Reviewerly/exHarmony huggingface dataset:
Chinese text multi-classification based on Sentences Order Prediction improved Bert model

Abstract For the strong noise interference brought by the NSP mechanism (Next Sentences Prediction) in Bert to the model, in order to improve the classification effect of the Bert model when it is used in text classification, an SOP (Sentences Order Prediction) mechanism is used to replace the Bert model of the NSP mechanism-Multi-classification of Chinese news texts. At first, use randomly sorted adjacent sentence pairs for segment embedding. Then use the Transformer structure of the Bert model to encode the Chinese text, and obtain the final CLS vector as the semantic vector of the text. Finally, connect the different semantic vectors to the multi-category Classification. After ablation experiments, the improved SOP-Bert model obtained the highest F1 value of 96.69. The results show that this model is more effective than the original Bert model on text multi-classification problems.
Experiência em Gerenciamento de Projetos de Desenvolvimento Distribuído de Software – DDS

The process of software development companies are increasinglydistributed in several possible ways in different locations in search of lowerrisk, higher profits, and competitive advantages, among others. This paper reports the experience of Project Managing Distributed Software Development -DDS, with the case study of a Y-design company X, organizing information technology, outsourcing,overcoming the challenges of communication, coordination, team collaboration, and other factors which are compounded in a DDS environment, reporting the results lessons learned
The role and place of ethnopedagogy in the educational ecosystem

This article addresses various educational systems that have led to the transition to the educational ecosystem. Application of ethno-pedagogical bases in the modern innovative educational process expands frontiers of knowledge on the way of comprehension of this environment, provides the formation of ecological consciousness and forms world outlook structures, a priori providing coevolution of the person and society, the individual and nature, the person and the world. The process of transition from the educational environment to the educational ecosystem, focuses on learning throughout a lifetime and continuous professional development, adapting the person to the new challenges of our time. The relevance of the transition is due to the progressive development of the human community, which tirelessly modernizes the essence and place of the educational system in the sociocultural environment. Not the lowest of the roles should be given to traditional folk pedagogical methods, mechanisms, and ways of education and training.
Implementasi Extract Transform Load Pada Data Akademik Perguruan Tinggi

Each department at university needs to analyze student data and scores. By analyzing student grades, majors can improve lecturer performance in learning; one way to explore student grades is to collect student grade data and then process the data to produce information in the form of learning performance results that can be used to make decisions to improve lecturer performance. The author will analyze a structured programming course student score data; the following collected data are related to student attendance, assignment scores, mid-semester exam scores, and final semester exam scores. After all the data needed has been organized to build the data warehouse, the following process is the ETL process (Extract, Transform, and Load), as the tool used in the ETL process is Pentaho. This data extraction process using 1 data source, namely student value data with excel file type. After carrying out the extraction process, there is a data transformation process, namely making some changes to the extracted data to make it more consistent and uniform according to the needs of the data warehouse.
A Quasi-experimental Study to Assess the Effectiveness of Structured Teaching Programme on Knowledge Regarding Cord Blood Banking among Antenatal Women in Selected Areas of District Tarn Taran (2019)

Umbilical Cord Blood (UCB) is used as a source of haematopoietic hematopoietic stem cells (HSC) for bone marrow transplantation in the treatment of malignant and non non- malignant diseases. The aim of the study was to assess the knowledge of antenatal women and to teach them regarding cord blood banking. The non-randomized research design was used. The sample size was 60 which were selected from the area of Fatehabad, Tarn Taran , . The tool for the data collection was self structured questionnaire. The non-probability purposive sampling technique was used to select the subjects. The finding of present study shows that overall mean knowledge score of pre-test experimental and control group was 5.62 with SD 2.371 and 5.83 with SD 2.41 respectively. The mean knowledge score of post post- test experimental and control group was 21.03 with 4.809 SD and 9.4 with SD 3.407 respectively. The paired “t‟ test value is was 9.15 which is significant at 0.05 level. The age, educational status and gravida had a great impact on knowledge of antenatal women regarding cord blood banking. The present study recommended that a similar study can be undertaken on large sample for better generalization by adopting a quasi quasi- experimental design to improve the knowledge of antenatal women regarding cord blood banking.
Ocean Coefficient: A Feature Extraction Technique for Five Factor Model based Classifications

Natural Language Processing has opened up several avenues in the field of research and developments. It has supported wide variety of applications, but still the opportunities are enormous for the researchers to look into several other aspects in the discovery of new dimensions. In this regard the current paper is trying to introduce a revolutionary feature extraction technique, particularly for the studies/research corresponding to five factor model based behaviour analysis.
Developing a Sound Design Creative A.I. Methodology

This chapter discusses the overall goal of how a computer program can simulate human-like sound design processes. An example using music information retrieval methodologies demonstrates developing a computational model for machine listening of aesthetic criteria for a Creative A.I. system. Creative tasks, such as graphic design, video production, game design and music-making, have grown to be the leading multi-modal professional use of computers. Recent initiatives in artificial intelligence and machine learning are driving a renaissance in how creative tasks are carried out by amateurs and professionals alike. For example, it is now possible to generate hundreds of hours of music or playable game levels in only minutes. However, generating the sound design for entertainment media remains an open problem. The challenges provided by computational sound design rest upon the subjective experience of the listener response, the continuous signals of the media and the complexity in the alignment of sound elements with the richness of the narrative and visual environment. Given the importance of sound design in the user experience and the growing amount and sophistication in production, it is critical to advance the research and development of computationally assistive technologies in this field.
Towards Concept Change Detection in Marine Ecosystems

The research presented in this paper aims to accelerate the natural science research process by partially automating the execution of experiments using AI-assisted Concept-Change Detection (C-CD), e.g., for monitoring systems and studying biodiversity and ecosystem functions. The purpose of C-CD is to detect concept changes, also known as concept drift, that may be relevant to the study or ecosystem state. For example, in intertidal marine ecosystems, the event of sudden flooding can lead to dramatic changes in biodiversity. It could also be of scientific interest to take sensor samples more frequently in the period leading up to such events. The paper proposes an architecture for C-CD to customize AI-based analysis of sensor data streams. Furthermore, the paper implements portions of the architecture and is applied on sensor data from the Spiekeroog Coastal Observatory (SCO) as a feasibility study. The study demonstrates C-CD's ability to detect anomalies that are either of scientific or technical interest to the operation and exploration activities of SCO.
LibGuides: Luncho Libre: Discussion Guidelines

This guide provides information about the University Library's Luncho Libre, a series of virtual lunch dates to engage and interact with students.
Problem-Based Learning Approaches as a Form of the Chinese Lesson Arrangement

In modern education, the problem-based learning approaches is one of the most effective ways of educating and the most effective method of self-educational activity of school students. Problem learning is one type of developmental learning, in which students simultaneously activate creative and cognitive activity, accompanied by mental activity, therefore the best learning of a new training material, by use of problem situations is reached, which in turn stimulates students’ search activity and it develops their self-education activities.Students’ ability to isolate a problem from the general informational context is not an end in itself in the educational process. The problem proposed by the learners for solving with the use of materials from the school curriculum and from outside the school course must have a certain cognitive content. New textbooks on the Chinese language are developed taking into account the technology of problem-based learning and include a set of learning problems consistently solved by students.The problem-based learning approaches is different from traditional subject studies.It puts the student in a position where he is forced to actively and intensively think, mobilizing his intellectual potential to solve the problem and form a theoretical conclusion. The theoretical conclusion obtained in the independent search is learning by the student as his own labor.Thus, problem-based learning in Chinese lessons complements the traditional illustrative and explanatory education. At the same time, it contributes to the destruction of old stereotypes of passive learning, makes students think, look for answers to difficult life questions together with the teacher.
LibGuides: LAIR (Lenoir-Rhyne Academic Institutional Repository): LAIR Policies

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LibGuides: KCAD Library - COVID-19 Update: KCAD Faculty Services

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The Preliminary Research: Multimedia Development on Deaf Learning For The 21st Century

The industrial revolution 4.0 relies on cyber-physical systems is a phenomenon accompanying by technological advances, information bases, knowledge, innovation, and networks in the era of affirmation of the emergence of the creative century. In education, the industrial revolution is prepared with the implementation of 21st century learning that includes the diversity of learners/students, the diversity of digital technology, access to information, and global. For students who are deaf or deaf, 5 domains of 21st century skills experience barriers specifically to communication skills. This research will focus on examining the problems and development of multimedia in the learning of the Deaf class by using the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) recommendations. Research related to multimedia development in Deaf classroom learning has not been done much. Multimedia development is only commonly found at the level of formal education classes in kindergarten, elementary, junior high school with subjects such as mathematics, Indonesian, English, science and art. Meanwhile, for high school and tertiary education levels, there have not been many studies regarding multimedia development. Related to these conditions, educational technology as a study of practical and theoretical knowledge is needed as a solution to educational problems.
КОМПЬЮТЕРЛИ МОДЕЛЛАШТИРИШДАН МАСАЛАЛАРИНИ ЕЧИШНИНГ ЭЛЕКТРОН ЎҚУВ-МЕТОДИК ТАЪМИНОТИ: С.Жумабоев

The article deals with solving the programming using computer technology for higher education. An approach to the implementation of training and how to solve problems by using electronic tutorial.
An Estimator for Matching Size in Low Arboricity Graphs with Two Applications.

In this paper, we present a new degree-based estimator for the size of maximum matching in bounded arboricity graphs. When the arboricity of the graph is bounded by α, the estimator gives a α+2 factor approximation of the matching size. For planar graphs, we show the estimator does better and returns a 3.5 approximation of the matching size. Using this estimator, we get new results for approximating the matching size of planar graphs in the streaming and distributed models of computation. In particular, in the vertex-arrival streams, we get a randomized O((√n)/(e²)log n) space algorithm for approximating the matching size of a planar graph on n vertices within (3.5+e) factor. Similarly, we get a simultaneous protocol in the vertex-partition model for approximating the matching size within (3.5+e) factor using O((n^{2/3})/(e²)log n) communication from each player. In comparison with the previous estimators, the estimator in this paper does not need to know the arboricity of the input graph and improves the approximation factor in the case of planar graphs.
Perancangan dan Pembuatan Website Ujian Online Jurusan Kimia Analisis

Author designing websites online exam easily used when conducting examinations at SMAK SMK Padang. This study aims to determine the validity, practicalities and Effectiveness Website Designing and Making Class X Examination Department of Chemical Analysis In SMAK SMK Padang Academic Year 2018/2019. This study uses research and development (R &amp; D) 4D. Sabjek study amounted to 31 people, with design and development steps are as follows. (1) Define, in step define will do a needs analysis of the system that we created (2) Design, at this step is to design tehadap system will be made (3) Develop, in this step will be the stage of assessment of the system created and ( 4) Disseminate, at this stage of deployment of products that have been created. The validity of the test results by the experts overall assessment of the validator test Website Online Class X Exam Chemical Analysis Department at SMK Padang SMAK by 89.87%, so the rate can be interpreted validity Invalid use. Results of votes overall assessment practicalities test the practicalities of the Website Online Class X Exam Chemical Analysis Department at SMK Padang SMAK by 90.84%, so the rate can be interpreted praktikalitasnya Very Practical use. Results of votes overall effectiveness test assessing the effectiveness of the Website Online Class X Exam Chemical Analysis Department at SMK Padang SMAK by 89.44%, so that their effectiveness can be interpreted Very Good used. In conclusion, based on the assessment along with expert input as well as the results of the field trial Website Online Exam as the system is tested the feasibility, advantages, and can be used onnew admissions process SMAK SMK Padang.
Motion sickness detection through deep learning techniques

Motion Sickness is a disorder caused by incoherent inputs arising from the visual system and the vestibular system. Motion Sickness is subdivided into different cases: sickness due to visual stimulation, sickness due to vestibular stimulation and less frequently sickness due to somatosensory stimulation. Individual susceptibility to Motion Sickness varies according to different factors such as age, gender, physical condition. The most common symptoms caused by this disorder are pallor, vomiting, nausea, dizziness, frequent sweating, excessive salivation. This thesis focuses on the analysis of physiological signals to automatically detect patterns characterizing Motion Sickness disorders. The Electrocardiogram signal has been preprocessed by applying various types of filters, to reduce possible noise and artefacts. Subsequently, the target signal has been analysed using the Wavelet analysis coupled with the application of a Convolutional Neural Network (CNN) that has been trained and validated. In this way, the created Deep Learning model aims to classify different patterns characterizing the disorder of motion sickness.
Utilization Of Sentiment Analysis Using The Data Science Approach To Improve Customer Satisfaction

One of the biggest problem for customer satisfaction is how to understand the user need and the user point of view, to make it visible social media is giving huge impact especially tweeter comment . However, the number of comments submitted is very large and become difficulty to analyse. Besides the comment data on Twitter is an unstructured type of data so that if processing uses a relational database engine the results obtained are not optimal. To deal with these problems, a big data approach is needed in data extraction combined with the comment data processing model. This study uses a combination of big data in data processing and lexicon based to analyse customer comments. Data processing using big data especially with the NoSQL approach is very effective and efficient in conducting searches on unstructured data because the search for big data is based on meta text rather than cardinality between data. While the lexicon based method used depends on the completeness of the dictionary used. The purpose of this study is to analyse comments and share whether they have positive, negative, or neutral sentiments so that they can be used as parameters in decision making in an organization.
Application of augmented reality technology as an interactive learning medium in geography subjects

This research studies e-learning environments based on the Earth layers via Augmented Reality. It is a technology that can insert and provide input in the form of 3D virtual objects into a real-time environment. It can be applied in learning activities. In this research, authors offer to use it in geography subjects on the topic of layers and structures of the earth. Learning media on the topic of layers and structures of the earth in schools today is still conventional and difficult to present in-class learning. In addition, there is still a lack of technical knowledge to properly use digital technologies in lessons and this application is user-friendly. This study was conducted to determine the user's response regarding the learning media layer and structure of the earth-based Augmented Reality of secondary school students. Augmented Reality is a type of interactive technology that combines real and virtual objects to produce real 3D objects in life. The research was developed with the waterfall model. The results of the study showed that the learning media geography layer and Augmented Reality based earth structure are valid to be used as a learning medium in secondary school. Based on the conducted research, authors came to a conclusion that usage of the Augmented Reality technology showed a positive dynamic.
Autocad Learning Video Development Using Open Broadcaster Software Application

Autocad is one of the most important applications, especially in engineering, including architecture.However, there are no specific courses that teach design using Autocad.Thus causing some problems found in the implementation of teaching and learning.First, there are not a few students who do not understand the functions and uses of Autocad itself, thus making lecturers have to provide basic material about Autocad outside of the subjects that should be delivered.Second, the limitations of students who have personal computers, so that students are less than optimal in independent learning regarding the functions and uses of Autocad and rely more on learning in the computer laboratory.Third, the low interest of students in reading books related to Autocad knowledge.For this reason, researchers will make learning videos for the basics of Autocad, besides that with this learning video, it will make it easier for lecturers to assign courses according to the subject matter but require Autocad so that the ability of students who still do not understand the functions and uses of Autocad are not constrained.In this study, the learning video was validated by DOsen Aexperts who will validate the overall content of the product in the form of learning videos.In addition to validation sheets, data collection was also carried out through questionnaires or questionnaires distributed to students.This questionnaire instrument uses a Likert scale.From the research validation process, it shows that the results of the material test have a value of 68.75% which are categorized as good enough criteria, the media test has a value of 90.38% which is categorized in very good criteria and the test to students has a value of 79.54% which is categorized in very good criteria, so the Autocad learning video is feasible to be used in the learning process..
LibGuides: Faculty Curriculum Support: Technology Support

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LibGuides: Finding Media: Citing or Attributing

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LibGuides: Library Technologies: Home

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Research Guides: (ECC) Using the Ellsworth Community College Library: ECC Library

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Performance Evaluation of Embedded Feature Selection Techniques over Filter and Wrapper-based Feature Selection Techniques

This paper compared the performance of filter-based and wrapper-based feature selection techniques with that of embedded-based feature selection technique. Recursive Feature Elimination (RFE) with SVM Feature selection techniques were explored on Random Forest (F) and Logistic Regression (RFE-LR). Recursive Feature Elimination (RFE) with SVM Feature selection techniques were explored on Random Forest (RF) and Logistic Regression (LR) using ten (10) publicly available defect datasets. SVM-RFE-LR approach of Embedded Feature selection Techniques produced consistent software metrics within the range oThis paper compared the performance of filter-based and wrapper-based feature selection techniques with that of embedded-based feature selection technique. Recursive Feature Elimination (RFE) with SVM Feature selection techniques were explored on Random Forest (F) and Logistic Regression (RFE-LR). Recursive Feature Elimination (RFE) with SVM Feature selection techniques were explored on Random Forest (RF) and Logistic Regression (LR) using ten (10) publicly available defect datasets. SVM-RFE-LR approach of Embedded Feature selection Techniques produced consistent software metrics within the range of 18% to 55% across the datasets, and SVM-RFE-RF reported within 33% to 96%. Significance performance was witnessed over Filter and Wrapper based techniques.f 18% to 55% across the datasets, and SVM-RFE-RF reported within 33% to 96%. Significance performance was witnessed over Filter and Wrapper based techniques.