A signal adaptive diffusion filter for video coding: Mathematical framework and complexity reductions

In this paper we combine video compression and modern image processing methods. We construct novel iterative filter methods for prediction signals based on Partial Differential Equation (PDE) based methods. The mathematical framework of the employed diffusion filter class is given and some desirable properties are stated. In particular, two types of diffusion filters are constructed: a uniform diffusion filter using a fixed filter mask and a signal adaptive diffusion filter that incorporates the structures of the underlying prediction signal. The latter has the advantage of not attenuating existing edges while the uniform filter is less complex. The filters are embedded into a software based on HEVC with additional QTBT (Quadtree plus Binary Tree) and MTT (Multi-Type-Tree) block structure. In this setting, several measures to reduce the coding complexity of the tool are introduced, discussed and tested thoroughly. The coding complexity is reduced by up to 70% while maintaining over 80% of the gain. Overall, the diffusion filter method achieves average bitrate savings of 2.27% for Random Access having an average encoder runtime complexity of 119% and 117% decoder runtime complexity. For individual test sequences, results of 7.36% for Random Access are accomplished.     

论携号转网行为的私法规制

以电信用户入网协议为切入点,电信用户的携号转网行为应受到《合同法》《消费者权益保护法》等私法规范的保护与限制。该行为引起的格式条款解释、合同终止、违约责任、损失赔偿等问题,不能仅靠《电信条例》等公法规范来调整。应当积极引导广大消费者用户以私法领域相关规定为依据,转变争议解决思维,拓宽纠纷处理途径,合理选择维权手段,以保护自身合法民事权益,与行业监管部门共同推动电信行业有序发展。     

An experiential account of phantom vibration syndrome

A small handful of recent studies have addressed a phenomenon known as “phantom vibration syndrome”. This refers to when phone users perceive their device to vibrate, indicating that a call or text is incoming, when in fact the phone did not vibrate at all. Though these studies show that most users do not find phantom vibration hallucinations to be very bothersome, they also find that a large majority of users experience this phenomenon. This paper explores what the striking prevalence of phantom vibration syndrome means for our contemporary relationships with technology. I begin with a review of the theories purporting to explain these data, which largely rely on particular understandings of the brain. Next I develop an alternative theory of phantom vibration syndrome based on insights from the philosophical tradition of phenomenology. This account considers the ways users develop bodily and perceptual habits regarding how the phone is understood and used. By critically contrasting these different theories, we can refine our questions about what the high prevalence of phantom vibration syndrome implies about our contemporary technological situation.     

Nonlinear dynamic behaviors and control based on simulation of high-purity heat integrated air separation column

In this paper, the dynamic behaviors on the basis of simulation for high-purity heat integrated air separation column (HIASC) are studied. A nonlinear generic model control (GMC) scheme is proposed based on the nonlinear behavior analyses of a HIASC process, and an adaptive generic model control (AGMC) scheme is further presented to correct the model parameters online. Related internal model control (IMC) scheme and multi-loop PID (M-PID) scheme are also developed as the comparative base. The comparative researches are carried out among these linear and nonlinear control schemes in detail. The simulation research results show that the proposed AGMC schemes present advantages in both servo control and regulatory control for the high-purity HIASC.     

Control of the particle microstructure during the synthesis of bulk-polymerized transparent methacrylate-acrylonitrile-butadiene-styrene resin

A series of methacrylate-acrylonitrile-butadiene-styrene (MABS) resins was prepared using bulk polymerization. The polarity of the continuous phase and the compatibility of two phases were changed by adjusting the methyl methacrylate (MMA) content, choosing values that were close to styrene-butadiene rubber solubility value. The possibility of controlling the microstructure of the MABS resin by changing the polarity of the components and the compatibility of two phases was assessed. The dynamic mechanical analysis shows that the compatibility of two phases varies with the MMA content. The morphological analysis shows that increasing MMA contents results in a gradual decrease in the sub-inclusion structure with a network skeleton of rubber particles, and that all the particles become solid rubber when the MMA content reaches 75%. The sub-inclusion structure reappears but does not have a network skeleton when the MMA content is 90%. The impact strength and morphological analysis indicate that the solid rubber particles and the sub-inclusion structure with a network skeleton provide excellent toughness, while the sub-inclusion structure without a network skeleton does not. In contrast, the transmittance of the ABS resin first increased and then decreased with increasing MMA content.     

Evolving an Accurate Decision Tree-Based Model for Predicting Carbon Dioxide Solubility in Polymers

Solubility is one of the most indispensable physicochemical properties determining the compatibility of components of a blending system. Research has been focused on the solubility of carbon dioxide in polymers as a significant application of green chemistry. To replace costly and time-consuming experiments, a novel solubility prediction model based on a decision tree, called the stochastic gradient boosting algorithm, was proposed to predict CO₂ solubility in 13 different polymers, based on 515 published experimental data lines. The results indicate that the proposed ensemble model is an effective method for predicting the CO₂ solubility in various polymers, with highly satisfactory performance and high efficiency. It produces more accurate outputs than other methods such as machine learning schemes and an equation of state approach.     

Sensor network design based on system-wide reliability criteria. Part I: Objectives

Reliability based criteria are quite popular for optimal sensor network design. We present a modified definition of system reliability for sensor network design for two applications: reliable estimation of variables in a steady state linear flow process, and reliable fault detection and diagnosis for any process. Unlike the weakest-link based definition of system reliability in the literature, the proposed definition considers the entire system and is consistent with the reliability concept used in classical reliability literature. For each application, dual approaches for defining system reliability are proposed, and their analogy with the reliability problem in the classical reliability literature is established. Using examples and stochastic simulations, the advantage of using the proposed system reliability in contrast to the existing definition is illustrated. Part II of this series of articles presents methods for efficient generation of the system reliability function and its use in optimization-based approaches for designing optimal sensor networks.