Reviewerly/exHarmony huggingface dataset:
Connected component labeling algorithm in streaming image processing with FPGAs

The task of image fragments extraction with objects of interest is not new. The choice of appropriate segmentation algorithm and its implementation in real time mode become a problem in systems operating with a high-speed video data stream. Connected components labeling is an important step in training samples images preparation for usage in neural networks. To ensure high speed and feasibility of image labeling algorithm for the FPGA, it is necessary to justify the choice of segmentation algorithms, considering the hardware capabilities of the platform. In this paper, we propose a modified one-pass image labeling algorithm for FPGAs, as well as its implementation using the Xilinx System Generator for DSP and the Matlab/Simulink package. As a hardware platform the FMC-200-A mezzanine is used to provide high-speed video data stream from the line camera TELEDYNE DALSA LA-CC-04K05B00-R to the ZYNQ Ultrascale + MPSoC ZCU106 evaluation kit board. The procedure of using hardware implemented SPI interface on the MPSoC ZCU106 board, which is to configure and control the FMC200-A module is described. Implementation of SPI interface is made by using Vivado and Vitis IDE. The labeling results of proposed algorithm on test images, as well as images obtained experimentally are presented.
Analisis Tata Ruang Perpustakaan Sekolah

This study aims to determine the arrangement of the library space in SMA N 5 Solok Selatan and to know the physical and non-physical conditions of the library space in SMA N 5 Solok Selatan. This research is a descriptive study with qualitative methods which have 2 types of data, namely primary data and secondary data. This research instrument uses a list of interview questions and data collection techniques by conducting observations, interviews, and documentation to support the implementation of this research. Based on the research results, it shows that: the library of SMA N 5 Solok Selatan is in line with the function of the school library in general, where the location of the library can be said to be strategic because it is in the middle of a school environment. However, the area of the library building / space is currently categorized as narrow when compared to the large number of students. Then, for the arrangement of the library space is still classified as not paying attention to psychological, functional and aesthetic aspects. Another thing is also seen from the physical condition of the library which is still said to be inadequate, this can be seen from the less bright lighting and the dark and hot air circulation. Meanwhile, the non-physical condition is still incomplete, seen from the lack of furniture and equipment available in the library.
Sentence-level Planning for Especially Abstractive Summarization

Abstractive summarization models heavily rely on copy mechanisms, such as the pointer network or attention, to achieve good performance, measured by textual overlap with reference summaries.As a result, the generated summaries stay close to the formulations in the source document.We propose the sentence planner model to generate more abstractive summaries.It includes a hierarchical decoder that first generates a representation for the next summary sentence, and then conditions the word generator on this representation.Our generated summaries are more abstractive and at the same time achieve high ROUGE scores when compared to human reference summaries.We verify the effectiveness of our design decisions with extensive evaluations.
Terrestrial Unmanned Roving Vertical Take-off and Landing (TURVTOL)

As the uses for autonomous rovers and drones has increased with their variability and utility,a fundamental gap has emerged - one which melds multi-modal capabilities into a singular unit. This project aims to fill that gap with the introduction of a multi-modal unmanned vehicle concept that can traverse ground quickly, hop or fly over obstacles and hazardous areas, and operate without the use of GPS or a human in the loop. The 2020 NASA Academy at Langley has developed a first iteration conceptual design of such a vehicle. This design has proven to be feasible through analyses confined to simulated environments.
Peningkatan Kemampuan Menulis untuk Menentukan Topik dalam Paragraf Melalui Pendekatan Contextual Teaching and Learning

This study aims to improve writing skills to determine topics in paragraphs through a contextual teaching and learning approach to class VIII students at State Junior High School 8 Bayung Lencir, Muba. The method used is a class room action research method with data in the form of tests classified as quantitative data and data in the form of observations classified as qualitative data. Based on the results of data analysis that has been carried out on class VIII students of State Junior High School 8 Bayung Lencir, Muba from cycle I to cycle III there was a positive increase in each cycle of writing ability to determine topics in paragraphs through a contextual teaching and learning approach. Thus, there is an increase in the results of the writing ability test to determine the topic in the paragraph through a contextual teaching and learning approach
Students Who Study Together Learn Better: On the Importance of Collective Knowledge Distillation for Domain Transfer in Fact Verification

While neural networks produce state-of-the-art performance in several NLP tasks, they depend heavily on lexicalized information, which transfers poorly between domains.Previous work (Suntwal et al., 2019) proposed delexicalization as a form of knowledge distillation to reduce dependency on such lexical artifacts.However, a critical unsolved issue that remains is how much delexicalization should be applied?A little helps reduce over-fitting, but too much discards useful information.We propose Group Learning (GL), a knowledge and model distillation approach for fact verification.In our method, while multiple student models have access to different delexicalized data views, they are encouraged to independently learn from each other through pair-wise consistency losses.In several cross-domain experiments between the FEVER and FNC fact verification datasets, we show that our approach learns the best delexicalization strategy for the given training dataset and outperforms state-of-theart classifiers that rely on the original data.
AN APPLICATION FOR THE DOCTORS+

Doctors+ is an application intended with the focal goal of creating a convenient and reliable health care system. It holds data integrity, effective communication, reliable storage and relay of information among many of its central objectives. Further integration with intelligent systems allows it to provide an interactive and predictive interface for the stakeholders involved.
MiSS: An Assistant for Multi-Style Simultaneous Translation

In this paper, we present MISS, an assistant for multi-style simultaneous translation.Our proposed translation system has five key features: highly accurate translation, simultaneous translation, translation for multiple text styles, back-translation for translation quality evaluation, and grammatical error correction.With this system, we aim to provide a complete translation experience for machine translation users.Our design goals are high translation accuracy, real-time translation, flexibility, and measurable translation quality.Compared with the free commercial translation systems commonly used, our translation assistance system regards the machine translation application as a more complete and fullyfeatured tool for users.By incorporating additional features and giving the user better control over their experience, we improve translation efficiency and performance.Additionally, our assistant system combines machine translation, grammatical error correction, and interactive edits, and uses a crowdsourcing mode to collect more data for further training to improve both the machine translation and grammatical error correction models.A short video demonstrating our system is available at https://www.youtube.com/watch?v=ZGCo7KtRKd8.
Review on Phishing Attack Detection using Recurrent Neural Network

Abstract: Phishing is a crime that involves the theft of personal information from users. Individuals, corporations, cloud storage, and government websites are all targets for the phishing websites. Anti-phishing technologies based on hardware are commonly utilised, while software-based options are preferred due to cost and operational considerations. Current phishing detection systems have no solution for problems like zero-day phishing assaults. To address these issues, a three-phase attack detection system called the Phishing Attack Detector based on Web Crawler was suggested, which uses a recurrent neural network to precisely detect phishing incidents. Based on the classification of phishing and non-phishing pages, it covers the input features Web traffic, web content, and Uniform Resource Locator (URL). Keywords: Attack detection, Recurrent Neural Network, Deep Learning.
Deep Learning Through the Lens of Example Difficulty

Existing work on understanding deep learning often employs measures that compress all data-dependent information into a few numbers. In this work, we adopt a perspective based on the role of individual examples. We introduce a measure of the computational difficulty of making a prediction for a given input: the (effective) prediction depth. Our extensive investigation reveals surprising yet simple relationships between the prediction depth of a given input and the model's uncertainty, confidence, accuracy and speed of learning for that data point. We further categorize difficult examples into three interpretable groups, demonstrate how these groups are processed differently inside deep models and showcase how this understanding allows us to improve prediction accuracy. Insights from our study lead to a coherent view of a number of separately reported phenomena in the literature: early layers generalize while later layers memorize; early layers converge faster and networks learn easy data and simple functions first.
Rewards with Negative Examples for Reinforced Topic-Focused Abstractive Summarization

We consider the problem of topic-focused abstractive summarization, where the goal is to generate an abstractive summary focused on a particular topic, a phrase of one or multiple words.We hypothesize that the task of generating topic-focused summaries can be improved by showing the model what it must not focus on.We introduce a deep reinforcement learning approach to topic-focused abstractive summarization, trained on rewards with a novel negative example baseline.We define the input in this problem as the source text preceded by the topic.We adapt the CNN-Daily Mail and New York Times summarization datasets for this task.We then show through experiments on existing rewards that the use of a negative example baseline can outperform the use of a self-critical baseline, in ROUGE, BERTSCORE, and human evaluation metrics.
Legendre wavelet approximation of functions having derivatives of Lipschitz class

In this paper, Legendre Wavelet approximation of functions f having first derivative f' and second derivative f'' of Lip? class, 0 &lt; ? ? 1, have been determined. These wavelet estimators are sharper, better and best possible in Wavelet Analysis. It is observed that the LegendreWavelet estimator of f whose f'' ? Lip? is sharper than the estimator of f having f ' ?Lip? class.
RANCANG BANGUN SISTEM INFORMASI AKUNTANSI PEMBAYARAN UANG SEKOLAH BERBASIS CLIENT SERVER

Along with the development of technology, computerized systems are needed in the business world. The computer has a function as a data processing tool that will assist in completing work quickly and precisely. MA Nurul Ulum as an educational institution, especially in the implementation of payment administration activities, still uses a manual or conventional system, so there are still many shortcomings and obstacles that result in a job not being able to run properly. Therefore we need a new system, namely a computer-based payment administration system in order to be able to manage and process payment data quickly, because with computer technology both students and other parties who want to know information related to tuition payments can get it quickly.&#x0D; The purpose of this study is to improve the quality of service to students or parents in making tuition payments. The advantage of the system that will be made is that it provides an administrative information system for paying school fees so that it can make it easier to perform data processing and data retrieval. With an administrative information system that has been integrated in a database, it will facilitate the process of financial calculations and the existence of a Client Server-based school administrative information system will connect between sections, namely the administrative section, school treasurer, principal and head of the foundation making it easier to access financial information. school any time
Analisa Perbandingan Squid 2.7, Squid3, Dan Squid Lusca Sebagai Cache Proxy Server Pada Ubuntu Server

RT/RW Net Joho Baru is one of the internet service provider organizations. As one of the growing internet service provider RT/RW Net Joho Baru has to give the best and the quickest services to the customers. So that it need appropriate technology which is support to the best networks to give good services to the customers. The Important factors are cost and speed factors which related to the material efficiency and time. This research is comparing about proxy server operating systems such as Squid 2.7, Squid3, and Squid Lusca, so that it can easier to find out the appropriate operating systems to build the best network. SDLC Method has several steps. The first step is the analysis of feasibility study which included software and hardware. The second step is the analysis of needs which is planning relate to the system project. Then network planning design is going apply. Next, continuing design system to system testing. Based on these steps, the proxy server is successfully to shorten time management on accessing the website. The results of the efficiency acquisition are Squid 2.7 at 75,1%, Squid3 at 83,5%, and Squid Lusca at 86,9%.
The Implementation of Padlet to Foster EFL Students’ Achievement in Writing

This study is the quasi experimental research that aimed to know the effect of the implementation of Padlet to the students’ achievement in writing. The implementation Padlet as independent variables and the students’ achievement in writing as a dependent variable. The population in this research is all students class XI MIA MAN 1 Makassar that consist of eight classes. Class XI MIA 5 as a control group that consist of 30 students and class XI MIA 1 as an experiment group that consist of 30 students. The data of the research was obtained by the study results test on the subject of the velocity reaction for pre-test and post-test. The data was analyzed by writing test. Based on analysis of inferential statistics for writing achievement, the P = 0.001, and it less than  = 0,05 was obtained, it is means that the implementation Padlet is significantly influence to the students’ achievement in writing of the students’ class XI MIA 1 MAN I Makassar on the material subject of writing.
MENTALITY PHENOMENON IN THE EXPLICATIONS OF MODERN UKRAINIAN MUSICOLOGY

One of the concepts that has been filled with musicological content in recent decades is the mentality, through the prism of which trends and phenomena of musical culture are analyzed. Thus, the current musicological problem is the systematization and generalization of knowledge and ideas in order to form a holistic view about the mental features of certain musical cultures and their academic art manifestations. The aim of the article – on the basis of mentality scientific explanations to create a sketch vision of this phenomenon in modern Ukrainian musicology. Research methodology is reflected in the following problems: 1) analysis of basic research on the problem of mentality in Ukrainian musicology; 2) highlighting the main ideas of leading domestic scientists on this phenomenon; 3) introduction of own opinion in processing of a task; 4) generalization and disclosure of prospects for further research on this topic. Scientific novelty. The development of Ukrainian musicological thought on the mentality phenomenon and highlights the main achievements of domestic scientists in this perspective is followed in the article. The idea about differentiating the collective unconscious archetypes as artistic creativity basis into two types is declared: invariant («symbols») and variant («symbols of symbols»). Conclusion. Among the most important achievements on the raised problem are the following ideas. I. Liashenko’s idea about the differentiation of thinking ways as mental manifestations, ideas by N. Goryukhina and N. Gerasimova- Persidskaya about national identity in music, by L. Kyianovska on cordocentrism and stylistic aclassicism in Ukrainian music, by O. Katrych about the Dionysian archetype as dominant in Ukrainian musical-performing stylistics, M. Severinova's differentiation of artistic thinking levels in accordance with the provisions of the K. H. Jung’s collective unconscious theory and others.
Discursive learning of students in terms of polytasking: retrospective analysis

The article presents the results of the theoretical research of the issue of using the potential of discursive learning in the process of teaching students of the university in terms of specific polytasking. Possibilities of using discursive learning by structuring the educational material according to different forms of presentation (oral, written, problematic, non-verbal, indirect) have been emphasized. The model of hypothetical trajectories of discursive learning of a student of the university taking into account the features of polytasking has been developed based on the involvement of polytasking potential. The developed model specifies its target orientation (purpose, goal, expected result) and technological completeness. At the theoretical level, the stage-by-stage implementation of the model has been substantiated and the effects of its use in terms of the students’ classroom and extracurricular activities have been determined.
Android Based Application of Bussines License at Department Of Industry and Trade In Jayapura City

Android Based Application of Bussines License at Department Of Industry and Trade In Jayapura City was built with the aim of making it easier for applicants to apply for SIUP online using cellphones and to improve public services at the Jayapura City Industry and Trade Office. The processing of a Trade Business Permit (SIUP) which has been done manually, which is submitted directly to the Jayapura City Office of Industry and Trade, can be done by accessing it via an Android phone. The research methods used are 1) Data collection methods are carried out through literature studies, interviews and documentation, 2) application development methods with communication stages, planning quickly, designing quickly, modeling and designing quickly, forming prototypes, software to users and feedback. Programming language used is PHP MYSQL and AppGeyser. The results of the design are in the form of an application that can process input data: applicant's personal data, company data, submission data, admin data, data confirmation, SIUP upload and the resulting output is SIUP data print, SIUP application number report.
A Text Editing Approach to Joint Japanese Word Segmentation, POS Tagging, and Lexical Normalization

Lexical normalization, in addition to word segmentation and part-of-speech tagging, is a fundamental task for Japanese user-generated text processing.In this paper, we propose a text editing model to solve the three task jointly and methods of pseudo-labeled data generation to overcome the problem of data deficiency.Our experiments showed that the proposed model achieved better normalization performance when trained on more diverse pseudo-labeled data.
What If Sentence-hood is Hard to Define: A Case Study in Chinese Reading Comprehension

Machine reading comprehension (MRC) is a challenging NLP task for it requires to carefully deal with all linguistic granularities from word, sentence to passage.For extractive MRC, the answer span has been shown mostly determined by key evidence linguistic units, in which it is a sentence in most cases.However, we recently discovered that sentences may not be clearly defined in many languages to different extents, so that this causes so-called location unit ambiguity problem and as a result makes it difficult for the model to determine which sentence exactly contains the answer span when sentence itself has not been clearly defined at all.Taking Chinese language as a case study, we explain and analyze such a linguistic phenomenon and correspondingly propose a reader with Explicit Span-Sentence Predication to alleviate such a problem.Our proposed reader eventually helps achieve new a state-of-the-art on Chinese MRC benchmark and shows great potential in dealing with other languages.
A longitudinal study on how informal science learning is applied in generic learning outcomes (GLO)

Education in the informal educational environment is very important in terms of be ing able to provide essential knowledge that formal education cannot provide.But the reality is that there is no research on how the study of ISL has been done from the past to the present.Thus, this paper seeks to compare and analyze the recent research trends of paper s relating to ISL published within a specific timeframe.The target research papers for analysi s are based on ISL-related academic dissertations, articles and research reports, which were l ocated via Google and Google Scholar, within the period of 2010 to 2019.Each research pap er was classified into 8 indicators: 'Paper Type', 'ISL Type', 'Research Design', 'Subject of stud y', 'GLO Type' and 'Country', which were then analyzed accordingly and tested for suitability through 'Chi-Square Test'.The study of ISL was led by the United States and the United Kin gdom and there was no significant difference by year.Most of the research samples tended t o converge towards 'Empirical research articles' and 'Position papers', with studies on ISL als o mostly containing information related to advice, recommendation and support.It was found that the researchers were using ISL in order to pursue 'Knowledge and Understanding' and 'Attitudes and Values', of the 5 indicators of the 'GLO'.In contrast, they were found to have the least expectations for 'Skills' and 'Enjoyment, Inspiration and Creativity', suggesting the n eed for future improvement in these areas.Although this paper suffers from limitation with r egards to time period as it focuses on research work published from 2010 to 2019, it attem pts to suggest a direction for program development and research for various educational prac titioners working in 'ISL'.Also, it hopes to provide a good opportunity for institutions using 'ISL' in the field, as well as teachers and future researchers.