Reviewerly/exHarmony huggingface dataset:
ANALISIS KANDUNGAN KAJIAN TEKNOLOGI DALAM PENDIDIKAN BAHASA MELALUI ARTIKEL-ARTIKEL TERPILIH

In line with the advancement of technology, educators should not use the old approach to teaching students. This is because, by the 21st-century education is increasingly emphasizing the use of technology to produce innovative, brilliant and competitive generations. In the past, the use of computer technology was more focused on science and technology, but now all fields of social science such as language field have taken advantage of its use. Therefore, the language teaching and learning process should also evolve in line with the advancement of information and communication technology. This paper provides the content analysis of the use of technology in language education published in online journals from the Academic Search Premier @EBSCOhost databases. The study analysed 21 technology-related articles in language education from 2017 to 2018. Findings from content analysis found that the majority of articles on technology in language education were using experimental approaches. The study also found that most studies focus on English as a second language or foreign language. In addition, students are more often used as samples than teachers. The use of technology is found to have a positive impact on language learning, but some obstacles need to be addressed. The findings of this study can be used as a reference by researchers who study technology related to language education. This article also provides recommendations for future research on technology in language education.
Symbolic Approach for Word-Level Script Classification in Video Frames

In recent years, addiction towards internet and digital world has made difficult for people to understand multilingual scripts in various circumstances. In this work, we proposed a model for classification of South Indian multilingual word script extracted from video frames namely, Kannada, Tamil, Telugu, Malayalam and English. Firstly, we extracted Local Binary Pattern (LBP), Histogram of Oriented Gradients (HoG) and Gradient Local Auto-Correlation (GLAC) features for each multilingual word script. The multilingual word script consists of five classes and each class of images are clustered by implementing k-means clustering technique. Further, we proposed symbolic representation to capture intra-class variations between each clusters and symbolic classifier is employed for classification. For experimentation, we have extracted 600 word images from each script and total of 3000 word images from video frames. Further, we have made comparative study to show the robustness of symbolic representation and classifier with SVM and ANN classifiers.
Charity Token - improving trust on charity organizations through Blockchain technology

Purpose of the article: The main intention of this project is using the characteristics of blockchain technology to recover the trust on charity projects and offer full transparency to the use of charity funds. Methodology/methods: This research will be conducted with qualitative research methods including literature review and use cases. The implementation of the project will require some IT methods. Findings: The value of the non-profit sector is above $1,3 trillion. However, there is a decrease on spending in general regarding the donation sector. This decrease has mainly to do with a lack of trust on the managing organizations. Donors doubt that the donated money reaches the intended project and due to that, there has been a reduction on the general amount of money being donated.Blockchain offers a great solution to this problem due to its transparency and possibility to track transactions. The charity token project aims to develop a platform, where each project needing donation can easily create a verified token with its name on it and offer donors the possibility to exactly know which project they are donating to and track the usage of the donation and the development of the project Conclusions The implementation of this idea requires the involvement of different actors such as NGOs, financial institutions, charity organizations and maybe the state offering some regulation to the issue. Financial institutions will make it possible to exchange money to tokens when a donation takes place and to accept these tokens and exchange them into a fiat currency at the time they reach to the intended project. NGOs have already projects which are looking for donations but in the most cases the NGO receives the money and then transfers it to the project. Unfortunately, there is a huge lack of transparency in this process and as a consequence the amount of donations is decreasing. This can be avoided if the NGOs promote the project-exclusive token together with the project asking for donations. This will ensure the donors that their money can’t be mismanaged by the NGO und will reach the intended project.The Charity token main platform will check every project in cooperation with trusted partners like Transparency International before allowing them to issue a certified project-specific token. In this way every donor will be sure that they are not donating to a scam but to a verified project. Keywords:  charity, blockchain, trust, NGOs, donations, transparency, distributed ledger
Effect of downsampling on the quality and resolution of super-resolved images

More and more municipalities in the Philippines are installing CCTV cameras in their streets. But if the cameras are of low resolution or the cars are too far away then identity marks of the car cannot be read. If a video of the car was captured, super-resolution techniques can be applied to reconstruct a high-resolution image from the low-resolution video. In this paper, we examine the effect of downsampling on the quality and resolution of a super-resolved image by measuring their structural similarity index and modulation transfer function at varying resize factors. We simulated a CCTV footage by capturing movies of a remote controlled toy car with a signage attached to its side. To simulate low resolution, we resized video frames from a factor of 0.1 to 1 of their original dimensions. It was observed that text is recognizable at super-resolved images having SSIM index values of greater than or equal to 0.5 which corresponds to a scale factor of 0.41 (in SSIM = 0.5). At this scale factor, the resolution limit is at 7 pixels per line pair.
Research on Application of Missile Blockchain Based on Nation Secret Algorithm

Abstract Missile data has the characteristics of multiple data items, large data volume and high data value, which puts forward higher requirements for data storage security. The application of block chain technology in missile business data storage can realize the safe, reliable and decentralized storage of data. The SM3 algorithm is a Hash function that supports the data structure and detects whether the data is tampered with in the blockchain. The SM3 algorithm is applied to the missile business blockchain to realize the localization of encryption, and the operation of SM3 algorithm is optimized under the condition that the missile business data contains a large number of documents, tables and pictures. Finally, the Go language was used for testing, and the results showed that the operation speed of SM3 algorithm could be improved by about 30% through optimization, and the optimization effect was obvious.
Extension of longitudinal measuring range of a confocal surface profilometer using a gradient-intensity probe beam

A confocal surface profilometer with a long vertical range was developed by using a gradient-intensity probe beam. In conventional confocal microscopy, vertical scanning of a tested surface by either stage height movement or the shifting of objective focus is time-consuming, thus making unacceptable measurement efficiency for in situ inspection. To overcome this, in this research, a quasi-Bessel beams (QBB) with the properties of narrow lateral spot and gradient-intensity axial distribution is adopted as a probe beam to generate an accurate intensity-to-height conversion for 3-D profile measurement. The influences of the incident Gaussian beam and the real axicon lens with an oblate-tip shape on the axial probe beam are calculated and analyzed. By switching the axicon lenses with different base angles, the measurable height of the surface profilometer can be ranged from a few millimeters to several hundred millimeters. According to the measured results, it was found that by using the axicon lens with a base angle of 20°, the measurable height reached at least 2 mm. By integrating a high-speed acquisition unit, the proposed profilometer can further increase the measurement efficiency, especially fitting in situ automatic optical inspection (AOI).
FastV2C-HandNet: Fast Voxel to Coordinate Hand Pose Estimation with 3D Convolutional Neural Networks

Lekhwani, Rohan Singh, BhupendraHand pose estimation from monocular depth images has been an important and challenging problem in the Computer Vision community. In this paper, we present a novel approach to estimate 3D hand joint locations from 2D depth images. Unlike most of the previous methods, our model using a voxel to coordinate(V2C) approach captures the 3D spatial information from a depth image using 3D CNNs thereby giving it a greater understanding of the input. We voxelize the input depth map to capture the 3D features of the input and perform 3D data augmentations to make our network robust to real-world scenarios. Our network is trained in an end-to-end manner which mitigates time and space complexity significantly when compared to other methods. Through comprehensive experiments, it is shown that our model outperforms state-of-the-art methods with respect to the time it takes to train and predict 3D hand joint locations. This makes our method more suitable for real-world hand pose estimation.
Discovering test statistics using genetic programming

We describe a genetic programming-based system for the automated discovery of new test statistics. Specifically, our system was able to discover test statistics as powerful as the t-test for comparing sample means from two distributions with equal variances [1].
Social Scene Understanding: Group Activity Parsing, Human-Robot Interactions, and Perception of Animacy

Author(s): Shu, Tianmin | Advisor(s): Zhu, Song-Chun | Abstract: This dissertation proposes new computational frameworks to address three core challenges for social scene understanding -- group activity parsing, human-robot interactions, and perception of animacy. The goal of these frameworks is to represent the underlying structure of social scenes and to unify the perception and concept learning of both physics and social behaviors. For this, we first develop a joint parsing of group activities that yields a hierarchical representations of groups, events, and human roles, which provides a holistic view of a social scene. In a follow up work, the idea of joint parsing is also shown to be effective for boosting the performance of deep neural networks on group activity recognition. Second, we formulate social affordances as a hierarchical representation of human interactions, which can be learned from a handful of RGB-D videos of human interactions. Based on the symbolic plans derived from the learned knowledge, we further design a real-time motion inference to enable motion transfer from human interactions to human-robot interactions, which generalizes well in unseen social scenarios. Finally, we study human perception of animacy by designing new approaches to generate Heider-Simmel animations and by developing new computational models to account for human physical and social perception. Particularly, we propose a unified framework for modeling physics and social behaviors through i) a joint physical-social simulation engine, ii) a joint physical and social concept learning as the pursuit of generalized coordinates and their potential energy functions, and iii) a unified psychological space that integrates intuitive physics and intuitive psychology.
A System for Discovery of Knowledge in Data Repository Education

Studies on scientific production date have received attention from Researchers in various fields to gain insight into the evolution of research in general.Such studies enable the analysis of scientific production for various purposes and one of the challenges in this type of analysis lies in the diversity of repositories containing data in different formats and structures.Currently, Bibliometric and scientometric Analyzes are the Characterized the main scientific analysis techniques on the production of a set of Researchers.These Analyzes aim to carry out the measurement of scientific communication, including the study of sciences to identify its structure, evolution and connections.The proposal of this project is to Develop an information system to perform scientificometric Analyzes of sets of Individuals, having as a source of data repositories of scientific publications.As a case study will be Analyzed the Brazilian Researchers who have acted in the Interdisciplinary area in Brazil.These Analyzes intend to present an overview of the area under study in Brazil, having the main source of data for the Analyzes, date of scientific publications of this set, extracted from its curricula of the Lattes Platform.Therefore, it will be possible to identify the profile of These Researchers, where They are acting, how the collaboration between Them Occurs, and Also, the qualitative analysis of Their research, Thus enabling the accomplishment of Analyzes comparative with the different areas of knowledge.After validation with the case study carried out Several other sets of Individuals Can Be Analyzed.
Correction: Efficient oxygen evolution on mesoporous IrO<sub>x</sub> nanosheets

Correction for ‘Efficient oxygen evolution on mesoporous IrO<sub>x</sub> nanosheets’ by Bo Jiang <italic>et al., Catal. Sci. Technol.</italic>, 2019, DOI: 10.1039/c9cy00302a.
Perancangan Sistem Informasi Akuntansi Persediaan Barang Dagang Pada Toserba Selamat Menggunakan Php Dan Mysql

The purpose of this research is to find out the accounting information system of merchandise inventory used by Toserba Selamat. Toserba Selamat itself stands in retail. Retail is an activity involved in selling goods or services directly to consumers for personal use. This research method uses descriptive by looking for research related theories about the system of accounting information on merchandise inventory. Data collection used is observation and interview. The type of data used is quantitative data. The results of this study are expected to be able to find out information about merchandise inventory accounting information systems. The design of the merchandise inventory accounting information system uses the method of developing the Dynamic System Development Method system with 3 main stages (before the project, project life cycle and after the project) and 5 sub stages (feasibility studies, business studies, looping models, repetition of design and manufacture and application). The discussion of design research on inventory inventory accounting information systems is expected to facilitate convenience stores in making inventory reports and financial reports.
Real-time Raytracing and Screen-space Ambient Occlusion

This paper investigates the advances in real-time ambient occlusion (AO). Topics discussed are state-of-the-art screen-space techniques and raytraced ambient occlusion. Methods compared are our scr ...
Predicting Loss of Communication Between Radio Enabled Devices Using Deep Recurrent Neural Networks

This thesis investigates the effectiveness of applying recurrent neural networks (RNN) to detect communication errors between radio devices, also known as supervision violations, on imbalanced data. The task is to classify whether a supervision violation is to occur within seven days. The available data is in the form of radio packets, which are being re-sampled and pre-processed such that they can be interpreted by RNNs. The RNNs are trained as both classifiers and generators to enable detection of supervision violations. Using RNNs, an extensive evaluation is made into different pre-processing methods, using multiple test sets and network architectures, applying average precision as metric and precision-recall curves as the main evaluation technique. The results show that it is possible to achieve an average precision of 0.75, and that experimentation with pre-processing parameters along with multiple testsets are needed to ensure a generalised model.
Implementation and adoption plan "23 Things Revisited: Field Guides to Research data Management" Version 07/03/2019

Implementation and adoption plan “23 Things Revisited: Field Guides to Research data Management” is a project funded by RDA Europe following its Adoption Open Call in 2019. Research support staff, such as data stewards, IT support staff, librarians or policy officers, often have different levels of understanding of Research Data Management (RDM). However, they need to collaborate closely to offer state-of-the-art support for researchers wishing to do responsible RDM. The 23 Things: Libraries for Research Data resource that has been developed by the RDA's Libraries for Research Data Interest Group can act as a shared reference tool that enhances mutual understanding and improves collaboration in the Netherlands. It can also be used for quick reference and as a guideline for training. We propose to update and adjust the 23 Things to the above-mentioned audiences and stimulate nationwide adoption. The implementation plan, together with the workplan and Gantt chart describe the goals, activities, stakeholders involved in the adoption, implementation and dissemination of the '23 things' in The Netherlands.
The missing link? Using LinkedIn to market your professional programs

Dominated by career‐oriented professionals and industry thought leaders, LinkedIn is often untapped as a platform to reach prospective students. What once seemed like only a place to host your résumé and connect with colleagues has become an incredibly active space for conversation, career information, and learning.
Solving <i>legends of the three kingdoms</i> based on hierarchical macro strategy model

Legends of the Three Kingdoms is a Chinese card game based on the novel Romance of the Three Kingdoms. As a turn-based strategy game, Legends of the Three Kingdoms is an imperfect information game where agents interact with one another to deduce the unknown information. The most famous solution for an imperfect information game is to find a Nash equilibrium where no agent can benefit from changing strategies. Tencent AI Lab has recently developed a novel learning-based Hierarchical Macro Strategy model for AI to master MOBA games, a sub-genre of RTS games. In this paper, we adopt this method on our AI to solve Legends of the Three Kingdoms in a shrunken size of 4 players.
Mind the Gap… A Case Study about Cross-functional Collaboration between Teams in Game Development

Game development today is a complex process that differs from traditional software development by presenting unique challenges stemming from a multidisciplinary structured process, including teams ...
LEXICAL COHESION IN NEWS ARTICLE ON THE JAKARTA POST ENTITLED “WHY FULL DAY SCHOOL WILL NOT WORK IN INDONESIA?”

The purpose of this study is to investigate what types and what is mostly found of lexical cohesion in the news article. Written texts are different from spoken interaction. To make the readers know what the writers mean, the writers should compose a well formed of the text. Cohesion is an aspect of a text, which entails that the letter forms a unified whole, rather than unrelated sentences. Cohesion plays a special role in the creation of text. There are two main types of cohesion there are grammatical cohesion and lexical cohesion. Grammatical cohesion consist of reference, ellipsis, substitution and conjunction, whereas lexical cohesion has two aspects, they are reiteration and collocation. Lexical cohesion refers to the way related words are chosen to link elements of a text. This study used qualitative research as the research method. Based on the result of this study, it can be concluded that there are six types of lexical cohesion and the types of lexical cohesion which is mostly used by the writer is repetition but this article is lack of antonym. And the use of lexical cohesion in writing a text can deliver the meaning of whole text itself for the readers easily and clearly.
Media Literation Model for Development of Tolerance and Multicultural Attitudes in The Students of Universitas Negeri Semarang

Indonesia is a multicultural country that consists of various races, ethnicities, customs, cultures, ethnicities, languages, and gender that are different from one another. Multicultural communities prioritize differences in equality. This condition is reinforced bytheexistenceofslogans“Bhinekatunggalika”.Becauseofthisdiversityisoursocial capital for life with respects and tolerance each other also acknowledges equality. However, the phenomenon of intolerance issues which latterly emerged in Indonesia, has created an atmosphere of injury to diversity. The problem is not only triggered by internal friction between the elements of the nation, but also is a part of the reﬂection of global conditions in the contemporary era as if no longer geographically isolated because of the ease of access to information through the sophistication of its technology. There is an ideological network that unites to develop participation in variouscountriesintheworld.ThisresearchwasconductedonstudentsofUniversitas Negeri Semarang (UNNES). If students can build tolerance and multicultural values, it is expected to minimize the incidence of intolerance in the future. The objectives in this study are: 1) Knowing the implementation of the media literacy movement at Universitas Negeri Semarang. 2) Develop a media literacy model and the strategy for implementingmedialiteracymodelsforthedevelopmentofmulticulturaltoleranceand values among students. Outcomes of research: 1) Making articles on scientiﬁc journal publications. 2) Arranging Textbooks. The research method uses qualitative research and is a Research and Development.
Seleksi Arah Sudut Komputasi Dan Fitur Glcm Pada Kstraksi Citra Kayu Jati, Mahoni, Mindi, Dan Sengon

Research on feature extraction of wood texture with features and angle direction is rarely done, especially in teak, mahogany, mindi, and albasia. This research is needed to select more efficient and effective features and angle directions to identify wood species. The features tested were Angular Second Moment (ASM), Contrast, IDM / Homogenity, Entropy, Correlation and the direction of the computational 0, 45, 90, and 135 degrees of gray level co-occurrence matrix (GLCM). The experimental results show that the selected angles are 0, 45, and 90 degrees and features are IDM and Entropy. Kata kunci : gray level co-occurrence matrix (GLCM), features extraction, wood classification
“Big Screen Is Watching Me?”: A Study on the Attractiveness and Reading Efficiency of a Rotating Screen

Interactive public displays are often deemed to be more effective and engaging in delivering information to people. This paper presents three studies on directive displays − a type of display that rotates in response to a passerby’s movement direction and their effectiveness in drawing the attention of a single nearby passerby. The studies build progressively on each other, using three iterations of rotating directive displays, with evaluations of their performance compared with a static screen. Our results demonstrate a rotating screen that adapts to a passerby’s movement in real-time is more effective in both attracting passerby attention and improving screen reading efficiency. These results may provide a reference for future designs of public displays.