Reviewerly/exHarmony huggingface dataset:
THE USE OF SMALL GROUP DISCUSSION IN IMPROVING STUDENTS’ READING COMPREHENSION (A STUDY CONDUCTED AT SMP NEGERI 1 LANGOWAN)

The purpose of this research is to found out whether or not small group discussion could improve students’ reading comprehension through pre experimental design with one group pre-test and post-test design as quantitative research. The data collection in this research consists of 10 essay questions with 2 points for each question and 20 points for total point of the questions. The subject of this research was the eighth students in SMP N 1 Langowan which consisted of 20 students. This research is conducted during pandemic of Covid-19 so it is held online with using social media and video call to ensure students and teacher health following the health protocol to minimalized physical interaction and to make sure parents and students feel save in their house but still maintained to make sure students were focus in their online class meeting. The data of this research are analysed statistically using mean score formula. The result in this study shows that the score of the post-test is higher than the result of the pre-test. The mean score of the pre-test is 42,5 and in post-test is 77,5. It could be concluded that Small Group Discussion is effective to improve students’ reading comprehension on narrative text.
MDF-Net: A Multi-scale Dynamic Fusion Network for Breast Tumor Segmentation of Ultrasound Images

Breast tumor segmentation of ultrasound images provides valuable information of tumors for early detection and diagnosis. Accurate segmentation is challenging due to low image contrast between areas of interest; speckle noises, and large inter-subject variations in tumor shape and size. This paper proposes a novel Multi-scale Dynamic Fusion Network (MDF-Net) for breast ultrasound tumor segmentation. It employs a two-stage end-to-end architecture with a trunk sub-network for multiscale feature selection and a structurally optimized refinement sub-network for mitigating impairments such as noise and inter-subject variation via better feature exploration and fusion. The trunk network is extended from UNet++ with a simplified skip pathway structure to connect the features between adjacent scales. Moreover, deep supervision at all scales, instead of at the finest scale in UNet++, is proposed to extract more discriminative features and mitigate errors from speckle noise via a hybrid loss function. Unlike previous works, the first stage is linked to a loss function of the second stage so that both the preliminary segmentations and refinement subnetworks can be refined together at training. The refinement sub-network utilizes a structurally optimized MDF mechanism to integrate preliminary segmentation information (capturing general tumor shape and size) at coarse scales and explores inter-subject variation information at finer scales. Experimental results from two public datasets show that the proposed method achieves better Dice and other scores over state-of-the-art methods. Qualitative analysis also indicates that our proposed network is more robust to tumor size/shapes, speckle noise and heavy posterior shadows along tumor boundaries. An optional post-processing step is also proposed to facilitate users in mitigating segmentation artifacts. The efficiency of the proposed network is also illustrated on the “Electron Microscopy neural structures segmentation dataset”. It outperforms a state-of-the-art algorithm based on UNet-2022 with simpler settings. This indicates the advantages of our MDF-Nets in other challenging image segmentation tasks with small to medium data sizes.
Development of leave information system and office travel costs in Private Hospital HR with scrum method

One of the needs for Human Resource Information System at private hospitals is a system for calculating official travel costs and the remaining leave for workers in private hospitals as one of the agency units under the corporation. Both guidelines for calculating official travel fees and for employee leave rights in private hospitals are still in the form of books and decrees signed by the director. The rules in the guideline for official travel fees and in the collective work agreement are include in the information system to calculate employee leave entitlements and official travel fees. The outbreak of the Covid-19 pandemic that hit during the last 1 year required changes in the handling of patients in all health facilities around the world. Changes in patient handling not only change health care procedures but also encourage function shifts in several hospitals. The shift in the function of the hospital to a special Covid-19 hospital also affects the information system that is already running in the hospital. One of the factors that influence information systems is requirement physical distancing and social distancing. The method used to minimize changes in information systems is the Scrum method. The Scrum Method was chosen due to the shorter time for system development and cost efficiency arising from the COVID-19 pandemic outbreak.
The Effects of Sports Sponsorship on Buying Response for Jordanian Fans

This study aims to investigate the effect of sports sponsorship activities on the buying behavior of sports audiences, in addition to determining the statistical differences in the level of sports sponsorship activities and the buying response according to some organizational and demographics. The research population consists of Jordanian sports audiences who live in Amman city. The Convenience sampling technique is used. The researcher selects the respondents from coffee shops, cafes, famous malls in Amman, and social media users. The recommended sample size is 385. The unit of analysis is the Jordanian who attended and watched the sports activities for up to 19 years living in Amman. The study concludes that sports sponsorship activities strongly positively affected the buying response “ATR” of the sports audience. It is found statistically significant differences in the awareness tend to males and B. A degree holder. It is also found that the age between 42 - 46 is the most experienced, but it is found that there are no differences between the sports audience segments in the repeated purchase stage. Finally, it is a statistically significant difference in sponsorship activities and tends to the telecom companies in Jordan. The study presents a set of recommendations that enhance using the sponsorship in the local sports market.
UJI EFEKTIFITAS METODE FUZZY LOGIC MAMDANI PADA PENERIMAAN BEASISWA BANTUAN MENGGUNAKAN MATLAB

One of the supporters in creating an even educational climate is the existence of scholarships. In general, scholarships in the form of financial assistance intended for the community of higher education, both lecturers, teachers, students and students. In the awarding of scholarships, some findings were obtained, including not being on target which caused the scholarship assistance to be ineffective. One solution in determining the acceptance of scholarships is the existence of a system that is integrated with decision-making methods. Fuzzy logic mamdani becomes one of the recommendation methods that can be implemented in decision making. So the formulation of the problem of this research is (1) How is the implementation of fuzzy logic mamdani methods to the decision-making system of receiving aid scholarships?; (2) How effective fuzzy logic methods mamdani to the decision-making system of aid scholarship. The scope of the research is (1) The method of inference with Fuzzy Logic Mamdani; (2) The tools used are Matlab version R2021b; (3) The input variable criteria consist of parental income, achievement (academic and non-academic) and average grades throughout the semester; (4) The variable output criterion is the amount of the scholarship. The final results of the study resulted in the calculation of the effectiveness of the Fuzzy Mamdanil Method of more than 50%, so that the fuzzy mamdani method can be recommended as an alternative in the decision-making method determining the amount of acceptance of aid scholarships.
Innovative interactive technologies in the training of professional education specialists by means of digital technologies

This article is devoted to the study and analysis of the role and influence of innovative interactive technologies in the training of professional education specialists using digital technologies. Digital technologies are becoming an increasingly integral part of our daily lives and impacting various fields, including education. The article examines the modern foreign and domestic experience of using modern innovative interactive technologies in the professional training of future vocational education specialists. The possibilities of implementing augmented reality (AR) and virtual reality (VR) to create immersive learning environments are described. Emphasis is placed on adaptive educational platforms that are able to individualize the educational process taking into account the personal needs and individual characteristics of students. The analysis of the influence of interactive technologies on the activity and interest of students, increasing the level of involvement and motivation to study was carried out. The advantages of these technologies in the training of specialists are analyzed, their impact on student motivation, understanding of complex concepts and the creation of interactive learning environments is noted. It highlights how the adaptability of learning platforms helps create personalized learning paths for each student, taking into account their needs and pace of learning. The experience of using innovative and interactive technologies in various fields, including education, science and technological development, is outlined.&#x0D; The results of the study indicate the importance of integrating digital technologies into the educational process to achieve more effective learning and development of relevant skills among students of vocational education.
The Impact of Cognitive Differences on Processing COVID-19 Data Visualizations

This study explored the impact of people’s working memory capacity (WMC) on COVID-19 real data visualization (DV) processing when DV is represented (a) as counts versus percent growth, and (b) with COVID-19 related versus unrelated seductive details versus no details. 70 undergraduates of US university explored six stimuli each comprising two DVs, one question, and four answer options. Additionally, they completed ACCES test of reading span (rspan), visuospatial span (sspan), and operations span (ospan). The following novel approach was proposed that leverages eye movement data for understanding people’s visual processing. First, gaze-maps were created as color-based probability distributions of people’s eye fixations on regions for each stimulus. They were saved as images and clustered with Agglomerative algorithm of unsupervised machine learning. Two, three, and four hierarchical clusters were identified as different types of people's attention distributions. The examination of images in two-cluster model revealed that people’s attention was relatively more distributed around DVs and less around verbal sections in cluster 1 as opposed to cluster 2. More clusters specified around which DVs and verbal areas attention was relatively more distributed. Second, multiple mixed-effects logistic regression analyses were performed with rspan, sspan, and ospan scores as predictors of the clusters for different DV representations. The findings indicated that people's WMC was significantly associated with different clusters of attention distribution. Specifically, there were higher chances that people with higher visuospatial WMC had their attention distributed around (a) DVs, when they were represented with COVID-19 related seductive details, or data was represented as counts, and (b) verbal areas, when DVs were represented with COVID-19 unrelated seductive details. On the contrary, people with higher operational WMC had their attention distributed around verbal areas, when data was represented as percent growth. The proposed method motivate designing personalized technologies sensitive to the differences in users’ WMC.
Pemodelan Numerik Hubungan Pola Curah Hujan Wilayah Equatorial di Pulau Sumatera Terhadap Fenomena ENSO dan IOD

A numerical modeling has been built for the relationship between rainfall in the equatorial region of Sumatra to the ENSO and IOD phenomena by taking data from 1991 to 2020 at three stations located in the western region of Sumatra Island, namely SM Japura, SM Minangkabau and SM Hang Nadim. The method used in this study is the method of correlation and linear regression on the Niño3.4 Index variable and the Dipole Mode Index on the amount of rainfall. The data visualization process is carried out with the output in the form of plots and graphs with Goole Colab coding. The resulting graph is a graph of the ENSO and IOD phenomena, as well as a regression graph between The Niño3.4, DMI and the amount of rainfall per month. This study was conducted with the aim of knowing how much influence the El Niño Southern Oscillation (ENSO) variable represented by the Niño3.4 Index and the Indian Ocean Dipole (IOD) represented by DMI had on rainfall in the equatorial region in the 1991 – 2020 period and to see the trend of significance between the two towards the equatorial region on the island of Sumatra. Rainfall in Indonesia's equatorial region tends to be influenced by IOD compared to ENSO. The combination of the two at the same time can cause a significant change in the amount of rainfall. La-Niña and negative IOD occurred in 1992, 1996, 1999, 2000, 2005, 2008, 2011 and 2016. The average rainy day index (SDII) tended to decrease in Japura Island in 1996, 2005, 2011, 2016 , at SM Minangkabau in 1992, 1996, 1999, 2000, 2016 and at SM Hang Nadim in 1996, 1999 and 2008. Meanwhile the longest series of wet days tended to decrease in SM Japura in 1992, 1996, 1999, 2005, in SM Minangkabau in 1992, 1996, 2005, 2008, and in SM Hang Nadim in 1992, 2000, 2005, 2008 and 2011. The longest series of dry days tended to increase in SM Japura in 1996, 2011, in SM Minangkabau in 1996, 2000, 2011, and at SM Hang Nadim in 1996.
Tantangan Orang Tua dalam Membimbing Anak Selama Belajar Daring

This study aims to address the challenges faced by parents and strategies to overcome the difficulties associated with online learning. The motivation for this research comes from the increasing number of parents encountering obstacles in guiding their children's education amidst the prevalence of online learning, particularly during the pandemic. Employing a qualitative approach, this study utilizes a case study method to investigate the difficulties encountered by parents and explore potential solutions. Informant selection is conducted through purposive sampling, involving both parents and teachers. Primary data is collected through various means such as observation, interviews, and documentation studies. To ensure data validity, triangulation is employed, and data analysis encompasses techniques such as data reduction, data presentation, and drawing conclusions. The research findings reveal that parents employ several strategies to mitigate online learning challenges, including accompanying and supervising their children, creating a conducive study environment, providing regular reminders for completing tasks, sourcing supplementary learning materials, maintaining communication with teachers, balancing household responsibilities with assisting children, and optimizing teaching opportunities. While this research primarily focuses on parents' perspectives, it acknowledges that children also face difficulties during online learning.
Embracing FAIR Data on the Path to AI-Readiness

Key principles of data management achieved via FAIR implementation can have positive effects on many aspects of R&amp;D, from workflow efficiency to collaboration to costs. While machines offer incredible benefits in terms of the speed and scale at which they can process data, they lack the judgment, intuition, and contextual understanding that humans bring to the table. Making data FAIR is in essence making them more accessible to machines and humans alike.
How does color distribution learning affect oculomotor selection?

The visual world is rich and complex, but it also contains many statistical regularities. Previous studies have shown that our perceptual system can encode surprisingly detailed information about feature distributions. For example, such feature distribution learning has been demonstrated in visual search tasks, where observers learn the distribution that distractors from consecutive visual search trials are drawn from. Their ability to find the target on a subsequent test trial depended on the distance between the current target feature and the distractor distribution on preceding trials. Response times were slowed if the target feature was drawn from the previous distractor distribution and reflected the shape of the distribution. These studies have typically assessed search performance through manual responses. However, we suggest that eye movements can provide a complementary, precise and ecological measure of feature distribution learning. Here, observers were asked to make a saccade towards an oddly colored target among heterogeneous distractors, taken from either a Gaussian or uniform color distribution. Preliminary results revealed better search performance on learning trials when the color of the distractors came from a Gaussian distribution rather than a uniform distribution. Moreover, saccade latencies during test trials depended on the distance between the color of the current target and that of the previous distractor. Indeed, saccade latencies were slowed when the target color was within the previous distractor's color distribution. Saccade latencies did not, however, reflect the precise shape of the previous distractor's color distribution. Overall, our results suggest that previous distractor characteristics can guide gaze in visual search tasks, but further investigations are needed to determine whether the precise shape of the distractor distributions is taken advantage of.
Representation of an object through visual occlusion

We have strong predictions about what happens to an object when it becomes occluded during motion. Here, we used three separate tasks to examine the underlying mechanisms supporting object tracking through periods of occlusion. In the first experiment (n=21), we tested if accurate extrapolation of an object's position into the occluder was modulated by time. In each trial, an object moved horizontally before becoming occluded. Object movement was associated with a sound, traveling at one of three speeds. Behind the occluder, the sound stopped indicating that the object stopped moving. Participants indicated where the object stopped moving, revealing they consistently lagged behind the true object position. The error increased with occlusion time and faster speeds. Estimated positions and eye movements were highly correlated. In the second experiment (n=20), we tested whether spatiotemporal continuity could be perceived across occlusion. Starting at one velocity, the object became occluded and reappeared after occlusion. During occlusion, the object sped up, slowed down, or moved at initial velocity. The participant was asked if the object reappeared too early or too late. We found that participants were highly accurate at determining these speed modifications, suggesting continuity can be achieved regardless of poor representation during occlusion as observed in experiment one. One possibility for the disparity in performance between the first two experiments is that post-occlusion information is critical for bridging the occlusion period. We therefore asked participants in the third experiment (n=21) to estimate when the object reached the end of the occluder, beginning to re-emerge. We found consistently late estimation of object reappearance time regardless of object speed, indicating that post-occlusion information is critical to perceptual continuity. We provide evidence of brief extrapolation into the occluder without accurately bridging the entire occluder. When post-occlusion information is available, the occlusion period can be accurately reconstructed.
Eye Movements during Free Viewing and Scene Description are Similarly Directed to Objects Critical to Scene Understanding

Introduction: The extent to which eye movements are influenced by low-level saliency vs. other processes during free viewing of scenes (in the absence of any task) is debated (Koehler, 2014). Recent studies (Henderson et al., 2017, Peacock et al., 2019) suggest that eye movements during free viewing are directed to regions rated as semantically meaningful. Here, we compare eye movements during free viewing to those during a scene description, object search, and salient object search tasks. Methods: Two hundred participants were equally split across four conditions (free viewing, scene description, free viewing, object search, and saliency search) while viewing the same forty images. Images were presented for 2 seconds while eye position was measured. Objects within each image were categorized by independent raters on their relevance to the understanding of the scene and their saliency. Results: The mean correlation of fixation maps between free-viewing and scene description (r=0.67) was significantly greater (p<0.0005) than the correlation between free viewing and object search fixation maps (r=0.32) and greater (p<0.0005) than the correlation between free viewing and saliency search fixation maps (r=0.51). Participants fixated more frequently on objects that are relevant to scene understanding than other objects in the free viewing (fixation number difference=0.25, p<0.01) and scene description (fixation number difference=0.35, p=0.01). The target object was fixated on more frequently in the object search. There was a trend to fixate the most salient object over other objects in the saliency search but it did not reach significance (p=0.16). Conclusions: Our findings suggest that eye movement exploration during free viewing is most similar to a scene description task with fixations falling on regions that are important to understanding the scene.