Reviewerly/exHarmony huggingface dataset:
Primary students’ reading habits of printed and e-books

Technological advancement has made books available not only in printed format but also in electronic format. To understand primary students’ reading habits of printed books and e-books and discover if differences can be found in students of different gender or different level of studies, 99 primary schools students were invited to complete a questionnaire. Results show that boys generally read more than girls regardless of the book format, while boys are more positive about reading e-books and using digital libraries for reading online books. Students who read more printed books also tend to read more e-books. Implications for boys’ positive attitudes towards e-books in developing their reading habits, as well as the potential development of digital libraries are drawn.
Continuous Software Engineering and Unit Testing: From Theory to Practice

With the Agile development approach, the software industry has moved to a more flexible and continuous Software Development Life Cycle (SDLC), which integrates the stages of development, delivery and deployment. This trend has exposed a tendency of increasing reliance on both unit testing and test automation for the fundamental quality-activities during the code development. To implement Continuous Software Engineering (CSE), it is vital to assure that unit-testing activities are an integral and well-defined part of a continuous process. This paper focuses on the initial role of actual testing – viewing unit testing as a quality indicator during the development life cycle. We review the definition of unit-testing from the CSE world, and describe a qualitative study in which we examined implementation of unit testing in three software companies that recently migrated to CSE methodology. The results from the qualitative study corroborate our argument that under the continues approach, quality-based development practices such as unit testing are of increasing importance, lacking common set of measurements and KPI's. A possible explanation to this may be the role of continuous practices as well as unit testing in the software engineering curriculum
The Socio-Economic Impact of Identity Theft and Cybercrime

The purpose of this chapter is to explore and address the socio-economic impact of identity thefts and cybercrime in general. The chapter will further explain the various ways employed in their implementation. The chapter will also put forward ways to prevent the threats and vulnerabilities of the attacks. The study will also recommend solutions to stop and/or mitigate the consequences of cyber-thefts. The study will define social engineering as well as provide various social engineering tactic. The chapter will also discuss the reasons for the rise in cybercrime. Such reasons will include financial gain, revenge, as well as non-financial gains. Also cited are examples that demonstrate the capabilities of cybercriminal. The chapter will also provide justification for the reasons behind the cumbersome task and failure in instituting a lasting solution to the criminal activities. Finally, this chapter will close with a conclusion on the economic implications of social engineering on the general cyberwar on cybercrime at the national and global levels.
Learning a Triplet Embedding Distance to Represent Gleason Patterns

Gleason grade stratification is the main histological standard to determine the severity and progression of prostate cancer. Nonetheless, there is a high variability on disease diagnosis among expert pathologists (kappa lower than 0.44). End-to-end deep representations have recently deal with the automatic classification of Gleason grades, where each grade is limited to namely code high-visual-variability sharing patterns among classes. Such limitation on models may be attributed to the relatively few labels to train the representation, as well as, to the natural imbalanced sets, available in clinical scenarios. To overcome such limitation, this work introduces a new embedding representation that learns intra and inter-Gleason relationships from more challenging class samples (grades tree and fourth). The proposed strategy implements a triplet loss scheme building a hidden embedding space that correctly differentiates close Gleason levels. The proposed approach shows promising results achieving an average accuracy of 74% to differentiate between degrees three and four. For classification of all degrees, the proposed approach achieves an average accuracy of 62%.
Latent Semantic Structure of the WMS-III Verbal Paired-Associates

Abstract Objective To investigate the factor structure of the verbal paired-associates (VPA) subtest in the WMS-III using a theoretically driven model of semantic processing previously found to be well-fitting for the WMS-IV version of the test. Method Archival data were used from 267 heterogeneous neurosciences patients and 223 seizure disorder patients who completed the WMS-III as part of a standard neuropsychological evaluation. Confirmatory factor analysis was used to test theoretically driven models for VPA based on principles of semantic processing. Four nested models of different complexities were examined and compared for goodness-of-fit using chi-squared difference testing. Measurement invariance testing was conducted across heterogeneous neuroscience and seizure disorder samples to test generality of the factor model. Results After removing items with limited variability (very easy or very hard; 12 of 40 items), a four-factor model was found to be best-fitting in the present patient samples. The four factors were “recreational”, “functional”, “material”, and “symbolic”, each representing semantic knowledge associated with the function of the target word referent. This model subsequently met the criteria for the strict measurement invariance, showing good overall fit when factor loadings, thresholds, and residuals were held to equality across samples. Conclusions The results of this study provide further evidence that “arbitrary” associations between word pairs in VPA items have an underlying semantic structure, challenging the idea that unrelated hard-pairs are semantic-free. These results suggest that a semantic-structure model may be implemented as an alternative scoring in future editions of the WMS to facilitate interpretation.
Skeleton2Stroke: Interactive Stroke Correspondence Editing with Pose Features

Inbetweening is an important technique for computer animations where the stroke correspondence of hand-drawn illustrations plays a significant role. Previous works typically require image vectorization and enormous computation cost to achieve this goal. In this paper, we propose an interactive method to construct stroke correspondences in character illustrations. First, we utilize a deep learning-based skeleton estimation to improve the accuracy of closed-area correspondences, which are obtained using greedy algorithm. Second, we construct stroke correspondences based on the estimated closed-area correspondences. The proposed user interface is verified by our experiment to ensure that the users can achieve high accuracy with low correction in stroke correspondence.
Analisis Wacana Kritis terhadap Berita Serangan Bom Afghanistan Portal Online Media SINDOnews.com dan republika.ac.id

This research is the result of Critical Discourse Analysis ( CDA ) on news of the bomb attack at Afghanistan's Kabul International Airport. The purpose of this research is to find out the textual practice of the discourses of the two Indonesian national media as those that can influence the reader's view of news issues. This research uses a qualitative descriptive method with a three-dimensional theoretical approach from Fairclough, namely textual practice, discourse practice and socio-cultural practice. This discourse analysis research uses three stages in analyzing Fairclough's perspective discourse, namely description, interpretation, and explanation. The results of the text analysis show that the two news ’ media have different content. The text on SINDOnews.com often shows actor Joe Biden as the President of the United States who demands accountability and will retaliate against those who carried out the bombings. Meanwhile, Republikasi.ac.id tends to focus more on representing the victims of the bombing. The difference in the focus of news representation in the two media seems to coincide with the different institutional and social contexts of each media. Abstrak Penelitian ini hasil Analisis Wacana Kritis (AWK) pada berita serangan bom di Bandara Internasional Kabul Afghanistan. Penelitian dimaksudkan untuk mengetahui praktik tekstual wacana kedua media nasional Indonesia sebagai alat informasi yang dapat mempengaruhi pandangan pembaca terhadap isu pemberitaan. Penelitian ini menggunakan metode deskriptif kualitatif dengan pendekatan teori tiga dimensi dari Fairclough yaitu praktik tekstual, praktik wacana dan praktik sosial budaya. Penelitian analisis wacana ini menggunakan tiga tahapan dalam menganalisis wacana perspektif Fairclough, yaitu deskripsi, interpretasi, dan eksplanasi. Hasil analisis teks menunjukkan bahwa kedua media berita tersebut memiliki konten yang berbeda . Teks di SINDOnews.com lebih sering memunculkan aktor Joe Biden sebagai Presiden Amerika serikat yang meminta pertanggungjawaban dan akan membalas pihak yang melakukan pengeboman. Sementara itu, Republikasi.ac.id cenderung lebih fokusmerepresentasikan korban-korban akibat peristiwa bom tersebut. Perbedaan fokus representasi berita yang ada dalam kedua media tersebut tampak bertepatan dengan perbedaan konteks institusi dan sosial tiap-tiap media.
Digitalizing Community Health

Through the study of ‘Motech’—a global mHealth programme on maternal health implemented in Ghana and India—this chapter offers the first analysis of the use of mobile phones as a tool in such programmes. This chapter focuses on the particular role of community health workers in establishing this programme. It questions the competing strategies to enhance or substitute these workers that are linked to the expansion of these new technical artefacts. This vision—of the health worker assisted by the mobile—is twofold: on the one hand, it would make the health worker efficient and omniscient; on the other hand, it calls into question the knowledge of health workers and their autonomy through an automated system of communication. This research provides a better understanding of the special status of mobile phones and mHealth applications for community health workers and how their use changes the practice of community health.
The Necessity of Alternative Narratives and Building ‘Big Idea’ Concept of the Korean History Subject

State-issued textbooks which had been used at educational sites for some time since the 1970s during the ‘Yusin period’, were used as a means of injecting the historical view, created by the Park Chung-hee Administration. The textbook included the logic that the state develops when it equates today’s power elected under democratic stagnation with the king of premodern times and establishes pre-modern absolute power. After the release of the textbook, numerous historians pointed out that such inappropriate descriptions should be overcome, raising the need for a democracy-oriented narrative to correct problems not only in modern history but also in pre-modern areas. <BR>The emergence of the concept of ‘historical education to raise democratic citizens’ after the controversy over state-issued textbook during the Park Geun-hye administration was settled can be positively evaluated in that it is similar to the thoughts of those who had a critical view on the content of state textbooks. However, today’s discussions are mainly limited to the issue of how to increase the proportion of learning elements related to modern and contemporary history.<BR>In order for this discussion to develop in a positive direction, the curriculum should be structured so that learners can develop subjective and critical competencies in various fields such as knowledge, values, and attitudes.
Mobile Robot Computer Simulation System

Abstract The constant development of science and technology, mobile simulation robot become one of the people of tea after a meal, want the simulation robot to human operation level, premise condition clearly understand the principle of the simulation robot, and the mobile robot simulation system the required functionality, and after understanding we should how to realize the function of them. In this paper, the principle, function and realization of the mobile robot simulation system are designed.
Dialog Development Manager

This chapter shows how software development professionals use the provided flow charts and pseudo-code to create the Dialog Development Manager. Analysts then use the Dialog Development Manager to create the problem-specific knowledge needed by a natural language processor to support the conversation between Socrates DigitalTM and end users. The Dialog Development Manager guides the analysts through design and development of the Understand, Explore, Materialize, and Realize phases to create the conversational interface for Socrates DigitalTM.
Contracts Used to Procure Cloud Services I

This chapter contains the first part of the book’s study on cloud computing contracts evaluating the organization and structure of cloud computing contracts in addition to their content. This includes an evaluation of Service Level Agreements (SLAs), the use of master-service and framework agreements, issues related to subcontractors and subcontracting, third-party rights, and liability considerations.
SODAR: Exploring Locally Aggregated Learning of Mask Representations for Instance Segmentation

Recent state-of-the-art one-stage instance segmentation model SOLO divides the input image into a grid and directly predicts per grid cell object masks with fully-convolutional networks, yielding comparably good performance as traditional two-stage Mask R-CNN yet enjoying much simpler architecture and higher efficiency. We observe SOLO generates similar masks for an object at nearby grid cells, and these neighboring predictions can complement each other as some may better segment certain object part, most of which are however directly discarded by non-maximum-suppression. Motivated by the observed gap, we develop a novel learning-based aggregation method that improves upon SOLO by leveraging the rich neighboring information while maintaining the architectural efficiency. The resulting model is named SODAR. Unlike the original per grid cell object masks, SODAR is implicitly supervised to learn mask representations that encode geometric structure of nearby objects and complement adjacent representations with context. The aggregation method further includes two novel designs: 1) a mask interpolation mechanism that enables the model to generate much fewer mask representations by sharing neighboring representations among nearby grid cells, and thus saves computation and memory; 2) a deformable neighbour sampling mechanism that allows the model to adaptively adjust neighbor sampling locations thus gathering mask representations with more relevant context and achieving higher performance. SODAR significantly improves the instance segmentation performance, e.g., it outperforms a SOLO model with ResNet-101 backbone by 2.2 AP on COCO test set, with only about 3% additional computation. We further show consistent performance gain with the SOLOv2 model.
Graphical abstracts

Graphical abstracts – visuals summarizing scientific arguments – have become increasingly prominent elements of scientific journals’ publishing infrastructures and social media strategies. This chapter synthesizes existing graphical-abstracts research and demonstrates a systematic case-based approach for navigating the complexities of summarizing and circulating science visually.
Encrypted Cloud Quantum Computation

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Elekta Medical Linear Accelerator

Biomedical Safety & Standards: January 15, 2022 - Volume 52 - Issue 1 - p 4 doi: 10.1097/01.BMSAS.0000805480.75140.30
Word Search on the "SITUK" Application Using the Levenshtein Distance Algorithm

Integrated System for Online Competency Certification Test (SITUK) is an application used to carry out the assessment process (competency certification) at LSP (Lembaga Sertifikasi Profesional) UPN (University of Pembangunan Nasional) “Veteran” Jawa Timur, each of which is followed by approximately five hundred (500) assessments. Thus the data stored is quite a lot, so to find data using a search system. Often, errors occur in entering keywords that are not standard spelling or typos. For example, the keyword "simple," even though the default spelling is "simple." Of course, the admin will get incomplete information, and even the admin fails to get information that matches the entered keywords. To overcome the problems experienced in conducting data searches on the SITUK application, we need a string search approach method to maximize the search results. One of the algorithms used is Levenshtein which can calculate the distance of difference between two strings. Implementation of the Levenshtein algorithm on the data search system in the SITUK application has been able to overcome the problem of misspelling keywords with the mechanism of adding, inserting, and deleting characters.
Multiphoton intersubband transitions in an armchair graphene nanoribbon

Abstract We present an analytical approach to the problem of the interband transitions in an armchair graphene nanoribbon (AGNR), exposed to the time-periodic electric field of strong light wave, polarized parallel to the ribbon axis. The two-dimensional Dirac equation for the massless electron subject to the ribbon confinement is employed. In the resonant approximation the probability of the transitions between the valence and conduction size-quantized subbands are calculated in an explicit form. We trace the dependencies of the Rabi frequency for these transitions on the ribbon width and electric field strength for both the multiphoton-assisted and tunneling regimes relevant to the fast oscillating and practically constant electric field, respectively. Estimates of the expected experimental values for the typically employed AGNR and laser technique facilities show that the Rabi oscillations can be observed under laboratory conditions. The data, corresponding to the intersubband tunneling, makes the AGNR a 1D condensed matter analog, in which the quantum electrodynamic vacuum decay can be detected by the employment of the attainable electric fields.
Introduction

In an increasingly digitalized economy and society, the security and accountability of data transactions are critical elements for creating trust and enabling breakthrough innovations in the digital world. In this regard, blockchain technology could be a game-changer, with the potential to revolutionize processes from finance to pharmaceutical industries, from government public services to humanitarian work and development aid. The blockchain serves as the base technology for cryptocurrency, enabling open (peer-to-peer), secure and fast transactions. The blockchain application has expanded to include various financial transactions (e.g., online payments and exchange platforms), Internet of things (IoT), health systems and supply chains.
Proposed Methods t o Rollback A Failed Update of IoT Devices

The increasing number of IoT devices leads to the demand for updating them securely, and stably. Without updating there is a high risk of being attack by hackers or malfunction due to outdated packages. To the date of this article, a lot of IoT updating methods were introduced. Among them are updating using VM containers, using packages, or using blockchain. However, some methods take time to recover a failed update while some cases require the minimum downtime of the IoT devices, or even some devices cannot communicate to the control server or cannot perform the rollback themselves after the update failure. In this article, our contribution is implementing different methods to reduce the rollback down time issue including using primary - secondary selection, using git revert, and using blockchain-based revert.
A Deeper Dive into R

The last chapter explored some introductory concepts in R, from using the console to importing data. We installed packages and discussed data types, including different list types. We finished up by talking about functions and creating closures.
Research on visual intelligent report based on big data of electricity marketing

In recent years, with the continuous development of power grids, more power marketing data is generated, and the traditional EXCEL tables can no longer effectively mine the information in big data. In order to solve these problems, for the grid marketing data, an evaluation system with the collection of support as the main indicator was established, and the information was visualized through interactive visualization technology. This can greatly improve the work efficiency of the power marketing department. In this paper, the power marketing data of 4 league cities and 48 counties in eastern Inner Mongolia is visualized by using the pyecharts module in python, and visual report is generated to evaluate the business level of power companies in each region. The results show that the visual report can analyze and evaluate the business level of various regions intuitively and efficiently, which improve work efficiency. Meanwhile, the weak links in the entire marketing process of various regions and counties can also be found in time, which greatly improving the power marketing department management efficiency and level.
Research on Automatic Modulation Classification Technology under α Stable Distribution Noise

The Automatic modulation classification is the base and significant part of spectrum utilization and the corresponding design of receiver. Therefore, the influence of automatic modulation classification complex electromagnetic environment is very important. In this paper, we consider the diversity of signal noise in complex electromagnetic environment. So we construct the directory in the same modulation signal containing different signals under different Mixed signal-to-noise (MSNR), use the deep learning model, and finally the classification will be obtained. This method only needs to train one model to recognize modulation classification, which avoids the redundancy of model training which trains in different SNR, and the robustness of the network is improved.
AMU et missions stratégiques des PSM

In this paper, an efficient multiple description coding (MDC) method, called the adaptive data reuse MDC (ADR-MDC), is proposed for robust video transmission. The proposed ADR-MDC first groups four sub-sequences, which are generated by performing spatial down-sample operation on each frame of input video sequence, into two descriptions. In each description, one sub-sequence is directly encoded and decoded by applying the H.264/AVC encoder and decoder, while the other is encoded and decoded at each macroblock (MB) based on the adaptive data reuse criterion, which are developed by making full use of the spatial and temporal correlations among the sub-sequences. Experimental results have shown that the proposed ADR-MDC scheme possesses higher error resilient ability and obtains better reconstructed video than the existing state-of-the-art MDC method.
R Language Primer

In the last chapter, we defined what data visualizations are, looked at a little bit of the history of the medium, and explored the process for creating them. This chapter takes a deeper dive into one of the most important tools for creating data visualizations: R.