Reviewerly/exHarmony huggingface dataset:
Diagnostic Statistics and Predictive Statistics as a Re-Definition to Inferential Statistics

The traditional way for statistics in any statistical book starting with descriptive statistics, followed by Probability and ends with inferential Statistics. The probability is considered as the link between descriptive and inferential statistics. Inferential Statistics has wide definition and is defined as “the branch of statistics concerned with using sample data to make inferences about a population. In inferential statistics, predictions are made and conclusions are drawn for the target population based on the sample”. The main topics of inferential statistics are Estimation, Testing Hypotheses about means, variances, goodness of fit and proportions, Correlation, Regression and Time series. In this article we are trying to organize the statistics by splitting the inferential statistics into two parts, namely Diagnostic Statistics and Predictive Statistics and explaining the importance of each part. Also we will discuss a Perspective Statistics. Based on that we will have four levels in statistics that can be used to analyze data (Descriptive, Diagnostic, Predictive and Perspective Statistics). Descriptive statistics are primarily concerned with graphs, frequency tables, measures of central tendency, measures of variation, and measures of shape. Diagnostic statistics are primarily concerned with the effects of the Independent variables (inputs) on the Dependent (Target) variable, as measured by Tests of Correlation or Association, Tests for Mean Differences, and Tests for Classification. Predictive statistics are primarily concerned with estimation, regression techniques, and time series analysis for the dependent (target) variable. Perspective statistics mainly related to the previous three levels and acts as a prescription to how to solve or prevent the problem, which means to take a decision in advance. In this article, we will clarify idea through giving an example on a real data related to Gynecologic Cancer, and show how the perspective analytics can prevent it.
한국 금리, 환율, 주가의 수익률과 변동성 간의 동적 연계성

Purpose - This research aims to examine the dynamic interaction of return and volatility of interest rate, exchange rate and stock price in Korea. For this, we investigate the volatility spillovers, volatility asymmetric effects and pricing of uncertainty to asset price returns of each market. Design/methodology/approach -The sample period is from the beginning of 2001 to the December 28, 2018. Total 4,386 daily data are analyzed using the multivariate GARCH model framework. Findings -The result are as follows. First, the DCC GARCH model with student t error distribution is the most superior than other multivariate GARCH models. Second, there are bidirectional volatility spillovers between interest rate and exchange rate. However, the spillover from exchange rate to interest rate is disappeared when the global financial crisis dummy variables are included in the model. Third, the volatility asymmetric effects are found in exchange rate and stock price. However, the negative shock of exchange rate return decrease the volatility of foreign exchange market, while that of stock price return increase the volatility of equity market. Finally, the uncertainty of equity market influences on other markets’ asset returns as well as its own price return. However, equity market uncertainty has a negative effect to bond market return, while it have a positive effects to foreign exchange and equity market. Research implications or Originality - This study can provide a better understanding of the dynamic linkage between Korean financial markets and the nature of the risks that market participants have to deal with. For the future analysis, the expansion of the analyzing countries, more exquisite sample periods segmentation, and the policy establishment for financial market stabilization are needed.
Project: ScreenshotMatcher - Taking Smartphone Photos to Capture Screenshots

Project: ScreenshotMatcher - Taking Smartphone Photos to Capture Screenshots Application that allows creating screenshots of a computer screen by photographing it with a smartphone. Status: ongoing Runtime: 2020 - Participants: Andreas Schmid, Thomas Fischer, Alexander Weichart, Alexander Hartmann)
Model, sample, and epoch-wise descents: exact solution of gradient flow in the random feature model

Recent evidence has shown the existence of a so-called double-descent and even triple-descent behavior for the generalization error of deep-learning models. This important phenomenon commonly appears in implemented neural network architectures, and also seems to emerge in epoch-wise curves during the training process. A recent line of research has highlighted that random matrix tools can be used to obtain precise analytical asymptotics of the generalization (and training) errors of the random feature model. In this contribution, we analyze the whole temporal behavior of the generalization and training errors under gradient flow for the random feature model. We show that in the asymptotic limit of large system size the full time-evolution path of both errors can be calculated analytically. This allows us to observe how the double and triple descents develop over time, if and when early stopping is an option, and also observe time-wise descent structures. Our techniques are based on Cauchy complex integral representations of the errors together with recent random matrix methods based on linear pencils.
Image Dehazing with Scattering Coefficient Estimation using CNN-based Image Regression

The estimation of the scattering coefficient in depth image-based dehazing is of paramount importance. Since scattering coefficients are used to estimate the transmission image for dehazing, the optimal scattering coefficients for effective dehazing must be obtained depending on the level of haze and fog generation. In this study, we performed a CNN-based image regression to obtain the optimal scattering coefficients for each image with fog and haze. A three-channel image was used as the input data, and the learning was performed with approximately 2,000 labeled synthetic haze and fog datasets. Subsequently, the transmission image was estimated using the scattering coefficient obtained for the input image through the learned model, and the depth image was obtained through the LiDAR point cloud projection for performing the dehazing. This paper presents a qualitative and quantitative comparison of the results obtained using the proposed dehazing technique with those obtained using the existing dehazing algorithms.
Video and media technologies in the educational space as a form of mental representation of students of different cultures

The search for conditions to create a developing learning environment, methods and means of teaching is the main objective of psychological science. The relevance of the problem under study is due to the active development of intercultural communication processes, in which advertising plays an important role. This circumstance requires the inclusion of video and media technologies in the training of specialists in the field of advertising. The purpose of the paper is to describe the course and the results of the study of imaginal representations in advertising aimed at promoting goods in different cultures. The leading method in the study of this problem was the semantic differential which allows one to identify the difference in the semantic content of the commercial of a popular drink produced by an international company. Fifty students who are representatives of religious and non-religious cultures, aged between 18 and 30 participated in the study. The authors of the paper put forward the assumption that since social representations are formed and depicted in different cultures which are different from the social representations of other cultures, the content of the advertising text will be interpreted in different ways. This can affect people’s behavior of different cultures. The content of imaginal representations was studied in the process of perceiving the advertisement of a popular drink. The results of the study showed a significant difference in the content of imaginal representations of the experimental groups. However, the study showed that this difference did not influence consumers’ behavior. The materials of the paper may be useful for psychologists studying intercultural differences, as well as specialists in advertising psychology, when developing advertising texts for multicultural goods and services.&#x0D; Keywords: video and media technologies, imaginal representations, advertisement, culture, types of cultures, behavior.
The smartest time of the year

Our Techonologist compares the best of smartwatch technology and speaks to the companies behind the products.
La capacidad creativa en los sistemas de inteligencia artificial y sus consideraciones en el derecho de autor (Creative Capacity of Artificial Intelligence Systems and How They Are Considered by Copyright Law)

Spanish Abstract: El debate que se concibe en este articulo gira en torno a la creacion de obras por sistemas de Inteligencia Artificial (IA) y su fin es determinar si es posible que dichas creaciones puedan estar bajo el amparo de la proteccion de derechos de autor. Esta problematica es importante ya que son muchas las obras artisticas, como pinturas, canciones, traducciones, libros o articulos que se crean a partir del uso de la IA. Para el desarrollo de este objetivo se analizaron los componentes de una obra y, ademas, se evaluo si una pieza escrita por un sistema de IA cuenta con dichos requisitos1. Igualmente, se investigaron varias doctrinas y sistemas normativos internacionales que han asumido diferentes puntos de vista sobre este debate, un punto en el que se coincide es que la creatividad artificial nunca podra equiparar a la del intelecto humano, sin embargo, el aporte que se concluye de esta investigacion es que es necesario regular especificamente las obras creadas por IA. English Abstract: The debate conceived in this article revolves around the creation of works by artificial intelligence systems (IA). The purpose is to determine if it is possible that such creations may be protected by Copyright Law. This issue is important since there are many works, such as paintings, songs, translations, books, and articles, which are created using AI. To develop this objective, an analysis of the components of a work was carried out and, in addition, it was evaluated if a work written by an AI system has these requirements. Likewise, several of the researched doctrines and international normative systems have assumed different points of view on this debate, a point where they coincided is that artificial creativity can never equate that of the human intellect. However, the contribution that is concluded in this paper is the need create a specific regulation for works created by IA.
GUESTBOOK SYSTEM FOR LABORATORY SECRETARIAT DURING COVID-19 PANDEMIC

“Go Green Campus” is a university program that requires all elements on campus to minimize the use and waste of paper and plastic. This encourages the transition from paper data collection to digitizing data storage to computer media. The Guest Book web application for Secretariat Lab of Faculty of Computer Science (FIK) Universitas Pembangunan Nasional Veterans Jakarta (UPNVJ) is a website-based software to facilitate the process of collecting visitor’s data who visit the FIK lab secretariat room. This application can replace the previous conventional guestbook to digital. The application built using the waterfall method and using the PHP programming language with the Laravel framework and MySQL database running on a local server. The Guestbook Web-based system for the Secretariat of the Laboratory of the FIK, UPNVJ can gather student’s data who visit the FIK lab secretariat room and the information can be downloaded in pdf and excel form. This web application also provides features such as covid-19 self-screening survey, news information, critics and suggestions, and the activity log list. The system that has been developed has also passed the security aspect test, reliability aspect test, portability aspect test, usage aspect test and is able to carry out the designed process.
Environmental Computing and Community Engagement in STEM education: Building Effective and Sustainable Relationships.

Earth and Space Science Open Archive Presented WorkOpen AccessYou are viewing the latest version by default [v1]Environmental Computing and Community Engagement in STEM education: Building Effective and Sustainable Relationships.AuthorsMorewellGasselleriDDavidBrooksTimothyGlaudeKennedyJefferyiDHibaAbdelazizSee all authors Morewell GasselleriDCorresponding Author• Submitting AuthorXavier University of LouisianaiDhttps://orcid.org/0000-0002-0645-1852view email addressThe email was not providedcopy email addressDavid BrooksInstitute of Earth Science Research and Educationview email addressThe email was not providedcopy email addressTimothy GlaudeXavier University of Louisianaview email addressThe email was not providedcopy email addressKennedy JefferyiDXavier University of LouisianaiDhttps://orcid.org/0000-0003-3217-3187view email addressThe email was not providedcopy email addressHiba AbdelazizXavier University of Louisianaview email addressThe email was not providedcopy email address
Cross-lingual Intermediate Fine-tuning improves Dialogue State Tracking.

Recent progress in task-oriented neural dialogue systems is largely focused on a handful of languages, as annotation of training data is tedious and expensive. Machine translation has been used to make systems multilingual, but this can introduce a pipeline of errors. Another promising solution is using cross-lingual transfer learning through pretrained multilingual models. Existing methods train multilingual models with additional code-mixed task data or refine the cross-lingual representations through parallel ontologies. In this work, we enhance the transfer learning process by intermediate fine-tuning of pretrained multilingual models, where the multilingual models are fine-tuned with different but related data and/or tasks. Specifically, we use parallel and conversational movie subtitles datasets to design cross-lingual intermediate tasks suitable for downstream dialogue tasks. We use only 200K lines of parallel data for intermediate fine-tuning which is already available for 1782 language pairs. We test our approach on the cross-lingual dialogue state tracking task for the parallel MultiWoZ (English -> Chinese, Chinese -> English) and Multilingual WoZ (English -> German, English -> Italian) datasets. We achieve impressive improvements (> 20% on joint goal accuracy) on the parallel MultiWoZ dataset and the Multilingual WoZ dataset over the vanilla baseline with only 10% of the target language task data and zero-shot setup respectively.
Reprogramando la Universidad Sénior para un modelo de enseñanzaaprendizaje semipresencial

espanolEn este trabajo se describe como se realizo la adaptacion de la Universidad Senior de la Universidad de A Coruna a un modelo de ensenanza-aprendizaje semipresencial en el curso 2020/2021 motivada por la situacion de emergencia sanitaria debida a la COVID-19. En el proceso de reprogramacion se tuvieron en cuenta, por una parte, las necesidades de nuestro personal docente y, por otra parte, las necesidades de formacion de nuestro estudiantado, que hubo de romper la barrera tecnologica e incorporar las nuevas tecnologias para el seguimiento de la docencia. En el trabajo se recogen los resultados de las encuestas al inicio a docentes y estudiantado, una descripcion del nuevo Programa de Formacion Especifico “Actualidad, Ciencia., Salud y Vida” y, por ultimo, un analisis de la satisfaccion con el nuevo programa desde el punto de vista de todos los agentes implicados: docentes, estudiantado y equipo de direccion y gestion de la Universidad Senior. Tanto docentes como estudiantes se muestran, en lineas generales, muy satisfechos con el modelo semipresencial que permanecera en los siguientes cursos como complemento formativo a la docencia presencial. EnglishThis work describes the adaptation process of the Senior University (University of A Coruna) to a blended teaching-learning model, in the academic year 2020/2021, motivated by the health emergency situation due to COVID. On the one hand, the needs of our teaching staff and, on the other hand, the training needs of our students, who had to break the technological barrier and to incorporate new technologies in order to attend classes, were taking into account in the scheduling process. The work includes the results of surveys to teachers and students at the beginning, a description of the new specific training program “Present, Science, Health and Life”, and finally, an analysis of satisfaction with the new program from the point of view of all the agents involved: teachers, students and management team of the Senior University. Both teachers and students are, in general, very satisfied with the blended model that will remain in the following courses as a training complement to face-to-face teaching.
Psychological Factors of EFL Students on Speaking Performance

This research aimed to explore the psychological factors that caused college learners felt hard in delivering speaking performance. This study was conducted to the fifth semester English program students at IKIP PGRI Pontianak. The 37 students were chosen as the participant of this study which was obtained by doing purposive sampling. It was chosen since the problem occurred in IKIP PGRI Pontianak specifically at the fifth semester students. The research design used in this research was descriptive qualitative and quantitative design. The data were taken from online questionnaire and semi structured interview of students. The questionnaire was employed to find out the dominant factor. The other tool of collecting data was students’ semi structured-interview. It was used to support the questionnaire data. The researcher revealed that the psychological factor including anxiety, shyness, lack of confident, lack of motivation, and fear of making mistake were some factors that influenced students’ speaking performance. The researcher investigated that between five aspects, the dominanat factors influenced the students’ speaking performance was anxiety with the mean score (2,06). They worried to do speaking performance. Another factor were shyness, lack of confident, lack of motivation, and fear of making mistake, those factors hindered learners to practice their speaking ability in front of the class. The conclusions of this research were students feel anxious and afraid of making a mistake when they did speaking performance. This study suggested that the lecture should aware those factors affected students’ speaking performance in the class.
Interacting Multiple Model Estimator with Output Reference Learning

A class of interacting multiple model (IMM) estimators are regarded as one kind of instrumental tool to estimate the state of jump Markov systems, in which the overall estimate only can be considered as output. In this paper, the overall estimate is used to design output reference learning terms in the IMM estimator and they are utilized to update the mode-conditioned estimates recursively. Finally, simulations are presented to testify the validity of proposed estimator.
Effect of cyclical short-time exercise on metabolic syndrome indicators and behavioral fitness

The purpose of this study was to examine the effect of cyclical short-time exercise on metabolic syndrome indicators and behavioral fitness. To this end, a cyclical short-time exercise program was constructed and the study subjects were selected as 10 exercise groups who could participate in this program and 10 subjects from the comparison group who could compare the effects of cyclical short-time exercise. Changes in metabolic syndrome index and behavioral fitness were compared by participating in 30 minutes of exercise 3 times a week for 8 weeks.<BR> Through these goals and procedures, the results of the 8 weeks before and after are as follows.<BR> First, in the metabolic syndrome index of the exercise group and the control group subjected to the short-term cyclical exercise program, there were significant interaction effects in LDL and TG, but no significant interaction effects in TC and HDL.<BR> Second, in the change in behavioral physical strength of the exercise group and the control group subjected to the cyclical short-time exercise program, there were statistically significant interaction effects in muscular endurance, flexibility, agility, and agility except for muscle strength.
Efek Google Meet: Sebuah Aplikasi Berbasis Pembelajaran Dalam Pembelajaran Bahasa Inggris Kala Wabah Covid-19

The Covid-19 outbreak has had a significant impact on our educational system. As a result of this situation, teachers have decided to switch from face-to-face to online learning. Furthermore, this circumstance resulted in low student motivation to learn English. In other words, due to monotonous learning, pupils may be too bored to participate and engage in the teaching-learning process. Some pupils were discovered to be late or unwilling to finish their homework. Google has published a number of applications as part of its Google For Education program so that instructors can use to improve their information technology (IT) oriented teaching and learning. Google Meet is one of the most popular programs that is currently available for free. This research explains how to use Google Meet as an alternate application for online learning during the outbreak, such as delivering a virtual English classroom and to make students comfortable in learning English. This paper will go through some of the theoretical and practical reasons why English teachers should be more comfortable with online learning using Google Meet. Although additional research is needed to determine the efficiency of this application in improving students' learning, it is considered that incorporating this technology into the teaching process can fundamentally revolutionize a typical classroom in many ways.
Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

We study the power of cross-attention in the Transformer architecture within the context of transfer learning for machine translation, and extend the findings of studies into cross-attention when training from scratch. We conduct a series of experiments through fine-tuning a translation model on data where either the source or target language has changed. These experiments reveal that fine-tuning only the cross-attention parameters is nearly as effective as fine-tuning all parameters (i.e., the entire translation model). We provide insights into why this is the case and observe that limiting fine-tuning in this manner yields cross-lingually aligned embeddings. The implications of this finding for researchers and practitioners include a mitigation of catastrophic forgetting, the potential for zero-shot translation, and the ability to extend machine translation models to several new language pairs with reduced parameter storage overhead.