nils-herrmann/clean_scirepeval huggingface dataset:
Encryption for High Efficiency Video Coding with video adaptation capabilities

In this paper, we describe encryption possibilities for the High Efficiency Video Coding (HEVC) standard under development. Bitstream elements which maintain HEVC compatibility after encryption are listed and their impact on video adaptation is described. From this list, three bitstream elements are selected, namely intra prediction mode difference, motion vector difference sign, and residual sign. These elements provide good protection of the video information and result in 0.0% Bjontegaard delta bitrate increase because of their equal probability entropy encoding property.
JPEG2000. Part 10. Volumetric data encoding

The joint photographic experts group (JPEG) committee (ISO/IEC JTC1/SC29/WG1) is currently pursuing the standardization of a three-dimensional extension of the JPEG-2000 standard (Parts 1 and 2) to support the encoding of volumetric data sets. This extension, Part 10 - extensions for three-dimensional data (JP3D), will support functionalities like resolution scalability, quality scalability and region-of-interest coding, while exploiting the entropy in the additional third dimension to improve the rate-distortion performance. In this paper, we give an overview of the markets and application areas targeted by JP3D, the imposed requirements and the algorithm under study
Aspects regarding controlled switching of the vacuum circuit breaker

The paper describes how different parameters from vacuum circuit breaker influence the closing and opening time. Operational voltage, ambient temperature or hydraulic pressure can introduce delays in opening and closing the circuit breaker. These parameters are motorized through sensors that send all the data to a control unit. The control unit calculates the decision/(time) when to make controlled switching. This paper presents a study case that demonstrates how one of the parameter introduces delays in the opening or closing processes of the circuit breaker.
Dictionary Learning-Based, Directional, and Optimized Prediction for Lenslet Image Coding

In this paper, a novel approach to encode lenslet (LL) images is proposed. The method departs from traditional block-based coding structures and employs a hexagonal-shaped pixel cluster, called macro-pixel, as an elementary coding unit. A novel prediction mode based on dictionary learning is proposed, whereby macro-pixels are represented by a sparse linear combination of atoms from a generic dictionary. Additionally, an optimized linear prediction mode and a directional prediction mode specifically designed for macro-pixels are proposed. Rate-distortion optimization is utilized to select the best intra prediction mode for each macro-pixel. Experimental results on the light field image data set show that the proposed coding system outperforms HEVC and the state-of-the-art in LL image coding with an average peak signal to noise ratio gain of 3.33 and 1.41 dB, respectively, and with rate savings of 67.13% and 34.30%, respectively.
Study of neural networks to improve performance for character recognition

Three methods are proposed to improve the performance of a system based on feedforward neural networks, that is used for character recognition which are perturbed with noise up to 50%. Have been studied neural networks using backpropagation algorithm. The first element introduced in this study is to train the network in stages, using input data with noise, from 0 to 25% (steps 10,15,20,25) and then from 30% to 40% (steps 30,35,40). This approach has allowed fewer errors up to 1,2% for noise plateau 40%-50%. The second proposed method consists in introducing a vector of stability for the primary information, in stages of network training and then character recognition, with role to reduce the influence of noise on the input data. Stability vector proposed is a linear array with 5 constant parameters. The network used has 35 inputs, 16,20,25,30 or 50 nodes in the hidden layer and 26 outputs (one for each letter). The simulation and experimental results demonstrate that the proposed “vector of stability” can improve performance by decreasing the number of errors up to 1,7% for a neural network with 30 or 50 nodes in hidden layer. The third element proposed is to use reverse information (reverse the bits 0 with 1 and 1 with 0). Have been used two networks that process information. Then their outputs are analyzed and processed by a logic block. With this technique performances have been improved by decreasing the number of errors with 1%, 1.5% and 2.3% for 40%, 45% and 50% noise data.
Efficient directional and L1-optimized intra-prediction for light field image compression

Light field images can be conveniently captured by consumer-level plenoptic cameras. However, as the resulting data rates are very high, providing efficient compression for this type of data is of critical importance.  In this paper, a novel intra-prediction method for disk-shaped pixel clusters is proposed. An L1 minimization of the prediction residuals is performed followed by clustering of the predictors, leading to an optimized set of predictors for the macro-pixels. Furthermore, directional intra-prediction modes based on HEVC are devised for the macro-pixels. Experimental results obtained on the EPFL light field image dataset demonstrate that the proposed coding scheme yields an average of 3.22 dB and 1.45 dB gain in PSNR, and 59.6% and 30.88% average rate savings compared to HEVC and the state-of-the-art in light field image coding respectively.
Robust Multiview Synthesis for Wide-Baseline Camera Arrays

In many advanced multimedia systems, multiview content can offer more immersion compared to classical stereoscopy. The feeling of immersiveness is increased substantially by offering motion-parallax, as well as stereopsis. This drives both the so-called free-navigation and super-multiview technologies. However, it is currently still challenging to acquire, store, process, and transmit this type of content. This paper presents a novel multiview-interpolation framework for wide-baseline camera arrays. The proposed method comprises several novel components, including point cloud-based filtering, improved de-ghosting, multireference color blending, and depth-aware MRF-based disocclusion inpainting. The method offers robustness against depth errors caused by quantization and smoothing across object boundaries. Furthermore, the available input color and depth are maximally exploited while preventing propagation of unreliable information to virtual viewpoints. The experimental results show that the proposed method outperforms the state-of-the-art View Synthesis Reference Software (VSRS 4.1) both in objective terms as well as subjectively, based on a visual assessment on a high-end light-field three-dimensional display.
Wavelet image compression - the quadtree coding approach

Perfect reconstruction, quality scalability and region-of-interest coding are basic features needed for the image compression schemes used in telemedicine applications. This paper proposes a new wavelet-based embedded compression technique that efficiently exploits the intraband dependencies and uses a quadtree-based approach to encode the significance maps. The algorithm produces a losslessly compressed embedded data stream, supports quality scalability and permits region-of-interest coding. Moreover, experimental results obtained on various images show that the proposed algorithm provides competitive lossless/lossy compression results. The proposed technique is well-suited for telemedicine applications that require fast interactive handling of large image sets over networks with limited and/or variable bandwidth.
Performance optimizations for PatchMatch-based pixel-level multiview inpainting

As 3D content is becoming ubiquitous in today's media landscape, there is a rising interest for 3D displays that do not demand wearing special headgear in order to experience the 3D effect. Autostereoscopic displays realize this by providing multiple different views of the same scene. It is however unfeasible to record, store or transmit the amount of data that such displays require. Therefore there is a strong need for real-time solutions that can generate multiple extra viewpoints from a limited set of originally recorded views. The main difficulty in current solutions is that the synthesized views contain disocclusion holes where the pixel values are unknown. In order to seamlessly fill-in these holes, inpainting techniques are being used. In this work we consider a depth-based pixel-level inpainting system for multiview video. The employed technique operates in a multi-scale fashion, fills in the disocclusion holes on a pixel-per-pixel basis and computes approximate Nearest Neighbor Fields (NNF) to identify pixel correspondences. To this end, we employ a multi-scale variation on the well-known PatchMatch algorithm followed by a refinement step to escape from local minima in the matching-cost function. In this paper we analyze the performance of different cost functions and search methods within our existing inpainting framework.
Joint DC coefficient band decoding and motion estimation in Wyner-Ziv video coding

In contrast to traditional predictive coding, Wyner-Ziv video coding enables low-cost encoding architectures, in which the computationally expensive tasks for performing motion estimation are shifted to the decoder-side. In Wyner-Ziv video coding, side-information generation is a key aspect profoundly affecting the compression capacity of the system. This paper presents a novel technique which enables side-information refinement after DC coefficient band decoding in a transform-domain Wyner-Ziv video codec. The proposed side-information refinement approach performs overlapped block motion estimation and compensation, utilizing multi-hypothesis pixel-based prediction. The experimental results show that the presented Wyner-Ziv video codec incorporating the proposed technique yields significant and systematic compression gains of up to 23.22% with respect to the state-of-the-art DISCOVER codec.
Influence of operational voltage on switching time of the circuit breakers

This paper refers to the magnetic actuator from vacuum circuit breaker. The actuator is one of the main component with functions for switching, latching and release. Due to the low quality of power supply of actuator, undesirable effects such as the delay during the operation of connecting or disconnecting the circuit breaker can result. As case of study to observe this delay was used a monopolar vacuum circuit breaker with to measure the operating time.
Maximum Likelihood Laplacian Correlation Channel Estimation in Layered Wyner-Ziv Coding

The distributed source coding theory teaches that efficient compression can be achieved by exploiting the correlation between encoded sources at the decoder only. A critical issue in this coding paradigm is how to accurately estimate the correlation statistics at the decoder. This paper proposes a novel correlation channel estimation method designed for generic layered Wyner-Ziv (WZ) coding. Driven by real-life applications, i.e., video coding, the correlation noise is assumed to be memoryless zero-mean Laplacian with a block-stationary behavior. Unlike existing methods, the proposed technique derives a novel maximum likelihood estimate of the noise scaling parameter per stationarity block. Adhering to layered coding, the derived estimate is successively refined as more stages are decoded. The Crámer-Rao lower bound (CRLB) for our estimator is derived and the mean squared error performance of the proposed successive refinement algorithm is evaluated through simulations. Apart from achieving an accuracy close to the derived CRLB, the proposed algorithm is shown to yield a WZ rate-distortion performance approaching the ideal but unrealistic scenario where the decoder knows a priori the correlation statistics. Moreover, the proposed technique has been integrated into our latest WZ video codec for wireless capsule endoscopy. Experimentation reveals that the proposed method delivers improved compression performance compared to state-of-the-art techniques, while simultaneously reducing the overall decoding complexity.
Video coding based on motion estimation in the wavelet detail images

This work proposes a new block based motion estimation and compensation technique applied on the detail images of the wavelet pyramidal decomposition. The algorithm uses two matching criteria, namely the absolute difference and the absolute sum. For a wavelet decomposed one-dimensional step function, it is shown that for odd translations of the step, the absolute sum reaches a smaller minimum than the absolute difference. We also derive in this case a constraint on the highpass filter coefficients so that a zero prediction error can be reached by using the absolute sum. Although this cannot be easily generalized for an arbitrary signal profile, experimental results obtained with photorealistic image sequences indicate that the prediction error can be reduced with respect to techniques that only use the absolute difference as matching criterion.
Dual FEM-Simulink analysis of induction motor operating under unbalanced state

This paper presents a dual approach concerning the influence of unbalanced supply voltage on the three-phase induction motor operation. On one hand, a FEM-based analysis examines the ill effects upon the magnetic field, as main concern, and a few electric and mechanical parameters. On the other hand, a study of the transitory regime (including no-load startup and sudden loading) is employed under Simulink environment. To this aim, an original equation system, developed by the authors and called “in total fluxes” is used. The both analyses take into discussion a 3.5kW cage induction motor and two unbalanced degrees. Among other effects, the results put in view the huge influence of the voltage unbalances upon the torque and speed smoothness, which finally turns into vibrations and noise.
IoT system for monitoring vital signs of elderly population

The leading cause of death of elderly Europeans (over 65 years) is heart diseases . Adding up to that, there is also the fact that 30% of elderly people encounter unintentional falls each year, and most of them are fatal [2]. Our paper describes the concept and architecture of a system which is able to monitor the body's vital signs, pre-process the data, generate emergency alerts and use the power of cloud machine learning to predict medical states.
Information-Theoretic Analysis of Dependencies Between Curvelet Coefficients

This paper reports an information-theoretic analysis of the inter-scale, inter-orientation and inter-location dependencies that exist between curvelet coefficients. We show that the marginal statistics of these coefficients can be accurately modeled using generalized Gaussian density functions. Though generally decorrelated, we find that curvelets exhibit unusually high dependencies in intra-band local micro-neighborhoods, of a magnitude not found for instance in classical wavelets. Furthermore, dependencies are subject to and decrease with increasing orientation and location differences. Finally, we conclude that intra-band coefficient dependencies are stronger than either their inter-scale or inter-direction counterparts.
Scalable video coding based on motion-compensated temporal filtering: complexity and functionality analysis

Video coding techniques yielding state-of-the-art compression performance require large amount of computational resources, hence practical implementations, which target a broad market, often tend to trade-off coding efficiency and flexibility for reduced complexity. Scalable video coding instead, not only provides seamless adaptation to bit-rate variation, but also allows the end user to trim down the resources he needs to perform real-time decoding by limiting the process to a subset of the original content. Hence, by choosing the quality, frame-rate and/or resolution of the reconstructed sequence, each decoder can meet its hardware limitations without affecting the encoding process of the media provider. This paper proposes a preliminary analysis of the memory-access behavior of a fully scalable video decoder and investigates the capability of selecting the operational settings in order to adapt to the available hardware resources on the target device.
Joint Source-Channel Coding for the Scalable Extension of H.264/MPEG-4 AVC

In this paper, we propose a joint source-channel coding (JSCC) methodology which minimizes the end-to-end distortion for the transmission of H.264/MPEG-4 scalable video over packet loss channels. The proposed JSCC-approach employs low-density parity-check codes in order to provide channel protection and relies on Lagrangian-based optimization techniques to derive the appropriate protection levels for each layer produced by the scalable source codec. Experiments show that our JSCC methodology delivers competitive results to state-of-the-art Lagrangian-based algorithms. However, in contrast to the state-of-the-art, our approach significantly reduces the computational complexity. We conclude that the proposed JSCC methodology provides optimized resilience against transmission errors in scalable video streaming over variable-bandwidth error-prone channels.
Context-conditioned composite coding of 3D meshes based on wavelets on surfaces

In this paper, a novel wavelet-based composite mesh coding scheme is presented. In contrast to the state-of-the-art scalable interband mesh codec, the proposed codec relies on composite dependency models that capture both the interband and intraband statistical dependencies between wavelet coefficients. Additionally, each wavelet subband is processed independently, which allows for parallelized processing and for a progressive reconstruction of each mesh resolution level. Compared to the state-of-the-art, the proposed codec yields for almost all rate points superior compression performance in L2 -sense. Furthermore, the generated bitstreams are near-optimal in rate-distortion sense, which eliminates the need of a post-compression rate-distortion optimization technique.
Scalable wavelet video-coding with in-band prediction - implementation and experimental results

In this paper we elaborate on a recently proposed approach for scalable video-coding based on in-band prediction in the overcomplete wavelet domain. It is shown that, through a new calculation scheme for the level-by-level complete to overcomplete discrete wavelet transform (DWT) that exploits certain symmetries, important reductions in the multiplication budget are obtained in comparison to the fastest-known algorithm of the literature. Based on the derived overcomplete transform-domain coefficients, a pixel-accurate motion estimation and compensation (ME/MC) algorithm is proposed, which provides a hybrid-coding framework that supports full scalability in resolution, quality and frame rate. To give an indication of the coding performance of such a system, some preliminary results are reported.
Wavelet analysis in monitoring and diagnosis of power circuit breakers

Monitoring of electrical equipment is a direction of current development in the maintenance domain. The method aims to establish the operation state of the monitored equipment. Fault diagnosis existing on power circuit breakers is very important aspect in emergency situations, when it must be interrupted by high current circuit breakers. This paper presents a model of vibration monitoring using Wavelet-Morlet transform. Here are reviewed theoretical problems of using Wavelet-Morlet transform, signal processing techniques and experimental results that highlight the difference between faulty equipment and one in a proper working condition.
Using fuzzy logic for diagnosis of technical condition of power circuit breakers

Monitoring and diagnosis of power circuit breakers represent an important activity for increase the reliability and safety in power system. In order to deal with the uncertain information in the process of diagnosis, the paper presents a diagnosis system based on fuzzy logic which has the role to acquire information about the monitored equipment for faults detection. Also, the paper describe the LabVIEW software application based on fuzzy logic used for diagnosis of power circuit breakers which enable to generate alarms when something it is wrong with the electrical equipment.
Markov analysis of an induction motor

The paper deals with the reliability of induction motors by using Markov techniques. The basis of this process is to perform the reliability predictions to obtain the necessary indicators in order to support the Markov analysis. The analysis is made on a single-phase induction motor, taking into consideration the most critical components that could lead to the failure of the motor. Furthermore, the possible states of the motor and the importance of maintenance in the lifecycle of the motor are presented. By having a well implemented maintenance policy, the life of the motor can be extended and unwanted defects can be avoided.
Design and simulation of a small wind-hydro power plant

Due to climate changes that have been observed in regions all over the world and which are believed to be caused by the use of conventional energy sources, we must draw our attention to renewable energy sources which are the most suitable in the future. This paper presents a study about designing and simulation of a small wind-hydro power plant which will be located in the Didactical and Agreement Base Marisel belonging to the Technical University of Cluj Napoca, Romania, and which will be used in didactical and research purposes. After execution, this pilot station will be used mainly for studding the possibilities of pumped hydro power plant to store the wind energy in the form of hydro-energy of water.
Scalable Joint Source-Channel Coding for the Scalable Extension of H.264/AVC

This paper proposes a novel joint source-channel coding (JSCC) methodology which minimizes the end-to-end distortion for the transmission over packet loss channels of scalable video encoded using SVC, the scalable extension of H.264/AVC. The proposed JSCC approach performs channel protection using low-density parity-check codes and relies on Lagrangian-based optimization techniques to derive the appropriate protection levels for each layer produced by the scalable source codec. Our JSCC approach for SVC can support spatial, temporal and quality scalability and can provide an optimized channel protection in any scalable setting. Experiments show that our JSCC methodology yields competitive results against state-of-the-art Lagrangian-based JSCC algorithms. Compared to the state-of-the-art, our approach significantly reduces the number of computations needed to derive the rate-distortion hulls. Moreover, the proposed approach constructs convex rate-distortion hulls for each frame, irrespective of the target rate. This allows the pre-computation of the convex rate-distortion hulls for typical packet loss channels, such that the extraction of a near-optimal JSCC allocation can be achieved on-the-fly for any target rate or packet-loss rate. We conclude that the proposed JSCC methodology provides optimized resilience against transmission errors in scalable video streaming over variable-bandwidth error-prone channels.