Reviewerly/exHarmony huggingface dataset:
Analysis of Text Readability of College English Course Books

Course books are an important source of knowledge input in classroom teaching.Text difficulty is one of the key factors in choosing course books while text readability serves as an important indicator to measure the text difficulty.However, there have been few studies on text readability of college English course books in the past.This survey uses the WE Research platform and adopts Flesch Reading Ease and other readability formulas as the detection tools to study the text readability development of the course books.The researcher analyzes the surface text characteristics of word and sentence length as well as the readability index 1 and 2 of the texts in the 4 volumes of New Target College English Integrated Course to verify whether the compilation of the course books obeys the rule of text difficulty development from low to high.This article firstly summarizes the background, discusses the necessity of understanding text readability in college English teaching.Secondly, it reviews the development and the study of text readability both at home and abroad.Thirdly, it talks about the methodology of the study and discusses the data collected from the platform.It is hoped that this study can provide some guiding significance for editors, publishers, teachers as well as students.
Using PQ4R to Improve Students’ Reading at Emergency Remote Learning

Emergency remote learning is a substitute for face-to-face teaching and learning activities during the COVID-19 pandemic. Students feel various problems in the teaching and learning process, especially reading English text in this study. Students feel uncomfortable, less handling, reading text must be repeated to understand, and the more wanted problems in this study are the mean score of reading students is still lacking. There is no particular method used in reading. Therefore, this study proposed the PQ4R method as a method that could be used to improved students' homework. This research was qualitative and quantitative with the CAR (Classroom Action Research) method, and the data collection techniques were tests and questionnaires. This study also used triangulation as data validation. The mean score of students ' reading has increased from the existing situation, the first cycle, to the second cycle. The current situation means the score was 65.16, the mean score of the first cycle was 78.03, and the mean score of the second cycle was 88.94. In addition, students' responses to the PQ4R method were positive. The results of this study indicated that the PQ4R process could improve students' reading mean scores.
Agent in a Box: A Framework for Autonomous Mobile Robots with Beliefs, Desires, and Intentions

This paper provides the Agent in a Box for developing autonomous mobile robots using Belief-Desire-Intention (BDI) agents. This framework provides the means of connecting the agent reasoning system to the environment, using the Robot Operating System (ROS), in a way that is flexible to a variety of application domains which use different sensors and actuators. It also provides the needed customisation to the agent’s reasoner for ensuring that the agent’s behaviours are properly prioritised. Behaviours which are common to all mobile robots, such as for navigation and resource management, are provided. This allows developers for specific application domains to focus on domain-specific code. Agents implemented using this approach are rational, mission capable, safety conscious, fuel autonomous, and understandable. This method was used for demonstrating the capability of BDI agents to control robots for a variety of application domains. These included simple grid environments, a simulated autonomous car, and a prototype mail delivery robot. From these case studies, the approach was demonstrated as capable of controlling the robots in the application domains. It also reduced the development burden needed for applying the approach to a specific robot.
MENINGKATKAN KETERAMPILAN MENULIS, KETERAMPILAN BERKOMUNIKASI LISAN, DAN MOTIVASI BELAJAR SISWA MELALUI PENDEKATAN PROSES MENULIS [IMPROVING WRITING SKILLS, ORAL COMMUNICATION SKILLS, AND STUDENT LEARNING MOTIVATION THROUGH THE WRITING PROCESS APPROACH]

&lt;p class="1eAbstract-text"&gt;The writing process approach is used to help students to write more competently through stages of the approach. The design of Static-Group Pretest-Postest is used to investigate the increase on students' writing skills, oral communication skills and learning motivation in Indonesian classes. The subject of the study was 41 Grade 8 students consisting of 21 students in experiment group and 20 students in control group. The study was conducted by implementing the writing process approach as the treatment in experiment class and conventional approach in the control class. The data was analysed using descriptive statistics and Wilcoxon test by comparing the results between pretest and posttest, and Mann Whitney test was used to find the difference between two groups. The findings show that there were increase on writing skills in middle category (N gain =0.48; p =0.000), oral communication skills in middle category (N gain = 0,47; p = 0,000), and learning motivation in low category (N gain = 0,25; p = 0,000) after the implementation of the writing process.&lt;/p&gt;&lt;p class="1eAbstract-text"&gt; &lt;/p&gt;
Efficient Graph Analytics in Python for Large-Scale Data Science

Graph analytics is important in data science research, where Python is nowadays the most popular language among data analysts. It facilitates many packages for graph analytics. However, those packages are either too specific or cannot work on graphs that cannot fit into the main memory. Moreover, it is hard to handle new graph algorithms or even customize existing ones according to the analyst's need. In this paper, we develop a general graph C++ function based on a semiring algorithm including two math operators. The function can help solve many graph problems. It also works for graphs that cannot fit in the main memory. Our function is developed in C++, but it can be easily called in Python. Experimental comparison with state-of-art Python packages show that our C++ function has comparative performance for both small and large graphs.
OPTIMALISASI PENGGUNAAN PROYEKTOR DALAM PEMBELAJARAN PADA MATA PELAJARAN I.P.A

The objectives to be achieved in this study are to determine the us of projector media in I.P.A learning and to determine the impact of using projector media in I.P.A learning. The use of projector learning media can help teachers develop teaching techniques so that they can get maximum result. Optimal use of the projector in the teaching and learning process, especially in science subjects, is expected to increase student motivation in learning. This research is a library research type with document data collection techniques in this study in the from of journals from previous research related to the us of projectors in I.P.A learning. From the discussion, it can be concluded that the us of projectors in I.P.A learning is useful as a presentation tool, as an information medium and as a video player. In additiom, the us of projector learning media in science subjects can increase student motivation in learning so that it has apositive impact in increasing student achievement.&#x0D;
Enhanced Cuckoo Search Optimization and Hybrid Firefly Artificial Neural Network Algorithm for Cyberbullying Detection on Twitter Dataset

With the exponential increase of social media users, cyberbullying has been emerged as a form of bullying through electronic messages. Cyberbullying detection is generally in social networks like Twitter is one of the focussed research area. Cyberbullying is serious and widespread issues affecting increasingly more Internet users. Text mining tools are detecting cyber bullying and deal with several issues. However the existing system has issue with time consumption and inaccurate Cyberbullying detection results for the given Twitter dataset. To avoid the above mentioned issues, in this work, Enhanced Cuckoo Search optimization (ECSO) and Hybrid Firefly Artificial Neural Network (HFANN) algorithm is proposed. The proposed system contains three main phases are such as preprocessing, feature subset selection and classification. The preprocessing is done by using k-means algorithm for reducing the noise data from the given Twitter dataset. It handles the missing features and redundancy features through k-means centroid values and min max normalization respectively. It is used to increase the classification accuracy more effectively. The pre-processed features are taken into feature selection process for obtaining more informative features from the Twitter dataset. It is performed by using ECSO algorithm and the objective function is used to compute the relevant and important feature based on the best fitness values. Then the HFANN algorithm is applied for classification through training and testing model. It classifies the features more accurately using best fireflies rather than the previous algorithms. The experimental result proves that the proposed ECSO+HFANN algorithm provides better classification performance in terms of lower time complexity, higher precision, recall, f-measure and accuracy than the existing algorithms.
Decision support system on quality assessment of the prospective civil servant’s education and training using fuzzy method

&lt;p&gt;This study aims to develop a decision support system using the fuzzy method in order to assess the quality of education and training of prospective civil servants and highlight possible improvement considerations. The assessment consists of six criterias, namely coaches, lecturers, preachers, mentors, examiners, and administrators. Based on the evaluation result of the quality level of each criterion, it is obtained that the top two criterion are examiners and preachers, followed by coaches, lecturers, advisors, and the lowest is organizer. In addition, the quality of the civil servant class III training is better than the class II civil servant training. It also shows that the value of the organizers criterion has different level of satisfactions. Overall, the quality of the training (according to the participants' opinion) was very good with a score of 92.50 for training class II and 95.20 for training class III. Furthermore, it is necessary to conduct research to determine the quality of the training each year by looking at the achievements of the participants. The &amp;gt;system testing obtained an accuracy of 100%, whichs implies that the system can be used to assess the quality of education and training appropriately.&lt;/p&gt;
Moral values found in the album thankyou allah by maher zein

This study aimed to find out the moral values in the album thank you Allah by Maher Zein and the theoretical implication for teaching songs and ELT. The research method used in this study was descriptive qualitative method. The sources of data were ten song lyrics from Maher Zein album. Method of collecting the data was triangulation: lyrics, interview, and book review. The data of this study were analyzed through: listening the songs, reading ten lyrics from the album, and analyzing the moral values by underlining, defining, classifying, reanalysing, and coding. The research found ten moral values in the album were: love and affection, believe, thankfully, forgiveness, loyalty, togetherness, honesty, bravery, courage and struggle. By analyzing the moral values, hopefully it could build the good character for us and finally we could give an inspiration to others. For the theoretical implication, it could be concluded that moral values could be taught through songs
Post2Event: Extracting Key Events from Microblogs

This paper demonstrates a prototype system called Post2Event that aims to extract key events from microblogs.While many events are hidden in microblogs, people may only care about those critical events, which are named key events in Post2Event.Specially, we propose to model the topic-related significance of an event and integrate the influence with the temporal characteristics of the event to measure the event's importance.We briefly present the architecture and technical details of Post2Event.Then, we report the comparative results of Post2Event on a real dataset.Finally, we demonstrate the running process of the system.
Формування готовності магістрів-філологів до науково-дослідницької діяльності

International scientific and practical conference «Pedagogy, psychology and teaching methods: international experience» : conference proceedings, July 16–17, 2021. Riga, Latvia : «Baltija Publishing», 2021. 295 pages.
Effective Geometric Hashing of the Feature Hyperspace for a Quick Accurate Search of the Most Similar Descriptors in Large Datasets

The algorithm of effective geometric hashing of the facial feature hyperspace for the accelerated search of the most similar face descriptors by their cosine similarity is described in the present study.The algorithm includes 6 required stages of processing descriptors extracted by a neural network from face images.The first stage is filtration of the descriptor database by selecting the most representative descriptor for each person from the set of descriptors corresponding to his/her different face images.The second stage is evaluation of a number of statistical values for all the components of the selected descriptors.The third stage is intermediate hashing through quantization of every descriptor component value so that almost the same quantity of descriptors corresponds to any quantum number.The fourth stage is statistical processing of the descriptor database to determine the most discriminative descriptor key components and their hierarchy.The fifth stage is calculation of the descriptor hash code for every most representative descriptor from the considered database.The sixth final stage is a special cataloging of data in the form of a multi-tiered directory ordered by the hash codes.The search acceleration is achieved through sparse processing of the whole directory when the hash code obtained for the requested person descriptor acts as a very selective search filter.The developed algorithm always provides the same absolute accuracy as the brute-force search.Through the example of the LFW dataset consideration, the average search acceleration by about 100 times is achieved under conditions that the descriptors have been extracted by a neural network trained on the WiderFace dataset with application of the additive angular margin loss function.
Prosody of Case Markers in Urdu

This paper studies the prosody of case clitics in Urdu, for which various different claims exist in the literature.We conducted a production experiment and controlled for effects potentially arising from the phonetics of the case clitics, the syntactic function they express and clausal position.We find that case clitics are incorporated into the prosodic phrase of the noun and that they become part of the overall LH contour found on accentual phrases in Urdu/Hindi.We also find some differences across case type and position which we tie to information structural effects.
MODEL COOPERATIVE INTEGRATED READING AND COMPOSITION (CIRC) UNTUK MENINGKATKAN HASIL BELAJAR BAHASA INDONESIA MATERI SURAT RESMI KELAS VI SD (The Cooperative Integrated Reading Composition [CIRC] Model to Increase The Student's Learning Result in Bahasa Indonesia Material Formal Letter Discussion in The Sixth Grade of Elementary School)

Kemampuan peserta didik dalam materi surat resmi sangat rendah sehingga perlu suatu model pembelajaran yang sesuai untuk mengingkatkan kemampuan tersebut. Penelitian ini bertujuan untuk meningkatkan hasil belajar Bahasa Indonesia materi surat resmi dengan model Cooperative Integrated Reading and Composition (CIRC) pada peserta didik kelas VI semester 2 SD Negeri 5 Manggar. Metode yang digunakan pada penelitian ini adalah penelitian tindakan kelas dengan metode analisis data kuantitatif dan deskriptif. Hasil analisis data kuntitatif, yaitu ketuntasan peserta didik secara klasikal pada kegiatan prasiklus 25%, siklus 1 41,7%, dan siklus 2 91,7%. Sedangkan analisis deskriptif terdapat peningkatan aktivitas positif peserta didik, yaitu bersemangat dan aktif mengikuti proses pembelajaran pada prasiklus 33,3%, siklus 1 75%, dan siklus 2 100%. Senang bertanya kepada guru atupun teman tentang materi yang sedang dipelajari pada prasiklus 25%, siklus 1 58,3%, dan siklus 2 83,3%. Menanggapi pertanyaan guru dengan baik pada prasiklus 25%, siklus 1 50%, dan siklus 2 91,7%. Student's competency in writing the formal letters was very low, so it's necessary to create a learning model that is able to increase the competency. The research aims to increase the learning result in Bahasa Indonesia subject on formal letter material by using cooperative integrated reading and composition to sixth-grade students of SD Negeri 5 Manggar in the second-semester academic year. The action research is chosen as a research method by quantitative and descriptive data analysis Through quantitative analysis result shown students' classical passing grade in the pra cycle is 25% than in the first cycle is 41.7 % and in the second cycle 91.7%. On the other hand, the result of descriptive analysis showed that there were some positive achievements in students' activities such as the level of curiosity and their involvement in the learning process. The achievement can be shown by the improvement of percentage in every cycle like 33.3 % in the pra cycle, 75% in the first cycle, and 100% in the second cycle. The study also impacts the increase of student's asking behavior, in the pra cycle 25%, the first cycle 58.3%, and the second cycle 83.3%. The student's responses to the teacher's questions increases from 25% in the pra cycle to 50% in the first cycle and 91.7% in the second cycle.
Оцінювання як функція управління та моніторингу якості вищої освіти України

International scientific and practical conference «Pedagogy, psychology and teaching methods: international experience» : conference proceedings, July 16–17, 2021. Riga, Latvia : «Baltija Publishing», 2021. 295 pages.
VR 360 as an Alternative for Virtual-Based Practicum Learning with Stereoscopic View

School education especially on primary school have a big impact to the children. Good and right education can sharpening the brain and influence the student with good attitude. Every information that attractive and easy to understanding is very important to give big impact for every primary school student, it also can provide a pleasant learning experience for these students. Therefore, this research develops a smartphone application that can provide a pleasant experience in learning knowledge of the surrounding environment from objects with virtual reality technology. To display these objects, a 360 ° panoramic image is used or a 2048px width 1024px width with a wide viewing angle (360 degrees) and this can be done by teachers to make the image or search for material sources on the internet. This technology allows students to see objects virtually. In use, this study requires a VR headset as a device for visualizing stereoscopic displays but it does not need installation because it is enough to access a smartphone browser then it will work. The system is designed using the spiral method as a process model and uses a-frame in application development. The interface can be run on the Android operating system. In making this application using the html programming language, laravel framework and a-frame framework.
Komunikasi Bencana di Twitter: Studi Kasus Bencana Banjir Perkotaan di Daerah Khusus Ibukota (DKI) Jakarta`

Social media occupies increasingly important roles in disaster response management. However, there are still doubts regarding the effectiveness of social media-based disaster communication. This paper aims to understand the discourse that emerge in Twitter containing facts or opinion regarding the flood disaster communication in DKI Jakarta under the different leadership of Basuki Tjahaja Purnama (2014- 2017) and Anies Rasyid Baswedan (2017-2020). This research used the methods of Corpus Assisted Discourse Study (CADS) and Actor Network Theory (ANT). These methods collected data on the discourse that is happening on Twitter and analyzes the network of actors who are active in discussions about floods in DKI Jakarta at different periods of leadership. This research found that the discourse that has developed on Twitter about floods in DKI Jakarta covers the personal problems of the leaders, the personality of the leaders, and the political position of the leaders, offered little messages that leads to solving the problem of flooding in DKI Jakarta. The active actor network is dominated by the local government of Jakarta as the responsibility holder or the main actor in delivering in information is only played by BPBD Jakarta.
Use of the mind mapping learning model to improve the ability of students writing fantasy story text

This study aims to see the ability to write fantasy stories in Indonesian language learning with the mind mapping model of class VII-2 students at SMP Negeri 13 OKU in the 2020/2021 academic year. The approach used is a quantitative approach. This type of research is descriptive research. The data analysis in this study is the result of the assessment of student work, namely 2 assessors, namely assessor 1 and assessor 2 accompanied by an average. The results showed that the implementation of teacher learning was going well. Based on the research results, it can be concluded that the ability to write fantasy stories using the Mind Mapping model is in the ability category. Suggestions for this research are 1) so that grade VII students can improve their writing skills to get better results. 2) so that teachers of SMP Negeri 13 OKU can use an easy and precise learning model in the learning process. 3) so that other researchers can use this thesis as a reference source.
Dynamic Simulation of the Jaynes-Cummings model ‎using the hybrid quantum-classical algorithm

The Jaynes-Cummings model is the canonical model for atom-light interactions, describing ‎a single confined bosonic mode interacting with a two-level system (qubit). This is ‎sufficient to describe a wide range of phenomena in quantum optics and quantum ‎computing. We simulate the dynamics of this model using the hybrid quantum-classical ‎algorithm (HQCA) consisting of quantum and classical computers. The parametric quantum ‎state preparations and quantum measurements are performed on the quantum computer ‎and parameters optimization employ on the classic computer. For implement of hybrid ‎quantum-classical algorithms, the Noisy Intermediate Scale Quantum (NISQ) computer is ‎used. In Noisy Intermediate Scale Quantum computers, we don’t need to error correction. ‎For this purpose, we transform Hamiltonian to qubit form and using an algorithm to obtain ‎the dynamic of the Jaynes-Cummings model. We obtain occupation probability and ‎transition probability in the Jaynes-Cummings model using the hybrid quantum-classical ‎algorithm. The output of the algorithm is compatible with the exact calculation‎‎‎‎.‎
Evaluating Visual Explanation of Bug Report Assignment Recommendations (S)

Software development projects typically use an issue tracking system where the project members and users can either report faults or request additional features.Each of these reports needs to be triaged to determine such things as the priority of the report or which developers should be assigned to resolve the report.To assist a triager with report assigning, an assignment recommender has been suggested as a means of improving the process.However, proposed assignment recommenders typically present a list of developer names without an explanation of the rationale.This work presents the results of a small user study to validate our approach to visually explaining bug report assignments.