Reviewerly/exHarmony huggingface dataset:
The Changes in the Consciousness of Knowledge and Modern Knowledge in the SAMINPHILJI

This article compares the four types of Homer B. Hurbert’s the SAMINPHILJ I (士民必知, Knowledge that everyone should know)and aims to describe the changes in his linguistic consciousness and modern knowledge. Until now, there have been some researches on four kinds of the SAMINPHILJI, but there is no comprehensive comparison between the first edition of the book, the character of the Korean version, the 1906 edition and the 1909 edition. From this point of view, Hurbert s linguistic consciousness of Hulbert, modernity of the SAMINPHILJ I , understanding of Korean situation and consciousness of enlightenment were searched. The summary is as follows. First, the first edition and the 1906 edition of Alaska related articles estimated the year of publication to be 1890. This is based on the United States describing Alaska s purchase from Russia 25 years ago in the first edition and 41 years in the 1906 edition. Second, Hulbert s linguistic awareness is characterized by recognizing the convenience of Hangeul and respecting its native language. The publishing of the SAMINPHILJI in Korean is reflected in his people-centered and equality ideology. The appearance of the 1906 version of the Korean-English version relates to the increase in Herbert s missionary activities and knowledge of Korea s history and culture. Third, I tried to examine the modern consciousness of Hulbert reflected in the first edition the SAMINPHILJI and the characteristics of the system which appeared in the 1906 edition. The SAMINPHILJI was a textbook that provided a broad knowledge of modern science and human geography. Fourth, the first edition and the 1906 edition were compared with Korean related contents. Although included in the missionary s point of view of Confucianism and Christianity, he was passionate about emphasizing and enlightening Korean independence.
Beginning Rhythm Section

How does one take a concert band snare drummer, classically trained pianist, orchestral bass player, and self-taught guitar player and turn them into a jazz rhythm section? The drummer has never had so many drums and cymbals to worry about, the pianist may be playing with a group for the very first time, the bass player has to learn to “walk” a bass line, and the guitar player has to play in foreign keys. This chapter addresses the teaching of the rhythm section with regard to (a) rhythm section notation, (b) bass, (c) piano, (d) guitar, (e) drum set, (f) auxiliary instruments, and (g) rhythm section rehearsal strategies. It presents a sequential approach to teaching the beginning rhythm section: (a) walking bass lines, (b) voicing chords, (c) comping patterns, (d) playing setups and fills, and (e) interpreting and realizing instrument-specific rhythm section notation markings.
Atuação profissional na normalização bibliográfica: um campo promissor para o bibliotecário

The normalization exercise is an expanding market segment, most of which is occupied by professionals from different areas of knowledge, many even without adequate training and not supported by legal determinations. Thus, this text refers to a descriptive research, with a qualitative approach, supported by a bibliographical, documentary and experience report about the extension of librarian tasks beyond the information units. It aims to present the librarian performance in the field of bibliographic normalization, highlighting the potential of this activity as a market segment for the contemporary librarian. It also aims to identify what has been taught in professional training that enhances normative practice and what has been determined by competent bodies that legalize this practice to the librarian. From the results, the study found that the practice of bibliographic normalization may constitute, at present, an innovative and promising market segment for the librarian. Future research is recommended, based on on-the-spot studies, with graduating students and professionals working in the market, regarding what they consider in relation to the consulting segment in standardization, as well as investigations regarding professional training for the normative exercise.
Travel Track Recognition Based on Natural Language Process

Travel track surveys have been an effective method to analyze travel rules. The internet is filled with large amounts of text data. This kind of data contains abundant information about travel tracks that can be revealed via natural language processing (NLP). This article presents a new way to recognize travel tracks based on text data, differing from GPS data and cellular signaling data; it is a novel method to reflect the real trace of a person. First, thousands of travel notes was collected and preprocessed as a training set. Second, the paper utilizes Bi-GRU and CRF to train these long text data. Then we used a neural network model to recognize site names and temporal words described in the text. Lastly, the trace emerges after individually mapping the site names and temporal words.
<i>Early Russian Film Prose. Online Research Team Project</i>

Clea Wanner`s review of the online research team project Early Russian Film Prose https://hum.hse.ru/ditl/filmprose/
The IoT Design Deck 2.0: Improving the Tool for the Co-design of Connected Products

Designing the User Experience of an Internet of Things (IoT) product is a complex activity that requires multidisciplinary and specific competencies and that raises new challenges for designers. In this context the IoT Design Deck [1] is a method to help design teams to collaborate in order to design a connected product and an omnichannel service. The main strengths of the method are: to create a common language and a common knowledge base to help multidisciplinary teams working together; to focus on UX factors rather than on technological ones; to discover and use the potential of the IoT and take into account its threats; to have a service oriented approach rather than a device centrical one; to accelerate the design process. In this work we present the evolution of the method, obtained through a test campaign, made with experts and non-experts, and a redesign phase based on tests results.
An Adversarial Attack Method in Gray-Box Setting Oriented to Defenses Based on Image Preprocessing

Recently, many studies have proposed adversarial defenses of image preprocessing based on gradient masking to deal with the threats of adversarial examples in deep learning models. These defenses have been broken through in white-box threat models, where attackers have full knowledge of target models. However, they have not been proved to be invalid in gray-box threat models, where attackers only partially know about target models. In this paper, by integrating stochastic initial perturbations into momentum iterative attack, we propose SMIM which is an efficient adversarial attack method. Based on this, BPDA attack framework is applied to the attack in the gray-box setting. Experiments show that this method can generate adversarial examples with strong attack ability and transferability on seemingly non-differentiable defensive models, thereby evading defenses with only partial knowledge of target models.
Analysis of Korean Pronunciation Errors Pattern of Foreign Students

본 연구의 목적은 외국인 유학생의 한국어 발음을 향상시키기 위해 한국에 거주한 기간이나 한국어 수준, 조음위치와 방법에 따라 한국어 발음의 정확도를 살펴보고자 하였다. 외국인 유학생 30명을 대상으로 우리말 조음음운검사(U-TAP)를 실시하였고, 외국인 유학생이 산출한 모든 발음을 녹음하여 2명의 언어재활사가 분석하였다. 한국에 거주기간이나 한국어 수준에 따른 조음정확도 결과는 이변량분산분석으로 처리하였고, 조음위치와 방법에 따른 자료는 반복측정 분산분석을 실시하였다. 연구결과, 외국인 유학생의 한국어 발음은 한국에 거주하는 기간이나 한국어수준에 따라 차이가 없었으며, 자모음간 발음 정확도에서도 유의한 차이가 나타나지 않았다. 음절상에서 어두-초성에 위치한 음소는 어중-초성에 위치한 음소보다 통계적으로 유의하게 정확하였다. 조음 위치에서는 양순음이, 조음 방법에서는 비음과 유음이 다른 음소에 비해 정확하게 산출하였다. 따라서 외국인 유학생에게 한국어 발음을 지도할 때 모음의 정확도가 강조되어야 하며, 자음을 지도할 때는 공명음과 단서가 많은 음소위주로 먼저 교육하고, 가능하다면 각 국가별 음성학적 특성을 고려한 발음교육 접근이 제시되어야 할 것이다.The purpose of this study was to investigate the error patterns of Korean pronunciation according to the duration of Korean residents, Korean language level, and placement and method of articulation. In this study there were 30 people involved foreign students, the Korean articulation phonological test (U-TAP) was conducted to evaluate their pronunciation. All pronunciation of foreign students was recorded and analyzed by two language therapists. Data were analyzed by two-way ANOVA, paired t-test and repeated measures ANOVA. As a result, the Korean pronunciation of foreign students was not different according to the duration of Korean residence or the level of Korean and show no different of accuracy between vowel and consonant pronunciation. In the position of consonants on the syllable, the phonemes located in the word initial-syllable initial were statistically more accurate than the phonemes located in the word middle-syllable initial. Bilabial sound in the articulation placement and nasal/liquid sound in the articulation method are pronounced more accurately than other phonemes. Therefore, vowel pronunciation should be emphasized when teaching Korean language to foreign students and consonant guide to focus on phonemes with many resonance tones and clues.
Study on the Persuasive Design Method of Health Education for the Elderly Adults

In the aging society, it will play an effective role in preventing chronic diseases that the elderly adults improve the health knowledge and form a healthy lifestyle with health education. At present, people did not pay enough attention to the health education, because of some reasons. This paper explores the persuasive design method of health education in accordance with the PSD model and health behavior theory. Through literature review, questionnaire survey and focus group interviews, user’s motivation and ability are studied and the corresponding persuasive design method and design principles are put forward.
Improving Chinese Named Entity Recognition with Semantic Information of Character Multi-position Representation

Named entity recognition is an important basic task for information extraction and construction of knowledge graph, but the recognition rate needs to be further improved, especially in Chinese. There are two main implementations based on the sequence tagging method. Among them, the character-based method lacks the support of word information, and the word-based method is affected by the word segmentation efficiency. In order to comprehensively utilize the information of characters and words and to reflect the semantic information that changes due to different combinations of characters and words in a sentence. We designed a tagging scheme based on word segmentation and dictionaries. Then, neural networks are used for learning multi-position feature vectors and character-based tagging task. Experiments with MSRA datasets show that this method outperforms word-based and character-based baselines and achieves a higher recall rate compared to other methods.
Broadcast Congested Clique: Planted Cliques and Pseudorandom Generators.

We develop techniques to prove lower bounds for the BCAST(log n) Broadcast Congested Clique model (a distributed message passing model where in each round, each processor can broadcast an O(log n)-sized message to all other processors). Our techniques are built to prove bounds for natural input distributions. So far, all lower bounds for problems in the model relied on constructing specifically tailored graph families for the specific problem at hand, resulting in lower bounds for artificially constructed inputs, instead of natural input distributions.One of our results is a lower bound for the directed planted clique problem. In this problem, an input graph is either a random directed graph (each directed edge is included with probability 1/2), or a random graph with a planted clique of size k. That is, k randomly chosen vertices have all of the edges between them included, and all other edges in the graph appear with probability 1/2. The goal is to determine whether a clique exists. We show that when k = n(1/4 - e), this problem requires a number of rounds polynomial in n.Additionally, we construct a pseudo-random generator which fools the Broadcast Congested Clique. This allows us to show that every k round randomized algorithm in which each processor uses up to n random bits can be efficiently transformed into an O(k)-round randomized algorithm in which each processor uses only up to O(k log n) random bits, while maintaining a high success probability. The pseudo-random generator is simple to describe, computationally very cheap, and its seed size is optimal up to constant factors. However, the analysis is quite involved, and is based on the new technique for proving lower bounds in the model.The technique also allows us to prove the first average case lower bound for the Broadcast Congested Clique, as well as an average-case time hierarchy. We hope our technique will lead to more lower bounds for problems such as triangle counting, APSP, MST, diameter, and more, for natural input distributions.
МОДЕЛЬ ТА МЕТОД НАВЧАННЯ СИСТЕМИ КЛАСИФІКАЦІЇ РУХОМИХ ОБ’ЄКТІВ ДЛЯ МАЛОГАБАРИТНОГО БЕЗПІЛОТНОГО АПАРАТУ

The classification model which consists of the motion detector, object tracker, convolutional sparse coded feature extractor and stacked information-extreme classifier is developed. It is proposed to build a motion detector based on the difference of consecutive aligned frames where alignment is performed via keypoints matching, homography estimation, and projective transformations. Motion detector seeks to simplify object classification task through reduction of input data variations and resource savings for motion region search model synthesis without training. The proposed model is characterized by low computational complexity and it can be used as labeling dataset gathering tool for deep moveable object detector. Furthermore, the training method for moving object detector is developed. The method consisting in unsupervised pretraining feature extractor based on sparse coding neural gas, supervised pretraining and following fine-tuning of stacked information-extreme classifier. Using soft-competitive learning scheme in sparse coding neural gas facilitates robust convergence to close to optimal distributions of the neurons over the data. Sparse coding neural gas reduces the requirements for the volume of labeled observations and computational resource. As a criterion for the effectiveness of classifier's machine training, the normalized modification of S. Kullback’s information measure is considered. Labeling new emerging data through self-labeling for high prediction score cases and manual labeling for low prediction score cases, and following labeled object tracking are also offered. In this case, class balancing using undersampling within dichotomous strategy “one-against-all”. The set of classes include bicycle, bus, car, motorcycle, pickup truck, articulated truck, and background. Simulation results on MIO-TCD dataset confirm the suitability of the proposed model and training method for practical usage.
Review of Modern Cryptography and Elliptic Curves, A Beginner's Guide by Thomas R. Shemanske

The equation y2 = x3 + ax2 + bx + c might seem a little innocuous at first. However, studying the sets of rational points (x; y) obeying this equation has proven to be one of the most far-reaching and fruitful areas of mathematics. For example, it led, aided and abetted by much of the most powerful mathematics of the past century, to Wiles' proof of Fermat's Last Theorem. And furthermore, these so-called "elliptic curves" (the terminology having little to do with ellipses) are actually useful. You can factor numbers with them! And send secret messages!
UNDERSTANDING GROVER'S SEARCH ALGORITHM THROUGH A SIMPLE CASE OF STUDY

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 1730-1737ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.0502Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
Piecewise constant reconstruction of damaged color images

A variational model for reconstruction of damaged color images is studied, in particular in the case where only finitely many colors are admissible for the reconstructed image. An existence result and regularity properties of minimizers are presented.
Ethereum Wallets and Smart Contracts

In Chapter 1 , I introduced Ethereum when I covered bitcoin, altcoins, and different consensus mechanisms. Specifically, I covered Ethereum’s PoW consensus and how utilizing Ethereum enables developers to create their own smart contracts and tokens. I mentioned that the Ethereum tokens can be generated as Ethereum requests for comment (ERCs) such as ERC-20, ERC-223, or ERC-777. In Chapter 3 , you created your own blockchain, and I covered bitcoin wallets and transactions.
The success of the web

Connecting the unique factors that influenced the origination and subsequent development of the World Wide Web.
The Non-Negative –Matrix Completion Problem for 5×5 Matrices Specifying Cyclic Diagraphs with 5 Vertices and 4 Arcs

The non-negative P0-matrix completion is considered for 5×5 matrices specifying digraphs with p=5 and q=4.The research determines which of the digraphs with p=5 and q=4 and specifying 5×5 partial matrices have non-negative P0-completion. Considering the 5×5 matrices with q=4, all the sixty one (61) non-isomorphic digraphs shall be constructed. All the partial non-negative P0-matrices will be extracted from each digraph. To establish if the pattern has non-negative P0-completion or not, zero completion will be performed on each of the partial matrix extracted. The study establishes that all acyclic digraphs of an 5×5 matrix with q=4 have non-negative P0-completion. The matrix completion problem is to find the values of an n x m matrix M, given a sparse and incomplete set of observations. Possible areas of applications include Seismic data reconstruction to recover missing traces when data is sparse and incomplete ,say due to malfunctioned measuring instruments, biased or corrupted traces, ground barriers, or due to financial limitation to access complete data. Others include incomplete market surveys (eg movie ratings to complete missing data so as to recommend appropriately to viewers), weather forecasting from historical data recordings as well as future predictions from computer simulations, reconstruction of images in computer; and finding the positions of sensors in Global Positioning from distances available in a local network.
Apara: Workload-Aware Data Partition and Replication for Parallel Databases

Data partition and replication mechanisms directly determine query execution patterns in parallel database systems, which have a great impact on system performance. Recently, there have been some workload-aware data storage techniques, but they suffer from problems of narrow support to complex workloads or large requirements for storage. In order to enable the support for complex analytical workloads over massive distributed database systems, we design and implement a workload-aware data partition and replication tool, called Apara. We design two heuristic algorithms and define two cost models for effective data partition calculation and efficient replication usages. We run a set of experiments to compare and demonstrate the performance between Apara and the other representative work. The results show that Apara consistently outperforms the primary solutions on TPC-H workloads.
Shape Descriptor Based on Centroid with Chord Lengths for Image Retrieval

Shape is considered as a significant characteristic in object detection. In applications such as recognizing the shapes and classification, retrieval of shapes, extraction of shape features and their depiction plays an important role. We propose a shape descriptor which is computationally economical, compact and fast. In this work, we present three methods of feature computation based on chords. Among three, good result is obtained by the third method. Since the proposed work is based on centroid involving a global histogram, shape descriptor is invariant to all transformations. When compared to other shape signatures the proposed shape descriptor resulted in bull’s eye score of 84.56% on MPEG-7 dataset.
EFFECTIVENESS OF TEACHING METHODS IN INVOLVING STUDENTS: PRACTICAL DIGITAL EXPERIENCES AND GAMIFICATION

EFFECTIVENESS OF TEACHING METHODS IN INVOLVING STUDENTS: PRACTICAL DIGITAL EXPERIENCES AND GAMIFICATION
Low-Precision Random Fourier Features for Memory-constrained Kernel Approximation

We investigate how to train kernel approximation methods that generalize well under a memory budget. Building on recent theoretical work, we define a measure of kernel approximation error which we find to be more predictive of the empirical generalization performance of kernel approximation methods than conventional metrics. An important consequence of this definition is that a kernel approximation matrix must be high rank to attain close approximation. Because storing a high-rank approximation is memory intensive, we propose using a low-precision quantization of random Fourier features (LP-RFFs) to build a high-rank approximation under a memory budget. Theoretically, we show quantization has a negligible effect on generalization performance in important settings. Empirically, we demonstrate across four benchmark datasets that LP-RFFs can match the performance of full-precision RFFs and the Nystrom method, with 3x-10x and 50x-460x less memory, respectively.
INTERACTIVE METHODS FOR TRAINING CHILDREN FROM PRIMARY SCHOOL

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 2034-2039ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.0554Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
ANALISIS KEPUASAN KEPENTINGAN DALAM PENGADAAN BAHAN PUSTAKA DI PERPUSTAKAAN SEKOLAH

The growth of information technology becomes a challenge for the school librarian, especially in developing the book collections. Book procurement for the library must be matched with the library user’s need. In this research we develop a method to measure the library user’s opinion about the importance and performance of each kind of books in the library, in this case in a school library. The user’s opinions were obtained using questionnaire and analyzed by calculate the average of each score and placing each category in the importance-performance diagram. From the diagram, it could be observed which kinds of books should be added, weeded, or preserved in the library. Several adaptations could be carried out to implement this method outside the school library.
A Study on Organization of Blockchain Startup According to Market Situation and ICO Funding Result

ICO is a newly attempted funding method in the blockchain field in 2013, with an increasing number of projects each year. However, the number of startups failing to raise funds below $100,000 has risen from 51% in 2017 to a maximum of 75% in the second quarter of 2018. Accordingly, startups preparing for ICOs need to study what factors affect successful funding.BR In this study, we apply the formal concept analysis technique to classify the major occupational groups in the block chain field as development, legal, public relations, business development, financial and investment attraction. As a result of the analysis, we found that the job of the marketing is particularly important when the market situation is good. When the market situation is not good, the job of the business development such as securing a strong business partner was identified as important.