Immunity-based hybrid evolutionary algorithm for multi-objective optimization in global container repositioning

The development of evolutionary algorithms for optimization has always been a stimulating and growing research area with an increasing demand in using them to solve complex industrial optimization problems. A novel immunity-based hybrid evolutionary algorithm known as Hybrid Artificial Immune Systems (HAIS) for solving both unconstrained and constrained multi-objective optimization problems is developed in this research. The algorithm adopts the clonal selection and immune suppression theories, with a sorting scheme featuring uniform crossover, multi-point mutation, non-dominance and crowding distance sorting to attain the Pareto optimal front in an efficient manner. The proposed algorithm was verified with nine benchmarking functions on its global optimal search ability as well as compared with four optimization algorithms to assess its diversity and spread. Sensitivity analysis was also carried out to investigate the selection of key parameters of the algorithm. It is found that the developed immunity-based hybrid evolutionary algorithm provides a useful means for solving optimization problems and has successfully applied to the problem of global repositioning of containers, which is one of a constrained multi-objective optimization problem. The developed HAIS will assist shipping liners on timely decision making and planning of container repositioning operations in global container transportation business in an optimized and cost effective manner.     

A local experts organization model with application to face emotion recognition

This paper presents a novel approach for recognizing human facial emotion in order to further detect human suspicious behaviors. Instead of relying on relative poor representation of facial features in a flat vector form, the approach utilizes a format of tree structures with Gabor feature representations to present a facial emotional state. The novel local experts organization (LEO) model is proposed for the processing of this tree structure representation. The motivation for the LEO model is to deal with the inconsistent length of features in case there are some features failed to be detected. The proposed LEO model is inspired by the natural hierarchical model presented in natural organization, where workers (local experts) reports to their supervisor (fusion classifier), whom in turn reports to upper management (global fusion classifier). Moreover, an Asian emotion database is created. The database contains high-resolution images of 153 Asian subjects in six basic pseudo-emotions (excluding neutral expression) in three different poses for evaluating our proposed system. Empirical studies were conducted to benchmark our approach with other well-known classifiers applying to the system, and the results showed that our approach is the most robust, and less affected by noise from feature locators for the face emotion recognition system.     

Identification of tool and product effects in a mixed product and parallel tool environment

In the semiconductor manufacturing industry, production resembles an automated assembly line in which many similar products with slightly different specifications are manufactured step-by-step, with each step being a complicated physiochemical batch process performed by a number of tools. This constitutes a high-mix production system for which effective run-to-run control (RtR) and fault detection control (FDC) can be carried out only if the states of different tools and different products can be estimated. However, since in each production run, a specific product is performed on a specific tool, absolute individual states of products and tools are not observable. In this work, a novel state estimation method based on analysis of variance (ANOVA) is developed to estimate the relative states of each product and tool to the grand average performance of this station in the fab. The method is formulated in the form of a recursive state estimation using the Kalman filter. The advantages of this method are demonstrated using simulations to show that the correct relative states can be estimated in production scenarios such as tool-shift, tool-drift, product ramp-up, tool/product-offline and preventive maintenance (PM). Furthermore, application of this state estimation method in RtR control scheme shows that substantial improvements in process capabilities can be gained, especially for products with small lot counts. The proposed algorithm is also evaluated by an industrial application.     

A survey of aesthetics-driven image recomposition

The advancement of digital photography and the popularity of photo sharing social media such as Instagram and Facebook have undoubtedly stimulated growing interest in aesthetics quality improvement. One aspect of photography that contributes to high quality photos is image composition; the spatial arrangement of photo subjects in the image frame. Professional photographers often apply a wealth of photographic composition rules, e.g., rule of thirds, visual balance and simplicity to capture compelling photos. In the recent years, aesthetics-driven recomposition that attempts to computationally modify the composition of an image to mimic a professional photo has started to receive considerable research interest. Researchers have proposed numerous recomposition techniques that utilize a single or a combination of multiple image operators, i.e., cropping, warping and patch rearrangement operators, to modify the composition of an image. In this paper, we present a survey on the state-of-the-arts aesthetic-driven image recomposition. We define the image recomposition problem, outline its objectives, and provide a comprehensive review of the existing image recompositoin techniques, together with a detailed analysis of the effectiveness of each technique in achieving the recomposition objectives. This survey is intended as a good reference for researchers interested in image recomposition.     

Equivalence of Szegedy’s and coined quantum walks

Szegedy’s quantum walk is a quantization of a classical random walk or Markov chain, where the walk occurs on the edges of the bipartite double cover of the original graph. To search, one can simply quantize a Markov chain with absorbing vertices. Recently, Santos proposed two alternative search algorithms that instead utilize the sign-flip oracle in Grover’s algorithm rather than absorbing vertices. In this paper, we show that these two algorithms are exactly equivalent to two algorithms involving coined quantum walks, which are walks on the vertices of the original graph with an internal degree of freedom. The first scheme is equivalent to a coined quantum walk with one walk step per query of Grover’s oracle, and the second is equivalent to a coined quantum walk with two walk steps per query of Grover’s oracle. These equivalences lie outside the previously known equivalence of Szegedy’s quantum walk with absorbing vertices and the coined quantum walk with the negative identity operator as the coin for marked vertices, whose precise relationships we also investigate.     

A Graph‐based Approach to Continuous Line Illustrations with Variable Levels of Detail

This paper introduces a method for automatically generating continuous line illustrations, drawings consisting of a single line, from a given input image. Our approach begins by inferring a graph from a set of edges extracted from the image in question and obtaining a path that traverses through all edges of the said graph. The resulting path is then subjected to a series of post‐processing operations to transform it into a continuous line drawing. Moreover, our approach allows us to manipulate the amount of detail portrayed in our line illustrations, which is particularly useful for simplifying the overall illustration while still retaining its most significant features. We also present several experimental results to demonstrate that our approach can automatically synthesize continuous line illustrations comparable to those of some contemporary artists.     

RFID-initiated workflow control to facilitate patient safety and utilization efficiency in operation theater

Objective

To control the workflow for surgical patients, we in-cooperate radio-frequency identification (RFID) technology to develop a Patient Advancement Monitoring System (PAMS) in operation theater.

Methods

The web-based PAMS is designed to monitor the whole workflow for the handling of surgical patients. The system integrates multiple data entry ports Across the multi-functional surgical teams. Data are entered into the system through RFID, bar code, palm digital assistance (PDA), ultra-mobile personal computer (UMPC), or traditional keyboard at designated checkpoints. Active radio-frequency identification (RFID) tag can initiate data demonstration on the computer screens upon a patient's arrival at any particular checkpoint along the advancement pathway.

Results

The PAMS can manage the progress of operations, patient localization, identity verification, and peri-operative care. The workflow monitoring provides caregivers’ instant information sharing to enhance management efficiency.

Conclusion

RFID-initiate surgical workflow control is valuable to meet the safety, quality, efficiency requirements in operation theater.     

Structural application of a shape optimization method based on a genetic algorithm

This paper presents a structural application of a shape optimization method based on a Genetic Algorithm (GA). The method produces a sequence of fixed-distance step-wise movements of the boundary nodes of a finite element model to derive optimal shapes from an arbitrary initial design space. The GA is used to find the optimal or near-optimal combination of boundary nodes to be moved for a given step movement. The GA uses both basic and advanced operators. For illustrative purposes, the method has been applied to structural shape-optimization. The shape-optimization methodology presented allows local optimization, where only crucial parts of a structure are optimized as well as global shape-optimization which involves finding the optimal shape of the structure as a whole for a given environment as described by its loading and freedom conditions. Material can be removed or added to reach the optimal shape. Two examples of structural shape optimization are included showing local and global optimization through material removal and addition. Received October 14, 1999