nils-herrmann/clean_scirepeval huggingface dataset:
Current state of the art, challenges and future directions for audio watermarking

Transparent data embedding algorithms embed binary streams in host multimedia signals. The embedded data is perceptually inaudible to maintain the quality of the source data. The embedded data can add features to the host multimedia signal or provide copyright protection. We review developments and requirements in transparent data embedding techniques for audio signals. We describe our latest audio embedding algorithm and include experimental results indicating robustness to low bit rate MPEG-Layer 3, AAC, and Dolby AC-3 coding. We conclude with a discussion of future research directions.
Ultra-low power multi-channel data conversion with a single SAR ADC for mobile sensing applications

Based on the recently emerging compressive sensing theory, the paper proposes an ultra-low power multichannel data conversion system whose architecture is almost as simple as a single SAR ADC. The proposed architecture is capable of simultaneously converting multi-channel sparse signals while running at the Nyquist rate of only one channel. A chip is fabricated in a 0.13μm CMOS process. Operating at 1MS/s, the SAR ADC itself achieves a 66dB SNDR and a 25fJ/step FoM at 0.8V. Using convex optimization methods, 4-channel 500kHz-bandwidth signals can be reconstructed with a 66dB peak SNDR and a 41% max occupancy, leading to an effective FoM per channel of 6.25 fJ/step.
Performance and complexity trade off in CDMA multiuser communications

In this paper, we describe a new tree-based CDMA receiver that can optimally trade complexity for detection performance. It yields the detector with the best detection performance for a given desired complexity level. Alternatively, it yields the lowest complexity receiver for any given desired detection performance. We describe a technique for designing receivers with linear complexity (including the optimal linear detector and decorrelator). We then explain how we can increase performance at the expense of a minimal increase in complexity. We show that as complexity increases to the level of that of the optimal receiver, our design approach automatically produces the optimal receiver. We also explain how our approach can be used with a minimum-mean-square-error design criterion and coded CDMA transmission. Finally, we illustrate with several examples the superiority of the receivers designed with our approach and discuss their advantages.
High efficient surgical simulation based on structured dictionary

This paper presents a method of real time 3D surgical simulation for deformable organs. It employs the technique of structured surface representation to decrease the description dimensionality, which allows for efficient deformation simulation by reducing the computational cost involved in the regular ODE solver. Majority of the deformation is estimated by surface reconstruction in the best-fit subspace. Experimental results are presented to demonstrate the feasibility of the method. The achieved accuracy is 2.3% ± 1.3% in terms of normalized Euclidean distance and 0.71 ± 0.30mm for Hausdorff distance. The maximum error is below 2mm. Therefore, the proposed method achieves accuracy close to that of the traditional simulation method.
Time robust movement direction decoding in Local Field Potentials using channel ranking

Movement direction for Brain Machine Interface (BMI) can be decoded successfully using Local Field Potentials (LFP) and Single Unit Activity (SUA). A major challenge when dealing with the intra-cortical recordings is to develop decoders that are robust in time. In this paper we present for the first time a technique that uses the qualitative information derived from multiple LFP channels rather than the absolute power of the recorded signals. In this novel method, we use a power based inter-channel ranking system to define the quality of a channel in multi-channel LFP. This representation enables us to bypass the problems associated with the dynamic ranges of absolute power. We also introduce a parameter based ranking system that provides the same rank to channels that have comparable powers. We show that using our algorithms, we can develop models that provide stable decoding of eight movement directions with an average efficiency of above 56% over a period of two weeks. Moreover, the decoding power using this method is 46% at the end of two weeks versus the 13% using the traditional approaches. We also applied these models to decoding movements performed in a force field and again achieved significantly higher decoding power than the existing methods.
Robust biclustering algorithm (ROBA) for DNA microarray data analysis

Recently, biclustering algorithms have been used to extract useful information from large sets of DNA microarray experimental data. They refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. The goal is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. Almost all of the methods proposed in the literature search for one or two types of bicluster among four. Also, most of the proposed methods rely on solving an optimization problem. Therefore, the method is dependant on the optimally criterion which most of the time, is likely to miss some significant biclusters. In this study, we develop a robust biclustering algorithm (ROBA) to address some of the issues mentioned above. Our algorithm is simple because it uses basic linear algebra and arithmetic tools and there is no need to solve and optimization problem. Our algorithm is robust because it can be used to search for any type of bicluster defined by the user in a timely manner and, it is also shown to be more efficient than the ones proposed in the literature
Convolutional codes for channels with substitutions, insertions, and deletions

We introduce modifications to common convolutional decoders to accommodate channels with Insertions and deletions. For the Viterbi decoder, new states are added to the trellis diagram to represent the new situation and the expansion algorithm is modified accordingly. For sequential decoding, we provide modifications to the stack algorithm and a new metric is introduced. Also, we developed a systematic way for convolutional code construction using Simulated Annealing so as to maximize the distance between codewords In the presence of insertions and deletions. The proposed techniques are shown to be superior to previous approaches for this problem, and have no additional code overhead.
Optimal transmission strategies for channel capture mitigation in Cognitive Radio Networks

Temporal Dynamic Spectrum Access (DSA) in Cognitive Radio Networks exploits time gaps between the primary users transmissions. In this work, the fundamental performance limit on the throughput of cognitive radio networks that coexist with a primary network that uses a Carrier Sensing Multiple Accesses (CSMA) medium access protocol is studied. Secondary transmission strategies that do not explicitly account for the CSMA protocol of the primary network usually lead to a channel capture. The problem cannot be addressed by monitoring interference or probability of collision. Here we formulate the optimal transmission strategy problem that avoids channel capture. We show the proposed strategy achieves a performance close to the optimal strategy that do not account for channel capture, while completely eliminates channel capture effect.
Robust wavelet domain array processing

A new iterative procedure for estimating the direction of arrival of plane waves in the presence of noise with an unknown correlation structure can also be used to separate line spectra from a wide class of smooth spectra. It exploits the differences between the correlation structures of the generalized wavelet coefficients of the noise and signal processes. For simplicity of exposition, the procedure is explained in the context of the problem of localizing narrowband signal sources located in the far-field of a uniformly spaced linear sensor array. It can be applied as well to non-linear or non-uniform arrays and wideband signals.<<ETX>>
Cognitive biases in Bayesian updating and optimal information sequencing

In this paper, we consider the problem of optimally ordering information to a human subject to maximize detection performance in a binary hypothesis testing problem. We begin by proposing a modification of the traditional Bayesian solution to hypothesis testing problems to incorporate the effect of human cognitive biases. Next, we consider the problem of selecting a subset of information to maximize detection performance in truncated hypothesis testing problems. We then use the solution to that problem to determine the real time ordering of information to enhance human binary hypothesis testing. We verify through simulations that the proposed ordering methods with and without cognitive biases minimize the probability of miss and the probability of false alarm.
Internal models and recursive estimation for 2-D isotropic random fields

Efficient recursive smoothing algorithms are developed for isotropic random fields that can be obtained by passing white noise through rational filters. The estimation problem is shown to be equivalent to a countably infinite set of 1-D separable two-point boundary value smoothing problems. The 1-D smoothing problems are solved using a Markovianization approach followed by a standard 1-D smoothing algorithm. The desired field estimate is then obtained as properly weighted sum of the 1-D smoothed estimates. The 1-D two-point boundary value problems are also shown to have the same asymptotic properties and yield a stable spectral factorization of the power spectrum of the isotropic random fields.
A resource management strategy in wireless multimedia communications-total power saving in mobile terminals with a guaranteed QoS

The integration of multimedia services into wireless communication networks is a major source of future technological advances. One of the main challenging issues in this endeavor is the resource optimization strategy. This paper addresses this issue from the perspective of minimizing the total power consumption of a mobile terminal while maintaining a guaranteed quality-of-service (QoS). For many years, the management strategy has dealt primarily with bandwidth allocation, network capacity, and QoS. However, due to the integration of multimedia services, the increasing energy consumption of a mobile unit is also becoming a dominant factor in the design of communication systems. In this paper, we describe two technologies that can make a wireless multimedia communication system more energy-efficient while ensuring QoS. These technologies consist of an energy-efficient communication protocol for the uplink channel and a low-complexity multirate transmission scheme. We also provide a video transmission example using the H.263 standard in the proposed system to demonstrate the importance of our total power optimization strategy. The simulation results show that a savings of 10-32% is achieved in the total energy consumption of the mobile unit.
Detecting Changes in DNA Copy Number: Reviewing signal processing techniques

Alterations in the number of DNA copies of portions of a genome are both a process that contributes to natural genetic diversity in healthy individuals and also a driving cause for cancer and other genetic diseases. Even though recent advances in microarray technology and high throughput sequencing now allow very high resolution scans for very large cohorts of samples, small alterations remain particularly difficult to detect, especially under severe noise degradation conditions. Thus, estimation of the DNA copy number remains a challenging problem. Some of the core challenges in copy number estimation can be seen as essentially signal processing problems, where it is necessary to exploit fundamentally different characteristics between the desired underlying biological signal and the measurement noise. Indeed, some of the most successful methods used to address this problem have been inspired by well-known signal processing techniques.
Efficient Cooperative Spectrum Sensing in Cognitive Radio

This paper presents a new cooperative spectrum sensing scheme, which allocates two separate short periods for sensing and cooperation to achieve high capability of detecting the Primary User (PU) with low interference. A mathematical model is built to derive a closed formulation of the detection probability of the CR users for guiding a real system design. Extensive simulations results demonstrate that the proposed method is superior to non-cooperative sensing and relay-based method  in terms of high sensing agility and less interference to the PU. Especially, comparing with , the proposed design increases the detection speed by 48% and reduces the interference to PU by 43%. This new sensing protocol owns the features of low complexity and independence of special hardware support, making it easy and flexible for real system implementation.
A network flow model for playlist generation

In This paper we introduce a system for constructing a constrained sequence of music pieces that satisfy users preferences. The proposal system has the ability to retrieve music excepts with predefined constraints. These constraints can be related to the nature of the melody, instruments specifications, singer gender, as well as the instruments specifications, singer gender, as well as the in between feature differences. The proposed solution to the music selection problem finds applications in online music distribution system which replace the physical CD which we do not have control on its contents. We adopt a joint network flow model and a vector space interpretation to find the optimal solution. The problem finally is transformed into a linear program which is solvable in a reasonable amount of time.
A novel high-capacity data-embedding system

In this paper, we present a novel data-embedding system with high embedding capacity. The embedding algorithm is based on the quantized projection embedding method with some enhancement to achieve high embedding rates. In particular, our system uses a random permutation of the columns of a Hadamard matrix as projection vectors and a fixed perceptual mask based on the JPEG default quantization table for the quantization step design. As a result, the data-embedding system achieves 1/167 (1 bit out of 167 raw image bits) to 1/84 hiding ratios with a BER of around 0.1% in the presence of JPEG compression attacks, while maintaining visual distortion at a minimum.
Proactive transmit opportunity detection in cognitive radio networks

The wide proliferation of wireless services and applications with increasing bandwidth needs is rapidly creating a spectrum shortage. However, the problem is caused primarily by inefficient legacy spectrum allocation and utilization policies, so that even when some applications suffer from lack of bandwidth, there is idle capacity in the band they are using or other bands. The FCC, ITU and other regulatory organizations have adopted, or are exploring, alternative spectrum usage policies and regulations to address the issue. The new policies and regulations support an open spectrum policy implemented by cognitive radios and overlay transmissions implemented via ultrawideband technology and/or cognitive radios. This talk describes a revolutionary approach for addressing spectrum scarcity and unlocking hidden communication capacity thereby increasing the reach and utility of wireless connectivity. The non-traditional communication technique studied in this research effort detects transmission opportunities that occur when incumbent primary users enjoy signal to noise ratio values that are higher than the minimum value required to maintain their quality of service. It then judicially exploits these opportunities while preserving the current quality of service of the primary users.
A multigrid approach to object support estimation from diffraction-limited images

A procedure for object support estimation from diffraction-limited images is developed under the assumptions that the (not necessarily spatially invariant) point spread function of the imaging system and the object location are known. The problem is formulated as a generalized hypothesis-testing problem with unequal a priori probabilities. The a priori probabilities are determined in such a way as to minimize the probability of incorrectly identifying the object support. This formulation leads to a sequence of statistical hypothesis tests which involve projections of the observed noisy image on the null spaces of certain matrices derived from the point spread function of the imaging system. The projections are computed using a multigrid iterative scheme. The statistical tests are done in an optimal order to minimize the total number of tests that have to be performed
A single SAR ADC converting multi-channel sparse signals

This paper presents a simple but high performance architecture for multi-channel analog-to-digital conversion. Based on compressive sensing, only one SAR ADC is needed to convert multi-channel sparse inputs, leading to significant analog power saving and hardware saving. Moreover, it helps avoid problems occurring in conventional multi-channel ADCs such as timing skew, offset mismatch, and gain mismatch. A 12-bit SAR ADC converting 4-channel sparse signals simultaneously is designed in 130nm CMOS process. The design reaches a SNDR of 66.3dB and consumes an average power of 58μW at the sampling frequency of 1MHz. The L1 minimization method is chosen to reconstruct the input signals. The single-tone and multi-tone inputs can be reconstructed with a minimum precision of 68dB and 55dB THD, respectively.
Heuristic Reusable Dynamic Programming: Efficient Updates of Local Sequence Alignment

Recomputation of the previously evaluated similarity results between biological sequences becomes inevitable when researchers realize errors in their sequenced data or when the researchers have to compare nearly similar sequences, e.g., in a family of proteins. We present an efficient scheme for updating local sequence alignments with an affine gap model. In principle, using the previous matching result between two amino acid sequences, we perform a forward-backward alignment to generate heuristic searching bands which are bounded by a set of suboptimal paths. Given a correctly updated sequence, we initially predict a new score of the alignment path for each contour to select the best candidates among them. Then, we run the Smith-Waterman algorithm in this confined space. Furthermore, our heuristic alignment for an updated sequence shows that it can be further accelerated by using reusable dynamic programming (rDP), our prior work. In this study, we successfully validate "relative node tolerance bound” (RNTB) in the pruned searching space. Furthermore, we improve the computational performance by quantifying the successful RNTB tolerance probability and switch to rDP on perturbation-resilient columns only. In our searching space derived by a threshold value of 90 percent of the optimal alignment score, we find that 98.3 percent of contours contain correctly updated paths. We also find that our method consumes only 25.36 percent of the runtime cost of sparse dynamic programming (sDP) method, and to only 2.55 percent of that of a normal dynamic programming with the Smith-Waterman algorithm.
Opportunistic Scheduling in Decentralized OFDM Systems

Orthogonal frequency division multiplexing (OFDM) is emerging as a key modulation scheme for future high speed packets based wireless transmission systems. In a wireless multiuser network system, when an opportunistic scheduling is employed in the OFDM system with adaptive modulation, it may encounter implementation problems due to the need for a large amount of channel information. In this paper we propose a decentralized scheduling scheme to exploit multiuser diversity (MUDiv) in OFDM systems. Users access the channel using a simple variation of the ALOHA random access protocol, termed channel-aware/collision-limited ALOHA. Based on the channel quality, users randomly transmit a request packet with a probability p. When a collision occurs, collided users will retransmit a request packet with probability p. We present an analytical analysis of the average system throughput (average spectral efficiency). We compare our proposed scheduling scheme with the proposed scheduling scheme , the optimal selective diversity scheduling scheme (centralized scheduling), and the round-robin scheduling scheme.
Ranging in multi-band communication systems

We present a new scheme to refine the range and time resolution of multi-band communication systems. The resolution of range or delay estimation in any communication system is inversely proportional to the bandwidth of the transmitted signal. In a multi-band system where only a portion of the total bandwidth is available to any transmission, the resolution appears to be proportional to the inverse of the bandwidth of a sub-band. In this paper we describe a scheme that coherently processes received signals from different sub-bands to achieve a resolution proportional to the inverse of the total system bandwidth. We show that in the high signal to noise ratio regime this scheme outperforms conventional schemes, such as averaging the estimates from different sub-bands to reduce the effect of noise. In particular, we show that the resolution we achieve is inversely proportional to the number of sub-bands while that of traditional schemes is inversely proportional to the square root of the number of sub-bands. We provide simulation results to show the performance of the scheme in additive white Gaussian noise. We also study the effect of oscillator phase mismatches that occur when switching from one sub-band to another.
An improved error control paradigm for multimedia transmission over wireless networks

Providing quality-of-service (QoS) guarantees over wireless packet networks requires a thorough understanding and quantification of the interactions among the traffic source, the wireless channel characteristics, the underlying link-layer error control mechanisms, and the various packet dropping policies adopted by the upper network layers. We explore the idea of cooperation among some of these different aspects to assist the packet level error recovery. First, we revise UDP to tolerate a certain amount of channel error and to allow the delivery of partially corrupted packets. Secondly, we propose a novel technique to resolve the problem of missed bits without the need to identify their exact locations. It is based on modifying the stack algorithm for convolutional decoding. Simulation results establish the effectiveness of the proposed approach for detecting and correcting missed bits, which have direct impact on packet loss and on the overall system performance.
Synthesis/coding of audio signals using optimized wavelets

A novel audio synthesis/coding approach based on an optimization of the wavelet transform of the audio signal is presented. In each frame of the audio signal, the authors identify the wavelet which yields an approximation to the audio segment that requires the minimum number of bits. The wavelet approximation is constrained to have no perceptual distortion or a distortion that is less than some fixed maximum level. Two wavelet coefficient representations are considered. In the first representation, the quantization step is fixed and the magnitude of the transform coefficients is optimized. In the second approach the wavelet coefficients are adaptively quantized. The authors show that the second representation leads to simpler optimization problems. They suggest several approximations which reduce the complexity of the optimization problem. Experiments indicate that high quality speech and audio reconstruction is possible in the range of 8-9 kb/s.<<ETX>>