Reviewerly/exHarmony huggingface dataset:
The Workers’ Attitudes in Using Tourism English in Ubud

This research aims at describing the attitude of Tourism English usage shown by the tourism workers in their work seen from three components of attitude namely, (1) cognitive, (2) affective and (3) conative. Futhermore, the factors influencing the use of Tourism English include (1) situation and background, (2) participants in the interaction, (3) topic of conversation and the last is (4) interaction function.The subjects in this study are the tourism workers in Ubud area with the total of respondents 25 people. The data were collected using questionnaire, then descriptively analyzed and statistic patterns in frequency and percentage form (tabulation) were calculated. The research findings show that the workers have a positive attitude towards Tourism English, because it is very useful and necessary language to work in the world of tourism and it is very helpful in the work while doing and providing services to the tourists.
Visual and interactive tools for a multiple cross-reading of a database source

Interpreting the need to process complex data in contemporary research processes, the research group worked on developing a web-based tool that integrated the potential of the visual language of interactive infographics into the process of organizing documentary sources. After analysing the major tools currently used to search and catalogue data through online collaborative systems and the study of specific examples of data visualisation, the paper presents the project for an online platform that allows researchers to analyse and query data in order to create transversal readings and new narrations that make it possible to interpret the field of study in new and original ways.
A Common Vision Realized: Holistic Educators’ and Utopian Visionaries’ Ideas Brought to Life

This article will explore the common educational vision of two distinct groups — holistic educators and American utopian authors of late-19th to mid/late-20th century — and then propose that this joint vision, along with its actualization in a variety of forms of alternative education (e.g. unschooling, democratic free schooling, Montessori and Waldorf schools, etc.) is positive evidence of a “self-organizing revolution” (Miller, 2008).  This revolution is working to challenge dominant educational paradigms, and should serve as a source of hope for many who despair that more idealistic visions of education will never come to be in our country.
Model Selection: Finding the Right Fit

There are numerous possible goals for building statistical models. Those statistical goals, the associated model types, and each statistical tool involved in model building come with its own assumptions and requirements. In turn, these requirements must be met if we are to ensure that our models produce meaningful, interpretable results. However, beyond these technical details is the intuition, and the additional set of tools and algorithms, used by the statistician, to build the contextually appropriate model: not only must we build an interpretable model, we must build a model that answers the particular question at hand and addresses the particular goal we have in mind. In this column we discuss the methods by which statisticians build models for description, risk factor identification, and prediction.
Priority Based Trimmed Median Filter for Removal of High Density Salt and Pepper Noise

This paper proposes an efficient and less complex priority-based trimmed median filter algorithm for restoring images corrupted by high density salt and pepper noise. Noisy pixel is replaced by trimmed median value of the horizontal and vertical adjacent four pixels, through this algorithm. If these four are 0's and 255's, then the next priority diagonal adjacent four pixels are used to calculate trimmed median for replacing noisy pixels. If these four are also found as 0's and 255's, then the noisy pixel is left unchanged until the next iteration. Experimental results on different greyscale and colour images show that the proposed algorithm outperforms the standard median filter, adaptive median filter, decision-based algorithm, modified progressive switching median filter and modified decision-based unsymmetric trimmed median filter.
Collaborations with Breathing Space Collective

Breathing Space are a London based five piece collective. Their evolving sound performance practice fuses voice and experimental instrumentation with techniques of improvisation, deep listening, assemblage and field recordings. They create site specific performances exploring architectural acoustics, uncovering the social and physical resonances to shape content and form. Working outside the traditional performance space they re-imagine place, adding new memory to sites, often encountering unsuspecting audiences.I regularly collaborate with Breathing Space as technical advisor, creative collaborator, musician, performer, composer and sound designer. Details of various events are in documents attached to this dataset.
An Overview of Bitcoin's Legal and Technical Challenges

This paper examines Bitcoin from a legal and regulatory perspective, answering several important questions. Bitcoin has been the focus of the forums for the past few years by causing a whirlwind of arguments in a various number of fields all over the globe, such as finance, technology and most importantly the legal field. Currency’s evolution through time has been steady and sturdy, but after the creation of crypto currencies, the whole ground structure of a traditional currency has been shattered and transformed dramatically thus changing the core qualities of currencies with its intangibility, anonymity and decentralized nature which are considered as the main merits of Bitcoin as a cryptocurrency. But on second thought, these benefits arose huge complications on both the legal and financial surface where illegal activities from criminals and drug addicts take place by using Bitcoins as a currency, such as fraud, money laundering and terror finance. On the other hand, lack of trust among individuals and merchants in Bitcoin users is the prime factor leading to theft. Nations around the world started to work on defining the nature of Bitcoin in order to regulate crypto currencies in general with a sound legal framework because with great power comes great responsibility to protect citizens from the risks accompanying Bitcoin. The focus of the paper is to cover positive aspects of Bitcoin as a currency and mainly the controversy circling around Bitcoin’s regulations. The focus of this paper is to examine legal and technical issues and current international legal status regarding Bitcoin as a crypto currency and recent legal developments affecting Bitcoin, based upon their actual use.
July 1, 2019 is just around the corner! Ready to move up? Things to reflect on…

…Ready to move up? ...Perhaps!Applying for a new leadership job in education should not be a last minute decision. One should give serious thought to the idea that it may take up to a year to prepare for a transition. Why?  Well, because of the complexities, variables, and reflection involved in anyone “moving up” in an organization. Nonetheless, and whether we know it or not, we are ALWAYS “interviewing” for the next job. In other words, your current performance, results, and relationships are already being observed.
Conditional proxy broadcast re-encryption with fine grain policy for cloud data sharing

Conditional proxy broadcast re-encryption (CPBRE) enables a semi-trusted proxy to convert Alice's ciphertext satisfying a certain condition into a set of users' ciphertext. The proxy, however, cannot learn anything about the underlying plaintext. The traditional CPBRE schemes cannot support flexible control on conditions. In this paper, we present a new primitive named conditional proxy broadcast re-encryption with fine grain policy (CPBRE-FG). In a CPBRE-FG scheme, the re-encryption key is generated with an access tree, and the ciphertext is constructed under a set of descriptive conditions. The proxy can convert a ciphertext if and only if the set of conditions satisfies the access tree. We formalise the notion of CPBRE-FG and present an efficient CPBRE-FG scheme. Finally, we prove it against chosen-ciphertext attack (CCA) security in the random oracle model.
Disinfection of microbes in different environments: An annotated selection of World Wide Web sites relevant to the topics in environmental microbiology

Environmental MicrobiologyVolume 21, Issue 3 p. 1170-1171 Web alert Disinfection of microbes in different environments: An annotated selection of World Wide Web sites relevant to the topics in environmental microbiology Lawrence P. Wackett, Lawrence P. Wackett McKnight Professor Department of Biochemistry, Molecular Biology & Biophysics, BioTechnology Institute, University of Minnesota, St. Paul, Minnesota 55108, USASearch for more papers by this author Lawrence P. Wackett, Lawrence P. Wackett McKnight Professor Department of Biochemistry, Molecular Biology & Biophysics, BioTechnology Institute, University of Minnesota, St. Paul, Minnesota 55108, USASearch for more papers by this author First published: 13 March 2019 https://doi.org/10.1111/1462-2920.14573Read 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. Volume21, Issue3Special Issue on Pathogen and drug resistance ecologyMarch 2019Pages 1170-1171 RelatedInformation
Mixture of Forward-Directed and Backward-Directed Autoregressive Hidden Markov Models for Time series Modeling

Mixture of Forward-Directed and Backward-Directed Autoregressive Hidden Markov Models for Time Series Modeling
The blockchain, plums, and lemons: Information asymmetries & transparency in decentralized markets

Despite a growing interest, researchers and practitioners still struggle to transfer the blockchain concept introduced by Bitcoin to market-oriented application scenarios. To shed light on the technology's usage in markets with asymmetric information, this study analyzes the eect of the blockchain's public transparency paradigm on behavioral patterns and market outcomes. In line with prior research, our ndings indicate that the blockchain's shared record mitigates adverse selection eects and reduces moral hazard of good market participants (plums). In addition, we identify an incentive for bad market participants (lemons) to behave opportunistically in the presence of perfect quality information. More specically, the disclosed information allows them to learn about quality dierences between plums and lemons, deceive their counterparties, and move to a new equilibrium with increased utility. As a result, the market collapses despite a welfare gain and future generations are denied market access. In addition, plums and lemons are committed to inecient equilibria following irrational behavior. In total, this study aims to provide initial guidance for blockchain adoption in the context of markets with information asymmetries and highlights risks that arise from competition, the exposure to irrational behavior, and the implementation of services on the infrastructure level.
Immersive University Education

Immersive University Education has been an international initiative of the Federico II University of Naples in collaboration with the immersive education network Rockcliffe University Consortium, CA, USA; with the INDIRE educational research institute; with national and international universities. The initiative was held on October 24, 2017 in the Aula Magna of the Federico II University of Naples. The Think Tank Notebook of RTH 6 (2019) Immersive University Education includes part of the Proceedings.
Unconstrained Face Verification and Open-World Person Re-identification via Densely-connected Convolution Neural Network

Although various methods based on the hand-crafted features and deep learning methods have been developed for various applications in the past few years, distinguishing untrained identities in testing phase still remains a challenging task. To overcome these difficulties, we propose a novel representation learning approach to unconstrained face verification and open-world person re-identification tasks. Our approach aims to reinforce the discriminative power of learned features by assigning the weight to each training sample. We demonstrate the efficiency of the proposed method by testing on datasets which are publicly available. The experimental results for both face verification and person re-identification tasks show that its performance is comparable to state-of-the-art methods based on hand-crafted feature and general convolutional neural network.
Identity Management Based on Frontal Facial Recognition for Voters Register in Zambia

Biometric technology offers a great opportunity to identify individuals, authenticate individuals and separate individuals. Using these advantages, an election or voting model can be developed to perform elections for a country such as Zambia. Zambia currently uses a manual based voting or election model that heavily relies on paper presented documents that must be physically verified and or matched to existing prior collected information before an individual is allowed to participate in an election or a voting system. This paper proposes a frontal facial election based biometric model that can be used to rid the current election system of redundancy and introduce a paperless, accurate and efficient identification, authentication and voting process. A baseline study conducted shows that biometric authentication based on this proposed model improves a work related process such as a voting system. We start by introducing the elements that make a biometric model ideal, we then give an insight into the Zambian based election system and then we review various biometric technologies available and then finally introduce our biometric model.
Automatic Gaze Correction based on Deep Learning and Image Warping

When people take a selfie photo or talk through a video chat system, they tend to look at the screen. Since the position of the camera is usually different from that of the screen, the eyes of the person in the photograph or transmitted live video seem to make contact with something other than the viewer. This paper proposes a method to correct the gaze by synthesizing the image texture. The image synthesis uses feature points around the eyes as landmarks. A common convolutional neural network and long-term recurrent convolution network are used to extract or detect these feature points in a still image and video image, respectively. The deep learning-based feature point detections are very accurate compared to conventional methods. These feature points are used as landmarks, and the internal texture of these feature points are synthesized with the prepared template image in advance. Through these procedures, an automatic and natural gaze correction is realized. This method realized a natural gaze correction with little blur, even for a video image.
Analysis of Ethnolinguistic Knowledge of Elementary School Teachers in Indonesia

Ethnolinguistics in the learning perspective is the knowledge that teachers have about regional languages that are related or included in learning.This study aims to determine the ethnolinguistic knowledge of classroom teachers in Indonesia Elementary School, to know the ways and obstacles experienced by teachers in implementing ethnolinguistics in-class learning at Indonesia primary school.This study uses the mix methods approach with the sequential explanatory design.The sample in this study were 18 teachers.The sampling technique used purposive sampling.The quantitative data collection technique used was in the form of a questionnaire.Qualitative data collection techniques used are interviews and document analysis.The questionnaire data shows that elementary school teachers in Indonesia have ethnolinguistic knowledge in the less good category with an average of 30.72.Interview data obtained results about the ways teachers use ethnolinguistics in the classroom in terms of 4 aspects and data on the constraints of teachers in implementing ethnolinguistics can be viewed from five aspects.
An Experimental Exploration of Segmentation Techniques for Modi Script

The segregation of image is most significant phase to identify borderline information of an image effectively.As various degradation exists in an image such as distorted pixel value, blurring in an image, poor luminance etc that affects the visual representation of an image.Using segmentation techniques, we attempts to improve the content of an image and make it clear for representation.There exist various edges and clustering based segmentation techniques such as perwitt, roberts, canny, sobel and K-means clustering that assist in segregating distortion information from a Modi character image to great extent.The comparative analysis of these segmentation techniques based on some performance parameters is performed to segment Modi character components.As a result, K-means clustering technique shows more appropriate outcome for segregating Modi numerals efficiently.
The Contribution Of Reading Habit, Vocabulary Mastery, And Learning Motivation Towards English Writing Achievement

This research is aimed to know the contribution of reading habit, vocabulary mastery, and learning motivation towards english writing achievement at the tenth grade of TKR program in SMK Muhammadiyah 1 Blora.The type of this research is associational quantitative research. The sample of this research was 160 students which are chosen by using cluster random sampling. The techniques of collecting data used were questionnaire and test. The questionnaires are dealing with student’s reading habit and student’s learning motivation, while the test is dealing with student’s vocabulary mastery and English writing achievement. The researcher used SPSS version 21.0 to analyze the data which consist of descriptive statistic, classic assumption test, multiple regressions and hypothesis testing such as t-test (partial), f-test (simulation), coefficient of determination, predictor contributions.The result of this research shows that Fresult is 57,488 with the significant is 0,000. The result of R2 is 52,6%. The result above shows that there are positive and significant contributions of independent variables toward dependent variable individually and simultaneously. Statistically, Time spent on non-academic reading has high contribution in student’s reading habit, grammar has high contribution in vocabulary mastery, and intrinsic motivation has high contribution in student’s learning motivation.
Problems of Categorization in Micro-Phenomenological Analysis

The authors describe how the structures of experience unfold in the course of micro-phenomenological analysis step by step by suggesting iterative interrogation. The proposed abstraction operations…
Comparison over Encrypted Data for Privacy Preservation Based on Homomorphic Encryption

Now a days, with data mining computation being performed by cloud servers it is a problem to securely determining whether x>y, given two input values x, y, which are held as private inputs by two parties, respectively. The output which is result of comparison becomes known to both parties. In this paper we consider a variant of comparison problem in which the inputs x, y are encrypted and the actual values are not known to the parties. Our solution deals with single comparison; however, in many applications, we encounter situations where it is necessary to make multiple comparisons to find the maximum among several encrypted data, so we make a modification to our protocol to solve the multiple comparisons problem. Such a secure comparison is an important building block for applications like privacy preserving data mining and secure business. Also our protocols can be performed in constant rounds and do not use general circuit evaluation techniques so they are more efficient than circuit based ones but not general. Implementation is easy and fast.
Empowering young adults on the autistic spectrum: Reframing assistive technology through design

Increasingly, assistive technologies are designed to ‘empower’ people with cognitive and social challenges. But what does it mean to say technology empowers? In a four-year participatory Research-through-Design project we addressed this question. Eleven autistic young adults participated in designing MyDayLight: an IoT system supporting self-management of domestic activities. Contextual inquiry, co-design, design reflection, prototype deployment and embodied interaction theory were woven together in an iterative reflective process. This allowed us to critically address certain background assumptions that typically underly common understanding of assistive technologies. We present three reframings of our evolving concept of ‘empowering technology’: 1) From ‘planned reminder’ to ‘situated attention grabber’ 2) From ‘supporting action’ to ‘scaffolding developing your own supportive environment’ 4) From ‘assistive product’, to ‘co-design tool in a larger transformational process’. Instead of supporting ‘self-sufficiency’, MyDayLight expresses a developmental-experiential interpretation of empowerment. It helps users experiment with reconfiguring their own environment, reflect on their experiences and gradually develop more grip on life. The design artifacts enabled young adults on the spectrum and their care-givers to share, question- and reframe implicitly held understandings and to imagine and explore new ways for assistive technology to play an empowering role in a person’s life-world.
Pairwise Preference Regression on Movie Recommendation System

Recommendation System is able to help users to choose items, including movies, that match their interests. One of the problems faced by recommendation system is cold-start problem. Cold start problem can be categorized into three types, they are: recommending existed item for new user, recommending new item for existed user, and recommending new item for new user. Pairwise preference regression is a method that directly deals with cold-start problem. This method can suggest a recommendation, not only for users who have no historical rating, but also for those who only have less demographic info. From the experiment result, the best score of Normalized Discounted Cumulative Gain (nDGC) from the system is 0.8484. The standard deviation of rating resulted by the recommendation system is 1.24, the average is 3.82. Consequently, the distribution of recommendation result is around rating 5 to 3. Those results mean that this recommendation system is good to solving cold-start problem in movie recommendation system.
Monika Kopytowska (ed.), Contemporary discourses of hate and radicalism across space and genres. Amsterdam: John Benjamins, 2017. Pp. 279. Hb. €95.

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.