nils-herrmann/clean_scirepeval huggingface dataset:
Efficient error control in 3D mesh coding

Our recently proposed wavelet-based L-infinite-constrained coding approach for meshes ensures that the maximum error between the vertex positions in the original and decoded meshes is guaranteed to be lower than a given upper bound. Instantiations of both L-2 and L-infinite coding approaches are demonstrated for MESHGRID, which is a scalable 3D object encoding system, part of MPEG-4 AFX. In this survey paper, we compare the novel L-infinite distortion estimator against the L-2 distortion estimator which is typically employed in 3D mesh coding systems. In addition, we show that, under certain conditions, the L-infinite estimator can be exploited to approximate the Hausdorff distance in real-time implementations.
Wavelet based edge detection method for analysis of coronary angiograms

The assessment of coronary anatomy is one of the prime determinants in choosing medical or interventional therapy for patients with ischemic heart disease. We report a wavelet based method of coronary border identification which has the advantage of the detection of the edges at different scales (the image changes are computed in a variable neighborhood), unlike the conventional methods where a fixed, heuristic neighborhood is used. Additionally, the conventional methods are more noise sensitive than a wavelet based method. We propose an algorithm to combine the information from the multiple scales. The computer determined diameters are compared to the actual diameters of the simulated vessels of three test objects. These comparisons show that our method allows accurate identification of the borders of phantom vessels (correlation coefficient in the range 0.90-0.99 for different wavelets).
Semi-regular remeshing with reduced remeshing error

In this paper we present a remeshing algorithm which drastically reduces the aliasing artifacts inherent in regularly-sampled remeshed objects. Starting from a semi-regular mesh, the proposed algorithm reduces the remeshing error and avoids aliasing by displacing vertices such that most samples of the original mesh are present in the remeshed model as well. Computational efficiency is provided by using a search-tree, which efficiently gathers vertices near a given point in a 3D space. Compared to the state-of-the-art semi-regular remesher, the proposed remesher drastically improves the visual quality of the high-frequency regions in remeshed objects. Additionally, the proposed algorithm yields a lower remeshing error, which is reflected by a significantly increased PSNR upper-bound in wavelet-based compression of such meshes.
The water impact on the aging of power transformer oil

The paper deals with the aging mechanisms of the power transformer oil insulation. Through the degradation of the electroinsulating paper, a great number of decomposition compounds appears, such as gases, water and solid organic compounds which accelerate the aging process of the mineral oil. As a result of the degradation, redox reactions are developed that amplify the processes of formation of free radicals, or sometimes even of ions that propagate undesirable side reactions in the oil-paper electroinsulation system. The paper analyses the impact of water content on the mineral oil characteristics. The dependence of the breakdown voltage of TR 30 MOL mineral oil on the water content is experimentally obtained, confirming the strongly fall of the electric strength of the oil with increasing of water contents.
Transform-domain Wyner-Ziv video coding for 1K-pixel visual sensors

Efficient coding of extremely low-resolution video has received a mere shadow of the attention given to their high-definition counterpart. However, low-resolution video still proves suitable for video processing and may enable the design of advanced video-based applications in a cost-effective manner. Indeed, visual sensors with modest frame resolutions can be designed to be small, low-cost and low-power. This paper introduces a novel efficient codec, specifically designed to handle extreme low-resolution video captured by such visual sensors. By applying Wyner-Ziv coding principles, the encoding complexity is reduced since temporal redundancy is exploited at the decoder. The proposed system outperforms H.264/AVC Intra and is therefore particularly attractive to wireless, resource-constraint low-resolution visual sensor applications by reducing the amount of transmitted data at a reduced computational cost.
Correlation modeling with decoder-side quantization distortion estimation for distributed video coding

Aiming for low-complexity encoding, distributed video coders still fail to achieve the performance of current industrial standards for video coding. One of most important problems in this area is the accurate modeling of the correlation between the predicted signal and the original video. In our previous work we showed that exploiting the quantization distortion can significantly improve the accuracy of a correlation estimator. In this paper we describe how the quantization distortion can be exploited purely at the decoder side without any performance penalty when compared to an encoder-aided system. As a result, the proposed correlation estimator delivers state-of-the-art modeling accuracy while neatly fitting the low-encoder-complexity characteristic of distributed video coding.
Wavelet Coding of Volumetric Medical Datasets

Several techniques based on the three-dimensional (3-D) discrete cosine transform (DCT) have been proposed for volumetric data coding. These techniques fail to provide lossless coding coupled with quality and resolution scalability, which is a significant drawback for medical applications. This paper gives an overview of several state-of-the-art 3-D wavelet coders that do meet these requirements and proposes new compression methods exploiting the quadtree and block-based coding concepts, layered zero-coding principles, and context-based arithmetic coding. Additionally, a new 3-D DCT-based coding scheme is designed and used for benchmarking. The proposed wavelet-based coding algorithms produce embedded data streams that can be decoded up to the lossless level and support the desired set of functionality constraints. Moreover, objective and subjective quality evaluation on various medical volumetric datasets shows that the proposed algorithms provide competitive lossy and lossless compression results when compared with the state-of-the-art.
Segmentation-based intra coding of depth maps using texture information

Emerging video technologies, such as 3DTV, increase the demand for high efficiency coding tools. To allow the transmission of a multiview video over the employed transmission channels, a new data format including texture and the corresponding depth information has been proposed. In this paper we present a novel segmentation-based intra codec for depth maps, utilizing the correlation between depth and color data. Our system performs a low-complexity color segmentation on the texture image and encodes the depth values within the segments. The same segmentation is calculated at the decoder, ensuring the closed-loop property of the system. Experimental results show that the proposed system is a viable alternative for 3D-HEVC in low-complexity applications.
Study on the influence of noise in the printed character recognition system

In this paper we present the implementation of a neural network model trained with a high noise level using backpropagation algorithm and the experimental results for printed character recognition, based on the idea of using the primary information by reorganising it in a different format. The model is made up of four neural networks and the values obtained at the outputs of each network are processed by using three analysis modules. For noise input vector applied to all 35 bits and up to 50% change their values obtained performance is 99.5% and this value decreased to 93.5% for a noise level of 60%. For a three bits input vector disturbing rate of 90-100%, three bits at a rate of 70-90%, two bits at a rate of 50-70% and ten bits between 0-50%, the performance obtained is 90.7 % for module MAX and 91.7% for SUM module. The performed model increased the printed character recognition rate by using the same primary information in a different manner.
Wavelet-Based ${L_\infty }$ Semi-regular Mesh Coding

Polygonal meshes are popular three-dimensional virtual representations employed in a wide range of applications. Users have very high expectations with respect to the accuracy of these virtual representations, fueling a steady increase in the processing power and performance of graphics processing hardware. This accuracy is closely related to how detailed the virtual representations are. The more detailed these representations become, the higher the amount of data that will need to be displayed, stored, or transmitted. Efficient compression techniques are of critical importance in this context. State-of-the-art compression performance of semi-regular mesh coding systems has been achieved through the use of subdivision-based wavelet coding techniques. However, the vast majority of these codecs are optimized with respect to the <inline-formula><tex-math notation="LaTeX">${L_2}$</tex-math></inline-formula> distortion metric, i.e., the average error. This makes them unsuitable for applications where each input signal sample has a certain significance. To alleviate this problem, we propose to optimize the mesh codec with respect to the <inline-formula><tex-math notation="LaTeX">${L_\infty }$</tex-math></inline-formula> metric, which allows for the control of the local reconstruction error. This paper proposes novel data-dependent formulations for the <inline-formula><tex-math notation="LaTeX">${L_\infty }$</tex-math></inline-formula> distortion. The proposed <inline-formula><tex-math notation="LaTeX">${L_\infty }$</tex-math></inline-formula> estimators are incorporated in a state-of-the-art wavelet-based semi-regular mesh codec. The resulting coding system offers scalability in <inline-formula><tex-math notation="LaTeX">${L_\infty }$</tex-math></inline-formula> sense. The experiments demonstrate the advantages of <inline-formula><tex-math notation="LaTeX">${L_\infty }$</tex-math></inline-formula> coding in providing a tight control on the local reconstruction error. Furthermore, the proposed data-dependent <inline-formula> <tex-math notation="LaTeX">${L_\infty }$</tex-math></inline-formula> approaches significantly improve estimation accuracy, reducing the classical low-rate gap between the estimated and actual <inline-formula> <tex-math notation="LaTeX">${L_\infty }$</tex-math></inline-formula> distortion observed for previous <inline-formula> <tex-math notation="LaTeX">${L_\infty }$</tex-math></inline-formula> estimators.
Wavelet lossless compression of coronary angiographic images

The final diagnosis in coronary angiography has to be performed on the original images, therefore the lossless compression schemes play a key role in medical data base management and tele-diagnosis applications. This work proposes a wavelet based compression scheme that is able to operate in the lossless mode. The quantization module implements a new modality for the coding of the coefficient's significance map that is more effective than the classical zero-tree representation. The experimental results obtained on a set of 20 angiograms show that the algorithm outperforms with 0.38 bpp the embedded zero-tree coder combined with the lifting scheme, with 0.20 bpp the set partitioning coder and with 0.70 bpp the lossless JPEG. The scheme is a good candidate in applications like remote browsing through large image data sets and real-time archiving of coronary angiograms.
Feedback-constrained Wyner-Ziv video coding

Distributed video coding (DVC) systems described in the literature often make use of a feedback channel to determine the rate. However, supporting such a feedback channel in practice may be difficult, particularly considering that current approaches are unable to incorporate constraints on feedback channel usage. Therefore, in this paper we propose a system in which the number of requests per Wyner-Ziv frame can be constrained to a fixed value. Our technique involves decoder-side rate estimation, modeling of its accuracy, and finally defining the number of Wyner-Ziv bits for each of the requests allowed. The experimental results indicate that the performance loss is limited when compared to a configuration operating without constraints on the feedback channel.
Model based approach in fault detection and diagnosis for DC motor

Recent advances in microelectronic circuit have enabled the application of process diagnostics to a variety of systems to improve performances and the reliability. Failure detection and isolation strategies monitor a system for degradations and if detected, classify the failure source. One of the most important methods for failure detection and diagnosis is the analysis of the variations of the estimated parameter of DC Motor. In this paper is presented a structure of a method for failure detection and diagnosis based on continuous time parameter estimation of a mathematical model of the DC Motor. Continuous time parameters can be related easily to the physical characterizations of DC Motor. The parameter is directly estimated by well-known prediction error method of identification for dynamic systems. The failure detection it is based on changing the process coefficient and statistical decision methods. Unlike usual papers, the failure can be detected whether others process parameters are not constant.
Control of the distortion variation in video coding systems based on motion compensated temporal filtering

The paper proposes a new framework for the control of the distortion variation in video coding schemes based on motion-compensated temporal filtering (MCTF). The distortion in an arbitrary decoded frame at any temporal level in the MCTF pyramid is expressed as a function of the distortions in the reference frames at the same temporal level. The approach is formulated for the bi-directional unconstrained MCTF (UMCTF) scheme of Turaga et al., (2002), which does not include the update-lifting step. The proposed framework can be extended to the generalized form of MCTF by utilizing additional control parameters. Experimental results demonstrate the control of the distortion variation in video coding systems based on spatial-domain and wavelet-domain MCTF. One concludes that the proposed framework provides the means of controlling the tradeoff between the average distortion and the distortion variation in each group-of-pictures (GOPs) within the decoded sequence.
Scalable multiple description video coding for error-resilient transmission over hybrid networks

In this paper a scalable multiple description video coding approach based on embedded multiple description scalar quantization (EMDSQ) is presented. The proposed approach enables the progressive transmission of video over unreliable channels with variable bandwidth. Experimental results show that in lossy transmission conditions the proposed embedded multiple description coding system yields better rate-distortion performance compared to single description video coding and can efficiently sustain 20% of losses.
Modeling the Correlation Noise in Spatial Domain Distributed Video Coding

Conventional models in distributed video coding (DVC) consider the correlation noise to be distributed independently from the realization of the side-information. This paper introduces a novel model, of which the standard deviation depends spatially on the realization of the side-information. The performance penalty in video coding caused by side-information-independency assumptions is theoretical quantified and experimentally confirmed. Furthermore, inspired by the spatial side-information-dependency of the proposed model, a novel approach for estimating the correlation channel from the partial knowledge of it is introduced. The proposed technique is incorporated into a spatial-domain unidirectional DVC system, providing state-of-the-art performance.
Induction Motor With Outer Rotor and Ring Stator Winding for Multispeed Applications

This paper presents a complex study of the performance developed by an outer rotor induction motor with multipole stator winding. The novelty of the proposed structure consists in the replacement of the regular lap winding with a ring type one, which allows a higher flexibility in changing the number of pole pairs. The purpose is mainly to obtain a superior torque capability by changing the synchronous speed. This study is based on FEM, Simulink analyses, and experimental tests. A startup strategy for the reduction of starting time, current, and electric power consumption is developed as well.
Demo: Distributed video coding applications in wireless multimedia sensor networks

Novel distributed video coding (DVC) architectures developed by the IBBT DVC group realize state-of-the-art video coding efficiency under stringent energy restrictions, while supporting error-resilience and scalability. Therefore, these architectures are particularly attractive for application scenarios involving low-complexity energy-constrained wireless visual sensors. This demo presents the scenarios, which are considered to be the most promising areas of integration for IBBT's DVC systems, considering feasibility and commercial applicability.
Efficient scalable compression of sparsely sampled images

Advanced sparse sampling acquisition systems capture only scattered information from the continuous image domain. Unfortunately, conventional image encoders are not yet able to properly compress arbitrarily subsampled image data. This work introduces a system leveraging the JPEG 2000 image compression framework by enabling scalable compression of the selected image samples. Using a complete dictionary of CDF 9/7 wavelets, a minimum l1-norm compressed sensing solution is recovered which can be fed directly into the encoder, producing a bitstream that can be decoded with existing JPEG 2000-compliant implementations. Experiments on standard images with quasi-random subsampling demonstrate that the proposed system outperforms regular JPEG 2000 compression of stacked sample images and quad-tree based compression for point-clouds. We also demonstrate the robustness of the technique for images that infringe the sparsity prior of compressed sensing.
A statistical approach to create side information in distributed video coding

The distributed video coding (DVC) paradigm constitutes a flexible framework where computational complexity can be freely distributed between encoder and decoder, hence favoring up-link oriented video applications where recording devices are modest in terms of computational power and are faced with energy consumption constraints. This contribution presents an original transform domain DVC architecture, which performs hash-based motion estimation at the decoder combined with a novel probabilistic motion compensation technique to generate side information. The proposed probabilistic motion compensation incorporates knowledge of the correlation channel statistics and extracts additional information from the hash. Experimental results report Bj⊘ntegaard rate savings of up to 4.61%, when using the novel probabilistic motion compensation method instead of our previous approach. Moreover, the compression performance of the presented DVC architecture, featuring the proposed probabilistic motion compensation, surpasses the performance of the state-of-the-art DISCOVER codec, showing Bj⊘ntegaard rate savings of up to 15.69%.
Modeling and simulation of DC resonant circuit breakers

The specific problems of the disconnection of HVDC breakers need an analysis of performances at laboratory scale. In the study of hybrid circuit breakers with commutation, three steps are necessary: modeling, simulation and experimental tests. The paper presents a modeling procedure for a hybrid commutation breaker intended to operate using resonant circuits phenomenon. Using the Matlab platform, the simulation of the disconnection of short-circuit process, highlights the reduction of the disconnection period at a low value of the short-circuit current. The performance of the electric equipment is analyzed in the laboratory, in terms of the concordance between the model and the simulation procedure.
A new family of embedded multiple description scalar quantizers [image coding applications]

A new family of embedded multiple description scalar quantizers (EMDSQ) that support the progressive transmission of images over variable-bandwidth error-prone channels is proposed in this paper. A control mechanism that allows for tuning the redundancy between the two descriptions for each quantization level is also designed. The employed mechanism enables control of the tradeoff between the coding efficiency and error-resilience, and provides an increased robustness by improving the error resilience in the most important layers of the embedded bit-streams. Instantiations of the proposed family are incorporated in a wavelet-based embedded coding system, and the redundancy-control mechanism is practically demonstrated. Experimental results show that the proposed EMDSQ outperform the state-of-the-art multiple description uniform scalar quantizers (MDUSQ) previously proposed in the literature for error-resilient progressive image transmission.
Aspects concerning the influence of environmental factors in infrared monitoring of electrical equipment

This paper presents the influence of the environmental factors over the electrical equipment thermal stresses when it is monitored with infrared monitoring device. A good definition of the correction parameters for this monitoring device and the choice of the optimal conditions for monitor performing can lead to good results. In particular, the paper presents the influence of the dust layer from electrical equipment over the captured thermal image by the infrared monitoring device and further more to estimate its thermal stress. To achieve this, it was used an experimental stand where a copper bar was split in different areas and they were covered with different dust types and in the end the thermal stress of each area was estimated with the infrared monitoring device.
Scalable wavelet video-coding with in-band prediction - the bottom-up overcomplete discrete wavelet transform

A new in-band motion compensation algorithm for wavelet-based video coding is proposed: the bottom-up prediction algorithm (BUP). The BUP algorithm overcomes the periodic shift-invariance of the discrete wavelet transform (DWT) and is formalized into new prediction rules using filtering operations. BUP is based on the relationships between the subbands of the shifted input signal and the subbands of the non-shifted reference signal, whereby the number of shifts is limited by the periodic shift-invariance of the DWT. We derive the algorithm for the 1-D DWT with three decomposition levels. The combination of all prediction rules of the BUP algorithm defines a new transform: the bottom-up overcomplete DWT or BUP ODWT, which is shift-invariant. The BUP ODWT calculates the overcomplete subbands by applying the prediction rules to the critically sampled subbands of a wavelet-transformed image. The envisaged application for the BUP algorithm is spatially scalable video coding.
CDF 9/7 wavelets as sparsifying operator in compressive holography

Compressive sensing is a mathematical framework, which seeks to capture the information of an object using as few measurements as possible. Recently, it has been applied to holography, where the most frequently used reconstruction method is l1-norm minimization with the Haar wavelet as the sparsifying operator. In this work, we promote the CDF 9/7 wavelet as the sparsifying operator. We demonstrate that the CDF 9/7 wavelet performs better than the Haar wavelet.