Reviewerly/exHarmony huggingface dataset:
INDEPENDENT WORK OF HIGHER EDUCATION SEEKERS AS THE HIGHEST FORM OF PROFESSIONAL FORMATION AND PERSONAL DEVELOPMENT

The article analyzes the essence of the concepts "independent work", "self-education", "independence" and their relationship and interdependence. The types of independent work in the process of educational and extracurricular activities are characterized. Approaches to their classification according to various criteria are presented. The organization of independent work in institutions of higher education is characterized, including its purpose, content, forms, methods, and conditions of effectiveness, which are determined. The higher school is gradually but steadily moving from the transfer of information to the management of educational and cognitive activities, the formation of the abilities and skills of independent work in the students of higher education. According to the Regulation on the Organization of the Educational Process in Higher Education Institutions, the independent work of students of higher education is the main means of mastering educational material in the time that is free from compulsory educational classes. The study time allocated for the independent work of higher education seekers is regulated by the curriculum and must be no less than 1/3 and no more than 2/3 of the total study time of students devoted to the study of specific disciplines.&#x0D; The conditions-factors of the effectiveness of the organization of independent work of higher education seekers have been determined. They include: organizational (time management, educational literature and corresponding facilities); methodical (planning, teaching methods of acquiring information and managing the independent work); psychological and pedagogical (taking into account the individual psychological qualities and properties of the higher education seekers); information-technology (the degree of accessibility of new information systems, the level of computer literacy); organization of control and assessment (observance of systematicity and phasing in the organization and conduct of independent work). The results of a study among higher education applicants regarding the effectiveness of organizing independent work in universities are highlighted.
Contract Law and Persuasive Design: Dark Patterns, AI and the Concept of Free Choice

Contract law presumes free choice, where only undue influence as intimidation, and information asymmetry are regulated. Influences by marketing (presentation, sales skills) are allowed, as long as they do not turn into abusive commercial practices. With the advent of digital contracting and AI, we find that the User experience (UX) is deliberately designed to influence choices (dark patterns in general, personalization in particular). There is hardly any theoretical discussion on why those influences are allowed and where the boundaries lie.The question is therefore to what extent influence of choice is allowed, and more particular whether UX and AI influence of choice is allowed. This requires an investigation of the underlying assumptions and justifications of existing rules of contract law. AI is important as it straddles the boundary between the delegation of tasks to an auxiliary (presumed human), and the use of mere technical means by the principal, therefore requires also a way to handle this duality of AI, which the notion of diligence in the UCP Directive may provide. It is submitted that the structural character of influences may require stronger regulation, while traditional sales techniques do not.
Improving Log-Cumulant-Based Estimation of Heterogeneity Information in SAR Imagery

Synthetic Aperture Radar (SAR) image understanding is crucial in remote sensing applications, but it is hindered by its intrinsic noise contamination, called speckle. Sophisticated statistical models, such as the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sup> family of distributions, have been employed to SAR data and many of the current advancements in processing this imagery have been accomplished through extracting information from these models. In this paper, we propose improvements to parameter estimation in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sup> distributions using the Method of Log-Cumulants. First, using Bayesian modeling, we construct that regularly produce reliable heterogeneity estimates under both <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sup> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</sub> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sup> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</sub> models. Second, we make use of an approximation of the Trigamma function to compute the estimated heterogeneity in constant time, making it considerably faster than the existing method for this task. Finally, we show how we can use this method to achieve fast and reliable SAR image understanding based on heterogeneity information.
Extracting Key-Value Pairs in Business Documents

Key-value extraction is a challenging task in document AI, particularly in business documents such as invoices. Accurately extracting key-value pairs from such documents is crucial for downstream tasks like accounting, analytics, and decision-making. In this paper, we propose a method for grouping and linking key-value pairs in business documents using a combination of rule-based methods and pretrained transformers. Our method comprises three steps: grouping words into word groups using rule-based methods that rely on layout information obtained via OCR, classifying the groups of words into key, value, or other using a pretrained BERT multilingual model, and linking the predicted key-value pairs based on their relative positions in the document, leveraging the layout information. Furthermore, we present a comparative study of our approach against state-of-the-art methods for key-value extraction in business documents. Our approach is designed to be adaptable and requires minimal semantic and language-specific knowledge, making it suitable for a wide range of business documents. This flexibility allows our method to be easily applied to real-world scenarios, where documents may vary in layout and language. Additionally, our method is computationally efficient, allowing for fast processing of large volumes of documents. Our results demonstrate the effectiveness of combining rule-based methods with pretrained transformers for key-value extraction in business documents, providing a strong foundation for developing more accurate and robust methods in the future.
Document Layout Annotation: Database and Benchmark in the Domain of Public Affairs

Every day, thousands of digital documents are generated with useful information for companies, public organizations, and citizens. Given the impossibility of processing them manually, the automatic processing of these documents is becoming increasingly necessary in certain sectors. However, this task remains challenging, since in most cases a text-only based parsing is not enough to fully understand the information presented through different components of varying significance. In this regard, Document Layout Analysis (DLA) has been an interesting research field for many years, which aims to detect and classify the basic components of a document. In this work, we used a procedure to semi-automatically annotate digital documents with different layout labels, including 4 basic layout blocks and 4 text categories. We apply this procedure to collect a novel database for DLA in the public affairs domain, using a set of 24 data sources from the Spanish Administration. The database comprises 37.9K documents with more than 441.3K document pages, and more than 8M labels associated to 8 layout block units. The results of our experiments validate the proposed text labeling procedure with accuracy up to $$99\%$$ .
Subgraph-Induced Extraction Technique for Information (SETI) from Administrative Documents

Information Extraction plays a key role in the automation of auditing processes in administrative documents. However, variety in layout and language is always a challenging task. On the other hand, large volumes of public training datasets related to administrative documents such as invoices are rare to find. In this work, we use Graph Attention Network model for information extraction. This type of model makes it easier to understand the mechanism as compared to classical neural networks due to the visualization of link between entities in the graph. Moreover, it maximizes the layout and structure retrieval which is a crucial advantage in administrative documents. From the same graph, our model learns at different graph levels to encapsulate dynamic and more enriched knowledge in each batch, thus maximizing the generalization on smaller dataset. We present how the model learns in each graph level and compare the results with baselines on private as well as public datasets. Our model succeeds in improving recall and precision scores for some classes in our private dataset and produces comparable results for public datasets designed for Form Understanding and Information Extraction.
KAP: Pre-training Transformers for Corporate Documents Understanding

Pre-trained models have proven their efficiency. Despite their good performance, these models require a lot of data and resources to allow state-of-the-art results. In this paper, we propose KAP a pre-trained model adapted for the domain specificity for corporate documents. KAP takes into account the domain specificity of corporate documents and proposes a model that integrates the local context of each word (i.e the words at the top, bottom, and right of the word). That is useful to help a better understand the 2D context of a document. We also propose a co-attention for a better understanding of the correlation between image and text. In addition to this, we integrate a special tokenizer to focus on the essential words in a corporate document in order to reduce the vocabulary size. KAP achieves state-of-the-art results on several datasets despite being pre-trained on only 72,000 documents.
Transformasi Konsep Kegiatan Perpustakaan Berbasis Inklusi Sosila di Masa Pandemi (Studi Kasus Perpustakaan Universitas Teknokrat Indonesia)

The University Library is an integrated library of educational, research and community service activities and functions as a learning resource center to support the achievement of educational goals located in higher education. The library provides various kinds of information that can help people who do not have a job base by providing information about the job market and providing training or practice for someone to be able to become an entrepreneur. The author uses qualitative research with library research methods. In collecting data, the author makes observations, documentation and direct interviews. From the recap in January-April, it shows that there has been an increase in student interest in visiting the library, this is shown by the number that continues to increase every month. From this it can be concluded that library activities have a very effective role in attracting student visits. Therefore, it is proper for us librarians to present activities that increase knowledge and knowledge in the university environment. The increase in interest in visiting is always accompanied by interest in borrowing/reading library users.
Utilization Of Pop-Up Book as a Learning Media For Student Of Major Of Library Science

A library is a room, part of a building where books are stored for reading. Some people's understanding of libraries is also developing. There is no doubt that the library is a very important/vital tool for all levels of society, both for developed countries, developing countries and even poor countries. Therefore, it takes a graduate majoring in library science to process libraries. The Department of Library Science is a department that learns how to collect, analyze , process, manage, and communicate information from various media, such as documents, books, or digital. So the department of library science is required to prepare media to make it easier for prospective librarians to easily understand the processing of library materials in the library. One of the media that can help facilitate According to Dzuanda (2011: 11) Pop-Up Book is a book that has moving parts or has three-dimensional elements and provides a more interesting visualization of stories, starting from the image display. which can be moved ak when the page is opened. The purpose was made to help facilitate students in the learning process through the media pop-up book.
Answer Set Programming (DLV – Clingo):Connect 4 Solver

Answer set programming is an approach that has recently gained a lot of popularity in solving complex problems due to its efficient knowledge representation and reasoning. Knowledge is represented as answer set programs, and reasoning is performed by answer set solvers. Answer set programming enables default reasoning, which is required in commonsense reasoning. In this paper, we discuss the potential role of answer set programming (ASP) in the context of approaches to the development of agents especially in the realm of Computational Logic. So, we focus on the usage of DLV for solving problems in a declarative manner particularly, in the solution of the game “connect four”. Additionally, we present the solution to this same problem from Clingo's perspective. We address this challenge with the ASP system clingo and its grounding and solving components by equipping them with well-defined generic interfaces facilitating the manifold integration efforts.
Resource-Efficient Fine-Tuning Strategies for Automatic MOS Prediction in Text-to-Speech for Low-Resource Languages

We train a MOS prediction model based on wav2vec 2.0 using the open-access data sets BVCC and SOMOS.Our test with neural TTS data in the low-resource language (LRL) West Frisian shows that pre-training on BVCC before fine-tuning on SOMOS leads to the best accuracy for both fine-tuned and zeroshot prediction.Further fine-tuning experiments show that using more than 30 percent of the total data does not lead to significant improvements.In addition, fine-tuning with data from a single listener shows promising system-level accuracy, supporting the viability of one-participant pilot tests.These findings can all assist the resource-conscious development of TTS for LRLs by progressing towards better zero-shot MOS prediction and informing the design of listening tests, especially in earlystage evaluation.
Recycle-and-Distill: Universal Compression Strategy for Transformer-based Speech SSL Models with Attention Map Reusing and Masking Distillation

Transformer-based speech self-supervised learning (SSL) models, such as HuBERT, show surprising performance in various speech processing tasks.However, huge number of parameters in speech SSL models necessitate the compression to a more compact model for wider usage in academia or small companies.In this study, we suggest to reuse attention maps across the Transformer layers, so as to remove key and query parameters while retaining the number of layers.Furthermore, we propose a novel masking distillation strategy to improve the student model's speech representation quality.We extend the distillation loss to utilize both masked and unmasked speech frames to fully leverage the teacher model's high-quality representation.Our universal compression strategy yields the student model that achieves phoneme error rate (PER) of 7.72% and word error rate (WER) of 9.96% on the SUPERB benchmark.
Analisis Kesalahan Penggunaan Bahasa Indonesia Pada Penulisan Papan Nama, Spanduk, Pamflet di Kecamatan Medan Denai

This study aims to describe what forms are found in the analysis of Indonesian language usage errors in the writing of signboards, banners, and pamphlets in Medan Denai District. The research method used is descriptive research method whose data is already listed on the writing of signboards, banners, and pamphlets. The instrument used by the researcher in collecting data is from the form of documentation which is done by photographing or taking data in the form of pictures/photos on the subject and object under study, and assisted by a research tool in the form of a cellphone (HP) or smartphone. The data collection techniques used in this research are (1) observation techniques, (2) documentation techniques, and (3) recording techniques. The data analysis technique in this research is descriptive with the steps of (1) searching for data, (2) documenting data, (3) selecting and choosing data, (4) analyzing data and giving marks, (5) identifying data, (6) completing the data that has been obtained, (7) understanding the overall data that has been selected, and (8) concluding the research results. Based on the results of the study, it can be concluded that language errors in the use of spelling, punctuation, word choice, and standardized language vocabulary and non-standardized language vocabulary are still commonly found on signboards, banners, and pamphlets in Medan City, especially in Medan Denai District. The image data obtained by the researcher in accordance with his research amounted to 30 image data that had been taken in the North Sumatra region, specifically in Medan Denai District. The data were categorized by looking at the objects that have been determined by the researcher in his research which are Indonesian language usage errors in writing signboards, banners, and pamphlets. Therefore, the results of the language errors that have been analyzed are as follows: errors in the use of spelling on signboards, banners, and pamphlets amounted to 5 data; errors in the use of punctuation on signboards, banners, and pamphlets amounted to 5 data; errors in the use of word choice (diction) on signboards, banners, and pamphlets amounted to 1 data; and errors in the use of non-standard language vocabulary on signboards, banners, and pamphlets amounted to 9 data; and errors in the use of foreign language terms or elements on signboards, banners, and pamphlets amounted to 5 data
The Effect of Using Intensive Reading Strategy on Students’ Vocabulary Achievement at The First Year Student

This research aimed to determine whether intensive reading strategy is effective to increase students’ English vocabulary. This research used quantitative method as its design. The population in this research consists of 40 students from SMAS EKLESIA. The sample of this research was 20 students in experimental group and 20 students in control group. To collect the data from both classes, this research used pre-test and post-test. The data from both classes analyzed by using SPSS program to calculate and determine the validity of the data. Based on the data analysis, the result of T-test revealed that the post-test score of the experimental group was higher than control group. Additionally, the result of hypothesis analysis showed that t-test is higher than t-table (2.831 &gt; 2.021). It indicated that H0 (Null Hypothesis) was rejected and Ha (Alternative Hypothesis) was accepted. Based on the result of this research, it showed that there was significant improvement on students’ vocabulary achievement in using intensive reading as a strategy in teaching.
An Analysis of Daily Mixed Language Conversation in Assisting The Sixth Semester Students' of English Education Department Speaking Skills at Universitas Muslim Nusantara Al-Washliyah Medan

In everyday life, people sometimes communicate with other people with mixed language and also as nowadays trend in social. There are words in English that commonly used in our daily conversation as Indonesian people to make the sentences clear and easy to be understood. This study aims to analyze the improvement of speaking skills through the habit of mixing languages in daily communication and conversation activities. The purpose of this research is to explain about the effect of mixed language in improving students' speaking skills and increasing their self-confidence. The researcher uses observation and interview approach to do the data collection of the sixth semester student in English Education Department Universitas Muslim Nusantara Al Washliyah Medan. The respondents were five students of the sixth semester students in English English Education Department Universitas Muslim Nusantara Al Washliyah Medan.
An Efficient Approach for Text-to-Speech Conversion Using Machine Learning and Image Processing Technique

This study explores the conversion of English to Hindi, first to text, and subsequently to speech.The first part of the implementation is the text recognition from images, in which two approaches are used for text character recognition: a maximally stable extensible region (MSER) and grayscale conversion the second part of the paper deals with the geometric filtering in combination with stroke width transform (SWT).Subsequently, letter/alphabets are grouped to detect text sequences, which are then fragmented into words.Finally, a 96 percent accurate spell check is performed using naive Bayes and decision tree algorithms, followed by the use of optical character recognition (OCR) to digitize.The word Give our text-to-speech synthesizer (TTS) the recognized text to convert it to Hindi language using the text-to-speech model.Based on aspects such speech speed, sound quality, pronunciation, and clarity.
Emerging Trends in Database and its Applications in MNC’s

When information is set for easy retrieval, access, updation, and management, then it is known as Database.Its major purpose is storing aggregations of records and data files that contain information regarding transactions, customer details, product details and financials.The paper deals with a briefing on DBMS which is a collection of interrelated data and set of programs to retrieve and access the data which focuses on :-a) exchange of data, b) retrieve the data, c) storage of data, and d) manipulation on data.The paper also gives a glance on elements of DBMS also describes the architecture which is consist of: a) internal level, b) conceptual level, and c) external level.The paper also mentions some of the uses of databases and will try to give an idea about the applications of Database in different MNC's and projects in Data ware.