Reviewerly/exHarmony huggingface dataset:
An Analysis of Students Speaking Anxiety of Eleventh Grade Students at SMK Negeri 1 Lubuk Pakam

The objective of the research is to know the causes of students' anxiety in speaking English, the types of students' anxiety, and the level of students' anxiety in speaking English in the eleventh grade of SMK Negeri 1 Lubuk Pakam. This study uses qualitative methods by collecting data through observation, interviews, questionnaires, and documentation. The results of this study indicate that there are 3 factors of student anxiety in learning English according to Horwits' theory (2011), namely (1) Communication Apprehension, where students have difficulty speaking English because they do not have much knowledge about English, (2) Test Anxiety, where students feel anxious when they have to take an English test, and (3) Fear of Negative Evaluation, where students are afraid that the teacher and their friends will laugh if students make mistakes. According to Thomas (2009), there are also two types of student anxiety: State Anxiety and Trait Anxiety. And the questionnaire was developed by Horwitz with 33 statements, the results showed that 1 student (10%) experienced a high level of anxiety, 7 students (70%) experienced a moderate level of anxiety, and 2 students (20%) experienced mild anxiety.
Module Development of Teaching Materials for Explanation Text Materials in Indonesian Language Subjects to Increase the Reading Interest of Students in Class V Elementary School

&#x0D; &#x0D; &#x0D; &#x0D; Modules are learning materials that are designed in accordance with the applicable curriculum and are intended to achieve predetermined competency standards. Modules can be used to support subject matter, as well as make learning more interesting and fun. This study aims to develop a teaching material module for explanatory text material to increase students' interest in reading, to find out the assessments of three experts and the opinions of teachers and fifth grade elementary school students. In this study using the type of learning design development research or R&amp;D using the ADDIE module. The subjects of this study consisted of three experts (materials experts, linguists and media experts) as well as fifth grade elementary school students. The instrument used in this study was a questionnaire given to three experts obtained through research results, namely qualitative data which was analyzed using quantitative data in the form of numerical data. The results of this study are, to produce a module product of explanatory text material that meets very good criteria with the acquisition of an average validation score from three validators obtaining a value of 99% with a very feasible category to use, and a practicality level of 90% is in the very practical criteria and the level of effectiveness with an average of 91.8% is in the very effective category. The teaching material module of explanatory text material is feasible, practical and effective for use in learning.&#x0D; &#x0D; &#x0D; &#x0D;
Analisis Metode K-Nearest Neighbor Menggunakan Rapid Miner Untuk Memprediksi Hujan Kota Surakarta

This study aims to implement the K-Nearest Neighbor (KNN) algorithm using the Rapid Miner application to predict rain in Surakarta City. Rainfall has an erratic pattern making it difficult to predict manually. Rainfall cannot be determined with certainty but this can be estimated. Thus, the existence of Data Mining can enable machines to recognize and study complex data patterns. Therefore program learning can learn patterns of rainfall data to make some predictions. This study uses three variables as criteria, namely temperature, wind speed, and humidity. The test results using the K-Nearest Neigbor (KNN) algorithm and the Rapid Miner application with a value of K = 3, found an accuracy of 83.87%. From 31 data taken in July 2023. The results of the analysis prove that the KNN method using the Rapid Miner application can be used to predict rain in Surakarta City.
The Metric is the Message: Benchmarking Challenges for Neural Symbolic Regression

The neural symbolic regression (NSR) literature has thus far been hindered by an over-reliance on individual, ad hoc evaluation metrics, producing seemingly favorable performance for the method using it but making comparison between methods difficult. Here we compare the performance of several NSR methods using diverse metrics reported in the literature, and some of our own devising. We show that reliance on a single metric can hide an NSR method’s shortcomings, causing performance rankings between methods to change as the evaluation metric changes. We further show that metrics which consider the structure of equations generated after training can help reveal these shortcomings, and suggest ways to correct for them. Given our results, we suggest best practices on what metrics to use to best advance this new field.
Unsupervised Domain Adaptation via Bidirectional Cross-Attention Transformer

Unsupervised Domain Adaptation (UDA) seeks to utilize the knowledge acquired from a source domain, abundant in labeled data, and apply it to a target domain that contains only unlabeled data. The majority of existing UDA research focuses on learning domain-invariant feature representations for both domains by minimizing the domain gap using convolution-based neural networks. Recently, vision transformers have made significant strides in enhancing performance across various visual tasks. In this paper, we introduce a Bidirectional Cross-Attention Transformer (BCAT) for UDA, which is built upon vision transformers with the goal of improving performance. The proposed BCAT employs an attention mechanism to extract implicit source and target mixup feature representations, thereby reducing the domain discrepancy. More specifically, BCAT is designed as a weight-sharing quadruple-branch transformer with a bidirectional cross-attention mechanism, allowing it to learn domain-invariant feature representations. Comprehensive experiments indicate that our proposed BCAT model outperforms existing state-of-the-art UDA methods, both convolution-based and transformer-based, on four benchmark datasets.
MMA: Multi-Metric-Autoencoder for Analyzing High-Dimensional and Incomplete Data

High-dimensional and incomplete (HDI) data usually arise in various complex applications, e.g., bioinformatics and recommender systems, making them commonly heterogeneous and inclusive. Deep neural networks (DNNs)-based approaches have provided state-of-the-art representation learning performance on HDI data. However, most prior studies adopt fixed and exclusive $$L_2$$ -norm-oriented loss and regularization terms. Such a single-metric-oriented model yields limited performance on heterogeneous and inclusive HDI data. Motivated by this, we propose a Multi-Metric-Autoencoder (MMA) whose main ideas are two-fold: 1) employing different $$L_p$$ -norms to build four variant Autoencoders, each of which resides in a unique metric representation space with different loss and regularization terms, and 2) aggregating these Autoencoders with a tailored, self-adaptive weighting strategy. Theoretical analysis guarantees that our MMA could attain a better representation from a set of dispersed metric spaces. Extensive experiments on four real-world datasets demonstrate that our MMA significantly outperforms seven state-of-the-art models. Our code is available at the link https://github.com/wudi1989/MMA/
DualMatch: Robust Semi-supervised Learning with Dual-Level Interaction

Semi-supervised learning provides an expressive framework for exploiting unlabeled data when labels are insufficient. Previous semi-supervised learning methods typically match model predictions of different data-augmented views in a single-level interaction manner, which highly relies on the quality of pseudo-labels and results in semi-supervised learning not robust. In this paper, we propose a novel SSL method called DualMatch, in which the class prediction jointly invokes feature embedding in a dual-level interaction manner. DualMatch requires consistent regularizations for data augmentation, specifically, 1) ensuring that different augmented views are regulated with consistent class predictions, and 2) ensuring that different data of one class are regulated with similar feature embeddings. Extensive experiments demonstrate the effectiveness of DualMatch. In the standard SSL setting, the proposal achieves 9% error reduction compared with SOTA methods, even in a more challenging class-imbalanced setting, the proposal can still achieve 6% error reduction. Code is available at https://github.com/CWangAI/DualMatch .
Book review: Methodology for developing reading literacy "From text to meaning" (from work experience): a guide for learning and teaching / sci. eds.: N. L. Mishatina, I. V. Mushtavinskaya. Saint Petersburg: KARO, 2023. 208 p.

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PROBLEMS AND TRENDS OF FUNCTIONING OF PRINT MEDIA IN MODERN MEGAPOLISES

The article lists the functions of the metropolis; Threats for print media in St. Petersburg were identified: lack of sales opportunities for printed products, decline in popularity, emergence of similar niche media on the market, worsening of the general economic situation, intensification of rivalry from direct and indirect competitors, imitation of technologies for creating rating media by competitors, increasing demand for online publications; analyzed the advertising market of print media in St. Petersburg; estimated the volume of advertising in the means of its distribution in St. Petersburg over the past 12 years; describes the history of changes in the cost of print media; revealed the dynamics of development of enterprises in the industry; options for solving problems and neutralizing negative trends are proposed: increasing the revenue side of the print media budget by selling advertising space through an increase in demand for their products in the market, clearer segmentation of their target audience and, accordingly, developing an appropriate content strategy, increasing reader loyalty, increasing productivity through more detailed planning of the employee motivation system, income growth in the digital media segment, growth in the cost of services associated with limited supply.
HOTS-Based Pocketbook Development Using QR Scan

The purpose of this study is to develop a HOTS-based pocketbook using QR scans to create student-friendly learning media. The effectiveness of the products developed makes development research activities meaningful. This type of research uses R&amp;D (Research and Development) research or development research using the ADDIE model developed by Dick and Carry. This ADDIE model has five stages, namely, analysis, design, development, application, and evaluation. The subjects of the study were material experts, media experts, teachers, observers, and XI Science 1 students at MAN 1 Medan, totaling 30 students. Data collection techniques in this study are in the form of questionnaires and post-tests. Initially, the researcher designed the book, then made it until it reached the evaluation stage. The results showed that the percentage value of media experts was 84% and the results of material expert validation were 88% with very feasible criteria. While the practicality value is 93.33% with very practical criteria. The effectiveness value of this study was 76.83% with effective criteria. &#x0D; Keywords: pocketbook, QR scans, HOTS&#x0D;
OPPORTUNITIES AND CHALLENGES OF DIGITAL TRANSFORMATION IN EDUCATION IN THE COVID DISASTER IN VIETNAM

Coronavirus affects the education system in the world. Schools, colleges, and universities are closed to control the spread of the coronavirus. School closure brings difficulties for students, teachers, and parents. So, online learning is a solution to continue the education system. However, the lack of network infrastructures, computers, and internet access is challenging. This paper aims to review the impact of the COVID-19 pandemic on the education and status of digital transformation in education in Vietnam. Verify the opportunities and challenges in the digital transformation in education and recommend some issues that need to do be concerned to promote the transformation process in education in Vietnam.
An Assessment of the Broadcast Media Campaign against Drugs Abuse in Nigeria

The use of drugs to cure and heal the body system has been of irreplaceable value to humanity. In other words, it is practically impossible, if not impossible, to dispose of drugs. According to the World Health Organization (WHO), drug means any substance or product that is used or intended to be used to modify the physiological system or pathological state for the benefit of the recipient or user. Different scholarly studies have shown that drugs are useful to boost the immune and metabolic systems of a living being. However, the misuse and abuse of drugs have been problematic issues for the wellbeing of society. As a matter of fact, the abuse of drugs has been on the rise among youths in Nigeria. On a daily basis, many youths in Nigeria consume and abuse different drugs and substances such as heroin, cocaine, marijuana, codeine, amphetamines, narcotics, and the like that produce high dependence. This undoubtedly exposed many Nigerian youths to different harmful health conditions, such as deterioration and weak physical appearance, and irresponsible attitudes like stealing and fighting, among others. Hence, the aim of this paper is to critically examine the use and impacts of drug abuse or addiction among youths in Nigeria and the effectiveness of broadcast media campaigns against drug abuse in Nigeria. The paper will employ different research methods, such as conceptual analysis, to delineate the meaning of major concepts like drugs, drug abuse, and media; the method of critical assessment will also be used to critically evaluate and assess the impacts of media in the campaign against drug abuse among youths in Nigeria. The paper concludes with an affirmation that the intake of illegal drugs among youths in Nigeria is alarming and, as such, dangerous and harmful to their health. Hence, the paper recommends that the government and Non-government organizations should engage more in media campaigns against drug abuse and also be firm and unbiased in enforcing the laws against lawbreakers, especially youths engaging in the consumption of illegal drugs.
Evaluasi Jalur Evakuasi Bencana Kebakaran pada Vihara Prajna Chan

Vihara is a public building that is used to serve the needs of the general public as a meeting building for worship. Worship buildings must have comfort and security in every situation that can protect the facilities and visitors inside, including in the case of fire disaster rescue. At the Prajna Chan Temple, the fire disaster evacuation routes are still not fully met. Therefore, it is necessary to carry out an evaluation to determine the effectiveness of its use in accordance with the requirements of Minister of Public Works Regulation no. 26 of 2008, SNI 03-1735-2000, SNI 03-1746-2000, and SNI 03-6574-2001. The aim of this research is to determine the suitability of the conditions for the effectiveness of fire disaster evacuation routes in accordance with applicable standards and regulations and to become a more optimal design solution option for the monastery circulation area during the fire disaster evacuation process. The quantitative descriptive method is used as a research method where this method is carried out in several stages, such as through analysis of each component part based on existing standards and regulations. Quantitative data was obtained through the process of literature study, understanding working drawings, and observing data collection at the location. In general, the research results show that the feasibility level for fire disaster evacuation at Prajna Chan Temple only obtained 32% of the 88 requirements. The fulfillment of evacuation routes needs to be reviewed to optimize comfort, safety and smoothness of the evacuation process as a mitigation effort at the Prajna Chan Temple when a fire occurs.
Optimizing Local Repository Search with Bidirectional Encoder Representations from Transformer Models

—In this research, we investigate the relationship between sentence transformer models and the accuracy and recall of asymmetric semantic search engines. Our results show that the chosen sentence transformer model has a significant impact on the performance of the search engine. Using a pre-trained model specific to the domain resulted in a high cosine similarity score of 0.64. Fine-tuning a pre-trained sentence transformer for asymmetric semantic search improved the score to 0.4, but a larger corpus was needed for optimal results. Our findings highlight the importance of careful model selection and training data in the development of asymmetric semantic search engines.
Motion of energy

In [1], it was given that the principle defining movement of energy is equilibrium. This paper describes a further notion or reason that defines movement of energy. In [2], it was stated that energy moves from a place of higher magnitude to a place of lower magnitude. This paper highlights a simple reason defining motion of energy by reasoning.
The Relationship between Physical Fitness, Obesity and School Grades in Elementary School Students

The purpose of this study was to investigate the relationship between physical fitness level & obesity and school grades among elementary school students. For this study, 158 elementary school students were selected. Their physical fitness levels were classified using the Physical Activity Promotion System(PAPS) and collected final term school grades was analyzed. There was a statistically significant correlation between the physical fitness level and school grades in each subject among female students. After adjusting for body mass index, when school grades was compared according to physical fitness level, the English, mathematics, social study, and total grades of female students with high physical fitness levels were statistically significantly higher than female students with lower physical fitness levels. There was no statistically significant difference in grades according to obesity. Recently, due to COVID-19, opportunities for students to participate in sports activities have decreased very dramatically, resulting in lower physical fitness levels and increased obesity. The role of school physical education is proposed as the best way to improve students
Calibration and 3D Reconstruction of Telecentric Structured Light System

Three-dimensional (3D) reconstruction of micromechanical components and semiconductors is the key task of precision manufacturing and inspection. In this paper, a precise and flexible calibration and 3D reconstruction method is proposed for a structured light microscopy (SLM) system with two telecentric lenses. Firstly, a dual-telecentric SLM system consisting of a telecentric camera and a telecentric projector with different magnifications is designed, which not only takes full advantage of the depth of field (DOF), but also could expand the field of view. Secondly, a simple algorithm is proposed for joint calibration of the telecentric camera and projector, by establishing an unambiguous formula for the rotation matrix related to the telecentric imaging system. Thirdly, a 3D reconstruction method is presented for the dual-telecentric SLM system based on the fringe projection profilometry (FPP), which could obtain the reference phase and the relationship between the phase difference and depth. Experimental results well demonstrate the effectiveness and accuracy of the proposed method.
Intelligent Planning of the Lifting Path of Bridge Crane in Dynamic Environment

Aiming at the operation of bridge crane in three-dimensional dynamic environment, a new method of dynamic obstacle avoidance intelligent path planning based on improved artificial bee colony algorithm is proposed. Considering the hoisting height of bridge crane, by changing the honey source initialization mechanism, adding adaptive coefficient, changing the onlooker bees following mechanism and introducing scout bees, the artificial bee colony intelligent algorithm is improved. So, the search accuracy is improved and the original shortest path is planned. When the number of obstacles increases or moving obstacles appear on the original planned path during the operation of the crane, the dynamic obstacle avoidance strategy is used to avoid collisions, and the secondary planning of the path is carried out, finally an optimal path with fewer inflection points and smoother path is obtained. The security and operation efficiency of the bridge crane system are enhanced. The simulation results show the feasibility and effectiveness of the scheme.
MONITORING GERAKAN SHALAT MELALUI KAMERA DENGAN METODE POSE PREDICT

&#x0D; Worship is a spiritual activity that is routinely carried out as a form of respect to God, this worship itself has various forms and ways to do it, one of which is prayer where this prayer is an activity of respecting God and also praying. This prayer also has several requirements and procedures that must be followed such as doing purification or self-cleaning by doing ablution then reading intentions and prayers during the prayer process, etc.To facilitate the worship process, efforts have been made to assist humans in the worship process such as reminding prayer times and also helping to inform worship activities. But as humans there will always be new problems, one of which is memory because humans have a condition where the brain is overworked so humans experience a state of forgetting or not remembering something. This tools using webcam as input data and the computer portable or laptop to process the image and show the output text, to detect the pose this tools using mediapipe library to helping object detection.
TMPU: A Framework for Terrain Traversability Mapping and Planning in Uneven and Unstructured Environments

In this paper, we propose an autonomous navigation framework (TMPU) for ground mobile robots in uneven and unstructured environments. The novelty of this framework is twofold: 1) The terrain traversability mapping module is proposed to build a low-resolution 2D (Two-Dimensional) occupancy map by plane analysis based on plane slope and terrain roughness. 2) A multi-resolution motion planning framework is proposed to obtain a high-resolution traversable corridor by A* low-resolution search. Then an improved global planning H-lattice planning is performed on the traversable corridor. Furthermore, extensive experiments are conducted to demonstrate the feasibility and safety of the proposed autonomous navigation framework. All test results show that the computing time consumption is reduced by up to 97.1%, compared with an advanced 3D navigation framework. (Supplemented video link: https://youtu.be/rvYoyR3imEk)
Fusion Estimation for Stochastic Systems with Mixed Attacks and Correlated Noises

The information fusion estimation problems are investigated for a class of stochastic systems with mixed network attacks and correlated noises in this paper. The system and observation noises are correlated at the same time stamps. The signal encountered mixed attacks including deception attacks and denial of service (DoS) attacks during the transmission from sensors to remote estimators. The optimal centralized fusion estimators including filter, predictor and smoother are proposed in the linear unbiased minimum variance sense. Furthermore, based on local filters and estimation error cross-covariance matrices between any two local filters, the distributed fusion filter weighted by matrix is presented, which has better robustness and flexibility. Simulation example shows the effectiveness of the proposed algorithms.