Reviewerly/exHarmony huggingface dataset:
Machine Learning as a helper component of an email client

Email is an important means of communication and is largely used in corporations and businesses due to its efficiency, low cost and its practical asynchrony. In order to automate email-managing tasks for an efficient and easy utilization, many intelligent techniques were proposed and applied by researchers in the field of machine learning and data mining. In this research, a survey on the different techniques used for recommendation system and information retrieval in emails is presented. A case study of text classification using email content was elaborated using pre-trained language models (BERT, Elmo). A three baseline models were used to evaluate the performance: Random Forest, support vector machine and Naive Bayes. The classic classification metrics (Precision, Recall and F score) were used to assess the performance of the models. The results of experiments show that Elmo performed poorly in the binary classification with an accuracy of 38%, whereas the lake of sufficient Resources (GPU) and expensive computation of language model Bert presented a limitation for extracting its accuracy. The baseline models achieved good accuracy with random forest having highest value of 81%. This work does not imply an innovation in the state of the art, only the application of methods learned in the Master of Data Science to a problem of interest.
Deep Learning based Oral Cancer Image Classification for Imbalanced Dataset

We use both data- and algorithm-level methods to improve the neural network performance of oral cancer image classification with imbalanced multi-class dataset captured from high-risk populations during oral cancer screening.
auth.js: Advanced Authentication for the Web

Several research works attempt to replace simple authentication schemes, where the cryptographic digest of a plaintext password is stored at the server. Those proposals are based on more elaborate schemes, such as PAKE-based protocols. However, in practice, only a very limited amount of applications in the web use such schemes. The reason for this limited deployment is perhaps their complexity as far as the cryptography involved is concerned. Today, even the most successful web applications use text-based passwords, which are simply hashed and stored at the server. This has broad implications for both the service and the user. Essentially, the users are forced to reveal their plain passwords for both registering and authenticating with a service. In this paper, we attempt to make it easier for any web service to a) enable easily advanced authentication schemes, and b) switch from one scheme to another. More precisely, we design and realize auth.js, a framework that allows a web application to offer advanced authentication that leverages sophisticated techniques compared to typical cryptographically hashed text-based passwords. In fact, auth.js can be easily enabled in all web applications and supports traditional passwords – however, once enabled, switching to a more elaborate scheme is straight forward. auth.js leverages advanced cryptographic primitives, which can be used for implementing strong authentication, such as PAKE and similar solutions, by ensuring that all cryptographic primitives are trusted and executed using the browser’s engine. For this, we extend Mozilla Crypto with more cryptographic primitives, such as scrypt and the edwards25519 elliptic curve. Finally, we evaluate auth.js with real web applications, such as WordPress.
The Referential–Attributive Distinction

This chapter argues that the referential-attributive distinction as applied to definite descriptions is not a semantic distinction, as is often assumed, but an epistemic one. I argue for this on theoretical grounds, as well as by appeal to some empirical work on the topic.
Secret Sharing with Threshold Schemes

In this thesis, four different methods for secret sharing with threshold schemes will be investigated. We will discuss theory, implementation and security aspects. For example, we show how some kno ...
Python in Computer Algebra

SymPy (for Symbolic Python) is a Python program package for the symbolic solution of mathematical problems. In the area of computer algebra, the commercial products Maple and Mathematica are probably the best known. However, SymPy does not have to hide from these professional environments.
Linear Regression Evaluation of Search Engine Automatic Search Performance Based on Hadoop and R

The automatic search performance of search engines has become an essential part of measuring the difference in user experience. An efficient automatic search system can significantly improve the performance of search engines and increase user traffic. Hadoop has strong data integration and analysis capabilities, while R has excellent statistical capabilities in linear regression. This article will propose a linear regression based on Hadoop and R to quantify the efficiency of the automatic retrieval system. We use R's functional properties to transform the user's search results upon linear correlations. In this way, the final output results have multiple display forms instead of web page preview interfaces. This article provides feasible solutions to the drawbacks of current search engine algorithms lacking once or twice search accuracies and multiple types of search results. We can conduct personalized regression analysis for user’s needs with public datasets and optimize resources integration for most relevant information.
Uso de herramientas tecnológicas y su impacto en el rendimiento en el curso de cálculo II de la universidad nacional

The use of ICT in scholar contexts is a valuable resource for teaching-learning processes in many disciplines and Mathematics is not an exception. The goal of the document is to contrast the hypothesis that the use of technological tools in classes of Calculus II course, improves the students' academic performance. Hence, a quasi-experiment was designed with three treatment levels whose dependent variable is represented by the second partial exam mark in the subject. The first experimental group used videos and mathematical software as support for the classes and the second group only videos were used, the third treatment was constituted by the control group. As control variables were: the scores on the calculation I course and the first test the calculation II course were taken, which did not show significant differences between groups. An analysis of variance with Welch's correction was applied along with effect sizes between the treatments were calculated. Although the result of the analysis of variance was not to significant (p = 0.053), the effect sizes and promotion levels per treatment show evidence in favor of the use of ICT as a means to improve academic performance in the course of MAT003 Calculus II.
The Courage to Teach Well Online

This paper explores the principles at the heart of Parker Palmer’s seminal book on teaching with purpose and passion, The Courage to Teach, within the online environment. It reports the results of four faculty members from diverse disciplines who teach online and who have discussed, debated, and explored Palmer’s ideas in the context of online teaching. The paper argues that, as with traditional, face-to-face teaching, effective online teaching must address many of the same kinds of paradoxes originally described by Palmer. In particular, it focuses on ways in which identity and wholeness, fear and separation, and community present challenges that require courage in order to teach well online.
Experiencias educativas virtuales desde un perspectiva global

In this talk, we have explored different alternatives and strategies to improve the teaching delivery and assessment using technologies that are available today.
COMPARATIVE ANALYSIS OF CROSS-PLATFORM FRAMEWORKS FOR MOBILE APPLICATIONS DEVELOPMENT

The article considers the comparison of existing cross-platform frameworks for mobile development. Analysis of their features and interaction with the mobile operating system. Identify key properties for maximum performance.
Comparison between genetic algorithm and differential evolution tuning a fuzzy controller

This work brings a performance comparison between the genetic algorithm (GA) and differential evolution (DE) in tuning the parameters of a Fuzzy controller applied to an armature-controlled DC motor. Both heuristics are consolidated, being GA the most popular in tuning fuzzy parameters. To make the comparison, the results found after 10 iterations are presented, as well as the box plots obtained from the collected data. The methodologies presented satisfactory answers, showing punctual differences between one and the other for the presented problem: the AG depends more on an assertive initial population, while the ED does not, managing to do better local searches.
Research and Practice on the Application of ESP Informatizational Education Technology in Higher Vocational Education Based on the College-Enterprise Dual System Integration Mode

This paper introduces how to implement Business English Majors Education Plan on the basis of government policies and the dual system of “College-Enterprise” integration mode by means of Informatizational Education Technology.
Ensemble Deep Learning Features for Real-World Image Steganalysis

The Alaska competition provides an opportunity to study the practical problems of real-world steganalysis.Participants are required to solve steganalysis involving various embedding schemes, inconsistency JPEG Quality Factor and various processing pipelines.In this paper, we propose a method to ensemble multiple deep learning steganalyzers.We select SRNet and RESDET as our base models.Then we design a three-layers model ensemble network to fuse these base models and output the final prediction.By separating the three colors channels for base model training and feature replacement strategy instead of simply merging features, the performance of the model ensemble is greatly improved.The proposed method won second place in the Alaska 1 competition in the end.
Research of deformation wheel for getting over steps

This paper proposes a new deformed wheel for steps Circular wheels which are excellent in moving speed and steering on flat ground. However, the step height that can be getting over depends on the wheel diameter. In the outdoor environment, there is a step between the road and the sidewalk, so the place where the wheel robot plays an active role is not prepared. Therefore, we have developed a deformed wheel for steps, which generates protrusions by deforming the wheels and improves getting over performance. In order to confirm the effectiveness of the developed robot, we conducted a comparative experiment of getting over steps ability. As a result of the experiment, it was possible to get over the step higher than the circular wheel by using the deformed wheel for the step, and it was possible to get over a step of 0.68 times the wheel diameter at the maximum.
Model Pembelajaran Berbasis Literasi di Madrasah

This article is aimed to describe the implementation of literacy-based learning model in fostering readingand writing interest, developing listening and speaking skill, and mastering information and technology. To these days, teachers seem to fail in constructing literacy-based learning model which lead to the weak culture and tradition of reading, listening and writing among the students, and the low skill in information and technology in this digital era of 4.0. The study was conducted in a qualitative approach employing library research method. Data collection was performed by reading relevant literature associated with the implementation of literacy-based learning model in Madrasah. The result of the study pointed that to implement literacy-based learning model can be performed through the following ways: 1) fostering reading interest, 2) developing writing interest and make it as a habit, 3) training and building up listening skill, 4) training and practising speaking skill, and 5) developing the ability and skill in information technology. The result of the study is recommended to madrasah headmasters and teachers so that they can implement a literacy-based learning model eagerly, accountably, and responsibly. Also, it is expected that they can work together with other stakeholders for the best implementation of the literacy-based learning model.
A Cloud-Based DevOps Toolchain for Efficient Software Development

In the traditional software development life cycle, development and operation are divided into different departments. The conflict between departments and, besides, the lack of automation usually leads to low software development efficiency and slow software delivery. Thus, the concept of DevOps is introduced, which combines different departments and automates the process to make software delivery faster and easier. The DevOps toolchain is one important component for adopting DevOps. On the other hand, the adaptation of cloud technology, especially serverless computing makes it tempting for us to investigate what benefits serverless computing brings to the DevOps toolchain. In the first research question, we examine the benefits that AWS serverless platforms bring to DevOps toolchain. To answer this research question, we develop a DevOps toolchain hosted in Amazon Web Services (AWS) and leverage the serverless computing service. In addition, we examine what does each serverless computing service brings to the DevOps toolchain, examine how does the performance of the DevOps toolchain changes with or without using serverless computing service. Our research shows that serverless computing services such as AWS Fargate could reduce the cost, operation effort, and improves performance by enabling parallel execution. Our experiments show that in contrast to a toolchain hosted in a traditional cloud server vs the toolchain that was developed by us using serverless computing service could reduce the total runtime of parallel execution up to 65%. In the second research question, we focus on the integrated toolchain build with AWS DevOps tools from AWS serverless platform. We build a demo integrated DevOps toolchain with AWS DevOps tools and compare the integrated toolchain with the non-integrated toolchain that we built. We find that the integrated toolchain significantly reduces the development time by providing an out-of-box solution for the software team. In addition, the better integration with underlying cloud infrastructure provides more functionality such as global monitoring and blue/green deployment. However, we also find that from the experiment that the performance of the integrated toolchain is lower due to the limitation of resources which also come with a high cost.
Simple administrative tools for networking

The management of large networking systems is complex and riddled with inefficiencies. A large cause of inefficiency is that most administrative tools are old fashioned, complex and dangerous. This means that most daily tasks are done by senior staff, which are fewer and more expensive than the junior staff. The senior staff is also more likely to be working on critical projects, which the small daily tasks distract from. This problem is solved by creating an internal web service for a selection of simple operations. Traditionally due to the dangerous nature of administrative tools, access has been highly restricted. With the web service access can be granular, ranging from limited rendering of information to full access equivalent to the traditional approach. The project was done in collaboration with the National Hospital of Iceland.
REMOTE-LEARNING ADAPTATION: EXPERIENCE AT DIFFERENT EDUCATION LEVELS

The COVID-19 pandemic has generated a great surge of changes and, in turn, a prompt response and adaptation by the education system. The principle objective of this paper is to delve into the adaptation from face-to-face to virtual classroom multitasking and academic performance under the real experience of teachers of different education levels in this time of crisis. For this purpose, we analyse the multiple measures that have been taken by different educational institutions in the short time and how the different needs have been addressed in the study stages. In this sense, multiple questions arise: Have teachers been able to adapt to this critical situation? Have teachers been reluctant to use online platforms? Have they found a lack of resources to employ in their use of remote learning? Has electronic and complementary material been provided to cover this disadvantage? In ramping up capacity to teach remotely, institutions should take advantage of synchronous learning (that is a vital element in digital formats) (Daniel, 2020). In addition, technology-enabled have the possible to disrupt through barriers associated with time and accessibility. Thus, it is vital to emphasize the use of synchronous technologies for office hours over class instruction. The utility and value of technology-enabled, asynchronous in space and virtually have been written about and studied for decades but not universally implemented. Still, technology-enabled virtual learning may be essentially a logical progression of the initiatives (such as flipped classroom and hybrid classroom) that already exist in many schools, and there would still be a need for faculty to serve as coaches, to provide feedback, and to moderate and host online debates (Woolliscroft, 2020). Faculty members are already in the process of transitioning to online teaching platforms. In this article, we analyse the real experience of a sample of teachers of different education levels: Primary, Secondary, High School and University. Thus, a qualitative study in a sample of teachers will be carried out through in-depth interviews. In short, we study the process of transition to online teaching platforms by faculty members, according to the teaching training received, the resources available, the working method and the contact method with the student. This will allow us to analyse and compare the adaptation and methods employed at different educational levels.
Overcoming the problem of uncertain tracking errors in an AR navigation application

This thesis proposes four different Augmented Reality (AR) display techniques that can overcome the problem of uncertain tracking errors. Where most other papers focus on limiting the amount of error that a user tracking system generates, this paper pro-poses visualizations that limit their impact instead. For this, four different display techniques have been developed and evaluated using criteria found in related literate. Two of the four proposed solutions consistently ranked better within these criteria. The first, Bending Words, uses a mix between spatially registered information and turn instructions to achieve that result. The second, WIM, mostly relies on context infor-mation of the building instead.
Histotechnology a self instructional text, 5<sup>th</sup> edition

This 5th edition text has 13 contributors, contains 15 revised chapters with 2 completely new chapters for a total of 17 chapters. There are many new images throughout the text. A great resourceful...
Investigating the Impact of Pre-processing and Prediction Aggregation on the DeepFake Detection Task.

Recent advances in content generation technologies (widely known as DeepFakes) along with the online proliferation of manipulated media content render the detection of such manipulations a task of increasing importance. Even though there are many DeepFake detection methods, only a few focus on the impact of dataset preprocessing and the aggregation of frame-level to video-level prediction on model performance. In this paper, we propose a pre-processing step to improve the training data quality and examine its effect on the performance of DeepFake detection. We also propose and evaluate the effect of video-level prediction aggregation approaches. Experimental results show that the proposed pre-processing approach leads to considerable improvements in the performance of detection models, and the proposed prediction aggregation scheme further boosts the detection efficiency in cases where there are multiple faces in a video.
Relationship between Agro-climatic parameters and Sugarcane Yield in Adamawa State, Nigeria

The study examined the relationship between the major climatic parameters and the yield of sugarcane in Southern parts of Adamawa state, Nigeria. The parameters considered include rainfall, temperature, relative humidity and solar energy. To achieve the aim of the study, Pearson’s Product Moment Correlation Coefficient (PPMCC) tool was used to examine the relationship between each climatic condition and the yield of sugarcane. Climatic data were obtained from Nigerian Meteorological Agency (NiMet), Global Weather Data for SWAT (GWDS) and NASA Prediction of Worldwide Energy Resources (POWER). The data were from 1979 to 2014 (35 years). The result indicated that, there is weak positive correlation between the yield of sugarcane and Minimum temperature, rainfall and relative humidity (RH) which had PPMCC values of 0.1, 0.2 and 0.1 respectively. While weak negative correlation was observed between the yield of sugarcane and Maximum temperature, and solar energy with PPMCC values of -0.3 and -0.1 respectively. This shows that as the values of Minimum temperature, rainfall and RH increase, the yield of sugarcane increases gradually too. On the other hand, as the values of Maximum temperature and solar energy increase the yield of sugarcane declines gradually in response. Therefore, the trend of these climatic conditions should be considered when investing in sugarcane production. Advice on the expected prevailing weather by authorities such as Nigerian Meteorological Agency should be taken serious by stakeholders for maximum yields. Keywords: Agro-climatic, correlations, dataset, sugarcane, yield.
LibGuides: Getting Started with Archives: Using the Archives Portal

This guide serves as an introduction to locating and evaluating collection description, and beginning archival research at NYPL This page provides details on locating archival collections using the finding aid database.
Mathematical Background and Its Applicability in Cryptography

The chapter will discuss the concepts of experiments, probability distribution, events, complementary events, and mutually exclusiveness. These concepts will help the reader to understand the basic notions of what cryptographic and cryptanalysis mechanisms stand for and how they are designed in terms of probabilities [1].
Peningkatan Kinerja Belajar Ekonomi Melalui Penerapan Media Sparcol Video Scribe pada Siswa Kelas X di SMK Muhammadiyah 2 Klaten Utara

The purpose of this study is to improve economic learning using a media sparcol video scribe. This type of research is Classroom Action Research (CAR) which is conducted in 2 cycles. The subjects of this study were teachers and class X AK 1 students of SMK Muhammadiyah 2 Klaten Utara who denied 25 students. Data collection methods used were interviews, observation, tests, field notes and documentation. Data analysis techniques that use data reduction methods, data presentation, and complete conclusions. The results showed. This can be seen through the following indicators. In the pre cycle 12 students (48%) completed, 13 students (52%) did not complete. In the first cycle 16 students (64%) completed, 9 students (36%) did not complete. In the second cycle 21 students (84%) completed, 4 students (16%) did not complete. Then the classical mean value also increased, namely in the pre-cycle 70.12, in the first cycle increased to 73.84 and in the second cycle increased to 80.8. Based on this research, it can be concluded that sparcol video scribe media can improve the economic learning outcomes of students of class X AK 1 SMK Muhammadiyah 2 Klaten Utara.