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This paper proposes a planning system for empty container repositioning. It is said that movement of empty containers account for thirty percentage of movement of all containers. Moreover, empty container repositioning cost no less than 234 million dollars in 2010. Therefore, we have developed planning system to reduce the cost of repositioning empty containers. To achieve this purpose, we have developed...
Whole genome re-sequencing plays a crucial role in biomedical studies. The emergence of genomic big data calls for an enormous amount of computing power. However, current computational methods are inefficient in utilizing available computational resources. In this paper, we address this challenge by optimizing the utilization of the fastest supercomputer in the world - TH-2 supercomputer. TH-2 is...
In this study, central composite design (CCD) and response surface methodology (RSM) were applied to optimize the C/N and current density in a heterotrophic/biofilm-electrode autotrophic denitrification reactor (HAD-BER). Results showed that nitrate could be effectively reduced over a wide range of C/Ns (0.84–1.3535) and current densities (96.8–370.0mA/m 2 ); however, an optimum C/N of 1.13...
To reduce the fossil energy consumption and the operational expenses, the hybrid energy powered cellular network (HybENet) with BSs powered by on-grid or renewable energy is studied. To minimize the total expenses of energy consumption (EEC) and guarantee the quality of service of HybENet, a liquid cell management algorithm, which adaptively and cooperatively adjusts the service coverage of BSs according...
Kernel learning is an important research topic in the machine learning area. Research on self-optimization learning of kernel function and its parameter has an important theoretical value for solving the kernel selection problem widely endured by kernel learning machine, and has the same important practical meaning for the improving of kernel learning systems. In this paper, we focus on two schemes:...
This paper demonstrates that 2D pose SLAM has an underlining near convex structure when formulated as a least squares (LS) optimization problem. By introducing new variables and some approximations, the LS pose SLAM problem can be formulated as a quadratically constrained quadratic programming (QCQP) problem. The QCQP formulation can then be relaxed into a semi-definite programming (SDP) problem which...
In this paper, we propose a novel method for Super-Resolution Medical image based sparse representation, with the aim to solve the problem of MR image resolution owing to the limitations of hardware and acquisitions. With two coupled dictionaries the sparse representation of a low resolution medical image blocks is used to generate a high resolution. Some evaluations are implemented to compare with...
Map joining is an efficient strategy for solving feature based SLAM problems. This paper demonstrates that joining of two 2D local maps, formulated as a nonlinear least squares problem has at most two local minima, when the associated uncertainties can be described using spherical covariance matrices. Necessary and sufficient condition for the existence of two minima is derived and it is shown that...
Reducing delay is a key issue for nested Network Mobility (NEMO). When handover bursts out, the process of the Care-of Address (CoA) generation and the duplicate-address detection is much more time-consuming than other processes. In this paper, by utilizing the access router tree model and the Hash method, we propose a novel scheme for CoA configuration and a corresponding handover algorithm, to reduce...
Traffic microsimulation is a widely used tool in the field of computer-aided traffic engineering. In procedure of building traffic microsimulation model, the step of model calibration is difficult. Although several factors of calibration has been discussed by scholars, the calibration step has been handled by means of the experience of individual traffic engineer up to now. This unsystemic approach...
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