Reviewerly/exHarmony huggingface dataset:
Brazilian Universities – Problems, COVID-19 &amp; Efforts

It is necessary to know the state of the brazilian universities. In this paper the general objective was determine the situation of brazilian universities: Problems, COVID-19 &amp; efforts. Methodology, in this research, 36 documents have been selected, carried out in the period 2016 - 2021; including: scientific articles, review articles and information from websites of recognized organizations. The keywords used in the searches were: Brazilian universities and COVID-19. Results, brazilian universities stand out for the great effort they make in the training of researchers, as well as in the publication of numerous scientific articles and patent registration. Each year they manage to rank better in the Latin American and international rankings. Conclusions, brazilian universities have been affected by the pandemic, largely due to the ineffective response of the current government. Therefore, it is necessary for the university community to work in coordination to overcome this critical situation. Brazilian universities are an important example for the rest of Latin American universities, due to their outstanding position in international rankings and their continuous effort in scientific research.&#x0D; Es necesario conocer el estado de las universidades brasileñas. En este trabajo el objetivo general fue determinar la situación de las universidades brasileñas: problemas, COVID-19 y esfuerzos. Metodología, en esta investigación se han seleccionado 36 documentos, realizados en el período 2016 - 2021; incluyendo: artículos científicos, artículos de revisión e información de sitios web de organizaciones reconocidas. Las palabras clave utilizadas en las búsquedas fueron: universidades brasileñas y COVID-19. Resultados, las universidades brasileñas se destacan por el gran esfuerzo que realizan en la formación de investigadores, así como en la publicación de numerosos artículos científicos y registro de patentes. Cada año logran posicionarse mejor en los rankings latinoamericanos e internacionales. Conclusiones, las universidades brasileñas se han visto afectadas por la pandemia, en gran parte debido a la respuesta ineficaz del gobierno actual. Por tanto, es necesario que la comunidad universitaria trabaje de forma coordinada para superar esta situación crítica. Las universidades brasileñas son un ejemplo importante para el resto de universidades latinoamericanas, por su destacada posición en los rankings internacionales y su continuo esfuerzo en la investigación científica.&#x0D;
Quantum photonics: how far can we go?

Although existing experiments have implemented protocols employing up to 10 or even 12 photons, the inefficiencies of sources has resulted in exceedingly low rates of these high-photon events. Single and entangled-photon emitters both suffer from probabilistic operation, substantial losses, or both, so that extrapolating even to 20 photons is discouraging. However, recent experiments employing multiplexing techniques can trade overall rate (or component count) for increased probability, e.g., factors of 10-30 enhancement have been demonstrated. How far can such experiments be pushed? Using our best guesstimates on what system capabilities may be feasible, we discuss the near-term future for multi-photon quantum processing.
Cloud Accounting: A Risk Mitigation Perspective

Modern businesses are moving towards Cloud based applications due to the flexibility, cost effective and business sense. However, there has been a noted hesitation by firms to migrate towards Cloud Accounting. This research aims to explore the reasons behind this reluctance by identifying the major risks that are preventing firms from embracing Cloud Accounting and recommending measures to mitigate the risks. This study deploys a qualitative approach to explore and understand the specific problems and solutions by interviewing Cloud Accounting experts internationally. The findings of this research suggest that Cloud Accounting provides unique features like the global network access, scalability, automation, ERP integration and enhanced measures of security at a fraction of the cost in comparison to the traditional AIS. However, organizations hesitate to embrace the Cloud Accounting services because of the lack of awareness about the concept, threats to data security because of the distributed nature of Cloud infrastructure, short lived business lives of Cloud vendors, and the dependency relation customers fall into because of the lack of transparency. The research believes that these risks are caused by lack of governance, compliance and audit in enterprise risk management framework, which if brought in place will mitigate the identified risks. This study aims to motivate more users to embark onto the Cloud Accounting platformto enjoy the benefit of this business enhancing technology.Keywords: Cloud Computing, Cloud Accounting, Enterprise Resource Planning (ERP), Accounting Information Systems (AIS), Enterprise Risk Management Framework
Perception of action-relevant egocentric distance is not underestimated in virtual reality

In the past few decades, advances in virtual reality technologies have led to an explosion of investigations into visual perception. While each new generation of VR systems brings improvements in optics and graphical fidelity, an open question remains: To what degree, and under what circumstances, will visual perception in the real-world correspond to visual perception in the virtual world? The well documented phenomenon of the compression of egocentric distance perception in VR suggests that such correspondence may depend on factors such as graphical fidelity, presence, and the like (Armbrüster et al., 2008). We investigated whether real-world egocentric distance perception would correspond to virtual egocentric distance perception in two experiments. Participants were asked to make affordance judgments about the reachability of a real (Experiment 1) or virtual (Experiment 2) ping pong ball that rested on a real or virtual table, respectively. Participants in both experiments exhibited perceptual boundaries occurring at distances approximately equal to 118% of their physical reaching capabilities. This suggests that, while participants generally overestimated the boundary of their reach, there were no significant differences between the degrees to which this occurred in both types of environments. This underestimation of distance (or overestimation of reach) comports with another well documented phenomenon that suggests people generally overestimate their reaching capabilities by about 20% (Carello et al., 1989; Weast & Proffitt, 2018). The importance of these findings rests in the fact that virtual reality is increasingly being used in psychological, visual, and health related research as well as for different types of neuro-training and therapy. Taken together, these results provide empirical evidence of the close correspondence of perceptual boundaries across the real world and virtual reality.
Deep Light Direction Reconstruction from single RGB images

In augmented reality applications, consistent illumination between virtual and real objects is important for creatingan immersive user experience. Consistent illumination can be achieved by appropriate parameterisation of thevirtual illumination model, that is consistent with real-world lighting conditions. In this study, we developed amethod to reconstruct the general light direction from red-green-blue (RGB) images of real-world scenes using amodified VGG-16 neural network. We reconstructed the general light direction as azimuth and elevation angles. Toavoid inaccurate results caused by coordinate uncertainty occurring at steep elevation angles, we further introducedstereographically projected coordinates. Unlike recent deep-learning-based approaches for reconstructing the lightsource direction, our approach does not require depth information and thus does not rely on special red-green-blue-depth (RGB-D) images as input.
PERAWATAN KECANTIKAN &amp; KEBUGARAN WANITA DI BANJARBARU

Current development makes many women have much activity that make them have no time to keep their physical fitness, beside that daily routine would cause boredom which leads into stress if not balanced with recreational activities. The presence of a beauty salon and spa in the middle of town can be one of choice recreational activities for women to get relaxed after their busy activity all day long, so a natural concept would be a great help therapeutic activities for visitors. Biophilic design themes will be applied to create natural feels by trying to ‘bring up’ nature into a building that can improve the space user's well-being in both physiological and psychological by using nature as the main approach.
PLATFORM YANG EFEKTIF UNTUK MENINGKATKAN KEMAMPUAN BERBAHASA ASING DI INDONESIA

Language is one of the most important means by which humans communicate and interact with other humans. In this era of globalization, digital technology has been increasingly developing, in modern times people can easily access and learn foreign languages through social media platforms or applications specifically for foreign languages. This research discusses the most effective platforms in improving foreign language skills for users, and  the effectiveness of using the platform in increasing language learning skills. The study used a qualitative descriptive method by collecting data using Google Form as a medium for data collection. 100 respondents were taken randomly as sample in this study from around 20 cities in Indonesia were used. The results and conclusions of the research are that the most widely used platform as a medium for learning foreign languagesindependently is social media. Of the 100 respondents, 71% chose social media accounts with language learning content on social media as the platform used to improve their ability to learn foreign languages independently. The most dominant type of social media account used is Instagram . 48.1% of the respondents answered that Istagram can help them to improve the ability to learn foreign languages with its effectiveness reaching 53.5%. It is stated to be quite good in helping to learn foreign languages independently. In conclusion, Instagram accounts with foreign language learning contents are the most effective in learning foreign languages independently.
FAKTOR YANG MEMPENGARUHI IMPLEMENTASI SISTEM INFORMASI MANAJEMEN RUMAH SAKIT (SIMRS) TERINTEGRASI DENGAN MENGGUNAKAN MODEL HOT–FIT

Implementation of information systems in hospitals (SIMRS) is very important to achieve quality services. However, monitoring and evaluation need to be carried out to find out how the benefits of SIMRS in hospital work units are. Thus, it allows hospitals to develop SIMRS by considering the factors that influence and benefit the use of SIMRS. The case study approach was carried out using the Human, Organization, Technology–Fit (HOT-fit) framework introduced by Yusof in 2006. The study was conducted at Bahteramas Hospital with a sample size of 162 respondents. The results of the analysis show that there is an influence of information quality on the use of the SIMRS system, SIMRS system development, user satisfaction. The inhibiting factors include SIMRS not according to needs, the perception that using manual recording is easier and faster, the perception that the use of SIMRS adds to the workload, and SIMRS output is considered not relevant to user needs.
ANALYSIS OF ACCURACY IMPROVEMENT IN RANDOM FOREST USING PRINCIPAL COMPONENT ANALYSIS (PCA)

Decision tree is used to classify a data that still does not know its class to existing classes. The data testing path is the first step that the root node goes through and finally the leaf node will predict the class for the data that has been concluded. Random Forest cannot be relied on for data types that have different categorical variables and therefore needs to be improved in the classification process, this is influenced by differences in the value of the variable. Therefore a method is needed to reduce features that are less relevant to the process of determining accuracy in the classification of the Random Forest method. In research conducted on the PCA + Random Forest classification model, using the Water Quality Status Dataset that has been simplified into 5 attributes, 4 classes and 117 instances with an accuracy rate of 91.43% with a classification error rate of 8.57%. Based on the test results from the four classification models, it can be concluded that the success of the PCA can be used as a reference to improve the accuracy performance of the Random Forest classification model
Συστήματα βασισμένα στη γνώση και η συμμετοχή τους σε υβριδικά συστήματα υπολογιστικής νοημοσύνης

The scope of this thesis is the systematic review of hybrid computational intelligence methods in the recent literature, which are utilized to solve complex problems. More specifically, the four hybrid categories consist of neuro-expert systems, fuzzy neural systems, evolutionary neural systems, and evolutionary fuzzy systems, were extensively investigated. Initially, two of the most well-known academic databases, the IEEE Xplore of IEEE and the ScienceDirect of Elsevier were selected. The search was applied by considering specific terms and selected advanced search features. The found papers were classified into valid, invalid, and selected. Key characteristics of each selected paper were recorded and presented in the relative section. Finally, the key points of the thesis are highlighted, and some interesting future work directions are discussed.
Academic Reading Format Preferences and Behaviours: An Exploratory Study amongst Undergraduate African University Students

To be academically successful a university student is required to read extensively on topics related to his or her field of study. The current proliferation and availability of electronic academic reading materials on various online platforms require academic staff to gain an understanding of their impact on the format preference and reading behaviour of students. Knowledge of emerging trends can guide academic staff to provide reading materials in the format best suited to the reading preferences of students. To establish the current format and reading behaviour trends a multiple case study design was employed targeting undergraduate students from the University of Zululand, South Africa and Delta State University, Nigeria. A questionnaire was used to collect data from a sample of 237 students. A combined return rate of 69.9% was achieved. The findings revealed a strong preference for reading textbooks in printed format. The preference for reading documents in electronic or print format was influenced by factors such as the length of the document, the purpose of reading the document, and whether the document is written in the student’s native language or not. External factors such as access to electronic gadgets and data, and the cost thereof, as well as peer pressure also influenced preference for a specific format. The study recommends that regular surveys should be conducted in academic institutions to keep track of current and changing trends in the format preferences and resultant reading behaviour of the students to enable academics to adapt their prescribed reading materials to a format best suited to the students’ preferences.
Transforming Latent Descriptors into memory Representations: The TLDR model of working memory

Visual knowledge is an inseparable part of working memory (WM) that affects encoding of information (Baddeley & Hitch, 1974; Baddeley, 2000; Ericsson & Kintsch, 1995). For example, the number of familiar items that people can remember is more than unfamiliar items (Zimmer & Fischer; 2020). And, active long-term memory is known to be a key component of WM (Cowan 2017; Oberauer 2009). Yet, no computational model has explained the underlying mechanism between visual knowledge and WM. In this study, we used a generative deep learning network to build a neurally-plausible computational model of WM that we call it TLDR. The visual knowledge in the TLDR is represented by a modified Variational Autoencoder (VAE; Kingma & Welling, 2013) that compresses the visual information in multiple layers. The TLDR encodes visual information by flexibly allocating neural resources to create an actively stored representation in a binding pool (BP; Swan & Wyble, 2014). The stored information in the BP is then retrieved to recreate those latent representations that were generated at the time that the stimuli were perceived. Consistent with human behavior in memory tasks, the TLDR is capable of explaining the following aspects of WM: efficient storage of familiar shapes with the aid of visual knowledge, storing novel configurations (Lake et al., 2011), encoding relevant attributes (e.g., color, shape, etc.) with varying degrees of precision (Swan, Collins, & Wyble, 2016), storing categorical information along with visual details with minimal interference, showing interference when multiple items or attributes are encoded in one memory trace, and rapid tuning the encoding parameters to accomplish unexpected memory tasks. In general, the TLDR provides new insights on the representations of WM in relation to the visual knowledge.
What Connects Dark Matter and Black Holes? Scientific Explanation

Dark matter is a major component of the universe, about six times more abundant than ordinary visible matter. We measure the effects of its mass, but it escapes the telescopes. It has the particularity of emitting no radiation and interacting only by the action of gravity. The main purpose of this article is to try to answer what dark matter is: we conjecture that it is composed of magnetically charged neutrinos, true magnetic monopoles. But that requires a huge conceptual leap: Maxwell's laws must be inverted and the electric charge becomes a magnetic charge. Asymmetric "reversed" Maxwell's laws would provide the "dark" magnetic charge that would replace the electric charge. The very form of the Dirac equation, which imposed on ordinary matter that the particle carries an electric charge and obeys the principal properties of the electron, would impose in the dark matter that the "dark" particle obeys the main properties of a neutrino associated with a magnetic charge. Dark matter is intimately related to black holes. The darkness of dark matter and black holes is caused by the reversal of Maxwell's laws. The second aim of the article is to show that dark matter is derived from black holes, mainly from active supermassive black holes. This requires a second conceptual leap: the horizon of the black hole undergoes a high temperature and an intense pressure of magnetic fields which cause a blackout and a phase transition (or broken symmetry) when the matter crosses the horizon. The result is a reversal of Maxwell's laws: A magnetic charge is substituted for the electric charge, and the electric current becomes a tributary of the magnetic current. A third important conceptual leap follows: sterile magnetic neutrinos created inside the black hole would cross the horizon to the outside to constitute dark matter.
Evolutionary Ann Design Using Improved Selection Method

Study Objective: The important issue in Evolutionary Algorithms (EAs), is time-complexity analysis. Here, 1. To consider the concept of take-overtime to obtain the mean hitting time of EA. i.e.&nbsp; the concept of the takeover time is generalized rather than a selection of operator alone. This generalization is applied to benchmark problems like N-Bit parity. For various input sizes N, the time complexity in terms of number of generations is estimated. To develop an empirical model is also generated for proposed EA using statistical tool. To apply the proper selection method to find the take-overtime.
Compact Architecture of the ECC Coprocessor for Binary Extension Fields

In Chapter 5, we have presented two coprocessor architectures that provide high flexibility for calculating the point multiplication. Flexibility is an important aspect for ECC systems. However, in this chapter we develop a cryptographic system for flash memories, where all users agree on the curve parameters, key length, and the same algorithm for the point multiplication. Hence, the flexibility is less demanding regarding the intended application. Consequently, it is advantageous to consider the calculation of the point multiplication for a single special prime such as Solinas primes [16], where the modulo reduction is very simple.
Uncertainty and Sensitivity Analysis in Archaeological Computational Modeling. MARIEKA BROUWER BURG, HANS PEETERS, and WILLIAM A. LOVIS, editors. 2016. Springer, Cham, Switzerland. xiv + 175 pp. $119.99 (hardcover), ISBN 978-3-319-27831-5. $119.99 (paperback), ISBN 978-3-319-80225-1. $89.00 (e-book), ISBN 978-3-319-27833-9.

Uncertainty and Sensitivity Analysis in Archaeological Computational Modeling. MARIEKA BROUWER BURG, HANS PEETERS, and WILLIAM A. LOVIS, editors. 2016. Springer, Cham, Switzerland. xiv + 175 pp. $89.00 (e-book), ISBN 978-3-319-27833-9.
Meaning guides clicks like fixations and drives memory for real-world scenes

Eye-movement data is useful for understanding visual and cognitive processes, but research-grade eye trackers can be cost-prohibitive. Further, the COVID-19 pandemic has made in-person eye-tracking studies impossible. In this study, we collected fixation-like data online by monitoring clicks on real world scene photographs using BubbleView (Kim, Bylinskii, et al., 2017). We sought to predict click locations using meaning maps and to examine the role of attention to meaning in long-term scene memory. [METHOD] Participants were presented with a blurred image for 12s. Whenever the participant clicked on the image, a region of the unmodified scene became visible around their click location. In three experiments, we manipulated the amount of time participants saw each scene before it was blurred (preview: 0, 50, and 200ms). Participants’ memory for the scenes was tested at the end of the experiment. [RESULTS] We compared participants’ click data from each experiment to previously-collected fixation data for the same scenes and found they were remarkably similar. Participants’ click maps correlated strongly with meaning maps (Henderson & Hayes, 2017) and participants were more likely to click high- than low-meaning scene regions, especially with longer scene previews. Finally, we found a significant relationship between participants’ clicks on meaningful scene regions and their performance on the memory test. Higher correlations between click maps and meaning maps and higher meaning values at click locations both predicted better memory. [DISCUSSION] Meaning-maps predicted click locations, suggesting click data can be used much like fixation data for studying scene-processing. This result also demonstrates meaning maps’ flexibility. We also found a relationship between attention to meaning and long-term memory for scenes, supporting the idea that meaning maps capture the distribution of semantic information in real-world scene images and suggesting that memory for scenes is fueled by semantic information.