nils-herrmann/clean_scirepeval huggingface dataset:
Predominant pitch contour extraction from audio signals

This paper describes a computationally efficient method for estimating the predominant pitch in audio recordings. The proposed method is intended for building a content-based indexing and retrieval system that can search in a audio database using the melody line of a complex input audio sample. Available pitch estimation methods are effective primarily when dealing with recordings of human voice that is either unaccompanied or accompanied with one or two musical instruments. These methods perform poorly when applied to pitch estimation in complex music signals due to their reliance on directly estimating the fundamental frequency (F/sub 0/), a task that is affected by the overlapping presence in frequency of instrumental sounds such as those of guitar, piano, etc. In our method we exploit the higher harmonic structure of the human voice to develop a low-complexity system for estimating predominant pitch. Experimental results show that this computationally efficient method provides a robust estimate of predominant pitch in real-world audio signals with 85% success rate.
Role of Solar Phenomena in Large-Scale Terrestrial Meteorology

The impact of climate on humans is visible from severe distortions like wider scale of floods, ever powerful storms, more frequent droughts, contagious poverty, growing articulation of poverty alleviation, and the like. Astrophysical 'folklore'' has it that the terrestrial environment is determined by extra-terrestrial influences, largely by solar activity. In fact, however, the posited correlations between solar and terrestrial phenomena require that their scientific bases be improved, particularly from the standpoint of long-term forecasts. In this work, we introduced global fractal analysis to look into the problem. Further, this communication introduces a local analysis to study the dynamic behaviour of climatic phenomena, especially in relation to the solar activity influences on our ocean-atmosphere complex. Albeit further work needs to be undertaken for enhancing the reliability of future forecasts, our analysis shows the existence of a satisfactory correlation between the dynamical behaviour of the primally important atmospheric parameters of temperature and rainfall and of solarspots. These findings can find applications in fisheries industry, coastal and offshore studies, flood estimation and mitigation studies, oceanography, etc. "The influence of this eminent body on the globe we inhabit is so great and is so widely diffused that it becomes almost a duty to study the operations which are carried on upon the solar surfaceldrldrldr".
Distortion exponent for multiple description coding

Distortion exponent has been proposed as performance measure to characterize how fast the average distortion decays to zero when the SNR increases to infinity. The distortion exponent for Multiple Description Coding (MDC) has only been investigated for two descriptions and symmetric SNR. In this paper, we consider the case of any number of descriptions and asymmetric SNR. We derive an achievable distortion exponent for MDC with N ≥3 description and an upper bound for the distortion exponent for N =3. Our results are based on an high-SNR approximation which we named noise cancellation method. We also consider a special case of our noise cancellation approximation method which we refer to as equal correlation. For each method, the distortion exponent is obtained as the solution of a linear program. Numerical results verify the validity of our approximation method.
Network coding for cooperative mobile devices with multiple interfaces

Cooperation among mobile devices and utilizing multiple interfaces such as cellular and local area links simultaneously are promising to meet the increasing throughput demand over cellular links. In particular, when mobile devices are in the close proximity of each other and are interested in the same content, device-to-device connections such as WiFi-Direct, in addition to cellular links, can be utilized to construct a cooperative system. However, it is crucial to understand the potential of network coding for cooperating mobile devices with multiple interfaces. In this paper, we consider this problem, and (i) develop network coding schemes for cooperative mobile devices with multiple interfaces, and (ii) characterize the performance of network coding by using the number of transmissions to recover all packets as a performance metric.
Improved Image-Based Localization Using SFM and Modified Coordinate System Transfer

Accurate localization of mobile devices based on camera-acquired visual media information usually requires a search over a very large GPS-referenced image database collected from social sharing websites like Flickr or services such as Google Street View. This paper proposes a new method for reliable estimation of the actual query camera location by optimally utilizing structure from motion (SFM) for three-dimensional (3-D) camera position reconstruction, and introducing a new approach for applying a linear transformation between two different 3-D Cartesian coordinate systems. Since the success of SFM hinges on effectively selecting among the multiple retrieved images, we propose an optimization framework to do this using the criterion of the highest intraclass similarity among images returned from retrieval pipeline to increase SFM convergence rate. The selected images along with the query are then used to reconstruct a 3-D scene and find the relative camera positions by employing SFM. In the last processing step, an effective camera coordinate transformation algorithm is introduced to estimate the query's geo-tag. The influence of the number of images involved in SFM on the ultimate position error is investigated by examining the use of three and four dataset images with different solution for calculating the query world coordinates. We have evaluated our proposed method on query images with known accurate ground truth. Experimental results are presented to demonstrate that our method outperforms other reported methods in terms of average error.
Frame-based approach for peak-to-average power ratio reduction in OFDM

A new method for reducing the peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing is proposed. The new method, called erasure pattern selection (EPS), is based on the use of frame expansion for adding redundancy to the data. Part of the redundancy is removed by examining several patterns for erasing subcarriers and selecting the pattern that produces the lowest PAPR for transmission. The residual redundancy in the data is exploited at the receiver to aid both the reconstruction of the erased data and correction of errors. The implementation is aided with the incorporation of a projection-onto-convex-sets (POCS) method in EPS in order to select and assign the best values to the unused subcarriers and further reduce the PAPR. Complexity analysis and simulation results show that the POCS-based EPS method outperforms existing probabilistic methods, while requiring lower overall complexity
Content-Aware Network Coding Over Device-to-Device Networks

Consider a scenario in which a source broadcasts a common content to a group of cooperating mobile devices that are within proximity of each other. Devices in this group may receive only partial content from the source due to packet losses over wireless broadcast links and these packet losses may differ for different devices. The remaining content missing at each device can then be recovered, thanks to cooperation among the devices by exploiting device-to-device (D2D) connections. In this context, the minimum amount of time that guarantees a complete acquisition of the common content at every device is referred to as the “completion time”. It has been shown that instantly decodable network coding (IDNC) reduces the completion time as compared with no network coding in this scenario. However, for applications such as video streaming, not all packets have the same importance and not all devices are interested in the same quality of content. This problem becomes more interesting and challenging when additional, but realistic constraints, such as strict deadline, bandwidth, or limited energy are added in the problem formulation. We assert that direct application of IDNC in such a scenario yields poor performance in terms of content quality and completion time. In this paper, we propose a novel Content- and Loss-Aware IDNC scheme that improves content quality and network coding opportunities jointly by taking into account the contribution of each packet to the desired quality of service (QoS) as well as the channel losses over D2D links. Our proposed Content- and Loss-Aware IDNC (i) maximizes the quality under the completion time constraint, and (ii) minimizes the completion time under the quality constraint. We demonstrate the benefits of Content- and Loss-Aware IDNC through simulations.
Compression of prosody for speech modification in synthesis

Methods of compressing the prosodic information about a speaker's delivery-pitch, duration, and amplitude - are described. The objective is to use available or extracted knowledge of the spoken text along with the prosodic information to synthesize speech from a suitable inventory of stored basic units. Techniques for compressing pitch and amplitude of speech units using transform coding are investigated. Discrete cosine and sine transforms are found to be effective in compressing pitch and amplitude information respectively. In order to generate speech with these coded pitch and amplitude contours, the prosodic features of speech units stored in an inventory are modified using a method that was proposed to perform speech modification for concatenative synthesis. In this method, the stored speech unit is processed with a suitably shaped time-varying prefilter, whose parameters are chosen to have a low sensitivity to pitch changes. The filtered signal is modified according to the required change in its prosodic structure, and then applied to the inverse of the prefilter. Examples of application of the proposed representation and modification of prosody to a variety of speech units are presented.
Pitch modification of speech using a low-sensitivity inverse filter approach

A simple and effective method for modifying the pitch of recorded speech units is described. This method was developed to overcome some limitations in the promising residual-excited linear prediction (RELP) technique. The key difference is that the choice of filter parameters in the new method is driven by a need for reducing sensitivity to pitch modification, rather than creating a residual with minimum energy as in RELP. Speech modifications using this method are superior in quality to those obtained with RELP, while at the same time being less sensitive than RELP to errors in pitch marking.
Predictive Modeling for Comfortable Death Outcome Using Electronic Health Records

Electronic health record (EHR) systems are used in healthcare industry to observe the progress of patients. With fast growth of the data, EHR data analysis has become a big data problem. Most EHRs are sparse and multi-dimensional datasets and mining them is a challenging task due to a number of reasons. In this paper, we have used a nursing EHR system to build predictive models to determine what factors impact death anxiety, a significant problem for the dying patients. Different existing modeling techniques have been used to develop coarse-grained as well as fine-grained models to predict patient outcomes. The coarse-grained models help in predicting the outcome at the end of each hospitalization, whereas fine-grained models help in predicting the outcome at the end of each shift, therefore providing a trajectory of predicted outcomes. Based on different modeling techniques, our results show significantly accurate predictions, due to relatively noise-free data. These models can help in determining effective treatments, lowering healthcare costs, and improving the quality of end-of-life (EOL) care.
Real-time low-complexity adaptive approach for enhanced QoS and error resilience in MPEG-2 video transport over RTP networks

In this paper, the problems of redundancy allocation for providing effective error-resilience and service class distribution for enhanced quality of service (QoS) in real-time MPEG-2 video transport are addressed. A real-time low-complexity content-based adaptive error-resilient approach is proposed for the transport of MPEG-2 video streams, encapsulated using real-time transport protocol (RTP) and delivered over heterogeneous networks. An algorithm is derived using spatial and temporal properties of MPEG-2 video for assigning weights to each packet based on the estimated perceptual error. These weights, which indicate the relative importance of RTP packets, together with the communication channel characteristics are used to determine the allocation of resources for providing improved error-resilience and for assigning data packets to various classes of service in order to enhance the quality of transmission. Parameters extracted from the RTP header are used to determine the weights, so that the proposed algorithm can be implemented in real-time. This algorithm is used for adaptively allocating redundant forward error correction packets as well as for marking and forwarding of RTP packets in differentiated services (DiffServ). Simulation results are presented to show the significant improvement in performance based on our proposed approach to video transport.
Effects of image preprocessing/resizing on diagnostic quality of compressed medical images [chest radiographs application]

The effect of prefiltering and resizing on the diagnostic quality of compressed images at various compression ratios is examined in this paper. A key object of the work is to get an insight on selecting an optimal combination of resolution and quantizer coarseness for a given ratio of compression of medical images. Test images were decimated by several decimation factors, and compressed to achieve a target file size. The decompressed images were assessed for their diagnostic quality. The authors' results demonstrate two things: (1) the higher sampling rates allow a quality margin that may offset the effects of subsequent quantization; and (2) gains in quality due to higher resolution levels may eventually be outstripped by the degrading effects of compression as the compression ratio increases. The result suggests a more gradual reduction in resolution would provide better control over loss of quality.
Slice-level rate-distortion optimized multiple description coding for H.264/AVC

We propose a novel standard-compliant multiple description coding (MDC) method that exploits the H.264/AVC redundant slice tool, performing rate-distortion optimization at the slice level. The strategy to allocate redundancy to each slice jointly takes into account its contribution to distortion, its position in the GOP, the effect of decoder error concealment, and the transmission conditions. This makes the algorithm more accurate with respect to previous frame-based solutions, and experimental results show that it compares favorably with other state-of-the-art standard-compliant MDC techniques.
Low complexity adaptation of H.264/MPEG-4 SVC for multiple description video coding

The scalable video coding (SVC) extension of the H.264/MPEG-4 AVC standard provides a feature-rich partition of the video that is amenable to multiple description coding (MDC) for transmission over multiple unreliable channels. In this paper we propose a novel low-complexity MDC scheme where we enforce compliance with H.264/MPEG-4 SVC and restrict our processing to the network adaptation layer (NAL) level. In our scheme video is encoded with two spatial and multiple temporal layers. The lower resolution spatial layer is coarsely encoded using a high quantization parameter (QP) value, while the higher resolution spatial layer is encoded with finer QP. The MDC is performed on an already encoded video stream by partitioning the NAL units from the encoded video stream into the two descriptions, where the coarse lower spatial resolution is duplicated in the two descriptions while finely encoded enhancement layer information is symmetrically distributed between the two descriptions. Experimental results show that compared with single description coding (SDC) the performance of proposed scheme results in gains of up to 3 dB.
Robust Data Hiding in Audio Using Allpass Filters

A novel technique is proposed for data hiding in digital audio that exploits the low sensitivity of the human auditory system to phase distortion. Inaudible but controlled phase changes are introduced in the host audio using a set of allpass filters (APFs) with distinct parameters of allpass filters, i.e., pole-zero locations. The APF parameters are chosen to encode the embedding information. During the detection phase, the power spectrum of the audio data is estimated in the z-plane away from the unit circle. The power spectrum is used to estimate APF pole locations, for information decoding. Experimental results show that the proposed data hiding scheme can effectively withstand standard data manipulation attacks. Moreover, the proposed scheme is shown to embed 5-8 times more data than the existing audio data hiding schemes while providing comparable perceptual performance and robustness
Structure and design of two-channel filter banks derived from a triplet of halfband filters

A novel approach for the construction of two-channel one-dimensional (1-D) biorthogonal filter banks is described. This approach is intended to help overcome limitations in an otherwise effective set of recently proposed techniques while retaining the advantages of a simple design and feature-rich structure. The novelty of the method rests on the use of a triplet of halfband fillers, which are combined in a convenient form of the transfer function with adjustable parameters that provide the necessary flexibility in obtaining the desired response. Design procedures are described for the construction of the filter banks by casting the approximation problem in a form that easily lends itself to Remez exchange algorithm. In these design procedures, the analysis and synthesis filters can be either finite-duration impulse response, infinite duration impulse response, or a hybrid. Examples of design of 1-D filter banks and extension of the technique to two-dimensional diamond filter banks are presented. Finally, subband image-coding examples are given to demonstrate the advantage of the proposed filter-bank structure.
Power-efficient nonuniform 2-D fourier analysis using compressive sensing in WSNs

NDFT) has been well-investigated for performing fast computation of the frequency content of nonequispaced data samples. This nonuniform formulation is also well-suited for Fourier analysis of data samples collected in randomly deployed wireless sensors. However, most of the existing NDFT formulations employ global communication patterns and thus are inefficient in terms of energy consumption and execution time for in-network realization of NDFT. In this paper, we investigate NDFT implementation that leverages compressive sensing (CS) to reduce the amount of data and global communication, thus allowing the use of a few random measurements to adequately represent sparse signal. Our main idea is to organize 2D random deployment of sensors into a hierarchy of clusters. A local interpolation step is performed in the clusters at the lowest level to convert a nonuniform grid into a uniform grid. The global 2D Fast Fourier Transform (FFT) is then implemented using a multiresolution data aggregation architecture and exploiting CS to reduce data transmission. Using theoretical analysis as well as SIDnet-SWANS based simulations, we demonstrate significant advantages of the proposed method over existing state of the art, in terms of execution time, transmission energy efficiency, signal-to-noise ratio and communication overhead.
Energy efficient decentralized detection based on bit-optimal multi-hop transmission in one-dimensional Wireless Sensor Networks

Existing information theoretic work in decentralized detection is largely focused on parallel configuration of Wireless Sensor Networks (WSNs), where an individual hard or soft decision is computed at each sensor node and then transmitted directly to the fusion node. Such an approach is not efficient for large networks, where communication structure is likely to comprise of multiple hops. On the other hand, decentralized detection problem investigated for multi-hop networks is mainly concerned with reducing number and/or size of messages by using compression and fusion of information at intermediate nodes. In this paper an energy efficient multi-hop configuration of WSNs is proposed to solve the detection problem in large networks with two objectives: maximizing network lifetime and minimizing probability of error in the fusion node. This optimization problem is considered under the constraint of total consumed energy. The two objectives mentioned are achieved simultaneously in the multi-hop configuration by exploring tradeoffs between different path lengths and number of bits allocated to each node for quantization. Simulation results show significant improvement in the proposed multi-hop configuration compared with the parallel configuration in terms of energy efficiency and detection accuracy for different size networks, especially in larger networks.
Gesture, speech, and gaze cues for discourse segmentation

Psycholinguistic evidence has established the complementary nature of the verbal and non-verbal aspects of human expression. We present our findings in the detection of these cites in interaction. We use the psycholinguistic device known as the 'catchment' as the locus of integration of gesture, speech and gaze components. We videotape conversation elicitation experiments in which subjects convey complex spatial plans to an interlocutor using a calibrated three-camera setup. We extract the gestural motion of both hands, gaze direction, and voiced units in the discourse and compare these with transcripts generated by expert microanalysis of the video. Our results show the complementary nature of these communicative modalities. Where there is ambiguity in the structure of one modality (such as in haptologies or owing to noise in the audio signal), other modalities provide evidence for correct segmentation.
FIR/IIR exact reconstruction filter banks with applications to subband coding of images

A class of two-channel analysis/synthesis filter banks which are useful in subband coding is described. The procedure is particularly useful in hierarchical coding where a low-resolution embedded signal is obtained by using separable halfband filters. The filter bank can be composed of finite-duration impulse response or infinite-duration impulse response filters. The basic structure is simple and one can use well-known classes of filters as prototypes in a flexible manner to obtain the exact reconstruction solutions. Even if the filter coefficients are quantized for a low-bit representation, the exact reconstruction property is preserved. Some examples of exact reconstruction solutions are presented.<<ETX>>