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نتیجه جستجو - Belief

تعداد مقالات یافته شده: 161
ردیف عنوان نوع
1 Is the Internet of Things a helpful employee? An exploratory study of discourses of Canadian farmers
آیا اینترنت اشیا یک کارمند مفید است؟ بررسی اکتشافی گفتمان های کشاورزان کانادایی-2022
The increasing global population and the growing demand for high-quality products have called for the modernization of agriculture. “Internet of Things” is one of the technologies that is pre- dicted to offer many solutions. We conducted a discourse analysis of 19 interviews with farmers in Ontario, Canada, asking them to describe their experience of working with IoT and related technologies. One main discourse with two opposing tendencies was identified: farmers recognize their relationship with IoT and related technology and view technology as a kind of “employee”, but some tend to emphasize (1) an optimistic view which is discourse of technology is a “Helpful Employee”; while others tend to emphasize (2) a pessimistic view which is a discourse of tech- nology is an “Untrustworthy Employee”. We examine these tendencies in the light of the literature on organizational behavior and identify potential outcomes of these beliefs. The results suggest that a farmer’s style of approaching technology can be assessed on a similar scale as managers’ view of their employees and provide a framework for further research.
keywords: فناوری اینترنت اشیا | کشاورزی | تحلیل گفتمان | سبک استفاده از تکنولوژی | Internet of things technology | Agriculture | Discourse analysis | Style of use of technology
مقاله انگلیسی
2 الگوریتم ژنتیک چند هدفه و طرح معماری یادگیری عمیق مبتنی بر CNN برای تشخیص موثر spam
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 18
معمولا ایمیل به عنوان قدرتمندترین رسانه در شبکه‌های اجتماعی آنلاین در نظر گرفته می‌شود که امکان گفتگو و ارتباط آنلاین کاربران رسانه‌های اجتماعی آنلاین را با یکدیگر فراهم می کند، همچنین امکان اشتراک گذاری لینک هم وجود دارد. به ویژه، توییتر به عنوان محبوب ترین شبکه اجتماعی شناخته شده است که بهترین کانال ارتباطی برای به اشتراک گذاشتن اخبار، ایده ها، افکار، نظرات و عقاید فعلی کاربران خود با سایر کاربران رسانه های اجتماعی آنلاین است. علیرغم تلاش‌هایی که برای مبارزه با عملیات اسپم در شبکه اجتماعی آنلاین انجام شده است، اسپم توییتر دارای عملکرد جدیدی محدود به 140 کاراکتر است. این نه تنها علت اصلی آزار کاربران روزمره است، بلکه اکثر مسائل امنیتی رایانه نیز ناشی از آن است که میلیاردها دلار کاهش بهره وری هزینه را در پی دارد. در این مقاله، یک الگوریتم ژنتیک چندهدفه و یک طرح معماری یادگیری عمیق مبتنی بر CNN (MOGA-CNN-DLAS) برای فرآیند تشخیص اسپم غالب در توییتر پیشنهاد می‌کنیم. جزئیات تجربی و نتایج و بحث حاصل از MOGA-CNN-DLAS پیشنهادی از نظر دقت ، صحت، فراخوان، FScore، RMSE و MAE مورد ارزیابی قرار گرفتند. این ارزیابی با تغییر نسبت داده‌های آموزشی کاربردی از سه مجموعه داده واقعی، مانند مجموعه داده توییتر k100 و ASU انجام شد.
کلمات کلیدی: اسپم توییتر | یادگیری عمیق | شبکه عصبی پیچشی یا همگشتی (CNN) | الگوریتم ژنتیک | آنالیز رسانه های اجتماعی | تشخیص موثر اسپم
مقاله ترجمه شده
3 Toward a Union-Find Decoder for Quantum LDPC Codes
به سمت رمزگشای Union-Find برای کدهای LDPC کوانتومی-2022
Quantum LDPC codes are a promising direction for low overhead quantum computing. In this paper, we propose a generalization of the Union-Find decoder as a decoder for quantum LDPC codes. We prove that this decoder corrects all errors with weight up to Anα for some A, α > 0, where n is the code length, for different classes of quantum LDPC codes such as toric codes and hyperbolic codes in any dimension D ≥ 3 and quantum expander codes. To prove this result, we introduce a notion of covering radius which measures the spread of an error from its syndrome. We believe this notion could find application beyond the decoding problem. We also perform numerical simulations, which show that our Union-Find decoder outperforms the belief propagation decoder in the low error rate regime in the case of a quantum LDPC code with length 3600.
keywords: Quantum computing | error correction | decoding.
مقاله انگلیسی
4 Deep belief network-based hybrid model for multimodal biometric system for futuristic security applications
مدل ترکیبی مبتنی بر باور عمیق برای سیستم بیومتریک چند حالته برای برنامه های امنیتی آینده-2021
Biometrics is the technology to identify humans uniquely based on face, iris, and fingerprints, etc. Biometric authentication allows the person recognition automatically on the basis of behavioral or physiological charac- teristics. Biometrics are broadly employed in several commercial as well as the official identification systems for automatic access control. This paper introduces the model for multimodal biometric recognition based on score level fusion method. The overall procedure of the proposed method involves five steps, such as pre-processing, feature extraction, recognition score using Multi- support vector neural network (Multi-SVNN) for all traits, score level fusion, and recognition using deep belief neural network (DBN). The first step is to input the training images into pre-processing steps. Thus, the pre-processing of three traits, like iris, ear, and finger vein is done. Then, the feature extraction is done for each modality to extract the features. After that, the texture features are extracted from pre-processed images of the ear, iris, and finger vein, and the BiComp features are acquired from individual images using a BiComp mask. Then, the recognition score is computed based on the Multi-SVNN classifier to provide the score individually for all three traits, and the three scores are provided to the DBN. The DBN is trained using the chicken earthworm optimization algorithm (CEWA). The CEWA is the integration of the chicken swarm optimization (CSO), and earthworm optimization algorithm (EWA) for the optimal authentication of the person. The analysis proves that the developed method acquired a maximal accuracy of 95.36%, maximal sensitivity of 95.85%, and specificity of 98.79%, respectively.
Keywords: Multi-modal Bio-metric system | Chicken Swarm Optimization | Earthworm Optimization algorithm | Deep Belief Network | Multi-SVNN
مقاله انگلیسی
5 In defense of the one-factor doxastic account: A phenomenal account of delusions
در دفاع از حساب تک عاملی دوکساستیک: روایتی خارق العاده از توهمات-2021
According to the doxastic model, delusions are beliefs. In the metacognitive model, delusions are imaginings mistaken for beliefs. I argue that endorsement of false second-order beliefs could also create unpleasant dissonance, that mentally healthy people often endorse irrational or conflicting beliefs, and that the lack of delusion-motivated action can be explained by the influence of nonbelief factors on action. The two-factor doxastic model posits irrationality as necessary, and one metric of rationality many scholars employ is whether a response is easily understood by folk psychology. A precedent for folk-psychological acceptance of contextually bizarre beliefs as a result of personal experience can already be found in the lack of imaginative resistance encountered not in response to the impossibilities portrayed in speculative fiction, but in response to the characters’ ability to incorporate these occurrences into their mental frameworks, despite them often being at odds with these characters’ bedrock understanding of the world.
keywords: توهم | حساب Doxastic | مدل دو عامل | جنون جوانی | حساب کاربری فراشناختی | مدل یک عامل | Delusion | Doxastic account | Two-factor model | Schizophrenia | Metacognitive account | One-factor model
مقاله انگلیسی
6 Magic, Bayes and wows: A Bayesian account of magic tricks
جادو، بیز و واو: شرح بیزی از ترفندهای جادویی-2021
Magic tricks have enjoyed an increasing interest by scientists. However, most research in magic focused on isolated aspects of it and a conceptual understanding of magic, encompassing its distinct components and va- rieties, is missing. Here, we present an account of magic within the theory of Bayesian predictive coding. We present the “wow” effect of magic as an increase in surprise evoked by the prediction error between expected and observed data. We take into account prior knowledge of the observer, attention, and (mis-)direction of perception and beliefs by the magician to bias the observer’s predictions and present a simple example for the modelling of the evoked surprise. The role of misdirection is described as everything that aims to maximize the surprise a trick evokes by the generation of novel beliefs, the exploitation of background knowledge and attentional control of the incoming information. Understanding magic within Bayesian predictive coding allows unifying all aspects of magic tricks within one framework, making it tractable, comparable and unifiable with other models in psychology and neuroscience.
keywords: شعبده بازي | سورپرایز بیزی | برنامه نویسی پیش بینی شده | سوء تفاهم | توجه | Magic | Bayesian surprise | Predictive coding | Misdirection | Attention
مقاله انگلیسی
7 Narrative accounting for mining in Ghana: An old defence against a new threat?
حسابداری روایت برای معدن در غنا: دفاع قدیمی در برابر یک تهدید جدید؟-2021
This article is concerned with aspects of how accounting and accountants figure in economics and policy issues related to mineral and fossil fuel extraction, production and use. Starting by appraising whether narrative ac- counting by a transnational mining corporation is attuned to the people working or living in an area affected by the mining operations, it goes on to considering how data, calculations and communications pertaining to sus- tainability are applied. This includes what connections the people involved perceive between accounting and sustainability. Data were obtained through qualitative fieldwork in and around the Damang Mine in Ghana, comprising interviews with employees and in the community, and analysis of documents. Corporation executives use narrative accounting to back claims that they invest hugely in sustainability, so having, in their words, a social licence to operate from host community stakeholders. This reflects accounting figuring in resource allocation choices, including in terms of how shareholder capital is managed to generate greater societal value and to operate sustainably. However, although many local people see themselves as deriving some benefit from the socio-economic activities of the mining corporation, they see accounting as not their business, being more economic than environmental or social. The inference is that accounting continues to serve purposes of man- agement control of production, distributing value-added in favour of capital providers and managing image reflected in the notion of having a social licence to operate. Despite their belief that accounting and accountants having roles to play in sustainability, they generally cannot identify these roles. These findings imply that, if account providers are serious about being corporately responsible towards affected people, they must do more to ensure that environmental and social aspects receive enough attention to convince those people that they are truly being engaged with on equal terms, in addition to convincing a wider audience that the reports they produce are reliable and relevant to sustainability in practice.
keywords: پایداری | حسابداری | غانیان | بخش معدن | مجوز اجتماعی | Sustainability | Accounting | Ghanaians | Mining sector | Social licence
مقاله انگلیسی
8 Testing the effectiveness of consumer financial disclosure: Experimental evidence from savings accounts
تست اثربخشی افشای مالی مصرف کننده: شواهد تجربی از حساب های پس انداز-2021
While popular with policymakers, most evidence on consumer financial disclosure’s effectiveness studies borrowing decisions (where optimality is unclear) or lab experiments (where attention is not scarce). We provide field evidence from randomized controlled trials with 124,000 savings account holders at five UK depositories. Treated consumers were disclosed varying degrees of salient information about alternative products, including one with their current provider strictly dominating their current product. Despite switching taking roughly 15 minutes and the moderate average potential gains ($190/year), switching is rare across disclosure designs and depositors. We find pessimistic beliefs drive disclosure inattention and limit disclosure’s effectiveness, helping explain deposit stickiness. -
keywords: افشاء | سپرده های چسبنده | مقررات مالی | عدم توجه | هزینه های تعویض | Disclosure | Sticky deposits | Financial regulation | Inattention | Switching costs
مقاله انگلیسی
9 Capturing causality and bias in human action recognition
ثبت علیت و سوگیری در تشخیص عمل انسان-2021
Human action recognition using various sensors is a mandatory component of autonomous vehicles, humanoid robots, and ambient living environments. A particular interest is the detection and recognition of falls. In this paper, we propose the use of temporal convolution networks guided by knowledge distilla- tion for detecting falls and recognizing types of falls using accelerometer data. Tri-axial accelerometers attached to the body measure the acceleration of the body joints when an action occurs. These data are used for pattern analysis and body action recognition. We demonstrate the existence of biases caused by soft biometrics when recognizing human body actions. We introduce a causal network to capture the influences of biases on system performance and illustrate how knowledge distillation can be applied to mitigate the bias effect. Crown Copyright © 2021 Published by Elsevier B.V. All rights reserved.
Keywords: Machine learning | Decision support | Human action recognition | Machine reasoning | Belief networks
مقاله انگلیسی
10 Knowledge, beliefs and management of childhood fever among nurses and other health professionals: A cross-sectional survey
دانش، باورها و مدیریت تب دوران کودکی در پرستاران و سایر متخصصان بهداشت و درمان: یک مرور مقطعی-2021
Background: Fever phobia, the unfounded fear regarding the potential harms of fever in children, has been internationally documented among parents. This fear causes anxiety in parents and health professionals are regularly consulted for advice. Objectives: This study aimed to investigate the knowledge, beliefs and recommended treatments among Australian nurses, pharmacists, general practitioners and paediatricians in the management of febrile children. Design, setting and participants: This was an online cross-sectional survey of Australian nurses, pharmacists, general practitioners and paediatricians designed to evaluate the knowledge and preferred recommendations in the management of febrile children. Methods: The health professionals were recruited via Facebook. Demographic information, knowledge, beliefs and preferred treatments were collected through the online survey, and responses were compared across professions. Results: Of the 839 health professionals who completed the survey, 52.0% correctly identified a fever as 38 ◦C or above. Overall, 23.6% underestimated the temperature that constitutes a fever. Respondents reported concerns leaving fever untreated in children, with dehydration (65.1%), seizures (65.2%), serious illness (34.4%) and brain damage (29.9%) the most common concerns. Pharmacists were more likely to hold these concerns. The beliefs that reducing a child’s fever with medication will reduce the risk of harm (34.7%) and prevent febrile convulsions (51.1%) were prevalent among respondents. These beliefs were more common among pharmacists. Pharmacists were also more likely to recommend parents monitor a child’s temperature (48.5%) and give medication to reduce fever (64.6%). Conclusions: Australian nurses, pharmacists, general practitioners and paediatricians reported many mis- conceptions surrounding the definition of fever, the potential harms of fever and its management, which may perpetuate parental fears. These misconceptions were most common among pharmacists. Continuing profes- sional development is essential to ease unfounded concerns and ensure the safe and judicious care of febrile children.
keywords: تب | کودک | پرستاران | داروسازان | پزشکان عمومی | مرورها و پرسشنامه ها | Fever | Child | Nurses | Pharmacists | General practitioners | Paediatricans | Surveys and questionnaires
مقاله انگلیسی
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