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This paper describes a fast algorithm for transforming Legendre coefficients into Chebyshev coefficients, and vice versa. The algorithm is based on the fast multipole method and is similar to the approach described by Alpert and Rokhlin [SIAM J. Sci. Comput., 12 (1991), pp. 158--179]. The main difference is that we utilize a modal Galerkin approach with Chebyshev basis functions instead of a nodal approach with a Lagrange basis. Part of the algorithm is a novel method that facilitates faster spreading of intermediate results through neighboring levels of hierarchical matrices. This enhancement leads to a method that is approximately 20 percent faster to execute, due to fewer floating point operations. We also describe an efficient initialization algorithm that for the Lagrange basis is roughly 5 times faster than the original method for large input arrays. The described method has both a planning and an execution stage that asymptotically require O(N) flops. The algorithm is simple enough that it can be implemented in 100 lines of vectorized Python code. Moreover, its efficiency is such that a single-threaded C implementation can transform 1,000,000 coefficients in approximately 20 milliseconds on a new MacBook Pro M3, representing about 3 times the execution time of a well-planned (single-threaded) type 2 discrete cosine transform from FFTW (www.fftw.org). Planning for these coefficients requires approximately 50 milliseconds. [ABSTRACT FROM AUTHOR]

In the late Permian and Triassic, the continental Mitu Group formed in extensional basins along the length of the Cordillera Oriental and Altiplano of present-day Peru. Given the presence of coeval arc systems only in northern Chile and southern Ecuador but not in Peru the tectonic setting of the Mitu basin has been interpreted variably as orthogonal continental rift, sinistral transtensional rift, aulacogen and back-arc basin. The Mitu Group comprises continental mass flow and alluvial fan, fluvial, aeolian and minor lacustrian facies and hosts thick piles of subalkaline and alkaline intermediate and felsic ignimbrites and mafic lavas. The age of the Mitu Group had originally been established as ranging from the Late Permian to the late Triassic on the basis of structural considerations and scarce biostratigraphic data. Recently, U-Pb zircon ages from ignimbrites and sedimentary rocks have been taken to constrain the Mitu Group to the Middle and Late Triassic. We performed a sedimentological, heavy mineral, and zircon geochronological and Lu-Hf isotope study of the Mitu Group in 14 sections mainly in southern and central Peru, and one section in northern Peru. Ten new U-Pb concordia ages on ignimbrites intercalated in the Mitu Group successions offer a new robust stratigraphic framework and constrain the stratigraphy of the Mitu Group between 260 and 205 Ma. In combination with maximum likelihood ages of deposition derived from detrital zircon, U-Pb geochronology places the deposition of the Mitu Group between ca. 270 and 194 Ma (lower Guadalupian into the Sinemurian). Detrital zircon U-Pb age distributions and heavy mineral assemblages reflect a strongly recycled Precambrian Amazonian and Palaeozoic proto-Andean provenance. The Palaeozoic detrital age patterns are highly variable, and temporally and spatially random. A local provenance can generally not be identified. εHf(t) values in zircon obtained from ignimbrites and sedimentary rocks indicate variable degrees of crustal recycling. In the course of the Palaeozoic, εHf(t) values become on average progressively less negative, with a large proportion particularly of Mitu age zircons' εHf(t) values encompassing less evolved and moderately juvenile compositions. Along strike of the basin stratigraphic thicknesses, and rates and times of accumulation vary strongly with larger thicknesses and rates being registered in southern Peru. This suggests that the Mitu basin had been divided into a number of subbasins with individual histories of subsidence, accumulation, and volcanism. Absent a magmatic arc, late Permian-Triassic Peru evolved in a sinistral plate tectonic and regional framework expressed particularly in the sinistral Late Gondwanide orogeny predating the Mitu Group. We interpret that a sinistral transform fault linked the subduction zones in southern Ecuador and northern Chile and that the Mitu Group basin has formed by sinistral transtensional and transpressional movements along a related transcurrent fault inboard of the transform margin. In the broader framework of the accretionary Terra Australis orogen along the western Gondwana margin, this interpretation fits its evolution in the Andean segment in an internally consistent way. [ABSTRACT FROM AUTHOR]

Thousand-grain weight is the main parameter for accurately estimating rice yields, and it is an important indicator for variety breeding and cultivation management. The accurate detection and counting of rice grains is an important prerequisite for thousand-grain weight measurements. However, because rice grains are small targets with high overall similarity and different degrees of adhesion, there are still considerable challenges preventing the accurate detection and counting of rice grains during thousand-grain weight measurements. A deep learning model based on a transformer encoder and coordinate attention module was, therefore, designed for detecting and counting rice grains, and named TCLE-YOLO in which YOLOv5 was used as the backbone network. Specifically, to improve the feature representation of the model for small target regions, a coordinate attention (CA) module was introduced into the backbone module of YOLOv5. In addition, another detection head for small targets was designed based on a low-level, high-resolution feature map, and the transformer encoder was applied to the neck module to expand the receptive field of the network and enhance the extraction of key feature of detected targets. This enabled our additional detection head to be more sensitive to rice grains, especially heavily adhesive grains. Finally, EIoU loss was used to further improve accuracy. The experimental results show that, when applied to the self-built rice grain dataset, the precision, recall, and mAP@0.5 of the TCLE–YOLO model were 99.20%, 99.10%, and 99.20%, respectively. Compared with several state-of-the-art models, the proposed TCLE–YOLO model achieves better detection performance. In summary, the rice grain detection method built in this study is suitable for rice grain recognition and counting, and it can provide guidance for accurate thousand-grain weight measurements and the effective evaluation of rice breeding. [ABSTRACT FROM AUTHOR]

RGB-D sensors can be a low-cost solution for an accurate silo's content monitoring which is fundamental for its efficient management. Some reference information such as the position and orientation of the sensor with respect to the silo's geometry is fundamental for obtaining correct content measurements from acquired data. Since in real cases this information is not always known, a new method to obtain these measurements is proposed. This, taking as input sensor acquired data (represented as a point cloud), automatically computes the silo's axis to provide a new reference system from which the point cloud can be easily processed. The z-axis of this reference system coincides with the gravity axis and the xy-plane is parallel to the ground plane. It is obtained in a six-step process that exploits the silo geometry properties and an estimation of the shape tensors of the acquired points. The method has been implemented and tested on both synthetic and real silos, considering a complete silo's discharge process and different camera positions. Data acquired at each discharge has been transformed using the new reference system and compared with the silo's ground truth (manually obtained for the real silos). To evaluate the accuracy the input point cloud to adjusted point cloud average distance has been considered. In all the tests, the well-performance of the proposal has been demonstrated, achieving a maximum average distance error of less than 6 cm. [ABSTRACT FROM AUTHOR]

A Personal Health Record (PHR) is a patient-managed platform for health data. Most hospitals provide a PHR as an extension of the Electronic Medical Record (EMR). However, there are unresolved issues around the adoption rate, functionalities, barriers and, more importantly, the impact of the PHR on patients' health. A cross-sectional, survey-based descriptive study was conducted in which patients from four main tertiary hospitals in Saudi Arabia were targeted from September 2022 to February 2023. The survey was tested and validated to address the objectives of the study. The survey covered components related to intention to use the PHR, required functions, obstacles and expected outcomes. This study involved 396 participants from the top four hospitals. It was discovered that the majority of them had intentions to use the PHR (93%) and believed it to be useful (94%) and easy to use (94%). It was widely agreed that accessing medical records (77%), scheduling appointments (88%), renewing medication (90%), tracking patient data (70%) and receiving personalized education (78%) were essential aspects of the PHR. Furthermore, the survey revealed that 54% of respondents saw a positive effect on their health status. A significant number of participants, around 54%, expressed concerns about the privacy of their PHR, and 46% reported concerns about the accuracy of their information. The study found that demographic factors and the type of hospital did not have a statistically significant association with the intention to use the PHR. Our findings showed that there were no significant barriers to adopting the PHR. Additionally, we found that less than half of the participants believed that their current PHR helped them to improve their health. This highlights the need for healthcare organizations to focus on improving the PHR's functionality and overall purpose. Instead of simply providing basic features, the PHR should allow patients to manage their health information comprehensively, including compiling information from hospitals and patient-generated data. Having a PHR is crucial in improving an individual's overall health. As technology advances, more data are being generated that should be included in the PHR to ensure an accurate and comprehensive view of the patient's health. Expanding the scope of the PHR to include capabilities beyond merely hospital data is important. Achieving this requires an open and honest discussion about the role of the PHR, potential obstacles and how to coordinate efforts among different stakeholders. [ABSTRACT FROM AUTHOR]

This paper offers several approaches for solving multiplicative second-order linear differential equations with variable exponentials, such as normalization and reduction to Riccati equations. In addition, in this paper, the multiplicative version of the Airy equation, which emerges in fluid mechanics, geophysics, and atomic physics, is solved using the multiplicative power series solution method. [ABSTRACT FROM AUTHOR]

BACKGROUND: In order to reduce the impact of CT radiation, low-dose CT is often used, but low-dose CT will bring more noise, affecting image quality and subsequent 3D reconstruction results. OBJECTIVE: The study presents a reconstruction method based on wavelet transform-total variation (WT-TV) for low-dose CT. METHODS: First, the low-dose CT images were denoised using WT and TV denoising methods. The WT method could preserve the features, and the TV method could preserve the edges and structures. Second, the two sets of denoised images were fused so that the features, edges, and structures could be preserved at the same time. Finally, FBP reconstruction was performed to obtain the final 3D reconstruction result. RESULTS: The results show that The WT-TV method can effectively denoise low-dose CT and improve the clarity and accuracy of 3D reconstruction models. CONCLUSION: Compared with other reconstruction methods, the proposed reconstruction method successfully addressed the issue of low-dose CT noising by further denoising the CT images before reconstruction. The denoising effect of low-dose CT images and the 3D reconstruction model were compared via experiments. [ABSTRACT FROM AUTHOR]

The social change and ideological change movement in modern China promoted the reform of women's footwear, and the concept of women's choice of footwear and wearing them had changed, which was the innovation of the concept of women's footwear. The transformation of traditional women to have an independent personality step by step was reflected from the bow shoes of women with bound feet to the diversification of footwear for women with natural feet, women from the humble era of small feet to fighting for equal status with men, and then to the consumption behavior and methods of women's footwear of different classes. Thus, the process of changing the concept of women's footwear was also deeply engraved with the evolutionary trajectory of modern civilized women. We adopt the research method of comparative demonstration combined with historical documents, compare the attitudes towards women's foot-binding, natural feet, women's social space and women's social behavior in ancient and modern societies, and summarize three directions for the transformation of the concept of women's footwear in modern times including equality, fashion and hygiene. Furthermore, we explore the reasons and impact of the transformation. The following conclusions are drawn: (i) from the perspective of the spatial sequence of concept change, the concept of women's footwear in Shanghai, Tianjin, Guangzhou and other open-minded cities was first innovated, which was accompanied by a series of new social behaviors, and soon the new concept and new behaviors spread to the surrounding urban and rural areas through the flow of people and goods; (ii)from the perspective of the impact of concept change, the shapes of women's shoes were constantly changing, the colors were coordinated and broke the tradition before, and the materials were comfortable and hygienic, which reflected the domestic shoe industry; (iii) from the perspective of women's life practice, women of different classes had different consumption behaviors and ways of footwear, but the standards of pursuing beauty and the goal of modernization were the same, which promoted the progress of new women's lives. The research on the concept of modern women's footwear is an important part of the new trend of clothing in modern times. From the perspective of modern women's footwear reform, we closely combine social reform and ideological change movements, analyze the changes in women's wearing and choosing shoes before and after they put their feet on, and reveal the scientific understanding of new women's footwear. The spread and popularity of this concept have accelerated the modern people's ability to accept new shoe styles and new clothing, and promoted the transformation and development of modern clothing. [ABSTRACT FROM AUTHOR]

With the aim of solving the problem of coal congestion caused by big coal blocks in underground mine scraper conveyors, in this paper we proposed the use of a YOLO-BS (YOLO-Big Size) algorithm to detect the abnormal phenomenon of coal blocks on scraper conveyors. Given the scale of the big coal block targets, the YOLO-BS algorithm replaces the last layer of the YOLOv4 algorithm feature extraction backbone network with the transform module. The YOLO-BS algorithm also deletes the redundant branch which detects small targets in the PAnet module, which reduces the overall number of parameters in the YOLO-BS algorithm. As the up-sampling and down-sampling operations in the PAnet module of the YOLO algorithm can easily cause feature loss, YOLO-BS improves the problem of feature loss and enhances the convergence performance of the model by adding the SimAM space and channel attention mechanism. In addition, to solve the problem of sample imbalance in big coal block data, in this paper, it was shown that the YOLO-BS algorithm selects focal loss as the loss function. In view of the problem that the same lump coal in different locations on the scraper conveyor led to different congestion rates, we conducted research and proposed a formula to calculate the congestion rate. Finally, we collected 12,000 image datasets of coal blocks on the underground scraper conveyor in Daliuta Coal Mine, China, and verified the performance of the method proposed in this paper. The results show that the processing speed of the proposed method can reach 80 fps, and the correct alarm rate can reach 93%. This method meets the real-time and accuracy requirements for the detection of abnormal phenomena in scraper conveyors. [ABSTRACT FROM AUTHOR]

Despite the recent success of neural network models in mimicking animal performance on various tasks, critics worry that these models fail to illuminate brain function. We take it that a central approach to explanation in systems neuroscience is that of mechanistic modeling, where understanding the system requires us to characterize its parts, organization, and activities, and how those give rise to behaviors of interest. However, it remains controversial what it takes for a model to be mechanistic, and whether computational models such as neural networks qualify as explanatory on this approach. We argue that certain kinds of neural network models are actually good examples of mechanistic models, when an appropriate notion of mechanistic mapping is deployed. Building on existing work on model-to-mechanism mapping (3M), we describe criteria delineating such a notion, which we call 3M++. These criteria require us, first, to identify an abstract level of description that is still detailed enough to be "runnable", and then, to construct model-to-brain mappings using the same principles as those employed for brain-to-brain mapping across individuals. Perhaps surprisingly, the abstractions required are just those already in use in experimental neuroscience and deployed in the construction of more familiar computational models — just as the principles of inter-brain mappings are very much in the spirit of those already employed in the collection and analysis of data across animals. In a companion paper, we address the relationship between optimization and intelligibility, in the context of functional evolutionary explanations. Taken together, mechanistic interpretations of computational models and the dependencies between form and function illuminated by optimization processes can help us to understand why brain systems are built they way they are. [ABSTRACT FROM AUTHOR]

The nonstationary time series prediction is challenging since it demands knowledge of both data transformation and prediction methods. This paper presents TSPred, a framework for nonstationary time series prediction. It differs from the mainstream frameworks since it establishes a prediction process that seamlessly integrates nonstationary time series transformations with state-of-the-art statistical and machine learning methods. It is made available as an R-package, which provides functions for defining and conducting time series prediction, including data pre(post) processing, decomposition, modeling, prediction, and accuracy assessment. Besides, TSPred enables user-defined methods, which significantly expands the applicability of the framework. [ABSTRACT FROM AUTHOR]

Zone A in Nanpu Sag of Bohai Bay has the characteristics of multiple provenances, multiple sedimentary systems, fast phase transition, many faults, a short fault distance, thin reservoirs and rapid lateral changes. At present, due to the low resolution of seismic data and thin sand layer of the target formation, it is difficult to depict the channel sand body, and it is also difficult to meet the requirements of accurately implementing low amplitude structures, reservoir prediction and well location deployment. When a seismic wave propagates in the stratum, it has the characteristics of multi-scale, multi-resolution and multi-directionality, while the Curvelet transform has the advantage of expressing these characteristics. In this paper, according to the geological characteristics and seismic response characteristics of continental thin interbedded strata in zone A, the seismic data are first transformed to the Curvelet domain. Then, the formation absorption and seismic wave attenuation are compensated in the Curvelet domain. Lastly, the data mentioned above are inversely transformed into the time–space domain. This paper presents the method and process of using the Curvelet transform to enhance the resolution of seismic data in thin interbedded strata. The application of a theoretical model and field data show that this method can effectively enhance the resolution of seismic data while maintaining a high signal-to-noise ratio. The innovative use of this method in zone A lays the foundation for the follow-up work of this structure. [ABSTRACT FROM AUTHOR]

In this action, we study a new integral transform identical to laplace, ZZ and Sumudu transforms are started. (ZMA)–Transform is asymptotic to ZZ transforms with some modification. The feature of this transform solves the differential equations (DE) smoothly and effectively without complications and with guaranteed results, moreover presented application for initial value problem (IVP) show that the transformation. In addition to this, I prepared a table for these transfers. [ABSTRACT FROM AUTHOR]

Currently, it remains one of the most challenging issues to distinguish brain functional networks of early mild cognitive impairment subjects (eMCIs) and normal control subjects (NCs). Unlike images, functional networks are non‐Euclidean data and not easily classified by dilated convolutional neural network (DCNN). To address this problem, we developed a sparse structure deep network embedding (SSDNE) method which transforms brain functional networks into a double‐channel image in eMCI classification. First, the eigenvector of each node in the functional network was obtained by SSDNE, and principal component analysis (PCA) was employed to sort the importance of eigenvectors. Next, two eigenvector groups with the highest contribution rate were extracted in turn and divided into several equal‐length intervals along its direction respectively, and the numbers of nodes that fall into the intervals were counted to obtain the corresponding two‐dimensional histograms. Then, the both histograms were stacked up and down into a double‐channel image. Finally, a double‐channel image was input into DCNN for feature learning to achieve final classification results. Experimental results show that, SSDNE performed better in maintaining the original structure of brain functional networks, and the transformed double‐channel image achieved comparably identifying results on eMCI classification compared with other network embedding algorithms. This novel method solved the problem that brain functional networks cannot be directly applied to convolutional neural networks for feature extraction and classification. Meanwhile, it can provide a reference for the early auxiliary diagnosis of Alzheimer's disease (AD). [ABSTRACT FROM AUTHOR]

Aiming to study the temperature distribution along buried pipelines containing hot fuel oil, a new large-scale laboratory is constructed from the perspective of the corresponding fluid thermophysical properties. Also, a modeling of the pipeline, and the soil around it, was performed along the pipeline for observation of all three modes of turbulent, laminarization, and laminar flow, which is validated by experimental results. Furthermore, the appropriate data are also gathered from the actual pipeline, 107 km of the 26? pipeline between Abadan Refinery and Mahshahr Port, and the results of the experiment and modeling are reconfirmed. The experiment shows that the viscosity and fluid density of fuel oil is strongly temperature-dependent. Many experiments are performed on the parameters affected by temperature according to their importance. The method chosen to simulate three flow modes along the pipeline shows less than 2% error in turbulent and laminar zones and reveals just a 3% error to experimental data in the laminar region. The maximum safe time during the stopping period of the pipeline and holding fuel oil in it is calculated based on the pour point of fuel oil. This time is critical for the real pipeline in sudden shutdown and is calculated 41 hours. [ABSTRACT FROM AUTHOR]

The past decade has witnessed the great success of deep learning in many disciplines, especially in computer vision and image processing. However, deep learning-based video coding remains in its infancy. We review the representative works about using deep learning for image/video coding, an actively developing research area since 2015. We divide the related works into two categories: new coding schemes that are built primarily upon deep networks, and deep network-based coding tools that shall be used within traditional coding schemes. For deep schemes, pixel probability modeling and auto-encoder are the two approaches, that can be viewed as predictive coding and transform coding, respectively. For deep tools, there have been several techniques using deep learning to perform intra-picture prediction, inter-picture prediction, cross-channel prediction, probability distribution prediction, transform, post- or in-loop filtering, down- and up-sampling, as well as encoding optimizations. In the hope of advocating the research of deep learning-based video coding, we present a case study of our developed prototype video codec, Deep Learning Video Coding (DLVC). DLVC features two deep tools that are both based on convolutional neural network (CNN), namely CNNbased in-loop filter and CNN-based block adaptive resolution coding. The source code of DLVC has been released for future research. [ABSTRACT FROM AUTHOR]

This research investigates the role of users' proactive personality when they mitigate the adverse impacts of ICT's (information and communication technologies') technostress in an experimental setting. Further, this study examines genuinely two types of individuals' proactive personality, i.e. confront and transform. Both types can handle ICT's technostress creators by different attitudes and behaviours. This article contributes to a novelty by inducing chaos theory. This inducement laid in the experimental setting that the users had been in a chaotic situation. Results of this research show that users' proactive personality mitigates the negative impact of ICT's technostress on their performance and satisfaction. This study found that the user's proactive personality, rested in a chaotic situation, does mitigate greatly. This research finds that users' performance and satisfaction are higher to the proactive personality verging to the transform than that of confront. It implies that information system managers should consider the ICT user's characteristics. Besides, it means that ICT's developer should make users do their innovativeness. [ABSTRACT FROM AUTHOR]

Vision is the main way for people to perceive and recognize the world. In this paper, four categories of the redundant information of video encoding, spatial redundancy, time redundancy, visual redundancy and statistical redundancy, are first introduced. Spatial redundancy is redundant information existing in static frames, time redundancy is the luminance and chrominance correlation between adjacent frames in the video sequence, visual redundancy is information that the human visual system cannot perceive, statistical redundancy is the expression redundancy of the information source symbols. Then the performance assessment of video coding are introduced. And the future development of video coding and conclusion are finally discussed in this paper. [ABSTRACT FROM AUTHOR]

Background: Cytokeratin-positive interstitial reticulum cells (CIRCs), which are a subgroup of fibroblastic reticular cells (FRCs), are known to be present in the lymph nodes. There have been only a few cases of tumors derived from CIRCs. Case presentation: We have reported a new case involving a CIRC tumor in a 75-year-old man and reviewed the literature. The resected mediastinal lymph nodes showed epithelial-like proliferation of large atypical round and polygonal epithelioid cells. The tumor cells expressed CK8, CK18, CAM5.2, AE1/AE3, epithelial membrane antigen, vimentin, fascin, and some FRC markers, which is consistent with the diagnosis of a CIRC tumor. Following chemotherapy, the CIRC tumor was observed to have responded very well and became difficult to confirm on imaging, but a small cell lung carcinoma developed 12 months later. Chemoradiotherapy was performed, but the patient passed away 29 months after the initial diagnosis. The autopsy revealed the recurrence of the CIRC tumor, residual small cell lung carcinoma, and a very small latent carcinoma of the prostate. The relapsed CIRC tumor cells had a spindle shape; they were highly pleomorphic and had invaded the superior vena cava. Conclusion: We first reported autopsy findings of CIRC tumors and demonstrated the transformation of the tumor from the epithelioid cell type to the spindle cell type. [ABSTRACT FROM AUTHOR]

Defects can be generated when growing diamond on heterogeneous substrates. The problem dampers the widespread use of diamond films. In this paper, a novel approach is proposed which grows diamond on graphene quasi-homogeneous epitaxial substrate. Results showed that high quality diamond was synthesized on a quasi homoepitaxial graphene substrate through sp2-sp3 hybridization and covalent bond transformation. Firstly, D peak-free graphene was synthesized on nickel metal surface. C–H and C C bonds were then exploited to produce dehydrogenation and coupling reaction which caused the transform of graphene to transform into diamond. In virtue of the superior intermiscibility and catalysis of nickel to carbon, few-layer graphene grew efficiently on nickel foil surface. An internal space microstructure network of carbon atoms was produced through different non-covalent interactions. At last, graphene is converted into diamond. This process can also be used to synthesize hydrophilic porous diamond film. It is a promising approach to the development of new graphene/diamond-based components in the future. [ABSTRACT FROM AUTHOR]

Supershear earthquakes, propagating faster than the Earth's shear wave velocity, can generate strong ground motion at distances far from the ruptured fault. Despite the hazards associated with these earthquakes, the exact fault properties that govern their occurrence are not well constrained. Although early studies associated supershear ruptures with simple fault geometries, recent dynamic rupture models have revealed a supershear transition mechanism over complex fault geometries such as fault stepovers. Here we present the first observation of a supershear transition on a fault stepover system during the 2017 Mw 7.7 Komandorsky Islands earthquake. Using a high‐resolution back‐projection technique, we find that the earthquake's rupture velocity accelerates from 2.1 to 5.0 km/s between two offset faults, demonstrating the viability of a new supershear transition mechanism occurring in nature. Given the fault complexity of the Earth's transform plate boundaries, this result may improve our understanding of supershear rupture processes and their associated hazards. Plain Language Summary: Earthquakes traveling faster than the shear wave velocity of the earth are occasionally observed in large strike‐slip events. These so‐called supershear earthquakes generate a potentially destructive shock wave analogous to the sonic boom of a supersonic aircraft. Although many supershear earthquakes are coincident with straight, continuous fault sections, we find that the 2017 Komandorsky Islands earthquake reached supershear speeds following a jump in rupture across two fault segments. The results of this study confirm that supershear ruptures can occur on complex fault systems, allowing the seismic hazard on similar fault systems to be better evaluated. Key Points: A supershear transition across a fault stepover is observed in nature for the first time during the 2017 Komandorsky Islands earthquakeThese results have implications for the assessment of seismic hazard on fault stepover systems at all transform plate boundaries [ABSTRACT FROM AUTHOR]

In this article, we solve in closed form a class of Fredholm integral equations and systems of Fredholm integral equations with nondegenerate kernels by using techniques of convolutions and generalized convolutions related to the Kontorovich-Lebedev, Fourier sine, and Fourier cosine integral transforms. [ABSTRACT FROM AUTHOR]

Frequency channelization is a fundamental signal processing operation employed across various domains, including communications and radio astronomy. The polyphase filterbank (PFB) represents an efficient and versatile means of channelization. When strict constraints are placed on the allowable spectral leakage between neighboring channels, an oversampled PFB design is advantageous. A helpful consequence of the oversampling is that inversion of the PFB to recover high temporal resolution is simplified and can be accomplished accurately using Fourier transforms. We describe this inversion approach and identify key design considerations. We examine the residual error and spectral/temporal leakage behavior when a channelizer and its corresponding inverter are cascaded, concluding that near-perfect reconstruction can be approached with appropriate selection of PFB and inverter design parameters. [ABSTRACT FROM AUTHOR]

Curvelets are multiscale and multidirectional operators that have many applications in image and data processing. Because of the effect of depth and source dimensions on the wavelength (or frequency content) of potential field anomalies, the study of magnetic data in the curvelet domain is of interest. In this paper, the consequences of transforming magnetic data to the curvelet domain are studied using synthetic models and real data for the first time. Based on the results of the theoretical models, we applied the method to airborne and ground magnetic survey data. We show the utility of the curvelet transformation for removing relatively large amounts of noise and its utility as a qualitative method for relatively robust delineation of magnetic sources, especially sources that are close, with overlapping anomalies. In the first step, the data in the curvelet domain are divided into scales or bands. Each scale is then split into multiple sub-bands that have different directional properties. We focus on the scale properties of magnetic data by studying the effects of debilitation or removing some scales in the curvelet domain. The first band (scale 1) of magnetic data in the curvelet domain corresponds to lower frequencies and contributes most to the energy of the signal. Thus, decreasing or removing this scale can highlight detailed (high-frequency) information. By contrast, the highest band has the highest frequency content and contains most of the noise. In this paper, we show that applying the inverse curvelet transform to the middle bands only (after deleting both low and high bands) gives the best results for the purpose of defining the horizontal locations of compact magnetic bodies. [ABSTRACT FROM AUTHOR]

A diverse, urban district's Personalized Learning Initiative (PLI), committed to transforming instructional tasks through integration of technology, created spaces for collaboration, voice, and choice for the PLI teachers and students. The teachers and students used various web-based technologies for collaboration with their peers, had more choices in teaching and learning and voice in making instructional decisions through meaningful integration of technology. The PLI's aims include 1) accelerating transformation of learning experiences for all students and preparing future teachers with necessary competencies for the 21st-century skills set and 2) designing learning opportunities and teaching practices that realize student's full potentials. [ABSTRACT FROM AUTHOR]

Liquid-fueled nuclear reactors, particularly molten salt reactors (MSRs), have recently gained significant interest in the advanced reactor community. As with all reactors, modeling and simulation are critical to advanced reactor design and licensing and will be required for MSR deployment. However, there are significant gaps in existing simulation capabilities for MSRs, particularly with the unique challenges of liquid-fueled systems (e.g., fission product transport). Furthermore, advanced reactor designers require near-term tools that are readily modifiable to perform design and analysis, including the ability to extend their analysis beyond the primary system to auxiliary systems. Transient Simulation Framework of Reconfigurable Models (TRANSFORM), a Modelica-based, system modeling library developed at Oak Ridge National Laboratory, is an advanced tool that can help meet some of the near-term needs of the advanced reactor community. This paper describes advanced system modeling criteria and presents TRANSFORM to the advanced reactor community by demonstration of system modeling capabilities and support of advanced analysis workflows, i.e., the Risk Analysis Virtual Environment (RAVEN) framework from Idaho National Laboratory, using the liquid-fueled Molten Salt Demonstration Reactor (MSDR) as a reference design. [ABSTRACT FROM AUTHOR]

• Exhaustive survey of methods for removal of Gaussian noise. • Categorisation of denoising methods into various domains. • Extensive experimental analysis of state-of-the-art techniques. At the crossing of the statistical and functional analysis, there exists a relentless quest for an efficient image denoising algorithm. In terms of greyscale imaging, a plethora of denoising algorithms have been documented in the literature, in spite of which the level of functionality of these algorithms still holds margin to acquire desired level of applicability. Quite often noise affecting the pixels in image is Gaussian in nature and uniformly deters information pixels in image. Based on some specific set of assumptions all methods work optimally, however they tend to create artefacts and remove fine structural details under general conditions. This article focuses on classifying and comparing some of the significant works in the field of denoising. [ABSTRACT FROM AUTHOR]

Radar is the most eminent device in the prolonged scattering era. The mechanisms involve using electromagnetic waves to take Synthetic Aperture Radar (SAR) images for long reaching. The process of setting edges is one of the important processes used in many fields, including radar images, which assists in showing objects such as mobile vehicles, ships, aircraft, and meteorological and terrain forms. In order to accurately identify these objects, their edges must be detected. Many old-style methods are used to isolate the edges but they do not give good results in the determination process. Conservative methods use an operator to detect the edges, such as the Sobel operator which is used to perform edge detection where the edge does not appear well. The proposed method which combines Ridgelet transform, Bezier curve and Sobel operator is used to detect edges very efficiently. Ridghelet transform resolves the harms in the wavelet transform and it can well detect the edges in images. Bezier curve can profit gradual variation of the data and their mutability. Hence, the efficiency of the edged image is improved and, when used with Sobel operator, the quality of the edge image become very good. The data show that the advocated method has superior fallouts over the Sobel edge detection and the wavelet method in both subjective and impartial experiments. While the Peak Signal to Noise Ratio(PSNR) values were equal to 9.3812, 9.8918, 9.6521 and 9.0743using the Sobel operator method and to10.2564, 10.7927, 10.5612and 10.8633 using the wavelet method, they were increased in the proposed method to 12.6542, 12.9514, 12.8574 and 12.3013 respectively. [ABSTRACT FROM AUTHOR]

This paper presents a novel adaptive predictive current controller (PCC) with improved flux estimator for a sensorless direct field oriented control (DFOC) induction motor (IM) drive. Classical PCC performance depends on the stator resistance of the motor which varies with temperature. In the proposed method, a discrete stator resistance estimator is developed to increase the robustness of the system toward stator resistance variations. An improved nonlinear discrete stator flux estimator is also developed to replace the pure integrator which reduces the initial value and dc offset problems. Sensorless operation of IM drive has advantages of reduced overall cost and increased reliability of motor operation. Dynamic and steady-state performances of the IM under different operating conditions are analyzed in MATLAB/Simulink as well as experimentally using dSPACE1104 controller and have been compared with conventional PCC. The simulation results of the classical and proposed methods are also validated experimentally. Smooth starting, reduced oscillations in speed and flux at low speed operation, fast speed and torque dynamics, robust operation of drive against load and variation in stator resistance, fast and smooth speed reversal are the main advantages of the proposed method over classical PCC-based DFOC IM drive. [ABSTRACT FROM AUTHOR]

Purpose: This study sought to use child and parent counselling to investigate aspects of maladjustment in parent–child and peer relationships of children who had been exposed to excessive private education in early life. Method: The Case study method was used for three children and their mothers, analyzing the process of transformation in awareness of the issue of excessive education, based on the content of the counselling session. Result: The process of change in awareness of problems due to their experiences of excessive private education experiences was divided into five domains and 13 categories. The participants showed that they were aware of the problems in their relationship and consequently made changes to their lives. Conclusion: This study found that counselling helped alleviate the aforementioned problems, which suggests the need for preventive interventions on parent–child relationship in the context of the negative effects of excessive private education. [ABSTRACT FROM AUTHOR]

We have recovered legacy 2D seismic data from the Kalahari Karoo Basin, Botswana, which show signatures associated with the coalbed-methane-bearing seams of the Mmamabula and Morupule formations. These deeply buried coal seams (∼ 500 m below surface) may represent a new alternative source of energy for the region. Prior to interpreting the seismic data, we improved imaging of the coal seams by attenuating noise with the curvelet transform. The data were transformed to the curvelet domain, and scale and angular direction thresholds were selected and applied, thereby removing previous processing artefacts and noise. The resulting denoised seismic data are characterised by a high signal-to-noise ratio, showing a clear continuity of the seismic reflections associated with the coal seams. We constrained the seismic interpretation with borehole logs, which confirmed the locations of the coal sequence at the top of the Mmamabula and Morupule formations. The curvelet-denoised seismic sections enable a more reliable mapping of the coal zone, which is displaced by major faults with throws of up to ∼ 500 m. Following these encouraging results, we emphasised the value of enhancing and reinterpreting legacy data, as it is a cost-effective and environmentally-friendly method for deep coal seam and mineral exploration. [ABSTRACT FROM AUTHOR]

We establish a duality for two factorization questions, one for general positive definite (p.d.) kernels K, and the other for Gaussian processes, say V. The latter notion, for Gaussian processes is stated via Ito-integration. Our approach to factorization for p.d. kernels is intuitively motivated by matrix factorizations, but in infinite dimensions, subtle measure theoretic issues must be addressed. Consider a given p.d. kernel K, presented as a covariance kernel for a Gaussian process V. We then give an explicit duality for these two seemingly different notions of factorization, for p.d. kernel K, vs for Gaussian process V. Our result is in the form of an explicit correspondence. It states that the analytic data which determine the variety of factorizations for K is the exact same as that which yield factorizations for V. Examples and applications are included: point-processes, sampling schemes, constructive discretization, graph-Laplacians, and boundary-value problems. [ABSTRACT FROM AUTHOR]

Abstract This paper continues the study of combinatorial properties of binary functions — that is, functions f : 2 E → ℂ such that f (0̸) = 1 , where E is a finite set. Binary functions have previously been shown to admit families of transforms that generalise duality, including a trinity transform, and families of associated minor operations that generalise deletion and contraction, with both these families parameterised by the complex numbers. Binary function representations exist for graphs (via the indicator functions of their cutset spaces) and indeed arbitrary matroids (as shown by the author previously). In this paper, we characterise degenerate elements – analogues of loops and coloops – in binary functions, with respect to any set of minor operations from our complex-parameterised family. We then apply this to study the relationship between binary functions and Tutte's alternating dimaps, which also support a trinity transform and three associated minor operations. It is shown that only the simplest alternating dimaps have binary representations of the form we consider, which seems to be the most direct type of representation. The question of whether there exist other, more sophisticated types of binary function representations for alternating dimaps is left open. [ABSTRACT FROM AUTHOR]

The molten salt reactor (MSR), being a liquid-fueled reactor, exhibits a strong coupling between neutronics and thermal hydraulics originating from the simultaneous utilization of the fuel as the coolant. Analysis of the dynamic behavior of MSRs thus necessitates the use of coupled multiphysics tools. This work leverages the multiphysics capabilities of the Modelica-based, open-source component library Transient Simulation Framework of Reconfigurable Modules (TRANSFORM) and demonstrates its ability to simulate the behavior of an MSR with the focus on modeling the Molten Salt Reactor Experiment (MSRE). The model employs 1D thermal-hydraulic components with a coarse radial and axial discretization of the active core region approximating the design of the MSRE. The power generation within each node is determined by neutron point kinetics which are modified to account for the effects of fuel circulation. Using the developed model, neutronic and thermal-hydraulic behavior under steady-state conditions is characterized and compared to experimental data and alternative computational codes. Some discrepancies are found but most of them are explained by the modeling choices and uncertainties in input data. Performance of the model under transient conditions is then investigated by simulating experiments conducted on the MSRE; the results are again benchmarked against reference data. Overall, good agreement is attained. • Leveraging Modelica/TRANSFORM to simulate MSR behavior • Coupling of 1D thermal hydraulics and distributed model of modified point kinetics • Steady-state and transient benchmarking of MSRE model. [ABSTRACT FROM AUTHOR]

Potential risk of endocrine disrupting compounds on non-target organisms has received extensive attentions in recent years. The present work aimed to investigate the behavior and effect of a synthetic steroid estrogen quinestrol in duckweed Spirodela polyrhiza L. Experimental results showed that quinestrol could be uptaken, accumulated, and biotransformed into 17 α-ethynylestradiol in S. polyrhiza L. The accumulation of quinestrol had a positive relation to the exposure concentration. The bioaccumulation rate was higher when the duckweed was exposed to quinestrol solutions at low concentrations than at high concentration. While the transformation of quinestrol showed no concentration-dependent manner. Quinestrol reduced the biomass and pigment content and increased superoxide dismutase and catalase activities and malondialdehyde contents in the duckweed. The results demonstrated that quinestrol could be accumulated and biotransformed in aquatic plant S. polyrhiza L. This work would provide supplemental data on the behavior of this steroid estrogen compound in aquatic system. [ABSTRACT FROM AUTHOR]

Trifluoroacetic acid (TFA) was measured at an urban site in Beijing from April 2013 to April 2016 and examined its characteristics and particle/gas distributions. The average monthly atmospheric TFA concentration fluctuated significantly and presented marked seasonal variations. The concentration levels of gas-phase TFA were significantly higher in spring and summer than in fall and winter. The PM 2.5 mass concentration and ambient temperature were important factors affecting the concentration of particulate-phase TFA. Hence, at higher PM 2.5 concentrations and lower temperatures, atmospheric TFA tended to be enriched in particulate matter. Our findings suggest that the percentage of gas-phase TFA in Beijing is higher than that in the steady state; thus, gas-phase TFA can still be transformed to the particulate phase and increase the contribution of TFA to haze formation. [ABSTRACT FROM AUTHOR]

Transform, as one of the most important modules of mainstream video coding systems, seems very stable over the past several decades. However, recent developments indicate that bringing more options for transform can lead to coding efficiency benefits. In this paper, we go further to investigate how the coding efficiency can be improved over the state-of-the-art method by adapting a transform for each block. We present a variable block-sized signal-dependent transforms (SDTs) design based on the High Efficiency Video Coding (HEVC) framework. For a coding block ranged from $4\times4$ to $32\times32$ , we collect a quantity of similar blocks from the reconstructed area and use them to derive the Karhunen–Loève transform. We avoid sending overhead bits to denote the transform by performing the same procedure at the decoder. In this way, the transform for every block is tailored according to its statistics, to be signal-dependent. To make the large block-sized SDTs feasible, we present a fast algorithm for transform derivation. Experimental results show the effectiveness of the SDTs for different block sizes, which leads to up to 23.3% bit-saving. On average, we achieve BD-rate saving of 2.2%, 2.4%, 3.3%, and 7.1% under AI-Main10, RA-Main10, RA-Main10, and LP-Main10 configurations, respectively, compared with the test model HM-12 of HEVC. The proposed scheme has also been adopted into the joint exploration test model for the exploration of potential future video coding standard. [ABSTRACT FROM AUTHOR]

Objective To migrate and reconstruct the hospital network to solve its problems in obsolete equipment, network architecture, software configuration and etc. Methods A network migration and reconstruction scheme was proposed based on the physical environment of one hospital with two addresses as well as some network technologies such as open shortest path first (OSPF) protocol, port trunking and stacking. Results The network migration and reconstruction were implemented as desired, and the core switching network was upgraded to ten gigabit Ethernet. Conclusion The hospital network is optimized in architecture, software configuration, reliability and performances, and lays a foundation for hospital informatization. [ABSTRACT FROM AUTHOR]

This study introduces the theory of the Laplace wavelet transform (LWT). The Laplace wavelets are a generalization of the second-order under damped linear time-invariant (SOULTI) wavelets to the complex domain. This generalization produces the mother wavelet function that has been used as the Laplace pseudo wavelet or the Laplace wavelet dictionary. The study shows that the Laplace wavelet can be used to transform signals to the time-scale or time-frequency domain and can be retrieved back. The properties of the new generalization are outlined, and the characteristics of the companion wavelet transform are defined. Moreover, some similarities between the Laplace wavelet transform and the Laplace transform arise, where a relation between the Laplace wavelet transform and the Laplace transform is derived. This relation can be beneficial in evaluating the wavelet transform. The new wavelet transform has phase and magnitude, and can also be evaluated for most elementary signals. The Laplace wavelets inherit many properties from the SOULTI wavelets, and the Laplace wavelet transform inherits many properties from both the SOULTI wavelet transform and the Laplace transform. In addition, the investigation shows that both the LWT and the SOULTI wavelet transform give the particular solutions of specific related differential equations, and the particular solution of these linear time-invariant differential equations can in general be written in terms of a wavelet transform. Finally, the properties of the Laplace wavelet are verified by applications to frequency varying signals and to vibrations of mechanical systems for modes decoupling, and the results are compared with the generalized Morse and Morlet wavelets in addition to the short time Fourier transform’s results. [ABSTRACT FROM AUTHOR]

Wireless image sensor networks are capable of sensing, processing and transmitting the image in hard-to-access regions without expensive network infrastructure and will have great contribution in Internet of Things. These networks are resource constraint systems with limited memory, energy, processing speed and bandwidth. Low computational energy and communication energy will improve the lifetime of these resource-limited networks. In this paper, an energy-efficient low-memory and low-bitrate image coding is designed exclusively for low-power camera-equipped sensor node. The performance of the proposed image coder is analysed in terms of bitrate, image quality, memory size and energy consumption. Experiments are carried out with Atmel ATmega128 processor. The experimental results show that this system consumes only 0.23% of energy consumed by true Discrete Cosine Transform-based Joint Photographic Experts Group (JPEG) standard and offers reasonable image quality suitable for visual perception at low bitrate. This system requires only 19% of memory required by standard JPEG. [ABSTRACT FROM AUTHOR]

Thermal imaging is an increasingly widespread alternative to other imaging methods. As a supplementary method in diagnostics, it can be used both statically and with dynamic temperature changes. The paper proposes a new image analysis method that allows for the acquisition of new diagnostic information as well as object segmentation. The proposed serpentine analysis uses known and new methods of image analysis and processing proposed by the authors. Affine transformations of an image and subsequent Fourier analysis provide a new diagnostic quality. The method is fully repeatable and automatic and independent of inter-individual variability in patients. The segmentation results are by 10% better than those obtained from the watershed method and the hybrid segmentation method based on the Canny detector. The first and second harmonics of serpentine analysis enable to determine the type of temperature changes in the region of interest (gradient, number of heat sources etc.). The presented serpentine method provides new quantitative information on thermal imaging and more. Since it allows for image segmentation and designation of contact points of two and more heat sources (local minimum), it can be used to support medical diagnostics in many areas of medicine. [ABSTRACT FROM AUTHOR]

Using a three-dimensional (3D) seismic reflection dataset from the Shipwreck Trough, offshore Otway Basin, southern Australia, we aim to characterise and understand the structural evolution of the Shipwreck Fault Zone (SFZ) and associated extensional structures. The SFZ is a key structural element of the Otway Basin, which is a NW striking, Upper Jurassic-Cenozoic, rift-to-passive margin basin that formed due to the breakup of Australia and Antarctica. The SFZ marks the transition from the major southern margin rift system to the west and the oceanic-continental transform margin to the SE. The SFZ formed and bounds the Shipwreck Trough on the eastern side and is interpreted as a N S striking transtensional fault zone, representing the northern en echelon extension of the transform margin to the south. The Shipwreck Trough is the downward thrown (western) side of the SFZ and is host to an array of horst and half-graben structures, two of which contain the producing Geographe and Thylacine gas fields. The Shipwreck Trough and SFZ are imaged by the Investigator 3D seismic dataset, which has previously been studied to conduct 2D restorations and interpret the timing, magnitude, orientation and nature of the structural events of the Shipwreck Trough. Our study adds to this previous research by using spectral decomposition and coherence volumes to further characterise the SFZ (and associated igneous features), basement structural elements and Late Cretaceous horst and half-graben structures. We have identified examples of releasing bend, releasing jog and restraining jog structures along the SFZ that are indicative of sinistral transtensional deformation and have highlighted areas of increased basement fault block relief, which have driven extensional faulting in the cover. We have also conducted throw-distance and throw-depth analysis on four horst and half-graben structures and shown that the associated normal faults have had continuous Late Cretaceous growth with the structures being formed through incidental linkage of normal fault segments. Finally, our two-way-time (TWT) and isochronal mapping of the entire 3D survey shows the development of the Late Cretaceous rifting event in the Shipwreck Trough and highlights numerous other structural closures similar to (and with close vicinity of) the Thylacine and Geographe gas fields, providing implications for prospectivity. [ABSTRACT FROM AUTHOR]

The Fourier transform (FT), the nonlinear least-squares algorithm (NLSA), and eigenvalue decomposition algorithm (EDA) are used to evaluate the phase field in depth-resolved wavenumber-scanning interferometry (DRWSI). However, because the wavenumber series of the laser's output is usually accompanied by nonlinearity and mode-hop, FT, NLSA, and EDA, which are only suitable for equidistant interference data, often lead to non-negligible phase errors. In this work, a compressed-sensing method for DRWSI (CS-DRWSI) is proposed to resolve this problem. By using the randomly spaced inverse Fourier matrix and solving the underdetermined equation in the wavenumber domain, CS-DRWSI determines the nonuniform sampling and spectral leakage of the interference spectrum. Furthermore, it can evaluate interference data without prior knowledge of the object. The experimental results show that CS-DRWSI improves the depth resolution and suppresses sidelobes. It can replace the FT as a standard algorithm for DRWSI. [ABSTRACT FROM AUTHOR]

Transformers are known as one of the most important equipment in power system transmission and distribution networks. Partial Discharge (PD) measurement and PRPD interpretation is a powerful tool to monitor the situation and evaluating the risk of power transformer failure. Multiple discharge sources affect the accuracy of interpretation of PRPD. This paper presents a PD signal separation algorithm based on extraction of high level image features. The time-frequency S transform (ST) is applied to the PD signal waveforms, acquired by digital detection instruments at 100 MS/s. The resultant ST matrix is then converted to gray scale image from which high level features are extracted using Bag of Words (BoW). Principle component analysis (PCA) transform is applied to BoW feature to reduce the dimension of features. Calinski-Harabasz criterion is calculated to identify the number of active sources and then Gaussian mixture model (GMM) clustering is used to discover clusters in the feature space. The proposed separation algorithm is examined with mixed current impulse signals acquired from PD experiments on artificial multi-defect models. The separation results indicate that the proposed algorithm is effective for identifying the number of active sources and separating mixed PD signals initiated from multiple sources. [ABSTRACT FROM AUTHOR]

Previously, the synthesis of reversible and quantum permutative circuits based on products of Exclusive-OR (EXOR) sums of inputs (POE) was explored as an approach to reduce quantum cost. Herein, the mathematical representation used in POE expressions is formally detailed and contrasted with the pseudoproduct-based theory of Luccio and Pagli. The theory and practice of product transformation, or computation of equivalent POE expressions, is presented. To demonstrate the generality of the mathematical representations outside of the reversible domain, a new method to synthesize incompletely specified functions as EXOR-AND-OR circuits is introduced. The method is heuristic. It first uses spectral information from the Walsh–Hadamard transform to compute a set of POE implicants for a function, and then uses product transformation to minimize both the total number of literals and unique EXOR sums (ignoring polarity) used in the POE implicants. The product transformation minimization extends to multioutput functions. The new method has no performance guarantees, i.e., it does not have a fallback mode of minimum or near-minimum sum of products; therefore, it is suited to a tournament synthesis approach. When synthesizing benchmark functions of up to 26 inputs, the new method is shown to typically produce lower cost circuits than heuristic pseudoproduct-based methods. [ABSTRACT FROM PUBLISHER]

Since few decades ago, Discrete Cosine Transform (DCT) based digital image signal compression had been adopted as the JPEG international standard. Later, Wavelet Transform (WT) has replaced the DCT and its being applied in medical image compression. JPEG 2000, the international standardization of WT is using separable lifting structure where the multidimensional image signal is transformed separately in its horizontal and vertical direction. Besides that, each process is realized by cascading in lifting calculation. However, the necessity of waiting for previous step before calculating to the next step will make the overall delay time become longer. The delay time between input and output of WT is reduced as the proposed method reduces its lifting steps. Since the lifting step contains a rounding operation, variance of the rounding noise generated due to the rounding operation inside the transform is reduced. In this paper, unlike the conventional separable structure, the proposed non-separable structure reduces the rounding noise inside the transform, which will lead to the increasing of coding performance. The proposed wavelet transform has a merit that its output signal, apart from the rounding noise, is exactly the same as the conventional separable structure which is a cascade of 1D structure. As a result of experiments, it was observed that the proposed method reduces the rounding noise as well as increases the performance of data compression of various 4D input signals. [ABSTRACT FROM AUTHOR]

For a minimal surface in a 5-dimensional space form, we give transforms to get another minimal surface in another 5-or 4-dimensional space form. [ABSTRACT FROM AUTHOR]

This survey presents the broad range of research on using wavelets in the analysis and design of dynamic systems. Though wavelets have been used with all types of systems, the major focus of this survey is mechanical and electromechanical systems in addition to their controls. However, the techniques presented can be applied to any category of dynamic systems such as economic, biological, and social systems. Wavelets can be classified into three different types: orthogonal, biorthogonal, and pseudo, all of which are employed in dynamic systems engineering. Wavelets-based methods for dynamic systems applications can be divided into vibrations analysis and systems and control analysis. Wavelets applications in vibrations extend to oscillatory response solutions and vibrations-based systems identification. Also, their applications in systems and control extend to time–frequency representation and modeling, nonlinear systems linearization and model reduction, and control design and control law computation. There are serious efforts within systems and control theory to establish time–frequency and wavelets-based Frequency Response Functions (FRFs) parallel to the Fourier-based FRFs, which will pave the road for time-varying FRFs. Moreover, the natural similarity of wavelets to the representation of neural networks allows them to slip into neural-networks-based and fuzzy-neural-networks-based controllers. Additionally, wavelets have been considered for applications in feedforward and feedback control loops for computation, analysis, and synthesis of control laws. [ABSTRACT FROM AUTHOR]