Automatic collision avoidance of ships

One of the key elements in automatic simulation of ship manoeuvring in confined waterways is route finding and collision avoidance. This paper presents a new practical method of automatic trajectory planning and collision avoidance based on an artificial potential field and speed vector. Collision prevention regulations and international navigational rules have been incorporated into the algorithm. The algorithm is fairly straightforward and simple to implement, but has been shown to be effective in finding safe paths for all ships concerned in complex situations. The method has been applied to some typical test cases and the results are very encouraging

Electromagnetic and gravitational radiation from the coherent oscillation of electron-positron pairs and fields

Integrating equations of particle-number and energy-momentum conservation and Maxwell field equations, we study the oscillation and drift of electron and positron pairs coherently with fields after these pairs are produced in external electromagnetic fields. From the electric current of oscillating pairs, we obtain the energy spectrum of electromagnetic dipole radiation. This narrow spectrum is so peculiar that the detection of such radiation can identify pair production and oscillation in strong laser fields. We also obtain the energy spectrum of gravitational quadrapole radiation from the energy-momentum tensor of oscillating pairs and fields. Thus, we discuss the generation of gravitational waves on the basis of rapid development of strong laser fields.Comment: 6 pages, 4 figure

Efficient Microparticle Trapping with Plasmonic Annular Apertures Arrays

In this work, we demonstrate trapping of microparticles using a plasmonic tweezers based on arrays of annular apertures. The transmission spectra and the E- field distribution are simulated to calibrate the arrays. Theoretically, we observe sharp peaks in the transmission spectra for dipole resonance modes and these are redshifted as the size of the annular aperture is reduced. We also expect an absorption peak at approximately 1,115 um for the localised plasmon resonance. Using a laser frequency between the two resonances, multiple plasmonic hotspots are created and used to trap and transport micron and submicron particles. Experimentally, we demonstrate trapping of individual 0.5 um and 1 um polystyrene particles and particle transportation over the surface of the annular apertures using less than 1.5 mW/um2 incident laser intensity at 980 nm

CONFPROFITT: A CONFIGURATION-AWARE PERFORMANCE PROFILING, TESTING, AND TUNING FRAMEWORK

Modern computer software systems are complicated. Developers can change the behavior of the software system through software configurations. The large number of configuration option and their interactions make the task of software tuning, testing, and debugging very challenging. Performance is one of the key aspects of non-functional qualities, where performance bugs can cause significant performance degradation and lead to poor user experience. However, performance bugs are difficult to expose, primarily because detecting them requires specific inputs, as well as specific configurations. While researchers have developed techniques to analyze, quantify, detect, and fix performance bugs, many of these techniques are not effective in highly-configurable systems. To improve the non-functional qualities of configurable software systems, testing engineers need to be able to understand the performance influence of configuration options, adjust the performance of a system under different configurations, and detect configuration-related performance bugs. This research will provide an automated framework that allows engineers to effectively analyze performance-influence configuration options, detect performance bugs in highly-configurable software systems, and adjust configuration options to achieve higher long-term performance gains. To understand real-world performance bugs in highly-configurable software systems, we first perform a performance bug characteristics study from three large-scale opensource projects. Many researchers have studied the characteristics of performance bugs from the bug report but few have reported what the experience is when trying to replicate confirmed performance bugs from the perspective of non-domain experts such as researchers. This study is meant to report the challenges and potential workaround to replicate confirmed performance bugs. We also want to share a performance benchmark to provide real-world performance bugs to evaluate future performance testing techniques. Inspired by our performance bug study, we propose a performance profiling approach that can help developers to understand how configuration options and their interactions can influence the performance of a system. The approach uses a combination of dynamic analysis and machine learning techniques, together with configuration sampling techniques, to profile the program execution, analyze configuration options relevant to performance. Next, the framework leverages natural language processing and information retrieval techniques to automatically generate test inputs and configurations to expose performance bugs. Finally, the framework combines reinforcement learning and dynamic state reduction techniques to guide subject application towards achieving higher long-term performance gains

The impact of corporate governance on the choice of transfer pricing methods in China

Recent scandals involving related party transactions (RPTs) have attracted researchers’ and governments’ attention. Because imperfections exist in the legislation of RPTs, business groups might abuse transfer pricing of such transactions for certain purposes. These purposes include earnings management of listed companies that seek to attract investors and profit shifting from subsidiaries to parent companies. This study investigates the impact of corporate governance on the choice of transfer pricing methods in China. I classify transfer pricing methods into two major groups (i.e., market-based and cost-based methods). I hypothesize that companies with weak corporate governance are more likely to use cost-based pricing methods, which are regarded as subjective and more easily manipulated. According to previous studies on corporate governance, a smaller board size, CEO-Chairman duality (i.e. the CEO and the Chairman of the company are the same person), and a lower percentage of independent directors on the board are indicators of weak corporate governance. Using data collected from annual reports of Chinese listed firms in the Shanghai and Shenzhen Stock Markets from 2003 to 2005, I find that government-controlled companies are more likely to use market-based methods than others. It is consistent with the hypothesis that ownership has an impact on the choice of transfer pricing methods. The results also show that when the chairman of the board and the CEO of the company is the same person, companies are more likely to use cost-based methods. However, inconsistent with my hypothesis, the results indicate that firms with small boards are more likely to choose cost-based methods than firms with large boards. This study extends prior research on transfer pricing by focusing on the impact of corporate governance. Furthermore, this study suggests that regulators might limit transfer pricing manipulations by stipulating a firm’s corporate governance structure. This research also draws both regulators’ and investors’ attention to the impact of corporate governance on transfer pricing methods

Novel analytical tools for studies in molecular assemblies : I. Electro-active single-mode integrated optical waveguides ; II. Coupled plasmon waveguide resonances.

Two optical analytical tools were developed for studying molecular assemblies at solid/liquid interfaces. Electro-active single-mode integrated optical waveguide (EA-SM-IOW) technology was developed as a platform for spectroelectrochemical investigations on redox adsorbates at the sub-monolayer level. With an optimized ultra-thin indium tin oxide film combined with a single-mode integrated optical waveguide, for the first time, a more than 14,000 times higher sensitivity (compared to conventional potential-modulated transmittance) was achieved. From optical signals, this technique was able to reconstruct electrochemical information of redox adsorbates, including the formal potential and the electron transfer rate. A few major advantages were achieved with the developed EA-SM-IOW technology. I) As low as 10−15 mol/cm2 electrochemically active surface coverage of redox species could be detected; II) A new analytical methodology was developed to combine optical impedance spectroscopy (OIS) with electrochemical impedance measurements to retrieve the electron transfer rate of redox process. This approach bypasses specific knowledge of every electrical element in the electrochemical flow cell; and III) The novel technique of OIS based on EA-SM-IOW platform was applied to examine the electron transfer processes of cytochrome c proteins under different environments that the surface densities were well below the limits of detection in conventional techniques. For molecular assemblies without a convenient absorbance band, a complementary analytical tool, coupled plasmon waveguide resonance (CPWR), was developed to detect surface binding events through changes in the real part of the refractive index and shown to be superior to the surface plasmon resonance (SPR), which has been considered as a gold standard technique. The advantages of CPWR included. I) When compared to SPR theoretically, the designed CPWR sensor was featured more than 30 times better resolution for the bulk solution changes and approximately 2 times superior for probing molecular surface adsorption; II) The smaller (and better) resolution of CPWR was demonstrated experimentally for the first time; and III) The CPWR was applied in an angle-multiplexed configuration to measure the fluorescence decay of a Ru-complex molecular assembly in the nano-second time scale. These two outstanding optical analytical tools provide unprecedented information and reach new detection limits that are expected to enable novel fundamental investigations and technological applications in molecular assemblies

Simultaneous Feature and Body-Part Learning for Real-Time Robot Awareness of Human Behaviors

Robot awareness of human actions is an essential research problem in robotics with many important real-world applications, including human-robot collaboration and teaming. Over the past few years, depth sensors have become a standard device widely used by intelligent robots for 3D perception, which can also offer human skeletal data in 3D space. Several methods based on skeletal data were designed to enable robot awareness of human actions with satisfactory accuracy. However, previous methods treated all body parts and features equally important, without the capability to identify discriminative body parts and features. In this paper, we propose a novel simultaneous Feature And Body-part Learning (FABL) approach that simultaneously identifies discriminative body parts and features, and efficiently integrates all available information together to enable real-time robot awareness of human behaviors. We formulate FABL as a regression-like optimization problem with structured sparsity-inducing norms to model interrelationships of body parts and features. We also develop an optimization algorithm to solve the formulated problem, which possesses a theoretical guarantee to find the optimal solution. To evaluate FABL, three experiments were performed using public benchmark datasets, including the MSR Action3D and CAD-60 datasets, as well as a Baxter robot in practical assistive living applications. Experimental results show that our FABL approach obtains a high recognition accuracy with a processing speed of the order-of-magnitude of 10e4 Hz, which makes FABL a promising method to enable real-time robot awareness of human behaviors in practical robotics applications.Comment: 8 pages, 6 figures, accepted by ICRA'1