Reviewerly/exHarmony huggingface dataset:
Best practices for TLS Downgrade

Content providers delivering content via CDNs will sometimes delivercontent over HTTPS (or both HTTPS and HTTP) but configure the CDN topull from the origin over cleartext and unauthenticated HTTP. From theperspective of a client, it appears that their requests and associatedresponses are delivered over HTTPS, while in reality their requestsare being sent across the network in-the-clear and responses aredelivered unauthenticated. This exposes user request data to pervasivemonitoring [RFC7258]; it also means response data may be tampered withby active adversaries. Terminating TLS connections on a load balancerand contacting a backend over cleartext has long been common withindata centers, but doing this TLS termination and downgrade to HTTP ata CDN introduces additional risk when the unprotected traffic is sentover the general Internet, sometimes across national boundaries.While it would be nice to say never do this, customer demand,content provider use-cases, and market forces today make it impossiblefor CDNs to not support downgrade. However, following a set of bestpractices can provide visibility into when this is happening and canreduce some of the risks.
Study on the Control Method of Temperature and Humidity Environment in Building Intelligent System

Due to the difficulty of establishing the accurate control model for building an intelligent system, a neural network predictive control method is proposed, in this paper, based on a weed optimization algorithm. Through considering indoor temperature and relative humidity environment factors, a control model of temperature and humidity environment is first established in an intelligent building. Then, the hidden layer nodes center of the RBF neural network is optimized by using the weed optimization algorithm. The above mentioned work focuses on improving the shortcomings of Orthogonal Least Squares (OLS) algorithm, and simultaneously simplifies the network architecture. The simulation results show that the RBF neural network predictive control method based on the weed optimization algorithm has better approximation ability and generalization ability contrasting with the OLS algorithm.
Local Uniqueness Under Two Directions in Discrete Tomography: A Graph-Theoretical Approach

The goal of discrete tomography is to reconstruct an image, seen as a finite set of pixels, by knowing its projections along given directions. Uniqueness of reconstruction cannot be guaranteed in general, because of the existence of the switching components. Therefore, instead of considering the uniqueness problem for the whole image, in this paper we focus on local uniqueness, i.e., we seek what pixels have uniquely determined value. Two different kinds of local uniqueness are presented: one related to the structure of the directions and of the grid supporting the image, having as a sub-case the region of uniqueness (ROU), and the other one depending on the available projections. In the case when projections are taken along two lattice directions, both kinds of uniqueness have been characterized in a graph-theoretical reformulation. This paper is intended to be a starting point in the construction of connections between pixels with uniquely determined value and graphs.
Multimedia Software Engineering Methodology: A Systematic Discipline for Developing Integrated Multimedia and Software Products

There are strong demands for integrating various digital multimedia products such as 2D and 3D images, models, and animations in the development of software applications. Many software engineering methodologies provide a structured discipline that explicitly specifies how to develop software applications in details. However, there is a lack of a methodology like software engineering methodologies that explicitly specifies how to develop multimedia products as well as how to integrate them with existing software engineering methodologies. This research proposes a multimedia software engineering methodology. Our methodology exploits the engineering discipline of the current software engineering methodologies and integrates the phases of multimedia production with them. This methodology might be considered as a generic process for multimedia products development which provides a guideline for undergraduate students on how to develop their own graduation projects. Moreover, specialists can adapt and use it according to their business needs.
설득적 글쓰기에 나타난 고등학생 필자의 자료 활용 특징 분석

The purpose of this study is to investigate the differences in selecting and using the source Contents by levels on persuasive writing by high school students.In this study, we extracted key words from source text and student writing, We analyzed the selecting of the source contents through the degree centrality and the cohesiveness of the texts through the component analysis. In addition, we examined patterns of utilizing the source Text in persuasive writing through sentence transformation in the argument structure. The results of the study are as follows.First, The selecting of the source contents in the source Text varies by level. Second, The using of the source Text varies by level. Third, There are differences in the way in which the information selected from the source Text is converted into the argumentative structure of persuasive writing.This study focuses on the selecting and using of information after high school students read the source considering the context of the situation from a single source Text. This study can contribute to the study of high school students'' information processing and semantics. meaning construct ability.
Teleportation algorithm settled in a resonant cavity using non-local gates

This work presents the implementation of teleportation algorithm inside of a two-mode magnetic resonant cavity using non-local gates. Process can be grown easily to larger states than the single-qubit case shown here.
이공계 대학 융합 교육의 한계와 가능성 탐색

The purpose of this study is to discuss the current status and limitations of convergence education in universities and to explore new possibilities...
Blockchain for Trusted Future

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Demonstration of Einstein-Podolsky-Rosen Steering via Enhanced Subchannel Discrimination

We designed a feasible collection of subchannels for a quantum channel and experimentally demonstrated the corresponding subchannel discrimination task where probabilities of correct discrimination are clearly enhanced by exploiting steerable states with the optical system.
GEO GAMES “RUSSIA ONLINE”: CONSCIOUSNESS OF IDENTITY BY MEANS OF DIGITAL TECHNOLOGIES

The article describes the technology of developing and conducting geo games aimed at developing teenagers’ digital competence and consciousness of civic identity. Recommendations for creating and conducting an educational quest are presented. Step-by-step work with the Google Maps service is described. The results of the project are analyzed.
New Help for the Sightless

Duke Lumsden operates a candy shop in Tacoma, Wash. Duke is blind, yet he has no trouble differentiating between the values of currency he handles in the course of business. He is aided by a spinoff from space-developed optical-electronic scanning technology known as the Paper Money Identifier. The PMI is manufactured by EMR Ltd., Los Angeles. It's not distinguishable by the human eye, but each denomination of American currency has a unique distribution of colors. This fact enables the PMI to tell the difference between different denominations of paper money. The device, the size of a cigarette pack, emits a narrow beam of invisible infrared light. This beam reacts to the reflectivity of the colors on the bill and causes an oscillator to generate an audible signal. As Duke passes his PMI lengthwise along the back of a bill, he hears a distinctive series of tones that identifies each denomination. Duke Lumsden is very pleased with the paper money identifier, which he got through Tacoma's Technology Transfer Center. He not only handles paper money with ease, but he has discovered another use for the device. Before receiving the PMI, he had difficulty operating his tape recorder because he couldn't determine which track the tape was using; now his PMI tells him, by reacting to the different colors on the switch button light.
Aircraft Type Identification Using Reinforcement Active Learning

As a subclass of Automatic Target Recognition problem, Automatic Aircraft Recognition plays an important role in air traffic management and modern battlefield for automatic monitoring and detection. The research on Automatic Aircraft Recognition is still in the exploratory stage. Since aircrafts move at high speeds in complex background, it is still a challenging task of fast data processing and accurate aircraft type recognition. Besides, active learning has recently attracted many researcherâ€™s interesting. Based on this, we employ a learning-based approach which combines active learning with reinforcement learning to learn how and when to request labels for the aircraft type recognition problem. The experimental results show that the model can achieve a good prediction accuracy with few label requests.
Library Guides: ENG 2 - Stoepker: I need a book or an electronic book

This guide is designed to assist Professor Stoepker's ENG 2 Students in completing their research projects. I need a book or an electronic book . . .
Logical Problem Solving Framework

We propose Logical Problem Solving Framework (LPSF), an axiomatic structure for generating methods of logical problem solving. Input parameters of LPSF consist of (1) a canonical logical structure, (2) a set of equivalent transformation rules (ET rules), (3) a control, and (4) an answer mapping. Given these input parameters, LPSF provides a logical problem solver, which receives an original problem, sets an initial state in a formula on the logical structure, makes a computation path, and if the computation path reaches the domain of the answer mapping, it outputs an answer, which is guaranteed to be correct. By taking input parameters such as KR-Logic, a set of extended clauses obtained through meaning-preserving Skolemization, ET rules including unfolding in the extended clause-set space constructed on KR-Logic, we can solve, with strict guarantee of correctness, a larger class of logical problems, compared to conventional methods.
Evolution of Generic Programming in OOPLs

Generic Programming enables program constructs to be reused in a variety of situations. In programming languages, idea of generic programming is being opted through a variety of generic mechanisms. Generic mechanisms are either directly applied to pre-existing language constructs or it provides its own components for generic implementation. In this paper, we present such generic mechanisms in an organized way such that it appears as "one mechanism intensify other". Our aim is to exhibit generic evolution among mainstream object oriented programming languages (OOPLs). Hence, we analyze such approaches for better expressiveness and type-safety of generic programming as they evolved in OOPLs. This brief review article will help developers and researchers to precisely understand the generic mechanism in mainstream OOPLs.
Transformational leadership on follower's creativity: an empirical study

Purpose: This study is an investigation into relationship between transformational leadership and innovation at the organisational level and creativity at the individual level as an empirical study in the public sector in the Kingdom of Saudi Arabia (KSA). A survey instrument was adapted to obtain the data from different organizations. A Self administrated questionnaire was distributed to employees randomly selected from a public organisation. The final sample of 503 was selected for the study analysis. The results show that transformational leadership is positively and significantly correlated to the follower's creativity and organisational innovation. In addition, the relationship between the transformational leadership and follower's creativity through the mediating role of employee psychological empowerment, support for innovation, workplace relationship, and employee learning were found positive and significant. This research provides supportive insights into the state of transformational leadership for field experts, policy makers, and administration of the public organizations especially from the Gulf countries.
Time/frequency high-dimensional entanglement via engineered parametric downconversion

We introduce and experimentally benchmark a new scheme for generating frequency-entangled photon pairs in engineered parametric downconversion processes. We discuss how this technique can be used to easily generate high-dimensional entangled bi-photon states.
UMP creating excellence together with the industry to empower entrepreneurial activity

In facing the year 2019, Universiti Malaysia Pahang (UMP) will continue to create excellence and dynamism in fulfilling its vision on becoming the leading technology university.
User Behaviour Analysis and Personalized TV Content Recommendation

Nowadays, there are many channels and television (TV) programs available, and when the viewer is confronted with this amount of information has difficulty in deciding which wants to see. However, there are moments of the day that viewers see always the same channels or programs, that is, viewers have TV content consumption habits. The aim of this paper was to develop a recommendation system that to be able to recommend TV content considering the viewer profile, time and weekday. For the development of this paper, were used Design Science Research (DSR) and Cross Industry Standard Process for Data Mining (CRISP-DM) methodologies. For the development of the recommendation model, two approaches were considered: a deterministic approach and a Machine Learning (ML) approach. In the ML approach, K-means algorithm was used to be possible to combine STBs with similar profiles. In the deterministic approach the behaviors of the viewers are adjusted to a profile that will allow you to identify the content you prefer. Here, recommendation system analyses viewer preferences by hour and weekday, allowing customization of the system, considering your historic, recommending what he wants to see at certain time and weekday. ML approach was not used due to amount of data extracted and computational resources available. However, through deterministic methods it was possible to develop a TV content recommendation model considering the viewer profile, the weekday and the hour. Thus, with the results it was possible to understand which viewer profiles where the ML can be used.
Community by Design: Prioritizing the Factors that Drive Knowledge Use in Online Question &amp; Answers Platforms

The question of how knowledge assets are utilized in the context of online communities is the primary impetus of this research. Using a multilevel approach, this paper investigates factors that influence the use of knowledge in an online question and answer platform (OQA). It focuses on three levels including informational, individual, and community, and reviews interactions across each level. The study tests the multilevel model with data from StackOverflow.com, a renowned online community for programmers to exchange knowledge assets, especially questions and answers about coding issues. Traditional hierarchical regression analysis proved insufficient to explicate the complexity associated with human decision-making processes with respect to asset utilization. However, a machine learning technique with a Chi-square automatic interaction detection algorithm provided a richer understanding of the relative importance of factors and their thresholds for influencing knowledge asset use.
Pengaruh Gaya Belajar dan Pemanfaatan Internet terhadap Motivasi Belajar Mata Kuliah Akuntansi Keuangan Syariah pada Mahasiswa Pendidikan Akuntansi Fakultas Keguruan dan Ilmu Pendidikan Universitas Muhammadiyah Surakarta Tahun 2018/2019

The purpose of this study was to determine: 1) the influence of learning styles on student learning motivation. 2) the influence of internet usage on student learning motivation. 3) the influence of learning styles and the use of the internet on student learning motivation. This research conducted a quantitative approach with survey research design. The population in this study were all students of the Accounting Education Study Program FKIP-UMS who took the course of Islamic Financial Accounting in 2018/2019 which amounted to 299 students. The sample was taken as many as 45 students with area random sampling proportional technique. The data collection techniques was questionnaires. The data analysis technique conducted multiple linear regression analysis. Result of regression analysis regression equation Y = 43,100 + 0,55X1 + 0,022X2. The equation shows that student learning motivation is influenced by learning styles and internet use. Based on the analysis and discussion it could be concluded that: 1) learning styles has a significant effect on student learning motivation. 2) the use of the internet effected on student learning motivation but not significant. 3) learning styles and internet usage simultaneously affected the students learning motivation. 4) Effective contribution of learning style variables of 31.75% and internet utilization of 0.65%. So the total effective contribution of both variables is 32.4%, while the remaining 67.6% the rest influenced by other variables not examined by the author.
Exploring the meaning of project science activities using local environment

본 연구의 목적은 유아들의 생활에 기반이 되는 지역 환경을 활용한 프로젝트 과학 활동을 실시하고 유아와 교사에게 주는 의미를 분석하여 과학교육의 실천적 방향을 탐색해보는 것이다. 이를 위해 실행연구 방법을 활용하여 연구자와 교사가 협력하여 D시에 위치한 공립단설유치원 유아 28명을 대상으로 지역 환경을 활용한 프로젝트 과학 활동을 실시하고, 수업녹화영상, 수업일지, 연구일지, 교사 저널을 통해 그 의미를 분석해 보았다. 연구 결과, 지역 환경을 활용한 프로젝트 과학 활동의 의미는 다음과 같다. 지역 환경을 활용한 프로젝트 과학 활동이 유아에게 주는 의미는 ‘공동의 관심사 탄생’, ‘자연스럽게 이어지는 과학적 탐구’, ‘지켜주고 싶은 자연’으로 범주화 되었다. 지역 환경을 활용한 프로젝트 과학 활동이 교사에게 주는 의미는 ‘생활과 교육과정의 통합’, ‘지속적 탐구와 몰입을 이끄는 과학적 탐구과정’, ‘가정과의 연계를 통해 확장된 과학적 탐구’로 범주화 되었다. 결론적으로 유아의 생활을 기반으로 지역 환경을 활용한 프로젝트 과학 활동은 유아의 과학적 탐구와 지역 자연에 대한 긍정적 태도 형성에 도움이 되었으며, 이를 통해 교사는 의미 있는 과학교육의 실천을 경험하는 기회를 가질 수 있었다고 결론지을 수 있다.The purpose of this study is to explore the practical direction of science education by analyzing the meanings of project science activities using the local environment based on the lives of young children, and giving them to young children and teacher. For this purpose, researcher and teacher collaborated using the action research methodology to conduct project science activities with 28 local children in public kindergarten located in D city, and tried to analyze the meaning through class recording video, classes diary, research journal, and teacher journal. As a result of the study, the meaning of the project science activities using the local environment are as follows. The meaning of project science activities using the local environment for children have been categorized as the creation of common interests , natural pursuit of scientific inquiry , and nature that we want to protect . The meaning of project science activities using the local environment for teacher were categorized as integration of life and curriculum , scientific inquiry process leading to continuous inquiry and immersion , and scientific inquiry expanded through linkage with home . In conclusion, it can be concluded that young children could develop positive attitude toward science inquiry and local nature, and teacher had opportunity to experience meaningful science education practice by project science activities using local environment.
Self-Predicting Boolean Functions

A Boolean function $g$ is said to be an optimal predictor for another Boolean function $f$ if it minimizes the probability that $f(X^n)=g(Y^n)$ among all functions, where $X^n$ is uniform over the Hamming cube and $Y^n$ is obtained from $X^n$ by independently flipping each coordinate with probability $\delta$. This paper is about self-predicting functions, which are those that coincide with their optimal predictor.
A Distributed Multi-source Feature Selection Using Spark

Feature selection is one of the key problems in data pre-processing because it brings the immediate effects on the data mining algorithm. Using high-dimensional data sets, we can describe the data based on multiple sources, which corresponding to different knowledge sources. Multi-source feature selection is another topic relevant with large-scale data. Learning and selecting features from multiple data sources is becoming more common and much needed in many real-world applications. In this work, we propose a new multisource feature selection method based on traditional filters where data sources contain the same set of instances but different sets of features. This method is implemented using Spark as a powerful parallel framework for large-scale data processing. Conducted experiments approve the effectiveness of our approach in terms of execution time and where the classification accuracy is maintained.
Nondestructive, Noncontact Quantification of Carbon Fiber Alignment and Orientation By High-speed Microwave Ellipsometry

Novel short-fiber composites facilitate the manufacture of tailorable feedstock for small formed parts. In these composites, the alignment and orientation of the short fibers must be controlled to achieve the desired composite properties. While there are several processing variables that can be correlated to fiber alignment and orientation, there is a need for a fast, nondestructive, noncontact measurement technique to quantify local alignment and orientation in real time. Such a technique would enable real-time control of processing variables, resulting in higher quality composites. Here, we propose high-speed microwave ellipsometry as such a technique. To evaluate our approach, we measured five short-fiber composites samples made from a four-layer stack of carbon-fiber mats. These samples included one known control sample and four blind samples that were unknown at the time of testing. The four blind samples were known to be either a control, a sample with all layers rotated by 5°, a sample with a single unknown layer rotated by 5°, or a sample with a single unknown layer rotated by 15°. In this paper, we present our results demonstrating the effectiveness of this technique and discuss a path for real-time, large-scale imaging of fiber alignment and orientation.
Reasons, argumentation and justification : DEON 2016 special issue

Special issue of the *Journal of Logic and Computation*, edited by Olivier Roy, Allard Tamminga and Malte Willer