nils-herrmann/clean_scirepeval huggingface dataset:
Variable Accuracy Sensing in Energy-Constrained Wireless Sensor Networks

Networks comprising large numbers of low-cost, low-power and miniature wireless sensors are used to capture accurate and reliable information of the physical phenomena they are proximate to. However being operated by batteries of finite capacity, energy efficiency is still the major concern in the design of protocols in such networks. In this paper, we first introduce a new sensing scheme that allows variable accuracy to be specified by end users to achieve a trade-off between accuracy and energy efficiency. We then consider the connected active node selection for network lifetime prolongation problem under the proposed scheme by modifying the route weights in a pre-existing algorithm and introduce a new algorithm. The objective of this work is to allow trade-off between accuracy and energy efficiency in a sensor network and use only a subset of sensors to realize a given query, so that energy at inactive ones can be conserved. Extensive experiments show that the proposed sensing scheme and algorithms attain a longer network lifetime by selecting a subset of sensors to provide data at an accuracy determined by end users.
Stream morphing approaches to temporal scalable video coding

Stream morphing has been previously introduced as an efficient way of simulcasting a hierarchy of single-layer descriptions of a single video sequence with different levels of quality while sharing the same frame size and rate. One application for this process was SNR scalable video coding. This paper presents two different adaptations of the stream morphing process to temporal scalability, one with bi-directional motion compensated prediction and one without. Both methods retain the attractive features of the original SNR scalable structure, notably the use of a single quantization cycle and single decoder motion-compensated prediction loop irrespective of the number of layers present and the ability to convert between single-layer and scalable forms without transcoding.
A statistical error detection technique for low bit-rate video

Multimedia services requiring image and video compression are now widely available over fixed telecommunications networks such as cable television networks and the Internet. In the future, these services will also be provided over wireless networks similar to those currently used for digital mobile telephony. As a consequence of the high bit error rates associated with these channels, special error-resilient coding techniques are required to achieve a satisfactory picture quality. An error detection scheme based on the detection of statistically incorrect information, is introduced. The new technique calculates statistical information about the video sequence currently being decoded and uses this information to detect and conceal macroblocks which have been incorrectly decoded. Simulation results show this technique provides a significant improvement in the decoded image quality while requiring no additional information to be transmitted to the decoder.
Enhanced Motion Compensation Using Elastic Image Registration

In this paper we propose a method for extending the standard motion estimation algorithms used in video compression algorithms, to incorporate motion parameters that describe non-translational motion. This method uses an elastic image registration algorithm with two-dimensional discrete cosine basis functions to estimate the motion between block partitions in two video frames. A rate and a distortion are then determined for the elastic motion compensation and these are included in the mode decision calculations of the encoder algorithm. This allows the encoder to trade off bits to describe a more complex motion with bits to describe a larger residual error from a simpler translational motion model. Experimental results show an improvement in compression efficiency of 10-20% can be obtained with this enhanced motion compensation algorithm.
Optimal QoS mapping for streaming video over Differentiated Services networks

We investigate streaming packet video over relative Differentiated Services (DiffServ) networks which can provide a number of aggregated traffic classes, ordered in a way such that class q+l is better or at least no worse than class q in terms of packet loss. We propose an algorithm for optimal quality of service (QoS) mapping from the video packets to a set of available DiffServ classes. The performance of our algorithm is evaluated through experimental tests and compares favorably to previous works.
Improved Resilience for Video Over Packet Loss Networks With MDC and Optimized Packetization

We investigate the problem of robust video transmission over lossy packet networks. A resilient video coding framework is important to ensure quality video over these networks. We propose a combination of a rate-distortion optimized multiple description codec and an integrated packetization method to constitute the error resilient codec. Multiple description (MD) coding techniques utilize path-diversity (multiple paths between sender and receiver) in networks by sending the descriptions along different paths. Two different optimization controls for the MD codec are proposed that are suited to variable rates of packet loss for multipath transmission of the MD coded video. An optimized strategy for packetizing the descriptions is also proposed which guarantees that each packet is self-contained and efficient. Simulations done under various packet loss scenarios show the need for two different optimization strategies and also that the developed MD codec achieves significantly improved video quality when compared with similar techniques.
A Propagation-delay-tolerant Collision Avoidance Protocol for Underwater Acoustic Sensor Networks

Underwater acoustic sensor networks can be employed by a vast range of applications, retrieving accurate and up-to-date information from underneath the water surface. Although widely used by radios in terrestrial sensor networks, radio frequencies do not propagate well underwater. Acoustic channels are therefore employed as an alternative to support long-distance and low-power communication underwater, even though such channels suffer from long propagation delay and very limited bandwidth. In this paper, we investigate the impact of the large propagation delay on the throughput of selected classical MAC protocols and their variants, and show that protocols need to be revised to accommodate large propagation delay in order to achieve good throughput. We then introduce a propagation-delay-tolerant collision avoidance protocol named PCAP and show that by taking into account the propagation delay, PCAP offers higher throughput than the protocols that are widely used by conventional wireless communication networks.
Fast simulation of buffer overflows in queuing systems

Because of their rarity, the estimation of the statistics of buffer overflows in queuing systems via direct simulation is often very expensive in computer time. Past work on fast simulation using importance sampling has concentrated on systems with Poisson arrival processes and exponentially distributed service times. The authors demonstrate how, using large deviations theory and deterministic optimal control, an asymptotically optimal simulation system (in the sense of variance) can be generated for queues with a variety of arrival and service processes. In particular it is shown how to generate an optimal simulation system for a number of queues with deterministic service times. Such systems are of great practical interest because of their application of the modeling of asynchronous transfer mode switches.<<ETX>>
Error Resilience in Video and Multiplexing Layers for Very Low Bit-Rate Video Coding Systems

The transmission of audio-visual services on low-bit-rate, wireless telecommunications systems requires the use of coding techniques that are both efficient in their use of bits and robust against errors introduced in transmission. In this paper, we present efficient techniques for improving the error resilience of audio-visual services. These techniques are based on coding simultaneously for synchronization and error protection or detection. We apply the techniques to improve the performance of the multiplexing protocol (which combines the video and audio streams so that they can be transmitted on a single circuit), and also to improve the robustness of the coded video. We show through simulations that the techniques are efficient in their use of bits and effective against bursty errors common in wireless channels. For a simulation of the DECT channel at a bit-error rate of 10/sup -3/, the techniques give an order of magnitude improvement in the probability of lost packets in the multiplexer layer over more conventional techniques. In the video layer, the techniques give an improvement of between 1-2 dB over ITU-T Recommendation H.263. The techniques proposed for the video layer also have the advantage of permitting simple transcoding with bit streams complying with H.263.
Window-Based Image Registration using Variable Window Sizes

We present an unsupervised image registration algorithm to estimate the background object motion in a real video sequence. The algorithm is based on a Gaussian minimisation technique. It has been shown earlier that initialization of such an approach is very important to achieve the motion parameters of the background object precisely, and that the use of a windowing technique can give better background object motion estimation results, even with large background occlusions. In some cases, however, the fixed window size initializes the gradient descent algorithm in a sub-optimal way. Here, another window size would bring the desired estimation direction. In this paper, we present a technique where variable window sizes are used to prevent these outliers. Experimental results show that the technique works very well with the considered test sequences.
A fast approach for geometry-adaptive block partitioning

State-of-the-art video compression standards such as H.264 employ tree-structured motion compensation by splitting macro-blocks into fixed square or rectangular sub-blocks. Although, this approach leads to improved compression performance, recent studies have shown that further gain can be achieved via slicing blocks with arbitrary line segments to better match the boundaries between moving objects. However, finding the best partition remains an extremely computationally-intensive task. In this paper, we propose a fast method to identify efficient partitions using a two-step search of the radius and angle of the line segment. Experimental results show that this scheme is able to identify efficient motion boundaries using less iterations than existing techniques while maintaining comparable performance.
Efficient Streaming Packet Video Over Differentiated Services Networks

We investigate streaming video over Differentiated Services (Diffserv) networks that can provide a number of aggregated traffic classes with increasing quality guarantee. We propose a method to measure the loss impact of a video packet on the quality of the decoded video images. We show how the optimal Quality-of-Service (QoS) mapping from the video packets into a set of traffic classes depends on the loss rates of the classes and the pricing model, and we develop an algorithm to accurately find the optimal QoS mapping. The performance of our algorithm is evaluated through computer simulations and compares favorably to an existing algorithm
Impact of audio on subjective assessment of video quality

In the real world, we commonly receive information simultaneously through two or more senses, with the brain fusing this data to produce a single-coherent message. Lip-reading is one example of this phenomenon. Laboratory studies, on the other hand often measure the response to a stimulus by a single sense and extrapolate these results to predict real-world behaviour. In this paper, we show that semantics have a significant impact on viewers' sensitivity to the quality of a video sequence for spatially separated parts of the sequence-and, more importantly, that this difference in sensitivity can be changed by the presence of an audio signal. This result is important for any testing of subjects' responses to visual material. One example is the subjective assessment of the quality of video-in an audio-visual communications system (such as television or video conferencing).
Multiple Description Video Codingwith 3D-Spiht Employing a New Tree Structure

Multiple description coding (MDC) of video is a useful technique for robust video transmission over unreliable networks. MDC not only provides at least acceptable quality of video in error-prone network but it also efficiently utilizes the multipath nature of Internet and wireless networks. In this paper, multiple description video coding with 3-D set partitioning in hierarchical tree (3D-SPIHT) codec has been proposed. In particular, we propose branch-pruning technique to generate multiple descriptions. We then propose a new tree structure for 3D-SPIHT which is particularly efficient for MDC. Experimental results prove the effectiveness of the proposed method.
Multiple Description Wavelet Video Coding Employing a New Tree Structure

We describe a multiple description (MD) video coding technique using 3D-set partitioning in hierarchical tree algorithm (3D-SPIHT). Multiple description coding (MDC) is a way of coding video information into multiple bitstreams and is useful in a number of scenarios including peer-to-peer video streaming and video transmission over error-prone networks. We propose a modified tree structure for 3D-SPIHT that is more efficient for MD coding. We also propose a branch-pruning technique to generate multiple descriptions. We then show how rate-distortion optimization can be incorporated into the MDC framework to develop an efficient MD video coding system. Experimental results show that the proposed MD system achieves significant improvement in performance compared to existing methods.
Optimal Pruning Quad-Tree Block-Based Binary Shape Coding

In object-based video coding, shape masks are used to specify the shape of a video object. The binary shape means each pixel is either background or object. In this paper, we present a new lossless block-based coding algorithm for binary shapes that combines a quad-tree structure with block-based arithmetic coding; an optimal pruning quadtree structure searching algorithm is proposed to further reduce the spatial redundancy of quad-tree blocks. Experimental results demonstrate that this new approach provides a saving in bits generated between approximately 40-75% compared to the MPEG-4 binary shape coding algorithm
Improved estimation procedure for counting neighbors in underwater networks

In ad-hoc networks, at the beginning of network formation or later for routing purposes it is essential for a node to know how many neighbors it has. The capture effect, the effect of receiving a packet from a collision, can degrade the performance of the procedure of estimation of number of neighbors (ENN). The capture effect depends on different network parameters which are different in underwater communication networks (UCNs) than terrestrial communication networks (TCNs). Both electromagnetic (EM) and acoustic waves can be used in UCNs. Furthermore, underwater acoustic networks (UANs) have the problem of long propagation delays. These issues make the ENN procedure complicated. Here we propose an improved ENN procedure for UCNs as well as for TCNs which is not affected by the capture effect. The procedure requires fewer slots than earlier approaches and is much effective with packet reception time variations.
Importance sampling, jump distributions and event-time distributions

Two different methods have been proposed for performing asymptotically optimal simulation to obtain the statistics of buffer overflows in queueing networks, with both using large deviations and importance sampling. In the first, based on heuristic arguments, the distributions of interarrival and virtual service times are analyzed to find the simulation system. In the second, it is the distribution of jumps occurring in a Markov chain that is examined. The authors show that the approaches produce identical fast simulation systems for an arbitrary G1/G1/1 queue.<<ETX>>
Recurrence times of buffer overflows in Jackson networks

Estimation of the statistics of buffer overflows in networks of queues by means of simulation is inherently costly, simply because of the rarity of these events. An alternative analytic approach with very low computational cost is presented for calculating the recurrence times of buffer overflows in Jackson networks in which the recurrence times of buffer overflows in a network are expressed in terms of the recurrence times for overflows of individual buffers, isolated from the network. Equivalent results are given for continuous and discrete-time networks. This result is applied to the buffer allocation problem for queueing networks, providing extensions and further justification for a previously derived heuristic approach to this problem.<<ETX>>
Generalized framework for reduced precision global motion estimation between digital images

The efficiency of real-time digital image processing operations has an important impact on the cost and realizability of complex algorithms. Global motion estimation is an example of such a complex algorithm. Most digital image processing is carried out with a precision of 8 bits per pixel, however there has always been interest in low-complexity algorithms. One way of achieving low complexity is through low precision, such as might be achieved by quantization of each pixel to a single bit. Previous approaches to one-bit motion estimation have achieved quantization through a combination of spatial filtering/averaging and threshold setting. In this paper we present a generalized framework for precision reduction. Motivated by this framework, we show that bit-plane selection provides higher performance, with lower complexity, than conventional approaches to quantization.
Subjective evaluation and statistical analysis for improved frame-loss error concealment of 3D videos

Broadcasting of high definition stereoscopic 3D videos is growing rapidly because of increased demand in the mass consumer market. In spite of increasing consumer interest, poor quality, crosstalk or side effects and lack of defined broadcast standards has hampered the advancement of 3D displays. Real time transmission of 3DTV sequences over packet based networks may result in visual quality degradation due to packet loss and delay. In conventional 2D videos, different extrapolation and directional interpolation strategies have been used for concealing the missing blocks but in 3D, this is still an emerging field of research. Also, subjective testing is the most direct way to evaluate 3D quality and human perception on the concealed videos. This paper reviews state-of-the-art error concealment strategies and proposes a low complexity frame loss concealment method for a video decoder. Subjective testing on common 3D video sequences and its statistical comparison with existing concealment methods shows that the proposed method is efficient for the concealment of error frames of stereoscopic videos in terms of visual comfort and 3D quality.
A new method for boundary artefact reduction in JPEG 2000

It is well known that tile boundary artefacts occur in wavelet-based lossy image coding. However, until now, their cause has not been well understood. We show that boundary artefacts are an intrinsic feature associated with the common method used to choose the tile size and the type of symmetric extension employed in wavelet-based image decomposition. A novel method of reducing tile boundary artefacts is presented. This method has recently been adopted as part of the JPEG 2000 verification model. In this technique, odd tile sizes of 2/sup N/+1 are chosen rather than the conventional even tile sizes of 2/sup N/. We show that, for the same bit-rate, an image compressed using odd tile length and low pass first convention (OTLPF) has significantly fewer boundary artefacts than an image compressed using even tile sizes.
Object-Based Multiple Sprite Coding of Unsegmented Videos using H.264/AVC

In spite of recent progress in the development of hybrid block-based video codecs, it has been shown that for low-bitrate scenarios there is still coding gain applying object-based techniques. We present a sprite-based codec, based on latest H.264 features using an inbuilt segmentation approach for scenes recorded by a rotating camera. The segmentation itself is built up on reliable background estimation from the sprite and short-term image registration. Moreover, we generate multiple sprites based on physical camera parameter estimation that overcome three of the main drawbacks of sprite coding techniques. First, the coding cost for the sprite image is minimized. Second, multiple sprites allow temporal background refresh and finally, registration error accumulation is kept very small. Experimental results show that this coding approach significantly outperforms latest H.264 extensions applying hierarchical B pictures.
A New M-Estimator Approach for Global Motion Estimation

Global motion estimation (GME) is an extensively used tool in a variety of video processing applications. The major challenge in this field is the presence of large foreground objects. There is a wide variety of algorithms addressing this problem. The major shortcoming of these algorithms is inconsistent performance over several video sequences. In this paper, we propose a GME approach that is fully automatic, can successfully handle large foreground objects and provides consistent results over a range of different video sequences. The proposed method initially coarsely determines the foreground pixels by a clustering technique. The effect of remaining foreground pixels in the estimation process are then reduced by using a modified Lorentzian estimator. Experimental results prove the superiority and consistency of the proposed method compared to some recent approaches.
A motion confidence measure from phase information

The reliance of many video processing techniques on motion estimation requires a good motion confidence measure, in order to ensure that unreliable estimations are not accepted into a system. This paper proposes a new measure of motion confidence based on phase information from Fourier transform of a video frame. Using the measure, blocks associated with unreliable motion estimation are detected efficiently and accurately. The merit of the technique is a much improved sensitivity over circumstances where other measures show ambiguity. This improvement is demonstrated through our experimental and analytical results.
A distributed smart routing scheme for terrestrial sensor networks with hybrid Neural Rough Sets

The limited power consumption, as a major constraint, presents challenges in improving the network throughput for Wireless Sensor Networks (WSNs). Due to the limited computational power, the applications of WSNs in Terrestrial Networks require the capability to pre-process the observation data so as to remove irrelevant features or factors from multi-dimensional dataset. This paper proposes a intelligent distributed energy efficient routing algorithm inspired from natural learning and adaptation process with the aid of hybrid Neural Rough Sets theory, which is used to efficiently reduce the dimensionality of input dataset. The algorithmic implementation and experimental validation are described in this paper. Details of the algorithm and its testing procedures are presented in comparison with the other power-aware protocols, e.g., mini-hop. The validation of the proposed model is carried out via a wireless sensor network test-bed implemented in Castalia Simulator. The experimental results show the network performance measurements such as delay, throughput and packet loss that have been greatly improved as the outcome of applying this integration with Neural Rough Sets.