nils-herrmann/clean_scirepeval huggingface dataset:
Analysis of time-varying collusion attacks in fingerprinting systems: Capacity and throughput

We analyze time-varying collusion attacks for a fingerprinting system using concepts of capacity and throughput in this work. Continuous media provide a limited resource for data embedding, which is analogous to the capacity of a wireless communication channel. Here, we characterize the capacity of a host media using the just-noticeable-distortion (JND) of the human visual system (HVS). Furthermore, the collusion attack can be interpreted as a channel shared by multiple users. Based on this analogy, the colluder detection performance can be understood from the viewpoint of throughput. Specifically, we show how to determine instantaneous throughput using the fingerprint-to-interference-plus-noise ratio (FINR), and extend it to the total throughput and the averaged throughput over a time interval. Our analysis provides a good framework to the understanding of collusion attacks and ways to enhance the traitor tracing performance of a fingerprinting system.
Codeword design for ultra-wideband (UWB) precoding

A precoding technique applied to symbols transmitted in an ultra-wideband (UWB) system can concentrate the signal power at the receiver for a higher data detection rate. The codeword design problem for optimal UWB precoding is investigated in this work. After the problem formulation, we examine its solution in the full-rank and the reduced-rank subspaces to obtain different tradeoffs between the detection performance and the amount of feedback messages. Furthermore, we propose two subspace selection schemes, each of which corresponds to a code design method. The resultant optimal codewords improve the performance of previous work significantly at the expense of a slightly increased amount of feedback messages. Finally, the performance of a precoded UWB system with various codewords is compared via computer simulation.
Compressed video quality assessment with modified MSE

A method to adjust the mean-squared-errors (MSE) value for coded video quality assessment is investigated in this work by incorporating subjective human visual experience. First, we propose a linear model between the mean opinioin score (MOS) and a logarithmic function of the MSE value of coded video under a range of coding rates. This model is validated by experimental data. With further simplification, this model contains only one parameter to be determined by video characteristics. Next, we adopt a machine learing method to learn this parameter. Specifically, we select features to classify video content into groups, where videos in each group are more homoegeneous in their characteristics. Then, a proper model parameter can be trained and predicted within each video group. Experimental results on a coded video database are given to demonstrate the effectiveness of the proposed algorithm.
Design and analysis of Toeplitz preconditioners

The solution of symmetric positive definite Toeplitz systems Ax=b by the preconditioned conjugate gradient (PCG) method was recently proposed by Strang (1986) and analyzed by Chan (1989) and Chan and Strang (1989). The convergence rate of the PCG method depends on the choice of preconditioners for the given Toeplitz matrices. The authors present a general approach to the design of Toeplitz preconditioners based on the idea to approximate a partially characterized linear deconvolution with circular deconvolutions. All resulting preconditioners can therefore be inverted via various fast transform algorithms with O(N log N) operations. For a wide class of problems, the PCG method converges in a finite number of iterations independent of N so that the computational complexity for solving these Toeplitz systems is O(N log N).
Efficient music representation with content adaptive dictionaries

An efficient music representation based on the matching pursuit (MP) technique with content-adaptive dictionaries (CADs) is investigated in this work. The Gabor atoms are commonly adopted in the MP-based signal representation due to their excellent time-frequency localization property. However, the Gabor dictionary may not yield a concise representation for music signals. Music signals have special characteristics which are specified by pitches and durations of music notes. In this work, we exploit music characteristics to create a set of content-adaptive elementary functions called atoms that efficiently capture the inherent structure of music signals. As a result, we are able to project musical signals onto a subspace spanned by atoms from CAD for a concise and efficient representation. The proposed CAD representation technique is applied to music enhancement with noisy background to demonstrate the power of the proposed representation.
A Quad-Tree Decomposition Approach to Cartoon Image Compression

A quad-tree decomposition approach is proposed for cartoon image compression in this work. The proposed algorithm achieves excellent coding performance by using a unique quad-tree decomposition and shape coding method along with a GIF like color indexing technique to efficiently encode large areas of the same color, which appear in a cartoon-type image commonly. To reduce complexity, the input image is partitioned into small blocks and the quad-tree decomposition is independently applied to each block instead of the entire image. The LZW entropy coding method can be performed as a postprocessing step to further reduce the coded file size. It is demonstrated by experimental results that the proposed method outperforms several well-known lossless image compression techniques for cartoon images that contain 256 colors or less
Interactive image retrieval: concept, procedure and tools

The concept, procedure and tools for interactive image retrieval with multiple seed images are investigated in this research. In this paper, we consider integrating the semantic image organization and low level feature representation by user interactivity. First, high level image classification has been initiated by a supervised learning process. The classification result is dynamically adjusted by the feedback information extracted from the interactive query process, which is considered as a long term interactive refinement process. Second, the initial interactive retrieval procedure is determined by both low level features and high level semantic classification. The procedure is further refined by the user feedback so that the meaning of "similarity" defined by a specific user for a particular application can be approached gradually. The process is regarded as short term refinement. With the help of interactive query operation, system performance can never stop to be improved.
Dynamic spectrum access MAC for multi-channel ad-hoc networks

Dynamic spectrum access (DSA) technique enables dynamic access of unused or under-utilized spectrum without causing interference to existing incumbent service. Through DSA, a DSA device (second user) is offered opportunities to monitor a swath of spectrum, which is divided into myriad channels, in the licensed band. A great number of available channels offers DSA networks higher throughput as a whole and allows DSA MAC design to adopt frequency domain backoff scheme to avoid unnecessary delay in particular. Our observation indicates that the operation range (OR), the set of available channels that the MAC of a DSA device would use, has significant impact on the throughput performance of the MAC that adopts frequency domain backoff scheme. Three OR strategies, namely non-sharing (NS), partial sharing (PS), and full sharing (FS), are thoroughly studied. To validate our design, a slotted CSMA model with poisson packet arrival rate is developed to analyze the performance of the three OR strategies. We also conducted simulations to verify our theoretical work. We found that there is tradeoff between the throughput and the white space filling rate. While FS gives the best throughput performance, NS has the best performance in terms of white space filling rate.
Joint PN code acquisition and DOA estimation in asynchronous DS-CDMA systems

A technique that combines temporal filtering and spatial beamforming for joint PN (pseudonoise) code acquisition and DOA (direction-of-arrival) estimation in asynchronous direct-sequence code-division multiple access (DS-CDMA) systems with antenna arrays is proposed in this research. Traditionally, the joint code acquisition and DOA estimation is a 2-D search problem in the space-time domain. In this work, we apply window-based spatial filtering to antenna outputs to result in a set of temporal vectors, and then perform PN code acquisition on these vectors. Search results from several 1-D temporal vectors are combined to determine delay positions. Once delay positions are determined, the soft information provided by the acquisition process can be fully exploited by the next stage, i.e. DOA estimation. The proposed algorithm is a blind approach, which means that the training sequence is not necessary. Besides, the number of antennas required can be much less than that of the incoming signals, and the DOA search range can be largely reduced based on the soft information from the acquisition phase. Numerical simulations are given to demonstrate that the proposed solution is resistant to the near-far effect and robust to the change of the fading environment.
Enhancing secrecy in fading wiretap channels with only transmitter-side channel state information

This work examines the advantages of having only channel state information at the transmitter (CSIT), and not at the receiver and the eavesdropper, when achieving secrecy in fading wiretap channels. The key idea is that, with only CSIT, the transmitter can pre-compensate for the amplitude and phase distortions on the main channel. This allows the receiver to decode coherently even without knowledge of the CSI, while leaving the eavesdropper confused by the unknown variations of its own channel. When the channel is reciprocal, this CSI assumption can be achieved in practice through reverse training, i.e., by having the receiver emit the training signal so that the transmitter can estimate the channel by itself. Two secrecy-enhancing transmission schemes are proposed to exploit the CSIT. The truncated channel inversion scheme is used when the receiver and the eavesdropper have no CSI available, and the truncated phase compensation scheme is adopted when they can practically measure the SNR. The achievable secrecy rates of these schemes are derived for both single-antenna and multi-antenna wireless fading scenarios. Numerical results show significant improvements in secrecy rate compared to the case with full CSI at all terminals.
Design of detection system against the denial of service attack in 3G1x system

A denial-of-service (DoS) attack which can waste wireless resources by using the destination address of IP packets is introduced. To prevent the attack more effectively, early detection, efficiency, and small overhead are suggested as requirements in a detection system. We use a second order Markov model to suggest a detection system against the attack in 3G1x system. The states in the model are representative of each user's transmission activities during a fixed interval. Parameters of the model in our simulation are obtained from a traffic model. Our proposed detection system detects the attack by comparing the parameters in the model with each user's parameters which are generated during their transmission activity. The proposed system is analyzed in terms of the requirements for the detection system by varying the interval. Finally, we conclude that there are tradeoffs between efficiency, overhead and early detection for the design of the detection system.
Joint synchronization and channel estimation in uplink OFDMA systems

We consider the uplink of an OFDMA system and address the problem of estimating the carrier frequency offset, timing error and channel response of each active user. In doing so we follow a maximum likelihood (ML) approach and assume that a training sequence is available. Unfortunately, joint ML estimation of all the above parameters involves a multi-dimensional grid-search that is difficult to implement in practical systems. Therefore we resort to the alternating-projection algorithm and replace the multidimensional search with a sequence of one-dimensional searches. Compared to other existing methods, the proposed estimator has more flexibility since it can be used with any subcarrier assignment scheme. Simulations indicate that the accuracy of the frequency estimates asymptotically achieve the relevant Cramer-Rao bound (CRB).
An efficient anonymous communication protocol for peer-to-peer applications over mobile ad-hoc networks

An efficient anonymous communication protocol, called MANET Anonymous Peer-to-peer Communication Protocol (MAPCP), for P2P applications over mobile ad-hoc networks (MANETs) is proposed in this work. MAPCP employs broadcasts with probabilistic-based flooding control to establish multiple anonymous paths between communication peers. It requires no hop-by-hop encrypt ion/decryption along anonymous paths and, hence, demands lower computational complexity and power consumption than those MANET anonymous routing protocols. Since MAPCP builds multiple paths to multiple peers within a single query phase without using an extra route discovery process, it is more efficient in P2P applications. Through analysis and extensive simulations, we demonstrate that MAPCP always maintains a higher degree of anonymity than a MANET anonymous single-path routing protocol in a hostile environment. Simulation results also show that MAPCP is resilient to passive attacks.
A new stochastic block matching algorithm (SBMA) for video coding based on modified 3-step search

Motion compensated predictive coding is one of the most efficient video coding methods. Full search gives the optimal performance in minimizing the sum of absolute difference (SAD) of pixel values within a block for residual images. We propose a new fast SBMA which exploits spatial and temporal correlations existing in the motion vector field. The new SBMA has a variable search window size and a shiftable search center. Within a given search window, we consider a new search procedure based on a modified 3-step search. Compared to full block matching, we achieve a speed up factor ranging from 70 to 150. As a trade off, we see a 1-12% increase in the error residuals, and the corresponding PSNR value degrades by 0.1-0.5 dB only.
Video-on-demand server system design with random early migration

A random early migration (REM) scheme is proposed to handle the request migration in a video-on-demand (VoD) server system. When a new request is dispatched to a media server, REM compares the current service load with thresholds and decides whether request migration is needed with a certain probability, which is a function of the service load. We also present an initial video copy allocation algorithm to increase the connectivity degree among video servers to achieve the static load balance. Simulation results demonstrate that REM can achieve an enhanced performance for the VOD system in terms of the service failure rate and the migration cost.
Efficient VLSI design for SIFT feature description

The scale invariant feature transform (SIFT) is a very efficient algorithm to extract and describe distinctive invariant features from images, and usually applied for many image applications such as object recognition, robotic mapping, and navigation. In the SIFT computation, the complexity of the feature description is quite high. Hence, it is desirable to have an efficient VLSI architecture to compute the feature descriptor quickly. We first investigate the performance analysis for SIFT and then employ the proper hardware circuit to implement the feature description process. Besides, the pipelining technique is adopted to increase the speed of our design. Synthesis results show that the proposed circuit contains 555,062 transistors by using the TSMC 0.13µm cell library. It works with a clock rate of 200 MHz and can support the throughput rate of about 65300 SIFT descriptors per second in real time.
Video skimming based on story units via general tempo analysis

A skimming system for movie content exploration is proposed using story units extracted via general tempo analysis of audio and visual data. Quite a few schemes have been proposed to segment video data into shots with low-level features, yet the grouping of shots into meaningful units, called story units here, is important and challenging. In this work, we detect similar shots using keyframes and include these similar shots as a node. Then, an importance measure is calculated based on the total length of each node. Finally, we select sinks and shots according to this measure. Based on these semantic shots, a meaningful skim can be successfully generated. Simulation results are presented to show that the proposed video skimming scheme can preserve the essential and significant content of the original video data
Bit allocation for spatial scalability in H.264/SVC

We propose a model-based spatial layer bit allocation algorithm for H.264/SVC in this work. The spatial scalability of H.264/SVC is achieved by a multi-layer approach, where an enhancement layer is bound by the dependency on its preceding layers. The inter-layer dependency is decoupled in our analysis by a careful examination of the signal flow in the H.264/SVC encoder. We show that the rate and the distortion (R-D) characteristics of a dependent layer can be represented by a number of independent functions with a group of pictures (GOP) as a basic coding unit. Finally, a low complexity spatial layer bit allocation scheme is developed using the proposed GOP-based R-D models. It is shown by experimental results that our proposed bit allocation algorithm can achieve the coding performance close to the optimal R-D performance of full search and is significantly improved from current reference software JSVM.
Motion Compensation Complexity Model for Decoder-Friendly H.264 System Design

An improved motion compensation decoding complexity model is proposed and its application to H.264/AVC decoding complexity reduction is examined in this work. This complexity model considers a rich set of inter prediction modes of H.264 as well as the relationship between motion vectors and frame sizes, which turn out to be highly related to the cache management efficiency. An H.264 encoder equipped with the complexity model can estimate the decoding complexity and choose the best inter prediction mode to meet the decoding complexity constraint of the target receiver platform. The performance of the proposed complexity model and its application to video decoding complexity reduction are demonstrated experimentally.
Box Refinement: Object Proposal Enhancement and Pruning

Object proposal generation has been an important preprocessing step for object detectors in general and the convolutional neural network (CNN) detectors in particular. Recently, people start to use the CNN to generate object proposals but most of these methods suffer from the localization bias problem, like other objectness-based methods. Since contours offer a powerful cue for accurate localization, we propose a box refinement method by searching for the optimal contour for each initial bounding box that minimizes the contour cost. Experiments on the PASCAL VOC2007 test dataset show that our box refinement method can significantly improve the object recall at a high overlapping threshold while maintaining a similar recall at a loose one. Given 1000 proposals, the average recall of multiple existing methods is increased by more than 5% with our box refinement process integrated.
Analysis of multistage linear successive interference cancellation in long-code CDMA systems using graphical representation

The bit error probability of the multistage linear successive interference canceller (LSIC) in a long-code code division multiple access (CDMA) system is analyzed with a graphic approach in this research. The receiver decision statistic is modelled as a Gaussian random variable, whose conditional mean and variance are related to the moments of functions of matrix L, where L is the strict lower triangular part of the correlation matrix of the signature sequences. The complexity of calculating these moments increases rapidly with the growth of the stage index. A graphical representation of moments is developed here to facilitate their computation. For the multistage linear parallel interference canceller (LPIC), we showed previously that its moment calculation can be decomposed into several well known problems in graph theory. Besides graphic tools developed by Hwang, Kim and Jay Kuo (see Proc.  2002) we introduce a new tool, i.e. the chromatic polynomial of a directed graph, to carry out the current task. It is shown that analytic results match well with simulation results in the bit error probability of the LSIC.
V-BLAST Receiver for MIMO Relay Networks with Imperfect CSI

Previous work demonstrated that the improvements in spectral efficiency and link reliability can be obtained in wireless relay networks employing terminals with MIMO capability. We propose to apply the non layered and layered ZF (V-BLAST) receiver to the relay and destination terminals in coherent MIMO relay networks under two-hop half-duplex relaying. Considering the channel estimation is often imperfect due to the noise and interference, this paper assumes that no perfect channel state information (CSI) is available for both backward and forward channels. The V-BLAST receiver is extended to the imperfect CSI under the assumption that the channel estimation errors are independent complex Gaussian random variables with zero mean and known second-order statistics. A robust symbol detection ordering criterion is proposed for applying ZF V-BLAST to the MIMO relay networks. This new ordering rule aims at providing, in each layer, the maximum average signal to interference- plus-noise ratio (SINR), over the random channel errors. Our simulations show that aided by the new ordering criterion, the suboptimal ZF operators, directly resulted from the imperfect CSI, is capable of alleviating the effect of CSI errors and improving the robustness of V-BLAST system.
Synthesis-based texture coding for video compression with side information

This paper presents a synthesis-based texture coding technique that uses low-quality video as side information to control the output texture for video compression. As compared with the current pure synthesis algorithm, the proposed algorithm is generic, in the sense that the behavior and quality of the output texture can be adjusted by the amount of the side information and determined by the user. We develop an area-adaptive side information assignment technique to improve coding efficiency. Additionally, we present a fast-searching algorithm to reduce computational complexity. Simulations demonstrate the performance of the proposed technique.