Reviewerly/exHarmony huggingface dataset:
Meningkatkan Ketrampilan Membaca Permulaan Menggunakan Media Kartu Kata Di Kelas 1 Sd Negeri 4 Gunungan Kecamatan Manyaran

The ability to read is very important for all students at every level of education. Because the ability to read is the initial capital to take part in learning, and is also a foundation for students before acquiring other knowledge. The purpose of this research is to improve early reading skills by using word card media in grade 1 SD Negeri 4 Gunungan. It was carried out at SD Negeri 4 Gunungan involving 16 students consisting of 9 female students and 7 male students in the 2020/2021 school year. This research includes planning, action, observation and reflection. Data collection is done by using observations and tests. The data analysis used is quantitative and qualitative. From the results of the study, it was found that there was an increase in students' initial reading skills from cycle 1 to cycle 2. In cycle 1 only 44% of students who completed got criteria B (Good), while in cycle 2 it increased to 69%. This increase occurred because the teacher made improvements to learning including learning methods and learning media. In this learning using word card media so that students more easily master the material quickly. Based on the results of this study,it can be concluded that the use of world card media can improve students’ initial reading skills at SD Negeri 4 Gunungan students.
A Study on Customer Sentiment Analysis of Commuter Airlines using Twitter Data Mining

Sentiment mining has mainly been correlated with analysis of text to establish whether an entity is of positive or, negative polarity. Recently, sentiment mining has been broadened to focus on objects such as distinguishing objective from subjective intentions, and determining the cradles and topics of different opinions expressed in textual formats such as tweets, web blogs, message board reviews, and news. Enterprises can leverage the opinion polarity and sentiment topic recognition to achieve a deeper perspective of the drivers and the overall scope of sentiments. These insights can improve customer service, establish better brand image, and enhance competitiveness. This paper solely examines the trend of analysing consumer feedbacks given in Twitter for various US based Airlines. Researchers are applying data mining and machine learning tools to accommodate different business centric evaluations such as Customer Feedback Assessment, Airline Quality Control, and Consumer Loyalty Prediction etc. Various knowledge building tools (lexicon creation, feature extraction, polarity formation) are emphasized in this study.These are applied to process the raw twitter data into characterized sentiment blocks which determine consumer intuition for choosing desired airlines. Also, external metrics such as weather condition, airline punctuality and service, staff oversight are taken into consideration that impact customer conclusions. This paper succinctly looks through sentiment recognition algorithms with their data processing paradigm and finally possible future directions for improvement are discussed.
The Effect Of Transition Action Details (TAD) Strategy Toward Students’ Writing Ability Of Recount Text At Senior High School 6 Pariaman

The purpose of this research was to find out the Effect of Transition Action Details strategy toward Students’ writing ability of recount text to the first Grade at SMAN 6 Pariaman. The kind of This researches in the form of experiment, especially pretest and posttest control group design. The research population was all students in class X IPS SMAN 6 Pariaman school year 2018/2019 that consist of 100 students. The samples were X IPS1 class as the experimental class that consist of 25 students and X IPS2 class as the control class that consist of 25 students. This research used cluster random sampling technique.Experimental class was taught by using transition action details, and control class was taught by using conventional strategy. The instrument of collecting the data that used by the researcher was writing test. The technique of analyzing data was the hypothesis test was t-test formula, which was used test the difference in mean and standard deviation of the two samples.Based on the analysis of data obtained, tcalculate=3,33 and ttable=1.67 .Because tcalculate (3,33) &gt; ttable (1.67), then H0 was rejected and H1 was accepted, it can be concluded that the application of Transition Action Details strategy provides a significant effect on students’ writing ability of class X rather than conventional strategy at SMAN 6 Pariaman.&#x0D; Key words: transition action details, wrriting, recount text
Deep Learning Model for Context-Dependent Survival Analysis

In this article, we introduce a deep learning model (denoted thereafter DCM: Deep Contextual Model ) for survival analysis able of predicting the probability that a subject meets an event of interest according to its past life.The subject and the event of interest can be diverse depending on the field of application, thus the model can be applied in various contexts.We present an application in the aerospace field that consists in forecasting hot corrosion in turbofan. IntroductionSurvival analysis is a branch of statistics that aims to predict the time until an event of interest occurs.Various kinds of events of interest can be considered depending on the field of application.In the context of predictive maintenance, it is often the time to failure (see for example [1] in the aeronautical field).When it is relevant, many survival analysis methods allow to model the time before event according to some explanatory variable X i describing the subject i.In this paper, we introduce a model that is able to estimate the time before an event according to a time series (X t ) t∈N (which represents the context).Indeed, in many fields where survival analysis is applied, data describing the past life of the subject are available.In the case of predictive maintenance, many complex devices are equipped with several digital sensors which produce data throughout the device life.Although sensors may not be intended for predictive maintenance, they can provide meaningful information on the health status of the devices.Thus, these data can be used to predict the probability of an event of interest to occur.Especially if this event of interest is correlated with an abnormal operation of the device.This paper is organized as follows.Section 2 introduces the problem of survival analysis with times series, Section 3 describes the proposed model, Section 4 gives an application in the aeronautical field and section 5 concludes the article. Framework Background on survival analysisLike all statistical models, survival models need to be fitted on data.Survival data can be represented by a tuple (t, c) where t is a time and c a label.Survival data can be
Summary of Research Methods of Voice Activity

As neural networks are more and more widely used in various fields, speech signal processing has also achieved many remarkable results in the field of deep learning. As a very important part of the front-end processing part of voice signal processing, voice endpoint detection is the basis of various voice tasks. Carrying out research on voice endpoint detection technology is of great value and significance in promoting the development of voice signal processing. This article gives a detailed overview of the development of voice endpoint detection technology, introduces the beginning to the development of voice endpoint detection in recent years, and the maturity of the current very popular deep learning application in voice endpoint detection technology. The traditional voice endpoint detection and based on The development trend of deep learning voice endpoint detection has been analyzed, and it has revealed the shortcomings of traditional voice endpoint detection, the limitations of voice endpoint detection based on deep neural networks, and the future development direction, so that it can be better built based on depth Neural network voice endpoint detection system.
PENGGUNAAN TEKNOLOGI VIRTUAL REALITY DALAM PENDIDIKAN KEPERAWATAN JIWA : LITERATURE REVIEW

Introduction: In the era of industrial revolution 4.0, distance learning has a strategic role for spreading and equity in higher education, including nursing science. Triggered by the COVID 19 pandemic, nursing education needs to innovate how to achieve the competency without direct contact with patients. This study aimed at exploring the virtual reality method in nursing education, moreover in mental health nursing. Method: The study design is a literature review, using Pubmed as the search engine, continued with literature search from the selected articles, using the following key words: nursing education, virtual reality, competency; and nursing education, virtual reality, and mental health. We selected only English and articles of the recent 10 years Result: Eight articles were selected using the two sets of key words, consisted of 5 articles about nursing education and 3 articles were more on mental health nursing education. The study designs were varied from RCT, review and scoping review, descriptive study, and qualitative study. The context were undergraduate and postgraduate students.. Conclusion: Virtual reality is one candidate in nursing education, especially in mental health nursing education to improve competency among nursing student.&#x0D; Keyword: nursing education; virtual reality; mental health.
RANCANG BANGUN PENGELOLAAN E-SERTIFIKAT BERBASIS WEB DI POLITEKNIK CALTEX RIAU

Politeknik Caltex Riau’s students are required to have academic and non academic ability. PCR itself has a series of student activities on non-academic fields organized by student’s activity unit (UKM) or Student Association (HIMA). In carrying out student activities, a certificate is required as proof that the student has actually participated in the activities that has been held. Based on a survey of 57 respondents, it was found that students had problems receiving certificates after participating in an activity. To overcome this problem, computerized mechanism is required for the creation and delivery of certificates. Therefore, an E-Certificate Management system was built in Politeknik Caltex Riau that can facilitate certificate management. System testing has been carried out. The results of the functional test using the Black Box method which consists of 11 items, show that the system is running as expected.. Usability tests conducted by students found that this system is Usefulness, Ease of use, Ease of learning and Satisfaction.
Fast and flexible inference in time-varying parameter regression models

In this paper, we write the time-varying parameter (TVP) regression model involving K explanatory variables and T observations as a constant coefficient regression model with KT explanatory variables. In contrast with much of the existing literature which assumes coefficients to evolve according to a random walk, a hierarchical mixture model on the TVPs is introduced. The resulting model closely mimics a random coefficients specification which groups the TVPs into several regimes. These flexible mixtures allow for TVPs that feature a small, moderate or large number of structural breaks. We develop computationally efficient Bayesian econometric methods based on the singular value decomposition of the KT regressors. In artificial data, we find our methods to be accurate and much faster than standard approaches in terms of computation time. In an empirical exercise involving inflation forecasting using a large number of predictors, we find our models to forecast better than alternative approaches and document different patterns of parameter change than are found with approaches which assume random walk evolution of parameters.
RANCANG BANGUN DASHBOARD BUSINESS INTELLIGENCE UNTUK VISUALISASI DATA PASIEN (STUDI KASUS: PUSKESMAS PAKAN KAMIS)

The Public Health Center (Puskesmas) is a technical implementation unit of the district / city office which is responsible for carrying out health development in a work area. One of the existing community health centers is the Pakan Kamis puskesmas. Based on the interviews conducted, the puskesmas still experienced difficulties in seeing the pattern of disease spread, drug use patterns and patient development, because the process of recapping and calculating data was still done manually. This causes the puskesmas management to have difficulty in analyzing data and obtaining information for decision making. Therefore, a web-based business intelligence dashboard was created that can visualize patient data related to these problems. This Business Intelligence dashboard is built using the PHP programming language and MySQL database. From the results of user satisfaction testing, it was found that 97% of the business intelligence system dashboard for visualizing patient data was in accordance with the needs and could assist the health center in monitoring the pattern of disease spread, patient usage and development, as well as assisting the health center in analyzing data to make appropriate decisions. and efficient.Keywords: Puskesmas Pakan Kamis, Patient Data, Visualization, Dashboard, Business Intelligence
The use of electronic educational resources in an agrarian university during the pandemic

The coronavirus pandemic brought major changes to virtually all spheres of human life. Despite seeming a fantastic reality at first glance, fulfilling professional duties using electronic resources has gradually become an integral part of our lives. All spheres of society had to adapt to the changed reality in a short amount of time including in the sphere of education. However, despite all the difficulties associated with the problems of getting access to high-speed Internet, traffic speed, the lack of modern electronic devices, etc, the sphere of education has handled them quite shortly. The goal of the study is to disclose the specific features of the organization of the educational process with the use of electronic educational resources in an agrarian university during the pandemic. The article indicates the distinguishing characteristics of distance learning, identifies and characterizes the main instruments of distance learning in the force majeure circumstances of self-isolation in a specific university, as well as provides an example of the minimum requirements for filling up the Moodle e-learning environment. The attitudes of teachers and students to distance education in the new conditions are studied through a survey. The scientific novelty of the study lies in the interdisciplinarity of the consideration of the topic of interest. As a result, the study reveals a common trend characteristic of both students and teachers, consisting in the division into those who feel good about the electronic educational environment and those who have difficulty using it in the learning process.
Faster Identification and Resolution of Risk in Mobile and Internet Banking Using CLOUDSHIFT

The security risk report on mobile and internet banking technology has recorded a high-level financial loss globally, while personal data of customers and sensitive bank information are constantly at risk. This research explores the contextual banking technology issues in the financial industry. The study uncovers different security issues in the existing mobile and internet banking technology and proposes a CLOUDSHIFT implementation framework as secure haven. Our CLOUDSHIFT solution evolves a faster cloud technology that can easily investigate, detect and resolve real-time potential failures or breaches within the banking system from any secure web server. CLOUDSHIFT leveraged on where internet-based computing thrive, as such the case of Malaysia was considered. To leverage further on this benefit, banks and financial services need a co-security centric approach in conjunction with cloud providers and third-party solution partners to implement this cyber fraud event management process. The CLOUDSHIFT provides important implications of cloud computing in combating cyber-fraud with better strategic cloud migration framework that addresses the operational challenges of the internet and mobile banking. The framework was evaluated using Gai proposition value chain system and Amazon AWS proof of concept applicable to the financial industry.
90 years of the Biology Faculty of the Saratov State University

The Biological Faculty of the Saratov State University turns 90 years old in 2021. The first students were enrolled at the Faculty in the 1931–1932 academic year. However, the faculty’s history began long before its opening, when the Department of Botany and the Department of Zoology with Comparative Anatomy were organized in the new Saratov Imperial Nikolaev University in 1909. The article describes important events in the life of the Faculty and the contribution of scientists who stood at the origins of the birth of biological science at Saratov State University and played an important role in the formation and development of the Biological Faculty. A whole galaxy of famous biologists and eminent personalities worked at the university at different times. These are the academicians N. I. Vavilov, N. A. Maksimov, A. A. Richter, corresponding members A. Ya. Gordyagin, S. D. Lvov, professors D. E. Yanishevsky, A. D. Fursaev, I. V. Krasovskaya, V. S. Elpatevskiy, B. K. Fenyuk, P. A. Vunder, A. A. Chiguryaeva, S. S. Khokhlov, M. P. Gnutenko, V. V. Ignatov and others. They founded scientific schools, laid down faculty traditions and set a high standard for biological education, which the modern faculty team strives to maintain to this day.
ARTIFICIAL INTELLIGENCE FOR CYBERSECURITY: A SYSTEMATIC MAPPING OF LITERATURE

This paper discussed how artificial intelligence (AI) may be used to address cybersecurity issues. Although secure communication between people, services, and devices is possible via centralized digital organizations, there are significant dangers associated with the digital revolution. Data mining, profiling, and exploitation are can be done without the users' expressed permission [1]. The continued provision of central solutions from service providers is wasteful in duplication, has significant security deficiencies, and is difficult for users. Digital identity authentication and verification are critical for ensuring the privacy and security of dispersed digital identities. However, the present body of knowledge is deficient in terms of thorough studies on unified communications aspects as well as user privacy and data security measures included in identity management systems. Digital identity management and verification are almost certainly the most promising of the many emerging applications of blockchain technology. In 2018, individual security breaches affected billions of individuals worldwide. Unquestionably, more secure methods of storing, exchanging, and validating sensitive data are required. In this respect, the development of blockchain solutions for identification systems may offer helpful solutions to some of the issues that most centralized databases face. Physical devices and human impedance are inadequate to manage and protect against cybercrime. Criminals utilize the Internet to perpetrate a wide variety of cybercrimes [1]. The experts seek assistance in preventing assaults and security breaches, as well as responding to attacks. The primary objective of cybersecurity is to minimize assaults via the use of AI technologies. There are existing applications of artificial intelligence in cybersecurity, and certain cybersecurity problems may be addressed via the use of AI methods, as well as some beneficial AI applications [2].
PENERAPAN MODEL PEMBELAJARAN BERBASIS PROYEK TERHADAP KEMAMPUAN MENULIS TEKS PUISI

Writing activities are an indirect way of communicating by delivering written messages using language in the form of notes. writing is not just ordinary writing that is poured, but many kinds of written works such as writing poetry. Poetry is written work with expressions of feelings, experiences or knowledge that contain elements and linguistic rules. Sometimes there are still many students who are confused in writing poetry because of a lack of interest or knowledge. Therefore, this research was conducted according to the circumstances that occurred by applying a project-based learning model to writing poetry to motivate students to be more active, creative and to take the initiative in writing poetry. This study used descriptive qualitative method. In this study, the subjects were students of class X MIPA 1 at SMAN 1 Gununghalu with a total of 21 students, consisting of 6 male students and 15 female students. The results showed 11 students got high scores, 7 students got sufficient scores, and 3 students got low scores. The results concluded in this study that the use of project-based learning models in class X MIPA 1 students can improve students' skills in writing poetry texts.
An Efficient Approach to Sensor Fusion Development

Autonomous vehicles rely on a variety of sensors for accurate positioning, navigation, and timing (PNT). Data from these sensors are typically provided to a navigation fusion engine where an optimal estimate of the vehicle's state vector is formed to include position, velocity and time. Sensor fusion is required due to the ever-present organic threats to satellite based navigation systems that limit autonomous vehicle navigation such as urban canyons, multipath, and privacy jammers. The ability to fully simulate a sensor fusion environment, to include GNSS and non-GNSS based sensors, is essential to efficient development and accurate characterization of sensor fusion systems. Spirent Federal is working to develop a full simulation environment where all sensor data, including GNSS data, are coherent, and sensor outages and corruptions are modelled to measure the effects on fusion algorithms. Our cutting-edge simulation technology is the first of its kind to truly offer a comprehensive development environment that allows for full system stimulation with the added benefit of reducing cost and schedule associated with real-world testing. This paper takes a systems engineering approach to show how to design and develop a sensor fusion system to pace the organic threat environment, how to characterize and verify the system through our advanced simulation capabilities, and validate the end solution against customer needs.
A Speaker-Aware Learning Framework for Improving Multi-turn Dialogue Coherence

This paper presents a novel open-domain dialogue generation framework emphasizing the differentiation of speakers in multi-turn conversations. Differing from prior work that solely relies on the content of conversation history to generate a response, we argue that capturing relative social relations among utterances (i.e., generated by either the same speaker or different persons) benefits the machine capturing fine-grained context information from a conversation history to improve context coherence in the generated response. Given that, we propose a speaker-aware framework, named Parallel Hierarchical Attentive Encoder-Decoder (PHAED), that aims to model each utterance with the awareness of its speaker and contextual associations with the same speaker's previous messages. Specifically, in a conversation involving two speakers, we regard the utterances from one speaker as responses and those from the other as queries. After understanding queries via our encoder with inner-query and inter-query encodings, our decoder reuses the hidden states of previously generated responses to generate a new response. Our empirical results show that PHAED outperforms the state-of-the-art in both automatic and human evaluations. Furthermore, our ablation study shows that dialogue models with speaker tokens can generally decrease the possibility of generating non-coherent responses regarding the conversation context.