Reviewerly/exHarmony huggingface dataset:
Multi-Task Media-Bias Analysis Generalization for Pre-Trained  Identification of Expressions

Authors:
raw_author_name: Wessel, Martin
raw_author_name: Wahle, Jan Philip
raw_author_name: Ruas, Terry
raw_author_name: Greiner-Petter, André
raw_author_name: Aizawa, Akiko
raw_author_name: Gipp, Bela
raw_author_name: Spinde, Timo

Abstract: Media bias detection poses a complex, multifaceted problem traditionally tackled using single-task models and small in-domain datasets, consequently lacking generalizability. To address this, we introduce MAGPIE, the first large-scale multi-task pre-training approach explicitly tailored for media bias detection. To enable pre-training at scale, we present Large Bias Mixture (LBM), a compilation of 59 bias-related tasks. MAGPIE outperforms previous approaches in media bias detection on the Bias Annotation By Experts (BABE) dataset, with a relative improvement of 3.3% F1-score. MAGPIE also performs better than previous models on 5 out of 8 tasks in the Media Bias Identification Benchmark (MBIB). Using a RoBERTa encoder, MAGPIE needs only 15% of finetuning steps compared to single-task approaches. Our evaluation shows, for instance, that tasks like sentiment and emotionality boost all learning, all tasks enhance fake news detection, and scaling tasks leads to the best results. MAGPIE confirms that MTL is a promising approach for addressing media bias detection, enhancing the accuracy and efficiency of existing models. Furthermore, LBM is the first available resource collection focused on media bias MTL.
Design and Integration of JUNO-OSIRIS

Authors:
raw_author_name: Wang, Zhimin

Abstract: The Jiangmen Underground Neutrino Observatory (JUNO) is a neutrino detection experiment characterized by an acrylic sphere, measuring 35.4 m in diameter, containing 20,000 tons of liquid scintillator. This sphere is encompassed by as many as 17,600 photomultiplier tubes (PMTs) with a 20-inch diameter, achieving an overall coverage of 77.9%. With these impressive capabilities, the JUNO experiment aims to achieve an exceptional effective energy resolution of 3% at 1 MeV. The Online Scintillator Internal Radioactivity Investigation System (OSIRIS) serves as a precursor detector, around 100 m aside in horizontal of the site of the JUNO detector underground, tasked with monitoring and examining the purity of the liquid scintillator prior to its transfer to the JUNO central detector. The OSIRIS, also as a pre-detector of JUNO, is constructed with a cylindrical acrylic vessel designed to hold 18 tons of liquid scintillator. It is situated within a 9-m height cylindrical tank filled with 550 tons of pure water. This detector was specifically engineered to search for the fast coincidence decays of $^{214}$Bi -$^{214}$Po and $^{212}$Bi -$^{212}$Po in the decay chains of $^{238}$U and $^{232}$Th, respectively.OSIRIS has been designed to reach a sensitivity of 10$^{-16}$ g/g for U/Th to test scintillator radiopurity to the level required for the detection of solar neutrinos. Additionally, 64 20-inch microchannel plate PMTs (MCP PMTs) were positioned around the liquid scintillator vessel to observe incoming interactions, along with an additional 12 20-inch MCP PMTs for the water Cherenkov muon veto system. The OSIRIS pre-detector has been fully constructed and integrated, providing a plenty of preliminary results from the air runs. The next step in the process involves commencing the filling soon, aiming to involve an in-depth examination of the impurities within the liquid scintillator.
Gray Images of Constacyclic Codes over a Non-chain Extension of Z 4

Authors:
raw_author_name: Cruz Mohan
raw_affiliation_string: Department of Mathematics, Bishop Heber College, Trichy, Tamil Nadu, India
raw_author_name: Karthick Gowdhaman
raw_affiliation_string: Presidency University, Bengaluru, Karnataka, India
raw_author_name: Durairajan Chinnapillai
raw_affiliation_string: Department of Mathematics, Bharathidasan University, Trichy, Tamil Nadu, India
raw_author_name: Jian Gao
raw_affiliation_string: School of Mathematics and Statistics, Shandong University of Technology, Zibo, Shandong 255000, China

Abstract: Let [Formula: see text] be the ring of integers modulo 4. We study the [Formula: see text]-constacyclic and [Formula: see text]-cyclic codes over the non-chain ring [Formula: see text] for a unit [Formula: see text] in [Formula: see text]. We define several Gray maps and find that the respective Gray images of a quasi-cyclic code over [Formula: see text] are cyclic, quasi-cyclic or permutation equivalent to this code. For an odd positive integer [Formula: see text], we determine the generator polynomials of cyclic and [Formula: see text]-constacyclic codes of length [Formula: see text] over [Formula: see text]. Further, we prove that a [Formula: see text]-cyclic code of length [Formula: see text] is a [Formula: see text]-constacyclic code if [Formula: see text] is odd, and a [Formula: see text]-quasi-twisted code if [Formula: see text] is even. A few examples are also incorporated, in which two parameters are new and one is best known to date.
Performance Optimization of Document Clustering for Harry Potter Series Comments using Cosine Similarity

Authors:
raw_author_name: Nina Dwi Putriani

Abstract: This research delves into the distinctive realm of comment clustering, focusing on the extensive discourse generated by the Harry Potter series. Leveraging a dataset from Kaggle, the study aims to optimize document clustering using cosine similarity within the K-Means algorithm. The research addresses the nuanced dynamics of sentiment and preferences within the Harry Potter fan community. A comprehensive methodology involves data collection, preprocessing, TF-IDF initialization, K-Means clustering with varying distance metrics, and result evaluation. The dataset of 491 respondents unveils diverse gender, geographical, and age distributions, adding complexity to the analysis. The K-Means clustering results highlight predominant positive sentiment, emphasizing the enduring popularity of the series. The study's originality lies in its focus on the Harry Potter cultural phenomenon, contributing to sentiment analysis and fan engagement discourse. The implications extend to researchers, practitioners, and enthusiasts seeking a deeper understanding of online discussions surrounding iconic media franchises.
Double and triple character sums and gaps between the elements of subgroups of finite fields

Authors:
raw_author_name: Zhefeng Xu

Abstract: International Journal of Number TheoryAccepted Papers Free AccessDouble and triple character sums and gaps between the elements of subgroups of finite fieldsJiankang Wang and Zhefeng XuJiankang Wang and Zhefeng Xu Search for more papers by this author https://doi.org/10.1142/S1793042124500842Cited by:0 (Source: Crossref) PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail Remember to check out the Most Cited Articles! Check out new Number Theory books in our Mathematics 2021 catalogue FiguresReferencesRelatedDetails Recommended Accepted Papers Metrics History Received 20 June 2023 Accepted 18 January 2024 PDF download
Innovative Deep Learning Strategies for Chaotic Data Classification: A Multi-Algorithm Comparison in the Presence of Noise

Authors:
raw_author_name: Shih-Lin Lin
raw_affiliation_string: Graduate Institute of Vehicle Engineering, National Changhua University of Education, No.1, Jin-De Road, Changhua City 50007, Taiwan

Abstract: Chaos is prevalent in both nature and science, appearing in data, time series and complex systems. Chaotic systems exhibit numerous uncertainties, akin to noise, which challenge researchers to distinguish or analyze potential underlying patterns or even identify the type of system involved. However, determining the kind of chaotic system is essential, as it enables prediction, synchronization, control, treatment and application. This study employs machine learning to classify chaotic data through a simulation involving three types of research data: Lorenz data, Lorenz combined with Gaussian white noise, Gaussian white noise and pink noise, utilizing six distinct algorithms. The most effective testing results are achieved using Mobilenet, with a classification accuracy of 97.38% and a loss of 0.2680 across these six data types.
CHEAT DETECTION IN ONLINE EXAMINATIONS USING ARTIFICIAL INTELLIGENCE

Authors:
raw_author_name: Santosh Gopane
raw_author_name: Radhika Kotecha

Abstract: With increasing use of ICT and technical advancements in the education sector, distant and online education as well as examinations are being carried out frequently. However, online examination, as a method of assessment offers the risk of an unmonitored setting where students have full access to external resources. Online-proctored exams are the most efficient way for educational institutions to ensure academic honesty and ethics to counteract this. Typically, proctoring requires human assistance in the form of online proctors who remotely monitor students' performance. Yet, due to the rising demand for personnel and the intrusive nature of human proctoring, it is imperative to explore other areas. To tackle this pressing issue, this research work aims to devise a novel architecture that, through the development of a robust and automated Artificial Intelligence system, enables students to take exams remotely and reduces proctor involvement. The method overcomes the shortcomings of the previous automated proctoring system by combining important components of online exam cheating detection with cost-effective and efficient hardware. By proposing a Hybrid of FaceNet Model, Lucas Kanade Algorithm, and Active Appearance Model for Face Detection and Activity Monitoring of the student, the proposed system extracts semantic indicators to evaluate whether an applicant is cheating in an online examination. The proposed Cheat Detection system's experimental results measured via an F-score of 0.94 demonstrate its efficacy, and promising performance compared to the standard baseline techniques.
INDOOR VISUAL UNDERSTANDING THROUGH IMAGE CAPTIONING

Authors:
raw_author_name: Dhomas Hatta Fudholi
raw_author_name: Royan Abida N. Nayoan

Abstract: Transformers have been widely used in image captioning tasks on English language datasets such as MSCOCO and Flickr. However, research related to image captioning in Indonesian is still rare and relies on machine translation to obtain the Indonesian dataset. In this study, the Transformer model is used to generate caption using the modified MSCOCO datasets to gain visual understanding in an indoor environment. We modified the MSCOCO dataset by creating new Indonesian text description based on the MSCOCO images. A few simple rules are made to create the Indonesian dataset by including the object’s location, colour, and its characteristics. Experiments were carried out using several CNN pre-trained models to extract the image features before feeding them to the Transformer model. We also performed hyper-parameter settings on the models by assigning different values for batch size, dropouts, and attention heads to get the best model. BLEU-n, METEOR, CIDEr, and ROUGE-L are used to evaluate the model. From this study, by utilizing the EfficientNetB0 with a batch size of 128, dropouts of 0.2, and attention heads of 4, the model can get the best score in four different evaluation matrices. The EfficientNetB0 model reached the highest score on BLEU-4 with a score of 0.344, ROUGE-L of 0.535, METEOR of 0.264, and CIDEr of 0.492.
The Optimal Model for Copy-Move Forgery Detection in Medical Images

Authors:
raw_author_name: Ehsan Amiri
raw_affiliation_string: Department of Computer Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran
raw_author_name: Ahmad Mosallanejad
raw_affiliation_string: Department of Computer Engineering, Sepidan Branch, Islamic Azad University, Ardakan, Sepidan, Iran
raw_author_name: Amir Sheikhahmadi
raw_affiliation_string: Department of Computer Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran

Abstract: Abstract Background: Digital devices can easily forge medical images. Copy-move forgery detection (CMFD) in medical image has led to abuses in areas where access to advanced medical devices is unavailable. Forgery of the copy-move image directly affects the doctor’s decision. The method discussed here is an optimal method for detecting medical image forgery. Methods: The proposed method is based on an evolutionary algorithm that can detect fake blocks well. In the first stage, the image is taken to the signal level with the help of a discrete cosine transform (DCT). It is then ready for segmentation by applying discrete wavelet transform (DWT). The low-low band of DWT, which has the most image properties, is divided into blocks. Each block is searched using the equilibrium optimization algorithm. The blocks are most likely to be selected, and the final image is generated. Results: The proposed method was evaluated based on three criteria of precision, recall, and F1 and obtained 90.07%, 92.34%, and 91.56%, respectively. It is superior to the methods studied on medical images. Conclusions: It concluded that our method for CMFD in the medical images was more accurate.
AMERICAN PERCEPTIONS ON BARRIERS OF LEARNING INDONESIAN AS A FOREIGN LANGUAGE

Authors:
raw_author_name: R. Dian Dia-an Muniroh
raw_affiliation_string: Universitas Pendidikan Indonesia

Abstract: Foreign language acquisition is one of the important issues in the current era of globalization. Indonesian is not an exception because, within the last twenty years, the significance of Indonesian language has increased. This study aims to reveal the problem of the learning of Indonesian language as a foreign language. It focused on adolescent learners from the United States of America in a reputable language institution. More specifically, there are two questions in this study. First, what are the barriers of learning Indonesian that were found by the American learners? Second, what are the types of teaching materials that these learners like? This study is a case study with descriptive methods. It was conducted in a training institution focusing to train Christian preachers. Four learners from the United States of America were the informants in this study. The data were generated from the four American learners in obtained through (1) observation; (2) depth interviews with informants; and (3) relevant documents. This study concluded that (1) in general, the barriers faced by the American learners can be classified into four types: social, mental, phonological, and grammatical; and (2) the learners prefer various teaching materials but their common preference is the authentic learning materials that consider aspects of audiovisual media use, Indonesian cultural diversity, and language formality. Since the study only relied on four informants, the results cannot be generalized to all learners of Indonesian Language. However, they can provide a figure in the learning of Indonesian language involving non-native speakers, especially the Americans.
Implementation of INLISLITE 3.1 in Processing Printed Book Materials at SMAN 1 Kalanganyar Library

Authors:
raw_author_name: None Katrin Setio Devi
raw_affiliation_string: Universitas Sebelas Maret

Abstract: This research aims to provide an overview of the implementation of the INLISLite in processing printed book materials at the library of SMAN 1 Kalanganyar. The INLISLite 3.1 is a library automation system application designed and officially developed by the National Library of the Republic of Indonesia, used to assist in the process of managing library materials. The method used in this research is a descriptive qualitative research method. Utilizing data collection techniques through observations and interviews with two informants consisting of the head librarian and library staff of SMAN 1 Kalanganyar. The implementation of the INLISLite serves as a solution for the SMAN 1 Kalanganyar library in transitioning from conventional to automated processing of printed book materials. Equipped with comprehensive program features, it aids the staff in their library activities. However, the use of the INLISLite 3.1 at SMAN 1 Kalanganyar has not been fully optimized and is still hindered by human resources, resulting in suboptimal data input due to a lack of cataloging expertise.
EXPERT SYSTEM FOR DIAGNOSING BEHAVIORAL DISORDERS USING THE DEMPSTER-SHAFER THEORY ALGORITHM

Authors:
raw_author_name: Hendra Mayatopani
raw_affiliation_string: Universitas Pradita

Abstract: Behavioral disorders, especially in children, can have a significant impact on their development in various domains, such as social, emotional, and academic. The diagnostic process for this disorder can be complicated due to overlapping symptoms and the possibility of complex causal factors. Early identification and appropriate treatment of behavioral disorders is essential to prevent more serious impacts on an individual's psychological well-being. Lack of knowledge and difficulty in accessing psychiatrists to find out about behavioral disorders in children are factors that result in this problem requiring a solution. The aim of this research is to create an expert system that utilizes the Dempster-Shafer Theory algorithm to detect behavioral disorders, thus simplifying the diagnosis process and ensuring accurate results. The Dempster-Shafer theory, as an inference engine, can overcome uncertainty by combining several sources of evidence or data that may overlap or be incomplete, resulting in a stronger conclusion. The main feature of this expert system is its ability to carry out diagnoses based on symptoms and display diagnosis results, disease descriptions, and treatment options. Test accuracy produces a value of 90%, which shows that the Dempster-Shafer Theory approach can diagnose behavioral disorders effectively.
ENGLISH TEACHER’S STRATEGIES IN TEACHING STUDENTS WITH HEARING IMPAIRMENT AT SMP LUAR BIASA YPAC

Authors:
raw_author_name: Anwar Ismail
raw_affiliation_string: Universitas Khairun

Abstract: This research aimed to identify English teachers’ strategies in teaching students with hearing impairment and the challenges which the teacher faced in classroom practices. The research method used is qualitative with a case study approach, The subject of this research was an English teacher at SMPLB YPAC. The data were collected by using observation checklist and interview. The result of research showed that there are two strategies used by teacher at SMPLB YPAC grade 8th, namely the manual method which has two basic components, namely sign language and finger spelling and the oral method, namely lip reading or speech reading. Implementing the strategy, there are challenges faced by teachers. The challenges are that first, students sometimes have difficulty understanding words and teachers sometimes need to repeat words or write them down. Second, the limited vocabulary of students and how to overcome them with the teacher needing to explain the definition and provide examples with the media. Third, the teacher did not push students to do exactly what the teacher says. Last, the need for repetition in delivering material with a long duration compared to regular students and the ability of the teacher to remain patient with students is very necessary in answering the last challenge.
Utilization of Augmented Reality Technology in Independent Speech Therapy Applications

Authors:
raw_author_name: Linda Perdana Wanti
raw_author_name: Oman Somantri

Abstract: One of the uses of information technology is augmented reality technology in the health sector. Augmented reality is used in the development of applications that are used for speech therapy for children with autism or children with speech delays. The method used for the development of speech therapy applications is the extreme programming method. This method can adapt to the development of an application in a short time and quite a lot of changes. The stages in the extreme programming method include identifying system requirements, planning activities during system/application development, system development process, iteration for system improvement until the final iteration, and no more user feedback, system/application production, and system maintenance with data backup and system recovery. After testing the system, it was concluded that three iterations occurred during the development of the speech therapy application. The last test showed that the user accepted the speech therapy application with a percentage of 77,14%. The output of this research is an augmented reality-based speech therapy application that is useful for independent speech therapy for children with speech delays.
Syllabus Analysis of English for Hotel Receptionist Program with SKKNI in Kartu Prakerja by Mobile English

Authors:
raw_author_name: Neni Nurkhamidah
raw_affiliation_string: Universitas Media Nusantara Citra

Abstract: Hotel receptionists who work as frontline in the hospitality industry are supposed to be able to perform their duties no matter where the guests come from. In handling foreigners, English can be used as a medium to communicate and serve guests. To achieve a certain level of communication in English; the employee could take training programs and courses to upskill their language level in ESP. This study intends to analyze a syllabus of the ESP. By conducting this study, the researcher tries to find out the competencies being taught in the program and the suitability of the SKKNI as the standard reference. The method used in this study was qualitative research with a content analysis approach. The subject of this study was a syllabus developed by Mobile English as a learning institution that partners with the Kartu Prakerja Program. The instrument used to examine the study was a form of table. The study's results examined only five competencies taught in the program out of 14 competencies that should be acquired based on the SKKNI. The finding implies that future improvements in the syllabus and the program are needed to help the student be competent in their role as hotel receptionists
Uji Validasi Rancangan Aplikasi Kelengkapan Resume Medis di Klinik Almeta Medika

Authors:
raw_author_name: Galih Persadha
raw_affiliation_string: Politeknik Unggulan Kalimantan
raw_author_name: Husin Husin
raw_affiliation_string: Politeknik Unggulan Kalimantan

Abstract: The quality of medical records becomes more valuable if the information written is complete, especially on the medical resume. Complete medical resume writing at Almeta Medika Clinic Banjarmasin has not been carried out, this causes patient information to be incomplete. So a complete medical resume application was designed. This research aims to validate the complete medical resume application at the Almeta Medika Clinic, Banjarmasin. This research method is descriptive qualitative, collecting data using questionnaires and checklists. The subjects in this research were medical records officers, Almeta Medika Banjarmasin clinic managers, IT expert respondents and materials experts. The results of this research were that by testing it was found that the design of the ERD, DFD and application for complete medical resumes at the Almeta Medika Banjarmasin Clinic contained a login, dashboard, 4 components of quantitative analysis and the results of quantitative analysis reports/summaries. ERD and DFD were created using Microsoft Visio and the medical resume application was created using Microsoft Access after identifying user needs and identifying data requirements. The complete medical resume application at Almeta Medika Clinic Banjarmasin has been designed according to the clinic's needs. Validation with medical records officers, Almeta Medika Banjarmasin clinic manager, IT expert respondents and material experts found the appropriate category. Validation testing of the medical resume completeness application at Almeta Medika Clinic Banjarmasin is designed according to the clinic's needs and is feasible to implement.