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1 |
Construction of CCZ transform for quadratic APN functions
ساخت تبدیل CCZ برای توابع APN درجه دوم-2019 Almost perfect nonlinear (APN) function is an important type of function in cryptography, especially quadratic APN function. Since
the notion of CCZ-equivalence developed, the construction of CCZ transform for APN functions to obtain new APN functions became a
critical issue in cryptography. Inspired by the result of Budaghyan who used Gold functions, this article gives the construction of CCZ
transform for all quadratic vectorial Boolean functions and proves that for quadratic APN functions, the functions transformed have
algebraic degree 3, thus EA-inequivalent to all quadratic functions, and have minimum algebraic degree 2, thus EA-inequivalent to
all power functions. Keywords: APN function | CCZ transform | Quadratic function | Power function | EA-equivalence |
مقاله انگلیسی |
2 |
Tomato volume and mass estimation using computer vision and machine learning algorithms: Cherry tomato model
حجم گوجه فرنگی و تخمین جرم با استفاده از الگوریتم های بینایی ماشین و یادگیری ماشین: مدل گوجه فرنگی گیلاس-2019 A prediction method of mass and volume of cherry tomato based on a computer vision system and machine
learning algorithms were introduced in this study. The relation between tomato mass and volume was established
as M = 1.312V 0.9551, and was used to estimate mass on a test dataset at an R2 of 0.9824 and RMSE of
15.84g. Depth images of tomatoes at different orientations were acquired and features extracted by image
processing techniques. Five regression prediction models based on 2D and 3D image features were developed.
The RBF-SVM outperformed all explored models with an accuracy of 0.9706 (only 2D features) and 0.9694 (all
features) in mass and volume estimation respectively. The model predicted mass or volume can then be applied
to the established mass-volume power function. This introduced system can be applied as a non-destructive,
accurate and consistent technique to in-line sorting and grading of cherry tomatoes based on mass, volume or
density. Keywords: Computer vision | Cherry tomato | Mass estimation | Machine learning algorithms | Volume estimation | Fruit sorting and grading |
مقاله انگلیسی |
3 |
Research on the characteristics of evolution in knowledge flow networks of strategic alliance under different resource allocation
تحقیقات بر روی ویژگی های تکامل در شبکه های جریان دانش از اتحاد استراتژیک تحت تخصیص منابع مختلف-2018 This paper takes the four types of resource allocation (randomly oriented, relationship-oriented, cooper
ation oriented, and knowledge-embedded) as its premise and investigates the complex characteristics of
knowledge flow network evolution in strategic alliances, taking into account the mutual variance effects
of the evolution mechanism. Existing research has neglected the differences in resource allocation types,
by and large employed statistical analysis methods, and identified only the linear relationships among
experimental variances of cross-sectional data. The present study differs from existing research in the
following ways: First, we thoroughly consider the multi-faceted nature of resource allocation. Second, we
use the method of multi-agent imitation according to perspective of dynamic system evolution and the
principle of phase theory, allowing the explicitly analysis of nonlinear functional logic, forms and pat
terns in the variance. Finally, we analyze the appropriateness of different resource allocation models. Our
paper features several significant findings: (1) The evolution of the knowledge flow network of a strate
gic alliance can produce a bifurcation phenomenon composed of saddle-node bifurcation and transcritical
bifurcation. (2) The number of nodes exhibits a logarithmic growth distribution, the connection intensity
and the network gain exhibit exponential growth distributions, and the connectivity and knowledge flow
frequency are mutually influential in the form of a power function. (3) Knowledge-embedded resource
allocation is most effective for improving the knowledge flow rate of networks and can further supply
ample impetus for evolution. (4) Cooperation-oriented resource allocation is most beneficial for quickly
propelling the network into the evolution realm. (5) Relationship-oriented resource allocation can aid
the network in capturing more profit. Furthermore, this research is beneficial for understanding the key
problems of each resource allocation model and the evolution of strategic alliance in knowledge flow
networks. Our proposed methods and framework can be more widely applied to the fields of complex
networks, knowledge management, and strategic innovation.
Keywords: Strategic alliance ، Knowledge flow ، Networks ، Evolution ، Resource allocation ، Characteristics |
مقاله انگلیسی |
4 |
Detrended cross-correlation analysis of urban traffic congestion and NO2 concentrations in Chengdu
Detrended تجزیه و تحلیل همبستگی متقاطع از تراکم ترافیک شهری و غلظت NO2 در Chengd-2017 In urban congested road sections, usually there exhibits elevated exhaust emissions due to
longer idling and more frequent acceleration of vehicles. Using detrended cross-correlation
analysis (DCCA), the relationship between air pollution and traffic congestion in the urban
area of Chengdu was investigated. In order for a better quantification of the congested con
dition in a relatively large spatial region, a new measure, i.e., the congestion length (CL), is
developed, extracted, and estimated using the Google Real-Time Traffic Maps and GIS tech
nology. Relationships between the hourly average congestion length (HACL) and NO2 con
centrations in the urban area of Chengdu from 12 May to 17 May, 2013 were analyzed. A
high long-term cross-correlation between HACL and NO2 was observed, implying the ambi
ent NO2 concentration fluctuations are positively cross-correlated with urban traffic con
gestion in the form of a power function. However, the ambient NO2 concentration did
not respond immediately to the change of road traffic due to a relatively slow and lagged
photochemical reaction process. A time lagged cross-correlation was further analyzed and
showed that the time lag could be as large as 10 h. These findings can be used for improv
ing air quality forecasting accuracy by taking into account the time lags in correlation
between emissions and air quality.
Keywords: Detrended cross-correlation analysis | Traffic congestion | Hourly average congestion length | Vehicle emissions | Global positioning system |
مقاله انگلیسی |