Reviewerly/exHarmony huggingface dataset:
‘Past’ masters, present beats

Previous research dealing with sample-based music production has favored notions of musical borrowing in sampling over the sonic rationale of the practice—that is, the appeal of past ‘sonic signatures’ to samplists and the processes involved in incorporating them within contemporary phonographic constructs. This appeal can be attributed not only to recording and mixing approaches, but also to mastering strategies. A more recent phenomenon in hip hop music production involves practitioners creating their own material for subsequent sampling and infusing it with convincing phonographic qualities, to satisfy a sample-based aesthetic that until recently has relied heavily on the past. In this sample-based context, the lesser attention given to the sonic ‘object’ calls for a focused investigation of the variables involved in the fusion of ‘past’ (or previously constructed) and present phonographic processes. This inquiry focuses on the merging of ‘staging’ illusions as a subset of such variables, questioning how full-range masters function as source content in sample-based engineering and production processes. The examination explores how hip hop producers negotiate the dimensions of ‘depth,’ ‘height,’ and ‘width’ imbued into masters when used as sampled sources, and the ways in which beat-makers stage previously-constructed mix architectures into newly-juxtaposed sonic illusions.
Exploring the potential of ivr technology to promote collaborative learning in science experiences

This poster explores how different types of virtual reality technology (VR) allow for various degrees of collaborative enactment within virtual environments. This two-staged study analyzed the engagement and reflections of 27 students with three forms of VR hardware. Findings from direct observations and students’ perceptions suggest that the capabilities of high-end immersive virtual reality (IVR) can allow for more meaningful and natural forms of embodied interactions, locomotion, and verbal communication.
On Sampling and Inference using Quantum Algorithms

Quantum computers are projected to handle the Gibbs sampling and the related inference on Markov networks effectively. Apart from noting the background information useful for those starting the explorations in this important thread of Quantum Machine Learning, we capture some results and observations obtained through extensive simulations with two popular paradigms of sampling based on Quantum Annealing and Quantum Approximate Optimization Algorithm.
Assessment of left ventricle dynamic from cardiac magnetic resonance imaging by means a correspondence approach

Abstract In this research, an approach to assess the heart dynamics is reported. The cardiac magnetic resonance images are considered for assessing the left ventricle motion and deformation. The shape of the cavity is obtained by means a segmentation procedure based on a clustering algorithm at an initial instant. This three-dimensional structure is used to establish a region of interest around the border of the structure. An optical flow method allows determining the displacement vector of this region and then defining the shapes of the cavity during the all cardiac cycle. The points of the left ventricle are followed using the displacement vectors in the cardiac cycle, obtaining thus, a dense motion field of the cavity. This approximate deformation field is refined with a correspondence method that working in the three-dimensional space. The mapping of the points that define the left ventricle in the cardiac cycle obtained with the correspondence procedure are then used for computing a set of clinical parameters that allows assessing the motion and deformation of this principal structure of the human heart. The torsion, radial and longitudinal contraction are quantified. The obtained results are promising for evaluating the heart dynamics.
EXPERIENCE OF USING ELECTRICAL TOMOGRAPHY, RADON SURVEY AND MICROSEISMIC SOUNDING IN SEARCH FOR PIPES CONTROLLED BY FAULT ZONES

The complex of geophysical methods was successfully applied in the Alakit-Markha kimberlite field of the Yakutsk diamondiferous province. A pipe was identified in the local forecast area specified within the field at the previous stage of prospecting. The studies using electric tomography (ET), radon survey (RS) and microseismic sounding (MS) covered an area of ≈1000⨯500 m. Based on the jointly processed ET and RS plan images and MS profiles, a tubular body was detected in the sedimentary cover. It is confined to a fault node and stands out among the host rocks by low electrical resistivity, increased soil radon concentrations and high spectral ratios of the horizontal and vertical components of microseisms. Its complex shape is manifested at the ground surface by two isometric structures (each being several hundred meters long), which jointly form a dike-like body at a depth of ≈40 m, as shown by the electrical tomography images. According to the MS data, its root part is detected to comprise one or two fractured narrow zones that are traceable to a depth of 2 km and below. The structure of the identified body and its chemical composition will be determined after exploratory drilling is complete. Today there are grounds to conclude that using ET, RS and MS methods jointly as a complex described in the article proved effective for identifying pipes controlled by fault zones in the sedimentary cover areas.
Sequential Feature Filtering Classifier

We propose Sequential Feature Filtering Classifier (FFC), a simple but effective classifier for convolutional neural networks (CNNs). With sequential LayerNorm and ReLU, FFC zeroes out low-activation units and preserves high-activation units. The sequential feature filtering process generates multiple features, which are fed into a shared classifier for multiple outputs. FFC can be applied to any CNNs with a classifier, and significantly improves performances with negligible overhead. We extensively validate the efficacy of FFC on various tasks: ImageNet-1K classification, MS COCO detection, Cityscapes segmentation, and HMDB51 action recognition. Moreover, we empirically show that FFC can further improve performances upon other techniques, including attention modules and augmentation techniques. The code and models will be publicly available.
Hardness of efficiently generating ground states in postselected quantum computation

Generating ground states of any local Hamiltonians seems to be impossible in quantum polynomial time. In this paper, we give evidence for the impossibility by applying an argument used in the quantum-computational-supremacy approach. More precisely, we show that if ground states of any $3$-local Hamiltonians can be approximately generated in quantum polynomial time with postselection, then ${\sf PP}={\sf PSPACE}$. Our result is superior to the existing findings in the sense that we reduce the impossibility to an unlikely relation between classical complexity classes. We also discuss what makes efficiently generating the ground states hard for postselected quantum computation.
Genetic Algorithm with Chaotic Fruit Fly Optimization Algorithm for Discrete Wavelet Transform based Secret Sharing Cryptography Model

At present times, secure data transmission becomes essential to safeguard the images while communicating with other people through Internet.Image Stegnography defines the way of concealing data in an image. The image chosen for this task is referred by cover image and the image attained next to stegnography is known as stegno image. This paper presents an effective secret sharing cryptography method for secure data transmission by incorporating discrete wavelet transform (DWT) and secret sharing (SS) model. Initially, discrete wavelet transform (DWT) is employed for transforming the region. For optimal selection of the parameters involved in DWT, Genetic algorithm with Chaotic FruitFly Optimization algorithm (GACFFOA) is employed. Then, SS gets executed for lower band stegno images with highly secure process. At the same time, Visual Cryptography is applied for encrypting a secret data. A detailed experimental validation has ensured the superior features of the GACFFOA over the compared models.
Dynamic Classifier Selection for Data with Skewed Class Distribution Using Imbalance Ratio and Euclidean Distance

Imbalanced data analysis remains one of the critical challenges in machine learning. This work aims to adapt the concept of Dynamic Classifier Selection (dcs) to the pattern classification task with the skewed class distribution. Two methods, using the similarity (distance) to the reference instances and class imbalance ratio to select the most confident classifier for a given observation, have been proposed. Both approaches come in two modes, one based on the k-Nearest Oracles (knora) and the other also considering those cases where the classifier makes a mistake. The proposed methods were evaluated based on computer experiments carried out on datasets with a high imbalance ratio. The obtained results and statistical analysis confirm the usefulness of the proposed solutions.
Multiclass Membership Determination Integrating an ID-Bound Method with Bloom Filter

Membership determination with classification is an essential function for a variety of applications, such as network routing and packet inspection. We aim to constitute a mechanism capable of performing such a service with the considerations of efficiency and error ratio issues. The proposed method employs an array structure, in which each unit composes of multiple bits. The array houses a circular bound representation and a Bloom filter, where the former encodes the members and makes judgments of queries, while the latter acts as a secondary means for programming cases indeterministic by the former. Experimental results show that the error ratios were competitive and consistent with different levels of classification, as well as the memory space utilized. The lookup time decreased as the memory space increased. We depict specific characteristics for tackling the problem, including simplicity of data structure for encoding the members, avoidance of checking all classification IDs in the lookup process, and adoption of an auxiliary means for improving the error ratios. The ID-bound method is novel, and with the Bloom filter as the assistant, the proposed approach is robust in performances of both efficiency and error ratio.
ANALISIS KESALAHAN BERBAHASA PADA SOAL UJIAN PELAJARAN BAHASA INDONESIA DI SMA

&lt;em&gt;This research aims to describe and explain: (1) the kinds of mistakes-speaking on the matter, (2) the cause of the error on the question of language, (3) communication effects caused due to an error on a question of language Final Assessment subjects Indonesian Language grade XI public senior high school in Sukoharjo Area school, (4) understanding teacher against the rule drafting problem , and (5) precision drafting problem Final Assessment subjects Indonesian Language grade XI public senior high school in Sukoharjo based on rules of preparation of a matter. This type of research is qualitative research. Qualitative research this time is both a content analysis (content analysis) with the main data source about the Final Assessment of the Odd Semester subjects Indonesian Language grade XI public senior high school in Sukoharjo . The technique of sampling with purposive sampling and snowball sampling. This research uses data sources triangulation and triangulation method as a test of the validity of the data. The results of the analysis of the findings can be explained as follows. First, errors in language reserved assessment of the end of the Semester in the form of spelling errors, Word, and sentence. Second, language mistakes caused by internal factors and external factors. Internal factors in the form of less understand linguistic rules, the lack of rigour in drawing up the question, a habit of relying on a team of editing, and the wrong habits. While external factors in the form of the mistakes of other languages, is vulnerable for a short time, and there is no evaluation. Third, the effect of communication language errors are significant because the learners feel difficulty in understanding the intent of the question. Fourth, teachers less understand rule drafting reserved either in theory or practice. Fifth, the question of the drafting of the Rules contained in the matter of the assessment of the finalsemester subjects Indonesian Language grade XI public senior high school in Sukoharjo is not fully using the rules of preparation of the matter that is being applies both from the aspect of material and construction aspects.&lt;/em&gt;
Creativity through the prism of the unconscious in S. Freud's concept of psychoanalysis

The modernizing global world with new socio-cultural practices actualizes the study of creativity as a constitutive phenomenon of human personality in the context of&amp;nbsp;challenges of the modern era. The object of this research is creativity as a cultural phenomenon, while the subject is creativity in the S. Freud's concept of psychoanalysis. In the era of&amp;nbsp;transformations and uncertainty, when the role of creativity is growing, the ideas of S. Freud acquire special significance. The article considers the unconscious in the context of social, in conjunction with social factors and as&amp;nbsp;the key position in creativity. The theoretical and methodological framework us comprised of the cultural-historical and comparative methods. Systemic approach allowed considering the phenomenon of creativity as a system in the assembly of elements. The author also applies the methods of analogy, analysis, comparison, generalization. Sublimation mechanism, discovered by Freud,&amp;nbsp;is&amp;nbsp;viewed in the context of creativity, as a method for redirection of energy displaced into the field of the unconscious by social factors, into the sphere of creativity. The concept of psychoanalysis serves as&amp;nbsp;the methodological basis for explaination of&amp;nbsp;creativity as a complex process&amp;nbsp;of cumulation of conscious and unconscious.
LibGuides: Graphic Novels: Non Fiction Books

This guide shows the value of Graphic Novels not only as a source of entertainment for kids, but as a tool for increasing learning skills.
Immersive Mobile Telepresence Systems: A Systematic Literature Review

Telepresence can be defined as a system that provides remote collaboration between people in different locations, creating the feeling that both users share in fact the environment. The advances in communication, media and internet, has made possible the popularization of these systems. Smartphones have become increasingly powerful in processing, less expensive and more widespread. A single device combines various sensors, one or more cameras and internet connection, thus a potential hardware for telepresence applications. The main objective of this paper is to present a Systematic Literature Review to identify the main characteristics of immersive telepresence systems designed for mobile environment and to analyze research opportunities that can be further exploited or optimized. This research revealed that the development of immersive telepresence systems for mobile devices has increased in recent years, but is not yet widespread.
LibGuides: COVID-19 Library Updates & Resources: Further Information

An updated description of McFarlin Library's services during the COVID-19 pandemic and a list of COVID-19 resources
Analysis of Mathematics Curriculum Ability Development Based on Computer Data Mining

Abstract In this paper, the data mining techniques is used to analyze the mathematics curriculum ability development. Firstly, a data warehouse of students’ academic achievement is established. The comparative concept description method in data mining techniques is used to analyze various abilities of students of different genders from different majors over the years, and the corresponding reform measures for the teaching contents and approaches are proposed.
Influence of CNN Input Modification for Red Blood Cells Trajectory Prediction in Blood Flow

Computer simulations of blood flow in microfluidic devices help for their development. These simulations are limited by their computational complexity. A possible solution to this problem is to analyze the simulation output data using machine learning methods. We use convolutional neural networks (CNN) for red blood cells (RBCs) trajectory prediction, which is very important for blood flow modeling. In this paper, we study how miscellaneous modifications of a CNN input affect the results from the learning experiments. All performed neural network experiments have sufficient accuracy. We evaluated, which CNN input parameters and their values have a significant impact on experiments accuracy.
Grammatical Inference by Answer Set Programming

In this paper, the identification of context-free grammars based on the presentation of samples is investigated. The main idea of solving this problem proposed in the literature is reformulated in two different ways: in terms of general constrains and as an answer set program. In a series of experiments, we showed that our answer set programming approach is much faster than our alternative method and the original SAT encoding method. Similarly to a pioneer work, some well-known context-free grammars have been induced correctly, and we also followed its test procedure with randomly generated grammars, making it clear that using our answer set programs increases computational efficiency. The research can be regarded as another evidence that solutions based on the stable model (answer set) semantics of logic programming may be a right choice for complex problems.
Description and Classification of Balti Consonant Stop Sounds

The study aims to describe and classify consonant stop sounds of the Balti language, which is spoken in Gilgit-Baltistan, Pakistan. In order to describe and classify these sounds, 120 words were selected from literature written in the Balti language. A purposive sample of 20 Balti speakers from 16 to 35 years of age, who were studying in various degree programs at Government College for Boys, Model Town, Lahore and University of Management and Technology, Lahore, was selected to record possible Balti consonant stop sounds. The physical features of each consonant stop sound were carried through the software package for speech analysis in phonetics. The study reveals that there are 15 consonant stop sounds in the Balti language. The study helps document the Balti language, which follows mostly a verbal tradition like many other languages of the region.
Multilevel Polarization for Quantum Channels

Recently, a purely quantum version of polar codes has been proposed in [3] based on a quantum channel combining and splitting procedure, where a randomly chosen two-qubit Clifford unitary acts as channel combining operation. Here, we consider the quantum polar code construction using the same channel combining and splitting procedure as in [3] but with a fixed two-qubit Clifford unitary. For the family of Pauli channels, we show that the polarization happens although in multilevels, where synthesised quantum virtual channels tend to become completely noisy, half-noisy or noiseless. Further, it is shown that half-noisy channels can be frozen by fixing their inputs in either amplitude or phase basis, which reduces the number of preshared EPR pairs with respect to the construction in [3]. We also give an upper bound on the number of preshared EPR pairs, which is an equality in the case of quantum erasure channel. To improve the speed of polarization, we provide an alternative construction, which again polarizes in multilevel way and the earlier upper bound on preshared EPR pairs also holds. We confirm by numerical analysis for a quantum erasure channel that the multilevel polarization happens relatively faster for the alternative construction.
Design of Montgomery Multiplier for High Speed Pairing Computation with Modified Compressor for Floating-point Unit

Pairings are adorable and captive cryptographic primitives for endowing different unique and effective information security schemes. Cryptosystem is generally attained using repeated modular multiplication for integers in large volume. To gear the security providing process high speed Montgomery multiplication modular VLSI architectures and algorithms and adapt addition by carry save method to prevent the carry propagation for every addition operation in add-shift loop. The suggested architecture consumes less energy and through put is high. In extension the compressor is modified with modified Kogge-stone adder to prominently increase the speed of the circuit.
Análise de tratamento da segurança da informação de uma instituição de ensino público federal

Information Technology (I.T.) and its governance are increasingly present in educational institutions development by improving strategies and objectives. This study aims to verify how is information security processed through risk management within I.T. governance. As a mixed exploratory research, this study was developed in a federal public education institution through questionnaires for data survey and analysis regarding information security practices within I.T. governance. Data analysis suggests that the verified components are applicable to the institution, allowing improvements on principles implementation and maintenance by awareness of the risk environment and the opportunities it offers.
Dual Formulation of the TV-Stokes Denoising Model for Multidimensional Vectorial Images

The TV-Stokes denoising model for a vectorial image defines a denoised vector field in the form of the gradient of a scalar function. The dual formulation naturally leads to a Chambolle-type algorithm, where the most time consuming part is application of the orthogonal projector onto the range space of the gradient operator. This application can be efficiently executed by the fast cosine transform taking advantage of the fast Fourier transform. Convergence of the Chambolle-type iteration can be improved by Nesterov’s acceleration.
THE RESPONSE OF 2nd GRADE “SDN 3 SEKARBANYU” TOWARD CREATIVE READING BOOK (CREBO) MEDIA TO ACHIEVE READING SKILLS FOR LEARNING THEME 7 AND SUB THEMES 2

Based on research that has been conducted, researchers found that students in grade 2 at “SDN 3 Sekarbanyu” still not effective when the train reading skills due to lack of media support, the necessary media to attract the attention of students so that the students' reading skills more effectively. The purpose of this research are: (1) describes the development process Crebo media, (2) determine student’s response to media Crebo. The method used in this research is qualitative and quantitative approach. This research was descriptive. The research procedure adapted from Borg and Gall in Sugiono (2013). The results of this research indicate Crebo media assessment of the material aspects of obtaining a mean score of 87.7% to the category of It's Worth. While aspects of the media get a mean score of 87.8% to the category of Very Decent instructional simulation test with respondents 22 students got the results from the aspect of the attractiveness of 92.7% and from 87.2% retention of material aspects. The conclusion of this study is Crebo get a positive response from the respondent and Crebo fit for use as a medium of learning the skills of reading theme 7 and sub themes 2 in 2nd grade