Cryptanalysis of an iterated halving-based hash function: CRUSH

Iterated Halving has been suggested as a replacement to the Merkle?Damga?rd (MD) construction in 2004 anticipating the attacks on the MDx family of hash functions. The CRUSH hash function provides a specific instantiation of the block cipher for Iterated Halving. The authors identify structural problems with the scheme and show that they can trivially identify collisions and second preimages on many equal-length messages of length ten blocks or more. The cost is ten decryptions of the block cipher, this being less than the generation of a single digest. In addition, these attacks can be used to differentiate CRUSH from a random oracle in O(1). The authors show that the complexity of finding a preimage in the unpadded CRUSH with the length encoding is negligible and extend this attack on CRUSH with the length encoding in cost O(2/sup 32/). This attack is a multi-preimage attack, since the attacker can produce a large number of messages for a given message digest for the cost of O(2/sup 32/). Hence, this attack can be used as a multi-collision and a multisecond- preimage as well. They show that if the attacker knows the last 64-bits of the message digest in advance, he can do the time-consuming part of the attack off-line. The authors show that even if Iterated Halving is repaired, the construction has practical issues that means it is not suitable for general deployment.     

Decoupled adaptive neuro-fuzzy (DANF) sliding mode control system for a Lorenz chaotic problem

This paper introduces a decoupled adaptive neuro-fuzzy (DANF) sliding mode control system for the chaos control problem in a system without precise system model information. It has on-line learning ability to deal with the parametric uncertainty and disturbance by adjusting the control parameters and no constrained conditions and prior knowledge of the controlled plant is required in the design process. Also, a decoupled adaptive sliding mode controller is developed to control the chaotic Lorenz system for comparison. Finally, the effectiveness of the proposed decoupled adaptive sliding mode and DANF sliding mode controllers are demonstrated by some simulated results.     

An efficient parallel algorithm for the longest path problem in meshes

The longest path problem is the problem of finding a simple path with the maximum number of vertices in a given graph, and so far it has been solved polynomially only for a few classes of graphs. This problem generalizes the well-known Hamiltonian path problem, hence it is NP-hard in general graphs. In this paper, first we give a sequential linear-time algorithm for the longest path problem in meshes. Then based on this algorithm, we present a constant-time parallel algorithm for the problem, which can be run on every parallel machine.     

A powerful hybrid clustering method based on modified stem cells and Fuzzy C-means algorithms

One of the simple techniques for Data Clustering is based on Fuzzy C-means (FCM) clustering which describes the belongingness of each data to a cluster by a fuzzy membership function instead of a crisp value. However, the results of fuzzy clustering depend highly on the initial state selection and there is also a high risk for getting the best results when the datasets are large. In this paper, we present a hybrid algorithm based on FCM and modified stem cells algorithms, we called it SC-FCM algorithm, for optimum clustering of a dataset into K clusters. The experimental results obtained by using the new algorithm on different well-known datasets compared with those obtained by K-means algorithm, FCM, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) Algorithm demonstrate the better performance of the new algorithm.     

Weighted label propagation based on Local Edge Betweenness

The Journal of Supercomputing - In complex networks, especially social networks, networks could be divided into disjoint partitions. However, nodes could be partitioned such that the number of...     

Multiresolution HVS and statistically based image coding scheme

In this paper a novel multiresolution human visual system and statistically based image coding scheme is presented. It decorrelates the input image into a number of subbands using a lifting based wavelet transform. The codec employs a novel statistical encoding algorithm to code the coefficients in the detail subbands. Perceptual weights are applied to regulate the threshold value of each detail subband that is required in the statistical encoding process. The baseband coefficients are losslessly coded. An extension of the codec to the progressive transmission of images is also developed. To evaluate the performance of the coding scheme, it was applied to a number of test images and its performance with and without perceptual weights is evaluated. The results indicate significant improvement in both subjective and objective quality of the reconstructed images when perceptual weights are employed. The performance of the proposed technique was also compared to JPEG and JPEG2000. The results show that the proposed coding scheme outperforms both coding standards at low compression ratios, while offering satisfactory performance at higher compression ratios.     

The sequence of precipitation in the Al-Mg-Si-Cu alloy AA6111

The preciptation behavior of the aluminum alloy AA6111 in the advanced stages of aging has been studied using differential scanning calorimetry (DSC), transmission electron microscopy (TEM), and high-resolution TEM (HRTEM). The results have demonstrated the formation of various precipitate types and morphologies of quaternaryQ phase andβ (Mg₂Si) families at the peak-aged condition and during overaging at different temperatures. The work has clarified the sequence ofQ phase formation and showed evidence for a new morphology of this phase. The sequence of precipitation in AA6111 is elaborated in light of the new findings.     

Symbiotic artificial immune system

Artificial Immune System algorithms use antibodies that fully specify the solution of an optimization, learning, or pattern recognition problem. By being restricted to fully specified antibodies, an AIS algorithm cannot make use of schemata or classes of partial solutions, while sub solutions can help a lot in faster emergence of a totally good solution in many problems. To exploit schemata in artificial immune systems, this paper presents a novel algorithm that combines traditional artificial immune systems and symbiotic combination operator. The algorithm starts searching with partially specified antibodies and gradually builds more and more specified solutions till it finds complete answers. The algorithm is compared with CLONALG algorithm on several multimodal function optimization and combinatorial optimization problems and it is shown that it is faster than CLONALG on most problems and can find solutions in problems that CLONALG totally fails.     

Nonisothermal suspension polymerization of vinyl chloride for enhanced productivity

In the present study, a mathematical model is developed to numerically predict nonisothermal batch suspension polymerization of vinyl chloride. Free volume theory was used to consider diffusion‐controlled reactions. Model predictions were validated against field data obtained in a pilot scale stirred tank reactor. Variable temperature trajectory was considered during the course of the reaction to improve productivity by reducing the polymerization time for a certain conversion. Variable temperature during the course of the polymerization was successfully implemented by considering the predefined K value. By using variable temperatures during the course of the reaction, the density of the short branches per 1,000 monomer units as a criterion for structure defect remained relatively unchanged. Maximum reduction in reaction time relative to the isothermal case with the same K value and final conversion was 44% for the best temperature trajectory. J. VINYL ADDIT. TECHNOL., 22:470–478, 2016. © 2015 Society of Plastics Engineers