با سلام خدمت کاربران عزیز، به اطلاع می رساند ترجمه مقالاتی که سال انتشار آن ها زیر 2008 می باشد رایگان بوده و میتوانید با وارد شدن در صفحه جزییات مقاله به رایگان ترجمه را دانلود نمایید.
الگوریتم تکاملی چند هدفه مبتنی بر شبکه عصبی برای زمانبندی گردش کار پویا در محاسبات ابری
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 16 - تعداد صفحات فایل doc فارسی: 45
زمانبندی گردشکار یک موضوع پژوهشی است که به طور گسترده در محاسبات ابری مورد مطالعه قرار گرفته است و از منابع ابری برای کارهای گردش کار استفاده می¬شود و برای این منظور اهداف مشخص شده در QoS را لحاظ می¬کند. در این مقاله، مسئله زمانبندی گردش کار پویا را به عنوان یک مسئله بهینه سازی چند هدفه پویا (DMOP) مدل می¬کنیم که در آن منبع پویایی سازی بر اساس خرابی منابع و تعداد اهداف است که ممکن است با گذر زمان تغییر کنند. خطاهای نرم افزاری و یا نقص سخت افزاری ممکن است باعث ایجاد پویایی نوع اول شوند. از سوی دیگر مواجهه با سناریوهای زندگی واقعی در محاسبات ابری ممکن است تعداد اهداف را در طی اجرای گردش کار تغییر دهد. در این مطالعه یک الگوریتم تکاملی چند هدفه پویا مبتنی بر پیش بینی را به نام الگوریتم NN-DNSGA-II ارائه می¬دهیم و برای این منظور شبکه عصبی مصنوعی را با الگوریتم NGSA-II ترکیب می¬کنیم. علاوه بر این پنج الگوریتم پویای مبتنی بر غیرپیش بینی از ادبیات موضوعی برای مسئله زمانبندی گردش کار پویا ارائه می¬شوند. راه¬حل¬های زمانبندی با در نظر گرفتن شش هدف یافت می¬شوند: حداقل سازی هزینه ساخت، انرژی و درجه عدم تعادل و حداکثر سازی قابلیت اطمینان و کاربرد. مطالعات تجربی مبتنی بر کاربردهای دنیای واقعی از سیستم مدیریت گردش کار Pegasus نشان می¬دهد که الگوریتم NN-DNSGA-II ما به طور قابل توجهی از الگوریتم¬های جایگزین خود در بیشتر موارد بهتر کار می¬کند با توجه به معیارهایی که برای DMOP با مورد واقعی پارتو بهینه در نظر گرفته می¬شود از جمله تعداد راه¬حل¬های غیرغالب، فاصله¬گذاری Schott و شاخص Hypervolume.
|مقاله ترجمه شده|
Truth finding by reliability estimation on inconsistent entities for heterogeneous data sets
یافتن حقیقت با برآورد قابلیت اطمینان در واحدهای متناقض برای مجموعه داده های ناهمگن-2020
An important task in big data integration is to derive accurate data records from noisy and conflicting values collected from multiple sources. Most existing truth finding methods assume that the reliability is consistent on the whole data set, ignoring the fact that different attributes, objects and object groups may have different reliabilities even wrt the same source. These reliability differences are caused by the hardness differences in obtaining attribute values, non-uniform updates to objects and the differences in group privileges. This paper addresses the problem how to compute truths by effectively estimating the reliabilities of attributes, objects and object groups in a multi-source heterogeneous data environment. We first propose an optimization framework TFAR, its implementation and Lagrangian duality solution for Truth Finding by Attribute Reliability estimation. We then present a Bayesian probabilistic graphical model TFOR and an inference algorithm applying Collapsed Gibbs Sampling for Truth Finding by Object Reliability estimation. Finally we give an optimization framework TFGR and its implementation for Truth Finding by Group Reliability estimation. All these models lead to a more accurate estimation of the respective attribute, object and object group reliabilities, which in turn can achieve a better accuracy in inferring the truths. Experimental results on both real data and synthetic data show that our methods have better performance than the state-of-art truth discovery methods.
Keywords: Truth finding | Attribute reliability | Object reliability | Group reliability | Entity hardness | Probability graphical mod
Use of a big data analysis technique for extracting HRA data from event investigation reports based on the Safety-II concept
استفاده از روش تجزیه و تحلیل داده های بزرگ برای استخراج داده های مجموعه فعالان حقوق بشر از رویداد گزارش تحقیقات بر اساس مفهوم ایمنی-II-2020
The safe operation of complex socio-technical systems including NPPs (Nuclear Power Plants) is a determinant for ensuring their sustainability. From this concern, it should be emphasized that a large portion of safety significant events were directly and/or indirectly caused by human errors. This means that the role of an HRA (Human Reliability Analysis) is critical because one of its applications is to systematically distinguish error-prone tasks triggering safety significant events. To this end, it is very important for HRA practitioners to access diverse HRA data which are helpful for understanding how and why human errors have occurred. In this study, a novel approach is suggested based on the Safety-II concept, which allows us to collect HRA data by considering failure and success cases in parallel. In addition, since huge amount of information can be gathered if the failure and success cases are simultaneously involved, a big data analysis technique called the CART (Classification And Regression Tree) is applied to deal with this problem. As a result, it seems that the novel approach proposed by combining the Safety-II concept with the CART technique is useful because HRA practitioners are able to get HRA data with respect to diverse task contexts.
Keywords: Human reliability analysis | Nuclear power plant | Safety-II | Classification and regression tree | Event investigation report
Rigor and reproducibility for data analysis and design in the behavioral sciences
دقت و تکرارپذیری برای تجزیه و تحلیل داده ها و طراحی در علوم رفتاری-2020
The rigor and reproducibility of science methods depends heavily on the appropriate use of statistical methods to answer research questions and make meaningful and accurate inferences based on data. The increasing analytic complexity and valuation of novel statistical and methodological approaches to data place greater emphasis on statistical review. We will outline the controversies within statistical sciences that threaten rigor and reproducibility of research published in the behavioral sciences and discuss ongoing approaches to generate reliable and valid inferences from data. We outline nine major areas to consider for generally evaluating the rigor and reproducibility of published articles and apply this framework to the 116 Behaviour Research and Therapy (BRAT) articles published in 2018. The results of our analysis highlight a pattern of missing rigor and reproducibility elements, especially pre-registration of study hypotheses, links to statistical code/output, and explicit archiving or sharing data used in analyses. We recommend reviewers consider these elements in their peer review and that journals consider publishing results of these rigor and reproducibility ratings with manuscripts to incentivize authors to publish these elements with their manuscript.
KEYWORDS: statistics | big data | reproducibility | reliability | p-hacking
A new measure of wind power variability with implications for the optimal sizing of standalone wind power systems
اندازه گیری جدیدی از تغییرات انرژی باد با پیامدهای لازم برای اندازه بهینه سیستمهای بادی مستقل-2020
This paper proposes a new measure of wind power variability and investigates the impacts of wind power variability on the optimal sizing of Standalone Wind Power (SWP) systems. The proposed new measure of the wind power variability in the frequency domain, which mainly includes a cumulative energy distribution index and a fluctuation factor, is applied to assess the variability of wind power throughout 6 consecutive years from 6 far apart sites from latitude 0e50 across America. Big data assessment results indicate the intermittent wind power at one site can be treated as Quasi-Time- Invariant (QTI) in the frequency domain. Big data simulations of the six SWP systems with the same residential load demand at the six sites provide QTI responses of the power supply reliability against the sizing of the system components in the mitigation of wind power variability. A case study of optimal sizing of a SWP system at Chicago, was carried out, which aims to minimize the system cost while satisfying the requirement of power supply reliability. It can be found from the study that, the proposed approach provides a new way to significantly reduce the computation in the optimal sizing of SWP systems.
Keywords: Wind power variability measurement | Standalone wind power system | Power fluctuation mitigation | Power supply reliability | Optimal sizing
Development of reversible and durable thermochromic phase-change microcapsules for real-time indication of thermal energy storage and management
توسعه میکروکپسولهای تغییر فاز گرمایشی برگشت پذیر و بادوام برای نشان دادن زمان واقعی ذخیره انرژی و مدیریت انرژی-2020
We reported a design of novel thermochromic phase-change microcapsules (TCMs) with a sandwich-structured shell for reversible and durable indication of thermal energy storage and management in real-time. Two types of TCMs with red and blue color indicators were successfully constructed by fabricating a silica base shell onto the n-docosane core, followed by formation of a thermochromic indication layer and a polymeric protective layer, and their multilayered configuration and well-defined core-shell structure were confirmed by microstructural investigation and chemical composition analysis. These two types of TCMs not only showed an outstanding latent heat-storage/release capability with a high capacity over 150 J/g, but also exhibited a good shape stability, high thermal stability and excellent phase-change reversibility and durability. The optimum operation conditions for thermal energy charge/discharge were also determined by nonisothermal and isothermal differential scanning calorimetric analyses. Most of all, the two types of TCMs presented an entirely reversible thermochromic behavior individually with high-contrast red and blue color indications for the phase-change state of n-docosane core. Both of them exhibited high reversibility and long cycle life in thermochromic indication, which meets the design requirements for durable indication of latent heat storage and thermal management in real-time. In the light of an innovative configuration of sandwich-structured shell and a smart combination of latent heat-storage and thermochromic functions, the TCMs designed by this study has a great potential for applications in smart fibers and textiles, wearable electric devices, energy-saving buildings, temperature- sensitive medical system, safety clothing, smart windows, aerospace engineering and many more.
Keywords: Phase-change microcapsules | Sandwich-structured configuration | Reversible thermochromic behavior | Thermal energy storage | Reliability and durability
The trustworthiness of travel and tourism information sources of social media: perspectives of international tourists visiting Ethiopia
قابلیت اطمینان سفر و منابع اطلاعات گردشگری رسانه های اجتماعی: چشم اندازهای گردشگران بین المللی که از اتیوپی بازدید می کنند-2020
Credibility of social media travel information sources is one of the most debatable topics among scholars. This research is designed to address the trustworthiness of travel and tourism information sources of social media platforms. Cross-sectional research design and convenience sampling was applied. Statistical Package for Social Science version 23 was employed to compute mean, one sample T-test, independent sample T-test and one-way Analysis of variance. Eta squared was calculated to measure the effect size or magnitude of mean difference. The effective sample size is 310 visitors. The findings revealed that visitors had a positive perception towards the trustworthiness of social media travel information sources. Visitors with the age of 18–35 years have a higher level of agreement towards the trustworthiness of social media travel information sources. As the age of visitors increases, the mean scores marginally decreases where the lowest mean scores lay on visitors who are above 46 years. Limitations and managerial/industrial implications are detailed.
Keywords: Digital ecosystem | e-word of mouth | International visitors | Traditional media | Trustworthiness | Tourist destination | Ethiopia | Tourism | Information science | Business | Technology management | Management | Marketing
A reliable PUF in a dual function SRAM
PUF قابل اعتماد در SRAM با عملکرد دوگانه-2019
The Internet of Things (IoTs) employs resource-constrained sensor nodes for sensing and processing data that require robust, lightweight cryptographic primitives. The SRAM Physical Unclonable Function (SRAM-PUF) is a potential candidate for secure key generation. An SRAM-PUF is able to generate random and unique cryptographic keys based on start-up values by exploiting intrinsic manufacturing process variations. The reuse of the available on-chip SRAM memory in a system as a PUF might achieve useful cost efficiency. However, as CMOS technology scales down, aging-induced Negative Bias Temperature Instability (NBTI) becomes more pronounced resulting in asymmetric degradation of memory bit cells after prolonged storage of the same bit values. This causes unreliable start-up values for an SRAM-PUF. In this paper, the on-chip memory in the ARM architecture has been used as a case study to investigate reliability in an SRAM-PUF. We show that the bit probability in a 32-bit ARM instruction cache has a predictable pattern and hence predictable aging. Therefore, we propose using an instruction cache as a PUF to save silicon area. Furthermore, we propose a bit selection technique to mitigate the NBTI effect. We show that this technique can reduce the predicted bit error in an SRAM-PUF from 14.18% to 5.58% over 5 years. Consequently, as the bit error reduces, the area overhead of the error-correction circuitry is about 6 × smaller compared to that without a bit selection technique.
Keywords: Aging | Physical unclonable function | SRAM | Reliability
Analytical games for knowledge engineering of expert systems in support to Situational Awareness: The Reliability Game case study
بازی های تحلیلی برای مهندسی دانش سیستم های خبره در حمایت از آگاهی وضعیتی: مطالعه موردی بازی اطمینان-2019
Knowledge Acquisition (KA) methods are of paramount importance in the design of intelligent systems. Research is ongoing to improve their effectiveness and efficiency. Analytical games appear to be a promis- ing tool to support KA. In fact, in this paper we describe how analytical games could be used for Knowl- edge Engineering of Bayesian networks, through the presentation of the case study of the Reliability Game. This game has been developed with the aim of collecting data on the impact of meta-knowledge about sources of information upon human Situational Assessment in a maritime context. In this paper we describe the computational model obtained from the dataset and how the card positions, which reflect a player belief, can be easily converted in subjective probabilities and used to learn latent constructs, such as the source reliability, by applying the Expectation-Maximisation algorithm.
Keywords: Source reliability | Expert knowledge | Knowledge acquisition | Bayesian networks | Parameter learning | Analytical game
An improved certificateless aggregate signature scheme without bilinear pairings for vehicular ad hoc networks
یک طرح امضایی جمع دارایی دارای قابلیت اطمینان بدون جفت شدن دوقطبی برای شبکه های ادهاک وسایل نقلیه-2019
Certificateless aggregate signature (CL-AS) is a digital signature technique used to achieve improved per- formance in resource-constrained environments like vehicular ad hoc networks (VANETs) by eliminating the certificate issue in the traditional public key cryptography (PKC), addressing the key escrow problem in identity-based PKC, and utilizing the efficiency benefits of aggregate signature. Recently, an efficient CL- AS scheme for VANETs was proposed which the authors claimed to be existentially secure against forgery attacks in the random oracle model. In this paper, the scheme was analyzed and found to be insecure under existing security model. Consequently, we propose a new efficient certificateless aggregate signa- ture scheme for VANETs applications based on elliptic curve cryptography. The proposed scheme does not only meet the privacy and security requirements for VANETs, but supports batch verification, auton- omy, and conditional privacy preservation. In addition, the proposed scheme is provably secure against existential forgery on adaptive chosen message attack in the random oracle model based on the hardness assumption of the elliptic curve discrete logarithm problem. Extensive efficiency analysis demonstrates that the performance of the proposed scheme exceeds those of the recent related schemes in terms of computation cost and communication overhead.
Keywords: Certificateless aggregate signature | Vehicular ad hoc networks (VANETs) | Random oracle | Elliptic curve cryptography | Conditional privacy | Batch verification