Reviewerly/exHarmony huggingface dataset:
Analysis and Design Ecommerce with User Centered Design (UCD) Method at PT. Multi Prima Mandiri Sukses

The development of technology moves so rapidly beyond human expectations in general, all eyes and minds are shocked by the sophistication of a technology that is packaged to represent various systems in the world, as well as the business world which is touched by technological developments and changes the way of doing business from the old model to be more sophisticated and efficient. PT. Multi Prima Mandiri Sukses is a company that sells laserjet toner ink and various laserjet printer rentals for office needs. The problem that occurs is in the sales department that so far sales are still carried out conventionally by ordering by telephone and sales records are still in the form of physical data where sales reach is not wide and sales data are easily lost. To overcome this problem, an online sales platform was built in the form of e-commerce with the UML (Unified Modeling Language) approach and with the design of the UCD (User Centered Design) method, the programming language used was PHP with MySQL database. The results of this research are in the form of an available online sales system which includes purchases and sales reports with a user center as a reference for developing an e-commerce sales system.
The Case for Data-sharing Policies and FAIR Sharing Principles: Analyzing Journals and Articles of Engineering and Medical Faculty

Numerous government and private funding agencies require data management plans and encourage data sharing.These mandates and levels of encouragement have extended to journal publications and publishers.Yet current literature indicates data sharing is infrequent despite recommendations and mandates.This article examines one hundred and one research data policies and publisher statements to understand data sharing policies, trends and patterns within scholarly journals.More specifically, it addresses the following research questions: (1) What are the data sharing policies of these research journals, (2) Have these policies improved since the Joint Information Systems Committee (JISC) study, and (3) What are current journal articles applicability to Findability, Accessibility, Interoperability and Reusability (FAIR) Sharing Principles.Examining these journals' research data sharing policies and articles applicability to FAIR Sharing principles provides an opportunity for librarians to review and enhance research data management services provided to researchers and research groups.
An incremental nonsmooth optimization algorithm for clustering using L_1 and L_\infty norms

<p style='text-indent:20px;'>An algorithm is developed for solving clustering problems with the similarity measure defined using the <inline-formula><tex-math id="M3">\begin{document}$ L_1 $\end{document}</tex-math></inline-formula> and <inline-formula><tex-math id="M4">\begin{document}$ L_\infty $\end{document}</tex-math></inline-formula> norms. It is based on an incremental approach and applies nonsmooth optimization methods to find cluster centers. Computational results on 12 data sets are reported and the proposed algorithm is compared with the <inline-formula><tex-math id="M5">\begin{document}$ X $\end{document}</tex-math></inline-formula>-means algorithm.
Prosodic asymmetries in nominal vs. verbal phrases in Bantu

Investigations into phonological differences between nouns and verbs focus almost exclusively on the lexical (word) level, showing that underlying contrasts are more numerous and stable ("faithful") on nouns (Smith 1998(Smith , 1999)).This raises the question of whether these (or other) alleged differences in word level phonology generalize to the nominal vs. verbal phrase.The Bantu family provides an ideal testing ground for such an investigation.Based on Bantu, I show that nouns are more likely to undergo modification at the phrase level than verbs, thereby obeying less "faithfulness" to the input than verbs.Nominal phrases also show more distinct outputs and complex idiosyncracies than their verbal counterparts.After establishing that there are distinct asymmetric properties in the phrasal phonology of nominal vs. verbal constituents in Bantu, I raise the question of what causes these asymmetries and whether they are general or pertain only to Bantu and other African languages.
Traditional Game “Bakiak” Assisted Project-Based Learning Model Influences Students’ Social Skills

The problems that underlined this research included: the development of children's social skills was still not optimal, learning models in the classroom were less varied, including in the selection of media and, the interaction of students with other students was still lacking so that learning was still monotonous and less interesting. This study aimed to analyze the effect of the project-based learning model which is assisted with traditional clogs toward the social skills of the fifth-grade elementary school students. The study applied a non-equivalent control group design. Determination of the sample applied random sampling techniques. The population of this study was all students of class V. In this study, the obtained samples were 62 people. Data collection applied observation techniques. The instrument was the observation sheet. The calculation results of average gain in students’ social skills scores were given the treatment of project-based learning models in which learning was assisted with traditional game clogs included 0.295 in the category of very sufficient, while students who were taught conventional learning models had an average score of social skills score of -0.022 , belongs to the less category. Thus, based on these findings, it can be concluded that the project-based learning model assisted by traditional game clogs influences the social skills of fifth grade elementary school students. This model can be used as a choice by teachers to be used as an alternative to improve social skills.
TREND KAJIAN PEMBELAJARAN DARING: SUATU TELAAH PUSTAKA

This study aims to determine research trends related to online learning and the effectiveness of online learning. The study used a qualitative approach with the online literature review method where in collecting data information with documentation techniques, namely looking for data on relevant matters from various online sources such as journals, research results, documents, books, magazines, news. The criteria for the articles and news chosen were a discussion of the online learning process. The results of this study from 40 articles collected showed that the trend of online learning research was dominated by a qualitative approach, followed by quantitative and combined methods using primary and secondary data. As for data collection using interviews, observation, participatory. The data analysis used was descriptive analysis, literature review and experimental. Learning is considered effective before the pandemic by 58.8%, decreasing at the time of the pandemic by 41.2%. Based on the level of early childhood education, primary schools, secondary schools and tertiary institutions are considered effective, but in practice there is still a need for improvement to be better. Keyword : effectiveness; literature review; online learning; trend of online learning.
Verification of Ethereum Smart Contracts: A Model Checking Approach

Ethereum smart contracts based on blockchain technology are powerful and promising applications that provide a global platform for exchanging cryptocurrencies and public services.This technology are garnering a huge impact and is widely adopted in the current times as it can transform the way we transfer and exchange value by passing the need for a middleman and reducing cost.These smart contracts also represent a basis for true ownership of digital assets and a wide range of decentralized applications.Besides this, since Ethereum and its smart contracts are a publicly accessible, unchangeable and distributed platform, they are extremely vulnerable to various forms of attack, with their security becoming a top priority.However, current security-verifying programs tend to provide many technical details which are pretty hard for normal people to understand briefly.To tackle this problem, we designed a process aiming to mitigate these limitations, with our key insight being a combination of semantic structure analysis and symbolic execution on control-flow graphs (CFG for short).This article proposes a new approach for auditing Ethereum smart contracts, applying this technique would benefit both average users without any technical knowledge and security experts as well.
The design and feasibility test of drive-thru market prototype based on Wemos as the learning media of internet of things (IoT) application

This research aims at (1) developing a learning media for the internet of things (IoT) applications in the form of Wemos-based drive-thru market module which is appropriate for Interface Engineering Courses at Electrical Engineering Education, Faculty of Engineering, Universitas Negeri Yogyakarta; and (2) determining the feasibility of the developed learning media. The subject of the research was the 2015 Mechatronics Engineering Education students. The object of the research was the drive-thru market prototype. The research instrument was the questionnaire to obtain data on media feasibility. The proper research results were in the form of (1) the hardware namely the drive-thru market prototype and it's Android application software, (2) the proper function of the prototype and Android applications with the design, (3) the feasibility from the media experts with the percentage of 78% and 83 % respectively that can be categorized as Appropriate, and from the user obtained the percentage of 86.15% with the category of Very Appropriate.
Vodcasting tasks in online L2 classes: investigating the potentials and challenges in distance language learning

Video podcasting technology or 'vodcasting' has proven to be in the forefront of distance education in general and computer assisted language learning in particular. It has flourished by minimising the possible needs of learners' physical presence in second language classes and removing their affective barriers. The purpose of this study was to investigate the major potentials and challenges of vodcasting technology in improving major language skills from EFL learners' perspectives. In order to achieve this, 120 EFL students were selected to receive a long term treatment of collaborative online practice of different skills by using Telegram application. The participants received the video podcasting tasks and were assigned to do the tasks collaboratively. At the end of the treatment, they were interviewed about the experience. The results of the semi-structured interview yielded remarkable information about the capabilities of the experience and the challenges which need to be obviated for future studies.
Joint Semantic Analysis with Document-Level Cross-Task Coherence Rewards

Coreference resolution and semantic role labeling are NLP tasks that capture different aspects of semantics, indicating respectively, which expressions refer to the same entity, and what semantic roles expressions serve in the sentence. However, they are often closely interdependent, and both generally necessitate natural language understanding. Do they form a coherent abstract representation of documents? We present a neural network architecture for joint coreference resolution and semantic role labeling for English, and train graph neural networks to model the 'coherence' of the combined shallow semantic graph. Using the resulting coherence score as a reward for our joint semantic analyzer, we use reinforcement learning to encourage global coherence over the document and between semantic annotations. This leads to improvements on both tasks in multiple datasets from different domains, and across a range of encoders of different expressivity, calling, we believe, for a more holistic approach for semantics in NLP.
A Meta-Analysis of Scholarly Research on Corona virus through Big Data Approach

The purpose of the study is to examine the status of scholarly literature on Corona virus indexed in the big database, the Lens, taking into account, top-cited articles, top contributors, top active country region, most accepted study field and open access status.Relative growth rate (RGR) and Doubling time (Dt) calculation is also a major reflects of the paper.The study analyzes the status of scholarly publications on Corona virus research as indexed by Lens spanning a period from the oldest record until July 15, 2020."Structured Search" was made under "New Scholar Search" using the term "Corona virus" and restrict the search result only for "Journal Article".Results obtained were imported through email (.csv file) for further analysis and visualization using spreadsheet software.The results of the study show that out of total 26628 scholarly outputs 2109 are cited in a patent while 15963 in another scholarly literature."The University of Hong Kong" is the most productive university with 412 scholarly literature, "The United States" as a most contributing country provides 8433 publications, "Journal of Virology" is the most contributing journal with 1012 publications, "Kwok-Yung Yuen" contributed maximum as an individual author and "Elsevier" as a top journal publisher.Among the Lens indexed scholarly publications on Corona virus, 64.04% obtained open accessibility in terms of open access colour while 64.09% under an open-access.No previous study could be identified dealing with such meta-analysis using the Lens database.
Improving Learning Outcomes of 2nd Grade Students Through Video-Based Learning Media

The low student learning outcomes due to the lack of learning media make it difficult for students to understand learning material. This study aimed to develop video-based learning media about the properties of objects around us in theme 2, sub-themes 1 grade 2nd. This study used a Research and Development (R&amp;D) type of research with a 4D development model consisting of four stages, namely define, design, develop, and disseminate. The methods used in collecting data were observation, interviews, and questionnaires. Data were analyzed using descriptive statistics. The development of video media is valid with: (a) the results of the reviews by linguists get very good qualifications, (b) the results of the reviews of instructional media experts get very good qualifications, (c) the results of the reviews of subject matter experts get very good qualifications, (d) the results of the trial individuals get very good qualifications, (e) the results of small group trials get very good qualifications, and (e) the results of field trials get very good qualifications. So, this study showed that the validity of video-based learning media on qualifications is very good and can improve student learning outcomes.
Study on the Evolution Monitoring of Topographic and Hydrological Characteristics of Small Watershed Based on Remote Sensing and GIS

Soil and water conservation is one of the key measures to improve the ecological environment of small watersheds and maintain the healthy life of the region. With the current method used to monitor the evolution of topographic and hydrological characteristics of a small watershed, the edge keeping index of the image and the signal-to-noise ratio of the image are low, the monitoring results are inaccurate, and there are some problems such as low edge keeping ability, poor denoising effect, and low monitoring accuracy. A monitoring method based on remote sensing and GIS for the evolution of topographic and hydrological characteristics of small watersheds is proposed. The hyperspectral data was transformed by the Principal Component Analysis (PCA). Group principal component images, use sparse representation method based on adaptive dictionary and dual-tree complex wavelet transform method to denoise principal component images with a small amount of information were the objectives of the paper; also the use the multi-scale wavelet transform to detect image edge; build a binary model of a pixel, extract vegetation index, and terrain factor based on a binary model of the pixel, and realize terrain and hydrological characteristics of the small watershed. The experimental results show that the proposed method has the high edge-preserving ability, good denoising effect, and high monitoring accuracy.
PENGARUH STRATEGI IMAGE STREAMING DALAM PEMBELAJARAN MENULIS CERPEN SISWA KELAS XI SMA

The Effect of Image Streaming Strategies in Short Story Writing Learning in Class XI High School Students. This study aims to describe the short story writing skills of class XI students of SMA Negeri 3 Takalar Regency before and after using the image streaming strategy and to prove the effect of the image streaming strategy on short story writing skills. This type of research is pre-experimental, with the research design of One Group Pretest-Posttest. The data analysis technique used is descriptive and inferential statistics. The results showed that the short story writing skills of students before using the image streaming strategy were classified as less skilled and after using the image streaming strategy were classified as quite skilled, and the image streaming strategy had an effect on students' short story writing skills.
Emergency responses to teaching, assessment and student support during the COVID-19 pandemic

Under COVID-19 conditions higher education institutions responded rapidly with technological solutions to maintain teaching and assessment for students and to adjust support mechanisms to compensate for the lack of face-to-face interaction with students. Using critical reflection as a research method, this paper captures the experiences of three education developers from different institutions to business as usual in the context of emergency remote teaching. The authors utilise the Substitution, Augmentation, Modification, and Redefinition (SAMR) model of technology integration as a conceptual frame to compare their institutions’ approaches to educational delivery during the pandemic. Additionally, the authors reflect on student diversity, inclusion and equity during the period of emergency remote teaching.
Implementasi Metode Improved K-Means dengan Algoritma Dbscan untuk Pengelompokan Film

The Indonesian film industry continues to experience an increase seen from the number of films that appear in theaters today with a box office increase of 28 percent each year in the past four years. Internet Movie Database (IMDb) is a website that provides information about films around the world, including the people involved in it from actors, directors, writers to makeup artists and soundtracks. In this case the researcher wants to conduct research on the characteristics of the film and the factors that make a film to be included in the IMDb Top 250. The data used in this study uses scraped data from the website. The method used is a non-hierarchical clustering method, namely kmeans and Dbscan. Where the Dbscan algorithm is used to determine the optimum number of clusters then proceed by grouping data based on centroids with k-means algorithm. From the analysis it was found that the factors that could influence a film included in the IMDB Top 250 were duration, number of votes, and films directed by Rajkumar Hirani and the optimal number of clusters using Dbscan algorithm obtained six clusters. With the improved k-means algorithm, the accuracy value for the cluster results is 87.2%.
Optimized and robust implementation of mobile networks confidentiality and integrity functions

In mobile networks, sensitive information is transmitted over the radio link between the Base Station (BS) and the Mobile Station (MS). Therefore, a security mechanism based on confidentiality and integrity functions is designed to protect the anonymity of users’. More precisely, the confidentiality function was standardized by the Third Generation Partnership Project (3GPP) to protect users’ data and the integrity function to protect control (signaling) data. However, both functions are based on the same kernel algorithm. For example, the functions used in the Universal Mobile Telecommunications System (UMTS) network are based on the algorithm, namely the KASUMI block cipher. In this work, we proposed an optimized function that combines the confidentiality and integrity functions in one Running-Block-Cipher and ensures the same functionalities as the basic functions (UMTS F8 and F9 functions). We used an architectural synthesis technique that allows for achieving a significant reduction in the area occupied on the hardware device. The designed architecture was implemented on Xilinx Virtex Field Programmable Gate Arrays (FPGA) technology. The synthesis results after a place-and-route and comparison with previous works show the good performance of the proposed architecture in terms of throughput, consumed energy, and occupied hardware logic resources.
Blockchain and Smart contract’s contributions to Zakat management system

Blockchain is an open distributed database that carries out transactions on an open decentralized ledger. It is a technology that will probably be the source of a huge digital change especially in the financial sector. The application of this technology has started to take its first steps recently and its importance is undeniable in an emerging and expanding field such as Islamic finance. In this context, the purpose of this article is to study the integration of the blockchain and one of its important components, namely the smart contract in the management of the compulsory Islamic charity the zakat. To do this, we have developed a funding model linking all the stakeholders in question and the diversities of blockchain technology. We were thus able to conclude huge benefits and technical contributions in this context which encourages Islamic financial institutions to develop more models likely to support this technology without ignoring the compliance with the Islamic jurisprudence rules.
A Sketch-Based Tool for Authoring and Analyzing Emergent Narratives

We present a real-time tool for authoring and analyzing emergent narratives (EN) built using a possible worlds EN framework. The tool works by reducing the emergent narrative into a discrete tension space (TS), based on possible conflicts between characters, and actions treated as movements in the space. The shape and structure of the TS enables an analysis of higher-level narrative and character properties. Likewise, TS can be constructed through a sketch-based interface, that enables the creation of context-free emergent narrative systems.
CaM-Gen: Causally Aware Metric-Guided Text Generation

Content is created for a well-defined purpose, often described by a metric or signal represented in the form of structured information.The relationship between the goal (metrics) of target content and the content itself is nontrivial.While large-scale language models show promising text generation capabilities, guiding the generated text with external metrics is challenging.These metrics and content tend to have inherent relationships and not all of them may be of consequence.We introduce CaM-Gen: Causally aware Generative Networks guided by user-defined target metrics incorporating the causal relationships between the metric and content features.We leverage causal inference techniques to identify causally significant aspects of a text that lead to the target metric and then explicitly guide generative models towards these by a feedback mechanism.We propose this mechanism for variational autoencoder and Transformer-based generative models.The proposed models beat baselines in terms of the target metric control while maintaining fluency and language quality of the generated text.To the best of our knowledge, this is one of the early attempts at controlled generation incorporating a metric guide using causal inference.