Multiscale retinex is one of the most popular image enhancement methods. However, its control parameters, such as Gaussian kernel sizes, gain, and offset, should be tuned carefully according to the image contents. In this letter, we propose a new method that optimizes the parameters using practical swarm optimization and multi-objective function. The method iteratively verifies the visual quality (i.e. brightness, contrast, and colorfulness) of the enhanced image using a multi-objective function while subtly adjusting the parameters. Experimental results shows that the proposed method achieves better image quality qualitatively and quantitatively compared with other image enhancement methods.

Advanced metering infrastructure (AMI) is a kind of wireless sensor network that provides two-way communication between smart meters and city utilities in the neighborhood area of the smart grid. And the routing protocol for low-power and lossy network (RPL) is being considered for use in AMI networks. However, there still exist several problems that need to be solved, especially with respect to QoS guarantees. To address these problems, an improved algorithm of RPL based on triangle module operator named as TMO is proposed. TMO comprehensively evaluates routing metrics: end-to-end delay, number of hops, expected transmission count, node remaining energy, and child node count. Moreover, TMO uses triangle module operator to fuse membership functions of these routing metrics. Then, the node with minimum rank value will be selected as preferred parent (the next hop). Consequently, the QoS of RPL-based AMI networks can be guaranteed effectively. Simulation results show that TMO offers a great improvement over several the most popular schemes for RPL like ETXOF, OF-FL and additive composition metric manners in terms of network lifetime, average end-to-end delay, average packet loss ratio, average hop count from nodes to root, etc.

Recognition of second language (L2) speech is a challenging task even for state-of-the-art automatic speech recognition (ASR) systems, partly because pronunciation by L2 speakers is usually significantly influenced by the mother tongue of the speakers. Considering that the expressions of non-native speakers are usually simpler than those of native ones, and that second language speech usually includes mispronunciation and less fluent pronunciation, we propose a novel method that maximizes unified acoustic and linguistic objective function to derive a phoneme set for second language speech recognition. The authors verify the efficacy of the proposed method using second language speech collected with a translation game type dialogue-based computer assisted language learning (CALL) system. In this paper, the authors examine the performance based on acoustic likelihood, linguistic discrimination ability and integrated objective function for second language speech. Experiments demonstrate the validity of the phoneme set derived by the proposed method.

A novel Two-dimensional Fuzzy Discriminant Locality Preserving Projections (2D-FDLPP) algorithm is proposed for learning effective subspace of two-dimensional images. The 2D-FDLPP algorithm is derived from the Two-dimensional Locality Preserving Projections (2D-LPP) by exploiting both fuzzy and discriminant properties. 2D-FDLPP algorithm preserves the relationship degree of each sample belonging to given classes with fuzzy k-nearest neighbor classifier. Also, it introduces between-class scatter constrain and label information into 2D-LPP algorithm. 2D-FDLPP algorithm finds the subspace which can best discriminate different pattern classes and weakens the environment factors according to soft assignment method. Therefore, 2D-FDLPP algorithm has more discriminant power than 2D-LPP, and is more suitable for recognition tasks. Experiments are conducted on the MNIST database for handwritten image classification, the JAFFE database and Cohn-Kanade database for facial expression recognition and the ORL database for face recognition. Experimental results reported the effectiveness of our proposed algorithm.

This paper presents two halftoning methods to improve efficiency in generating structurally similar halftone images using Structure Similarity Index Measurement (SSIM). Proposed Method I reduces the pixel evaluation area by applying pixel-swapping algorithm within inter-correlated blocks followed by phase block-shifting. The effect of various initial pixel arrangements is also investigated. Proposed Method II further improves efficiency by applying bit-climbing algorithm within inter-correlated blocks of the image. Simulation results show that proposed Method I improves efficiency as well as image quality by using an appropriate initial pixel arrangement. Proposed Method II reaches a better image quality with fewer evaluations than pixel-swapping algorithm used in Method I and the conventional structure aware halftone methods.

An improved algorithm of Guided Local Search called objective function adjustment algorithm is proposed for combinatorial optimization problems. The performance of Guided Local Search is improved by objective function adjustment algorithm using multipliers which can be adjusted during the search process. Moreover, the idea of Tabu Search is introduced into the objective function adjustment algorithm to further improve the performance. The simulation results based on some TSPLIB benchmark problems showed that the objective function adjustment algorithm could find better solutions than Local Search, Guided Local Search and Tabu Search.

In this paper, we describe a worst-case design optimization approach for statistical design of integrated circuits with a circuit performance model scheme. After formulating worst-case optimization to an unconstrained multi-objective function minimization problem, a new objective function is proposed to find an optimal point. Then, based on an interpolation model scheme of approximating circuit performance, realistic worst-case analysis can be easily done by Monte Carlo based method without increasing much the computational load. The effectiveness of the presented approach is demonstrated by a standard test function and a practical circuit design example.