A New Transcoding Scheme for Scalable Video Coding to H.264/AVC

Requests from various video terminals push video servers to equip with scalability for video contents distribution in different ways. Scalable Video Coding (SVC) as the extension of H.264/AVC standard can provide the scalability for video servers by encoding videos into one base layer and several enhancement layers. To enable mobile devices without scalability receive videos at their best extent, converting bit-streams from SVC into H.264/AVC becomes the key technique. Bit-stream rewriting is the simplest way without quality loss. However, rewriting is not a real transcoding scheme, since it needs to modify SVC encoders. This paper proposes a novel transcoding approach to support spatial scalability by minimizing the distortions generated from re-encoding process. The proposed scheme keeps the input bit-streams’ information at maximum and adopts the hybrid upsampling method to do residue scaling, which can reduce the transcoding distortion into minimization. Experimental results demonstrate that the loss of the rate-distortion (RD) performance of the proposed transcoding scheme is better than Full Decoding Re-encoding (FDR) which can get the highest video quality in general sense, by achieving up to 0.9 dB Y-PSNR gain while saving 95%~97% processing time

Impact of Connected Vehicles on Mitigating Secondary Crash Risk

Reducing the risk of secondary crashes is a key goal for effective traffic incident management. However, only few countermeasures have been established in practices to achieve the goal. This is mainly due to the stochastic nature of both primary and secondary crashes. Given the emerging connected vehicle (CV) technologies, it is highly likely that CVs will soon be able to communicate with each other through the ad-hoc wireless vehicular network. Information sharing among vehicles is deemed to change traffic operations and allow motorists for more proactive actions. Motorists who receive safety messages can be motivated to approach queues and incident sites with more caution. As a result of the improved situational awareness, the risk of secondary crashes is expected to be reduced. To examine whether this expectation is achievable or not, this study aims to assess the impact of connectivity on the risk of secondary crashes. A simulation-based modeling framework that enables vehicle-to-vehicle communication module was developed. Since crashes cannot be directly simulated in micro-simulation, the use of surrogate safety measures was proposed to capture vehicular conflicts as a proxy for secondary crash risk upstream of a primary crash site. An experimental study was conducted based on the developed simulation modeling framework. The results show that the use of connected vehicles can be a viable way to reduce the risk of secondary crashes. Their impact is expected to change with an increasing market penetration of connected vehicles. © 2017 Tongji University and Tongji University Press

On the radiation force fields of fractional-order acoustic vortices

Here we report the creation and observation of acoustic vortices of fractional order. Whilst integer orders are known to produce axisymmetric acoustic fields, fractional orders are shown to break this symmetry and produce a vast array of unexplored field patterns, typically exhibiting multiple closely spaced phase singularities. Here, fractional acoustic vortices are created by emitting ultrasonic waves from an annular array of sources using multiple ramps of phase delay around its circumference. Acoustic radiation force patterns, including multiple concentration points, short straight lines, triangles, squares and discontinuous circles are simulated and experimentally observed. The fractional acoustic vortex leading to two closely spaced phase singularities is used to trap, and by controlling the order, reversibly manipulate two microparticles to a proximity of 0.3 acoustic wavelengths

Supporting Transportation System Management and Operations Using Internet of Things Technology

Low power wide-area network (LPWAN) technology aims to provide long range and low power wireless communication. It can serve as an alternative technology for data transmissions in many application scenarios (e.g., parking monitoring and remote flood sensing). In order to explore its feasibility in transportation systems, this project conducted a review of relevant literature to understand the current status of LPWAN applications. An online survey that targeted professionals concerned with transportation was also developed to elicit input about their experiences in using LPWAN technology for their projects. The literature review and survey results showed that LPWAN’s application in the U.S. is still in an early stage. Many agencies were not familiar with LPWAN technology, and only a few off-the-shelf LPWAN products are currently available that may be directly used for transportation systems. To conceptually explore data transmission, a set of lab tests, using a primary LPWAN technology, namely LoRa, were performed on a university campus area as well as in a rural area. The lab tests showed that several key factors, such as the mounting heights of devices, distance between the gateway and sensor nodes, and brands of devices affected the LPWAN’s performance. Building upon these efforts, the research team proposed a high-level field test plan for facilitating a potential Phase 2 study that will address primary technical issues concerning the feasibility of transmitting data of different sizes, data transmission frequency, and transmission rate, deployment requirements, etc

Secure Split Learning against Property Inference, Data Reconstruction, and Feature Space Hijacking Attacks

Split learning of deep neural networks (SplitNN) has provided a promising solution to learning jointly for the mutual interest of a guest and a host, which may come from different backgrounds, holding features partitioned vertically. However, SplitNN creates a new attack surface for the adversarial participant, holding back its practical use in the real world. By investigating the adversarial effects of highly threatening attacks, including property inference, data reconstruction, and feature hijacking attacks, we identify the underlying vulnerability of SplitNN and propose a countermeasure. To prevent potential threats and ensure the learning guarantees of SplitNN, we design a privacy-preserving tunnel for information exchange between the guest and the host. The intuition is to perturb the propagation of knowledge in each direction with a controllable unified solution. To this end, we propose a new activation function named R3eLU, transferring private smashed data and partial loss into randomized responses in forward and backward propagations, respectively. We give the first attempt to secure split learning against three threatening attacks and present a fine-grained privacy budget allocation scheme. The analysis proves that our privacy-preserving SplitNN solution provides a tight privacy budget, while the experimental results show that our solution performs better than existing solutions in most cases and achieves a good tradeoff between defense and model usability.Comment: 23 page

Methodological evolution and frontiers of identifying, modeling and preventing secondary crashes on highways

© 2018 Elsevier Ltd Secondary crashes (SCs) or crashes that occur within the boundaries of the impact area of prior, primary crashes are one of the incident types that frequently affect highway traffic operations and safety. Existing studies have made great efforts to explore the underlying mechanisms of SCs and relevant methodologies have been e volving over the last two decades concerning the identification, modeling, and prevention of these crashes. So far there is a lack of a detailed examination on the progress, lessons, and potential opportunities regarding existing achievements in SC-related studies. This paper provides a comprehensive investigation of the state-of-the-art approaches; examines their strengths and weaknesses; and provides guidance in exploiting new directions in SC-related research. It aims to support researchers and practitioners in understanding well-established approaches so as to further explore the frontiers. Published studies focused on SCs since 1997 have been identified, reviewed, and summarized. Key issues concentrated on the following aspects are discussed: (i) static/dynamic approaches to identify SCs; (ii) parametric/non-parametric models to analyze SC risk, and (iii) deployable countermeasures to prevent SCs. Based on the examined issues, needs, and challenges, this paper further provides insights into potential opportunities such as: (a) fusing data from multiple sources for SC identification, (b) using advanced learning algorithms for real-time SC analysis, and (c) deploying connected vehicles for SC prevention in future research. This paper contributes to the research community by providing a one-stop reference for research on secondary crashes

Interaction of Flavonoids from Woodwardia unigemmata with Bovine Serum Albumin (BSA): Application of Spectroscopic Techniques and Molecular Modeling Methods

Phytochemical investigation on the methanol extract of Woodwardia unigemmata resulted in the isolation of seven flavonoids, including one new flavonol acylglycoside (1). The structures of these compounds were elucidated on the basis of extensive spectroscopic analysis and comparison of literature data. The multidrug resistance (MDR) reversing activity was evaluated for the isolated compounds using doxorubicin-resistant K562/A02 cells model. Compound 6 showed comparable MDR reversing effect to verapamil. Furthermore, the interaction between compounds and bovine serum albumin (BSA) was investigated by spectroscopic methods, including steady-state fluorescence, synchronous fluorescence, circular dichroism (CD) spectroscopies, and molecular docking approach. The experimental results indicated that the seven flavonoids bind to BSA by static quenching mechanisms. The negative ∆H and ∆S values indicated that van der Waals interactions and hydrogen bonds contributed in the binding of compounds 2–6 to BSA. In the case of compounds 1 and 7 systems, the hydrophobic interactions play a major role. The binding of compounds to BSA causes slight changes in the secondary structure of BSA. There are two binding sites of compound 6 on BSA and site I is the main site according to the molecular docking studies and the site marker competitive binding assayThis work was supported by the Natural Science Foundation of China (81502921) and the Young Scholars Program of Shandong University (2015WLJH50).Peer Reviewe