Reviewerly/exHarmony huggingface dataset:
The Effect of the Elderly's Motivation to Participate in Lifelong Education on their Life Satisfaction

The purpose of this study is to research the effect of the elderly's motivation to participate in lifelong education on their life satisfaction.Data was collected from November 1, 2018 to December 31, 2018.The survey was distributed to 250 elderly living in K city and a total of 209 responses were used in the final data analysis.As a result, activity-oriented motivation (β = .448p <.001) was found to have the greatest influence in regards to the effect of the elderly's lifelong education motivation on life satisfaction.The explanatory power of this model was 35.3%.Such results show the importance of increasing activity-oriented motivation in the elderly to improve life satisfaction of those participating in lifelong education.The increase in life expectancy and various social changes necessitate lifelong education of the elderly.In the case of the elderly, lifelong education programs provide an opportunity to improve the quality of life by overcoming social alienation and promoting interpersonal relationships.Hence, activity-oriented motivation can be construed to be effective in improving the life satisfaction of the elderly.
Al-Quran Learning Through Information Processing Model Ala Joyce and Weil MTs Works in The Village Lara Mulya Baebunta District District North Luwu

Research is executed with Actions Observational method braze (PTK). This research is executed at MTs Mulya's Opus with the subject of research student brazes VII by a total of 22 students, 1 teacher and Headmaster. Acquired Data source of that student covers, formative student essay in work problem that is given at the early cycle. Observation sheet result to measure the result step-up studies student with implemented a model of Information proceedings. Observation result and field note that gets bearing with student activity's learning on al Qur 'an happens. Observational result and the analysis concludes that deep upgrade in observational learning. 1). Proceedingses implement models models suit to arouse student information point and student studying with information yen proceedings concept has a mission to help the student to concentrate at one particular domain the which they can gain control. Observation / control, helping student develops conceptual grasp about a particular domain. 2). Learned yielding step-up student of each cycle, the which is on essays average value interest quiz 69 on 1. cycle is average value of 68.4 and on cycle IV. average value is 76.77. 3. Interference in implementation is as follows: 1) student were given by the task extant a portion out of focus little deep and serious solve that task, 2) reducings the late UNDERSTATING of material already being taught by the teacher were the caused by reducing it concentrate while word teacher.
Binary Logistic Regression Analysis of Instructional Leadership Factors Affecting English Language Literacy in Primary Schools

This paper discusses the factors contributing to student achievement in English language literacy in primary schools within Sibu division, Sarawak, Malaysia. The study involved 694 teachers who taught in 105 lower primary schools. Binary logistic regression was applied to predict the instructional leadership’s influence on student achievement in literacy. The findings revealed that one dimension of instructional leadership - supervising and evaluating instruction - emerged as strong predictors of literacy. The result indicated that schools were more than 17 times more likely to achieve 100% literacy rate when the instruction processes were supervised and evaluated by the headmasters . Supervision and evaluation of instruction had a positive influence on students’ achievement for English language literacy, hence making this a possible course of action for school heads. More comprehensive studies are needed to ascertain its consistency as well as investigating other predictors for literacy. Keywords: Instructional leadership; literacy; binary logistic regression; LINUS2.0
Beginners’ Quest to Formalize Mathematics: A Feasibility Study in Isabelle

How difficult are interactive theorem provers to use? We respond by reviewing the formalization of Hilbert’s tenth problem in Isabelle/HOL carried out by an undergraduate research group at Jacobs University Bremen. We argue that, as demonstrated by our example, proof assistants are feasible for beginners to formalize mathematics. With the aim to make the field more accessible, we also survey hurdles that arise when learning an interactive theorem prover. Broadly, we advocate for an increased adoption of interactive theorem provers in mathematical research and curricula.
Board 156: Enriching Communication in Introductory Computer Science Courses: A Retrospective of the Agile Communicators Project

Tools in this project include process oriented guided inquiry learning, automated feedback to students through an intelligent tutoring system, case studies in software communication, and guided reflective exercises on team communication.As part of this research, the Agile Communicators team has investigated communication practices in a variety of student and professional software development environments.
BOTH PEER EDUCATION AND DEMONSTRATION METHOD IMPROVE STUDENT’S KNOWLEDGE IN FIRST AID OF TRAFFIC ACCIDENT

Traffic accident has become one of the main problems in the world with increasing numbers of occurrence annually.Traffic accident needs immediate and accurate treatment before main aid from medical staff.First aid becomes important and immediate interventions which a lay person can perform with minimum or without medical equipment.First aid is closely related to knowledge of a lay person.The people's knowledge can be improved through peer education and demonstration methods toward students' knowledge in giving first aid related to traffic accident.This study was quasi experiment with pretest-posttest with control group approach.There were respondents consisting of 48 participants devided into two groups.The data was analyzed by using paired t-test and independence sample t-test.Questionnaire were used to measure the knowledge before and after intervention.The findings showed improvement on students' knowledge about traffic accident with peer education and demonstration methods respectively (p=0.000).There was no difference in improvement of the knowledge for both methods (p=0.512).Peer education and demonstration methods can be used to improve students' knowledge dealing with first aid of traffic accident.
Studi Pengaruh Empat Faktor Tipografi terhadap Waktu Pencarian Kata pada Layar Komputer

This study aims to investigate the effect of font type, font size, line spacing and text background colour on visual search of “a predetermined word”. The study used a multifactorial experiment with four factors and 48 combinations. A number of 20 female undergraduate students participated in this study and their response time for each treatment combination was recorded. Anova test results showed that there were significant effect of font type (F=2.72, p=0.042) and font size (F=8.14, p=0.004) to the response time of subject. Further analysis using ANOM chart showed that verdana for font type and 12 pt for font size provide the fastest response time. Results of this study could be used by web designers for the production of web pages so that it will optimize interaction with the users.
UNH at SemEval-2019 Task 12: Toponym Resolution in Scientific Papers

The SemEval-2019 Task 12 is toponym resolution in scientific papers.We focus on Subtask 1: Toponym Detection which is the identification of spans of text for place names mentioned in a document.We propose two methods: 1) sliding window convolutional neural network using ELMo embeddings (CNN-ELMo), and 2) sliding window multi-Layer perceptron using ELMo embeddings (MLP-ELMo).We also submit a bi-directional LSTM with Conditional Random Fields (bi-LSTM) as a strong baseline given its stateof-art performance in Named Entity Recognition (NER) task.Our best performing model is CNN-ELMo with a F1 of 0.844 which was below bi-LSTM F1 of 0.862 when evaluated on overlap macro detection.Eight teams participated in this subtask with a total of 21 submissions.
PENGEMBANGAN SISTEM INVENTARIS BERBASIS QR CODE MENGGUNAKAN WEB SERVICE PADA BIDANG SARANA DAN PRASARANA STMIK STIKOM INDONESIA

Web service is one of the methods which is very useful in solving problems in various fields such as from government, education, economics, social, culture. Web services can be defined as methods in exchanging data that can be done without paying attention to where the database is embedded and made in any language. Web services are able to support interoperability, so that the web service is able to become a bridge between various existing systems. STMIK STIKOM INDONESIA is an institution that has used an information system in managing all activities of the academic community within the institution. One of them is the inventory information system, but when doing the overall inventory there was a problem in synchronizing data in the field with the system. It required a long process and took a long time. So that a QR code-based inventory system was developed to simplify and speed up the synchronization process using a web service. The results of the study proved to be able to facilitate and accelerate the performance of staff in synchronizing data in the field with data on the system.
Interaction of higher and post-university education as a factor of the formation and development of the professionalism of young specialists

The aim of this study is to analyze interaction of university and postgraduate education as a factor in formation and development of qualification of the young specialists. Students of higher educational institutions and young employees aged 18 - 30 years at the industrial enterprises of the Urals serve as the object for empirical analysis. In order to achieve this goal, a set of complementary methods was used: theoretical and empirical (study and generalization of practical experience; questionnaires; qualitative and quantitative analysis of the results), as well as statistical data analysis. The article presents the results of modern students’ monitoring analysis displaying the issues of primary professional development, as well as the survey of young employees at the modern industrial enterprises, reflecting the problems of their professional advancement and prospects for professional and career growth. The conclusion is made about the need for interaction between higher and postgraduate education not only to ensure formation and development of professionalism of the young employees, but also the economic sustainability of enterprises.
Exposure time shortened integrating-bucket method for sinusoidal phase shifting interferometry

Traditional four-bucket method for sinusoidal phase shifting interferometry (PSI) assumes the integration time Ts to be equal to a quarter of the modulation period Tc. As some image sensors need certain vacant time between two integrations, this assumption makes it somehow unrealistic to perform one measurement within a modulation period. Addressing this problem we investigated the four-integrating-bucket method with a shortened exposure time. We assume Ts to be any value between 0 and Tc/4 such that there would be some time between two adjacent integrations and the measurement can be fulfilled in one modulation period. The optimum modulation depth and phase offset of the sinusoidal modulation are deduced for different Ts by minimizing xthe phase noise induced by additive noise. It is found that the optimum modulation depth is always around 2.45 whatever the value of Ts is. What is more, decreasing the integration time to less than Tc/4 helps to improve the fringe visibility as well and to further reduce the phase noise by up to 2.5 dB at most, which are demonstrated by both simulation and experiment.
A Survey Based Investigation for Cloud Computing Adoption Internationally

Cloud computing (CC) is a new trend in information technology and has the potential to play a major role, in addressing inefficient resources, make a fundamental growth and competitiveness for large, small and medium enterprises (SMEs) internationally.The main benefits of adoption of CC services by Large and SMEs will be able to use the latest technology, without the need for the upfront cost, but reducing cost, providing a secure information platform and increasing productivity.The main drawback is that most organisations are adopting the CC without properly understanding that information data they are storing in the cloud is secure or not.The primary objective of this paper is to explore the CC adoption from large and SME perspective internationally.The current state of CC information intensity, different levels of external and other support in the organisations, motivations, requirements prevent the intensity of information and various level of external and other support for CC environment, the study findings can provide guidance on how to address the business and technology risks associated by CC adoption.However, a survey is conducted internationally on 107 Large and SMEs through survey monkey website, which shows interest in the CC services adoption.Specifically, in this paper users are evaluated through 6 factors, for instance, external support, competitive pressure, senior management support, employees cloud knowledge, adequate resources and information intensity.Though survey it is revealed that already adopted some cloud services are 84.11%, are in the processes of Implementing 8.41%, intend to adopt cloud services in the next 3 years 6.54% and don 't intend to adopt any cloud services in near future 0.93%.The findings are expected to be beneficial for Large and SMEs in their adoption of CC services and may also be useful for service providers with respect to end-users'concerns.
Ubiquitous Fitting: Ontology-Based Dynamic Exercise Program Generation

In order to reduce the incidence of disease and decrease the proportion of “sub-health”, exercise regularly is one of the most important factors to solve these problems. Regular exercise has many positive effects on body’s systems, while inappropriate forms of exercise can cause problems or even have adverse consequences for health. Therefore, this research aims to develop an ontology-driven knowledge-based system to dynamically generating personalized exercise programs. The generated plan exposing REST style web services, which can be accessed from any Internet-enabled device and deployed in cloud computing environments. To ensure the practicality of the generated exercise plans, encapsulated knowledge used as a basis for inference in the system is acquired from domain experts. Also, we integrate the system with wearable devices so that we can collect real-time data, for example, heart rate. In the future, break through the limitations of equipment, the accuracy and reliability can be promoted.
STUDENTS’ PERCEPTION TOWARDS THE USE OF CODE-SWITCHING USE IN EFL CLASSROOM

As a foreign language in Indonesia, English is still difficult subject for majority of the Indonesian students, even though it has been taught in junior high school, senior high school, English course, and another education institution. Therefore, many English learning-teaching activities in Indonesia use code-switching. Code-switching is language change (switch) in communication, from one language to another, code-switching here means Indonesian to English or English to Indonesian. This research examined the students’ perception towards code-switching use in English Foreign Language (EFL) classroom. This research applied survey research method, and the instruments were consisted of questionnaire and interview session. Thirty students were involved in filling questionnaire and nine students were involved in both questionnaire and interview. The result showed that (1) majority of students agree on code-switching use in learning teaching activity (2) they perceive code-switching helps them in improving their listening skills (3) they give more respect to teachers who use code-switching when they teach (4) they consider code-switching use increases their chance in passing examination and (5) they feel more comfort and more confident when they study English.
Deep Learning-Based Real-Time Failure Detection of Storage Devices

With the rapid development of cloud technologies, evaluating cloud-based services has emerged as a critical consideration for data center storage system reliability, and ensuring such reliability is the primary priority for such centers. Therefore, a mechanism by which data centers can automatically monitor and perform predictive maintenance to prevent hard disk failures can effectively improve the reliability of cloud services. This study develops an alarm system for self-monitoring hard drives that provides fault prediction for hard disk failure. Combined with big data analysis and deep learning technologies, machine fault pre-diagnosis technology is used as the starting point for fault warning. Finally, a predictive model is constructed using Long and Short Term Memory (LSTM) Neural Networks for Recurrent Neural Networks (RNN). The resulting monitoring process provides condition monitoring and fault diagnosis for equipment which can diagnose abnormalities before failure, thus ensuring optimal equipment operation.
Beyond Context: A New Perspective for Word Embeddings

Most word embeddings today are trained by optimizing a language modeling goal of scoring words in their context, modeled as a multiclass classification problem.Despite the successes of this assumption, it is incomplete: in addition to its context, orthographical or morphological aspects of words can offer clues about their meaning.In this paper, we define a new modeling framework for training word embeddings that captures this intuition.Our framework is based on the well-studied problem of multi-label classification and, consequently, exposes several design choices for featurizing words and contexts, loss functions for training and score normalization.Indeed, standard models such as CBOW and FAST-TEXT are specific choices along each of these axes.We show via experiments that by combining feature engineering with embedding learning, our method can outperform CBOW using only 10% of the training data in both the standard word embedding evaluations and also text classification experiments.
Digitalization and A.I. as Challenges and Chances for Future Teaching and Teacher Education: A Reflection

Digitalization as a key issue of society is increasingly a topic in school. Authorities like the recently deceased scientist Stephen Hawking and the founder and ceo of Tesla, Elon Musk, see both challenges and chances in the developing artificial intelligence (A.I.). Musk remarked: “A.I. will be the best or worst thing ever for humanity” ( cnbc 1 2017). The solution, Musk said, is to increase regulatory oversight of the development and implementation of A.I. immediately: “AI is a rare case where I think we need to be proactive in regulation than be reactive.” ( cnbc 2 2017). Stephen Hawking emphasizes the same point: “The emergence of A.I. could be the “worst event in the history of our civilization” unless society finds a way to control its development (…). Success in creating effective A.I. could be the biggest event in the history of our civilization. Or the worst. We just don’t know.” Hawking said during a talk at the Web Summit technology conference in Lisbon, Portugal, in 2017. ( cnbc 3 2017). In view of these considerations and in regard to the meaning for education in school the question arises: Which topics and competencies should be presented to pupils against the background of the rapid processing in the field of digitalization and the corresponding uncertainty of topics and competencies that could be of importance in some years and decades? Verbalized differently: What does sustainable education for our future include? The answer will be aimed at the teaching and acquirement of basic competencies in general and in the field of digitalization. What should this “basic education” include? Another question is: How is it possible to combine learning processes in a “virtual reality” with learning processes in a “natural reality”? Further considerations are given in this article.
PENGARUH PEMANFAATAN SIMARI SEBAGAI IMPLEMENTASI PEMBELAJARAN BERBASIS E-LEARNING TERHADAP HASIL BELAJAR MAHASISWA PRODI PENDIDIKAN EKONOMI

Utilization of SIMARI (Integrated Lambung Mangkurat University Information System) as a form of implementation of the application of e-learning in learning, has begun at Lambung Mangkurat University, especially in the Economic Education Study Program since the even semester of the academic year 2017/2018. The problem that arises is that there are still limited subjects applying SIMARI. This study aims to analyze the effect of SIMARI utilization as the implementation of e-learning based learning on the learning outcomes of ULM FKIP Economics Education students. Research uses a quantitative approach. The population in this study were all students of the Economic Education Study Program who had participated in e-learning totaling 291 people. Samples were taken as much as 25%, namely 73 people with stratified sample techniques. Data were collected through questionnaires related to SIMARI utilization in learning as independent variables and documentation of student learning outcomes in subjects that had used SIMARI as the dependent variable. Data were analyzed using simple regression techniques. The results showed that SIMARI utilization in e-learning was in a fairly good category. Student learning outcomes are in a fairly high category. There is a significant effect of SIMARI utilization as the implementation of e-learning based learning on student learning outcomes which is indicated by the Fcount of 4.554 with a significance of 0.036. It was concluded that SIMARI's utilization as an implementation of e-learning in learning could significantly improve student learning outcomes especially in the ULM FKIP Economic Education Study Program.
Continuous-Variable Arbitrated Quantum Signature Based on Dense Coding and Teleportation

Motivated by the dense coding and teleportation of two-mode squeezed vacuum (TMSV) state, a continuous-variable arbitrated quantum signature (CV-AQS) scheme is proposed. The signer Alice generates the signature by the dense coding and sends it to the verifier Bob. The measurement results of two quadrature components serve for the recovery of the secret message. With the help of the arbitrator Charlie, Bob verifies the validity of the signature. The security of the presented protocol is protected by the calculation of the fidelity parameter and the implementation process of two-mode squeezed vacuum (TMSV) state teleportation. Moreover, the proposed scheme can be correctly implemented in the lossy and lossless transmission with a higher capacity.
A fuzzy mixed data clustering algorithm by fast search and find of density peaks

If we endow an intelligent system with fuzzy logic, we hope that it can deal with fuzzy data, including the clustering of fuzzy data. This paper proposes a fuzzy mixed data clustering algorithm by fast search and find of density peaks (FMTD-CFSFDP), which is a development of the CFSFDP clustering a lgorithm. The proposed algorithm is a kind of density-based clustering method established using fuzzy sets for fuzzy mixed data. Mathematical definitions for fuzzy mixed data are presented. Combined with the definition of traditional fuzzy Euclidean distance, we defined an improved Euclidean distance for both continuous and discrete fuzzy sets with smaller error. On this basis, the weight between continuous and discrete indicators is introduced for establishing the global difference for fuzzy mixed data. Referring to the clustering procedures of the CFSFDP algorithm, a Gaussian Kernel function for fuzzy samples is calculated and the clustering procedures of our proposed algorithm are described in detail. Furthermore, four different sets of random simulations are performed, which illustrates the feasibility of the proposed algorithm.