Miracle-dz/UniFAR-FTUs huggingface dataset:
Semi-Supervision in ASR: Sequential MixMatch and Factorized TTS-Based Augmentation

Semi and self-supervised training techniques have the potential to improve performance of speech recognition systems without additional transcribed speech data. In this work, we demonstrate the efﬁcacy of two approaches to semi-supervision for automated speech recognition. The two approaches leverage vast amounts of available unspoken text and untranscribed audio. First, we present factorized multilingual speech synthesis to improve data augmentation on unspoken text. Next, we propose the Sequential MixMatch algorithm with iterative learning to learn from untranscribed speech. The algorithm is built on top of our online implementation of Noisy Student Training. We demonstrate the compatibility of these techniques yielding an overall relative reduction of word error rate of up to 14.4% on the voice search tasks on 4 Indic languages.
Temporal Minimal-World Query Answering over Sparse ABoxes

Ontology-mediated query answering is a popular paradigm for enriching answers to user queries with background knowledge. For querying the absence of information, however, there exist only few ontology-based approaches. Moreover, these proposals conflate the closed-domain and closed-world assumption and, therefore, are not suited to deal with the anonymous objects that are common in ontological reasoning. Many real-world applications, like processing electronic health records, also contain a temporal dimension and require efficient reasoning algorithms. Moreover, since medical data are not recorded on a regular basis, reasoners must deal with sparse data with potentially large temporal gaps. Our contribution consists of two main parts: In the first part, we introduce a new closed-world semantics for answering conjunctive queries (CQs) with negation over ontologies formulated in the description logic $${\mathcal E}{\mathcal L}{{\mathcal H}_ \bot }$$ , which is based on the minimal canonical model. We propose a rewriting strategy for dealing with negated query atoms, which shows that query answering is possible in polynomial time in data complexity. In the second part, we extend this minimal-world semantics for answering metric temporal CQs with negation over the lightweight temporal logic and obtain similar rewritability and complexity results.
Retention of Nickel in Soils: Sorption-Desorption and Extended X-ray Absorption Fine Structure Experiments

Abstract Adsorption and desorption of heavy metals in soils are primary factors that influence their bioavailability and mobility in the soil profile. To examine the characteristics of nickel (Ni) adsorption-desorption in soils, kinetic batch experiments were carried out followed by Ni release using successive dilutions. Two soils of distinctly different properties were used: one acidic (Olivier) and one neutral (Webster) soil, where a wide-range Ni concentration was implemented. Adsorption of Ni by both soils was kinetic and increased with increasing initial (input) Ni concentration. The rate of sorption was initially rapid and was followed by gradual retention over time. A sequential extraction procedure and extended X-ray absorption fine structure (EXAFS) spectroscopy were implemented to characterize Ni kinetic sorption behavior. Five sequential extractions were quantified: exchangeable, bound to carbonates, bound to Fe-Mn oxides, bound to organic matter, and residual fraction. The exchangeable fraction showed a slight increase as initial Ni concentration increased, indicating weakly bound Ni adsorption complexes. Extended X-ray absorption fine structure analyses indicated that Ni hydroxide precipitate formed over time for the neutral Webster soil. This precipitate was likely bound to the Fe/Al oxide fraction. We conclude, based on EXAFS analyses and sequential extractions, formation of Ni hydroxide precipitate depends on soil pH and the amount of Ni sorbed. No Ni hydroxide precipitate was formed on the acidic Olivier soil.
Quantification of GFP Transfection Using a Cost-Effective Microplate Reader

Transfection, the introduction of exogenous DNA into a eukaryotic cell, is an important tool for studying the regulation of gene expression as well as protein expression and function.1 In stable transfection, the foreign DNA becomes integrated into the genomic DNA of the cell so that it is passed on in the cell lineage and continues to express the encoded gene of interest. More commonly used is transient transfection, in which the foreign DNA are present in the cell for only a limited period of time. There are several methods available for cell transfection, including the formation of DNA-DEAE dextran or DNA-calcium phosphate complexes to facilitate endocytosis and electroporation, which use high-voltage pulses to form transient pores in the cell membrane through which the DNA can enter. Currently, the most common method for transfecting cells uses cationic lipids that result in high transfection efficiencies with low cytotoxicity.3
A Prototype of a Web Server Clustering System M.s. Project Report

More and more companies have turned to the World Wide Web as an alternative way to do business. The function performed by the web server is critical to a company's business. Web server clustering has been accepted as a good choice for improving server performance. In this project we implemented one prototype of a web server clustering system and measured its performance. One advantage of our prototype over some available commercial products is its wide portability due to its application-layer implementation.
Experimental modelling for the Prediction of Heat and Mass Transfer in an Air-Conditioned Space Environment for Life Support Systems

For the success of long-term space flights, and the establishment of permanent bases in space, a well controlled self sustained environment is required. In order to optimize a closedloop bio-regenerative life support system, it is necessary to control the hydrodynamics and the coupled heat and mass transfer, which develops in a space habitat concerned with humans and plants. Thus, we have proposed an experimental set up that can gives us accurate predictions of heat and mass transfer at interfaces. We intend to introduce later on the measured heat and mass transfer coefficients in a global theoretical model. More precisely, this study focuses on the condensation phenomena of humid air on specific and simple geometries. For that purpose we induce condensation on an active surface maintained isothermal, and measure the mass transfer. The experiments were carried out in a wind tunnel, where a low turbulent flow develops and the temperature and hygrometric distributions are also well controlled. We have already studied the velocity profiles on vertical and horizontal flat plates with and without condensation. Velocity profiles within the boundary layer have already been discussed in dry conditions.
Methodological aspects of semantic annotation and representation

EC project officer Erwin Valentini Document title Methodological aspects of semantic annotation and representation Deliverable ID D4.1 Document type Report Dissemination level Public Contractual date of delivery M9 Actual date of delivery 30th September 2005 At a time when semantic content annotation is proving to be at the cutting edge of rapid and accurate information extraction of all varieties, there is some urgency in setting standards for reusability and interoperability of resources for wide application and distribution. The LIRICS project therefore has as one of its aims to propose a common and well-defined set of descriptors for semantic annotation in the form of data categories in an on-line registry, in accordance with ISO standard 12620 (Terminology and other language resources – Data categories for electronic lexical resources; see Romary 2004). The work in this part of the LIRICS project is performed in Work Package 4 in close collaboration with two related initiatives. First, the area of semantic content annotation has been recognized as important by the International Organization for Standardization (ISO), which has formed the ad hoc Task Domain Group TDG 3 devoted to this area, within Technical Committee 37, Subcommittee 4 (Language Resources Management). In addition, an independent expert group was formed within the ACL Special Interest Group on Computational Semantics (ACL/SIGSEM), the Working Group on the Representation of Multimodal Semantic Information (MMSemR). The work in WP 4 of the LIRICS project is carried out in close collaboration with the activities of this Working Group and in ISO TC 37/SC 4/TDG 3, as witnessed by a joint workshop that took place in January 2005 in Tilburg So far, the activities have consisted primarily of: 1. identifying commonalities in alternative approaches to the annotation and representation of various types of semantic information; and 2. developing methodological principles and concepts for identifying and characterizing representational concepts for semantic content. The present deliverable is concerned especially with the latter point, inspired by discussions in the MMSemR Working Group and by methodologies that have been developed in ISO activities in other domains of annotation of linguistic resources. Any effort to annotate or represent semantic information presupposes a delineation of what is meant by semantic information. We follow Bunt & Romary (2002) who define meaning, in relation to the processing of linguistic textual, spoken or multimodal utterances, as the way in which the information state of an interpreting system is meant to be affected …
Omnidirectional Image-based Rendering

The paper summarizes omnidirectional image-based rendering techniques giving a user a complete freedom of motion in a virtual reality. Image-based representation provides a photorealistic scene representation. We discuss two VR scenarios, the " window into reality " and the " door of perception ". We overview the complete process from the acquisition to the rendering focusing on the advantages of omnidirectional images for the user experience. We also discuss the acquisition setups and practical issues such as the equipment used for real setups, presented for example at the CeBit 2005 fair.
Synthesis, spectroscopic characterisation, and potential application of dyes containing a carbostyril skeleton as sensors for thiols

Several dyes based on a carbostyril skeleton were synthesised and characterised using proton nuclear magnetic resonance spectroscopy and electron ionisation mass spectrometry. Their basic spectroscopic properties, such as absorption and emission spectra, were also measured. The behaviour of the obtained dyes in the absence and presence of thiol amino acids and other compounds under various conditions were studied. These dyes contain various moieties in the structure, acting as Michael acceptors. Results show that the studied compounds have the potential to act as colorimetric sensors for thiols, but the benzothioazolium dyes are less effective than dicyanoethylene derivatives.
Hole‐Conductor‐Free Fully Printable Mesoscopic Solar Cell with Mixed‐Anion Perovskite CH3NH3PbI(3−x)(BF4)x

J. Z. Chen, Dr. Y. G. Rong, A. Y. Mei, Dr. Y. L. Xiong, T. F. Liu, Y. S. Sheng, P. Jiang, L. Hong, Y. J. Guan, X. T. Zhu, X. M. Hou, M. Duan, J. Q. Zhao, Dr. X. Li, Prof. H. W. Han Michael Grätzel Center for Mesoscopic Solar Cells Wuhan National Laboratory for Optoelectronics School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan , Hubei 430074 , P. R. China E-mail: hongwei.han@mail.hust. edu.cn
Early Esophageal Cancer detection using Deep learning Techniques. (Review Article)

Esophageal cancer is one of the deadliest diseases for humans, since it is discovered in very advanced stages. As result, pathologists are increasingly relying in image recognition and artificial intelligence tools to aid in the early identification and evaluation of this lesion. We examined a number of papers that dealt with this issue during the time span in order to shed light on the studies that were performed in this area (2017 and 2020). We have looked at experiments that used Convolutional Neural Network (CNN) technologies in the study of endoscopic images to help with early detection or diagnosis of esophageal cancer and its various forms. More research on esophageal malignant growth is required, as well as improving the disease’s indicative existence and employing more proven techniques for feature selection/extraction of endoscopic images. The aim of this review is to highlight the research conducted on endoscopic images of the esophagus using deep learning algorithms, including CNN, Support Vector Machine (SVM), Random Forests (RF) and other techniques that were used to design the Computer-Aided Detection (CAD) system. In this review we covered some but not all articles that was of great contact with our master’s thesis research in this regard.
The Radio Number for Some Classes of the Cartesian Products of Complete Graphs and Cycles

A radio coloring of graphs is a modification of the frequency assignment problem. For a connected simple graph G, a mapping g of the vertices of G to the positive integers (colors) such that for every pair u and v of G, | g(u) − g(v)| is at least 1 + diam(G) − d(u, v), is called a radio coloring of G. The largest color used by g is called span of g, denoted by rn(g). The radio number, rn(G), is the least of { rn(g) : g is a radio coloring of G }. In this paper, for n ⩾ 7 we obtain the radio number of Cartesian product of complete graph K n and cycle C m , K n ☐C m , for n even and m odd, and for n odd and m 5 (mod 8).
Simulation of InGaAs-Based Planar Nanodevices As Terahertz Rectifiers

A planar nanodevice, known as the self-switching diode (SSD), has a non-linear current-voltage characteristic that resembles a typical diode behaviour. Unlike other conventional diodes that depending on barrier junction or gate, SSD utilized its L-shaped trenches to exhibit non-linear I-V behaviour, which can be exploited for high-frequency operations. This paper presents technology computer-aided design (TCAD) rectification studies of two InGaAs-based SSDs connected in parallel with similar/different length operating at sub-terahertz frequencies and at zero bias. As expected, the combination of SSDs with the shortest length possess the highest cut-off frequency, and in this case, at approximately 0.35 THz. This is comparable with the recent proposed hybrid structure of SSD and planar barrier diode (SSD/PBD). In fact, it has lower leakage current than SSD/PBD which can reflect to a better rectification performance.
Energy-Efficient Load Balancing Technique to optimize Average response time and Data Center Processing Time in Cloud Computing Environment

Cloud infrastructure is a modern computing system in which pooled services are made available to users at various times depending on their demands. The process of distributing workload among computing system nodes is known as load balancing. Loads include things like CPU power; ram capacity, and network traffic. A well-balanced load avoids the situation when some nodes are fully loaded while others are inactive or not working. Where there are many tasks in a virtual machine (VM), these tasks are delegated to underutilize VMs in the same or a separate datacenter. Modified Round Robin and Modified Honey Bee Algorithms are proposed in this article for effective load balancing based on honey bee and Round Robin foraging activity to control load through VMs. Tasks taken from VMs that are crowded are viewed as honey bees. In the suggested method which is a circular ribbon, filled VMs are considered. In order to ensure a fast responding time and a minimum number of task migrations, the planned protocol also explores the aims of tasks in VM queues. The results of the test indicate that the quality of service has improved considerably (QoS).
Nonclassicality of Photon Added Bipartite Glauber Lachs State

Mixture of coherent state with thermal noise is known as the Glauber Lachs state, which is taken into consideration. Nonlocal photon addition is imposed on the two mode Glauber Lachs state by the application of bosonic creation operators. This nonlocal photon addition induces nonclassicality, revealed in the single mode and two mode squeezing properties. The ratio of the coherent noise to thermal noise is the key factor in observing the nonclassical features. The tolerance limit of the noise for the nonclassicality is discussed in single mode squeezing and two mode squeezing quadrature operators. The results show that the squeezing properties are less pronounced even for the low level of thermal noise.
Closest approach of a quantum projectile

We consider the simplest case of Rutherford scattering, i.e. the head-on collision, where the projectile is treated quantum mechanically. The convexity of repulsive Coulomb force invokes a disagreement between the Ehrenfest’s and Hamilton’s dynamics. We show that the quantum projectile cannot approach as close as the corresponding classical one, and that the average distance of closest approach depends on the position spread of the wave function describing the projectile.
Potential of Fuzzy Methodology for Investigation in Nanofluids Heat Transfer

In this paper, the Fuzzy Nanofluid Model (FNFM) used to develop a fuzzy analysis investigation on heat transfer optimal performance at different Nanofluids flow rate. The fuzzy Nanofluid model is applied to examine the effects of heat transfer parameters on heat transfer performance. Silicon Oxide SiO2 Nanofluid is used to explain their effects on heat transfer by two methods traditional and fuzzy (with two shapes of member ship function triangular and trapezoidal). This study evaluates the effects of nanoparticles SiO2 with different value of particle concentration PC (0.0-4.0%) using the water as a base fluid. This investigation covers a Reynolds number (Re) in the range of (100-500) as a flow rate (FR) for laminar flow. The main objective of present research, first one, compared a developed FNFM model with traditional model (TM) and determines how fuzzy model plays a significant role in prediction of Heat Transfer performance. Second one, to provide developed methodology for performance evaluation of heat transfer by connecting more than one parameter to a single output which is invaluable supplements relative to classical models. Third one, a developed FNFM can be used as a help tool for decision making to get the best judge (optimum) the performance of any system. The results of fuzzy model showed the heat transfer of SiO2/H2O Nanofluids significantly increased the PC compared with the increase in FR. However, however, using this method, there will be no need to resort to solving complex equations to arrive at a representation of the performance of any system. Finally, the study shows that fuzzy model plays significant role in prediction of heat transfer investigation without the complexity of mathematical tradition models. The correlations coefficients R2 between TM and FNFM models for heat transfer coefficient (0.97) and the average relative error (ε) is ((4.4%). FNFM models can predict heat transfer characteristics with higher accuracy than that of the traditional model.
Malware Detection Using Machine Learning Algorithms Based on Hardware Performance Counters: Analysis and Simulation

In the last decade, Hardware Performance Counters (HPCs) events are increasingly used by Machine Learning (ML) algorithms for malware detection. Modern processors provide a variety of HPCs to measure and monitor processes’ events such as memory accesses, instructions, etc. during their execution. In this paper, an analysis study to categorize the machine learning algorithms based on HPCs that have been used for malware detection is introduced. Besides, the most efficient and effective features of HPCs that have been exploited to recognize the abnormal activities on various systems are identified. Furthermore, the Neural Network (NN) algorithms including Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), and Full Order Radial Basis Function (RBF) algorithms are used to simulate several experiments from the literature. The simulation results show that the accuracy of MLP, CNN, and Full Order RBF are 96.95%, 98.22%, and 98.68%, respectively.
Impact of Electro-Magnetohydrodynamic Nature on Dispersion of solute in the Peristaltic Mechanism

The present article deals with the dispersion of a solute in peristaltic system. This mathematical model provides the analytical solution of electro-magnetohydrodynamic flow of biofluids through a channel. Treating blood as a Jeffrey fluid and considering homogeneous chemical reaction, the closed form of solution of effective dispersion coefficient is obtained by using Taylor’s limiting condition and long wave length approximation. The impacts of physiological parameters such as the electro osmotic velocity, electro kinetic, Jeffrey fluid parameter and Hartmann number on the Peristaltic movement have been investigated. It is found that the average equivalent dispersion coefficient is reduced with respect to the enhancement of homogeneous chemical reaction parameter and Hartmann number. It is pertinent to point out here that the electro osmotic velocity and electro kinetic parameter help to enhance average equivalent dispersion coefficient in comparison with the absence of applied electric field. The present analytical study provides useful information to artificial bio-processors.
Digital Image Recovery Based on Lifting Wavelet Transform

Recently, with the wide distribution of digital media, the need for authenticating digital images was increased. Therefore, many image tamper detection and recovery algorithms were introduced in literature to detect malicious modifications and retrieve the original images. The process of detection and recovery, however, used to have complex operation which requires long processing time. In this paper, a simplified image recovery algorithm is presented by using lifting wavelet transform. In the proposed method, the approximation band is hidden inside the bits of the original image and to be retrieved without relying on source image. For images with hidden data, the average PSNR and SSIM values were 31.22 and 0.977 respectively, and images were successfully retrieved after block attack.
The Scientific Value of a Sustained Exploration Program at the Aristarchus Plateau

The Aristarchus plateau hosts a diversity of volcanic features, including the largest pyroclastic deposit on the Moon, the largest sinuous rille on the Moon, and intrusive and extrusive examples of evolved, Th-rich silicic lithologies. We provide an overview of previous remote-sensing measurements of the Aristarchus plateau and provide new analyses of Diviner Lunar Radiometer thermal IR data, Lunar Prospector Gamma Ray Spectrometer Th data, Chang’e-5 Microwave Radiometer data, and hyperspectral and multispectral visible/near-infrared images and spectra from the Chandrayaan-1 Moon Mineralogy Mapper and the Kaguya Multispectral Imager. The rich diversity of volcanic features on the Aristarchus plateau presents an opportunity for a sustained science and exploration program. We suggest a series of missions to the Aristarchus crater floor or ejecta, the Cobra Head, and Herodotus Mons to investigate the link between pyroclastic, effusive basaltic, and silicic volcanism in the region. Such missions would enable analyses of silicic rocks that are rare in the Apollo sample collection and demonstrate in situ resource utilization of FeO- and H2O-bearing pyroclastic materials.