Reviewerly/exHarmony huggingface dataset:
Performance Evaluation of Airborne GLS Receiver under Non-normal Distribution Error Model

Normal distribution model is often adopted in traditional performance evaluation of airborne equipments. This approach ignores the effect of non-normal distribution of multipath errors, and then makes the integrity evaluation results inaccurate and the system availability reduced. After reviewing of the existing problems, the relationship between performance parameters in precision approach operations and the requirements of airworthiness certification are analyzed, and a performance evaluation scheme for airborne GLS receiver under a non-normal distribution model is proposed and designed. The evaluation results of aircraft track data using actual GLS for landing show that the performance evaluation scheme and system in this paper are feasible.
Physics applications in eradicating Global Warming

The UN Intergovernmental Panel on Climate Change (IPCC) have warned there is only a dozen years for global warming to be kept to a maximum of 1.5C. To restore carbon storage intooceans, plants and landmasses thus first stabilizing new unwanted creations and then reducing greenhouse gasses like Carbon Dioxide and Methane before the Earth becomes like Venus. Common procedures over geologic time have changed the info and influenced both yield heat and outside temperature. It is the major issue. So, to eradicate this problem lot of experiment and my experiment is discussed below. The aim of this research is to basically show how physics applications are used to reduce Global Warming.
Bought and Bound for Melbourne

Discusses provenance evidence left behind as part of James Goold's personal collection at Mannix Library
ENSINO REMOTO, PRÁTICA DOCENTE E SAÚDE MENTAL EM TEMPOS DE PANDEMIA DA COVID-19: NOTAS INTRODUTÓRIAS

The present work aims, in an introductory way, understandable the possible effects of the new "normality" of teaching assumed in pandemic times on the mental health of teachers.These adversities bring the long-and medium-term disorders to the emotional scope of the teaching and student category, both being the main protagonists in the school scenario.It is necessary that educational managers take care of their teachers, so that they have emotional health to take care of their students.It is suggested that they introduce training in distance education that instrumentalizes them.For that, as specific objectives, a survey turns, bulletin, to an analysis of the transformations and reorganizations of social life from COVID-19, to investigate how changes brought about by the new logic in teaching practice, and, finally, to evaluate the likely impacts of these abrupt and severe transformations on teachers 'and teachers' mental health.Thus, a research adopted in this work is of a basic nature, assuming a qualitative approach, with an exploratory characteristic, having as a technique employed the literature review, under the systematic format.
Convergence Rate of the (1+1)-Evolution Strategy with Success-Based Step-Size Adaptation on Convex Quadratic Functions

The (1+1)-evolution strategy (ES) with success-based step-size adaptation is analyzed on a general convex quadratic function and its monotone transformation, that is, $f(x) = g((x - x^*)^\mathrm{T} H (x - x^*))$, where $g:\mathbb{R}\to\mathbb{R}$ is a strictly increasing function, $H$ is a positive-definite symmetric matrix, and $x^* \in \mathbb{R}^d$ is the optimal solution of $f$. The convergence rate, that is, the decrease rate of the distance from a search point $m_t$ to the optimal solution $x^*$, is proven to be in $O(\exp( - L / \mathrm{Tr}(H) ))$, where $L$ is the smallest eigenvalue of $H$ and $\mathrm{Tr}(H)$ is the trace of $H$. This result generalizes the known rate of $O(\exp(- 1/d ))$ for the case of $H = I_{d}$ ($I_d$ is the identity matrix of dimension $d$) and $O(\exp(- 1/ (d\cdot\xi) ))$ for the case of $H = \mathrm{diag}(\xi \cdot I_{d/2}, I_{d/2})$. To the best of our knowledge, this is the first study in which the convergence rate of the (1+1)-ES is derived explicitly and rigorously on a general convex quadratic function, which depicts the impact of the distribution of the eigenvalues in the Hessian $H$ on the optimization and not only the impact of the condition number of $H$.
The Study of Clausal Predicate in Modern Chinese

Clausal predicate is a sentence predicated by a subject-predicate phrase, it is a very special sentence structure in chinese language. subject-predicate structure serves as predicate, there are two Noun Phrases in front of predicate VP. its structure is very complicated, thematic roles is extremely varied. this paper based on existing research, according to the generation grammar
Conventional database management systems

Before the advent of Database Management Systems, computer programmers or developers spent a lot of time writing codes to create and manage databases also known as data files before venturing into the actual programming work, thereby making it possible for only trained computer professionals to operate and manipulate databases or data files. It left the programmers who are targeting high performance application to deal with first data integrity and security challenges, inefficient process to access and manipulate stored data, data recovery challenges in the case of crashes and many other challenges. In this paper, we present a review of the traditional database management system (DBMS).First; we gave a detailed explanation of the meaning, types and uses of a database management system. We highlighted the features of Conventional Database Management Systems and the challenges it faces today especially in the handling of high-profile data for many enterprise systems, hardware requirements, human resources, network challenges and costs are also discussed in this research. Finally, we propose a solution to the challenges facing the conventional database system. From our findings, we discovered that the Big Data technology is a potential solution to the limitations of the conventional database management systems. This research will be beneficial to scholars and researchers who are interested in Database management systems.
Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation

Data augmentation is vital for deep learning neural networks. By providing massive training samples, it helps to improve the generalization ability of the model. Weakly supervised semantic segmentation (WSSS) is a challenging problem that has been deeply studied in recent years, conventional data augmentation approaches for WSSS usually employ geometrical transformations, random cropping and color jittering. However, merely increasing the same contextual semantic data does not bring much gain to the networks to distinguish the objects, e.g., the correct image-level classification of "aeroplane" may be not only due to the recognition of the object itself, but also its co-occurrence context like "sky", which will cause the model to focus less on the object features. To this end, we present a Context Decoupling Augmentation (CDA) method, to change the inherent context in which the objects appear and thus drive the network to remove the dependence between object instances and contextual information. To validate the effectiveness of the proposed method, extensive experiments on PASCAL VOC 2012 dataset with several alternative network architectures demonstrate that CDA can boost various popular WSSS methods to the new state-of-the-art by a large margin.
Mind Mapping-Enhanced Reading Comprehension to Indonesia Islamic Junior High School Students: An Action Research

This classroom action research was conducted in a State Islamic Junior High School in Tanjung Pinang at the 8th grade in academic year 2020-2021. The purpose of the research was to describe how mind mapping can improve students’ reading comprehension of descriptive texts. The participants of the research consisted of 27 students. To gather the research data, the researchers used observation and test. The test was administered three times (pre-test, post-test 1, and post-test 2). Then, the data got from the observation were analyzed qualitatively while those from test were analyzed quantitatively. The result of pre-test was 9 students (33,3%) scored ≥70. In the post-test first cycle, the score of 16 students (59,25%) was ≥70, and in the post-test cycle II, 20 students (74,1%) scored ≥70. The results of the tests showed that the number of students who got score ≥70 improved. Meanwhile, the result of the observation showed that the use of mind mapping was successful in improving students’ reading comprehension. The students became more interested and more motivated to learn. It showed that ≥70% of the students participated actively in the teaching and learning process. Therefore, it is recommended for teachers to use this technique to upgrade students’ learning achievement.
COVID-19 as a scam challenge

Any nature-related occurrence can be seen as a security threat as it puts under the risk the human lives, their well-being as well as the entire infrastructure. The natural disasters and pandemic events are by many classified as the threats and they can seriously make harm to the majority of people and their assets. In the practice, the recent pandemic occurrence such as the Ebola is recognized by the Interpol as a bio-terrorism. That illness has taken the lives to so many people in Africa and wider, but with the discovery of the vaccine the pandemic has been put under the control. Even now the similar situation is with the COVID-19 pandemic as such a biological threat is not fully manageable due to the lack of the immunization. However, there are some empirical indications suggesting that with the appearance of the critical situation so many people will show the solidarity and willingness to support those being in the need. On the other hand, not any appeal for a help will be honest and so many fraudsters can try to take advantage over the people's weaknesses. Those persons deal with the entire psychology of the victim and they can accurately choose the moment to attack and which strategy to use. Basically, what we talk about is the criminological challenge and it does not appear in the physical environment only but also in the cyberspace as the skillfully planned hacking operation. The reason why so many people get hooked with such a criminality is that the donations are symbolic, so the number of victims can increase as the majority will be willing to give the money away. In other words, so many victims will be in deception and the criminals will take only several dollars from each of them, so if the minority of the victims even report about such an event they will signalize that someone took the very small amount of the money from them and in such a case the punishment is so weak or even does not exist. The different schemes are present regarding the cybercrime as those criminal groups could try to avoid the severe punishment doing the camouflage in the virtual domain. Finally, the role of this effort is to provide a comprehensive insight into the challenges of such scams as well as analyze their impacts to communities.
Cambios experimentados durante el cursado virtual en tiempos de pandemia y expectativas sobre exámenes finales virtuales

The objective of this paper was to take knowledge of changes in social and individual habits experienced by students during the virtual classes and their expectations at the time of taking the final evaluations with distance modality in times of pandemic. An online survey was conducted with 38 Industrial Engineering students of the Faculty of Agricultural Sciences at the National University of the Northeast, from 19 to 37 years old (34 % women, 66 % men). Ninety two percent of students changed their study habits, related to schedules, having to study on their own, returning to their homes of origin, sharing the computer with family members, not having fixed schedules in some subjects, among other things. In addition, 16 % considered that their level of understanding of the topics improved, whereas 37 % were able to better organize their time during the purely virtual classes. Regarding the possibility of taking a virtual final exam, it was observed anxiety in 68 % of the respondents, added to conditions of interest. In summary, students have experienced changes during the virtual course, having to organize their time, their study space, depending on external factors, such as connectivity and availability of technological devices, the change of place of residence with the factors involved. It is noted that, at the time of the survey, they had not yet had virtual final exams and were mainly eager to pass that moment.
Can the Press Meet the Challenges of Time? Print Media in the Context of the Information Revolution in the Second Decade of the XXI Century

The article discusses the main trends in the print media market over the past 10 years. The authors deal with the most topical problems of print media related to the necessity of restructuring traditional forms of editorial work in the context of the information revolution, the search for new ways of attracting target audience, and the increasing competition between the press and new electronic media. The study shows that these challenges have required prompt transformation in the work, which a number of traditional media have failed to do. As a result, they had to either reduce the covering or stop printing the copies. This trend is typical of both foreign and Russian print media. In the process of transformation and optimization of content production costs, print media have faced a number of companion problems caused by the increasing intensification of journalist work in convergent editorial offices, competition between professional journalists and freelance employees, and getting an optimal balance between profitability of the publications and quality of the media content.
The Influence of the School Literacy Movement through the Utilization of Reading Angles on Reading Interest of Elementary School Students

The purpose of this study is to determine the effect of the School Literacy Movement on students' interest in reading at Kendalrejo 01 Public Elementary School. This study used a quantitative approach with an ex post facto method. The instruments used were questionnaires and learning outcomes. The results showed the value of t_ (count) of 5.498, while t_table is known to be 1.987, then 5.498&gt; 1.987. So it can be concluded that there is a significant effect of the School Literacy Movement on the reading interest of students at SDN Kendalrejo 01 with a coefficient of determination of 25.4%.
Integrating Fast Regional Optimization into Sampling-based Kinodynamic Planning for Multirotor Flight

For real-time multirotor kinodynamic motion planning, the efficiency of sampling-based methods is usually hindered by difficult-to-sample homotopy classes like narrow passages. In this paper, we address this issue by a hybrid scheme. We firstly propose a fast regional optimizer exploiting the information of local environments and then integrate it into a global sampling process to ensure faster convergence. The incorporation of local optimization on different sampling-based methods shows significantly improved success rates and less planning time in various types of challenging environments. We also present a refinement module that fully investigates the resulting trajectory of the global sampling and greatly improves its smoothness with negligible computation effort. Benchmark results illustrate that compared to the state-of-the-art ones, our proposed method can better exploit a previous trajectory. The planning methods are applied to generate trajectories for a simulated quadrotor system, and its capability is validated in real-time applications.
Recognizing flight manoeuvre with deep recurrent neural nets

Machine Teaming (MMT) program. MMT is an initiative launched and funded by the DirectorateGeneral of Armaments (DGA). It is led by Dassault Aviation and Thales. As part of the definition ofthe Future Air Combat System (SCAF), MMT is exploring the possibility of developing a cognitiveair system.
Capelin: Data-Driven Capacity Procurement for Cloud Datacenters using Portfolios of Scenarios -- Extended Technical Report

Cloud datacenters provide a backbone to our digital society. Inaccurate capacity procurement for cloud datacenters can lead to significant performance degradation, denser targets for failure, and unsustainable energy consumption. Although this activity is core to improving cloud infrastructure, relatively few comprehensive approaches and support tools exist for mid-tier operators, leaving many planners with merely rule-of-thumb judgement. We derive requirements from a unique survey of experts in charge of diverse datacenters in several countries. We propose Capelin, a data-driven, scenario-based capacity planning system for mid-tier cloud datacenters. Capelin introduces the notion of portfolios of scenarios, which it leverages in its probing for alternative capacity-plans. At the core of the system, a trace-based, discrete-event simulator enables the exploration of different possible topologies, with support for scaling the volume, variety, and velocity of resources, and for horizontal (scale-out) and vertical (scale-up) scaling. Capelin compares alternative topologies and for each gives detailed quantitative operational information, which could facilitate human decisions of capacity planning. We implement and open-source Capelin, and show through comprehensive trace-based experiments it can aid practitioners. The results give evidence that reasonable choices can be worse by a factor of 1.5-2.0 than the best, in terms of performance degradation or energy consumption.
«Elementary units» in Multimedia: Cinemagraphy in Mass Media and Blogs in the 2010s

The article studies peculiarities of cinemagraphies - special types of images that appeared due to the development of digital technologies in the early 2010s and combine features of photography and video/cinema. Cinemagraphies are positioned as elementary multimedia units, and perception of these is technologically dependent: the viewer actively perceives not only the depicted image, but also the image-generating technology. Cinemagraphic way of seeing is not peculiar to human vision, its a «machines view». The author suggests defining the properties of these units, namely, multimediality, multimodality, affectivity of technological items, segmentary actuality and segmentary iconicity, hybrid temporality, visual variability; soundlessness; and poetic character, orientation to sensory perception. The duration of one cycle of cinemagraphies, according to the analysis, falls within the interval of 4-10 seconds. The effect exerted on the viewer is largely determined by the percentage of the animated area: if &lt; 25 % of the frame area is animated, the focus is on the movement, while if &gt; 50 %, it is on static objects perceived as «anomalous» in the flow of life. The use of cinemagraphies in the media as illustrative material has a precedent character nowadays. The author managed to detect 151 such cases. The article analyzes in detail some examples of cinemagraphies, published in The Guardian, The New York Times and other media, as well as in blogs in the period 2011-2019. The author defines the following criteria for the analysis: substantive, genre, structural, visual characteristics, functions and distribution channel.
Towards Connecting Use Cases and Methods in Interpretable Machine Learning.

Despite increasing interest in the field of Interpretable Machine Learning (IML), a significant gap persists between the technical objectives targeted by researchers' methods and the high-level goals of consumers' use cases. In this work, we synthesize foundational work on IML methods and evaluation into an actionable taxonomy. This taxonomy serves as a tool to conceptualize the gap between researchers and consumers, illustrated by the lack of connections between its methods and use cases components. It also provides the foundation from which we describe a three-step workflow to better enable researchers and consumers to work together to discover what types of methods are useful for what use cases. Eventually, by building on the results generated from this workflow, a more complete version of the taxonomy will increasingly allow consumers to find relevant methods for their target use cases and researchers to identify applicable use cases for their proposed methods.
Adapting MARBERT for Improved Arabic Dialect Identification: Submission to the NADI 2021 Shared Task

In this paper, we tackle the Nuanced Arabic Dialect Identification (NADI) shared task (Abdul-Mageed et al., 2021) and demonstrate state-of-the-art results on all of its four subtasks. Tasks are to identify the geographic origin of short Dialectal (DA) and Modern Standard Arabic (MSA) utterances at the levels of both country and province. Our final model is an ensemble of variants built on top of MARBERT that achieves an F1-score of 34.03% for DA at the country-level development set -- an improvement of 7.63% from previous work.
A Crash Course on Reinforcement Learning

The emerging field of Reinforcement Learning (RL) has led to impressive results in varied domains like strategy games, robotics, etc. This handout aims to give a simple introduction to RL from control perspective and discuss three possible approaches to solve an RL problem: Policy Gradient, Policy Iteration, and Model-building. Dynamical systems might have discrete action-space like cartpole where two possible actions are +1 and -1 or continuous action space like linear Gaussian systems. Our discussion covers both cases.
Metode Data Mining Klasifikasi Pada Kualitas Pelayanan Terhadap Nasabah Bank Syariah Mandiri dengan Model C4.5

Customer satisfaction is the most important thing in assessing the level of management and services provided by the bank to its customers. The existence of banking services in society is indeed more profitable, especially in the economic sector, where economic actors are more free to carry out the process of economic activities to support survival. Data mining is an analysis of observations of large amounts of data to find relationships that are not known beforehand, data processed by the data mining method will produce a new knowledge sourced from old data, the results of processing can be used to determine future decisions. Using the C4.5 algorithm will predict which aspects are more dominant towards customer satisfaction. The data source of this research was collected based on a questionnaire (questionnaire) filled out by customers of Bank Syariah Mandiri in Pematangsiantar City. Data will be processed by calculating the value of entropy, calculating the gain value. So that the final results obtained in the form of a decision tree are expected to be input to the Bank Syariah Mandiri in Pematangsiantar City in maintaining the quality of its services to customers and improving the quality so that customers are always satisfied with the services provided