Coding Speed Research Articles

UAVS2—Fast encoder for the 2nd generation IEEE 1857 video coding standard

The recently issued second generation IEEE 1857 video coding standard (AVS2) provides a doubling in coding efficiency relative to previous standards such as H.264/AVC and AVS1. The coding performance improvement is mainly due to the adoption of advanced coding tools. However, these coding tools also cause a dramatic increase in computational complexity. A fast encoder design for AVS2 is strongly demanded to promote it being widely used in video compression practice. In this paper, we propose a fast encoder design for AVS2. In our design, we propose a new quantization step (QStep) dependent fast CU depth decision algorithm for inter frames, and a combination strategy to integrate fast algorithms in different coding Presets to get a good trade-off between coding speed and coding efficiency. In addition, instruction optimization, parallel coding and some coding flow optimizations are also used in our design. According to the proposed design, we developed the first fast AVS2 encoder, and named it as uAVS2. Experimental results show that uAVS2 is 56.58 times faster than the AVS2 reference software, and 19.32 times faster than the HEVC reference software, with negligible performance loss. uAVS2 is 2.7–6.6 times faster than the well-known fast HEVC encoder x265 under similar coding performance configurations. Under similar coding speed, the coding performance of uAVS2 is superior to x265 by 10–30% in BD-rate. uAVS2 with the highest speed Preset can encode 1080P video in real-time on PC platform.

Graphics Processing Unit-Accelerated Code for Computing Second-Order Wiener Kernels and Spike-Triggered Covariance.

Sensory neuroscience seeks to understand and predict how sensory neurons respond to stimuli. Nonlinear components of neural responses are frequently characterized by the second-order Wiener kernel and the closely-related spike-triggered covariance (STC). Recent advances in data acquisition have made it increasingly common and computationally intensive to compute second-order Wiener kernels/STC matrices. In order to speed up this sort of analysis, we developed a graphics processing unit (GPU)-accelerated module that computes the second-order Wiener kernel of a system’s response to a stimulus. The generated kernel can be easily transformed for use in standard STC analyses. Our code speeds up such analyses by factors of over 100 relative to current methods that utilize central processing units (CPUs). It works on any modern GPU and may be integrated into many data analysis workflows. This module accelerates data analysis so that more time can be spent exploring parameter space and interpreting data.

System approach to the choice of capacity of a high-speed radio data link for modern Earth remote sensing spacecraft

The main principles of choosing the capacity of a high-speed radio data link for modern Earth remote sensing spacecraft are discussed in the paper. The following points are taken into account: overfilling of the onboard memory storage device; duration of communication sessions between the spacecraft and the downlink point; the required bandwidth and the reliability of the radio data link. Mathematical restrictions for the conditions of the overflow of the on-board memory storage of target information and the amount of information transmitted to the downlink points during a communication session between the spacecraft and the downlink point are specified. An expression is proposed for the estimation of radio data link capacity on the basis of the Shannon formula with account for the energy relations for satellite communication links, the required width of the passband and the probability of data transmission error. The influence of the probability of the information transmission error and the main parameters of the radio signal (the speed of protective coding and the phase deviation) on the value of high-speed radio data link capacity is analyzed. Changes in radio data link capacity in retrospect for the years immediately ahead are analyzed in accordance with the predicted value of the required volume of space information of Earth remote sensing for radio data links of different reliability.

Enhanced pipelined architecture of H.264/AVC intra prediction

This paper presents a high-performance encoder for H.264/AVC intra prediction. Due to long data dependency loop of intra 4×4 prediction and complex algorithms, improving encoding speed turns into a stumbling block we have to face. To solve this problem, we first propose a pipelined method in and between macro blocks with new block processing order to accelerate the encoding speed. Benefiting from the pipelined method, reconstructed pixels of up-right blocks are available for two blocks in a macro block which could not take advantage of reconstructed pixels of up-right blocks in JM. So diagonal down left mode and vertical left mode are effective for these two blocks, which ultimately achieves a better bit-rate. Secondly, all 4×4 mode formula sharing method is proposed to reduce the redundancy of predicting formulas. Thirdly, streamlined reconstruction method is applied to improve the performance of reconstruction. CAVLC encoder with three parallel units is proposed to improve entropy coding speed significantly. As a result, it takes 268 cycles to encode a macro block. The experimental results indicate that synthesized into a 0.18µm CMOS cell library, the new architecture only requires about 238K gates and it is able to encode 1080pHD video sequences at 30 frames per second (fps), at the operating frequency of 56MHz.

Modular Tool for the Simulation of Compressor Trains for Oil and Gas Applications

Recently, in the oil and gas extraction and transportation field, much attention has been paid both to increase efficiency and to reduce the environmental impact of the extraction techniques that, by now, consists mainly on Enhanced Oil Recovery processes based on gas or water injection into the reservoirs. Thus, compressor trains are a crucial part of the overall plant, and they require precise performance estimation during the whole oilfield lifespan, when production rates and compression demands significantly change. For this reason, in compression plant design and in-service behavior prediction, modular simulation codes turns out to be the best choice respect to tools for specific plant configuration, since they provide flexibility without losing accuracy.In this paper, a new modular tool for compression plant simulation is described; it is based on a wide database of centrifugal compressors and a library of elementary components that can be freely assembled to build any plant's configuration, regardless of its layout. The code's numerical solver is the implementation of a trust-region Gauss-Newton method, called TRESNEI, which possess a larger convergence region than standard Newton methods.The performance of the code has been tested on two compression train arrangements with both series and parallel-mounted compressors; comparison with the solution of the test cases obtained with a dedicated pre-existing in-house code, shows a good matching between the results. Computational speed and robustness of the new code is also shown.

A fast mode decision algorithm applied in medium-grain quality scalable video coding

To increase the flexibility of bit stream adaptation in the H.264/Scalable Video Coding, Medium-Grain Scalable Video Coding (MGS), a variation of Coarse-Grain Scalable Video Coding (CGS), is included. The encoding structure of MGS is significantly different from that of CGS, and the encoding procedure of MGS is very complex. It is important to reduce encoding complexity without sacrificing MGS coding performance. In this paper, a fast mode decision algorithm is proposed for the enhancement layer of MGS based on its specific coding structure. First, the candidate modes and the coding sequence of the current macro-block (MB) are predicted based on mode correlations and correlation degrees. Next, early termination strategies, including Direct Mode, inter-layer, layer and spatial, and spatial-only, are proposed based on the coding structure of MGS and correlations. Finally, MBs are encoded in the order predicted with the four proposed early termination strategies to improve the coding speed. Experimental results show that the algorithm can achieve an average time saving of up to 85.44% with strong robustness and negligible loss in coding efficiency.

Accuracy of First Recorded “Last Known Normal” Times of Stroke Code Patients

Given the time sensitivity of thrombolytic therapy, the accurate documentation of last known normal (LKN) time is crucial to ensure optimal management of stroke patients. This study investigates whether a difference exists between preliminary LKN times (first responders and emergency department practitioners) and revised LKN times (neurology/stroke practitioners), and what potential impact on emergent management of acute stroke this discrepancy may pose. All stroke code patients from UC San Diego hospitals from October 2008 to July 2013 with treatment time data were included and grouped based on the disparity between preliminary LKN time and revised LKN time: preliminary earlier than revised, 2 times equal, and preliminary later than revised. We compared baseline characteristics, stroke code intervals, rates of recombinant tissue plasminogen activator (rt-PA) administration, 90-day modified Rankin Scale (mRS) score, discharge disposition, and symptomatic intracerebral hemorrhage. Of 261 patients, 73.6% had disparity between preliminary and revised times: 57.5% had later preliminary LKN than revised, and 16.1% had earlier preliminary LKN than revised. Baseline characteristics, stroke code speed, 90-day mRS score, rates of rt-PA administration, discharge disposition, or rates of symptomatic intracerebral hemorrhage were not significantly different between the groups. Among rt-PA-treated stroke patients whose preliminary time was earlier than the revised time, had the preliminary LKN been used, 29.4% would have had rt-PA withheld inappropriately. In those stroke patients excluded from rt-PA treatment for being outside the treatment window, whose preliminary time was later than the revised time, had the preliminary time been used, 69.7% would have been inappropriately treated outside the relevant rt-PA window. Most patients had disparity between preliminary and revised LKN times. Had the preliminary LKN time been used for acute stroke decision-making, 58% of patients would have potentially been treated outside the approved thrombolytic time window, with higher risk of adverse events, and 16% may have been inappropriately excluded from thrombolysis. This study highlights the need for training in the determination and refinement of the actual time of stroke onset, especially at hospitals without stroke expertise.

A Fractal Image Compression Method Based on Multi-Wavelet

How to effectively store and transmit such multi-media files as image and video has become a research hotspot. The traditional compression algorithms have a relatively low compression ratio and bad quality of decoded image, at present, the fractal image compression method with a higher compression ratio fails to meet the requirements of the practical applications in the quality of the compressed image as well as the coding and decoding time. This paper integrates fractal thought and multi-wavelet transform and proposes a fractal image compression algorithm based on multi-wavelet transform. To transform the image model into a combination of relevant elements in the frequency domain instead of merely building on the foundation of the neighborhood gray-scale correlation has the ability to code larger image blocks, eliminates the possibility of global correlation in the image and improves the coding speed of the existing fractal image compression algorithm. The experimental result shows that the algorithm proposed in this paper can accelerate the coding speed of the present fractal image compression and have certain self-adaptivity while slightly reducing the quality of decoding image.

Fast Intra prediction algorithm for quality scalable video coding

The coding efficiency of currently scalable video coding is very high at the cost of high coding complexity. Therefore, it is extremely important to improve the coding speed. By making use of the advantage of the quality scalable video coding (QSVC) structure, we propose a new fast Intra coding algorithm for QSVC. Based on the coding structure of QSVC, temporal, spatial and inter-layer correlations are employed together to predict candidate macro-block (MB) modes and their encoding orders to exclude low possible modes, and then three new early termination methods are proposed. In addition to MB modes, temporal, spatial and inter-layer correlations are also adopted together to estimate weight values and orders of all directional modes. Experimental results demonstrate that the coding speed of the proposed algorithm can be improved by 63.58 % in average with negligible coding loss.

Beam-splitting code for light scattering by ice crystal particles within geometric-optics approximation

The open-source beam-splitting code is described which implements the geometric-optics approximation to light scattering by convex faceted particles. This code is written in C++ as a library which can be easy applied to a particular light scattering problem. The code uses only standard components, that makes it to be a cross-platform solution and provides its compatibility to popular Integrated Development Environments (IDE׳s). The included example of solving the light scattering by a randomly oriented ice crystal is written using Qt 5.1, consequently it is a cross-platform solution, too. Both physical and computational aspects of the beam-splitting algorithm are discussed. Computational speed of the beam-splitting code is obviously higher compared to the conventional ray-tracing codes. A comparison of the phase matrix as computed by our code with the ray-tracing code by A. Macke shows excellent agreement.

DCT-JPEG Image Coding Based on GPU

In this paper, the parallel algorithm of JPEG coding based on GPU is proposed, most image compression systems have efficiency problem and the real-time of wireless multimedia sensor networks (WMSN) which used in image compression and transmission is also an issue need to be solved, so in this paper parallel computation is used in JPEG coding, it is an effective ways to solve these problems. The system of JPEG coding system mainly has eight parts: discrete cosine transform (DCT) and inverse DCT, quantization and inverse quantization, Zig-zag ordering and inverse Zig-zag ordering, Huffman coding and decoding. The proposed parallel algorithm of JPEG coding makes all the parts of JPEG system run on GPU, so the speed of JPEG coding is improved significantly. DCT and Huffman coding are wildly used in image processing; therefore the proposed parallel algorithm can be used in many fields about image compression and processing. We use the CUDA toolkit based on GPU which is released by NVIDIA to design the parallel algorithm of DCT-JPEG algorithm. The experimental results show that compared with conventional JPEG coding, the maximum speedup ratio of parallel algorithm of JPEG coding can reach more than 120 times, and the reconstructed image has almost the same performance with the serial algorithm in terms of objective quality and subjective effect.

Code, Nintendo’s Super Mario and Digital Legality

The rise of technology in controlling and performing legal processes has created a new digital legality, signalling a transformation of law from an analog paper-based interpretative activity to an autonomous system governed by the rigidity and speed of code. This emerging digital legality converts life and living to data to be processed and catalogued. This process is exemplified and normalised within video games making them important cultural artefacts through which to identify the features and anxieties of digital legality. While video games have so far gone unrepresented in cultural legal theory, this article uses the iconic video game franchise of Super Mario to unlock the emerging features and anxieties of digital legality as involving rigidity, speed and the normalisation of self as data.

Construction of Cryptosystem on the Basis of Triangular Codes

In this article the triangular codes found dependence of the power of these codes on the length of codewords in them. The methods of construction codes and some triangular propose an effective general method for constructing such codes based on monotone Boolean functions. Designed with correcting codes cryptosystem on the basis of such a code, which allows one to correct the error. The advantage of this cryptosystem is the speed of coding and decoding, and the ability to quickly change the code without changing tables, coding and decoding. Change the code is implemented using the substitution, and the choice of codes is very large. The number of possible codes is 20! (approximately equal to 2.4*10 18 ) has at length codeword of 20.

A fast mode decision algorithm applied to Coarse-Grain quality Scalable Video Coding

A fast mode decision algorithm is proposed for a Coarse-Grain Scalable (CGS) video encoder based on the encoding characteristics of quality Scalable Video Coding (SVC). First, candidate modes and coding orders are predicted, based on inter-layer and spatial correlations. Three early termination methods are then proposed based on CGS encoding structure. Finally, all candidate modes are checked sequentially, according to their predicted order with three early termination conditions, to improve the coding speed. Experimental results have demonstrated that the proposed algorithm could reduce the encoding time by an average of 84.39%, with negligible coding efficiency losses.

Evaluation of Tests of Perceptual Speed/Accuracy and Spatial Ability for Use in Military Occupational Classification

With the exception of Assembling Objects (AO), a spatial ability test used only by the Navy in enlisted occupational classification, the Armed Services Vocational Aptitude Battery (ASVAB) is academic and knowledge-based, somewhat limiting its utility for occupational classification. This article presents the case for integrating the AO test into military classification composites and for expanding the breadth of ASVAB content by including a former ASVAB speed/accuracy test, Coding Speed (CS). Empirical evidence is presented that shows AO and CS (a) increment the validity of the ASVAB in predicting training grades for a broad array of occupations, (b) reduce adverse impact defined as test score barriers for women and minorities, and (c) improve classification in terms of matching recruits to occupations. Some cognitive theory is presented to support AO and CS, as well as nonverbal reasoning and working memory tests for inclusion in or adjuncts to the ASVAB.

Introduction to the Special Issue on Selected New Developments in Military Enlistment Testing

This article provides a brief discussion of the historical context for the major recent advances in enlisted selection and classification that are the subject of this special issue. By providing a perspective on the difficulty personality assessment has had gaining traction as a screening measure, it supplies a basis for understanding the significance of recent advances in personality measurement. This article also summarizes the military research on interest measurement that will receive more extended treatment later in this issue. It relates the work in this issue on new information technology testing to the role of information testing in the current military operational selection and classification test battery, the Armed Services Vocational Aptitude Battery (ASVAB), and discusses the background for 2 additional cognitive measures, Coding Speed and Assembling Objects. Finally, it previews issues to be discussed in the commentary article at the end of this issue.

A framework for reliability-aware embedded system design on multiprocessor platforms

This paper presents a model-driven framework that provides a tool-supported design flow for fault-tolerant embedded systems. Its system models comprise abstract descriptions of the application and the underlying execution platform. They provide the input to our analysis and optimization techniques that enable the automated exploration of design alternatives for applications with reliability requirements. The automated generation of source code and platform configuration files speeds up the development process. Our contribution is to advance reliability-aware design further into practice by providing an integrated tool framework and removing unrealistic assumptions in the analyzes. The case studies demonstrate the effectiveness of our approach.

An Innovative Software for Analysis of Sun Position Algorithms

A fundamental aspect of concentrating solar power is the ability to compute the position of the sun within a desired accuracy and speed. There are many algorithms from which to choose, and these algorithms range from quite simple to fairly complex. The tradeoff is one of code size, complexity and speed vs. accuracy. The solar plant designer must evaluate the available models and choose the best fit. Tietronix Software has developed a software called TieSOL::SolTime to assist the designer in this process.TieSOL::SolTime is an innovative tool that provides instantaneous sun (and moon) position data, to varying precisions, between the years 1753 and 6000. More importantly, TieSOL::SolTime also allows the designer to graphically compare sun position algorithms. Built in to TieSOL::SolTime are ten baseline models, ranging in accuracy from 36 to 0.01 arc seconds. The user can select two algorithms and graphically compare the evolution and behavior of the sun position vector components, range, right ascension, declination, ecliptic latitude and longitude, and azimuth and elevation angles over a user-defined time span, at a user- specified step size. Furthermore, the user can evaluate their own algorithm by importing an ephemeris file. Errors, abnormalities and numerical instabilities in a proposed algorithm can be easily identified.TieSOL::SolTime utilizes the GPU as well as all CPU cores, generating sun ephemerides as fast as 95 million vectors per second at the 36 arc second level of accuracy. Comparing two algorithms at 1 arc second precision, over a 30 year period with a time step size of 5minutes, takes less than 20seconds.

Using Wavelength/Time Signatures Scrambling to Realize Cryptographic Coded-WDM Data Networks

To combat with multiple-users interference and malicious eavesdropping, this paper proposes a double scrambling scheme over time/wavelength for a cryptographic optical CDMA (OCDMA) data transmission. By using wavelength-spreading/time-hopping, data reliability in OCDMA network can be highly improved. On the transmitter side, data bits are sliced into spectral chips, coded into M-sequence codes, and conducted with different units of time-delay. In the receiver side, fiber-delay lines (FDLs) reverse the spectral chips back to the same time basis, and optical switches (OSWs) turn on-off spectral chips into balanced detector for the final data decoding. By changing signature code frequently, the eavesdroppers cannot catch on the changing code speed and have little chance to detect the channel waveform to solve the code. To against eavesdropping, we take advantages of linear cyclic, periodic, and nearly-orthogonal characteristics of M-sequence codes. OSWs and FDLs are added into the arrayed-waveguide grating (AWG) codecs. The spectral codes and the time-delay units will follow cell states of a controlling shift register. Different shift register states will reconfigure AWG light spectra into different coding sequences. After pass through the associated OSWs and FDLs, user signature code appears to be a two-dimensional code matrix. In perspective of eavesdropper, smooth eavesdropping presents difficulties due to signature codes’ frequent changing. The system can therefore achieve a high level of network confidentiality.

Persistent viral pathogens and cognitive impairment across the life course in the third national health and nutrition examination survey.

Herpesviruses have been linked to cognitive impairment in older individuals but little is known about the association in the general US population. We determined whether cytomegalovirus (CMV) and herpes simplex virus 1 (HSV-1) seropositivity were associated with cognitive impairment among children (aged 6-16 years) and adults aged 20-59 or ≥60 years, using data from the National Health and Nutrition Examination Survey (NHANES) III. Linear and logistic regression models were used to examine the associations between pathogen seropositivity and cognitive impairment. Among children, HSV-1 seropositivity was associated with lower reading and spatial reasoning test scores (β, -0.69; 95% confidence interval [CI], -1.18 to -.21 and β, -0.82; 95% CI, -1.29 to -.36, respectively). Among middle-aged adults, HSV-1 and CMV seropositivity were associated with impaired coding speed (odds ratio [OR], 1.54; 95% CI, 1.13-2.11, and OR, 1.41; 95% CI, 1.09-1.82, respectively). CMV seropositivity was also associated with impaired learning and recall (OR, 1.43; 95% CI, 1.14-1.80). Among older adults, HSV-1 seropositivity was associated with immediate memory impairment (OR, 3.26; 95% CI, 1.68-6.32). Future studies examining the biological pathways by which herpesviruses influence cognitive impairment across the life course are warranted.