Demonstration of the double Q^2-rescaling model

In this paper we have demonstrated the double Q^2-rescaling model (DQ^2RM) of parton distribution functions of nucleon bounded in nucleus. With different x-region of l-A deep inelastic scattering process we take different approach: in high x-region (0.1\le x\le 0.7) we use the distorted QCD vacuum model which resulted from topologically multi -connected domain vacuum structure of nucleus; in low x-region (10^{-4}\le x\le10^{-3}) we adopt the Glauber (Mueller) multi- scattering formula for gluon coherently rescattering in nucleus. From these two approach we justified the rescaling parton distribution functions in bound nucleon are in agreement well with those we got from DQ^2RM, thus the validity for this phenomenologically model are demonstrated.Comment: 19 page, RevTex, 5 figures in postscrip

What about the contribution from reggeons in hard process of strong interactions?

We discuss in this paper the possible contributions from R_\rho(\rho-reggeon associated with \rho meson) in DIS process on protons. Using results from phenomenological analysis of high energy \pi-N charge-exchanged scattering process, we get the expression of effective propagator of R_\rho and the coupling constant \beta_\rho between R_\rho and light quarks. As a simple and concrete example, we use them to evaluate the contributions of R_\rho to F_2(x,Q^2) from charge-exchanged photoproduction quark-pair process,\gamma^* + p-->n + q_u + \bar{q}_d (--> n + X), in HERA kinematical regions. For a comparison, we also evaluate contributions both from pomeron and partons in the same process. The ratio of contributions in F_2(x,Q^2) from R_\rho versus IP is larger than 1%, therefore, the former may be tested experimentaly.Comment: 13 page, LaTex, 4 figure in postscript. To appear in Commu. in Theor. Phy

Numerical modelling of moisture motion in heterogeneous soils using 1D-MIRBF method

In the present paper, we develop an efficient and accurate numerical approach based on one-dimensional-moving integrated radial basis function (1D-MIRBF) and fully implicit modified Picard method for simulating fluid movement in heterogeneous soils governed by the highly non-linear Richards equation. The major advantages of the proposed 1D-MIRBF method include (i) a banded sparse system matrix that helps reduce the computational cost; (ii) the Kronecker Delta property of the constructed shape functions, which helps impose the essential boundary conditions in an exact manner; and (iii) high accuracy and fast convergence rate owing to the use of the IRBF approximation. The performance of the present method is demonstrated through several 1--D and 2--D soil infiltration problems. Numerical results obtained are in agreement with other published results in the literature. This solver for moisture motion in soils will be incorporated into a surface-water-flow solver to handle the surface irrigation problem

An Image-Based Rice Weighing Estimation Approach on Clock Type Weighing Scale Using Deep Learning and Geometric Transformations

AI impacts surrounding human life, such as the economy, health, education, and agricultural production; however, the crop prices in the harvest season are still on manual calculation, which causes doubts about accuracy. In this study, an image-based approach is proposed to help farmers calculate rice prices more accurately. YOLOv5 is used to detect and extract the scales in the images taken from the harvesting of rice crops. Then, various image processing techniques, such as brightness balance, background removal, etc., are compiled to determine the needle position and number on the extracted scale. Lastly, geometric transformations are proposed to calculate the weight. A real dataset of 709 images is used for the experiment. The proposed method achieves good results in terms of [email protected] at 0.995, mAP@[0.5:0.95] at 0.830 for scale detection, and MAE at 3.7 for weight calculation

Energy-efficient secure outsourcing decryption of attribute based encryption for mobile device in cloud computation

This is a copy of the author 's final draft version of an article published in the "Journal of ambient intelligence and humanized computing". The final publication is available at Springer via http://dx.doi.org/10.1007/s12652-017-0658-2In this paper two new ways for efficient secure outsourcing the decryption of key-policy attribute-based encryption (KP-ABE) with energy efficiency are proposed. Based on an observation about the permutation property of the access structure for the attribute based encryption schemes, we propose a high efficient way for outsourcing the decryption of KP-ABE, which is suitable for being used in mobile devices. But it can only be used for the ABE schemes having tree-like access structure for the self-enclosed system. The second way is motivated from the fact that almost all the previous work on outsourcing the decryption of KP-ABE cares little about the ciphertext length. Almost all the previous schemes for secure outsourcing the decryption of ABE have linear length ciphertext with the attributes or the policy. But transferring so long ciphertexts via wireless network for mobile phone can easily run out of battery power, therefore it can not be adapted to practical application scenarios. Thus another new scheme for outsourcing the decryption of ABE but with constant-size ciphertexts is proposed. Furthermore, our second proposal gives a new efficient way for secure outsourcing the decryptor’s secret key to the cloud, which need only one modular exponentiation while all the previous schemes need many. We evaluate the efficiency of our proposals and the results show that our proposals are practical.Peer ReviewedPostprint (author's final draft

Predicting water allocation trade prices using a hybrid Artificial Neural Network-Bayesian modelling approach

This paper proposes an integrated (hybrid) Artificial Neural Network-Bayesian (ANN-B) modelling approach to improve the accuracy of predicting seasonal water allocation prices in Australia’s Murry Irrigation Area, which is part of one of the world’s largest interconnected water markets. Three models (basic, intermediate and full), accommodating different levels of data availability, were considered. Data were analyzed using both ANN and hybrid ANN-B approaches. Using the ANN-B modelling approach, which can simulate complex and non-linear processes, water allocation prices were predicted with a high degree of accuracy (RBASIC = 0.93, RINTER. = 0.96 and RFULL = 0.99); this was a higher level of accuracy than realized using ANN. This approach can potentially be integrated with online data systems to predict water allocation prices, enable better water allocation trade decisions, and improve the productivity and profitability of irrigated agriculture

3-(4-{3,3,4,4,5,5-Hexafluoro-2-[5-(3-methoxy­phen­yl)-2-methyl-3-thien­yl]cyclo­pent-1-en­yl}-5-methyl-2-thien­yl)benzonitrile

The title compound, C29H19F6NOS2, is a new unsymmetrical photochromic diarylethene derivative with different meta-phenyl substituents. The distance between the two reactive (i.e. can be irradiated to form a new chemical bond) C atoms is 3.501 (4) Å; the dihedral angles between the mean plane of the main central cyclo­pentene ring and the thio­phene rings are 47.7 (5) and 45.1 (2)°, and those between the thio­phene rings and the adjacent benzene rings are 29.4 (2) and 28.4 (3)°. The three C atoms and the F atoms of hexa­fuorocyclo­pentene ring are disordered over two positions, with site-occupancy factors of 0.751 (4) and 0.249 (4)