Reviewerly/exHarmony huggingface dataset:
Analysis Student's Comprehension in Reading Narrative Text on English Learning at Junior High School

Indonesia become is one of the nations which have characteristics almost of community not like reading activity. There is a number of advantages that can be picked when applied reading habits in life. Therefore, researchers are very interested in using research topics related to students' comprehension of reading skills. This study examines more deeply the factors that cause students to have difficulty in understanding the narrative text in English lessons. This type of research is qualitative research that involves descriptive information while the use of the method is more than one such as observation, interview, and documentation. The results of this study indicate that students have difficulty in reading narrative texts because of internal and external factors.
Pengujian Perangkat Lunak untuk Penulisan Hasil Belajar pada Pelajar SMK pada Pelaksanaan Kurikulum 2013

This review meant to portray execution of learning results report composing of professional understudies on Educational plan 2013 utilizing the web-based report composing programming. This examination was elucidating exploratory review, which was essential for the exploration improvement by utilizing Sharma's model. Information gathered by perception and poll. Members in this review included 9 both public and private professional school in Exceptional Locale, including the VPs of educational plan, study hall educators, and data innovation experts from school members. The outcomes look that 56% of respondents expressed that the created programming has great quality and the leftover 44% of source person expressed that the product created has mid-range quality. A few respondents ideas for enhancements to the product, to be specific (1) the requirement for synchronization of the framework with the freshest unofficial laws (2) improvement of the culmination of data inside the framework; (3) the requirement for participation with the branch of instruction / other related organizations; (4) impediment the power of the understudies. In view of these ideas have been led further developing the framework with the goal that the product was prepared for using to help professional instructors in Indonesia to set up the learning results writes about Education plan program 2013.
Can I Get There? Can I Play? Can I Stay? Creating an Inclusive Playspace Guide in Australia

Playspaces bring children and adults together for fun and social interaction but are rarely designed for the inclusion of all community members. In Australia, local government authorities (councils) are responsible for parks and playspaces. The New South Wales state government launched their inclusive playspaces policy in 2017. A guideline document was proposed but a guideline does not guarantee implementation. Consequently, an inclusive design process for developing the guide became the strategy. The task was to develop a guide that explained the concepts of inclusion and universal design within the playspace context. The project took an iterative and collaborative approach to the design of the guide. Intended users were those involved in creating playspaces, not playspace users per se. The participatory governance structure involved three levels of collaboration: a small steering group of experts, a larger group with key stakeholders, and a wider group of stakeholders and interested persons. This collegial and participative process consisted of a series of meetings and workshops which fostered learning and ideation for all participants. Through this process three underpinning concepts emerged: Can I get there? Can I play? Can I stay? The process educated and informed stakeholders, encouraged participants to contribute to the outcomes and provided community-led guidance for those contracted to design the guideline. The result was an inclusive playspace guide that recognized the design guidance required by council personnel in the context of universal design. The process and governance structure provides a good working model to build on. The success of the guideline was recognized with a national award from the Institute of Landscape Architects for Community Contribution. The purpose of this paper is not to comment on or evaluate the outcome of the guidelines. Rather, it is to document the inclusive and participatory governance structure and iterative process from a professional participant perspective.
Analysis of Lexical and Grammatical Errors of Korean Teachers in Russia and CIS Regions

This study aims to analyze lexical and grammatical errors found in 25 Korean writing materials of Korean teachers in Russia and CIS regions. Error analysis criteria are reconstructed with reference to the the error level presented by ‘National Institute of Korean Language Republic of Korea’ and long writing evaluation items of TOPIK. As a result of the analysis, there were many errors in vocabulary, inflection(declension), inflection (conjugation), natural sentence construction, spelling, spacing. These results are similar to those of a study on overseas Korean learners in the region. Furthermore, this study examined error characteristics depending on whether they are Koryo-Saram or not and Korean proficiency level. The Koryo-Saram teachers showed commonalities and differences from the local teachers in vocabulary errors and inflection(declension) errors. Inflection(conjugation) errors and natural sentence construction errors were more common in the advanced class than in the intermediate class. And many spelling and spacing errors were found regardless of status and level. Finally, this study suggested the direction of how Korean teachers in Russia and CIS regions can improve their vocabulary and grammatical abilities. (Hankuk University of Foreign Studies)
Fast Gated Recurrent Network for Speech Synthesis

The recurrent neural network (RNN) has been used in audio and speech processing, such as language translation and speech recognition. Although RNN-based architecture can be applied to speech synthesis, the long computing time is still the primary concern. This research proposes a fast gated recurrent neural network, a fast RNN-based architecture, for speech synthesis based on the minimal gated unit (MGU). Our architecture removes the unit state history from some equations in MGU. Our MGU-based architecture is about twice faster, with equally good sound quality than the other MGU-based architectures.
Risk Mitigation Decisions

It is highly complex for organizations to navigate the emerging cybersecurity landscape due to the lack of available decision-support tools. In this chapter, we present a systematic approach to supply chain risk mitigating decision-making in IoT systems and networks. The framework discovers relationships between suppliers and service providers across the different interconnected devices and provides an analysis of the associated cyber risks including the weakest and most vulnerable links. The decision-support engine allows for planning new system deployments from a supply chain viewpoint by recommending an optimized selection of suppliers.
KENYA: Voter Bribes

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 59, Issue 7 p. 23942A-23942C Policy and Practice KENYA: Voter Bribes First published: 05 September 2022 https://doi.org/10.1111/j.1467-6346.2022.10700.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL No abstract is available for this article. Volume59, Issue7September 2022Pages 23942A-23942C RelatedInformation
Flooding Events

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 59, Issue 7 p. 23941A-23941C Policy and Practice Flooding Events First published: 05 September 2022 https://doi.org/10.1111/j.1467-6346.2022.10699.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL No abstract is available for this article. Volume59, Issue7September 2022Pages 23941A-23941C RelatedInformation
Transformaciones educativas: EDUvsCOVID19 como iniciativa de aprendizaje abierto para la práctica docente

The moment in which the society and educational modalities are situated, implies that the teachers resort to capacitation that allow innovate the knowledge that they already have and the apprenticeship that they impart to their students. This work pretends to contribute about the impact of the educational project EDUvsCOVID19 as an initiative that offers the open and free learning to teachers of educational centers through webinars that are provide for teachers, researchers, and consultants of different parts of the world that have a wide experience in the develop of the technologies within the education. The study had a mixed approach descriptive-exploratory scope, 289 teachers were surveyed, a focus group with teachers who participated of the Ecuador and Peru initiative and interviews with experts to know their different perceptions about this initiative. This is how they managed to identify the categories of knowledge and self-training, reduction of gaps, teacher practice, and transformation of schools. As results it was confirmed that open training spaces contribute to innovate or transform the teacher practices within the schools, as they contribute to the teachers’ knowledge development.
Using SGX for Meta-Transactions Support in Ethereum DApps

Decentralized applications (DApps) gained traction in the context of the blockchain technology. Ethereum is currently the public blockchain that backs the largest amount of the existing DApps. Onboarding new users to Ethereum DApps is a notoriously hard issue to solve. This is mainly caused by lack of cryptocurrency ownership, needed for transaction fees. Several meta-transaction patterns emerged for decoupling users from paying these fees. However, such solutions are mostly offered via off-chain, often paid relayer services and do not fully address the security issues present in the meta-transaction path. In this paper, we introduce a new meta-transaction architecture that makes use of the Intel Software Guard Extensions (SGX). Unlike other solutions, our approach would offer the possibility to deploy a fee-free Ethereum DApp on a web server that can directly relay meta-transactions to the Ethereum network while having essential security guarantees integrated by design.
Elucidating the role of emotion in privacy-concerns: A text-Convolutional Neural Network (Text-CNN)-based tweets analysis of contact tracing apps

The extant contact tracing privacy literature is yet to explore the significance of user emotions in privacy-related decision-making such as whether to use such potentially privacy-invasive apps. Using social media analytics, the present study examines users’ privacy-related emotions stimulated by privacy-related aspects of contact tracing apps. A text-Convolutional Neural Network (Text-CNN)-based emotion analysis of tweets on the Indian contact tracing app Aarogya Setu and its Singaporean counterpart TraceTogether conducted in the paper reveals that users expressed negative privacy-related emotions towards these apps indicating high levels of perceived privacy risks and the perceived lack of privacy protection. For TraceTogether, users have also exhibited positive emotions to appreciate the steps taken by the government to protect their privacy. Based on these findings, the government/data controllers can devise strategies to assuage users’ negative emotions and promote positive emotions to encourage the adoption of contact tracing apps. This work incorporates privacy related emotions as key informants about user privacy concerns within the Privacy Calculus Theory. By relying on candid user opinions available through rich but inexpensive user-generated content, the research provides a quick, reliable, and cost-effective approach to study potential app users’ emotions to gain insights into privacy concerns related to any e-governance platform.
$$ST^2PE$$: Spatial and Temporal Transformer for Pose Estimation

Spatial and temporal information and multi-view mutual promotion are two keys to solve depth uncertainty for 2D-to-3D Human pose estimation. However, each key requires a huge model to handle, so previous methods have to choose one of them to solve depth uncertainty. Thanks to transformer’s powerful long-term relationship modeling capability and latent adaptation of one view to another, we can adopt both with an acceptable number of model parameters. To the best of our knowledge, we are the first to propose a multi-view multi-frame method for 2D-to-3D human pose estimation, called $$ST^2PE$$ . The proposed method is combined with a Single-view Spatial and Temporal Transformer ( $$S{-}\textrm{ST}^2$$ ) and a Multiple Cross-view Transformer-based Transmission ( $$M{-}\textrm{CT}^2$$ ) module. Inspired by the structure of the Transformer in Transformer, the single-view spatial and temporal transformer has two nested transformer modules. The internal one extracts spatial information between joints, while the external one extracts temporal information between frames. The cross-view transformer-based transmission module extends the original encoder-decoder setting of Transformer into a multi-view setting. Experiments on three mainstream datasets (Human3.6M, HumanEva, MPI-INF-3DHP), demonstrate that $$ST^2PE$$ achieves state-of-the-art performance among all the 2D-to-3D methods.
On Pdf/A Conformance and Font Usage in Pdf Documents Provided by Public Sector Organizations

The overarching purpose of this study is to assess the PDF/A conformance and font usage in PDF files collected from various sources provided by Swedish public sector organizations (PSOs). This paper presents a categorization of the PDF files’ properties and their font usage including into which licensing category those fonts fit best. This font usage study is motivated by the PDF/A1 standard’s statement that ‘only fonts that are legally embeddable in a file for unlimited, universal rendering shall be used.’ The proportion of files that claim or even succeed at conforming to any PDF/A standard greatly varies among PDF sets. We find that the most popular fonts by number of files where used are proprietary fonts, for example ‘Times New Roman’ or ‘Arial’. The most popular way to make use of fonts in PDF files is by embedding a subset of the font data, i.e. including only glyphs for used symbols. Findings from analysis of the embedded font data shows that the fonts’ metadata in the vast majority of cases allows embedding of said data. However, for some fonts expected to be ‘always available’, for example ‘Times New Roman’ or ‘Arial’, a considerable proportion of PDF files do not include any font data but put the onus of locating this data on the PDF reader which is problematic for long-term archival.
Knowledge-Aware Self-supervised Graph Representation Learning for Recommendation

Representation learning improves the accuracy of recommendation through mining high-order neighbors information on the user-item graph, but still suffers the data sparsity and cold start problems. Although knowledge-aware representation learning can alleviate the above problems to some certain extent by using knowledge graphs to capture rich addition information of the items, this method relies heavily on a large amount of training data and annotations in a supervised learning manner. Self-supervised learning has been proved to be a good substitute because of its ability to avoid the cost of annotating large-scale datasets. In this paper, we explore the self-supervised contrastive learning on the hybrid structure of the knowledge graph and user-item graph to solve above problems. We design a Knowledge-aware Self-supervised Graph Contrastive Learning model called KSGL. The core idea is to learn the representation of users and items effectively by pulling the augmented versions of the same users/items close to each other while pushing away different ones. Specifically, KSGL first performs data enhancement on the input hybrid graph, generates multiple views of the target node, and then refines the node embedding in each view through Graph Convolutional Networks (GCN), and finally updates the model by contrast loss. We conduct experiments on three benchmark datasets to demonstrate the effectiveness of KSGL and the results of the experiment show that our model can not only improve recommendation accuracy but also obtain robustness against interactive noise.
Robust message authentication in the context of quantum key distribution

Universal hashing-based message authentication code (MAC) is used as the de facto method to achieve information-theoretically secure authentication in quantum key distribution. We present a critical look at the most widely used type, namely Wegman-Carter MAC based on polynomial hashing and analyse its robustness against physical attacks exploiting side information. In particular, we mount a classical DPA attack on the hash part of the Wegman-Carter MAC which leads to a possible intercept-and-resend attack on the BB84-like QKD protocols. We illustrate this case with polynomial-evaluation MACs as their variants are used in commercial QKD systems. We show that our attack methodology is much simpler compared to that of Belaid et al. at ASIACRYPT 2014. Finally, we present an algebraic countermeasure so that the resulting MAC is not susceptible to the identified attack.
Intricacies in image steganography and innovative directions

With the advancement in digital communication and data sets getting huge due to computerisation of data gathering worldwide, the need for data security in transmission also increases. Cryptography and steganography are well known methods available to provide security where the former use techniques that control information in order to cipher or hide their presence and the latter concentrates on data concealment. Steganography is the practice of masking data especially multimedia data within another data. Visual contents get more importance from people compared to audio contents and moreover visual content file is huge when compared to audio file thereby helping increase robustness of the hiding algorithms. In this paper, we consider three domains in which the image steganography algorithms are proposed along with the experimentation results on USC-SIPI image database which prove the betterment of the algorithms as compared with the traditional algorithms. We propose to use rule based LSB substitution method in spatial domain, XOR based hiding in frequency domain and data encryption standard based embedding in wavelet domain. We find that the proposed algorithms have a better PSNR value averaging close to 53 after embedding the secret data, while the existing algorithms has values of around 50.
Improving Fault Seal Analysis through Innovative Fault Interpretation

Summary Fault seal analyses require valid fault interpretations, and errors in fault interpretation are often attributed to be the cause of unexpected subsurface results. To improve fault interpretation we propose a method that begins with a conservative deep learning technique that provides an incomplete but high confidence fault highlighting visualization. The fault interpretation is completed by combining this initial visualization with a technique that highlights laterally-persistent geophysical anomalies, which include subtle faults near the limit of the resolution of the seismic data. This technique helps to reduce fault interpretation errors, and to quantify the ambiguity of interpreted faults, which can be translated into an uncertainty range in a fault seal analysis.
Institutes for Historical Editing (NARA)

Federal Grants & ContractsVolume 46, Issue 19 p. 1-1 Grants alerts Institutes for Historical Editing (NARA) First published: 06 September 2022 https://doi.org/10.1002/fgc.32557Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume46, Issue198 September 2022Pages 1-1 RelatedInformation
Engaging Students in Oral History in the Archival Science Study Program, Vocational College, Universitas Gadjah Mada

The Archival Science Study Program, run by the Vocational College at Universitas Gadjah Mada, has produced numerous oral history archives since 1997 and has contributed diverse themes through the Oral History Program course in practical subjects. These oral history archives can be used by the public, through information technology, to facilitate knowledge transfer and as oral evidence using the ARISAN (Arsip Sejarah Lisan) mobile application. This study aims to describe the implementation of the oral history archives dissemination program, as one of the models used for oral evidence, as well as for recording the oral history published in the community.
Acute Effects Of Virtual Reality Exercise On Young Adults’ Blood Pressure And Feelings

PURPOSE: This study examined the acute effects of virtual reality (VR) on young adults’ blood pressure and emotions. Specifically, we examined the effects of three types of VR exercises (one immersive VR and two non-immersive VR exercises) on young adults’ blood pressure and emotion (i.e., feelings) as compared to a traditional exercise biking session. METHODS: A total of 36 college students ( females; Mage = 23.6) participated in this study and completed four separate 12-minute exercise sessions: 1) immersive VR biking on VirZoom VR bike using PlayStation 4; 2) non-immersive VR biking on Gamercize bike using Xbox 360; 3) non-immersive VR biking on Game Rider EZ Gaming Bike; and 4) traditional biking on Spirit Fitness XBU55. Their blood pressures (systolic and diastolic) were measured before and after each session. Exercise-induced feelings were assessed via the established survey after each session. Participants’ previous experience with VR was used as the covariate in the ANOVA with repeated measures. RESULTS: Overall, significant main differences were seen between biking sessions for systolic blood pressures [F (2, 29) = 3.04, p = 0.02, η2 = 0.38)] and feelings [F (3, 32) = 7.74, p < 0.01, η2 = 42]. Post-hoc LSD comparisons suggested that immersive VR (21.31 ± 8.04) and traditional biking (24.02 ± 9.11) had significantly greater increased systolic blood pressures compared to two non-immersive VR exercises (16.00 ± 8.83 vs. 14.92 ± 10.41, p < 0.05, respectively). In addition, immersive VR (1.86 ± 0.72 vs, p < 0.01) had significantly greater increased feelings than the two non-immersive VR (2.61 ± 1.63 vs. 2.58 ± 1.46), whereas these two non-immersive VR exercises had significantly greater increased feelings compared to traditional biking (1.78 ± 2.06, p < 0.05), respectively. CONCLUSION: The findings suggest immersive VR-based exercise bike could lead to higher exercise intensity and feelings among healthy young adults in comparison with non-immersive VR bike exercises. It also yielded higher feelings than traditional biking. Thus, immersive VR-based exercise can be a fun and physically active health promotion approach for young adults.