Explore the vast range of titles available.

Process-based restoration of fluvial systems removes human constraints on nature to promote ecological recovery. By freeing natural processes, a resilient ecosystem may be restored with minimal corrective intervention. However, there is a lack of meaningful design criteria to allow designers to evaluate whether a project is likely to achieve process-based restoration objectives. We describe four design criteria to evaluate a project’s potential: the expansion of fluvial process space and connectivity lost because of human alterations, the use of intrinsic natural energy to do the work of restoration, the use of native materials that do not overstabilize project elements, and the explicit incorporation of time and adaptive management into project design to place sites on recovery trajectories as opposed to attempts to “restore” sites via a single intervention. Applications include stream and infrastructure design and low-carbon construction. An example is presented in California’s Sierra Nevada foothills.

This paper presents a novel concept of real-time catadioptric stereo tracking using a single ultrafast mirror-drive pan-tilt active vision system that can simultaneously switch between hundreds of different views in a second. By accelerating video-shooting, computation, and actuation at the millisecond-granularity level for time-division multithreaded processing in ultrafast gaze control, the active vision system can function virtually as two or more tracking cameras with different views. It enables a single active vision system to act as virtual left and right pan-tilt cameras that can simultaneously shoot a pair of stereo images for the same object to be observed at arbitrary viewpoints by switching the direction of the mirrors of the active vision system frame by frame. We developed a monocular galvano-mirror-based stereo tracking system that can switch between 500 different views in a second, and it functions as a catadioptric active stereo with left and right pan-tilt tracking cameras that can virtually capture 8-bit color 512 × 512 images each operating at 250 fps to mechanically track a fast-moving object with a sufficient parallax for accurate 3D measurement. Several tracking experiments for moving objects in 3D space are described to demonstrate the performance of our monocular stereo tracking system.

The solutions to real-life problems are challenging to find out in the exact form as the dimensions of the problems are significant. A multi-period multi-product inventory model is tested in this study through an artificial neural network for experiencing an uncertain environment. Whenever obstacles present in every period, a neural network with multithreading is one of the optimization procedures to find the best optimal solution with an inflation and time value of money. A fuzzy approach is used here to deal with the uncertainty, and the total cost of the system is calculated using the bi-objective constraint objective function. The first objective is to find the minimum cost of the system with the optimum space, which is the second objective. The solutions of the mathematical model are obtained by generating multiple threads that every thread is a possible solution. The numerical experiment chooses the best fit from the multiple solutions. An illustrative comparative study with the existing methodologies is provided. Results show that the proposed approach is the best for cost optimization and time minimization. It is found that the neural network with multithreading converges over other algorithms and the results obtain within less than 30% time of the existing algorithm.

According to the development of personnel positioning system, with the use of data storage technology, multithreading technology, information buffer technology and TCP communication technology, this simulator can not only simulate multidevice reporting to multiuser, but also realize pressure test for the upper software by adjusting the amount of reporting data, therefore, the software problems can be found in advance and solved in time.

Tchebichef polynomials (TPs) play a crucial role in various fields of mathematics and applied sciences, including numerical analysis, image and signal processing, and computer vision. This is due to the unique properties of the TPs and their remarkable performance. Nowadays, the demand for high-quality images (2D signals) is increasing and is expected to continue growing. The processing of these signals requires the generation of accurate and fast polynomials. The existing algorithms generate the TPs sequentially, and this is considered as computationally costly for high-order and larger-sized polynomials. To this end, we present a new efficient solution to overcome the limitation of sequential algorithms. The presented algorithm uses the parallel processing paradigm to leverage the computation cost. This is performed by utilizing the multicore and multithreading features of a CPU. The implementation of multithreaded algorithms for computing TP coefficients segments the computations into sub-tasks. These sub-tasks are executed concurrently on several threads across the available cores. The performance of the multithreaded algorithm is evaluated on various TP sizes, which demonstrates a significant improvement in computation time. Furthermore, a selection for the appropriate number of threads for the proposed algorithm is introduced. The results reveal that the proposed algorithm enhances the computation performance to provide a quick, steady, and accurate computation of the TP coefficients, making it a practical solution for different applications.

Serial communication has been widely used in varies fields, and its application in the measuring system for the keel-line of ships is discussed in this paper. The main function of the measuring system is to fulfill the orientation introducing, thus to realize the unification of coordinates. Serial communication is applied in the measuring system to achieve real-time data communication between self-collimation theodolite, electronic gradienter, center computer and computer of measuring system. The component of a communication system, the function, the system protocol and the program design are introduced in this paper. It is proved that the communication system, which fulfills real-time as well as accurate and reliable data communication, has already been applied in measuring system of ships keel-line.

The web data collection is the process of collecting the semi-structured, large-scale and redundant data which include web content, web structure and web usage in the web by the crawler and it is often used for the information extraction, information retrieval, search engine and web data mining. In this paper, the web data collection principle is introduced and some related topics are discussed such as page download, coding problem, updated strategy, static and dynamic page. The multithread technology is described and multithread mode for the web data collection is proposed. The web data collection with multithread can get better resource utilization, better average response time and better performance.

Sorting is one of the most frequent concerns in Computer Science, various sorting algorithms were invented for specific requirements. As these requirements and capabilities grow, sequential processing becomes inefficient. Therefore, algorithms are being enhanced to run in parallel to achieve better performance. Performing algorithms in parallel differ depending on the degree of multi-threading. This study determines the optimal number of threads to use in parallel merge sort. Furthermore, it provides a comparative analysis of various degrees of multithreading. The implementation in this empirical experiment takes a group of devices with various specifications. For each device, it takes fixed-sized data set and executes merge sort for sequential and parallel algorithms. For each device, the lowest average runtime is used to measure the efficiency of the experiment. In all experiments, single-threaded is more efficient when the data size is less than 105 since it claimed 53% of the lowest runtime than the multithreaded executions. The overall average of the experiments shows either four or eight threads, with 72% and 28%, respectively, are most efficient when data sizes exceed 105.

Electronic navigational charts (ENCs) are geospatial databases compiled in strict accordance with the technical specifications of the International Hydrographic Organization (IHO). Electronic Chart Display and Information System (ECDIS) is a Geographic Information System (GIS) operated by ENCs for real-time navigation at sea, which is one of the key technologies for intelligent ships to realize autonomous navigation, intelligent decision-making, and other functions. Facing the urgent demand for high-precision and real-time nautical chart products for polar navigation under the new situation, the projection of ENCs for polar navigation is systematically analyzed in this paper. Based on the theory of complex functions, we derive direct transformations of Mercator projection, polar Gauss-Krüger projection, and polar stereographic projection. A rational set of dynamic projection options oriented towards polar navigation is proposed with reference to existing specifications for the compilation of the ENCs. From the perspective of nautical users, rather than the GIS expert or professional cartographer, an ENCs visualization idea based on multithread-double buffering is integrated into Polar Region Electronic Navigational Charts software, which effectively solves the problem of large projection distortion in polar navigation applications. Taking the CGCS2000 reference ellipsoid as an example, the numerical analysis shows that the length distortion of the Mercator projection is less than 10% in the region up to 74°, but it is more than 80% at very high latitudes. The maximum distortion of the polar Gauss-Krüger projection does not exceed 10%. The degree of distortion of the polar stereographic projection is less than 1% above 79°. In addition, the computational errors of the direct conversion formulas do not exceed 10−9 m throughout the Arctic range. From the point of view of the computational efficiency of the direct conversion model, it takes no more than 0.1 s to compute nearly 8 million points at 1′×1′ resolution, which fully meets the demand for real-time nautical chart products under information technology conditions.

In this study, we propose a multi-thread artificial intelligence (AI) camera system that can simultaneously recognize remote objects in desired multiple areas of interest (AOIs), which are distributed in a wide field of view (FOV) by using single image sensor. The proposed multi-thread AI camera consists of an ultrafast active vision system and a convolutional neural network (CNN)-based ultrafast object recognition system. The ultrafast active vision system can function as multiple virtual cameras with high spatial resolution by synchronizing exposure of a high-speed camera and movement of an ultrafast two-axis mirror device at hundreds of hertz, and the CNN-based ultrafast object recognition system simultaneously recognizes the acquired high-frame-rate images in real time. The desired AOIs for monitoring can be automatically determined after rapidly scanning pre-placed visual anchors in the wide FOV at hundreds of fps with object recognition. The effectiveness of the proposed multi-thread AI camera system was demonstrated by conducting several wide area monitoring experiments on quick response (QR) codes and persons in nature spacious scene such as meeting room, which was formerly too wide for a single still camera with wide angle lens to simultaneously acquire clear images.