Reviewerly/exHarmony huggingface dataset:
Chinese-Portuguese bilingual’s phonological awareness: annotations

Economic and trade cooperation between China and Portuguese-speaking countries have increased, as consequence more universities began offering Portuguese courses and the demand of Portuguese/Chinese bilinguals increased in China. However, the principal focus is mostly on areas such as grammar, translation and literature; also in terms of research, those areas are preferred, leaving for second place important linguistic aspects of Portuguese language. This study aims to identify some of the characteristics of the development of European Portuguese’s phonological awareness of Chinese speakers. By conducting different tests, we are able to highlight some of the characteristics and most common difficulties presented by Chinese speakers learning Portuguese. Furthermore, one present some suggestions in order to help both teachers and students overcoming some obstacles. On our study, we gathered data from 40 informants (average age 18-23 years) answers to the surveys and tasks covering the three types of phonological awareness. The more evident characteristics of phonological awareness development by Chinese speakers, include: 1) third-year subjects performance is better than first-year’s; 2) Phoneme awareness is slightly inferior to the syllable awareness; 3) Third-year students present better results on syllable awareness performance then in phonemic; 5) the pair [p, b] discrimination is the most difficult. According to the characteristics of phonological awareness development and learning habits of Chinese speakers, it is desirable to explore methodologies that combine games, tests, activities that may dynamically stimulate and mature phonological awareness.Keywords: Portuguese as a foreign language; phonological awareness; Chinese speakers.
Updating semantic annotations in RDF format

Semantic annotations are sets of labels that help structure the information available in web documents, making it easier for machines to interpret this information automatically. While previous works have explored the (semi-) automatic maintenance of these semantic annotations in relation to ontology-level changes, this work will focus on the effects of instance-level changes, specifically regarding annotations in RDF format. Given a set of annotations affected by an instance-level change, a classification-based approach will be used in order to determine which out of all possible update operations is most appropriate for each annotation, thus keeping the information system consistent and up-to-date.
The Improvement reasoning ability of students to mathematic and logic through colour chip worksheet in the basic education unit in Tanjung Morawa

Learning media is tools for teaching and learning process. Related to the use of instructional media as a component that can help teachers and students in the learning process. In learning mathematics at SDIT Deli Insani, there is still lack of learning media as a component in the learning process. The selection of the most appropriate media that must be considered to achieve the expected goals is to stimulate the ability to choose, increase communication power, stimulate independence, encourage motivation, and increase student creativity. The worksheet is a piece of learning media as well as an innovative game that can be carried around, the exam material is in accordance with the K-13 curriculum for elementary school students grade 1 to 4. By taking a sample of students grade 3 and 4 consist of 30 students per class, done a pre-test about material of mathematics, then explained the use of color chip worksheets. Next, learned the material using a worksheet of color chips. And finally, a post test was conducted to measure up which students could absorb the material. The evaluation, carried out about 2 months after the training, the teachers and students have independently used a worksheet of color chips and the students' abilities significantly improved.
THE EFFECTIVENESS OF USING SMALL GROUP DISCUSSION ON STUDENTS' SPEAKING SKILL

English is an international language that has been learned by every country in the world and also Indonesia.In learning English, students should acquire the four skills that are reading, writing,listening and speaking. These four skills are abilities that are mandatory for everyone who wants to learn English. Specifically speaking.Speaking is quite important to be owned to students.It is also statedin the English syllabus of Curriculum 2013 (K-13) torequire students to be able to express and response some kinds of expression orallyin English.In reality, many students are still poor in speaking English. This research classified certain aspects into two classes namely the control class and the experimental class. In the experimental class and the control class the researcher used the pre-test and post-test methods throughout the study. As a sample or research subject, researchers worked with seventh grade students at the Masehi General High School, Medan.
Optimal Load Balancing and cloud resource management by space shared scheduling technique

Cloud computing is the availability and management of a large number of resources without the involvement of users. The Characteristics of Cloud Environment are its elasticity, availability, and scalability of the resources which is done by sharing the cloud resources. Resource monitoring and prediction are the keys to achieve resource utilization with high-performance management in cloud computing. Resource scheduling is one of the major issues of cloud computing, the scheduling policy and algorithm affect the performance of the cloud system directly. Moreover, Load balancing is also one of the major aspects which are the process of distributing the load on various nodes providing the best resource utilization when nodes are overloaded. The major focus of this work is to develop a space shared resource sharing technique that allows one job to utilize the available resource at a time as per the requirement for job completion. The Proposed System also provides optimal resource sharing and Load balancing by utilizing the Optimized Throttled Load Balancing Algorithm (OTLBA). In order to optimize resources scheduling of cloud computing and to improve the utilization ratio of the resource as well as guarantee application quality of service, the dynamic resources scheduling based on the Optimal Load balancing algorithm has been designed and implemented.
The Augmented Reality (AR) in Malaysian Construction Industry

Building construction sector directly determines the performance of the economy in Malaysia. Hence, the success of the construction project is the critical factor to determine the performance of the Malaysian Construction Industry. A building project is considered successful when it accomplishes with cost, time and quality. Nevertheless, some of the building construction in Malaysia has plagued with cost overruns, uncontrolled and unrealistic schedule, poor workmanship, accidents and conflicts. In order to solve these problems, the construction industry shall introduce advanced information technology to increase the productivity and the success rate in the construction project. Therefore, the new technology called Augmented Reality (AR) now beginning to invest in Malaysian Construction Industry. The first research objective which is to study on the application of Augmented Reality (AR) in Pre-Construction Planning and Design and the second research objective which is to determine the usage, benefits, challenges and barriers of applying Augmented Reality (AR) in Pre-Construction Planning and Design will be identify in order to form the content of this study. Furthermore, literature review and questionnaire survey will carry out as a research methodology to achieve the aim and objective of the study. From the result obtained from the questionnaire, the benefits of using AR in project development, most of the respondents agree that AR provides better understanding even complex project is proposed. Furthermore, as referred to the questionnaire feedback, most of the respondents agree that AR can clearly explain the building design from interior and exterior during project design. Lastly, most of the respondents agree that AR able to increase the efficiency of measurement during project planning. On the other hand, there are also several challenges and barriers that make Malaysian Construction Industry refuse to use the new technology of AR. Most of the respondents have chosen high cost as the barriers to use AR. In addition, the suggestions and recommendations also provided which is providing seminars, training and education on the new technology of AR to increase the usage of AR technology in the Malaysian Construction Industry. Henceforth, this may enhance the understanding of construction parties on the AR technology.In short, this study is to contribute to the construction industry in Malaysia in a way of applying AR technology to solve the problem arise in the construction industry.
Cyberespionage Goes Mobile: FastTrans Company Attacked

The use of mobile devices, such as smartphones and tablets, in the workplace continues to increase. However, these devices’ capabilities make them a prime target for espionage activities. Thus, employees need to understand mobile espionage and how to protect against it. In this paper, we present a teaching case based on two fictitious self-driving car competitors that educators across the world can use in information systems or business courses at the undergraduate or graduate levels. The case introduces students to FastTransportation Company (“FastTrans”), a fictitious American multinational car manufacturing company, who suspects its rival, Wheelz Corporation, a leading ride-hailing company, of engaging in corporate mobile espionage to steal and use trade secrets from its self-driving car division.
FMN: Two-stage web image fine-grained text detection method based on full convolutional network

Abstract In the Internet, there are large-scale web images with different image sizes and different resolutions. In order to accurately and efficiently identify fine-grained texts in web images, this paper uses FCN to support the ability to semantically segment images, and treats text and background as different detection targets. A two-stage web image fine-grained text detection method FMN is proposed. For the problem that the output result of the whole convolutional network is not fine enough, the MSER+NMS algorithm is used to extract the fine-grained features of the FCN output, and the ellipse fitting method is introduced to detect the text. Features such as character tilt and morphological differences ultimately result in text detection of the image. Compared with the existing methods, the FMN algorithm proposed in this paper has achieved certain improvement in detail resolution and precision.
Effective Practices of Updating the Subjectivity of the Mother during the Restoration of Parental Rights

Taking into account the special importance of the blood family for the psychological well-being of the child, the problem of preparing women who restore parental rights to the implementation of educational functions is of particular relevance. One of the most important conditions for the effectiveness of a family education is the integrative characteristic of mother’s personality — her subjectivity, which reflects an active-selective, proactive and responsible attitude to educational activities, a child and her to herself as a subject of a family education. The article describes the effective practices that make up the core of the program of psychological and pedagogical support “I am a subject of education”. The program is a phased organization of activities and events that launch psychological mechanisms of reflected subjectivity and reflection. During the implementation of the program, conditions are created that allow mothers to realize and accept responsibility for the process and result of upbringing, the mothers activate semantic foundations of educational activity, ensure the design of a positive “I am a mother” image of herself, harmonize the attitude towards the child and to herself as a subject of family education.
Colonial Hygienist In-kyu Lee's Public Health Activities and Research

이 논문은 식민지 조선의 위생학자 이인규의 공중보건 활동과 위생학 연구를 살펴본다. 식민정부에 의해 양성된 피지배 민족의 위생학자로서 이인규는 조선인 아동의 건강 증진을 둘러싼 조선인 사회와 식민정부의 서로 다른 입장이 교차하는 지점에 있었다. 그의 위생학 연구는 조선의 발전과 해방을 목적으로 수행되었지만, 애초 의도와 달리 식민정부의 통치력을 강화하기 위한 수단으로 사용되었다. 이런 상황이 전개되는 과정을 이인규와 식민권력의 관계를 중심으로 추적함으로써, 이 논문은 식민지의 피지배인 위생학자가 직면한 딜레마와 식민지 위생학의 성격을 이해하고자 한다.This paper examines the public health activities and research by colonial hygienist In-kyu Lee (李仁圭). As a Korean hygienist cultivated by the Japanese colonial government, Lee stood at the intersection of the two different views of the public health for Korean children between the Japanese colonial government and the Korean subjects. Lee’s research was conducted on the purpose of the development and independence of colonial Korea, but contrary to his original intention, it was used as a means to strengthen the governing power of the colonial government. By focusing on the relationship between Lee and colonial power, this paper seeks to understand the nature of colonial public health and the its dilemma that caused the chaos in the role and the identity of Korean hygienist.
Handwritten Character Recognition for Palm-Leaf Manuscripts

Palm-leaf manuscripts are ancient documents primarily used as writing material in South Asia and South-East Asia. Over hundreds of years, these manuscripts have been damaged. In an attempt to preserve these potentially valuable documents, many organizations have surveyed and digitized palm-leaf manuscripts in form of digital images. It is more desirable to transform the palm-leaf images into machine-encoded texts so that the document can be edited, retrieved, accessed and processed conveniently. Optical handwritten character recognition (OHCR) is a viable option for the purpose. Challenges in OHCR are often associated with types of writing media and the complexity of the alphabet under consideration. Several OHCR techniques for palm-leaf manuscripts have been developed during the past decade. In this chapter, we illustrate the problems associated with performing OHCR on palm-leaf manuscripts. The state-of-the-art OHCR techniques which have been successfully applied to palm-leaf manuscripts are outlined. We finally conclude the chapter with a working example of an ancient Lanna Dhamma character recognition system.
Engaging Users through Social Media in Public Libraries

The participatory library is an emerging concept which refers to the idea that an integrated library system must allow users to take part in core functions of the library rather than engaging on the periphery. To embrace the participatory idea, libraries have employed many technologies, such as social media to help them build participatory services and engage users. To help librarians understand the impact of emerging technologies on a participatory service building, this paper takes social media as an example to explore how to use different engagement strategies that social media provides to engage more users. This paper provides three major contributions to the library system. The libraries can use the resultant engagement strategies to engage its users. Additionally, the best-fit strategy can be inferred and designed based on the preferences of users. Lastly, the preferences of users can be understood based on data analysis of social media. Three such contributions put together to fully address the proposed research question of how to use different engagement strategies on social media to build participatory library services and better engage more users visiting the library?
BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders

Variational Autoencoders (VAEs) provide a flexible and scalable framework for non-linear dimensionality reduction. However, in application domains such as genomics where data sets are typically tabular and high-dimensional, a black-box approach to dimensionality reduction does not provide sufficient insights. Common data analysis workflows additionally use clustering techniques to identify groups of similar features. This usually leads to a two-stage process, however, it would be desirable to construct a joint modelling framework for simultaneous dimensionality reduction and clustering of features. In this paper, we propose to achieve this through the BasisVAE: a combination of the VAE and a probabilistic clustering prior, which lets us learn a one-hot basis function representation as part of the decoder network. Furthermore, for scenarios where not all features are aligned, we develop an extension to handle translation-invariant basis functions. We show how a collapsed variational inference scheme leads to scalable and efficient inference for BasisVAE, demonstrated on various toy examples as well as on single-cell gene expression data.
3D dynamic hand gestures recognition using the Leap Motion sensor and convolutional neural networks

Defining methods for the automatic understanding of gestures is of paramount importance in many application contexts and in Virtual Reality applications for creating more natural and easy-to-use human-computer interaction methods. In this paper, we present a method for the recognition of a set of non-static gestures acquired through the Leap Motion sensor. The acquired gesture information is converted in color images, where the variation of hand joint positions during the gesture are projected on a plane and temporal information is represented with color intensity of the projected points. The classification of the gestures is performed using a deep Convolutional Neural Network (CNN). A modified version of the popular ResNet-50 architecture is adopted, obtained by removing the last fully connected layer and adding a new layer with as many neurons as the considered gesture classes. The method has been successfully applied to the existing reference dataset and preliminary tests have already been performed for the real-time recognition of dynamic gestures performed by users.
Deteksi dan Identifikasi Pelaku Kecurangan Skema Pembagian Rahasia Linear Berbasis Skema Shamir

The method that can be used to maintain security of secret in the form of cryptographic keys is by using secret sharing scheme (SSS). This method is first proposed by Adi Shamir in 1979, where the proposed scheme is a (k, n) threshold scheme. Shamir scheme is a perfect scheme under the assumption that all shareholders present their original share. However, if there are dishonest shareholders who present faked shares then the honest shareholders get nothing but a faked secret. Secret sharing scheme based on linear scheme is a scheme that can detect and identify cheaters who submit faked shares at the secret reconstruction. Detectability of this scheme when and identifiability when under the assumption that all shareholders present their shares randomly. After conducting a security analysis of the proposed scheme, it is obtained that to succeed in attack with cheaters who work together to fool honest shareholders then a new polynomial g(x) such that g(1) = , g(2) = , …, g(k - 1) = and a new detector that has the same value as detector d are needed.
Reseña de Alonso-Ramos, Margarita. 2016. Spanish Learner Corpus Research. Current trends and future perspectives. Amsterdam / Philadelphia: John Benjamins.

Obra ressenyada: Margarita ALONSO-RAMOS, Spanish Learner Corpus Research. Current trends and future perspectives. Amsterdam / Philadelphia: John Benjamins, 2016.
예비보육교사의 아동권리 인식에 관한 주관성 연구

The purpose of this study was to demonstrate the subjective structure of children’s right of Korean college students majoring in Child Care & Education who would be child care center teachers. This study was conducted using Q methodology and the various 33 items were selected through comprehensive review, focus group interview and revision process. Also, 38 college students were selected for the P sample. The results of the study showed 4 types of children’s right perception; Type 1 ( Type of Universal Child Development Rights) includes those who respect for children to eat well, play well, and show their potential; Type 2 (Type of Cultural Protection Right) includes those who consider it important that the children express their opinions, keep them clean, and should not be discriminated depending on their nationality. Type 3 (Type of Child Right with Priority) includes those who feel decision making of child is important and think their rights first; Type 4 (Psycho social Right-Focused Type) includes those who feel that rights are related to society in national level.
Mind the Gap: Enlarging the Domain Gap in Open Set Domain Adaptation

Unsupervised domain adaptation aims to leverage labeled data from a source domain to learn a classifier for an unlabeled target domain. Among its many variants, open set domain adaptation (OSDA) is perhaps the most challenging, as it further assumes the presence of unknown classes in the target domain. In this paper, we study OSDA with a particular focus on enriching its ability to traverse across larger domain gaps. Firstly, we show that existing state-of-the-art methods suffer a considerable performance drop in the presence of larger domain gaps, especially on a new dataset (PACS) that we re-purposed for OSDA. We then propose a novel framework to specifically address the larger domain gaps. The key insight lies with how we exploit the mutually beneficial information between two networks; (a) to separate samples of known and unknown classes, (b) to maximize the domain confusion between source and target domain without the influence of unknown samples. It follows that (a) and (b) will mutually supervise each other and alternate until convergence. Extensive experiments are conducted on Office-31, Office-Home, and PACS datasets, demonstrating the superiority of our method in comparison to other state-of-the-arts. Code available at https://github.com/dongliangchang/Mutual-to-Separate/
Ghost Loss to Question the Reliability of Training Data

Supervised image classification problems rely on training data assumed to have been correctly annotated; this assumption underpins most works in the field of deep learning.In consequence, during its training, a network is forced to match the label provided by the annotator and is not given the flexibility to choose an alternative to inconsistencies that it might be able to detect.Therefore, erroneously labeled training images may end up ''correctly'' classified in classes which they do not actually belong to.This may reduce the performances of the network and thus incite to build more complex networks without even checking the quality of the training data.In this work, we question the reliability of the annotated datasets.For that purpose, we introduce the notion of ghost loss, which can be seen as a regular loss that is zeroed out for some predicted values in a deterministic way and that allows the network to choose an alternative to the given label without being penalized.After a proof of concept experiment, we use the ghost loss principle to detect confusing images and erroneously labeled images in well-known training datasets (MNIST, Fashion-MNIST, SVHN, CIFAR10) and we provide a new tool, called sanity matrix, for summarizing these confusions.