Reviewerly/exHarmony huggingface dataset:
Evaluating Restrictions in Pattern Based Classifiers

Generalizations, also known as patterns, are in the core of many learning systems. A key component for automatically mine generalizations is to define the predicate to select the most important ones. This predicate is usually expressed as a conjunction of restrictions. In this paper, we present an experimental study of some of the most used restrictions: the minimal support threshold, the jumping pattern and the minimal pattern. This study that uses 93 databases and two different classifiers reveals some interesting results, including one that should be very useful for building better classifiers: using minimal patterns could degrade the accuracy.
Sociocultural and legal aspects of the education-related migration in Russia

In this article, the prospects of the implementation of the new State migration policy framework of the Russian Federation for 2019-2025 as applied to student migrants are analyzed. We have studied the educational process for foreign students at all levels of higher education as a part of education-related (study-related) migration. We have defined the following three aspects: social, cultural, and legal as equivalent factors of adaptation and socialization for foreign students. We highlight that apart from the basic learning competencies, it is crucial to develop skills for communicating in the language of the host country while acknowledging the basic values of the social and cultural realia that are new for foreign students. The teacher has a significant role in the organization of the education process for foreign students. We have studied the stages of students’ adaptation and integration into the new sociocultural and academic environment. The hypothesis is that it is crucial to learn and take into account national and psychological characteristics of student migrants from around the world. We provide examples based on the research results of the adaptation analysisof Volgograd State Technical University foreign students. We also provide recommendations for the organization of the education process and communication with foreign students.
Impact of Cereals Production and Cross-border Trade on Food Security in Nigeria: A Time Series Analysis between 1986 and 2017

This study aims to examine the impact of cereals production and cross-border trade on food security in Nigeria between 1986 and 2017. The Autoregressive Distributed Lag (ARDL) econometric technique was employed to analyze the time series secondary data sourced from World Bank Development Indicators, 2017 in order to explain the relationship between food security and the cereal production and cross-border trade. The findings of this study reveal that both in short-run and long-run estimation of error correction model (ECM), cereal domestic production, cereal exports and cereal imports have significant impact on the food security. Accordingly, cereal domestic production and cereal imports have a positive sign, which implies that an increase in cereal domestic production and cereal imports influence food security. While, cereal exports have a negative sign, which suggest that Nigeria as a nation is experiencing deficit in cereal production and therefore, the little quantity produced and exported posit a treat to food security. Based on the findings of this study, it is therefore recommended that policy formulation such as government subsidies in the agricultural sector and any other intervention programmes that will encourage an increase in domestic cereal production as well as policy formulation that will not totally discourage cereal importation should be implemented since its impact on food security is positive. This can be achieved through trade liberalization. On one hand, in as much as cereal export have significant impact on food security; government should be mindful that policy formulation on cereal exports should take into consideration the level of domestic cereal production and consequently its negative impact on food security.
Open the Boxes of Words: Incorporating Sememes into Textual Adversarial Attack

Adversarial attacks are carried out to reveal the vulnerability of deep neural networks. Textual adversarial attacking is challenging because text is discrete and a small perturbation can bring significant change to the original input. Word-level attacking, which can be regarded as a combinatorial optimization problem, is a well-studied class of textual attack methods. However, existing word-level attack models are far from perfect, largely because unsuitable search space reduction methods and inefficient optimization algorithms are employed. In this paper, we propose a novel attack model, which incorporates the sememe-based word substitution method and particle swarm optimization-based search algorithm to solve the two problems separately. We conduct exhaustive experiments to evaluate our attack model by attacking BiLSTM and BERT on three benchmark datasets. Experimental results demonstrate that our model consistently achieves much higher attack success rates and crafts more high-quality adversarial examples as compared to baseline methods. Also, further experiments show our model has higher transferability and can bring more robustness enhancement to victim models by adversarial training. All the code and data of this paper can be obtained on this https URL.
An Efficient Density Parameter-Light in Enhanced Subspace Clustering in High Dimensional Data

Subspace clustering identifies the clusters stored in subspaces of a high dimensional dataset.Various Density-based strategies have been determined to mine clusters of arbitrary shape successfully even in the appearance of noise in full dimensional space clustering techniques.The performance and result of a subspace clustering algorithm highly depend on the parameter values of the algorithm is tuned to execute.Although determining the proper parameter values are crucial for both clustering quality and performance of the algorithm.Further, as high dimensional data has converted more and more prevalent in real-world applications due to the advances of vast data technologies.Precisely Density-based subspace clustering have gained their importance owing to their ability to identify arbitrary shaped subspace clusters.Density Divergence Query is an essential subject in high dimensional data clustering.Density divergence involves having various subspace cardinalities for complex region densities.To defeat this problem, Efficient-EnSubClu employs an efficient subspace clustering model.It discovers the clusters using different epsilon density thresholds in various subspaces.In this research, we propose an Efficient enhanced Subspace Clustering Model named Efficient-EnSubClu (Enhancement of ENSUBCLU) for discovering precise values of parameters in subspace clustering.It allows efficient neighboring core points to be clustered and find quality subspace clusters satisfying specific qualitative and quantitative properties.Furthermore, apply the post-processing clustering steps on each found subspaces.It aims a merging model at the first step of evaluation of clusters connected with DBSCAN algorithm.Also, find the number of subspace clusters in a particular dimension and calculate the low mean dimensionality of subspace clusters.It represents every cluster with a fewer number of dimensions as visible from the low utility of mean dimensionality.Hence, we can obtain knowledge more concisely with an enhanced quality of clusters in terms like Accuracy and Silhouette Coefficient.
A Bio-Inspired Methodology for Digital Imaging Forensic Detection

The increasing number of digital media users, as well as the development of multimedia platforms, such as smartphones and tablets, has also increased the number of users who professionally and fraudulently manipulate all types of digital media. This paper proposes a methodology based on an image processing pipeline to detect mainly copy-move type frauds, which are intended to hide or enlarge visual information. Our proposal has been tested in a Copy-Move Forgery database and the results were equal or better in performance than the state-of-art methods.
A New Method to Evaluate Subgroup Discovery Algorithms

A Subgroup Discovery algorithms is usually considered better than other method if the average of all its mined subgroups is higher, with respect to some predefined quality measures. This process has some drawbacks: it ignores the redundancy in mined patterns and it might hide important differences among algorithms that return subgroup sets with the same averaged value. In this paper, we propose a new method to evaluate and compare subgroup discovery algorithms. This method starts by removing redundancy using a novel procedure based on the examples covered by the patterns and the statistical redundancy between them. Then, a new similarity and quality methods is used to compared the algorithms based on their ability to detect the patterns and the quality of the mined patterns, respectively. The experimental results obtained show some interesting results that would be unnoticed by the traditional approach.
Anxiety and informal education (cross-cultural aspect)

Introduction.Secondary education system in the post-soviet countries experience a significant crisis -traditional methods of education lose their significance under the influence of information society development and globalization.The courses, trainings, distance learning and other forms of informal education is starting to spread instead.Therefore, research of the informal education influence on its participants` mental health is particularly relevant.Purpose.The purpose of the study was to identify the mutual anxiety of parents and students from staying in the informal education system in two countries with different mentality -Ukraine and Vietnam. Design/Methodology/ApproachThe study had two stages: a survey of parents whose children are involved or not involved in informal education and a survey of teen students involved in traditional and informal education systems.The participants of a survey were 215 parents having school age children (143 Ukrainian and 72 Vietnamese).All of the Ukrainian surveyed parents were residents of large cities of Ukraine: Kyiv, Kharkiv, Lviv and Dnipro, where exists the wide range of non-formal education options; Vietnamese participants are residents of Biên Hòa city, Dong Nai province.In total, these parents have 346 children who are involved in different educational options.For this research we used E.S. Schaefer`s and R.Q.Bell`s Parent Attitude Research Instrument (PARI) in adaptation of T. V. Nescheret, Spielberg-Hanin test of state anxiety level and author's questionnaire.In addition, we examined Ukrainian and Vietnamese children enrolled in general education schools, in distant learning and in combined general-informal education with English courses.In total 208 children were studied, 140 of them are Ukrainian and 68 are Vietnamese.For children` survey we used Phillips` School Stress and Anxiety level test and Pip Wilson`s Blob Tree test.The study found that the parents` choice of the educational form for their children depends on such peculiarities of parental attitudes as anxiety, overprotection desire, excessive control and their own schooling and informal education
An Unforeseen Equivalence Between Uncertainty and Entropy

Uncertainty and entropy are related concepts, so we would expect there to be some overlap, but the equality that is shown in this paper is unexpected. In Beta models, interactions between agents are evidence used to construct Beta distributions. In models based on the Beta Model, such as Subjective Logic, uncertainty is defined to be inversely proportional to evidence. Entropy measures measure how much information is lacking in a distribution. Uncertainty was neither intended nor expected to be an entropy measure. We discover that a specific entropy measure we call EDRB coincides with uncertainty whenever uncertainty is defined. EDRB is the expected Kullback-Leibler divergence between two Bernouilli trials with parameters randomly selected from the distribution. EDRB allows us to apply the notion of uncertainty to other distributions that may occur in the context of Beta models.
Signal Processed Texture Features

Signal processing methods analyze the frequency content of the image. Texture features are then extracted from the transformed (frequency domain) images.
Development of Framework for Information System Strategy Formulation

This study aims to develop a framework that can be used to assess the quality of information system services and formulate an improvement strategy. The method used in the research is qualitative methods. The proposed framework is a combination of SERVQUAL and Kano to measure the quality of information system services and Quality Function Deployment (QFD) to determine its improvement strategy. The proposed framework has 6 (six) stages, namely: (1) determining user requirements (UR), (2) determining the importance of UR, (3) determining technical requirements (TR), (4) determining UR correlation with TR, (5) determine the importance of TR, and (6) determine the priority of implementing the strategy. The highest priority is occupied by TR with the largest value, while the lowest priority is occupied by TR with the smallest value.
Occupancy Visualization towards Activity Recognition

We present a sensor visualization system that integrates data streams from individual custom sensor arrays together with Building Automation System (BAS) data. To help bridge the gap between actual building usage by the occupants, and the aggregate assumed usage by the control system, we have developed several sensor processing subsystems moving toward automated human activity recognition without the need for directly instrumenting the occupants. By having a system with a detailed understanding of occupancy behavior and needs, we believe buildings could be much more efficient thereby reducing energy consumption, working toward sustainability of the built environment.
Model Based Texture Features

Model-based texture analysis attempts to represent an image texture using the stochastic model and generative image model.
A New Discriminative Feature Learning for Person Re-Identification Using Additive Angular Margin Softmax Loss

In this paper, a new end-to-end framework is proposed for person re-identification (re-ID) by combining metric learning and classification. In this new framework, the Additive Angular Margin Softmax is used which imposes an additive angular margin constraint to the target logit on hypersphere manifold. This is aimed to improve the similarity of the intra-class features and the dissimilarity of the inter-class features simultaneously. Compared with the three popular used softmax-based-loss methods, the experiments show that the proposed approach has achieved improved performance on Market1501 and DukeMTMC-reID datasets for person re-ID.
Low-Power Advanced Encryption Standard for Implantable Cardiac Devices

Advanced Encryption Standard (AES) is one of the most popular and widely adopted symmetric encryption/decryption algorithms. The increasing use of AES in severely power constrained devices such as the implantable cardiac devices makes the low power implementation of AES critical. Traditionally, one of the AES core functions, ShiftRows, is accomplished by implementing a series of shift registers. In this paper we propose a new power efficient implementation of AES by introducing a new realization of the ShiftRows operation using muxes. Simulations of these implementations, using 45nm and 90nm technology nodes, yielded respective averages of 13.5% and 10.6% reduction in overall power consumption of AES.
Real-time people detection from thermal images by using an Unmanned Aerial System

In this paper a real-time approach for human bodies detection at outdoors environments by using thermal images taken from an Unmanned Aerial System (UAS) is presented. The first step of the proposed algorithm consist on the extraction of the thermal signature of human bodies. After that, we used the Moments Representation technique as a shape descriptor to identify human presence in a scene. Finally, a robust controller is developed to enable the multi-rotor vehicle to track a desired reference in order to scan a region of interest. To show the effectiveness of the developed algorithm when it is implemented on an octorotor vehicle, a set of real-time experimental test were conducted and we present the obtained results.
Investigation of Frauds in Signature Rubber-Stamps

In the 21st century, new digital electronic technologies like computer, scanner, digital camera, computerized photo-stat machines and different types of printers, editing soft-wares are used, which can be utilize to commit document frauds. Rubber-stamps are used as an official seal describing government, private officer’s designation, department information etc. They sometimes use rubber-stamp for authentication, certification or verification of original documents. Fraudster uses digital technology to develop imitation of ‘signature rubber-stamp’ to perform white caller crime. Such rubber-stamps containing ‘Signatures’ and utilize it for committing crime by applying on documents. This is a case study, which defines a specific modus operandi used by fraudsters in India. Authors have investigated such modus operandi of fraud, which is very difficult to identify by a layman. This type of modus operandi could only be detected with the scientific instrument namely VSC-6000/HS with different functionality. The main aim of this research work is to develop simple, rapid, sensitive, eco-friendly and non-destructive method to identify signatures applied with rubber-stamps. The research in such field will be directly beneficial to society, financial institutions, law enforcement agencies which give additional motivation to do research for examination of questioned documents.
MOTION GRAPHIC "AKHLAK" SEBAGAI MEDIA EDUKASI PENYIMPANGAN PERILAKU SOSIAL PADA REMAJA

Adolescence is a transition from children to adulthood, usually this is a very vulnerable period for parents because at this age children begin to look for identity. Teenagers begin to want to have their own desires and no longer want to be regulated by parents because they already feel as adults. Environmental factors in the residence and school environment are very influential on the stability of development in adolescence. Teenagers who are out of control and unable to control themselves will very easily fall into social behavior deviations such as fighting with friends, brawl to drug abuse. To help the school and parents in overcoming this problem, media education needs to be deviated social behavior in adolescents based on visual multimedia. Visual multimedia technology was chosen because this media tendency is much easier to be accepted and understood by teenagers compared to just a lecture or seminar. The making of educational media for social behavior deviations in adolescents was built using motion graphic techniques. Then for the development method used is the Multimedia Development Life Cycle. The results obtained in this study in the form of motion graphics with the title of Morals with duration 00: 02:20.
Carrying advertising messages across media and borders: multilingualism and multimodality in international campaigns

Multimodality is a ubiquitous feature of advertising, especially in new digital media, which incorporate different modes, such as pictures (including moving pictures), text (including subtitles) and sound.In addition to this multimodal character, more often than not, such platforms often provide multilingual experiences, as they are normally designed to be used across different countries and cultures.They thus offer significant opportunities to analyse translational strategies in multimodal texts and seem to bring a different light to concepts traditionally discussed in translation research, especially dichotomies such as source/target text and original/translated text.This article will attempt to raise some of these issues, namely the way multimodality and multilingualism are handled in international promotional messages, by examining the websites of two international brands.
ANALISIS DAN DESAIN APLIKASI PEMBELAJARAN METAMORFOSIS KUPU-KUPU BERBASIS AUGMENTED REALITY

Augmented Reality is one of technology that combines virtual world objects with the real world that allows it to be applied to Android-based smartphones because its users have penetrated into the realm of children. The need for analysis and design before building applications that later can help facilitate teachers in learning by displaying 3D objects and animations that make Students more interested in paying attention to the material provided and becoming more active in participating in the learning process. The purpose of this study is to analyze and design learning applications for Butterfly metamorphosis using Augmented Reality as an alternative learning media. Methods of collecting data are literature, observation, and interviews. The results of this study are in the form of application design regarding the metamorphosis phase of Butterflies ranging from caterpillars, larvae, pupae, to cocoons.
A Reference Conceptual Model for Virtual Network Function Online Marketplaces

Recently, we witnessed a shift in the Networking paradigm, with large part of the network control moving from hardware to software. This move has been accompanied by an increase of interest in declarative software models (conceptual models) for the domain. Moreover, novel architectures allow services to be deployed in multiple domains. These changes call for new business models to allow the commercialization of Virtual Network Functions (VNFs). This paper proposes the creation of an ontology-based reference conceptual model to support VNF Marketplaces, allowing VNF vendors and infrastructure providers to commercialize VNFaaS (VNFs as services). The proposed reference model has been engineered by using foundational ontology techniques (UFO/OntoUML), it has been formally validated by using model simulation techniques, and it has been implemented in OWL.
PENGARUH CARA MENGGOSOK GIGI TERHADAP KARIES GIGI ANAK KELAS IV DI SDN SATRIA JAYA 03 BEKASI

This research is motivated by the number of dental caries experienced by children in grade IV SDN Satria Jaya 03. The purpose of this study was to examine the effect of how to brush teeth on dental caries. The method used is a quantitative method. The results showed that there was a significant influence on how to brush teeth correctly on dental caries of class IV SDN Satria Jaya 03 Bekasi. This is evident from the results of the t test calculation of 7.52 greater than t table of 2.02. Thus it can be concluded that there is an influence on how to brush teeth correctly on dental caries of class IV SDN Satria Jaya 03 Bekasi.