Reviewerly/exHarmony huggingface dataset:
Teaching Primary English: Subject Knowledge and Classroom Practice by EveBearne and DavidReedy2018. Oxon: Routledge. ISBN: 9781138681569 £25.99, 422pp.

LiteracyVolume 54, Issue 2 p. 71-71 Book Review Teaching Primary English: Subject Knowledge and Classroom Practice by Eve Bearne and David Reedy 2018. Oxon: Routledge. ISBN: 9781138681569 £25.99, 422pp. Elizabeth Parr, Corresponding Author Elizabeth Parr parre@hope.ac.uk orcid.org/0000-0002-9794-503X School of Teacher Education, Liverpool Hope University, Liverpool, UK Correspondence: Dr Elizabeth Parr, School of Teacher Education, Liverpool Hope University, Liverpool, UK. E-mail: parre@hope.ac.ukSearch for more papers by this author Elizabeth Parr, Corresponding Author Elizabeth Parr parre@hope.ac.uk orcid.org/0000-0002-9794-503X School of Teacher Education, Liverpool Hope University, Liverpool, UK Correspondence: Dr Elizabeth Parr, School of Teacher Education, Liverpool Hope University, Liverpool, UK. E-mail: parre@hope.ac.ukSearch for more papers by this author First published: 03 May 2019 https://doi.org/10.1111/lit.12191Read 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. Volume54, Issue2May 2020Pages 71-71 RelatedInformation
Enhancing Remembrance of Password as an Image

This paper focuses on changing the system of having `text' as password as people tend to often forget their passwords and have to recover it. Proposing the system of having picture as a password which is kept encrypted in a database and decrypted and matched to check for authorization of user. It has been scientifically proven that it's easier for a human mind to remember a picture, something they can see rather than text.
Opportunities of Quantified Self for Resocialisation of (Ex-)Convicts

Resocialisation is a guided process by which ex-convicts are introduced back into society. An issue that arises in this process is that ex-convicts are behind on technological developments when they return to society. Here, we present work on how quantified self technology, as an alternative to the present-day ankle monitor, can be a helpful tool to obtain overview and insight in their progress. In particular, we present a prototype that physically monitors stress levels as an indicator of behavioural patterns. Results from research with former convicts shows how giving ownership over tracking data can help the user group understand their societal status and become more sovereign during their resocialisation process. Finally, we reflect on ethical questions regarding data gathering, Quantified Other and privacy for ex-convicts.
Grabbing of Specific News from Emotion State on Recent News

The abstract must clearly indicate the ideas of the proposed work, suggested solution framework and expected outcome in brief. The abstract can be of minimum 300 words. The abstract should not same as that of the referred base paper.
The development of work sheet tracker-based students using project-based learning models on straight movement learning materials in Class X Senior High School

The student worksheets are one of the learning resources that can help students in the learning process and improve their competencies. The purpose of this study was to determine the needs of students needed in the use of Tracker-Based Student Worksheets by using the Project Based Learning model on Regular Straight Motion (GLB) material. This research is a qualitative research method which is included in descriptive research. Respondents selected in this study were Class X High School. The instrument used is an observation sheet in the form of a questionnaire whose data is processed using a Likert scale. In the field obtained, teachers tend to only use whiteboards and books as learning media which results in students feeling bored and bored so that they have a low impact on student learning outcomes. This is because the models and assessments used in schools are not in accordance with the 2013 recommended curriculum. For attitudes, good category is 79.4%, while for knowledge competencies 64.7% and skills competencies are 67.9% in good categories. learners during the learning process are lacking. The conclusion is the need to use Tracker-based Student Worksheets by using the Project Based Learning model in the Regular Straight Motion (GLB) material.
Video motion amplification vs. operating deflection shapes for machinery diagnosis

Operating Deflection Shape (ODS) has been an important tool in visualizing the vibration of a machine and its system, including piping networks. The input for ODS is the phase-linked signal set from a group of accelerometers, moved over often hundreds of test points. The data is superimposed onto a CAD model, and then scaled-up vibration motion is animated at frequencies of interest. This process is time-consuming and therefore expensive each time it is applied by experts, and is error-prone. An alternative method has been developed that is based on evaluation of high resolution/ high speed videos. The method provides information equivalent to a high-sensor-count ODS, by treating each pixel as an accelerometer, using the pixel’s light intensity modulation to translate information embedded in the video into vibration motion able to be observed and interpreted by human investigators.
Multi-language Handwritten Recognition in DWT Accuracy Analysis

Discovery of gender orientation from penmanship of an individual shows an intriguing exploration issue with applications in measurable record test, essayist recognizable proof and mental investigations. This paper displays a compelling strategy to anticipate the gender orientation of a person from disconnected pictures of penmanship. The proposed strategy depends on a worldwide approach that thinks about composing pictures as surfaces. Each written by hand picture is changed over into a finished picture which is disintegrated into a progression of wavelet sub-groups at various levels. The wavelet sub-bands are then stretched out into information successions. Every datum succession is quantized to create a Discrete Wavelets Transform (DWT) that produces extraction. These highlights are utilized to prepare two classifiers, numerous occurrence learning, and multiclass bolster vector machine to separate among male and female handwriting recognition compositions. The execution of the proposed framework was assessed on two databases, HWSC and TST1, inside various testing exploratory situations and acknowledged arrangement rates of up to 94.07%.
Professional self-determination as a quality criterion of competitive specialists training

In accordance with the competence-based approach, a specialist developing professionally should be able to create something new in his profession, even in a small way. Professional self-determination is considered by researchers both as a process and as a result of professional development, each stage of which is characterized by a different content. The solution to the problem of professional self-determination of the individual is carried out in two dimensions: theoretical-oriented and practice-oriented. The work of the individual on professional-determination and research activities, like any other holistic activity, has the same organizational and psychological characteristics and methodological foundations. Recently, the interest of professional educational organizations to the problem of self-determination of students has increased due to the fact that timely and reasonable choice of profession, training specialty is a guarantee of both personal success of future professionals and sustainable development of society. The main characteristics of self-determination as a psychological and pedagogical phenomenon are: belonging to the subject, processuality, consciousness, independence. Self-determination is a conscious, independent, purposeful process of identification and disclosure of the essential forces of personality, ways of development and realization of its capabilities and abilities, carried out in interaction with other people. Analysis of the essence of professional self-determination from the standpoint of philosophy, psychology, sociology, acmeology, pedagogy confirms the complexity and diversity of this phenomenon, the need for a systematic approach to its study.
Finding the Real News in News Streams

The current trend of the modern highly mobile society is in the receiving information of any kind by people from one handheld device. This way is simple, convenient, cheap, and practical. The users tend to have only one application on their devices to be universal for any purposes. The social networks have advantages over traditional mass-media instruments such as TV, radio, newspapers, and magazines. This advantage is in the speed of information spreading. Unfortunately, not all of published on-line articles are factual or true. Finding the real news in the news streams is not easy for ordinary users. Even state news agencies do not publish the real news in many cases. In this paper, we discuss different approaches to get the real news from news streams. Among them are the move from the social media to a trusted state agency, the move from one stat agency to several ones to get information on the breaking news from state agencies of different countries. This strategy is the most realistic for the serious users. We introduce the methods to support this strategy and automatically retrieve publications from the trusted sources specified by the user in order to simplify his/her work to obtain the information helping to get and understand the real news better.
Fast orthogonal recurrent neural networks employing a novel parametrisation for orthogonal matrices

Training Recurrent Neural Networks (RNNs) is challenging due to the vanishing/exploding gradient problem. Recent progress suggests to solve this problem by constraining the recurrent transition matrix to be unitary/orthogonal during training, but all of which are either limited-capacity, or involve time-consuming operators, e.g., evaluation for the derivation of lengthy matrix chain multiplication, the matrix exponential, or the singular value decomposition. This paper addresses this problem based on the exponentials of sparse antisymmetric matrices with one or more nonzero columns and an equal number of nonzero rows from a geometric view. An analytical expression is presented to simplify the computation of the sparse antisymmetric matrix exponential, which is actually a novel formula for parameterizing orthogonal matrices. The algorithms of this paper are fast, tunable, and full-capacity, where the target variable is updated by optimizing a matrix multiplier, instead of using the explicit gradient descent. Experiments demonstrate the superior performance of our proposed algorithms.
Enhanced Classification of Incomplete Pattern Using Hierarchical Clustering

More often than not values are absent in database, which ought to be managed. Missing qualities are occurred in light of the way that, the data segment individual did not know the right regard or frustration of sensors or leave the space cleanse. The course of action of missing regarded lacking case is a trying errand in machine learning approach. Divided data is not proper for classification handle. Exactly when insufficient cases are masterminded using prototype values, the last class for comparable illustrations may have distinctive results that are variable yields. We can't describe specific class for specific cases. The structure makes a wrong result which also realizes contrasting effects. So to oversee such kind of lacking data, system executes prototype-based credal classification (PCC) strategy. The PCC procedure is intertwined with Hierarchical clustering and evidential reasoning methodology to give correct, time and memory profitable outcomes. This procedure readies the examples and perceives the class prototype. This will be useful for recognizing the missing qualities. By then in the wake of getting each and every missing worth, credal procedure is use for classification. The trial occurs exhibit that the enhanced type of PCC performs better similar to time and memory viability.
Applying Dialogue Breakdown Detection to Dialogue Systems

Dialogue breakdown detection is a technique used for identifying inappropriate utterances in dialogue systems. Although it is generally assumed that dialogue breakdown detection avoids generating system responses that then cause difficulties in continuing the given dialogue, this has yet to be verified. In this paper, we apply the dialogue breakdown detection technique to generate responses for a chat-oriented dialogue system and experimentally verify that performance is improved by measuring the extent to which dialogue breakdown is avoided. Our experimental results show that naturalness of dialogue and user satisfaction level are improved but enjoyment of dialogue is deteriorated when using this technique.
Weighted Chroma Downsampling and Luma-Referenced Chroma Upsampling for HDR/WCG Video Coding

High dynamic range (HDR) and wide color gamut (WCG) video coding adopt chroma downsampling and upsampling for coding efficiency, which causes degradation in visual quality. In this paper, we propose weighted chroma downsampling and luma-referenced chroma upsampling for HDR/WCG video coding. We adopt ICtCp color space for HDR/WCG video coding instead of Y’CbCr color space due to its advantage in the chroma data processing. We perform weighted chroma downsampling prior to encoding based on the difference between neighboring pixels. Moreover, we take advantage of the full resolution luma data to generate weights for chroma upsampling by exploring the correlation between luma and chroma data after decoding. The experimental results show that the proposed method reconstructs high quality HDR videos with better image details and less color distortion, and outperforms HDR Anchor in terms of both objective and subjective evaluations.
Children's Reflection in Action with DIY

The present case study describes and comments on an experimental activity with 9-11 year old children of a public school in Lecce (Italy) in August 2018. The pupils were required to create computational tools using materials recycled from their own home. We adopted a constructionist perspective; we wanted to foster reflection and discussion among the young participants on the amount of household waste produced and how it can be repurposed for creating novel objects. In order to achieve our scope, we were guided by collapse informatics theory and research through design.
Bad Signature Identification in a Batch Using Error Detection Codes

In today’s digital communication world, authentication of data and the sender is very important before processing. Digital Signatures are the best way for verifying the authenticity of the message or document. When multiple signatures need to be verified together, we use batch signature verification. There are multiple batch verification algorithms for various digital signature schemes such as ECDSA, RSA, DSS and others. Most of the batch verification techniques fail to locate the position of the invalid signature/s in a batch. Hence there are multiple bad signature identification algorithms available to locate the bad signatures. The existing algorithms are inefficient in identifying position of bad signature, if the number of bad signatures increases in the batch or if the number of bad signatures are not known before verification. Hence such schemes are practically not suitable for real time environment. Our proposed CRC based verifier scheme overcomes these disadvantages, as well as outperforms the existing schemes in efficiently identifying the bad signature/s. The comparative analysis of the proposed scheme and the existing schemes, is also discussed in the paper.
Passive Approximation with High-Order B-Splines

Convex optimization has emerged as a well-suited tool for passive approximation. Here, it is desired to approximate some pre-defined non-trivial system response over a given finite frequency band by using a passive system. This paper summarizes some explicit results concerning the Hilbert transform of general B-splines of arbitrary order and arbitrary partitions that can be useful with the convex optimization formulation. A numerical example in power engineering is included concerning the identification of some model parameters based on measurements on high-voltage insulation materials.
iC <scp>ore</scp>

In this paper, we present iCore, a novel continuous and proactive extrospection system with high visibility on IoT devices deploying multi-core ARM platforms. Dedicated cores named Isolated Cores are configured to stay in the TrustZone secure world upon system boot to perform monitoring functionalities to extrospect static normal world kernel memory area proactively, continuously, and stealthily. Different from the existing TrustZone paradigm, in which secure world serves as the slave of the normal world, iCore makes the secure world play a master role. Therefore, iCore remains stealthy and proactive to perform monitoring functionalities. The evaluation results show that iCore is effective and imposes negligible performance degradation using the SPEC CPU2017 benchmark.
Keystream Generators Based on Irregular Decimation

In this chapter, we study the definition and the principal characteristics of the main keystream generators based on irregular decimation: the shrinking generator, the self-shrinking generator, the modified self-shrinking generator and the generalized self-shrinking generator.
Preliminary study of the use of games interactive multimedia module to increase critical thinking of students in senior high school

The poor of students critical thinking skill in senior high school is happened because the materials used do not challenge them to think high. Therefore, it is important to do some efforts to produce challenging materials for students using critical thinking proces. One of them is by develoving interactive multimedia module in a form of games to increase students critical thinking skill. The study is research and development using Plomp model. This model consisted of 3 phases: preliminary research, prototyping phase, and assessment phase. In preliminary research, problem analysis use questionnaire followed by literature study. Based on analysis finding in preliminary research, the student interest in learning physics is high enough, it is around 65.3%, the student interest in using multimedia and games is high, they are around 86.2% and 85.6%, however of the use of technology and games level in learning process is low enough, they are around 37.6% and 36.5%. In learning activity, teachers tend to use more lecture methode or teachers center than student center. In the use of materials, especially module, teachers tend to use printed module existed in market. It cause the poor of students critical thinking skill.
Avoiding and Mitigating Ethical Traps in Technocentric Fieldwork

We are witnessing an increase in fieldwork within the field of HCI, particularly involving marginalized or under-represented populations. This has posed ethical challenges for researchers during such field studies, with "ethical traps" not always identified during planning stages. This is often aggravated by the inconsistent policy guidelines, training, and application of ethical principles. We ground this in our collective experiences with ethically-difficult research, and frame it within common principles that are common across many disciplines and policy guidelines - representative of the instructors' diverse and international backgrounds.
Multi-view Neural Network Integrating Knowledge for Patient Self-diagnosis

The electronic medical records contain a wealth of information, and are used in many medical tasks such as medical diagnosis. Most of the research are to assist doctors in diagnosis, and few studies are based on patient self-diagnosis. Our work is completely from the patient's point of view, through the patient's symptoms and discomfort body parts to determine the patient's possible disease. We have designed a multi-view neural network to fully capture the characteristics of multiple aspects of the patient, then perform feature fusion, and finally achieve the purpose of predicting disease only through the patient's symptoms and body parts. At the same time, we create a medical knowledge graph based on the patient's electronic medical record data. The facts in knowledge graph can effectively screen out the candidate disease of the patient, reduce the range of disease selection, and effectively improve the accuracy of the prediction. The experimental results also confirmed the effectiveness of the modified method.
Interactive reconstruction of the 3D-models using single-view images and user markup

This paper presents a method for reconstruction of 3D-model using single view image of the object. To do this, we need to detect the edges of the object on the image and get a small markup from the user. In addition, our method allows us to obtain the texture of the 3D model.
Using Augmented-Reality to Aid in Lego Construction

LEGO structures are generally constructed by following an instruction manual in paper or digital form, which shows the LEGO model at different stages of assembly. Some instructions can be very complicated and difficult to illustrate on paper. Augmented reality (AR) is a technology that superimposes 3D models onto the physical world. This chapter explores the use of AR for assembly through a mobile application for Android devices that serves as an assembly guide for LEGO structures. The system can recognize the current step of the LEGO assembly using data captured via Microsoft Kinect while providing visual feedback through a mobile application. To identify the current step, the system obtains the color and depth data from the Kinect camera and converts the data into a point cloud, which is compared to stored LEGO model data. The system was evaluated based on the accuracy of the recognition, latency of the feedback and the assembly time of the user.