Reviewerly/exHarmony huggingface dataset:
A Comparative Study on Writing Style of Chinese Korean Learners for Academic purposes in Korean and Writing Style in Chinese

The purpose of this study was to compare the Korean writing style and Chinese writing style on the same subject, with a focus on Chinese Korean learners for academic purposes. A total of 28 Chinese international students performed the writing task on the same subject. As a result, the difference in syntactic proficiency was not significant between the Korean essays and the Chinese. However, it confirmed that the pattern of errors in Korean writing was influenced from the native language. In addition, the writer's stance and voice expression patterns can often enhance the genre characteristics of the essay, and it was found that more expressions revealing the writer's stance and voice appeared in the Chinese essays. In addition, the expressions in the Korean essays and the expressions in the Chinese essays were often different. As writing activities using digital devices increase, it is expected that sentences and awkward expressions of translation will increase. Therefore, applying the understanding of error patterns based on the characteristics of the native language to the teaching field will greatly help Korean learners write for academic purposes.&#x0D;
Data-driven detector signal characterization with constrained bottleneck autoencoders

A common technique in high energy physics is to characterize the response of a detector by means of models tunned to data which build parametric maps from the physical parameters of the system to the expected signal of the detector. When the underlying model is unknown it is difficult to apply this method, and often, simplifying assumptions are made introducing modeling errors. In this article, using a waveform toy model we present how deep learning in the form of constrained bottleneck autoencoders can be used to learn the underlying unknown detector response model directly from data. The results show that excellent performance results can be achieved even when the signals are significantly affected by random noise. The trained algorithm can be used simultaneously to perform estimations on the physical parameters of the model, simulate the detector response with high fidelity and to denoise detector signals.
The Influence of New Media on Cybersecurity and Law Implementation: A Qualitative Study

This paper aims to provide an explanation the influence of new media on cybersecurity.Through the Media Dependency Theory lens, researcher can see the use of new media from a media perspective where the media plays a role in this society.This paper describes the influence of new media on cybersecurity and law implementation in Malaysia.The researcher conduct focus group discussion for this paper.Focus group discussion is a qualitative research technique that involves conducting intensive group around 4 groups with six persons each group until get the saturation data.This small number of informants is to explore informants perspectives on a particular idea and situation.Analysis document also use as approach to analyse the law implementation related cybersecurity.The findings of this study identify new media dependency, namely impact of new media and the influence of new media that related to the cybersecurity.In addition, the study highlights about the law implementation in Malaysia.This paper provides a comprehensive critical picture of the growing new media usage literature and information that offers the basis for a comprehensive assessment of new media usage contributions to people in particular and enhances relevant knowledge new media.
Abstract 461: Mixed supervision to improve the classification and localization: Coherence of tumors in histological slides

Abstract With the growing standardization of Whole Slide Images (WSIs), deep learning algorithms have shown promising results for the automated classification and localization of tumors. Yet, it is often difficult to train such algorithms, as they usually require careful detailed annotations from expert pathologists, which are tedious to produce. This is why in general only slide-level labels are accessible while annotations of small regions (or tiles) are limited. With only slide-level information, it is difficult to obtain accurate predictions of the localization of pathological tissues inside a slide, despite reaching good slide-level classification. Besides, existing algorithms show limited consistency between slide- and tile-level predictions, leading to difficult interpretation in case of healthy tissue. Using the attention-based multiple instance learning framework, we propose to combine slide-level labels on all slides with tile-level labels on a small fraction (e.g. 20%) of slides within a histology dataset to improve both classification and localization performances. With this mixed supervision of slides, we aim to enforce a better consistency between slide- and tile-level labels. To this end, we introduce an attention-based loss function to further guide the model’s attention on discriminative regions inside tumorous slides, and display an equal attention among all tiles of normal slides. On the Camelyon16 dataset, we reached precision and recall scores as high as 0.99 and 0.85 respectively with an AUC of 0.93 on the competition test set, using only 50% of the slides with tile-level annotations in the training set. Experiments using various proportions of fully annotated slides in the training set show promising results for an improved localization of tumors and classification of slides. In this work, we showed that using a limited amount of fully annotated slides we can improve both the classification and localization performances of an attention-based deep learning model. This increased consistency and performances should help pathologists to better interpret the algorithm output and to focus on suspicious regions in probable tumorous slides. Citation Format: Paul Tourniaire, Marius Ilie, Paul Hofman, Nicholas Ayache, Hervé Delingette. Mixed supervision to improve the classification and localization: Coherence of tumors in histological slides [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 461.
The End of Genetics: Designing Humanity's DNA

"The End of Genetics: Designing Humanity's DNA." Journal of Consumer Health on the Internet, 26(2), pp. 232–233
Historicising and Theorising Social Media and the Demotic Turn in Communication in Africa 1

Social media platforms have exploded in the last decade and have emerged as the arenas for discursive democracy, sociality, and digital dissidence across Africa. This chapter historicises and genealogises the exponential, if slightly imperceptible but nonetheless phenomenal, growth, maturation, and spread of social media on a continent that had been described in the scholarly literature as the blackhole of informational capitalism. It argues that the progressive centrality of social media in the quotidian lives of Africans, which has invited consternation and censorship from many African governments and inspired precarity in the traditional media sphere, instantiates the materialisation of the demotic turn in communication, which situates the ordinary person as the fulcrum of the communicative process.
K-anonymity applied to the energy grid of things distributed energy resource management system

The violation of information privacy in Smart Grids can be a significant barrier to customers' participation. Employing privacy protection models such as K-anonymity in a Smart Grid implementation adds desirable privacy guarantees. This work provides an approach to applying the Mondrian algorithm to ensure data within the system excludes Personally Identifiable Information. Results suggest that a dynamically generated generalization hierarchy minimizes information loss incurred by the anonymization process.
Letter frequency analysis of proprietary prescription drug names in the United States: Minding the Zs and Qs

Proprietary or brand names of prescription drugs are generally with letters that are unusual in common English. There is little academic research exploring if this perception is true, despite the fact that manufacturers pay millions of dollars to research and develop drug names that conform to regulatory standards while remaining marketable. To assess the extent to which letters used in prescription drug names may deviate from common English and to test if prescription drug names show measurable trends in letter frequency over time. The names of all prescription drugs approved in the United States between 1985 and 2020 were downloaded. Duplicates were removed and products without a proprietary name were excluded. Letter frequency analyses were then conducted on all letters in these names as an aggregate and year-over-year. Letter frequencies were compared to a validated academic reference, a corpus derived from all Google Books data, and the scoring system from the board game Scrabble. Regardless of the comparator, prescription drug names use letters that are not common in typical English. Letters A (11.96% of all observed letters), V (3.08%), X (2.31%), and Z (1.91%) are all overrepresented in prescription drug names, while E (10.23%), H (0.90%), T (6.30%), and S (4.21%) are underrepresented. The letters C and N are becoming less common over time (frequency decrease of 0.10 percentage points and 0.12 percentage points per year, respectively), while V, Y, and Z are becoming more common (frequency increases of 0.61 to 0.86 percentage points per year). Proprietary prescription names use letters that are unlike words used in everyday American English, and there are measureable trends in letter selection. It remains to be seen how drug manufacturers will cope with an increasingly-narrow naming space as more products continue to be approved over time.
Unitary rotation of pixellated polychromatic images

Unitary rotations of polychromatic images on finite two-dimensional pixellated screens provide invertibility, group composition, and thus conservation of information. Rotations have been applied on monochromatic image data sets, where we now examine closer the Gibbs-like oscillations that appear due to discrete "discontinuities" of the input images under unitary transformations. Extended to three-color images we examine here the display of color at the pixels where, due to the oscillations, some pixel color values may fall outside their required common numerical range [0, 1], between absence and saturation of the red, green, and blue formant color images.
Features of labor activity motivation in management psychology

In the article the authors consider the conditions, regularities and contradictory emergence of motives of labor activity. The article is devoted to the leading professional motives, peculiarities of the work motivation and psychological support of professional activity.
Development of a Real-Time Simulator for a Semi-Autonomous Tele-Robot in an Unknown Narrow Path

This study proposes a teleoperation system for assistive controlling of the movement of a mobile robot in a narrow path. The teleoperation system is created by combining data from real and virtual devices. In CoppeliaSim we applied the Braitenberg algorithm and the open motion planning library module (OMPL). The Braitenberg algorithm is a sensor-based automatic motion designed to aid the robot operator in maneuvering through the narrow path. While the OMPL is used to create a path for the operator to control the robot in narrow paths or intersections within a narrow path, the simulation uses a virtual proximity sensor to fulfill the Braitenberg algorithm requirement. With dynamic simulation a laser rangefinder obtains the environmental data and displays it on the simulation screen. The simulation scene is subjected to the virtual proximity sensor and the Braitenberg algorithm is applied to the simulation scene. Afterward, simulation scripts are written to incorporate the linear and angular velocities into a robot operating system for real-time robot control. The results showed that the system was capable of combining real-time dynamic simulation with the real world. Furthermore, the proposed system could aid the operator in narrow path environments while avoiding collision.
Analysis of Argumentation Form Changes in High School Students' subject inquiry essays

Objectives The purpose of this study is to understand the change in argument form through the results obtained after applying the subject inquiry essay to actual school classes.&#x0D; Methods To this end, a subject inquiry essay was conducted on 30 first grade high school female students sampled through the stratified random sampling method, and the argument format of the resulting essay text was analyzed. The students' essay texts were analyzed with frequency and correlation using the SPSS 28.0 program, establishing an analysis frame and analysis criteria based on whether or not the 4th level components of the OREO Map were included.&#x0D; Results The results are as follow. First, the subject inquiry essay showed differences according to the argument form elements. Second, it was confirmed that subject inquiry essay represents a stage with a high level of argumentation form. Third, in the learning of the argument form according to the session, it was found that the components of the argument form increased from the first to the third session. Fourth, it was found that the level of argumentation significantly improved in the learning of the argument form for each session. That is, subject inquiry essay is effective in the development of argument form elements and the development of argument form elements and levels according to the session. This suggests that subject inquiry essay is effective in learning argumentation form. In addition, although there was a difference in the correlation between elements of the argument form, it was found that the correlation of elements of the argument form improved as the number of sessions increased.&#x0D; Conclusions The results of this study will serve as a basic study to confirm the effect of argumentation-form learning in subject inquiry essays.&#x0D;
Lean-Agile Development Tools

This chapter introduces Agile development approaches commonly used in software development and explains how these tools can be used with the learning engineering process. Agile was originally coined in February 2001 by a group of software engineers who were tired of seeing software development projects fail. Lean principles are all about removing delay and waste, which is defined as any action or step in a process that doesn’t add value to the customer. In larger companies or institutions, the coordination of multiple Agile teams can be daunting. Agile teams are designed to be driven by the team members, thereby challenging many long-held governance, budgeting, and release planning processes, along with top-down decision-making. It briefly introduce concepts, roles, and activities typically seen in organizations that use Lean-Agile methods. The overall effort is expected to span more than a two-week sprint for development and requires a healthy runway of research preceding the start of development.
Advanced Mathematics in Vocational Universities

Science and technology are advancing at a breakneck pace. Only individuals with strong mathematical skills and knowledge will be able to adapt to social development and progress. However, advanced mathematics education is often neglected in vocational universities. Student and conceptual factors are invariably to blame. Therefore, it is urgent to improve the teaching quality of advanced mathematics in vocational universities. In improving the teaching quality, it is necessary to change the teaching mode, advocate interest in learning, emphasize on the cultivation of students’ skills during teaching, implement stratified teaching, lay emphasis on mathematical models, and strengthen the evaluation and assessment of students.
GUI Based Optical Character Recognition using Neural Networks

The Optical Character Recognition (OCR) process means the transition from examined primer or written images to a machine- adjudged document. The American Standard Code for Information Interchange (ASCII) in cognitive processing uses OCR. The challenge is two primary clans word segmentation by letters and character recognition. Apply a new approach to include the two functions by Scale-Invariant Transforming Feature (SIFT) descriptors. To compare SIFT descriptors (RootSIFT), construct a new procedure, that offers outstanding results without accelerating calculation or repository conditions. In order to identify English characters, proposed system suggests that the reverse propagation neural network for bracket of character be employed. Conducted trials with further than 10 expedients aimed for every character and tried the delicacy for numerical figures, map letters, small letters, and alphanumeric symbols. The interpretation analysis of optimized neural network algorithm has attained an outside.
Single Image Super-Resolution Algorithm based on Fixed-Point Multi-Model Gaussian Process Regression

Abstract To solve the problem of large amount of computation in matrix inversion of Gaussian process regression model, a super-resolution algorithm based on local Gaussian process regression of fixed point multi-model is proposed. Firstly, the training samples are classified by Gaussian mixture model, and image patches are randomly selected as fixed points in each type of training samples, and its K nearest neighbor patch are searched. Secondly, local Gaussian process regression model by using its low-mid-frequency components and the corresponding high frequency components. Again, low resolution test image patch is classified, only the K nearest neighbor test image patch is searched during reconstruction. And then, find the nearest fixed point in each kind of image patch, and use the local Gaussian process regression model based on the fixed point to predict its corresponding high-frequency component. Finally, corresponding high frequency information is predicted by using this trained model, which improves the reconstruction efficiency. Experimental results have demonstrated that the proposed algorithm is superior in both quantitative and qualitative aspects against other algorithms.
Distributed Morphology

In this paper we aim to explain and illustrate the theory of Distributed Morphology for non-specialists. The goal is to take away any misunderstandings and to provide some illustrations of the workings of the theory, mainly on the basis of data from Dutch. Distributed Morphology is a theory of morphology that embraces the so-called Separation Hypothesis: derivation – the forming of a new word by some abstract operation – is separated from affixation – the realization or spell-out of the abstract operation by the addition of some phonologically specified element. The means used by DM to implement the Separation Hypothesis is by late (after syntax) insertion of affixes. Furthermore, Distributed Morphology claims that there is no separate component of the grammar where word-formation takes place. The operations that form new words are the same operations that may create syntactic phrases. Starting from these fundamental claims, we go into some detail of the way Distributed Morphology accounts for different morphological patterns. The paper also points at some cognate, but alternative, approaches to word-formation and inflection. In particular, we briefly address Borer’s so-called exo-skeletal model, and the nanosyntactic approach.
An Action Research on Citizen Participation in the Establishment of the National Museum Complex of KOREA Children's Museum Based on Public Service Design: Focused on Participatory Public Service Policy Design Group

This study is an action research to examine operation process of the Participatory Public Service Policy Design Group in the National Museum Complex of KOREA Children's Museum. It is the perspective of public service design and to explore the role of citizens and civic participation.&#x0D; In this study, participants in the study selected children, parents, and teachers through a purposive or judgmental sampling based on the application for participation. By adding service designers and public officials, the triangulation technique was used so that various stakeholders could participate.&#x0D; As a result of the analysis of the study, it was confirmed that citizens who participated in the museum construction process recognized themselves as co-producers of public services and played an active role as citizens. It led to the following deductions and conclusions. ① Citizens should be able to actively participate from the establishment process of the museum. ② Policy providers and consumers must achieve balance and mutual communication. ③ The social justification and consensus must be reached for citizens to participate as users and co-producers of the museum. ④ It is necessary to view the establishment of a museum as a cultural activity and expand it to include society, region, and community. This study is meaningful in that it analyzes the museum establishment process and citizen participation from the point of view of public service, and reflects the suggested opinions in the field.
The electroweak standard model

After introducing the basic symmetry principles, the full Lagrangian is derived in detail and the most relevant aspects of the electroweak phenomenology are discussed with special emphasis on the determination of the input parameters and the consistency checks of the model.
Experimental Control of Thermal Processes Inside the Datacenter

Optimizing the thermal processes inside data centers in order to reduce the energy consumption and lowering the environmental footprint was always a big challenge.Finding solutions to improve the current cooling system and reduce the energy inefficiency can be achieved with various approaches.The purpose of this work was to improve the thermal processes in the INCDTIM’s data center by developing a smart cooling system that provides localized cooling when and where is needed. For this, experimental methods were used, implementing both, passive solutions (pipes, optimizations of the plenum) and active solutions (active grills for more efficient air control, remote control automation). First, we started from a 3D model of the data center, followed by the simulations of the actual thermal conditions in Ansys CFD (Computational Fluid Dynamics) software module. These simulations identified the problems, and the cold pockets and provided a tool to deliver a finite product that will significantly improve the cooling system. After this, a comparison was made with the improved thermal conditions in order to prove that the physical model matches the theoretical one. After that, the automation needs to be built in order to control the thermal processes. The experimental connection of the PLC to a cloud-based platform aims to monitor and control the thermal processes in the Cloud.