Incremental labeling in closed-2PM model

We consider an incremental optimal label placement in a closed-2PM map containing points each attached with a label. Labels are assumed to be axis-parallel square-shaped and have to be pairwise disjoint with maximum possible length each attached to its corresponding point on one of its horizontal edges. Such a labeling is denoted as optimal labeling. Our goal is to efficiently generate a new optimal labeling for all points after each new point being inserted in the map. Inserting each point may require several labels to flip or all labels to shrink. We present an algorithm that generates each new optimal labeling in O(lgn+k) time where k is the number of required label flips, if there is no need to shrink the label lengths, or in O(n) time when we have to shrink the labels and flip some of them. The algorithm uses O(n) space in both cases. This is a new result on this problem.     

Decision system for a team of autonomous underwater vehicles—Preliminary report

The paper presents preliminary research whose main goal is to build a ship protection system. One of the elements of the system will be a sub-system responsible for capturing and destroying/neutralizing all dangerous objects occurring inside a guarded area. This task will be performed by a team of autonomous underwater vehicles. To construct a decision system for the vehicles, i.e. the system whose task is to provide high-level decisions regarding direction and velocity of move, many different methods can be applied. Examples are evolutionary neural networks and expert systems with fuzzy decision rules. To test usefulness of the above methods in a role of the decision system, experiments in a predator-prey problem were carried out. In the experiments, the task of vehicles-predators was to capture a vehicle-prey behaving by a simple deterministic strategy. The current paper is a report on all the experiments mentioned.     

Parallel merged multiplier-accumulator coprocessor optimized for digital filters

In an attempt to improve the speed of VLSI signal processing systems, a new architecture for a high-speed multiply-accumulate (MAC) unit optimized for digital filters is proposed. This unit is designed as a coprocessor for the LEON2 RISC processor [LEON2 Processor; 2005 [Online]. <http://www.gaisler.com/products/leon2/leon.html>]. In this work, four parallel MAC units with two dual-port coefficient register-files, a three-port general register-file and a control unit are included in the coprocessing block. With the existence of four parallel units, several SIMD format instructions have been added to LEON2 instruction set. Each MAC unit has two 16-bit inputs, 32-bit output register and a programmable round-saturate block. The MAC unit uses a new architecture which embeds the accumulate module within the partial products summation tree of the multiplier with minimum overhead. A central control unit controls inputs of the four MACs and loading of the output registers. Our experimental results demonstrate a high performance in implementation of digital filters at elevated speeds of up to 33 millions of input samples per second in a 0.18 μm technology.     

Influence of phosphate species on green rust I transformation and local structure and morphology of γ-FeOOH

To clarify the role of phosphate in the formation of corrosion products, the transformation of GRI(Cl⁻) with the addition of phosphate was characterized through XRD, TEM, and solution analysis. Electrochemical analysis showed that the transformation of GRI(Cl⁻) was delayed and the size of the final products, i.e., γ-FeOOH was reduced in the phosphate added case. X-ray absorption spectroscopy indicated that the neighboring Fe–Fe coordination number of FeO₆ octahedral unit in γ-FeOOH was decreased. These effects of phosphate are attributed to its adsorption on GRI(Cl⁻) and nucleated γ-FeOOH that prevented particle growth during oxidation process.     

Understanding social networking sites adoption in China: A comparison of pre-adoption and post-adoption

Prior experience is an important determinant factor of individual behavior. This paper developed a theoretical model to predict the adoption intention of pre-adopters and post-adopters on social networking sites based on the theory of planned behavior. Using data from online surveys of netizens in China, the proposed model was tested in the context of pre-adoption and post-adoption by using the Partial Least Squares (PLS) technique. Then, multi-groups analysis was explored to compare the difference between the two groups. The results show that attitude, subjective norm and perceived behavior control have significant effect on the adoption intention of pre-adopters and post-adopters, and there is no significant difference between the two groups. In addition, information, meeting new people, and conformity motivations have the same significant effect on both groups. However, entertainment motivation has a significant effect on pre-adopters but connecting with old friends has none; in contrast, connecting with old friends has significant effect on post-adopters while entertainment motivation has no significant effect.     

Microscale surface thermometry using SU8/Rhodamine-B thin layer

In the present paper, we propose a microscale surface thermometry using SU8/Rhodamine-B thin layer (SRTL). The ultra-thin SRTL is coated on the microheater which serves as a heat source for microscale heating. Surface-temperature distribution of the SRTL is measured with high spatial and temperature resolutions in a temperature range between 30 and 80 °C. Propagation of isotherms on the SRTL is visualized with a temperature resolution on the order of 0.1 °C. Spatial error in the measurement was analyzed, which depends on the size of interrogation window. The present concept of SU8 thin film in combination with Rhodamine-B signifies a considerable improvement in the indirect measurement method of surface temperature inside polymer-based microfluidic channels.     

Clipping algorithms for solving the nearest point problem over reduced convex hulls

The nearest point problem (NPP), i.e., finding the closest points between two disjoint convex hulls, has two classical solutions, the Gilbert-Schlesinger-Kozinec (GSK) and Mitchell-Dem’yanov-Malozemov (MDM) algorithms. When the convex hulls do intersect, NPP has to be stated in terms of reduced convex hulls (RCHs), made up of convex pattern combinations whose coefficients are bound by a μ<1 value and that are disjoint for suitable μ. The GSK and MDM methods have recently been extended to solve NPP for RCHs using the particular structure of the extreme points of a RCH. While effective, their reliance on extreme points may make them computationally costly, particularly when applied in a kernel setting. In this work we propose an alternative clipped extension of classical MDM that results in a simpler algorithm with the same classification accuracy than that of the extensions already mentioned, but also with a much faster numerical convergence.     

Learning low-rank Mercer kernels with fast-decaying spectrum

Low-rank representations have received a lot of interest in the application of kernel-based methods. However, these methods made an assumption that the spectrum of the Gaussian or polynomial kernels decays rapidly. This is not always true and its violation may result in performance degradation. In this paper, we propose an effective technique for learning low-rank Mercer kernels (LMK) with fast-decaying spectrum. What distinguishes our kernels from other classical kernels (Gaussian and polynomial kernels) is that the proposed always yields low-rank Gram matrices whose spectrum decays rapidly, no matter what distribution the data are. Furthermore, the LMK can control the decay rate. Thus, our kernels can prevent performance degradation while using the low-rank approximations. Our algorithm has favorable in scalability—it is linear in the number of data points and quadratic in the rank of the Gram matrix. Empirical results demonstrate that the proposed method learns fast-decaying spectrum and significantly improves the performance.