Reviewerly/exHarmony huggingface dataset:
Cardiac Segmentation from MRI images using Recurrent & Residual Convolutional Neural Network based on SegNet and Level Set methods

In recent years, semantic segmentation with Deep Learning (DL) is popularly found in many real-world applications. It is also specific, mentioned that these techniques are regularly applied to various segmentation and classification techniques in the medical field. The most popular deep learning techniques, especially SegNet and U-Net, are the most used for this type of medical application. Generally, in case of U-Net architecture which can be used with a skip connection and is capable of retrieving fine data during training. However, such a network consumes a lot of computation time compared to other networks. But SegNet is another network used to retrieve the desired information with a computing efficient. Inspired by the work, the skip connection is introduced into SegNet using the residual neural network (ResNet). ResNet consists of a layer and it has taken inputs involving multiple layers of the neural network, giving precise performance. This article offers first a recurrent convolutional neural network (RecNet) based on Seg-Net called R-SegNet and also a recurrent residual convolutional neural network (R2Net) based on SegNet models called R2-SegNet respectively. The strength of SegNet, RecNet and ResNet are used and have produced the architectures to perform the segmentation of cardiac MRI images. There are a number of advantages derived from the proposed architecture. First of all, using a residual unit, proposed architectures were used to carry out training in deep architecture. Second, the use of recurrent residual convolutional layers ensures that the relevant features retrieved to perform the segmentation tasks. Third, the proposed architecture has designed a good SegNet with a limited network parameters and also produce better performance for performing the task of segmentation in cardiac images. In addition, then, applied the level definition method, to extract the contours or surfaces of the cardiac MRI images. The results proves that the hybrid proposed deep learning methods successfully segments the images and also achieves better accuracy compared to standard architectures.
Improving Students’ Conceptual Understanding Through Geogebra-Assisted “5E” Learning Cycle: Is It Effective?

This study aims to investigate the effectiveness of GeoGebra-assisted 5E Learning Cycle model toward student’s understanding of mathematical concept with control of student’s prior knowledge. This study was a quasi-experiment with post-test only control group design. The population of the study was 324 ninth grader students where 81 of them were selected as sample through cluster random sampling technique. The data collected in this study were student’s mathematical prior knowledge obtained by giving objective tests before starting the learning process and data of student’s mathematical conceptual understanding obtained by giving an essay test at the end of learning process. The hypotheses were tested using t-test and one-way analysis of covariance test. The results showed that: the usage of GeoGebra-assisted 5E Learning Cycle Model has a positive impact toward student’s understanding of mathematical concept, where t = 2,977 and p = 0,002; the usage of GeoGebra-assisted 5E Learning Cycle Model has a positive impact toward student’s understanding of mathematical concept after the prior knowledge variable was controlled, where F = 31,880 and p = 0,000. The findings of this research implied that GeoGebra-assisted 5E Learning Cycle Model can be used as an alternative learning model in an effort to improve students' understanding of mathematical concepts.
Tools for promoting educational services in the field of labor protection

Тhe article discusses the tools for promoting educational services in the field of labor protection. The purpose of the work is to analyze the essential technologies for the communication promotion of educational services in the field of labor protection. The article considered the foreign and Russian experience in promoting services in the field of labor protection. Methods used in the analysis: expert interview, observation, case study. Based on the results of the work, it was concluded that, in addition to traditional methods of promotion, Internet marketing tools are used to promote educational services in the field of labor protection.
KAJIAN LITERATUR IMPLEMENTASI BUILDING INFORMATION MODELING (BIM) DI INDONESIA

One of the most common obstacles encountered in the construction industry is the fragmented delivery process and relies on paper-based documentation and communication. To overcome these problems a good integration system is needed. Building Information Modeling (BIM) is a construction technology innovation that can help stakeholders to collaborate, visualize, and manage construction work better. However, the adoption rate of BIM in Indonesia is still behind compared to other countries. This research was conducted to gather information about the BIM adoption experience and the challenges and benefits faced by construction actors in Indonesia. This study uses the literature review method for data collection. Based on the results of the study it was found that in general the level of adoption of BIM by construction actors in Indonesia is still low, the main challenge faced is the high investment costs of BIM applications, while time efficiency is the dominant benefit of using BIM .
Implementasi debat bahasa Inggris dengan metode British Parliamentary

Debating is one of the communication activities which aims at conveying constructive, innovative, sistematic, and convincing ideas and thoughts. One of the debating methods which can facilitate that aim is British Parliamentary. This debating system uses English. British Parliamentary method consists of two opposite lines, government who agrees and supports the motion and opposition who disagrees and contradicts with the motion. In debating, there are four competing teams which argue againts to win each other ideas and thoughts, they are: Opening government, Opening opposition, Closing government, and Closing opposition. Each team and speaker has their own respective rules and roles leading them to the systematic and structured way of conveying ideas and thoughts. To debate using this method, students at Senior High School in Makassar have conducted debating activities. The methods of the activties are introduction of rules and roles, case building, presentation, discussion, assignment, and debate exhibition. Based on these activities, it is indispensable to conduct a reguler and routine training in order to reassure the students’ way of thinking analytically, systematically, and critically and to be more accustomed with communicating meaningfully in English.
The Dynamics of High-Growth Firms: Evidence from Tunisia

This paper examines the dynamics and characteristics of high-growth firms in Tunisia. Further knowledge about the dynamics of these firms can inform the design of business support policies, especially toward small and medium-size firms. The analysis suggests that between 1999 and 2015, about 9 to 10.5 percent of the firms in Tunisia achieved high-growth status per year, on average, depending on the definition used, and these shares have been remarkably stable over time. Although a small share of firms achieves high growth annually, almost one in every three firms that survive for more than a decade has achieved high-growth status at least once. High-growth status is more prevalent among small and young firms, as well as firms that export, import, or receive foreign direct investments.
Analisis Data Hasil Web Scraping untuk Menentukan Kualitas Jurnal Ilmiah

Portal of Science Journal has many journals or scientific papers with many subjects. In other words, there are many searchable journals and it takes time to search and manage. Web Scraping is a process of taking some documents from a website to other needs. The result of web scraping is managed as csv file. For this study, web scraping data was taken from SINTA and SCIMAGOJR portals. Data file from web scraping is given to an application written in Python. The application is equipped with features to display and search paper data.
KEMAMPUAN MENULIS TEKS PIDATO PERSUASIF PADA SISWA KELAS IX SEMESTER GANJIL SMP MUHAMMADIYAH 2 KALIANDA LAMPUNG SELATAN TAHUN PELAJARAN 2018/2019

The problems studied in this study relate to the ability to write persuasive speech texts. The aim is to find out and describe students' abilities, constraints, and solutions to overcome the difficulties of writing persuasive speech texts based on aspects of title suitability with content, spelling use and writing, choice of words or diction, sentence structure, interfaith cohesion, coherence between paragraphs, overall content, and show persuasive content. To achieve these objectives, descriptive quantitative methods are used. The study population was 49 students in class IX.a and IX.b which were taken using total sampling. Data collection uses assignments to write persuasive speech texts and analyzed by quantitative analysis. The results showed that the ability to write persuasive speech texts in the odd semester IX students of Kalianda Muhammadiyah 2 Junior High School in South Lampung 2018/2019 Academic Year was in sufficient category because the average score achieved was 66. The highest score was 96 in the category of excellent conformity aspects. title with content, the overall content aspect achieves an average score of 71 in sufficient categories and in the aspect of interalimic cohesion 68 in sufficient categories. The coherence aspect between paragraphs reached an average score of 67 in sufficient categories, while the aspect of using sentence structure scored an average of 66 in sufficient categories. In the persuasive aspects it reaches an average score of 62 in sufficient categories, while aspects of the use of word or diction choices with an average score of 59 in sufficient categories. The lowest aspect is the spelling and writing aspects 36 less.
Proposed Balanced Constraint Measure-Based Algorithm for Privacy Preserved Information Distributing

Security insurance against mining calculations, an advancing exploration territory, finds the pessimistic symptoms of information mining techniques that start from the protection dissemination of people and associations. Late research in security insurance information mining has focused on finding a legitimate soundness between data protection and learning revelation. In this paper, we present a calculation that creates a disinfected database which keeps up the best possible harmony between data security and information revelation. We initially create the significant sicknesses from the first database, at that point convert the first database into a cleaned (sanitized ) database through our proposed arbitrary cleaning(sanitization) process. Next, we assess the produced cleaned database based on Knowledge Discovery (KD) and Privacy Factor (PF). This assessment procedure computes the KD and PF by looking at the noteworthy illnesses created from the first database versus the sterilized database. On the off chance that the estimations of KD and PF are fulfilled by the client determined limit esteem, the sterilized database is prepared for distributing, else our proposed calculation rehashes the sterilization procedure until the KD and PF qualities are fulfilled. At long last, our proposed calculation is assessed by contrasting it and comparative well known calculations on the criteria of KD and PF. The trial results demonstrate that our proposed calculation performed well at 77% running time contrasted with comparative prevalent calculations. The memory prerequisite for our proposed calculation is 25%, while past calculations need 31% memory. Our proposed calculation additionally performed 53% superior to past calculations regarding number of critical sicknesses influenced by the proposed cleansing procedure.
THE NEEDS OF TECHNOLOGY TRANSFORMATION IN FRENCH LITERATURE LEARNING

The development of technology has a real impact on the development of education. Education must be able to adapt to be more better, one of which is learning French literature. This study aims to determine learners' perceptions of the need for technology implementation in French literature learning. This study used a survey method with a qualitative descriptive approach. The findings show that from 90 respondents, 37.9% were strongly agreed, 56.6% were agreed, 5.0% were neutral, 0.1% were disagreed, and 0.3% were strongly disagree with the need for technology implementation in French literature teaching and learning activities. Based on these findings, the implementation of technology is a must and even a necessity in learning French literature
The Unclear Picture of Social Media Evidence

This article considers the unclear picture of social media evidence in the courtroom and offers a snapshot glimpse into the digitized world where modern trial narratives reside. This will be done by highlighting the dissonance between the social media form of evidence and our evidential rules. This disconnect between principle and evidence obscures the pristine categorization of evidential rules and principles causing us to question the position of social media in the evidential space of the courtroom. Instead of fashioning social media evidence into a manageable evidential category, we must be amenable to creating a unique approach to the introduction of social media evidence. The objective of this article is to challenge our learned knowledge of the evidential world so that we may create a new evidential language for application to social media evidence. This new approach will be truer to the purpose and objective of evidence rules and will provide much needed judicial oversight in determining its admissibility.
Bio-Inspired Requirements Variability Modeling with Use Case

Aims. This paper proposes a bio-inspired use case variability modeling methodology dealing with the above shortages.Method. The methodology is carried out through variable business domain use case meta modeling, variable applications family use case meta modeling, and variable specific application use case generating.Results. This methodology has leaded to integrated solutions to the above challenges: it decreases the gap between computing concepts and real world ones. It supports use case variability modeling by introducing versions and revisions features and related relations. The variability is supported at three meta levels covering business domain, applications family, and specific application requirements.Conclusion. A comparative evaluation with the closest recent works, upon some meaningful criteria in the domain, shows the conceptual and practical great value of the proposed methodology and leads to promising research perspectives.
The Barrier of meaning in archaeological data science.

Archaeologists, like other scientists, are experiencing a data-flood in their discipline, fueled by a surge in computing power and devices that enable the creation, collection, storage and transfer of an increasingly complex (and large) amount of data, such as remotely sensed imagery from a multitude of sources. In this paper, we pose the preliminary question if this increasing availability of information actually needs new computerized techniques, and Artificial Intelligence methods, to make new and deeper understanding into archaeological problems. Simply said, while it is a fact that Deep Learning (DL) has become prevalent as a type of machine learning design inspired by the way humans learn, and utilized to perform automatic actions people might describe as intelligent, we want to anticipate, here, a discussion around the subject whether machines, trained following this procedure, can extrapolate, from archaeological data, concepts and meaning in the same way that humans would do. Even prior to getting to technical results, we will start our reflection with a very basic concept: Is a collection of satellite images with notable archaeological sites informative enough to instruct a DL machine to discover new archaeological sites, as well as other potential locations of interest? Further, what if similar results could be reached with less intelligent machines that learn by having people manually program them with rules? Finally: If with barrier of meaning we refer to the extent to which human-like understanding can be achieved by a machine, where should be posed that barrier in the archaeological data science?
Perbandingan Optimasi Feature Selection pada Naïve Bayes untuk Klasifikasi Kepuasan Airline Passenger

The quality of an airline's services cannot be measured from the company's point of view, but must be seen from the point of view of customer satisfaction. Data mining techniques make it possible to predict airline customer satisfaction with a classification model. The Naïve Bayes algorithm has demonstrated outstanding classification accuracy, but currently independent assumptions are rarely discussed. Some literature suggests the use of attribute weighting to reduce independent assumptions, which can be done using particle swarm optimization (PSO) and genetic algorithm (GA) through feature selection. This study conducted a comparison of PSO and GA optimization on Naïve Bayes for the classification of Airline Passenger Satisfaction data taken from www.kaggle.com. After testing, the best performance is obtained from the model formed, namely the classification of Airline Passenger Satisfaction data using the Naïve Bayes algorithm with PSO optimization, where the accuracy value is 86.13%, the precision value is 87.90%, the recall value is 87.29%, and the value is AUC of 0.923.
A Study on Relationship between Adult Learners’ Participation Motives, Awareness of the Class, and Learning Participation at Lifelong Education Center Affiliated with University

초록·키워드 목차 오류제보하기 This study aims to investigate the following: 1) whether adult learners" gender, age, educational background, and learning motivation are correlated with their awareness of the classroom activities such as interest, satisfaction, and foreign language learning anxiety, and also 2) which of the factors has much to do with their participation in the class. The participants are 12 adult learners participating in a program at the University-affiliated Lifelong Education Center. The findings indicated the two followings: 1) learn- ers’motivation, satisfaction, positive attitude toward classes (usefulness), foreign languages classroom anxiety and gender showed no significant correlation to each other, except the correlation between academic background and learning motivation or class satisfaction. The learners’ learning motivation, however, was correlated with the learners’ academic background, as well as their class satisfaction. However, among the motivation factors, only those who participated in the program to pursue a meaningful life in the future showed significant correlation with learners" satisfaction. 2) The correlation between their satisfaction of the class and their participation in class showed a higher correlation in both sides than the correlation between their learning motivation and participation in class. But the other factors had no correlation with their participation. #Lifelong Education #Adult Learner #Participation Motives #Awareness of the Class #Learning Participation #평생교육 #성인학습자 #참여동기 #수업에 대한 인식 #학습참여도 Ⅰ. 서론Ⅱ. 이론적 배경Ⅲ. 연구 방법Ⅳ. 연구 결과 및 논의Ⅳ. 결론 및 시사점참고문헌Abstract
Grammatical Barriers in Writing A German Essay: A Case Study of Secondary High School Students

Abstract : This research was conducted to identify the grammatical barriers most often carried out by high school students. This type of research is a case study research to reveal the grammatical errors obtained instead of writing essays. These researchers uses a qualitative descriptive study. The data in this study are the results of German sentences written by 10 students in an essay, which then identified and classified the error Grammatically reviewed by Morphology and Syntax. The types of grammar errors analyzed specifically: capitalization, conjugation, verbposition , personalpronomen and article.
ЯВЛЕНИЕ ГЕОСИНОНИМИИ В СОВРЕМЕННОМ ИТАЛЬЯНСКОМ ЯЗЫКЕ

Te expansion of the phenomenon of geosynonymy in the Italian language is due to the coexistence of the standard Italian language and a large number of dialects and their variations in a single language space, which characterizes a signifcant linguistic and cultural fragmentation of the country. Te use of literary standard language in oral communication, which has always been the domain of dialects, inevitably led to multilevel interference and the formation of regional variants of Italian, which absorbed, in particular, diatopically labeled lexical units of dialectal origin. In some situations, when communicating in Italian, people of di ﬀerent geographical areas may face misunderstanding. Te aim of this article is to examine these phenomena in the contemporary Italian language, to analyze the dynamics of the occurring changes and the a ﬀecting factors, to reveal general patterns and trends in the development of the described processes. Te question of the tendency to reduce the number of Italian geosynonyms along with the vocabulary unifcation of regional variations of the language, or to expand the phenomenon, is becoming extremely relevant, given the increased interest in dialects among Italian youth, their parallel or mixed use with Italian, including the written form.
A gentle introduction to Girard's Transcendental Syntax

We present a gentle introduction to the technical content of Girard's Transcendental Syntax suggesting a new framework for the proof theory of linear logic and an alternative understanding of proof-nets. In this framework, we investigate the emergence of logic from a model of computation related to tiling models and logic programs.
Thematic Progression in Students’ Descriptive Text

A way for developing good writing skills is by using thematic progression. It can help students improve their writing abilities. Theme and rheme are used to analyze the thematic progression. This study aimed to find out the types of thematic progression of students' descriptive texts and the most dominant pattern of thematic progression in students’ descriptive texts. The researcher used the descriptive qualitative method in the research design. There were 50 texts written by students at SMP Swasta Sultan Agung Pematangsiantar. The data was analyzed using (Eggins, 2005) theory as the theoretical framework that found three types of thematic progression. The findings revealed that the students' descriptive texts follow three thematic progression patterns: reiteration or constant pattern, zig-zag or linear pattern, and multiple patterns or split rheme pattern. The constant pattern was the most dominant used by students in 271 occurences (91.80%), followed by zig-zag or linear pattern occurred 13 times (4.4%) and multiple patterns or split rheme pattern occurred 11 times (3.8%)l. The findings show students, in writing descriptive text, tend to use simple thematic progression due to their level of knowledge in grammar and thematic progression is relatively low.
Mental Actions and Explainability in Kripkean Semantics: What Else do I Know? (Student Abstract)

The ability of an agent to distinguish the ramification effects of an action from its direct effects adds value to the explainability of its decisions. In this work, we propose to encode the ramification effects of ontic and epistemic actions as single-point update models in an epistemic planning domain modeled with Kripkean semantics of Knowledge and Belief. We call them “mental actions”. We discuss a preliminary approach to realize our idea, and we conclude by pointing out some optimizations as our ongoing pursuit.