Reviewerly/exHarmony huggingface dataset:
Pedestrian detection based on multi-scale feature fusion

To solve the problem of a large difference in target size in pedestrian detection, which leads to high pedestrian false detection rate and high miss detection rate of small-scale pedestrians, a multi-scale feature fusion method based on RetinaNet is proposed. After feature enhancement by extracting features from the backbone network, three branches of different scales are formed, which are effectively fused with the corresponding feature layer to further enrich the target information, and then detect pedestrians of different scales. Test on the open dataset shows that compared with the original RetinaNet algorithm, it can detect more pedestrians, especially small-scale pedestrians, and the model detection performance is better.
Data monitoring and management system based on ASP.NET and Echarts

This paper proposes a data monitoring management system based on ASP.NET and Echarts, the application of B/S development mode, through the use of ASP.NET three-tier architecture and database technology to develop a set of management system with authority management, map module, three-dimensional model module, real-time data monitoring module and historical data monitoring module and other function-s;Through real-time monitoring of environmental factors and other influencing factors, the health status of monitored objects can be evaluated to ensure that their design and use safety and durability meet the expected standards, and provide basis and guidance for the maintenance, repair and management decisions of monitored objects.
A COMPARATIVE STUDY OF RHETORICAL STRUCTURE OF SEVERAL THESIS ABSTRACTS BY UNDERGRADUATE STUDENTS OF UNIVERSITAS BENGKULU

The abstract in every research paper has always served as an attention-grabber, either encouraging readers to continue reading the research or discouraging them from doing so. This research is aimed to find the most dominant move and step of thesis abstract by undergraduate students and to identify any differences. This research used a mix method approach. The design of this research is descriptive, using quantitative as well as qualitative data. The data was taken from thirty undergraduate thesis abstracts of Education faculty from University of Bengkulu who graduated between 2019 to 2022. Hyland’s five-move model will be used for research instrument. The result showed that, the majority and most dominant moves that found were Move 2 (purpose) 100%, followed by Move 3 (Method) 97%, Move 4 (Product) 97% and Move 5 (Conclusion) 80%, while the most dominant Step that found was Step 1 of Move 2 (Stating the purpose directly) 100%. Also, there is no significant differences of Move from the three study programs (English, Physic and Guidance and Counselling). Conclusion, most of the students were simply following the “Thesis Writing Guidelines” in writing their abstracts. Therefore, it would be better for the department in charge to revise the guidelines and use this research as a reference or guidance for a better abstract writing.
Analysis of error rate in hierarchical menu selection in immersive augmented reality

The emergence of new immersive AR/VR headsets recently resulted in major improvements in hand-gesturebased user interfaces. Devices such as MS HoloLens II and Oculus Quest II support hand-gestures. Although using hand-gestures increases the sense of presence and ease of natural interactions, it has been shown that hand-gestures require extensive physical activity. Furthermore, it has been shown that the error rate in hierarchical menu selection is much higher when using hand-gestures than when using a desktop environment or the controllers. Therefore, assessing the difficulty of a hierarchical menu design when using hand-gestures and gaze for menu selection will enable UI designers to develop more effective user interfaces. In this work, we provide a validated index for estimating the hierarchical menu selection error using hand-gesture and head-gaze as input modalities. The index is informed by cognitive WAIS data gathered from participants, which measures subjective cognitive performance. The proposed index is the result of a user study that includes hundreds of hierarchical menu selections using MS HoloLens, and is validated against the data of a group of different participants. The results demonstrate that the index can successfully capture the trend of the users’ errors in selecting the hierarchical menu items in immersive environments.
Stabilizing the training of deep neural networks using Adam optimization and gradient clipping

The field of neural network training and optimization has seen significant advancements in recent years, with new techniques and algorithms being proposed to improve the efficiency and effectiveness of training. In this paper, we review several key optimization techniques and their impact on training neural networks, with a focus on long-term dependencies and the difficulties that can arise during training. We begin by discussing the challenges of learning long-term dependencies with gradient descent, as highlighted in the 1994 paper by Bengio et al. We then introduce Adam, a method for stochastic optimization proposed by Kingma and Ba in 2014. We also explore the difficulties of training recurrent neural networks, as discussed in the 2013 paper by Pascanu, Mikolov, and Bengio. We also review recent advances in optimization techniques such as Convergence of Adam and Beyond by Jianmin et al. (2017), Yogi by Dong et al. (2018), AdaBound by Zhang et al. (2018) and On the Variance of the Adaptive Learning Rate and Beyond by Liu et al. (2019). We will highlight the advantages and disadvantages of each technique and discuss their potential impact on the field. Overall, this paper provides a comprehensive overview of recent advancements in neural network optimization and their implications for training and performance. Keywords: Deep neural networks, optimization, Adam, gradient clipping, training, stabilization, overfitting, generalization, recurrent neural networks, non-convex loss landscapes.
The Numeracy Competency Profile of Elementary School Teachers in Ponjong District, Gunungkidul Regency Viewed from Demographic Factors

&lt;p&gt;&lt;span lang="EN-US"&gt;This study aims to describe the numeracy competency profile of elementary school teachers in Ponjong District, Gunungkidul Regency, viewed from demographic factors. The demographic factors used to describe, there were gender, type of school (public or private), length of teaching, age, and whether the teacher in question was certified as an educator. This numeracy competency was essential to explore because this skill was one of the most critical primary education goals; it helped realize successful advanced learning, social interaction, meeting the necessities of life, and global employment. This study used a design-based research (DBR) approach combined with professional learning community (PLC) and participatory action research (PAR), in which a sample of forty teachers was drawn equally from each group of teachers working groups (KKG). The data were taken using test instruments and analyzed using inferential statistical tests. The results showed that from the gender aspect, there was no difference in numeracy competence for both men and women. The second, based on the type of school, there was no difference in numeration competence between public and private schools. The third, from the length of teaching, it was found that teachers with a duration of education under five years had a higher numeracy score. The fourth, in terms of age, there was no difference in numeracy ability from twenty-five to fifty-six years. The conclusion, from the aspect of educator certification, was fascinating. Although not significant, there was an average difference in the numeracy ability test between teachers who were certified educators and those who were not certified, where teachers who did not have an educator certificate had a higher test average than those who already had an educator certificate.&lt;/span&gt;&lt;/p&gt;
Functions of Pragmatic Presuppositions in Advertisements: Promoting Cosmetics on Instagram

Presuppositions as pragmatic strategies have been a much-discussed topic, yet there need to be more studies on the pragmatic presupposition in advertisements on social media platforms. The present study explores the distribution and functions of different types of presuppositions in cosmetics advertisements on Instagram to fill the gap. Fifty advertisements posted by the ten most-followed beauty brands on Instagram were chosen as samples. It is found that advertisers prefer fact presupposition over other types of presuppositions since it is helpful when it comes to persuading customers to buy a particular product. This paper contributes to studies on presuppositions in ads on social media platforms and advances our understanding of the functions of pragmatic presuppositions.
Radar Signal Modulation Recognition based on 1-D CNN

In order to solve the problems of low recognition accuracy and high computation complexity of radar signal processing under low signal-to-noise ratio (SNR), this paper studies a neural network based on 1-D convolution for radar intra-pulse modulation recognition. First, we generate seven different types of radar continuous FM signals and phase coded signals (LFM, NLFM, Frank, P1, P2, P3, P4). Then, the three-dimensional convolutional network suitable for image processing is improved into a one-dimensional convolutional network which will process the generated radar signal in an end-to-end approach. The simulation results show that the recognition algorithm using one-dimensional (1-D) MobileNetV2 network can effectively extract the essential characteristics of radar signal under the condition of low SNR, avoid the huge calculation caused by using time-frequency method, and achieve over 85% recognition accuracy at −6dB.
A Business Workflow For Providing Open-Domain Question Answering Reader Systems on The Wikipedia Dataset

In a variety of sectors, we observe the emerging need for responding to user questions in a fast and efficient manner. We argue that addressing this need by developing question answering reader system applications will lead to several benefits: a) the density of call centers is reduced, and b) time is saved by getting answers through the application instead of going to the company itself. Examples of these applications, such as search engines help users find answers to their questions on documents containing important information, such as legal documents. These applications can be applied in digital banking, electronic commerce, and legal documents. In this study, we investigate the design of a business workflow that can provide answers to questions through documents containing important information, such as legal documents. In this study, we examine open-domain reader systems and propose a business workflow for open-domain reader systems. We are implementing a prototype application on the dataset to investigate the usability of the proposed business workflow. We discuss the prototype’s implementation details and share its evaluation results. The results show that the T5-based model provides better results in open-domain reader systems.
An Analysis of Chronological Changes Based on Feature Words Using the Cross-Tabulation Search Engine

In Japan, university evaluation is compulsory, and many universities issue self-assessment reports yearly, often with the same table of contents. With this in mind, feature words from each chapter can extract for documents with nearly identical hierarchical structures. For example, by setting “table of contents” on the vertical axis and “fiscal year” on the horizontal axis and visualizing the feature words in a cross table, it is possible to find chronological changes in the feature words at a glance. This makes it possible to quickly grasp what has changed or not in each chapter. The present study looked at the chronological changes in Yamaguchi University's self-assessment documents from 2012 to 2016. With the developed system, we discovered a significant chronological change in Yamaguchi University’s Diploma Policy, which is one of three policies. Yamaguchi University had already formulated and operated a similar policy called the Graduation Policy before the Diploma Policy became mandatory. The system showed that Yamaguchi University changed the “Graduation Policy” to “Diploma Policy” in line with the mandatory Diploma Policy. By using this system, even those who are not affiliated with Yamaguchi University have been able to grasp the significant changes in the past at the University. The reasons for any change in university policy should be explained to its stakeholders. The system can be an effective means for examining the decision-making process.
Homodyne nonclassical area as a nonclassicality indicator

Abstract We propose a legitimate and easily computable nonclassicality indicator for the states of the electromagnetic field based on the standard deviation in the measurement of the homodyne rotated quadrature operator. The proposed nonclassicality indicator is the nonclassical area projected by the optical tomogram of the quantum state of light on the optical tomographic plane. If the nonclassical area projected by the optical tomogram of a quantum state is greater than zero, the state is nonclassical, and the area is zero for the pure classical state. It is also noted that the nonclassical area of a quantum state increases with an increase in the strength of nonclassicality-inducing operations on the state, such as squeezing, photon addition, etc. We have tested the validity of the nonclassical area measure by calculating the same for certain well-known nonclassical states, and found that essential features of the nonclassicality shown by the states are captured in the nonclassical area. We also show that the nonclassical area is robust against environment-induced decoherence of the states. The nonclassical area projected by the optical tomogram of a quantum state of light is experimentally tractable using the balanced homodyne detection of the quadrature operator of the field, avoiding the reconstruction of the density matrix or the quasiprobability distribution of the state.
USE OF STUDY PROJECTS IN DEVELOPING PERSONAL-CREATIVE COMPETENCE OF STUDENTS

The article describes the need to develop the personal creative abilities of students in the digital environment, the possibilities of organizing pedagogic subjects in a creative direction, and the importance of using educational project assignments in the process of teaching pedagogic subjects to improve the quality of education.
Uncertainty Resolution with Fuzzy Inference System Approach towards Stress, Anxiety, and Depression

There is indisputable proof that stress, anxiety, and depression significantly and negatively impact people's well-being. Recently, problems with stress and sadness have frequently resulted in a variety of chronic health concerns or even mortality. It is important to remember that stress, anxiety, and depression are all dangerous and closely associated. According to a proverb, "Life is 10% what you experience and 90% how you respond to it." This suggests that how we react to and equally manage whatever happens to us depends on how we respond to it. Several unknowns make the condition more ambiguous, such as diverse symptoms and different underlying causes of health disorders. Fuzzy can benefit medical professionals, experts, hospitals, drugs, etc. by handling the ambiguity and uncertainty of such vast amounts of data on people in these circumstances. To solve so many ambiguities, gaps in knowledge, or imprecision, fuzzy logic is frequently used. The current experiment applies a fuzzy method with fuzzy logic in R to develop a fuzzy inference system for pattern identification and classification to increase performance. This focuses on creating a fuzzy rule foundation, model, and inference for the study of data related to stress, anxiety, and depression. The results show that using a fuzzy inference system for uncertainties aided in making decisions that could have resulted in more serious problems if not handled on time. This study should only be used to observe the symptoms and causes of stress, anxiety, and depression; it should not be used to treat the identified health problems. Hospitals are the best places to solve problems.
Free Speech Regimes and Democratic Cooperation

Liberal-democratic polities increasingly diverge on free speech rights, and such divergence undermines their cooperation. A “procedural-rights” (PR) perspective would protect the rights, and promote the capacity, of individuals to express alternative viewpoints. Conversely, a “victim-rights” perspective would restrict speech that offends or psychologically harms victimized (marginalized) groups, although its advocates from the political left and right disagree on who are victims. I posit less cooperation between democratic polities with different rules of public discourse on a contested issue, i.e., different _discourse regimes_. The ruling elites in one discourse regime view that in another as allowing or committing violations of individual rights. Critically, they also access different information, as VR-oriented media report selective information supporting the victimized groups. Cooperation is especially difficult when one polity follows a VR-hegemonic regime (leftist or rightist) that comprehensively restricts discourse among all major organizations. In Europe and North America, democratic polities (national and subnational) with diverging discourse regimes on ‘culture war’ issues frame each other as illiberal and express mutual animus (‘vehemence’). Mutual animus is especially severe in East Asia, as one democracy (South Korea) comprehensively restricts discourse on Japanese colonialism and the other (Japan) does not. Conversely, the discourse regimes of South Korea and Japan increasingly converge (procedural-rights) on other issues, such as communist North Korea and China, which promotes bilateral consensus and cooperation.
Development of Android-Based Learning as Interactive Learning Media in Reaction Rate Material on XI Class SMA Student

This aims of this study are to: (1) find out whether android-based interactive learning media that developed have met the feasibility standards based on the android-based integrated BSNP, (2) find out whether student learning outcomes taught using android-based interactive learning media that have been developed higher than the Minimum Completeness Criteria (KKM) score on the reaction rate material. This research is a Research and Development with the ADDIE (Analysis, Design, Development, Implementation and Evaluation) model which was carried out in the odd semester of the 2021/2022 academic year at SMAN 12 Medan. At the implementation stage, a one-group pre-test post-test design was used, with sampling using a cluster random sampling technique consisting of one XI science class at SMAN 12 Medan. The results of the validation of the android-based media obtained for the feasibility of the contents is 3.75; display feasibility is 3.83; language feasibility is 4, and graphic feasibility is 3.83. Overall, android-based learning media obtained a feasibility level of 3.85, with a very feasible category. Furthermore, android-based learning media on the reaction rate material is implemented in the learning process. The KKM scores and the students' average post-test scores were 78 and 85.6, respectively. The data obtained were analyzed using the right-hand t-test. The result of data analysis is that tcount is in the significant area, tcount &gt; ttable = 4.146 &gt; 1.711. So that Ha is accepted and H0 is rejected, it can be concluded that the learning outcomes of students who are taught using Android-based interactive learning media are higher than the KKM value.
ANALISIS ISI: KARAKTERISTIK TEKS DALAM BUKU BAHASA INDONESIA PEGANGAN SISWA SMA

The research aims to identify the characteristics of the text in teaching materials in the form of Indonesian language textbooks for class XI students of junior high school. The type of text chosen is procedure text, Lectures, Short Stories, and Dramas on the basis of the choice that there is a new paradigm of language and text, curriculum development, the need to optimize learning references for teachers and students, the importance of improving students' analytical abilities, and to see the extent of feasibility use of these teaching materials. The research method is content analysis of the collected literature. Covers key aspects of reading and writing skills and assessment. Is a type of descriptive analysis with a type of qualitative research. Research as a tool is a collection of someone's writings in the form of hardcopy/softcopy so that they are in the form of a grid. The results of the data analysis showed that there were differences between the substance of the text content and the students' social backgrounds, and there were errors/errors/negligence in the preparation/presentation of the text, such as the use of punctuation marks. conjunctions, contradictions between titles and contents, and so on. So it is recommended to review.
Effectiveness of Discovery Learning Model Based on Team Games Tournament Assisted with Thematic English Media on Learning Achievement

Learning achievement in learning is very important because the success of learning carried out in teaching and learning activities can be seen from student learning outcomes. Learning achievement is the result achieved by students or someone after carrying out learning activities. Thematic learning achievements at SD N 1 Patukangan class IV in 2018/2019 still vary widely. Not all students' Thematic learning outcomes are high or good. There are several Thematic learning achievements that are unsatisfactory. The purpose of this study was to determine the effectiveness of using the discovery learning model based on team games tournaments assisted by thematic workshop media on student achievement in class IV SD N 1 Patukangan. The method used in this study was a quasi-experimental method with a research design using Nonequivalent [Pre-Test and Post-Test] Control Groups Design (NCGD). The results showed that the experimental class mean was 82.50, while the control class showed a result of 71.09. This shown that the average learning achievement of students in the experimental class is higher than the average learning achievement of students in the control class. The n-gain results in the experimental class show moderate criteria with an average gain of 0.45 while those in the control class show moderate criteria with an average of 0.30. This shows that there is the effectiveness of the discovery learning model based on team games tournament assisted by thematic workshop media on student achievement. Keywords: engklek thematic, model discovery learning, team games tournament, learning achievement