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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 |
Deep unsupervised methods towards behavior analysis in ubiquitous sensor data
روش های عمیق بدون نظارت برای تجزیه و تحلیل رفتار در داده های حسگر همه جا حاضر-2022 Behavioral analysis (BA) on ubiquitous sensor data is the task of finding the latent distribution of
features for modeling user-specific characteristics. These characteristics, in turn, can be used for a
number of tasks including resource management, power efficiency, and smart home applications.
In recent years, the employment of topic models for BA has been found to successfully extract the
dynamics of the sensed data. Topic modeling is popularly performed on text data for mining
inherent topics. The task of finding the latent topics in textual data is done in an unsupervised
manner. In this work we propose a novel clustering technique for BA which can find hidden
routines in ubiquitous data and also captures the pattern in the routines. Our approach efficiently
works on high dimensional data for BA without performing any computationally expensive
reduction operations. We evaluate three different techniques namely Latent Dirichlet Allocation
(LDA), the Non-negative Matrix Factorization (NMF), and the Probabilistic Latent Semantic
Analysis (PLSA) for comparative study. We have analyzed the efficiency of the methods by using
performance indices like perplexity and silhouette on three real-world ubiquitous sensor datasets
namely, the Intel Lab, Kyoto, and MERL. Through rigorous experiments, we achieve silhouette
scores of 0.7049 over the Intel Lab dataset, 0.6547 over the Kyoto dataset, and 0.8312 over the
MERL dataset for clustering. In these cases, however, it is di cult to validate the results obtained as
the datasets do not contain any ground truth information. Towards that, we investigate a self-
supervised method that will be capable of capturing the inherent ground truths that are avail-
able in the dataset. We design a self-supervised technique which we apply on datasets containing
ground truth and also without. We see that our performance on data without ground truth differs
from that with ground truth by approximately 8% (F-score) hence showing the efficacy of self-
supervised techniques towards capturing ground truth information. keywords: تحلیل داده های فراگیر | تحلیل رفتار | یادگیری خود نظارتی | Ubiquitous data analysis | Behavior analysis | Self supervised learning |
مقاله انگلیسی |
3 |
A Remote Security Computational Ghost Imaging Method Based on Quantum Key Distribution Technology
یک روش تصویربرداری شبح محاسباتی امنیت از راه دور بر اساس فناوری توزیع کلید کوانتومی-2022 Computational ghost imaging (CGI) is a method of acquiring object information by measuring
light field intensity, which would be used to achieve imaging in a complicated environment. The main issue
to be addressed in CGI technology is how to achieve rapid and high-quality imaging while assuring the secure
transmission of detection data in practical distant imaging applications. In order to address the mentioned
issues, this paper proposes a remote secure CGI method based on quantum communication technology.
Using the quantum key distribution (QKD) network, the CGI system can be reconstructed while solving the
problem of information security transmission between the detector and the reconstructed computing device.
By exploring the influence of different random measurement matrices on the quality of image reconstruction,
it is found that the randomness of the numerical sequence constituting the matrix is positively correlated
with the imaging quality. Based on this discovery, a new type of quantum cryptography measurement
matrix is constructed using quantum cryptography with good randomness. In addition, through further
orthogonalization and normalization of the matrix, the matrix has both good randomness and orthogonality,
and high-quality imaging results can be obtained at a low sampling rate. The feasibility and effectiveness of
the method are verified by simulation imaging experiments. Compared with the traditional GI system, the
method proposed in this paper has higher transmission security and high-quality imaging under this premise,
which provides a new idea for the practical development of CGI technology.
INDEX TERMS: Computational ghost imaging | quantum key distribution | quantum cryptography | measurement matrix | randomness | schimidt orthogonalization. |
مقاله انگلیسی |
4 |
Chemical adsorption on 2D dielectric nanosheets for matrix free nanocomposites with ultrahigh electrical energy storage
جذب شیمیایی روی نانوصفحات دی الکتریک دوبعدی برای نانوکامپوزیت های بدون ماتریس با ذخیره انرژی الکتریکی فوق العاده بالا-2021 Relaxor ferroelectric polymers display great potential in capacitor dielectric applications because of their
excellent flexibility, light weight, and high dielectric constant. However, their electrical energy storage
capacity is limited by their high conduction losses and low dielectric strength, which primarily originates
from the impact-ionization-induced electron multiplication, low mechanical modulus, and low thermal
conductivity of the dielectric polymers. Here a matrix free strategy is developed to effectively suppress
electron multiplication effects and to enhance mechanical modulus and thermal conductivity of a dielectric polymer, which involves the chemical adsorption of an electron barrier layer on boron nitride
nanosheet surfaces by chemically adsorbing an amino-containing polymer. A dramatic decrease of leakage current (from 2.4 106 to 1.1 107 A cm2 at 100 MV m1) and a substantial increase of breakdown strength (from 340 to 742 MV m1) were achieved in the nanocompostes, which result in a
remarkable increase of discharge energy density (from 5.2 to 31.8 J cm3). Moreover, the dielectric
strength of the nanocomposites suffering an electrical breakdown could be restored to 88% of the original
value. This study demonstrates a rational design for fabricating dielectric polymer nanocomposites with
greatly enhanced electric energy storage capacity.
Keywords: Boron nitride nanosheets | Electron barrier layer | Relaxor ferroelectric polymers | Nanocomposites | Electrical energy storage |
مقاله انگلیسی |
5 |
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 |
6 |
Cultural consensus knowledge of rice farmers for climate risk management in the Philippines
دانش اجماع فرهنگی کشاورزان برنج برای مدیریت ریسک آب و هوایی در فیلیپین-2021 Despite efforts and investments to integrate weather and climate knowledges, often dichotomized
into the scientific and the local, a top-down practice of science communication that tends to
ignore cultural consensus knowledge still prevails. This paper presents an empirical application of
cultural consensus analysis for climate risk management. It uses mixed methods such as focus
groups, freelisting, pilesorting, and rapid ethnographic assessment to understand farmers’
knowledge of weather and climate conditions in Barangay Biga, Oriental Mindoro, Philippines.
Multi-dimensional scaling and aggregate proximity matrix of items are generated to assess the
similarity among the different locally perceived weather and climate conditions. Farmers’
knowledge is then qualitatively compared with the technical classification from the government’s
weather bureau. There is cultural agreement among farmers that the weather and climate con-
ditions can be generally grouped into wet, dry, and unpredictable weather (Maria Loka).
Damaging hazards belong into two subgroups on the opposite ends of the wet and dry scale, that
is, tropical cyclone is grouped together with La Ni˜na, rainy season, and flooding season, while
farmers perceive no significant difference between El Ni˜no, drought, and dry spells. Ethnographic
information reveals that compared to the technocrats’ reductive knowledge, farmers imagine
weather and climate conditions (panahon) as an event or a phenomenon they are actively
experiencing by observing bioindicators, making sense of the interactions between the sky and
the landscape, and the agroecology of pest and diseases, while being subjected to agricultural
regulations on irrigation, price volatility, and control of power on subsidies and technologies. This
situated local knowledge is also being informed by forecasts and advisories from the weather
bureau illustrating a hybrid of technical science, both from the technocrats and the farmers, and
personal experiences amidst agricultural precarities. Speaking about the hybridity of knowledge
rather than localizing the scientific obliges technocrats and scientists to productively engage with
different ways of knowing and the tensions that mediate farmers’ knowledge as a societal
experience. keywords: دانش اجماع | پیش بینی آب و هوا | کشاورزی | خطر ابتلا به آب و هوا | Consensus knowledge | Weather forecasting | Agriculture | Climate risk |
مقاله انگلیسی |
7 |
Heat recovery in an actual LNG supply chain: Retrofitting of designed heat exchange networks (HENs) for potential fuel saving
بازیابی گرما در یک زنجیره تامین LNG واقعی: مقاوم سازی مجدد شبکه های تبادل گرما (HENs) برای صرفه جویی احتمالی در سوخت-2021 The demand for liquefied natural gas (LNG) is steadily increasing and projected to become an important component of global energy demand. Although LNG processing requires high-energy to convert the gas into liquid, it is still the most preferable method of supply due to technical, economic, safety, and political reasons. Energy integration strategies and process optimization between units have been emphasized as ways to reduce energy demand. In this study, a rigorous simulation for proposed heat exchanger networks (HENs) between sulfur recovery units (SRU) and gas sweetening units (GSU) that exhibit heat sources and sinks was conducted. The HENs were designed using pinch analysis tools in Aspen Energy Analyzer (AEA) and were used to determine the maximum energy recovery and potential fuel savings after retrofitting within LNG supply chain. The feasibility of retrofitting the HENs into LNG plant without affecting process conditions or product quality was also determined. Although universal HEN reduces energy consumption of the existing plant by 68%, the network complexity limits its practical application. Simplified HENs between the sub-units reduced energy demand by 50% and achieved fuel saving of 34%. Retrofitting HENs improved existing LNG energy integration, enhanced process economy, reduced fossil fuel burning and protected the environment. Keywords: Supply chain management | Risk management | Policy matrix |
مقاله انگلیسی |
8 |
Vision based prediction of surface roughness for end milling
پیش بینی مبتنی بر دید از زبری سطح برای فرز نهایی-2021 Measurement of surface roughness helps to assess the machined component’s functionality. In the past three decades, several scientists have contributed to the computation of surface roughness. This research article deals with two distinct methods for prediction of surface roughness employing the surface pro- filometer and machine vision for AISI 1040 steel specimens prepared by varying cutting parameters of end milling viz. feed rates, speed and cutting depth. Using a surface profilometer, the surface roughness parameters are evaluated. At the other hand, the texture features were extracted using a Gray Level Co- occurrence Matrix Algorithm (GLCM) and a computer vision system. Correlations are formed among characteristics of machined surface and the texture feature such as contrast, entropy, energy, and homogeneity. The comparable findings revealed a maximum relative error of —8% using contrast and energy, — 11% using entropy and —10% using homogeneity.© 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Materials, Processing & Characterization. Keywords: Surface roughness parameter | Gray Level Co-occurrence Matrix (GLCM) | Texture feature | Machine vision system | Linear regression |
مقاله انگلیسی |
9 |
Exploring learning processes associated with a cancer pain self-management intervention in patients and family caregivers: A mixed methods study
بررسی فرآیندهای یادگیری مرتبط با مداخله خود مدیریت سرطان در بیماران و مراقبت های خانوادگی: مطالعه یک روش ترکیبی -2021 Aim: Explore learning processes associated with a psychoeducational pain selfmanagement intervention.
Background: Self-management of cancer pain is challenging for patients and their family caregivers (FCs). While
psychoeducational interventions can support them to handle these tasks, it remains unclear how learning pro-
cesses are hampered or facilitated.
Methods: A convergent parallel mixed methods design with qualitative data collection embedded in a randomized
controlled trial (RCT) was used. Outpatients with cancer and FCs were recruited from three Swiss university
hospitals. The six-week intervention consisted of education, skills building, and nurse coaching. Quantitative
data on pain management knowledge and self-efficacy were analyzed using multilevel models. Patients and FCs
were interviewed post-RCT regarding their learning experiences. Qualitative data analysis was guided by
interpretive description. Finally, quantitative and qualitative data were integrated using case level comparisons
and a meta-matrix.
Results: Twenty-one patients and seven FCs completed this study. The group-by-time effect showed increases in
knowledge (p = 0.035) and self-efficacy (p = 0.007). Patients and FCs learning through experience was sup-
ported by an intervention nurse, who was perceived as competent and trustworthy. After the study, most
intervention group participants felt more confident to implement pain self-management. Finally, data integration
showed that declining health hampered some patients pain self-management.
Conclusions: Competent and trustworthy nurses can support patients and FCs pain self-management by providing
individualized interventions. Using a diary, jointly reflecting on the documented experiences, and addressing
knowledge deficits and misconceptions through the use of academic detailing can facilitate patients and FCs
learning of critical skills. keywords: سرطان | مدیریت درد | آموزش بیمار | روش های ترکیبی تحقیق | خودکار کارآمدی | Cancer | Pain management | Patient education | Mixed methods research | Self-efficacy |
مقاله انگلیسی |
10 |
Economic impact of the bioeconomy in Spain: Multiplier effects with a bio social accounting matrix
تأثیر اقتصادی اقتصاد زیستی در اسپانیا: اثرات چند برابری با ماتریس حسابداری زیست اجتماعی-2021 The bioeconomy emerges as a new economic model to help address issues related to environmental care
and focus on a more sustainable economy. In the last decade, it has become a global priority and many
countries have published their own strategies that clearly refer to the development of the bioeconomy.
The symmetric social accounting matrix with basic prices was constructed, including the breakdown of
biobased accounts belonging to the bioeconomy to determine which sectors of the bioeconomy are most
strategic to promote sustainable economic growth. This constructed matrix was used to analyse the
economic influence of the bioeconomy products and their impact on job creation. The analysis was
carried out using the diffusion and absorption multipliers, which enabled the interpretation of the
linkages between the different economic agents. The results were analysed in depth and the multipliers
decomposed into their different effects, own, open and circular, and complemented with the calculation
of the employment multiplier to evaluate the most important sectors for employment generation. The
analysis was applied to the case of Spain. The results of this research enabled the identification of the
strategic sectors where economic policies can be applied since these are the ones that increase economic
growth and activities within the bioeconomy and create jobs. The conclusions indicated that the Spanish
bioeconomy is still focused on traditional sectors and has not yet developed its potential in more
innovative biobased products, demonstrating that the bioeconomy in Spain still has a long way to go.
keywords: زیست توده | اسپانیا | ماتریس حسابداری اجتماعی | مدل های چند منظوره | آنالیز تاثیرات | ضغطه | Bioeconomy | Spain | Social accounting matrix | Multisectoral models | Impact analyses | Multipliers |
مقاله انگلیسی |