Reviewerly/exHarmony huggingface dataset:
Analysis on School-enterprise Co-construction of "Semiconductor Device" Course

device course is a professional basic course for students majoring in electronic information science and technology, and is also a required course for the school-enterprise cooperative class in our college. The enterprise requires the students to be able to combine theory with practice and have the ability to solve practical problems. Because this course has the characteristics of high basic theory requirement, strong comprehensiveness and abstract content, our college work together with an enterprise for the semiconductor device course. To construct the Semiconductor Devices course by school and enterprise jointly can strengthen the linkage between them, which is of great significance for deepening the reform of application-oriented personnel training mode, deepening the reform of teaching content and teaching methods, highlighting the cultivation of students' practical ability, innovative and entrepreneurial ability, and improving the quality of personnel training. Jointly, by building a teaching team, making a course standard, improving the teaching files, developing the teaching resources, compiling the textbooks and examining the students, We have built an excellent teaching team with theoretical knowledge and practical experience, standardized and enriched various teaching documents and resources, and finally improved students' interest and enthusiasm in learning. Students could master the theoretical knowledge, at the same time possess the operational skills. High-quality talents who can meet the market demand have been cultivated.
PNS203 Machine Learning for Subpopulation Analysis in Datasets without Control Arm

Develop machine learning (ML) and predictive analysis models to identify patient attributes and biomarkers predictive of a particular outcome – desirable or undesirable. This can be used in one arm clinical trials and real world data towards various outcomes including disease-free survival and adverse events. We used decision trees to rank the top biomarkers splitting criteria and validated them using hypothesis tests. We used these to develop ML models predicting the mortality of sepsis patients. 10-fold cross-validation was performed using the best parameters from the grid search to predict the study outcome. The finalized decision tree has at least 30 samples on each node and returns the biomarkers splitting criterion of each node until maximum depth reaches five. We used Receiver Operating Characteristic (ROC) to assess model performance. permutation tests were applied for splitting criterion validation plus survival status. We then applied scanning algorithms to search all values of each variable. After data splitting found each threshold, log-rank tests of Kaplan-Meier survival curves and likelihood ratio tests from Cox proportional hazard models were applied, testing for survival variances. The decision tree method returned three sub-groups with differentiated outcomes, and the information gain increased by an average of 0.2 for each one. Assessed cutoffs based on the splitting criteria from the decision tree, Kaplan-Meier and Cox Regression models showed statistical significance of the outcome of the optimal sub-group vs. the rest. ML models and survival analysis used to extract optimal sub-groups enhances identification of the differential outcome between sub-groups in clinical trial data without a control arm. We envision that these algorithms have the potential to do subpopulation analysis of clinical trial data as well as real world data when having a control arm is not practical.
SKILLS IMPROVING PROCEDURE TEXT WRITING THROUGH THE NUMBERED HEAD TOGETHER (NHT) TYPE LEARNING MODEL IN THE FIRST MIDDLE SCHOOL STUDENT

The purpose of this study is to improve students' skills in writing procedural texts using the Inquiry learning model. This research is a classroom action research. This research activity was carried out in two cycles using data collection techniques, observation sheets, and assessment sheets. Data were analyzed in three stages, namely data reduction, data exposure, and conclusions. From the results of this study, it is evident that there is an increase in the skills of students in writing procedural texts using the numbered head together (NHT) type learning model in cycle I, with an average value of 59,16% and cycle II, with an average value of 80,65%.
Ways to increase the prospects for youth participation in the innovation sphere of the country

The article provides a socio-philosophical analysis of the innovative activity of young people, which makes it possible to understand the originality of the innovative properties of young people, taking into account their natural ability for creative activity and increasing their innovative potential. Ways of increasing the prospects of youth participation in the innovation sphere of the country are proposed, taking into account the urgency of the task of developing intellectual potential and increasing the innovative activity of youth.
Glocal, Holistic and Performative Education

We look at innovative education through a global and local approach to the philosophy of existence, known as glocalization, and through the psychological Gestalt of experiencing a whole that is inevitably viewed within social science by a sociological holistic principle.Our glocal, holistic, aesthetic practice has been experienced and realized through intensive performative education that enhances the existential capacity in multi / media projects through the humanistic approach, affectively using digital framing.Performative projects are performed in the Media Culture course at the Faculty of Teacher Education in Osijek, Department in Slavonski Brod (FOOZOS), including vertical education of primary and secondary students.The education process is performed through lectures, intensified through e-learning, and finalized by group orchestration in a large project supported by the non-profit organization Culture, Media and Education -Arthea and the Ministry of Culture of the Republic of Croatia.Examples of successfully implemented glocal, holistic and performative education can be seen in the videos: Baroque in Postmodern Glocal Approach, (created for the European Schoolnet Academy, 2019), Situationally Performative Smartphone Orchestra (conducted performance, Slavonski Brod town square, 2018), Post-Modern Dystopic Deconstruction for Mobile Phones Orchestra (FOOZOS, Department in Slavonski Brod, 2017), Project with Mobile phones (mobile
A Corpus-based Study on the Keyword of Airline English Materials : Focused on Native Language Publishment

The main purpose of this study is to suggest the implications for ESP learners based on Corpus by constructing the text and analyzing the airline’s English materials. Linguistic corpus for ESP study has been increasing a lot, as it was frequently applied to English education and related research. Checking the high- frequent vocabulary is a basic way to start airline English for those who want to be a flight attendant. So it could be an efficient approach to introduce contents for ESP-related discipline. Therefore, 6 different airline english books from native countries were used to make a list and extracted from corpus program called AntConc 3.5.8.version. The total number of word types from text was 222,899 while token numbers was shown 22,908. First of all, total number of 50 vocabulary list was produced according to the order of high frequency. Secondly, lexical bundle list was extracted either 3 or 4 words. Lastly, the concordance list of vocabulary ‘you’ and ‘have’ was checked. Through the results of this research, developed lists could be used as an useful tool for those who are studying in Aviation service major at college in the ESP classes or who is about to fly under the training at Airlines. This study has showed a practical way of ESP class by checking on high-frequency vocabulary from data used in real site which is Airlines.
New Text Compression Method Based on Direct Solution Method Neural Networks

The aim of this work is to create a text compression technique using a single layer neural networks trained using direct solution method.In this work, the text is made as desired output and the weights are pre-defined then, by using the direct solution method, we calculate the input vector.This process, exhibits decreasing the number of the input neurons, the computing size and memory space.The present work has been demonstrated through several experiments and show very promising results in compression rates as well as in the reconstructed text.
Automated Image Suggestions for News Articles : An Evaluation of Text and Image Representations in an Image Retrieval System

Multimodal machine learning is a subfield of machine learning that aims to relate data from different modalities, such as texts and images. One of the many applications that could be built upon thi ...
The Structure of Scientific Disciplines. Some Notes on the Epistemology of Algorithmic Representations of Disciplines

Representations of research fields are devices that are used to grasp the inner structure of disciplines.They play a crucial role in the disciplinary life since they ease the fulfillment of many epistemicand social tasks (from systematizing the intellectual content to organizing the cognitive labor ofresearchers, to manage appointments in the university). In the first part of the paper, I will distinguishbetween two types of field representations: top-down and bottom-up. The former are based on theassessment of the structure of research fields by experts, whereas the latter are based on computeralgorithms. In the second part of the paper, I will focus on these ones and, by taking as an exampleco-citation maps, I will argue that they capture the latent forces that shape the intellectual actionof the researchers contributing to a scientific discipline. These forces have both a negative andpositive function (i.e., they are structuration forces). The negative function is to constraint thepossible intellectual actions of the researchers, the positive is to enable the organized accumulation ofknowledge by channeling information and reducing noise.
Self-supervised Human Detection and Segmentation via Multi-view Consensus.

Self-supervised detection and segmentation of foreground objects in complex scenes is gaining attention as their fully-supervised counterparts require overly large amounts of annotated data to deliver sufficient accuracy in domain-specific applications. However, existing self-supervised approaches predominantly rely on restrictive assumptions on appearance and motion, which precludes their use in scenes depicting highly dynamic activities or involve camera motion. To mitigate this problem, we propose using a multi-camera framework in which geometric constraints are embedded in the form of multi-view consistency during training via coarse 3D localization in a voxel grid and fine-grained offset regression. In this manner, we learn a joint distribution of proposals over multiple views. At inference time, our method operates on single RGB images. We show that our approach outperforms state-of-the-art self-supervised person detection and segmentation techniques on images that visually depart from those of standard benchmarks, as well as on those of the classical Human3.6M dataset.
SISTEM PAKAR UNTUK DIAGNOSA PENYAKIT SARS, MERS, DAN COVID-19 MENGGUNAKAN METODE CERTAINTY FACTOR

SARS, MERS, and COVID-19 are viral infections of the respiratory tract that can be fatal. All three diseases are caused by viruses originating from the same family. All three are caused by corona virus. SARS is caused by SARS-CoV, MERS is caused by MERS-CoV, and the Wuhan corona virus is caused by 2019-nCoV (renamed COVID-19). This paper aims to implement the Expert System of the Certainty Factor method to diagnose the symptoms of the three diseases. This method can overcome the uncertainty in decision making based on the symptoms felt or inputted by the user. This method is suitable for use in expert systems to measure whether something is certain or uncertain in diagnosing a disease as an example. Based on the calculation results, an expert system can be used for initial diagnosis of the three diseases.
LibGuides: Quick Guide to Finding Scholarly Articles: Using Databases A to Z

This LibGuide is intended for librarians to use with students with questions about how to use Databases A-Z and E-Journals A-Z to find full-text scholarship for college research papers This page is intended to assist students who want to navigate Marymount Manhattan College databases to find full-text documents for college research papers.
Effect of Mobile App on undergraduate students performance in Physics

Welcome to the Introduction to the Instructional Systems Design course. The purpose of this course is to provide you with theoretical and experiential perspectives of Instructional Systems Design. Instructional Design (ISD) is a systematic development of instructional materials using learning theories. It is the process of analyzing needs and developing materials to meet those needs. It includes development of instructional activities and exercises; as well as the evaluation of learners' progress.
PROBLEMS OF HIGHER EDUCATION AS A THREAT TO SUSTAINABLE DEVELOPMENT (ON THE EXAMPLE OF EARTH SCIENCE SPECIALTIES)

The purpose of this article is to draw the attention of researchers to the topic of mismatch of the future and group expectations of higher school students’ image with the educational goals of global sustainable development (SD). The article shows the relevance of studying these concepts, assuming that they pose a threat to SD. To eliminate it, it is necessary to develop higher education in the direction of its futurization. The novelty of the work is related to the results of research among Russian students majoring in Earth Sciences.
LibGuides: Active Reading and Notetaking Skills for Research: Further Resources and Support

This tutorial consists of short instructional videos that introduce you to effective strategies for reading and notetaking for research projects.
MODEL MATEMATIKA MENGENAI KESADARAN MASYARAKAT DALAM PERILAKU HIDUP BERSIH DAN SEHAT DI KOTA SAMARINDA

Samarinda is one of the big city in Kalimantan since it is a capital city of East Kalimantan Province. Its population is about 988,943 in 2015, but only 28.62 percent of the whole households were applying clean and healthy living behavior. To encourage this behavior to the society, it needs some health promotions to be introduced to them. In order to know the pattern of clean and healthy behaving households with respect to time, so this research is aimed to perform a mathematical model of the implementation of clean and healthy living behavior which involves health promotion. Runge-Kutta is the used model to solve this model. The result informs that the rate of change of the households which implement a clean and healthy life, called as good people, increases for all sub-districts in Samarinda City. In contrast, households that do not know and do not behave clean and healthy life, called as bad people, are reduced because of the promotion. Keywords: clean and healthy living behavior, health promotion, modeling mathematics.
Smart image enhancement technique by removal of undesirable objects/background from the image

The devil is always in your picture. You always miss the best shot and that particular tiny object in your photo can worsen the entire composition and result in something opposite from what you hoped for. The proposed AI based image enhancement model will first detect unwanted objects/background based on the training of large set of already edited images by users then intelligently reconstructs the image without those objects. We have prepared a dataset with distracting elements in the images and used it to train our predictor model which predicts the distracting regions and thereafter used image-inpainting to remove those areas which results in a standalone system for distractor removal with no user input. In the proposed method of this paper, the image is first segmented using Convolutional networks for semantic segmentations and then each segment is classified in terms of the score of distractors on the basis of various features which almost covers all types of distractors in an image. Our main focus was to collect the data which contains all kinds of distractors and then deciding the features which classify an object as a distractor in an image. Detection and removal of distracting regions helps to enhance the beauty and visual quality of the image which can be fulfilled by using our model.
Subfield Codes of Linear Codes from Perfect Nonlinear Functions and Their Duals

Let $\mathbb{F}_{p^m}$ be a finite field with $p^m$ elements, where $p$ is an odd prime and $m$ is a positive integer. Recently, \cite{Hengar} and \cite{Wang2020} determined the weight distributions of subfield codes with the form $$\mathcal{C}_f=\left\{\left(\left( {\rm Tr}_1^m(a f(x)+bx)+c\right)_{x \in \mathbb{F}_{p^m}}, {\rm Tr}_1^m(a)\right)\, : \, a,b \in \mathbb{F}_{p^m}, c \in \mathbb{F}_p\right\}$$ for $f(x)=x^2$ and $f(x)=x^{p^k+1}$, respectively, where $k$ is a nonnegative integer. In this paper, we further investigate the subfield code $\mathcal{C}_f$ for $f(x)$ being a known perfect nonlinear function over $\mathbb{F}_{p^m}$ and generalize some results in \cite{Hengar,Wang2020}. The weight distributions of the constructed codes are determined by applying the theory of quadratic forms and the properties of perfect nonlinear functions over finite fields. In addition, the parameters of the duals of these codes are also determined. Several examples show that some of our codes and their duals have the best known parameters with respect to the code tables in \cite{MGrassl}. The duals of some proposed codes are optimal with respect to the Sphere Packing bound if $p\geq 5$.
LibGuides: LIS 511 (2019 Spring): Julius Caesar: Websites

A guide for resources about the Roman military general, dictator, politician and leader Gaius Julius Caesar
2020 Electronic Resource Usage Statistics

This usage report contains the FY 2020 Electronic Resource Statistics, which report the amount of items downloaded from Columbus State University's electronic resources from July 2019 - June 2020.
Digital deception in cybersecurity: an information behaviour lens

Introduction. Digital deception is a double-edged sword used by both blackhats and whitehats in cybersecurity. A status quo review of the reintroduction of digital deception can reveal challenges and initiatives and show how information behaviour expertise might inform cybersecurity research and vice versa. Aim. To use a status quo review of digital deception to reveal links between cybersecurity and information behaviour and to stimulate further research. Method. Critical review of digital deception in cybersecurity regarding whitehats and blackhats using an information behaviour lens. Findings. There is a need for research that tackles digital deception from both information behaviour and cybersecurity. There is also a need to bridge the gap between the two research fields and link cybersecurity concepts with information behaviour theories. Conclusions. The reintroduction of digital deception in cybersecurity highlights the challenges for the unreliability of defence-based detection systems. Although many solutions are available from cybersecurity, information behaviour might contribute to multidisciplinary research on digital deception and the future of defence technologies. Understanding the interplay between whitehats and blackhats in cybersecurity can help information behaviour practitioners to design models or frameworks for predicting changes in information-seeking behaviour.
THE CORRELATION BETWEEN LISTENING HABIT TO ENGLISH SONGS TO WRITING SKILLS AT ELEVENTH GRADE STUDENTS OF SMA ISLAM SUDIRMAN AMBARAWA IN THE ACADEMIC YEAR OF 2019/2020

Khairani, Leila. 2020. The Correlation between Listening Habit to English Songs and Vocabulary Mastery to Writing Skills at the Eleventh Grade Students of SMA Islam Sudirman Ambarawa in the Academic Year of 2019/2020. A Graduating Paper. English Education Department. Teacher Training and Education Faculty. State Institute for Islamic Studies Salatiga. Counselor: Dr. Setia Rini, M.Pd.This research is aimed to find out whether there is correlation between students’ listening habit to English songs and vocabulary mastery toward their writing skills for the eleventh grade of SMA Islam Sudirman Ambarawa in the academic year of 2019/2020.In this research, the writer conducted a correlational study. The research was carried out at SMA Islam Sudirman Ambarawa in the academic year of 2019/2020. The population was the eleventh grade students of SMA Islam Sudirman Ambarawa. While the sample was 33 students for each classes, XI Bahasa 2 (real test class) and XI IPS 2 (validity test class) taken by cluster random sampling technique. The instrument to collect the data was a questionnaire and a test. There are two kinds of test, multiple choice test to measure students’ mastery of vocabulary and simple past tense and writing test to measure students’ writing ability in recount text. In analyzing the data, the writer used simple, multiple correlation and regression by Person Product Moment formula assisted by SPPS version 16. The result of correlation coefficient significant of students’ listening habit to English songs and vocabulary mastery to writing skill showed that F0 (20.678) is higher than Ft (3.28) at the level of significance ? = 0.05 and df (degree of freedom) for n = 33 is 3.28. It can be conclude that the coefficient correlation is significant. It means that the correlation between the students’ listening habit to English songs and vocabulary mastery toward writing skill, both partially and simultaneously was significant. The writer concluded that Ha was accepted and Ho was rejected in the research.Key words: correlation, habit, vocabulary mastery, writing skills
Recognition of Indian Classical Dance Single-Hand Gestures Using Moment Invariant Features

Recognition of single-hand gestures of classical dance is a challenging task due to its variation of age group of dancer. It is also a difficult task to find out the invariant features specially when same images are captured from different angle of view. The main objective of this paper is to recognize single-hand gestures of Indian Classical dance using $${Hu\acute{s}}$$ invariant features. In this paper, three different types of image dataset namely boundary image, gray image and binary image dataset used. The seven $${Hu\acute{s}}$$ invariant features were extracted from all the three image dataset. This paper also presents performance of accuracy for twenty eight different classes of hand gesture based on the extracted features set.
LibGuides: Sport : E-Resources

A comprehensive guide to the resources provided by the Library service to support you with your course. How to find electronic resources for your course
The Dark Side of IoT : Revealing Activities in the Smart Home Environment using Machine Learning

With the emerging trend of smart IoT devices, providing and ensuring the privacy of the users'-devices interaction relationship is a must; risks such as identifying users' activities and detecting ...