Reviewerly/exHarmony huggingface dataset:
Towards Communication-Efficient Distributed Background Subtraction

Road traffic monitoring is one of the essential components in data analysis for urban air pollution prevention. In road traffic monitoring, background subtraction is a critical approach where moving objects are extracted via facilitating motion information of interest to static surroundings, known as backgrounds. To work with various contextual dynamics of nature scenes, supervised models of background subtraction aim to solve a gradient-based optimization problem on multi-modal sequences of videos by training a convolutional neural network. As video datasets are scaling up, distributing the model learning on multiple processing elements is a pivotal technique to leverage the computational power among various devices. However, one of major challenges in distributed machine learning is communication overhead. This paper introduces a new communication-efficient distributed framework for background subtraction (CEDFrame), alleviating the communication overhead in distributed training with video data. The new framework utilizes event-triggered communication on a ring topology among workers and the Partitioned Globally Address Space (PGAS) paradigm for asynchronous computation. Through the new framework, we investigate how training a background subtraction tolerates the trade-offs between communication avoidance and accuracy in model learning. The experimental results on NVIDIA DGX-2 using the CDnet-2014 dataset show that the new framework can reduce the communication overhead by at least 94.71% while having a negligible decrement in testing accuracy (at most 2.68%).
Female education and economic growth: an empirical investigation for Egypt

Since the 1970s, Egypt has been pursuing policies to boost female education. However, no empirical study has attempted to quantify the impact of female education on the Egyptian economy. This paper examines the effect of female education on economic growth in Egypt between 1971-2014, using time-series analysis. Cointegration test and error correction model are utilised to examine long-run relationship and short-run Granger causality between female versus male education and economic growth. Results suggest that the expansion of female education does not Granger cause economic growth in the short-run. The remarkable finding of the study is that female education has a significant positive impact on economic growth in the long-run even more pronounced than that of male education, labour and capital. The paper recommends a number of policy interventions to boost women's education impact on sustainable economic growth in Egypt.
Image Recognition Algorithm Based on Deep Learning

Image Recognition (IR) is one of the important research topics in the field of computer vision and pattern recognition, and it is also an important tool for the realization of an intelligent society in the future. Deep learning is a process of simulating the human visual system and the cognitive link of the human brain, extracting data features in a structured manner, and finally obtaining the deep information of the image. The whole training process can get a good IR effect without manual participation. The purpose of this article is to research IR algorithms based on deep learning. This paper firstly summarizes the algorithms of IR and deep learning. Aiming at the problems of deep learning objective cost function that is easy to fall into local minimum, slow convergence speed and over-fitting, it proposes the improvement of the algorithm on the deep learning model. At the same time, analyze and design the relevant parameters that affect the model to optimize the model. This paper proposes the weight threshold parameter variable analysis method, the original golden section method, the network structure determination method based on the sensitivity of network nodes, and the pyramid model structure method based on the convolutional network. The experimental results show that the algorithm based on the node sensitivity structure can recognize 1000 images in 3.14s, and the recognition accuracy rate is 98.6%, which is better than other methods.
Implementasi LSTM Pada Analisis Sentimen Review Film Menggunakan Adam Dan RMSprop Optimizer

Movies are an entertainment that is in great demand by many groups from children, teenagers, adults, and parents. In the current digital era, various films can be watched on television to digital streaming services. Public opinion on the films watched can be in the form of positive opinions or negative opinions. Sentiment analysis is one of the fields of Natural Language Processing (NLP) which is able to build a system to recognize and extract opinions in the form of text, sentiment analysis is usually used to find out people's opinions or assessments of a products, services, politics, or other topics. Through sentiment analysis from the collection of reviews, the public can get various recommendations for films that can be watched. The method implemented to classify review data into positive reviews and negative reviews in this study is LSTM by comparing two different optimizers, namely Adam and RMSprop. This study succeeded in providing sentiment predictions with different optimizers with accuracy values ??for the LSTM application with Adam Optimizer reaching 77.11% and the LSTM application with RMSprop reaching 80.07%.
The Problem of Autopoiesis of Technogenic Civilization and the Formation of Value Base for the Use of Digital Technology

The paper discusses the self-reproduction ability of the existing technogenic civilization and the issues of the influence of self-reproduction mechanisms on the formation of axiological grounds for the use of digital technologies generated by this civilization. The self-reproduction of civilizational structures is considered through their constant repetition in the process of communication. In existing philosophical and sociological studies based on systems approach, the term autopoiesis, introduced for these purposes in the works of N. Luhmann, has already been used to describe such processes. Considering the autopoiesis of the technogenic civilization, the articles relies on the works of V.S. Stepin to determine the main features of that civilization. As a result of the conducted research, it was revealed that the existing internal contradictions of the technogenic civilization that can lead and are already leading to its crisis, including the value one, are caused by simultaneous presence of mutually non-complementary autopoietic structures: (1) the ones related to the industrial and post-industrial era and to the scientific worldview; (2) and structures that have passed into modernity from the pre-industrial era, and yet still are have value and cultural significance in modern society. The author concludes that, forming the value foundations of the use of modern digital technologies, the technogenic civilization is forced to overcome the abovementioned gaps in its own autopoietic structures and create value systems free from these contradictions.
LOGIC: A Coq Library for Logics

LOGIC is a Coq library for formalizing logic studies, concerning both logics’ applications and logics themselves (meta-theories). For applications, users can port derived rules and efficient proof automation tactics from LOGIC to their own program-logic-based verification projects. For meta-theories, users can easily formalize a standard soundness proof or a Henkin-style completeness proof for logics like classical/intuitionistic propositional logic, separation logic and modal logic with LOGIC’s help. In this paper, we present how compositional and portable proof engineering is possible in LOGIC.
ONLINE EDUCATIONAL PLATFORMS AS A MEANS OF ORGANIZING A DIGITAL EDUCATIONAL ENVIRONMENT IN A MODERN SCHOOL

the article substantiates the need to organize a digital educational environment in a modern school. The content of the concepts “digital educational environment”, “online educational platform” is disclosed. The importance of the use of online educational platforms by teachers in their professional activities as a means of organizing a digital educational environment is substantiated. The available online educational platforms for modern schools are highlighted: Learn.ru, Russian Electronic School, Yandex.Textbook, Yaklass, Open School, My achievements. A brief description of them is given, the advantages of their use in school are described.
Study on Reduction of Side Slippage for Cutting Weeding Vehicle with Outrigger Arm

In recent years, the population of agricultural workers is declining and aging in Japan. Therefore, the management of weeding on the levee slope is a heavy burden. As part of new agriculture, research and development of levee slope weeding robots is progressing rapidly. However, as critical problem, there is the occurrence of sideslip when crossing a slope. In previous studies, the camber angle mechanism was proposed, and then its effectiveness was verified by some traveling experiments on slope. However, it was found that the blades for the mowing mechanism made the surface of ground contact directly. Therefore, this study proposes the weeding cutting vehicle with“ Outrigger Arm ”to reduce sideslip during working on steep slope. Actually, the effectiveness of proposed vehicle was confirmed by some traveling tests on real state.]
PSYCHOLOGICAL AND PEDAGOGICAL SUPPORT OF THE EMOTIONAL DEVELOPMENT OF CHILDREN OF LATE PRESCHOOL AGE BY THE MEANS OF VISUAL ART

The article clarifies the essence of psychological and pedagogical support of the individual and reveals the features of psychological and pedagogical support of the emotional development of late preschoolers. Ways and methods of organizing classes with elements of visual arts in the form of sand painting have been presented. Conclusions about the benefits of creative activity for the child's emotional sphere development have been made.
Participation Analysis of Class IV A Female Students in Learning at SD Kemala Bhayangkari 10 Porong

This study aims to describe the participation of female students at IV A SD Kemala Bhayangkari 10 Porong. This research is a qualitative critical research. The subject of this study was fourth grade students of SD Kemala Bhayangkari 10 Porong. Data collection techniques using observation, interviews, and documentation. The data analysis in this study uses domain analysis, compound analysis, taxonomy analysis and theme analysis. Data validity techniques using technical triangulation. The results showed that the participation of female students in grade IV A SD Kemala Bhayangkari 10 Porong was low. Internal factors that influence the low participation of female students in grade IV A are psycological factors, namely the interest of female students based on the attitude of subjects. External factors that influence the low participation of female students in grade IV A are school factors, namely the stereotype of male students towards female students’ intellectual and symbolic violence in the relationship between teacher and child.
Corruption, Political Instability and Mortality in Africa: A Panel-Var Approach

This paper attempts an empirical examination of the interaction between corruption, political instability and the mortality rate, as well as their transmission mechanisms in Sub-Saharan Africa. We use panel VAR techniques to test the causality and the cointegration between these three variables across a sample of 52 African countries covering the period from 1960 to 2016. Our results provide evidence of a unidirectional relationship going from corruption to political instability and from political instability to the mortality rate. We also find that an increase in corruption can create a climate of political instability which leads to an increase in the mortality rate. We subsequently suggest some policy implications.
Property-Driven Code Obfuscations Reinterpreting Jones-Optimality in Abstract Interpretation

Jones-optimality determines whether a specializer improves program performances. Reinterpreting this concept in terms of the precision of an abstract interpreter means to determine whether specializing a source program is able to improve the precision of a given static analysis. In the opposite direction, a specializer failing optimality (disoptimal) would decrease the precision of the analysis when applied to the specialized code. In this paper, we exploit this reinterpretation of Jones-optimality relatively to the precision of an abstract interpreter with the aim of systematically deriving obfuscated code. In line with the idea behind Futamura’s projections, we factorize the construction of the obfuscated code by separating specialization and interpretation. An interpreter specializer is then systematically made disoptimal by means of language transduction. The result is a language agnostic code obfuscator which is able to foil any given static analyzer.
Cryptography: Confidentiality

Confidentiality of data is enforced by using encryption. Encryption algorithms can be symmetric – here sender and recipient of a message need the same key – or asymmetric – sender and recipient use different keys. In this chapter, we focus on aspects of encryption that are crucial for the security of cryptographic applications on the Internet but are not fully covered in textbooks. Here are some examples: We discuss block cipher modes but not the AES algorithm’s internal structure.We do not discuss algorithms for integer factorization and their relevance for the security of the RSA algorithm, but rather the encoding (PKCS#1) of the message to be encrypted. We explain how hybrid encryption works. The security of Diffie-Hellman-based cryptography is discussed in detail to reflect the importance of this building block in protocols such as SSH, IPsec IKE, and especially TLS. The question if a specific encryption algorithm is secure can only be answered if we have a clear concept of what “security” means. Thus we conclude this chapter with a discussion of the most important security definitions.
Story Generation Based on Multi-granularity Constraints

Generating a coherent story is a challenging task in natural language processing, which requires maintaining the coherence of plots and inter-sentence semantics throughout the generated text. While existing generation models can generate texts with good intra-sentence coherence, it is still difficult to plan a coherent plot and inter-sentence semantics throughout the text. In this paper, we propose a novel multi-granularity constraints text generation model, which constrains at the token level and sentence level, respectively. For the plot incoherence issue, the token-level constraint is added, which is a new plot guidance method to maintain the coherence of the plot while avoiding the introduction of extra exposure bias. For the problem of semantic incoherence, an auxiliary task of modelling the semantic relations between sentences is designed on the sentence-level constraint. Extensive experiments have shown that our model can generate more coherent stories than the baselines.
Applying Rough Set Theory for Digital Forensics Evidence Analysis

With the growth of digital crime and the pressing need for strategies to counteract these forms of criminal activities, there is an increased awareness of the importance of digital forensics. However, due to the poor quality or the availability of incomplete information, the evidence gathered from a crime scene may not always be optimal in practical situations. Digital evidence can be present in different kinds of devices and in many different forms, much of which is found in an imprecise format making it very difficult to be analyzed. We propose the use of Rough Set theory for the classification of digital evidence. Rough Set theory is a computational model which is an effective tool for analyzing uncertainty and incomplete information. In this paper, we apply a Rough Set model to two digital forensics datasets proving Rough Set to be a valid tool that can be used for digital forensics investigations. We applied two algorithms for feature selection namely, Recursive feature elimination and Fuzzy Rough feature selection. Additionally, various algorithms such as Support Vector Machine (SVM), Naïve Bayes, Decision Tree (J48), Logistic Regression, and Rough Set theory were used for classification. Rough Set when used for both feature extraction and classification gives higher accuracy compared to other algorithms.
Opposition-Sooty Tern Algorithm for Fuzzy Control Optimization of an Inverted Pendulum System

This paper presents a novel Opposition-Sooty Tern Algorithm (OSTA) which is an improved version of the original Sooty- Tern Optimization Algorithm (STOA). An opposition scheme is incorporated into the STOA structure. This is to enhance the exploration and exploitation of all searching agents throughout a feasible search area. In solving a real-world problem, the algorithm is applied to optimize parameters of a fuzzy logic model for controlling cart's position and pendulum's angle of an inverted pendulum system. Result of the optimization test shows the OSTA has a better accuracy performance compared to its predecessor algorithm. For controlling the inverted pendulum, both OSTA and STOA acquired sufficiently good control performance for the system. However, the fuzzy control scheme optimized by OSTA has resulted in a better tracking and control performance for both cart's position and pendulum's angle.
Effects of Virtual Space in Soccer Tactical Instruction

When soccer coaches provide tactical knowledge to players, they use soccer tactic boards and films. However, players often struggle to understand the instructions because the players require spatial cognition skills to convert information from a bird’s-eye view or third-person view to a first-person view. Therefore, we have created a system that can present the content of instruction from a first-person perspective using a virtual space to support spatial cognition. According to the experiment result, the proposed system improved the players’ tactical understanding and tactical performance. To evaluate the system’s effectiveness, we conducted a comparative experiment in which tactical instructions were given from three different perspectives: first-person view, bird’s-eye view, and third-person view. According to the experiment result, the proposed system improved the players’ tactical understanding and tactical performance.
EDUCATION MANAGEMENT ACCORDING TO THE „NEW RULES”

The pandemic coronavirus brought major disruptions to education between 2020 and 2022, giving an important role to online education/ learning. Attendance at online courses has largely depended on the existence of computer/laptop and internet connections. Family involvement in children’s education was crucial, sometimes being forced to assume the role of teachers. It is sad but thru that, the success of the children during this period largely depended on the financial situation of the parents. The unpreparedness of students in the online teaching and learning process from the beginning over time was replaced with quality and competency in the use of communication and technology. The need for teachers was underlined by the crisis. Virtual learning versus traditional in-person learning has been the favourite topic of debate for scientists in 2021. The detailed analysis of the weaknesses and strengths fills whole volumes, but most of them agree with one thing a strong education means combining them. Knowledge management in a virtual environment is difficult and requires a lot of attention and skills. The composition of the virtual pedagogical portfolio must be done in the interest of the students. Adapting the curriculum to local needs is a demand for a successful education, satisfied students who will be capable to assume a role in economic development. We must not lose sight of the fact that by 2022 over 50 million students are enrolled on the most popular online platforms. The development of a new educational system that is sustainable and equipped for all kinds of unexpected scenarios is a global necessity.
TEA/COFFEE AND THEIR WORD ASSOCIATES FROM THE BINOMIAL PERSPECTIVE IN TEACHING ENGLISH

In search of diversification of the teaching process, the paper suggests that foreign language can be acquired relying on word associations and at the same time involving binomial pairs. To provide a relatively substantial data on word associations a survey has been done. Two words for drinks and their word associates from the binomial perspective are at the core of the research. A couple of subsections can be distinguished in it as different groups of respondents have completed two types of a questionnaire. A comparison between the associations produced in a mother tongue and in a foreign language contribute to the understanding of the way words are stored in learner’s mind. In addition, the research leans on a couple of corpora which illustrate the aspect of language usage surprisingly different at times from what can be inferred from the answers of the informants.
Chapter 9: ES for Distributed Delays

9.1 ▪ The Bewildering, Perilous Effect of Distributed DelaysAs challenging as discrete delays on the input are for the control designer, such as in the system Ẋ(t) = AX(t)+BU(t−D), they are benign in comparison with distributed delays. Let us illustrate this.
The Effect of Wordwall Based Media on Students' Procedure Text Achievement in Ninth Grade Students

The goal of this study was to analyse if there was a difference in student achievement in class IX when utilizing the Wordwall application to write procedure texts. Post-test In this study, only the Control Group Design was used. The students in this study were grade IX. One complete group cluster random sampling was utilized to collect the sample. There were two sample groups in this study: an experimental group that was taught using the Wordwall application, and a control group that was taught using the traditional technique or without the use of the Wordwall program. A post-test was used to collect data after the two groups received different treatments for seven meetings. The data was then analyzed using descriptive statistical analysis and inferential analysis. The experimental group scored better in writing, with a mean score of 77.20 compared to 73.70 for the control group, according to descriptive statistical analysis. Furthermore, based on hypothesis testing in inferential analysis, the computed t value = 2.112 (tobs) is greater than the t table value of 2.001 (tcv) with a standard alpha level (a = 0.05). As a result, the first hypothesis is rejected in favour of the alternate hypothesis. As a result, it can be determined that there is a significant difference in the learning accomplishment of class IX students when it comes to creating procedural texts utilizing the Wordwall application.