Reviewerly/exHarmony huggingface dataset:
SISTEM INFORMASI AKUNTANSI PENGGAJIAN PEGAWAI BERBASIS WEB DENGAN METODE ACCRUAL BASIS

The purpose of this research is to produce a computerized employee payroll information system where the employee payroll information system of PT. Gemah Makmur Sejahtera still uses a manual system. The preparation of reports that still use Microsoft Excel worksheets also takes a long time, besides that the manual preparation is also vulnerable to user negligence in recording it. In this study, to minimize negligence in recording, the author will apply the accrual basis recording method, where the recording of salary expenses is carried out when a transaction occurs. This research was arranged by research and development method. The Employee Payroll Information System at PT Gemah Makmur Sejahtera is an employee payroll information system designed using a research and development methodology with UML (Unified Modeling Language) tools, direct observations and interviews with related parties. which can make it easier for the salary calculation stage, automatic report preparation, and automatic salary slips, resulting in more effective and efficient information.
A Systematic Review on Knowledge Graphs Classiﬁcation and Their Various Usages

A Knowledge Graph is a directive graph where the nodes state the entities and the edges describe the relationships between the entities of data. It is also referred to as a Semantic Network. The massive amount of data generated every day can be transformed into knowledge via knowledge graphs for the effective use of these data. Knowing the classification of Knowledge Graphs is required to adapt to different requirements of Knowledge Graphs. Knowledge Graphs are primarily classified concerning their building techniques and their usages. In building techniques, it is considered how the Knowledge Graph is built. For example, the graph can be constructed as a triplet, quadruplet, etc., or created from structured data, e.g., database, or unstructured data, e.g., text, image, etc. On the other hand, Knowledge Graphs can be used for various purposes. For example, Knowledge Graphs can be used for Information Retrieval, Semantic Query, etc., or different types of data visualization. Nowadays, Knowledge Graph is one of the trending topics in the modern technology-dependent world. However, clear and specific discussions on the classifications of Knowledge Graphs and their various usages are less available. In this paper, we will describe the classification of knowledge graphs and their various usages in detail so that the readers can get a clear concept of this topic.
Quantum simulation of colour in perturbative quantum chromodynamics

Quantum computers are expected to give major speed-ups for the simulation of quantum systems. In this work, we present quantum gates that simulate the colour part of the interactions of quarks and gluons in perturbative quantum chromodynamics (QCD). As a first application, we implement these circuits on a simulated noiseless quantum computer and use them to calculate colour factors for various examples of Feynman diagrams. This work constitutes a first key step towards a quantum simulation of generic scattering processes in perturbative QCD.
Conditional Generators for Limit Order Book Environments: Explainability, Challenges, and Robustness

Limit order books are a fundamental and widespread market mechanism. This paper investigates the use of conditional generative models for order book simulation. For developing a trading agent, this approach has drawn recent attention as an alternative to traditional backtesting, due to its ability to react to the presence of the trading agent. We explore the dependence of a state-of-the-art conditional generative adversarial network (CGAN) upon its input features, highlighting both strengths and weaknesses. To do this, we use “adversarial attacks” on the model’s features and its mechanism. We then show how these insights can be used to improve the CGAN, both in terms of its realism and robustness. We finish by laying out a roadmap for future work.
Progressive Logic

In this chapter, Kit Fine and Errol Martin provide a formal account of non-circular reasoning, i.e. of reasoning in which the conclusion of an argument is not somehow presupposed in its premises. Martin (along with R. Meyer) had previously shown that the implicational system $$\textbf{P}\!\mathbf {-W}$$ does not contain any theorems of the form $$A \rightarrow A$$ . Fine and Martin then extend this result to systems that also contain conjunction.
Digital Natives’ Academician-Student Relationships

Digital natives born with advanced digital media technologies are acknowledged as the first generation of the 21st century. This quantitative study seeks to explore digital natives’ stimuli and perceptions towards technology-oriented academician-student interactions at a major university in North Cyprus amid the COVID-19 pandemic. Participants (N=259 Gen Z learners) in a developing country seem to value the virtualization of academician-student interactions in higher education because digital technologies eliminate the existing and possible communication obstacles between educators and learners especially during the crisis situations. It was underlined that digital natives mostly prefer mobile communication in their lives with the belief that technology facilitates, enhances, enriches and triggers interactions between educators and learners. Hence, digital learners mostly prefer blended education and digital communication because participants claim that digitalization escalates the effectiveness of teaching and communication. Digital-assisted education ascends learners’ self-confidence and desire towards initiating interactions and comprehending the course contents.
DESIGN OF RETRIBUTION ACCOUNTING INFORMATION SYSTEMS IN MARDIKA MARKET

The goal of this study is to create a web-based payment accounting information system that meets the needs of the Ambon Mardika Market Company in order to overcome the shortcomings of the manual registration system. This is a developmental study utilising a qualitative methodology. The research subject is the market payment information system, and the research aim is the Mardika Market Company. Data is gathered through interviews, documentation, and observation. The system development life cycle is used in this study, with the steps of system analysis, system requirements analysis, and system feasibility analysis. Database modelling with database tables, process modelling with flowcharts, and user interface modelling with form design, input design, and output design are all part of system design. Design of a sales accounting information system using MySQL and PHP software. The new architecture is believed to enable more automatic and precise recording and computation, hence supporting the Mardika Regional Market Company's performance continuity.
Modification Of Kaolin Capkala With Benzalkonium Chloride (Bkc) Surfactant And Antibacterial Activity Test Against Escherichia Coli

A study was conducted to determine the antibacterial activity of modified benzalkonium chloride (BKC) kaolin Capkala against Escherichia coli (E. coli) bacteria. Kaolin modification begins by melting kaolin with sodium hydroxide (NaOH) and reacting using a reflux device. Furthermore, the sample was reacted with BKC at a concentration variation of 0, 2.5×10-3; 5×10-3, and 2.5×10-2 M for 6 hours with a stirring speed of 150 rpm. The modified kaolin was characterized using Fourier Transformed Infrared (FTIR), and adsorption tests were performed on Cl-. The FTIR spectrum of the modified kaolin showed an absorption peak at 2926.19 cm-1 C-H symmetrical from CH2, which indicated the attachment of surfactant to the kaolin. BKC modified kaolin antibacterial activity test using the halo test method. The adsorption test on Cl- and the antibacterial activity test on kaolin and modified kaolin increased with increasing BKC concentration, namely 3545; 3828.6, 3970.4; 4183.1 mg/L and the inhibitory diameter were 2.1±0.14, 3.3±0.14, 4.5±0.14, and 6±0.14 mm, respectively. The results showed that BKC can increase the antibacterial activity of kaolin
The Next Chapter: A Study of Large Language Models in Storytelling

To enhance the quality of generated stories, recent story generation models have been investigating the utilization of higher-level attributes like plots or commonsense knowledge. The application of prompt-based learning with large language models (LLMs), exemplified by GPT-3, has exhibited remarkable performance in diverse natural language processing (NLP) tasks. This paper conducts a comprehensive investigation, utilizing both automatic and human evaluation, to compare the story generation capacity of LLMs with recent models across three datasets with variations in style, register, and length of stories. The results demonstrate that LLMs generate stories of significantly higher quality compared to other story generation models. Moreover, they exhibit a level of performance that competes with human authors, albeit with the preliminary observation that they tend to replicate real stories in situations involving world knowledge, resembling a form of plagiarism.
Tackling Hallucinations in Neural Chart Summarization

Hallucinations in text generation occur when the system produces text that is not grounded in the input. In this work, we tackle the problem of hallucinations in neural chart summarization. Our analysis shows that the target side of chart summarization training datasets often contains additional information, leading to hallucinations. We propose a natural language inference (NLI) based method to preprocess the training data and show through human evaluation that our method significantly reduces hallucinations. We also found that shortening long-distance dependencies in the input sequence and adding chart-related information like title and legends improves the overall performance.
Fluorescence in Situ Hybridization Cell Image Segmentation Method

Fluorescence in situ hybridization (FISH) is a molecular cytogenetic technique that provides reliable imaging biomarkers for the diagnosis of cancer and genetic diseases at the cellular level. An important prerequisite for identifying cancer cells in FISH images is the accurate segmentation of cells to quantify the DNA/RNA signal within each cell. However, FISH images often have problems such as low contrast, unclear cell boundaries, and potential cell defects, which hinder the complete identification and effective segmentation of cells. Therefore, this paper proposes a cell image segmentation method for fluorescence in situ hybridization. First, an improved adaptive histogram equalization is used to enhance the image. Then, the watershed segmentation method is used to calculate the optimal segmentation feature value, which is used as the seed point of the watershed method. The proposed method was applied to segment 273 cells from 5 images of leukemia cells, with a detection rate of 99% and an effectiveness of 94.5%. The results showed that the fluorescence in situ hybridization cell image segmentation method can accurately segment cells, and has a high detection rate and effectiveness.
ANALISIS PELAKSANAAN LITERASI BACA DAN TULIS SISWA KELAS IV SD NEGERI 1 NGROPOH TEMANGGUNG

&#x0D; Literacy is seen as the ability to read and write. Literacy understanding then begins to develop into language skills, which include the ability to read, write, speak and listen. Over time, the definition of literacy has expanded to encompass a variety of scientific disciplines. The focus of this research is how is the implementation of reading and writing literacy for class IV students at SD Negeri 1 Ngropoh Temanggung? The author uses a descriptive qualitative approach method. This research aims to describe the implementation of reading and writing literacy in class IV students at SD Negeri 1 Ngropoh Temanggung. Qualitative research data analysis techniques through data collection, data reduction, data presentation, and drawing conclusions. The research results obtained in the field show that the reading and writing literacy activities carried out in class IV students at SD Negeri 1 Ngropoh Temanggung have the habit of reading and writing both inside and outside the classroom. The teacher asks students to read 15 minutes before class starts, provides a reading corner in the classroom so students can read without going to the library, gives rewards to students who have read and written a lot from a story or other, the teacher also encourages students to be interested in reading and writing by displaying audio visuals.
Workshop Pembuatan Media Pembelajaran Inovatif Bagi Guru SMP di Kabupaten Takalar

Learning media are facilities or tools used in the learning process to assist teachers in conveying information and learning materials to students. Learning media can be electronic media, such as video, audio and presentations, as well as non-electronic media, such as books, pictures and real objects. The use of learning media in the classroom can help students understand and remember learning information more easily and effectively, as well as increase student interaction and learning motivation. Apart from that, the use of learning media can also increase the efficiency of the learning process in the classroom and help teachers manage learning time more effectively. Based on the results of initial observations carried out in Takalar Regency, the research team found that the available learning tools did not fully support the achievement of learning objectives. There are still shortcomings in developing and using concepts and implementing innovative and interactive media. In fact, the use of learning media in class can help students understand and remember learning information more easily and effectively, as well as increase student interaction and learning motivation. It is considered important to develop teacher competency in Takalar district so that training is held which is expected to improve teachers' abilities in developing more innovative and effective teaching techniques so that they can improve the quality of learning in the classroom and achieve the desired learning goals.
Analyzing Differences in Subjective Annotations by Participants and Third-party Annotators in Multimodal Dialogue Corpus

Estimating the subjective impressions of human users during a dialogue is necessary when constructing a dialogue system that can respond adaptively to their emotional states. However, such subjective impressions (e.g., how much the user enjoys the dialogue) are inherently ambiguous, and the annotation results provided by multiple annotators do not always agree because they depend on the subjectivity of the annotators. In this paper, we analyzed the annotation results using 13,226 exchanges from 155 participants in a multimodal dialogue corpus called Hazumi that we had constructed, where each exchange was annotated by five third-party annotators. We investigated the agreement between the subjective annotations given by the third-party annotators and the participants themselves, on both per-exchange annotations (i.e., participant’s sentiments) and per-dialogue (-participant) annotations (i.e., questionnaires on rapport and personality traits). We also investigated the conditions under which the annotation results are reliable. Our findings demonstrate that the dispersion of third-party sentiment annotations correlates with agreeableness of the participants, one of the Big Five personality traits.
BERT-based distractor generation for Swedish reading comprehension questions using a small-scale dataset

An important part when constructing multiple-choice questions (MCQs) for reading comprehension assessment are the distractors, the incorrect but preferably plausible answer options. In this paper, we present a new BERT-based method for automatically generating distractors using only a small-scale dataset. We also release a new such dataset of Swedish MCQs (used for training the model), and propose a methodology for assessing the generated distractors. Evaluation shows that from a student's perspective, our method generated one or more plausible distractors for more than 50% of the MCQs in our test set. From a teacher's perspective, about 50% of the generated distractors were deemed appropriate. We also do a thorough analysis of the results.
Biomedical Data-to-Text Generation via Fine-Tuning Transformers

Data-to-text (D2T) generation in the biomedical domain is a promising - yet mostly unexplored - field of research. Here, we apply neural models for D2T generation to a real-world dataset consisting of package leaflets of European medicines. We show that fine-tuned transformers are able to generate realistic, multisentence text from data in the biomedical domain, yet have important limitations. We also release a new dataset (BioLeaflets) for benchmarking D2T generation models in the biomedical domain.
Rigorous Foundations for Dual Attacks in Coding Theory

Dual attacks aiming at decoding generic linear codes have been found recently to outperform for certain parameters information set decoding techniques which have been for 60 years the dominant tool for solving this problem and choosing the parameters of code-based cryptosystems. However, the analysis of the complexity of these dual attacks relies on some unproven assumptions that are not even fully backed up with experimental evidence. These dual attacks can actually be viewed as the code-based analogue of dual attacks in lattice based cryptography. Here too, dual attacks have been found out those past years to be strong competitors to primal attacks and a controversy has emerged whether similar heuristics made for instance on the independence of certain random variables really hold. We will show that the dual attacks in coding theory can be studied by providing in a first step a simple alternative expression of the fundamental quantity used in these dual attacks. We then show that this expression can be studied without relying on independence assumptions whatsoever. This study leads us to discover that there is indeed a problem with the latest and most powerful dual attack proposed in [CDMT22] and that for the parameters chosen in this algorithm there are indeed false candidates which are produced and which are not predicted by the analysis provided there which relies on independence assumptions. We then suggest a slight modification of this algorithm consisting in a further verification step, analyze it thoroughly, provide experimental evidence that our analysis is accurate and show that the complexity claims made in [CDMT22] are indeed valid for this modified algorithm. This approach provides a simple methodology for studying rigorously dual attacks which could turn out to be useful for further developing the subject.
On the Multi-user Security of LWE-Based NIKE

Non-interactive key exchange (NIKE) schemes like the Diffie-Hellman key exchange are a widespread building block in several cryptographic protocols. Since the Diffie-Hellman key exchange is not post-quantum secure, it is important to investigate post-quantum alternatives. We analyze the security of the LWE-based NIKE by Ding et al. (ePrint 2012) and Peikert (PQCrypt 2014) in a multi-user setting where the same public key is used to generate shared keys with multiple other users. The Diffie-Hellman key exchange achieves this security notion. The mentioned LWE-based NIKE scheme comes with an inherent correctness error (Guo et al., PKC 2020), and this has significant implications for the multi-user security, necessitating a closer examination. Single-user security generically implies multi-user security when all users generate their keys honestly for NIKE schemes with negligible correctness error. However, the LWE-based NIKE requires a super-polynomial modulus to achieve a negligible correctness error, which makes the scheme less efficient. We show that We then turn to a stronger model of multi-user security that allows adversarially generated public keys. For this model, we consider a variant of the LWE-based NIKE where each public key is equipped with a NIZKPoK of the secret key. Adding NIZKPoKs is a standard technique for this stronger model and Hesse et al. (Crypto 2018) showed that this is sufficient to achieve security in the stronger multi-user security model for perfectly correct NIKEs (which the LWE-based NIKE is not). We show that This stronger security notion has been previously achieved for LWE-based NIKE only in the QROM, while all our results are in the standard model.
Quality Evaluation of the Low-Resource Synthetically Generated Code-Mixed Hinglish Text

In this shared task, we seek the participating teams to investigate the factors influencing the quality of the code-mixed text generation systems. We synthetically generate code-mixed Hinglish sentences using two distinct approaches and employ human annotators to rate the generation quality. We propose two subtasks, quality rating prediction and annotators' disagreement prediction of the synthetic Hinglish dataset. The proposed subtasks will put forward the reasoning and explanation of the factors influencing the quality and human perception of the code-mixed text.
CIDER: Commonsense Inference for Dialogue Explanation and Reasoning

Commonsense inference to understand and explain human language is a fundamental research problem in natural language processing. Explaining human conversations poses a great challenge as it requires contextual understanding, planning, inference, and several aspects of reasoning including causal, temporal, and commonsense reasoning. In this work, we introduce CIDER -- a manually curated dataset that contains dyadic dialogue explanations in the form of implicit and explicit knowledge triplets inferred using contextual commonsense inference. Extracting such rich explanations from conversations can be conducive to improving several downstream applications. The annotated triplets are categorized by the type of commonsense knowledge present (e.g., causal, conditional, temporal). We set up three different tasks conditioned on the annotated dataset: Dialogue-level Natural Language Inference, Span Extraction, and Multi-choice Span Selection. Baseline results obtained with transformer-based models reveal that the tasks are difficult, paving the way for promising future research. The dataset and the baseline implementations are publicly available at https://cider-task.github.io/cider/.