driven supply chain design and applications for blockchain: An action research using case study approach
داده های بزرگ طراحی زنجیره تأمین و کاربردهای بلاکچین: یک اقدام پژوهی با استفاده از رویکرد مطالعه موردی-2021
Blockchain appears to still be nascent in its growth and a relatively untapped asset. This research investigates the need of blockchain in Industry 4.0 environment from Big Data perspective in supply chain management. The research method used in this study involves a combination of an Action Research method and Case Study research. More specifically, the action research method was applied in two industry case studies that implemented and tested the designed architecture in a global logistics environment. Case Study A examined the blockchain application in cross-border cargo movements whereas Case Study B investigated the application in a liquid chemical logistics company serving to petroleum industries. Our research analysis has identified that the Case A subject had disconnected systems and services for blockchain wherein the big data interactions had failed (failure case). Whereas in Case B, the company has achieved nearly 25% increase in revenue through its customer service after the blockchain implementation and thereby reduction in paperwork and carbon emissions (success case). This research contributes to the advancement of the body of knowledge to big data and blockchain by identifying key implementation guideline and issues for blockchain in supply chain management. Further, action-based research coupled with a case study approach has been used to evaluate the application aspects of the architecture’s scalability and functionality of bigdata and blockchain in supply chain management.
Keywords: Big data architecture | Action research | Case study research | Blockchain adoption | Supply chain management
مقاله انگلیسی
52 Data-driven detection and characterization of communities of accounts collaborating in MOOCs
شناسایی و توصیف مبتنی بر داده جوامع حساب‌هایی که در MOOC همکاری می‌کنند-2021
Collaboration is considered as one of the main drivers of learning and it has been broadly studied across numerous contexts, including Massive Open Online Courses (MOOCs). The research on MOOCs has risen exponentially during the last years and there have been a number of works focused on studying collaboration. However, these previous studies have been restricted to the analysis of collaboration based on the forum and social interactions, without taking into account other possibilities such as the synchronicity in the interactions with the platform. Therefore, in this work we performed a case study with the goal of implementing a data-driven approach to detect and characterize collaboration in MOOCs. We applied an algorithm to detect synchronicity links based on their submission times to quizzes as an indicator of collaboration, and applied it to data from two large Coursera MOOCs. We found three different profiles of user accounts, that were grouped in couples and larger communities exhibiting different types of associations between user accounts. The characterization of these user accounts suggested that some of them might represent genuine online learning collaborative associations, but that in other cases dishonest behaviors such as free-riding or multiple account cheating might be present. These findings call for additional research on the study of the kind of collaborations that can emerge in online settings.
keywords: تجزیه و تحلیل یادگیری | داده کاوی آموزشی | یادگیری مشارکتی | دوره های آنلاین گسترده باز | هوش مصنوعی | Learning analytics | Educational data mining | Collaborative learning | Massive open online courses | Artificial intelligence
مقاله انگلیسی
53 Blockchain-based royalty contract transactions scheme for Industry 4:0 supply-chain management
طرح معاملات قرارداد حق امتیاز مبتنی بر بلاکچین برای مدیریت زنجیره تأمین صنعت 4:0-2021
Industry 4.0-based oil and gas supply-chain (OaG-SC) industry automates and efficiently executes most of the processes by using cloud computing (CC), artificial intelligence (AI), Internet of things (IoT), and industrial Internet of things (IIoT). However, managing various operations in OaG-SC industries is a challenging task due to the involvement of various stakeholders. It includes landowners, Oil and Gas (OaG) company operators, surveyors, local and national level government bodies, financial institutions, and insurance institutions. During mining, OaG company needs to pay incentives as a royalty to the landowners. In the traditional existing schemes, the process of royalty transaction is performed between the OaG company and landowners as per the contract between them before the start of the actual mining process. These contracts can be manipulated by attackers (insiders or outsiders) for their advantages, creating an unreliable and un-trusted royalty transaction. It may increase disputes between both parties. Hence, a reliable, cost-effective, trusted, secure, and tamper-resistant scheme is required to execute royalty contract transactions in the OaG industry. Motivated from these research gaps, in this paper, we propose a blockchain-based scheme, which securely executes the royalty transactions among various stakeholders in OaG industries. We evaluated the performance of the proposed scheme and the smart contracts’ functionalities and compared it with the existing state-of-the-art schemes using various parameters. The results obtained illustrate the superiority of the proposed scheme compared to the existing schemes in the literature.
Keywords: Blockchain | Smart contract | Oil and gas industry | Supply chain management | Royalty
مقاله انگلیسی
54 A Requiem for ‘‘Blame It on Beijing” interpreting rotating global current account surpluses
مرثیه ای برای «سرزنش آن به گردن پکن» که در حال تفسیر جهانی در حال چرخش است مازاد حساب جاری-2021
Global current account imbalances have reappeared, although the extent and distribution of these imbalances are noticeably different from those experienced in the middle of the last decade. What does that recurrence mean for our understanding of the origin and nature of such imbalances? Will imbalances persist over time? Informed by empirical estimates of the determinants of current account imbalances encompassing the period after the global recession, we find that – as before – the observable manifestations of the factors driving the global saving glut have limited explanatory power for the time series variation in imbalances. Fiscal factors determine imbalances, and have accounted for a noticeable share of the recent variation in imbalances, including in the U.S. and Germany. For advanced economies, the financial component of the current account has been playing an increasing role in determining the movements of the account. Examining observable policy actions, it is clear that net official flows have been associated with some share of imbalances, although tracing out the motivations for intervention is difficult. Looking forward, it is clear that policy can influence global imbalances, although some component of the U.S. deficit will likely remain given the U.S. role in generating safe assets.
keywords: تعادل حساب جاری | دارایی های خارجی خالص | صرفه جویی | مروریسم | محافظت از خود | دارایی های ایمن | fi flows | Current account balance | Net foreign assets | Saving glut | Mercantilism | Self-protection | Safe assets | Official flows
مقاله انگلیسی
55 بازاریابی جاذبه ای دیجیتال: اندازه گیری عملکرد اقتصادی تجارت الکترونیکی خواروبار در اروپا و آمریکا
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 13 - تعداد صفحات فایل doc فارسی: 30
این تحقیق به بررسی رابطه هزینه-نتیجه اقدامات بازاریابی جاذبه ای مورد استفاده تجارت الکترونیکی خواروبار می پردازد. این تحلیل بر اساس به کارگیری مدل درفمن و استینر (1954) برای بودجه تبلیغات بهینه است که مولفین آن را با بازاریابی دیجیتال تطبیق می دهند و با تحلیل آماری تجاری تایید میکنند. با توجه به 29 شرکت عمده در شش کشور در افق زمانی شش سال، تحلیل ترکیبی تکنیک های بهینه سازی موتور جستجو و بازاریابی موتور جستجو هدف جذب کارکنان به صفحات وب شرکت ها را دنبال می کند. نتایج تایید می کند که تجارت الکترونیکی بازاریابی جاذبه ای دیجیتال را بهینه سازی می کند. تفاوت ها بسته به نوع فرمت و سطح کشور فرق دارند.
واژگان کلیدی: بازاریابی جاذبه ای | بازاریابی دیجیتال | تجارت الکترونیک | خرده فروشی | عملکرد اقتصادی | بهینه سازی سرمایه گذاری بازاریابی.
مقاله ترجمه شده
56 063-S0893608020304470
063-S0893608020304470-2021
Deep Neural Networks (DNNs) have become popular for various applications in the domain of image and computer vision due to their well-established performance attributes. DNN algorithms involve powerful multilevel feature extractions resulting in an extensive range of parameters and memory footprints. However, memory bandwidth requirements, memory footprint and the associated power consumption of models are issues to be addressed to deploy DNN models on embedded platforms for real time vision-based applications. We present an optimized DNN model for memory and accuracy for vision-based applications on embedded platforms. In this paper we propose Quantization Friendly MobileNet (QF-MobileNet) architecture. The architecture is optimized for inference accuracy and reduced resource utilization. The optimization is obtained by addressing the redundancy and quantization loss of the existing baseline MobileNet architectures. We verify and validate the per- formance of the QF-MobileNet architecture for image classification task on the ImageNet dataset. The proposed model is tested for inference accuracy and resource utilization and compared to the baseline MobileNet architecture. The inference accuracy of the proposed QF-MobileNetV2 float model attained 73.36% and the quantized model has 69.51%. The MobileNetV3 float model attained an inference accuracy of 68.75% and the quantized model has 67.5% respectively. The proposed model saves 33% of time complexity for QF-MobileNetV2 and QF-MobileNetV3 models against the baseline models. The QF-MobileNet also showed optimized resource utilization with 32% fewer tunable parameters, 30% fewer MAC’s operations per image and reduced inference quantization loss by approximately 5% compared to the baseline models. The model is ported onto the android application using TensorFlow API. The android application performs inference on the native devices viz. smartphones, tablets and handheld devices. Future work is focused on introducing channel-wise and layer-wise quantization schemes to the proposed model. We intend to explore quantization aware training of DNN algorithms to achieve optimized resource utilization and inference accuracy.© 2020 Elsevier Ltd. All rights reserved.
Keywords: Deep Neural Network | Classification | MobileNet | Computer vision | Embedded platform | Quantization
مقاله انگلیسی
57 Disingenuous natures and post-truth politics: Five knowledge modalities of concern in environmental governance
طبیعت بی نظیر و سیاست های پس از حقیقت: پنج روش دانش از نگرانی در زمینه حکومتداری محیط زیست-2021
In this paper I examine our current post-truth politics and use the concept ‘disingenuous natures’ to describe the intersecting knowledge constructs, management practices and material conditions that enable authoritative knowledge of human-environment interactions to take hold and persist. These conditions are disingenuous because they are both artifactual and generative of social-ecological reifications, knowledge distortions and information deficiencies, yet retain a position of authority and legitimacy in decision-making contexts. I argue that researchers seeking to confront our current post-truth wave lack a clear framework for describing the process through which post-truthism unfolds and disingenuous natures are produced. I describe five interrelated ‘knowledge modalities of concern’ that illuminate key elements of this process. I argue for continued engagement with these knowledge types by critical scholars of the environment because they pose serious challenges for progressive environmental governance.
keywords: حکومتداری محیط زیست | دانش | جهل | اکولوژی سیاسی | پس از حقیقت | ناشناخته شناخته شده | Environmental governance | Knowledge | Ignorance | Political Ecology | Post-truth | Unknown-Knowns
مقاله انگلیسی
58 COVID-19 impacts on Flemish food supply chains and lessons for agri-food system resilience
تأثیرات COVID-19 بر روی زنجیره های تأمین مواد غذایی فلاندی و درس هایی برای انعطاف پذیری سیستم کشاورزی-غذایی-2021
Context: Resilience represents the ability of systems to anticipate, withstand, or adapt to challenges. Times of great stress and disturbance offer opportunity to identify and confirm key contributors to agri-food system resilience. The COVID-19 pandemic and its related consequences constituted major shock, challenging the resilience of many agri-food systems worldwide.
Objective: This paper aimed to report the immediate effects of the COVID-19 crisis on various key actors from Flemish food supply chains. By analysing and assessing the observed impacts of and reactions to this crisis from a resilience perspective, it also aimed to gain empirical evidence on resilience-enhancing characteristics of agri-food systems to sudden shocks.
Methods: A first, quantitative step of our mixed method approach measured 718 farmers’ experienced impacts and applied strategies following the crisis through an online survey. A second, qualitative step captured impacts and responses from other key actors downstream the food supply chain through 22 in-depth interviews and 18 on-line questionnaires. Data gathering and interpretation followed a conceptual framework for analysing resilience of agri-food systems to external challenges, that we developed based on the literature. The framework states that resilience actions stem from three types of resilience capacities: anticipatory, coping and responsive capacities. These are determined by both resources allocated by system actors, as well as by resilience attributes from the system.
Results and conclusions: The COVID-19 crisis induced a simultaneous dropped demand for food products in the hospitality industry and risen demand in retail. This shifted demand significantly disturbed food production, processing and marketing processes in terms of labour organization, planning, operation, logistics, and economic returns. Perceived impacts varied extensively across actors from the agri-food system, mostly depending on their marketing strategy, customer base, and flexibility and diversity of their practices. Reported reactions to this crisis revealed that resilience capacities varied according to actors’ abilities to negotiate prices, adjust production processes, and maintain or reorient sales. Some agri-food sectors showed higher responsive capacity because of a higher connectivity and self-organization within the system.
Significance: Our findings suggest that flexibility and diversity, despite their tendency to diminish price optimums, increase resilience capacities, which may be more beneficial to systems for thriving in turbulent and uncertain environments. A more tangible, operationalized understanding of resilience is necessary to effectively improve agri-food system resilience. Our conceptual framework proved a valuable tool for operationalizing resilience assessments to major shocks.
Keywords: COVID-19 | Farmers | Resilience | Shocks | Agri-food system | Food supply chain
مقاله انگلیسی
59 Vision-assisted recognition of stereotype behaviors for early diagnosis of Autism Spectrum Disorders
تشخیص رفتارهای کلیشه ای برای تشخیص زودهنگام اختلالات طیف اوتیسم با کمک بینایی ماشین-2021
Medical diagnosis supported by computer-assisted technologies is getting more popularity and acceptance among medical society. In this paper, we propose a non-intrusive vision-assisted method based on human action recognition to facilitate the diagnosis of Autism Spectrum Disorder (ASD). We collected a novel and comprehensive video dataset f the most distinctive Stereotype actions of this disorder with the assistance of professional clinicians. Several frameworks as a function of different input modalities were developed and used to produce extensive baseline results. Various local descriptors, which are commonly used within the Bag-of-Visual-Words approach, were tested with Multi-layer Perceptron (MLP), Gaussian Naive Bayes (GNB), and Support Vector Machines (SVM) classifiers for recognizing ASD associated behaviors. Additionally, we developed a framework that first receives articulated pose-based skeleton sequences as input and follows an LSTM network to learn the temporal evolution of the poses. Finally, obtained results were compared with two fine-tuned deep neural networks: ConvLSTM and 3DCNN. The results revealed that the Histogram of Optical Flow (HOF) descriptor achieves the best results when used with MLP classifier. The promising baseline results also confirmed that an action-recognition-based system can be potentially used to assist clinicians to provide a reliable, accurate, and timely diagnosis of ASD disorder.© 2021 Elsevier B.V. All rights reserved.
Keywords: Action recognition | Autism Spectrum Disorder | Patient monitoring | Bag-of-visual-words | Convolutional neural networks
مقاله انگلیسی
60 Never the twain shall meet? Knowledge strategies for digitalization in healthcare
هرگز این دو نفر ملاقات نخواهند کرد؟ استراتژی های دانش برای دیجیتالی شدن در مراقبت های بهداشتی-2021
This paper explores the formation of knowledge strategies in digitalization of healthcare organizations. Adopting a case study design, we investigate how divergent professional groups including the management team, healthcare professionals and IT engineers in a Chinese hospital come together to develop coherent knowledge strategies during its digital transformation. The findings reveal four phases by which the interplays between the professional groups shaped the knowledge strategies. We systematically analyze the drivers, formation processes and outcomes of the knowledge strategies. Based on the findings, we propose four lessons that may help pro- fessional organizations at different stages of digitalization structure knowledge strategies that can stimulate knowledge creation, application, and synthesis. The study advances the understanding of knowledge strategy by emphasizing the interactions between diversified professional groups and the integration of different types of knowledge in achieving organizational goals. It also sheds light on the complexity and dynamics of knowledge strategy in the digitalization process of knowledge-intensive organizations.
keywords: مدیریت دانش | استراتژی دانش | سازمان دانش فشرده | دیجیتالی کردن | مراقبت های بهداشتی | مطالعه موردی | Knowledge management | Knowledge strategy | Knowledge-intensive organization | Digitalization | Healthcare | Case study
مقاله انگلیسی
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