Reviewerly/exHarmony huggingface dataset:
Learning Motivation and Parenting Styles of Parents and Their Relationship to Social Studies Learning Outcomes for Elementary School Students

The problem of this research is the variation in student social studies learning outcomes. There is a tendency caused by two factors: learning motivation as an internal factor and parenting as an external factor. This study analyzes parents' learning motivation and parenting styles on students' social studies learning outcomes. This type of research is Expo facto research. The population is 49 students. The population was taken using a saturated sample (study population). Data were collected using questionnaires and document recording. Data were analyzed by regression analysis technique. The prerequisite test for regression analysis and hypothesis testing uses simple regression, product-moment correlation, and multiple regression. The results showed a real and positive relationship between parenting styles and social studies learning outcomes. This was indicated because the R-count (0.449) &gt; from r-table 5% = (0.233) was significant. Simultaneously, it was found that there was a relationship between learning motivation and parenting styles on social studies learning outcomes. It can be seen that r count 0.740 &gt; r table 0.233 as well as based on the results of testing with the F test (simultaneously) with = 5% then it can be seen that the learning motivation and parenting styles of parents are simultaneously significantly related to social studies learning outcomes. The research implications are related to the second problem, namely the relationship between parenting styles and students' social studies learning outcomes.
TINJAUAN PERENCANAAN DRAINASE JALAN RAYA SIMPANG EMPAT – AIR BALAM KABUPATEN PASAMAN BARAT

The problem of flooding or inundation often occurs on Indonesian roads, including on the Simpang Empat-Air Balam road, West Pasaman Regency. So that it annoys road users and causes damage to the pavement. Stagnant caused by a drainage system that is not optimal due to sedimentation in the curb inlet and in the side channel. So to find out how the drainage system is performing, a hydrological analysis is carried out to calculate the design discharge for a period of 10 years according to the drainage area and typology of the district and then compared with the discharge of the existing channel and culvert. The results of the comparison of the planned discharge and the existing discharge indicate that the side channel cannot accommodate the design discharge, so it is necessary to redesign the dimensions of the side and culvert. Keywords: hydrological analysis, design discharge, side dimension re-planning
Analisis Sitasi dalam Penulisan Skripsi Mahasiswa Prodi Ilmu Hukum Universitas Lancang Kuning dan Prodi Ilmu Hukum Universitas Islam Riau

This study aims to determine the citation of thesis students of the law study program at Lancang Kuning University and the law study program at the Islamic University of Riau. The research method used is descriptive quantitative with a literature study approach. The results showed that there were 14 types of regulations used by Lancang Kuning University students and 19 types of regulations that were most widely used by law study program students at the Islamic University of Riau. The type of citation most widely used by these two universities is the law with the use of almost all of it in part with a total of 48.98% carried out by students of the Lancang Kuning University law study program and mostly used by students of the law study program at the Islamic University of Riau with a total of 60.87%. The most widely used type of law is law. No. 8 of 1981 concerning Criminal Procedure Code by Lancang Kuning University and the Civil Code by the Islamic University of Riau. The most widely used citation year at the two universities was in the range of 2000 to 2010.
Making Ends Meet by Mining on Blockchain

While public narratives indicate that blockchain is widely used in developed societies among privileged elites, either from socio-economic, ethnic, or techno-cultural perspectives, this study examines how some disadvantaged marginal others, specifically the subaltern shehuiren in China, survive in the increasingly precarious post-socialist Chinese society by engaging with blockchain and cryptocurrencies. Literally translated as “society people”, shehuiren are the socio-economically and techno-culturally disadvantaged others who face marginality due to various post-socialist institutional inequalities. This study aims at unpacking how, on the one hand, the blockchain scene has been reconfigured by the disadvantaged in the local context, and on the other hand, how subalternity is actualized in post-socialist China, where blockchain-related technologies deeply intertwine with various forms of social inequalities. By tracing a group of shehuiren crypto miners through ethnography, I demonstrate that this subaltern scene of blockchain not just reshapes the shehuiren individuals’ notion of time, space, and value and the social relationship among themselves, but also profoundly impacts the power dynamics between the subalterns, the more privileged others, and the state authorities. Specifically, I underline that, despite being treated as losers, outsiders, and potential wrongdoers due to the existing social structures, shehuiren miners are neither victims nor rebels opposing either the authoritarian state or the global neoliberal order. Instead, they are actors who harvest limited profits through their unacknowledged creativity, adeptly making use of various resources within their reach and weaving their differential aspirations by attaching themselves to the larger technology-mediated networks in an unequal post-socialist society where a united subaltern hardly exists.
Deep Learning-based Reconstruction of Shredded Documents

This thesis addresses the reconstruction of shredded paper documents, a relevant task in various domains such as forensic investigation and history reconstruction. Despite previous research, dealing with real-shredded data is a sensitive issue in the literature. To face this challenge, we proposed two deep learning approaches that have achieved state-of-the-art accuracy in more realistic scenarios. As a second major contribution, human interaction was explored to improve reconstruction. Our framework, inspired by the field of active learning, automatically selects potential mistakes in the solution for user analysis enabling better accuracy in a scalable way. The results yielded works in top-tier publications such as CVPR and the Pattern Recognition journal.
Dynamic allocation of microservices for virtual reality content delivery to provide quality of experience support in a fog computing architecture

Virtual Reality (VR) content is gaining popularity and allowing users to immerse themselves in a new world over the Internet. However, the high-demand for resources and the low latency requirements of VR services require changes in the current 5G networks to deliver VR with quality assurance. Microservices present a suitable model for deploying services at different levels of a 5G fog computing architecture for managing traffic and providing Quality of Experience (QoE) guarantees to VR clients. However, finding the most suitable fog node to allocate microservices for VR clients in QoE-aware 5G scenarios is a difficult task. This article proposes a QoE VR-based mechanism for allocating microservice dynamically in 5G architectures, called Fog4VR. Fog4VR determines the optimal fog node to allocate the VR microservice based on delay, migration time, and resource utilization rate. This article also presents the INFORMER, an integer linear programming model aiming to find the optimal global solution for microservice allocation. Results obtained with INFORMER serve as a baseline to evaluate Fog4VR in different scenarios using a simulation environment. Results demonstrate the capabilities of Fog4VR compared to existing mechanisms in QoE, migration time, fairness index, and terms of cost.
Study of the underground tunnel planning. Cognitive modelling

A study of the underground tunnel planning reliability for megacities is proposed based on the use of foresight and cognitive modeling methodologies. Using the foresight methodology allows, with the help of expert estimation procedures, to identify critical technologies and build alternatives of scenarios with quantitative characteristics. For the justified implementation of a particular scenario, cognitive modeling is used, which allows to build causal relationships based on knowledge and experience, understand and analyze the behavior of a complex system for a strategic perspective with a large number of interconnections and interdependencies. The suggested study allows the reliability planning of underground tunnels on the basis of reasonable scenarios selection and justification of their creation priority.
Research on the Effect of the Students’ Online Learning and Its Influencing Factors

In order to clarify the related factors that affect the online learning effect and better help teachers to effectively improve the quality of online teaching, a random sampling survey was conducted through online questionnaires, and stata26.0statistical tools were used to analyze the influence of individual characteristics on college students' online learning effect, in order to find out the main influencing factors.The results show that there is a correlation between the selected individual characteristics and the learning effect.Students' previous experience, learning motivation and self-efficacy have a significant positive impact on online learning effect.
The conclusion of the limitless hotel problem

Mathematician Cantor's Set theory appeared paradox and mathematical theory crisis. The famous German mathematician Hilbert used "Hilbert Hotel" to describe Cantor's Set theory paradox. At that time, people could not find a strict mathematical theory to refute Cantor's Set theory, but let everyone get used to and accept Cantor's Set theory, and thought that it was not a paradox. After the proposal of the limitless Hotel question, it caused controversy between the two parties. I quoted the definition of mathematical logic and got the correct answer. Proved that there is no paradox in limitless hotels (Reason: limitless hotels cannot increase the number of new guests staying.). A deep analysis of Cantor's limitless elements and the infeasibility of one-to-one correspondence was conducted. 2020 Mathematics Subject Classification: 03G27, 03F07, 03D45, 03F55
PEMBELAJARAN MENULIS TEKS BERITA BERFOKUS PADA STRUKTUR TEKS MENGGUNAKAN METODE NATURE LEARNING PADA PESERTA DIDIK KELAS VIII DI SMP ANGKASA LANUD HUSEIN SASTRANEGARA

This study is motivated by the low ability of students in writing news texts. This is because educators are less creative in choosing learning methods and less motivating students to write. The formulation of the problem compiled by the author is the author's ability to plan, implement, apply the ability to write news texts focusing on text structure using the nature learning method, the ability before and after using the nature learning method, and the difference in the ability of students to write news texts after using the nature learning method. The objectives of this study include to test the author in planning, implementing, applying, and evaluating the nature learning method in writing news texts, testing the ability of students before and after using the nature learning method, and testing the difference in the ability to write news texts using the nature learning method. The method used is quantitative method. The object of this research is students of class VIII of SMP Angkasa Lanud Husein Sastranegara Bandung, using two classes as experimental and control classes. The results showed that the ability to write news texts of grade VIII students at SMP Angkasa Lanud Husein Sastranegara Bandung was in the good category. This is supported by the data of the average results of the pretest of 40.00 and posttest of 84.80. Thus, the nature learning method is effectively used to improve the ability to write news texts. In addition, the nature learning method is significant in improving the ability to write news texts, this is proven based on the results of statistical calculations using the Mann Whitney-U Test which shows that the Asymp. Sig. 0,021&lt;0,05. Based on the results of the study, the nature learning method is effective and can be used as an alternative in learning to write news texts in class VIII.
High-Performance Elliptic Curve Cryptography: A SIMD Approach to Modern Curves

Cryptography based on elliptic curves is endowed with efficient methods for public-key cryptography. Recent research has shown the superiority of the Montgomery and Edwards curves over the Weierstrass curves as they require fewer arithmetic operations. Using these modern curves has, however, introduced several challenges to the cryptographic algorithm’s design, opening up new opportunities for optimization. Our main objective is to propose algorithmic optimizations and implementation techniques for cryptographic algorithms based on elliptic curves. In order to speed up the execution of these algorithms, our approach relies on the use of extensions to the instruction set architecture. In addition to those specific for cryptography, we use extensions that follow the Single Instruction, Multiple Data (SIMD) parallel computing paradigm. In this model, the processor executes the same operation over a set of data in parallel. We investigated how to apply SIMD to the implementation of elliptic curve algorithms. As part of our contributions, we design parallel algorithms for prime field and elliptic curve arithmetic. We also design a new three-point ladder algorithm for the scalar multiplication P + kQ, and a faster formula for calculating 3P on Montgomery curves. These algorithms have found applicability in isogeny-based cryptography. Using SIMD extensions such as SSE, AVX, and AVX2, we develop optimized implementations of the following cryptographic algorithms: X25519, X448, SIDH, ECDH, ECDSA, EdDSA, and qDSA. Performance benchmarks show that these implementations are faster than existing implementations in the state of the art. Our study confirms that using extensions to the instruction set architecture is an effective tool for optimizing implementations of cryptographic algorithms based on elliptic curves. May this be an incentive not only for those seeking to speed up programs in general but also for computer manufacturers to include more advanced extensions that support the increasing demand for cryptography.
Research on the Application of Multimedia Technology in Junior High School Music Classrooms

Music education is an important part of quality education in our country.Music education is an important way to improve people's comprehensive culture and artistic accomplishment, and an important means to promote our music development.In the process of junior high school music teaching, the author found that the traditional junior high school music teaching model has been unable to adapt to the development of The Times, the junior high school music education model needs to be innovative.Nowadays, with the continuous update of science and technology and the rapid development of multimedia education technology, traditional music education should be combined with modern multimedia education technology.This study mainly finds out the factors that influence the effect of multimedia educational technology in junior middle school music education, and improves the SVM Algorithm, and establishes the I-P-O analysis framework.
Assessing system impedance based on data regrouping

In recent years, assessing supply system impedance has become crucial due to the concerns on power quality and the proliferation of distributed generators.In this paper, a novel method is shown for passive measurement of system impedances using the gapless waveform data collected by a portable power quality monitoring device.This method improves the overall measurement accuracy through data regrouping.Compared with the traditional methods that use the consecutive measurement data directly, the proposed method regroups the data to find better candidates with less flotation on the system side.Simulation studies and extensive field tests have been conducted to verify the effectiveness of the proposed method.The results indicate that the proposed method can serve as a useful tool for impedance measurement tasks performed by utility companies.
Modulation Recognition Method for Underwater Acoustic Communication Signals Based on Passive Time Reversal-Autoencoder with the Synchronous Signals

In the process of the modulation recognition of underwater acoustic communication signals, the multipath effect seriously interferes with the signal characteristics, reducing modulation recognition accuracy. The existing methods passively improve the accuracy from the perspective of selecting appropriate signal features, lacking specialized preprocessing for suppressing multipath effects. So, the accuracy improvement of the designed modulation recognition models is limited, and the adaptability to environmental changes is poor. The method proposed in this paper actively utilizes common synchronous signals in underwater acoustic communication as detection signals to achieve passive time reversal without external signals and designs a passive time reversal-autoencoder to suppress multipath effects, enhance signals’ features, and improve modulation recognition accuracy and environmental adaptability. Firstly, synchronous signals are identified and estimated. Subsequently, a passive time reversal-autoencoder is designed to enhance power spectrum and square spectrum features. Finally, a modulation classification is performed using a convolutional neural network. The model is trained in simulation channels generated by Bellhop and tested in actual channels which are different from the training period. The average recognition accuracy of the six modulated signals is improved by 10% compared to existing passive modulation recognition methods, indicating good environmental adaptability as well.
THE USE OF MORPHOLOGICAL AWARENESS TO IMPROVE STUDENTS’ VOCABULARY KNOWLEDGE

Vocabulary plays an important role in language acquisition. By mastering vocabulary, the students can express their idea easily. The reality, many students have a limited vocabulary. This paper focuses on the use of morphological awareness to increase students' vocabulary knowledge. The researcher applied Quantitative Research. The instrument used to collect the data was tests. The pre-test is to determine the level of students' vocabulary mastery before being given the treatment, while the post-test test is used to find out the results after being given the treatment. There is a significant difference between pre-test and post-test scores, there is a morphological effect on vocabulary knowledge at Ma'had Al-Jamiah IAIN Palu with foreign languages. This is evidenced by the results obtained where the final result of the average value of students is 67.2 while the previous grade was 34 and has increased by about 97%. This research is in accordance with the target. Thus, there is a significant increase after being given the treatment of Using Morphological Awareness to Increase Students' Vocabulary Knowledge.
Optimized Deep Neural Networks Audio Tagging Framework for Virtual Business Assistant

A virtual assistant has a huge impact on business and an organizations development.It can be used to manage customer relations and deal with received queries, automatically reply to e-mails and phone calls.Audio signal processing has become increasingly popular since the development of virtual assistants.Deep learning and audio signal processing advancements have dramatically enhanced audio tagging.Audio Tagging (AT) is a challenge that requires eliciting descriptive labels from audio clips.This study proposes an Optimized Deep Neural Networks Audio Tagging Framework for Virtual Business Assistant to categorize and analyze audio tagging.Each input signal is used to extract the various audio tagging features.The extracted features are input into a neural network to carry out a multi-label classification for the predicted tags.Optimization techniques are used to improve the quality of the model fit for neural networks.To test the efficiency of the framework, four comparison experiments have been conducted between it and some of the others.From these results, it was concluded that this framework is better than the others in terms of efficiency.When the neural network was trained, Mel-Frequency Cepstral Coefficient (MFCC) features with Adamax achieved the best results with 93% accuracy and a 0.17% loss.When evaluating the performance of the model for seven labels, it achieved an average of precision 0.952, recall 0.952, F-score 0.951, accuracy 0.983, and an equal error rate of 0.015 in the evaluation set compared to the provided Detection and Classification of Acoustic Scenes and Events (DSCASE) baseline where he achieved and accuracy of 72.5% and a 0.209 equal error rate.
Policy for Media School Activity for the Youth in the Gedeg Village Community

Universitas Negeri Semarang (UNNES) as a state university organizes community services (KKN) in the form of UNNES GIAT. During the implementation of UNNES GIAT in Gedeg Village, one of the problems found was the lack of education and knowledge levels. Based on the problems faced, policies are needed to improve education and knowledge, one of which is by providing Graphic Design Training. Students conduct workshops and educational assistance through media schools as an effort to solve problems in the field of graphic design, especially the younger generation group in Gedeg Village, namely IPNU and IPPNU. From the results of the activity it was found that the participants were very enthusiastic and fully accepted the material provided, from this it indicated that the activity was successful. In the end, special policies need to be made for schools in Gedeg in order to improve the quality of education from the perspective of technological progress, namely media schools.
Developing Augmented Reality Mobile App for Learning Nucleophilic Substitution Reaction Mechanisms in Organic Chemistry: User Perception and Experience

A prototype AR mobile app "Immersive Nucleophilic Substitution" (INS) has been developed to assist students in understanding the concept of unimolecular nucleophilic substitution (S N 1) and bimolecular nucleophilic substitution (S N 2) reaction mechanisms.This study aims to examine the perception and user experience of the INS app among the university Foundation in Science students.An online questionnaire with a 7-point Likert scale was used to measure the perceptions towards the AR from the aspects of performance, effort, social influence and motivation, and the user experience in terms of presence, usability, and flow.Open-ended questions were included to further understand the participant's experience with the INS app.There were 29 responses collected.The overall perception of students was rather positive (M = 5.00, SD = 1.00).Students perceived the app as more beneficial to increase their learning productivity but less enjoyable and motivating.They felt the app provided sufficient realism, responded well to the students' actions and had a good-quality interface.However, it is somehow unnecessarily cumbersome, dull, and boring.The overall positive rating (M = 5.55, SD = 1.33) indicates the INS app was fairly well received by students and feasible to progress for the learning outcome evaluation.