Reviewerly/exHarmony huggingface dataset:
Student engagement in mobile learning activities: breakdowns and breakthroughs

The ubiquity of mobile devices together with the potential to bridge classroom learning to real-world has added a new angle to contextualising mathematics learning. The goal of this research was to evaluate student engagement in a series of mobile learning activities. The study uses critical incident analysis to evaluate the breakdowns and breakthroughs of mobile learning. Twenty-four Primary 7 students participated in the study. The mobile learning activities were found to have facilitated visualisation, encouraged reflection and promoted active learning. However, some issues regarding mobile use affected student engagement with the activity. The challenges identified highlighted the role teachers play in designing and carrying out novel technology use.
Fundamental Structure of Shor’s Quantum Algorithm for Factoring Integers

One of the most well known mathematically hard problems in number theory is the integer factorization problem, roughly stated that decomposition of a composite number into its prime factors. In modern cryptography, RSA encryption algorithm whose security is based on integer factorization problem is highly practical, widespread and up to date no classical algorithm having polynomial running time for the factorization of large numbers is known. In 1994, Peter Shor proposed an efficient algorithm on quantum computer. In this paper, we  mention about the fundamentals of  Shor's quantum algorithm illustrating a concrete example.
Finding Groups in Data

Data Mining algorithms try to address the issue as scientifically as possible, defining methods and rules aimed to assign units of observation into classes, which are not defined a priori, and are supposed to somehow reflect the structure of the entities that the data represent. Homogeneity within each cluster and the degree of separation among clusters are measured by referring to a distance metric or a dissimilarity measure. Cluster Analysis is a classification technique aiming at dividing individual cases into groups such that the cases in a cluster are very similar to one another and very different from the cases in other clusters. The ordering of pairs of units is sensitive to the selected measure of distance or dissimilarity, so an important step in Cluster Analysis is the choice of the most appropriate measure, which in practice should be based on the type of data at hand: for numerical variables while for categorical variables dissimilarity measures should be preferred.
GRaCe: A Relaxed Approach for Graph Query Caching

SPARQL query optimization is an important issue for RDF data stores that can benefit from the usage of caching frameworks. Most caching approaches rely on a precise match semantics, that limits the number of cache hits and, as a consequence, the potential benefit. Others propose relaxed matches for the entire query, which is precisely executed over the cached result set. In this paper, to overcome these limitations we propose GRaCe, a Graph Relaxed Caching approach for RDF data stores. GRaCe supports relaxed cache matches and a relaxed query semantics, thus increasing the number of cache hits. Experimental results show that a relaxed cache can significantly reduce query execution time in all the scenarios where a relaxed query result is tolerated.
The Use Of Diary To Improve Students’ Ability At Writing Recount Text At MTs Madani Islamiyah School Pematangsiantar

This research aimed to improve students’ ability at writing recount text by using diary. The background of the study in this research was based on the students’ difficulties in writing recount text. In order to solve this problem, the teacher should have creative media. A diary can be an alternative way as a learning media that will make students enjoy and easy to write recount text. In this research, the researcher conducted a classroom action research as the methodology. The subject of this research was the eighth grade students of MTs Madani Al-Islamiyah School Pematangsiantar. This research used two types of data, namely qualitative data and quantitative data. The qualitative data were obtained through an interview, observation sheet and field note. Meanwhile, the quantitative data used test that done before the implementation of the actions (pre-test) and after the implementation of the actions (post-test I and post-test II). The result of this research showed that there was increasing of students in writing recount text. The mean of the pre-test was 45.93, the mean of the first cycle was 69.8, and the mean of the second cycle was 79.06. It showed that the mean in the second cycle were better than the pre-cyle and first cycle. And by using t-test, the researcher found that tobservation (7.09) > ttable (1.09). It means that the hypothesis (Ha) of the research is accepted. Based on the findings, it can be concluded that the use of diary can improve the students’ ability at writing recount text.
Mobile Authentication Using Tapping Behavior

Mobile phones or smartphones are rapidly becoming the primary and essential communication device in people’s lives that cannot be replaced by other communication devices, because of the portability, the size, and the multifunctionality provided in it. Nowadays, mobile phones are being used in almost every aspect of life and work as your personal assistant e.g. meeting reminders. It monitors your daily activities and gives suggestions accordingly e.g. health applications. With the help of smartphone online transactions can be performed, meetings can be conducted via video conferencing. It contains your personal files, emails, bank information, and your social network accounts record. It also contains information related to the credentials, which are stored in its memory. Despite all the benefits, there is a great threat to private information, in the case when mobile is snatched, misplaced, or in the use of an unauthorized user. An attacker can steal the user’s private data and can misuse it without the owner’s consent. Although the traditional authentication methods are in use, they have several limitations. In this paper, an authentication system is proposed that uses a combination of user behavior and touchscreen which can seamlessly capture the user’s tapping behavior. The information obtained from the touch screen sensors reflects the unique tapping behavior of each user. Moreover, machine learning is utilized to perform the classification for the user’s authentication.
Balancing the composition of word embeddings across heterogenous data sets.

Word embeddings capture semantic relationships based on contextual information and are the basis for a wide variety of natural language processing applications. Notably these relationships are solely learned from the data and subsequently the data composition impacts the semantic of embeddings which arguably can lead to biased word vectors. Given qualitatively different data subsets, we aim to align the influence of single subsets on the resulting word vectors, while retaining their quality. In this regard we propose a criteria to measure the shift towards a single data subset and develop approaches to meet both objectives. We find that a weighted average of the two subset embeddings balances the influence of those subsets while word similarity performance decreases. We further propose a promising optimization approach to balance influences and quality of word embeddings.
Sequence Prediction for Identifying User Equipment Patterns in Mobile Networks

With an increasing demand for bandwidth and lower latency in mobile communication networks it becomes gradually more important to improve current mobile network management solutions using available ...
The Structural Relations among Professor Support, Self-Determining Motivation to Learn, Flow-in-Learning, and Intent-to-Persist for Learning of Junior College Students

본 연구의 목적은 전문대학생의 교수지지, 자기결정성 학습동기, 학습몰입, 학습지속의도 간의 구조적 관계를 알아보고자 하였다. 연구의 대상은 대구·경상북도지역에 소재한 전문대학생 707명이었다. 연구도구는 교수지지, 자기결정성 학습동기, 학습몰입, 학습지속의도 척도를 사용하였다. 본 연구의 결과는 다음과 같다. 첫째, 전문대학생의 교수지지, 자기결정성 학습동기, 학습몰입은 학습지속의도에 직접 영향을 미친다. 둘째, 교수지지는 자기결정성 학습동기, 학습몰입에 직접 영향을 미친다. 셋째, 자기결정성 학습동기는 학습몰입에 직접 영향을 미친다. 넷째, 교수지지는 자기결정성 학습동기, 학습몰입을 통하여 학습지속의도에 간접 영향을 미친다. 교수지지는 자기결정성 학습동기를 부분 매개하여 학습지속의도에 간접 영향을, 교수지지는 학습몰입을 부분 매개하여 학습지속의도에 간접 영향을, 교수지지는 자기결정성학습동기, 학습몰입을 이중 매개하여 학습지속의도에 간접 영향을 미친다.The purpose of this study was to examine the structural relations among professor support, self-determining motivation to learn, flow-in-learning and intent-to-persist for learning of junior college students. The subjects consisted of 707 students in junior colleges located in Daegu Metropolitan City and Gyeongsangbuk-do Province. The instruments employed were the scales of professor support, self-determining motivation to learn, flow-inlearning and intent-to-persist for learning. First, professor support, self-determining motivation to learn, and the flow-in-learning of junior college students proved to have a significant direct effect upon their intent-to-persist for learning. Second, professor support of the students proved to have a significant direct effect upon their selfdetermining motivation to learn and flow-in-learning. Third, self-determining motivation to learn of the students had a significant direct effect upon their flow-in-learning. Fourth, professor support of the students was found to have an significant indirect effect upon their intent-to-persist for learning through self-determining motivation to learn and then flow-in-learning.
Granular Material Display: Information Presentation System using Two Layers of Granular Material and Speakers

In this paper, we propose a method of presenting information by manipulating granular material that are placed on two layers. In recent years, substantial displays, which are displays that present information by manipulating some form of material have been gaining traction in the research community. As these displays utilize materials found in nature, they are capable of blending in with the surrounding environment. To create a novel substantial display, we propose a substantial display that utilizes granular material and speakers. In the proposed system, two types of granular material with different colors and sizes are placed on two layers. By emitting sound waves from a speaker installed under the lower layer, the granular material on the lower layer rises to the upper layer and creates a pattern as the color of the granular material on each layer is different. To determine the optimal parameters, we examined four different granular material and varied the sound wave frequency. Finally, we implemented a system that allows users to emit sound waves at any arbitrary position on the canvas with two layers of granular material.
Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation

Recently, recommender systems have been able to emit substantially improved recommendations by leveraging user-provided reviews. Existing methods typically merge all reviews of a given user or item into a long document, and then process user and item documents in the same manner. In practice, however, these two sets of reviews are notably different: users' reviews reflect a variety of items that they have bought and are hence very heterogeneous in their topics, while an item's reviews pertain only to that single item and are thus topically homogeneous. In this work, we develop a novel neural network model that properly accounts for this important difference by means of asymmetric attentive modules. The user module learns to attend to only those signals that are relevant with respect to the target item, whereas the item module learns to extract the most salient contents with regard to properties of the item. Our multi-hierarchical paradigm accounts for the fact that neither are all reviews equally useful, nor are all sentences within each review equally pertinent. Extensive experimental results on a variety of real datasets demonstrate the effectiveness of our method.
Complexity Issues of String to Graph Approximate Matching

The problem of matching a query string to a directed graph, whose vertices are labeled by strings, has application in different fields, from data mining to computational biology. Several variants of the problem have been considered, depending on the fact that the match is exact or approximate and, in this latter case, which edit operations are considered and where are allowed. In this paper we present results on the complexity of the approximate matching problem, where edit operations are symbol substitutions and are allowed only on the graph labels or both on the graph labels and the query string. We introduce a variant of the problem that asks whether there exists a path in a graph that represents a query string with any number of edit operations and we show that is is NP-complete, even when labels have length one and in the case the alphabet is binary. Moreover, when it is parameterized by the length of the input string and graph labels have length one, we show that the problem is fixed-parameter tractable and it is unlikely to admit a polynomial kernel. The NP-completeness of this problem leads to the inapproximability (within any factor) of the approximate matching when edit operations are allowed only on the graph labels. Moreover, we show that the variants of approximate string matching to graph we consider are not fixed-parameter tractable, when the parameter is the number of edit operations, even for graphs that have distance one from a DAG. The reduction for this latter result allows us to prove the inapproximability of the variant where edit operations can be applied both on the query string and on graph labels.
A Light in Dark Places – 3D Reconstruction from Stereo Views with a Moving Light Source

In this paper we consider the problem of recovering depth from a moving camera with an attached light. The fact that the light is moving means that the appearance of the scene changes, making intensity-based correlation difficult. These appearance changes, however, are governed by the motion of the camera, and are intimately related to the depth of the scene. This allows us to derive constraints on the intensities of corresponding points. We show that, in principle, this approach allows us to recover depth and surface albedo (up to a scale from light intensity) from two calibrated views. This is possible even when viewing textureless surfaces, which are intractable for traditional stereo methods. However, the method is very sensitive to quantisation of intensity values, and so is not practical on its own for normal camera images. The underlying constraints, however, may be useful as part of larger systems.
Comparative Analysis of Noise Filtering Performance of Quadratic Image Filters

Quadratic image filters are filters belonging to a subclass of nonlinear model known as Volterra filters. Because of the nonlinear characteristics of images, nonlinear image filters generally produce better results than linear filters. In the present study, performance of the Quadratic image filters for Gaussian noise is examined by comparing with Gaussian filter and Median filter.  For this purpose, the mask weights used were determined by using Differential Evolution algorithm on synthetic training images. Noise added colour test images were filtered using Quadratic image filter using the calculated weights and the results were compared with Gaussian filter and Median image filter.
The Evolution of Digital Currency and the Exploration of the Operating Mechanism of the Global Digital Currency System

With the change of economic form, digital currency is issued in various forms such as private digital currency and central digital currency, However, most of the current currency distribution and circulation system management frameworks have certain defects in credit supervision, technical support and operational mechanism. On the basis of the existing research, we will explore the operating mechanism of the global digital currency system and construct a ternary digital currency model system framework to promote the research of the digital currency system.
Evaluation of Rock Slope Stability based on Multi-Dimension Cloud Model

Abstract In this paper, slope stability is classified into five grades in terms of very steady, steady, basically steady, unsteady, and very unsteady. Ten indicators of slope height, tendency difference between structural plane and slope, structural plane inclination, etc., were selected. To solve the uncertainty and randomness, multi-dimension cloud model was applied with weights determined by projection pursuit method. The grade of steadiness was determined by maximum subject degree. The method was applied to 34 rock slopes to assess stability. The accuracy of the method reaches 50%, which indicates that the method has higher accuracy, and can be applied to other fields.
(strong) AuCPace, an augmented PAKE

This document describes AuCPace which is an augmented PAKE protocolfor two parties. The protocol was tailored for constrained devices andsmooth migration for compatibility with legacy user credentialdatabases. It is designed to be compatible with any group of bothprime- and non-prime order and comes with a security proof providingcomposability guarantees.
USING WORD BANK TO ENRICH VOCABULARY OF GRADE X STUDENTS OF TAMAN KARYA MADYA VOCATIONAL HIGH SCHOOL

This paper explored the teaching techniques to enhance the tenth grade students’     vocabulary items in Taman Karya Madya Vocational High School Yogyakarta, Indonesia. The researchers conducted a pre-test before undertaking the classroom action research (CAR) and a post-test to measure the students’ improvement afterwards. Data were analyzed using the qualitative method by comparing the results of the pre-test and of the post-test. This study sought to answer the research questions related to how the word bank helped students in enriching vocabulary and whether there was any relationship between the teaching method applied in this CAR and the students’ improvement in vocabulary mastery. Results indicated that word bank assisted the students in enhancing vocabulary and that it was essential to choose an appropriate technique in teaching vocabulary.
A Statistical Correlation Coefficient To Validate The Effect of Age on Handwriting

Handwriting is a legitimate text created by an individual using a writing instrument which can be a pen or a pencil on any writing surface. When speaking analytically handwriting is an indicator of personality which is clearly depicted by a neurological pattern of the brain [1]. Putting it more simply, human brain produces character due to habit, which is developed over a period of time thus imparting individuality to a person’s handwriting. Our brain guides the movement of our hand. With the learning process the skill to master handwriting is developed. But when it comes to analysis it is a very complex trait. It involves a number of studies namely linguistic, cognitive, psychological, perceptual and motor components considering temporal conditions as well.
Corporate Social Responsibility: Governance through a Conceptual Blockchain Framework

The objective of this paper is to analyse the feasibility and associated benefits of using blockchain technology for the management of corporate social responsibility (CSR) funds which have to be deployed in government-mandated areas of social sector development. The paper addresses the specific problems that exist in the current ways of managing CSR activities by comparing the current model to the proposed blockchain-based framework. The paper further goes on to show how this proposed method could bridge this gap in terms of accountability and transparency using blockchain-enabled technology, while at the same time increasing citizen involvement, i.e., pervasive participation, in the process.
Biased Render

This article explores the digitality of Indigenous bodies within contemporary 3D video games by mainstream and Indigenous developers. Its analysis relies on a critical examination of digital image synthesis via real-time graphics rendering, which algorithmically generates the visible world onscreen from 3D geometries by mapping textures, generating light and shadow, and simulating perceptual phenomena. At a time when physically based, unbiased rendering methods have made photorealistic styles and open-world structures common across AAA games in general, Indigenous game designers have instead employed simplified “low res” styles. Using bias as an interpretive model, this article unpacks how these designers critique mainstream rendering as a cultural-computational practice whose processes are encoded with cultural biases that frame the relation of player and screen body (avatar). The algorithmic production of digitally modeled bodies, as an essential but masked element of video games, offers a territory where Indigenous developers claim aesthetic presence in the medium.
Negative Effects of Complex Promotion Strategy in Online Shopping Evidence from Lab Experiment

Abstract This study discusses the negative Effects of the complex promotion strategy on consumers. Based on the dual-systems theory, we conducted lab behavioral experiments to obtain real decision data with Mouselab, a decision-making tracking technology. A sample of 116 students in Shaanxi Province participated in the experiment. The results show: (1) Under the complex promotion strategy, the quality of consumer decisions deteriorates. (2) Under the complex promotion strategy, the cognitive cost of consumers increases.
Employee Training and its Effectiveness among IT and ITES Employees of Bengaluru City

Information technology is the key sector of modern and digitalized India. The sector is considerably contributing towards the GDP of the nation. The IT sector offers numerous job offerings to the young and talented professionals. Teamwork and diversified work environment is predestined in any work environment. In this era IT industry is facing lots of changes and succession planning becomes most important. Knowledge transfer practices will help the employees in tactical decision-making, leadership and in technical expertise. Attrition rate need to be brought down in the industry. Training is the only solution for achieving productivity and improving employee performance. For this purpose, the author identified 6 important constructs of training based on existing literature and tried to explore the interrelationship and impact on effectiveness of training. Among all the assets, human asset is very important and precious too. Those companies who invest in human capital will alone survive in this dynamic and competitive business scenario. Improved training will reduce the staff attrition, trim down the miscommunication, cut down the redundant costs. Improved employee performance will be an empowered employee who needs less supervision and guidance. Findings of the study proved that there exists interrelationship between professional technical expertise, diversity, relationship building, leadership, teamwork and coaching. When an organization optimally executes these constructs, undoubtedly there will be enhanced performance and greater productivity.