Reviewerly/exHarmony huggingface dataset:
Menanamkan Motivasi Belajar Online dari Orang Tua melalui Seminar Parenting

Since being shocked by the corona virus / Covid-19. This virus has spread widely to various parts of the world including Indonesia. Until April, the Indonesian government announced a lockdown policy, namely completing all activities, which carried out settlements in worship activities, schools, offices, or universal facilities, social and cultural activities, modes of transportation, and other activities related to regional security, some of the mandatory requirements followed by regions following lockdown regulations. Courageous learning does not always go as desired, the problems faced by children are difficulty concentrating on learning and many school assignments. This can also cause a feeling of stress, boredom, and has the potential to cause depression in children, on the part of parents also have difficulties in accompanying their children to study at home, due to other responsibilities and difficulties understanding children's lessons and methods, also not understanding applications or features. which is used as a support for the brave learning process. However, in this regard, especially in Pangulah Utara Village, Kota Baru District, Karawang, where generally parents are not highly educated, there are certainly difficulties in this regard. These various obstacles need confirmation between teachers, students, as well as the cooperation between parents and children and parents and good teachers so that the learning process carried out at home can run as expected.
Seismic Soundoff: Searching for the perfect X-ray image of the earth

In this episode of Seismic Soundoff, Neelsh Neelamani traces the history of the seismic method to showcase recent breakthroughs and future advancements.
Editor’s Letter

1. Hossein Kazemi 1. Editor-in-Chief In March 2021, Goldman Sachs announced that Bitcoin is a new asset class, and, for the first time, it was “officially” included in the firm’s asset allocation recommendations. If one agrees with this statement, the next step is to examine Bitcoin’s
An Analysis of Questions in History Textbooks to Develop 'Questions Reflecting the Characteristics of History Subjects' and Its Implications -Focusing on Unit 4 of Middle School 'History' based on the 2015 National Curriculum-

This study aims to analyze the questions in history textbooks based on the 2015 national curriculum, to suggest the direction of improvement for those who develop textbooks based on the 2022 national curriculum. To this end, I analyzed questions in "Imperialist Invasion and Nation-State Construction Movement(unit 4)" in the middle school history textbooks based on the 2015 national curriculum. As a result, the questions in the current textbook were less consistent with the curriculum and focused on memorizing historical facts rather than exploration. It tried to present various types of questions, although the function of guiding information was stronger than asking questions. However, problems such as the mismatch between source data and questions, the loss of the function of data or questions, and the ambiguity of sentence statements were also found. Based on the above, it can be said that the questions in the history textbook should reflect the aims of history learning and the characteristics of the history subject as follows. First, it is necessary to emphasize the exploration process of analyzing sources to find clues to problem-solving. Second, questions that can reveal the constructive and interpretative characteristics of history should be presented. Third, it should be considered that questions in the history textbook reflect temporality.
Zur Syntax der polnischen Leichten Sprache

Summary Easy Language as a means for communicative accessibility is designed for use by people with communication impairments and low literacy skills in general, e. g. persons with intellectual disability, functional illiterates or individuals with dementia. Compared to standard written Polish, the complexity of this variety is reduced on all linguistic levels. The present article deals with the level of syntax and follows on from a previous study concerning the syntax of Easy-to-read Russian. It aims to contribute to the linguistically substantiated elaboration of Easy-to-read Polish by submitting suggestions for avoiding complex syntactic structures. Various subgroups of clause constructions and complex sentences are included. It turns out that the endeavour to make sentences as short, simple and comprehensible as possible is quite complex and certainly not easy. The presented suggestions await further discussion among linguists as well as systematic testing with target groups of Easy-to-read Polish. Since Easy Language has been implemented in Polish legislation, it is to be expected that this fact will result in an amplification of Easy-to-read text offers in the future. Therefore, there is a need for more intensive research in the field of Easy Language that can be seen as crucial in enabling people with disabilities and other persons with reading difficulties to fully enjoy the fundamental right to information and participation in social life.
Databases and Data Sets of Medical Image Processing and Neurology

Databases and Data Sets of Medical Image Processing and Neurology
The Stock Price Prediction Formula Using the Concept of Equality in the Amount of Data Between the Average Difference of Order One and Two at Levels n and n+1

Technological developments are getting faster, as is the dissemination of existing information, especially on the capital market. In order for investors to avoid losses from the capital market, a method is needed that is able to analyze the movement of the stock price. This study focuses on the application of the Data Scales Analysis (DSA) method which uses a formula with the concept of the same amount of data between the first and second order average differences at levels n and n + 1 for predicting the stock price of issuers, in predicting stock prices in the capital market. The resulting formula is named JIC-FLY 2 which is a new formula used to predict stock prices in the capital market. The population used in this study are issuers who are members of IDX 30 from the banking sub-sector with the sample used is the issuer of BBCA (PT Bank Central Asia Tbk). The results of this study note that the DSA method with this formula is able to produce the best predictive value, namely DSA 12 with an error percentage of 0.035%.
Rewriting and Redefining the Aspects of Marketing with Metaverse – A Brief Insight

Purpose : With the emergence of the new technological innovation – ‘Metaverse,’a fundamental change has been witnessed in the marketing arena with a deeper connection and inclusive experience. For marketers, the metaverse has opened up opportunities that are extremely exciting for sales and marketing. The current study is a short communication that gives a glimpse of the new marketing aspects in the metaverse that have generated fresh routes toward commerce and creativity. Design/Methodology/Approach : The current study delivered a perspective of marketing with the metaverse. Scholarly articles about this aspect were reviewed and interpreted, along with recent reports on the real business of the virtual world. Findings : The study revealed that marketers could capitalize on the metaverse, which has enlarged the breadth and depth of customer experience. Furthermore, the facets of the metaverse have provided a deeper knowledge of the preferences and behavior of customers. Practical Implications : With changing consumer behavior, the metaverse has rightly catered to the needs and demands of customers through an immersive experience. The metaverse has successfully facilitated the self-sustaining loop that has driven brand affinity for companies. Moreover, metaverse-specific marketing techniques have enhanced the strategic positioning of marketing divisions. Originality/ Value : The paper has delved deep into understanding the realistic interactions in marketing through the metaverse that are meticulously designed to stimulate customers’ emotions. The study’s insights inform about the greater personalization aspect of marketing in the metaverse that can strengthen the relationships with customers as well as the overall margins.
Semantic Regions of Interest Applied to Adaptive Image Compression, Color Enhancement, and Automated Pan-and-Scan

One of the most challenging problems in computer vision and image processing is the detection of the semantic regions of interest (SRoIs). In this article, we propose a method using OpenAI’s contrastive language-image pretraining (CLIP) model to find SRoIs by performing a semantic search for objects in the image that are detected by an object detection model called generic RoI extractor (GRoIE). Finding the SRoI can be used in different image-processing tasks such as image and video compression, enhancement, and reformatting. By knowing the SRoI within images, we can improve the visual quality of images by compressing the more important parts with higher quality and the less important parts, such as the background, with a lower quality. This operation can be achieved without changing the overall compression ratio and the peak signal-to-noise ratio (PSNR) quality metric. Finding the SRoI can make the processes of image enhancement and color correction more accurate by focusing only on the important parts. Moreover, in the image reformatting process, the important parts of the image may be lost. But by using the SRoI, we can reformat the image in a better way by keeping the regions within a frame that draw the greatest audience attention.
Problems and Improvement Plans of the Korean History Test in College Scholastic Abilities Test

In this paper, we looked at the background of Korean history becoming essential in the College Scholastic Ability Test(CSAT) and the problems in the process. Against the background of strengthening history education, they compromised by easily taking tests with the aim of reducing private education costs. In the question of fairness of tests, the reduction of private education costs is very important. This is especially true when university entrance exams show a fierce competition rate like in Korea. However, in order to protect this fairness, it is necessary to overcome the reality that the form of a national selection test, which requires high-level thinking skills of history and shows the dignity of a country, loses its "classity" that even mocks examinees. Attempts to exclude the Korean history test from the function of placing importance on the discrimination ability of the university selection test are a measure that does not recognize reality. To this end, the purpose of the CSAT Korean History Test should be changed to the purpose of the university selection test like other subjects, and questions faithful to the high school curriculum should be developed as important and key contents. The purpose of the current CSAT Korean history test is not just "easy" with a rating system, and considering the increasingly difficult test, it will have to be a test that only represents the reduction of private education costs.
Wafer Eccentricity Deviation Measurement Method Based on Line-Scanning Chromatic Confocal 3D Profiler

The wafer eccentricity deviation caused by misalignment between the center of the wafer and rotary table will lead to edge image distortion and quality degradation of the defect signals during automated inspection. However, wafer end jump and edge topography change will bring great challenges to the accurate measurement of micrometer deviations. A new wafer eccentricity deviation measurement method based on line-scanning chromatic confocal sensors (LSCCSs) is proposed. Firstly, the LSCCS with Z-axis submicron resolution used in the experiment acquires the 3D profile height of the wafer edge as the turntable rotates, and the edge distance is calculated at each rotation angle. Secondly, a robust Fourier-LAR fitting method is used to fit edge distance serial to reduce sensitivity to outliers. Finally, the wafer eccentricity deviation that is equal to the wafer center coordinate can be calculated using the wafer eccentricity deviation model. In the simulated experiment, the results show that the eccentricity deviation measurement accuracy was insensitivity to noise and reached the micron level. Additionally, the measurement uncertainty of eccentricity deviation coordinate Xw,Yw was (0.53 µm, 1.4 µm) in the actual data of the 12-inch wafers.
A Fast-Dehazing Technique using Generative Adversarial Network model for Illumination Adjustment in Hazy Videos

Haze significantly lowers the quality of the photos and videos that are taken. This might potentially be dangerous in addition to having an impact on the monitoring equipment' dependability. Recent years have seen an increase in issues brought on by foggy settings, necessitating the development of real-time dehazing techniques. Intelligent vision systems, such as surveillance and monitoring systems, rely fundamentally on the characteristics of the input pictures having a significant impact on the accuracy of the object detection. This paper presents a fast video dehazing technique using Generative Adversarial Network (GAN) model. The haze in the input video is estimated using depth in the scene extracted using a pre trained monocular depth ResNet model. Based on the amount of haze, an appropriate model is selected which is trained for specific haze conditions. The novelty of the proposed work is that the generator model is kept simple to get faster results in real-time. The discriminator is kept complex to make the generator more efficient. The traditional loss function is replaced with Visual Geometry Group (VGG) feature loss for better dehazing. The proposed model produced better results when compared to existing models. The Peak Signal to Noise Ratio (PSNR) obtained for most of the frames is above 32. The execution time is less than 60 milli seconds which makes the proposed model suited for video dehazing.
Abstract 4191: Assessing performance of biomarker extraction from electronic health records: Data augmentation methods for a hierarchical self-attention network (HiSAN)

Abstract Background: Extraction of HER2 status from electronic health records (EHR) may expedite clinical trials matching and be used for survivorship research. Deep learning (DL) algorithms have potential to extract this data; however, inherent class imbalance leads to reduced model performance. We compare state of the art strategies to handle class imbalance in models trained to extract HER2 status. This comparative analysis may be used as a guideline for HER2 extraction. Methods: 680,117 pathology reports collected from 2017-2021 by the National Cancer Institutes’ Surveillance, Epidemiology, and End-Results (SEER) program were used for this study. Pathology reports are manually labelled by cancer registrars as HER2 -, HER2+, or Unknown (class ratio 65%, 11%, 24% respectively). We compare six data augmentation (DA) methods: balanced frequency weighting, ROS while up-sampling HER2+ by 595%, RUS while down-sampling HER2- by 83%, SMOTE, ADASYN, and SMOTE-Tomek. As a comparison we consider the HiSAN model i.e., a DL architecture currently used by SEER for automatic classification of reports. Result: Applying DA strategies did not improve the performance of the HiSAN model (Table 1). Frequency based class-weighting (Acc=0.78), ROS (Acc=0.81), and RUS (Acc=0.80) perform worse than the baseline model, suggesting simple data augmentation methods do not boost performance for this task. Advanced oversampling with SMOTE (Acc=0.88) and ADASYN (Acc=0.88) perform better than simple approaches, but do not improve the predictive accuracy of the baseline HiSAN. Conclusion: Common DA methods do not improve the performance of the HiSAN biomaker method. While the overall accuracy of the baseline HiSAN model is quite high, other methods for improved accuracy should be explored. Table 1. Method Accuracy (Acc) Sensitivity Specificity Precision HiSAN (Baseline) 0.8898 0.7583 0.8944 0.8507 Frequency class weighting 0.7826 0.8033 0.8932 0.7040 Random Over Sampling (ROS) 0.8057 0.7672 0.8883 0.7130 Random Under Sampling (RUS) 0.8042 0.7883 0.8930 0.6902 Synthetic Minority Oversampling Technique (SMOTE) 0.8796 0.7341 0.8827 0.8340 Adaptive Synthetic Sampling (ADASYN) 0.8764 0.7467 0.8863 0.8142 SMOTE-Tomek 0.8823 0.7620 0.8956 0.8200 Citation Format: Shalini Priya, Alina Peluso, Mayanka Chandra Shekhar, Ioana Danciu, Jordan Miller, Heidi A. Hanson. Assessing performance of biomarker extraction from electronic health records: Data augmentation methods for a hierarchical self-attention network (HiSAN). [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4191.
Is Bitcoin Exciting? A Study of Bitcoin’s Spillover Effects

In this study, we examine the cross-excitation effects of Bitcoin’s jumps and diffusive variations on traditional asset classes using high frequency data. For our cross-asset study, we detect the presence of positive jump spillovers from Bitcoin to risk assets and negative jump spillovers from Bitcoin to defensive assets. For our study on single name U.S. stocks, we observe a significant increase in positive jump and diffusion spillovers from Bitcoin to U.S. stocks in the post-COVID19 era. For instance, only 0.3% – 0.4% of U.S. companies were excited by Bitcoin’s jumps in the pre-COVID19 era, compared to 9.6% – 10.4% in the post-pandemic period. Furthermore, we find that companies most exposed to blockchain and cryptocurrency technologies (BCEs) were most susceptible to Bitcoin’s spillover risks, with an average increase in sensitivity of 12.3% to Bitcoin’s jumps, and an average increase in sensitivity of 4.5% to Bitcoin’s diffusive variations.
A Validation Study on the Children's Playfulness Scale (CPS)

The purpose of this study was to validate the Children's Playfulness Scale (CPS) produced by Barnett (1990 and 1991), which is used to find out playfulness for Korean children. To this end, each class teacher measured the playfulness of children with a Children's Playfulness Scale (CPS) for 214 Korean children. The collected data were statistically processed with the SPSS 25.0 program and the AMOS 26.0 program. As a result of the analysis, Barnett's (1990 and 1991) Children's Playfulness Scale (CPS), which was translated into Korean, can be used by teachers to see and measure playfulness as one factor rather than looking at playfulness for children by factor. In order to measure the playfulness characteristics of each factor, it is necessary to modify and supplement the contents of the questions through research on content validity, and then check the convergence and discriminant validity.
‘The Limitations of Stylometry’: Unconscious Versus Conscious Use of Frequent Words

A PREVIOUSLY published note, ‘Titus Andronicus: Peele, Shakespeare, Peele’ shows that the final scene of the play was composed by the same author as the first scene, George Peele.1 Table 1 of the note shows that the first 5,000 words and the last 4,854 words of Titus Andronicus have similar relative frequencies of and. These two sections of the play are sorted in the table between the two whole plays, Peele’s David and Bethsabe and The Battle of Alcazar, that have the highest percentages of and out of the forty tabulated plays. While the first 5,000 words of Titus are now accepted as Peele’s, the last 4,854 have been in the past ascribed to Shakespeare along with the ten thousand words of the intervening body of the play. Macdonald Jackson chose and as a criterion for determining authorship in Titus Andronicus, later endorsed by Brian Vickers.2 Also among Hugh Craig and Arthur Kinney’s fifty-five best marker words for distinguishing Shakespeare and Peele, the words and and thy were at the top of the list ‘of the words that Peele uses more than Shakespeare’.3
SeSDF: Self-evolved Signed Distance Field for Implicit 3D Clothed Human Reconstruction

We address the problem of clothed human reconstruction from a single image or uncalibrated multi-view images. Existing methods struggle with reconstructing detailed geometry of a clothed human and often require a calibrated setting for multi-view reconstruction. We propose a flexible framework which, by leveraging the parametric SMPL-X model, can take an arbitrary number of input images to reconstruct a clothed human model under an uncalibrated setting. At the core of our framework is our novel self-evolved signed distance field (SeSDF) module which allows the framework to learn to deform the signed distance field (SDF) derived from the fitted SMPL-X model, such that detailed geometry reflecting the actual clothed human can be encoded for better reconstruction. Besides, we propose a simple method for self-calibration of multi-view images via the fitted SMPL-X parameters. This lifts the requirement of tedious manual calibration and largely increases the flexibility of our method. Further, we introduce an effective occlusion-aware feature fusion strategy to account for the most useful features to reconstruct the human model. We thoroughly evaluate our framework on public benchmarks, demonstrating significant superiority over the state-of-the-arts both qualitatively and quantitatively.
Multimeowdality

The chapter ’Multimeowdality’ looks at the interplay of textual and visual elements in social media and approaches multimodality in computer-mediated communication (CMC) and computer-mediated discourse (CMD). Digital discourse has evolved from text-only discourse to multimodal interactions involving text, audio, video, and graphics. The chapter shows the CMC modes and semiotic modes used in multimodal interaction. Based on examples from cat-related digital spaces, it applies the faceted classification tool and the CMDA tool to describe communication on the interactive multimodal platforms. The chapter describes the various visual elements, such as photos, videos, memes, meme-like photos, GIFs, emoticons, emoji, and stickers, and discusses their functions in discourse.
Deformable registration of 3D CT images with partial liver

Multiphase contrast-enhanced computed tomography (CT) is a popular method used by radiologists to diagnose patients with liver diseases. The analysis of multiphase images may involve image segmentation and registration. While the latter can be addressed using traditional registration techniques, it can be proven difficult when dealing with sub-optimal acquisitions. In real conditions, a registration process not only needs to accommodate patient’s motion occurring between acquisitions but also the variation in the scanner field of view that changes between the acquisitions. Actually, each image acquisition acquired during an individual exam may cover different portions of the liver, resulting in full or partial liver scans. Partial liver scans present a challenge to registration methods that expect to see the same portion of the body in the input data. Such methods would tend to register partial liver volumes to full liver volumes, and as a result, misplace locations of internal liver landmarks. In this work we present a method that registers multiphase CT scans with partial and full liver while ignoring portions of liver that are represented only in one of the scans. We assess its performance and discuss its capacity to improve tracking of liver lesions across phases.