Reviewerly/exHarmony huggingface dataset:
Impact of the Half Space on High Resolution Range Profile

Abstract High resolution range profile (HRRP) which contains the characteristics of the scattering centers of the target, has an important application in the field of radar automatic target recognition. Based on the formation principle of HRRP, this paper analyzes the scattering mechanism of targets in half space and the influence of half space environment on HRRP. The half space HRRP of the same object in different viewing angles and relative dielectric constant is obtained by simulation, and it is compared with the HRRP in free space to further verify the correctness of the analysis. The analysis results have certain significance for processing half space HRRPs and half space target recognition.
Propuesta de un programa de alfabetización informacional para los estudiantes de octavo y noveno grado del Colegio Antonio Nariño Hermanos Corazonistas. Un enfoque desde el derecho de autor y manejo de las fuentes de información

Currently, information literacy has been configured as one of the most important alternatives in the training of users in the process of searching and retrieving information. However, the arrival of information and communication technologies has caused an increase in the sources of information available to the user, which implies that they need to develop skills related to the correct application of copyright and critical thinking. to help them evaluate the sources consulted. For this reason, this project intends to design an information literacy program focused on car rights, which will be composed of three parts, in the first, the needs of the high school students of the Antonio Narino Hermanos Corazonistas School will be evaluated. Through a diagnosis, the second will present the creation of content and the design of the model, and finally the methodologies for applying the program will be established.
APPLICATION OF GENETIC ALGORITHM FOR IMAGE TRANSFER

For images transfer, different embedding system exist which works by creating a mosaic image from the source image and recovery from the target image using some sort of algorithm. In current study, a method is proposed using the genetic algorithm for recovery of image from the source image. The algorithm utilized is genetic algorithm which is a search method along with another additional technique for obtaining higher robustness and security. The proposed methodology works by dividing the source image into smaller parts which are fitted into target image using the lossless compression. The mosaic image is recovered at retrieving side by the permutation array which is recovered and mapped using the pre-select key.
Waste machines as an alternative way to enhance students’ speaking interest

The phenomenon this time was that many lecturers had fallen asleep with the technological advancements used in the learning media. By relying on a more unique creativity, this study used simple materials from spare parts of a machine that can be used as learning media especially in speaking interest. The paper aims to explore speaking interest through waste machines to the students of Mechanical Engineering, the State Polytechnic of Tanah Laut. It investigates how waste machines can be incorporated in English for Specific Purpose (ESP) learners’ speaking interest. This study was qualitative case study, and data were gathered through observations, field notes and interviews. Data were interpreted based on the prepared achievements indicator. The results of the study reveal that the utilization of waste machines such as shocks, piston, gear, and bold is successful improving speaking skill for the students of Mechanical Engineering. In addition, students also learnt how to deliver in presentation with their field studies.
DEVELOPMENT OF MICROALGA DIVERSITY MODULE AS A BIOLOGICAL LEARNING MEDIA TO IMPROVE LEARNING OUTCOMES OF X GRADE HIGH SCHOOL STUDENTS IN PROTISTA MATERIAL

Microalgae is a biological material that has an abstract nature, meaning that it cannot be directly observed by the five senses and must use certain tools to see it. The objectives of this study were: 1. Producing biology learning media in the form of modules, 2. Knowing the practicality of the module based on the activities and responses of students, 3. Knowing the effectiveness of using modules based on the achievement of indicators and 4. Knowing the feasibility of the module of microalgae diversity as a learning medium biology to improve the learning outcomes of class X high school students on protist material. This research method uses development research or R D with the development model of Borg and Gall, 1983. The results of the study based on the N-gain value showed that the experimental class got a higher score than the control class and had moderate effectiveness. Based on the validity test conducted by 3 validators, the results stated very valid so that it was suitable for use as a learning medium.Key word: Module, Microalgae, Learning Media
AUTOMATIC SUBJECT LABELING IN DOCUMENTS BY USING ONTOLOGY AND GRAPH DATABASES

Ontologies apply to many applications in recent years, such as information retrieval, information extraction, and text document classification. The purpose of domain-specific ontology is to enrich the identification of concept and the interrelationships. In our research, we use ontology to specify a set of generic subjects (concept) that characterizes the domain as well as their definitions and interrelationships. This paper introduces a system for labeling subjects of a text documents based on the differential layers of domain specific ontology, which contains the information and the vocabularies related to the computer domain. A document can contain several subjects such as data science, database, and machine learning. The subjects in text document classification are determined based on the differential layers of the domain specific ontology. We combine the methodologies of Natural Language Processing with domain ontology to determine the subjects in text document. In order to increase performance, we use graph database to store and access ontology. Besides, the paper focuses on evaluating our proposed algorithm with some other methods. Experimental results show that our proposed algorithm yields performance significantly
Fast and robust motion averaging via angle constraints of multi‐view range scans

The motion averaging problem arises when recovering the motions for a set of scans in three-dimensional (3D) reconstruction. Motion averaging is taken as an optimisation problem, whose solution can be obtained via matrix decomposition in principal component analysis. The latest motion averaging methods utilize the Cauchy kernel function or overlap rate to construct the weighted matrix in the cost function, yielding weighted low-rank sparse matrix decomposition solutions. Nevertheless, the over-reliance on the initial value and high computational complexity remain two major problems. Here, we aim to improve the motion averaging performance via a fast and robust method based on the angle constraints of multiple scans. The additional term representing the angle constraint is added into the original cost function. By doing this, two benefits are facilitated: 1) the iteration times for the optimisation process are reduced; and 2) it effectively mitigates the over-reliance on the initial value and thus caters for outliers and random noise of initial motions. Compared with state-of-the-art motion averaging methods, it is indicated that the proposed method is more efficient and robust for numerical simulations of using both simulated motions and real 3D scanning data, given a large range of angle constraint values.
PEMANFAATAN GLOBAL POSITIONING SYSTEM (GPS) PADA PRESENSI KARYAWAN BERBASIS SMARTPHONE

The development of technology allows one to obtain other people's spatial position data. One mobile technology that utilizes spatial data as a supported factor is location-based services. The large number of employees at the PT.XYZ causes the presence of a controlled process to be under control, and even tends to be questioned. Because it takes a GPS-based presence system on android that is expected to be a solution of the problems that occur at this time. The system development method used is a six-step R&D method, consisting of: Research and information gathering, Planning, Development of initial product forms, initial field testing, major product revisions, main field testing. The final result is the prototype of the Ganesha Employee Presence System Operations. The test results on the system shows the employee attendance system can run on the android platform. The system only responds to presence based on the position of the employee's coordinates with office coordinates. Besides checking the presence process is also based on devices that have been approved in the system.
Sistem Pengolahan Data Di Lingkungan Pemerintahan

Today we lived in the era of technology there for our government institutions must utilize these technologies. Technology can make our work more efficient and effective. Though good human resources are irreplaceable, suitable technologies are also invaluable in order to complete our work quickly and accurately. One area that requires accuracy is data processing of personal information, finance information and social information.these three areas are very important in making decisions in management, this is why when processing data it must be done accurately.
Percepción de la educación virtual durante la COVID-19 en los colegios del distrito metropolitano de Quito, Ecuador, 2019-2020. Perception of virtual education during COVID-19 in the schools of the metropolitan district of Quito, Ecuador, 2019-2020

The perception of the students of the different educational units of the Metropolitan District of Quito in relation to online education as a result of COVID-19, is important because not all institutions were organized in an efficient way to teach classes in the middle of the pandemic. Objective: know the educational deficiencies that were presented in the virtual modality, since teaching was the responsibility of each educational center. Methodology: quantitative approach, descriptive type, cross-sectional. An online survey was conducted with a sample of 7,678 students from the different schools, out of a total of 349,216 students enrolled in the 2019-2020 school year, information provided by the Ministry of Education. Results: 67% of students do not feel satisfied with the organization of their respective schools to teach classes, 12% of municipal educational units were subject only to send homework, 42% of surveyed students indicated that planning of virtual education should be improved, since 55% state that the explanations of the classes have not been clear. Conclusion: a quality and generalized education has not been provided under the online modality, and the appropriate schools did not make decisions to be on a par with other institutions. It is recommended to the Ministry, Secretariat and all competent Education entities, establish a control and adjustment at a general level, about the new modality of education and this, is guaranteed.
EXAMINING THE RISK-TAKING PERSONALITY EFFECT ON STUDENTS ENGLISH PUBLIC SPEAKING ABILITY

The objective of this research was particularly to find out the correlation between the students’ risk-taking and their public speaking ability. This study focused on the ILC’s speaker in public speaking. This research was examined by using a quantitative method conducted at the international students' conference on students of the English Educational Department in Gorontalo Indonesia in the academic year 2016. In collecting the data were obtained from a questionnaire to measure their risk-taking and oral test to measure their speaking ability further used an adaptation of the formula conducted by Sigit (1999, as cited in Fhonna, 2014) to see the correlation between 2 variable. As the result, the hypothesis of the research was accepted. It had been proved there was a strong correlation between students’ risk-taking personality and students’ public speaking ability in the presenter of international students’ conference. It appropriates with criteria testing the tcount as big as 4,3593 whereas table distribution ttable obtained 2,0932. The value tcount bigger than ttable (4,3593>2,0932). As a result, the hypothesis H0 is accepted, and H1 is rejected. While based on the result of calculation of r Pearson product-moment correlation formula between variable X and variable Y are obtained r= 0,81 and determination coefficient of risk-taking towards students’ public speaking ability was r² = 0,7768 or 77,68 %. Article visualizations:
Graph View-Consistent Learning Network

Recent years, methods based on neural networks have made great achievements in solving large and complex graph problems. However, high efficiency of these methods depends on large training and validation sets, while the acquisition of ground-truth labels is expensive and time-consuming. In this paper, a graph view-consistent learning network (GVCLN) is specially designed for the semi-supervised learning when the number of the labeled samples is very small. We fully exploit the neighborhood aggregation capability of GVCLN and use dual views to obtain different representations. Although the two views have different viewing angles, their observation objects are the same, so their observation representations need to be consistent. For view-consistent representations between two views, two loss functions are designed besides a supervised loss. The supervised loss uses the known labeled set, while a view-consistent loss is applied to the two views to obtain the consistent representation and a pseudo-label loss is designed by using the common high-confidence predictions. GVCLN with these loss functions can obtain the view-consistent representations of the original feature. We also find that preprocessing the node features with specific filter before training is good for subsequent classification tasks. Related experiments have been done on the three citation network datasets of Cora, Citeseer, and PubMed. On several node classification tasks, GVCLN achieves state-of-the-art performance.
The Role of Extensive Reading in Improving General English Proficiency

This paper investigates the benefits of implementing extensive reading (ER), supporting techniques or approaches of ER as well as the practical aspects of ER in English as a foreign language (EFL) context. The method used in this study was integrative literature review which was proposed by Torraco (2005). The literature related to ER, its supporting techniques or approaches and the practical aspects was reviewed comprehensively. The results of this study indicate that ER can increase students’ general reading proficiency, reading rate, reading strategies, motivation, attitude, vocabulary, speaking and writing skills. In other words, it can improve general English proficiency. On the question of supporting techniques or approaches, Task-Based (TBL) approach and The Lexical Approach (LA) can be used to support ERP. Another important finding was that there are several practical aspects that can be considered when practicing ERP such as using graded readers, classroom library and reading circles. Hence, in order to help improve English language teaching, these findings can contribute in several ways to our understanding of ER and provide basis for implementing ERP in EFL context.
A map of Research Data in Egypt … Towards a Strategic Management

The world is experiencing unprecedented interest in Research Data Management (RDM), on three levels: the level of individual researchers themselves, the level of research institutions, and the national level. The researcher believes that there are three main reasons or motives behind interest in RDM, firstly to make most of the efforts and other resources and data collected for the benefit of several researches that share the target data with different dimensions, angles and methods of research. Secondly, Information technology also provides tools and software that facilitate most of the collection, organization, preservation, retrieval, documentation and insurance of data required for research projects in different fields and communities. Thirdly, the global trend of what is known as bibliometrics, altmetrics analytics and others. In fact, most of these research data analytics provide global indicators related to researchers and their research from several angles or dimensions, and take several forms, including: reports, lists and statistical sites either in specific areas of knowledge, or at a specific regional or global level without boundaries. It is now clear and announced by most donor agencies and institutions that financial support for research should ensure and ensure the successful management of research data at most stages of research as a prerequisite for obtaining grants, both during the research process and after completion. In this exploratory paper, which explores many international experiences and expertise in the field of research data management plans, the researcher is subjected to a precise inventory of research institutions in Egypt, whatever their names, fields, or administrative dependencies (universities, ministries, independent centers ...).
Fluorescent light error suppression for high-speed phase-shifting profilometry based on deep learning

In the recording process of phase-shifting profilometry, intensity fluctuation caused by uorescent light source instability may occur and then introduce a non-ignorable phase error. More importantly, the selection of sampling speed will also affect the value of the phase error, which even up to 0.12 rad. To suppress this problem, a deep learning-based fluorescent light error suppression (DLFLES) method is proposed to achieve high-precise measurement under fluorescent light. Experiments demonstrate that the shapes of the reconstructed 3-D images are more precise using the proposed method. Our research would promote the development of accurate 3-D measurement under the interference of external light sources by using deep learning.
Understanding Web Search Patterns Through Exploratory Search as a Knowledge-intensive Proces

To better understand users’ intent, Web search engines need to transcend its information sorter utility and acquire a more relevant ability concerning semantics’ discernment. This master thesis presents the Exploratory Search KiP model, which helps clarify the reasons why a subject is searched and supports the visualization of decision criteria used for choosing a specific search result. It also introduces the ESKiP Taxonomy of Query States; a classification framework that helps to represent the structure and behavior of query reformulation in search systems. As a result, the artifacts allowed to identify Web search and query reformulation patterns. The Exploratory Search KiP model also aided to distinguish three main behaviors involved in exploratory searches: (1) The ability to increase the level of familiarity with the topic and content searched (topic familiarity); (2) The ability to control the search process itself; and (3) The ability to assess the retrieved information relevance. For further reading: [Dias 2019] at UNIRIO’s repository. A summary article from the complete work was submitted to an international Information System Journal and is currently under review
Exploring Students‟ Perception On Using Macromedia Flash 8 Listening Activities (A descriptive Study at the Eight Grade Students of MTs Daar Al-Ilmi).

Triana Bela Salma. 161230049. Exploring Students‟ Perception On Using Macromedia Flash 8 Listening Activities (A descriptive Study at the Eight Grade Students of MTs Daar Al-Ilmi). The paper of English Education Department at Faculty of Education and Teachers Training of State Islamic University Sultan Maulana Hasanudin Banten, 2019/2020.This study aimed to explore and describe the student‟s, perception on the use of Macromedia Flash 8 at the eighth grade of Islamic Junior High School. The subject of this research is the students of eighth grade (n=98). The method of this study was qualitative and descriptive design. The data collecting procedures is questionnaire by google form. The writer used tabulation for the gained data to make the description of the data. The result of this study showed that 87, 70% of students gave positive and good perception on the use of Macromedia in Listening Activities, and morethan 87% of the student agrees that using Macromedia helped the students focused on understanding the contents. The students „remarks increased and listening activities by using Macromedia was effective. The results show that using Macromedia in Listening Activities have met the rules of the research and learning process. The results have implication for teacher and students to adapt and challenge their experiences in designing and sharing learning experiences.
Publishing as a subject of the creative industries in the context of its economic performance and protection of intellectual property rights

Creativity has been considered a new type of competitive advantage in recent years.It becomes the basis of a new direction, a new economic paradigm -creative economy.The aim of this paper is to evaluate the economic performance of creative industries in the publishing segment.The indicator dependence of profit on sales, with the exception of other publishing activities (issuing stamps, checks, banknotes, etc.), reaches Multiple R values close to 1, it confirms a strong addiction, it is moving in the range of 0.98-0.36.The strongest dependence is shown in other software publishing activities.The strong dependence of profit on sales is a signal for the companies to carefully monitor the causes of changes in their revenues, to use qualified tools to increase revenues such as discounts, rebates, delivery terms, etc.The dependence of profit on assets shows lower values, with the exception of publishing magazines and periodicals, Multiple R is in the range of 0.99-0.50.The protection of intellectual property thus becomes an elementary precondition for preserving the potential of the creative and cultural industries.There is a need to raise European citizens' awareness of the value of copyright, as well as the benefits for the development of a prosperous European legal market.
A Feature Weighted Kernel Extreme Learning Machine Ensemble Method for Gas Turbine Fault Diagnosis

Abstract Fault diagnosis is a very important section of gas turbine maintenance. Kernel extreme learning machine (KELM), a novel artificial intelligence algorithm, is a potentially effective diagnosis technology. The existing KELMs are all assumed that there is the same influence to the optimal separating hyperplane from all features, which reduces its generalization performance. In this study, a feature weighted kernel extreme learning machine ensemble method (FWKELM-RF) is developed for application in the field of gas turbine fault diagnosis. First, information gain ratio is introduced to assign different weights to the feature space. Furthermore, random forest is used to enhance stable performance of feature weighted KELM. The fault datasets from a gas turbine with three shafts is generated to validate the performance of the developed method, and the results demonstrate that FWKELM-RF can achieve better accuracy and stability for detecting fault in gas turbine.