با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
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1 |
On the Logical Error Rate of Sparse Quantum Codes
در مورد میزان خطای منطقی کدهای کوانتومی پراکنده-2022 The quantum paradigm presents a phenomenon known as degeneracy that can potentially
improve the performance of quantum error correcting codes. However, the effects of this mechanism are
sometimes ignored when evaluating the performance of sparse quantum codes and the logical error rate is
not always correctly reported. In this article, we discuss previously existing methods to compute the logical
error rate and we present an efficient coset-based method inspired by classical coding strategies to estimate
degenerate errors and distinguish them from logical errors. Additionally, we show that the proposed method
presents a computational advantage for the family of Calderbank–Shor–Steane codes. We use this method
to prove that degenerate errors are frequent in a specific family of sparse quantum codes, which stresses
the importance of accurately reporting their performance. Our results also reveal that the modified decoding
strategies proposed in the literature are an important tool to improve the performance of sparse quantum
codes.
INDEX TERMS: Iterative decoding | quantum error correction (QEC) | quantum low density generator matrix codes | quantum low-density parity check (QLDPC) codes. |
مقاله انگلیسی |
2 |
Reconfiguration of electrical distribution network-based DG and capacitors allocations using artificial ecosystem optimizer: Practical case study
پیکربندی مجدد تخصیص DG و خازن مبتنی بر شبکه توزیع الکتریکی با استفاده از بهینه ساز اکوسیستم مصنوعی: مطالعه موردی عملی-2021 In this article, a new implementation of Artificial Ecosystem Optimizer (AEO) technique
is developed for distributed generators (DGs) and capacitors allocation considering the Reconfiguration of Power Distribution Systems (RPDS). The AEO is inspired from three energy transfer
mechanisms involving production, consumption, and decomposition in an ecosystem. In the production mechanism, the production operator allows AEO to produce a new individual randomly,
whereas the search space exploration can be improved as illustrated in the consumption mechanism
and exploitation can be performed in the decomposition. A practical case study of 59-bus Cairo distribution system in Egypt is simulated with different loading percentages. For optimizing the performance of that practical network, the AEO algorithm is employed for different scenarios. Besides,
the results obtained by recent optimization techniques which are Jellyfish Search Optimizer (JFS),
Supply Demand Optimizer (SDO), Crow Search Optimizer (CSO), Particle Swarm Optimization
(PSO), Grey Wolf Optimizer (GWO) and Whale Optimization Algorithm (WOA) are compared
with the developed AEO. The simulation results demonstrate the efficacies and superiority of the
AEO compared to the others. It surpasses the other algorithms in terms of obtaining the best, mean,
worst, and standard deviations. After optimal RPDS and DGs placements, the power losses are
decreased by 78.4, 77.84 and 71.4% at low, nominal and high levels, respectively. However, the best
scenario with its application prospects is mentioned after optimal RPDS, DGs, and capacitors
where the power losses are decreased by 68.8, 85.87 and 89.91% at low, nominal and high levels,
respectively.
KEYWORDS: Artificial ecosystem optimizer | Distributed generators | Electrical systems | Power losses | Reconfiguration |
مقاله انگلیسی |
3 |
DEGAN : شبکه های مولد متخاصم غیر متمرکز
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 9 - تعداد صفحات فایل doc فارسی: 23 در این مطالعه، یک چارچوب توزیع شده و غیرمتمرکز از شبکه های مولد متخاصم (GAN) بدون تبادل داده های آموزشی پیشنهاد شد. هر گره شامل مجموعه ی از داده محلی ، یک تفکیک کننده کننده و یک مولد است که فقط گرادیان ژنراتور آن با سایر گره ها به اشتراک گذاشته می شوند. در این مقاله ، تکنیک توزیع جدید معرفی می شود که در آن کارکنان مستقیماً با یکدیگر ارتباط برقرار می کنند و هیچ گره مرکزی وجود ندارد. نتایج تجربی ما در مجموعه داده های معیار ، عملکرد و دقت تقریباً یکسانی را در مقایسه با چارچوب های GAN متمرکز موجود نشان می دهد. چارچوب پیشنهادی به عدم یادگیری غیرمتمرکز برای GAN ها می پردازد.
کلمات کلیدی: یادگیری عمیق | شبکه های مولد متخاصم | یادگیری ماشین توزیع شده | معماری غیرمتمرکز |
مقاله ترجمه شده |
4 |
Energy storage behind-the-meter with renewable generators: Techno-economic value of optimal imbalance management
ذخیره انرژی پشت متر با ژنراتورهای تجدیدپذیر: ارزش فنی و اقتصادی مدیریت عدم تعادل مطلوب-2020 There is a growing body of evidence that energy storage systems can provide significant flexibility to the electricity grid. This study introduces a system comprising an energy storage unit connected behind-the-meter with a large-scale wind power generator. The associated constraints are derived from storage device and wind power parameters, and then implemented to carry out energy arbitrage, manage imbalance of the wind farm, and help the grid during times of peak demand in the winter. A suitable representation of the system components enables the straightforward implementation of energy storage dynamics in a purely linear rolling-planning optimisation framework. A case study is constructed for the simultaneous optimal allocation of energy to maximise profits, followed by a detailed financial investment analysis. It is demonstrated that a business case can be constituted only for the proposed energy imbalance management strategy, which also extends the cyclic lifetime of the storage unit. Keywords: Energy storage | Renewable energy sources | Business model | Energy markets | Capacity market |
مقاله انگلیسی |
5 |
PV generator and energy storage systems for laboratory building
ژنراتور PV و سیستم های ذخیره انرژی برای آزمایشگاه-2020 A microgrid contains a PV generator and energy storage system connected in a laboratory building. Power generation is
scheduled to meet the load of the building to adjust optimally the generation exchange within the microgrid. In this study,
the problem of decreasing the cost of energy under varied system constraints and user decisions is addressed. In addition,
minimizing electricity costs of the utility grid is proposed as an optimization model. To minimize the using of the grid, ESS
is scheduled according to the peak demand. The proposed algorithm schedules the charging and discharging of the battery.
A switching control technique is implemented for optimal scheduling of the hybrid system. Simulation is performed using
GAMS, the obtained results validate that the intended model can minimize the operation cost. Keywords: Day ahead | PV generation | Optimization | Multi objective scheduling | Energy management |
مقاله انگلیسی |
6 |
IEC 61850 based energy management system using plug-in electric vehicles and distributed generators during emergencies
IEC 61850 سیستم مدیریت انرژی مبتنی بر IEC با استفاده از وسایل نقلیه الکتریکی پلاگین و ژنراتور توزیع شده در مواقع اضطراری-2020 During emergencies, alternative power system operation that utilizes local assets to energize local loads will
change the face of the situation. While distributed generators (DGs) such as PV or wind turbines can be utilized
for generation, plug-in electric vehicles (PEVs) can act as mobile generators. Different strategies for forming
dynamic and networked microgrids utilizing the local generation during emergencies have been widely proposed
in literature. However, the underlying communication required for optimal formation of dynamic microgrids
and energy management during emergencies is not discussed. Addressing this gap, this paper develops a communication-
based energy management system for emergency cases based on IEC 61850 standard. The IEC 61850
based communication modeling provides interoperability and serves for plug-and-play purposes. Furthermore,
for establishing communication during emergencies the concept of Cognitive Radio (CR) is proposed in this
scheme. Simulation results show the feasibility of modeling and acceptability of its performance. Keywords: Emergency | Microgrid | Plugged in Electric Vehicle (PEV) | Vehicle-to-grid (V2G) | IEC 61850 and Communication modeling |
مقاله انگلیسی |
7 |
Measurement and evaluation of produced energy by thermoelectric generator in vehicle
اندازه گیری و ارزیابی انرژی تولید شده توسط ژنراتور حرارتی در خودرو-2020 Wasted heat from exhaust gas and the other parts of vehicles such as brake discs can be a daily great
source of energy for thermoelectric generators. Different features such as cross wind, vehicle speed, heat
sink structure, number of brakes during driving and engine operation influence the temperature of
exhaust and discs. Thus, measurement of vehicle’s wasted heat needs an accurate system. Hence, this
paper suggests a flexible measurement system along with a reliable sensor which transfers data with
high speed to a computer. The system measures temperature of heat resources during driving with considering
the real conditions. The measurement system is located on different places of exhaust and brake
discs. The transferred data is stored online in a computer for later applications including power and
energy calculation of thermoelectric generators. Due to time consuming and difficulties of the measurements
in all situations, an intelligent prediction algorithm is used to produce the extra data for various
conditions. The applied intelligent method in the algorithm is adaptive neuro fuzzy inference system
(ANFIS). The measured and estimated values are helpful to design an appropriate thermoelectric generator
system and energy management in hybrid vehicles. In order to validate the results, an experimental
prototype is built and used to compare the real data with theoretical one. Keywords: Adaptive neuro fuzzy inference system | Energy management | Electric vehicle | Experimental tests | Measurement system | Thermoelectric generator | Wasted power |
مقاله انگلیسی |
8 |
Discovering protein-binding RNA motifs with a generative model of RNA sequences
کشف نقوش RNA پروتئین اتصال با یک مدل تولیدی از توالی RNA-2020 Recent advances in high-throughput experimental technologies have generated a huge amount of data on interactions
between proteins and nucleic acids. Motivated by the big experimental data, several computational
methods have been developed either to predict binding sites in a sequence or to determine if an interaction exists
between protein and nucleic acid sequences. However, most of the methods cannot be used to discover new
nucleic acid sequences that bind to a target protein because they are classifiers rather than generators. In this
paper we propose a generative model for constructing protein-binding RNA sequences and motifs using a long
short-term memory (LSTM) neural network. Testing the model for several target proteins showed that RNA
sequences generated by the model have high binding affinity and specificity for their target proteins and that the
protein-binding motifs derived from the generated RNA sequences are comparable to the motifs from experimentally
validated protein-binding RNA sequences. The results are promising and we believe this approach will
help design more efficient in vitro or in vivo experiments by suggesting potential RNA aptamers for a target
protein Keywords: Protein-RNA interaction | Binding motif | Generator | Long short-term memory network |
مقاله انگلیسی |
9 |
On testing pseudorandom generators via statistical tests based on the arcsine law
در مورد آزمایش ژنراتورهای شبه تصادفی از طریق تست های آماری براساس قانون arcsine-2020 Testing the quality of pseudorandom number generators is an important issue. Security
requirements become more and more demanding, weaknesses in this matter are simply
not acceptable. There is a need for an in-depth analysis of statistical tests – one has to be
sure that rejecting/accepting a generator as good is not a result of errors in computations
or approximations. In this paper we propose a second level statistical test based on the
arcsine law for random walks. We provide upper bounds for the approximation of the
arcsine distribution, what allows us to perform a detailed error analysis of the proposed
test. Keywords: The arcsine law | Random walks | Pseudorandom number generator | Statistical testing | Second level testing | Dyck paths |
مقاله انگلیسی |
10 |
Theoretical Study of Superlubric Nanogenerators with Superb Performances
مطالعه نظری نانو ژنراتورهای Superlubric با عملکردهای عالی-2020 Nanogenerators promise self-powered sensors and devices for extensive
applications in internet of things, sensor networks, big data, personal healthcare
systems, artificial intelligence, et al. However, low electric current densities and
short product lifespans have blocked nanogenerators’ applications. Here we
show that structural superlubricity, a state of nearly zero friction and wear
between two contacted solid surfaces, provides a revolutionary solution to the
above challenge. We propose the first three types of superlubric nanogenerators
(SLNGs), namely the capacitor-based, triboelectric, and electret-based SLNGs.
With a systematical analysis on the influences of material and structural
parameters to these SLNGs’ performances, we demonstrate that these SLNGs
can achieve not only enduring lifespans, but also superb performances – three
orders of magnitude in current densities and output powers higher than those of
conventional nanogenerators. Furthermore, we show that SLNGs can be driven
by very weak external loads (down to ~1 ) in very low frequencies (down to
~ ), and are thus capable to harvest electric energies from an extremely
board spectrum of environments and biosystems. Among the three types of
SLNGs, the capacitor-based is synthetically most competitive in the senses of
performance, fabrication and maintaining. These theoretical results can guide
designs and accelerate fabrications of SLNGs toward real applications. Keywords: Structural superlubricity | Nanogenerators | Superb performances | Theoretical study |
مقاله انگلیسی |