Reviewerly/exHarmony huggingface dataset:
Multiclass Classification of Cervical Pap Smear Images Using Deep Learning-Based Model

One of the primary reasons for women's deaths is cervical cancer.The most important procedures that are to be performed to ensure the reduction of cervical cancer's side effects are possible diagnosis and the most definitive possible medical treatment.One of the best methods for identifying this type of cancer is using PaP smear images.For cervical cancer detection in PaP smear images, this research proposes a novel hybrid deep learning approach.The proposed methodology for cervical cancer classification performs the four efficient stages.A shape-based iterative method is used to detect nuclei in cell segmentation, and a marker-control watershed approach is used to separate overlapping cytoplasm.From the regions of segmented nuclei and cytoplasm, the practical features are extracted in the features extraction step.The simulated annealing integrated with a wrapper filter is employed for efficient feature selection.The classification of cervical cancer from pap-smear images is achieved using an attention-based nested classification network (Anu-Net) based on deep learning.The SIPaKMeD dataset is used for experiment analysis.The experimental results reveal that the developed deep-learning network model enabled high classification accuracy.The accuracy for a binary class problem was 99.95%; for a threeclass problem was 99.98%; and a five-class problem was 99.74%.The proposed approach significantly outperformed existing deep learning models in binary class, three-class, and five-class problems than the existing approaches.
A New Automatic Vehicle Tracking and Detection Algorithm for Multi-Traffic Video Cameras

Vehicle tracking systems are a vital tool in modern-day law enforcement and security operations.With the increasing threats of terrorism, organized crime, and illegal trafficking, monitoring and tracking suspicious vehicles has become a top priority for security agencies around the world.In this study, a target vehicle, which was described as suspicious, was tracked using the proposed vehicle tracking method that contains Gaussian Mixture Model (GMM) and Blob analysis.The same target vehicle was then detected using the Regions with Convolutional Neural Networks (RCNN), Faster RCNN, and You Only Look Once (YOLO) deep learning object recognition algorithms.In these applications, public traffic surveillance system images from the internet are used.Tracking is performed on images taken from more than one traffic surveillance system on the same road or route.The results from these methods were compared with each other, and the highest mean Average Precision (mAP) value was observed as 89.20% for the Faster RCNN algorithm using the Resnet101 deep learning architecture.
A Study on Convergence of Text Analysis Techniques for Social Science Research in the Age of Big Data

In this paper, we do not only propose appropriate application methods of the semantic network analysis technique, topic modeling technique and text clustering technique, which are techniques that can analyze text document sets but also the convergence application methods between each techniques. Appropriate application methods for the text analysis techniques were presented by dividing exploratory analysis process and modeling process for analyzing the text document set. Semantic network analysis would be not only suitable for exploratory analysis of the entire text document set, but also applicable to performance improvement of topic modeling and text clustering. The meaning of the topic could be interpreted more clearly by applying semantic network analysis secondarily to the document set of each topic derived by topic modeling. It can be used for text cluster interpretation by applying semantic network analysis to the document set of each cluster, which is the result of text cluster analysis. When deriving an appropriate number of topics, a more accurate number of topics could be derived by adding a silhouette analysis along with the degree of perplexity and coherence. New social science research can be expected to be revitalized by enabling more accurate analysis of online text documents using the method proposed in this paper.
The Representation of Target Culture in a Locally Published English Textbook

Culture is an important part of English language teaching and learning. Students must be exposed to the culture related to the communication skills being taught. Textbook can be a medium for the teachers to present different kinds of culture along with the language content. Therefore, it is essential for an English textbook to properly include cultural contents. This study aims to investigate the target culture included in a junior high school English textbook used by many teachers in Indonesia. Qualitative descriptive design was employed in order to describe the target culture in the textbook without any manipulation to the data. Moran’s (2001) five dimensions of culture that include products, practices, perspectives, communities, and persons was used to analyze the data. The results found 61 items in the textbook that contained references to the target culture. The ways those target culture were presented were not vary. Almost all of those items were presented in words or passages.
Robust Deep Convolutional Neural Network inspired by the Primary Visual Cortex

Most of the current advanced object recognition deep convolutional neural networks (DCNNs) are vulnerable to attacks of adversarial perturbations. In comparison, the primate vision system can effectively suppress the inference of adversarial perturbations. Many studies have shown that the fusion of biological vision mechanisms and DCNNs is a promising way to improve model robustness. The primary visual cortex (V1) is a key brain region for visual information processing in the biological brain, containing various simple cell orientation selection receptive fields, which can specifically respond to low-level features. Therefore, we have developed an object classification DCNN model inspired by V1 orientation selection receptive fields. The V1-inspired model introduces V1 orientation selection receptive fields into DCNN through anisotropic Gaussian kernels, which can enrich the receptive fields of DCNN. In the white-box adversarial attack experiments on CIFAR-100 and Mini-ImageNet, the adversarial robustness of our model is 21.74% and 20.01% higher than that of the baseline DCNN, respectively. Compared with the SOAT VOneNet, the adversarial robustness of our model improves by 2.88% and 8.56%, respectively. It is worth pointing out that our method will not increase the parameter quantity of the baseline model, while the extra training cost is very little.
Anomaly Handwritten Text Detection for Automatic Descriptive Answer Evaluation

Although there are advanced technologies for character recognition, automatic descriptive answer evaluation is an open challenge for the document image analysis community due to large diversified handwritten text and answers to the question. This paper presents a novel method for detecting anomaly handwritten text in the responses written by the students to the questions. The method is proposed based on the fact that when the students are confident in answering questions, the students usually write answers legibly and neatly while they are not confident, they write sloppy writing which may not be easy for the reader to understand. To detect such anomaly handwritten text, we explore a new combination of Fourier transform and deep learning model for detecting edges. This result preserves the structure of handwritten text. For extracting features for classification of anomaly text and normal text, the proposed method studies the behavior of writing style, especially the variation at ascenders and descenders. Therefore, the proposed work draws principal axis which is invariant to rotation, scaling and some extent to distortion for the edge images. With respect to principal axis, the proposed method draws medial axis using uppermost and lowermost points. The distance between the medial axis and principal axis points are considered as feature vector. Further, the feature vector is passed to Artificial Neural Network for classification of anomaly text. The proposed method is evaluated by testing on our own dataset, standard dataset of gender identification (IAM) and handwritten forgery detection dataset (ACPR 2019). The results on different datasets show that the proposed work outperforms the existing methods.
Personalized book recommendation algorithm based on attention enhancement mechanism

With the enrichment of human knowledge, the scale of books carrying knowledge is also increasing. Under this background, how to help readers accurately search book resources that are exactly suitable for them, has become an unavoidable problem in the ‘‘Information Explosion’’ era. In order to realize personalized and intelligent recommendation for books, this paper analyzes the recommendation algorithm based on bipartite networks, and proposes an improved method using the mechanism of attention enhancement. The proposed algorithm measures the reader’s attention to the books and enhances the role of the more attentive readers in the recommendation process. We conduct experiments on GoodBooks dataset. The results of experiment demonstrate that our improved algorithm is in a position to enhance accuracy of recommendations and ensure better diversity by selecting appropriate enhancement parameter.
LITERASI DIGITAL MAHASISWA BKPI FITK UIN SUMATERA UTARA MEDAN TAHUN 2021

This study describes the digital literacy of students BKPI FITK State Islamic University of North Sumatera Utara (UIN-SU) in Medan. Quantitative descriptive method was used in doing this study. There were 191 students BKPI FITK UIN-SU Medan in 2021 being samples for this study. The instrument of this study was questionnaire using a five-likert scales. Data obtaining process was conducted by utilizing google form which was shared to students. The results of study revealed that students’ digital literacy score is 70 which means average. The highest aspect of students’ digital literacy is safety aspect which shows score 20.68 and the lowest one is skill aspect namely 15.36. Based on sex type, female-students’ digital literacy is higher than male-students. Female-students’ digital literacy score is 73.19, meanwhile male-students is just 71.48. Moreover, digital literacy of students graduated from public senior high school is higher than students graduated from Islamic boarding school or pesantren. Specifically, the score of the former is 75.14 and the latter is 69.50.
Efektivitas E-modul Instalasi Penerangan Listrik di SMK Negeri 1 Sutera

This study aims to determine the effectiveness of the e-module for electric lighting installations at SMK Negeri 1 Sutera. This research was conducted using a type of experimental research which was categorized into the type of pre-experimental design with the One Group Pretest Posttest Design. The data obtained were analyzed using Effect Size and classical completeness analysis. Attitude assessment using a questionnaire with percentage analysis technical. Based on the research results, it was obtained that the average pretest before using the e-module learning media was 58.1 and the posttest average value was 72.6. From the calculation results, the Effect Size analysis value is 1.069 with the categorization of taste on a large scale. While the attitude assessment obtained an average result of 91.25 for a standard deviation of 12.26.
Supplemental Material for Morphology in Reading Comprehension Among School-Aged Readers of English: A Synthesis and Meta-Analytic Structural Equation Modeling Study

a URL, doi, or other permanent path for accessing the specified information in a public, openaccess repository, and the specified information must be provided in a format that is time-stamped, immutable, and permanent.Qualifying public, open-access repositories are committed to preserving data, materials, and/or registered analysis plans and keeping them publicly accessible via the web in perpetuity.Examples include the Open Science Framework (OSF) and the various Dataverse networks.Hundreds of other qualifying data/materials repositories are listed at http://re3data.org/.Preregistration of an analysis plan must take place via a publicly accessible registry system (e.g., OSF, ClinicalTrials.govor other trial registries in the WHO Registry Network, institutional registration systems).Personal websites and most departmental websites do not qualify as repositories.
The Ways to Optimize Mobile Phone Usage in English Instructional Activities

In the midst of controversial perceptions among students and teachers regarding the use of mobile phone in the classrooms, it is urgent to look for solution in order that these sophisticated devices are able to bring more benefits in language learning. This research aims at exploring students’ and teachers’ perceptions on how to optimize the mobile phones in English instructional activities so that the teaching and learning can be attractive and interactive, hence students’ participation in the classroom may increase as well as their learning outcome. This research applied qualitative research. The informants participated in this research were two English teachers and four students from two state Islamic senior high schools in Parepare, Indonesia. To collect the data, the researchers employed Focus Group Discussion (FGD). Students and teachers sat together in a forum to discuss and to argue their opinion or experiences in order that the use of mobile phones in the classroom during English learning activities can be optimal. To analyze the data, the researchers analyzed them by using thematic technique from Creswell. The results of this research show that there were five ways offered by both students and English teachers. Those ways are recommended to apply by both parties without too much worry because of potential distractions that may come up.
Gamified EFL learning: Utilizing 4 Pics 1 Word Application in Vocabulary Class

Mobile devices are widely utilized today in language classrooms across the globe, and experts have studied this phenomenon. This study examines the use of mobile devices and the 4 Pics 1 Word application (app) to support English language learning. This study seeks to investigate students’ perceptions of 4 Pics 1 Word app utilized in vocabulary class, specifically in terms of its benefits. Using a qualitative case study design, 40 EFL students attending a junior high school in Medan participated in this study. The data were collected through questionnaires containing ten statements in which the answer options are strongly agreed, agreed, neutral, disagreed, and strongly disagree; and semi-structured interview, which was done with five students who voluntarily participated. The findings indicate that students viewed the use of 4 Pics 1 Word in vocabulary class positively. It is believed that the application is efficient and well-designed, with an exciting and enjoyable learning environment. Enhanced learning motivation and interest, increased vocabulary mastery, and a more active and enjoyable learning process are among the benefits mentioned by the students.
HOTS Study: How are the literacy and thinking skills of students different?

This research was conducted to determine how the influence of digital literacy and critical thinking skills. This research was conducted using a mixed method with the convergent parallel design. The subjects of this study were students from SMAN 6 Batanghari and SMAN 10 Batanghari with a specialization in science, where each school took 2 classes with a total of 80 students as samples with 297 eleventh graders in both schools as population, where research sample chosen with purposive sampling. The data analysis carried out in this study was a normality test, linearity test, and regression test. From this research, it was found that there were significant differences in the level of digital literacy skills and understanding of students on digital literacy between the two test schools. Significant differences are also seen in the level of critical thinking of students. The interesting thing in the findings of this research is that students who have a good level of skills and understanding of digital literacy will have a good level of critical thinking as well. So, it was found that digital literacy also has an influence on students' critical thinking skills.
An Error Analysis of Students’ Translation from Indonesian into English Text at the 6th Semester Students of English Education Study Program in UIN Sjech M. Djamil Djambek Bukittingi

This research was due to some problems that were found in the 6th semester students of English Education Study Program in UIN Bukittingi. First, the students had vocabulary problem in translating Indonesian to English, especially the ability to use the proper vocabulary in translating. Second, the students had grammar problem in translating Indonesian to English, especially tenses and time condition. The purpose of this research was to find out the type of error that they make when translating text from Indonesian into English and to find out the most frequent error the students make when translating text from Indonesian into English. This research was a descriptive quantitative research. The sampling technique that researcher uses was total sampling. The instrument that was used in a research was translation test. It was a text consists of three paragraphs in Indonesian that must be translated into English. The researcher found that addition errors were made 7.31% of the time, omission errors were made 27.74% of the time, literalness errors were made 13.98% of the time, ambiguity errors were made 17.42% of the time, punctuation errors were made 4.95% of the time, spelling errors were made 3.44% of the time, and capitalization errors were made 25.16% of the time. It can be concluded that omission error is the most frequent error, followed by capitalization, ambiguity, literalness, addition, punctuation, and spelling. This make spelling as the least frequent error that the students made.
Enhancing Agricultural Productivity in Developing Countries with AI Technologies

Enhancing Agricultural Productivity in Developing Countries with AI Technologies
Investigating freshmen’s L2 speaking anxiety level in Indonesia

The present study aims at investigating freshmen’s English (hereafter is called L2) speaking anxiety level in the classroom. The data were derived from online survey on 155 freshmen on two English Education Departments in Palangka Raya. The result indicated that the freshmen were experiencing a high level of L2 speaking anxiety in the classroom. Further, the result of independent sample t-test analysis showed that there was no significant difference on freshmen’s L2 speaking anxiety level by their gender. Similarly, one-way ANOVA analysis indicated that there was no a statistical difference on freshmen’s L2 speaking anxiety by English learning experience. Considering the findings, a high level of speaking anxiety is a serious problem to measure as it will make students disinclined to L2 speaking activities leading to poor L2 speaking fluency.
Masyarakat Era Kontemporer Dalam Menghadapi Risiko Plastik

The presence of plastic in today's contemporary era, has various functions that greatly help people's lives. Plastic with all its properties, which are more inclined to the many advantages of its use and flexibility so that it is easy to use in various fields of life. With this fact, there are more and more products that rely on plastic as a basic ingredient in the manufacture of their products. This is of course supported by very high market demand, so that all types of production of goods made from plastic are mushrooming. If we return to our original purpose, the creation of plastic was indeed used as a substitute for paper bags, which at that time was experiencing a crisis of threats due to the increasing number of illegal logging incidents, so that there was a potential for the scarcity of the trees themselves. However, the opposite is currently true, where the use and production of plastics is increasingly dominating, making the remaining production waste and waste resulting from its use even more insurmountable. This is compounded by the fact that plastic is difficult to decompose, requiring hundreds of years of time. This, in the concept of a risk society is called the boomerang effect, because something that existed in the industrial era was created as a form of innovation that exists as a solution, but in the modern era like now it has become a separate risk for the surrounding community. For various phenomena as a result of the creation of plastic itself, society does not necessarily let them slowly be swallowed up by existing risks, but there are many efforts to create innovations as a way to protect themselves from various risks distributed by production and the increasingly widespread use of plastic in today's reality.
Public Speaking Anxiety and English Language Competency of Bachelor of Secondary Education English Majors

This research aimed to determine the public speaking anxiety and English language competency of the Bachelor of Secondary Education English majors at Laguna State Polytechnic University Los Baños Campus. The study employed a descriptive correlation research design using a validated survey questionnaire to find the relationship between the variables. In the study's findings, the respondents' public speaking anxiety level had a standard deviation of 0.71 and was descriptively interpreted as "agree". The level of English language competency of the students was proficient. The data showed that 70.5% of the respondents have proficient English Language competency while 22.7% were advanced, and 6.8% were approaching. Thus, the study shows no significant relationship between public speaking anxiety and English Language Competency. Based on the results, it is suggested that respondents should enhance their skills in public speaking though it did not affect their language proficiency. Implementing activities that would practice and develop the student's speaking skills is encouraged to future educators to prevent anxiety towards speaking. Since the students' PSA level is high, teachers need to guide the students with their speaking, their delivery and confidence along the process.
Preface

Metaverse, Non-Fungible Tokens (NFTs), Cryptocurrencies, Blockchain, Artificial Intelligence (AI), Service Robots etc. are a rapidly expanding field with an ever-increasing number of terms and community-specific jargon. A new term is not always accompanied by something truly novel. In addition to verbal „pseudo-innuendos“ and „crypto-slang“ introduced with the intent of attracting attention quickly, there are several significant new developments. The issue with this development is that the risk of „Babylonian language confusion“ is growing exponentially. Our observations indicate that this risk is particularly prevalent in the dialogue between science and practice. This book hopes to contribute to the clarification with quick access to all key terms. Obviously, many online marketplaces, platforms, encyclopedias, and glossaries already exist. However, our pre-book analysis has revealed that neither is even close to completion, sometimes with imprecise language and often with contradictory definitions and explanations. This glossary provides quick access for managers, students, and professors alike who are faced with the topics in their daily work. Students may keep track of the web 3.0‘s numerous terms as they study it. Instructors, teachers, and professors may use it as a guide for a consistent use of Metaverse, NFT, Cryptocurrency, and Blockchain terminology. Although, the more than 1,300 explanations of the individual terms are scientifically based, the focus is on easy understanding of the terms. The authors have made an effort to provide clear and concise definitions, an application-focused perspective, and simple language.