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نتیجه جستجو - potentials

تعداد مقالات یافته شده: 93
ردیف عنوان نوع
1 Computer vision for anatomical analysis of equipment in civil infrastructure projects: Theorizing the development of regression-based deep neural networks
چشم انداز کامپیوتری برای تجزیه و تحلیل آناتومیکی تجهیزات در پروژه های زیرساختی عمرانی: نظریه پردازی توسعه شبکه های عصبی عمیق مبتنی بر رگرسیون-2022
There is high demand for heavy equipment in civil infrastructure projects and their performance is a determinant of the successful delivery of site operations. Although manufacturers provide equipment performance hand- books, additional monitoring mechanisms are required to depart from measuring performance on the sole basis of unit cost for moved materials. Vision-based tracking and pose estimation can facilitate site performance monitoring. This research develops several regression-based deep neural networks (DNNs) to monitor equipment with the aim of ensuring safety, productivity, sustainability and quality of equipment operations. Annotated image libraries are used to train and test several backbone architectures. Experimental results reveal the pre- cision of DNNs with depthwise separable convolutions and computational efficiency of DNNs with channel shuffle. This research provides scientific utility by developing a method for equipment pose estimation with the ability to detect anatomical angles and critical keypoints. The practical utility of this study is the provision of potentials to influence current practice of articulated machinery monitoring in projects.
keywords: هوش مصنوعی (AI) | سیستم های فیزیکی سایبری | معیارهای ارزیابی خطا | طراحی و آزمایش تجربی | تخمین ژست کامل بدن | صنعت و ساخت 4.0 | الگوریتم های یادگیری ماشین | معماری های ستون فقرات شبکه | Artificial intelligence (AI) | Cyber physical systems | Error evaluation metrics | Experimental design and testing | Full body pose estimation | Industry and construction 4.0 | Machine learning algorithms | Network backbone architectures
مقاله انگلیسی
2 Quantum-Inspired Power System Reliability Assessment
ارزیابی قابلیت اطمینان سیستم قدرت با الهام از کوانتومی-2022
To enable an in-depth study of power system operation and planning, the assessment of standard reliability indices is inevitable. The Monte Carlo Simulation (MCS) approach is a broadly used method in replacing the analytical methods in reliability indices assessment. The accuracy of MCS, however, highly depends on the sampling size, and hence, a complicated system with large number of components requires a large sampling size and daunting computational effort. To address this shortcoming, this paper attempts to take advantage of potentials of the quantum computing (QC) for power system reliability assessment by realizing the following contributions: 1) an innovative quantum model designed for reliability assessment; 2) a quantum circuit that achieves the quadratic speed up compared to the classical MCS method; 3) an efficient quantum amplitude estimation (QAE) algorithm to accurately evaluate the reliability indices. The accuracy and efficacy of the quantum reliability method are extensively verified and demonstrated on both radial and mesh distribution systems.
Index Terms—Quantum computing | Quantum amplitude estimation | Reliability assessment | Distribution systems
مقاله انگلیسی
3 Tunneling Current Through a Double Quantum Dots System
جریان تونل زنی از طریق سیستم دو نقطه کوانتومی-2022
Electrostatically confined quantum dots in semiconductors hold the promise to achieve high scalability and reliability levels for practical implementation of solid-state qubits where the electrochemical potentials of each quantum dot can be independently controlled by the gate voltages.In this paper, the current and charge stability diagram of two-well potentials arising from electrostatically defined double quantum dot (DQD) are analytically realized. We propose to apply the Generalized Hubbard model to find the Hamiltonian of the system. The proposed analysis takes the tunnel coupling between the dots, Coulomb interaction, and Zeeman energy arising from an external magnetic field into account. Using quantum master equations to predict the probability of the final states in a DQD system, we study the tunneling current through two quantum dots coupled in series with two conducting leads, and therefore, the charge stability diagram is theoretically investigated. The impact of the tunnel coupling and Zeeman energy on the charge stability diagram is deeply discussed. The validity of the presented analysis is confirmed by experimental data as well as the classical capacitance model.
INDEX TERMS: Double quantum dot | hubbard model | zeeman energy | charge stability diagram | master equation.
مقاله انگلیسی
4 Person-identification using familiar-name auditory evoked potentials from frontal EEG electrodes
شناسایی فرد با استفاده از پتانسیل نام-آشنا شنوایی الکترودهای EEG جلو برانگیخته-2021
Electroencephalograph (EEG) based biometric identification has recently gained increased attention of re- searchers. However, state-of-the-art EEG-based biometric identification techniques use large number of EEG electrodes, which poses user inconvenience and consumes longer preparation time for practical applications. This work proposes a novel EEG-based biometric identification technique using auditory evoked potentials (AEPs) acquired from two EEG electrodes. The proposed method employs single-trial familiar-name AEPs extracted from the frontal electrodes Fp1 and F7, which facilitates faster and user-convenient data acquisition. The EEG signals recorded from twenty healthy individuals during four experiment trials are used in this study. Different com- binations of well-known neural network architectures are used for feature extraction and classification. The cascaded combinations of 1D-convolutional neural networks (1D-CNN) with long short-term memory (LSTM) and with gated recurrent unit (GRU) networks gave the person identification accuracies above 99 %. 1D-convolutional, LSTM network achieves the highest person identification accuracy of 99.53 % and a half total error rate (HTER) of 0.24 % using AEP signals from the two frontal electrodes. With the AEP signals from the single electrode Fp1, the same network achieves a person identification accuracy of 96.93 %. The use of familiar-name AEPs from frontal EEG electrodes that facilitates user convenient data acquisition with shorter preparation time is the novelty of this work.
Keywords: Auditory evoked potential | Biometrics | Deep learning | Electroencephalogram | Familiar-name | Person identification
مقاله انگلیسی
5 Accounting-based downside risk and stock price crash risk: Evidence from China
ریسک نزولی مبتنی بر حسابداری و خطر سقوط قیمت سهام: شواهدی از چین-2021
In the past 15 years, an emerging literature has extensively studied individual stock price crash risk, which refers to the likelihood of an abrupt and large-scale drop in stock prices (e.g., Chen et al., 2001; Hutton et al., 2009; Jin and Myers 2006; Kim et al., 2011a, Li and Zhang 2011b; Kim and Zhang 2016). An important strand of this literature focuses on the Chinese emerging markets where, arguably, the extent of “bad news hoarding” is severer compared to developed markets due to China’s less effective corporate governance environment (Wang et al., 2020). In this paper, we examine the relationship between accounting-based downside risk and stock price crash risk using a large sample of Chinese listed firms. The contribution of this study lies in a recently developed indicator of earnings fundamentals that is, arguably, more consistent with “bad news hoarding”: accounting-based downside risk, hereafter denoted as ABDR. Studies have shown that investors care more about downside losses than upside gain potentials and are therefore more sensitive to losses than to gains (e.g., Gul 1991; Kahneman and Tversky 1979). Accordingly, Koonce et al. (2005) show that economic agents judge negative and positive expectations differently in risk management, placing more emphasis on potential loss outcomes. However, earnings volatility and other existing accounting-based downside risk measures consist of both downside and upside variabilities with equal weights and little research has examined the downside risk of accounting-based measures. Konchitchki et al. (2016) are the first to construct measures of accounting-based downside risk and examine its pricing implications in U.S. markets. In particular, this study uses the relative root lower partial moment as a mathematical foundation to capture exposure to downside risk rather than the overall volatility. Accounting-based downside risk measures focus on the below-expectation variability in firm performance measures, particularly return-on-assets (ROA). We extend Konchitchki et al. (2016) by performing an investigation in the Chinese markets. Furthermore, we examine the variation
keywords: Accounting-based downside risk | Stock price crash risk | Bad-news hoarding, China | ریسک نزولی مبتنی بر حسابداری | ریسک سقوط قیمت سهام | احتکار اخبار بد، چین
مقاله انگلیسی
6 Data, data flows, and model specifications for linking multi-level contribution margin accounting with multi-level fixed-charge problems
داده‌ها، جریان‌های داده، و مشخصات مدل برای پیوند حسابداری حاشیه سهم چندسطحی با مشکلات شارژ ثابت چندسطحی-2021
This article describes the data, data flows, and spreadsheet implementations for linking multi-level contribution margin accounting as a subsystem in cost accounting with several versions of a multi-level fixed-charge problem (MLFCP), the latter based on the optimization approach in operations research. This linkage can reveal previously hidden optimization potentials within the framework of multi-level contribution margin accounting, thus providing better information for decision making in companies and other organizations. For the data, plausible fictitious values have been assumed taking into consideration the calculation principles in cost accounting where applicable. They include resourcerelated data, market-related data, and data from cost accounting needed to analyze the profitability of a companys´ products and organizational entities in the presence of hierarchically structured fixed costs. The data are processed and analyzed by means of mathematical optimization techniques and sensitivity analysis. The linkage between multi-level contribution margin accounting and MLFCP is implemented in three spreadsheet files, including versions for deterministic optimization, stochastic optimization, and robust optimization. This paper provides specifications for compatible solver add-ins and for executing sensitivity analysis. The data and spreadsheet implementations described in this article were used in a research article entitled “Making better decisions by applying mathematical optimization to cost accounting: An advanced approach to multi-level contribution margin accounting” [1]. The data sets and the spreadsheet implementations may be reused a) by researchers in management and cost accounting as well as in operations research and quantitative methods for verification and for further development of the linkage concept and of the underlying optimization models; b) by practitioners for gaining insight into the data requirements, methods, and benefits of the proposed linkage, thus supporting continuing education; and c) by instructors in academia who may find the data and spreadsheets valuable for classroom use in advanced courses. The complete spreadsheet implementations in the form of three ready-touse Excel files (deterministic, stochastic, and robust version) are available for download at Mendeley Data. They may serve as customizable templates for various use cases in research, practice, and education.
keywords: حسابداری هزینه | تحقیق در عملیات | مشکل ثابت شارژ | بهینه سازی | برنامه نویسی صحیح | تجزیه و تحلیل میزان حساسیت | بهینه سازی تصادفی | صفحه گسترده | Cost accounting | Operations research | Fixed-charge problem | Optimization | Integer programming | Sensitivity analysis | Stochastic optimization | Spreadsheet
مقاله انگلیسی
7 Making better decisions by applying mathematical optimization to cost accounting: An advanced approach to multi-level contribution margin accounting
تصمیم گیری های بهتر را با استفاده از بهینه سازی ریاضی به هزینه حسابداری: یک رویکرد پیشرفته به حسابداری حاشیه کمک چند سطح-2021
The purpose of multi-level contribution margin accounting in cost accounting is to analyze the profitability of products and organizational entities with appropriate allocation of fixed costs and to provide relevant information for short-term, medium- and longer-term decisions. However, the conventional framework of multi-level contribution margin accounting does not usually incorporate a mathematical optimization method that simultaneously integrates variable and fixed costs to determine the best possible product mix within hierarchically structured organizations. This may be surprising in that operations research provides an optimization model in the form of the fixed-charge problem (FCP) that takes into account not only variable costs but also fixed costs of the activities to be planned. This paper links the two approaches by expanding the FCP to a multi-level fixed-charge problem (MLFCP), which maps the hierarchical decomposition of fixed costs in accordance with multi-level contribution margin accounting. In this way, previously hidden optimization potentials can be made visible within the framework of multi-level contribution margin accounting. Applying the linkage to a case study illustrates that the original assessment of profitability gained on the sole basis of a multi-level contribution margin calculation might turn out to be inappropriate or even inverted as soon as mathematical optimization is utilized: products, divisions, and other reference objects for fixed cost allocation, which at first glance seem to be profitable (or unprofitable) might be revealed as actually unprofitable (or profitable), when the multi-level contribution margin calculation is linked to the MLFCP. Furthermore, the proposed concept facilitates assessment of the costs of an increasing variant diversity, which also demonstrates that common rules on how to interpret a multi-level contribution margin calculation may have to be revised in some cases from the viewpoint of optimization. Finally, the impact of changes in the fixed cost structure and other parameters is tested via sensitivity analyses and stochastic optimization.
keywords: حسابداری هزینه | حد مشارکت، محدوده مشارکت | هزینه های ثابت | نرم افزار | مخلوط محصول | تصمیم گیری | تحقیق در عملیات | مشکل ثابت شارژ | مشکل چند سطح قابل شارژ | بهینه سازی | برنامه نویسی صحیح | تجزیه و تحلیل میزان حساسیت | بهینه سازی تصادفی | صفحه گسترده | مطالعه موردی | Cost accounting | Contribution margin | Fixed costs | Profitability | Product mix | Decision making | Operations research | Fixed-charge problem | Multi-level fixed-charge problem | Optimization | Integer programming | Sensitivity analysis | Stochastic optimization | Spreadsheet | Case study
مقاله انگلیسی
8 The reduced auditory evoked potential component N1 after repeated stimulation: Refractoriness hypothesis vs: habituation account
کاهش مولفه بالقوه برانگیخته شنوایی N1 پس از تحریک مکرر: فرضیه نسوز در مقابل حساب عادت-2021
Similar to other event-related potential (ERP) components, the amplitude of the auditory evoked N1 depends on the interstimulus interval (ISI). At ISIs > 0.4 s, the amplitude of the N1 increases with longer ISIs, until it saturates at ISIs around 10 s. This amplitude increase with increasing ISI has been conceptualized as a function of N1 recovery or N1 refractoriness. Habituation (as a simple form of learning) represents an elaborated, opposing account for such stimulus repetition effects. For passive oddball experiments (stimulation protocols with frequent standards and rare deviants), the two accounts make different predictions. According to the habituation account, the presentation of small deviants should lead to an increased N1 for subsequent standards (= dishabituation); according to the N1 refractoriness account, there should be no or just minor effects on the N1. In the current study, we tested these predictions and compared the ERPs to standards after small deviants and to standards preceded by other standards. We observed that the ERPs to standards after small deviants were characterized by a small mismatch negativity with an onset latency > 150 ms, but the N1 to standards after deviants did not differ from the N1 to standards preceded by other standards. This negative finding is in line with other previous studies that were also not able to reveal evidence for N1 dishabituation. Aside from this repeated lack of evidence for dishabituation, the N1 habituation account is challenged by the finding that the N1 decrease is stronger for more intense stimuli. Overall, the current and previous findings are more compatible with the N1 refractoriness account, although the mechanisms underlying N1 refractoriness remain to be elucidated. Knowledge about these mechanisms would also help to understand why N1 deficits in schizophrenia are more pronounced at longer ISIs.
keywords: عادت | جهت دار | پتانسیل های ناشی از شنوایی | شدت محرک | نگرش ناسازگاری (MMN) | انطباق محرک-مشخصه (SSA) | Habituation | Dishabituation | Auditory evoked potentials | Stimulus intensity | Mismatch negativity (MMN) | Stimulus-specific adaptation (SSA)
مقاله انگلیسی
9 Exploiting knowledge graphs in industrial products and services: A survey of key aspects, challenges, and future perspectives
بهره برداری از نمودارهای دانش در محصولات صنعتی و خدمات: بررسی جنبه های کلیدی، چالش ها و دیدگاه های آینده-2021
The rapid development of information and communication technologies has enabled a value co-creation paradigm for developing industrial products and services, where massive heterogeneous data and multidisciplinary knowledge are generated and leveraged. In this context, Knowledge Graph (KG) emerges as a promising tool to elicit, fuse, process, and utilize numerous entities and relationships embedded in products and services, as well as their stakeholders. Nevertheless, to the best of the authors’ knowledge, there is scarcely any comprehensive and thorough discussion about making full use of KG’s potentials to solve pain points of product development and service innovation in the industry. Aiming to fill this gap, this paper conducted a systematic survey of KG exploitations in industrial products and services and the customizations towards higher adaptability to practices. The authors selected 119 representative papers (up to 10/03/2021) together with other 29 supplementary works to summarize the technical and practical efforts and discuss the current challenges of exploiting KG in industrial products and services. Meantime, this work also highlights enhancing KG’s availability and boosting its productivity in industrial products and services development as the core future perspectives to explore. It is hoped that this work can provide a basis for the explorations and implementations of KG-supported industrial product and services development, and attract more open discussions to the exploitation of KG-enabled industrial information systems.
keywords: گراف دانش | توسعه محصول | نوآوری خدمات | مدیریت دانش | سیستم های خدمات محصول | مرور | Knowledge graph | Product development | Service innovation | Knowledge management | Product-service systems | Review
مقاله انگلیسی
10 Improving supply chain resilience through industry 4:0: A systematic literature review under the impressions of the COVID-19 pandemic
بهبود انعطاف پذیری زنجیره تأمین از طریق صنعت 4:0: بررسی ادبیات سیستماتیک تحت تأثیر همه گیری COVID-19-2021
The COVID-19 pandemic is one of the most severe supply chain disruptions in history and has challenged practitioners and scholars to improve the resilience of supply chains. Recent technological progress, especially industry 4.0, indicates promising possibilities to mitigate supply chain risks such as the COVID-19 pandemic. However, the literature lacks a comprehensive analysis of the link between industry 4.0 and supply chain resilience. To close this research gap, we present evidence from a systematic literature review, including 62 papers from high-quality journals. Based on a categorization of industry 4.0 enabler technologies and supply chain resilience antecedents, we introduce a holistic framework depicting the relationship between both areas while exploring the current state-of-the-art. To verify industry 4.0’s resilience opportunities in a severe supply chain disruption, we apply our framework to a use case, the COVID-19-affected automotive industry. Overall, our results reveal that big data analytics is particularly suitable for improving supply chain resilience, while other industry 4.0 enabler technologies, including additive manufacturing and cyber-physical systems, still lack proof of effectiveness. Moreover, we demonstrate that visibility and velocity are the resilience antecedents that benefit most from industry 4.0 implementation. We also establish that industry 4.0 holistically supports pre-disruption resilience measures, enabling more effective proactive risk management. Both research and practice can benefit from this study. While scholars may analyze resilience potentials of under-explored enabler technologies, practitioners can use our findings to guide industry 4.0 investment decisions.
Keywords: Industry 4.0 | Supply chain risk management | Supply chain resilience | Supply chain disruption | Digital supply chain | Literature review
مقاله انگلیسی
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