Reviewerly/exHarmony huggingface dataset:
A Fast Switching-based Trajectory Planning Algorithm for Aggressive Quadrotor Flight

In this paper, an online trajectory planning problem is investigated for aggressive quadrotor flight in cluttered environments with multi-form narrow gaps. An efficient planning framework is developed, in which a switching policy is designed to choose planning methods based on the obstacle information. First, we propose the Guide State Set (GSS) generating algorithm to derive feasible states from the narrow free space (NFS). Next, the initial path is obtained using the generated GSSs: When the search process is near a GSS, a guide trajectory with an expected final state is generated to prevent the aimless expansions. If the current state is away from all GSSs, the graph search method is applied with a lazy checking strategy to speed up searching. Finally, the proposed method is validated by simulation and experimental results.
Identifying and Mapping Study of the Information Professional in Library with Scientometric Analysis

The development of information in the digital era forces librarians to change their roles to become information professionals who have modern skills to face challenges in the digital environment. This study aimed to determine the extent of the studies conducted on information professionals in libraries and to find out the themes and terms that were often used, the trend of topics each year, and the social networks of the authors. The method used was Scientometric analysis using a single search in the Lens.org database. Articles were searched using the terms “information professional” AND “library” in the title. The data obtained were 1523 publications from 1950 to 2020. The results of this study showed that in 2011 and 2014 the largest number of publications were 76 and 84 articles, respectively. In addition, the average growth rate related to publications among information professionals was quite high at 29% during the analyzed period. The study themes were divided into 4 major theme groups and the basic theme was the most frequently used. Then the term that most often appears was "information" with 1110 repetitions. There were also technical terms such as digital, application, and internet which indicate that the study of information professionals had adapted to systems in the digital era. Following the trend of topics in the third quarter (2013-2020), it showed more about the LIS and skills.
Technology Distractions in Multimedia-Enhanced English Class in Blended Teaching Environment

Under the background of covid-19, more and more universities began to adopt blended teaching approach in real practice.In English class, teachers began to integrate information technology in courses more than ever before, which leaves room for technology distraction in the process and it may harm the effectiveness of teaching and learning.This study aims to find out the advantages and disadvantages on technology distractions in English class from a student's perspective and explore the possible factors that affect students' technology distraction levels.The findings reveal that selfregulation, interest and learning-oriented goal are intrinsic factors while learning environment and peer influence are extrinsic factors for influencing students' distraction levels in technology use in class.Hopefully, this study will provide some practical suggestions to course instructors.
The Implementation Of Naive Bayes Method In Classification Of Good And Problem Customers At PT. Adira Finance

The problem that often arises is the number of customers who have problems paying installments, so the collectibility is not smooth. Customer installment payments affect their performance and existence in everyday life. We need a way to find out how the customer's installment payment pattern is so that it can be classified whether the customer is good or problematic so that the company can overcome the problem early on. The implementation of Naive Bayes Method in the classification of good and problem customers at PT. Adira Finance is a platform that can be used to determine whether a customer is classified as a good customer or a problem customer based on 4 (four) aspects of the assessment. The 4 (four) aspects of the assessment are financing, installments, time period, and income. The classification of customer data is done by comparing the training data that has been previously inputted with the test data for which you want to know the classification. The final result of the classification is the probability value of good and problematic customers by looking at the highest value. Based on the tests that have been carried out using the Black Box Method, the results show that the functionality of the application for determining customer classification is good and has problems at PT. Adira Finance has run as expected and the application is able to display the results of the classification of good and problem customer data.
Cost Evaluation of Substation Project Based on GA-BP Neural Network

This paper takes the influencing factors of substation project cost as the input variable and the cost evaluation value as the output result, and then uses the neural network algorithm to evaluate the cost. Considering the shortcomings of neural network algorithm, genetic algorithm (GA) is used to optimize the neural network to realize a stable and effective evaluation of substation project cost. The simulation is carried out in Matlab environment, and the proposed algorithm is compared with the traditional BP neural network. The results show that the model improved by GA has more remarkable effect in application, and can guide the project cost management.
Designing augmented reality as a means to support distanced learning at University during Covid-19 period

This article attempts to provide educators about information needs to be prepared to create Augmented Reality (AR) in teaching and learning process, especially in mathematics. In this case, the learning media was designed as a way to facilitate students in studying mathematics at home and and to support their self efficacy. In addition, the media could develop the students’ insights towards the subject that they studied. The process of making the media was conducted through the phases of developmental research ADDIE, such as Analysis, Design, Development, Implementation, and Evaluation. The development activities were embedded in each phase of the designing process. The process of implementation involved 50 mathematics education students at Medan State University. The results of this study shows that educators should pay attention to five crucial elements when designing Augmented reality for mathematics learning, such as mathematics content, storyboard, marker, interface, and AR Application.
Virtual Reality Flood Disaster with Variations of Water Levels in the Early Warning System

Indonesia experiences floods every year. According to the National Disaster Management Agency (BNPB), the most frequent disasters are floods with a total of 682 incidents in 2022. A person's unpreparedness when the water level rises causes victims when the flood disaster strikes. This study aims to develop a flood disaster virtual reality application to train someone when a flood event occurs. The application development method is VRDLC (Virtual Reality Development Life Cycle) and the variation method of increasing water levels based on flood warnings in the guidelines for implementing a flood early warning system that has been established by the Directorate of Early Warning of the National Disaster Management Agency (BNPB). The Flood Disaster VR application is presented in two stages, the first stage contains education when a flood occurs and the second stage is a game with a rescue mission when a flood occurs. The flood level variations in the game are safe level, warning level, on-guard level and high risk level. Games can be played with oculus equipment. The results of the study have succeeded in developing a VR simulator for preparedness during a flood disaster. And the results of user assessments state that the application is useful in the simulation of the stage when the flood with good and very good values is worth 81%, and the use of VR applications as flood education is of good and very good value is 72%.
READING STRATEGY TAXONOMIES: AN OVERVIEW

The crucial importance of reading in any language has stimulated a noticeable growth in the number of studies on reading strategies used in second and foreign language reading to improve readers’ comprehension. This paper examined the classifications of reading strategies by providing a variety of reading strategy taxonomies by different authors. The comparisons of the most well-known reading strategy taxonomies by Oxford (1990) and three other best-known ones by O’Malley and Chamot (1990), Mokhtari and Sheorey (2002), and Oxford (2013) were also demonstrated clearly. Two questionnaires, one of which was modified by Nguyen (2016) from the one by Sheorey and Mokhtari (2002) were also presented as useful recommendations for researchers in the field. The results of the research offer a quite comprehensive insight into reading strategy taxonomies, which might be useful for researchers in the field of reading strategies in choosing an appropriate theoretical framework for their studies in the future.&#x0D;
Improved Relationships of Moment Magnitude with Regional and Local Magnitudes for Earthquakes in the United States

ABSTRACT: The moment magnitude is the preferred magnitude to characterize the earthquake source. Moment magnitudes (Mw) are calculated from moment tensor inversion. In contrast, the regional short period surface-wave magnitude (Mblg) and local magnitude (ML) are calculated using the amplitude of the Lg surface waves and maximum horizontal amplitude measured by the seismograph, respectively. Moment magnitudes are inaccurate for small earthquakes (Magnitude &amp;lt; 3.5) and if the waveforms used in the moment tensor inversion are recorded in stations with inadequate azimuthal coverage for the earthquake. In such cases, the moment magnitude is estimated using other available magnitudes. Due to the difference in bedrock geology and anelastic attenuation coefficient, the National Earthquake Information Center (NEIC) uses different magnitudes for the Central Eastern (i.e., Mblg) and the Western (i.e., ML) United States. This study uses the Saint Louis University earthquake catalog to develop improved relationships of moment magnitude with the regional magnitude (Mblg) in the Central Eastern U.S., and the local magnitude (ML) for the Western U.S. to accurately estimate moment magnitude when the moment tensor inversion is unavailable. 1. INTRODUCTION Earthquake magnitude is a commonly accepted tool to quantitatively describe the size and severity of an earthquake. During an earthquake event, seismic energy at the hypocenter is radiated through the earth in different waveforms, i.e., body waves (P and S waves) and surface waves (Rayleigh and Love waves), which are recorded by the seismometers on the earth’s surface. In 1935, Charles F. Richter introduced the concept of measuring the earthquake magnitude based on the maximum amplitude of the waveform recorded in a particular type of seismograph (Woods - Anderson torsion instrument) in southern California (Richter (1935)). Richter magnitude (ML) developed by Richter (1935) was only valid for southern California for specific frequency and distance ranges. Thus, several magnitude scales were developed based on the amplitude of the specific type of seismic waves within specified frequency ranges to account for the regional anelastic attenuation of the waveforms and measure the earthquakes in regions other than southern California (e.g., USGS (2022a)).
ENGAGING EXTENSIVE READING PRACTICE MEDIATED BY LET’S READ ASIA IN ONLINE CLASSROOM

This research aims to find out the process of students’ engagement during extensive reading practice mediated by Let’s Read Asia and students’ responses during extensive reading practice mediated by Let’s Read Asia at the eleventh grade in one of the Senior High School at Karawang. This research used the qualitative approach and a basic interpretive research as the research design. The data were collected by observation checklist based on guidelines from the Extensive Reading Foundation, online interview by using Whatsapp application, online documentation, and written artifact of students. This research included 4 participants of eleventh grade of senior high school. The result of this research showed that the teacher can engage students, it because students actively followed teacher instructions during the process of extensive reading practice that mediated by Let’s Read Asia. During the extensive reading practice that mediated by Let’s Read Asia students could make their interest to read with books that have self selected by students. The students also give the positive responses in the process of extensive reading practice that mediated by Let’s Read Asia as a media of students reading activity.
Development of a face detection system with or without a mask using software

This article presents a software with artificial vision using the Python language in Visual Studio Code which is capable of detecting if a person is wearing a mask or not, this project was made in order to be able to identify people who are without masks or misplaced either at work or at the entrance of a premises, for example this would be applied in companies that work with toxic waste, gases, dust and any agent that is transmitted by air, thanks to this it will be possible to identify certain people and give them a feedback on the correct use of the mask. For the development of this software, the main modules such as opencv-contrib-python, numpy and mediapipe were used, in addition to having their dependencies which are installed automatically, as well as a camera with which to capture the images; The first step was to search for a data set and resize it, followed by training it using opencv and finally using mediapipe for face detection and implementing the model in programming. Finally, after the tests carried out, a result of 83.13% validation was obtained, however, its percentage would increase or decrease depending on the quality of the camera, since the errors would decrease if you have a camera with a good quality implemented.
Perancangan Sistem Ujian Online Pada Rumah Pintar Bahasa Inggris Di Kampung Semanggi

Kampung Semanggi has an English Smart House that accommodates school-age students. This smart house provides English learning facilities. Based on the results of observations and interviews with the manager, they want a system to be made for online exam activities. This system is not only a necessity during a pandemic, but becomes a breakthrough learning method in the future. Based on this background, we held a service program for designing an online exam system for the English Smart House in Semanggi Village. System development is carried out with the waterfall stage. We use CodeIgniter framework, PHP language and MySQL database in system development. The results of using the online exam system, the exam process becomes easier, faster and more practical. This system helps teachers and students for the efficiency of the exam process
CONTROL ALGORITHM USING LYAPUNOV STABILITY FOR TRAJECTORY FOLLOWING AND 3D POTENTIAL FIELDS IN OBSTACLE AVOIDANCE IN AN AERIAL ROBOT

Due to the high demand for aerial robots, it is essential to guarantee stable systems for the tasks assigned to these robots. Which is linked to control and stability; therefore, we talk about the design of optimal control algorithms. In this work, Lyapunov stability theory is used for trajectory tracking and three-dimensional potential field theory for obstacle avoidance. The Lyapunov candidate function was chosen in compliance with the requirements for the necessary stability, being necessary in the tracking of trajectories to saturate the speeds of the aerial robot and in the avoidance of obstacles, the theory of potential fields is applied, which builds a field potential with gradient therefore rejects obstacles. To demonstrate that there is an optimal algorithm that allows the aerial robot to follow trajectories in a stable way and avoid obstacles, we have compared the results with solutions implemented with controllers using numerical methods and implemented in reality and in simulation, seeing that the errors tend to zero from one quickly and their speeds are consistent with the reality of these robots. We have worked different test trajectories and we have had speeds in different ranges such as 5 m/s, -3.8 m/s and 7 m/s or 1.8 m/s and 2.2 m/s these speeds depend on the type of trajectory, as well as if it has obstacles , we can see all this in the figures of the work simulations, in the same way we can see the errors that tend to 0 m at different times 2 s, 6 s. The results of this research can be applied in the design of controllers for aerial robots, offering stable systems in the task assigned to the aerial robot.
HEDGING IN ACADEMIC WRITTEN DISCOURSE

The recent proliferation of studies on hedging in written academic discourse shows that hedging has been widely employed and is considered effective and a prerequisite for scientific journals. Hedging is generally used for making a proposition and its relationship with the representation of reality and for attenuating the claims to avoid any risks of negations. The present research analyses the use of hedging in the Indonesian academic context. The data were taken from a corpus, named C-Smile, of undergraduate students’ theses of the English Department, Faculty of Letters, State University of Malang, totaling up to 1,587,059 words. Employing the hedging taxonomy advocated by Hyland (1996), the present project discovers that “reliability” hedges were the most frequent (88.13%) in use. Of the reliability hedges, modal verbs were found to have the highest frequency (79.60%). Furthermore, the modal auxiliary verb ‘can’ was the most frequently occurring hedging device (38.94%). Nevertheless, there is a scarce occurrence of highly-technical terms of hedges, such as allegedly, presumably, supposedly, etc. Moreover, hedges were more frequent in the Discussion section (56.74%) than in the Introduction section (43.26%). It was concluded that they mostly employ reliability hedges referring to the not-feel-confident due to the influence of culture, i.e., collectivism. It is also possible that they use hedges for the sake of politeness and to make their claims accepted by the readers (Bonyadi et al., 2012). Additionally, the typical kinds of hedges employed and (mis)use of hedges may be attributed to the fact that the corpus is the product of EFL learners whose English falls into the category of interlanguage.&#x0D; &#x0D;
An Analysis of Trap Monopoly Game in Teaching Speaking

The aims of these research were to know the process of teaching speaking by using trap monopoly game at XI TKJ Grade of Students of SMK Muhammadiyah 2 Sukoharjo, and to describe the implementation of using trap monopoly game itself.This research conducted by the researcher using qualitative method..The data was collected by virtual observation, interview, questionnaire, and documentation. The researcher analyzed the data by interactive model from Miles and Huberman (1984). The result of this research were : First, the process of teaching speaking by using trap monopoly game in teaching speaking. On pandemic of Covid-19, the teacher used virtual learning by zoom meeting application. Second, the implementation of teaching speaking by using trap monopoly game as the learning media on vocabulary, narrative and recount text, procedure text, giving opinion materials.The strenghtness of using the trap monopoly game was helping the teacher in learning activity, more interesting and as the alternative teaching speaking media. Moreover,using of trap monopoly game was helping the students more active and confidence to speak english. The weakness of using trap monopoly game as the teaching media was the teacher must prepare the teaching media previously, E-learning process was less smoothly because the internet signal was bad
Penatalaksanaan awal pada pasien dengan cedera otak traumatik

Traumatic brain injury is a major cause of morbidity and mortality, and the third most common cause of injury that causes death. 69 million people suffer from traumatic brain injuries each year. Initial treatment was carried out on a man aged 21 years, with a weight of 62 kg and a height of 160 cm. The patient came to the emergency unit brought by his family because of a traffic accident with a motor vehicle, when the accident the patient was not under the influence of drugs and was not drunk. The patient's GCS was E2V2M4. The patient was given initial management in the form of an airway evaluation by installing an oropharyngeal airway (OPA) for airway patency, breathing at a respiratory rate of 22 times/minute, and circulation with a blood pressure of 133/78 mmHg and a pulse rate of 102 times/minute, the patient's body temperature was 36. ,50 C. The patient was diagnosed with extensive subarachnoid hemorrhage based on radiological examination with non-contrast CT scan of the head requiring craniotomy for evacuation of bleeding by a neurosurgeon specialist. Initial management of the patient is carried out in the emergency unit by evaluating the primary survey and secondary survey. Evaluation of the patient is carried out while monitoring the patient's hemodynamic state remains stable. Speed and accuracy in providing initial treatment to traumatic brain injury patients play a very important role in preventing the development of primary injury to secondary injury and can provide a better prognosis for patients.
Railway Traffic Volume Prediction Method Based on Hadoop Big Data Platform

In order to improve the accuracy and efficiency of railway traffic volume prediction, a railway traffic volume prediction method based on Hadoop big data platform is proposed. Firstly, the traffic big data preprocessing mainly includes three parts: redundant data processing, numerical abnormal data processing and missing data processing. Then the spatial cross-correlation characteristics of traffic flow are calculated. Finally, a combined prediction model based on multi features and multifractals is established to realize the railway traffic volume prediction based on Hadoop big data platform. The experimental results show that the prediction method in this study has high prediction accuracy, reduces the prediction time, and meets the needs of method design.
Identifikasi Ujaran Kebencian Multilabel Pada Teks Twitter Berbahasa Indonesia Menggunakan Convolution Neural Network

There has been a significant increase in communication activities between internet users in online media due to the increase in social media users. For instance, Twitter users may send messages via their tweets. However, tweets can also contain negative meanings. Therefore, it deserves special attention as it has the potential to contain hate speech. Even the government deems it necessary to publish regulations to deal with hate speech cases such as the Information and Electronic Transactions Law (ITE Law) issued in 2018 Article 28 paragraph 2 of the Hate Speech. Machine Learning (ML) is one of the techniques that can be used in identifying patterns. There are various types of data that ML can be applied to, including text (known as Text Analytic). Previous research has used the Support Vector Machine (SVM) method to identify hate speech on Twitter text with more than one label (multilabel). The purpose of this study was to identify hate speech on Twitter with a label of more than one (multilabel) via Convolutional Neural Network (CNN). The study obtained the best CNN model with an accuracy of 98.76% from the multi-label dataset on hate speech in Indonesian texts