Reviewerly/exHarmony huggingface dataset:
Pembelajaran Legenda Tiongkok pada Mahasiswa Pendidikan Bahasa Mandarin di Universitas Negeri Malang melalui Podcast Teatime Chinese

Podcast as learning media are believed to enlarge learners' motivation when learning a foreign language. In Chinese Literature History (CLH) course, the most difficult material faced by students of the Chinese Language Education Study Program at State University of Malang (CLESP UM) is fairy tales and legends. Students said that this theme will be easier to understand if it is presentive in audio form. Therefore, this study aimed to describe the use of the TeaTime Chinese 茶歇中文 [Chá Xiē Zhōngwén] podcast in the CLH course by means of students of the CLESP UM and to describe students responses to the utilization of the podcast media. This research used descriptive qualitative method with observation and questionnaire sheets as instruments. The first instrument was filled out by two observers and the second was filled out by 46 students of CLESP UM class of 2021. The results show that the utilize of the TeaTime Chinese 茶歇中文 [Chá Xiē Zhōngwén] podcast in the CLH course run well. Moreover, the questionnaire results depict that this podcast gain positive responses from students. They are able to understand the content of the podcast easier, find intrinsic and extrinsic elements in the story, and make cultural connections between China and Indonesia through the applied media. They also stated that the use of podcast can boost the learning atmosphere.
Current Status and Prospect in Research on Learner Cognitive Load Measurement

In recent years, a large number of studies have explored the specific methods of measuring learners' cognitive load from the perspectives of task performance, subjective assessment and physiological signals. In terms of task performance measurement, relevant researches mainly focus on learners' objective performance evaluation, and dual task measurement is an important method of task performance measurement. In terms of subjective assessment, relevant researches mainly focus on the development of cognitive load measurement scale. In terms of physiological signal measurement, different cognitive loads can lead to differences among learners in heart rate variability (HRV), electroencephalogram (EEG), skin electrical activity, and eye movement signals, etc., and cognitive loads are mainly indirectly measured using relevant instruments.
Creation of State Police and its Constitutionality: An Imperative for the Nigerian State

This paper makes a case for the creation of state police in Nigeria because of the country’s ongoing security challenges. It states that the police force is under the control of the federal government. It addresses the Nigerian police’s plethora of problems such as inadequate manpower among others which have resulted in their incapacity to maintain peace and order and safeguard people’s lives and property. The case for the establishment of state police is justified and well-founded because states are closer to the people and will be able to prevent alleged violent criminal offences. The paper also draws inferences from the United States in supporting the creation of state police as it exists there and the police have been playing its role in maintaining law and order. It states that for state police to become a reality, the provisions of section 214 CFRN 1999 should be amended to accommodate it.
The Intersections Based on Joint Observables In Fuzzy Probability

“Fuzzy probability theory” appeared as a smooth extension of classical probability theory in 1995. It was expected that it will be of great importance in quantum mechanics, but the theory doesn’t keep its development as it was expected. This necessitates revising some of its fundamental basic concepts. We argue that if quantum probability theory should have less constrained than classical probability theory as can be seen in the case of joint random variables, we surely need to weaken the definition of the intersection operation. In this paper, discuss the definition validity in quantum probability theory and to discuss the consistency of the given definitions with the whole theory and the possibility to have a more suitable definition.
Student satisfaction about the online teaching of the Engineering in Business Management program of the Technological Institute of Toluca

In the year 2020, educational institutions worldwide found it necessary to modify the way of teaching in response to the recommendations of health agencies to maintain social distancing to reduce the circulation of SAR-COV 2 and the development of COVID 19. The traditional way of teaching in which a classroom was attended in person, became staying at home and connecting to an electronic device that allowed the transmission of classes online. Given this new modality, this research aims to collect information through a student satisfaction survey of the academic program of Engineering in Business Management at the Technological Institute of Toluca of online classes during the semester of August-December 2020, period in which it was in pandemic. The variables to be considered were: Teaching, Academic Organization and Infrastructure and University Services. It is concluded from the results obtained that the students are satisfied with the performance of the teacher, however, there are also areas of opportunity in the management of digital platforms, as well as in the feedback and the time that is assigned to carry out conduct assessments online.
From Machine Learning to Deep Learning

This chapter provides a thorough grounding in the fundamental mathematical concepts of deep learning. It is first shown how a simple linear classifier can be defined based on the equation for a straight line. A more general scheme for optimization of the parameters of classifiers is introduced, based on gradient descent and its variants. We then see how the basic classifier model can be extended to produce simple artificial neural networks such as the perceptron and logistic regression. Next, these models are taken further to show how multiclass classification problems and nonlinearly separable data can be handled. Finally, the idea of a convolutional neural network is introduced and we see how this leads to the idea of deep learning. A practical tutorial is provided to give the reader some practical experience of developing classification models using Python.
ANALISIS DEBIT BANJIR RANCANGAN UNTUK NORMALISASI SALURAN DRAINASE DAN DESAIN DINDING PENAHAN TANAH DI DAERAH SEKITAR SUNGAI EPHEMERAL

Rehabilitation of buildings around the area around the river is considered by the owner of the activity because during high rainfall it will cause flooding. Flooding will result in delays in the building rehabilitation process because river water overflows into the activity location. One of the areas around a river in Bali, namely Tukad Bangin located in Pecatu Badung, is an ephemeral river, namely a river whose water only exists during the rainy season and often floods due to abnormal drainage channels and the absence of retaining walls. In the environment around Tukad Bangin there are buildings which during the rainy season cause frequent flooding, so a plan for building rehabilitation is carried out by making drainage channels and senders, then the results of calculating the design flood discharge in the Tukad Bangin Pecatu Badung area are carried out. The method used in this study is a quantitative method, namely measuring from direct observation at Tukad Bangin and then calculating the design flood discharge for various return periods for planning the design of drainage channels and shores. The results of the design flood discharge analysis with Q1 year are 15.47 m3/sec, Q2 year is 49.74 m3/sec and Q5 year is 65.89 m3/sec. From the simulation results of the water surface profile, the extreme depth values for discharge at 2-year return period are 1.54 m, 5-year return periods are 1.80 m, 10-year return periods are 1.93 m, 25-year return periods are 2.06 m and a 50-year return period of 2.04 m, so that with the HEC-RAS modeling it can control the height of the flood protection embankment and the design of the planned drainage channels and canals can be carried out.
Strategies Of Responding To Praise Used By Hasanuddin University Students: Sociopragmatic Analysis

This study aims to analyze the strategies for responding to praise used by Hasanuddin University students. This research is a qualitative research using descriptive method and the approach used in this research is a socio pragmatic approach. The data from this study were obtained from questionnaires distributed by researchers. After the data was obtained, the researcher analyzed the answers from the respondents using 12 praise response strategies according to Holmes, after which they were linked to the theory of praise indicators from Golato. The results in this study, namely the respondents in this study tend to accept the praise given and the most widely used praise response strategy is Strategy 1, namely Appreciation Token, Strategy 2 is Comment Acceptance and Strategy 3 is Praise Upgrade. Between the three ethnic backgrounds (Makassar, Bugis and Toraja) and the two sex groups (Male and Female), there was no significant difference in the choice of strategies to receive praise (Use of strategies 1, 2 and 3). Among the three categories of familiarity level, respondents tend to receive praise and use Strategy 1 (Appreciation Token) the most when meeting foreigners compared to using strategy 2 or strategy 3 where both of these strategies are used quite a lot (besides strategy 1) to provide an acceptance response a compliment delivered by a friend or friend
Trustworthiness Management Based on Blockchain in the Internet of Things

In the smart Internet of Things (IoT), if the identity of the message source is not evaluated, malicious nodes will attack other nodes by publishing malicious information or requests. This paper proposes a trust management mechanism for IoT devices based on blockchain. The information of each node is stored through the blockchain, and the Internet of Things equipment receiving communication messages grants different permissions by querying the reputation level of relevant nodes through the blockchain. The reputation level of nodes is calculated by historical behavior. Due to the limited storage capacity of some IoT devices, this paper proposes a special node, namely the cluster head, for storage and trust management. At the same time, the security of the proposed trust mechanism is evaluated, and the results show that the management mechanism can protect the secure communication of IoT devices more effective.
Research on language expression query method based on XML

Data is self-descriptive, extensible, and has both content and structure information. Documents are commonly found on web pages, business texts, digital libraries, etc., and the number of documents is increasing exponentially. In this paper, through the research of the language keyword query method based on XML, it can effectively reduce the query result set and improve the query accuracy. In the process of evaluation, we use the grading gauge and present it online to the raters based on the computer platform, which can not only standardize the grading process and ensure the reliability of the grading results to a great extent, but also provide personalized ability performance feedback for learners and teachers, so as to facilitate them to check the gaps and make up for the gaps, aiming to promote learning through evaluation.
Application Analysis of Forecasting Model Based on BP Neural Network Algorithm

With the development of big data technology, the hotel industry has also entered the era of big data. The imbalance between supply and demand in the hotel industry will directly affect the hotel's operating conditions. This paper uses the BP neural network algorithm to predict the hotel's demand analysis and reservation rate, and establishes a prediction model based on the BP neural network algorithm through the two variables of reservation time and consumption time. Investors can make better decisions, thereby increasing hotel revenue.
User Study: Implementation of OCLC FAST Subject Headings in the Lafayette Digital Repository

Digital repository migrations present a periodic opportunity to assess metadata quality and to perform strategic enhancements. Lafayette College Libraries implemented OCLC FAST (Faceted Application of Subject Terminology) for its digital image collections as part of a migration from multiple repositories to a single one built on the Samvera Hyrax open-source framework. Application of FAST has normalized subject headings across dissimilar collections in a way that tremendously improves descriptive consistency for staff and discoverability for end users. However, the process of applying FAST headings was complicated by several features of in-scope metadata as well as gaps in available controlled subject authorities.
DisCoHead: Audio-and-Video-Driven Talking Head Generation by Disentangled Control of Head Pose and Facial Expressions

For realistic talking head generation, creating natural head motion while maintaining accurate lip synchronization is essential. To fulfill this challenging task, we propose DisCoHead, a novel method to disentangle and control head pose and facial expressions without supervision. DisCoHead uses a single geometric transformation as a bottleneck to isolate and extract head motion from a head-driving video. Either an affine or a thin-plate spline transformation can be used and both work well as geometric bottlenecks. We enhance the efficiency of DisCoHead by integrating a dense motion estimator and the encoder of a generator which are originally separate modules. Taking a step further, we also propose a neural mix approach where dense motion is estimated and applied implicitly by the encoder. After applying the disentangled head motion to a source identity, DisCoHead controls the mouth region according to speech audio, and it blinks eyes and moves eyebrows following a separate driving video of the eye region, via the weight modulation of convolutional neural networks. The experiments using multiple datasets show that DisCoHead successfully generates realistic audio-and-video-driven talking heads and outperforms state-of-the-art methods. Project page: https://deepbrainai-research.github.io/discohead/
High-Level Feature Fusion Network for Session-Based Social Recommendation

The session-based social recommendation task aims to leverage knowledge from social networks to predict user actions based on their sessions. Most previous studies pay more attention to complex transitions to get item embedding in various ways and neglect the importance of users’ role in social network. Therefore, we design a High-level Feature Fusion Network to address these issues. Firstly, to better leverage the knowledge from social networks, we use a heterogeneous graph neural network to enhance the user/item representation. Secondly, a user-based graph attention network is adapted to learn the user’s deep interest evolution process. Next, user and session features are transferred to our feature fusion module to generate fusion features, and the original and fusion features are combined to make recommendations. Extensive experiments on three public datasets show that the proposed model outperforms existing state-of-the-art models.
Plasmon Enhanced Quantum Properties of Single Photon Emitters with Hybrid Hexagonal Boron Nitride Silver Nanocube Systems

Hexagonal boron nitride (hBN) has emerged as a promising ultrathin host of single photon emitters (SPEs) with favorable quantum properties at room temperature, making it a highly desirable element for integrated quantum photonic networks. One major challenge of using these SPEs in such applications is their low quantum efficiency. Recent studies have reported an improvement in quantum efficiency by up to two orders of magnitude when integrating an ensemble of emitters such as boron vacancy defects in multilayered hBN flakes embedded within metallic nanocavities. However, these experiments have not been extended to SPEs and are mainly focused on multiphoton effects. Here, we study the quantum single photon properties of hybrid nanophotonic structures composed of SPEs created in ultrathin hBN flakes coupled with plasmonic silver nanocubes. We demonstrate > 200% plasmonic enhancement of the SPE properties, manifested by a strong increase in the SPE fluorescence. Such enhancement is explained by rigorous numerical simulations where the hBN flake is in direct contact with the Ag nanocubes that cause the plasmonic effects. The presented strong and fast single photon emission obtained at room-temperature with a compact hybrid nanophotonic platform can be very useful to various emerging applications in quantum optical communications and computing.
Correlation filter tracking of channel response constraints

Abstract To solve the problem of moving object loss and inaccurate localization caused by the rapid change of object appearance, partial occlusion, and scale change in the tracking process, the channel response constraints correlation filter was proposed, i.e., CRCCF. Firstly, the channel self-optimizing regularization is introduced on the background-aware correlation filter (BACF), reducing the interference of redundant channel information to adapt to the complex environment. Then, the different response error regularization was introduced, the work used differences of adjacent frames response figures to learn the object appearance changes, which can smooth the volatility of the response figure to alleviate the drift problem model. And the Alternating Direction Method of Multipliers (ADMM) is used to optimize the model. Finally, a large number of experiments were carried out on OTB50, and OTB100 datasets to verify that the proposed algorithm has better performance under the conditions of fast motion, background clutter, and motion blur.
Integração de Dados de Publicações Científicas usando uma Abordagem baseada em Ontologias

ABSTRACTData integration has gained increasing importance with the growingvolume of available data (so-called Big Data). It allows to putdata from different sources together in an aligned way, so meaningfulinformation can be extracted. Scientific publications are availablein several data sources along the Internet. Integrating data fromthese distributed sources faces a challenge, mainly if we considerthe heterogeneous aspects inherent to the structure/schema andthe semantics of data. This paper presents a semantic integrationinitiative for integrating data from three distinct scientific publicationsources into a shared repository. The integration processis conducted by a systematic approach that creates and applies awell-founded domain ontology to address the semantic aspects andto map concepts, relations, and data between the different datasources. As a final result, a web tool was built over the integratedrepository to support some final user queries.
Pengaruh Edukasi Media Power Point dan Lagu Terhadap Pengetahuan Serta Sikap Konsumsi Sayur dan Buah Siswa

The prevalence of vegetable and fruit eating habits &lt;5 servings a day in children aged ≥ 5 years in Banten Province is 97%. This figure is greater than the national figure of 95.5% (Riskesdas, 2018). Lack of access to information in children can result in children's knowledge and attitudes are also not good towards vegetable and fruit consumption. This study aims to improve the knowledge and attitudes of students of SDN Cireundeu 01 about vegetable and fruit consumption using power point media and songs. This education is given to students aged 11-12 years, because at that age children are considered to be able to think abstractly according to Jean Piaget's Theory. Experimental research with sampling technique, namely Pusposive Sampling. The study used data analysis with the Paired T-test and Wilcoxon Test to determine the average difference in pre-test and post-test values. In the power point group, the knowledge level of p value 0.150 means that there is no significant difference, while the attitude of p value 0.538 means that there is no significant difference. In the song group, the knowledge level of p value 0.005 means that there is a significant difference, while the attitude of p value 0 means that there is a significant difference. Education with songs has a higher mean difference than education with a power point at the student's knowledge level of 7.38. In addition, education with songs also has a higher mean difference than education with a power point on the change in student attitudes by 0.295.
Application Possibilities of Computer Software in the Context of the Art Teaching

The development of technology has significant implications for human creativity. The nature of creative processes is being redefined, and technology is playing an increasingly important role in creative activities, becoming a tool or an extension of the creator's hand helping to integrate a new idea. Implications are also evident in the teaching of fine arts, enhancing the possibilities of stimulating students’ creativity using computer software. This assisted creation system is empowering for the student, as it enables him / her to acquire new abilities and a wide range of creative skills, as well as facilitating the formation of personal semantics. In order to determine the possibility of using computer software in the teaching of fine arts, research has been conducted among subject teachers. The aim is to determine the extent to which teachers of fine arts are familiar with software suitable for visual design, to establish whether they use it in their educational work, and to examine the methodical specifics of the realization such teaching. The results of the research are significant for the processes of designing initial university education programs, as well as in programs for lifelong professional teacher training, both for the purpose of educating teachers about the possibilities of using computer software and their impact on enhancing students’ creativity. The results can be a real boost for teachers who want to complement and strengthen their educational practice.
Peningkatan Hasil Belajar Siswa Kelas V dengan Penerapan Model Pembelajaran Kooperatif Tipe STAD

The main problem of this research is the starting point of the low learning outcomes of grade V SDN 1 Sijunjung caused by the conventional learning process. Learning that is passive and does not create student creativity results in learning goals that are not optimal. The purpose of this study was to determine the improvement of student learning outcomes in grade V SDN 1 Sijunjung by applying the STAD learning model. The method used is Classroom Action Research (PTK) which consists of two cycles, with each cycle consisting of 2 meetings. Each hypothesis cycle was tested through hasial learning data from 20 grade V students of SDN 1 Sijunjung 2019/2020 academic year through observation and documentation techniques. The data analysis technique used is qualitative and quantitative analysis. The results showed that the pre-test data for the cognitive aspects were 1375 with a mean of 68,75, then after the application of the STAD learning model, the number of values increased by 21,75 points to 1810 with a mean of 90,50. Meanwhile, the pre-test data for the psychomotor aspect amounted to 1415 with a mean of 70,75 and the post-test increased by 9,75 points to 1690 with a mean of 84,50. Thus the application of the STAD learning model can improve the learning outcomes of fifth grade students at SDN 1 Sijunjung.