Reviewerly/exHarmony huggingface dataset:
Cultivating EFL students’ speaking competence using discourse role play task

Foreign language students tend to have problem in arranging conversation. They have difficulties in communicating spontaneously with their friends. Therefore, it is important to cultivate the speaking competence of EFL students. In this study, those EFL learners are students of Arabic Education department. The research design used in this study was collaborative classroom action research. The collaboration was done with the other English teacher of English Center UIN Maulana Malik Ibrahim, Malang in designing the lesson plan, setting the criteria of success, implementing the action, observing the action, and having reflection. In addition, the subjects of this study were 25 students of the third semester of Arabic Education Department at UIN Maulana Malik Ibrahim, Malang. The result of the study revealed that the use of Discourse Role Play Task improve the students’ speaking competence. The students were able to deal with pragmatic situation and speech act.
Reasoning about non-functional properties using compiler intrinsic function annotations

Funding: European Union’s Horizon 2020 research and innovation programme under grant agreement No 779882.
DeepLABNet: End-to-end Learning of Deep Radial Basis Networks

Radial basis function (RBF) networks provide an interesting mechanism for learning complex non-linear activation functions in a neuralnetwork. However, the interest in RBF networks has waned dueto the difficulty of integrating RBFs into deep neural network architectures in a tractable and stable manner. In this work, we presenta novel approach that enables end-to-end learning of deep RBFnetworks with fully learnable activation basis functions in a tractablemanner. We demonstrate that our approach for enabling the use oflearnable activation basis functions in deep neural networks, whichwe will refer to as DeepLABNet, is an effective tool for automatedactivation function learning within complex network architectures.
Assessing Architectural Similarity in Populations of Deep Neural Networks

Evolutionary deep intelligence has recently shown great promisefor producing small, powerful deep neural network models via thesynthesis of increasingly efficient architectures over successiveGen No. Gene Tagging No Gene Tagging generations. However, little has been done to directly assess architectural similarity between networks during the synthesis process.We present a preliminary study into quantifying architectural similarity via the percentage overlap of architectural clusters. Resultsshow that networks synthesized using architectural alignment (viagene tagging) maintain higher architectural similarities within eachgeneration, potentially restricting the search space of highly efficientnetwork architectures.
Computation of avoidance regions for driver assistance systems by using a Hamilton-Jacobi approach

We consider the problem of computing safety regions, modeled as nonconvex backward reachable sets, for a nonlinear car collision avoidance model with time-dependent obstacles. The Hamilton-Jacobi-Bellman framework is used. A new formulation of level set functions for obstacle avoidance is given and sufficient conditions for granting the obstacle avoidance on the whole time interval are obtained, even though the conditions are checked only at discrete times. Different scenarios including various road configurations, different geometry of vehicle and obstacles, as well as fixed or moving obstacles, are then studied and computed. Computations involve solving nonlinear partial differential equations of up to five space dimensions plus time with nonsmooth obstacle representations, and an efficient solver is used to this end. A comparison with a direct optimal control approach is also done for one of the examples.
PENGGUNAAN MODEL PEMBELAJARAN TEAMS GAMES TOURNAMENTS  (TGT)  BERBANTU  MEDIA POSTER UNTUK  MENINGKATKAN KREATIVITAS  DAN HASIL BELAJAR PKn PADA SISWA KELAS IV SD 2 BAE KUDUS

Abstract This study aims to promote creativity and student learning outcomes 2 Bae fourth grade second semester of academic year 2016/2017 on subjects Civics material   Know the State institutions at the central level   through a  model of Learning Teams Games Tournaments (TGT) Assisted Media Poste r  To achieve these objectives, This research was designed in two cycles. The procedure in each cycle includes the stages: 1) planning, 2) implementation, 3) observation, 4) reflection.The effectiveness of actions in each cycle is measured from the results of observations described, interpreted, and then reflected to determine corrective actions in the next cycle.Action research conducted in two cycles obtained results in the first cycle, the creativity observation results reached a score of 3.0 with a value of 75 with enough predicate and on the learning outcomes of 21 students there were already 12 students or 58% achieved the specified completeness while the remaining 9 students or 42% have not yet reached completion. The highest score obtained by students is 100 while the lowest score is 60, the average student learning outcomes are 75. The average increase in learning outcomes in the first cycle is 9.3% of the average pre-cycle achievement. Cycle II data on the results of observations of creativity reached a score of 3.3 with a score of 83 with a good predicate and learning outcomes showed that of 21 students there were 20 students or 95% had achieved predetermined completeness while the remaining 1 child or 5% had not reached completeness. The highest value obtained by students is 100 while the lowest value is 70. The average student learning outcomes are 83. The increase in learning outcomes that occurred in the second cycle is 9.6%Based on the actions taken, it can be concluded that the application of the  Teams Games Tournaments (TGT)  Learning Model  Assisted by Media Posters ,  can improve the creativity and achievement of fourth grade students of SD 2 Bae in the second semester of 2016/2017 academic year in the subject of Civics  Knowing the State Institutions at the Central Level   . an increase in student learning creativity will bring influence to the increased achievement of students. Keyword : TGT, creativity, learning outcomes
Security Challenges in Software Engineering for the Cloud: A Systematic Review

Cloud computing is among the fastest growing technologies, and it has brought noticeable growth in securitySecurity concerns. Despite the securitySecurity challenges, cloud computing has proven pivotal in the development and success of distributed systems. This comes from certain features such as rapid elasticity, on-demand service deployment, and support for self-service. All these features are associated with securityService security challenges such as data breaches, network securitySecurity, data access, denial of service attacks, hijacking of accounts, and exploitable system vulnerabilities. Regardless of the cloud model, the cloud software development process and the consideration of integrated securitySecurity features are critical for securing cloud computing. As such, software engineering is required to play an essential role in combating cloud securitySecurity issues in the future applications. In this paper, we introduce a systematic review of articles in the area of software engineeringSecurity securitySoftware engineering security challenges on the cloud. The review examines articles that were published between 2014 and 2019. The procedure for article qualification relied on the elucidation of Preferred Reporting Items for Systematic Reviews and Meta-Analyses premises. Meta-analysis checklist was employed to explore the analytical quality of the reviewed papers. Some of the issues considered were included, but were not limited to, cloud models of service delivery, access control, harm detection, and integrity. All these elements are discussed from the perspective of software engineering and its prospect in improving cloud securitySecurity.
Det som är Roligt, är Roligt

This thesis explores the perceived enjoyability of Deep Reinforcement learning AI agents (DeepRL agent) that strives towards optimality within the First Person Shooter game Unreal Tournament 2004 ( ...
Risk Assessment and Heavy Metal (Cu and Ni) Contamination in Sediments of Shatt Al-Arab Canals, Iraq

The present study aims at investigate the relationships between physic-chemical and seasons to determined heavy metals (copper Cu and Nickel Ni) contaminated of sediments of Shat Al-Arab canals. The pH, Electrical Conductivity (EC), Total Organic Carbon (TOC), Oil and grease were measured. The study investigated the effects of season on the sediment characteristics of Shat Al-Arab canals. Data analyses were done using analysis of variance, Tukey's multiple range, Pearson correlation coefficient and descriptive statistics. pH, EC and TOC were significantly higher at dry season (7.44 ± 0.129), (544.212 ± 133.8 μcm/cm2) and (13.94 ± 2.157%) respectively, than at wet season (P<0.05). However, hydrocarbons (Oil and grease) was significantly higher at wet season (4360 ± 1129 mg/l) than at dry season (1920 ± 638.3) (P<0.05). The presence of high levels of organic pollutants indicates organic pollution and stress. Positive and negative Pearson correlation relationship between both heavy metals and physic-chemical parameters were found. Contamination of sediments was assessed on basis of contamination factor (CF), geo-accumulation index (Igeo), pollution load index (PLI) Potential Ecological Risk (Eir) and Potential Ecological Risk Index (RI). Results of geo-accumulation index (Igeo) indicated that sediments were uncontaminated with Cu, uncontaminated to moderately pollution with Ni.
Effects on Chaotic Semiconductor Laser Emission under Power Conversion in Nonlinear Propagation

Chaotic bandwidth and time-delay signature (TDS) are investigated in relation to the power conversion during nonlinear fiber propagation. Bandwidth broadening with TDS elimination is demonstrated when there is power conversion from the central band.
Comparative Analysis Of Objective Assessment And Self-Assessment Of University Graduates' Professional Identity

Training at university involves assessment of the outcomes of educational activities aimed to form graduate’s professional identity. The need to obtain objective information concerning the level of professional identity of a university graduate has led to analyzing the available scientific and pedagogical experience in the field of assessment and assessment procedure. Consequently, it caused the need to turn to search and selection of methods for implementing the complex objective assessment procedure in conjunction with the students’ self-assessment, development of tools for an objective assessment of personal, meta-subject and subject outcomes, self-assessment. The method of humanitarian examination of university graduates’ training achievements has been adopted as one of the methods of external objective assessment. With the purpose to identify self-assessment, interactive technologies of pedagogical workshops, pedagogical laboratories and training through sensory perception were applied. The combination of methods of external (objective) assessment and internal and analysis of the results enabled to conclude that it is necessary to take into account the combination of regulatory requirements and developed criteria in the assessment process. The results of the experiment led to the conclusion that not all of the studied professional identity indicators are assessed adequately from the standpoint of an independent objective assessment and from the standpoint of subjective self-assessment. The positions of an expert and a student do not coincide in assessing the value-behavioral component. The results of the study subjected to statistical processing confirmed the need to develop psycho-pedagogical approaches and a special diagnostic technique.
A Study on The Use of Political Rhetoric Device and Discourse Analysis in Political Speeches

Political speeches involve a persuasive strategies and it aims to move audience. In an elaborate political process of choosing correct representative and in high stakes politics, speeches form a very important part. Ever wondered how speech like “I have a dream” became one of the most famous speeches across the world? The aim of the paper is to study the approaches of linguistics in political speeches. The sample speeches are Hon. Donald Trump’s Presidential Campaign Announcement in 2015 and Hon. Barack Obama’s Democratic National Committee’s speech in 2012.
Potensi Kecerdasan Linguistik pada Anak Usia Dini melalui Mendongeng Di Rumah Baca Madina Kota Metro

The Children have linguistic intelligence in a great ways. During childhood, from birth to 6th years old, the children never learn vocabulary specifically. When teachers tell stories, children will gradually play important games and not only in developing interest and reading habits, but also in developing children's language and thoughts. Early childhood is a great imitator, whatever we say and do will be attached to the child, so we as adults must be able to control our speech and behavior in front of early childhood, because that will have an effect in the future. One method that can be used in developing aspects of children's language is the storytelling method.&#x0D;
Signal modulation identification in multipath channels

The research of the technology of modulation identification of digital communication signals is one of the key technologies of receivers in non-cooperative communication systems, and it also has important application value in civil and military fields. In the actual wireless communication environment, the phenomenon of multipath transmission exists all the time. However, most of the existing modulation identification methods are based on the ideal environment, which ignore the influence of multipath interference, and the performance of these algorithms is seriously degraded in multipath fading channels. In order to solve this problem, in this paper we proposed a new algorithm for modulation identification in multipath channels, which based on wavelet transform, higher order cyclic cumulant and high-order cumulant. The simulation results show that the algorithm proposed can effectively eliminate the influence of multipath channel and performs well for the identification of signal modulation.
Business Trends Based on News Portal Websites for Analysis of Big Data Using K-Means Clustering

Business analysis is performed to determine the business that are popular, in Indonesia with text mining can take data from several news portal in Indonesia. Text preprocessing is used to change the text title and tags on the news to be converted into weights. The weight of the data will be processed using the K-Means algorithm to be grouped into clusters and each cluster will be visualized using Word Cloud so that words that often appear as popular word identification are known. Testing uses the Silhouette Coefficient to calculate the quality of each member against the cluster. Furthermore, each member will be interpreted according to the test results. Analysis is carried out every month in 2018 with a total of 995 data with a monthly average of 6 clusters, in January were the most popular business according to the number of members from 64 data formed 6 clusters, the most member clusters were cluster 1 the Silhouette Coefficient test results are strong 0.00%, medium 65.22%, weak 30.43%, not substantial 4.35%, Word Cloud formed was a leather bag business.
Arquivista e a formação continuada: análise comparativa dos países de língua portuguesa e Espanha

The article presents a mapping of the courses of continuing education, lato sensu and stricto sensu, as well as short-term technical courses, updating and training that address the theoretical corpus and its practice in archival science and information science, with some strand in archives, taught in the Community of Portuguese Speaking Countries, CPLP, plus Spain. The research, of an informative nature, identified the offerings of the courses, in a virtual way, browsing the Web pages of the promoting institutions, national archives, associations and postgraduate programs. The theoretical basis was based on Souza (2011), which indicates a reduced number of archivists with continuing education in Brazil. We observed that of all the countries analyzed, seven of them: Angola, Cape Verde, Guinea Bissau, Equatorial Guinea, Mozambique, Sao Tome and Principe and East Timor, present a deficit in the supply of courses. On the other hand, the most satisfactory results are in Brazil, Portugal and Spain, providing an opportunity for the knowledge of the information professionals community, especially the archivists, who are looking for a continuous training in archival science.
Style Guide for the User Interface Structure of the Courses Created in the Learning Management Platform of the Technological University of Panama

The aim of this article is to present a research project carried out to develop a style guide for the design of the user interface structure of virtual courses created on the Technological University of Panama learning management platform. This style guide is a powerful tool and a starting point for ensuring that the structure of the courses is easy to use for users (students) of the Technological University of Panama.
Need for Using Artificial Intelligence in the Evaluation of New Industrial Project

Our research work aimed to provide a new intelligent decision support approach able to reproduce partially the human’s decision making. This paper proposes a new relational Multicriteria K-means algorithm. The originality of this work is due to the use of the research resulting from the clustering approaches and the preference concept to build new model able to assist stakeholders in their decision-making. The main idea of this new method is to split the projects into hierarchical levels, classified over time. In each level, the criteria are weighed, and a mathematical relation function is developed. In order to demonstrate the usefulness and efficiency of the proposed approach, it was chosen to apply this method to the evaluation of 8 Moroccan Concentered Solar Power (CSP). The obtained result has matched the CSP’s strategy.
KESALAHAN BERBAHASA INDONESIA BERDASARKAN KATEGORI LINGUISTIK PADA TUTURAN MAHASISWA ASING DALAM INTERAKSI PEMBELAJARAN BIPA

ABSTRAK Penelitian ini bertujuan untuk mendeskripsikan kesalahan penggunaan diksi dalam tuturan mahasiswa asing UM saat pembelajaran BIPA, mendeskripsikan kesalahan penggunaan diksi yang sering terjadi dalam tuturan mahasiswa asing UM saat pembelajaran BIPA, dan mendeskripsikan faktor penyebab kesalahan penggunaan diksi dalam tuturan mahasiswa asing UM saat pembelajaran BIPA. Data penelitian ini berupa tuturan mahasiswa asing baik dengan pengajar maupun dengan tutor selama pembelajaran BIPA yang sesuai dengan fokus penelitian. Hasil penelitian ini menunjukkan bahwa terdapat kesalahan penggunaan diksi pada aspek (1) kebakuan kata, (2) kecermatan kata, (3) ketepatan kata, (4) kelaziman kata, dan (5) keserasian kata. Kata Kunci : kesalahan, penggunaan diksi, tuturan, pembelajaran BIPA ABSTRACT The aims of this researchto describes errorsthe use of diction in the utteranceof foreign students UM during BIPA learning, describeserrorsthe use of diction which often occur in the utterance of foreign students during the BIPA learning, and describes the causative factor of error in the use of diction in theutterance of foreign students during BIPA learning. The research data is in the form of utteranceby foreign students both with lecturers and tutors during BIPA learning in accordance with the focus of the research. The results of this researchshows that there are errors in the use of diction in aspects (1) word rigidity, (2) word prudence, (3) word accuracy, (4) word prevalence, and (5) word harmony. Keywords : errors, diction usage, utterance, BIPA learning Normal 0 false false false IN X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable{mso-style-name:Table Normal;mso-tstyle-rowband-size:0;mso-tstyle-colband-size:0;mso-style-noshow:yes;mso-style-priority:99;mso-style-qformat:yes;mso-style-parent:;mso-padding-alt:0cm 5.4pt 0cm 5.4pt;mso-para-margin-top:0cm;mso-para-margin-right:0cm;mso-para-margin-bottom:10.0pt;mso-para-margin-left:0cm;line-height:115%;mso-pagination:widow-orphan;font-size:11.0pt;font-family:Calibri,sans-serif;mso-ascii-font-family:Calibri;mso-ascii-theme-font:minor-latin;mso-fareast-font-family:Times New Roman;mso-fareast-theme-font:minor-fareast;mso-hansi-font-family:Calibri;mso-hansi-theme-font:minor-latin;mso-bidi-font-family:Times New Roman;mso-bidi-theme-font:minor-bidi;}
Effectiveness of VR Training for Kinetic Visual Acuity in Visual Motion Task

Kinetic visual acuity (KVA) is one of the essentials in sports vision. Although virtual reality is thought to be a plausible tool for training KVA, it is not clear that the vision training in VR is effective in actual environment beause the focal point length is different. In this paper, the training effect in VR is evaluated in the real environment in the same visual motion task. It is confirmed that the task performance is improved after the training in VR in the medium target speed.
Inspection Techniques for Detecting CUI with Hammering Sound Analysis and Machine Learning

In Japan, deterioration of industrial plants, built during the period of high economic growth in the middle of the 20th century, has become a social issue recently. Above all, Corrosion Under Insulation (CUI) of piping in the plant is a pressing issue. As conventional methods, X-ray inspection and ultrasound inspection have been utilized for that but still have limitations because of consuming time and inspection cost. Therefore, easy and low-cost screening techniques for CUI are required. We developed a hammering-type inspection robot that moves inside the piping and proposed an acoustic analysis method to identify anomaly parts from the hammering sound using machine learning techniques. By using testing pipes, we could successfully identify anomaly parts by the acoustic analysis using Uniform Manifold Approximation and Projection (UMAP) as a dimensionality reduction method and a neural network as a classification method.
Cross domain sentiment classification of Thai reviews using co-train model

Online reviews are significant sources of information, which is useful for supporting customer and entrepreneur decision in terms of product and service satisfaction analysis. Online reviews containing feedback from various domains makes it difficult to analyze and classify all comments at once. The proposed technique analyses the cross-domain Thai review data using a co-train machine learning model. The co-train model consists of multiple single domain specific models followed by refinement analysis for the final sentiment classification. This allows for full flexibility in training of each individual domain, which can lessen the limitation on training complexity due to simple training on single domain. The experiments have been conducted on Wongnai restaurant domain and IMDB movie domain data. Our co-train model can achieve the highest average accuracy of 86.10 percent for cross-domain sentiment classification with approximately 38 seconds processing time.