Reviewerly/exHarmony huggingface dataset:
E - DOCUMENTATION IN PRESCHOOL INSTITUTIONS

E-documentation in preschool institutions is a modern way of keeping pedagogical documentation and recording of educational work in preschool institutions. Implementation of the E-documentation system has a number of advantages: simpler and faster recording of all forms of educational work, monitoring the realization and development of educational work programs, increasing the level of work efficiency, more efficient monitoring of activities - children's progress, improving communication with parents and all relevant factors. The application is a quality basis for the development and improvement of the Basics of pre-school education programs in the development of lifelong learning skills such as confidence, openness, curiosity perseverance, openness and creativity
3D Reconstruction of Video Sign Language Dictionaries

Today virtual and augmented reality applications become more and more popular. Such a trend creates a demand for 3D processing algorithms which may be applied to many areas. This work is focused on sign language video sequences. There are a lot of prerecorded photo and video dictionaries that can be transformed into 3D and uniﬁed in one place. We research nuances of hand pose video sequence analysis as well as the inﬂuence of results reﬁnement for 2D and 3D keypoint detection. Besides that, we designed a solution for the parametrization of hand shape and engineered system for 3D hand pose reconstruction. Model show good results on train data but lack generalization. Retraining on multiple datasets and usage of various data augmentation techniques will improve performance.
Library Guides: Collaborative Research Tools: About

This guide features library resources and other freely-available products that students can use to collaborate remotely.
Research on Voice Conversion from Tibetan Amdo to U-Tsang Dialect Based on Deep Learning

Tibetan Amdo dialect and Tibetan U-tsang dialect belong to the same dialect system of Tibetan. Although they use the same handwritten language, huge differences in pronunciation are caused by historical changes and geographical environment. As a result, Tibetans among different dialects have great difficulties in face-to-face communication. Therefore, we propose a method to realize voice conversion from Amdo dialect to U-tsang dialect. In this work, the problem of voice conversion from Amdo to U-tsang dialect is addressed leveraging upon deep learning framework. The deep model would function as a speech recognizer for Amdo and speech synthesizer for U-tsang. A pronunciation mapping table from one dialect to the other would also be built, which will be used to map phone sequences of U-tsang to Amdo and vice-versa. In the experiment, the input of Amdo dialect speech can be recognized as phoneme sequences. Through the phoneme mapping table, the phoneme sequences of U-tsang dialect are obtained. Then, we use them to synthesize U-tsang dialect speech. In this way, the voice conversion from Tibetan Amdo to U-tsang dialect based on deep learning in non-parallel corpus can be realized. The experiment results show that the converted speech quality and intelligibility are reliable and the original Tibetan Amdo and converted Tibetan U-tsang dialect share many similarities in duration and pitch.
Subject & Class Guides: Remote Library Learning Hub Services & Resources: Additional Support: Resources for Crisis, Work, Wellness, and More

As a result of the COVID-19 pandemic, Helena College has moved as many classes as possible online. This page serves as an up-to-date guide to Library Learning Hub resources and services available during this time.
Whether to delay the release of ebooks or not? an analysis of optimal publishing strategies for book publishers

The eBooks market has been growing rapidly in recent years. At the same time, evidence shows that eBooks are cannibalizing the market for physical books. To alleviate the cannibalization effect bet...
Improving Recommendation Performance with Auxiliary Information

In this article, to utilize available Auxiliary information (AI) for accurate recommendation, we propose a hybrid multitask learning based recommendation approach referred to as IRAI. In contrast to previous researches, IRAI tries to leverage available auxiliary information for representation vector learning for users and items respectively. In theory, IRAI generally focuses on exploiting the intricate hidden relationship within available side information via Gaussian Process method (GP), which could reduce the prediction uncertainty, overcome the data sparsity, and provide effective and efficient item recommendation. In practice, experiments conducted over two real life datasets also could demonstrate the significant superiority of IRAI, which could provide high performance in real life applications.
Large-Scale UAV Trajectory Planning Using Fluid Dynamics Equations

Abstract: Unmanned air vehicles (UAVs), particularly the small UAVs (sUAVs), have found several applications in civil, military and industrial domains. However, before these UAVs can be used in the National Airspace System (NAS), several research problems need to be solved. These include not only guidance, control and navigation but also problems arising from integration in NAS in a safe and reliable manner. Optimization is a very important aspect in aerodynamics and control because it has a significant impact on reducing costs and timely mission completion.
The Effectiveness Of The Implementation Of Health Care And Family Support Therapy For Blood Sugar Levels In Patients With Type 2 Diabetes In Diabetes Center And Kalumata Health Center In Ternate City

Abstract: Diabetes mellitus (DM) is a type of degenerative disease increasing every year in countries whole the world. This disease is characterized by an increase in blood sugar above normal values, because the body cannot release or use insulin adequately. A very high increase in DM will certainly be followed by an increased chronic complications due to poor handling of DM. Optimal glycemic control is a situation where glucose concentration in the blood and HbA1c can be controlled. Therefore, management of DM is needed to stabilize blood sugar levels in DM patients. Management of handling DM patients with health care are education, medical nutrition therapy, physical exercise, pharmacological intervention and family support. The purpose of the study is to analyze the effectiveness of the implementation of health care and family support therapy for blood sugar levels in patients with Type 2 diabetes in Diabetes Center and Kalumata Health Center in Ternate City. The research type is Quasi experimental using Posttest Only Control Group Design. The population was all patients with type II DM, the study sample was divided into 12 treatment groups and 12 control groups. then the data were analyzed using the Independent t-test. The results showed that fasting blood glucose levels had a significant difference between the treatment group and the control group with a significance value = 0,000 (p
Reseña de documentos de archivo como instrumento de divulgación y memoria, analizado a partir del archivo personal de Alfredo Bateman

The archives are conceived as information centers and part of the collective memory, guarantors of citizens' rights and duties. Thus, archival institutions complying with the provisions of the law encourage the organization, conservation, preservation and consultation of archival documents; therefore, archival institutions use instruments to allow access and consultation through inventories, guides, indexes, catalogs. From the theoretical analysis of the archival function, the pertinence of implementing the review of archival documents to understand archives beyond their organization, classification and description, make information visible with an intellectual production where is necessary the archivist work. The review is an instrument that allows academic, investigative, creative and productive performance; likewise, the possibility of extracting value from personal archives is presented by telling the history of the documents through the transmedia narrative. In this context, the proposal for the review of archive documents as an instrument of disclosure and memory was developed, analyzed from the personal archive of Alfredo Bateman.
LibGuides: Virtual Library Resources: Secondary and Beyond

Here you will find all kinds of things to help you as a parent, student or teacher. Extra worksheets, apps to keep your toddler busy, free access to research sites and much, much more. Resources for our Secondary Students and teenagers
Pustakawan Dalam Perspektif Manajer Informasi: Studi Kasus Pada Mahasiswa Jurusan S1 Ilmu Perpustakaan Fakultas Adab dan Humaniora UIN Ar-Raniry

This study aims to find out Librarian in Perspective of Information Manager (Case Study on Library Science Undergraduate Student of Adab and Humanities Faculty of UIN Ar-Raniry, Banda Aceh). This research uses quality descriptive approach, an approach that emphasizes more on the deductive and inductive deduc- tion process and on the analysis of the dynamics of relationship between observed phenomena, using scientific logic. The students of Library Science were observed to be 54 people for three months. For this research the author will explain in detail about UIN Ar-Raniry Banda Aceh Main Library in the perspective of information managers for llibrary users especially Library Science students class of 2016 intake. The research results are; Librarians are not yet fully able to become information managers at UIN Ar-Raniry Main Library of Banda Aceh, due the small number of librarians for this size of a college library. Lack of librarian contribution to be- come information manager, in order to be able to fulfill requirement of information for their users, in this case undergraduate student of Library Science. Regarding the perspective that a library must be able to provide all forms of information required has not been done well, especially the information needs fot this such of users in this case Library Science students.
An Information Delivery System on Disaster for Hearing-Impaired People Using LED Display – To Extend to Universal Use –

There is a sudden blackout on the big disaster. Under such circumstances, people get information verbally by voice, megaphone, and radio instead of looking at screen on PC smartphone, or TV by their eyes. After the big disasters, people have to find a safe place using voice announcements. However, hearing-impaired people cannot get information from voice announcements. Also, it is difficult to distinguish hearing-impaired people from others by their appearances. Therefore, they have little chance to be supported by others. We have researched and created a system for hearing-impaired people get information on the disaster using an LED display. Also, we found such a system is useful for elders and foreigners, too. People cannot use their smartphones as usual because of a shortage of their battery under disinters. Our system was designed to save battery using Bluetooth Low Energy (BLE) and small CPU. Besides, people will co-operate, looking at the same screen under the disaster situation.
Multi-Object Tracking Based on Deep Probability Fusion with Holistic Feature Reprentation and IMM-JIPDA

Among the difficult problem of multi-object surface feature representation, in order to better realize the feature representation method of multi-object and enhance the discrimination of multi-object, a new model of multi-object tracking surface feature representation based on deep probability fusion with holistic feature representation and Interacting multiple model with interacting multiple model joint integrated probabilistic data association is proposed, which is more consistent with the overall video scene understanding. We test the proposed method on data set Multiple Object Tracking 16. The experiment shows that our method has improvements in performance.
LibGuides: Library Technology: Policies

This guide contains a quick-start guide, FAQ, and policies for checking out and using Chomebooks and WiFi Hotspots.
Introduction to Open Source - Introduzione all'Open Source (Florence, Italy, 2012)

Lecturer/Speaker for the AIB Toscana TrainingAccesso all'Informazione e Collaborazione VirtualeCourse funded by the Regional Government of Tuscany9 January - 16 February 2012AIB - Associazione Italiana Biblioteche (Italian Library Association)This is the final version of my presentation.https://orcid.org/0000-0002-8183-8483SlideShare
PERGESERAN BENTUK PADA BUKU BILINGUAL SCIENCE BIOLOGY FOR JUNIOR HIGH SCHOOL GRADE IX

Transposition has a very important role in the translation because the structure of the source language is often different from that the target language. By applying the transposition, then the translator can customize the translation in the target language with a more flexible and easier to read and understand. Without applying the transposition, a translation will be stiff and could even have no meaning because the structure is not adapted to the target language, and it may be very confusing for readers. This study aims at 1) describe the types of transposition that occur in a book translation Bilingual Science Biology for Junior High School Grade IX.
LibGuides: A guide to Children's Literature on Emotional Wellness: Home

Information on children's literature appropriate for grade levels preschool-6th grade. Parents may find this guide useful when trying to locate relatable titles for children to read in order to understand larger, worldy concepts.
Data-Driven Collection Development: The Approval Plan in Today's Academic Library [Slides]

Slides and notes from a presentation given May 2, 2019. This ACRL/Choice webcast looks at GOBI approval plans and demand driven acquisitions (DDA) programs as a means of automatically receiving print and electronic book resources for academic library collections with UNC Greensboro and Texas A&M as examples.
The Application System to Know the Attendance List

SMP 1 Ambawara is one of the biggest junior high schools in this district. Among them there are many prospective students who register at junior high school. The students are enrolled in junior high school, the learning activities experience problems or problems. Some of them have problems in knowing attendance students every day. In today's modern era many advanced technologies are applied by the school. One of the application systems is to be able to know the attendance list of students. With the application system, the problems in presence can be identified quickly using the Delphi 7 application.
MVCC Libraries: Succeed in Online Classes: Strategies for Success

Study tips, useful links, and more to assist students during COVID-19. Learn how to succeed online!
An Efficient Person Reid Methed Based on Knowledge Distillation

Existing Person Reid (Person Re-identification) approaches often only consider how to improve the model generalization performance, which unfortunately comes at the cost of massive computation and storage consumption. Despite that those extensive neural networks are powerful to deal with a specific task and achieve excellent results on many tasks, they are too large to be deployed on edge devices like smart-phones and security cameras. Recently, [5] (Hinton, Vinyals, and Dean 2014) have shown that the dark knowledge within a powerful and massive neural network (a.k.a. teacher) can significantly help the training of a smaller and faster student network (a.k.a. student) and improve performance of the student network. In this work, we investigate the knowledge distillation strategy for training small Person Reid networks by making use of large networks. To this end, we present the Efficient Person Reid model, which is achieved by effective knowledge transferring the dark knowledge of a powerful teacher network. Extensive experiments on Person Reid standard datasets DukeMTMC substantiates the effectiveness of our proposed approach. Particular our efficient Reid model achieves Rank-1/mAP = 86.8%/72.9% on DukeMTMC with only 256 dimensions’ feature vector and with only 3.4M Params.
Perbandingan Klasifikasi Metode Naive Bayes dan Metode Decision Tree Algoritma (J48) pada Pasien Penderita Penyakit Stroke di RSUD Abdul Wahab Sjahranie Samarinda

Classification is a technique to form a model of the data that has not been classified, then the model can be used to classify new data. Naive Bayes is a classification using probability method based on the Bayes theorem with a strong assumption of independence. The decision tree algorithm (J48) is an implementation of the algorithm (C4.5) that produces decision trees. In this research, will be compared the results of classification accuracy with the naive Bayes method and the decision tree algorithm (J48) in stroke patients. That is, a person who has stroke will be classified by using the data of patients in Abdul Wahab Sjahranie Samarinda Hospital with 7 factors, namely age, gender, blood pressure, diabetes mellitus, dyslipidemia, uric acid levels and heart disease. The results showed that the decision tree algorithm (J48) method has the higher level of accuracy than the method naive Bayes for stroke classification.
Implementation of Dijkstra's Algorithm in the Shortest Route

Efficient travel in terms of distance, time and cost are the needs of every traveler.Not all travelers always make careful planning before going on a trip and it could be that the trip is done unexpectedly.In order to help travelers to get a wellplanned trip, technological utilization is needed so that travelers can easily get the shortest distance on the route.Smaller distances can optimize usage costs and possibly travel time.One of them is the creation of the website-based shortest route search destination search application with a mobile friendly display.The dijkstra algorithm is one of the algorithms for determining the shortest route from one tourist attraction to another.The calculation of the dijkstra algorithm begins with determining the node (point) that will be formed into a graph.
Bayesian Mixture Modeling and Order Selection for Markovian Time Series

Author(s): Heiner, Matthew | Advisor(s): Kottas, Athanasios; Munch, Stephan | Abstract: Nonlinearity and high-order auto-dependence are common traits of univariate time series tracking successive states from multidimensional systems. Standard statistical models based on linear stochastic processes are often inadequate to capture these complex dynamics. This work contributes Bayesian statistical methodology and modeling strategies to estimate Markovian transition distributions, particularly when these distributions exhibit non-Gaussianity and/or nonlinear dependence on multiple lags. Given the challenge of modeling high-order nonlinear dynamics, we place emphasis on detecting and exploiting low-order dependence.We propose models for both discrete and continuous state spaces with a common theme of mixture modeling. We first utilize mixtures for soft model selection. To this end, we develop two prior distributions for probability vectors which, in contrast to the popular Dirichlet distribution, retain sparsity properties in the presence of data. Both priors are tractable, allowing for efficient posterior sampling and marginalization. We derive the priors, demonstrate their properties, and employ them for lag selection in the mixture transition distribution model.We then extend the model for estimation and selection in higher-order, discrete-state Markov chains with two primary objectives: parsimonious approximation of high-order dynamics by mixing transition models of lower order, and model selection through over-specification and shrinkage with the new priors to an identifiable and interpretable parameterization. We also extend a continuous-state version of the mixture transition distribution model by admitting nonlinear dependence in the component distributions using Gaussian process priors. We discuss properties of the models and demonstrate their utility with simulation studies and applications to medical, geological, and ecological time series.Finally, we propose and illustrate a Bayesian nonparametric autoregressive mixture model applied to flexibly estimate general transition densities exhibiting nonlinear lag dependence. Our approach is related to Bayesian curve fitting via joint density estimation using Dirichlet process mixtures, with the Markovian likelihood defined as the conditional distribution obtained from the mixture. We extended the model to include automatic relevance detection among a pre-specified set of lags. We illustrate the model by repeating earlier analyses.
Libraries: Submission Workflow in OJS 3: Stage 3 - Copyediting

This guide will help work you through the four stages; Submission, Review, Copyediting, and Production of the OJS submission workflow.
Effect of Input Image Size on the Cancer Cells Identification in Pathological Image

In this research, we conducted to generate Convolutional Neural Network (CNN) models which can distinguish between cancer cells and normal cells in the large intestine under 11 input image size (number of pixels) conditions (50×50 px, 100×100 px, 200×200 px, 300×300 px, 400×400 px, 500×500 px, 600×600 px, 700×700 px, 800×800 px, 900×900 px, 1000×1000 px) for the purpose of clarifying the effect of the input image size on the cancer cells identification in colorectal cancer pathology image. When we conducted to train models, we calculated model accuracy by 5-fold cross validation in each condition. As a result, the accuracy rate increased as input image size increased in 3 conditions (50×50 px, 100×100 px, 200×200 px). However, the accuracy rate of the model trained by 4 conditions (700×700 px, 800×800 px, 900×900 px, 1000×1000 px) were lower than that trained by other conditions. These results are thought to be caused by setting the kernel size to the same value in all conditions. Therefore, we concluded that it is necessary to determine an appropriate kernel size and stride for each input image size which can extracted features included in the input image when we conduct to generate a model for the purpose of distinguish between cancer cells and normal cells in the large intestine.
PENGARUH MODEL PEMBELAJARAN KOOPERATIF TIPE STUDENT TEAMS ACHIEVEMENT DIVISION (STAD) TERHADAP HASIL BELAJAR SISWA PADA MATA PELAJARAN EKONOMI KELAS X SMA N 8 MEDAN TAHUN AJARAN 2019/2020

The purpose of this study was to determine the effect of the Student Teams Achievement Division (STAD) Cooperative Learning Model on Student Learning Outcomes in Economic Subjects in Class X SMA N 8 Medan in Academic Year 2019/2020. This type of research is experimental research with a quantitative approach. The sample in this study were 72 students of class X IPS-1 and X IPS-3. The technique used in data collection is a test of learning outcomes. The analytical method used in this study is the Normality Test and Simple Linear Regression Analysis. From the calculation of the research hypothesis shows that: STAD model has a positive and significant effect on Learning Outcomes, which is indicated by the acquisition value which indicates that the value of t>> 〖t〗 table is (8.752> 1.689) and the significance value (0,000 <0.05).
Mobile learning on organic chemistry course with LINE freeware instant messaging

The use of mobile phones in Organic Chemistry course learning has been performed for Chemistry Education students. This study was a quantitative-descriptive research that collected data with students’ discussion in instant messenger LINE and students’ responses questionnaire. The result showed students having an interest in the discussion topic, having the opportunity to interact with lecturers longer, and increasing the frequency of reading articles related to organic chemicals with mobile phones. From the questionnaire, it can be concluded that students’ responses in this were good.
LibGuides: eBooks: The platforms we have and their features: ProQuest Ebook Central

This guide shows the various eBook platforms that Campbell subscribes to and the features that each have. ProQuests eBook platform