Reviewerly/exHarmony huggingface dataset:
La tutoría como estrategia de la programación académica en la Facultad de Ingeniería Mecánica y Eléctrica de la Universidad Veracruzana en Poza Rica Veracruz, México

Academic tutoring represents a strength of support for all students in their Educational Programs (PE) that they have chosen to complete their professional studies for all higher education institutions. The Faculty of Mechanical and Electrical Engineering of the Universidad Veracruzana in the city of Poza Rica Veracruz, offers 3 PE of Engineering: Mechanical, Electrical and Industrial and in these there is an institutional program of tutoring that contributes in the orientation and advising of the tutorados for the decision making in the academic programming of each school period. The academic programming based on tutoring allows the Faculty to know the demand according to the needs of the students of the Educational Experiences (EE) that they require for a school period. The present work of analytical and descriptive study, shows the processes that are carried out in the Faculty towards an adequate academic programming and implementing with the tutors interview-survey work sessions to gather the required information so that each tutor can program the assignment of their EE For studying, in this case study the sample is a Mechanical Engineering group for the school period February-July 2019.
Resource estimation of the Damanghor gold deposit, based on geology and grade continuity

The selection of an appropriate estimation method is a crucial decision in resource estimation processes. There are multiple resource estimation methods of which the most important one is block modelling. Among the block modelling methods used for the estimation of gold resources, three methods have a broader application. These methods include Inverse Distance Weighting (IDW), Ordinary Kriging (OK), and Full Indicator Kriging (FIK). We compared the results of these three techniques and selected the most appropriate method for resource estimation of the Damanghor gold deposit. For this purpose, we prepared the geometric model of the deposit based on geological continuity and then, conducted the variography procedure to determine the grade continuity and the amount of gold resource. The dataset of the Damanghor area included eight diamond drilling boreholes and eight exploratory trenches comprising the grade results of 405 samples. The results show that FIK is the best method for resource evaluation of this case study. The OK method, however, is not suitable for this deposit. The IDW method provides reliable results when the drilling spacing is less than the variography range. This results can be used for the estimation of inferred resources when the geological continuity is appropriately determined.
Object Tracking with Multi-Classifier Fusion Based on Compressive Sensing and Multiple Instance Learning

Object tracking is a critical research in computer vision and has attracted significant attention over the past few years. However, the traditional object tracking algorithms often suffer from the object drifting problem due to various challenging factors in complex environments such as object occlusion and background clutter. This paper proposes a robust and effective object tracking algorithm, called MCM, which combines compressive sensing and online multiple instance learning in a multi-classifier fusion framework. In this framework, we integrate the different discriminative classifiers by learning the varied and compressed feature vectors based on different random projection matrices. And then an improved online multiple instance learning mechanism SMILE is adopted, which introduces the relative similarity to select and weight the instances in the positive bag. The experiments show that the proposed algorithm can improve the performance of object tracking on the challenging video sequences.
Data Analysis for the Preventive Maintenance of Machinery

This article shows the importance of data for the resolution of current problems, through a case study of preventive maintenance of a company’s machines. From a given inspection of the condition of the machines, enough data is obtained to simulate the operation of the machines under specific conditions using Python programming environment, for a long enough period of time to obtain reliable information about the machines’ lifetime. By using “R”, the statistical analysis of the data is performed to determine the optimal period between repairs, schedule the company’s preventive maintenance and show the possibility of solving complex problems from a simple data set.
MASKININLÄRNING FÖR PREDIKTIV DATAANALYS OCH VISUALISERING

Machine learning has a big influence over many different industries. A lot of research has already been done within this subject, and even more will be done in the future. This project aims to exam ...
PERANCANGAN APLIKASI PENERJEMAH OTOMATIS BAHASA SUNGAILIAT KABUPATEN BANGKA KE BAHASA INDONESIA

Language translator is the process of finding equivalent source language texts (BSU) to be placed as target language texts, in principle language translators aim to help find out the meaning of a particular language. Indonesia has a wide variety of regional languages, one of which is the Sungailiat language of Bangka Regency. sungailiat language is one of the Malay language family. In general, its function is as a means of communication or connecting in daily conversation. In addition, other functions as a sign or an identity or a symbol of pride in the Bangka Belitung Islands Province. in this study the researcher will design / blueprint an android application that functions to translate the sungailiat language into Indonesian automatically using the voice or text feature. Keywords: translator, design, application, real estate, language
Optimalisasi Layanan Perpustakaan Berbasis SIPRUS Di Perpustakaan UIN Sunan Kalijaga Yogyakarta

&lt;p&gt;Basically, library can provide fully information, and rather quickly in accordance with the needs of users. This research the optimization of the library information system through using the existed features, and hopefully, it can increase the service for the users. This research is using the qualitative approach method, and this is also field research. Based on the analysis of the results using the SDLC method, SIPRUS (Library Information System) is the library database collection of the State Islamic University of Sunan Kalijaga. This system uses MYSQL which means Open Resource-Based. SIPRUS has the same task to collect, process, conserve, refind the information, borrow and restore the book to the circulation section, and statistical functions to know the user's data, the library uses information technology to collect data as the library collection. In accordance with this analysis of the results, it can be said that OPAC is very helpful for users in searching for efficient and effective information.&lt;/p&gt;
Citation Analysis of Doctoral Dissertations in Animal Physiology Division Submitted to NDRI, Karnal, Haryana, India

ABSTRACT Citation Analysis is a scientific method of measuring frequency and pattern of research information citations in research papers to establish linkage of one research document to another revealing their importance and properties .  The present investigation aims to study the scientific literature use pattern through the Citation Analysis of doctoral dissertations.  For this five doctoral dissertations (P – 1541, P – 1535, P – 1507, P – 1506 and P – 1518) submitted to Animal Physiology Division, ICAR – NDRI, Karnal during the year 2017 were considered as base reference. The Citation Analysis of these five doctoral dissertations  revealed that out of  total 1628 citations,  highest 1477 numbers ( 90.72 % ) were cited from journals, followed by 73 (4.48%) from subject matter books and rest 78 numbers (4.80 %) from   scientific magazines, conference proceedings, theses,  etc.
ANALISIS PELAYANAN PENANGGULANGAN BENCANA KEBAKARAN OLEH PEMADAM KEBAKARAN PEMERINTAH (STUDI KASUS KOTA PONTIANAK)

Disasters are events that can occur anytime and anywhere, as well as fire disasters. Along with the frequent occurrence of fire disasters, it is necessary to provide effective, fast response services for fire disasters. Fires occur due to many factors. To reduce losses, it is necessary to improve services to fire services from the government which is one of the minimum services of the government. Analysis is a thinking activity to describe a whole as a component so that it can recognize the signs of components, their relationships with each other and their respective functions in an integrated whole. Service analysis is here to measure fire service levels in Pontianak City. This research is a descriptive qualitative research Measurement of service quality by using 5 (five) dimensions with several indicators of each dimension of Tangible, Reliabelity, Responsiviness, Assurance, Emphaty. Based on the results of research conducted stating that the fire disaster management service carried out by the Pontianak City Fire Department was not optimal This is because there are still problems faced by the Pontianak City Fire Department where firefighting organizations are not yet independent, lack of facilities and infrastructure, lack of resources humans, lack of fire stations, less attention to the apparatus regarding the safety guarantee of fire services especially.
간호대학생의 자기주도적 학습전략이 이러닝 사전학습 성과에 미치는 영향: 플로우 경험을 매개로

Purpose: The purpose of this study was to investigate the effect of self-directed learning strategies on e-learning pre-learning focusing on the flow experience. Methods: A structured self-report questionnaire was used to measure learning outcome achievement, pre-learning satisfaction, learning persistence, flow experience, and self-directed learning strategies. Data were collected from September 3~7, 2018. Participants were 150 nursing students studying at a university in D city. Data were analyzed using t-test, one-way ANOVA, Pearson correlation coefficients, and hierarchical multiple linear regression with the SPSS/WIN 23.0 program. Results: The flow experience had a partial mediating effect between self-directed learning strategies and pre-learning satisfaction (β=.73, p<.001). Also the flow experience had a partial mediating effect between self-directed learning strategies and learning outcome achievement (β=.17, p=.020) and learning persistence (β=.24, p=.001). Conclusion: Results suggest that flow experience has a positive effect as a mediating effect in the relationship between self-directed learning strategy and pre-learning satisfaction, learning outcome achievement, and learning persistence. Therefore, it is necessary to identify education methods that include flow experience with self-directed learning strategies.
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Consideration on application of the concept of Saak transform to convolutional neural networks

In this paper, we consider applying the concept of Saak (Subspace approximation with augmented kernels) transform to the convolutional neural networks (CNNs). In CNNs, the activation function known as ReLU (Rectified linear unit) is widely used for image or signal processing applications, e.g., image classification, image super resolution, etc. Activation functions including ReLU discards negative values of the input to achieve nonlinear input-output relations. In CNNs, therefore, ReLU discards negative values of filter outputs although those negative values may have equal importance as positive values in image processing. The Saak transform is proposed to utilize the information carried by the negative values. In this paper, we consider the CNN architectures to utilize the concept of Saak transform by introducing a modified ReLU which discards positive values. Then we show that we can construct several CNN architectures based on the concept of Saak and the modified ReLU. To see the possibility of the proposed architecture, we apply them to the image classification and consider the validity from the results.
Segmentation of Soft Tissues from MRI Brain Images Using Optimized KPCM Clustering Via Level Set Formulation

An important approach for medical images is image segmentation. Image segmentation is the way toward to eradicate the area of attentiveness by making various segments in an image. This segmentation helps to analyze the representation of image in an easier manner. The segmentation of an image in medical image analysis is considered as one of the challenging tasks in many clinical applications due to noise, poor illumination changes, and also the intensity inhomogeneity. In order to have segmentation of soft tissues from magnetic resonance imaging (MRI) brain images, a new approach had been proposed known as “optimized kernel possibilistic fuzzy c-means (OKPCM)” algorithm using a level set formulation. The proposed algorithm consists of two stages: In order to improve clustering efficiency in the preprocessing, we introduced a hybrid approach which is called particle swarm optimization (PSO) algorithm followed by kernel possibilistic fuzzy C-means (KPFCM) clustering. Firstly, with the help of PSO algorithm, automatically the optimal cluster centers are calculated. Later, these optimum cluster values acted as a cluster centers for KPFCM clustering in order to ameliorate the clustering efficiency. The membership function (MF) of the conventional clustering algorithms, i.e., FCM, PCM along with KFCM, was sensitive to the noise and outliers. The preprocessing segmentation results suffer from boundary leakages and outliers. So, to overcome these drawbacks, it is necessary to use post-processing where we introduce the level set method. The level set method utilizes the efficient curve deformation which is driven by an external and internal force in order to capture the important structures (usually edges) in an image as well as curve with minimal energy function is defined. The combined approach of both preprocessing and post-processing is called as optimized kernel possibility fuzzy c-means (OKPFCM) clustering using level set method. The accuracy and the noise effect in those images can be upgraded by using this method.
Forecasting the USD/SEK exchange rate using deep neural networks

This thesis is about predicting the average ten minute closing bid price of the USD/SEK exchange rate by applying deep learning methods. First, the time lag method is applied for the vanilla Feedforward Neural Network (FNN) to undertake one-step prediction. Secondly, three univariate Long Short-Term Memory (LSTM) models are used to undertake one-step and multi-step prediction. Each network is theoretically described and motivated. The results indicate that both the FNN and LSTM are applicable to time series prediction and that the LSTM outperforms the FNN. Furthermore, the results suggests the LSTM can outperform the naive predictor by a small margin but it remains uncertain. It is concluded that to detect structure in the exchange rate much more computing power might be required to learn from significantly longer time series as input. Finally, some economic theory is reviewed and presented which could be used as potential inputs improving the results. A small discussion on overlooked biases is also included. (Less)
LibGuides: Business: Find Articles

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An Exploration for Operational Audits: A Polymerization Focused Imposed Model

The objective of the work is to investigate expanding electronic business associations comprehend the hugeness of researching the online studies of their things. It is acknowledged that online review examinations fundamentally influence forming thing brand and arrangements headway. In this paper, we proposed a Polymerization Point Conclusion Model (PTSM) to coordinate printed assessment for online studies. We applied this model to focus and channel the inclination information from online studies. Through fusing this model with AI systems, we got a result which demonstrated that the conjecture precision had been improved. Besides, the exploratory results show that filtering feeling focuses concealed in the reviews are progressively huge in influencing bargains desire and the PTSM is more careful than various procedures. The revelations of this assessment add to the data that isolating the supposition purposes of online studies could improve the desire precision. In like manner, it could be applied by web business specialists as another system to lead examinations of online reviews.
Hoshi: A Japanese morphological adorner for TEI XML

Abstract Morphological adornment of text in Text Encoding Initiative (TEI) XML can be useful for studies in textual analysis. MorphAdorner is a principal tool for providing such functionality in English texts. However, its practical use is limited when the input XML contains branching text, e.g. when &amp;lt;choice&amp;gt; appears, as it modifies the input document. In such cases, preprocessing is required to obtain the desired results. This article introduces a new tool Hoshi with the purpose of determining how this issue can be best handled with minimal input modification and preprocessing needed. It also investigates whether parsing software available online can be used to supply morphological information that can be encoded in an output format like MorphAdorner, and whether such a tool can be developed to adorn text in other languages. Challenges include those posed by the target language, the current software available for providing morphological analysis in it, and the schema needed for encoding the results. Moreover, technical hurdles presented by segmented and branching text can complicate the alignment process, especially when the intent is to guarantee input document integrity. Our approach for handling these is presented, and the article ends by outlining future applications of Hoshi that can help to enhance TEI scholarship that prioritizes the use of morphological word metadata.
More Than Coding

In order to prosper as a society, science, technology, engineering and mathematics (STEM) education needs to be a focus for all stakeholders and at all levels. The acronym of STEM was itself coined by the National Science Foundation in the United States in the mid 1990s. The big ideas of science are both interdisciplinary and transdisciplinary and thus provide a conceptual basis for STEM initiatives in education and beyond. By choosing real-world scenarios and challenges as teaching contexts, STEM education is an exciting way of enhancing children’s natural curiosity in science and showing them the relevance of science to their future. There is a global policy push for space to be found to accommodate and integrate STEM learning and teaching into classroom activities. STEM education is certainly much more than the integration of digital technologies into practice. The chapter also presents an overview of the key concepts discussed in this book.
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Things are rapidly changing here at UTA due to the COVID-19 CoronaVirus outbreak. If you have questions about what resources will be available to you during this time, check out this FAQ page first.
THE IMPACT OF CORRUPTION ON FINANCIAL DEVELOPMENT IN AFRICA

This study examines the impact of corruption on financial development in 50 African countries during the period 2000 â 2014. The study uses dynamic system GMM estimator because it take care the endogeneity and country-specific-effect problems that may arise in panel data estimation. The results show that control of corruption, bank branches, human capital are highly determine financial development in Africa. The results provide empirical evidence for African policy-makers to introduce polices that aim to lower and to control corruption and to cover large areas by commercial bank branches in addition to invest more in the education of human capital.
THE USE OF VIDEO BLOG (VLOG) TO DEVELOP STUDENTS’ VOCABULARIES (A Classroom Action Research at the Seventh Grade Students of SMP AL-HUSNA JAWILAN in the Academic year 2018/2019)

Adriyani Zein. 152301863. 2019. The Use of Video Blog to Develop Students’ Vocabularies. (A Classroom Action Research at the Seventh Grade Students of SMP AlHusna Jawilan Academic Year 2018/2019). This research is “The Use of Video Blog to Develop Students' Vocabularies (A Classroom Action Research at the seven grade students of SMP Al-Husna Jawilan). It consists of two problem statements: 1) How is the student’s vocabulary in learning noun on the seventh-grade students of SMP Al- Husna Jawilan. In the academic year of 2018/2019? 2) How is the implementation of vlog to develop vocabulary mastery on the seven grade students of SMP Al-Husna Jawilan. In the academic year of 2018/2019? The objective of this research such as 1) To develop vocabulary in learning nouns on the seven grade students of SMP Al-Husna Jawilan. In the academic year 2018/2019. 2) To describe the implementation of vlog to develop vocabulary mastery on the seven grade students of SMP Al-Husna Jawilan academic year of 2018/2019. This research consists of two cycles. They are planning, acting, observing, and reflecting. The subject of the research consists of 31 students of VII at SMP Al-Husna Jawilan. The instruments of this research test which analyze by quantitative analysis and observation sheet which analyze by qualitative analysis. The result of the research showed that there is a significant improvement in the students’ vocabulary after using visual media. This statement could prove by the students’ mean score the ability test was 57.68, it increased to 64.81 in the first cycle and 83.42 in the second cycle. The students’ vocabulary from the first cycle to the second cycle increased. It means the Video blog can develop the students’ vocabulary
El pensamiento de los docentes sobre el uso formativo del teléfono móvil

This study analyses the idea which Secondary School and Vocational Education teachers have of the educational use of smartphones in the classroom. Educational institutions must be aware of the especial influence of these gadgets in our current society and should strive to integrate and normalize these potential educational tools. The research has been raised by sending a questionnaire to teachers, getting a sample of 42 answers. We carried out an exploratory and descriptive study throughout the results obtained, applying a quantitative approach with univariate and bivariate statistical analysis in order to obtain the maximum information on the crossing of variables: The results show that the teachers have knowledge about some educational experiences using the mobile phone as well as show interest in learning how to carry out their educational integration in the classroom, being more flexible and receptive teachers the younger, who also show a higher level of ICT knowledge. Through this study we have tried to continue another one already started three years ago, therefore we have compared the current results with those obtained then, appreciating a positive evolution regarding the uses, attitudes and educational possibilities that teachers perceive on the mobile phone.