Reviewerly/exHarmony huggingface dataset:
Optimised Statistical Model Updates in Distributed Intelligence Environments

This paper explores a sequential decision making methodology of when to update statistical learning models in Intelligent Edge Computing devices given underlying changes in the contextual data distribution. The proposed model update scheduling takes into consideration the optimal decision time for minimizing the network overhead while preserving the prediction accuracy of the models. The paper reports on a comparison between the proposed approach with four other update delaying policies found in the literature, an evaluation of the performances using linear and support vector regression models over real contextual data streams and a discussion on the strengths and weaknesses of the proposed policy.
Design Of Pest Diagnostic Expert System And Rice Plant Disease Forward Chaining Method

Rice is the primary need of humans in Indonesia, therefore farmers must plant quality rice free from pests and diseases. One of the factors in the decline in rice production is rice pests and diseases, such as rat pests, planthopper pests, blast diseases and so forth. Many communities, especially farmers who are confused about the types of pests or diseases that attack their rice plants so that the way to handle them is wrong. For proper information on rice diseases, you should ask the experts of rice plants to be able to find out diseases and appropriate handling can also be through internet network access ) but the time needed to determine an ordinary disease is too long, so the need for fast knowledge and proper access can help them, in the information of the disease, because the use of gadgets has been growing rapidly and almost everyone in the villages have it required a mobile access that informs the disease rice appropriately. The expert system is an artificial intelligence using the forward chain method to determine the type of disease in rice, this method collects partial data from an expert in their field and sampling until finally the data is converted to a system created. The application is made on a mobile platform using the android studio application, the expected results are that this application can help the community in determining rice diseases that attack plants.
Mathematics Education Game Using the Finite State Machine Method to Implement Virtual Reality in Game Platformer

Rapid technological developments have changed the patterns and systems that existed before. One of them is a Gim that has collaborated with the world of Education, the Gim is called an educational Gim. There are advantages in building an educational Gim that is visualization of real problems and increasing interest in learning. Mathematics is one of the subjects that is considered difficult for students. This is due to a lack of understanding of students in mastering the material given. In grade 5 elementary school students, desperately need rapid understanding because the class students receive more material and lessons from the previous class. The Finite State Machine method that was applied to the Gim "The Story of Rino’s Life" with additional multimedia and storyline, the Gim became more interesting and fun to play. The results of this study indicate that this Gim has fulfilled the needs of players, namely as a learning medium that makes it easier for students in grade 5 to understand mathematical material and also provides motivation to always learn mathematics.
Research on Quality Evaluation Technology of “Model Data Platform” for PaaS Layer

With the transformation of the operation characteristics of the power grid and the in-depth development of the dispatching and control cloud platform (dCloud platform), in order to ensure that the dCloud platform can safely and stably support the needs of power grid information perception and synchronization, lean dispatch management, and deep application of data, research must be focused on the measurement technology and quality improvement methods for dCloud platform applications. This article analyzes the Iaas, Paas, Saas layer system structure of dCloud platform, and studies key technologies such as data quality verification of model data platform of the Paas layer, and collaborative testing of the entire process data. This article extracts key technical indicators, and implements the comprehensive indicators of the model data platform based on the analytic hierarchy process, which can improve the quality of software while ensuring the stability of the cloud platform software's ability to operate.
21ST Century Characteristics of Educators as Perceived by Laguna State Polytechnic University Faculty

This descriptive research aimed to determine the level of perception of faculty of Laguna State Polytechnic University on the 21st century characteristics of educator. Demographic profile of the respondent includes age, sex, status, educational attainment, academic rank, and years of service. The study identified six characteristics of 21st century educators such as adaptor, lifelong learner, technology savvy, collaborator, visionary, and leader. It was found out that the highest computed mean and standard deviation of 5.59 (0.13) was obtained from collaborator as one of the characteristics of educator and was interpreted as strongly agree. The faculty have developed and enhanced their knowledge and skills in teaching in order to adopt with the demands of 21st century learners. It is suggested that faculty members should continue to enhance their 21st century skills such as developing and applying new pedagogies in teaching and learning; and implementing design thinking and system thinking for educators.
Simple and Efficient Approach to the Aspect Extraction from Customers’Product Reviews

In this paper we present an approach to the one of the most popular natural language processing tasks of automatic aspect extraction from product reviews. Our approach is based on using clustering of word embeddings, morphological features, information about syntax dependencies and word frequencies. We use these features in the well-known machine learning method - the Decision tree. The primary evaluation of our method quality for the task of identifying the explicit aspects from the reviews demonstrate good performance in the precision and recall for cross-domain aspect extraction task.
Year One of SlideShare

SlideShare (www.slideshare.net) is an online service for hosting and sharing professional content such as presentations, infographics, and documents (Figure 6-1). It was founded by Rashmi Sinha, Jonathan Boutelle, and Amit Ranjan. In May 2012, when it was sold to LinkedIn for about $119 million, it had about 53 million monthly visitors.
Why Grade Distribution Is Often Multi-modal: An Uncertainty-Based Explanation.

There are many different independent factors that affect student grades. There are many physical situations like this, in which many different independent factors affect a phenomenon, and in most such situations, we encounter normal distribution – in full accordance with the Central Limit Theorem, which explains that in such situations, distribution should be close to normal. However, the grade distribution is definitely not normal – it is multi-modal. In this paper, we explain this strange phenomenon, and, moreover, we explain several observed features of this multi-modal distribution.
A new intelligent VR biological learning system based on natural interaction

In middle school biology teaching and learning, there are many biological structures that students need to understand and master. Traditional classrooms mostly use video and PPT to teach, which is not conducive to students' understanding of three-dimensional structure, thus making it difficult to learn biological knowledge. In order to solve the problem of 3D biological structure learning, this paper proposes a natural interaction-based VR biology learning system method, which intelligently perceives the user's interaction intention and interacts with the user through virtual reality technology and multi-modal fusion technology. The innovation of this paper lies in: Firstly, a new VR biological learning system based on natural interaction is proposed. Through the fusion of gestures and speech, the user interacts naturally with the system. This method frees the user's hands from the constraints of the mouse and keyboard and the handle, enhancing the immersion of virtual reality. Secondly, this paper proposes a multi-modal fusion algorithm, which makes full use of the advantages of gestures and speech and compensates for their shortcomings, so as to better perceive the user's operational intention. It makes up for the shortcomings of the virtual learning system's lack of intelligence, so that users get a more convenient and more natural interactive experience. According to the user's experience feedback, the system proposed in this paper can better stimulate students' interest in learning, and can present the abstract three-dimensional knowledge in front of the user more intuitively. It has the good intelligence and the operation experience feeling, can reduce the user's use load effectively, the user operates more conveniently.
An efficient packet image transmission based on texture content for border side security using sensor networks

In surveillance, several algorithms are used to extract meaningful information from an image captured. In the presence of intrusion, cameras will transmit captured images to the sink node via other intermediate nodes. Since, WSNs operate with limited resources; utilisation of resource is needed while processing and transporting images. As the node doesn't need whole image, prioritisation is one of the methods to utilise the available resource. It will prioritise images from its macro-blocks dynamically. Here the camera is attached in sensor nodes, which forms wireless multimedia sensor networks (WMSN). It applies an encoding scheme at the source node by naming the blocks as 'important' or 'not-important' based on the information they contain. Here image texture and spectral feature is used as priority measures to weight importance of macro-blocks by their GLCM properties. Experimental result discloses that priority scheme adapts itself to the quality requirements while reducing the bandwidth comparatively.
Electronic education: the world and Russia

The article speaks about current issues of the development of electronic education in the world, about problems and prospects for its development in Russia. Online education in the field of higher education is analyzed, as well as the prospects for the export of educational services based on massive open online courses (MOOC) developed by Russian universities in foreign languages within the frame of the project of export Russian education.
Deep Latent Variable Model for Longitudinal Group Factor Analysis.

In many scientific problems such as video surveillance, modern genomic analysis, and clinical studies, data are often collected from diverse domains across time that exhibit time-dependent heterogeneous properties. It is important to not only integrate data from multiple sources (called multiview data), but also to incorporate time dependency for deep understanding of the underlying system. Latent factor models are popular tools for exploring multi-view data. However, it is frequently observed that these models do not perform well for complex systems and they are not applicable to time-series data. Therefore, we propose a generative model based on variational autoencoder and recurrent neural network to infer the latent dynamic factors for multivariate timeseries data. This approach allows us to identify the disentangled latent embeddings across multiple modalities while accounting for the time factor. We invoke our proposed model for analyzing three datasets on which we demonstrate the effectiveness and the interpretability of the model.
A Study on the Relationship between Team Innovativeness of Teachers and their Self-efficacy: Focusing on TALIS 2018

본 연구는 2018 교수-학습 국제조사(Teaching and Learning International Survey, TALIS)』자료를 활용하여, 우리나라 교사들의 동료교사 혁신성과 교사 자기효능감과의 관계를 살펴보았다. 분석에는 초등학교 및 중학교 교사 6,140명을 포함하였고, 다중 대체법과 클러스터 강건 표준오차, 중다회귀를 활용하였다. 분석 결과에 따르면, 첫째, 우리나라 동료교사 혁신성은 학교급과 관계없이 유사하게 나타났으나, OECD 회원국을 포함한 TALIS 2018 참여국가와 비교했을 때에 다소 낮았다. 둘째, 우리나라의 동료교사 혁신성은 다른 변인들을 통제한 후에도 초등학교 및 중학교 교사의 자기효능감과 모두 정적인 관계가 있었다. 셋째, 동료교사 혁신성은 자기효능감 하위요인들과도 유의한 관계가 있었으며, 그 효과의 크기는 학생참여, 수업전략, 교실관리 순으로 나타났으나 학교급 별로 약간의 차이가 있었다. 이러한 분석 결과는 우리나라 교사들의 효능감, 특히 학생참여 및 수업참여 효능감을 높일 수 있는 방안으로서의 동료교사 혁신성이 우선적으로 고려될 수 있음 논의하였다.This study employed 2018 Teaching and Learning International Survey(TALIS) and analyzed the relationship between innovative teachers and their self-efficacy, including sub-self-efficacy scales: student engagement, instructional strategy, and classroom management self-efficacy. For this purpose, this study included 6,140 elementary and middle school teachers and utilized multiple imputation, cluster-robust standard error, and multiple regression. As a result, first, the value of team innovativeness scale is significantly different between elementary and middle school teachers in Korea. But the value of innovative teacher scale in Korea is relatively lower than OECD average. Second, team innovativeness of teachers is positively related to their self-efficacy, regardless of the school-level. Third, team innovativeness is positively associated with the three sub-scales of self-efficacy, particularly student engagement and instructional strategy self-efficacy. Still, there are differences in beta coefficients, between elementary and middle school teachers. These results show that teacher self-efficacy could be much increased when school teachers have innovative peers, so policymakers and educational administrators can consider team innovativeness of teachers as a means of improving teacher self-efficacy, especially student engagement and instructional strategy self-efficacy.
HUBUNGAN BERAT BADAN DAN TINGGI BADAN DENGAN KECERDASAN ANAK DI SDN CANDIMULYO 1

The process of growth and development determines the child's future both physically, mentally and behaviorally. Intelligence is an indicator of the quality of human resources. The aspect of intelligence that affects children's success is cognitive ability. The purpose of this study was to analyze the relationship between and height with the intelligence of school-age children at SDN Candimulyo 1.Cross-sectional research design. The dependent variables in this study were weight and height. The independent variable in this study is the level of intelligence of school-age children. The population in this study were all students in grades 1-5 at SDN Candimulyo 1 in Jombang, totaling 156 respondents. The sample in this study were some of the students in grades 1-5 at SDN Candimulyo 1, Jombang, which amounted to 39 respondents using a proportionate stratified random sampling technique. Measuring instruments used in this study are for weight variables using body scales, for intelligence using the Stanford-Binet Test and observation. Data processing by editing, coding, scoring and tabulating. Analysis using the Multiple Linear Regression Test.The results showed the respondent's weight less than half was 28-30 as many as 12 people (31%), the height of the respondents less than half were 138 - 142 as many as 10 people (26%), the level of intelligence of respondents less than half was 10-12 as much 18 people (46%), there was a positive and significant correlation between intelligence and body weight with a correlation value of 0.320 and a p-value of 0.023, there was a significant correlation between intelligence and body height with a correlation value of 0.391 and a p-value of 0.007.The conclusion in this study is that there is a relationship of weight with the intelligence of school-age children at SDN Candimulyo 1, there is a relationship of height with the intelligence of school-age children at SDN Candimulyo 1.
Visual Analytics for Regional Economic Environment Factors Based on a Dashboard Design

Economic environment is vital for commercial investment, city planning and company strategy planning in urban areas. Mastering the economical trend may help the entrepreneurs, government officers and individuals in their decision-making process. In this study, we explore multiple geo-economic datasets using visual analytics methods for understanding the economic environment. More specifically, we user time-series Gross Domestic Product (GDP) data as an economic indicator of economic development and land use data to support the spatial analysis at a refined geographic scale. The spatiotemporal patterns of the regional economic environment are revealed both qualitatively and quantitatively. The work has a three-fold contributions: (1) we apply a grid-based spatial interpolation model to derive GDP values at a file granularity based on land use data; (2) we design a novel interactive dashboard for the GDP data exploration, which serves as a visual analytical tool between data and users; (3) we combine quantitative analysis with visualizations to strengthen the qualitative analysis. The feasibility of visual analytics methods and the dashboard design are tested in one of the most developed regions, Jiangsu Province, China. Both expected and unexpected economical patterns were extracted.
Effective image stego intrusion detection system using statistical footprints of the steganogram and fusion of classifiers

Enlightening the processing record of a digital image is a significant problem for steganalysers and the forensic analysers. In the present day, the most precise steganalysis techniques are built as supervised classifiers by extracting the feature vectors from the digital media. This paper presents an ensemble classification method for effective image stego intrusion detection system on JPEG images consists of two step process. In the first step the features are engineered as higher-order statistics for blind steganalysis. In the second step ensemble classifier is used by fusing the classifiers such as support vector machine, neural networks, k-nearest neighbours. By applying the mentioned classifiers to these features, the steganogram and the clear (unadultered) carrier signals are effectively discriminated. For generating the image dataset, images are undergone with six embedding schemes with different payload. Experimental results show that the proposed approach remarkably improve the metrics such as specificity, sensitivity and accuracy of the system.
Training configuration analysis of a convolutional neural network object tracker for night surveillance application

&lt;span lang="EN-US"&gt;Automated surveillance during the night is important as it is the period when crimes usually happened. By providing continuous monitoring, coupled with a real-time alert system, appropriate action can be taken immediately if a crime is detected. However, low lighting conditions during the night can degrade the quality of surveillance videos, where the captured images will have low contrast and less discriminative features. Consequently, these factors contribute to the problem of bad appearance representation of the object of interest in the tracking algorithm. Thus, a convolutional neural network-based object tracker for night surveillance is proposed by exploiting the deep feature strength in representing object features spatially and semantically. The proposed convolutional network consists of six layers that consist of three convolutional neural networks (CNN) and three fully connected (FC) layers. The network will be trained by using a binary classifier approach of objects and its background classes, which is updated on a fixed interval so that it fully encapsulates the changes in object appearance as it moves in the scene. The algorithm has been tested with different sets of training data configurations to find the best optimum ones with regards to VOT2015 evaluation protocols, tested on 14-night surveillance videos. The results show that the configuration of a total of 250 training samples with a sample ratio of 4:1 between positive and negative data delivers the best performance for the sequence length of [1,550]. It can be inferred that more information on the object is required compared to the background, where the background might be homogeneous due to low lighting conditions. In conclusion, this algorithm is suitable to be implemented for night surveillance application.&lt;/span&gt;
LibGuides: Libraries Resources and Services During COVID-19 Crisis: Remote Resources and Services

Relevant information related to ODU Libraries operations, resources and services during the COVID-19 crisis.
Gratitude Expressions and Responses used by theCharacters in the Vow Movie

Gratitude expression and gratitude responses isthe choosing way to express and to response one kind feeling orappreciation toward action, saying or benefit received. Peoplelook at it as politeness behavior as the crucial part to build andestablish good social relationship. This research aims to analyzethe expression and response of gratitude by the characters in TheVow movie. The researcher describes what are the gratitudeexpression and gratitude responses used by the characters in TheVow movie. This research is qualitative. It is analyzeddescriptively based on related to Aijmer Theory of gratitudeexpression and Hymes Theory of gratitude responses. The databe explains by showing the context of situation and the meaningof the utterances.
РЕГИОНАЛЬНАЯ ПРАКТИКА РЕАЛИЗАЦИИ КУРСОВ ПОВЫШЕНИЯ КВАЛИФИКАЦИИ В СФЕРЕ ХУДОЖЕСТВЕННОГО ОБРАЗОВАНИЯ

Modern requirements for the level of competence of teachers in the field of art education make it necessary to demonstrate high results in professional activity. The article defines the organizational and substantive foundations of organizing continuing education courses for teachers of children's art schools, describes the experience of implementing additional professional programs in the Sverdlovsk region.
ДОСТОИНСТВА И РИСКИ ПРИМЕНЕНИЯ ИКТ НА ПЕРВОЙ СТУПЕНИ ОБУЧЕНИЯ В УСЛОВИЯХ МАЛОКОМПЛЕКТНОЙ ШКОЛЫ

Definition of notion «ungraded school» discovered in this article. The main problems of school organization and problems of quality primary student’s knowledge are required there. In addition, the main negative and positive sides of using information and communication technologies (ICT) in ungraded primary school considered in this article. The authors propose principles of educational process organization in primary school, on which it is necessary to rely when using information and communication technologies in conditions of small school.
LibGuides: LaGuardia Library Essentials: Home

Information on the services available at LaGuardia's Library Media Resources Center. Includes iPad, laptop, and calculator loan programs.
PELATIHAN KARYA TULIS ILMIAH BAGI MAHASISWA UNIVERSITAS SELAMAT SRI

The purpose of this devotional activity is 1) to provide participants with knowledge in writing scientific papers, 2) to improve students ability in writing scientific papers, 3) to improve and encourage students in writing scientific papers. The Method used in community service are: by method precentation, question and answer, discussion, and practice of composing scientific paper proposal after participating in this training. The participants have understood the types of scientific papers, the tecnique in writing scientific papers, topic determination and preparation of scientific papers. The results in community service are: 1) provide knowledge to the students of University of Selamat Sri, 2) Student who studied this activity are mostly the final study students, so this material helps students in facing process of completing study, 3) Students to preparing and making scientific papers