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نتیجه جستجو - Statistical techniques

تعداد مقالات یافته شده: 14
ردیف عنوان نوع
1 A fuzzy based hybrid decision framework to circularity in dairy supply chains through big data solutions
چارچوب تصمیم ترکیبی مبتنی بر فازی برای مدور بودن در زنجیره های تامین لبنیات از طریق راه حل های داده های بزرگ-2021
This study determines the potential barriers to achieving circularity in dairy supply chains; it proposes a framework which covers big data driven solutions to deal with the suggested barriers. The main contribution of the study is to propose a framework by making ideal matching and ranking of big data solutions to barriers to circularity in dairy supply chains. This framework further offers a specific roadmap as a practical contribution while investigating companies with restricted resources. In this study the main barriers are classified as ‘eco- nomic’, ‘environmental’, ‘social and legal’, ‘technological’, ‘supply chain management’ and ‘strategic’ with twenty-seven sub-barriers. Various big data solutions such as machine learning, optimization, data mining, cloud computing, artificial neural network, statistical techniques and social network analysis have been suggested. Big data solutions are matched with circularity focused barriers to show which solutions succeed in overcoming barriers. A hybrid decision framework based on the fuzzy ANP and the fuzzy VIKOR is developed to find the weights of the barriers and to rank the big data driven solutions. The results indicate that among the main barriers, ‘economic’ was of the highest importance, followed by ‘technological’, ‘environmental’, ‘strategic’, ‘supply chain management’ then ‘social and legal barrier’ in dairy supply chains. In order to overcome circularity focused barriers, ‘optimization’ is determined to be the most important big data solution. The other solutions to overcoming proposed challenges are ‘data mining’, ‘machine learning’, ‘statistical techniques’ and ‘artificial neural network’ respectively. The suggested big data solutions will be useful for policy makers and managers to deal with potential barriers in implementing circularity in the context of dairy supply chains.
Keywords: Dairy supply chain | Barriers | Circular economy | Big data solution | Fuzzy ANP - VIKOR | Group decision making system
مقاله انگلیسی
2 Advanced atherosclerosis imaging by CT: Radiomics, machine learning and deep learning
تصویربرداری پیشرفته آترواسکلروز توسط CT: رادیولوژی ، یادگیری ماشین و یادگیری عمیق-2019
In the last decade, technical advances in the field of medical imaging significantly improved and broadened the application of coronary CT angiography (CCTA) for the non-invasive assessment of coronary artery disease. Recently, similar breakthroughs are happening in the post-processing, analysis and interpretation of radiological images. Technologies such as radiomics allow to extract significantly more information from scans than what human visual assessment is capable of. This allows the precision phenotyping of diseases based on medical images. The increased amount of information can then be analyzed using novel data analytic techniques such as machine learning (ML) and deep learning (DL), which utilize the power of big data to build predictive models, which seek to mimic human intelligence, artificially. Thanks to big data availability and increased computational power, these novel analytic methods are outperforming conventional statistical techniques. In this current overview we describe the basics of radiomics, ML and DL, highlighting similarities, differences, limitations and potential pitfalls of these techniques. In addition, we provide a brief overview of recently published results on the applications of the aforementioned techniques for the non-invasive assessment of coronary atherosclerosis using CCTA.
Keywords: Atherosclerosis | Coronary CT angiography | Radiomics | Machine learning | Deep learning
مقاله انگلیسی
3 تاثیر استرس شغلی بر رضایتمندی شغلی کارکنان: مطالعه تجربی بانک های خصوصی پاکستان
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 16 - تعداد صفحات فایل doc فارسی: 13
کارکنان تقریبا در هر بخش کاری تحت تاثیر استرس هستند که در نهایت تاثیر منفی بر رضایتمندی شغلی آنها می گذارد. هدف این مقاله بررسی تاثیر استرس کارکنان بر رضایتمندی شغلی آنها در بانک های خصوصی مشغول به کار در پنجاب به ویژه در منطقه مولتان می باشد. این مقاله با استفاده از پرسشنامه ساختار یافته انجام شد. تعداد کل 185 پرسشنامه توزیع گردید که از بین آنها 162 مورد پاسخ داده و به ما برگردانده شدند. آزمون اعتبار برای بررسی اعتبار ابزار تحقیق به کار رفت. تحلیل داده ها با استفاده از نرم افزار اس پی اس اس مدل 17 انجام شد. تحلیل تناسب و تحلیل رگرسیون به عنوان تکنیک های آماری تحلیل داده هابه کار رفت. تاثیر محیط کار، پاداش های مالی، حجم کار، اقتدار در تصمیم گیری و رفتار مدیریت بر رضایتمندی شغلی بررسی گردید. نتیجه گرفته شد که رابطه منفی قوی بین محیط کار، پاداش های مالی، اقتدار در تصمیم گیری و رفتار مدیریت از رضایتمندی شغلی وجود دارد. به هر حال تاثیر مثبت حجم کار بر رضایتمندی شغلی نیز مشاهده گردید. این تاثیر همچنین با برخی مطالعات قبلی پشتیبانی و تایید شد.
واژگان کلیدی: استرس شغلی | رضایتمندی شغلی | بخش بانکداری خصوصی | محیط کاری | پاداش های مالی | اقتدار در تصمیم گیری | رفتار مدیریت | حجم کار در شغل
مقاله ترجمه شده
4 Combination of complementary data mining methods for geographical characterization of extra virgin olive oils based on mineral composition
ترکیبی از روش های داده کاوی مکمل برای تعیین ویژگی های جغرافیایی روغن زیتون فوق العاده با استفاده از ترکیبات معدنی-2018
This work explores the potential of multi-element fingerprinting in combination with advanced data mining strategies to assess the geographical origin of extra virgin olive oil samples. For this purpose, the concentrations of 55 elements were determined in 125 oil samples from multiple Spanish geographic areas. Several un supervised and supervised multivariate statistical techniques were used to build classification models and in vestigate the relationship between mineral composition of olive oils and their provenance. Results showed that Spanish extra virgin olive oils exhibit characteristic element profiles, which can be differentiated on the basis of their origin in accordance with three geographical areas: Atlantic coast (Huelva province), Mediterranean coast and inland regions. Furthermore, statistical modelling yielded high sensitivity and specificity, principally when random forest and support vector machines were employed, thus demonstrating the utility of these techniques in food traceability and authenticity research.
Keywords: Olive oil ، Geographical traceability ، Mineral profile ، Inductively coupled plasma-mass spectrometry ، Data mining
مقاله انگلیسی
5 Big data techniques in auditing research and practice: Current trends and future opportunities
تکنیک های داده های بزرگ در حسابرسی تحقیق و عمل: روند فعلی و فرصت های آینده-2018
This paper analyses the use of big data techniques in auditing, and finds that the practice is not as widespread as it is in other related fields. We first introduce contemporary big data techniques to promote understanding of their potential application. Next, we review existing research on big data in accounting and finance. In addition to auditing, our analysis shows that existing research extends across three other genealogies: financial distress modelling, financial fraud modelling, and stock market prediction and quantitative modelling. Auditing is lagging behind the other research streams in the use of valuable big data techniques. A possible explanation is that au ditors are reluctant to use techniques that are far ahead of those adopted by their clients, but we refute this argument. We call for more research and a greater alignment to practice. We also outline future opportunities for auditing in the context of real-time information and in colla borative platforms and peer-to-peer marketplaces.
Keywords: Auditing ، Big data ، Data analytics ، Statistical techniques
مقاله انگلیسی
6 The Human Aspects of Information Security Questionnaire (HAIS-Q): Two further validation studies
جنبه های انسانی و پرسشنامه امنیت اطلاعات (HAIS-Q): دو مطالعه اعتبار سنجی بیشتر-2017
Information security awareness (ISA) is integral to protecting an organisation from cyber threats. The aim of this paper is to further establish the validity of the Human Aspects of Information Security Questionnaire (HAIS-Q), as an effective instrument for measuring ISA. We present two studies to further establish the construct validity of this instrument. In Study 1, 112 university students completed the HAIS-Q and also took part in an empirical lab based phishing experiment. Results indicated that participants who scored more highly on the HAIS-Q had better performance in the phishing experiment. This means the HAIS-Q can predict an aspect of information security behaviour, and provides evidence for its con vergent validity. In Study 2, the HAIS-Q was administered to a larger and more representative population of 505 working Australians to further establish the construct validity of the in strument. The results of a factor analysis and other statistical techniques provide evidence for the validity of the HAIS-Q as a robust measure of ISA. We also describe the practical implications of the HAIS-Q, particularly how it could be used by information security practitioners.
Keywords: Information security (InfoSec) | Security behaviours | Questionnaire design | Cyber security | Information security awareness | (ISA)
مقاله انگلیسی
7 Predicting bank failure: An improvement by implementing machine learning approach on classical financial ratios
پیش بینی شکست بانک: بهبود با اجرای روش یادگیری ماشین در نسبت های مالی کلاسیک-2017
This research compares the accuracy of two approaches: traditional statistical techniques and machine learning techniques, which attempt to predict the failure of banks. A sample of 3000 US banks (1438 failures and 1562 active banks) is investigated by two traditional statistical ap proaches (Discriminant analysis and Logistic regression) and three machine learning approaches (Artificial neural network, Support Vector Machines and k-nearest neighbors). For each bank, data were collected for a 5-year period before they become inactive. 31 financial ratios extracted from bank financial reports covered 5 main aspects: Loan quality, Capital quality, Operations efficiency, Profitability and Liquidity. The empirical result reveals that the artificial neural net work and k-nearest neighbor methods are the most accurate.
Keywords: Failure prediction | Intelligent techniques | Artificial neural network | Support vector machines | K-nearest neighbors | US banks
مقاله انگلیسی
8 Addressing the endogeneity dilemma in operations management research: Theoretical, empirical, and pragmatic considerations
خطاب به معضل درون زایی در تحقیقات مدیریت عملیات: ملاحظات نظری، تجربی و عملی-2017
In this paper, we examine the problem of endogeneity in the context of operations management research. Whereas the extant literature has focused primarily on the statistical aspect of the problem, a comprehensive treatment requires an examination of theoretical and pragmatic considerations as complements. The prevailing problem with the focus on statistical techniques is that the standards tend to be derived from idealizations: the correlation between a regressor and a disturbance term must be exactly zero, or the analysis will be invalid. In actual empirical research settings, such a knife-edge assumption can never be satisfied, indeed it cannot even be directly tested. Idealizations are useful in helping us understand what it would take to eliminate endogeneity, but when applied directly and unconditionally, they lead to unreasonable standards that may unnecessarily stifle substantive inquiry. We believe that it is far more productive and meaningful to ask: “What can we realistically expect empirical scientists to be able to achieve?” To this end, we cover and revisit some of the general technical material on endogeneity, paying special attention to the idiosyncrasies of operations management research and what could constitute reasonable criteria for addressing endogeneity in empirical opera tions management studies.
مقاله انگلیسی
9 Detection and visualization of non-linear structures in large datasets using Exploratory Projection Pursuit Laboratory (EPP-Lab) software
تشخیص و بصری سازی ساختارهای غیرخطی در سری داده های بزرگ با استفاده از نرم افزار آزمایشگاه توصیفی پیگیری تصویری (EPP-Lab)-2017
This article consists of using biologically inspired algorithms in order to detect potentially interesting structures in large and multidimensional data sets. Data exploration and the detection of interesting structures are based on the use of Projection Pursuit that involves the definition and the optimization of an index associated with each direction or projection. The optimization of a projection index should provide a set of multiple optima that is expected to correspond to interesting graphical representations in low dimensional space. The implementation of the bio-inspired algorithms along with the projection pursuit develops a new software called EPP-Lab. Projection pursuit is widely used in different scientific domains (biology, pharmacy, bioinformatics, biometry, etc) but not widely present in the well-known softwares. EPP-Lab is dedicated to recognize and visualize clusters and outlying observations on one dimension from high dimensional and multivariate data sets. It includes different statistical techniques for results analysis. It provides several features and gives the user the option to adjust the parameters of the selected bio-inspired methods or to use defaults values. EPP-Lab is a unique software for detection, visualization and analysis of non-linear structures. The performance of this tool has been validated by testing different real and simulated data sets.
KEYWORDS : Exploratory Projection | Pursuit | Genetic Algorithm | Particle Swarm Optimization | Tribes | Clustering | Outliers
مقاله انگلیسی
10 Influence of rotor position on the repeatability of frequency response analysis measurements on rotating machines and a statistical approach for more meaningful diagnostics
تاثیر موقعیت روتور در قابلیت تکرار اندازه گیری تجزیه و تحلیل پاسخ فرکانسی بر روی ماشین های دوار و یک روش آماری برای تشخیص معنی دار تر-2016
This work presents an investigation on the influence of rotor position on the Frequency Response Analysis (FRA) of electric machines. Different types of machines have been analyzed. Contrary to common belief, not only the salient-pole machine suffered from rotor position influence on the FRA. This can have severe impact on the repeatability of the tests and, consequently, their ability to identify early damage in the insulation system of the machine. This paper is intended to warn practitioners of FRA that care should be taken while analyzing the results, in order to avoid false positives in their measurements. Recommendations are made aiming to avoid the influence of rotor position on the results. Also, the use of statistical techniques is proposed, in order to improve the diagnosis, even when there is some lack of repeatability.
Keywords: AC machines | Condition monitoring | Frequency response analysis | Rotating machine insulation testing
مقاله انگلیسی
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