摘要：
Phosphorylation is the major post-translation modification to proteins, and it can be classified as kinase-specific and non-kinase-specific. This paper focuses on the prediction methods of non-kinase-specificity and using Dou's dataset of phosphorylation sites as the template, this paper develops a position-based chi-square table feature, χ~2-pos, and then integrates this feature with the pseudo position-specific scoring matrix (PsePSSM). A Support Vector Machine (SVM) classifier with balanced positive and negative samples was created, and the S, T, Y independent testing results for the Matthew correlation coefficient, the inferior surface integral of the ROC curve and the precision were (0.59, 0.87, 79.74%), (0.55, 0.85, 77.68%) and (0.50, 0.81, 75.22%), respectively, which are significantly superior to the results reported previously. The integration of the χ~2-pos and the PsePSSM offers a promising method to predict phosphorylation sites more accurately in proteins.
摘要：
The rapid development of many open source and commercial image editing software makes the authenticity of the digital images questionable. Copy-move forgery is one of the most widely used tampering techniques to create desirable objects or conceal undesirable objects in a scene. Existing techniques reported in the literature to detect such tampering aim to improve the robustness of these methods against the use of JPEG compression, blurring, noise, or other types of post processing operations. These post processing operations are frequently used with the intention to conceal tampering and reduce tampering clues. A robust method based on the color moments and other five image descriptors is proposed in this paper. The method divides the image into fixed size overlapping block. Clustering operation divides entire search space into smaller pieces with similar color distribution. Blocks from the tampered regions will reside within the same cluster since both copied and moved regions have similar color distributions. Five image descriptors are used to extract block features, which makes the method more robust to post processing operations. An ensemble of deep compositional pattern-producing neural networks are trained with these extracted features. Similarity among feature vectors in clusters indicates possible forged regions. Experimental results show that the proposed method can detect copy-move forgery even if an image was distorted by gamma correction, addictive white Gaussian noise, JPEG compression, or blurring. (C) 2016 Published by Elsevier Ireland Ltd.
关键词：
Cache;Multi-core;task scheduling;schedule length;average response time
摘要：
In the past few years, multi-core processors incorporating four, six, eight, or more cores on a single die have become ubiquitous. Those cores, having their own private caches, often share a higher level cache memory, which leads to compete among different tasks. This can seriously affect the average performance of multi-core systems as the probability of cache hit could be lowered. In realizing this, we study the problem of scheduling bag-of-tasks (BoT) applications with shared cache constraint on multi-core systems. We first use cache space isolation techniques to divide shared caches into partitions. Then, we give a motivational example and outline the shared cache aware scheduling problem of multi-core systems. Finally, to provide an optimum solution for this problem, we propose a heuristic shared cache contention aware scheduling (SCAS) algorithm on multi-core systems. Our extensive simulation performance evaluation study clearly demonstrate that our proposed SCAS algorithm outperforms the existing traditional scheduling algorithm Min-min and the modified algorithm MSCAS in terms of schedule length and average response time.
摘要：
The amount of energy needed to operate high-performance computing systems increases regularly since some years at a high pace, and the energy consumption has attracted a great deal of attention. Moreover, high energy consumption inevitably contains failures and reduces system reliability. However, there has been considerably less work of simultaneous management of system performance, reliability, and energy consumption on heterogeneous systems. In this paper, we first build the precedence-constrained parallel applications and energy consumption model. Then, we deduce the relation between reliability and processor frequencies and get their parameters approximation value by least squares curve fitting method. Thirdly, we establish a task execution reliability model and formulate this reliability and energy aware scheduling problem as a linear programming. Lastly, we propose a heuristic Reliability-Energy Aware Scheduling REAS algorithm to solve this problem, which can get good tradeoff among system performance, reliability, and energy consumption with lower complexity. Our extensive simulation performance evaluation study clearly demonstrates the tradeoff performance of our proposed heuristic algorithm. The amount of energy needed to operate high-performance computing systems increases regularly since some years at a high pace, and the energy consumption has attracted a great deal of attention. Moreover, high energy consumption inevitably contains failures and reduces system reliability. However, there has been considerably less work of simultaneous management of system performance, reliability, and energy consumption on heterogeneous systems. In this paper, we first build the precedence-constrained parallel applications and energy consumption model. Then, we deduce the relation between reliability and processor frequencies and get their parameters approximation value by least squares curve fitting method. Thirdly, we establish a task execution reliability model and formulate this reliability and energy aware scheduling problem as a linear programming. Lastly, we propose a heuristic Reliability-Energy Aware Scheduling REAS algorithm to solve this problem, which can get good tradeoff among system performance, reliability, and energy consumption with lower complexity. Our extensive simulation performance evaluation study clearly demonstrates the tradeoff performance of our proposed heuristic algorithm.
摘要：
Nutrition diagnosis plays a key role in the crop’s growth, which has mainly been carried out in the field by agricultural workers. Currently, automatic nutrition recognition technologies have been widely used in this field. A procedure is proposed in this paper to diagnose nitrogen nutrition non-destructively for rapeseed qualitatively based on the multifractal theory. Twelve texture parameters are given by the method of multifractal detrended fluctuation (MF-DFA), which contains six generalized Hurst exponents and six relative multifractal parameters that are used as features of the rapeseed leaf images for identifying the two nitrogen levels, namely, the N-mezzo and the N-wane. For the base leaves, central leaves and top leaves of the rapeseed plant and the three-section mixed samples, three parameters combinations are selected to conduct the work. Five classifiers of Fisher’s linear discriminant algorithm (LDA), extreme learning machine (ELM), support vector machine and kernel method (SVMKM), random decision forests (RF) and K-nearest neighbor algorithm (KNN) are employed to calculate the diagnosis accuracy. An interesting finding is that the best diagnose accuracy is from the base leaves of the rapeseed plant. It is explained that the base leaf is the most sensitive to the nitrogen deficiency. The diagnose effect by the base leaves samples is outshining the existing result significantly for the same leaves samples. For the mixed samples, the averaged discriminant accuracy reaches 97.12% and 97.56% by SVMKM and RF methods with the 10-fold cross-validation respectively. The resulting high accuracy on N-levels identification shows the feasibility and efficiency of our method.
摘要：
Multi-proxy signature is a variant of proxy signature, which allows that a delegator may delegate his signing rights to many proxy signers. Compared with proxy signature, multi-proxy signature can effectively prevent that some of proxy signers abuse signing rights. In this paper, we propose an efficient multi-proxy signature scheme in the standard model, which is based on the Waters’ signature scheme. Compared with other multi-proxy signature schemes in the standard model, the proposed scheme further reduces the amount of computations and communications.
摘要：
Toxicity prediction can provide important information for environmental protection. The toxicity predictions of 228 alcohols and phenols were performed by quantitative structure-activity relationship (QSAR). Feature selection can reduce the training time of modelling, improve the prediction accuracy and enhance the interpretability of a model. Both dependent variables (toxicity) and independent variables (molecular descriptors) of the QSAR data sets are usually continuous variables. The well-known feature selection method, minimal redundancy maximal relevance (mRMR) can eliminate redundancy and extract relevant features effectively but can only be applied to discrete dependent variables. The distance correlation (dCor) can detect the nonlinear correlation of two continuous variables. In the present work, a new mRMR-dCor feature selection method was developed by combining mRMR with dCor and used to construct the QSAR models for three datasets based on the retained molecular descriptors and support vector regression (SVR). mRMR-dCor feature selection method showed better predication performance (the Q(2) of three datasets are 0.954, 0.941 and 0.981 respectively) than the reference feature selection methods and other methods reported in literature. In all, mRMR-dCor feature selection has a promising application prospect in the numerous domains of high dimensional feature selections such as QSAR.
关键词：
Almost periodic solution;Exponential dichotomy;Multidirectional associative memory neural networks;Multistability
摘要：
In this paper, the multiplicity of almost periodic solutions is studied for a multidirectional associative memory (MAM) neural network with almost periodic coefficients and continuously distributed delays. Under some assumptions on activation functions, some invariant subsets of the MAM neural network are constructed. The existence of multiple almost periodic solutions are obtained by using the theory of exponential dichotomy and Schauder's fixed point theorem. Furthermore, a sufficient condition is derived for the local exponential stability of some almost periodic solutions and their exponential attracting domains are also given. An example is given to illustrate the effectiveness of the results. (C) 2015 Elsevier B.V. All rights reserved.
摘要：
Most computational methods for identifying essential proteins focus on the topological centrality of protein-protein interaction (PPI) networks. However, these methods have limitations, such as the difficulty for identifying essential proteins with low centrality values and the poor performance for incomplete PPI network. In this paper, protein complex is proven to be an important factor for determining protein essentiality and a new centrality measure, complex centrality, is proposed. The weighted average of complex centrality and subgraph centrality, called harmonic centrality (HC), is proposed to predict essential proteins. It combines PPI network topology and protein complex information and has better performance than methods based on PPI network. The improvement is higher when the PPI network is incomplete. Furthermore, a weighted PPI network is generated by integrating cellular localisation and biological process to a PPI network. The performance of HC measure is improved 5% in this weighted PPI network.
摘要：
This paper is concerned with a discrete predator-prey model with Holling II functional response and delays. Applying Gaines and Mawhin's continuation theorem of coincidence degree theory and the method of Lyapunov function, we obtain some sufficient conditions for the existence global asymptotic stability of positive periodic solutions of the model.
摘要：
A multidirectional associative memory (MAM) neural network with periodic coefficients and distributed delays is studied. By constructing a Poincaré mapping, some sufficient conditions are obtained ensuring existence, uniqueness and the global exponential stability of a periodic solution of MAM neural network. The result is new to MAM neural networks. An example is given to illustrate the effectiveness of the result.
