nils-herrmann/clean_scirepeval huggingface dataset:
Enhanced multiple Huffman table (MHT) encryption scheme using key hopping

Efficient multimedia encryption algorithms play a key role in multimedia security protection. One algorithm known as the MHT (multiple Huffman tables) method was recently developed by Wu and Kuo (2001; 2000). Although MHT has many desirable advantages, it is vulnerable under the chosen-plaintext attack (CPA). In this work, an enhanced MHT encryption scheme is proposed to remedy this drawback using the idea of key hopping. It is demonstrated by mathematical analysis that our proposed scheme is secure against chosen plaintext attack.
A wavelet approach to compressed image quality measurement

The understanding and characterization of various forms of image degradation due to compression is important. The most commonly used image distortion measure is the mean squared error (MSE). However the MSE value does not provide a good subjective performance measure, since it does not take human perception into account. We present a wavelet approach to measure the visual quality of compressed images based on a psycho-visual human vision model. Wavelet filter banks are shown to have a good space frequency localization property and can be directly linked to the Michelson contrast and compactly supported features. Experimental results are provided to demonstrate the effectiveness of the Haar wavelet.
Image compression with fully-decomposed wavelet transform

The authors propose a novel transform which recursively applies the two-scale wavelet decomposition to all subimages. It is called the full wavelet transform (FWT). The authors use the FWT to transform an image into blocks of the same size, and show that these blocks have strong space-frequency correlation which can be effectively utilized to achieve high image compression ratio while preserving good image quality. The proposed method can be related to several other popular image compression schemes such as the DCT (discrete cosine transform), PWT (pyramidal wavelength transform), and SCB (subband coding) methods.<<ETX>>
Underdetermined audio source separation from anechoic mixtures with long time delay

We propose a technique to separate audio sources from their anechoic mixtures with long delay in an underdetermined setting (i.e., the number of audio sensors is smaller than that of sources). It consists of two stages: 1) to estimate anechoic mixing parameters of attenuation and arrival delay and 2) to recover original audio sources based on estimated mixing parameters. When delay is longer than one sample, previous algorithms perform poorly. To address this shortcoming, we estimate the maximum delay and use it to find a proper frequency range that produces no phase ambiguity. Then, we determine mixing parameters with time-frequency points in this range. Finally, mathematical tools are used to solve the underdetermined linear system to recover original audio sources. The effectiveness of the proposed technique on various mixing scenarios with noisy observation of mixtures and different types of sounds is demonstrated by experimental results.
Visual-saliency-enhanced image quality assessment indices

Modern image quality assessment (IQA) indices, e.g. SSIM and FSIM, are proved to be effective for some image distortion types. However, they do not exploit the characteristics of the human visual system (HVS) explicitly. In this work, we investigate a method to incorporate the human visual saliency (VS) model in these full-reference indices, and call the resulting indices SSIMVS and FSIMVS, respectively. First, we decompose an image into non-overlapping patches, calculate visual saliency, and assign a parameter ranging from 0 and 1 to each patch. Then, the local SSIM or FSIM values of the patches are weighed by the said parameter. Finally, the weighed similarity of all patches are integrated into one single index for the whole image. Experimental results are given to demonstrate the improved performance of the proposed VS-enhanced indices.
A semi-supervised learning approach to online audio background detection

We present a framework for audio background modeling of complex and unstructured audio environments. The determination of background audio is important for understanding and predicting the ambient context surrounding an agent, both human and machine. Our method extends the online adaptive Gaussian Mixture model technique to model variations in the background audio. We propose a method for learning the initial background model using a semi-supervised learning approach. This information is then integrated into the online background determination process, providing us with a more complete background model. We show that we can utilize both labeled and unlabeled data to improve audio classification performance. By incorporating prediction models in the determination process, we can improve the background detection performance even further. Experimental results on real data sets demonstrate the effectiveness of our proposed method.
Feature-Based Intra-/InterCoding Mode Selection for H.264/AVC

A fast feature-based intra/inter coding mode selection scheme for the H.264/AVC video coding standard is proposed in this paper. First, three features are extracted from a macroblock to form a feature space. Then, the feature space is partitioned into three regions, i.e., risk-free, risk-tolerable, and risk-intolerable regions, where the risk is calculated using the rate-distortion (RD) performance loss due to wrong mode decision as well as the probability distribution of inter/intra modes in the feature space obtained from an off-line training process. Depending on the region where the feature vector of a macroblock is located, we can apply mechanisms of different complexity for final mode decision. To calculate the likelihood function of the risk, both parametric and nonparametric density estimation schemes are developed to offer different rate-distortion-complexity tradeoffs. It is demonstrated by experimental results that the proposed algorithm can save approximately 20%-32% of the total encoding time of H.264 (JM7.3a) with little degradation in the rate-distortion performance
Precoded Multiuser OFDM Transceiver in Timing Asynchronous Environment

The performance of a multiuser orthogonal frequency-division multiplexing (OFDM) transceiver, called the precoded multiuser OFDM (PMU-OFDM), with time asynchronous access is investigated in this paper. It is shown that multiaccess interference (MAI) due to time asynchronism is asymptotically zero as the number of parallel input symbols N becomes large in the PMU-OFDM system. Then, we show that PMU-OFDM with even or odd Hadamard-Walsh codewords can significantly suppress the MAI effect due to time asynchronism. For the half-loaded case, no sophisticated signal processing technique is needed by PMU-OFDM for MAI suppression. For the fully loaded situation, PMU-OFDM demands less complexity than does conventional OFDMA for interference suppression since PMU-OFDM deals with only one half of interferers.
H.264/SVC Mode Decision Based on Optimal Stopping Theory

Fast mode decision algorithms have been widely used in the video encoder implementation to reduce encoding complexity yet without much sacrifice in the coding performance. Optimal stopping theory, which addresses early termination for a generic class of decision problems, is adopted in this paper to achieve fast mode decision for the H.264/Scalable Video Coding standard. A constrained model is developed with optimal stopping, and the solutions to this model are employed to initialize the candidate mode list and predict the early termination. Comprehensive simulation results are conducted to demonstrate that the proposed method strikes a good balance between low encoding complexity and high coding efficiency.
Quantification of self-diffusion process in brain white matter tracts via numerical PDE simulation

Diffusion MRI (DMRI) signal is characterized by the self-diffusion propagation profile within the brain white matters. Despite previous efforts on quantification of this physical phenomenon in the literature, most existing methods suffer from a number of constraints which severely limit the extent of their practical applicability. In this work, we relax these limitations to a large degree by addressing the solution of the self-diffusion process in its most general partial differential equation (PDE) form. Specifically, we develop an approach based on the finite element method (FEM) to obtain numerical self-diffusion solution in multi-compartments models of the white matters. Besides, due to sensitivity of the DMRI signal to the average self-diffusion process, we provide a formulation for this process of a voxel in terms of microstructure parameters of white matters. Several simulation results based on the proposed FEM method are given to demonstrate its flexibility and accuracy.
Advanced colluder detection techniques for OSIFT-based hiding codes

In this work, we examine a family of anti-collusion codes using the principle of "orthogonal spreading followed by the inverse Fourier transform (OSIFT)" as introduced in (B.-H. Cha and C.-C. Jay Juo, 2007). The Hadamard-Walsh (HW) codes were adopted as the orthogonal spreading codes in (B.-H. Cha and C.-C. Jay Juo, 2007). Here, we introduce another type of orthogonal spreading codes; namely, the carrier interferometry (CI) codes, which are comparable to HW codes. To detect OSIFT hiding codes against weighted collusion attacks, we propose advanced detectors that can identify a large number of colluders with weighted collusion attacks. The proposed detection schemes include the maximal ratio combining (MRC) scheme for colluder detection in the same group and the multiuser detection (MUD) scheme for colluder detection in different groups. It is demonstrated that HW- and Cl-based OSIFT codes have robust performance with advanced detection schemes against weighted collusion attacks compared with conventional matched filter (MF) in an exemplary audio watermarking system.
Performance study on block-based image steganalysis

Block-based image steganalysis, which uses smaller homogenous blocks from a given test image, was previously proposed to improve the steganalysis performance. Performance study on block-based image steganalysis in terms of block sizes and block numbers is conducted in this research. First, we analyze the dependence of the steganalysis performance on one of these two factors, and show that a larger block size and a larger block number will lead to better steganalysis performance. Our study is verified by experimental results. For a given test image, there exists a trade-off between the block size and the block number, and it is shown that a balance between the block size and the block number can result in better steganalysis performance.
A multiscale error diffusion technique for digital halftoning

A new digital halftoning technique based on multiscale error diffusion is examined. We use an image quadtree to represent the difference image between the input gray-level image and the output halftone image. In iterative algorithm is developed that searches the brightest region of a given image via "maximum intensity guidance" for assigning dots and diffuses the quantization error noncausally at each iteration. To measure the quality of halftone images, we adopt a new criterion based on hierarchical intensity distribution. The proposed method provides very good results both visually and in terms of the hierarchical intensity quality measure.
Relay-Assisted Decorrelating Multiuser Detector (RAD-MUD) for Cooperative CDMA Networks

In this paper, we examine the uplink of a cooperative CDMA network, where users cooperate by relaying each other's messages to the base station. When spreading waveforms are not orthogonal, multiple access interference (MAI) exists at the relays and the destination, causing cooperative diversity gains to diminish. To address this issue, we adopt the multiuser detection (MUD) technique to mitigate MAI in achieving the full advantages of cooperation. Specifically, the relay-assisted decorrelating multiuser detector (RAD-MUD) is proposed to separate interfering signals at the destination with the help of preceding at the relays along with pre-whitening at the destination. Unlike the conventional zero-forcing (ZF) precoder or the decorrelating MUD, the proposed RAD-MUD experiences neither power expansion at the relays nor noise amplification at the destination. Three cooperative transmission strategies are considered on top of RAD-MUD; namely, transmit beamforming, selective relaying and distributed space-time coding. Since the reliability of each source-relay and/or relay-destination links are different, relay transmissions are weighted accordingly in our schemes to further combat MAI. The advantages of RAD-MUD over ZF precoding and other existing cooperative MUD schemes are shown through computer simulations.
SPCp1-11: Optimal Codeword Design for Precoded UWB (PUWB) Systems

A preceding technique applied to symbols transmitted in an ultra-wideband (UWB) system was proposed, which can concentrate the signal power at the receiver to facilitate data detection. The design of the optimal codeword for preceding is investigated in this work. After the problem is formulated, we examine its solution in the full-rank space as well as the reduced-rank subspace to get different tradeoff between detection performance and the amount of feedback messages. Furthermore, we propose two subspace selection schemes that are suitable for different channel conditions. The codeword obtained from this work improves the performance of the result significantly at the price of a larger amount of feedback messages.
Delay and DOA estimation for chip-asynchronous DS-CDMA systems using reduced rank space-time processing

A reduced-rank space-time processing algorithm is proposed in this work to estimate the time-delay and the direction-of-arrival (DOA) in short-code chip-asynchronous DS-CDMA systems. Most algorithms proposed before demand the inversion of the received signal correlation matrix, which has a high computational cost. Here, we attempt to reduce the complexity by decomposing the correlation matrix inversion step into the cascade of multiple stages, where each stage outputs a scalar value that is obtained without an explicit matrix inversion operation. Furthermore, it is proved that the interference signals can be suppressed effectively using a small number of stages, and the performance is not much improved by applying more stages. Computer simulations are conducted to compare the performance of the reduced rank and the full rank approaches.
Texture classification with tree-structured wavelet transform

Proposes a multiresolution approach based on a tree-structured wavelet transform for texture classification. The development of tree-structured wavelet transform is motivated by the observation that textures are quasi-periodic signals whose dominant frequencies are located in the middle frequency channels. With the transform, one is able to zoom into desired frequency channels and performs further decomposition. In contrast, the conventional wavelet transform only decomposes subsignals in low frequency channels. A progressive texture classification algorithm which is not only computationally attractive but also has excellent performance is developed.<<ETX>>
Enhanced performance for an approximately MAI-free multiaccess OFDM transceiver by code selection

A new code selection scheme is proposed to reduce the MAI of the approximately MAI-free OFDM transceiver that is known as repetitively coded multicarrier CDMA (RCMC-CDMA). If we use M/2 symmetric codewords or anti-symmetric codewords of the M Hadamard-Walsh codes, then the MAI of the system can be greatly reduced. With this code selection scheme, the requirement of a sufficiently large number of subchannels to achieve the MAI-free property can be relaxed so that the approximately MAI-free property still holds when the number of subchannels is relatively small.
A statistical approach to humming recognition

A statistical pattern recognition approach applied to human humming data is examined in this research. Query by humming provides a natural means for content-based retrieval from music databases. The proposed system aims at providing a robust front-end for such an application. The segment of a note in the humming waveform is modeled by a hidden Markov model (HMM) while data features such as pitch measures are modeled by a Gaussian mixture model (GMM). Preliminary real-time recognition experiments are carried out based on humming data obtained from eight users and an overall correct recognition rate of around 80% is demonstrated.
Fast and adaptive semantic object extraction from video

A smart interactive video object generation (SIVOG) system based on adaptive processing and semantic user interaction was developed in our previous work (1999). SIVOG is further improved to efficiently process video content based on semantic object's spatial and temporal characteristics in this work. The enhanced SIVOG system adaptively selects processing regions based on the object shape. Temporal skipping and interpolation procedures are applied to objects that have a slow motion activity. This system extracts simple semantic objects in real time with pixel-wise accuracy.
Sparse Representation of Musical Signals Using Source-Specific Dictionaries

The sparse representation of music sounds that consist of a single note at a time was examined in. Here, we extend the results to a more generic setting where music sounds may contain multiple notes (or chords) at the same time. The basic idea is to determine a set of elementary functions, called source-specific atoms, that efficiently capture music signal characteristics. We first decompose basic components of musical signals (i.e,, musical notes) into a set of Gabor atoms. Then, these Gabor atoms are prioritized according to their approximation capability to music signals of interest, and the prioritized Gabor atoms are used to synthesize source-specific atoms. To find a sparse representation for musical chords, we generate new atoms by regrouping source-specific atoms. This technique is applied to the approximation of real piano recordings, and its effectiveness in terms of good approximation capability and low computational complexity is demonstrated by experiments.
Texture Roughness Analysis and Synthesis via Extended Self-Similar (ESS) Model

The 2D fractional Brownian motion (FBM) model provides a useful tool to model textured surfaces whose roughness is scale-invariant. To represent textures whose roughness is scale-dependent, we generalize the FBM model to the extended self-similar (ESS) model in this research. We present an estimation algorithm to extract the model parameters from real texture data. Furthermore, a new incremental Fourier synthesis algorithm is proposed to generate the 2D realizations of the ESS model. Finally, the estimation and rendering methods are combined to synthesize real textured surfaces.
TCP-friendly assured forwarding (AF) video service in DiffServ networks

TCP-friendly assured forwarding (AF) video service provisioning in DiffServ (differentiated service) networks is investigated in this research. TCP and TFRC are the two main transport protocols adopted to realize the AF service, where traditional alphanumeric data are transmitted via AF-TCP for reliable delivery and multimedia applications are transmitted via AF-TFRC for smooth delivery. The quality of services (QoS) is simplified to contain only two levels of bandwidth consumption, i.e. the AF and BE classes. They are realized by the RIO queue in edge and core elements. We analyze the service assurance of AF-TCP and AF-TFRC services mathematically, and verify derived theoretical results with numerical simulation.
On the security of a secure Lempel-Ziv-Welch (LZW) algorithm

This paper re-evaluates the security of a secure Lempel-Ziv-Welch (LZW) algorithm proposed at ICME'2008. A chosen-plaintext attack is proposed to break all ciphertext indices corresponding to single-symbol dictionary entries. For short plaintexts the chosen-plaintext attack works well because string-symbol strings appear very frequently. The number of required chosen plaintexts is at the order of the alphabet size. The complexity of the chosen-plaintext attack is O(ML), where M is the number of chosen plaintexts and L is the size of the ciphertext. The chosen-plaintext attack can also be generalized to chosen-ciphertext attack. In addition to the security problem, we point out that the secure LZW algorithm has a lower compression efficiency compared with the original LZW algorithm. Finally we propose several enhancements to the secure LZW algorithm under study.
Dynamic throughput estimation for wireless multimedia transmission

Dynamic throughput estimation for wireless multimedia transmission is examined in this research. A novel dynamic mapping scheme from measurements of a real-world wireless environment to a discrete Markov model is first proposed. Then, the available throughput is estimated by using the derived discrete Markov model together with the number of negative acknowledgements (NACK) that are fed back from the receiver to the transmitter. The performance of the mapping scheme and throughput estimation is demonstrated via simulation based on a microcellular wireless environment.
Iterative Joint Channel Estimation and Multiuser Detection for DS-CDMA in Frequency-Selective Fading Channels

An iterative joint channel estimation, symbol detection, phase recovery and interference cancellation structure is proposed for asynchronous code-division multiple-access systems over frequency-selective fading channels. Based on the expectation maximization (EM) algorithm, a recursive channel estimator is developed for blind channel tracking, using a novel stochastic signal processing technique. To perform symbol detection given the phase ambiguities of the resultant EM channel estimates, a noncoherent scheme is developed to compute the a posteriori probabilities (APPs) of data symbols. Moreover, by incorporating the APPs into the proposed recursive channel estimator, phase ambiguity due to the EM channel estimation can be resolved, which enables soft multiple access interference cancellation for multiuser detection. Based on these new signal processing schemes, an iterative structure is proposed for joint channel estimation and multiuser detection over fast fading channels.
Node aging effect on connectivity of data gathering trees in sensor networks

Sensor nodes age over time due to device failure and/or battery energy depletion. Node survival rates affect data communication, sensing coverage, and, especially, the connectivity of data gathering trees that provide a forwarding path from each source to the sink and enable data aggregation. The node aging effect on the connectivity of a data gathering tree over time is analyzed. First, we discuss the general node aging problem by considering the device failure rate and the energy consumption rate. In the analysis of the energy consumption rate, we examine the effect of the data aggregation degree and the hop distance on the amount of data communication handled by a node of a data gathering tree. Then, we present the survival function and the connectivity probability per hop distance in a data gathering tree. Finally, the resulting non-uniform connectivity over time in a data gathering tree is examined with the comparison between the device failure effect and the energy depletion effect through extensive simulation. It is shown by mathematical analysis, as well as simulation, that the node aging process has a significant impact on connectivity as the hop distance increases.