Reviewerly/exHarmony huggingface dataset:
Using patient datasets to track COVID-19 prevalence

ince the start of the global COVID-19 pandemic, there have been almost 550 million confirmed cases of the disease, caused by the SARS-CoV2 virus.The rapid spread, alongside the constant evolution of viral strains, has presented significant challenges to tracking the true prevalence of this disease.
Study On Weighted Binary Classifier with Imbalanced SEM Defect Data

Class imbalance classifier is a common and hard topic in semiconductor industry field because of the limited killing defect counts. Most of the recent research are focusing on data level methods. This paper presents some interesting observations using algorithm level method - the weighted binary (for simplicity) classifier. We would want to have the binary classifier heavily weight the few samples (for example hole bridge defects) that are available. The imbalanced data skew rate is in different ranges from 27% to 1% and to extreme ratio of 0.1%. Our binary classifier performance is evaluated using metrics of confusion matrix and the receiver operating characteristic curve (ROC) instead of only the accuracy.
Augmented-Training-Aware Bisenet for Real-Time Semantic Segmentation

Semantic segmentation techniques have become an attractive research field for autonomous driving. However, it is well-known that the computational complexity of the conventional semantic segmentation is relatively high compared to other computer vision applications. Fast inference of the semantic segmentation for autonomous driving is highly desired. A lightweight convolutional neural network, the Bilateral segmentation network (BiSeNet), is adopted in this paper. However, the performance of the conventional BiSeNet is not so reliable that the model quantization could lead to an even worse result. Therefore, we proposed an augmented training strategy to significantly improve the semantic segmentation task’s performance. First, heavy data augmentation, including CutOut, deformable distortion, and step-wise hard example mining, is used in the training phase to boost the performance of the feature representation learning. Second, the L1 and L2 norm regularization are also used in the model training to prevent the possible overfitting issue. Then, the post-quantization is performed on the TensorFlow-Lite model to significantly reduce the model size and computational complexity. The comprehensive experiments verified that the proposed method is effective and efficient for autonomous driving applications over other state-of-the-art methods.
Optimization of Geological and Mineral Exploration by Integrating Remote Sensing Technology and Borehole Database

Mineral exploration as the basis for the development of important mineral resources and economic construction, improving the efficiency of geological exploration is conducive to improving the quality of mineral resources. In this paper, the study of modern mineral resources exploration and utilization methods, drawing on the problems in geological exploration work, discusses effective countermeasures to improve and optimize the level of geological exploration from the perspectives of remote sensing technology and borehole database, etc., with a view to improving the efficiency of geological exploration and mineral search technology, so that energy production can achieve sustainable development and be free from the constraints of increasingly difficult mineral resources development. Based on remote sensing technology, GIS is a system derived on the basis of advanced science and technology and information technology, and its application to geological and mineral exploration can help relevant personnel to have foresight to understand the development of geological exploration and provide detailed data support for optimizing geological exploration work. Coalfield geological exploration arranges a large number of boreholes to find out the thickness of coal seams in the exploration area, the distribution pattern of coal seams and the spacing of coal seams, the characteristics of the top and bottom of coal seams, and the characteristics of coal quality. In the coal mining excavation, the technical personnel need to study the geological data of the borehole in time to design or adjust the excavation plan scientifically and reasonably. By implanting an electronic chip in the drill hole markers completed by drilling, the borehole coordinates, elevation, preservation of the borehole markers, and the website address of the borehole database management system are sent to the users in real time, providing geologists with convenient query services of borehole geological information. This paper proposes a geological and mineral exploration optimization method that integrates remote sensing technology and borehole database, and the relevant experiments prove the effectiveness of the proposed method.
Research on the construction method of user interest model based on context

User interest model is the core of personalized information service, and its quality has a direct impact on the effect of personalized information service. However, the traditional interest model often only considers the user's interest in the text and ignores the influence of contextual information. Therefore, in order to avoid the interaction between context and interest features, this paper proposes a multi-level vector space interest model representation method. Then, the user's interest is weighted from many aspects by using the user's contextual information. Finally, the personalized retrieval experiment is carried out by using the constructed interest model. The experimental results show that the retrieval precision based on the model reaches 83.72%, which proves the validity and reliability of the model.
Transformer-based conditional generative adversarial networks for image generation

The recent transformers shows competitive performance on computer vision tasks, such as classification, detection, and segmentation. Inspire by its success, in this paper, we explore its application at some more notoriously difficult vision tasks such conditional generative adversarial networks and propose a transformer based conditional generative adversarial networks for image generation. Our model employs the transformer architecture to develop a generator discriminator and residual network as discriminator. To improve the performance, a spectral normalization technique is used to normalize the weights of discriminator and the hinge loss are determined for model optimization. The experimental results on four public datasets shows that our approach is capable of producing the high quality images with good consistence and diversity and outperforms existing works.
BiLSTM-IN-TRANS for Chinese NER

Transformer has good feature extraction ability and has achieved good performance on various NLP tasks such as sentence classification, machine translation and reading comprehension, but it does not perform well in named entity recognition tasks. According to recent researches, the Long Short-Term Memory (LSTM) usually performs better than Transformer in NER task. LSTM is a variant of Recurrent Neural Network (RNN), because of its natural chain structure, it can learn the front and back dependencies between words well, which is very suitable for processing text sequences. In this paper, the BiLSTM network structure is embedded into the Transformer Encoder, and a new network structure BiLSTM-IN-TRANS is proposed, which combines the sequential feature extraction capability of BiLSTM and the powerful global feature extraction capability of Transformer Encoder. The experiments can reflect that applying the model based on BiLSTM-INTRANS could work better than applying one of LSTM or Transformer alone in the NER task.
Study on stability control method of multi-load coupled spraying UAV

In the process of operation, spraying UAV will be affected by the coupling effect of pipeline tension, spray reaction force, spraying mechanism load and other factors. These dynamic loads will directly affect the stability of flight attitude of intelligent spraying platform, resulting in the spraying quality can not be guaranteed. Therefore, a spraying stability control method of UAV based on active Disturbance Rejection control (ADRC) algorithm was proposed to solve the spraying stability control problem and improve the spraying quality of UAV. The simulation results show that the proposed multi-load coupling spraying UAV stability control method has high control accuracy and meets the requirements of spraying UAV control stability and robustness.
Integrated Superconducting Isolator-Circulator-Isolator Device

There needs a large quantity of microwave devices like circulators, isolators and quantum noise limited amplifier in the development of scalable superconducting quantum computers. Traditional isolators and circulators have huge size and could induce a high thermal dissipation. This paper designs a kind of on-chip Isolator-Circulator-Isolator (ICI), which is able to act as isolator and circulator synchronous. The ICI is composed of tunable inductor bridge which based on an array of superconducting quantum interference devices (SQUID). It works on the frequency between 4 and 8 GHz, and operation temperature at 20 mK, with isolation exceeds 40 dB and insertion loss less than 3 dB.
COMPUTATIONAL FLUID DYNAMICS ANALYSIS BASED ON THE FLUID FLOW SEPARATION POINT ON THE UPPER SIDE OF THE NACA 0015 AIRFOIL WITH THE COEFFICIENT OF FRICTION

A new method that is more practical, efficient and applicable is proposed to track the position of fluid flow separation on the upper side of NACA 0015. The proposed method is the coefficient of friction curve (Cf) method on the airfoil's upper side. The approach used is a computational fluid dynamics (CFD) approach. The governing equation used is the Reynolds Averaged Navier-Stokes (RANS) equation. is the turbulence model implemented in this study. The research is conducted on the low Reynolds number category. The low Reynolds number is in the range of values from 104 to 3Í105. Cf can predict the location of fluid flow separation more practically, efficiently, and applicable than the fluid flow velocity profile method. Flow separation begins to form at =8° at position x/c=0.8. The location of the fluid flow separation continues to move closer to the leading edge as the airfoil increases. Through the Cf curve, the location of the fluid flow separation is when the Cf curve experiences a sudden decrease and approaches the x-axis. If the separation points are described in the form of velocity profiles and fluid flow velocity contours, it will form an extreme decrease.
Effect of Independent Digital Reading on Reading Comprehension in the Primary Grades: A Longitudinal Study

The importance of independent reading in children's reading development is well established by research and professional wisdom.Independent digital reading (IDR) is also increasingly integrated into classroom instruction.The present study examines the effect of IDR implemented in the primary grades in three student cohorts of a small public school.The results show that students in the project school score significantly higher on reading proficiency assessment at the end of the second grade than a matched control group.On the other hand, when focusing on data from within the project school, we find that the amount of time spent on IDR is not associated with reading proficiency in either grade 1 or 2 adjusting for the potential confounders.The findings suggest that teacher scaffolding may be effective in improving reading proficiency, while student-led IDR may not be effective due to various design issues of the reading programs.Limitations and potential future research ideas are also discussed.
Examining the Validity and Instructional Value of a Rubric for Evaluating Online Course Quality

This study investigated the validity and instructional value of a rubric developed to evaluate the quality of online courses offered at a midsized public university.This rubric was adapted from an online course quality rubric widely used in higher education, the Quality Matters rubric.We first examined the reliability and preliminary construct validity of the rubric using quality ratings for 202 online courses, and eliminated twelve problematic items.We then examined the instructional value of the rubric by investigating causal relationships between: 1) course quality scores, 2) online interactions between students, instructors, and content, and 3) student course performance (course passing rates).A path analysis model, using data from 121 online courses enrolling 5,240 students, showed that only rubric items related to learner engagement and interaction had a significant and positive effect on online interactions, while only student-content interaction significantly and positively influenced course passing rates.
A Longitudinal and Micro-Level View of One Teacher's Technology Integration Practices: Augmented Reality in Science

Articulating the practices that underlie classroom technology integration can be elusive.In this qualitative case study, we examined one science teacher's technology integration design practices as she planned and taught biology lessons involving augmented reality (AR) technology.Few researchers investigate the teacher's perspective in the everyday classroom in studies of AR integration.This study provides a longitudinal, in-situ, and micro-level examination of this teacher's technology integration practices, involving two iterations of instructional analysis, design, implementation, and revision within ten weeks.This study's data included teacher interviews, reflection notes, lesson plans, teaching artifacts, researcher observations, and students' content test outcomes and feedback during the two technology integration design iterations.Qualitative analysis was conceptually guided by a technology integration planning model and the technological pedagogical content knowledge (TPACK) framework to examine the teacher's technology integration process and knowledge development.Results revealed the teacher developed AR technical skills, redesigned AR-based instructional content representations, changed from a didactic to inquiry-based pedagogy, and showcased the entwined development of Technological Pedagogical Knowledge (TPK), Technological Content Knowledge (TCK), and Pedagogical Content Knowledge (PCK).This micro-analyzed approach unpacks one teacher's in-situ challenges and describes the reflective practices that supported her in applying AR's affordances to teach biology concepts.
Top-Down Action Research Implementation: Challenges Preschool Teachers Faced in Chihuahua, Mexico

Mexico 1. Objective or purposesThis paper was to explore how top-down teacher action research implementation has been established and processed in the preschool educational system in Chihuahua Mexico.In addition, this paper was to explore how this government involved top-down strategy, which intended to support teachers' professional growth and development wasn't functioning as planned but created frustrations and anxiety in the workforce.This tendency isn't unique or unusual, as many other countries such as Singapore and South Korea have gone through similar situations in the process of implementing action research.Instead of developing a strong supporting system in teacher training, implementing the government forced action research as a form of professional development in fact created more concerns and problems for practitioners in those countries (Kim & Kim, 2016;Peidong & Laidlaw, 2006;Salleh, 2006).In the finding section, issues and obstacles which restrain these teachers to get involved in action research was identified in the context of the current government forced system in Chihuahua.Suggestions and methods to support teachers to be more engaged in this practitioners' inquiry process were proposed which will result in a more grass rooted and self-motivated approach.
Gender, Social Distance, and Justifications: Statistical Discourse Analysis of Evidence and Explanations in Online Debates

This study examined how social (rather than cognitive) antecedents impact students' use of justifications in online debates.Eighty-seven graduate-level students participated in four weekly online debates.Statistical discourse analysis of 2,028 postings revealed that gender, social distance, and time were linked to use of evidence and explanations.Females used more explanations, while males used more evidence.Responses to males' messages presented more evidence than explanations.Responses to messages conveying greater versus less social proximity (we/you vs. he/she/they) presented more explanations and evidence, respectively.The findings suggest that systematic manipulation of debate protocol (pronoun usage, gender group composition) can be used to strategically elicit specific types of justifications to help groups work more effectively to achieve deeper shared understanding and learning.
Direct and Indirect Impacts of Voluntary Pre-Kindergarten on Kindergarten Readiness and Achievement

The purpose of this study is to investigate the direct and indirect effects that Florida's Voluntary Pre-Kindergarten (VPK) program has on kindergarten readiness and academic achievement and if these effects are moderated by students' socioeconomic
Addressing Defensive Objections: Adversarial Examples in Automatic Essay Scoring

While automatic essay scoring (AES) systems promise speed and objectivity, their usefulness is limited by defensible interpretation of the scores they generate.While AES systems have extremely high reliability, reliability is a necessary (but not sufficient) condition for validity.Any validity argument constructed around an AES system must consider how well scores reflect the construct, how the scoring decisions are made, and to what extent the scores can be manipulated.We examine these key considerations within the context of feature-based AES systems and AES systems based on neural networks.While neural AES systems boast increased reliability compared to feature-based systems, they are less significantly less transparent in how they make their decisions and what aspects of the essay they focus on.In addition, research from computer vision points to the fact that decisions in neural network based classifiers can be manipulated by maliciously crafted input.We investigate similar examples within natural language processing, propose a method for malicious manipulation of essay-length text inputs and evaluate the threat to validity posed by essay manipulation.
Hiding information using hybrid digital screening for product identification

Anti-counterfeiting is very important in commodity circulation area because it protects the interests of producers and consumers. Product identification is a kind of common anti-counterfeiting means. An innovative method was developed in this paper with aim to identify packaged products by means of printed image. Target information was hidden in digital gray patch by use of this method and then the digital gray patch was duplicated through digital printer to achieve a hard copy. The information hidden was invisible on the hard copy and could be extracted via a decoding software developed in this paper. The method created here is radically different from the digital watermark technology, since it intends to hide information in hard copies that usually adopted by commodity packages. Experiment results showed that various information could be hidden well in printed duplicates and identified clearly through the decoding software. The method constructed by this paper is low-cost and effective and therefore provided a new candidate for the field of commodity security and identification.
Establishing Multiple Chip-to-Chip Orthogonal Free-Space Optical Channels using Programmable Silicon Photonics Meshes

Two silicon photonics programmable meshes of Mach-Zehnder interferometers are used to automatically establish chip-to-chip orthogonal free-space communication links. Optimum channels with mutual isolation of more than 30dB are found even in case of a misaligned link or in presence of an obstacle in the path.
Impact of Round Table Technique towards Students’ Writing Ability

The objective of this research was to know whether there was influence using round table technique towards students’ writing ability. The writer used experimental method. In taking the sample of the research, the writer used cluster Random Sampling Technique. The writer took two classes as the sample, one class was experimental class who was taught by round table technique and the another class was control class who was taught by discussion technique. In collecting the data, the writer used the writing test. For analyzing the data, the writer used t_tes formula. Based on the calculation, there is significant influence of round table technique towards students’ writing ability at the tenth class of SMK Negeri 4 Bandar Lampung. The average score of students who learn through round table technique is higher than by using discussion technique. It can be shown from the result in experimental class (71.96) &gt; control class (60.71). Based on the result of data analysis, It shown that t_test = 5,51 is higher than t_table. At the significant level 5% or 1%, it was found the significance 0.05 = 2.00 and significance 0.01 = 2.66. It means that t_test&gt; t_table, therefore (H_0) is rejected and〖 (H〗_a) is accepted. It means that there is significant influence of Round Table Technique towards students’ writing ability at the tenth class of SMK Negeri 4 Bandar Lampung.
Collaborative Writing: It’s Influence towards Students’ Recount Text Ability

The objective of this research was to know the influence of collaborative writing ability towards students’ recount text of the tenth class students or not. The total populations are 61 students’ in two classes. The writer take two classes, one class as the experimental class that was taught by using Collaborative Writing and the second class as the control class that is taught without Collaborative Writing. In conducting the research, the writer use experimental method, the writer use writing test or t-test to know the students’ writing ability by using Collaborative Writing. The students ask to describe their experience the test use recorded in students’ writing ability, and the writer use the scoring system propose by Yendra Pratial. The writer determine the average rates (x) and variant (s2) before use t-test formula. The average score of experimental class that is taught by using Collaborative Writing is x2ratio = 7.77, and the average score of controll class that is taught with direct instruction is x2ratio= 7.23. Rejected Ho if : x2ratio ≥ x2table (1-α) (k-3), for the significant level of 5% obtained: x2table = 7.81, for the significant level of 1% (α=0.01) obtain: x2table= 11.3. So the Ho is accepted. The sample of this research the writer use cluster random sampling technique, and to test the hypothensis in this research, the writer use a statistical formula of t-test. According to the result of the data analyzing, the writer found that &gt; (=3.10 and =2.70 in significance level 1% and ttable= 2.02 in significance level 5%. It means that positive influence of collaborative writing towards students recount text ability