Reviewerly/exHarmony huggingface dataset:
KESALAHAN PENGGUNAAN KALIMAT EFEKTIF PADA TUGAS KARANGAN DESKRIPSI SISWA KELAS VII A SMP N 06 KOTA JAMBI TAHUN PELAJARAN 2020/2021

This study aims to describe an error in using effective sentences based on the criteria of effective sentences in the descriptive writing of class VII A students of SMP Negeri 06 Jambi city academic year 2020/2021. This research is qualitative descriptive. The data in this research is in the form of sentences, words that do not fit the criteria of effective sentences. This data is obtained from the descriptive writing of class VII A students of SMP Negeri 06 Jambi city. Based on the results of the research, it can be concluded that there was an error in the use of effective sentences in the descriptive writing of class VII A students of SMP Negeri 06 Jambi city academic year 2020/2021 based on four criteria of effective sentences, namely the criteria of completeness, alignment, frugality and variety. Of the four criteria of effective sentences, the least description of the student error found in using effective completeness while the most dominant error is in the criteria of frugality. From the results of this research, researcher suggests that students need to pay more attention in writing effective sentences. It is recommended that students pay more attention to effective sentences in essays and other writings.
Large Learning Gains in Pockets of Extreme Poverty: Experimental Evidence from Guinea Bissau

Children in many extremely poor, remote regions are growing up illiterate and innumerate despite high reported school enrollment ratios. Possible explanations for such poor outcomes include demand – for example, low perceived returns to education compared to opportunity cost; and supply – poor state provision and inability of parents to coordinate and finance better schooling. We conducted a cluster-randomized trial in rural Guinea Bissau to understand the effectiveness and cost of concerted supply-based interventions in such contexts. Our intervention created simple schools offering four years of education to primary-school aged children in lieu of the government. At endline, children receiving the intervention scored 58.1 percentage points better than controls on early grade reading and math tests, demonstrating that the intervention taught children to read and perform basic arithmetic, from a counterfactual condition of very high illiteracy. Our results provide evidence that particularly needy areas may require more concerted, dramatic interventions in education than those usually considered, but that such interventions hold great potential for increasing education levels among the world’s poorest people.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.
Government and It's Directive - The COVID-19 Pandemic Effect

Download This Paper Open PDF in Browser Add Paper to My Library Share: Permalink Using these links will ensure access to this page indefinitely Copy URL Copy DOI
An Auto-Scaling Approach to Load Balance Dynamic Workloads for Cloud Systems

With The Advances In Modern Technology, Need For Cloud Services Is Ever Increasing. In Such Case On Public Real-Time Cloud Environments The Workload On The Respective Server Can Vary Depending On The User Needs. Cloud Computing Is The Latest Technology That Provides On-Demand Availability Of Computer Resources Without Direct Intervention Of The User. This Technology Combined With Cloud Load Balancing Enables Enterprises To Manage Workload Demands. The Cloud Load Balancer, With Auto Scaling Features, Further Increases The Efficiency And Optimized Utilisation Of The Computing Resources. This Paper Discusses How Amazon Web Services As The Cloud Medium Along With Mobaxterm For Remote Control, And Implement ARR Configurations For The Load Balancer To Route The Requests. AWS Gives Us Knowledge About Various Concepts Such As Auto-Scaling Groups, Target Groups, Load Balancers, Etc.
Read and attend: temporal localisation in sign language videos

The objective of this work is to annotate sign instances across a broad vocabulary in continuous sign language. We train a Transformer model to ingest a continuous signing stream and output a sequence of written tokens on a large-scale collection of signing footage with weakly-aligned subtitles. We show that through this training it acquires the ability to attend to a large vocabulary of sign instances in the input sequence, enabling their localisation. Our contributions are as follows: (1) we demonstrate the ability to leverage large quantities of continuous signing videos with weakly-aligned subtitles to localise signs in continuous sign language; (2) we employ the learned attention to automatically generate hundreds of thousands of annotations for a large sign vocabulary; (3) we collect a set of 37K manually verified sign instances across a vocabulary of 950 sign classes to support our study of sign language recognition; (4) by training on the newly annotated data from our method, we outperform the prior state of the art on the BSL-1K sign language recognition benchmark.
Aspectos comparados en Formación de Profesorado

The purpose of this work is to carry out a comparative study on Teacher Training in the face of the health emergency due to COVID 19 in two public institutions of Higher Education in Mexico and Spain. The foundation of this work is found in teacher training models, virtual teaching and teaching innovation. It is necessary to innovate to respond to the unforeseen situation of total virtuality. It is important to reflect on the response in both contexts, because, according to Bray and Adamson (2007), the adoption of the educational institution as a unit of analysis requires that we focus on the institutional culture that is different in both contexts. In the case of Spain it is a University and in the case of Mexico it is an institution of Higher Education but it is not a University. We will focus on the narratives about the students' experience in confinement, about the teaching methodology that had to be changed and the situation experienced by the teachers. The research method used has been a comparative case study, focused on the development of two subjects, one from Mexico and the other from Spain. As Stake (1999) indicates, we intend to achieve an understanding of the changes produced in the teaching of both cases. It is a qualitative research that aims to find elements for improvement by delving into two different contexts. We have found that it is possible to distinguish a series of stages in the response to an unforeseen break in face-to-face teaching, ranging from a situation of uncertainty and concern for the health of students and teachers to the formal modification made in the teaching guides, ending with some difficulties encountered in evaluating student performance. It is important to draw conclusions about the pedagogical aspects that have transformed teaching-learning and that may be useful in similar situations.
Library Guides: EBSCOHOST Database: Using the Persistent Link

This guide has been designed to assist the students towards navigating around the databases
Real Time Contextual Based Gesture Recognition System Using Deep Learning

Nowadays Computer plays a crucial role in daily activities and used among various fields in society. The Interactions between a computer and human is done by basic input devices like keyboard, mouse etc. Hand Gestures can be one of the best and effective medium for human-computer interactions which help in interactions between the both easier. Convolution Neural Network (CNN) which is basically used for image classification and image representation. Also, CNN can learn nonlinear relationships among set of images, considering this we propose a gesture recognition system using CNN. Face recognition software’s are used in various fields like user detection, automobile control, bio metrics and security authentication and enhancements. This project focuses on developing a model to control a system using gestures, while simultaneously monitoring continuously for user and their profile using face recognition to avoid unauthorized access. An effective gesture recognition is developed and applied in conjunction with face recognition system to perform a mapped function in real time.
The Effect of Multipass Strategy in Teaching Reading on Students’ Reading Comprehension

This research aims to look at the effect of the Multipass strategy in teaching reading on students’ reading comprehension (A Library Research). The Multipass strategy and reading comprehension function as the independent variable and dependent variable consecutively. The Multipass strategy is a teaching strategy that aims to increase students' reading ability by using three main procedures; survey-pass, size-up pass, and sort-out pass. The researcher focuses on the lack of students' reading comprehension and aims to find out the effectiveness of the Multipass strategy to improve students' reading comprehension skills. The method of this study is library research and the data attached in this research are obtained from the previous works of the other researchers and some literature sources include journals, books, articles, and internet websites. The data analysis technique includes the process of data identification from relevant literature sources, determining where the data are located, obtaining the data, evaluating the data, and incorporating data into the research presentation. The results of this study show that the students reading comprehension skills were improved after they were given the treatment of the Multipass strategy using ten teaching instructions and the three Multipass main procedures (survey-pass, size-up pass, and sort-out pass). The results were proven by the students' test scores and validity tests. To sum up, the Multipass strategy is considered as the teaching strategy to improve students' reading comprehension skills.
E-learning and Covid-19 - The Nigerian experience: Challenges of teaching technical courses in tertiary institutions

This paper examines the challenges of teaching technical courses through e-learning in Nigerian tertiary institutions during the COVID-19 pandemic lockdown. The COVID-19 pandemic has widespread after-effect on education systems all over the world, with Nigeria, not an exception. Lack of the requirements needed for remote education during the world-wide lockdown caused by the COVID-19 pandemic has impeded teaching and learning. In the underdeveloped world, home education worked well for a few students who had adequate resources accessible to them and were adaptable to remote learning. This has not just affected teaching and learning but has posed a big problem in teaching technical courses. Problems associated with teaching technical courses in Nigeria during the pandemic lockdown especially the difficulties in handling practical and technical processes online is discussed. Students and educators at different programmes at the Federal Polytechnic Nekede Owerri, Nigeria will be interviewed to ascertain the most pressing problems. The paper will also proffer possible solutions through its recommendations at the different levels of the concerned stakeholders in the Nigerian education sector.
Robust GNSS Position Estimation Using Graph Optimization Based Vector Tracking

Vector tracking (VT) is proposed and demonstrated as a superior method to obtain more robust navigation solutions. In VT, instead of individually tracking the signals, VT accomplishes signal tracking and navigation solutions estimation through a central navigation filter, mutual aiding between the channels is realized in this manner. Commonly, a Kalman Filter (KF) is employed as the center navigation filter to estimate the navigation solutions, the estimated navigation solutions are then fed back to calculate the signal tracking parameters. However, KF works in a recursive manner, relationships between the current state and all the past states are ignored, which might degrade the estimation of the navigation solutions. In this paper, we proposed a Graph Optimization (GO) based on VT. GO optimized the state estimation utilizing all the past information instead of KF, the state transformation, and measurement model were all added to the GO as the constraints to optimize the state estimation. An experiment was carried out for assessing the proposed GO-VT, statistical analysis of the navigation solutions and the corresponding comparisons demonstrated the superiority of the proposed GO-VT method.
Thyroid Nodule Identification in Ultrasound Images using CNN

Early detection of any disease assists in reduction of disease progression. In this work discrimination of the thyroid nodules is studied by employing deep learningarchitectures. Deep learning algorithm mimics the function of the human cerebral cortex. Convolutional Neural Network (CNN) is based on deep neural network design which has many hidden layers that are used to train a large dataset.When the number of hidden layers is increased, it has a greater impact on the accuracy. In this study, CNN is employed for assessing the severity of the disease. In CNN, the output of the input layer is fed the convolutional layer followed by ReLU layer and Max pooling layer and the images are classified into Benign (TIRADS 2, TI-RADS 3, TI-RADS 4a) and Malignant (TI-RADS 4b, TI-RADS 5, TIRADS 6).The performance of CNN is compared with the pre-trained networks such as Alex net, VGG-19 and Resnet-50 using transfer learning. The CNN outperformed the pretrained networks with an accuracy of 99.17%.
The Physical Health Impacts of Playing Habits Online Games on Students

Online games are accessed via the internet, and online games can make someone forget the time and addicted. The World Health Organization has categorized game addiction as a mental disorder, and game addiction has many adverse effects, primarily physical health. This study aims to determine the impact of physical health from the habit of playing online games. This study uses a qualitative method with a phenomenological approach. With the incidental sampling technique, this study involved six students who like to play online games. The instrument used was a human instrument with interview guidelines. The triangulation technique used was method triangulation, namely, by using a gaming addiction scale, and the analysis used was content analysis. All participants experienced online game addiction (100%), then the health impacts of playing games were fatigue and feeling dizzy. Besides that, participants have the risk of gastritis and urinary tract infections because they often delay eating and delay urinating. When playing the game, the participants do not want to leave the game because they are not satisfied and cannot control themselves while playing the game. For participants to be able to prioritize physical needs such as rest, eat, drinking, and urinating and defecating, participants can limit their hours of playing games to a maximum of two hours a day to reduce the risk of harmful health impacts.
Research on Information Perception and Interaction Technology of Internet of Things

Abstract With the rapid development of today’s society, the continuous application of network technology has been able to gradually meet the pace of social development. The main purpose of this technology is to transmit and store data and information produced by users in their daily production and life. This technology is widely used in reality. Specifically, it refers to the information connection of the Internet of Things in the facilities with sensors in the user’s home, so as to process the data generated by the user in life. We can found that in real life is often the case, the information in the process of pass due to the inaccuracy of data information, leads to the iot on data transmission in the process of information processing, storage, and there will be a lot of the problem, the emergence of these problems will reduce the intelligent level. This technology mainly includes the interaction between the network and the user, the interaction between the network and the content, the interaction between the user and the content of these three main forms. This paper starts from the perception and interaction of the technology, analyzes the advantages and disadvantages of the Internet of Things technology in our life today, and makes a rational interpretation of the technology fundamentally.
Survey of machine learning methods for spam e-mail classification

The humongous volume of unsolicited bulk e-mail (spam) which is further increasing, is the major cause for developing anti-spam protection filters. Machine learning provides a very optimized approach to automatically filter spams at a very successful rate. Here, in this paper, we survey some of the most popular machine learning algorithms (Naive Bayes, k-NN, SVMs and ANN) and their applicability to the problem of spam e-mail classification. Descriptions of the algorithms are presented, and the comparison of their performance on the UCI spam base dataset is presented.
Optimized Performance and Utilization Analysis of Real-Time Multi Spectral Data/Image Categorization Algorithms for Computer Vision Applications

In the field of computer vision , the process of  acquiring, processing,   analyzing   and   understanding  multispectral data  images is a major requisite. The major tool for digital data analysis and object recognition is data categorization. The basic and main stages involved in data categorization are  the  identification  of  an  appropriate  categorization  system,  an  assortment  of training   and   testing   samples   and   the   categorization   method.  Data categorization (or) classification is to recognize and depict the features of any data that can be later used for knowledge discovery. This work aims to compare supervised data classification techniques. This paper  illustrates utilization of various techniques viz., Minimum distance (MD), Maximum likelihood (ML) and Mahalanob is distance (Mad). All the procedures are compared and analyzed for finest results and maximum accuracy.
태국인 근로자 대상 입국 후 단기 한국어 프로그램 개발 및 앱 설계를 위한 요구 분석

Since the implementation of the employment permit system in 2004, more than 100,000 immigrant workers have been entering the country every year. However, after entering the country, they have difficulty learning Korean due to irregular working hours and limited geographic mobility. The relative lack of Korean language programs for immigrant workers compared to those for international students and marriage immigrants is also a hindrance to Korean language learning. This study aims to conduct a needs analysis and develop a short-term Korean language program for Thai immigrant workers who have entered Korea. To this end, three needs analysis were performed. First, the existing textbooks for immigrant workers, textbook for EPS-TOPIK was analyzed. Second, the existing EPS-TOPIK learning app was analyzed. Third, based on the results of the analysis of the existing textbooks and apps, we surveyed Thai workers who actually entered Korea to examine their needs for the Korean language curriculum. Based on the results of the analysis, the ministry sought to develop a curriculum to design teaching requirements for Thai immigrant workers and use them in actual applications. In this manner, the government has been trying to provide basic data on the development of programs for immigrant workers who have been alienated from Korean language education sites.
Library: Access Services: Equipment

The Access Services Department is responsible for checkout of library materials and equipment and for Interlibrary Loan.
Augmented reality – A potential enabler for advanced medical device use and safety training

This project designed and built two proof of concept Augmented Reality (AR) models for use in two training scenarios; medical device and radiation safety.
LibGuides: March Manga Madness: Home

LPL is giving away manga this March 2021! Starting March 1st, you can call with the title you want from the list below and make an appt. to pick it up: 315-457-0310. All titles are secondhand. Each title is available on a first-come, first-serve basis.
Pengelolaan Dokumentasi Kegiatan Humas pada Institusi di Balai Diklat Lingkungan Hidup dan Kehutanan Kota Pekanbaru

The importance of environmental awareness must receive a special attention from public especially in Pekanbaru which is often affected by environmental demage such as wildfire or illegal logging. The existence of Balai Diklat Lingkungan dan Kehutanan (BDLHK) of Pekanbaru is expected to be able to provide the valid and educative information about environmental issues. Refers to those issues, they need to improve their abiltity to manage institusion’s company profile, informnation management through social media platform, and creating educative, creative, and persuasive content in stop motion video. The purpose of using social media platform is to achieve the society especially youth generation. There are three outputs of this event. first, basic training of making intitusion company profile, second, stop motion video, third, do the social campaign through social media. Hopefully the contribution of this program will be sustainable going forward.
Android Application for Smart Services in College Integrated With IOT and ML

An android application with which the students can have access to certain smart services related to college like canteen orders, Lost and found, Cleanliness, Library, Bus tracking using GPS, Applying for events and placements, etc. There are canteen admin, events admin, placements admin, etc to see the placed orders, post the events information and placements information which can be seen by students respectively. There is one ML module that helps in computing feedback given by students on food and converts that feedback into the rating. All the negative and positive feedbacks of each item can be checked by canteen admin which helps them to improve the quality of the food with more negative feedback. This model was trained using the RNN algorithm. The accuracy of this model is turned out to be around 94%. This model is integrated with android using the TensorFlow Lite file converted from the Keras model.
Loma Linda University Libraries: Mobile Printing: Android Printing

Details the various methods available for printing from mobile devices. Using the Android Pharos Print app
Determination of normality or nonnormality of data distribution

In this step the method for transformation of raw data from a study sample into Z-scores is detailed. This is a fundamental stage for shaping these data as a Gauss curve, in order to know their distribution pattern—normal or nonnormal. According to this key characteristic the researcher will choose either parametrical or nonparametrical statistical tests for finding—or not finding—a difference between studied groups.