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11 فعل و انفعالات فیکساسیون متقاطع جهت ها، پیشنهاد کدگشایی سطح بالا به پایین در حافظه کاری بصری
سال انتشار: 2022 - تعداد صفحات فایل pdf انگلیسی: 12 - تعداد صفحات فایل doc فارسی: 37
کدگذاری حسی (چگونگی برانگیختن پاسخ های حسی توسط محرک ها) به پیشرفت از ویژگی های سطح پایین به سطح بالا معروف است. کمتر به فهم و درک کدگشایی (چگونه پاسخ ها منجر به ادراک می شوند) پرداخته شده است اما اغلب فرض می شود که از سلسله مراتب مشابهی پیروی می کند. بر این اساس، کدگشایی جهت باید در مناطق سطح پایین مانند V1، بدون فعل و انفعالات فیکساسیون متقابل رخ دهد. با این حال، در مطالعه ی Ding, Cueva, Tsodyks, and Qian (2017) شواهدی برخلاف این فرض ارائه شد و آنها پیشنهاد کردند که کدگشایی بصری اغلب از سلسله مراتبی از سطح بالا به سطح پایین در حافظه کاری پیروی می کند، که در آن محدودیت‌های سطح از بالاتر به پایین‌تر ، تعامل بین ویژگی‌های سطح پایین‌تر را معرفی می‌کنند. دو جهت در سویه مخالف فیکساسیون، هم مربوط به کار هستند و هم حافظه کاری می و باید با یکدیگر تعامل داشته باشند. در واقع فعل و انفعالات فیکساسیون متقابل پیش بینی شده (دفعه و همبستگی) بین جهت ها را پیدا کرده. کارآزمایی‌ها و تجزیه و تحلیل‌های کنترلی، توضیحات جایگزین مانند گزارش سوگیری و انطباق در سراسر کارآزمایی‌ها را در جهت مشابه فیکساسیون، رد کردند. علاوه بر این، داده‌ها را با استفاده از چارچوب کدگشایی بیزی سطح بالا به پایین گذشته‌نگر شرح دادیم.
کلیدواژه ها: کدگشایی بصری | سوگیری ادراکی | نویز حافظه | گذشته نگر بیزی
مقاله ترجمه شده
12 A deep learning-based cow behavior recognition scheme for improving cattle behavior modeling in smart farming
طرح شناخت رفتار گاو مبتنی بر یادگیری عمیق برای بهبود مدل‌سازی رفتار گاو در کشاورزی هوشمند-2022
Farming and animal husbandry applications are improvised with the implication of machine learning and artificial intelligence in recent years. The precise estimation, recommendations, and performances are the prime reason for the technology implication. Owing to the modern agri- cultural and animal cultures, this article introduces an innovative Behavior Recognition and Computation Scheme (BRCS) for predicting cow behaviors. The information from the swallowed microchip is processed based on the observed animal action that is used for the forecast. Considering the information to be rectilinear, the distractions and distribution patterns (data) are augmented in identifying and forecasting its behavior. The proposed scheme identifies the pat- terns using a deep recurrent learning paradigm recurrently. This pattern is distinguished for idle and non-idle observations for improving the prediction accuracy. Distinguished data patterns are mapped for the consecutive time and observation data in classifying abnormalities. The proposed scheme’s performance is validated using the metrics accuracy, precision, computing time, and mean error.
keywords: رفتار گاو | تحلیل داده ها | یادگیری عمیق | تشخیص الگو | Cow behavior | Data analysis | Deep learning | Pattern recognition
مقاله انگلیسی
13 A survey on blockchain, SDN and NFV for the smart-home security
مروری بر بلاک چین، SDN و NFV برای امنیت خانه های هوشمند-2022
Due to millions of loosely coupled devices, the smart-home security is gaining the attention of industry professionals, attackers, and academic researchers. The smart home is a typical home where many sensors, actuators, and IoT devices are used to automate home users’ daily activities. Although a smart home provides comfort, safety, and satisfaction to users, it opens up multiple challenging security issues when automating and offering intelligent services. Recent studies have investigated not only blockchain but SDN and NFV to address these challenges. We present a comprehensive survey on blockchain, SDN, and NFV for smart-home security. The paper also proposes a new architecture of the smart-home security. First, we describe the features of the smart home and its current security issues. Next, we outline the characteristics of blockchain, SDN, and NFV, including their contribution to improving the smart-home security. While SDN enhances the management and access control of the home network by providing a programmable controller to home nodes, NFV implements the functions of network appliances (e.g., network monitoring, firewall) as virtual machines and ensures the high availability of the network. Blockchain reinforces IoT data’s privacy, integrity, and security and improves the trust in transactions among untrusted IoT devices. Finally, we discuss open issues and challenges in the field and propose recommendations towards high-level security for the smart home.
Keywords: Smart homes | IoT | Privacy | Security | Trust | Blockchain | SDN | NFV
مقاله انگلیسی
14 Adverse Reaction Detection from Social Media based on Quantum Bi-LSTM with Attention
تشخیص واکنش نامطلوب از رسانه های اجتماعی بر اساس کوانتوم Bi-LSTM با توجه-2022
Drug combination is very common in the course of disease treatment. However, it inevitably increases the overall risk of adverse drug reactions (ADRs). It is very important to early and accurately detect and identify the potential ADRs for combined medication safety and public health. Social media is an important pharmacovigilance data source for ADR detection. But the data are complex, mass, clutter, highly sparse, so it is difficult to detect the ADR information from these data. Deep learning stands out in terms of increased accuracy. However, it takes a lot of training time and requires a lot of computing power. Quantum computing has strong parallel computing capability, and requires less computing power. By introducing attention mechanism and quantum computing into Bi-directional Long Short-Term Memory (Bi-LSTM), a quantum Bi-LSTM with attention (QBi-LSTMA) model is constructed for ADR detection from social media big data. QBi-LSTMA is composed of 6 variable component subcircuits (VQC) stacked. Under the condition that the main topology of Bi-LSTM remains unchanged, the biases of QBi-LSTMA in input gate, forgetting gate, candidate memory unit and output gate are removed to simplify the network structure, and the weight and active value qubits of the model are used to update the network weight. The performance of the proposed method is evaluated on the SMM4H dataset, comparing with one traditional ADR detection method and three deep learning based ADR detection approaches. The experiment results show that the proposed method has great potential in ADRs detection. To the best of our knowledge, this is the first time to investigate quantum computing to detect ADRs from social media big data.
INDEX TERMS: Social media big data | Adverse drug reactions (ADRs) | Bi-directional Long Short-Term Memory (Bi-LSTM) | Quantum Bi-LSTM with attention (QBi-LSTMA).
مقاله انگلیسی
15 Algebraic Attacks on Block Ciphers Using Quantum Annealing
حملات جبری به رمزهای بلوکی با استفاده از آنیل کوانتومی-2022
Drug combination is very common in the course of disease treatment. However, it inevitably increases the overall risk of adverse drug reactions (ADRs). It is very important to early and accurately detect and identify the potential ADRs for combined medication safety and public health. Social media is an important pharmacovigilance data source for ADR detection. But the data are complex, mass, clutter, highly sparse, so it is difficult to detect the ADR information from these data. Deep learning stands out in terms of increased accuracy. However, it takes a lot of training time and requires a lot of computing power. Quantum computing has strong parallel computing capability, and requires less computing power. By introducing attention mechanism and quantum computing into Bi-directional Long Short-Term Memory (Bi-LSTM), a quantum Bi-LSTM with attention (QBi-LSTMA) model is constructed for ADR detection from social media big data. QBi-LSTMA is composed of 6 variable component subcircuits (VQC) stacked. Under the condition that the main topology of Bi-LSTM remains unchanged, the biases of QBi-LSTMA in input gate, forgetting gate, candidate memory unit and output gate are removed to simplify the network structure, and the weight and active value qubits of the model are used to update the network weight. The performance of the proposed method is evaluated on the SMM4H dataset, comparing with one traditional ADR detection method and three deep learning based ADR detection approaches. The experiment results show that the proposed method has great potential in ADRs detection. To the best of our knowledge, this is the first time to investigate quantum computing to detect ADRs from social media big data.
INDEX TERMS: Social media big data | Adverse drug reactions (ADRs) | Bi-directional Long Short-Term Memory (Bi-LSTM) | Quantum Bi-LSTM with attention (QBi-LSTMA).
مقاله انگلیسی
16 An integrated solution of software and hardware for environmental monitoring
راه حل یکپارچه نرم افزاری و سخت افزاری برای نظارت محیطی-2022
With the expansion of the Internet of Things (IoT), several monitoring solutions are available in the market. However, most solutions use proprietary software, which is costly and do not provide online monitoring, hampering data access and hindering preventive actions. This article presents LimnoStation, a low-cost integrated hardware and software solution that employs IoT concepts with LoRaWan, whose main objective is to monitor environmental and oceanographic data from surface and submerged sensors, which can be accessed online and has low-power consumption. Long-distance transmission tests were performed analyzing battery consumption and readings taken by the LimnoStation sensors. The results show that the average error of sensor readings was 0.51%, with a battery life of more than 2900 days and costing about 100 times less compared to commercial sensors. The evaluation of the LimnoStation showed that it is viable not only for academic use, but also as a replacement for presenting lower cost, high reliability, greater integration, and more functionality than most solutions found on the market.
Keywords: IoT | LoRaWan | LoRa | Environmental monitoring
مقاله انگلیسی
17 Intellectual engagements of accounting academics: The ‘forecasted losses intervention
تعاملات ذهنی دانشگاهی حسابداری: مداخله زیان پیش بینی شده-2021
This paper explores the social and political potential of accounting scholarship, presenting and discussing an intellectual intervention challenging a legislative reform that significantly affected Spanish industrial relations. In this reform, an accounting artifact (forecasted losses) played an unexpected role and was misrepresented, prompting a sizeable number of scholars to sign two manifestos in 2010 and 2012 against the use of forecasted losses made by the new legislation. As promoters of this manifesto, we perform in this paper a collaborative autoethnography to reflect on the context, events, reactions, and significance of this intervention for both the academic and the industrial relations fields. We mobilize Pierre Bourdieu’s ideas on the public intellectual to think more generally about academic engagements in the interplay between accounting, poli- cymaking, and social issues. This intervention illustrates the different manners in which admin- istrative and economic powers interfered in the Spanish accounting academic field, limiting the disposition of Spanish scholars to engage in public debates. We also interpret our engagement as mobilizing intellectual capital to expose how the notion of forecasted losses was used to produce a form of symbolic violence and how this capital is more effective as it produces messages addressed to the producers, i.e., policymakers and the judicature in this specific case.
keywords: حسابداری انتقادی | روابط صنعتی | مداخلات فکری | انعکاس | Critical accounting | Industrial relations | Intellectual interventions | Reflexivity
مقاله انگلیسی
18 A multi-objective fuzzy robust stochastic model for designing a sustainable-resilient-responsive supply chain network
یک مدل تصادفی محکم فازی چند هدفه برای طراحی یک شبکه زنجیره تأمین پایدار ، قابل انعطاف و پاسخگو-2021
This study proposes a multi-objective mixed-integer programming model to configure a sustainable supply chain network while considering resilience and responsiveness measures. The model aims at minimizing the total costs and environmental damages while maximizing the social impacts, as well as the responsiveness and resilience levels of the supply chain network. An improved version of the fuzzy robust stochastic optimization approach is proposed to tackle the uncertain data arising in the dynamic business environment. Furthermore, a new version of meta-goal programming named the multi-choice meta-goal programming associated with a utility function is developed to solve the resulting multi-objective model. A case study in the water heater industry is investigated to illustrate the application of the proposed model and its solution approach. The numerical results validate the proposed model and the developed solution method. Finally, interactions between the sustainability, responsiveness, and resilience dimensions are investigated and several sensitivity analyses are performed on critical parameters by which useful managerial insights are provided.
Keywords: Supply chain network design | Sustainability | Resilience | Responsiveness | Fuzzy robust stochastic optimization | Multi-choice meta-goal programming
مقاله انگلیسی
19 Improvements in biometric health measures among individuals with intellectual disabilities: A controlled evaluation of the Fit 5 program
بهبود اقدامات سلامت بیومتریک در افراد دارای معلولیت فکری: ارزیابی کنترل شده از برنامه Fit 5-2021
Background: Individuals with intellectual disabilities (ID) have poorer health statuses compared to the general population. Actions are needed to address
health disparities and promote healthy lifestyles among individuals with ID. Moreover, studies that consider program settings for this population are needed. Objective: The Special Olympics health program, Fit 5, was evaluated to assess effectiveness in improving health measures for individuals with ID. The settings of programs’ implementation were also considered. Methods: Four Special Olympics basketball teams participated as an intervention group, and three teams as a control group, in a study of the Fit 5 program that was implemented during, and as part of, a regular 8-week basketball season. Resting heart rate (RHR) and blood pressure, and height and weight to calculate Body Mass Index (BMI), were measured before and after the program. Differences in pre- and post-measures were compared between the two groups with paired samples t-tests and ANCOVA. Results: Participants in the intervention group had significantly greater improvements in resting systolic and diastolic blood pressures (p ¼ 0.02 and 0.03, respectively) and RHR (p ¼ 0.003). BMI increased for both groups; however, the increase in the intervention group was significantly less (p ¼ 0.006). The Special Olympics setting was considered familiar and supportive and effectively reached individuals with ID.
Conclusion: The Fit 5 program positively impacts RHR and blood pressure, and could help reduce extents of BMI increases, in individuals with ID when implemented in a common setting. Further investigation of the impact of Fit 5 and similar programs in additional settings is warranted.© 2020 Elsevier Inc. All rights reserved.
Keywords: Intellectual disability | Health promotion | Physical activity | Health risk factors | Program settings
مقاله انگلیسی
20 Accounts of NGO performance as calculative spaces: Wild Animals, wildlife restoration and strategic agency
حساب های عملکرد سازمان های غیر دولتی به عنوان فضاهای محاسباتی: حیوانات وحشی، ترمیم حیات وحش و آژانس استراتژیک-2021
Whereas corporations typically share a common primary objective of generating profits for their owners, non-governmental organisations (NGOs) principally pursue a panoply of various social and/or ecological objectives. Accordingly, an NGO’s performance in pursuit of its objectives can rarely be accounted for in straightforwardly comparable quantitative terms. How then can an NGO instead construct qualitative accounts of its performance that show how it makes a differ- ence in pursuit of its objectives? This paper examines qualitative accounts of performance against an objective to restore wildlife, which are included in the annual reports of a large conservation NGO. These accounts are conceptualised as being calculative spaces, configured by framing work being done within these accounts. Analysis of this framing work finds that these accounts identify a performance object (i.e. specific wild animal populations), establish relations that seemingly affect this performance object (i.e. threats to wild animal populations and actions to conserve these populations), and attribute the NGO with agency to make a difference to this performance object (i.e. as a strategic actor directing and co-ordinating wildlife restoration). Thus, this paper demonstrates that seeing quantitative and qualitative accounts of organisational performance in the same conceptual terms creates conditions of possibility for developing a fuller understanding of an organisation’s calculations of its own capacity to act upon society.
keywords: سازمان غیر دولتی | مسئوليت | کادر بندی | محاسبات | گفتمان | حفاظت | NGO | Accountability | Framing | Calculation | Discourse | Conservation
مقاله انگلیسی
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