Reviewerly/exHarmony huggingface dataset:
Pengembangan Aplikasi Math Mobile Learning “Smartline” Menggunakan Adobe Animate pada Materi Garis dan Sudut Di Tingkat SMP

This study aims to design, develop, and produce media products in the form of math mobile learning applications assisted by Adobe Animate software about lines and angles that meet the criteria of validity and media practicality so that the media can be applied in the learning process of lines and angles. The type of research used is research and development (Research and Development) which refers to the ADDIE model. The stages of developing this model include Analysis, Design, Development, Implementation, and Evaluation. 35 students of class VII MTs NU Raudlatus Shibyan were the subjects of this study. The data collection instruments were material expert validation sheets, media experts, and user response questionnaire sheets. The results of the development research are: (1) the results of the validation of material experts and media experts produce media validity in the "Very Valid" category and a validity score of 82.5 and 83.5 respectively; (2) the results of limited trials and the field gave results of "Very Practical" in the practicality category and the scores were respectively 85.2 and 85.43333333. Based on the validity and practicality scores of the media, the learning media in the form of a mobile learning math application using Adobe Animate software is feasible to be applied as a learning media for class VII mathematics about lines and angles.
Flexible Work Agreements: Here to Stay but Uneven in Equity and Promoting Success

A Review of:Hosoi, M., Reiter, L., &amp; Zabel, D. (2021). Reshaping Perspectives on Flexible Work: The Impact of COVID-19 on Academic Library Management. portal: Libraries and the Academy 21(4), 695-713. doi:10.1353/pla.2021.0038 Objective – The article seeks to assess the current state and the future of flexible work agreements (FWAs) in research libraries. Design – The authors held semi-structured interviews with 31 individuals in library leadership roles. Setting – Large American or Canadian research libraries during the COVID-19 pandemic. Subjects – 31 individuals in senior leadership roles (ex: associate dean, director) at the top 50 research libraries in North America (based on the Association of Research Libraries Investment Index). Methods – Interviews were conducted and recorded over Zoom with participant, investigator, and note taker. Investigators developed a quantitative coding instrument based on a selection of the interviews, then coded all interviews independently. Coded data were evaluated for broader themes in a collaborative fashion. Main Results – All participants had employees working partially or fully remotely at the time of the interviews. Half of participants observed gains in productivity during the pandemic, although even more commented on technology challenges. Other positives included remote project success and more inclusive meetings; other negatives included caregiving and job duties that did not allow for remote work. Conclusion – While FWAs were widely available pre-pandemic, they were not normative. The majority of participants think flexible work will only increase in libraries and will influence recruitment and retention of employees, as well as utilization of library space.
The Central Bank of Iraq between Independence and Public Financial Dominance during 2005-2022

Although the Central Bank of Iraq enjoys independence in its administrative and financial affairs and in the formulation and implementation of monetary policies in general, in accordance with Law No. 56 of 2004, but the interventions of the legislative and executive authorities, and the presence of public finance dominance on monetary policy, put this independence in an ambiguous position. This research has tried to determine the degree of legal independence of the Central Bank of Iraq according to the (CWN) criterion and based on the Central Bank Law. At the same time, he worked on analyzing and presenting the working mechanisms of public financial dominance on monetary policy as an antithesis to independence. The research concluded that the independence status of the Central Bank of Iraq according to the text of the law differs from its actual status in terms of operation. In order to solve this problem, the research put forward a number of suggestions, the most important of which are: respect for the law of the central bank by all parties and a complete cessation of interference in its affairs, enhancing the level of coordination, consultation and exchange of views between the legislative and executive authorities and the central bank, which is permitted by law, as well as Work to reduce public financial dominance on monetary policy by reducing the general budget deficit and reducing dependence on oil export revenues, thus reducing the impact of these two financial variables on monetary variables and directing monetary policy.
Psychological content of the concept of subjective personal well-being

Introduction. The problem of subjective well-being of the individual is taking on added importance at the time of increasing tension of globalization, crises and armed conflicts. Aim. To determine the psychological meaning of the concept of “subjective well-being of a personality”. Methods. Theoretical research methods are applied: analysis, systematization, comparison and generalization, interpretation of modern theoretical and empirical research in Ukrainian and foreign psychology. Results. The article carried out a theoretical and methodological analysis of research on the problem of the subjective well-being of a personality, which showed that scientists considered this concept in the context of hedonistic, eudemonistic approaches, basing well-being on the basis of positive, resource-based functioning of the personality. It was found out that as they delved into the content aspects of the personality's well-being through the different contexts of the subject's existence and activity, researchers began to single out various constructs in the characteristics of well-being, which were described in detail within the concepts of quality of life, axiological and subject-activity approaches. Conclusions. Subjective well-being is a multifaceted integrative phenomenon that reflects the individual's satisfaction from their optimal self-realization according to their value systems in various life areas and life in general.
The effect of emerging structural representation on spatial visual statistical learning

Studies of spatial visual statistical learning (SVSL) typically focus on the implicit acquisition of co-occurrence-based element chunks oversimplifying the complex process of structure-based visual learning. We investigated the rules of SVSL under complex visual stimulus and task structures. In Phase 1 of the experiment (N=227), observers were exposed to scenes composed of either only horizontally or vertically arranged pairs of shapes, while in Phase 2, they saw scenes based on both horizontal and vertical pairs but using a new set of shapes. 2AFC tests measured observers’ pair-learning for both phases and open questions assessed the explicitness of their knowledge. Participants with complete explicit knowledge were excluded (N=3), while the others were grouped into implicit (N=192) and semi-explicit (N=35) groups based on their reported knowledge about pairs in Phase 1 being none or rudimentary without mentioning orientation. Learning in Phase 2 showed a strong double dissociation between the types of pairs learned preferentially and implicitness of knowledge. Observers with semi-explicit knowledge exceeded learning pairs in Phase 2 with the same orientation as in Phase 1, whereas implicit observers were better at learning pairs with non-matching orientation. Further analyses showed that this pattern was independent of the overall strength of pair learning in Phase 1, but critically depended on the implicitness/explicitness of knowledge. These results suggest that the strength of learning a higher-level structure of the input (here general orientation of pairs) has a crucial role in utilizing the acquired structural knowledge. As expected, when it is sufficiently strongly articulated, it helps generalization, i.e. learning similar patterns in a new context. In contrast, when it is weakly and implicitly captured -regardless of the overall efficiency- it hinders generalization and promotes a structural novelty effect.
Using observer similarity matrices to understand individual differences in gaze behaviour towards objects in complex scenes

Previous research revealed stable individual gaze biases along several semantic dimensions when viewing complex scenes. For instance, some observers have a stronger tendency to fixate faces while others fixate text more often. However, it is unclear what proportion of individual gaze differences towards objects in complex scenes is explained by these known dimensions. Here, we used a novel approach to analyse individual differences in gaze behaviour by computing ‘dimension-agnostic’ (dis-)similarities between observers. We analysed an eyetracking data set of N = 103 subjects, who freely viewed 700 complex scenes, depicting > 5000 objects. To estimate the noise ceiling of stable individual differences independently of a priori dimensions, we computed the similarity (Euclidean distance) of dwell times across all objects for each pair of observers. These pairwise similarities were highly consistent across independent subsets of images (R2 = .81). To explore how much of these stable differences can be explained by known individual gaze tendencies towards semantic dimensions, we determined individual fixation tendencies towards objects of 5 semantic dimensions and computed the similarity between each pair of observers for each dimension. We then fitted a cross-validated ridge regression model, predicting overall observer similarity from similarity matrices for each dimension. Results indicated that known dimensions captured 27% of the explainable variance in object fixations. Individual tendencies to fixate Faces (β = .22) and Text (β= .17) carried the highest weights, followed by fixation biases for Taste (β= .11), Motion (β= .10) and Touched (β= .07). Together, our findings suggest that individual tendencies along known semantic dimensions account for a substantial part of individual differences in object fixations. At the same time, most of the explainable variance in object fixations is not captured by these dimensions. We currently explore further dimensions, including individual biases for lower level image features and saccadic behaviour.
PEMBELAJARAN MENULIS TEKS ULASAN BUKU NOVEL “LASKAR PELANGI” MENGGUNAKAN METODE MIND MAPPING PADA PESERTA DIDIK KELAS VIII MTSS SIRNAMISKIN BANDUNG

Indonesian Junior High School subjects in the 2013 Curriculum are already text-based, one of which is a review text that requires students to express factual ideas according to the object or work being reviewed. This study aims to determine the writer's ability to plan, implement, and evaluate learning to write review texts; knowing the ability of students in writing review texts; and knowing the level of effectiveness of using the Mind Mapping method in writing review texts. The type of research used is a quasi-experimental involving the experimental class and the control class. As for the results of this study, the researcher was able to plan learning to write novel book review texts. Researchers obtained planning scores with an average value of 3.56 in the experimental class and 3.56 in the control class, then in implementing and evaluating learning the researchers obtained an average value of 3.58 in the experimental class, and 3.52 in the control class. , so it is included in the very good category. The results of the pretest of the experimental class students obtained an average pretest score of 44, while the control class received an average score of 18. The posttest results of the experimental class students obtained an average score of 80, and the control class obtained an average score of 37. So that the average value of the pretest and posttest of the experimental class is better than the control class. The results of the effectiveness of the Mind Mapping method in the experimental class were carried out through the Gain test by obtaining a Mean value of 64. Meanwhile, the control class obtained an average value of Mean 22 with the discussion method. So the use of the Mind Mapping method is more effective than the discussion method.
PENGGUNAAN MEDIA PAPAN KANTONG PINTAR UNTUK MENINGKATKAN HASIL BELAJAR IPA SISWA KELAS IV SD INPRES MINASA UPA 1 KECAMATAN RAPPOCINI KOTA MAKASSAR

The research carried out aims to describe the use of smart pocket board media in improving science learning outcomes for fourth grade students of SD Inpres Minasa Upa 1, Rappocini District, Makassar City. This study uses a qualitative approach with the type of classroom action research carried out in 2 cycles. The research subjects were fourth grade teachers and 25 students consisting of 14 male students and 11 female students. Data collection techniques used are observation, documentation, and test techniques.
Using the DeepGaze III model to decompose spatial and dynamic contributions to fixation placement over time

Humans view images in scanpaths of fixations, where they move their gaze over the image to explore interesting parts of the image. Which factors govern the principles of such scanpaths and how they change over time has been the subject of substantial research. The deep learning based DeepGaze III model currently sets the state-of-the-art in free-viewing scanpath prediction on natural images. It combines a spatial prediction module, which captures the influence of scene content on fixation placement, with a scanpath history module that captures the influence of earlier fixations and therefore the dynamics of the scanpath. Here, we conduct a series of ablation studies to train variants of DeepGaze III with no access to scene content, scanpath history or both and analyse how well fixations are predicted over the course of free-viewing scanpaths. We find that the overall predictability of fixations decays substantially over the course of scanpaths. Comparing the ablated models allows us to attribute this decay nearly completely to a decay in the influence of scene content: early fixations focus on the most salient image areas. Additionally, there is an influence of the initial fixation, which is mostly decayed after one saccade. Interestingly, the effect of scanpath history stays nearly constant over the scanpaths, suggesting that the dynamics of scene viewing don't change substantially over time. Due to the capacity of our models relative to the size of the dataset, we can assume that the models are able to capture all substantive ways in which fixations could depend on image content and previous fixations (in the context of free viewing). This avoids the possible confounder that the models are simply not good enough to predict fixations well. This study provides an example of how deep learning based models can be used to further our understanding of human behaviour.
Searching the sock drawer: How do people find pairs?

In standard visual search tasks, observers compare what they see in visual displays to target representation(s) loaded into memory. Typically, response times increase linearly with visual set size and logarithmically with memory set size. In contrast, consider searching for any matching pair of socks from a jumble. Here, the searcher is free to choose the current target(s), potentially searching for one or several possible target socks at any one moment and then changing search target(s) if no pair is found. Little is known on how people perform such “pair search”. Our observers compared two simultaneously presented arrays of objects for a single match across arrays. They responded by clicking on either member of the pair. Eye movements were recorded. Set size was varied independently for the two arrays. Though RT was a linear function of both the smaller and of the larger set size, it was not a monotonic, linear function of the total set size. As an index of memory involvement, we also measured the number of eye movement transitions between the two displays as well as the number of fixations on an array between those transitions. The number of transitions was a roughly 1:1 function of the smaller set size. In addition, the number of fixations between transitions remained quite small, even for the larger set sizes. These findings can reject at least two simple models: Observers did not exhaustively memorize one display and then perform a single "hybrid" search through the other array. Nor did observers appear to memorize just one item at a time, and then exhaustively search for it before returning to memorize the next target item. Instead, the trade-off between scanning and transitioning likely reflects a trade-off between cheap eye movements and expensive memory.
Development of a Framework Model Using Blockchain to Secure Cryptocurrency Investment

A new concept of blockchain technology for cryptocurrency has been discussed in this chapter. Existing technologies are examined by us and a new model of blockchain has been developed that is decentralized and much more secure and trustworthy. Even though the internet is the key technology behind the development of the blockchain technology and ecommerce, it has always had security and privacy concerns. Security and privacy are most important when we are developing or discussing FinTech and E-Commerce. Blockchain technology is the key behind the success of cryptocurrency, which is revolutionary in nature and provides a unique mechanism of transaction (i.e. peer-to-peer), that does not require any intermediary, including government or banks, to establish trust. In fact, bitcoin shows the power of blockchain. It works as an open ledger accessible to all worldwide. It has the capacity to change the digital world with its implication in government projects, health care, identity, Internet of Things, insurance, money, music, real state, supply-chain etc.
Human Interaction

This textbook presents an innovative new perspective on the economics of development, including insights from a broad range of disciplines. It starts with the current state of affairs, a discussion of data availability, reliability, and analysis, and an historic overview of the deep influence of fundamental factors on human prosperity. Next, it focuses on the role of human interaction in terms of trade, capital, and knowledge flows, as well as the associated implications for institutions, contracts, and finance. The book also highlights differences in the development paths of emerging countries in order to provide a better understanding of the concepts of development and the Millennium Development Goals. Insights from other disciplines are used help to understand human development with regard to other issues, such as inequalities, health, demography, education, and poverty. The book concludes by emphasizing the importance of connections, location, and human interaction in determining future prosperity.
CUSTOMER SENTIMENT ANALYSIS THROUGH SOCIAL MEDIA FEEDBACK: A CASE STUDY ON TELECOMMUNICATION COMPANY

Customer sentiment analysis is an automated way of detecting sentiments in online interactions in order to assess customer opinions about a product, brand or service. It assists companies in gaining insights and efficiently responding to their customers. This study presents a machine learning approach to analyse how sentiment analysis detects positive and negative feedback about a telecommunication company’s products. Customer feedback data were taken from Twitter through Streaming API (Application Programming Interface), where Tweets are retrieved in real time based on search terms, time, users and likes. Responses from the twitter API are parsed into tables and stored in a CSV file. Based on the analysis, it was found that there was no negative sentiment from the customers. The data were then split into training and testing to be tested on the three different supervised learning algorithms used in this study which are Support Vector Machine, Random Forest, and Naïve Bayes. Lasty, the performance of each model was compared to select the most accurate model and from the analysis, it can be concluded that Support Vector Machine gives the best performance in terms of accuracy, Mean Squared Error, Root Mean Squared Error and Area Under the ROC curve.
Analysis Of Failed Business Products – The HCI Perspective

Most of the leading companies have increased their success through the growing use of HCI methods to avoid wasting precious investment money from failed deployments of inferior technologies and to generate new revenue by identifying under-served needs and then envisioning, designing, and testing innovative products and services that fulfill the under-served needs effectively. Our work aims at Analyzing and Improving various systems where failure to implement principles of HCI leads to failure of the overall business product like Google wave, Google Plus, Google catalogs. The methodology that we followed is collecting various real-time examples where business products failed due to lack of user satisfaction, analyzing these case studies based on HCI principles, and trying to provide an effective solution to make the system more usable. Keywords: User Satisfaction, Design Principles, Cognitive Science, Useful systems, safety-critical systems, design flaw impact, software defects, root causes.
Replaceability of two deep generative models trained with a pair of translucent objects with different geometries

Perceived translucency of objects with various geometries can be different, even when physical translucency is kept constant. The logic of linking translucent images with different geometries, e.g., sharp vs. rounded corner edges, has been missing. For instance, can the translucent appearance of an object with a sharp corner edge be synthesized from another object without it? One possibility is that different geometries share common latent image factors diagnostic for perceived translucency, and each geometry affects the latent image factors in a non-categorical manner. We investigate this possibility by exploring the functional replaceability of paired deep generative models (e.g., VAEs or GANs) trained with rendered translucent images of paired geometries. If the paired geometries have a continuous effect on translucent images, the latent codes of one network should be replaceable, i.e., linearly transferable to the other network. Specifically, in one condition, one side of a paired network was trained with the translucent images of a "cube" geometry rendered with many combinations of physical parameters such as extinction coefficients, albedos, lightings, and phase functions. The other side was separately trained using a "bunny" geometry with the same physical parameters. Subsequently, we trained linear regression decoders to transform the latent codes of one network into the other. We tested whether the input of one geometry (e.g., "cube") can produce the output of the other geometry (e.g., "bunny") through the regression of the latent codes. Our results using ten natural geometries (Che et al., 2020, IEEE ICCP) showed that all geometry pairs could be replaceable in terms of various image evaluation metrics (PSNR, LPIPS, and DISTS). Furthermore, changing the scale parameter of the regression could quantitatively alter the perceived translucency of the output image. These findings suggest that the ten natural geometries have common image features for translucent images, which are continuously controllable.