Reviewerly/exHarmony huggingface dataset:
The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization

We propose a model for multiclass classification of time series to make a prediction as early and as accurate as possible. The matrix sequential probability ratio test (MSPRT) is known to be asymptotically optimal for this setting, but contains a critical assumption that hinders broad real-world applications; the MSPRT requires the underlying probability density. To address this problem, we propose to solve density ratio matrix estimation (DRME), a novel type of density ratio estimation that consists of estimating matrices of multiple density ratios with constraints and thus is more challenging than the conventional density ratio estimation. We propose a log-sum-exp-type loss function (LSEL) for solving DRME and prove the following: (i) the LSEL provides the true density ratio matrix as the sample size of the training set increases (consistency); (ii) it assigns larger gradients to harder classes (hard class weighting effect); and (iii) it provides discriminative scores even on class-imbalanced datasets (guess-aversion). Our overall architecture for early classification, MSPRT-TANDEM, statistically significantly outperforms baseline models on four datasets including action recognition, especially in the early stage of sequential observations. Our code and datasets are publicly available at: https://github.com/TaikiMiyagawa/MSPRT-TANDEM.
A Survey Paper on Comparative Analysis of Web Browsers

A web browser is an essential application program for accessing the Internet.As more and more services become available on the Internet, the issue of fast and secured access to online resources gains more importance.The growth of the internet has encouraged a high number of people to explore and take advantage of the World Wide Web ( www). The window to the World Wide Web is a web browser, hence the development of various web browsers in the market today. This paper describes the analysis of the web browsers to conclude which browser is efficient for user. A comparative study of four web browsers namely Internet Explorer, Mozilla Firefox, Opera and Google chrome was carried out[2].
Improving technologic education on the basis of the steam method

This article provides information about the integration of science in improving the teaching of technology in the system of continuing education, focuses on the relevance of science, defines the integration and application of the STEAM method of a new approach to integrated education.
상호문화교육을 위한 문학교육의 방법론 연구 -다국적의 구비문학 자료를 바탕으로-

The purpose of this study is to establish a methodology for systematic literature education in intercultural education with defining the meaning of literary education in intercultural education. Also the standard selection of literary works in intercultural education with mutinational oral literature was discussed and then educational contents and application plans with the selected literray work were suggested. In this study, the methodology based on mutinational oral literature such as folktale, proverbs and folk beliefs was considered because the unique literature of each ethnic group along with a universal culture is dissolved together in multinational oral literature. Also there are extensive oral literary works which have been studied through previous research projects. This researcher has investigated the multinational oral literature of immigrants residing in Korea, and 1,493 multinational oral literature have been collected. Hence multinational oral literature is supposed to be most effective and practical research to establish a literary education methodology in intercultural education.To establish the methodology, the selection criteria, educational contents and application plans of literature were discussed.The criteria for selecting literary works is whether they have a common subject, theme and narrative. After selecting literary works, each literary work was compared. Through comparison of selected works, the culture of one''s own country is reminded and other cultures are studied. For effective education to select the content, each country''s value culture, natural culture, living culture and historical culture were considered. Through the educational contents, students will learn empathy and respect for other cultures.The criteria for selection of literatures, educational content and application plan established in this study will be a methodology of literature education that can be applied not only to multinational oral literature, but also to other literature education for intercultural education.(INHA University)
MENINGKATKAN RASA PERCAYA DIRI DAN HASIL BELAJAR SISWA MELALUI MODEL PEMBELAJARAN CONTEXTUAL TEACHING AND LEARNING MATA PELAJARAN BAHASA INGGRIS PADA KELAS VIII-3 SMP NEGERI 7 MEDAN TAHUN AJARAN 2016/2017

This study aims to determine the improvement of student learning outcomes by using the CTL learning model on speaking competency standards. This type of research is PTK. The subjects of the research were students of class VIII-3 SMP Negeri 7 Medan. Based on the results of this study, it shows that in the learning outcome test in cycle I, the number of student learning completeness reached 28 students (93.33%) with an average of 78. In cycle II the total student learning completeness reached 26 students (86.67%) with an average of 78 students. an average of 73.83 is said to have not increased then it will be continued to the third cycle. In the learning outcomes test in cycle III, the number of student learning completeness reached 29 students (96.67%) with an average of 79.50
Implementasi Manajemen Pelayanan Sirkulasi Perpustakaan SMPN 6 Rejang Lebong

Borrowing and returning library books is a process of circulation service activities. This research is motivated by the fact that library circulation service management is very important in order to improve the quality of existing services, where officers must understand the problems in the implementation of circulation in the library. The purpose of this study was to analyze the implementation of circulation service management in the Rejang Lebong 6 Junior High School Library. The type of approach used in this research is a qualitative approach. Data were collected using observation, interview, and documentation techniques. The results showed that the implementation of circulation service management at the Rejang Lebong 6 Junior High School Library has not run optimally, this is indicated by the many problems in circulation services. There are still officers who do not understand how to use the library so that the service has not been running optimally. On the other hand, library infrastructure is still lacking, so that it has an impact on library management, which will have implications for the learning process in schools.
On the Predictive Validity (Generalizability) of IELTS Academic Tests

Predictive validity of high-stake tests has attracted the attention of applied linguists since a couple of decades ago. Despite the existence of a plethora of studies on reliability and validity issues of high stake tests, it seems that predictive validity of International English Language Testing System (IELTS), as a high stake test should be measured appropriately. This study set out to investigate the predictive validity of IELTS academic tests practiced in Iran. The participants included 70Iranian IELTS test takers who took IELTS academic test in 2014 to 2015. To carry out the study, Construct and Validation Self-Assessment Inventory for Learners of English for Academic Purposes was used to collect data. The questionnaire included 48items on a five-point Likert scale. Coronbach's alpha coefficient of this questionnaire indicated the reliability of the instrument. The test-takers' scores on the four skills of academic IELTS were also used as another portion of data in this study. The collected data were subjected to a series of statistical analyses in relation to the proposed questions in this study. The data were analyzed using Regression and Analysis of Variance. The results of the study revealed that IELTS four modules significantly predict the test takers' performance in academic settings. The findings can be used by IELTS centers to make a change in test format, rubrics, as well as uses.
Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning

Active learning is widely used to reduce labeling effort and training time by repeatedly querying only the most beneficial samples from unlabeled data. In real-world problems where data cannot be stored indefinitely due to limited storage or privacy issues, the query selection and the model update should be performed as soon as a new data sample is observed. Various online active learning methods have been studied to deal with these challenges; however, there are difficulties in selecting representative query samples and updating the model efficiently without forgetting. In this study, we propose Message Passing Adaptive Resonance Theory (MPART) that learns the distribution and topology of input data online. Through message passing on the topological graph, MPART actively queries informative and representative samples, and continuously improves the classification performance using both labeled and unlabeled data. We evaluate our model in stream-based selective sampling scenarios with comparable query selection strategies, showing that MPART significantly outperforms competitive models.
CoreUI: Interactive Core Training System with 3D Human Shape

We present an interactive core training system for core training using a monocular camera image as input in this paper. It is commonly expensive to capture human pose using depth cameras or multiple cameras with conventional approaches. To solve this issue, we employ the skinned multi-person linear model of human shape to recover the 3D human pose from 2D images using pose estimation and human mesh recovery approaches. In order to support the user in maintaining the correct postures from target poses in the training, we adopt 3D human shape estimation for both the target image and input camera video. We propose CoreUI, a user interface for providing visual guidance showing the differences among the estimated targets and current human shapes in core training, which are visualized by markers at ten body parts with color changes. From our user studies, the proposed core training system is effective and convenient compared with the conventional guidance of 2D skeletons.
PROSEDUR PEMERIKSAAN MSCT NASOFARING PADA KASUS KARSINOMA NASOFARING DI RSPTN UNIVERSITAS HASANUDDIN MAKASSAR

Nasopharyngeal carcinoma is head and neck malignancy which most often occurs with etiology which is multifactorial and differentiated according to its geographical distribution. Radiology support facilities that become the standard in diagnosing tumors is examination of Computerized Tomography (CT) Scan. This study aims to determine the Nasopharyngeal MSCT examination procedure in cases of nasopharyngeal carcinoma, to find out the benefits of adding bone window and sagital slices on Nasopharyngeal MSCT in cases of nasopharyngeal carcinoma.The type of research conducted is descriptive qualitative research with a case study approach. The subjects in the study were three patients (different tumor staging), two radiographers, three radiologs and one sending doctor. Data collection methods used in the form of observation, documentation and interviews. The data analysis technique in this study is an interactive model analysis, including data collection, data reduction, data presentation and conclusion drawing.The results showed that nasopharyngeal MSCT examination in carcinoma cases at the Hasanuddin University Hospital in Makassar was carried out by patients with fasting for about 4 hours and taking axial, coronal and sagital slices. The benefit of adding a bone window is to see the spread and impact of carcinoma on the condition of the bones around the neck and head. The image of the bone window informs of the destruction or erosion of the bone, and is used to determine the staging level of the carcinoma. The addition of sagital slices aims to see the extent of the spread or metastasis of the carcinoma itself, by looking at this sagital slice, the specialist will more easily assess the spread in the anterior and posterior patients. Sagital slices are very helpful in informing the limits of the mass found.
SMASH: a Semantic-enabled Multi-agent Approach for Self-adaptation of Human-centered IoT

Nowadays, IoT devices have an enlarging scope of activities spanning from sensing, computing to acting and even more, learning, reasoning and planning. As the number of IoT applications increases, these objects are becoming more and more ubiquitous. Therefore, they need to adapt their functionality in response to the uncertainties of their environment to achieve their goals. In Human-centered IoT, objects and devices have direct interactions with human beings and have access to online contextual information. Self-adaptation of such applications is a crucial subject that needs to be addressed in a way that respects human goals and human values. Hence, IoT applications must be equipped with self-adaptation techniques to manage their run-time uncertainties locally or in cooperation with each other. This paper presents SMASH: a multi-agent approach for self-adaptation of IoT applications in human-centered environments. In this paper, we have considered the Smart Home as the case study of smart environments. SMASH agents are provided with a 4-layer architecture based on the BDI agent model that integrates human values with goal-reasoning, planning, and acting. It also takes advantage of a semantic-enabled platform called Home'In to address interoperability issues among non-identical agents and devices with heterogeneous protocols and data formats. This approach is compared with the literature and is validated by developing a scenario as the proof of concept. The timely responses of SMASH agents show the feasibility of the proposed approach in human-centered environments.
Nara: Learning Network-Aware Resource Allocation Algorithms for Cloud Data Centres.

Data centres (DCs) underline many prominent future technological trends such as distributed training of large scale machine learning models and internet-of-things based platforms. DCs will soon account for over 3\% of global energy demand, so efficient use of DC resources is essential. Robust DC networks (DCNs) are essential to form the large scale systems needed to handle this demand, but can bottleneck how efficiently DC-server resources can be used when servers with insufficient connectivity between them cannot be jointly allocated to a job. However, allocating servers' resources whilst accounting for their inter-connectivity maps to an NP-hard combinatorial optimisation problem, and so is often ignored in DC resource management schemes. We present Nara, a framework based on reinforcement learning (RL) and graph neural networks (GNN) to learn network-aware allocation policies that increase the number of requests allocated over time compared to previous methods. Unique to our solution is the use of a GNN to generate representations of server-nodes in the DCN, which are then interpreted as actions by a RL policy-network which chooses from which servers resources will be allocated to incoming requests. Nara is agnostic to the topology size and shape and is trained end-to-end. The method can accept up to 33\% more requests than the best baseline when deployed on DCNs with up to the order of $10\times$ more compute nodes than the DCN seen during training and is able to maintain its policy's performance on DCNs with the order of $100\times$ more servers than seen during training. It also generalises to unseen DCN topologies with varied network structure and unseen request distributions without re-training.
A Comparative Study of Conventional Machine Learning and Deep Learning Models to Find Semantic Similarity

In today’s scenario, with many platforms trying to provide answers to every question that the users try searching on the internet, the ease of finding things is direct but constrained for a limited number of users. It becomes arduous to find the answers even though they already exist. The uncertainty is due to semantic ambiguity. With the freedom of thought and linguistic diversity, there is a need for new tools to resolve this ambiguity. A new multidisciplinary field, natural language processing (NLP), incorporated with machine learning and statistical techniques, provides powerful analysis. In this paper, the basic machine learning models and state-of-the-art model Universal Sentence Encoder (transformer and deep averaging network) are compared using NLP techniques to detect duplicate questions in the Quora dataset. This paper aims to find which models out-do the others and the performance measures that affect each model such that there is a better understanding of the requirements to get the best results in finding semantic similarity between textual questions
RANCANG BANGUN APLIKASI PENDATAAN PENDUDUK BERBASIS WEB DI KELURAHAN BUGIS

Population data collection is intended to increase efficiency in terms of community services. So far, Bugis Village, Sumbawa Regency, still has a system that has not been computerized, making it difficult and slow in the processing of population data. Therefore, it is necessary to conduct research to build data processing applications. The purpose of processing this data is to make it easy for employees to provide efficiency in community service. In this implementation, the programming language PHP and MySQL are used as the database. Data collection methods used in this research are interview, observation, documentation and literature study methods as well as software development methods using the waterfall method. The test method in this study uses black-box testing which is done to test the software in terms of functional specifications.
한국 청소년의 악력과 비만의 관련성 : 2018년도 국민건강영양조사 자료를 이용하여

Purpose: The purpose of this study was to investigate the relationship between relative handgrip strength (HGS/BMI) and obesity (BMI above 95th percentile) in adolescents. Methods: The subjects of the study were 637 out of 701 adolescents aged 10~18 who participated in the 2018 National Health and Nutrition Survey (KNHANES), excluding those with missing values in body mass index (BMI) and handgrip strength (HGS). The relative handgrip strength (HGS/BMI) value was divided by quartile and composite sample logistic regression analysis was performed to see its relationship with obesity (BMI above 95th percentile). The collected data were analyzed using SPSS 18.0. Results: As a result of analyzing HGS according to gender-specific quartiles, age, height, and weight of male adolescents increased significantly as HGS/BMI increased (p trend<.001). In addition, as HGS/BMI increased, total cholesterol, triglycerides, and HDL cholesterol decreased significantly (p trend<.001). In the case of female adolescents, age and height increased significantly as HGS/BMI increased (p trend<.001). HGS/BMI was lower in the obese group (p=.023), while total cholesterol was higher in the obese group(BMI above 95th percentile) than in the non-obese group. As a result of the composite sample logistic regression analysis, the odds ratio (OR) decreased significantly as the quartile increased in both male and female adolescents. Conclusion: According to these results, a follow-up study is needed to confirm the factors affecting muscle strength of adolescents. In addition, this study intends to be used as basic data to conduct further research and to develop programs that can improve muscle strength and reduce obesity in adolescents.
Prospects of legal regulation and use of the digital rouble

This article considers the problems associated with the prospects of central banks issuing and circulating digital currency, in particular the digital rouble. The study found that at present there is virtually no need to issue such a currency as an alternative to cryptocurrency (virtual currency), because cryptocurrency has largely lost its properties as a means of payment with the acquisition of the qualities of an investment instrument. The advantages of a cryptocurrency over non-cash money, which is familiar and also has excellent qualities as a settlement tool, are also not obvious. The positioning of offline payments as a benefit of the digital rouble is questionable given the prospects of full Internet coverage in Russia and the significant technological and legal complexities involved in the organization and control of such payments. Building trust in the new form of the national currency, without which it will not be in demand, will require building a mechanism for legal protection of consumers' rights. There is also a need for a mechanism to address the risks associated with laundering proceeds of crime, financing terrorism and proliferation of weapons of mass destruction. It is difficult to formalise such a mechanism in the absence of international legal regulation
Learning a Single Neuron with Bias Using Gradient Descent

We theoretically study the fundamental problem of learning a single neuron with a bias term ($\mathbf{x} \mapsto \sigma(<\mathbf{w},\mathbf{x}> + b)$) in the realizable setting with the ReLU activation, using gradient descent. Perhaps surprisingly, we show that this is a significantly different and more challenging problem than the bias-less case (which was the focus of previous works on single neurons), both in terms of the optimization geometry as well as the ability of gradient methods to succeed in some scenarios. We provide a detailed study of this problem, characterizing the critical points of the objective, demonstrating failure cases, and providing positive convergence guarantees under different sets of assumptions. To prove our results, we develop some tools which may be of independent interest, and improve previous results on learning single neurons.
Psychological Aspects Of Pedagogical Design Development In The Context Of Digital Transformation Of Education

the article reveals the basic concepts of the psychological foundations of pedagogical design and the ways of its application in the structure of creating educational content on online platforms. Pedagogical design is considered as a field of science and practical activity in the development of digital educational content of an educational institution. Information and telecommunications technologies allow you to modify the nature of the development, acquisition and assimilation of knowledge, open up unique opportunities for updating the content of training and teaching methods
번역문체 분석 방법으로서의 주성분분석(PCA)

The present paper introduces a computational approach to analyzing translating style based on Principal Component Analysis (PCA), a multivariate statistical method popularly used to classify texts and attribute authorship. The paper describes merits of using PCA for exploring translating style and explains the typical procedure involved in performing a PCA analysis on corpus data. As a case study for illustrating this approach, the paper applies PCA to investigate stylistic differences between two English translations of a Korean novel, using most frequent 1-gram, 2-grams and 3-grams as linguistic features. The results reveal a marked distinction across all three PCA analyses between the two translated versions, which include differences in vocabulary diversity, reference chains, syntactic structure and use of general nouns in referring to fictional characters.