Proposing a new local density estimation outlier detection algorithm: an empirical case study on flow pattern experiments

Pattern Analysis and Applications - Outlier or anomaly detection is an important branch of data analysis that becomes a crucial task in many application domains. Data objects which significantly...     

Improved impossible differential and biclique cryptanalysis of HIGHT

HIGHT is a lightweight block cipher introduced in CHES 2006 by Hong et al as a block cipher suitable for low‐resource applications. In this paper, we propose improved impossible differential and biclique attacks on HIGHT block cipher both exploiting the permutation‐based property of the cipher's key schedule algorithm as well as its low diffusion. For impossible differential attack, we found a new 17‐round impossible differential characteristic that enables us to propose a new 27‐round impossible differential attack. The total time complexity of the attack is 2^120.4 where an amount of 2^59.3 chosen plaintext‐ciphertext pairs and 2^107.4 memory are required. We also instantiate a new biclique cryptanalysis of HIGHT, which is based on the new idea of splitting each of the forward and backward keys into 2 parts where the computations associated to each one are performed independently. The time complexity and data complexity of this attack are 2^125.7 and 2⁴², respectively. To the best of our knowledge, this is the fastest biclique attack on full‐round HIGHT.     

Phase Transformation Kinetics During Annealing of Cold-Rolled AISI 309Si Stainless Steel

Metallurgical and Materials Transactions A - The effects of cold rolling and the subsequent annealing were studied for the AISI 309Si stainless steel. During annealing of cold-rolled sheets, the...     

Generalized carrier to interference ratio analysis for shotgun cellular systems in multiple dimensions over composite Rayleigh–Lognormal (Suzuki) fading

Telecommunication Systems - This paper analyzes the carrier-to-interference ratio (CIR) of the so-called shotgun cellular systems (SCSs) in $$\tau $$ dimensions ( $$\tau =1, 2,$$ and 3). SCSs are...     

Efficient programmable power‐of‐two scaler for the three‐moduli set {2n+p, 2n − 1, 2n+1 − 1}

Scaling is an important operation because of the iterative nature of arithmetic processes in digital signal processors (DSPs). In residue number system (RNS)–based DSPs, scaling represents a performance bottleneck based on the complexity of inter‐modulo operations. To design an efficient RNS scaler for special moduli sets, a body of literature has been dedicated to the study of the well‐known moduli sets {2ⁿ ? 1, 2ⁿ, 2ⁿ + 1} and {2ⁿ, 2ⁿ ? 1, 2ⁿ⁺¹ ? 1}, and their extension in vertical or horizontal forms. In this study, we propose an efficient programmable RNS scaler for the arithmetic‐friendly moduli set {2^n+p, 2ⁿ ? 1, 2ⁿ⁺¹ ? 1}. The proposed algorithm yields high speed and energy‐efficient realization of an RNS programmable scaler based on the effective exploitation of the mixed‐radix representation, parallelism, and a hardware sharing technique. Experimental results obtained for a 130 nm CMOS ASIC technology demonstrate the superiority of the proposed programmable scaler compared to the only available and highly effective hybrid programmable scaler for an identical moduli set. The proposed scaler provides 43.28% less power consumption, 33.27% faster execution, and 28.55% more area saving on average compared to the hybrid programmable scaler.     

New Approaches for Estimation of Monthly Rainfall Based on GEP-ARCH and ANN-ARCH Hybrid Models

Accurate estimation of rainfall has an important role in the optimal water resources management, as well as hydrological and climatological studies. In the present study, two novel types of hybrid models, namely gene expression programming-autoregressive conditional heteroscedasticity (GEP-ARCH) and artificial neural networks-autoregressive conditional heteroscedasticity (ANN-ARCH) are introduced to estimate monthly rainfall time series. To fulfill this purpose, five stations with various climatic conditions were selected in Iran. The lagged monthly rainfall data was utilized to develop the different GEP and ANN scenarios. The performance of proposed hybrid models was compared to the GEP and ANN models using root mean square error (RMSE) and coefficient of determination (R²). The results show that the proposed GEP-ARCH and ANN-ARCH models give a much better performance than the GEP and ANN in all of the studied stations with various climates. Furthermore, the ANN-ARCH model generally presents better performance in comparison with the GEP-ARCH model.     

Evaluation of hydrogen effect on the fatigue crack growth behavior of medium-Mn steels via in-situ hydrogen plasma charging in an environmental scanning electron microscope

Fatigue crack growth(FCG)tests were conducted on a medium-Mn steel annealed at two intercritical annealing temperatures,resulting in different austenite(γ)to ferrite(α)phase fractions and different γ(meta-)stabilities.Novel in-situ hydrogen plasma charging was combined with in-situ cyclic loading in an environmental scanning electron microscope(ESEM).The in-situ hydrogen plasma charging increased the fatigue crack growth rate(FCGR)by up to two times in comparison with the reference tests in vacuum.Fractographic investigations showed a brittle-like crack growth or boundary cracking manner in the hydrogen environment while a ductile transgranular manner in vacuum.For both materials,the plastic deformation zone showed a reduced size along the hydrogen-influenced fracture path in comparison with that in vacuum.The difference in the hydrogen-assisted FCG of the medium-Mn steel with different microstructures was explained in terms of phase fraction,phase stability,yielding strength and hydrogen distribution.This refined study can help to understand the FCG mechanism without or with hydrogen under in-situ hydrogen charging conditions and can provide some insights from the applications point of view.