Processing Power Of Systems Research Articles

Design and Implementation of Blind Source Separation Based on BP Neural Network in Space-Based AIS

In space-based AIS (Automatic Identification System), due to the high orbit and wide coverage of the satellite, there are many self-organizing communities within the observation range of the satellite, and the signals will inevitably conflict, which reduces the probability of ship detection. In this paper, to improve system processing power and security, according to the characteristics of neural network that can efficiently find the optimal solution of a problem, proposes a method that combines the problem of blind source separation with BP neural network, using the generated suitable data set to train the neural network, thereby automatically generating a traditional blind signal separation algorithm with a more stable separation effect. At last, through the simulation results of combining the blind source separation problem with BP neural network, the performance and stability of the space-based AIS can be effectively improved.

A Decentralized Cloud Firewall Framework with Resources Provisioning Cost Optimization

A new flexible method for supplying more computer power in a shared media is called cloud computing. It offers a distributed paradigm based on self-evaluation methods to increase the system's processing power with less managerial worries. Clients, applications, platforms, servers, and infrastructures make up its components. This computing architecture provides end users with calculation skills as a computed service from the aforementioned components. Security management will lose importance when more devices and their integration become available. One needs to manage data, system, and confidentiality problems carefully since cloud users are growing daily. Therefore, in order to address protected access and integrity concerns in a cloud environment, new security firewall services must be deployed in addition to the current system. Numerous network-related issues, including load balancing, scheduling, traffic divergence, filtering, regulating the rate of arrival, instance management, and attack detection, make it difficult to implement firewalls for cloud computing. A centralised cloud firewall makes it very difficult to predict the response time. Consequently, a new line of work has been established for actually implementing the new firewall techniques for the cloud. In order to reduce the cost of ownership and operation, it also strives to achieve resource optimization-based provisions and guidelines.

VSE-fs: Fast Full-Sample Visual Semantic Embedding

The visual semantic embedding (VSE) aims to construct a joint embedding space between visual features and semantic information, whereby classes can be well retrieved for a given image. However, VSE faces the computational challenge due to the large scale image-class data and the constrained system processing power. To speed up model training, many researchers resort to different sampling strategies by involving only a small portion of the classes at each training step. However, these methods are greatly biased especially when the sampling distribution deviates from the true data distribution. In order to retain VSE models fidelity, we adopt the regular full-sample in our algorithm. We also devise two separate optimization strategies to reduce time complexity, and derive more effective updating rules. The experimental results on four real datasets demonstrate that our approach not only converges much faster than the state-of-the-art sampling models, but also generates more accurate class retrieval.

CO2 laser ablation of microchannel on PMMA substrate for Koch fractal micromixer

In this paper, we mainly study the processing and manufacturing methods of the Koch fractal micromixer on polymethyl methacrylate (PMMA) substrate using a flexible and low-cost CO2 laser system. The structure of Koch fractal microchannel can increase the contact area of the fluids, prolong the mixing time and improve the mixing efficiency of the micromixer. The study focuses on the effect of the CO2 laser system processing power, scanning speed and the number of scanning times on the quality of microchannel. With the increase in processing power and the number of scanning times, the width and depth of the microchannel change more obviously; this contributes to the hot-bonding success of the Koch fractal micromixer, avoiding the hot-bonding failure causes by the overvoltage or overheat. At last, the CO2 laser output power of 7 W and a laser scanning speed of 10 mm/s combining a hot press bonding technique are chosen to fabricate a microfluidic chip within half an hour. The fabrication of microchannel on PMMA substrates with CO2 laser system will have a wide range of application values, resulting in lower costs and easier fabrication.

Poe in Cyberspace: The “Mobile-Friendly” Sites

Poe in Cyberspace: The “Mobile-Friendly” Sites

Characteristics and Application of the Novel Synthetic Material AWPP for Water Purification

Through the hot pressing compound adhesive technology of synthesis of the Novel Synthetic Materials "Artificial Water-Purifying Plant" (AWPP) which is made of polyester fiber non-woven fabrics and Cross-linked polyethylene bubble. Material production process, principle and characteristics of AWPP are introduced in the article. From the different concentration of water purification contrast test, analysis of the material in ascension water purification system processing power play a role. The results indicate that AWPP have technologies advantages of qualitative light, corrosion resistance, buoyancy, more specific surface area, microbial attachment than large amount, form quickly microbial membrane and so on. To different concentrations of water quality of different pollutants index, it can effectively improve water purification effect 18%-40%, and use of low cost, market broad prospect of application.

A general parallelization approach to improve computation efficiency in a global chemical transport model (GEOS-Chem)

Despite increasing processing power of systems, sequential programs have limitations to achieve corresponding performance gains. Parallelization of sequential programs can exploit the computation potential to reduce overall execution expenditures. However, parallelization of a very large legacy program arises great challenges, because 1) former design of the program did not consider parallelization, 2) the large-scale program has been developed for long time even decades, and 3) some developers of the program are no longer available. In the atmospheric science field, there are many such legacy programs and GEOS-Chem model developed in Harvard University is one of examples. In this paper, we suggest simple procedures of the MPI parallelization which can be easily applied to a large legacy program. We applied this method to the GEOS-Chem model which is already parallelized with the OpenMP method alone. Our test results showed that the good performance improvement can be obtained by parallelizing a small portion of the program.

SYSTEM PARALLELISATION FOR COMPUTER VISION

This paper delineates the parallelisation of a computer vision system. It presents the system proposal and the relevant design phases of a laboratory based model. This model involves special purpose hardware implementing the early stages of processing with very high data rate. It Incorporates facilities enabling the user to capture, retain, retrieve, compare, and analyse video images. The output of this hardware is to be processed by a software running in a parallel processor. The latter is a VMEbus-based multiprocessing machine accommodating the system hardware and ensures for better flexibility. It also participates in a reasonable distribution of the systern processing power. The kernel philosophy here depends on the concept of modularisation to attain higher degree of design consistency. It believes that the spatiotemporal pixel variation of two adjacent video frames involves sufficient information to detect movement. This implies pixel encoding and motion parameters estimation. The system software is based on a data compressive technique (Strip Encoding of Adjacent Frames) to solve the bottlenecks problem in the whole system throughput. The research hereby attempts to attain a match in the degree of sophistication between the system hardware and software structures. This yields to make the system processing power better meets the system applications requirements. The research investigates the above presented design phases along with their logical, functional, technical, and modular specifications. The research is adequate for development in a wide range of applications (requiring parallel architectures for image processing) like: Artificial Intelligence, Features Extraction and Pattern Recognition, Expert Systems, Computer Vision and Robotic Vision, Industrial Control, and other civil and military applications.

MediaStation 5000: integrating video and audio

MediaStation 5000 is a highly integrated desktop multimedia system implemented on a single PC plug-in board. It performs multistandard compression, high-speed image processing, and fast 2D and 3D graphics functions. The Texas instruments Multimedia Video Processor (MVP), a single-chip multiprocessing device with a highly parallel internal architecture, provides the system's processing power and programmability. >

Semiautomated analysis of clay samples

Important information about physical characteristics of clays can be inferred from the distribution of the orientations of straight lines in photographs of cross sections of its samples. This article describes the development of a semiautomated system for clay analysis that is based on the application of computer vision techniques. Due to the inherent complexity of these techniques, two strategies have been used in order to reduce the execution time: an effective technique, the binary Hough transform, is applied for detection of straight lines and the transputer is used to enhance the system processing power. The article includes the characterization of the clay analysis application, the description of the binary Hough transform for detection of straight line segments, the presentation of the semiautomated system, and a complete illustrative example.

An image signal multiprocessor on a single chip

A digital image signal multiprocessor (ISMP), a multiprocessor version of a previous real-time image signal processor (RISP) for gray-level image processing, is discussed. It is composed of a main controller and four processor elements (PEs), which are programmable 12-b digital signal processors. One PE has the processing speed of 50-million microinstructions-per-second. The ISMP has 200-million microinstructions-per-second performance using parallel processing with a round-robin method for local image processing. In the other operation mode, each PE processes the same image data with different feature-extracting programs. In addition, system processing power can be easily increased through a novel multichip processing mode. It has 30000 transistors on a 14.4-mm*13.7-mm chip using 1.2- mu m double-metal CMOS process technology. Its power dissipation is 2.9 W. >