Intelligent hybrid system for dark spot detection using SAR data

Synthetic Aperture Radars (SAR) are the main instrument used to support oil detection systems. In the microwave spectrum, oil slicks are identified as dark spots, regions with low backscatter at sea surface. Automatic and semi-automatic systems were developed to minimize processing time, the occurrence of false alarms and the subjectivity of human interpretation. This study presents an intelligent hybrid system, which integrates automatic and semi-automatic procedures to detect dark spots, in six steps: (I) SAR pre-processing; (II) Image segmentation; (III) Feature extraction and selection; (IV) Automatic clustering analysis; (V) Decision rules and, if needed; (VI) Semi-automatic processing. The results proved that the feature selection is essential to improve the detection capability, keeping only five pattern features to automate the clustering procedure. The semi-automatic method gave back more accurate geometries. The automatic approach erred more including regions, increasing the dark spots area, while the semi-automatic method erred more excluding regions. For well-defined and contrasted dark spots, the performance of the automatic and the semi-automatic methods is equivalent. However, the fully automatic method did not provide acceptable geometries in all cases. For these cases, the intelligent hybrid system was validated, integrating the semi-automatic approach, using compact and simple decision rules to request human intervention when needed. This approach allows for the combining of benefits from each approach, ensuring the quality of the classification when fully automatic procedures are not satisfactory.     

A fuzzy approach to segment touching characters

Despite many years of research, correct and reliable segmentation of touching characters is still a hard task to solve. In the recent years, many methods and algorithms have been proposed; nevertheless the problem is still open. In this paper, we propose a novel method based on fuzzy logic that combines three different techniques to segment touching characters. These techniques have already been used in other studies but they have never been used all together. We propose a 3–input/1–output fuzzy inference system with fuzzy rules that are specifically optimized to segment touching Latin characters. The method is applicable to both printed and handwritten characters. We discuss the performances of our method by comparing it with state of the art. Results show that our method provide a better accuracy to segment characters even with noisy touching characters.     

Wavelet based medical image super resolution using cross connected residual-in-dense grouped convolutional neural network

In clinical analysis and diagnosis, high resolution (HR) computed tomography (CT) images are required for proper treatment of a patient. Developing HR medical images by X-ray CT devices require extended radiation exposure with large radiative dosages, putting the patient at potential risk of inducing cancer. So, radiation exposure should be reduced. However, photon starvation and beam hardening in low-dose X-rays will cause severe artifacts. Thus, an accurate reconstruction of low-dose X-ray CT images is required. To this end, we propose a wavelet based multi-channel and multi-scale cross connected residual-in-dense grouped convolutional neural network (WCRDGCNN) for accurate super resolution (SR) of medical images. The adopted filter groups reduce the connection weights, thereby reducing the computational complexity. Gradient vanishing problem is tackled by using residual and dense skip connections. The extensive experimentation results on benchmark datasets show that our method outperforms the state-of-the-art SR methods.     

船舶行为的语义建模与表达

船舶行为的语义表达是实现水上交通态势智能认知与知识推理的基础。为实现对船舶时空运动特征的语义表达和抽象,完善船舶轨迹的语义转换方法,提出了一种船舶行为语义的认知计算模型。通过融合船舶的时空轨迹数据及航行环境信息,以船舶时空轨迹单元为基础,根据船舶的运动状态、轨迹的空间拓扑特征以及行为的语义特征,依据空间拓扑学理论,将船舶时空行为抽象为原子行为、拓扑行为和交通行为,从船舶的时空轨迹到语义行为进行了不同层次的概念建模、语义描述和形式化表达;最后,基于该语义模型对船舶在港口水域中不同类型的航行行为进行实例验证。结果表明,该模型能够对港口水域中不同运动特征、不同空间拓扑特征的船舶行为进行语义建模与形式化表达,将其提取为5种典型的交通行为,表明该语义模型对船舶行为认知具有一定的合理性和良好的适用性。研究成果能够为船舶行为的语义认知、知识计算提供理论方法基础,实现对高级船舶行为的语义计算和认知推理。     

Integrating preventive and predictive maintenance policies with system dynamics: A decision table approach

A decision table is a practical tool that helps systems planners to make operational decisions, especially when they are under stress. With the effect of recent trends, such as the use of machine learning, data mining, and reinforcement learning methods, the maintenance decision has been a dynamic issue depending on system conditions. An expert may execute the maintenance or wait for the next periodic maintenance due to lack of maintenance workers, tools or budget, resources, etc., although the intelligent method predicts a failure approaching. Even sometimes, he/she may ignore the current periodic maintenance. Our method allows making some changes in the maintenance plan systematically. It integrates the results of preventive and predictive maintenance policies, and as different from the literature, it allows ignoring some maintenance actions depending on the maintenance resource levels in a decision table. Such a strategy helps to allocate limited resources to maintenance actions reasonably. We conducted an extensive simulation study on a real-life dataset. The preventive maintenance period is determined using classical approaches such as Weibull analysis. A machine learning algorithm is utilized to predict the type of failure. We have analyzed the performance of the proposed decision table approach under a variety of scenarios and with different parameter settings. We also showed the effect of parameter settings and the marginal utility of each maintenance policy. In addition, the approach provides several choices for planners. As a result, the proposed approach improves the system’s sustainability compared to traditional policies.     

船闸水域船舶列队协同停船预测控制器

为提高船舶在闸室水域的航行效率和安全性,开展了船闸水域船舶列队协同停船控制方法的研究.建立了闸室水域船舶列队直航运动模型,基于模型预测控制原理分别提出了速度-时间法和速度-位移法两种船舶停船控制方法.针对船舶列队协同停船控制需求,结合停船经济性和平顺性设计了船舶列队停船控制目标函数,以船舶纵向间距保持、输入为约束,提出...     

An Image-Processing Strategy for the Segmentation and Quantification of Microaneurysms in Fluorescein Angiograms of the Ocular Fundus

Digital image-processing techniques can provide an objective and highly repeatable way of quantifying retinal pathology. This study describes an image-processing strategy which detects and quantifies microaneurysms present in digitized fluorescein angiograms. After preprocessing stages, a bilinear top-hat transformation and matched filtering are employed to provide an initial segmentation of the images. Thresholding this processed image results in a binary image containing candidate microaneurysms. A novel region-growing algorithm fully delineates each marked object and subsequent analysis of the size, shape, and energy characteristics of each candidate results in the final segmentation of microaneurysms. The technique is assessed by comparing the computer's results with microaneurysm counts carried out by five clinicians, using Receiver Operating Characteristic (ROC) curves. The performance of the automated technique matched that of the clinicians' analyses. This strategy is valuable in providing a way of accurately monitoring the progression of diabetic retinopathy.     

Compression and bending performances of carbon fiber reinforced lattice-core sandwich composites

To restrict debonding, carbon fiber reinforced lattice-core sandwich composites with compliant skins were designed and manufactured. Compression behaviors of the lattice composites and sandwich columns with different skin thicknesses were tested. Bending performances of the sandwich panels were explored by three-point bending experiments. Two typical failure mechanisms of the lattice-core sandwich structures, delaminating and local buckling were revealed by the experiments. Failure criteria were suggested and gave consistent analytical predictions. For panels with stiff skins, delamination is the dominant failure style. Cell dimensions, fracture toughness of the adhesives and the strength of the sandwich skin decide the critical load capacity of the lattice-core sandwich structure. The mono-cell buckling and the succeeding local buckling are dominant for the sandwich structures with more compliant skin sheets. Debonding is restricted within one cell in bending and two cells in compression for lattice-core sandwich panels with compliant face sheets and softer lattice cores.     

Fiber-optic liquid-level continuous gauge

An intensity-based fiber-optic liquid-level gauge for continuous measurement is described. The sensing principle is based on the total internal reflection of light within the fiber optic, and for this, a measurement is made of the power attenuation which occurs in the fiber optic immersed in the liquid tank when the liquid level varies. The light from a LED is modulated before being directed into the fiber to minimize measurement errors. The device contains an alarm programmable to signal any liquid level in the tank (high or low), and data can be sent via Internet in real time to a distant point.     

Dynamic simulation of the effect of vehicle-side pressure loss of hydrogen fueling process

This study explains the fundamental mathematical equations used for the main component models that are implemented in freely available library for hydrogen fueling station. The paper provides a background to the model formulation and theory, useful for the further investigations of hydrogen fueling stations. The model was verified against a specific manufacturer model, and it was validated by using test data from an actual fueling station. The study works as documentation and validation of the model formulation. The simulation library is used to make a model for investigating how the pressure loss in the vehicle affects the fueling process. Keeping the temperature out of the station constant and fueling to 80 MPa in the compressed hydrogen storage system, the pressure loss in the compressed hydrogen storage system directly correlates to the final temperature. The final temperature increases with increasing pressure losses. It is also shown that with no pressure loss in the vehicle the fueling has no limit in fueling speed as the heat of compression depends on the mass filled and the enthalpy of the mass, and not the filling time.