Reviewerly/exHarmony huggingface dataset:
PENGARUH PELAKSANAAN METODE EKSPLORASI TERHADAP MOTIVASI BELAJAR SISWA DI SDN 34 BABA KECAMATAN CENDANA KABUPATEN ENREKANG

The purpose of this study was to determine whether there was an influence of the Exploration Method Implementation on Student Learning Motivation at 34 Baba Elementary School in Cendana Subdistrict, Enrekang Regency. This type of research was pre-experimental. testing of independent and bound variables is carried out on the sample. The design of this study uses a quantitative approach that examines changes in student motivation through exploration method techniques at Baba 34 Public Elementary School. The research design used was one group pretest posstest desing. The technique of collecting data through observation, questionnaire. The data analysis technique uses descriptive analysis, and inferential analysis that creates a normality test, homogeneity test, and hypothesis testing using the T Test. The results of the study showed that there was a positive influence on the method of exposure on the level of student learning motivation in students at 34 Baba Public Elementary School, which meant that the exploration method was carried out so that the level of student motivation in 34 Baba Public Elementary Schools would also increase.
Deep ecology and East-West dialog

The establishment of the water corporations in Israel, which are financial companies that took the place of the Water Departments in the local governments, constitutes a turning point in the relation between the local governments and the citizens.If in the past the local government saw itself as a nonprofit organization that served the community, the reform in the water industry converted the community activity of the municipal sector into a totally capitalist business operation.In the first years of the establishment of the State of Israel, it was clear that the State had to provide water to its residents as a source of livelihood and a basis for agricultural development and the conquest of the wilderness, but today in the era of privatization the precious resource, water, has become a "product" from which economic benefit can be derived and which can even be traded.The local governments acquire water "to the city gate" and then they sell it to the city resident at a high mark-up, with the addition of VAT, when the difference goes to the Water Corporations.The neoliberal approach has reached a basic product such as water, without distinction between the socioeconomic situations of people, while placing the burden on the resident.Many Investigation Committees on the topic of the water sector have noted the improper management of the government, which does not prioritize alternative solutions such as desalination, use of treated wastewater, and re-use of water for industry and agriculture.Instead, dozens of water corporations have been established to be used as collection agents and to place the economic burden on the citizen's back.
Comparing Quantitative Metrics for Generative Adversarial Neural Networks

Since their conception in 2014, a large number of Generative Adversarial Networks (GANs) [2] has been pro- posed and developed. GANs have achieved great results in realistic image generation, among other fields. Recently, stunning images have been produced. The theory and application of GANs has received much attention. However, the evaluation of these models has not been studied nearly as extensively. GANs are often evaluated by visual inspection. This is a time consuming process, that inherently suffers from being subjective. There has been research into quantitative metrics, which can be automated. There has even been some research into the relative merits of such metrics. [1][9][4]. However, the question which metric is the most suitable for evaluating GANs in the field of realistic image generation remains open. It is important that consensus is reached. If there is no agreed upon method of objectively measuring progress, it is hard to say which techniques are effective. This impedes the entire field of study. This paper hopes to contribute to answering this question by applying a variety of proposed metrics to a variety of different GANs. This way, it is possible to tell which metrics agree with each other, and which rate GANs differently. If all, or many, of the likely metrics proposed in earlier work agree with each other, this is a good sign that they are rating GANs objectively. The results of this experiment are combined with a very brief survey of earlier work, in order to recommend some quantitative metrics for rating GANs.
LibGuides: Library Programs and Events: Open Education Week

This guide has information about past and current Library and Learning Commons programming and events.
Maintenance strategies and design recommendations on input devices for musical expression

Various challenges must be overcome when designing and building input devices for musical expression such as digital musical instruments (DMIs), electronic wearables for performance, among others. Amid the technical ones are the rapid unpredictable advancement of technology, changes in supporting personnel, and a lack of technical documentation. These challenges, if not adequately addressed, in many cases lead to abandonment of such devices and endeavors. This thesis presents three case studies that aim to provide maintenance strategies and design recommendations for the creation of more robust, long-lasting interfaces. The first case study illustrates the challenge of maintaining several models of the DMI called the T-Stick in the hopes of extending their useful lifetime. The T-Sticks were originally conceived in 2006 and 20 copies have been built in the past 12 years. Although all of the instruments preserve the original DMI design concept, their evolution has distinguished them through variations in choice of microcontrollers, sensors, and size. For this case study, we worked with eight copies of the T-Sticks to overcome issues related to the aging and obsolescence of components, changes in external software, inconsistencies in firmware across versions, a lack of documentation, and, in general, the problem of technical maintenance. In the second case study, we redesigned the electronics of a ninth T-Stick, the WiFi Sopranino. For this process we used the lessons learned from the first case study, while keeping its original DMI design concept. This work, in turn, informed the third case study, where we sought to design and build a new interface for musical expression to augment cello performance by installing a visual affordance on the instrument. In short, this thesis aims to connect the concepts of technical maintenance and electronic redesign and design to provide a systematic approach to the maintenance of these type of devices. We articulate design recommendations such as maintainability, reusability, and self-containment as useful in the design of input devices for musical expression.%%%%Differents defis sont a surmonter lors de la conception et la construction d'interfaces pour l'expression musicale telles que les instruments de musique numeriques (IMNs), les technologies portables pour la performance, entre autres. Les principaux enjeux techniques sont le developpement rapide et imprevisible de la technologie, les changements dans le personnel de soutien et le manque de documentation technique. Ces defis, s'ils ne sont pas traites de maniere adequate, conduisent, dans de nombreux cas, a l'abandon de tels dispositifs. Cette these presente trois etudes de cas qui visent a fournir des recommandations relatives a l'entretien et a la conception pour la creation d'interfaces plus robustes et durables. La premiere etude de cas illustre le defi d'entretenir differents modeles d'un IMN appele le T-Stick dans l'espoir de prolonger leur duree de vie. Les T-Sticks ont ete originalement concus en 2006 et 20 exemplaires…
A Comparative Study between the Listening Comprehension of the Students of English Education Department Using Video and Audio

The result of this research lead to the conclusion that using video asmedia on students listening comprehension is better than using audio especially for the students of English Education Department. But there are factors that should be taken into accounts, such as the topic of the material should be familiar for the students and the type of the visual clues of video also must be noticed considering the way of the visual clues in giving the illustration of the speakers’ utterance also plays an important role in helping the students in listening comprehension. The implication of this research expects the teachers or lecturers to apply the video media in teaching listening especially in teaching listening comprehension. The video media contain visual clues which help the students to associated the word that they heard to the image that it’s presented, so that the students can get the meaning of the speakers’ utterance more easily in listening comprehension process.
Prediksi Peminatan Pelanggan dalam Penjualan Produk Sepatu Menggunakan Metode Decision Tree Berbasis Particle Swarm Optimization pada PT. Baskara Cipta Pratama

Abstract — T he PSO-based optimization C4.5 model gives a higher value of 78.16% compared to the C4.5 algorithm model that is 73.88 . The results obtained difference s between the two models by 4.28%. While for evaluation using ROC curve for second model that is, for model of algorithm C4.5 value of AUC is 0,764 with level of diagnosis classification fair, and for model of algorithm C4.5 based on PSO A UC is 0,780 with level of diagnosis of fair classification. It s concluded that ROC curvesmodels shows C4.5 algorithm based on PSO is larger. It can be inferred that C4.5 algorithm based on particle swam optimization is more accurate in predicting the customers’ interest for buying shoes . I ntisari — A nalisis optimasi model algoritma C4.5 berbasis PSO memberikan nilai akurasi yang lebih tinggi yaitu 78.16% dibandingkan dengan model algoritma C4.5 yaitu 73.88%. Dari hasil tersebut didapatkan selisih antara kedua model yaitu 4,28%. Sementara untuk evalusai menggunakan ROC curve untuk kedua model yaitu, untuk model algoritma C4.5 nilai AUC adalah 0.764 dengan tingkat diagnosa Fair classification , dan untuk model algoritma C4.5 berbasis PSO nilai AUC adalah 0.780 dengan tingkat diagnosa Fair classification. Dari evaluasi ROC curve tersebut terlihat bahwa model algoritma C4.5 berbasis PSO lebih besar  Sehingga dapat disimpulkan bahwa algoritma C4.5 berbasis particle swarm optimization lebih akurat dalam memprediksi minat beli prod u k sepatu. Kata Kunci — C4.5, Produk, Sepatu PSO
Research on the Cultivation of English Teachers' Informatization Technology Literacy and Teaching Integration Ability

The construction of information-based foreign language teaching mode based on computer and network technology is an effective way to reform the teaching of college English courses.The integration of information technology and college English teaching is a hot issue in the process of information technology education, and it is also an inevitable trend of college English teaching.This paper briefly introduces the concept of the integration of information technology and college English teaching, and probes into the significance and ways of the cultivation of college English teachers' information technology literacy and teaching integration ability, which is of great practical significance for promoting the development of college English teaching.
Anomaly Detection in Categorical Data with Interpretable Machine Learning : A random forest approach to classify imbalanced data

Metadata refers to about data, which contains information needed to understand theprocess of data collection. In this thesis, we investigate if metadata features can be usedto detect broken ...
Demystifying quantum weirdness in delayed-choice quantum eraser experiment using entangled photons

We have constructed the full density matrix for the quantum eraser experiment using two entangled photons in [Y. Kim et al., Phys. Rev. Lett. 84, 1 (2000)] by tracing the evolution of the initial entangled state to its final state when it reaches the different detectors. Several projective measurements were made on the full density matrix of the entangled system to exhibit the presence or absence of interference fringes which corresponds to the availability of the which path information. The results of the projective measurements agree with the experimental results. Therefore, all the information that can be accessed in the quantum eraser eraser experiment can be obtained in the full density matrix of the system and it is only a matter of postselecting the data points to exhibit the presence or absence of interference fringes.
Nonlinear diffusion based image segmentation using two fast algorithms

In this paper, a new variational model is proposed for image segmentation based on active contours, nonlinear diffusion and level sets. It includes a Chan-Vese model-based data fitting term and a regularized term that uses the potential functions (PF) of nonlinear diffusion. The former term can segment the image by region partition instead of having to rely on the edge information. The latter term is capable of automatically preserving image edges as well as smoothing noisy regions. To improve computational efficiency, the implementation of the proposed model does not directly solve the high order nonlinear partial differential equations and instead exploit the efficient alternating direction method of multipliers (ADMM), which allows the use of fast Fourier transform (FFT), analytical generalized soft thresholding equation, and projection formula. In particular, we creatively propose a new fast algorithm, normal vector projection method (NVPM), based on alternating optimization method and normal vector projection. Its stability can be the same as ADMM and it has faster convergence ability. Extensive numerical experiments on grey and colour images validate the effectiveness of the proposed model and the efficiency of the algorithms.
Time-Correlated MIMO Channels Using Decision Feedback Receiver

We design bit loading, precoding also receives filters to a Multiple-Input Multiple-Output (MIMO) computerized correspondence framework. Both these transmitter and the recipient are relied upon the channel grid superbly. It may be greatly distinguished that, for straight MIMO transceivers, orthogonal transmission (i.e., diagonalization of the channel matrix) will be perfect to a portion of benchmarks for example, most extremely imparted majority of the data. It needs to be uncovered that assuming that these recipient hones those linear Minimum Mean Squared Error (MMSE) detector. Those ideal transmission approaches may be settled on touch-stacking with respect to orthogonal sub-channels. That transmission rate of the channel is improved toward passing on the odds rapidly on the sub-channels of the MIMO framework. A variable-rate MIMO framework with a choice sentiment recipient may be deliberated. Those nested sub-matrices need aid induced that might make modernized concerning illustration the long run progresses. The transmission rate to the channel is adapted by assigning bits dynamically to the sub-channels of the MIMO system. To derive the optimal predictor of the next bit loading for predictive quantization and obtain the statistics of the prediction error using this method, that quantizer may be pointed on the scope of a littler quantization slip. That transform for linking those deciphering strategy is arranged to improve those outline what’s more its procedure. This offers better result associated with the MMSE and spot rate, same time relating with those traditional techniques.
Hard Pixels Mining: Learning Using Privileged Information for Semantic Segmentation.

It has been shown that incorporating depth features into RGB features helpsimprove semantic segmentation. However, depth information is usuallyunavailable for the test images. In this paper, we leverage only the depth oftraining images as the privileged information to mine the hard pixels insemantic segmentation. Specifically, we propose a novel Loss Weight Module(LWM), which outputs a loss weight map by employing two depth-relatedmeasurements of hard pixels: Depth Prediction Error (DPE) and Depth-awareSegmentation Error (DSE). The loss weight map is then applied to segmentationloss, aimed at learning a more robust model by paying more attention to thehard pixels. Besides, we also explore a curriculum learning strategy based onthe loss weight map. Meanwhile, to fully mine the hard pixels on differentscales, we apply our loss weight module to multi-scale side outputs. Our hardpixels mining method achieves the state-of-the-art results on two benchmarkdatasets, and even outperforms the methods which need depth input whiletesting.
Comprehending Ringads (keynote)

List comprehensions are a widely used programming construct, in languages such as Haskell and Python and in technologies such as Microsoft's Language Integrated Query. They generalize from lists to arbitrary monads, yielding a lightweight idiom of imperative programming in a pure functional language. When the monad has the additional structure of a so-called ringad, corresponding to "empty" and "union" operations, then it can be seen as some kind of collection type, and the comprehension notation can also be extended to incorporate aggregations. Ringad comprehensions represent a convenient notation for expressing database queries. The ringad structure alone does not provide a good explanation or an efficient implementation of relational joins; but by allowing heterogeneous comprehensions, involving both bag and indexed table ringads, we can accommodate these too.
Using Bright App to Enhance Saudi Intermediate Students’ L2 Vocabulary Knowledge

The purpose of this research was to investigate Saudi intermediate students’ attitudes toward using Bright App to enhance English vocabulary. The Repetition technique that Bright app use enables the brain to memorize the words for a long time. The participants of this research were ten female intermediate students studying at 169 School, Riyadh city, Saudi Arabia. It was an experimental study and the research tool used was a questionnaire. The results showed that Bright App is helpful to enhance the vocabulary knowledge of the students. Moreover, the participants showed a positive attitude towards using the Bright App.
Evaluating the Usability and Suitability of a Live Hockey Visualization in Mobile Augmented Reality

During the last couple of years, mobile augmented reality (MAR) has seen an increase in its potential due to improved available hardware and software. Applications such as Pokemon GO and IKEA Place ...
Classification of GPU rendering errors with Artificial Neural Networks

Image quality metrics are used to evaluate the percieved quality of processed images. Differences in hardware between graphics processors contribute to noise during quality evaluation. In this masters thesis paper we train and evaluate neural networks as metrics to evaluate GPU rendering quality. The neural networks can successfully ignore the rendering noise that occurs when the test and reference frames are rendered by different GPUs. This reduces tedious human interaction which requires manual updates of reference-frames during quality testing.
A novel secret sharing scheme using multiple share images

Secret image sharing has been widely applied in numerous areas, such as military imaging systems, remote sensing, and so on. One of the problems for image sharing schemes is to efficiently recover original images from their shares preserved by the shareholders. However, most of the existing schemes are based on the assumption that the shares are distortion-free. Moreover, the correspondence between secret images and their shares is definite. To overcome these shortcomings, we propose a novel secret sharing scheme using multiple share images based on the generalized Chinese remainder theorem (CRT) in this paper, where all of the shares are needed to recover the original images. Two categories of distortions are considered. In the first category, some pairs of shares with the same moduli are exchanged, while in the second category, some of pixels in the pairs of shares with the same moduli are exchanged. Based on these two sharing methods, we propose a generalized CRT based recovery method. Compared with the existing CRT based methods as well as combinatorial based methods, the proposed approach is much more efficient and secure. Furthermore, the conditions for successful recovery of two images from the given distorted shares are obtained. Simulations are also presented to show the efficiency of the proposed scheme.
Effects of the Mobile Self-managed Quiz on English Vocabulary Learning of College Students

Self-management skill can be a key factor to successful English learning, but few opportunities are available for Korean college students. In response...
O livro e suas tendências: da mídia impressa à digital

This article discusses the so-called disappearance of the book in face of its increasingly popular alternative, the e-book, in a historical analysis that considers the book's evolution from its origins to modernity.The growth of technology transformed the production, transmission and reception of texts, even modifying the means through which we access and preserve books.At each point along this trajectory, we have come to adopt even more modern resources to accompany the rapid technological growth.Before, the book was available in paper; now, the e-book pervades the digital media age.This text surveys the academic debate regarding the future of the book; seeks to identify a consensus among the leading thinkers in the field; and familiarizes the reader with the threats, risks and possible dangers that accompany preserving texts through exclusively digital means.Ultimately, there are strong implications of preserving texts through digital methods given the obsolescence and fragility of technology.In the long term, relying on technology will not guarantee the survival of texts, or will fail to inform future generations about the unique threats to which e-books and the digital age are presently subject.
A Comparative Mention-Pair Models for Coreference Resolution in DARI Language for Information Extraction

Coreference resolution plays an important role in Information Extraction.This paper covers the investigation of two strategies based on a mention-pair resolver using Decision Tree classifier on structured and unstructured dataset, targeting coreference resolution in Dari language.Strategies are (1) training separate models which is specialized in particular categories (e.g., lexical, syntactic and semantic) and types of mentions (e.g.pronouns, proper nouns) and (2) using a structured dataset on a machine learning library that is designed to classify numerical values.Moreover, these modifications and comparative models describe a contribution of comprehensive factors involved in the resolution of texts.Specifically, we developed the first Dari corpus ('DariCoref') based on OntoNotes and WikiCoref scheme.Both strategies are produced f-score of state-of-the-art.
Design and Implementation of B2B E-commerce Platform Based on Microservices Architecture

"Government Work 2018" report proposed the development of industrial Internet, manufacturing industry transformation driving B2B transformation. In recent years, the concept of industry 4.0 and B2B Industry Internet have developed in coordination, and the accelerated transformation of manufacturing industry has also ushered in a new service concept for B2B industry. In order to meet the increasing demand of business expansion and concurrency performance of modern e-commerce platform, we propose a B2B e-commerce platform based on microservices and Spring Cloud [1] is used as the basic framework of microservices.