Reviewerly/exHarmony huggingface dataset:
Analyzing Context Clues in Novel Based on Bauman's Theoretical Framework

Context clues are valuable tools employed by authors to assist readers in comprehending unfamiliar or complex vocabulary. These clues, whether intentionally or inadvertently provided, facilitate the reader's understanding and interpretation of the word in question. Drawing upon Bauman's theoretical framework, the present study sought to investigate the diverse contextual cues utilized by the author within the literary work entitled "Jet Black and the Ninja Wind." The primary objective of this investigation was to gain a comprehensive understanding of the semantic nuances associated with unfamiliar lexical items employed in the literary work "Jet Black and the Ninja Wind." Additionally, this study aimed to identify and analyze the predominant types of contextual cues prominently present within the book above. In this study, a descriptive qualitative approach was utilized by the researcher. The data collection method employed in this study involved the utilization of documentation as a means to gather relevant information. The human instrument, the researcher herself, was utilized as the primary instrument in this research endeavor. The data analysis process in this study consisted of three distinct stages: data condensing, data displaying, and conclusion drawing. Investigator triangulation was also employed in this study to corroborate and substantiate the findings derived from the comprehensive analysis of the collected data. After conducting an extensive examination of Jet Black and the Ninja Wind, 56 unfamiliar terms were identified. These terms were subsequently categorized into four distinct groups, taking into consideration contextual clues that suggested each group possessed a particular semantic significance. The categorization of context hint types encompasses inference/general cues, synonym/restatement clues, antonym/contrast clues, and definition/explanation clues. In the literary work entitled "Jet Black and the Ninja Wind," the author predominantly utilized various types of context clues, including but not limited to synonym/restatement clues, inference/general hint clues, definition/explanation clues, and antonym/contrast clues.
Investigating a Hierarchical Inductive Bias in L2-textbook Seq2Seq Language Model

The relations between words in natural language are governed by hierarchical structures rather than linear ordering. In recent years, artificial neural network-based language models (LMs) have demonstrated impressive achievements in tasks related to sentence processing. These models benefit from pre-training, which helps enhance their performance. However, our comprehension of the precise syntactic knowledge acquired by these models during sentence processing remains somewhat restricted. This paper examines whether the L2-textbook Seq2Seq (Sequence-to-Sequence) language model processes or transforms sentences based on a syntactic hierarchical inductive bias or a linear inductive bias through transformation tasks. We replicate several previous experiments and explore our model’s capacity to exhibit human-like behavior. Our experiments provide evidence that, in transformation tasks, our pre-trained L2-textbook LSTM-based Seq2Seq model performed based on the linear rule rather than hierarchical rule. In essence, our model showcased a linear inductive bias, consistent with the Scratch-Seq2Seq model.
EARTH SIZE MEASUREMENT IN SUMMER SOLSTICE USING “ÉRATOSTHÈNE” METHOD

The knowledge of solar deposit is very necessary in sizing and proper operation of any system powered by solar energy. Solar radiation data are used in the design development, construction, as well as in the solar energy systems performance evaluation, but also for the construction of buildings with a view to better thermal insulation adapted to the geographical location. According to the summer solstice 2022 occasion, in this work the measure of the earth radius is proposed using ’’Eratosthenes method’’. For this, three fundamental conditions have been taken for the correct application in our calculations. Which cities to choose? When to make the measurements? And what precautions to take? This document may be beneficial for students and the public
Micro-level Implementation Study on In-school Professional Learning Community Policy

이 연구는 자생적으로 출발한 교사전문학습공동체가 교육행정기관의 하향식 교육정책으로 변형되었을 때, 교사 자율성이 유지될지 아니면 하향식 정책의 특성을 드러낼지에 대한 궁금증에서 출발하였다. 이러한 의문을 풀기 위해서 연구자는 대전의 미래중학교를 대상으로 질적 사례연구를 통해서 정책과 학교 그리고 행정기관의 관계를 조사하였다. 분석은 McLaughlin과 Berman의 정책집행이론을 활용하였다. 연구결과, 미래중학교 정책집행의 특성은 정책의 내용과 학교조직의 관행이 서로 달라지는 ‘상호적응’이 주로 나타났으며, 학교의 관행에 따라 정책을 변화시키는 ‘흡수’ 양상이 일부 나타났다. 미래중학교의 전문적 학습공동체 정책집행에서 ‘상호적응’이 주요 적응 양상으로 나타난 것은 ‘자율성’과 ‘독립성’이 핵심가치였던 전문적 학습공동체가 하향식 정책으로 변화한 이후에도 유지할 수 있음을 시사한다. 이는 학교의 적극적 대응 노력과 함께 교사의 자율성과 독립성을 교육청도 존중하면서 정책을 조정해갔기 때문이다. 따라서 바람직한 정책집행을 위해서 교육청의 정책 집행자와 학교의 집행자들이 상호적응할 수 있는 정책의 유연함이 필요하다. The professional learning community within schools was initially a self-sustaining organization, but it transformed into a top-down policy. This study was to investigate how the professional learning community policy is implemented at Daejeon Mirae Middle School, using policy implementation theory of McLaughlin and Berman. Mirae Middle School showed mainly mutual adaptation, where the policy’s content and school practices interacted and influenced each other. Some aspects of absorption were observed, where the school practices influenced changes in the policy. This means that the core values of autonomy and independence within the professional learning community were maintained even after its transformation into a top-down policy. This was attributed to the active efforts of the school in responding to the policy, along with the Education Office respecting the autonomy and independence of teachers while adjusting the policy. Consequently, there is a need for policies to be flexibly designed to allow discretion for both educational administrative agencies and school policy implementers.
Research on Classification Construction of Degree Programs Based on Life Cycle Theory

The development of degree programs is not achieved overnight, but also has a certain internal growth cycle and development stage. Drawing inspiration from the life cycle theory, a four-stage lifecycle theory of degree programs with incubation period, growth period, development period, and differentiation period was proposed. Then, combining eight key tasks related to degree program construction, including degree program cultivation, application, special qualification evaluation, periodic qualification evaluation, discipline evaluation, level evaluation of professional degree, quality special inspection, and dynamic adjustment, this paper shoot the arrow at the target based on the main work and tasks of degree program construction at different stages. Finally, taking Henan Polytechnic University (HPU) as an example, classified construction of degree programs was implemented, corresponding governance strategies were adopted to improve the construction level of degree programs in different states, and high-quality connotation development of degree programs was promoted.
Lexical and Grammatical Cohesion in the Regional Regulation Discourse of West Sumatra Province

This study aims to explain the discourse structure, specifically the lexical and grammatical cohesion in the discourse of West Sumatra Province, with a discourse analysis approach. The object of this research is a special regional regulation (SRR) of West Sumatra Province, which is different from Regional Regulation (RR) in other regions in Indonesia, as evident in the use of local concepts and terms. This regulation is interesting to study in cohesion because its structures represent the social reality of the indigenous people’s lives. One notable regulation is Nagari, the lowest government level in West Sumatra Province, with authority to regulate their communities and customary land in the Republic of Indonesia. That social reality is illustrated in the cohesiveness and harmony of the relationships of the forms that construct the discourse. This mixed-method research employs both quantitative and qualitative data and applied lexical and grammatical cohesion theory in data analysis. Findings show that lexical cohesion is realized in the following forms: repetition, synonym, meronymy, hyponym, and collocation; while grammatical cohesion is realized in the form of references, substitutions, and conjunctions. Based on the analysis, lexical and grammatical cohesion are interconnected constituents in building the integrity of the discourse structure in the SRR of West Sumatra Province. Cohesion plays a role in determining the meaning of the discourse as a whole and reflects the coherence of ideational meanings in discourse.
The Rhetorical Structure of Review Article Abstracts in Applied Linguistics Published in High-Impact International Journals

It is generally acknowledged that an abstract is just a short text, but it is a gateway to publish and promote the article. However, writing a good abstract to publish in a prestigious international journal is quite challenging. Therefore, writing a well-constructed abstract based on the guideline is the best solution for writers. So far, the study on how to arrange rhetorical moves for writing the abstract of the review article is very limited. In this regard, this study aims to investigate the rhetorical structure of review article abstracts in applied linguistics published in high-impact international journals. The checklist obtained from the pilot project was used to analyze the 50 review article abstracts selected from four international journals. The results show that five moves are identified: Background, Objective, Method, Synthesis of Discussion, and Conclusion. The first two moves are regarded as conventional, while the rest of the moves are optional. Moreover, the outcomes indicate that some moves are constructed differently in terms of the content and structure, especially the linguistic features, compared to the research article abstracts. The findings also reveal that Background-Objective-Synthesis of Discussion (M1-M2-M4) is the common move pattern. As a practical implication, article writers should follow the common rhetorical move pattern and linguistic features as shown by this study when writing a review article abstract. For theoretical application, this study can be used to support future studies also.
College Life Experience in the Changed Education Environment due to the prolonged COVID-19 Pandemic: A Focus on K University

연구목적: 본 연구의 목적은 코로나19 장기화로 인한 변화된 교육환경 속에서 대학생들의 학교생활에는 어떤 변화가 있었는지 살펴보고 그 경험의 본질적 요소와 구조를 심층적으로 탐색한 후 그 의미 구조를 이해하는 데 있다. 연구방법: 경남지역 K대학교 대학생 7명을 대상으로 2020년 5월부터 2022년 7월까지 반구조화된 질문지를 활용하여 심층면담 및 FGI를 실시하였고 Giorgi의 기술적 현상학적 연구방법을 적용하여 분석하였다. 연구결과: 심층 면담 내용을 분석한 결과 71개의 의미단위와 11개의 하위구성 요소, 3개의 구성요소로 통합되었다. 코로나19 장기화로 달라진 대학생활 경험의 3개 구성요소는 ‘사이버 세계 내 존재: 폐쇄, 단절, 해체’, ‘두 세계 내 존재: 공존에 대한 저항, 재정비’, ‘새로운 세계 내 존재: 뉴노멀의 노멀화, 일상의 재구성’으로 나타났다. 결론: 본 연구결과는 포스트 코로나 시대에는 대학 교육환경을 새롭게 모색해야 함을 시사한다. 또한 포스트 코로나 시대 대학 교육의 새로운 방향성 및 대학의 학생 지원 전략 수립의 기초자료를 제공한다는 점에서 중요한 의의가 있다.Objective: This study sought, via an in-depth exploration, to understand the intrinsic meaning behind how to change college life experiences in the altered educational environment in the wake of the prolonged COVID-19 pandemic. Methods: This study conducted in-depth interviews and FGI with 7 K university students from May 2020 to July 2022. The data analyzed through the Giorgi’s phenomenological methodology. Results: 71 meaning units, 11 sub-components, 3 components were derived. The 3 components of the changed college life experience were “existence in the cyber world: closing, isolating, breaking up,” “existence in the two worlds: resistance to coexistence, reestablishment,” and “existence in the new world: normalization of new normal, reorganizing everyday life.” Conclusions: The results suggest that the university education system be changed in the post COVID-19 era. This study has significant implication in the provision of basic data that can help establish new directions of university education and strategies for supporting measures required for students in the post COVID-19 era.
Modified LeNet-5 Architecture to Classify High Variety of Tourism Object: A Case Study of Tourism Object for Education in Tinalah Village

This research aims to modify a CNN (Convolutional Neural Network) based on LeNet-5 to reduce overfitting in a Tinalah Tourism Village dataset object detection. Tinalah Tourism Village has many objects that can be identified for tourism education and enhanced tourist experience. While these objects, spread across the different sites ofÂ TinalahÂ do vary, some share similarities in their histogram patterns. Visually, if the size of a picture is reduced in the LeNet-5 â€˜preferred sizeâ€™ feature, it will inevitably lose some of its information, making pictures too similar reducing accuracy. In order to learn and classify objects, this research performs a modification on LeNet-5 architecture to provide a better performance geared toward larger input imaging. The previous state-of-the-art architecture showed an overfitting performance where the training accuracy performed too much better than the testing accuracy in our dataset. We brought in a dropout layer to reduce overfitting, increase the dense layer's size, and add a convolution layer. We then compared the modified LeNet-5 with other state-of-the art architecture, such as LeNet-5 and AlexNet. Results showed that a modified LeNet-5 outperformed other architectures, especially in performing accuracy for testing theÂ TinalahÂ dataset, reaching 0.913 or (91,3 %). This research discusses the dataset, the modified LeNet-5 architecture, and performance comparison between state-of-the-art CNN architecture. Our CNN architecture can be developed by involving a transfer learning mechanism to provide greater accuracy for further research.
The Effects of Organizational Creativity of Early Childhood Education Institutions and Early Childhood Teachers’ Play Beliefs on the Play Teaching Efficacy of Early Childhood Teachers

연구목적: 본 연구는 유아교육기관의 조직창의성과 유아교사의 놀이신념이 유아교사의 놀이교수효능감에 미치는 영향을 확인하는 것을 목적으로 하였다. 연구방법: 본 연구의 연구대상은 유치원, 어린이집에 근무하는 유아교사 총 311명이었다. 연구도구는 이새별(2021)이 개발한 유아교육기관의 조직창의성 척도, 권혜진(2013)이 재구성한 유아교사의 놀이신념 척도, 신은수, 유영의, 박현경(2004)이 제작한 놀이교수효능감 척도를 활용하였다. 이를 통해 수집된 자료는 SPSS 29.0 통계프로그램을 활용하여 빈도분석과 기술통계분석, Cronbach’s α 계수, Pearson 상관관계 분석, 단계적 다중회귀분석을 실시하였다. 연구결과: 첫째, 유아교육기관의 조직창의성과 유아교사의 놀이신념 및 유아교사의 놀이교수효능감은 서로 유의한 상관관계를 가졌다. 둘째, 유아교육기관의 조직창의성 하위요인 중 관리자의 리더십이 설명력이 가장 높았고, 창의적 운영제도, 창의적 효능감, 조직문화 그리고 긍정적 놀이신념과 부정적 놀이신념은 유아교사의 놀이교수효능감에 유의한 영향력을 보였다. 결론: 결론적으로 놀이를 지원하고 지지하는 과정에서 필수적인 놀이교수효능감을 증진시키는 데 있어 유아교육기관의 조직창의성과 유아교사의 놀이 신념을 높이는 것이 효과가 있을 수 있다. 따라서 유아교사의 놀이교수효능감을 지원하기 위한 방안으로 유아교육기관의 조직창의성과 유아교사의 놀이신념을 고려할 필요가 있다.Objective: This study sought to investigate the effect of organizational creativity of early childhood education institutions and early childhood teachers’ beliefs about play on early childhood teachers’ play teaching efficacy. Methods: The subjects of this study included 311 early childhood teachers working at early childhood education institutions. In this study, Lee Sae-byeol’s Organizational Creativity Scale (2021) was used to examine the organizational creativity of early childhood educational institutions, whereas Kwon Hye-jin’s Parent Play Beliefs Scale (2013) was used to measure early childhood teachers’ play beliefs. And in order to measure the play teaching efficacy of early childhood teachers, Shin Eun-soo, Yoo Young-eui, and Park Hyeon-kyung’s scale (2004) was used. Reliability analysis, frequency analysis, descriptive statistical analysis, correlation analysis, and stepwise multiple regression analysis were performed using the SPSS 29.0 statistical program by using the play teaching efficacy scale. Results: Organizational creativity of early childhood education institutions and early childhood teachers’ play beliefs have a significant effect on early childhood teachers’ sense of play teaching efficacy. Conclusions: The results suggests that the importance of early childhood teachers’ sense of play teaching efficacy is based on the their beliefs about play and how it affects children’s play; furthermore, the organizational creativity of early childhood education institutions affect early childhood teachers.
Skew Correction and Image Cleaning Handwriting Recognition Using a Convolutional Neural Network

Handwriting recognition is a study of Optical Character Recognition (OCR) which has a high level of complexity. In addition, everyone has a unique and inconsistent handwriting style in writing characters upright, affecting recognition success. However, proper pre-processing and classification algorithms affect the success of pattern recognition systems. This paper proposes a pre-processing method for handwriting image recognition using a convolutional neural network (CNN). This study uses public datasets for training and private datasets for testing. This pre-processing consists of three processes: image cleaning, skew correction, and segmentation. These three processes aim to clean the image from unnecessary ink streaks. In addition, to make angle corrections to characters in italics in their writing. The model testing process uses image test data of handwriting that are not straight. There are three images based on the inclination angle: less than 45 degrees, equal to 45 degrees, and more than 45 degrees. Picture cleaning removes unnecessary strokes (noise) from the image using a layer mask, whereas skew correction changes the handwriting to an upright posture based on the detected angle. The pre-processing model we propose worked optimally on handwriting with a skew angle of fewer than 45 degrees and 45 degrees. Our proposed model generally works well for handwriting with fewer than 45 degrees skew with an accuracy of 88,96%.Â Research with a similar scope can continue to improve optimization with a focus on algorithms related to analysis layout studies. Besides that, it can focus more on automation in the segmentation process of each character.
Measuring the Effect of E-Learning Information Quality on Student’s Satisfaction Using the Technology Acceptance Model

This study analyses a blended e-learning system's information resources. Their quality is assessed based on learners' perceptions using a modified version of the Technology Acceptance Model (TAM). To enable flexible learning and enhance understanding during the COVID-19 epidemic, most Iraqi universities have lately embraced Google Classroom and Moodle in addition to face-to-face (F2F) courses. Based on TAM, individual differences and perspectives were investigated concerning correlations between student satisfaction and technology adoption. There were 270 undergraduate students in the research sample who were enrolled in academic courses at Middle Technical University's (MTU) /Technical College of Management (TCM). A survey was used for data collection. The research was done after developing the model's essential and external variables and selecting their components. Partial least squares structural equation modelling (PLS-SEM) examined path-connected dependent and independent components. The study's results showed how "E-Learning Information Quality" (EIQ) positively impacted students' adoption of e-learning. That is demonstrated by the internal variables' positive correlation, which includes perceived usefulness (PU) and perceived ease of use (PEOU), which can be seen in H1 and H2 by the values of (Î² = 0.204, Î² = 0.715), and which both positively influence attitudes toward use (ATU), which can be seen in H5 were value (Î² = 0.643), and behavioral intention (BIU), which can be seen in H4 was value (Î² = 0.300). Therefore, e-Learning information sources must have value and meaning for students. However, more research is required to evaluate the system's quality. Furthermore, the acceptability of e-learning may change as pedagogies change
Max Feature Map CNN with Support Vector Guided Softmax for Face Recognition

Face recognition has made significant progress because of advances in deep convolutional neural networks (CNNs) in addressing face verification in large amounts of data variation. When image data comes from different sources and devices, the identifiability of other classes and the presence of profile face data can lead to inaccurate and ambiguous classification because other classes lack discriminatory power. Furthermore, using a complex architecture with many deep convolutional layers can become very slow in the training process due to a huge amount of Random Access Memory (RAM) usage during the reverse pass of backpropagation. In this paper, we design a light CNN architecture that addresses these challenges. Specifically, we implemented Max-feature-map (MFM) into each convolutional layer to improve the accuracy and efficiency of the CNN. The strength of the support vector-guided SoftMax (SV-SoftMax) is also used in the proposed method to emphasize misclassified points and adaptively guide feature learning. Experimental results show that the 9-Layers CNN with MFM layer and SV-SoftMax outperform VGG-19 with 96.22% validation accuracy and the second rank below FaceNet tested on the same dataset with fewer parameters. Moreover, the model performed well on data that is obtained from various capture devices such as webcam, CCTVs, phone cameras, and DSLR cameras. The implications of this research could extend to scenarios requiring face recognition technology implementation with light size, such as surveillance and authentication systems
Error-induced inverse pixel visual cryptography for secure QR code communication

&lt;p&gt;The rapid proliferation of Quick Response (QR) codes in various applications, particularly in sensitive domains like banking and financial transactions, necessitates robust data protection measures. Visual cryptography techniques are used to encode confidential information into multiple shares called shadows, which are communicated to the receivers. The receiving side decodes the shadows by stacking them together physically or digitally. In this research, an innovative solution titled “Error-induced inverse pixel visual cryptography (EIIPVC) for secure QR code communication” is proposed to enhance the security. The proposed EIIPVC leverages complementary shadows and introduces controlled errors during the sharing process. This feature makes it exceedingly challenging for potential malpractice to access or tamper with the data, ensuring a higher level of security. In this research, a single grayscale secret source (GSS) image in the form of QR code is used. This research also contributes to improving traditional issues, such as the quality of the reconstructed image and pixel expansion. The experimental results demonstrate that the EIIPVC approach significantly ensures enhanced security, safeguarding the transmitted data against potential attacks. The quality of the reconstructed image is improved by minimizing the mean square error (MSE) value up to 5%, indicating its superiority in preserving the visual clarity.&lt;/p&gt;