Reviewerly/exHarmony huggingface dataset:
Incorporating Tarsia to Foster Student Collaboration in the Mathematics Classroom

It is evident that we will be able to retain and apply more knowledge into practice if we have spent more time in reviewing and practicing. Active student practice and consistent review are the key components of mastery learning. However, in Mathematics teaching, some of the commonly used instructional approaches such as “Practice on the blackboard” and “Assignment of homework” contradict the above mentioned key elements of content mastery. In view of this, our study aims to examine the effectiveness of an interactive activity, Tarsia. Tarsia allows students to elicit the characteristics of fun and playfulness while ensuring enough practices are obtained. Our results have shown that students view Tarsia as an interesting activity which enables them to develop new knowledge as well as promoting collaborative skills among the team members. Collaboration, is one of the four 21st century skills proposed by National Education Association (NEA) as the important skills to possess in order to succeed in the constantly changing 21st century.
Postmodernism As The Dominant Of Education Development In The Information Society

To analyze the role and prospects of education in the information society, the presented paper shows a conceptual analysis of trends that have a significant impact on the society development in the era of postmodernism, on education, which, having a socio-cultural conditionality, traditionally reflects the development of all those processes in society that actively affect culture as a systemic set of different forms of its manifestation. Talking about the prospects of Russian education one should take into account the powerful traditions of the Russian school, the basis laid in the Soviet pedagogy. Yet, often responding to the "challenges of time" pedagogy and education theory fail to provide comprehensive answers to the current problems arising "here and now", the solution of which allows us to move forward. Education in any country and in Russia as well, includes, on the one hand, the translation of culture, that is, of its existing "sides, aspects, facets, abilities and properties", and, on the other hand, the process of appearance and preparation of its future state, since it is in the educational processes of today where the foundations for existence and activity in the future are laid. The key characteristics of postmodernism are refracted through the prism of educational processes.
Enhance knowledge graph embedding via fake triples

Embedding knowledge graphs (KGs) into continuous vector spaces is a focus of current research. Although previous works achieve great success, most of them are based on the closed-world assumption, where they only utilize knowledge explicitly exist in KGs but ignore implicit knowledge. This paper tries to improve the performance of KG embedding models by adding implicit knowledge to it. We consider that when an entity occurs only in head or tail of all triples in one KG, its connectivity with other entities is single and the inverse triples of it can provide as implicit knowledge to enrich its connectivity, and with this implicit knowledge KG embedding models can learn more accurate semantic of entities and relations in the KG. For this purpose, we introduce `fake triples' (triples that theoretically should exist but not appear in knowledge graph explicitly) via dummy relations for zero in-degree and zero out-degree entities to enrich their connectivity and further improve the embedding models' performance. Extensive experiments on entity alignment task and linking predication task show that our approach achieves good results. On entity alignment task, the entity alignment model with fake triples (EA+F) obtains better results than a number of state-of-the-art entity alignment models. On linking predication task, our method achieves better Mean Rank on FB15K. Our work can prove that the performance of knowledge graph embedding may be promoted by elaborate analysis on dataset rather than designing complex models.
Model the Long-Term Post History for Hashtag Recommendation

The goal of this work is to provide a keyword-suggestion-like hashtag recommendation service, which recommends several hashtags when the user types in the hashtag symbol "#" while writing a post. Different from previously published hashtag recommendation systems, which only considered the textual information of the post itself or a few numbers of the latest posts, this work proposed to model the long-term post history for the recommendation. To achieve this purpose, we organized the historical posts of a user in the time order, obtaining a post sequence. Based on this sequence, we proposed a recurrent-neural-network-based framework, called the Parallel Long Short-term Memory (PLSTM), to perform the post history modeling. This was motivated by the success of the recurrent neural network in modeling the long-term dependency of dynamic sequences. The hashtag recommendation was performed based on both the current post content representation and the post history representation. We evaluated the proposed model on a real dataset crawled from Twitter. The experimental results demonstrated the effectiveness of our proposed model. Moreover, we quantitatively studied the informativeness of different parts of the post history and proved the feasibility of organizing the historical posts of a user in the time order.
Second-order interference of two independent photons with different spectra*

The second-order interference of two independent photons with different spectra in a Shih–Alley/Hong–Ou–Mandel interferometer is studied in Feynman’s path integral theory. There is a second-order interference pattern for photons with different spectra if the photons are indistinguishable for the employed detection system. The conditions to observe the second-order temporal beating with photons of different spectra are analyzed. The influence of the response time of the detection system on the observed second-order interference pattern is also discussed. It is a direct result of that measurement in quantum mechanics is dependent on the employed measuring apparatus. The results are helpful to understand the physics of two-photon interference in different schemes.
Enhancing Visualization of Multidimensional Data by Ordering Parallel Coordinates Axes

Every year business is overwhelmed by the quantity and variety of data.Visualization of Multi-dimensional data is counter-intuitive using conventional graphs.Parallel coordinates are proposed as an alternative to explore multivariate data more effectively.However, it is difficult to extract relevant information through the parallel coordinates when the data are Multi-dimensional with thousands of lines overlapping.The order of the axes determines the perception of information on parallel coordinates.This paper proposes three new techniques in order to arrange the axes in the most significant relation between the datasets.The datasets used in this paper, for Egyptian patients, with many external factors and medical tests.These factors were collected by a questionnaire sheet, made by medical researchers.The first Technique calculates the correlation between all features and the age of the patient when they get diabetes disease.The second technique is based on merging different features together and arranging the coordinates based on the correlations values.The Third Technique calculates the entropy value for each feature and then arrange the parallel coordinates in descending order based on the positive or negative values.Finally based on the result graphs, we conclude that the second method was more readable and valuable than the other two methods.
Missing Entity Synergistic Completion across Multiple Isomeric Online Knowledge Libraries

Online knowledge libraries refer to the online data warehouses that systematically organize and categorize the knowledge-based information about different kinds of concepts and entities. In the era of big data, the setup of online knowledge libraries is an extremely challenging and laborious task, in terms of efforts, time and expense required in the completion of knowledge entities. Especially nowadays, a large number of new knowledge entities, like movies, are keeping on being produced and coming out at a continuously accelerating speed, which renders the knowledge library setup and completion problem more difficult to resolve manually. In this paper, we will take the online movie knowledge libraries as an example, and study the "Multiple aligned ISomeric Online Knowledge LIbraries Completion problem" (MISO-KLIC) problem across multiple online knowledge libraries. Miso-Klic aims at identifying the missing entities for multiple knowledge libraries synergistically and ranking them for editing based on certain ranking criteria. To solve the problem, a thorough investigation of two isomeric online knowledge libraries, Douban and IMDB, have been carried out in this paper. Based on analyses results, a novel deep online knowledge library completion framework "Integrated Deep alignEd Auto-encoder" (IDEA) is introduced to solve the problem. By projecting the entities from multiple isomeric knowledge libraries to a shared feature space, IDEA solves the Miso-Klic problem via three steps: (1) entity feature space unification via embedding, (2) knowledge library fusion based missing entity identification, and (3) missing entity ranking. Extensive experiments done on the real-world online knowledge library dataset have demonstrated the effectiveness of IDEA in addressing the problem.
TEACHING VOCABULARY USING FLASHCARD TO YOUNG LEARNER

This research entitled “ teaching vocabulary using flashcard to young learners” is a study to investigate the influence of using flashcard in teaching vocabulary to students of grade four in elementary school. This study was done using pre-experimental research. There are three steps in doing research design. First, the writer gave pretest to the students of elementary school grade two as the dependent variable. Second, the writer implicate the treatment to the subjects by teaching vocabulary using flashcard. Final steps, the writer gave subjects posttest. The results of the research showed that there is an improvement in student’s vocabulary mastery after the students were thought vocabulary mastery using flashcard. The students of elementary school grade two could memorize and understand easily and they were encouraged to learn English. Thus, the researcher could conclude that using flashcard in teaching vocabulary to the students grade two is recommended as teaching program to learn English.Keywords: teaching vocabulary, flashcard, young learner.
Students’ Ability in Using Direct and Indirect Speech of English Department Students at Universitas Muslim Indonesia

In this study the writer wishes to know the students’ ability by the fourth semester students of Foreign Language Academy UMI in using direct and indirect speech. The whole population of this study was 160 students at fourth semester of Foreign Language Academy. There were 24 students out of 160 students to represent the population as the sample. The sample is taken by using random sampling technique. The types of the test consist of simple past tense, simple present tense and future tense. Through the data, the researcher obtained that 1 student or 4% were included in the highest score or having excellent level. 1 student or 4% were included in good level. Then, 2 students or 9% were included in sufficient level, 20 students or 83% were included in the low score or having fail level. The result revealed that there were still many underprivileged students in learning this subject.
A Structural Design and Interaction Algorithm of Smart Microscope Embedded on Virtual and Real Fusion Technologies

The microscope is an important teaching tool in secondary school biology. This important equipment needs to be understood and mastered through biological experiments. However, in actual experimental teaching in China, microscope samples are difficult to produce, preserve and share, and the implementation status is not ideal. These conditions seriously affect student enthusiasm and require additional participant labor. Moreover, they hinder teachers' evaluation of experimental learning. Thus, this paper constructs a smart microscope physical interaction kit for secondary school biology experiments. First, the main components of the traditional microscope are replaced by a variety of different sensing elements, which are 3D printed. Then, a novel multichannel information integration strategy based on visual, auditory and tactile information is proposed to manage different channels of information, to understand the user's operational intent and to organize reasonable interactions (including the display of real-time adjustment effects). Then, we propose a navigational interaction paradigm based on multimodal intent understanding, aiming at reminding users of invalid behavior and providing necessary operational guidance for users, thus achieving the purpose of intelligent interaction and intelligent experimental teaching. The experimental results show that the proposed microscope kit, multichannel integration strategy and navigation interaction algorithm not only imbue microscopy experiments with the characteristics of intelligent interaction but also stimulate student enthusiasm and help the evaluation of experimental learning. We find that these capabilities are well received by users.
PANDU LOKASI WISATA KOTA TANGERANG DENGAN SISTEM INFORMASI GEOGRAFIS BERBASIS WEB

Around the tourists who come to the city of Tangerang at this time makes the problem faced by the Tangerang Culture and Tourism Office. To help solve the problem faced, the author designed a web-based geographic information system (GIS) which would later help tourists in finding tourist locations in the city of Tangerang easily and precisely. The advantages of this web service can be used to solve the problems that exist in the Tangerang City Culture and Tourism Office and help tourists in obtaining tourist information, looking for attractions, displaying the path to the desired tourist attractions as well as providing photographs of interesting attractions. So that it can increase public interest or tourists who will visit to tour the city of Tangerang. The research methodology uses a prototyping approach and the system design uses UML (Unifed Modeling Language).
Line Area Monitoring using Structural Similarity Index

Real-time motion detection in specific area is considered the most important task in every video surveillance system.In this paper, a novel real time motion detection algorithm introduced to process Line zones called Line Monitoring Algorithm (LMA).This algorithm integrates Bresenham's Algorithm and Structural Similarity Index (SSI) in order to achieve the best performance.Bresenham's Algorithm is used to collect line pixels from two given points.Then, the SSI is used for real-time calculation of similarity for line motion detection.The most attractive side of using the LMA is that the algorithm does not need to compare all pixels of the whole images or regions for line areas monitoring.This algorithm has high capability, treatment speed and efficiency for motion detection and also demands less compilation time for the hardware performance.The main objective of this paper is to use a video surveillance system implementing LMA to supervise the Car Reverse Test (CRT) for driving license exam in Morocco.The evaluation of the experiment results in implementing the proposed algorithm is reported in this paper.
Correlation Clustering with Same-Cluster Queries Bounded by Optimal Cost.

Several clustering frameworks with interactive (semi-supervised) queries have been studied in the past. Recently, clustering with same-cluster queries has become popular. An algorithm in this setting has access to an oracle with full knowledge of an optimal clustering, and the algorithm can ask the oracle queries of the form, Does the optimal clustering put vertices $ u $ and $ v $ in the same cluster? Due to its simplicity, this querying model can easily be implemented in real crowd-sourcing platforms and has attracted a lot of recent work. In this paper, we study the popular correlation clustering problem (Bansal et al., 2002) under this framework. Given a complete graph $G=(V,E)$ with positive and negative edge labels, correlation clustering objective aims to compute a graph clustering that minimizes the total number of disagreements, that is the negative intra-cluster edges and positive inter-cluster edges. Let $ C_{OPT} $ be the number of disagreements made by the optimal clustering. We present algorithms for correlation clustering whose error and query bounds are parameterized by $C_{OPT}$ rather than by the number of clusters. Indeed, a good clustering must have small $C_{OPT}$. Specifically, we present an efficient algorithm that recovers an exact optimal clustering using at most $2C_{OPT} $ queries and an efficient algorithm that outputs a $2$-approximation using at most $C_{OPT} $ queries. In addition, we show under a plausible complexity assumption, there does not exist any polynomial time algorithm that has an approximation ratio better than $1+\alpha$ for an absolute constant $\alpha >0$ with $o(C_{OPT})$ queries. We extensively evaluate our methods on several synthetic and real-world datasets using real crowd-sourced oracles. Moreover, we compare our approach against several known correlation clustering algorithms.
Reward-Punishment Actor-Critic Algorithm Applying to Robotic Non-grasping Manipulation

This paper presents a new actor-critic (AC) algorithm based on a biological reward-punishment framework for reinforcement learning (RL), named “RP-AC”. RL can yields capabilities where robots can take over complicated and dangerous tasks instead of human. Such capability, however, may require accounting for safety when achieving the tasks, because dangerous states and actions could cause the robot to breakdown and induce injuries. In the reward-punishment framework, robots gain both positive reward (called reward) as the degree of task achievement and negative reward (called punishment) as the risk of current state and action, which are composed in RL algorithms. In this paper, to control robots more directly, the AC algorithm, which operate in continuous action space, is employed. To this end, we propose policy gradients with the way to compose reward and punishment, more accurately, their value functions. Instead of merely composing them at a fixed ratio, we theoretically introduce immediate reward and punishment into the policy gradients, as animals do in decision making. In pushing task experiments, whereas the vanilla AC fails to acquire the task due to too much emphasis on safety, the proposed RP-AC successfully acquires the task with the same level of safety.
Authentication Modeling with Five Generic Processes

Conceptual modeling is an essential tool in many fields of study, including security specification in information technology systems. As a model, it restricts access to resources and identifies possible threats to the system. We claim that current modeling languages (e.g., Unified Modeling Language, Business Process Model and Notation) lack the notion of genericity, which refers to a limited set of elementary processes. This paper proposes five generic processes for modeling the structural behavior of a system: creating, releasing, transferring, receiving, and processing. The paper demonstrates these processes within the context of public key infrastructure, biometric, and multifactor authentication. The results indicate that the proposed generic processes are sufficient to represent these authentication schemes.
Mentality Influence On The Learning Process In China And Russia

The influence of mentality on educational process in higher education institutions of China and Russia is revealed through the analysis of key terms: mentality, behavior, ethno-cultural stereotypes. The research shows the national characteristics of Chinese and Russian peoples, analyzes the results of the survey in which Chinese and Russian students participated to identify ethnic stereotypes. The work also shows the influence of mentality through the role of teachers, behavior and differences in curricula and programs in higher education institutions of China and Russia. In our study, mentality as a specific psychological life of people is revealed through a system of views, assessments, norms and mindsets, based on the knowledge and beliefs typical of a given society, which, together with the dominant needs and archetypes of the collective unconscious, determines hierarchy of values, and hence beliefs, ideals, inclinations, interests characteristic of this community representatives’ as well as other social attitudes that distinguish this community from others. The Confucian educational tradition is dominant in Chinese history. In this case, the object of human intellectual attention, of his contemplation, practice and experiences is the individual self-improvement or self-education — not the world around — which is the main goal of human life and education in China.
SIMULATION IN HIGHER EDUCATION OF RUSSIA

The article describes the characteristics of simulation practices in modern society, the causes of the emergence and spread of imitations in the education system. The authors identified and classified into five groups the indicators of distribution of simulation practices in higher education. Groups of indicators include the interpretation of the results of sociological studies of the spread of imitations in higher education institutions of different years, contain conclusions and assumptions about the causes and consequences of the occurrence of imitations. The results of the expert survey on the impact of simulation practices on the development of the communication environment in the educational space and the problems arising during this process are presented. Among the problems the article highlighted the tension in relations not only vertically but also horizontally, which ultimately has a negative impact on the formation of the corporate educational environment.
The Construction and Validation of the SP-IE Questionnaire: An Instrument for Measuring Spatial Presence in Immersive Environments

The present study describes the construction and validation of an instrument for measuring spatial presence (the sense of “being there”) in the context of highly immersive environments: the SP-IE [Spatial Presence for Immersive Environments] questionnaire, for use in the French-speaking community. A first raw version of the questionnaire was submitted to an item selection procedure and reliability tests with 67 participants. An exploratory factor analysis (EFA) with 179 participants was then employed on the resulting version to explore its underlying scales. Finally, the outcome scale-structure from the EFA was evaluated using confirmatory factor analyses (CFAs). This process resulted in a well-structured 20-item questionnaire (link), based on seven scales: (i) the sense of spatial presence, (ii) the affordance of the environment, (iii) the user’s enjoyment, (iv) the user’s attention allocation to the task, (v) the sense of reality attributed to the environment, (vi) the social embodiment with avatars, and (vii) the possible negative effects of the environment (cybersickness). Results showed overall good internal consistency and satisfactory convergent validity of the scales. The fit indexes obtained (X2/df = 1.34, GFI = .95, CFI = .90, TLI = .87, SRMR = .068, and RSMEA = .045) demonstrated a good fitness of the structure proposed. However, even though the scale structure proposed in this paper was confirmed, its low discriminant validity encourages further evaluations.