Reviewerly/exHarmony huggingface dataset:
TEACHING WRITING OF RECOUNT TEXT BY USING PERSONAL LETTER AS MEDIA IN THE TENTH GRADE AT MAN JUNG CANGCANG PAMEKASAN

This research aims are to describe the teacher in using personal letter as media in teaching writing of recount textand tofind out the teacher’s problems in teaching writing of recount text by using personal letter as media in the tenth grade of MAN Jung Cangcang Pamekasan. Then, the object of this research obtain from the students of the tenth grade atMAN Jung Cangcang Pamekasan. There are 35 that consist 9 boys and 26 girls students.In gathering the data, the reseacher used observation process, interview, and documentation at the tenth grade of MAN Jung Cangcang Pamekasan. The research design of this study is descriptive qualitative. The result of this research, there are how the teacher in using personal letter and the problems the teacher in using personal letter as media in the tenth grade at MAN Jung Cangcang Pamekasan. In using personal letter of teaching writing recount text, there are some steps such as: pre-activity, whilst activity, and post activity. Then, the problems that was faced by the teacher in usingpersonal letter as media in teaching writing recount text are the first,the teachers’ problems in teaching writing recount text is difficult to get attention for students in teaching process by using personal letter media, the second problem, the teacher felt difficult to make the students activein the class because the students less of vocabularies, and the third problem, the teacher felt that the goal of the teaching process by using personal letter as media is not running well.
An Optimization Strategy for Offline Path Planning on High-Resolution Grid Maps

The robot offline path planning method generally takes a long time. To deal with the issue, an optimization strategy is proposed in this paper. Firstly, a simplicity kernel is introduced for dimensionality reduction of the high-resolution 0–1 grid maps, which retain the useful information for of-fline path planning. Secondly, to solve the problem that the dimension reduction makes key points impassable, a improved automata based on the greedy strategy is proposed, by which suitable machine-selected key points can be obtained. Finally, some simulation comparison experiments are carried out. The results show that the planning time is significantly reduced.
Design Education Measures Using a Deep Learning-Based Generative Model

본 연구의 목적은 4년제 대학의 디자인전공 학생들을 대상으로 딥러닝 기반 생성 모델을 활용한 이미지 생성 과정에 참여시켜 디자인 교육의 효과가 있는지 파악하고자 이미지 생성 과정의 적용 전과 후에 대한 디자인 성취도를 측정하고, 그 실험 결과를 근거로 디자인 교육 방안을 제안하는 데 있다. 연구 방법은 스테이블 디퓨전 버전을 이용하기 위해 이미지 생성에 필요한 디자인 요소 선정과 입력에 필요한 텍스트의 설명문 적용 기준을 설정한 후, 인공지능 스피커 이미지를 프로젝트 적용 사례로 제시한다. 주요 결과로는 첫째, 스테이블 디퓨전 버전이 디자인 성취도 향상에 긍정적인 효과를 주었다. 둘째, 디자인전공 학생들이 창의적 사고와 발상에 효과를 보인 경우가 있지만, 창의성 정도와 수준에 아직 미치지 못하고 모방 수준에 머무르는 것으로 나타났다. 이에 대한 디자인 교육 방안으로 시각적 이미지를 떠올릴 수 있는 이미지를 텍스트로 영어 설명문을 작성하는 능력, 창의력 계발과 함께 윤리적 측면의 모방을 지양하는 균형 감각, 이미지의 유사성을 판단하는 능력 그리고 협업도구로 사용하는 능력을 함께 배양해야 할 것이다.The purpose of this study is to have students majoring in design at a four-year university participate in an image generation process that utilizes a deep learning-based generative model, and to grasp the effects of design education. Then is to measure the degree of design achievement of students, and to propose a design education plan based on the experimental results. The research method is to select the design elements necessary for image generation in order to use the staple diffusion version, set the text description composition standards necessary for input, and then present the artificial intelligence speaker image as a project application example. As for the main results, first, the stable diffusion version had a positive effect on improving the degree of design achievement. Secondly, it was found that design majors showed some effects on creative thinking and ideation, but still fell short of the degree and level of creativity and remained at the level of imitation. As a design education plan for this purpose, the ability to create English explanations with visual image text, the enlightenment of creative ability, the sense of balance that eliminates imitation from an ethical point of view, the ability to judge the similarity of images, and We have to nurture them with the ability to use collaboration tools.
The Effect of Teacher Characteristics Recognized by Learners on English Academic Achievement

본 연구에서는 학습자가 인식한 영어교사의 특성과 영어 수업태도가 영어 학업성취에 미치는 영향을 살펴보았다. 서울교육연구정보원이 2018년 실시한 서울교육종단연구(SELS) 제9차년도 설문에 참여한 일반계 고등학생 2623명의 자료를 분석하였다. 분석에 앞서 참가자들이 인식한 교사특성과 수업태도에 하위변인이 있는지 살펴보고자 탐색적 요인분석을 실시하였고 두 요인의 신뢰도를 검증하였다. 교사특성을 3개 하위변인으로 분류한 선행연구와 달리 본 연구에서는 요인분석결과에 따라 하위변인으로 나누어 분석하지 않았다. 영어 수업태도가 교사의 수업에 대한 학습자 인식과 영어 학업성취 사이에서 매개역할을 한다는 가설을 검증하기 위하여 매개회귀분석을 실시하였다. 분석결과에 의하면 학습자가 인식한 영어교사 특성은 영어 수업태도를 매개로 영어 학업성취에 긍정적인 영향을 주었다. 학습자가 교사특성을 높게 인식할수록 영어 수업태도가 향상되었으며, 향상된 영어 수업태도는 영어 학업성취도를 높이는 것으로 나타났다. 학생들이 인식하는 교사특성과 학습태도 간의 관계를 분석한 본 연구결과는 영어 학업성취도의 차이를 설명하는 학생과 교사 수준의 요인들을 밝힘으로써 교사의 수업준비에 도움을 주고 궁극적으로는 학습자의 영어 학업성취 향상에 도움을 줄 것으로 기대한다.The purpose of this study is to examine the effect of teacher characteristics recognized by learners on English learners’ attitude and English academic achievement. This study analyzed the data of general high school students who participated in the 9th year of the Seoul Education Longitudinal Study. Prior to the analysis, an exploratory factor analysis was conducted to examine whether there were sub-variables in the English learners’ attitude and teacher characteristics recognized by learners. Unlike previous studies that divided teacher characteristics into three sub-variables, the result of factor analysis reported that there were no sub-variables, and the reliability of the two factors was verified. Mediation regression analysis was conducted to verify the hypothesis that English learners’ attitude would play a mediation variable between the teacher characteristics recognized by learners and English academic achievement. According to the results of the study, the teacher characteristics recognized by learners had a positive effect on English learners’ attitude and influenced English academic achievement through English learners’ attitude. The higher the teacher characteristics recognized by learners, the better English learners’ attitude, and English learners’ attitude was found to increase English academic achievement. The results of this study are expected to help teachers prepare for lessons by identifying student-level factors that explain differences in English academic achievement, and ultimately help learners improve their English academic achievement.
STUDENTS' WHATSAPP LANGUAGE POLITENESS ATTITUDES MESSAGES to LECTURER at AL-QOLAM MALANG

This research aims to determine language politeness in communicating via WhatsApp between students and lecturers. The research methodology used is descriptive qualitative with a research focus on the language style and the principle of politeness in WhatsApp using based on the ethics of sending messages. Data were collected using documentation and data analysis techniques with a normative method approach. The results of the investigation of this study indicate that the language style of students towards lecturers tends to ignore the correct language structure rules. In terms of the lexical aspect, a mixture of formal language and slang is still common. However, in communicating based on the social network, WhatsApp, some students have been able to meet the ethics of sending messages by paying attention to the principle of language politeness. Even so, there were also several messages sent by other students that contained violations of politeness to communicate based on media messages WhatsApp.
MANAJEMEN PEMBIAYAAN SEKOLAH DASAR BERBASIS ISLAM STUDY KASUS DI SD UMMU AIMAN LAWANG

In the implementation of education, financing is a potential that greatly determines the quality of human resources and is an inseparable part of education administration management. Because cost is very important in the implementation of education, so universities need effective and efficient financing management, in order to produce quality graduates. In improving the quality of graduates, strong support is needed in learning activities, the use of educational facilities and infrastructure in accordance with the provisions of national education standards. Of the many criteria for improving the quality of graduates, it is inseparable from the costs in the implementation of the educational process.&#x0D; This study aims to describe and find out: (1) Budget planning to improve the quality of education at Ummu Aiman Lawang Elementary School and Islamic Elementary School (2) Budget fulfillment strategy to improve the quality of education at Ummu Aiman Lawang Elementary School and Islamic Elementary School (3) Budget evaluation to improve the quality of education at Ummu Aiman Lawang Elementary School.&#x0D; This research uses a qualitative approach of analytical descriptive type. The methods of data collection are observation, interviews and documentation. The data analysis technique uses Miles and Huberman's interactive analysis model which includes four components, namely data collection, data reduction, data presentation and conclusion drawing. Checking the validity of data using Credibility, Transferability, Dependability, and Confirmability.&#x0D; The results showed that: 1) the planning of the education budget of SD Ummu Aiman Lawang was prepared and outlined in the form of an RKAS held at the end of each year by determining all programs along with the budget of each program. Involving school stakholders, through meetings and meeting decisions that have been agreed upon again decided by the head of the foundation 2) Strategies for fulfilling the budget to improve the quality of education at Ummu Aiman Lawang Elementary School and namely: a. independent work unit strategy, b. donations of funds from foundations and students, c. having links with foreign countries, and d. submitting proposals to the government. 3) Evaluation of Education Financing in Improving Quality. Education at SD Ummu Aiman Lawang is carried out through: 1) program evaluation is carried out every semester or year, 2) evaluation of employee performance results, 3) evaluation of organizational mechanisms, 4) evaluation of internal and external analysis results.&#x0D;
Unsupervised Learning

Packed with real-world examples, industry insights and practical activities, this textbook is designed to teach machine learning in a way that is easy to understand and apply. It assumes only a basic knowledge of technology, making it an ideal resource for students and professionals, including those who are new to computer science. All the necessary topics are covered, including supervised and unsupervised learning, neural networks, reinforcement learning, cloud-based services, and the ethical issues still posing problems within the industry. While Python is used as the primary language, many exercises will also have the solutions provided in R for greater versatility. A suite of online resources is available to support teaching across a range of different courses, including example syllabi, a solutions manual, and lecture slides. Datasets and code are also available online for students, giving them everything they need to practice the examples and problems in the book.
Using Picture-Series-On-Instagram to Improve Students’ Narrative Writing Skills at A Public Senior High School in Kampar

Instagram app allows its users to tell their stories worldwide through publishing their images which are sometimes accompanied by some verbal description of the texts. This study aims to find out if picture-series-on-instagram app can be used as a learning tool in the classroom to improve students’ writing ability on narrative text type. The design of the present research was quasi-experimental. The population of the research was the tenth-grade students of a public senior high school in Kampar. Two classes were selected as the experimental and controlled classes. The total number of both classes was ninety students. Data collection technique was a pre-test and post-test of writing a narrative text. The results of test were scored by two experts as the raters whereas a writing assessment rubric by Brown (2007) was employed as the reference. Data analysis technique of the research used an independent t-test formula to compare the post-test results from the experimental and the controlled classes. The findings found that the post-test results of the experimental students were significantly higher compared to post-test results of the controlled students (Sig, 2-tailed = 0.039 &lt; 0.05). As a conclusion, the use of the picture-series-on-instagram app was shown to significantly more effective to improve students’ ability to write a narrative text than the use of the conventional method. The findings of this present research support the findings of the previous studies that the picture-series is instrumental to improve the EFL students’ writing ability on narrative texts. Furthermore, it is recommended that the use of picture-series to improve students’ writing ability on narrative text could be used by the tenth-grade teachers in their classrooms.
Correction to: Information Systems and Neuroscience

In the original version of the book, the title of Chapter 12 includes a small error in the chapter title. It should be changed from “Resolving the Paradoxical Effect of Human-Like Tying Errors by Conversational Agents” to “Resolving the Paradoxical Effect of Human-Like Typing Errors by Conversational Agents”. In the original version of the book, the following belated corrections have been incorporated in chapter “Measurement of Heart Rate and Heart Rate Variability: A Review of NeuroIS Research with a Focus on Applied Methods”. The correction chapters and the book have been updated with the changes.
Assessment of Semi-supervised Approaches Applied to Convolutional Neural Networks

Convolutional neural newtorks have been presenting great results regarding image classification in different contexts. As known in the literature, this kind of network demands a great volume of labeled samples to reach a good convergence during the training process. However, in real scenarios labeled samples are scarce because the labeling process is costly and time consuming. Moreover, it is highly susceptible to errors when accomplished by human specialists. This fact impairs in a great extent the applicability of convolutional neural networks in several contexts where there is a lack of labeled samples. Thus, in this work we focus on mitigate this issue. To do so, we apply the semi-supervised paradigm to the convolutional neural networks. We proposed the aggregation of two semi-supervised techniques from literature with this kind of deep learning networks and analyse their behavior. We performed an extensive assessment of this aggregation. We also considered the transfer learning approach in the process to verify its generalization under the semi-supervised paradigm. Our experiments, with three public datasets, testify that our proposed aggregation obtained better results, gains of up to 88% in accuracy, when compared with the supervised paradigm.
Takagi-Sugeno fuzzy modeling applied to predict sales data based on inventory data and demand data

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter Facebook Reddit LinkedIn Tools Icon Tools Reprints and Permissions Cite Icon Cite Search Site Citation Dorteus Lodewyik Rahakbauw, Rahayu Aprilia Harun, Francis Yunito Rumlawang; Takagi-Sugeno fuzzy modeling applied to predict sales data based on inventory data and demand data. AIP Conference Proceedings 23 January 2023; 2588 (1): 050020. https://doi.org/10.1063/5.0111854 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAIP Publishing PortfolioAIP Conference Proceedings Search Advanced Search |Citation Search
Type-2 Fuzzy Classifier with Smooth Type-Reduction

The defuzzification of a type-2 fuzzy set is a two-stage process consisting of firstly type-reduction, and a secondly defuzzification of the resultant type-1 set. All accurate type reduction methods used to build fuzzy classifiers are based on the recursive Karnik-Mendel algorithm, which is troublesome to obtain a feedforward type-2 fuzzy network structure. Moreover, the KM algorithm and its modifications complicate the learning process due to the non-differentiability of the maximum and minimum functions. Therefore, this paper proposes to use the smooth maximum function to develop a new structure of the fuzzy type-2 classifier.
BEGL: boundary enhancement with Gaussian Loss for rock-art image segmentation

Abstract Rock-art has been scratched, carved, and pecked into rock panels all over the world resulting in a huge number of engraved figures on natural rock surfaces that record ancient human life and culture. To preserve and recognize these valuable artifacts of human history, 2D digitization of rock surfaces has become a suitable approach due to the development of powerful 2D image processing techniques in recent years. In this article, we present a novel systematical framework for the segmentation of different petroglyph figures from 2D high-resolution images. The novel boundary enhancement with Gaussian loss (BEGL) function is proposed aiming at refining and smoothing the rock-arts boundaries in the basic UNet architecture. Several experiments on the 3D-pitoti dataset demonstrate that our proposed approach can achieve more accurate boundaries and superior results compared with other loss functions. The comprehensive framework of petroglyph segmentation from 2D high-resolution images provides the foundation for recognizing multiple petroglyph marks. The framework can then be extended to other cultural heritage digital protection domain easily.
Helpful Neighbors: Leveraging Neighbors in Geographic Feature Pronunciation

Abstract If one sees the place name Houston Mercer Dog Run in New York, how does one know how to pronounce it? Assuming one knows that Houston in New York is pronounced /ˈhaʊstən/ and not like the Texas city (/ˈhjuːstən/), then one can probably guess that /ˈhaʊstən/ is also used in the name of the dog park. We present a novel architecture that learns to use the pronunciations of neighboring names in order to guess the pronunciation of a given target feature. Applied to Japanese place names, we demonstrate the utility of the model to finding and proposing corrections for errors in Google Maps. To demonstrate the utility of this approach to structurally similar problems, we also report on an application to a totally different task: Cognate reflex prediction in comparative historical linguistics. A version of the code has been open-sourced.1
Fine-Grained Head Pose Estimation Based on a 6D Rotation Representation with Multiregression Loss

Estimating the head pose is vital in action evaluation since it has extensive applications such as in automobile driver-assistance systems, performance evaluations of athletes and customers’ attention in retail stores. It is difficult to predict the head orientation from an RGB image by deep learning more accurately. We propose 6DHPENet, a fine-grained 6D head pose estimation network, to estimate the 3D rotations of the head. First, the model adopts a 6D rotation representation for 3D rotations as training objective to guarantee effective learning. 6D rotation representation is a continuous and one-to-one mapping function for 3D rotations. Second, achieving 3D facial landmarks from real-time activities consumes more time and is subject to frontal views. We drop the 3D facial landmarks to enhance the adaptability and generalization ability in various application scenes. Third, after the last convolution extraction layer, a squeeze-and-excitation module is introduced to construct both the local spatial and global channel-wise facial feature information by explicitly modeling the interdependencies between the feature channels. Finally, a multiregression loss function is presented to improve the accuracy and stability for a full-range view of the head pose estimation. In addition, our method is compact and efficient for mobile devices because of the lightweight CNN backbone. The quantitative experiment results trained on 300W-LP datasets show the superior performance of our 6D rotation representation-based multiregression fine-grained method on the AFLW2000 and BIWI datasets.
Calculation and analysis of quantum radar scattering characteristics of targets in atmospheric medium

Though much work has been done concerning quantum radar cross section (QRCS), the related question about quantum radar scattering characteristics of targets in the atmospheric medium has not been considered. Understanding this question is of primary significance in the military and civil fields of quantum radar. The main objective of the paper is to propose a new algorithm for the calculation of QRCS in homogeneous atmospheric medium (M-QRCS). Therefore, based on the chain of beam splitters proposed by M. Lanzagorta to describe homogeneous atmospheric medium, the photon attenuation model is established, the photon wave function is modified, and the M-QRCS equation is proposed. Furthermore, in order to obtain an accurate M-QRCS response, we carry out simulation experiments on a flat rectangular plate in the atmospheric medium composed of different atomic arrays. Based on this, we study the influence of the attenuation coefficient, temperature, and visibility on the intensity of the peak value of main lobe and side lobes of M-QRCS. In addition, it is worth noting that the numerical calculation method proposed in this paper is based on the interaction between photons and atoms on the target surface, so it is suitable for the calculation and simulation of M-QRCS for targets of any shape.
Development of E-modules to Improve Critical Thinking Skills of Grade IV Elementary School Students

The use of science material textbooks in the digitalization era needs to be developed into supplement teaching materials that are packaged electronically. Science learning is required to contain a combination of theory and practice to improve critical thinking skills. The purpose of this study is to determine the effectiveness of E-modules in improving students' critical thinking skills. The method used is Research and Development (RD) with a 4D model with stages of define, design, develop, and disseminate. Inkiri-based e-modules using inquiry syntax, there are materials, educational games, inquiry-based student worksheets are the main characteristics of inquiry-based E-module media that are developed. Based on the results of the study, the average score percentage of the validity of inquiry-based e-modules by material experts and media experts was obtained at 91.94% with details of material expert validation of 92.38% and media experts of 90.5% so that it can be used. Teacher and student responses to the practicality of inquiry-based e-modules Keywords: [E-modules, Inquiry, Critical Thinking]