Reviewerly/exHarmony huggingface dataset:
Voters face COVID-19 concerns at polls on Election Day

The COVID-19 pandemic has ravaged the world, with the world leader, the United States, also leading in cases and deaths, with more than nine million cases and more than 230,000 dead -- lives have been upended, businesses shuttered.
Kemampuan Menulis Mahasiswa PBJ UNNES Semester 3 Tahun 2019/2020 (Penilaian Kemampuan Berdasarkan JF Standard)

The application of JF Standard in learning Japanese especially in the Sakubun Shochukyu course is new and needs to be evaluated how the achievement of it’s learning targets. This study aims to find out how the semester 3 students' abilities are in writing. The research uses a quantitative approach and the research data are discussed with descriptive techniques. To assess the results of student essays used essay grading rubric based on JF Standard with 4 grading levels namely ganbare, mousukoshi, dekimashita, and subarashii for each item assessed. The results showed that in general, the students' writing ability was in the "dekimashita" or “very good” category with the note that there were still some errors in using grammar. Statistically, 1 student has a very high ability, 4 students have high ability, 18 students have the medium ability, and the remaining 8 are students who have low ability.
Diversification of distance foreign language education

International scientific and practical conference «Current trends and factors of the development of pedagogical and psychological sciences in Ukraine and EU countries» : conference proceedings, September 25–26, 2020. Lublin : Izdevnieciba «Baltija Publishing», 2020. 516 pages.
Factors Contributing to the English National Achievement Test (Nat) Performance

Purpose: The main purpose of this study was to determine the factors that contributed to the English National Achievement Test (NAT) Performance of the Top Five High Performing Secondary Schools in the Division of Bohol for school years 2009-2010 and 2010-2011.&#x0D; Approach/Methodology/Design: It utilized descriptive-correlational research design through survey method.&#x0D; Findings: The results of the study revealed that the practices of the teachers on the school factors that affect students’ English NAT performance were having: class size of 31 to 50 students, a student-book ratio of 1:1, monthly supervision of heads, review classes every Saturday and remedial teaching as the need arises. However, there was a significant relationship between all the four teacher factors namely: age, highest educational attainment, length of service and number of relevant seminars; eight of the nine school factors. Teacher’s age, number of relevant seminars attended, conduct of remedial teaching and students’ academic performance are the factors contributing to the students’ English NAT results for school year 2009-2010 while teacher’s number of relevant seminars attended, varying teaching strategies, pairing low performing students with high performing ones and students’ academic performance are the factors contributing to the students’ English NAT results for school year 2010-2011.&#x0D; Practical Implications: The results of this studying should be taken into account in order to improve students’ NAT performance in English.&#x0D; Originality/value: This research concludes that all the factors are interrelated.
Development of methods for pre-clustering and virtual merging of short documents for building domain dictionaries

The aim of research is to improve the quality of domain dictionaries by expanding the corpus of the documents under study by using short documents. A document model is proposed that allows to define a short document and the need to combine it with other documents to highlight verbose terms. An algorithm for highlighting the substantive part of the document has been developed, since in a short document the heading and closing parts usually contain terms that are not related to the studied domain. A method for preliminary clustering of short documents to highlight verbose terms has been developed. The method is based on highlighting and counting occurrences of nouns (one-word terms) for all analyzed documents. The concept of document proximity is introduced, which is determined by the combination of two criteria: the relative number of matching terms and the relative frequency of occurrence of matching terms. The principle of grouping documents at the customer's site often does not correspond to the principles of grouping necessary for building a dictionary of the domain. In a short document, it is usually impossible to isolate a verbose term because the repetition of terms is very low. A method has been developed for virtual combining of short documents based on the principle of achieving the necessary repeatability of one-word terms. The merged document has the highest possible frequency of terms for the cluster it belongs to. At the same time, the original text of documents is preserved and the ability to associate the selected verbose term with those documents in which it is included. The experiment made it possible to find the best ratio for the elements of the document proximity coefficient and confirm the effectiveness of the proposed preliminary clustering method
Analisis Rencana Pelaksanaan Pembelajaran (RPP) Kelas 1 Muatan Pelajaran Bahasa Indonesia Tema 6 Subtema 2 SDIT Savana Islamic School

Proses pengembangan Rencana Pelaksanaan Pembelajaran seharusnya disesuaikan dengan beberapa panduan yang telah diatur dalam peraturan menteri pendidikan tentang Kurikulum 2013 yang sedang berlaku. Penelitian ini bertujuan untuk mengetahui hasil analisis dokumen Rencana Pelaksanaan Pembelajaran (RPP) muatan pelajaran Bahasa Indonesia Tema 6 Subtema 2 SDITÂ  Savana Islamic School Tahun Pembelajaran 2019/2020. Penelitian ini menggunakan sumber data yaitu sebanyak 6 RPP tematik kelas 1 pada Tema 6 subtema 2 dengan fokus analisis terhadap muatan pelajaran Bahasa Indonesia. Metode penelitian yang digunakan pada penelitian ini adalah deskriptif kualitatif. Instrumen yang digunakan adalah peneliti sendiri, tabel kelengkapan komponen, sistematika penyusunan komponen RPP dan pedoman penelaah RPP. Hasil penelitian menunjukkan bahwa RPP yang dibuat oleh guru kelas 1 SDITÂ  Savana Islamic School Tema 6 subtema 2 memperoleh rata-rata skor 75 dengan kategori sesuai, namun beberapa komponen belum sesuai dengan pedoman penyusunan RPP yang terdapat pada Permendikbud nomor 22 tahun 2016. The process of developing a Lesson Plan should be adjusted to the guidelines set out in the current minister of education regulation. This study aims to determine the results of the analysis of the LessonÂ  Plan (RPP) document for the content of Indonesian Language Theme 6 Subthemes 2 SDITÂ  Savana Islamic School 2019/2020 Academic Year. This study uses data sources as many as 6 thematic RPPs grade 1 on Theme 6 subtheme 2 with a focus on analysis of Indonesian language content. The research method used in this research is descriptive qualitative. The instrument used was the researcher himself, the component completeness table, the systematic preparation of the components of the lesson plan and the guidelines for the review of the lesson plan. The results showed that RPP made by grade 1 elementary school teacher SDITÂ  Savana Islamic School Theme 6 obtained an average score of 75 with the appropriate category, but some components were not in accordance with the guidelines for the preparation of the RPP contained in Permendikbud number 22 in 2016
The CLASSLA-StanfordNLP model for named entity recognition of non-standard Croatian 1.0

This model for named entity recognition of non-standard Croatian was built with the CLASSLA-StanfordNLP tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the hr500k training corpus (http://hdl.handle.net/11356/1183), the ReLDI-NormTagNER-hr corpus (http://hdl.handle.net/11356/1241) and the ReLDI-NormTagNER-sr corpus (http://hdl.handle.net/11356/1240), using the CLARIN.SI-embed.hr word embeddings (http://hdl.handle.net/11356/1205). The training corpora were additionally augmented for handling missing diacritics by repeating parts of the corpora with diacritics removed.
The Fast Integration of a Rotated Rectangle Applied to the Rotated Haar-Like Features for Rotated Objects Detection

In the area of Object Detection, the most important step is the extraction of object features. One of the most used approaches is HaarLike features and the Integral Image technique to integrate them. The Integral Image technique, used by Viola and Jones, is generally used to calculate the integral of a rectangular filter in an input picture. This filter is a rectilinear rectangle. We propose a method to integrate a rotated one by any angle of rotation inside an image based on the Bresenham algorithm of drawing a segment. We use some pixels – called key points - that forms the four segments of a rotated rectangle, to calculate its Integral Image. Our method focuses on three essential tasks; the first is to determine the rule for drawing a segment (SDR), the second is to identify all the key points of the rectangle r, and the third is to calculate the integral image. The speed of this method depends on the size and angle of rotation of the rectangle. To demonstrate the efficiency of our idea, we applied it to the rotated Haar-like features that we proposed in a later work [12], which had as objectives the improvement of the Viola and Jones algorithm to detect the rotated faces in a given image. We performed tests on more widespread databases of images, which showed that the application of this technique to rotated Haar-Like features improves the performance of object detectors, in general, and faces in particular.
Weakly Supervised Sentiment-Specific Region Discovery for VSA

Abstract Local information has significant contributions to visual sentiment analysis (VSA). Recent studies about local region discovery need manually annotate region location. Affective local information learning and automatic discovery of sentiment-specific region are still the challenges in VSA. In this paper, we propose an end-to-end VSA method for weakly supervised sentiment-specific region discovery. Our method contains two branches: an automatic sentiment-specific region discovery branch and a sentiment analysis branch. In the sentiment-specific region discovery branch, a region proposal network with multiple convolution kernels is proposed to generate candidate affective regions. Then, we design the multiple instance learning (MIL) loss to remove redundant and noisy candidate regions. Finally, the sentiment analysis branch integrates both holistic and localized information obtained in the first branch by feature map coupling for final sentiment classification. Our method automatically discovers sentiment-specific regions by the constraint of MIL loss function without object-level labels. Quantitative and qualitative evaluations on four benchmark affective datasets demonstrate that our proposed method outperforms the state-of-the-art methods.
LOY 2017 2nd runner up award winner: a reflection by Mr Mnengi

LIASA Librarian of the Year 2nd Runner up award winner 2017 report poster in 2019 at LIASA annual Conference held at Durban ICC. The award was sponsored by SapNet now called NAVADA.
Perencanaan Strategis Sistem Informasi pada Industri Suku Cadang Otomotif Menggunakan Metode Ward dan Peppard (Studi Kasus PT XYZ)

The automotive industry is required to carry out product development and distribution of production results in accordance with market needs. PT XYZ is the largest and leading automotive group company in Indonesia that manufactures and distributes a wide range of two-wheeled and four-wheeled motor vehicle parts. The growth of national economy that relatively low affects on the weakening of the purchasing power of the people, thereby contributing negatively to the growth of the spare-parts market. In addition, there are several strategic issues that have occurred at PT XYZ. Based on these strategic issues, an information system strategic planning is needed, with the aim of supporting the course of the company's business processes and supporting the application of information systems and IT infrastructure that follows the development of business and technology. This research covers business models, analysis of the business environment, issues that arise from information systems strategies, and the preparation of IS, IT, and IS/IT management strategies. This study uses a model from Ward and Peppard. The stages carried out in this study are analysis of current conditions, analysis of future conditions, gap analysis and strategic planning, as well as the preparation of a roadmap and migration plan. The outputs of this study are twelve information systems development, five IT infrastructure developments, and three IS/IT management developments.
Pre-Conscious Automaticity of Sound-­‐Shape Mapping

The bouba–kiki effect depicts a non-arbitrary mapping between specific shapes and non-words: an angular shape is more often named with a sharp sound like ‘kiki’, while a curved shape is more often matched to a blunter sound like ‘bouba’. This effect shows a natural tendency of sound-shape pairing and has been shown to take place among adults who have different mother tongues (Ramachandran &amp; Hubbard, 2001), pre-schoolers (Maurer, Pathman, &amp; Mondloch, 2006), and even four-month-olds (Ozturk, Krehm, &amp; Vouloumanos, 2013). These studies therefore establish that similar sound-to-shape mappings could happen among different cultures and early in development, suggesting the mappings may be innate and possibly universal. However, it remains unclear what level of mental processing gives rise to these perceptions: the mappings could rely on introspective processes about ‘goodness-of-fit,’ or they could rely on automatic sensory processes which are active prior to conscious awareness. Here we designed several experiments to directly examine the automaticity of the bouba-kiki effect. Specifically, we examined whether the congruency of a sound-shape pair can be processed before access to awareness?
Modelling Human Capital Resource Mobilisation Practices for Sustaining Business Productivity among Small Businesses in Nigeria

Human capital has long been argued as a critical resource in most companies for sustaining development of business productivity. The study empirically determined the effect of human capital resource capacity on sustainable increase in productivity of agro-allied small businesses in Nigeria. The instrumentality of this study is the research questions structured in a five-point likert scale. The Linear Regression Analysis used to test the hypotheses. Statistical Packages for Social Sciences (SPSS) was used to aid the data analysis. The study discovered that human capital has positive and significant effect on sustainable increase in productivity of agro-allied small businesses in Nigeria. The study recommended education the small business entrepreneurs on the benefits of equity financing as a viable option towards business growth and expansion.
Empowering Organizations in the Food Sector to Provide Potentially Unknown Parties Easy Access to Trusted Data. Discussion of a Web-based, Globally Applicable Solution Based on Well-established Standards and Technologies

A number of the most relevant trends for the food sector require increased data sharing amongst different stakeholders. However, apart from established communication methods in the business-to-business (B2B) domain (e.g. bilateral exchange of EDI transactions or product master data synchronization), the level of standardization is low. There is no consistent, reliable and standardized entry point through which interested parties can easily discover and access data on products, shipments, parties, assets, or further business objects. Against this background, this paper aims at contributing to address this issue. To this end, it employs a number of prototypes and use cases to investigate the applicability of a new standard, GS1 Digital Link, in different areas of application. Thereby, it touches upon brand-authorized data (e.g. product information pages, list of retailers selling a given product), data for users of reusable transport items (e.g. temperature profiles provided by IoT-empowered trays), consumer-oriented data (e.g. nutrition information, related videos), master data pertaining to arbitrary business objects, service endpoints of EPCIS servers, and laboratory test data. The analysis reveals that the technical ecosystem GS1 Digital Link provides (especially normative specifications for resolvers, standardized link types, and consistent URI patterns) indeed represents an open, flexible, scalable, and future-oriented solution approach, which is superior to existing, proprietary solutions in various ways. In the course of the discussion, the paper also points to various open source projects intended to ease the adoption of this standard.
융합인재교육(STEAM) 프로그램의 학습 평가 경향 분석

The purpose of this study was to investigate learning assessment trend of STEAM program to provide it as understanding for STEAM process-oriented assessment. A total of 289 STEAM programs of elementary, middle, and high schools developed by STEAM research groups' teachers were analyzed. The analysis...
CARINA based Cognitive Agent for Factoid Wh-Questions Generation in EFL

The Metacognitive Architecture CARINA is used to execute cognitive agents. CARINA is defined as a metacognitive architecture for artificially intelligent agents and is derived from the MISM Metacognitive Metamodel. A Factoid WH- question (FWhQ) is an interrogative statement that begins with a WH word (when, what, where, who, which) and gives a fact as answer reflected in the text. A Cognitive Agent is an entity of software that perceives stimulus from its external environment to achieve its goals selecting actions from its internal knowledge rationally. The problem which is tackled in this research is the need to offer and develop educational resources enabling foreign language learners to better cope with this type of questions, problem perceived as a priority in the Foreign Language Program at Universidad de Cordoba. This paper aims at reporting the design of a Cognitive Agent-based on Metacognitive architecture CARINA for the generation of Factoid WH- Questions. The methodology used in this study involved the cognitive modelling designed for this purpose, which consists of seven steps and the application of a test for validation based on 2 research questions focused on two specific dimensions: Readability and Potential Usefulness. Results showed that cognitive models based in M++ are easy to read and allows understanding the relations among different elements of a cognitive model. This allowed a cognitive agent to be developed to answer Factoid questions in English.
Valley Viz

Describes the art of Scott Kildall. In presenting "Strewn Fields" to the art world, Scott Kildall demonstrated that data could be made into art. In showing the work to non-scientists or those more aesthetically or materially oriented, he told a story viewers could understand. Whereas if he showed them a graphics program or a computer-generated data visualization, it might be a turn-off.
INVESTIGATING THE EFFECT OF HIGH AND LOW WIND SPEED ON SURPLUS NET RADIATION IN MAKURDI, NIGERIA: AN IMPLICATION TO ENERGY IMBALANCE

This study aims at investigating the effect of wind speed on net radiation by conditioning the chance occurrence of surplus net radiation on high and low wind speed in Makurdi, Nigeria. A two – state (surplus net radiation conditioned on high wind speed and surplus net radiation conditioned on low wind speed) Markov Chain model was developed and used in the course of this work. The result revealed; net radiation is surplus all through the year, no definite linear trend between net radiation and wind speed and two extreme results of the Markov Chain model. This include; a steady state or long run chance of 62% surplus net radiation conditioned on low wind speed and 38% surplus net radiation conditioned on high wind speed occurring in the month of January and April. Further analysis with the model showed that it takes 2.44 days for surplus net radiation conditioned on high wind speed and 1.69 days for surplus net radiation conditioned on low wind speed on the average to reoccur from January – December. Thus, resulting to increase in air temperature in Makurdi all through the year.
Pedestrian Detection Based on Improved Mask R-CNN Algorithm

As the modern society evolves around digital media, object recognition becomes one of the important areas for computer vision. Pedestrian detection particularly draws much attention because it is closely related to everyday life. Recently, pedestrian detection has achieved great success in intelligent monitoring, intelligent driving, and environmental protection. Although, there are several pedestrian detection algorithms based on deep learning, the pedestrian detection is still a huge challenge. Background occlusion, pedestrians’ various changing postures and objects’ occlusion give significant impact on the recognition results; it still brings up much attention. In this paper, to reduce the influence of external factors, we propose a new method based on Mask R-CNN algorithm. The proposed system was evaluated on the Daimler pedestrian dataset for training and on the public Caltech and INRIA pedestrian datasets for testing. The experimental results have showed that the proposed algorithm achieves better detection accuracy than the conventional ones.
Pemodelan Fuzzy Mamdani untuk Mengukur Kinerja Dosen Menggunakan Key Performance Indicator

&lt;em&gt;The measurement of lecturer performance is done in terms of objectivity and the absence of measurable variables used, so that the assessment variables used in the measurement process are based on one's perception. Inaccuracy in measuring lecture performance can be applied with the fuzzy mamdani method so that measurements become more precise. Weighting is done for each parameter that refers to the Key Performance Indicator. To support the performance of the lecturer, the data was obtained from lecturer data in the Faculty of Engineering which was processed to get the output. The formation of fuzzy mamdani rules has 79 rulebases from experts, from the results of research that has been done, the input variables for fuzzy calculations in this system are the Education, Research, Community Service, Self-development and output variables namely the lecturer performance value. The fuzzy set used in each fuzzy variable is not good, moderate, and good. The Mamdani fuzzy method is a mathematical framework used to present uncertainty, obscurity, inaccuracy. In fuzzy mamdani done in stages (a) the formation of the fuzzy set, (b) the application of the implication function, (c) forming the rules, (d) affirmation (defuzzification). From the results of the study, obtained a comparison of measurements with KPI without fuzzy and KPI with fuzzy which produces fluctuating values, where KPI using fuzzy has better results than KPI without fuzzy. In the fuzzy mamdani method produces values that move smoothly, this difference is shown from the significance value (2-tailed) produced is smaller than α = 0.05 which is 6.09 x 10&lt;sup&gt;-5&lt;/sup&gt;, so that the KPI uses fuzzy significantly different from KPI without fuzzy. &lt;/em&gt;