nils-herrmann/clean_scirepeval huggingface dataset:
Smart Downlink Scheduling for Multimedia Streaming Over LTE Networks With Hard Handoff

This paper presents a novel smart downlink scheduling scheme to enhance the performance of multimedia transmission over long-term evolution (LTE) networks. LTE represents a promising framework for the next-generation broadband multimedia services because of its significantly increased data rate over 3G cellular networks. However, the current LTE scheduling scheme has largely been designed for general data traffic without adequate consideration of multimedia characteristics. Moreover, the hard handoff (HO) procedure adopted in LTE will further degrade the multimedia services when the mobile user moves from one cell to another. Even with increased data rate, current LTE systems still cannot deliver the expected quality of service (QoS) to the mobile users under various mobility scenarios, especially when the hard HO is evoked. Aiming at overcoming these major challenges, we develop in this paper a QoS-driven smart downlink scheduling scheme for enhanced multimedia transmission over LTE networks. The proposed design shall take the following QoS metrics into consideration: 1) the delay constraint of voice-over-Internet protocol flow; 2) the packet deadline of video flow; and 3) the service degradation induced by the hard HO procedure. We achieve the design objectives by creating three QoS-driven operational control modules: 1) a transmission delay control module to ensure the on-time arrival of various types of multimedia data; 2) an HO control module to warrant continuous multimedia services when the user moves across a cell boundary; and 3) a resource allocation module to strategically map the requested flows to best fit radio resource blocks. The simulation results confirm the performance gain of the proposed scheme.
A New Hybrid DCT-Wiener-Based Interpolation Scheme for Video Intra Frame Up-Sampling

Video frame resizing has received more and more research attention as contemporary video distributions need to deliver video to various receiving devices with different display resolutions. It is now becoming necessary for video distribution systems to be able to generate higher resolution video from lower resolution one for some end users. Current schemes in video up-sampling either only focused on improving visual quality with little or no improvement in objective quality or increasing the up-sampling accuracy by adaptively optimizing interpolation methods. Many such algorithms are typically quite complex and require substantial extra implementation efforts. In this letter, we propose a new hybrid DCT-Wiener-based interpolation scheme for video intra frame up-sampling without referencing the original high resolution video frames. This scheme takes full advantage of interpolation in both DCT domain and spatial domain and seamlessly integrates these two approaches to design an improved up-sampling filter. Experiments have been carried out to demonstrate that noticeable improvement in both objective and visual quality are obtained. With similar complexity, the proposed algorithm can achieve up to 4 dB gain in PSNR over fixed parameter Wiener filter-based interpolation, 4 dB gain over popular bicubic interpolation, and 1 dB gain over up-sampling scheme in DCT domain.
A fast H.264 compressed domain watermarking scheme with minimized propagation error based on macro-block dependency analysis

Embedding watermark into H.264 bit-streams directly can simplify encoding procedure and reduce computational cost comparing with conventional encoder based watermarking algorithms. However, possible error propagation may occur due to the prediction mechanism of the H.264 codec and cause video quality degradation. Expensive computation is often needed to compensate such drift. Furthermore, compensation in compressed domain usually leads to significant increase in the size of the watermarked video. To address these problems, we have developed a novel paradigm that can minimize the error propagation due to the watermarking process with very low complexity, high fidelity, robustness and security. This new paradigm is based on careful analysis of the dependency relation among the macro-blocks. We first extract the macro-block dependencies from the H.264 prediction mechanism and cache them as a graph. We then select these macro-blocks that have the least impact to the overall sequence to embed the desired watermark. This new way of embedding shall intrinsically minimize the error propagation without post processing of drift compensation. Extensive simulations have been carried out to confirm that the proposed watermark embedding is indeed able to achieve the desired performance with low complexity, high fidelity, robustness and security.
QoE management in emerging multimedia services

The realization of the paradigm of Internet anywhere, anytime and any-device and the diffusion of end-user multimedia devices with powerful and userfriendly capabilities, such as smartphones/PDAs, tablet PCs, mobile gaming terminals, and ebook readers, are leading to the proliferation of a wide range of emerging multimedia services, including immersive environments, mobile online gaming, 3D virtual world, book/newspaper consumption, social networking, and IPTV applications, just to cite a few. Some of these services have already reached a major market success, such as the case of newspaper/magazine mobile readers and smartphone multimedia apps. Their success has been achieved especially because a user-centric approach has been followed to design the whole process of content production, service activation, content consumption, service management, and updating. Indeed, the quality of the user experience, the perceived simplicity of accessing and interacting with systems and services, and the effective and acceptable hiding of the complexity of underlying technologies are determining factors for success or failure of these novel services.
Bayesian game based power control scheme for inter-WBAN interference mitigation

Wireless body area network (WBAN) is an emerging technology that provides socialized health monitoring service. However, the quality of service can be severely degraded by concomitant inter-WBAN interference in some specific environments where multiple WBANs are densely deployed, e.g., hospitals and senior citizen communities. In this work, we propose a Bayesian game based power control scheme to mitigate the impact of inter-WBAN interference. By modeling WBANs as players and active links as types of players in the Bayesian game model, the proposed power control scheme tries to maximize each player's expected payoff involving both throughput and energy efficiency. We prove the existence of Bayesian equilibrium (BE) for the proposed power control game and also derive a practical sufficient condition for the uniqueness of BE. A harmonic mean based algorithm is then proposed to obtain an approximation of BE point without the need to pass message among WBANs, which satisfies the non-cooperative manner for inter-WBAN interference mitigation. Simulation results show that the proposed algorithm can converge to the BE point effectively.
Robust uncoded video transmission over wireless fast fading channel

This research studies robust uncoded video transmission over wireless fast fading channel, where only statistical channel state information (CSI) is available at the transmitter. We observe that increasing channel diversity for high priority (HP) data is essential to improving the robustness of video transmission in fading channels. By utilizing the noise and loss resilient nature of video, we find it possible to design a more robust system by re-allocating the power and channel uses among HP and LP (low priority) data. With total power and channel use constraints, we derive an optimal resource allocation scheme under the squared error distortion criterion. In particular, we first propose a new power allocation algorithm at given channel allocation. Second, based on the proposed power allocation algorithm, we design a channel allocation algorithm to strike the tradeoff between the diversity increase of HP data and the information loss of LP data. Third, under known noise power distribution, we derive the optimal resource allocation for uncoded video multicast. Simulations show that the proposed system achieves 2dB and 5dB gain in average and outage PSNR over Softcast in video unicast, and around 1.4dB and 4dB gain in multicast.
Error resilient scalability for video bit-stream over heterogeneous packet loss networks

Robust transmission of compressed video bit-streams over heterogeneous packet loss network is one of the key challenges in the contemporary video communication system. Recent researches have focused on enhancing error resilience of bit-stream through the deployment of transcoder between wired and wireless networks. However, the conventional error resilient algorithms (e.g., Intra refresh) through cascading decoding and encoding processes usually have high degree of complexity. We introduce in this paper a completely new concept of error resilient scalability. We develop an extremely low complexity scheme based on redundant pictures information. In this scheme, redundant picture information is generated at the encoder and can be applied at media gateway to determine the redundant quantity of bit-stream according to the packet loss rate of access network. By transmitting compressed bit-stream together with redundant picture information, we are able to achieve the desired error resilient scalability of video bit-stream at the media gateway for heterogeneous networks. Joint rate source-channel-distortion model is adopted to optimize the generation of redundant picture information under various packet loss rates. Experimental results demonstrate expected effectiveness of the proposed scheme in error resilience scalability.
Flexible Polymer Photovoltaic Devices Prepared With Inverted Structures on Metal Foils

We have prepared top-illuminated organic photovoltaic devices on stainless-steel substrates, using molybdenum trioxide/indium tin oxide as the transparent top electrode. Incorporating an Al counter electrode grid having a shadow fraction of 10% effectively reduced the device resistance, thereby enhancing the power conversion efficiency to ca. 3%. This device exhibited superior mechanical flexibility. The inverted device architecture eliminated the need to use low-work-function metals, which are air sensitive and easily oxidized, thereby improving the air stability of the flexible devices.
On the effective capacities of distributed and co-located large-scale antenna systems

Effective capacity analysis is a powerful tool to investigate the impact of physical layer designs on the link layer delay-sensitive QoS performance, which is important for real-time multimedia applications. In this paper, we rigorously analyze the effective capacities of downlink large-scale antenna systems. The main focus is to establish the fundamental effective capacity in a very-large MIMO system, and to characterize the performance difference between co-located and distributed antenna layouts. To that end, we first analytically derive the closed-form effective capacities for two widely used linear precoding schemes, conjugate beamforming and zero-forcing beamforming. We then analyze the asymptotic average effective capacities when the number of BS antennas and the number of users grow unboundedly with a fixed ratio. The effective capacity gain of the distributed antenna layout over the co-located layout is established via theoretical analysis.
Fast Haze Removal for Nighttime Image Using Maximum Reflectance Prior

In this paper, we address a haze removal problem from a single nighttime image, even in the presence of varicolored and non-uniform illumination. The core idea lies in a novel maximum reflectance prior. We first introduce the nighttime hazy imaging model, which includes a local ambient illumination item in both direct attenuation term and scattering term. Then, we propose a simple but effective image prior, maximum reflectance prior, to estimate the varying ambient illumination. The maximum reflectance prior is based on a key observation: for most daytime haze-free image patches, each color channel has very high intensity at some pixels. For the nighttime haze image, the local maximum intensities at each color channel are mainly contributed by the ambient illumination. Therefore, we can directly estimate the ambient illumination and transmission map, and consequently restore a high quality haze-free image. Experimental results on various nighttime hazy images demonstrate the effectiveness of the proposed approach. In particular, our approach has the advantage of computational efficiency, which is 10-100 times faster than state-of-the-art methods.
Analysis of Retry Limit for Supporting VoIP in IEEE 802.11e EDCA WLANs

We present in this paper an analysis of retry limit for supporting VoIP in  The proposed research considers packet delay as an important factor of QoS performance measure for providing time-bounded service, such as VoIP and video in WLANs which usually implement default parameters. We also present an analytical method based on a Markov chain model that allows us to derive theoretical bounds for retry limit analysis. Based on the Markov chain model that considers retry limit, we can analyze the performance of VoIP over EDCA mechanism. In addition, in order to resolve the bottleneck transmission in VoIP in the downlink of AP, we maintain that the best service can be achieved when the throughputs of uplink and downlink are the same. Such a cross performance point is studied with respect to different retry limit parameters. Finally, extensive simulations have been carried out to validate the analytical model as well as to find out the corresponding cross point. We demonstrate that an enhanced VoIP capacity can be achieved by selecting appropriate retry limit and contention window size parameters.
Low-complexity rate control based on ρ-domain model for Scalable Video Coding

In this paper, we present a novel low complexity yet very efficient rate control algorithm for Scalable Video Coding (SVC) based on the ρ-domain model. Compared with the conventional ρ-domain model in determining quantization parameter, the proposed algorithm adopts a new linear model to obtain the quantization parameter at frame-level. This linear model is able to characterize the relationship between the percentage of zero among quantized coefficients and the quantization step. Since this model considers the Mean Absolute Difference (MAD) of each frame, individual frame only needs to be encoded once to control the bit-rate. In particular, the model parameter in the ρ-domain model can be adaptively estimated by utilizing either temporal or inter-layer information. This leads to significant improvement in estimation accuracy. Experimental results show that the proposed algorithm can achieve accurate bit-rate and maintain the maximum mismatch between actual bit-rate and target bit-rate within 0.5%. More importantly, the proposed low complexity algorithm is able to obtain PSNR improvement up to 0.6dB comparing with the algorithm adopted in the Joint Scalable Video Model (JSVM).
Robust sensor selection for collaborative spectrum sensing with attacks under correlated shadowing

Collaborative spectrum sensing is an effective technique to improve the performance of spectrum sensing in cognitive radio. However, collaborative gains are limited by attacks and correlated shadowing. In this paper we propose a robust sensor selection algorithm to select reliable and less correlated sensors under both independent and collaborative attacks in correlated environment. Firstly, we iteratively exclude sensors whose reports have abnormal high similarities since the reports of collaborative attackers have the highest similarities. Secondly, we select the desired number of sensors which are reliable and less correlated from the remained sensors based on a well designed cost matrix which measures sensors' reliabilities and correlations. The sensor selection is modeled as a cost sum optimization problem and a suboptimal solution is found by applying greedy algorithm. It is shown by simulations that the proposed robust sensor selection algorithm has a good performance.
Video denoising based on matrix recovery with total variation priori

This article presents a novel scheme for video denoising based on improved matrix recovery strategy. The proposed scheme attempts to go beyond the conventional approaches that focus on the rank properties of the matrix by making use of a priori knowledge derived from the characteristics of video and noise. In this paper, we will first demonstrate that the conventional approach such as robust PCA (principal component analysis) is not effective when the video is corrupted by the mixture of impulse and Gaussian noises. The impulse noise can be considered sparse in the image domain and can be effectively filtered by matrix recovery. However, the dense Gaussian noise cannot be easily filtered because it is not sparse in either spatial or frequency domain. We shall show that this Gaussian noise corrupted video can be considered sparse in the 3D total variation domain. Based on this, we formulate the problem as a 3D total variation optimization and design an algorithm to solve this convex problem efficiently. Experimental results show that the proposed scheme achieves noticeable improvement over the state-of-the-art algorithm VBM3D .
Joint Source-Channel-Authentication Resource Allocation and Unequal Authenticity Protection for Multimedia Over Wireless Networks

There have been increasing concerns about the security issues of wireless transmission of multimedia in recent years. Wireless networks, by their nature, are more vulnerable to external intrusions than wired ones. Many applications demand authenticating the integrity of multimedia content delivered wirelessly. In this work, we describe a framework for jointly coding and authenticating multimedia to be delivered over heterogeneous wireless networks. We firstly introduce a novel concept called unequal authenticity protection (UAP), which unequally allocate resources to achieve an optimal authentication result. We then consider integrating UAP with specific source and channel-coding models, to obtain optimal end-to-end quality by the means of joint source-channel-authentication analysis. Lastly, we present an implementation of the proposed joint coding and authentication system on a progressive JPEG coder. Experimental results demonstrate that the proposed approach is indeed able to achieve the desired authentication of multimedia over wireless networks
Modeling, Analysis, and Visualization of Left Ventricle Shape and Motion by Hierarchical Decomposition

This paper presents an approach to the modeling, analysis, and visualization of left ventricle motion and deformation. The authors' modeling of left ventricle shape and motion as a hierarchical representation enables them to develop a promising noninvasive technique for monitoring heart dynamics where both image analysis and image synthesis are involved. The proposed hierarchical motion model of left ventricle is constructed by combining several existing simple models and is able to capture major motion and deformation components of the left ventricle. The hierarchical decomposition characterizes the left ventricle motion and deformation in a coarse-to-fine fashion and leads to computationally efficient estimation algorithms. The authors estimate the global rigid motion of the left ventricle by establishing a time-varying object-centered coordinate system. The global deformations of the left ventricle are obtained by fitting the given data to superquadric modeling primitives. The local deformations are estimated by a tensor-description approach that is based on the locally deformable surface obtained by constructing spherical harmonic local surface from the residues of global shape estimation. The authors also describe in this paper methods of image synthesis and dynamic animation for visualizing the estimated results of the time-varying left ventricle shape, motion, and deformations. These animation results are consistent with the apparent motion pattern of the left ventricle and therefore show the success of the authors' hierarchical decomposition based approach.
Transmission-Rate-Adaption Assisted Energy-Efficient Resource Allocation With QoS Support in WBANs

With the advances in wearable sensors and wireless technologies, wireless body area network (WBAN) has become a promising network to provide health applications, such as ubiquitous e-Health services and real-time health monitoring. In these WBANs, quality of service (QoS) requirements, including packet loss rate, throughput, and delay, need to be guaranteed for providing reliable and real-time data transmission even under highly dynamic environment due to human mobility and postures. Meanwhile, energy efficiency is another key factor to consider for increasing the network lifetime in such a resource-constrained network. In this paper, a transmission-rate-adaption assisted and energy-efficient resource allocation scheme is proposed in which both constraints of QoS metrics and the characteristics of dynamic links are considered. Specifically, a QoS optimization problem is formulated to optimize the transmission power and time slots for each sensor, which minimizes energy consumption subjected to the QoS constraints. Due to the dynamic link characteristics, the link quality may become poor, and then the QoS requirements of normal packets and emergency packets cannot be satisfied. Besides, the emergency packets should receive more attentions with a high priority and high QoS requirements. To guarantee the QoS requirements when the link is very poor, a transmission rate adaption policy is proposed to carefully adjust the transmission rate at each sensor to assist the QoS optimization problem, and a priority-based retransmission strategy is designed to apply the retransmission strategy to further improve the performances of the emergency packets with a high priority. Numerical results demonstrate the effectiveness of the QoS optimization problem, the proposed transmission rate adaption policy, and the priority-based retransmission strategy.
Multiple bitstream image transmission over wireless sensor networks

In this paper, we proposed a novel scheme for error robust and energy efficient image transmission over wireless sensor networks. The innovations of proposed scheme are two folds: multiple bitstream image encoding to achieve error robust transmission and small fragment burst transmission to achieve efficient transmission. In the case of image encoding, a multiple bitstream image encoding is developed based on the decomposition of images in the wavelet domain. We first group wavelet coefficients into multiple trees according to parent-child relationship and then code them separately by SPIHT algorithm to form multiple bitstreams. We show that such decomposition is able to reduce error propagation in transmission. To further enhance the error robustness, unequal error protection strategy with RCPC/CRC is implemented. The coding rate is designed based on the bit error sensitivity of different bit planes. In the stage of image transmission, we divide the multiple bit streams into small fragments and transmit them in burst. We demonstrate that such transmission strategy matches well with the media access control layer protocol as well as the link layer protocol currently employed in wireless sensor networks. We achieve energy efficient transmission by saving energy consumed on control overhead and device switching from sleep to active. Experimental results show that the proposed scheme has not only high energy efficiency in transmission but also graceful degradation in PSNR performance over high BERs channels in terms of image reconstruction quality at the base station.