Reviewerly/exHarmony huggingface dataset:
General Adversarial Defense via Pixel Level and Feature Level Distribution Alignment

Deep neural networks (DNNs) have achieved amazing success on a wide range of high-level computer vision tasks. However, it is proved that DNNs are vulnerable to adversarial samples. The threat of adversarial samples comes from the large distribution gap between adversarial samples and clean samples in the feature spaces of the target DNNs. To this, we utilize deep generative networks with a novel training scheme to eliminate the distribution gap. Our training strategy introduces constraints in both pixel level as well as feature level, and the trained network can effectively align the distribution of adversarial samples with clean samples for target DNNs through translating their pixel values. Specifically, compared with previous methods, we propose a more efficient pixel-level training constraint to weaken the hardness of aligning adversarial samples to clean samples, which can thus obviously enhance the robustness on adversarial samples. Besides, a class-aware feature-level constraint is formulated for integrated distribution alignment. Our approach is general and suitable for multiple tasks like image classification, semantic segmentation and object detection. We conduct extensive experiments on these three tasks and different datasets, on which the superiority of our strategy over existing methods demonstrates its effectiveness and generality.
The problem of distance learning in modern Russian education (theory and practice)

In modern information society, information technology-based learning is becoming more and more popular. Learning via the Internet, that is, distance learning, has great potential. This paper focuses on the psychological and organizational features of distance learning. The psychological characteristics of the subjects of the educational process in the course of distance learning have been determined. Distance learning is the kind of learning in which the interaction of participants in the educational process takes place in a virtual space using information and communication technologies. Risks and problems of psychological readiness of teachers and students for distance learning have been analyzed. The paper emphasizes the difference between distance learning and the traditional form of education. In the course of theoretical analysis, the author considers the distinctive features of distance learning from correspondence learning in detail. The author brings up a question whether a sharp transition from traditional to distance learning can cause a psychological crisis, emotional instability, and entail negative consequences. The components for assessing the effectiveness of distance learning have been given in the paper: material and technical support; psychological climate in the study group; structure and content of educational material; individual achievements of students; teacher qualifications. The relationship between the type of perception and the effectiveness of distance learning is explored, the forms of interaction and presentation of the training content differ. Concrete steps are proposed for holding an event to optimize the distance educational process. The positive aspects of distance learning are pointed out. In the conclusion, specific preventive measures of psychological support for participants in distance learning have been presented.
IMM-CKF and Posterior Cramér-Rao Lower Bound for a Highly Maneuvering Target

We consider the dynamic state estimation of a highly maneuvering target with 6g and 8g accelerations. The target motion consists of the nearly constant velocity and nearly constant turn in clockwise andanticlockwise directions. An air moving target indicator (AMTI) radar measures the range, azimuth and radial velocity of the target. We use the interacting multiple model (IMM) filter based on the cubature Kalmanfilter (CKF) as an efficient and effective algorithm to estimate the state of the highly maneuvering target.The performance of the IMM-CKF is analyzed using the posterior Cramer-Rao lower bound (PCRLB), rootmean square (RMS) position and velocity errors, and average normalized estimation error squared(ANEES).
Discussion on the College Students' Evaluation on the Teaching Effect of PE Teachers

This paper summarizes the problems existing in the teaching quality of physical education teachers in China, and discusses the structure of College students' evaluation of teaching effect of PE teachers from an empirical point of view, and compiles a student evaluation questionnaire which is convenient for students and conforms to the characteristics of modern physical education teaching.
Composition, structure and magnetic properties of ore chrome spinels of the Klyuchevsky massif (Middle Urals)

The overall objective was to create a geological and geophysical field test site for chromite mineralization and detailed works in order to determine and test the main search criteria for disseminated mineralization. To create a field test site, an area was selected in the southern part of the Klyuchevsky massif characterized by abundant development of disseminated mineralization in the banded dunite-clinopyroxenite complex and strong processes of superimposed metamorphism. This paper gives a piece of research on the composition of chrome spinel from disseminated ores that underwent metamorphism of different stages. The composition of chrome spinelide, the evolution of its metamorphism and the related changes in its magnetic properties are examined in detail. It was established that all chrome spinels are of a high-chromium type, to one degree or another, they were subject to secondary changes, leading to the appearance of magnetic phases. The degree and nature of the change in chrome spinels in dunites directly depends on the degree of metamorphism of the rocks. The formation of the magnetic phase begins with the formation of nuclei consisting of single magnetic dipoles, groups of 2-3 dipoles or chains of magnetic dipoles, which was first discovered by us in chrome spinel grains. Then there is an increase in the number of such phases, the appearance of optically diagnosed secondary changes in chrome spinelide. A comparison of the degree of variation of chrome spinel and its reflection in the pattern of recorded anomalies of geomagnetic fields allows us to identify some criteria for the search for disseminated chromite ores of this type.
Online violence against women as an obstacle to gender equality: a critical view from Europe

Online violence against women operates – in an increasingly digital society – as an obstacle to gender equality. The 2018-2023 CoE Gender Equality Strategy sets a benchmark for the initiatives and policy changes across Europe to achieve gender equality. The strategy not only recognizes that ‘violence and sexual harassment of women in public space are strongly condemned [by the Istanbul Convention]’ but also notes a number of obstacles to gender equality which are rooted in online behaviours such as violent and degrading online content (including violent sexual threats online) and sexist online hate speech. Most recently, the EU Parliament highlighted the need to tackle online forms of VAW, including online misogyny and online harassment. Despite growing recognition at the European supranational level that violence against women is increasingly happening online, few steps have been taken in terms of law and policy making to combat these practices in a meaningful and cohesive way. In particular, limited attention has been paid to textual threats, harassment, and text-based abuse online, with the emphasis of legislators and policy makers falling predominantly on online image-based sexual abuse. Furthermore, fragmented approaches across European institutions and across EU member states compound this problem resulting in the current policy framework embodying the antithesis of equality when it comes to OVAW. This article critically examines the shortcomings of the current approaches to law and policy, highlighting the failings to date in enacting changes to address gender inequality at the European supranational level. It concludes by proposing practical solutions to addressing OVAW, especially online forms of gender-based harassment and hate speech.
Understanding the Performance Impacts Of Cross-Platform Development On IoT Applications

The Internet of Things (IoT) is an increasingly evident reality in everyday life. IoT makes possible to interconnect physical objects through a heterogeneous computer network, creating new ways to manage infrastructures. In the IoT systems, smartphones have a fundamental role due to their computational capacity and resources. Nowadays, the major mobile devices have several types of sensors that can be used to monitor and collect data from the physical world, such as GPS, accelerometer, barometer, among others. Thus, IoT developers have used different cross-platform frameworks to improve their productivity and to make the software maintainability easily and fast. In this context, the goal of this work is to understand the performance impacts of some cross-platform frameworks for IoT application development. To do this, we built three versions of the same Android application of an IoT system using (1) Ionic, (2) React Native, and (3) Java, which uses some smartphone's sensors commonly used in IoT applications, such as GPS, WiFi, and BLE. For each resource and performance evaluation metric for each version of our application, we created a specific test-case to measure and to compare the analyzed cross-platform framework. Our results showed slight differences between the three versions of our IoT application in some analyzed metrics.
WEBINAR PENGGUNAAN DESAIN SYSTEMATIC REVIEW DALAM PELAKSANAAN PENELITIAN SELAMA PANDEMI COVID-19 DI UNIVERSITAS ESA UNGGUL

Background: The Covid-19 pandemic has a negative impact on every aspect of Indonesian life. However, the learning process of academics is required to keep going. The lectures are required to conduct the three obligation of higher education, one of them is research. Webinars is delivered to present how to conduct research with a systematic review design which are seen as suitable strategies to help educators carry out the research process in the midst of the Covid-19 pandemic. Objective: to increase knowledge and skills in conducting research with a systematic review design. Method: The current virtual implementation seminar was conducted with media zoom software attended by 26 Esa Unggul University lecturers for 1 hour 30 minutes. Evaluation of participants' knowledge was carried out after a webinar consisting of 6 questions. Results: after this webinar activity, 15 of 26 participants (60%) answered all questions correctly and on average the participants answered correctly 5 of 6 evaluation questions. Conclusion: The implementation of the webinar can increase the knowledge of lectures in conducting research with a systematic review design as a suitable design alternative during the Covid-19 pandemic. Â  Keywords: webinar, systematic review, research
Deploy Docker Containers on GCP Compute Engine

In this chapter, we are going to explore Google Compute Engine and its key features, which allow us to run containers on GCP. The Google Compute Engine service sits under the GCP Compute Service offering, which includes services like App Engine, Cloud Run, Cloud Function, and more. The purpose of the compute services is to give us processing power to run applications, services, containers, and any other services that require access to CPU power. In essence, Compute Engine allows us to create and run virtual machines inside the GCP infrastructure, similar to AWS EC2 instances and Microsoft Azure virtual machines.
Codes over integers, and the singularity of random matrices with large entries.

The prototypical construction of error correcting codes is based on linear codes over finite fields. In this work, we make first steps in the study of codes defined over integers. We focus on Maximum Distance Separable (MDS) codes, and show that MDS codes with linear rate and distance can be realized over the integers with a constant alphabet size. This is in contrast to the situation over finite fields, where a linear size finite field is needed. The core of this paper is a new result on the singularity probability of random matrices. We show that for a random $n \times n$ matrix with entries chosen independently from the range $\{-m,\ldots,m\}$, the probability that it is singular is at most $m^{-cn}$ for some absolute constant $c>0$.
A Proposal of a Support System for Continued Grip Strength Measurement using Communication Robot in Older Adults at Home

The purpose of this study is to propose an intervention system that can continuously measure grip strength using a communication robot. And we verified the effect of this system. As a result, it was confirmed that the measurement behavior for three weeks could be continued by the face recognition and the voice call functions installed in the communication robot. It was suggested that grip strength is an effective index for health management of the older adults living at home. This study has shown that the communication robots are an effective tool for encouraging the continued measurement of healthcare monitoring systems.
Research Guides: Construction: eBooks

This guide should assist students in the Construction program to locate Library materials for research and projects This page will assist users in finding eBooks available through the Delta College Library
Quine’s Non-ontological Structuralism (and Mine)

In ‘Structure and Nature’ Quine advocates a ‘global ontological structuralism’, one that sees all objects, even nonmathematical ones, as positions or nodes in a structure. The term ‘ontological’ here is misleading and would be better deleted. For Quine is no ontological structuralist; in the same paper he makes it clear that he is not proposing a structuralist ontology or even an ontological doctrine in which structures are eliminated in favour of systems instantiating them. Resnick’s own mathematical structuralism evolved from a sui generis ontological form to a Quinean non-ontological form. In this chapter Resnick discusses the evolution of Quine’s structuralism and how it shaped his own.
“Ma con la B posso dirla?”: social media e percorsi di negoziazione della n-word tra appropriazione culturale e policy della piattaforma

This study aims to explore some issues related to the problems of the so-called n-word (Kennedy 2008). We refer to the context of rap music, whose transcultural consumption brings performative references to black culture (Taronna 2016) to controversial appropriations of meaning. We focus in particular on relationship between “n-word and the Italian rap scene, deepening in the context of social media some reflections that emerge within a particular audience community. Practices of participatory cultures within social web (Boccia Artieri 2012) can be an interesting clue about the collective construction of an interpretation of a controversial issue, within which we see several voices emerge on the possible contextualization of n-word uses, that have to deal with the normative negotiations of platforms policy (Gillespie 2010) and possible drifts of meaning.
Runtime Based Recommendations on Netflix Data using SBE-XGBoost model

Recommendation Systems (RS) are developed and improved to provide meaningfulrecommendations of a products or services or items to a set of users who might seek attention towards it. ManyRS were developed for the use by various real world companies like Amazon, Netflix, Spotify and some socialmedia websites etc, which uses it to make profits. The paper focuses on applying machine learning techniquesto offer recommendations on Netflix dataset by implementing Runtime based Recommendations. A runtimecomputation technique was designed to overcome the data sparsity, curse of dimensionality problem, memoryand computational issues for larger datasets. Here the experiments are performed in Google Colab platform forcomputing and analysing the large datasets. The proposed approach is a combination of Surprise BaselineEstimator (SBE) and eXtreme Gradient Boosting (XGBoost). The designed runtime computation techniqueoutperformed Matrix Factorization approaches Singular Value Decomposition (SVD) and Truncated SVD. Theproposed model SBE-XGBoost evaluated with novelistic approach by combining SBE and XGBoost model toevaluate the training and test data which gave good prediction results on test data compared to the existingsystem.
How strong will be the following earthquake?

&amp;lt;p&amp;gt;In this study, we have applied to northeastern Italy and western Slovenia medium-low seismicity an algorithm for strong aftershock forecasting we originally developed for medium-high seismicity in Italy (Gentili and Di Giovambattista, 2017). The method, called NESTORE (Next STrOng Related Earthquake), analyzes the seismicity after medium and strong earthquakes, in order to forecast if a subsequent large earthquake (SLE) will follow. A SLE following a main shock can cause significant damages to already weakened buildings and infrastructures, therefore a timely advisory information to the civil protection is of great interest for effective decision-making. We performed the analysis on different time-spans after the mainshock, in order to simulate the increase of information available as time passes during the seismic clusters. NESTORE subdivides the clusters of seismicity into two classes: &amp;amp;#8220;A&amp;amp;#8221; if the difference in magnitude between the mainshock and the strongest aftershock is lower than 1, and B otherwise. Several statistical features based on time-space and energy evolution of seismicity are analyzed separately and, if they are sufficiently informative for SLE forecasting, they are used for independent decision trees training. The results are merged together by a Bayesian approach, obtaining a time-dependent probability Prob(A) to have an A cluster, i.e. to have at least one SLE. This study is possible thanks to the OGS bulletins, an accurate local catalogue, characterized by low completeness magnitude, compiled by the National Institute of Oceanography and Experimental Geophysics. We tested the method on 1976 highly destructive Friuli cluster (mainshock magnitude 6.5 &amp;amp;#8212; the strongest in the last 80 years in the region) and on two small clusters of seismicity in NE Italy in 2019, obtaining encouraging results: 6 hours after the mainshock, for two A clusters NESTORE supplies Prob(A)=98% while for the B one Prob(A)=2%.&amp;lt;/p&amp;gt;
간호대학생의 COVID-19 감염 예방을 위한 사회적 거리두기 영향요인

Purpose: This study aims to understand the effect of attitudes toward COVID-19, subjective norms, and intentions toward social distancing as a preventative measure for COVID-19 in nursing university students, and to provide basic data for COVID-19 prevention. Methods: A cross-sectional study design was used in this study. The participants included 169 nursing students at a university in G city. Data were collected from 22 May 2020 to 1 June 2020. A self-report questionnaire was used. Data were analyzed using descriptive statistics, t-test, ANOVA, Pearson correlation coefficients, and multiple regression analyses with the IBM/SPSS 26.0 for Window Program. Results: Intention was the most influential factor on social distancing (β=.29, p=.002), followed by the number of breakfasts per week (β=.18, p=.005), school grade (β=-.16, p<.001), and smoking status (β=-.13, p=.046). These variables explained 35.0% of factors influencing social distancing (F=12.24, p<.001). Conclusion: The results of this study are meaningful and present a direction for nursing students and future medical personnel to effectively perform social distancing. It is necessary to educate nursing students so that they can practice proper health care habits and intentions for social distancing.
Safety Education in Primary and Secondary Schools based on Big Data

With the continuous development of primary and secondary education, higher requirements are put forward for the development of safety education. Therefore, a study on the effectiveness of primary and secondary school safety education is proposed based on big data. Firstly, a simple improvement model is designed for the safety education of primary and secondary schools. This model can be more targeted and achieve optimal education. Then, based on the security education model, the algorithm of data analysis is added to further improve the pertinence of security education. In order to test the feasibility of safety education, the accuracy of the test is passed through the data for safety education, and the results of the test are shown to be feasible. The application of this model has effectively improved the safety awareness of primary and secondary school students and further strengthened campus safety
Improve frequent pattern mining in spatial database with fpar and tfp

Improve frequent pattern mining in spatial database with fpar and tfp - Spatial database is defined data related to space such
Introduction to wavelet transform and two stage image de noising using principal component analysis with local pixel grouping (lpgpca) method

Introduction to wavelet transform and two stage image de noising using principal component analysis with local pixel grouping
Classification of Traditional Batik Motifs in Central Java using Gabor Filter andBackpropagationNeural Network

Batik has a variety of varied motifs, each region in Indonesia has certain characteristics on batik motifs. Based on literat ure studies the use of backpropagation neural network methods to recognize complex patterns has a satisfactory rate of success. The purpose of this research is to develop and apply neural networks that are fast, precise and accurate to classify batik desig ns and patterns . Types of batik motifs typical of Central Java that are used include; Truntum from Solo, Warak Ngendhog from Semarang, Sekar Jagad from Lasem, Burnt from Pati, and Jlamprang from Pekalongan. The image first undergoes RGB color feature extra ction based on mean values of R, G, and B, and Gabor filter texture characteristics. The tests were carried out using 90 batik images, 60 batik images for training data and 30 batik images for testing data. The results of the study concluded that the best parameter setti ngs were, the number of hidden layer 30 neurons in the first layer and 15 in the second layer, with 6 input layers and 5 output layers. Gabor filter with 90Âo orientation angle and wavelength 4 become the best combination in this study. From the results of training and testing results obtained an average accuracy of 93.3% in all batik classes in Central Java.