Miracle-dz/UniFAR-FTUs huggingface dataset:
Review on Texture Feature Extraction and Description Methods in Content-Based Medical Image Retrieval

Texture feature extraction and description is one of the important research contents in content-based medical image retrieval. The chapter first proposes a framework of content-based medical image retrieval system. It then analyzes the important texture feature extraction and description methods further, such as the co-occurrence matrix, perceptual texture features, Gabor wavelet, and so forth. Moreover, the chapter analyzes the improved methods for these methods and demonstrates their application in content-based medical image retrieval.
A Joint Source Channel Coding Approach to Delivery of Digital Images over CDMA 800 MHz Indoor Wireless Rayleigh Fading Channels

The following thesis developed in the area of Electrical Engineering and Telecommunications is aimed at improving current CDMA wireless network capabilities specifically targeting the transmission of JPEG compressed data with the possibility of a continued investigation in the transmission of MPEG video format. The aim or objective is to generate a solution to current transmission problems faced in 3rd generation CDMA networks where band limited transmission limits the capabilities of the network in delivering large data files such as image or video adequately. The rising importance in expanding network capabilities for CDMA networks, in this case for image transmission, is evident because of several factors including the following: • One of these factors is the increasing popularity of CDMA since its creation in 1995. In the cellular branch alone, there are over an estimates 106 million users utilizing a CDMA based network. This rapid increase is due to the fact that CDMA is able to support multiple users on one frequency channel, as will be discussed later. • Secondly and more importantly, the growing demand for image and video transmission generated by increasing multimedia usage has created the recent need to transmit video data over this and other types of wireless networks. In particular, the following thesis is thus aimed at improving the JPEG image compression algorithm for an 800MHz CDMA Cellular wireless network. In order to increase the efficiency of current image transmission over CDMA networks this thesis proposes jointly designing the source and channel code to generate an enhanced image compression algorithm. In order to accomplish this we will utilize a Rayleigh Fading Model to simulate the channel over which we will be transmitting and then include this information into the compression algorithm; our goal being to manipulate the image compression algorithm to improve image transmission over a specific channel and medium (i.e. An 800MHz wireless network). Furthermore, given that our expected results are met, we can also review the efficiency (bit compression) of our algorithm for transmission and hence review new possibilities for increased error correction in the transmission of image and video data. In addition, as mentioned before, an ongoing investigation in this area using the ideas presented in this paper applied to the MPEG compression algorithm could lead to an enhanced algorithm for video transmission over the same medium.
Guided Transcoding for Next-Generation Video Coding (HEVC)

Video content is the dominant traffic type on mobile networks today and this portion is only expected to increase in the future. In this thesis we investigate ways of reducing bit rates for adaptive streaming applications in the latest video coding standard, H.265 / High Efficiency Video Coding (HEVC). The current models for offering different-resolution versions of video content in a dynamic way, so called adaptive streaming, require either large amounts of storage capacity where full encodings of the material is kept at all times, or extremely high computational power in order to regenerate content on-demand. Guided transcoding aims at finding a middle-ground were we can store and transmit less data, at full or near-full quality, while still keeping computational complexity low. This is achieved by shifting the computationally heavy operations to a preprocessing step where so called side-information is generated. The side-information can then be used to quickly reconstruct sequences on-demand -- even when running on generic, non-specialized, hardware. Two method for generating side-information, pruning and deflation, are compared on a varying set of standardized HEVC test sequences and the respective upsides and downsides of each method are discussed.
Agent-Mediated Knowledge Acquisition for User Profiling

This chapter presents a tool for knowledge acquisition for user profiling in electronic commerce. The knowledge acquisition in e-commerce is a challenging task that requires specific tools in order to facilitate the knowledge transfer from the user to the system. The proposed tool is based on a hierarchical user model and is agent-based. The architecture of the tool incorporates four software agents: processing agent maintaining the user profile, validating agent interacting with the user when information validation is needed, monitoring agent monitoring the effects of the changes made to the user profile, and a filtering agent ensuring the safe information exchange with other software.
Entity extraction for people profile matching

With the rise in social media platform usage, the average number of people profiles has increased as well. The fact that people have social media profiles on multiple platforms reveals the interesting problem of matching them in order to aggregate all the profiles in one. As a significant part of these profiles are made of unstructured text, extracting labeled data using an entity extraction system can lead to an increase in precision and recall. This thesis documents the effects a bootstrapped pattern learning approach can have on a profile matching system. The entity extraction system is trained in a distributed manner on a big amount of data, in order to generate as many quality patterns as possible.
Upping the Ante: Video and Tagging Software to Improve Teacher Candidate Performance

This pilot study resulted in changes to how we support and understand the teacher candidate learning process. Student teachers recorded videos of several teaching segments and later both researchers and student teachers utilized software to identify, tag, and analyze teaching performances. The study was based on the following assertions: teacher candidates need to own their professional growth, and teaching behaviors can be identified, rated for proficiency and analyzed as a collection of techniques to enhance student learning. The findings suggested that use of the software has expanded our ability to document candidate performance and proficiency. Candidates not only became critically self-evaluative but also identified missed opportunities in teaching segments.
Error Concealment Techniques in H.264/AVC Standard for wireless video transmission

Problem Statement: One of the limitations within the mobile networks is the low transmission bit rate which demands the reduction of the video resolution and a high efficient video compression technique such as H.264 / AVC video compression standard. This codec is the newest standard, which provides a high compression gain. The video compression is based on the elimination of the spatial and temporal redundancies within the video sequence. This makes the video stream more vulnerable against bit stream errors. These errors can have the effect of degrading the quality of the received video.
Chaotic prediction of carbon-monoxide utilization ratio in the blast furnace

The carbon-monoxide utilization ratio (CMUR) is a significant factor for the energy consumption in the blast furnace (BF). CMUR cannot be well controlled on the spot due to the low predication in the previous research. In this paper, a chaotic prediction method is presented to forecast the variation tendency of CMUR. Firstly, CMUR time series sample data are acquired from two representative BFs as the sample. Then, the phase space reconstruction technology is employed to reconstruct the phase space of CMUR. Finally, based on the obtained value of the embedded dimension m and the lag-time τ in the CMUR's reconstructed phase space, the CMUR can be predicted by using chaos radial basis function (RBF) prediction method. The result shows the chaotic prediction model has high precision rate, which builds the foundation and guidance for the control of CMUR, so as the spot operation of BF.
African Development Report 2001

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Image processing in treatment of digitized virtual Chinese No. 1 female

Objective: To test the feasibility of applying the existing image processing software in treatments of the dataset of the digitized Chinese No. 1 female, such as 3d reconstruction, image segmentation and finite element modeling. Methods: Experimental studies were done on the dataset of the digitized Chinese No. 1 female by using such methods as equal space drawing out, format switch, image segmentation, 3d reconstruction, 3d display and finite element modeling. Result: Several editions of dataset were edited; image segmentation was realized; coronal and sagittal images were reconstructed; the static display was animated; real time 3d display was realized; the regional finite element modeling was set up based on CT images. Conclusion: The different compressed or converted editions of the dataset of the digitized virtual Chinese No. 1 female can meet the given requirements of morphological 3d reconstruction, image segmentation, and real time 3d display, and the skeleton models which are reconstructed on the basis of CT, MRI and sectional images permit the research on the construction of finite element modeling.
Automating meta-algorithmic analysis and design

Sophisticated empirical methods based upon automated experimental analysis techniques drive the development of high-performance solvers for an increasing range of problems from industry and academia. However, tools implementing these methods are often difficult to develop and to use. This thesis describes work towards addressing this issue. First, we develop a formal description of meta-algorithmic problems, and use it as the basis for a framework supporting the development and application of a broad class of automated algorithm analysis and design techniques. Second, we describe the High-performance Algorithm Laboratory (HAL), an extensible software implementa- tion of this framework that provides developers and users of automated empirical techniques with support for distributed execution, remote monitoring, data management, and statistical analysis of results. We use HAL to construct a suite of interoperable tools that implement a variety of automated empirical techniques, and demonstrate our approach by conducting a sequence of increasingly com- plex analysis and design tasks on state-of-the-art solvers for Boolean satisfiability and mixed-integer programming problems.
Smoothing methods for the treatment of digital texts

ONTARE. REVISTA DE INVESTIGACION DE LA FACULTAD DE INGENIERIA This article describes the exploration task known as smoothing for statistical language representation. It also reviews some of the state- of-the-art methods that improve the representation of language in a statistical way. Specifically, these reported methods improve statistical models known as N-gram models. This paper also shows a method to measure models in order to compare them.
DNA Bar-Coding: A Novel Approach for Identifying an Individual Using Extended Levenshtein Distance Algorithm and STR Analysis

DNA bar-coding is a technique that uses the short DNA nucleotide sequences from the standard genome of the species in order to find and group the species to which it belongs to. The species are identified by their DNA nucleotide sequences in the same way the items are recognized and billed in the supermarket using barcode scanner to scan the Universal Product Code of the items. Two items may look same to the untrained eye, but in both cases the barcodes are distinct. It was possible to create DNA-barcodes to characterize species by analysing DNA samples from fish, birds, mammals, plants, and invertebrates using Smith-waterman and Needleman-Wunsch algorithm. In this work we are creating human DNA barcode and implementing Extended Levenshtein distance algorithm along with STR analysis that uses less computation time compared to the previously used algorithms to measure the differential distance between the two DNA nucleotide sequences through which an individual can be identified.
The Neural Networks Modeling of Switched Reluctance Motor and its Arithmetic

In order to avoid the problems of slow rate of convergence,easy falling into local minimum and difficulty in determining the number of hidden nodes of the feed-forward neural network in BP algorithm,a fast self-configuring arithmetic was used to train BP neural networks.This arithmetic was the integration of Levenberg-Marquardt arithmetic and the improved self-configuring arithmetic.Furthermore,the nonlinear model of Switched Reluctance Motor(SRM) was developed,which made use of the measured accurate flux-linkage data and the nonlinear mapping ability of BP neural network based on fast self-configuring arithmetic.This neural network model was of fast training convergence,generalization and small network scale handy for real-time control.The accuracy of this model was proved with experiment results.This model will help to optimize energy conversion and will reduce torque ripples.
THE DUSTIEST POST-MAIN SEQUENCE STARS IN THE MAGELLANIC CLOUDS

Using observations from the Herschel Inventory of The Agents of Galaxy Evolution (HERITAGE) survey of the Magellanic Clouds (MC), we have found 35 evolved stars and stellar end products that are bright in the far-infrared. These 28 (LMC) and 7 (SMC) sources were selected from the 529 evolved star candidates in the HERITAGE far-infrared point source catalogs. Our source identification method is based on spectral confirmation, spectral energy distribution characteristics, careful examination of the multiwavelength images and includes constraints on the luminosity, resulting in a thoroughly vetted list of evolved stars. These sources span a wide range in luminosity and hence initial mass. We found 13 low- to intermediate-mass evolved stars, including asymptotic giant branch (AGB) stars, post-AGB stars, planetary nebulae, and a symbiotic star. We also identify 10 high mass stars, including 4 of the 15 known B[e] stars in the MC, 3 extreme red supergiants that are highly enshrouded by dust, a Luminous Blue Variable, a Wolf–Rayet star, and two supernova remnants. Further, we report the detection of 9 probable evolved objects which were previously undescribed in the literature. These sources are likely to be among the dustiest evolved objects in the MC. The Herschel emission may either be due to dust produced by the evolved star or it may arise from swept-up interstellar medium material.
Magnetism and Superconductivity in the Two-Dimensional 16-Band d– p Model for Iron-Based Superconductors

The electronic states of the Fe 2 As 2 plane in iron-based superconductors are investigated on the basis of the two-dimensional 16-band d – p model which includes the Coulomb interaction on a Fe site: the intra- and inter-orbital direct terms U and U ', the Hund's coupling J and the pair-transfer J '. Using the random phase approximation (RPA), we obtain the magnetic phase diagram including the stripe and the incommensurate order on the U '– J plane. We also solve the superconducting gap equation within the RPA and find that, for large J , the most favorable pairing symmetry is extended s -wave whose order parameter changes its sign between the hole pockets and the electron pockets, while it is d x y -wave for small J .
Dust production in debris discs: constraints on the smallest grains

Context. The surface energy constraint puts a limit on the smallest fragment ssurf that can be produced after a collision. Based on analytical considerations, this mechanism has been recently identified as being having the potential to prevent the production of small dust grains in debris discs and to cut off their size distribution at sizes larger than the blow-out size. Aims. We numerically investigate the importance of this effect to find out under which conditions it can leave a signature in the small-size end of a disc’s particle size distribution (PSD). An important part of this work is to map out, in a disc at steady-state, what is the most likely collisional origin for μm-sized dust grains, in terms of the sizes of their collisional progenitors. Methods. For the first time, we implement the surface energy constraint into a collisional evolution code. We consider a typical debris disc extending from 50 to 100 au and two different stellar types: sun-like and A star. We also consider two levels of stirring in the disc: dynamically “hot” (⟨e⟩ = 0.075) and “cold” (⟨e⟩ = 0.01). In all cases, we derive ssurf maps as a function of target and projectile sizes, st and sp, and compare them to equivalent maps for the dust-production rate. We then compute disc-integrated profiles of the PSD and estimate the imprint of the surface energy constraint. Results. We find that the (sp,st) regions of high ssurf values do not coincide with those of high dust production rates. As a consequence, the surface energy constraint generally has a weak effect on the system’s PSD. The maximum ssurf-induced depletion of μm-sized grains is ~30% and is obtained for a sun-like star and a dynamically “hot” case. For the e = 0.01 cases, the surface energy effect is negligible compared to the massive small grain depletion that is induced by another mechanism: the “natural” imbalance between dust production and destruction rates in low-stirring discs.
Wave propagation in infinite nonlinear acoustic metamaterial beam by considering the third harmonic generation

Nonlinear acoustic metamaterial (NAM) initiates new fields for controlling elastic waves. In this work, the flexural wave propagation in the half-infinite NAM beam consisting of periodic Duffing resonators is reported by considering the third harmonic generation (THG). Different analytical methods are proposed to describe the wave propagation in the equivalent homogenous medium. Then their effectiveness and accuracy are demonstrated in comparison with the finite element methods. We unveil analytically and numerically extensive physical properties of the strongly nonlinear AM, including the nonlinear resonance in a cell, the effective density, nonlinear locally resonant (NLR) bandgap, propagations and couplings of the fundamental and the third harmonics. These characteristics are highly interrelated, which facilitates the prediction of functionalities. In the near field, the identical bifurcation frequency of these features acts as the start frequency of the NLR bandgap for fundamental waves, whose width is narrower for a stronger nonlinearity. While in the far field, the NLR bandgap characterizes a distance-amplitude-dependent behavior leading to a self-adaptive bandwidth. Moreover, the transmission in the passband of the infinite NAM is different from the chaotic band effect of finite NAMs, and it is influenced by the shifted NLR gap. Our work will promote future studies and constructions of NAMs with novel properties.
Benford's law detects quantum phase transitions similarly as earthquakes

A century ago, it was predicted that the first significant digit appearing in a data would be nonuniformly distributed, with the number one appearing with the highest frequency. This law goes by the name of Benford's law. It holds for data ranging from infectious-disease cases to national greenhouse gas emissions. Quantum phase transitions are cooperative phenomena where qualitative changes occur in many-body systems at zero temperature. We show that the century-old Benford's law can detect quantum phase transitions, much like it detects earthquakes. Therefore, being certainly of very different physical origins, seismic activity and quantum cooperative phenomena may be detected by similar methods. The result has immediate implications in precise measurements in experiments in general, and for realizable quantum computers in particular. It shows that estimation of the first significant digit of measured physical observables is enough to detect the presence of quantum phase transitions in macroscopic systems.
The Global and Radial Stellar Mass Assembly of Milky Way-sized Galaxies

We study the global and radial stellar mass assembly of eight zoomed-in Milky Way (MW)-sized galaxies produced in hydrodynamics cosmological simulations. The disk-dominated galaxies (four) show a fast initial stellar mass growth in the innermost parts, driven mostly by in situ star formation (SF), but since z ∼ 2−1, the SF has entered a long-term quenching phase. The outer regions follow this trend but more gently, as they are more external. As a result, the radial stellar mass growth is highly inside-out due to both inside-out structural growth and inside-out SF quenching. The half-mass radius evolves fast; for instance, (z = 1) < 0.5 (z = 0). Two other runs resemble lenticular galaxies. One also shows a pronounced inside-out growth, and the other one presents a nearly uniform radial mass assembly. The other two galaxies suffered late major mergers. Their normalized radial mass growth histories (MGHs) are very close, but with periods of outside-in assembly during or after the mergers. For all of the simulations, the archaeological radial MGHs calculated from the z = 0 stellar particle age distribution are similar to current MGHs, which shows that the mass assembly by ex situ stars and the radial mass transport do not significantly change their radial mass distributions. Our results agree qualitatively with observational inferences from the fossil record method applied to a survey of local galaxies and from look-back observations of progenitors of MW-sized galaxies. However, the inside-out growth mode is more pronounced, and the growth is faster in simulations than in observational inferences.
Dispersion of resonant Raman peaks of CO and OH in SnO2, Mo1−xFexO2 thin films and SiO2 bulk glass

Resonance Raman (RR) peaks of CO and OH stretching modes and their higher harmonics have been observed superimposed on the photoluminescence (PL) spectrum of SnO2 thin films. Commercial fluorine doped SnO2 thin films deposited by sputtering on glass and SnO2 thin films deposited on Si by laser ablation have been studied. The dispersions of CO and OH stretching RR modes are ∼600 cm−1 eV−1 and 800 cm−1 eV−1, respectively. The dispersion of the third harmonic of the CO stretching mode is ∼2000 cm−1 eV−1. Similar dispersion of the RR peak of CO stretching modes and higher harmonics superimposed on PL spectra has been observed in Mo1−xFexO2 thin films and SiO2 bulk glass. Large dispersion of RR peaks seems to be a common property of oxides with impurities of CO and OH.