Reviewerly/exHarmony huggingface dataset:
Design and Development of Constructivist Web-Based Learning Environment with Augmented Reality to Enhance Critical Reading for First-Year Information Technology Students of Two-Year College in Cambodia

The purpose of this research is to design and develop of the constructivist web-based learning environment with augmented reality to enhance critical reading for first-year information technology students of two-year college in Cambodia. The design and development research model is employed in this study [11]. The research procedure consists of four main steps: (1.) document analysis and examination of learning and teaching context, (2.) examining and analyzing the related principles and theories such as learning theory, Constructivist theories, critical reading, media theory, and technology (3.) synthesizing of the theoretical framework based on the reviewed principles and theories, (4.) synthesizing design framework for the constructivist web-based learning environment to enhance critical reading based on the theoretical framework. The participants of this study consisted of seven experts. The result of this study who that there are six basic elements of the theoretical framework includes (1) psychological base, (2) pedagogical base, (3) contextual base, (4) critical reading base, (5) media theory base, and (6) technological base. The designing framework has four mains components as following: (1.) the activation of cognitive structure and critical reading enhancement, (2.) the enhancement of cognitive equilibrium, (3.) the enhancing of knowledge construction and critical reading, and (4.) the enhancement and support of knowledge construction, and the designing frameworks has 7 elements as following: (1.) Problem base, (2.) Learning resources center, (3.) Collaboration center, (4.) Cognitive tools, (5.) Critical Reading center, (6.) Scaffolding, and (7.) Coaching center.
Visual Object Tracking Using Perceptron Forests and Optical Flow

This work proposes a new approach for target representation and candidate proposal selection to track single objects in videos. Constructing an appearance model that is robust to visual appearance changes is a challenging problem in visual tracking. Typically, complicated models are used to achieve this robustness. However, such models have high computational cost and thus, are not suitable for real-time tracking. In this paper, we propose a visual tracking algorithm in which target objects are represented by compact low-dimensional codes, constructed using perceptron forests. We employ the highly successful tracking-by-detection framework to use these representations for training an online discriminative classifier to separate the object from the background. Moreover, the candidate proposals are generated from a two-phase strategy. First, we employ dense optical flow to estimate the geometric transformation undergone by the objects to generate one set of proposals. These proposals are used to initialize a particle swarm optimization framework which localizes the objects in the current frame. We integrated our algorithm with the VOT 2016 toolkit and report its performance compared to several state-of-the-art trackers.
Compeleted Participatory Mapping of Village Based on WebGIS

In order to make the land registration, it's required the land database information in the form of a basic map that contain information about the land, that has subjects, objects and other information.The development of land database can create the Government Policy that be a National Map as known as One Map Policy.The development of based online Geographic Land Information System Application (WEBGIS) is done by establishing the land database, starting with the preparation of data that be the land that has been given identification number and the collecting the textual data, then combined and forming the land database within the scope of one village. The development of WEBGIS focuses on the development of better spatial data by involving the active role of the village I offices by optimizing the empowerment of youth organization of the village. The community acts as a land data taker or land data information giver using Geojot+ Geotagging based on android and Ios- application. Spatial data and textual data are integrated using the application. The processing Spatial data is using AutoCAD applications, textual data using Geojot Core., and then will be integrated with ARCGIS with the addition of attributes based on Geojot Core data. The Using of WEBGIS Applications for village offices and their usefulness for land and village government offices. The goal is to create better land administration between agencies so will be formed one map policy. And as a consideration in the proposal draft of Village Bill, in order to make transition of land have report to the village officers.
Discussion and Practice on Teaching Innovation of the Fundamental of Programming

The Fundamental of Programming; Whole process evaluation; Project driven; Teaching innovation
Instructed late binding

Integration of a decentralised pattern matching is a technique that enables a recent solution to the Expression Problem. The single former implementation of this technique was in Scala. In this paper, we highlight the C++ implementation of the same technique to solve the Expression Problem in C++. Unlike the former implementation which relies on stackability of Scala traits, this new implementation relies on compile-time metaprogramming for automatic iterative pointer introspection at runtime. That iteration enables late binding using overload resolution, which the compiler is already capable of. The C++ implementation outperforms the Scala one by providing strong static type safety and offering considerably easier usage.
Text Based Shuffling Algorithm in Digital Watermarking

With the increasing image file size from megabyte to gigabytes, sequential Fisher-Yates shuffling algorithm step became slower and needed huge amount of memories to allocate. When allocating large megapixels index to memory array at the run time of standard personal computer, it is corrupted and existed unexpectedly because of the memory overflow problem. So, Fisher-Yates shuffling algorithm is not suitable for loading massive pixels at small memory buffer size computer in new LSB-based Steganography method. In this paper, the Text based shuffling algorithm is proposed using only necessary pixels of image according to the length of input text to solve that problem. This significantly provides the output result with faster performance in run time even running the encryption part in sequential. Moreover, the proposed algorithm does not infect the visual quality of an image even replacing the pixel selection step of a New LSB-based framework.
Variable-Length Intrinsic Randomness on Two Performance Criteria Based on Variational Distance

This paper investigates the problem of variable-length intrinsic randomness for a general source. For this problem, we can consider two performance criteria based on the variational distance: the maximum and average variational distances. For the problem of variable-length intrinsic randomness with the maximum variational distance, we derive a general formula of the average length of uniform random numbers. Further, we derive the upper and lower bounds of the general formula and the formula for a stationary memoryless source. For the problem of variable-length intrinsic randomness with the average variational distance, we also derive a general formula of the average length of uniform random numbers.
Authentication Model Based on JWT and Local PKI for Communication Security in Multi-agent Systems

This paper aims to present a new model based on JSON Web Token (JWT) and Public Key Infrastructure (PKI) for communication security as part of a Multi-Agent System Middleware for massively distributed systems. The proposed model aims to provide secure communications between agents to ensure the integrity of the exchanged messages, the authentication of agents, and the no-repudiation, articulated on an approach based on a Registration Authority (RA) and a Certification Authority (CA) that are managed by a Public Key Infrastructure (PKI). This architecture is based on the Stateless JWT security technology based on the asymmetric cryptographic algorithm used for validation of subsequent client requests for making frequent remote calls to the target server resources. The proposed solution uses a digital signature claim using a KeyStore.p12 generated periodically by the local PKI, to ensure message integrity, transmitter authentication, and non-repudiation based on asymmetric cryptographic technology. The article presents an approach based on digital trust micro-agent for better security.
Facial Photo Recognition Using Deep Learning in Archival Record Management System

A lot of information is stored in the archival record management system (archive), including photos and pictures. It is important to intelligently organize photos in the archive. Current approaches use face recognition technology based on deep learning to manage photos. However, due to the rapid growth of the volume of photos in the archive, face recognition processes on large photoset take lots of processing time. In addition, low resolution photo with small faces in the archive is difficult to identify and recognize. In this paper, we propose a method to identify and retrieve facial photos from the archive. In our approach, photo metadata is used for searching photos in the archive, and resolution enhancement step based on DCSCN model is used to reconstruct photos of low resolution to high resolution. Experiment shows that the proposed approach can search and retrieve facial photo quickly from large photoset and is efficient for identifying small faces of low resolution photos.
Software Reuse and Reusability Based on Requirements: Feature Modelling vs. Case-Based Reasoning

Software reuse and reusability range from operational, ad-hoc and short-term to strategic, planned and long-term. Often the focus of attention is just on code or low-level design. This tutorial presents and compares two different requirements-led approaches. The first approach deals with requirements reuse and reusability using feature modelling. The second approach deals with requirements reuse and reusability in the context of case-based reasoning. Both approaches have different key properties and trade-offs between the costs of making software artefacts reusable and the benefits of reusing them. To aid large-scale development, we have proposed a Feature-Similarity Model, which draws on both approaches to facilitate discovering requirements relationships using similarity metrics. A Feature-Similarity Model also helps with the evolution of a product line, since new requirements can be introduced first into a case base and then gradually included into a product line representation.
The development of the forecasting information system of HIV and tuberculosis coinfection’s outcome in inmates

Abstract The research describes the development of the forecasting information system that can predict the outcome of a disease in inmates with HIV-associated tuberculosis. The aim of the research is to develop an additional high-precision diagnostic criterion giving the possibility of the timely correction of diagnostic, treatment and organizational measures for patients with HIV and tuberculosis co-infection that helps to improve the quality of medical care. The research material is based on the data from clinical cases of patients with HIV and tuberculosis co-infection who were hospitalized in a tuberculosis hospital providing specialized medical care to inmates from 2012 to 2018. (367 people). The study methodology was developed in several stages with the use of the methods of system analysis and mathematical modeling (logical-statistical method of optimally reliable partitions, the method of analysis of hierarchies, artificial neural network, methods of statistical grouping). The result of a complex multi-stage research makes possible the development of the prognostic index forecasting outcome of HIV-associated tuberculosis in prisoners. For the automated calculation of the developed index a software package was created. Interpretation of the received data allows timely correcting of diagnostic and treatment tactics in order to improve the quality of medical care and reduce the hospital mortality rate. The developed information system does not require complex and expensive diagnostic measures, it is easy to use and can be suggested to use as a screening method.
Effects of Visualizing Technical Debts on a Software Maintenance Project

The technical debt (TD) metaphor is widely used to encapsulate numerous software quality problems. She describes the trade-off between the short term benefit of taking a shortcut during the design or implementation phase of a software product (for example, in order to meet a deadline) and the long term consequences of taking said shortcut, which may affect the quality of the software product. TDs must be managed to guarantee the software quality and also reduce its maintenance and evolution costs. However, the tools for TD detection usually provide results only considering the files perspective (class and methods), that is not usual during the project management. In this work, a technique is proposed to identify/visualize TD on a new perspective: software features. The proposed technique adopts Mining Software Repository (MRS) tools to identify the software features and after the technical debts that affect these features. Additionally, we also proposed an approach to support maintenance tasks guided by TD visualization at the feature level aiming to evaluate its applicability on real software projects. The results indicate that the approach can be useful to decrease the existent TDs, as well as avoid the introduction of new TDs.
GCNDA: Graph Convolutional Networks with Dual Attention Mechanisms for Aspect Based Sentiment Analysis

As the amount of user-generated content on the web continues to increase, a great interest has been shown in aspect-level sentiment analysis, which provides more detailed information than general sentiment analysis. In recent years, neural-based models have achieved success in this task because of their powerful representation learning capabilities. However, they ignore that the sentiment polarity of the target is related to the entire text structure. In this paper, we present a method based on graph convolutional neural networks named GCNDA, in which the given text is considered as a graph and the target is the specific region of the graph. Dual graph-based attention models are used to concentrate on the relation between words and certain regions of the graph. We conduct comprehensive experiments on publicly accessible datasets, and results demonstrate that our model outperforms the state-of-the-art baselines.
Security and Privacy Awareness: for Software Creators and Users

Information technology (IT) has far-reaching impact on society. Its security and privacy aspects are now under intense scrutiny. In this work we examine how we got where we are today. We focus on the Internet and related applications and review its evolution. We show that there was lack of security awareness among the innovators. The technology and its applications grew with minimal regulations, unfettered. When technical security awareness dawned for engineers and knowledgeable folks, users at large either remained unaware or they could not be weaned from the attractive and easy to use insecure applications. Without enough social awareness of the implications of the Internet based tools and systems, the Networked Society now has gigantic pools of information most of it without much protection for security and privacy. We discuss the importance of social checks and balances to ameliorate the situation.
Time Affordance Components impact on User’s Experience

If users are to instantly identify the interactive elements on a screen, and accurately predict the results of their interactions, a graphical object's sensory characteristics should intuitively imply its functionality and use. Therefore, this research focuses on user's perception and understanding of affordances which are the most common form of providing a system status for users when downloading large files from the internet. Download micro-interactions (DMI) precise design and attention to details may direct users' attention, make the user experience much more rewarding and influence users' actions. The challenge is to identify and design elements necessary to provide just enough information so that the user's actions, while waiting, properly address the true state of the task.
Towards a Qatar Cybersecurity Capability Maturity Model with a Legislative Framework

In an age when cybersecurity vulnerabilities can be used as a pretext for a blockade, as in the case of Qatar prompted by a hack of the Qatar News Agency, it becomes incumbent upon states to consider legislating the capability maturity measurement and the development of their cybersecurity programs across the community.This paper proposes a Qatar Cybersecurity Capability Maturity Model (Q-C2M2) with a legislative framework.The paper discusses the origin, purpose and characteristics of a capability maturity model and its adoption in the cybersecurity domain.Driven by a thematic analysis under the document analysis methodology, the paper examines existing globally recognized cybersecurity capability maturity models and Qatar's cybersecurity framework using publicly available documents.This paper also conducts a comparative analysis of existing cybersecurity capability maturity models in light of the Qatari cybersecurity framework, including a comparative analysis of cybersecurity capability maturity model literature.The comparative document analysis helped identify gaps in the existing Qatar National Information Assurance Policy and specifically the Qatar National Information Assurance Manual.The proposed Q-C2M2 aims to enhance Qatar's cybersecurity framework by providing a workable Q-C2M2 with a legislative component that can be used to benchmark, measure and develop Qatar's cybersecurity framework.The Q-C2M2 proposes the USERS domains consisting of Understand, Secure, Expose, Recover and Sustain.Each domain consists of subdomains, under which an organization can create cybersecurity activities at initial benchmarking.The Q-C2M2 uses the following five levels to measure the cybersecurity capability maturity of an organization: Initiating, Implementing, Developing, Adaptive and Agile.
Automatic ID Photos Matting Based on Improved CNN

Image matting that aims to estimate the foreground from the mixed pixels is key to ID photos processing. Recently, deep convolutional neural network (CNN) has shown competitiveness for image segmentation, but not achieved good accuracy in practical matting. In this paper, we propose an improved light network for ID photos matting. The model adopts the MobileNetV2 as backbone and leverages the densely connected blocks to predict a high-accuracy binary mask for K-nearest neighbor (KNN) matting. In addition, an automatic portrait matting system based on L-UNet is built, which is very fast without any interaction. Experimental results on a large scale real-world dataset verify the effectiveness of the proposed method on ID photos matting task.
Skew-Aware Collective Communication for MapReduce Shuffling

This paper proposes and examines the three in-memory shuffling methods designed to address problems in MapReduce shuffling caused by skewed data. Coupled Shuffle Architecture (CSA) employs a single pairwise all-to-all exchange to shuffle both blocks, units of shuffle transfer, and meta-blocks, which contain the metadata of corresponding blocks. Decoupled Shuffle Architecture (DSA) separates the shuffling of meta-blocks and blocks, and applies different all-to-all exchange algorithms to each shuffling process, attempting to mitigate the impact of stragglers in strongly skewed distributions. Decoupled Shuffle Architecture with Skew-Aware Meta-Shuffle (DSA w/ SMS) autonomously determines the proper placement of blocks based on the memory consumption of each worker process. This approach targets extremely skewed situations where some worker processes could exceed their node memory limitation. This study evaluates implementations of the three shuffling methods in our prototype in-memory MapReduce engine, which employs high performance interconnects such as InfiniBand and Intel Omni-Path. Our results suggest that DSA w/ SMS is the only viable solution for extremely skewed data distributions. We also present a detailed investigation of the performance of CSA and DSA in various skew situations.
Safety evaluation and risk reasoning of metro station based on IFPN

Abstract In order to realize the accurate evaluation of the safety status of metro station and the high-efficiency identification of the risk cause, an improved fuzzy petri net is introduced to describe the safety risk propagation process of the metro station. The normal gray cloud whiten weight model combined with whitening weight function in gray clustering system and cloud theory is introduced, and the uncertainty of the initial token of place is comprehensively described. The Apriori algorithm is used to extract the transition confidence and weight according to the strong association rules between places, and an IFPN analysis model to support the evolution of the safety state of metro station is established. Through the forward reasoning, the interpretation of the risk propagation path is realized, and the safety status of the metro station is solved. Through the reverse reasoning, the risk is identified and the risk place that has the greatest impact on the safety status of metro station is investigated. Finally, the model is reasoned with an example to verify the effectiveness of the evaluation method.
CALCULATION OF ERRORS OF SELF-MADE PHYSICAL APPLIANCES WITH DIGITAL AND ANALOG SENSORS

The article deals with the problem of calculation of errors of improvised devices and installations for physical training experiment in the construction of which digital and analog sensors are used, which are intended for measuring various physical quantities. The general requirements for educational devices are considered: scientific and pedagogical, technical, ergonomic, aesthetic, economic. In the article special attention is paid to the technical requirements of improvised devices and installations. It is noted that it is necessary to ensure their reliability and durability, perfection and simplicity of construction, high metrological indicators. The basic stages of calculation of errors of measurement of physical quantities, features of measurements with use of digital measuring devices are given. The measurement process using digital measuring instruments and automatic measurement methods remove the measurement from subjective errors and have a number of other advantages. It is convenient to make computers and sensors in combination with hardware platforms Arduino, STM32, Raspberry, etc. for the output of home-made appliances. Analog sensors are connected to the analog inputs of the hardware and software platforms that perform analog-to-digital conversion. Digital sensors are easier to use and capable of providing high metrological performance in the design of self-made physical devices. Most sensors have errors in the instructions. The cases of calculation of errors, when the home-made installation uses optical steam as the main measuring tool, are considered. Optical pairs are used in many homemade physics installations - studies of body motion on an inclined plane, studies of rotational motion using Oberbeck pendulum, studies of mathematical pendulum, etc. Examples and schemes of installations and description of experiments with methods of calculation of measurement errors using optical pairs are given. As a result, it is noted that homemade devices using digital sensors, hardware platforms Arduino, STM32, Raspberry and others meet the general requirements for training devices, in particular, have high metrological indicators, are easy to manufacture and require little financial cost.