Reviewerly/exHarmony huggingface dataset:
MaskCycleGAN-VC: Learning Non-parallel Voice Conversion with Filling in Frames

Non-parallel voice conversion (VC) is a technique for training voice converters without a parallel corpus. Cycle-consistent adversarial network-based VCs (CycleGAN-VC and CycleGAN-VC2) are widely accepted as benchmark methods. However, owing to their insufficient ability to grasp time-frequency structures, their application is limited to mel-cepstrum conversion and not mel-spectrogram conversion despite recent advances in mel-spectrogram vocoders. To overcome this, CycleGAN-VC3, an improved variant of CycleGAN-VC2 that incorporates an additional module called time-frequency adaptive normalization (TFAN), has been proposed. However, an increase in the number of learned parameters is imposed. As an alternative, we propose MaskCycleGAN-VC, which is another extension of CycleGAN-VC2 and is trained using a novel auxiliary task called filling in frames (FIF). With FIF, we apply a temporal mask to the input mel-spectrogram and encourage the converter to fill in missing frames based on surrounding frames. This task allows the converter to learn time-frequency structures in a self-supervised manner and eliminates the need for an additional module such as TFAN. A subjective evaluation of the naturalness and speaker similarity showed that MaskCycleGAN-VC outperformed both CycleGAN-VC2 and CycleGAN-VC3 with a model size similar to that of CycleGAN-VC2. Audio samples are available at http://www.kecl.ntt.co.jp/people/kaneko.takuhiro/projects/maskcyclegan-vc/index.html.
Choosing Classification Thresholds for Mobile Robot Coverage

Many robotic coverage applications involve detection of spatially distributed targets, followed by path planning to visit them for service. In these applications, the performance of the detection algorithm can have profound effect on planning decisions and costs. Range of operation, in both space and time, for robots is typically finite over a single mission and is a common constraint that needs to be accounted for in decision making. Misclassification may result in wastage of resources and can even jeopardize the completion of a mission if the length of a path extends beyond the range of the robot. In this work, we develop techniques on the computation of planning-aware classification thresholds. We discuss two versions that compute binary classification thresholds as a function of planning budget and detection accuracy. We present an implementation of our methods in path planning applications for an autonomous mower and show results on real and simulated data. Our method allows upto 25% improvement in coverage as compared to standard thresholding methods.
Development and Integration Test of an Improved Transponder for Hy–2B Altimeter

An improved transponder for HY-2B (Haiyang) radar altimeter is presented in this paper. HY-2B is the follow-on mission to HY-2A, the Chinese sea satellites for oceanography. An improved transponder was developed. It has some advantages over the HY-2A one. The paper describes the development and integration test of the transponder. Some new techniques are employed. Its performance is stable and qualified for HY-2B altimeter calibration.
KORELASI KETERAMPILAN MEMBACA PEMAHAMAN DENGAN KETERAMPILAN MENULIS TEKS EKSPOSISI SISWA KELAS X SMA NEGERI 3 PADANG

ABSTRACT This article was written to describe the correlation of reading comprehension and writing a exposition text seventh grade students of SMA Negeri 3 Padang. Tipe of this research is quantitative research with descriptive method and used a correlational research schema. The population and sample of this research is the seventh grade students of SMA Negeri 3 Padang in the year of 2019/2020. The sample of this research is 40 students. The sampling technique used is random sampling. From this research, it can be concluded that there is significant correlation between reading comprehention with writing exposition text seventh grade students of SMA Negeri 3 Padang by freedom degree n-1 with significants rate 95% and tobservation is bigger than ttabel that is 3,78 &gt; 1,68. It means, the students who have a higher ability in reading comprehension so they also have a good ability in write a exposition text. In contrast, if their ability in reading comprehension is low, their ability in write a exposition text is too low. Kata Kunci: Hubungan, Keterampilan, Membaca, Menulis, Teks Eksposisi
context-aware travel recommender system exploiting from Geo-tagged photos

Recommender systems are the systems that help users find and select their target items. Most of the available events for recommender systems are focused on recommending the most relevant items to the users and do not include any context information such as time, location . This paper is presented by the use of geographically tagged photo information which is highly accurate. The distinction point between this thesis and other similar articles is that this paper includes more context (weather conditions, users’ mental status, traffic level, etc.) than similar articles which include only time and location as context. This has brought the users close to each other in a cluster and has led to an increase in the accuracy. The proposed method merges the Colonial Competitive Algorithm and fuzzy clustering for a better and stronger processing against using merely the classic clustering and this has increased the accuracy of the recommendations. Flickr dataset is used to evaluate the presented method. Results of the evaluation indicate that the proposed method can provide location recommendations proportionate to the users’ preferences and their current visiting location.
Teaching and Learning with Digital Applications

In 2006 the European Commission recorded digital competence as one of the eight key competences for lifelong learning. Later, the competency was further defined by The Digital Competence Framework for Citizens called DigComp. Digital competences are divided into five areas: Information and data literacy, Communication and collaboration, Digital content creation, Safety and Problem solving, which are further defined in the form of 21 competencies. In Slovenia, as well as in some other European countries, there is a gap between the information and communication skills acquired by students in school and the skills needed by the economy. The development of digital competence is primarily a result of the teacher's efforts since it is not evaluated, neither entirely nor systematically. Digital gadgets can be seen, on the one hand, as an opportunity to make meaningful use of digital technology for teaching and learning, and on the other, as developing the digital competence of students to digitally change the whole society. As an example of good practice, we will show how we can use different digital gadgets to produce flyers, leaflets and video animations. We will use the free Adobe Spark application, which is available online, and we will list some more similar gadgets. With the application, we can convert our ideas into stunning visual stories with just a few clicks. Teachers can use the application to better represent the lessons and students can use it to prepare presentations of seminar papers, leaflets, greetings, and invitations, which allows both active and passive use.
Developing Think Talk Write Strategy on Students’ English Literation Capability

This study aims to determine the effect of developing Think Talk Write (TTW) Strategy in increasing literation capability of English text for 4th semester students of the 2019/2020 academic year of English Study Program, Education Faculty (FKIP) - Simalungun University (USI). The development of the TTW Strategy consists of three phases, namely Think, Talk and the Writing Phase. These three phases are the independent variables of the study, while the dependent variable is literation capability. The research was conducted for 30 students. The sampling technique used saturated sampling technique. The type of data used is primary data. Data were analysed using multiple linear regression analysis method. The results of the analysis show that the Think, Talk and Writing Phases have a positive and significant effect on increasing students’ literation capability in English text, both partially and simultaneously. Thus, it can be concluded that the development of the TTW Strategy has a positive and significant effect in improving students' literation capability.
Data Mining on the Candela Cloud Platform

This paper describes the work done with the Data Mining components of the H2020 CANDELA project, mainly the Data Model component on the CANDELA platform as its back end, and the user interaction component of the local user machine as front end. The Data Mining tool is basically composed of four main submodules: the Data Model Generation for Data Mining (DMG-DM), the database management system (DBMS) sub-module that has already been dockerized and deployed on the CANDELA platform, the image search and semantic annotation (KDD) sub-module and the multi-knowledge and query (QE) sub-module. They all require user inputs, and connect directly to the database on the platform; they can be started as a normal GUI (Graphical User Interface) tool.
The Correlation Between Students’ Vocabulary Achievement and Fluency in Speaking English

The objective of the study was to find out the correlation between students vocabulary achievement. The population was the second grade student of SMK Negeri Binaan PEMPROVSU. The population were 5 class consist 121 students. This study took a class TKJ and TKR as a sample by using Cluster Random Sampling. In gathering data, used a match test to measure vocabulary mastery and oral test to measure fluency in speaking English. In analyzing data, this study used Pearson Product Moment Formula. After analyzing, it was found r- calculated 0,873. It means that r-calculated was higher than r- table. So the relationship between two variables above were significant. And percentage if correlation between students’ vocabulary achievement and fluency in speaking English was 76,22%. It means that the students’ vocabulary achievement will support fluency in speaking English
ECONOMIC DIVERSIFICATION AND AGRO-FOOD TECHNOLOGICAL SOLUTIONS IN NIGERIA: LESSONS FROM MALAYSIA

The paper x-rayed the various aspects of the agro-food economic diversification in Malaysia to draw lessons for Nigeria’s agricultural economic growth and development. A descriptive statistical method was employed in the presentation. With a total population of 31.6 million people, Malaysia has been able to harness the factor endowments for its people such that its GDP per capita (USD, PPP) grew from 18,577 in 2005 to 25,669 in 2016, whereas Nigeria’s GDP per capita (USD, PPP) grew from 4,149 in 2005 to 5,435 in 2016. Nigeria failed in its capacity utilization of the available factor endowments. In 2016, the percentage of prevalence of undernourishment of Malaysian people was 2.9, while Nigeria’s data was 11.5%. Furthermore, there was no prevalence of severe food insecurity in Malaysia, but Nigeria recorded 24.8% in its prevalence of severe food insecurity, within the period under consideration. The paper concluded that Nigeria’s economic performances are dwindling. It was recommended that to enhance stable and viable sustainable and economic growth for its people, Nigeria’s mono-economy must give way to the productive development of all sectors of the economy, particularly the agro-technology.
A PAC-Bayes Analysis of Adversarial Robustness

We propose the first general PAC-Bayesian generalization bounds for adversarial robustness, that estimate, at test time, how much a model will be invariant to imperceptible perturbations in the input. Instead of deriving a worst-case analysis of the risk of a hypothesis over all the possible perturbations, we leverage the PAC-Bayesian framework to bound the averaged risk on the perturbations for majority votes (over the whole class of hypotheses). Our theoretically founded analysis has the advantage to provide general bounds (i) that are valid for any kind of attacks (i.e., the adversarial attacks), (ii) that are tight thanks to the PAC-Bayesian framework, (iii) that can be directly minimized during the learning phase to obtain a robust model on different attacks at test time.
Voting interest and the party manifesto in 2019 presidential election in Nigeria

It is central within the domain of many literature concerning election in most of the developing democracies that the political parties ‘officials, candidates as well as their members did not see party‘s manifesto as an effective instrument for attracting the voting interest of the electorate. Thus, they employ to the large possible extent non issues based campaign factors to canvass for votes, even thought that the 2010 electoral law(asamended) made it categorically clear that the campaign should be based on party manifesto. This paper seeks to explain the centrality of party manifesto or otherwise in determining the voting interest of the electorate. The total numbers of voters that casted their votes during the conduct of 2015 general election in Bomo ward Sabon-Gari Local government Area of Kaduna State constituted the population of the study in which the multi-sampling stages was adopted for the questionnaire administration in order to ensure every segment of Bomo diverse population has been included in the sampling population. It was found that voters do not have adequate knowledge of the party manifesto of their voting interest which gave rise to the party manifesto to remain insignificant indetermining of voters behaviours during the conduct of 2019 presidential poll in Nigeria.For this reason however, it should be one of the viable options for democracy and good governance in Nigeria the effective voters’ education to be taken into cognizance by all electoral stakeholders the party manifesto of registered political parties by all electoral stakeholders.
PEMILIHAN DAN PEMBENTUKAN KATA DALAM BERITA MEDIA CETAK DI KALIMANTAN SELATAN

Journalists have a strong ability to influence society through the language which they use in conveying information. However, some of the journalists do not have proficiency in standard language. Hence, there is a need to study the word choice and formation in printed mass media, published particularly in South Kalimantan. The study is intended for the journalists to use as a reference to improve their proficiency in using language in mass media. Qualitative descriptive analysis is used to describe the data. The data sample consists of 29 news articles from five printed mass media: Radar Banjar, Banjarmasin Post, Kalimantan Post, Mata Banua, and Barito Post. The selected article was published in March 2019. The result showed word choice and word formation errors consist of errors in using conjunctions that link words in a sentence and between sentences, prepositions, loan words, substandard words, and derivatives.
Distilling Double Descent

Distillation is the technique of training a "student" model based on examples that are labeled by a separate "teacher" model, which itself is trained on a labeled dataset. The most common explanations for why distillation "works" are predicated on the assumption that student is provided with \emph{soft} labels, \eg probabilities or confidences, from the teacher model. In this work, we show, that, even when the teacher model is highly overparameterized, and provides \emph{hard} labels, using a very large held-out unlabeled dataset to train the student model can result in a model that outperforms more "traditional" approaches. Our explanation for this phenomenon is based on recent work on "double descent". It has been observed that, once a model's complexity roughly exceeds the amount required to memorize the training data, increasing the complexity \emph{further} can, counterintuitively, result in \emph{better} generalization. Researchers have identified several settings in which it takes place, while others have made various attempts to explain it (thus far, with only partial success). In contrast, we avoid these questions, and instead seek to \emph{exploit} this phenomenon by demonstrating that a highly-overparameterized teacher can avoid overfitting via double descent, while a student trained on a larger independent dataset labeled by this teacher will avoid overfitting due to the size of its training set.
Training Stacked Denoising Autoencoders for Representation Learning

We implement stacked denoising autoencoders, a class of neural networks that are capable of learning powerful representations of high dimensional data. We describe stochastic gradient descent for unsupervised training of autoencoders, as well as a novel genetic algorithm based approach that makes use of gradient information. We analyze the performance of both optimization algorithms and also the representation learning ability of the autoencoder when it is trained on standard image classification datasets.
Effect of Pressure on the Synthesis of Compound Ba0.7Ca0.3TiO3 on the Dielectric Constant

Piezoelectric and ferroelectric ceramic materials are widely used for advanced technology. Barium Titanat is one of the ferroelectric materials that are still widely studied today. In this research, Ba0,7Ca0,3TiO3 was synthesized. The compound was synthesized by the solid reaction method with variations in pressure during the sample compacting process include 10, 20, and 30 kN. Samples in the form of solids (pellets) were calcined at 800 °C and sintered at 1000 °C for 4 hours respectively. The synthesized product was characterized by an LCR meter. The characterization results in the frequency range of 100-200000 Hz show that the pressure affects of the parameters value of the dielectric constant, especially at frequencies 100-10000 Hz. In that frequency range the dielectric constant decreases very sharply, then above 100 kHz the dielectric constant is almost unchanged with increasing frequency.
The Influence of Python on Logical Thinking and Analysis of Teaching Countermeasures

Abstract As a programming language that perfectly fits artificial intelligence and big data analysis technology, the Python language is simple and efficient, easy to learn and easy to understand, which can make students focus more on the problem itself than the details of programming technology, so as to effectively improve the students’ logical thinking ability to solve problems. This paper analyzes the characteristics and advantages of Python language, takes the computer network course as an example, and puts forward the countermeasure analysis to carry out Python programming teaching.
Should Regulators Shame Companies into Compliance

In the internet age, shaming individuals on social media and other online platforms for their behavior has become very common, especially in the #MeToo era. People shame others for all kinds of behaviors, such as parking in handicap spots, or just for being overweight (“fat shaming”). Some people consider such shaming immoral, undemocratic, and disproportionate, although others believe that it can serve as an effective and legitimate civilian deterrent of undesirable behavior.A new kind of shaming is now gaining momentum in an entirely different context: regulatory shaming. Regulatory shaming refers to the publication by administrative agencies of negative information about regulated private bodies, mostly corporations, in order to further public-interest goals.
Bilingual Language Modeling, A transfer learning technique for Roman Urdu

Pretrained language models are now of widespread use in Natural Language Processing. Despite their success, applying them to Low Resource languages is still a huge challenge. Although Multilingual models hold great promise, applying them to specific low-resource languages e.g. Roman Urdu can be excessive. In this paper, we show how the code-switching property of languages may be used to perform cross-lingual transfer learning from a corresponding high resource language. We also show how this transfer learning technique termed Bilingual Language Modeling can be used to produce better performing models for Roman Urdu. To enable training and experimentation, we also present a collection of novel corpora for Roman Urdu extracted from various sources and social networking sites, e.g. Twitter. We train Monolingual, Multilingual, and Bilingual models of Roman Urdu - the proposed bilingual model achieves 23% accuracy compared to the 2% and 11% of the monolingual and multilingual models respectively in the Masked Language Modeling (MLM) task.
Geometric machine learning algorithm helps sieve through structural data of tiny biological objects

By fusing manifold embedding with machine learning, the researchers create an algorithm that can pick out X-ray diffraction patterns of single particles from an ocean of data.
Collecting within the system of sociocultural practices

This article is dedicated to systematization and analysis of the key principles of the social practice of collecting. Analyzing the causes of collecting activity alongside motives and prerequisites for collecting, the author explores the social character of interaction between an object and a human. The article touches upon the phenomenon of personification of things and objectification of people. Significant attention is paid to comprehension of the basic principles of collecting &amp;ndash; a thing as such, and the time as the main condition of transformation of that think into a collectable item. The article reviews the integrated processes of cultural interaction in the course of creation and utilization of collection. Giving characteristics to communication space, the author determines and scrutinizes the three fields of communication: &amp;ldquo;subject &amp;ndash; exhibit item&amp;rdquo; (interaction between the owner of collection and its items); &amp;ldquo;subject &amp;ndash; subject&amp;rdquo; (the entire range of means of communication interaction, which makes a collection public and information rich; and &amp;ldquo;collection &amp;ndash; audience&amp;rdquo; (interactive events created for the formation of cross-cultural communication).
한국의 시와 시가를 한국문화 노래로 만나기

This article will illustrate how Koreanology could find a new way to create more exchanges with the foreign academic world, especially in collaboration with Korean Mass Culture: K-Pop, K-Drama etc. The Culture-based Language Teaching Methods for teaching Korean Mass Culture focused on songs and ballads should be an effective way to broaden access to open Koreanology.Korean Language and Korean Poetry Education could be realized efficiently by Korean Pop songs or Drama OSTs based on the korean poems from the ancient to the modern times. This type of Teaching Korean Language and Poetry can diffuse Koreanology in the world, adopting the emotional tools of Korean Wave in order to narrow down the gap between Korean Culture and Korean Language Learners’ Culture.
CRYPTOCURRENCIES BETWEEN UTOPIA AND REALITY

The typology of cryptocurrencies is a vast one and the existence of approximatively 1400 cryptocurrencies, besides tokens or crypto securities and applications of blockchain technology make the studying of this area of expertise even more difficult. This article intends to broadly understand the cryptocurrencies universe, to present a brief history of cryptocurrencies and their current development stage, while including quantitative data about the top 10 cryptocurrencies and their market capitalization. Other points presented in the article are the lack of regulation of virtual currencies, the influence that virtual coins have on real money, and the behavior of the central banks in regards to cryptocurrencies. Conclusions present an insecure, volatile and uncertainty future of cryptocurrencies.