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Effect of CNT additives on the electrical properties of derived nanocomposites (experimentally and numerical investigation)
تأثیر افزودنیهای CNT بر خواص الکتریکی نانوکامپوزیتهای مشتقشده (بررسی تجربی و عددی)-2021 In this work, two simulations models have been developed to study the electrical percolation and the
electrical conductivity of epoxy-based nanocomposite containing Multi-walled Carbon Nanotubes. The
models are based on resistor-model and finite element analysis. The former was evaluated using
MATLAB code and the finite element analysis using DIGIMAT software. The maximum tunneling distance
and its influence on the percolation probability and final electrical conductivity were studied. Electrical
measurements on the samples were conducted for numerical validation. The experimental data showed a
percolation achievement around 2 wt%, which was confirmed in the numerical simulations. This study
provides evidence of the effectiveness of the resistor model and finite element method approach to predict the electrical conductivity of nanocomposites.
Keywords: Polymer-matrix composites (PMCs) | Nanocomposites | Carbon nanotube | Electrical properties | Computational modelling |
مقاله انگلیسی |
2 |
AHP-TOPSIS social sustainability approach for selecting supplier in construction supply chain
رویکرد پایداری اجتماعی AHP-TOPSIS برای انتخاب تامین کننده در زنجیره تأمین ساخت و ساز-2021 Prequalification of suppliers in the Construction Supply Chain is considered a crucial step to assure to their ability to deliver socially sustainable projects. This research identifies the most important social sustainability prequalification criteria for supplier selection in Construction Supply Chain. Additionally, a Multi-Criteria Decision Making (MCDM) model based on social indicators of sustainability is proposed in this research. Structured interviews were organized with experienced practitioners to define the relative importance weights of criteria that have collected in the first phase using Analytic Hierarchy Process (AHP). As such, the AHP is applied to develop mathematical determination to achieve the weights of social indicators. Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method is used to evaluate the different suppliers in the construction supply chain against 17 identified attributes. Ultimately, the closeness coefficients of the suppliers are estimated in order to identify social performance. The research aims at proposing a computational model of MCDM in order to introduce it to the construction organizations to utilize in the supplier prequalification process. A computational model is developed and a case study is worked out to illustrate the proposed methodology in supplier selection to ensure sustainable construction projects. Afterwards, the model is validated and a sensitivity analysis is conducted to analyze the impact of changing the weights of the considered attributes in the model outputs. Keywords: Social sustainability | Supplier selection | Construction supply chain | Multi-criteria decision making | Analytical hierarchy process | TOPSIS | Sensitivity analysis |
مقاله انگلیسی |
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Sunk cost effects hinge on the neural recalibration of reference points in mental accounting
اثرات هزینه های غرق شده بر روی لولایت عصبی از نقاط مرجع در حسابداری ذهنی-2021 The context of reinforcement history drastically influences human value-based choices. Mental accounting
theory concerns how prior outcomes are perceived, combined and assigned into specific “mental” accounts to
influence subsequent decisions but remains agnostic about the underlying computational and neural mecha-
nisms. In a two-stage sequential decision-making task, we found previously incurred costs and bonuses biased
subjects’ choices in the opposite directions with similar magnitudes. Such effects were consistent with a
computational model where the reference point was recalibrated by prior gains and losses encoded in the
ventral striatum activities. Moreover, individual’s susceptibility to prior outcomes was captured by the
response of the dorsolateral prefrontal cortex and its functional connectivity with the medial orbitofrontal
cortex, whose activity tracked the value of the chosen option. Our findings provide both behavioral and neural
evidence of how sunk costs, benefits, and prospects are integrated within the mental accounting framework to
influence choice behavior. keywords: حسابداری ذهنی | هزینه غرق شده | باد کردن | قشر پیشانی Dorsolateral | ارزش انتخاب شده | Medial Orbitofrontal Cortex | Mental accounting | Sunk cost | Windfall | Dorsolateral prefrontal cortex | Chosen value | Medial orbitofrontal cortex |
مقاله انگلیسی |
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Neural markers of suppression in impaired binocular vision
نشانگرهای عصبی سرکوب در اختلال بینایی دو چشمی-2021 Even after conventional patching treatment, individuals with a history of amblyopia typically lack good stereo vision. This is often attributed to atypical suppression between the eyes, yet the specific mechanism is still un- clear. Guided by computational models of binocular vision, we tested explicit predictions about how neural responses to contrast might differ in individuals with impaired binocular vision. Participants with a history of amblyopia (N = 25), and control participants with typical visual development (N = 19) took part in the study. Neural responses to different combinations of contrast in the left and right eyes, were measured using both electro encephalography (EEG) and functional magnetic resonance imaging (fMRI). Stimuli were sinusoidal gratings with a spatial frequency of 3c/deg, flickering at 4 Hz. In the fMRI experiment, we also ran population receptive field and retinotopic mapping sequences, and a phase-encoded localizer stimulus, to identify voxels in primary visual cortex (V1) sensitive to the main stimulus. Neural responses in both modalities increased monotonically with stimulus contrast. When measured with EEG, responses were attenuated in the weaker eye, consistent with a fixed tonic suppression of that eye. When measured with fMRI, a low contrast stimulus in the weaker eye substantially reduced the response to a high contrast stimulus in the stronger eye. This effect was stronger than when the stimulus-eye pairings were reversed, consistent with unbalanced dynamic suppression between the eyes. Measuring neural responses using different methods leads to different conclusions about visual differences in individuals with impaired binocular vision. Both of the atypical suppression effects may relate to binocular perceptual deficits, e.g. in stereopsis, and we anticipate that these measures could be informative for monitoring the progress of treatments aimed at recovering binocular vision. Keywords: Dichoptic | fMRI | Interocular suppression | SSVEP | V1 |
مقاله انگلیسی |
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Touching events predict human action segmentation in brain and behavior
پیش بینی تقسیم بندی عملکرد انسان را در مغز و رفتار با رویدادهای لمسی-2021 Recognizing the actions of others depends on segmentation into meaningful events. After decades of research in this area, it remains still unclear how humans do this and which brain areas support underlying processes. Here we show that a computer vision-based model of touching and untouching events can predict human behavior in segmenting object manipulation actions with high accuracy. Using this computational model and functional Magnetic Resonance Imaging (fMRI), we pinpoint the neural networks underlying this segmentation behavior during an implicit action observation task. Segmentation was announced by a strong increase of visual activity at touching events followed by the engagement of frontal, hippocampal and insula regions, signaling updating expectation at subsequent untouching events. Brain activity and behavior show that touching-untouching motifs are critical features for identifying the key elements of actions including object manipulations. Keywords: Action observation | Event segmentation | Unit marking procedure | fMRI | Semantic event chain | Computer vision |
مقاله انگلیسی |
6 |
Deep-learning-based reading eye-movement analysis for aiding biometric recognition
خواندن تجزیه و تحلیل حرکت چشم مبتنی بر یادگیری عمیق برای کمک به تشخیص بیومتریک-2021 Eye-movement recognition is a new type of biometric recognition technology. Without considering the characteristics of the stimuli, the existing eye-movement recognition technology is based on eye- movement trajectory similarity measurements and uses more eye-movement features. Related studies on reading psychology have shown that when reading text, human eye-movements are different between individuals yet stable for a given individual. This paper proposes a type of technology for aiding biometric recognition based on reading eye-movement. By introducing a deep-learning framework, a computational model for reading eye-movement recognition (REMR) was constructed. The model takes the text, fixation, and text-based linguistic feature sequences as inputs and identifies a human subject by measuring the similarity distance between the predicted fixation sequence and the actual one (to be identified). The experimental results show that the fixation sequence similarity recognition algorithm obtained an equal error rate of 19.4% on the test set, and the model obtained an 86.5% Rank-1 recognition rate on the test set.© 2020 Elsevier B.V. All rights reserved. Keywords: Eye tracking | Eye-movement model | Deep-learning | Biometrics | Identity authentication | Reading eye-movement |
مقاله انگلیسی |
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An overview of longshore sediment transport on the Brazilian coast✩
مروری بر حمل و نقل رسوب longshore در سواحل برزیل-2020 The present study investigates the wave behavior and the longshore sediment transport rate on the
Brazilian continental shelf, using a computational model and four different formulations, for the period
between 1979–2015. The average significant wave height is substantially variable along the study
region, with the largest values occurring in southern Brazil, whereas the smaller values occur in
northern Brazil. The longshore sediment transport rates are well within the range of values presented
in previous works and indicate which method performs best in estimating annual mean rates of
sediment transport. The highest sediment transport rates were found in the sector situated within
the northern coast of the Bahia state and the Alagoas state, reaching 460 000 m3 year−1. On the other
hand, the opposite was found between the Rio de Janeiro and southern Bahia coast, where the smallest
transport rates occurred with a global average of 109 000 m3 year−1. Additionally, it is important to
emphasize that small variations in the wave incidence angle may cause significant changes in the
longshore drift of sediments, favoring the occurrence of zones of convergence and divergence along
the coast. The novel results presented for the entire Brazilian shore contribute to the literature related
to wave and sediment transport along the Brazilian coast and can be useful for future engineering
projects that consider the sustainable management of the coastal zone. Keywords: Numerical modeling | TOMAWAC | CERC | Kamphuis | Longshore sediment transport | Coastal zone |
مقاله انگلیسی |
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به سمت لبه هوشمند: ارتباطات بی سیم به یادگیری ماشین میرسد
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 14 - تعداد صفحات فایل doc فارسی: 31 احیای هوش مصنوعی در اواخر (AI) تقریباً در هر شاخهای از علم و فناوری، انقلابی ایجاد کرده است. با توجه به گجتهای تلفن همراه هوشمند و همه جا حاضر و دستگاههای اینترنت اشیا (IoT)، انتظار میرود که اکثر برنامههای هوشمند را بتوان در لبهی شبکههای بی سیم استقرار داد. این روند باعث شده است، تمایل قوی برای تحقق «لبه هوشمند» ایجاد شود تا از برنامههای کاربردی مجهز به AI در دستگاههای لبه مختلف استفاده شود. بر این اساس، یک حوزهی پژوهشی جدید به نام یادگیری لبه به ظهور رسیده است که از دو رشته عبور میکند و انقلابی در آنها ایجاد میکند: ارتباطات بی سیم و یادگیری ماشین. یک موضوع اصلی در یادگیری لبه غلبه بر قدرت محاسباتی محدود و همچنین دادههای محدود در هر دستگاه لبه است. این امر با استفاده از پلت فرم محاسبات لبه تلفن همراه (MEC) و استخراج دادههای عظیم توزیع شده در تعداد زیادی دستگاه لبه محقق شده است. در چنین سیستمهایی، یادگیری از داده توزیع شده و برقراری ارتباط بین سرور لبه و دستگاهها دو جنبهی حیاتی و مهم است و همجوشی آنها، چالشهای پژوهشی جدید و زیادی را به همراه دارد. این مقاله از یک مجموعه جدید از اصول طراحی برای ارتباطات بی سیم در یادگیری لبه پشتیبانی میکند که در مجموع ارتباطات یادگیری محور نامیده میشوند. مثالهای گویایی ارائه شدند تا اثربخشی این اصول طراحی مشخص شوند و برای این منظور فرصتهای تحقیقاتی منحصر به فردی شناسایی شدند.
کلمات کلیدی: سرورها | مدل سازی جوی | هوش مصنوعی | پایگاه های داده توزیع شده | ارتباطات بی سیم | یادگیری ماشین | مدل سازی محاسباتی |
مقاله ترجمه شده |
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An investigation into the effective role of astrocyte in the hippocampus pattern separation process: A computational modeling study
بررسی نقش مؤثر آستروسیت ها در فرآیند جداسازی الگوی هیپوکامپ: یک مطالعه مدل سازی محاسباتی-2020 A physiologically realistic three layer neuron-astrocyte network model is used to evaluate the biological mechanism in pattern separation. The innovative feature of the model is the use of a combination of three elements: neuron, interneuron and astrocyte. In the input layer, a pyramidal neuron receives input patterns from stimulus current, while in the middle layer there are two pyramidal neurons coupled with two inhibitory interneurons and an astrocyte. Finally, in the third layer, a pyramidal neuron produces the output of the model by integrating the output of two neurons from the middle layer resulting from in- hibitory and excitatory connections among neurons, interneurons and the astrocyte. Results of computer simulations show that the neuron-astrocyte network within the hippocampal dentate gyrus can generate diverse, complex and different output patterns to given inputs. It is concluded that astrocytes within the dentate gyrus play an important role in the pattern separation process. Keywords: Pattern separation | Astrocyte | Hippocampus | Computational model | Memory |
مقاله انگلیسی |
10 |
Towards the interpretation of complex visual hallucinations in termsof self-reorganization of neural networks
به سمت تفسیر توهمات پیچیده بصری از نظر خود سازماندهی مجدد شبکه های عصبی-2020 Patients suffering from dementia with Lewy body (DLB) often see complex visual hallucinations (CVH).Despite many pathological, clinical, and neuroimaging studies, the mechanism of CVH remains unknown.One possible scenario is that top-down information is being used to compensate for the lack of bottom-up information. To investigate this possibility and understand the underlying mathematical structureof the CVH mechanism, we propose a simple computational model of synaptic plasticity with particu-lar focus on the effect of selective damage to the bottom-up network on self-reorganization. We showneurons that undergo a change in activity from a bottom-up to a top-down network framework duringthe reorganization process, which can be understood in terms of state transitions. Assuming that thepre-reorganization representation of this neuron remains after reorganization, it is possible to interpretneural response induced by top-down information as the sensation of bottom-up information. This sit-uation might correspond to a hallucinatory situation in DLB patients. Our results agree with existingexperimental evidence and provide new insights into data that have hitherto not been experimentallyvalidated on patients with DLB. Keywords : Network self-reorganization | Complex visual hallucinations| Synaptic plasticity | State transition | Oscillology |
مقاله انگلیسی |