Reviewerly/exHarmony huggingface dataset:
The Impact of Augmented-Reality Head-Mounted Displays on Users' Movement Behavior: An Exploratory Study

The augmented-reality head-mounted display (e.g., Microsoft HoloLens) is one of the most innovative technologies in multimedia and human-computer interaction in recent years. Despite the emerging research of its applications on engineering, education, medicines, to name a few, its impact on users' movement behavior is still underexplored. The movement behavior, especially for office workers with sedentary lifestyles, is related to many chronic conditions. Unlike the traditional screens, the augmented-reality head-mounted display (AR-HMD) could enable mobile virtual screens, which might impact on users' movement behavior. In this paper, we present our initial study to explore the impact of AR-HMDs on users' movement behavior. We compared the differences of macro-movements (e.g., sit-stand transitions) and micro-movements (e.g., moving the head) between two experimental modes (i.e., spatial-mapping and tag-along) with a dedicated trivial quiz task using HoloLens. The study reveals interesting findings: strong evidence supports that participants had more head-movements in the tag-along mode where higher simplicity and freedom of moving the virtual screen were given; body position/direction changes show the same effect with moderate evidence, while sit-stand transitions show no difference between the two modes with weak evidence. Our results imply several design considerations and research opportunities for future work on the ergonomics of AR-HMDs in the perspective of health.
A trust-based, multi-factor system for assessing the veracity of video files in the era of ‘deep fakes’ (Conference Presentation)

A technology for creating video files that purport to be of an individual speaking words he or she has never necessarily said has been developed. This technology, commonly known as ‘deep fakes,’ uses machine learning technologies to train a system with images of the prospective subject of a video and reconstruct a video based upon words spoken by another individual. As these videos are convincing and can have negative effects ranging from embarrassing a subject to interfering with elections to impacting national security, it is critical to identify ways to determine whether a prospective video is genuine or not. This paper proposes a system to evaluate a presented video file, based on multiple characteristics, and make a recommendation as to the confidence of the veracity of the file. From a technical perspective, it combines assessment of multiple details related to the audio and video stored in the file, as well as other file characteristics. Additionally, other inputs related to assessment of the content of the video, its impact and timing can be added to this technical confidence metric to have a combined single metric that characterizes trust in the video to support decision making related to it. Several examples are presented and assessed. The paper concludes with a discussion of the problems of nefarious fake videos, the impact of fakeness detection and future work in this area. In particular, the impact of identifying a video as a fake towards countering the impact of the nefarious video is considered.
Terrorist attack security and soldier health monitoring system

Nation security is dependent on its defense system. The army is one of the defense systems. In this days terrorism increases and it focuses on soldiers destruction to make countries' defense system weak. So, in this case, it is necessary to provide more security to military base station and soldiers. These all things keeping in mind this project is built. The project works for defending any unauthorized person to enter in the military area with Pi-camera, IoT server and wireless communication it will provide 24-hour security and attacks on military base station will be controlled. Along with this, sensors like heartbeat sensor and temperature sensor is used for daily fast routine checkup of soldiers
Commonsense Properties from Query Logs and Question Answering Forums

Commonsense knowledge about object properties, human behavior and general concepts is crucial for robust AI applications. However, automatic acquisition of this knowledge is challenging because of sparseness and bias in online sources. This paper presents Quasimodo, a methodology and tool suite for distilling commonsense properties from non-standard web sources. We devise novel ways of tapping into search-engine query logs and QA forums, and combining the resulting candidate assertions with statistical cues from encyclopedias, books and image tags in a corroboration step. Unlike prior work on commonsense knowledge bases, Quasimodo focuses on salient properties that are typically associated with certain objects or concepts. Extensive evaluations, including extrinsic use-case studies, show that Quasimodo provides better coverage than state-of-the-art baselines with comparable quality.
Theoretical Research on Task-driving Mode of the Educational Reform in Higher Vocational Colleges—A Case Study on “Engineering Structure and Calculation”

â€œEngineering structure and calculationâ€ is a basic specialized course of civil engineering class with strong focus on practices. Based on the analysis of the role of task-driven method in higher vocational teaching, This paper expounded the present situation and the basic ideas of task-driven approach, it put forward the use through the general task design, applying mission design principles, analysis, lay out, implementation and completion with task-driven teaching, the analysis shows that the application of task-driving method in the teaching of â€œEngineering structure and calculationâ€, you can give students a clear teaching objectives, with a learning task, students and teachers through the design task, task analysis, task completion, summarizing, evaluating the four steps to consolidate professional knowledge, centering around students and fully mobilizing the enthusiasm of the students, good teaching results will been achieved.
NameCheap Hosting Review: Expert Opinion, Pros & Cons (2019)

Namecheap started its life in 2000 as a place to get domain names, but they have developed and expanded their offerings on that front continuously since then. And in 2007, they also added web hosting services. Today, they provide one of the most comprehensive ranges of web hosting plans available. This Namecheap hosting review is meant to help you get a better sense of those web hosting services.
Penerapan model e-learning berbasis website kalase dalam meningkatkan hasil belajar media pembelajaran pada mahasiswa Pendidikan Teknologi Pertanian

Kalase website-based e-learning distribution model aims to determine the strategies for implementing E-Learning-based models in the subject of Learning Media in the Agricultural Technology Education Study Program, Faculty of Engineering, Makassar State University. This study aims to find out the student learning outcomes by applying the E-Learing model based on the Kelase Website on Learning Media in the Agricultural Technology Education Study Program Faculty of Engineering, Makassar State University. The method used in data collection is by conducting observations, tests and producing descriptive data. The results achieved in this study are the increase in learning outcomes for Grade 02 students in the Agricultural Technology education program at the Faculty of Engineering, Makassar State University, on the subject of learning media.
Product Review Summarization for E-Commerce Site Using Gibbs Sampling Based LDA

In E-Commerce, Reputation-based trust models are important for business development.Webbased business site turns out to be increasingly important in our daily life because of data given by it.Seventyfive percent of individuals are using it for purchasing on the web and this figure is increasing exponentially.The buyer reviews on various products are growing day-by-day.Hence, the quantity of client reviews on different items is expanding.These huge quantities of reviews are helpful to manufacturers and customers alike.It is a stimulating task for an individual customer to read all product review to plan a better placement of the product and hence guide the customer in making a better buying decision.This framework is an electronic application where the client will view and buy different items on the web; the client can give feedback about the items and the experience on the whole for the internet shopping site.The System takes opinions of different users and dependent on the view, the framework will indicate the appropriateness of the items and organizations given by the E-business enterprise.The proposed work includes a multidimensional trust model for calculating trust scores from client's review.To implement this Modified LDA algorithm for mining dimensions of e-commerce feedback comments is used.In this proposed work NLP and opinion mining methods are used.This paper also includes the comparison based on accuracy, time complexity, trust score evaluation, sellers trust score and their ratings using Gibbs-sampling that creates various categories for feedback and assigns trust score
AN ERROR ANALYSIS OF SIMPLE PAST TENSE IN WRITING RECOUNT TEXT BY THE TENTH GRADE STUDENTS OF SMA NEGERI 2 DOLOKSANGGUL

The purpose of this study is to describe the errors in simple past tense of recount text. In addition, this study is also aimed to describe the causes of those errors. This study apllied the descriptive qualitative approach of which the data were obtained from the recount texts that were written by the tenth grade students of SMA Negeri 2 Doloksanggul. The data were collected by using students’ recount texts and interview. The data then were analyzed by identifying the errors first, then describing the errors, and the last explaining the errors. The errors that occurred in students’ recount text are error of omission, error of mis-formation, error of addition and error of mis-ordering. The result of the study indicates that the students made 893 of simple past tense errors which were 0,45% errors of misordering, 3,58% errors of addition, 30,12% errors of omission, and 65,85% errors of mis-formation. The dominant type of errors made by the student is errors of mis-formation. The students’ errors were caused by 36,17% intralingual interference, 58,23% interlingual interference, and 5,6% communication strategies.
The experiment is just as important as the likelihood in understanding the prior: A cautionary note on robust cognitive modelling

Cognitive modelling shares many features with statistical modelling, making it seem trivial to borrow from the practices of robust Bayesian statistics to protect the practice of robust cognitive modelling. We take one aspect of statistical workflow-prior predictive checks-and explore how they might be applied to a cognitive modelling task. We find that it is not only the likelihood that is needed to interpret the priors, we also need to incorporate experiment information as well. This suggests that while cognitive modelling might borrow from statistical practices, especially workflow, care must be made to make the adaptions necessary.
Process for Handling Non-Major Revisions to Existing RFCs

This document discusses mechanisms the IETF has historically used forupdating RFCs subsequent to their publication, and outlines an updatedprocedure for publishing newer versions (colloquially known as bisversions) that is appropriate in certain circumstances. Thisprocedure is expected to be easier for both authors and consumers ofRFCs.
Can steady-state Schr\"oinger cats survive in subharmonic generation with anharmonic nonlinearities?

We discuss general properties of the equilibrium state in superconducting quantum circuits with anharmonic nonlinearities and detunings, in the nonlinear regime. By comparing moments of the steady state and those of a Schroinger cat, we show that true Schroinger cats cannot survive in the steady state if there is a single-photon loss. A delta-function `cat-like' steady-state distribution can be formed, but this only exists in the limit of extremely large nonlinearity. In general, the steady state is a mixed state whose purity is reduced by driving.
Geometric Laplacian Eigenmap Embedding.

Graph embedding seeks to build a low-dimensional representation of a graph G. This low-dimensional representation is then used for various downstream tasks. One popular approach is Laplacian Eigenmaps, which constructs a graph embedding based on the spectral properties of the Laplacian matrix of G. The intuition behind it, and many other embedding techniques, is that the embedding of a graph must respect node similarity: similar nodes must have embeddings that are close to one another. Here, we dispose of this distance-minimization assumption. Instead, we use the Laplacian matrix to find an embedding with geometric properties instead of spectral ones, by leveraging the so-called simplex geometry of G. We introduce a new approach, Geometric Laplacian Eigenmap Embedding (or GLEE for short), and demonstrate that it outperforms various other techniques (including Laplacian Eigenmaps) in the tasks of graph reconstruction and link prediction.
Machine Learning based English Sentiment Analysis.

Sentiment analysis or opinion mining aims to determine attitudes, judgments and opinions of customers for a product or a service. This is a great system to help manufacturers or servicers know the satisfaction level of customers about their products or services. From that, they can have appropriate adjustments. We use a popular machine learning method, being Support Vector Machine, combine with the library in Waikato Environment for Knowledge Analysis (WEKA) to build Java web program which analyzes the sentiment of English comments belongs one in four types of woman products. That are dresses, handbags, shoes and rings. We have developed and test our system with a training set having 300 comments and a test set having 400 comments. The experimental results of the system about precision, recall and F measures for positive comments are 89.3%, 95.0% and 92,.1%; for negative comments are 97.1%, 78.5% and 86.8%; and for neutral comments are 76.7%, 86.2% and 81.2%.
Talking About the Prospect of Value Internet

The emergence of Bitcoin may not only bring about a financial revolution, but also bring about a brand new industrial revolution. The value of the Internet is the value of the Internet (digital currency or commodity) based on the blockchain agreement, forming a value interconnection chain, realizing the true reflection and transparent transfer of the Internet value. The article will focus on the concept and characteristics of the value Internet, and talk about the prospects of the value Internet, and strive to provide some reference and reference for the value Internet field.
Deep Learning Applications in Mobile Networks

The expected deployment of 5G networks, growing percentages of mobile networks' market penetration levels and increasing popularity of mobile applications induce new challenges and requirements for mobile network operators.One of the ways of tackling these new challenges is the deployment of advanced machine learning techniques in hopes of handling expected traffic volumes, performing real-time analytics and managing network resources.The paper presents the aspects of mobile networking in which deep learning methods can be implemented.After presenting the basic background and modern deep learning techniques and related technologies, paper presents an overview of the current advances made in these research areas.The paper also identifies the fields within the realm of mobile networking that show particular potential for new exploration.
Hybridized Particle Swarm Optimization for Constrained Problems

This paper presents hybridized implementation of the well-known particle swarm optimization algorithm that belongs to the family of swarm intelligence metaheuristics.The proposed approach was adapted for tackling constrained optimization problems.With the basic goals to enhance the converge of the algorithm and to improve the exploitation -exploration tradeoff, the mechanism that replaces exhausted solutions from the population with randomly generated solutions from the search domain was adopted from the artificial bee colony approach.Proposed metaheuristic was tested on standard constrained engineering benchmark, and comparative analysis with other state-of-the-art algorithms was conducted.Empirical results obtained from practical simulations proved that the hybridized particle swarm optimization for constrained problems is able to successfully tackle this type of NP hard challenges.
A Study on Literary Reading Education Contents as Social Practice

본고는 문학 독서와 실천의 관계를 살펴, 문학 독서의 실천적인 특성을 짚어보고, 그를 통해 문학 독서의 사회적 실천으로서의 특성과 그 과정에 대한 구체적 논의를 하는 것을 목표로 하였다. 이는 문학 독서를 사회적 실천과는 거리가 먼 행위로 인식하는 관점에 대한 반성적 연구이며, 문학 독서가 다양한 방식으로 개인과 사회의 행복에 기여할 수 있다는 것을 논의하고자 하는 바이다. 독자는 독서 과정에서 작품을 해석하는 동시에 자신이 속한 세계를 해석하고 나아가 자신의 사회적 신념이나 그 신념에 의한 실천 능력을 획득하고 형성하는 사회 문화적 실천을 한다. 이는 사회 · 문화적 관점으로 바라본 문학 독서인데, 맥락화의 원리, 수용 맥락탐구의 원리, 수용 맥락 간 대화화의 원리, 맥락 변형의 원리로 구성된다. 본고에서는 이러한 이론을 재개념화하고 신재효본 〈퇴별가〉를 대상으로 하여 신재효의 〈토끼전〉에 대한 독서를 사회적 실천 행위로서 파악하고자 하였다. 그 결과 중인으로서의 계층적 정체성 인식 및 이본에 대한 사회 문화적인 탐구, 기존의 〈토끼전〉해석과의 대화 끝에 〈퇴별가〉로 다시 쓰는 과정을 재구할 수 있었다. 이어서, 이와 같은 사회적 실천 행위로서 문학 독서의 교육 내용을 읽기 과정 중의 동의하기와 비판하기, 읽기 후의 은폐하기와 부각하기로 구안하였다. 문학 독서를 통한 사회적 실천의 교육 내용에 대한 구체적 논의를 이끌어 내었다는 데에 연구의 의의가 있다.This paper examines the relationship between literary reading and practice through which, I demonstrate the practical characteristics of literary reading. Herein, we aim to discuss the nature of reading as a social practice and conduct a concrete discussion on the process. This is a reflective study on the view that literary reading is distinct from social practice and can contribute to the happiness of individuals and society in various ways. The reader interprets a given work during the process of reading and interprets the world to which he belongs accordingly. He or she then acquires and forms his or her social beliefs and practical ability based on those beliefs. This constitutes a socio-cultural practice and is referenced as literary reading when viewed from a socio-cultural perspective, comprising the principles of contextualization, exploratory context inquiry, dialogue between receptive contexts, and contextual transformation. In this paper, we endeavored to reexamine these theories and understand Shinjae Hyo’s reading as an act of social practice for sinjaehyobon “Toebyeolga”. As a result, we were able to reconstruct the process of rewriting as “Toebyeolga” after dialogue with the recognition of hierarchical identity as middle people and a socio-cultural exploration of the preface and interpretation of the existing “Tokkijeon”. Then, as a social practice such as this, the education contents of literary reading were designed by agreeing and criticizing during the reading process, and concealing and highlighting after reading. It is significant that the study led to a specific discussion on the contents of social practice through literary reading. of the existing “Tokkijeon”. Then, as a social practice such as this, the education contents of literary reading were designed by ‘agreeing’ and ‘criticizing’ during the reading process, and ‘concealing’ and ‘highlighting’ after reading. It is significant that the study led to a specific discussion on the contents of social practice through literary reading.
Oracle Cloud Overview

As a CXO, you are looking for a cloud-based solution that should be able to store data efficiently, manage it with ease, and transact huge quantities of data, whether it is transactional data, a data warehouse, or from MIS, in a highly secure, performant, and cost-effective manner.
Edge Disjoint Caterpillar Realizations

In this paper, we consider the edge disjoint caterpillar realizations of tree degree sequences. We give the necessary and sufficient conditions when two tree degree sequences have edge disjoint caterpillar realizations. We conjecture that an arbitrary number of tree degree sequences have edge disjoint realizations if every vertex is a leaf in at most one tree. We prove that the conjecture is true if the number of tree degree sequences is at most $4$. We also prove that the conjecture is true if $n \ge \max\{22k-11, 396\}$, where $n$ is the number of vertices and $k$ is the number of tree degree sequences.
Content analysis &amp;amp; anonymization made simple

Imagine the world of possibilities where all information would be easily findable and usable without the burden of copyrights, privacy issues or sensitive information. We at the Digitalia research center at the South-Eastern Finland University of Applied Sciences have elaborated on this issue further. Copyright issues we of course cannot affect due to legislation, but in our recent paper [4], we discussed the hidden information that could be unleashed by using a simple ocr with content analysis. Now we will go further by enhancing the content detection and including an anonymization in our service repertoire. We will also focus on making these services more easily usable by the interested community with the development of REST API. .
An analysis on data curation using mobile robots for learning tasks in complex environments

Commercial Artificial Intelligence (AI), e.g., the self driving car industry, is often used in predictable settings, with structured surroundings. Significant AI and Machine Learning (ML) progress, particularly in visual perception, has been made in these settings with the use of large publicly available datasets. However, there still exists a prevalent domain mismatch between this data and military relevant environments. In this work we begin to analyze the importance of mobile robot platform design and heterogeneity to effectively collect data more representative of the military domain. The framework of our research is rooted in the importance of expressing constantly changing, yet repeated conditions, with disadvantageous lighting and perspectives in highly unstructured environments.
SEARCHING SIMILAR OF PAINT COLOR BASED ON RGB AND HSV SPECTRUM USING K-MEANS METHOD

Currently the community in determining the desired paint color choice still manually searches by selecting the drawings one by one in the manual paint catalog, the more color choices available in the catalog take a long time to determine the desired color choice. This research replaces the search manually by looking at the catalog with a computer based system. Similar paint color search uses image processing, ie reading the intensity of the Red, Green, Blue (RGB) value of the image, the value of the RGB is then calculated to get the HSV value, so as to get the RGB and HSV features as the input calculation method kmeans clustering, the data used as training data obtained from dulux wall paint catalog of 317 data. The results in this study average data can be grouped into 11 groups and 15 iterations, also calculated by a method to check the cluster validity of Davies Bouldin Index (DBI) sebanya 3 times the experiment got an average value of 0879. Keywords: Image, RGB, HSV, K-means, color, paint