Deep Video Precoding

Several groups worldwide are currently investigating how deep learning may advance the state-of-the-art in image and video coding. An open question is how to make deep neural networks work in conjunction with existing (and upcoming) video codecs, such as MPEG H.264/AVC, H.265/HEVC, VVC, Google VP9 and AOMedia AV1, AV2, as well as existing container and transport formats, without imposing any changes at the client side. Such compatibility is a crucial aspect when it comes to practical deployment, especially when considering the fact that the video content industry and hardware manufacturers are expected to remain committed to supporting these standards for the foreseeable future. We propose to use deep neural networks as precoders for current and future video codecs and adaptive video streaming systems. In our current design, the core precoding component comprises a cascaded structure of downscaling neural networks that operates during video encoding, prior to transmission. This is coupled with a precoding mode selection algorithm for each independently-decodable stream segment, which adjusts the downscaling factor according to scene characteristics, the utilized encoder, and the desired bitrate and encoding configuration. Our framework is compatible with all current and future codec and transport standards, as our deep precoding network structure is trained in conjunction with linear upscaling filters (e.g., the bilinear filter), which are supported by all web video players. Extensive evaluation on FHD (1080p) and UHD (2160p) content and with widely-used H.264/AVC, H.265/HEVC and VP9 encoders, as well as a preliminary evaluation with the current test model of VVC (v.6.2rc1), shows that coupling such standards with the proposed deep video precoding allows for 8% to 52% rate reduction under encoding configurations and bitrates suitable for video-on-demand adaptive streaming systems. The use of precoding can also lead to encoding complexity reduction, which is essential for cost-effective cloud deployment of complex encoders like H.265/HEVC, VP9 and VVC, especially when considering the prominence of high-resolution adaptive video streaming

Combined system of precise positioning of pilotless helicopter-type aircraft in the landing area

On-board equipment, ground equipment, and special software have been developed and tested that makes it possible to determine with high accuracy the relative coordinates of a helicopter-type unmanned aerial vehicle relative to a quick deployment runway in the absence of signals from global navigation systems

Method of W-Ni-Fe Composite Spherical Powder Production and the Possibility of Its Application in Selective Laser Melting Technology

For the first time, a powder of W-5Ni-2Fe composition with spherical particles from 15 to 50 microns and a tungsten grain size from 0.5 to 3 microns was obtained using a new technological approach, developed by the authors, based on plasma spheroidization of powder granules made from nanoparticles synthesized in a plasma chemical process. The possibility of using the obtained spheroidized powder W-5Ni-2Fe in the process of selective laser melting (SLM) has been proved. The microstructure, physical, and mechanical characteristics of experimental samples made using SLM technology from the produced W-5Ni-2Fe powder have been studied. The results of the performed studies have shown that the microstructure of experimental samples is extremely dependent on the parameters of the SLM process. The precise choice of the SLM process mode made it possible to obtain a homogeneous structure of experimental samples of tungsten heavy alloy (WHA), with a tungsten grain size of about 1–2 microns, which is much smaller than the tungsten grain size in traditional heavy alloys. This creates prerequisites for increasing the strength characteristics of parts of complex shapes made by the SLM method from such powders. The maximum values of density and hardness of experimental samples obtained in the conducted studies are not worse than the values of samples obtained using traditional liquid-phase sintering technology. It is determined that the main problem of SLM powder W-5Ni-2Fe during investigation is the heterogeneity of the microstructure of massive samples and the formation of micropores and microcracks

Method of W-Ni-Fe Composite Spherical Powder Production and the Possibility of Its Application in Selective Laser Melting Technology

For the first time, a powder of W-5Ni-2Fe composition with spherical particles from 15 to 50 microns and a tungsten grain size from 0.5 to 3 microns was obtained using a new technological approach, developed by the authors, based on plasma spheroidization of powder granules made from nanoparticles synthesized in a plasma chemical process. The possibility of using the obtained spheroidized powder W-5Ni-2Fe in the process of selective laser melting (SLM) has been proved. The microstructure, physical, and mechanical characteristics of experimental samples made using SLM technology from the produced W-5Ni-2Fe powder have been studied. The results of the performed studies have shown that the microstructure of experimental samples is extremely dependent on the parameters of the SLM process. The precise choice of the SLM process mode made it possible to obtain a homogeneous structure of experimental samples of tungsten heavy alloy (WHA), with a tungsten grain size of about 1–2 microns, which is much smaller than the tungsten grain size in traditional heavy alloys. This creates prerequisites for increasing the strength characteristics of parts of complex shapes made by the SLM method from such powders. The maximum values of density and hardness of experimental samples obtained in the conducted studies are not worse than the values of samples obtained using traditional liquid-phase sintering technology. It is determined that the main problem of SLM powder W-5Ni-2Fe during investigation is the heterogeneity of the microstructure of massive samples and the formation of micropores and microcracks

Pluripotency gene network dynamics: System views from parametric analysis.

Multiple experimental data demonstrated that the core gene network orchestrating self-renewal and differentiation of mouse embryonic stem cells involves activity of Oct4, Sox2 and Nanog genes by means of a number of positive feedback loops among them. However, recent studies indicated that the architecture of the core gene network should also incorporate negative Nanog autoregulation and might not include positive feedbacks from Nanog to Oct4 and Sox2. Thorough parametric analysis of the mathematical model based on this revisited core regulatory circuit identified that there are substantial changes in model dynamics occurred depending on the strength of Oct4 and Sox2 activation and molecular complexity of Nanog autorepression. The analysis showed the existence of four dynamical domains with different numbers of stable and unstable steady states. We hypothesize that these domains can constitute the checkpoints in a developmental progression from naïve to primed pluripotency and vice versa. During this transition, parametric conditions exist, which generate an oscillatory behavior of the system explaining heterogeneity in expression of pluripotent and differentiation factors in serum ESC cultures. Eventually, simulations showed that addition of positive feedbacks from Nanog to Oct4 and Sox2 leads mainly to increase of the parametric space for the naïve ESC state, in which pluripotency factors are strongly expressed while differentiation ones are repressed

Pluripotency gene network dynamics: System views from parametric analysis - Fig 5

<p><b>a-b:</b> Time series of mRNA and protein expressions for <i>Nanog</i> at <i>h = 10</i>: <i>v</i>_<i>1</i>—<i>Nanog</i> mRNA concentration, <i>v</i>_<i>2</i> –Nanog protein concentration in the nucleus, <i>v</i>_<i>3</i>—Nanog protein concentration in the cytoplasm; The insets in Fig 5A and 5B represent the same curves as on the main part, but with a zoomed scale of the y-axis. <b>c-d:</b> Time series for concentrations of pluripotent (<i>w</i>_<i>1</i>) and differentiation (<i>w</i>_<i>2</i>) factors. Concentration oscillations of Nanog and pluripotent/differentiation factors occurred at <i>A = 0</i>.<i>2</i> (a, c) and <i>A = 0</i>.<i>3</i> (b, d). The other parameters were fixed. c: The pluripotent factors <i>w</i>_<i>1</i> were suppressed and the differentiation factors <i>w</i>_<i>2</i> were expressed. This state corresponds to differentiation. d: Pluripotent factors were highly expressed, and differentiation factors were suppressed. This state corresponds to pluripotency.</p

Pluripotency gene network dynamics: System views from parametric analysis - Fig 1

<p><b>A:</b> The core transcriptional network of the factors orchestrating the pluripotency and differentiation genes (suggested by [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194464#pone.0194464.ref010" target="_blank">10</a>]). External A₊ and B_- signals activate and repress expression of <i>Oct4</i>, <i>Sox2</i> and <i>Nanog</i> genes, correspondingly. Oct4 and Sox2 form a heterodimer, Oct4/Sox2, which positively regulates <i>Oct4</i>, <i>Sox2</i> and <i>Nanog</i> expression. Nanog directly induces <i>Oct4</i>, <i>Sox2</i> and its own expression. Oct4/Sox2 heterodimer and Nanog positively regulate pluripotency genes and repress differentiation genes. <b>B:</b> The revised core gene network suggested in this paper, in which transcription and translation processes were added; external signal B- is removed and positive signal A+ activates transcription of <i>Oct4</i> и <i>Sox2</i> genes. Nanog represses its own transcription and does not influence on <i>Oct4</i> and <i>Sox2</i> expression.</p

Biological relevance and values of the model parameters.

<p>Biological relevance and values of the model parameters.</p

The bistable switch in the core network depending on (<i>a</i>_<i>3</i>, <i>a</i>_<i>7</i>) parameters and at <i>h = 6</i>.

<p>Highlighted region is the range of parameter values, having which the system has switch-like behavior. Furthermore, the analysis indicated that a straight line <i>a</i>_<i>3</i> = <i>a</i>_<i>7</i> divides the plane (<i>a</i>_<i>3</i>, <i>a</i>_<i>7</i>) it into two areas. When <i>a</i>_<i>3</i> < <i>a</i>_<i>7</i>, the cell has differentiated state at all values <i>A</i> ≥ <i>0</i>. When <i>a</i>_<i>3</i> > <i>a</i>_<i>7</i>, there will be some <i>A</i>_<i>0</i>, that upon <i>A</i> > <i>A</i>_<i>0</i> the cell is pluripotent, while at <i>A</i> < <i>A</i>_<i>0</i> the cell will differentiate.</p

Dependence of the Hill coefficient value on the value of OS activating signal at which transition from differentiation to pluripotency occurs.

<p>The horizontal and vertical axes represent the values of parameters <i>A</i>_<i>0</i> and <i>h</i>, respectively. The curve distinguishes between pluripotency and differentiation states.</p