Reviewerly/exHarmony huggingface dataset:
Transition in Early Childhood Education

The purpose of this article is to explain why the transition must be researched, comprehended, and included in the Early Childhood Education (ECE) level. In the early childhood education, we need to perceive that involvement, collaboration, and communication between children, families, schools, and community are important factors that will strengthen the transition towards a positive direction in helping children to go to school and encourage them in passing through the transition to Elementary School. Fundamentally a child's growth is influenced by child development aspects which include religious, moral values, physical and motor, cognitive, social-emotional, language and art that has become the basis of every development in learning programs that will be carried out at the level of Early Childhood and Elementary Education. By applying the literature review method, this article aims to gain a holistic apprehension from various perspectives on the significance of transition in Early Childhood Education. The aim of the transition in Early Childhood Education is none other than to help children develop the basic potential that has already existed inside them, not only for increasing children's knowledge and independence but also their apprehension which will later support each other in preparing themselves for Primary level
A Novel Approach for Enhancement of Security and Compression for Cloud Data Storage

Security plays a very important role in any environment. Now a day’s cloud computing environment is used in any industry or organization in order to store the data. So many vendors are providing free space for storing users or client data. The major problem in this environment is data is located in different places from different users or clients, protecting data from unauthorized person is a typical thing in now a days. There is necessity for proposing a better security approach for protecting data from unauthorized persons. In this paper we proposed new technique for protecting our secret data and also reduce the storage space. For protecting data here we can use image steganography technique along with the secret pixels and in combination with cascading neural network technique to train the selected pixels. After storing the data in image the image is compressed with new algorithm for reducing storage space in a cloud environment. The performance of the proposed approach is evaluated with various parameters like PSNR, MSE for different length of secret message and also bit ratio is tested and calculated. Results are good compared to various image steganography algorithms and compression algorithms.
DESIGN AND DEVELOPMENT OF MONITORING SYSTEM APPLICATIONS LYN SEPARATION OF STTAL PERSONNEL BASED ON ANDROID SYSTEM

The STTAL personnel pickup lyn mechanism and system is a means of pick-up transportation that helps STTAL personnel to transport departures from the pickup location to the work unit (satker). With the STTAL personnel pickup lyn facility can improve the performance of personnel at each work unit, travel time to the work unit is faster than using public transportation. Updated information related to vehicles in support of personnel pick-up cannot yet be fully accessed by personnel, so misinformation often occurs. Therefore, it is necessary to design an Android-based personnel pickup lyn monitoring system application. Here we will design a device for monitoring the pickup lyn by using a transmitter device in the form of a cellphone carried by a man or driver. This system can provide information through an application that is embedded on Android by looking at an integrated application in Open Street Map, which is able to send vehicle position data through an application that is planted on the Android user so that STTAL personnel can monitor the position of pickup service vehicles and updated information related to the vehicle. worn. Users can access the application and see the pickup lyn position on the android mobile. After this system is built, it makes it easy for all STTAL personnel who use the pickup service vehicles to monitor the position of the vehicle through applications that are planted on Android.&#x0D; Keywords : Android, Lyn pickup personnel, Open Street Map
Multi-Level Creation of Fuzzy Ensembles through Diversified Settings of Parameters

Due to the presence of shades of grey in reality, the fuzzy set theory has been popularly used for dealing with real-life classification problems in the setting of machine learning. In particular, fuzzy rule-based systems are trained using real-life data for classifying new instances that involve fuzziness, impression and uncertainty. Traditional approaches have been typically designed to produce fuzzy rule-based systems in a specific setting of parameters (e.g., t-norm and t-conorm). However, the same setting of parameters would usually lead to the production of fuzzy systems that show varied performance on different data sets. In order to keep the performance more stable and consistently good enough, in this paper, we propose a fuzzy rule ensemble approach that involves multi-level diversity creation through diversified settings of parameters, e.g., diversified use of features and heuristics for training of fuzzy rule-based classifiers. The experimental results indicate that the fuzzy classification performance is advanced on multiple data sets through adopting our proposed approach, in comparison with other approaches of training single fuzzy rule-based classifiers and creating fuzzy ensembles.
AMBER: Adaptive multi-batch experience replay for continuous action control

In this paper, a new adaptive multi-batch experience replay scheme is proposed for proximal policy optimization (PPO) for continuous action control. On the contrary to original PPO, the proposed scheme uses the batch samples of past policies as well as the current policy for the update for the next policy, where the number of the used past batches is adaptively determined based on the oldness of the past batches measured by the average importance sampling (IS) weight. The new algorithm constructed by combining PPO with the proposed multi-batch experience replay scheme maintains the advantages of original PPO such as random mini-batch sampling and small bias due to low IS weights by storing the pre-computed advantages and values and adaptively determining the mini-batch size. Numerical results show that the proposed method significantly increases the speed and stability of convergence on various continuous control tasks compared to original PPO.
Download FFmpeg Audacity in 2020 (How to Install & Update)

FFmpeg audacity is an order line apparatus that changes over sound or video groups. FFmpeg can likewise capture and encode progressively from different ...
Situational Self-Efficacy and Behavioral Responses to Wearable Use

Wearables have the potential to optimize health-related behaviors like physical activity and nutritional intake and to improve individual health outcomes. However, researchers are still doubtful about wearables’ capacity to induce behavior change in users. Research that has built on self-efficacy theory has shown that using wearables can influence the users’ perceptions of self-efficacy and behavioral responses both positively and negatively, indicating that there is little stability over time. This study will investigate the factors that cause instability in users’ situational perceptions of self-efficacy and behavioral reactions. We plan to conduct a longitudinal, quasi-experimental field study with wearable users who self-report in weekly intervals on action-related restrictiveness, contextual restrictiveness, personal restrictiveness, situational self-efficacy, and their behavioral responses over eight weeks. Preliminary results from a pilot study with a reduced sample showed promising results. We will contribute to self-efficacy research by clarifying the factors that cause variations in behavioral responses and finding quantitative support for a situationally varying construct of self-efficacy. We will contribute to practice by deriving implications for the design of wearable devices.
Operation Skill Acquisition and Fuzzy-Rule Extraction for Drone Control Based on Visual Information Using Deep Learning

In recent years, much research on the unmanned control of a moving vehicle has been conducted, and various robots and motor vehicles moving automatically are being used. However, the more complicated the environment is, the more difficult it is for the autonomous vehicles to move automatically. Even in such a challenging environment, however, an expert with the necessary operation skill can sometimes perform the appropriate control of the moving vehicle. In this research, a method for learning a human’s operation skill using a convolutional neural network (CNN) and setting visual information for input is proposed for learning more complicated environmental information. A CNN is a kind of deep-learning network, and it exhibits high performance in the field of image recognition. In this experiment, the operation knowledge was also visualized using a fuzzy neural network with obtained input-output maps to create fuzzy rules. To verify the effectiveness of this method, an experiment involving operation skill acquisition by some subjects using a drone control simulator was conducted.
Games and the metalinguistic dimension: reflections on grammar teaching

This paper presents some theoretical reflections on games for didactic purposes, used as a didactic instrument to enhance metalinguistic awareness. After a brief discussion of the ethics of games and of a pedagogical framework of playful teaching, the paper argues for the need for profound changes in traditional grammar teaching. Finally, it encourages to investigate the use of crossword games in the classroom as a method of supporting and developing metalinguistic awareness.
Motives of Foreign Direct Investment (FDI) in Ethiopia: An Empirical Analysis

The central aim of this paper is to investigate the major motives of inward FDI to Ethiopia from 1992-2015. Various economic and financial variables were taken into consideration to assess the relationship between FDI and its motivational factors. Ordinary Least Square method was applied to estimate the association, while Johansen’s co-integration test was employed to examine the combination, and Vector Auto-regressive (VAR) model was used to check whether there is a long run relationship between FDI and explanatory variables. The statistical results show that there is positive and significant relationship between FDI and market size, trade openness, exchange rate and financial freedom whereas inflation had negative and significant association with FDI. However, investment freedom and economic globalization indicated an insignificant relation. Even though all variables jointly affect FDI in the long run, the VAR result didn’t reveal any long term relationship between FDI and its motivational factors individually
A Protected Valid Theme for Private Image Sharing using Weiner Filtering

Confirmable Private Image Distribution has become an essential area of research in contemporary cryptography. Since time obliges the demand for privacy and confirmability to maintain the deception situation, a unique private picture sharing system recognizing the occurrence of a cheater is presented and interpreted in this paper. A method to assure the probity of the private picture before its replacement is recommended. An n x n private picture and n x n confirmation picture are used to create parts that are set into a cover picture for transmission. Structural comparison and mean square error model of reconstructed confirmation image with a unique confirmation image that verifies the integrity of the private picture. To minimize the value of the mean square root, the Weiner Filter method is used. The computational price of this system is low which makes it proper for covert information transfer and distribution of scanned records.
A Case Study of Programs for Enhancing Teaching Competency

본 연구에서는 대학에서 교수역량 지원을 위한 서포터즈 프로그램을 개발하여 실제 운영한 결과에 대한 학습자의 전반자인 인식과 서포터즈 활동으로 인해 나타나는 효과를 분석하는데 목적이 있다. 이에 위해 충청북도 소재 K 대학 교수학습센터에서 운영한 서포터즈 프로그램의 개발 및 운영 절차를 소개하고, 서포터즈 활동에 대한 구체적인 성찰 등을 사례로 제시하였다. 서포터즈 프로그램은 교수체제개발(ISD)의 대표적인 ADDIE 모형을 토대로 진행하였다. 분석 단계는 교수 프로그램을 분석하여 구체적인 요구사항을 도출하였고 설계 단계는 교수지원 요구 도출을 기반으로 서포터즈 프로그램 운영 계획 및 프로그램 만족도 측정 도구를 설계하였다. 개발 단계는 서포터즈 활동 가이드 개발 및 보고서 양식 개발을 진행하였고, 실행 단계는 프로그램 운영 및 교수자 대상으로 프로그램 홍보물 배포를 하였다. 마지막 평가 단계에서는 교수지원 서포터즈 프로그램 결과보고서 및 CQI 보고서 작성을 수행하였다. 프로그램 참여 경험을 토대로 학생들이 서포터즈 프로그램에 대하여 전반적인 인식 분석 결과는 다음과 같다. 첫째, 서포터즈 활동에 참여한 학생들은 프로그램에 대해 전반적으로 만족하는 것으로 나타났다. 이는 서포터즈 활동에 대한 세부적인 계획과 교수자 지원 방향 등을 팀 별로 고민하고 실행하기 위한 자기주도적인 수행이 촉진되었기 때문이라고 할 수 있다. 둘째, 프로그램 실행 전 사전 교육에 대한 중요성을 높게 인식하고 있었다. 프로그램의 목적, 구체적인 활동 영역, 추후 관리 방안 등의 내용을 안내하여 서포터즈 활동에 대한 수월성을 높였다고 할 수 있다. 마지막으로, 프로그램 만족도 요소 중 추천 의향이 높게 났다. 이는 학습자가 자신이 가지고 있는 지식과 기술 등을 교수자에게 지원해 주는 측면에서 상호작용 효과가 일어났기 때문이라고 할 수 있다. 이와 같은 결과를 바탕으로 본 프로그램에 참여한 교수자의 반응을 별도로 분석하여 실질적인 교수실행 효과를 측정해 볼 필요가 있다.This study is a case study on developing and operating supporters programs to support teaching competency. The program was developed based on the ADDIE model. The survey log for satisfaction and supporter activities was compiled and analyzed based on feedback from the students who participated in the supporters program. The research results are as follows. Firstly, learners were generally satisfied with the supporters program, which promoted self-directed performance while giving due consideration to each team’s detailed supporter activities plan as well as methods for increasing the teaching support effect. Secondly, because the program promoted supporter activity efficiency by informing participants about the program’s purpose and specific activities in advance, the participants recognized the importance of receiving such an education prior to the program’s implementation. Lastly, as a result of the interaction effect in terms of learners supporting the instructor with their knowledge and skills, the majority of participants expressed their intention to recommend the program, among other satisfaction indicators.
PRINCIPALS’ VIEW ON PERFORMANCE OF ELEMENTARY SCHOOL TEACHERS IN PEKANBARU - RIAU - INDONESIA

It cannot be denied that the performance of teachers will greatly influence the success of schools in achieving its goals. This descriptive research is intended to discuss: (1) the principals' view on the performance of public elementary school teachers in Pekanbaru, Riau, Indonesia; (2) principals' expectations for the teachers' performance in the future; and (3) challenges faced by principals to improve teachers' performance in the future. This descriptive quantitative research was carried out at public elementary schools in Pekanbaru in May 2019 to October 2019. By using a proportional random sampling technique, 66 of 191 elementary school principals spread across 12 districts in Pekanbaru were selected as the sample. The questionnaire addressed to the principal was used as an instrument which was then analyzed through descriptive statistical analysis. In the end, it can be concluded that the best performance of teachers is in implementing the learning process. However, their performance in carrying out additional tasks in schools was rated by principals as the lowest average of all categories. The principals' expectations of the teachers' performance in the future are related to improving teacher competencies as well as improving the ability to utilize technology and equipment available at school. While the challenges faced, however, are related to the lack of willingness of teachers to continue their education and limited funds to participate in various training.
Role of Nurses in Caring Patients with Amputation

Amputation is done commonly in Traumatic conditions such as crush injuries, where there is extensive tissue damage especially to the blood supply. As a surgical procedure, it is used to manage pain or a disease progression in the affected limb such as malignancy or gangrene. Usually medical treatment aims at prevention of any amputation. If preservation is not possible, amputation is done. It causes psychological trauma to the person and family involved. It is the responsibility of the nursing staff to prepare them for surgery and rehabilitation.
Inventory Information Systems of Health Equipment for the Need of Hospital Services

The hospital is a health service institution that is social and financial in nature. In hospitals, medical devices are very important in supporting the company's operational activities, therefore medical devices must be managed properly, so a supply information system for medical devices is needed so that the management of medical devices runs well, so it does not occur. shortages or excess supply of medical devices that will affect the need for inpatient services. This research was conducted at Siloam Hospital, Jakarta, Indonesia. The method used is descriptive analysis method. The results of the research done indicate that: (1) information system inventory of health equipment at Siloam Hospital, Jakarta, Indonesia is adequate, (2) the information system inventory of health equipment turned out to be instrumental to the needs of inpatient services at Siloam Hospital , Jakarta, Indonesia, (3) internal control of Siloam Hospital's inventory is still ineffective, because there are still standard operating procedures that are still not carried out properly in the control environment, which is caused by employee failure to follow procedures and employees who are not or not trained.
What should we do (or should not) with INVALSI data

The present contribution examines the debate in the press following the publication of the results of the Invalsi tests in July 2019, pointing out hasty interpretations, or misleading ones, proposed by journalists. The second part proposes some ideas on how to interpret the data on linguistic competence gained from the Invalsi tests correctly, and how to exploit them as a useful instrument for the improvement of teaching.
LibGuides: Assignment Planning: Write

This sections outlines the steps involved in planning and writing your assignment Description of the structure of a written assignment
PND80 USE OF MACHINE LEARNING VERSUS TRADITIONAL REGRESSION TO PREDICT MULTIPLE SCLEROSIS-RELATED INPATIENT VISITS AMONG NEWLY DIAGNOSED PATIENTS

Machine learning (ML) methodologies are increasingly used to provide insights in a wide variety of life sciences applications. This study aimed to compare the value of machine learning methodologies to traditional regression models when predicting risk of inpatient (IP) visits among newly diagnosed multiple sclerosis (MS) patients. Adult patients with 1+ inpatient MS diagnosis, 2+ outpatient MS diagnoses, or 1+ outpatient MS diagnosis with 1+ disease-modifying drugs between 1/1/2012-9/30/2018 with continuous enrollment of >1 year before and after their first MS diagnosis (index date) were selected from the IBM® MarketScan® Research Databases. Demographics were assessed on the index date, clinical characteristics were measured over 12 months prior to index, and MS-related IP visits were assessed over 12 months after index. Logistic regression, ridge regression, random forest, and neural net models were trained using a 75% random selection of patients. Model performance was evaluated on the remaining 25% of patients using area under the receiver operator curve (ROC-AUC) and Brier scores. 18,381 MS patients were identified, 412 of which had an inpatient visit within the 12-month follow-up period. The neural network model performed best (ROC-AUC =0.692, Brier score=0.0217), followed by the ridge regression ROC-AUC =0.691, Brier score = 0.0218), random forest (ROC-AUC =0.687, Brier score=0.0216), and logistic regression (ROC-AUC =0.675, Brier score=0.0218). All models identified age, pre-index healthcare expenditures, all-cause ER visits, and number of outpatient visits as important predictors of MS-related IP visits. ML methods modestly outperform traditional logistic regression at predicting the probability of MS-related IP visits within 1 year of MS diagnosis. The performance improvements should be weighed against the additional analytic complexity and reduced interpretability of the ML models.
Research on the Application of Formative Evaluation in Teaching Foreign Language in Colleges and Universities

Formative evaluation is relatively more scientific and accurate as compared to traditional teaching evaluation. Formative evaluation is a method of professional evaluation of students’ learning process, which is very important in the entire course of teaching. In the actual teaching process, formative evaluation can better help teachers understand the situation of students, and take effective improvement measures to address the problems existing in the process of learning. As a contribution to the teaching of foreign languages in the colleges and universities, this paper will start with an introduction of formative evaluation, and then the application of formative evaluation in teaching.
The prospect of the proposed Currency Union on intra-regional trade in East African Community

Currency union with a common policy is welfare superlative to the use of sovereign currencies even if a member of the East African Community uses a convertible currency. In this background, the study evaluates whether adopting a common currency will lead to trade using an augmented gravity model of international trade. Additionally, the study investigates the effect of tariffs and nontariff on trade in EAC. The results show that adopting a common currency will lead to trade. Also, the study showed that trade will be enhanced by six-folds when tariffs and nontariff is eliminated. The study concludes that a currency union with a common policy could serve as a panacea when the appropriate institutional policy framework is adopted to ensure transparency by reducing trade and non-trade barriers.
It's not easy being green - detecting arc-related mineral system fingerprints using mineral chemistry in 'propylitic alteration' in a Cambrian arc terrane Victoria, Australia

Epidote and chlorite compositional data were collected using laser ablation inductively-eoupled mass spectrometry (ICP-MS) on samples from two mineral prospects in the Cambrian Stavely Arc, western Victoria. The aim was to distinguish between regional metamorphic and hydrothermal alteration origins for epidote-chlorite-bearing assemblages. At the Thursday's Gossan Porphyry Cu(-Au-Ag) Prospect, chlorite signatures are similar to both propy1itic hydrothermal and regional metamorphic origins, however, elevated Zn and Sr contents are associated with the former. Application of the chlorite proximitors (predicted distance to a hydrothermal centre) identify a likely hydrothermal centre at depth. At the Eclipse Cu-Zn(-Au) VHMS Prospect, epidote As and Sb and chlorite Zn, Cu and Pb contents are consistent with propylitic alteration in most samples. Systematic variations in chlorite Cu and Pb and As and Cu in epidote contents identify a portion of the prospect for follow-up exploration. This study demonstrates that even a limited epidote-chlorite mineral chemistry dataset can provide fertility and vectoring information for mineral exploration targeting. These data are consistent largerscale geochemical data and geodynamic models that predict the Stavely Arc has significant arc-related mineral system potential.
Face Recognition Based on Weighted Fusion of Face Similarity Features

A method for weighted fusion of similarity features to describe faces is proposed. Similarity feature is extracted from similar face, which has good stability. The fusion of uncorrelated similarity features is more conducive to face recognition. Firstly, the Euclidean distance between similarity features is calculated, and the similarity features are screened to find a set of uncorrelated similarity features, which effectively reduces the number of features and removes redundant information between similarity features. Then, the similarity features are adaptive weighted fusion and the fusion result is detected in the AR face database. The final simulation experiment achieve good results.