Reviewerly/exHarmony huggingface dataset:
The overview of open education development tendencies in Russia and Canada

The aim of research is to describe the foreign experience of open educational resources implementation in higher education on the example of Canada. The concept of open education in this country requires federal and regional support from the government. Currently, there is a number of initiatives, aimed at maximizing the development of open educational resources. An increasing number of open educational resource initiatives in Canadian universities offer free courses to both Canadians and international students. National open education initiatives include the following projects: “Open Data”, the federal government “pilot” project; support of Canadian Council of Ministers of Education within 2012 Paris Open Educational Resources Declaration; and the Creative Society of Canada. British Columbia and Alberta support open educational resources as a part of the most important open education initiatives at the regional level. However, a number of problems prevent the full development of the open education system. Materials and methods of research include discourse-analysis of domestic and foreign scientific sources, devoted to the problems of open education. The methodological basis is the study of the legal framework of open education, a retrospective analysis of the open education development process in Canadian universities and the analysis of existing open educational projects. The results of the study show that the need to implement the policy of open education imposes new requirements to the process of determining the level of educational programs development and the formation of a unified system of formal credits. Conclusion. The Canadian examination of open educational resources regulates all sectors of education and training in the country. This examination is a review of the results of open education principles implementation at the national and regional levels. The article discusses the features of both regional and foreign projects functioning. The advantages of open educational policy for different segments of the population are described.
Fuzzy Min Max Neural Network for pattern classification: An overview of complexity problem

Over the last years, the pattern classification is considered one of the most significant domains in artificial intelligence (AI), because it shapes a fundamental in many diverse real live applications where the artificial neural networks (ANNs) and fuzzy logic (FL) are most extensively utilized in pattern classification. In order to construct an effective and robust classifier, researchers have invented hybrid systems that combine both FL and ANNs. The Fuzzy Min Max (FMM) neural network has been proven to be a robust classifier for handling pattern classification issues. Although FMM has several features, it suffers from several limitations. Thus, researchers have introduced a lot of improvements to beat the shortcomings of FMM neural network. This paper focuses on a complete review of developments carried out on FMM neural network for addressing the complexity problem in order to help new researchers in identifying the recent strategies used to address the complexity problem.
Morphological PDEs on graphs for saliency detection

Visual saliency is a computational process that seeks to identify the most attention drawing regions from a visual point. In this study, the authors propose a new algorithm to estimate the saliency based on partial difference equations (PDEs) method. A local or non-local graph is first constructed from the geometry of images. Then, the transcription of PDE on graph is done and resolved by using the mean curvature flow that can be used to perform regularisation and the Eikonal equation for segmentation. Finally, an extended region adjacency graph is built, which is extended with a k-nearest neighbour graph, in the mean RGB colour space of each region in order to estimate saliency. The proposed algorithm allows to unify a local or non-local graph processing for saliency computing. Furthermore, it works on discrete data of arbitrary topology. For evaluation, the proposed method is tested on two different datasets and 3D point clouds. Extensive experimental results show the applicability and effectiveness of the proposed algorithm.
Privacy-Driven Interaction Design: Creating Transparent Characters for Smart Objects

As more consumer products and services are getting intelligent and collect data about the user, privacy has become an important topic of debate in society. New rules and legislation are being implemented to safeguard the user’s privacy. In addition, from a technological perspective, developments like the creation of the seven principles of ‘privacy by design’ for systems engineering aim to ensure that privacy is embedded within the functioning of these ‘smart objects’. However, there has not yet been given much attention to creating privacy through interaction design. This project aimed to create a design approach which has the user’s control over their privacy at its core: The Privacy-Driven Interaction Design approach. Through the creation of a conceptual framework, this project started with an analysis of existing theory of Human-Computer Interaction. It proposes three design strategies for creating smart objects that give the user control over their privacy: 1 | Design smart objects with Character; 2 | Design smart objects with Expression of Presence; 3 | Design smart objects with Frictional Feedback. Through cinematic prototyping, this project explores these strategies and implements them in a case study. For the case study, two smart gloves were created which aid veterans during their therapy for post-traumatic stress disorder. Both of the gloves have different characters to show the impact of the smart object’s character on the interaction between the user and the object. The smart gloves have both a conceptual purpose, which is to demonstrate how the design strategies can be implemented in a design process, and a functional purpose, which is to put the disclosure of information about the veteran’s stress levels and therapy progress in the veteran’s hand. The conclusions from the creation of the conceptual framework and the smart objects during the case study lead to a guide for the Privacy-Driven Interaction Design approach. This guide is presented in the form of a checklist with ‘design questions’ and ‘design strategies’. This report aims to present the potential of this design approach and the smart gloves for veterans. However, more extensive research is recommended to further develop both the design approach and the design concepts.
Implementation of House Bill (HB) 3593, High School Cybersecurity Courses

PDF Version DATE: January 17, 2019 SUBJECT: Implementation of House Bill (HB) 3593, High School Cybersecurity Courses CATEGORY: Additional courses eligible for CTE w
Simulated Kalman Filter Algorithm with Improved Accuracy

This paper presents an improved Simulated Kalman Filter optimization algorithm. It is a further enhancement of a Simulated Kalman Filter (SKF) optimization algorithm. SKF is a random based optimization algorithm inspired from Kalman Filter theory. An exponential term is introduced into Estimation stages of SKF to speed up the searching process and gain more chances in finding better solutions. Cost function value that represents an accuracy of a solution is considered as the ultimate goal. Every single agent carries an information about the accuracy of a solution in which will be used to compare with other solutions from other agents. A solution that has a lower cost function is considered as the best solution. The algorithm is tested with various benchmark functions and compared with the original SKF algorithm. The result of the analysis on the accuracy tested on the benchmark functions shows that the proposed algorithm outperforms SKF significantly. Graphical results of the test show that the SKFIA has faster convergence speed as compared to SKF.
Component Fusion Image Encryption Method Based on Hybrid Chaotic Model

The current image encryption method is relatively simple, and there is the problem of poor image encryption effect. Based on the hybrid chaotic model, an image encryption method with component fusion is proposed in this paper. The image is mapped by using Arnold cat mapping method. Chaotic sequence is generated by chaotic model, and the original image is scrambled and substituted to achieve image encryption. Through the fixed point ratio, information entropy, gray mean change value, autocorrelation and similarity, the test of encrypted image is completed. Experimental results show that the proposed image encryption method has good performance, high security intensity, and can effectively encrypt the image.
Hybrid Deep Neural Network - Hidden Markov Model Based Network Traffic Classification

Traffic classification has been well studied in the past two decades, due to its importance for network management and security defense. However, most of existing work in this area only focuses on protocol identification of network traffic instead of content classification. In this paper, we present a new scheme to distinguish the content type for network traffic. The proposed scheme is based on two simple network-layer features that include relative packet arrival time and packet size. We utilize a new model that combines deep neural network and hidden Markov model to describe the network traffic behavior generated by a given content type. For a given model, deep neural network calculates the posterior probabilities of each hidden state based on given traffic feature sequence; while the hidden Markov model profiles the time-varying dynamic process of the traffic features. We derive the parameter learning algorithm for the proposed model and conduct experiments by using real-world network traffic. Our results show that the proposed approach is able to improve the accuracy of conventional GMM-HMM from 77.66% to 96.11%.
Basic Version of Gnostical Regression - Broader Sight I.

Our paper describes and graphically demonstrates properties of Kovanic’s Criterion Gnostical Regression Function. The main characteristics are highlighted here. A gnostical evaluation of data-files affords results with the maximal possible amount of information. So, gnostics always affords the most exact possible evaluation of a data-file contaminat-ed by uncertainties even in the cases when for some data-files there are an extremely low number of data-items at one’s disposal.
Neighbor Retrieval Visualizer for Monitoring Lifting Cranes

Gear wear is hard to monitor in lifting cranes due to the difficulties to provide appropriate models of such complex systems with varying functioning modes. Statistical machine learning offers an elegant framework to circumvent these difficulties. This work explores recent advances in statistical machine learning to provide a data-driven model-free approach to monitor lifting cranes, by investigating a large number of indicators extracted from vibration signals. The principal contributions of this paper are twofold. Firstly, it explores the recently introduced Neighbor Retrieval Visualizer (NeRV) method for nonlinear information retrieval. The extracted information allows to construct a low-dimensional representation space that faithfully depicts the evolution of the system. Secondly, it proposes a simple and efficient detection method to detect abnormal evolution and abrupt changes of the system at hand, using the distance measure with neighborhood retrieval in the same spirit as NeRV. The relevance of the proposed methods, for visualizing the evolution and detecting abnormality, is demonstrated with experiments conducted on real data acquired on a lifting crane benchmark operating for almost two years with more than fifty indicators extracted from vibration signals.
The Use of Sketching Technique to Help Deaf Children in Bahasa Melayu Essay’s Report

Deaf children usually face language difficulties which affect their writing skills. This qualitative research is conducted to introduce a sketching method that will improve children’s skills in writing Report in Bahasa Melayu . Scaffolding technique from Wood, Bruner and Ross is applied to lead deaf children in mastering writing technique proportionally. This experimental research involves 8 deaf students which are divided into two groups, namely experimental group and control group. Sample’s knowledge, personal experience and education level have been taken into consideration in the sampling technique. Pre-test Instrument, Post-test and semi-structured interview are used to measure the efficiency of this technique. Experimental group received writing intervention, guided by sketching of the essay structure in two phases, which are sketching phase and drawing and writing phase. Essays written during Intervention B are assessed based on the marking rubric prepared. The data is described descriptively to answer research questions. External validity depends on the ability of writing technique as a responding variable, affecting the manipulated variable, which is student’s writing ability. The findings in pre-test and post-test are compared. It is found that the mean of experimental group is higher, which is 8.5 compared to mean of control group, which is 0.5 after the intervention phase. When interviewed, all samples from the experimental group are interested to continue using this technique after the experiment. It is concluded that sketching technique is effective in helping deaf students to write a Malay language report.
spelling grammar are not static. Go try ...

spelling grammar are not static. Go try and read Constitution these inventions not set in stone. Technology has always shaped tools for #literacies cursive straight
Statistical Applications

At the beginning of the 1980s, there were fewer than 20 commercial statistical software packages. At the end of the 1990s, there were over 1,000 packages, and the annual revenue to the producers of those packages surpasses a billion dollars. This explosion in the availability of softfware to perform statistical calculations has caused a corresponding increase in both the available methodology and in the diversity of applications.
Petrochemical Characteristics and Age of Rare Metal (Ta-Nb) Mineralization in Precambrian Pegmatites, Komu, Nigeria

The Precambrian pegmatites of Komu area intrude semi discordantly older rock types, such as biotite gneiss,amphibolites and pelitic schists. The pegmatites occur as near flat lying bodies. This study aims at elucidating thegeological setting, petrography, geochemical features and age of mineralization of these pegmatite bodies, with a viewto classifying them and knowing their economic potential. The petrographic analysis shows that the pegmatite samplescontain mainly quartz (35%), plagioclase (15%), microcline (10%) and muscovite (12%) with accessories like tourmaline,tantalum, niobium and illmeno-rutiles. Geochemical analysis of the muscovites extracted from pegmatites show thatthese rocks are enriched in silica (>60%) and Al2O3 (>12%) and depleted in Fe2O3, MgO and TiO2. Trace element analysisshows that the pegmatites contain rare metals with moderately high Ta, Nb, Sn, Rb, Li and Cs values and depleted in Ti,Ba and Zr. Elemental ratios indicate low ratios of K/Cs, Th/U and K/Rb. Variation plots of Ta/(Ta+Nb) versus Mn/(Mn+Fe) show that the pegmatites plot in the complex (beryl subtype) field. The Na/K versus Sn, Nb, Rb variation plotsshow that the pegmatites of Komu area are mineralized and compare favourably with those of other mineralized pegmatiteareas like Egbe and Ijero in southwestern Nigeria. The variation plots of Ta versus K/Cs, and Ta/W versus Cs, alsoconfirm rare metal mineralization of Komu pegmatites, which plot over the mineralized line of Beus and Gordiyenko. TheK/Rb versus Rb, Cs and Sn plots indicate low K/Rb ratios indicating moderate differentiation. The Rare Earth Elements(REE) show high heavy REE values and lower light REE values with prominent positive Ce anomaly and negative Euanomaly from normalized chondrite plots. K/Ar dating of the age of mineralization of muscovites extracted from thepegmatite yielded late Pan-African ages between 502.8±13Ma and 514.5±13.2Ma. This period represents the coolingages of the muscovite and suggests that the pegmatites may not be cogenetic with the surrounding Pan-Africangranitoids.
Cryptocurrency -- What Estate Planners Need to Know

Less than a decade ago, if an estate planner asked clients whether they owned any cryptocurrency, the most likely response would be, “You mean, money to buy a crypt?” Now, due to the widespread media coverage of Bitcoin, the most famous of all cryptocurrencies, most clients will have some basic idea about what the estate planner is inquiring.The use of cryptocurrency is increasing at a rapid pace. As of December 31, 2018, there were approximately 17.5 million Bitcoins in circulation worth over $67 billion. Although only a few cryptocurrencies in addition to Bitcoin are well-known outside the cryptocurrency community (e.g., XRP, Ethereum, EOS, and Stellar), over 2,000 different virtual currencies are actively traded. These other cryptocurrencies are sometimes referred to as altcoins, meaning that they are an alternative to Bitcoin.A recent survey revealed that 25% of individuals between the ages of 24 and 38 who either had $50,000 of investable assets or earned $100,000 or more per year own cryptocurrency. A growing number of mainstream businesses already accept Bitcoin such as Microsoft, Subway, KFC Canada, many Etsy vendors, Whole Foods, Dish Network, and Expedia. In addition, some law firms are already accepting Bitcoin in payment of legal services. This article starts by building a basic foundation about virtual currencies and how they operate. The article then reviews the estate planning and administration issues that arise with owning cryptocurrency and concludes with recommendations for how to address virtual currency in your practice.
Persona-Technology footprint: an evaluation of 144 student’s perceptions of a person using assistive technology

The persona-technology footprint is the visual balance between the enabling technologies associated with an individual and the person. This design heuristic enables a practitioner to quickly assess the area of visible technology compared with that of the person. The objective of a designer is to minimise the perceived technology and emphasise the personality of the individual. This study looks to provide detail about the visual balance between areas of a person covered by assistive technology and which areas of a person it is important to ensure are visible. A survey of 144 undergraduate design students involved them choosing where they considered they no longer saw ‘the person’, due to them being covered by assistive technology. This involved three different line drawings: one that had different sections of the person’s profile blacked out to represent the presence of equipment in front of the person; the second with the outer profile of the person visually broken by the overlapping blacked section; and, a line drawing of a person’s head with blacked out sections that both covered areas of the head and broke the outer profile. The points chosen by students were collated and processed statistically using ANOVA. In all three choices, students chose the point where the person was covered up to the point of their eyes being covered. This suggests we view another person’s eyes to represent them more than any other part of their body. Further studies are required to explore this outcome.
이공 계열 교수의 강의 실행에 대한 이해: 문화역사적 활동이론(CHAT)을 활용한 사례연구

In this study, we analyzed professors performance of teaching in college of science and engineering from the perspective of the CHAT.Two professors...
Attention-Based Argumentation Mining

This paper is intended to make a breakthrough in argumentation mining field. Current trends in argumentation mining research use handcrafted features and traditional machine learning (e.g., support vector machine). We worked on two tasks: identifying argument components and recognising insufficiently supported arguments. We utilise deep learning approach and implement attention mechanism on top of it to gain the best result. We do also implement Hierarchical Attention Network (HAN) in this task. HAN is a neural network that gives attention to two levels, which are word-level and sentence-level. Deep learning with attention mechanism models can achieve better result compared with other deep learning methods. This paper also proves that on research task with hierarchically-structured data, HAN will perform remarkably well. We do present our result on using XGBoost instead of a regular non-ensemble classifier as well.
A Methodological Issue in Prediction of Cancer Masking in Screening Mammography Using Density and Textural Features

We read with interest the article recently published in Academic Radiology entitles “Prediction of Cancer Masking in Screening Mammography Using Density and Textural Features.” The aim of the paper was to predict masking status based on biometric and image-based parameters ( 1 Mainprize J.G. Alonzo-Proulx O. Alshafeiy T.I. et al. Prediction of cancer masking in screening mammography using density and textural features. Acad Radiol. 2018; https://doi.org/10.1016/j.acra.2018.06.011 Google Scholar ).
A Tight Net with Respect to a Random Matrix Norm and Applications to Estimating Singular Values

Presented on February 11, 2019 at 11:30 a.m. as part of the ARC12 Distinguished Lecture in the Klaus Advanced Computing Building, Room 1116.
A Gathered Images Analysis Method to Evaluate Sound Sleep

This paper proposes a method to evaluate a sound sleep using an image gathering technique and its analysis techniques. The proposed method consists of three phases; gathered images generation, gathered images analysis and sound sleep evaluation. The gathered images designed to gather sleep postures and their changes are generated at 1 second, 10 seconds, 1 minute, 10 minutes, 1 hour intervals and all times, respectively. In the gathered image analysis, the gathered images are analyzed by calculating difference values among the gathered images of 10-minute and all times. Then, the sound sleep conditions are evaluated by visual inspection and analysis results. In order to show the effectiveness of the proposed method, we conduct experiments using real movies and their images. In experimental results, we confirm that there were sound sleep conditions, bad sleep conditions and borderline cases, respectively, by checking subjective evaluation using questionnaire and generated gathered images visually. Moreover, we confirm that calculated difference values among the gathered images of 10-minute and all times are different between sound sleep and otherwise. Furthermore, the analyzed results show that the proposed method was successful in the sleep conditions classifications on four subjects out of five subjects. These results suggest that the gathered images analysis method is effective when evaluating whether sleep condition is sound sleep. In particular, it is important to calculate the difference values among the gathered images of 10-minute and all times to evaluate sleeping conditions.
Consumer Innovation Shout Out: Have it Your Way - Viome Leverages AI for a Custom Diet - Viewpoints on Innovation

Viome just bought Habit to combine technologies, providing an even more accurate picture of their customer’s biological needs.