Reviewerly/exHarmony huggingface dataset:
The Inclusion of Sociolinguistic Context in the Text Materials of English Text Books for Junior High School

This research is conducted for two main objectives, (1) to identify whether the sociolinguistic contexts have been included in the presentation of interpersonal and transactional text materials in the selected textbook; (2) to analyze the variables of contexts that might have been included. The text book being analysed is an English textbook for Grade VII, “The title is Bahasa Inggris When English Rings a Bell, SMP/MTs Kelas VII, which is written by Siti Wachidah, Asep Gunawan, Diyantari, Yuli Rulani Khatimah. It is reviewed and edited by Rd. Safrina Noorman and Lestari Manggong and published in 2017 by Pusat Kurikulum dan Perbukuan, Balitbang, Kemendikbud. This research is an evaluation research by applying content analysis method. The analysis is started by (1) identifying or codifying the text materials which belong to both interactional and transactional conversation; (2) categorizing the types of conversations (interactional or transactional); (3) analyzing the inclusion of sociolinguistic contexts in each of the conversations based on the four out of five variables of sociolinguistic contexts proposed by Harmer (2001). The variables include setting, participant, channel, and topic; the last (4)interpreting the result of analysis. The findings show that almost all the topics of the dialog texts have been designed concurrently with the English syllabus for SMP/MTs Kelas VII. Yet, there are only few variables of setting, participant, and channel which are identifiable. To conclude, the variables of sociolinguistic contexts have not been entirely included in the text materials.
Deep Learning by a Tensor Network Algorithm Provides Hyperfast Training of Business Finance

We show how tensor network theory and deep learning theory can be combined to provide a ground-state network (Orús, 2014) of financial information for hyperfast financial literacy. The resulting minimal-complexity structure encodes an infinite number of probable outcomes into a finite graphical alphabet of 12 potential dynamic relations, called double-entries; the pixels of financial information. Using the proposed many-layered (Serb & Prodromakis, 2019), financial wave function (Schrödinger, 1935), as a computational resource (Biamonte, 2016), allows hyperfast processing of financial statements, one pixel at a time; see fig. 1. This reveals a highly entangled architecture (Levine, et al., 2019), where complexity scales linearly, not exponentially (Huggins, et al., 2018). The new algorithm trains people on financial accounting in 10 hours; a process that would take at least one year with the conventional scheme. Results are based on solid empirical evidence.
Determining the Minimal Number of Images Required to Effectively Train Convolutional Neural Networks

Determining the minimal number of images required to effectively train convolutional neural networks (CNNs) is not trivial and no simple solution exists. In this paper, we propose a method that helps to determine that number of images and checks if sufficient data is collected. We did a series of experiments using different CNN architectures (classic one with 3 convolutional layers, ResNet18, and Inception v3) and images data sets with different complexity (MNIST, CIFAR-10, CIFAR-100, and STL-10). These experiments allowed us to propose guidelines for the discussed problem. We also proposed a method for establishing the complexity of image sets.
An Automated Approach to Recover the Use-case View of an Architecture

Many tools and techniques were described in the literature for automated recovery of software architecture from software artifacts, such as code. These approaches generate models of software architecture at different levels of granularity and notations. Whereas there is a vast literature in recovering components, packages, and interactions between them, we lack automated approaches for recovering the use-case view of an architecture. In the 4+1 view of the architecture, use-case view or scenarios represents a view of the architecture in terms of the systems' core functionalities provided to end-users. This view is essential in understanding the system and its underlying architectural decisions. Manually recovering and documenting the application's scenarios from source code is time-consuming, as large-scale enterprise systems can have a large number of scenarios. In this NEMI paper, we present a novel automated approach for recovering the scenarios from Web applications source code. These scenarios are shown in use case diagrams alongside with sequence diagrams that further describe how each use case is implemented in the system. Our approach works under the assumption that the URLs (endpoints) of a Web application can give us clues to the system's use cases. Therefore, our technique combines a set of heuristics and static analysis in order to detect the endpoints in a Java Web application as well as the backend classes and methods that will process the request. Subsequently, it uses Natural Language Processing (NLP) techniques to extract use cases from these identified endpoints and uses the computed program slices to generate sequence diagrams for each identified use case. We conducted an initial evaluation of our approach by detecting endpoints in Sagan, an existing open-source Web application. We then demonstrate the use cases generated and how their implementation looks like through sequence diagrams.
Chapter 8. A historical controversy about politeness and public argument

This article presents the Nineteenth-Century dispute arising from the criticism that the Italian philosopher Antonio Rosmini expressed against the arguments that the statesman Melchiorre Gioja supported in defense of fashion in his Apologia della moda ‘Apology of Fashion’ (1822) and against the utilitarian ideology that permeates the text. Gioja’s aggressive answer (in 1827) leads Rosmini to write a treatise on polite manners writers must have in public debate, thus offering an interesting ethical treatise. We aim to analyze the controversy adopting an interdisciplinary approach that investigates metapragmatic evaluative comments from the point of view of argumentation in order to reconstruct the argumentative justification behind each evaluation of (im)politeness and to show the principles defended by the disputants.
Excipients for Homeopathic Medicines: Characteristics and Quality Requirements

The current state-of-the-art regarding excipients used to manufacture and prepare homeopathic medicines is reviewed. The main groups of excipients are discussed with respect to application, i.e., the processing, storage, and transportation of raw material; the production of homeopathic drug substances and active ingredients; and the manufacturing of homeopathic drug dosage forms. Quality assessment of excipients is shown to use different categories of standards. The basic requirements for excipients in the State Pharmacopoeia of the Russian Federation and leading foreign pharmacopoeias are discussed.
Fingertip Detection Based on the Chord-to-Point Distance Accumulation

Fingertip detection is an important part of vision-based human-computer interaction. Due to the complexity of background and the real-time capability of system, there still exist many problems in the accuracy of fingertip positioning. In view of these problems, this paper proposed a simple and efficient fingertip detection method. First, the input video stream is preprocessed, and then the hand contour is extracted. The obtained hand contour is processed by the Chord-to-Point Distance Accumulation algorithm, so as to detect the fingertip in the image. The experimental results show that the method has high accuracy and stability in fingertip recognition.
Optimization of RSA encryption and decryption process with distributed computing method

Abstract Mathematics equation of the RSA is the complicated one between the other asymmetric encryption methods. It makes the RSA method needs more resources than the others. Most existing studies are trying to make another encryption method that need less computational resources, but it is less secure than using the RSA algorithm. In this paper, we proposed the Distributed Computing method to accommodate the limited computing resources in a single worker. We will distribute the computational process of RSA encryption and decryption to numerous workers. The test results showed that the implementation of Distributed Computing method made the encryption and decryption process finished faster. In conclusion, it increased completion time, made the encrypted data serve faster, and maximized the computational resources.
Poster Abstract: Secure Remote Key Initialization of Wireless IoT

Private key initialization is an essential and fussy part for cryptographic protection when a new Internet-of-Things device comes into service. Especially, when the IoT device is compromised in the field, a remote key re-initialization is needed. However, considering the operation convenience and cost for installation, most field IoT devices usually lack a wired user interface, it is difficult to perform a reliable key-initialization operation. How to ensure the secure key initialization of IoT devices wirelessly without user interface in an efficient way is a hard nut to crack. To tackle this problem, we propose a visual indicator-based method for the secure key initialization and verification of IoT devices without any hardware redesign or extra cost, which can fully reduce the management overhead of IoT devices for both the user and manufacturer.
Study on the Application Domain of Two Traditional Defogging Algorithms Based on Atmospheric degradation model

The development of artificial machine vision enables further research on image processing. As the direction of image enhancement, research on image defogging is also essential. Base on Atmospheric degradation model, the image defogging algorithm can execute precisely. Dark Channel Prior algorithm (DCP) and Color Attenuation Prior algorithm (CAP) are two classic algorithms in the traditional defogging algorithm. These two algorithms were implemented based on the degraded model and carried out a comparative analysis. By comparison, it was found that DCP performs better on images with no sky in the middle and short distances, while CAP performed better on images with larger sky areas and deeper depth of field. Regarding the difference between the two algorithms, further research was performed and the reason for the difference was attributed to the calculation method of transmittance, and the reasons for the difference between the two defogging algorithms were summarized.
Creativity of mathematics education students in producing instructional media-based on macromedia flash through blended learning

Abstract This study aims to train the creativity of mathematics education students in creating Macromedia flash-based instructional media through blended learning. Media is an important component in the learning process, which can help the student to achieve learning objectives. In order to produce instructional media, the teachers’ creativity of teacher is needed to create innovative products. This research is using a descriptive quantitative research method with 28 students of class VIB mathematics education study program, FKIP University of PGRI Palembang. Data were collected by observation and performance tests. The collected data from this research is analyzed quantitatively descriptively. Based on the analysis of observation data, it is known that there are 22 and 6 students included in the category of very good and good respectively. In the performance test, there are 20 students in the very good category, five students in the good category, two students inadequate category, and 1 student in the poor category.
Learning A Self-Inverse Network for Bidirectional Mri Image Synthesis

The one-to-one mapping is necessary for MRI image synthesis as MRI images are unique to the patient. State-of-the-art approaches for image synthesis from domain X to domain Y learn a convolutional neural network that meticulously maps between the domains. A different network is typically implemented to map along the opposite direction, from Y to X. In this paper, we explore the possibility of only wielding one network for bi-directional image synthesis. In other words, such an autonomous learning network implements a self-inverse function. A self-inverse network shares several distinct advantages: only one network instead of two, better generalization and more restricted parameter space. Most importantly, a self-inverse function guarantees a one-to-one mapping, a property that cannot be guaranteed by earlier approaches that are not self-inverse. The experiments on MRI T1 and T2 images show that, compared with the baseline approaches that use two separate models for the image synthesis along two directions, our self-inverse network achieves better synthesis results in terms of standard metrics. Finally, our sensitivity analysis confirms the feasibility of learning a one-to-one mapping function for MRI image synthesis.
Are Panoramic Education Lectures a Distraction?

Education in this 21st century has come a long way and it has seen several innovative methods in reaching its learners. In recent years, the development of IT and web services made it possible to reach a remote audience. Several platforms and academicians have started to adopt e-learning methodologies in a view of reaching massive learners across the globe. As a current trend, all these e-learning platforms are using videos as their major medium of content delivery and these videos are generally ‘flat.' Another advancement in recent years is the 360° panoramic videos that are gaining a lot of popularity in the field of entertainment. This paper summarises the attitude of the learners and how the 360° video's environment influences them when a panoramic video lecture is used for content delivery that replaces the traditional 2D flat educational videos.
Towards Intelligent User Interfaces to Prevent Phishing Attacks

Phishing is a type of fraud designed to steal important sensitive information such as credit card numbers, passwords and bank account data.The fraudulent website is graphically very similar to the original one and invites the users to enter some personal information then used to steal the identity of the person who takes the scam.Other times, the website injects malicious code in the user's computer.Despite the notable advances made in the last years by the active warning messages for phishing, this attack remains one of the most effective.In this paper we propose an intelligent warning message mechanism, that might limit the effectiveness of phishing attacks and that might increase the user awareness about related risks.It implements an intelligent behavior that, besides warning the users that a phishing attack is occurring, explains why the specific suspect site can be fraudulent.
Contemporary secondary school: what is the competitive edge of a school graduate?

In the context of the contemporary educational process, researchers consider competitiveness as a system-forming category. On the one hand, they reflect on the level of formation of basic skills and competencies of a person, and on the other — on the range of adaptive capabilities of a person in a system of the changing social relations. This article aims to analyze the main factors affecting the formation of competitiveness among the contemporary high school students. The results of this study indicate that the most significant factors contributing to the development of competitiveness include social activity, initiative, hard work, readiness for constant self-development, and actualization of personal potential. According to the surveyed respondents, the listed qualities become a prerequisite for successful studying and socializing of high school students, as well as for their further and professional development after graduation.
Knowledge Graph Query and Reasoning Based on Game Theory

Aiming at the problem of sparse information distribution and lack of good correlation between data in the era of big data, this paper proposes a knowledge graph query and reasoning method based on game theory. This method first establishes the domain ontology model according to the domain requirements, and establishes the domain knowledge graph according to the modified model, and then uses the PageRank algorithm to evaluate the value of each node in the knowledge graph, and then conducts the knowledge graph query based on the game thinking orientation and the talent recommendation system as an example. This method makes use of the relationship between knowledge and nodes in the knowledge graph and realizes the effective talent recommendation.
AHFNet: Aggregation of Hierarchical Features for Crowd Counting

Accurately estimating crowds is a particularly tricky problem for public safety. In this paper, we propose a pyramid network called AHFNet (aggregation of hierarchical features network) to effectively overcome this challenge. Different convolution layers extract rich features, which are then aggregated to generate useful crowd density maps. To further improve the method's performances, we also introduce a unique technique named PVBS (projection variance and background suppression) to obtain more effective labels. In the PVBS, the projection relation of people is considered to estimate variance of Gaussian kernels in the ground truths, and the background pixels are set to a negative value directly. Extensive experiments are conducted on the ShanghaiTech dataset, and the results demonstrate our method outperforms those state-of-the-art methods in terms of crowd counting accuracy, which shows that our method has greater practical potential.
TENDENCY OF IMPLEMENTATION OF INFORMATION TECHNOLOGIES INTO PRIMARY SCHOOL

Conference proceedings are devoted to modern global trends in the development of innovative scientific researches. General issues of the engineering, medical, psychological, philological, economic sciences, history of art, social communications and so on are considered. The publication is designed for scientists, lecturers, postgraduate students, students, as well as for the general readers. International Scientific Conference Modern Global Trends in the Development of Innovative Scientific Researches: Conference Proceedings, March 20th, 2020. Riga, Latvia: Baltija Publishing. 180 pages.
Fostering Reuse by Integration: A Directed System of Systems Development Case

Software reuse is a software engineering technique that fosters productivity and quality by encouraging the reuse of existing software artifacts. Despite advantages, we have identified that software engineers must cope with independent and isolated reuse activities. This isolation can hinder the success of an effective reuse activity. In this paper, we discuss how an integrated support for reuse would benefit this activity. Based on a previous approach for developing directed System of Systems (SoS), and on a systematic mapping about integration of reuse environments, we have identified that SoS and Service Oriented Architecture could be employed together for leveraging reuse, and this has motivated us to design and develop a new directed SoS, named SoS-Reuse. As validation, SoS-Reuse has been qualitatively assessed with software architects. Therefore, we claim that our SoS proposal could be used as a stepping stone to improve the reuse activity and for creating similar SoS for other domains.
Bringing a Change in Digital Mobile Banking Through Distributed Technology

Application-based mobile banking is a very commonly used term in the world. The data taken by the server are the personal sensitive data of the user. These data are very sensitive and should not be disclosed, so it must be stored securely. Moreover, the transactional data/metadata of the user should also be kept secured, and it has to be ensured that only the user can access and see his/her transactions. This paper introduces a secured system for application-based mobile banking. We are using blockchain to store the transactional data and bank server to store the personal data of the users. Cryptographic functions have been used here to encrypt the user data in this system to reduce the loss of transactional data and also to make the users reliable to the application-based mobile banking.
Identifications of increase, distribution pattern, and density level of sedimentation using Landsat 7 satellite images in the coastal area

Abstract Sedimentation at coastal of Cirebon City is caused by considerable abrasion process in Indramayu regency and the impact of sand mining on Gosong Island, Indramayu Regency, besides that, the habit of residents in coastal of Cirebon City who heap up garbage at the coastal for years to utilize the area for residential purpose also contributed significantly the problem of sedimentation in the coastal area of Cirebon City. This research applying remote sensing technology of Landsat 7 2005, 2010, and 2015 using Lemigas Algorithm to gain information of special and temporal increase of sedimentation, distribution pattern, and density level of sedimentation. The result shows that the most significant increase of sedimentation happened at 2010 to 2015 with 46,072 Ha. There are 2 types of distribution pattern at Cirebon City, the first one is the sedimentation that ends in the estuary of river. The other type is the sedimentation caused by the presence of longshore currents which carry sediment and stuck on the coast along coastal of Cirebon City. Identification of natural and artificial sedimentation is carried out based on surveys in the field. The Lemigas Algorithm used only for classification of sedimentation based on density level of sedimentation content (mg/L). This research contributes to the Cirebon City government in resolving the problems of abrasion, accretion, and siltation in coastal areas, for the development of the Cirebon City coastal area to be an asset supported the economy in the future.
The Research of the Persona of Online Car-hailing Drivers based on Density Peak Clustering

In order to study the types and characteristics of drivers in online car-hailing industry, we establish the model which combine user persona theory and density peak clustering algorithm. User persona is widely used in customer analysis of various industries because it can vividly and richly display user characteristics. This paper introduces the user persona theory when studying the customer clustering method, constructs the user persona model based on multi-level user data, and designs the process of user persona construction. In the empirical part, density peak clustering algorithm is used for data experiment. The results show the clustering result obtained by the model of user persona theory and density peak algorithm is well. According to the clustering centers, we analyze the characteristics of different types of customers and provide strategies and opinions for enterprise marketing, which is an effective research method of user persona.