Reviewerly/exHarmony huggingface dataset:
Performance evaluation of listwise deletion for impaired datasets in multiple regression-based prediction

&lt;span&gt;Multiple Regression-Based Prediction (MRBP) is an emerging calculation to or analysis technique cope with the future by compiling the history of data. The MRBP characteristic will include an approximation for the associations between physical observations and predictions. MRBP is a predictive model, which will be an important source of knowledge in terms of an interesting trend to be followed in the future. However, there is impairment in the MRBP dataset, wherein each form of missing and noisy data has caused an error and is unavailable further analysis. To overcome this unavailability, so that the data analytics can be moved on, two treatment approaches are introduced. First, the given dataset is denoised; next, listwise deletion (LD) is proposed to handle the missing data. The performance of the proposed technique will be investigated by dealing with datasets that cannot be executed. Employing the Massive Online Analysis (MOA) software, the proposed model is investigated, and the results are summarized. Performance metrics, such as mean squared error (MSE), correlation coefficient (COEF), mean absolute error (MAE), root mean squared error (RMSE), and the average error percentage, are used to validate the proposed mechanism. The proposed LD projection is confirmed through actual values. The proposed LD outperforms other treatments as it only requires less state space, which reflects low computation cost, and proves its capability to overcome the limitation of analysis.&lt;/span&gt;
RANCANG BANGUN SISTEM INFORMASI ADMINISTRASI PELANGGAN FITNESS BERBASIS WEB

Fitness is a necessity in life today, fitness also has a good impact and can provide health for anyone who does this activity. And as the rapid development of technology in the health sector, many facilities that can help humans in doing fitness activities. This has become a business area by providing services to support health, because opening a fitness center can provide good business prospects. Skala Gym is a company engaged in the field of services, namely renting equipment needed by users in performing fitness activities. The activities carried out so far are administrative management processes for customers who have not used a computerized system and still use books as a medium, so that the process of collecting and storing data is less effective and efficient. The purpose of this paper is to design and build a customer administration information system to manage all data for the purpose of running a fitness equipment rental business. The method used is to use the Waterfall method to help smooth the research process. By building information systems using the unifield modeling language (UML), and supported by the PHP5 programming language and connecting to the MySQL database
Smart Contract-Based Electronic Voting System that Provides Fairness

E-government systems have ensured reliable data and prevented the forgery and modulation of that information, and so far, this role has been carried out in traditional centralized management. However, centralized data management has the disadvantage of single point of failure and bottlenecks. Blockchain technology has emerged to solve this problem. It is characterized by decentralization, which has been considered insecure in the past, to ensure the integrity of data. However, there are many problems in applying general blockchain and smart contracts to e-government electronic voting. In this paper, we propose a scheme to guarantee the integrity of voting data and to automate the process of voting and counting by smart contract by applying blockchain and smart contract to provide integrity and automation function to electronic voting.
Penerapan Model Pembelajaran ROAR (Read, Observe, Auditory, Review) Meningkatkan Pemahaman Konsep Siswa

The ROAR learning model is learning that gives students the broadest opportunity to develop concepts, pre-existing ideas become new concepts. The concept is built through direct observation because during learning the teacher presents examples of reality so students will be more critical with the concepts of reality, so that in the end they are able to connect the material based on the concept of reality they are building. This integration aims to have concepts related so that the meaningfulness of learning can be achieved. This study is an experimental study with a nonequivalent control group design with a research focus on social studies subject material in junior high school 8th grade. The results of the analysis of the test analysis show that the application of the ROAR learning model has a consistent impact on students' conceptual understanding abilities. Positive responses from teachers and students to the application of the ROAR learning model as an alternative solution in supporting success in improving the ability to understand concepts that have implications for student motivation and learning achievement.&#x0D;
A Feature Comparison of Modern Digital Forensic Imaging Software

Fundamental processes in digital forensic investigation, such as disk imaging, were developed when digital investigation was relatively young. As digital forensic processes and procedures matured, these fundamental tools, that are the pillars of the reset of the data processing and analysis phases of an investigation, largely stayed the same. This work is a study of modern digital forensic imaging software tools. Specifically, we will examine the feature sets of modern digital forensic imaging tools, as well as their development and release cycles to understand patterns of fundamental tool development. Based on this survey, we show the weakness in current digital investigation fundamental software development and maintenance over time. We also provide recommendations on how to improve fundamental tools.
Penggunaan Metode ELECTRE Untuk SPK Pemilihan Makanan Sehat Bagi Penderita Hipertensi

Having a healthy body is all living things and avoiding all kinds of diseases. Maintaining a healthy body can be done by exercising and maintaining a healthy diet. Excess eating unhealthy foods can foster disease or disorders in the body. One of them is hypertension. Blood pressure more than 140 mmHg and diastolic blood pressure more than 90 mmHg at double the difference within five minutes under conditions of sufficient recovery. Hypertension is a disease that has a high prevalence in Indonesia, which is 25.8%. The case of a patient with hypertension is inseparable from changes in diet. The wrong diet, coupled with inappropriate food ingredients can cause bad blood pressure. In this study, researchers will create a support system for selecting healthy foods for hypertension sufferers. In this study, researchers used the El Choices Traditionant La Realite Elemination method (ELECTRE) in order to find out healthy foods for people with hypertension. Based on this study, carried out various stages, nutritionists provide healthy food ingredients, then hypertension sufferers choose several food items to be consumed. Next, the food ingredients are calculated by the ELECTRE method and the last step is to find food ingredients recommended for hypertension sufferers.
THE ANALYSIS OF STUDENTS’ PRONUNCIATION ERRORS IN READING ALOUD

It was aimed to identify students’ pronunciation errors in reading aloud by finding out how far the students’ pronunciation errors in reading aloud and kind of words which are pronounced by the students through reading aloud. Qualitative method was used to find out the fact and the evidence of students’ pronunciation errors in reading aloud. The observation and the interview were conducted to explore the student’s experience and their problems in pronouncing English.The findings revealed that there were satisfactory results proved that the students made pronunciation errors in six part of speech; Nouns, Verbs, Adjectives, Adverbs, Prepositions and Conjunction. It was found that 26 pronunciation errors in noun (26.8%), 49 pronunciation errors in verb (50.5%), 6 pronunciation errors in adjective (6.2%), 12 pronunciation errors in adverb (12.4%), 3 pronunciation errors in preposition (3.1%) and 1 pronunciation error in conjunction (1.03%) from 7 students who had read the same narrative text. The reasons why the students made errors in pronouncing the words were the students have difficulties in pronouncing and spelling the words with affixes and prefixes in consonants, vowels, and diphtongs. They are: upon, aunt, lived, died,answered, knocked, cottage, dwarf, enough.
A2_9 Raindrops keep falling on my head

In this paper we attempt to find the density need for an object of raindrop size to kill a human if it were to land on their head. We conclude that the density of titanium, 4500 kg m−3, is the lower limit for what it would take to fracture the skull.
Study on Face Direction Measurement and Object Detection for Gazed Object Estimation

Service robots that support people need a function to estimate gazed object. Conventional research has estimated gazed object by measuring face direction and using input data beforehand. However, in this method, it can be used only in the state where information is input beforehand, and it can be used only in a limited scene. Therefore, we proposed a method to estimate gazed object using face direction measurement and object detection. We estimated gazed object using two Kinect sensors: for face direction measurement and object detection. We conducted an experiment to ascertain the effectiveness of our proposed method. In the experiment, we estimated gazed object that set at 16 points using the proposal method. As a result, the effectiveness of the proposal method was suggested.
Cuando el lugar cuenta: el uso variable de las preposiciones a /en con verbos de movimiento por hablantes brasileños

In Brazilian Portuguese there is variation of a/para/em in sentences with verbs that express movement to a place ( go, arrive, come , among others). It is a non-normative variation, since the grammatical tradition prescribes, for these verbs, the selection of directional prepositions a/para ; however, in the colloquial speech of Brazil, the locative preposition em alternates with the directional ones, and this variation is not free, but motivated by semantic and pragmatic reasons that account for how speakers conceive of the event to which they refer. This alternation observed in Brazilian Portuguese seems to occur also in statements in Spanish produced by Brazilian speakers, and it becomes noticeable when they select the preposition in contexts equivalent to those in which the variant em in Portuguese would prevail. This work deals with a group of texts written in Spanish by Brazilian Portuguese speakers who are studying Spanish or already have some degree of performance in this language, records the alternating use of prepositions a/en and their meanings in the described contexts, and analyzes whether the variables that motivate the selection of one or the other preposition in Spanish are the same as those that operate in Portuguese. ARK:  http://id.caicyt.gov.ar/ark:/s26183455/1lbtg2z4u
SELF ASSESSMENT IN WRITING SKILL OF INTROVERTED STUDENTS

Self assessment is one of parts in assessment process. This process helps the students evaluate their own work and learning process. This study try to implement one of self assessments, namely Type Token Ratio (TTR). It calculates word repetition by deviding the total number of words in a text (tokens) by the number of individual words. This self assessment will be used to only one type of personalities, namely introverted students. The aims of the study are describing the types of token that most used by the introverted students, describing the types of token rarely used by the introverted students, and describing the introverted students opinion about Type Token Ratio (TTR) for their writing. The descriptive qualitative method was implemented in this study. the sources of the data were taken from twenty students of first semester in English Educational Program of UNISDA Lamongan. The findings showed that types of token most used by the introverted students are: nouns appear 466 times, verbs appear 266 times, pronouns appear 266 times and prepositions appear 251 times. Whereas, they rarey used: adverbs appears 171 times, determiners appears 159 times, conjunctions appear 123 times, adjectives appear 94 times and interjections appear 7 times. Based on the result, it can be concluded that the introverted students most often use noun and most rarely use interjection in their writing. Almost all of students think that TTR is good and help them to measure their vocabulary variety. Key words: Self Assessment, Writing Skill, Introverted
A Blended Learning Module on the Writing Academic Purpose Course (A Research and Development Approach)

This study aimed to determine the effectiveness of the module based on blended learning model in ‘Writing Academic Purpose” course, to evaluate the validity of the module based on the assessment by the Context, linguists and media experts used validation sheets. The module was developed using Research and Development Approach (R&amp;D). the outputs of this research was an blended learning module of “Writing Academic Purpose”. The module was implemented using the e-learning system of UNU Lampung. The subject of this research was the blended learning module that implemented to the English Department students. The object of the research were the content of the module. The module is declared valid from the validation by validators, the module could improve the students’ reasoning and creativity, the module’s effectiveness is achieved in this study.
Query-Driven Multi-Instance Learning

We introduce a query-driven approach (qMIL) to multi-instance learning where the queries aim to uncover the class labels embodied in a given bag of instances. Specifically, it solves a multi-instance multi-label learning (MIML) problem with a more challenging setting than the conventional one. Each MIML bag in our formulation is annotated only with a binary label indicating whether the bag contains the instance of a certain class and the query is specified by the word2vec of a class label/name. To learn a deep-net model for qMIL, we construct a network component that achieves a generalized compatibility measure for query-visual co-embedding and yields proper instance attentions to the given query. The bag representation is then formed as the attention-weighted sum of the instances' weights, and passed to the classification layer at the end of the network. In addition, the qMIL formulation is flexible for extending the network to classify unseen class labels, leading to a new technique to solve the zero-shot MIML task through an iterative querying process. Experimental results on action classification over video clips and three MIML datasets from MNIST, CIFAR10 and Scene are provided to demonstrate the effectiveness of our method.
Networking Information Technologies as a Method Innovative Changes in Academic Libraries

Objective. The article examined at current global trends to require significant changes of the educational and library infrastructure. The analysis of these tendencies and of the current state of development of the educational and library sphere gave an opportunity to understand to the implementation of network technologies can affect to the activities of academic institutions. Methods. At the present stage, the popularity of distance technologies is increasing because they are best able to meet the new needs of modern users of library networks. The authors identified the factors of popularity and scope of networking technologies and investigated their influence on various aspects of the practical activity of university libraries. Results. Practical experience of the Scientific and Technical Library of DNURN named after academician V. Lazaryan demonstrates to the use of the modern networking technologies, which changed, improved and expanded the scope of services of the library institution. Conclusions. The research allows conclude to mastering library specialists of new knowledge and working skills to mobile information technologies. The introduction these technologies to practical activity promotes further development of the academic library and helps to improve forms of service for remote users to digital content
Machine Learning based Post Processing Artifact Reduction in HEVC Intra Coding

The lossy compression techniques produce various artifacts like blurring, distortion at block bounders, ringing and contouring effects on outputs especially at low bit rates. To reduce those compression artifacts various Convolutional Neural Network (CNN) based post processing techniques have been experimented over recent years. The latest video coding standard HEVC adopts two post processing filtering operations namely de-blocking filter (DBF) followed by sample adaptive offset (SAO). These operations consumes extra signaling bit and becomes an overhead to network. In this paper we proposed a new Deep learning based algorithm on SAO filtering operation. We designed a variable filter size Sub-layered Deeper CNN (SDCNN) architecture to improve filtering operation and incorporated large stride convolutional, deconvolution layers for further speed up. We also demonstrated that deeper architecture model can effectively be trained with the features learnt in a shallow network using data augmentation and transfer learning based techniques. Experimental results shows that our proposed network outperforms other networks in terms on PSNR and SSIM measurements on widely available benchmark video sequences and also perform an average of 4.1 % bit rate reduction as compared to HEVC baseline.
Machine Learning Approach to a Low-Cost Day-Ahead Photovoltaic Power Prediction Based on Publicly Available Weather Reports for Automated Energy Management Systems

The fully automated and transferable predictive approach based on the long short-term memory machine learning algorithm is developed for the forecasting of the photovoltaic (PV) power output. The main challenge of this approach is using publicly available weather reports and measured PV power without any technical information about the PV system. Nevertheless, the developed model is able to predict the power output of the various PV systems for all seasons with a reasonably good accuracy. This transferability of the approach is proven by the prediction of the PV power for warm and cold periods and for two different PV systems located in Oldenburg and Munich, Germany. The mean absolute scaled error of the predictions decreases with increasing the size of training set and reaches its minimum by the training with 90 days.The PV power prediction made with the publicly available weather data is compared to the predictions made with the fee based solar radiation data. The usage of the solar radiation data leads to more accurate predictions even with small training sets. Although the model with the publicly available data needs a greater training set, it still can make reasonably good predictions. Therefore, it can be applied in forecast-based energy management systems.
TikTok trends to take into 2020

2019 has been a breakthrough year for TikTok. Armed with billions of dollars in funding, its aggressive marketing and appeal to ...
A Method of Automatic Memorabilia Generation Based on News Reports

This paper proposes a method of automatic memorabilia generation based on news reports, aiming to generate the memorabilia in a certain time period for specific enterprises or departments via machine learning technologies. Firstly, the nonparametric clustering algorithm DBSCAN is used to cluster news reports based on text similarity. Then, we propose a salience ranking model to calculate the salience score of each cluster from different aspects, such as news coverage, report forwarding and source website importance etc. Finally, time normalization and description generation are performed on the TOP-K clusters so as to generate the final memorabilia. Several experiments are carried out based on news reports crawled from the related website. Experimental results show that the proposed method can effectively discover important events from the corpus. This paper explores memorabilia generation and provides a baseline system for this task.
The End of Laissez-Faire and Rise of Algorithmic Management and Politics.

The ground breaking research and article in the November 2019 Scientific American from Bruce Boghosian and team in “The Inescapable Casino” is discussed, quoted often, and extended into other areas. The general idea being that systems involving transactions between humans will inevitably lead to oligopolies and that this is not only seen in economies but also organizations and politics and that their recommendations intimate a much larger impact from the conclusions of their research.
세브란스병원의 진료활동으로 본 3･1운동

This research aimed to reveal the roles of Severance Hospital during the March 1st Movement that triggered the independence movement. It also focused on the changes at Severance Hospital for short periods before and after the March 1st movement. The members of Severance Hospital participated in providing treatment to tortured people and injured people. Most of the patients receiving treatment had gunshot and stab wounds, and surgical treatments were necessary. The pinch skin graft was performed on patients who were flogged, which saved many who had been subjected to floggings that would have otherwise led to death. The members of Severance Hospital contributed to international awareness by publicizing the brutalities of Japanese imperialism abroad. This activity was despite Severance Hospital, a missionary hospital, not presenting political opinions because of being instructed by the missionary board to comply with the rule of separation of church and state. At Severance Hospital, the period before the March 1st Movement was considered to be a time to conform to the rule of the Governor-General of Korea (GGK) in order to be accredited by the GGK. The tensions between Severance Hospital and the GGK that had previously been resolved through a policy of appeasement had increased throughout the March 1st Movement. But Severance Hospital faced a difficult situation due to the resignations of full-time Japanese professors and F. W. Schofield’s return home. Therefore, Severance Hospital implemented the policy of recruiting qualified Korean professors and supported training aboard for Severance Union Medical School graduates to build a competitive faculty. The policy of recruitment of full-time Japanese professors was abolished, and part-time Japanese instructors only gave lectures on a few subjects.
Korean Classical Poetry and Song Education in the Revised Literature Textbooks of 2019

This study examined the current state of classical poetry education in the 10 types of published literature textbooks of the 2015 revised curriculum.It was confirmed that the content on Goryeo Gayo is the section where active participation, appreciation, and comprehensive inquiry of the learner, which are emphasized in the revised Literature textbooks, are reflected most excellently.In particular, the Goryeo Gayo section was designed to explore the identity of Korean poetry and songs before Hangul and to explore the universality and specialty of Korean literature by comparing it with Chinese poetry or poetry translated into Chinese.By allowing the learners to acknowledge the correlations between Hangul and Chinese texts, spoken and written language, and poetry and songs, this part of literature education is composed very organically to help learners understand the general trends of literary history while comprehensively grasping how the universality of Korean literature as national literature is revealed in classical poetry and songs.