Reviewerly/exHarmony huggingface dataset:
A multi-source information fusion method for soil compaction detection

In this study, from the soil compaction characteristics, the Swin Transformer network in deep learning method is used to identify the soil surface rough and smooth, and compared with the traditional network method, proving that the algorithm in this paper has good results in terms of recognition accuracy and recognition speed; using Mask leveling, wavelet transform denoising and other steps in the traditional image processing method to identify whether the soil contains cracking; using the methods of physics, mathematics and soil science, fusing gravity sensors to detect soil water content, porosity, etc; using BP neural network, fusing the extracted features to achieve the purpose of real-time detection of soil compaction, and the experimental results show that the accuracy of this algorithm is 98.8%.
TranSage: a translation-based inductive model for KG completion

Knowledge graph completion (KGC) continuously fills out the knowledge graphs (KGs) by adding linkages and entities. Modern models are frequently trained using random walk sequences or negative sampling triples. These methods either neglect the neighborhood information of triples, which makes it challenging to manage long-tailed entities, or they are unable to adaptively extract the neighborhood node attributes that are most pertinent for entities, which introduces duplicate information. The joint knowledge representation model TranSage, which includes pre-trained node features as entity features, convolves the entity neighborhood features to obtain the node neighborhood information, and generates node embeddings, is proposed in this study based on the aforementioned issues. The model can enhance inductivity, improve knowledge representation performance, and address some long-tailed entities' representation issues, according to experimental findings on the KGC task. Its effectiveness confirms the efficacy of aggregated node embedding and outperforms that of the baseline model.
The Aid of Principal Components and Discriminant Functions Logs in Chemostratigraphy

Summary Chemostratigraphy utilises variations in inorganic geochemistry of sedimentary rocks for characterisation and correlation. While this has been evolved into widely used applications, particularly in the Palaeozoic of Saudi Arabia, the process is often time-consuming and requires subject matter specialisation. Multi-component statistical techniques (i.e. Principal Component Analyses (PCA) and Discriminant Functions (DF)) have been assessed for their potential of providing additional value to chemostratigraphy and simplification of the process. Three exploration wells have been chosen for this study. The lithostratigraphic formations and members comprise of four Palaeozoic formations, separated by unconformities. The wells have robust petrophysical and biostratigraphic constraints, which has enabled appraisal of the chemostratigraphic zones. In addition, mineralogy from sidewall cores has given insights into the underlying mineral assemblages. Cross-plots of Principal Components (PC) and provenance Discriminant Functions (DF) logs have been employed to differentiate the four formations in this study. The multi-statistical values reflect distinct geochemical compositions of the lithostratigraphic formations and members. Furthermore, specific element ratios and abundances have enabled additional understandings of depositional settings. Provenance changes and an eroded/missing section have been identified. The application of PC and DF logs have proven to be effective tools to aid chemostratigraphic interpretations.
Exploring and Reflecting on Problems and Challenges in Teaching Culture for English Young Learners

This study aims to reflect on the problems and challenges in teaching culture to English Young Learners (EYL) primarily related to the English context. The study focused on two objectives; to find out problems and challenges faced by the teacher in teaching culture for EYL, as well as the effective methods used to teach culture for EYL. Recently, many more pre-schools in Indonesia have offered English as a major in the learning process. For example, KB TK Hj Isriati Baiturrahman 2 made English as a central subject in daily life. Ideally, the teachers are required to know English culture besides the teaching itself. However, they found some problems in teaching culture when they asked the students to practice “how to say, go to the toilet in English”; it made students’ perspectives in their home opposites. This study tried to investigate this issue from the teachers’ problems. The interviews and classroom observations data showed that the cultural aspects of language were still not good. The possible strategies also showed a solution to face the problems. Thus, teaching English in Indonesia should consider the culture because to communicate functionally using the language and the students have to be familiar with the culture.
TRAFFIC RULE VIOLATION DETECTION WITH COMPUTER VISION

The increase in traffic volume and the subsequent rise in traffic rule violations have become major concerns for road safety worldwide.To address this issue, there is a growing need for efficient and automated traffic rules violations detection systems.This abstract presents a comprehensive overview of the application of computer vision techniques in the detection of traffic rules violations.
REVIEW ON SECURITY CHALLENGES OF CLOUD COMPUTING

The research paper titled "Security Challenges of Cloud Computing" explores the numerous security challenges faced in cloud computing environments.As cloud computing continues to gain widespread adoption, it becomes crucial to understand and address the security risks associated with this technology.This paper provides a comprehensive analysis of the security concerns in cloud computing, covering areas such as data breaches, unauthorized access, insider threats, and vulnerabilities in virtual machines.The authors discuss the impact of multi-tenancy, shared resources, and the lack of physical control on security in the cloud.They explore various security mechanisms and technologies, including encryption techniques, access control models, secure data storage, and communication protocols, emphasizing their importance in mitigating the identified risks.Additionally, the paper discusses emerging trends in cloud computing, such as containerization and serverless computing, and their implications for cloud security.The research paper contributes to the field by consolidating existing knowledge, proposing practical solutions, and highlighting the need for adaptive security measures in the rapidly evolving landscape of cloud computing.Overall, this paper serves as a valuable resource for researchers, practitioners, and decision-makers seeking to enhance the security of their cloud computing deployments.
Prevalence and Effects of Body-Shaming on Social Media among Undergraduates of Nnamdi Azikiwe University Awka

One of the most widespread forms of humiliation used by people globally is body-shaming. It has frequently led to suicide because of its negative impacts on the people and their mental health. This paper examined the prevalence and effects of body-shaming among undergraduates of Nnamdi Azikiwe University Awka. The objectives of this study are to find out the causes, the effects and the prevalence level of body-shaming among undergraduates of Nnamdi Azikiwe University. The study was anchored on cultivation analysis theory; while survey method was used with the adoption of a questionnaire as a data collection instrument. A sample of 300 respondents were drawn from the population of the study, which comprises undergraduate students of Nnamdi Azikiwe University, Awka. Findings from the study showed that the majority of the respondents have been exposed to body-shaming at different times for either their facial looks or complexion and that females experience body-shaming more than the males. Lastly, that Social media has played a critical role in incessant form of body-shaming. The study recommended, that Students should be taken to workshops and awareness program where they should be guided about self- esteem, self- recognition and self- confidence. Public awareness program on the negative effect of body-shaming should also be promoted by the government and that National Information Technology Development Agency (NITDA) should censor contents that may likely lead to body-shaming especially on social media.
PENGARUH METODE SPEED READING TERHADAP KETERAMPILAN MEMAHAMI ISI BACAAN TEKS PADA MATA PELAJARAN BAHASA INDONESIA SISWA KELAS V SDN PEGADUNGAN 07 JAKARTA BARAT

&#x0D; This study aims to identify the effect of the Speed Reading method on the reading comprehension skills of fifth grade students at SDN Pegadungan 07 West Jakarta. The population in this study were students in class VA and VB at SDN Pegadungan 07 West Jakarta, which consisted of 62 students. The instrument used was an objective test consisting of 15 combination questions, namely multiple choice questions and filling in. The method used is Quasi Experiment. This research was conducted at SDN Pegadungan 07 West Jakarta for the 2022/2023 school year. The illustration method used is Simple Random Sampling. These results indicate that there is an effect of the Speed Reading method on the ability to understand the content of reading Indonesian language texts for Class V SDN Pegadungan 07 West Jakarta. Judging from the hypothesis testing using the t-test, the results obtained are t count = 2.967 t table = 1.67 at the significant level ɑ= 0.05 and dk = 60, so Ho is rejected.
AUMED (Automatic Media Dispenser): Inovation in automatic liquid media dispenser as a support for microbiology laboratory diagnosis

Objective: To create an innovative Automatic Media Dispenser as a liquid media pourer to support the diagnosis of microbiology laboratories. Methodology: This research used descriptive observational design supported by laboratory testing because it will test the volume of the media poured with the AUMED (Automatic Media Dispenser) prototype tool. The test of the tool was carried out 6 times. Results: Constant results were obtained in liquid media pipetted by the AUMED tool with average is 2.9982 ml, accuracy 99.7980%, precision 0.2720%, and there was no contamination seen on nutrient broth media. Conclusion: We succeeded in designing an AUMED (Automatic Media Dispenser) device with the principle of a time sensor that can facilitate the pipetting process and pouring a certain amount of liquid media to support microbiological diagnostics.
Fraud Detection and Analysis for Insurance Claim Using Machine Learning

Abstract: Insurance fraud is an illegal conduct that is done on purpose in order to profit financially. This iscurrently the most serious issue that numerous insurance companies throughout the world are facing. The majority of the time, one or more gaps in the investigation of false claims has been identified as the primary factor. As a result, the requirement to use computer tools to stop fraud activitiesincreased. Providing customers with a dependable and stable environment while significantly lowering fraud claims. We demonstrated the results of our research by automating the evaluation of insurance claims using a variety of data methodologies, where the detection of erroneous claims would be done automatically using Data Analytics and Machine Learning techniques.
Authorship Analysis and the Ending of Seven Against Thebes: Aeschylus' Antigone or Updating Adaptation?

The present paper revisits the discussion concerning the authenticity of a crucial part in Aeschylus' Seven Against Thebes: the highly controversial ending of the play. Much has been written on the subject by various scholars, and even though there is now a general consensus that at some point in antiquity the ending of the play was "touched" by an author other than Aeschylus, the problem still remains unresolved in its devilish details. The question is of critical importance for classicists and theatre practitioners but also for anyone interested in classical literature, since, if the ending in the manuscripts is in fact Aeschylean, then Aeschylus could have been the first dramatist—long before Sophocles—to put on stage a defiant Antigone, eager to bury her brother Polyneices despite the civic prohibition. If the ending is spurious, then this will decisively affect how the play in question is read, studied, and staged. To address the problem, we used various tried and tested computer authorship attribution methods: Common n-grams, Support Vector Machines, and n-gram tracing. Thus, this study sheds new, interdisciplinary light on an old and perplexing philological question.
PENERAPAN METODE NAÏVE BAYES DALAM KLASIFIKASI KABUPATEN/KOTA DI SUMATERA UTARA BERDASARKAN PRODUKTIVITAS PANGAN PADI

Rice production in North Sumatra Province from January to December 2021 reached approximately 2 million tons of GKG, or a decrease of around 36.36 thousand tons of GKG (1.78 percent) compared to 2020. The decline in rice production also had an impact on the level of rice productivity and also had an impact on rice production. In the economic sector, it is necessary to classify rice productivity in order to support the increase in future rice production in North Sumatra Province. The purpose of this study was to determine the classification of district/city rice productivity using the Naïve Bayes method. This study uses 20 districts/cities as training data and 12 districts/cities as testing data. From the test results, 6 regencies/cities are classified with high level and 26 regencies/cities are classified with low level. The accuracy results obtained are 75% where this accuracy is a fairly good result in classification
PENERAPAN METODE MULTIPLICATIVE DECOMPOSITION DALAM MEMPREDIKSI JUMLAH KASUS DBD DI RSU. HAJI MEDAN

DHF case are diseases caused by four types of dengue virus, where each type has its own characteristics and pattern of spread. The purpose of this study is to make predictions on DHF cases in the future. This study uses the Multiplicative Decomposition method, in which this method breaks down time series data into four patterns, namely trend, seasonality, cycles and error. This research was conducted at RSU Haji Medan using DHF case data from January 2017 to December 2021. The results showed that the Multiplicative Decomposition method has an MSE value of 0,0012 and a MAPE value of 0,23%, which means it has a very good accuracy value because less than 10%. The conclusion of the study is that the Multiplicative Decomposition method is a method in the good category in predicting future DHF cases
Learning Path Recommendation from an Inferred Learning Space

Defining a learning space of reference may be a challenging task for the concerned tutor(s). However, once formalized, such a representation of possible learning sequences may serve as a norm to evaluate the current state of a learner and to potentially derive recommendations about the next learning state to target. A pragmatic strategy is introduced in this article to ease the definition of a subjective learning space from a few tutor(s)-provided examples of representative learning paths. A measure is then also inferred from these representative paths that can then be used to evaluate an ongoing learning path. The learning space and the evaluation measure, combined together, are then used to suggest the learning activity the learner should address next.
Management of processes in education: the curriculum of the discipline – 011 Educational, pedagogical sciences

The training syllabus of the elective course " Management of processes in education" is developed in accordance with the curriculum "Theory of Education in General Secondary and Higher Education". Level of higher education – the third (educational and scientific). Educational degree – Doctor of Philosophy. Field of knowledge – 01 Education / Pedagogy. Specialty 011 Educational, pedagogical sciences. Qualification – Doctor of Philosophy in Education. The purpose of the working educational discipline of the elective course "Management of Processes in Education" is provided for postgraduate students to acquire knowledge of the theory and practice of the educational and scientific process in education, to master the achievements of national, European and world pedagogical thought, to study and analyze the practice of educational activities in educational institutions in Ukraine and in other countries of the world, development of organizational and managerial abilities and end-to-end skills, critical, system-analytical, creative thinking. Preparation of graduate students as future scientific and pedagogical workers, managers and teachers for managing processes in education and educational institutions, for managerial activities in conditions of decentralization and expanding autonomy, improving the quality of education, entering the European and global educational space. The program consists of two modules and two topics. 30 hours / 1 ECTS credit are allocated to the study of the academic discipline (lectures - 4 hours, seminar classes - 6 hours, independent work - 20 hours. Control form - credit). The study of the academic discipline is provided for in the third year in the 5th semester. The following modules and topics are presented in the program: Module 1. Topic 1. Education as a sociocultural phenomenon and pedagogical process. Module 2. Topic 2. Subject-subject management of processes in education based on human-centeredness and partnership. The topics of the lectures are divided into two subtopics and the issues for consideration are described. Three seminar sessions are presented with questions for discussion. Independent work - with the distribution of topics and study hours. The main tasks of the study of the discipline "Management of processes in education" are defined as the formation of a set of program competencies: integral, general and professional and clearly defined program learning outcomes. The teaching and control methods, the distribution of points received by graduate students, the evaluation scale (national and ECTS), the list of educational and methodological support, the list of basic and additional literature are described.
Simulating the BB84 Protocol

Abstract: Quantum Key Distribution (QKD) is a cryptographic technique that allows two parties to establish a secure communication channel by using the laws of quantum mechanics. The BB84 protocol is one of the earliest and most widely used QKD protocols that uses the properties of quantum entanglement and superposition to securely exchange cryptographic keys[3] . In this paper, we provide a detailed overview of the BB84 protocol and its implementation. We also discuss the security aspects of the protocol and its vulnerabilities. Finally, we conclude with a discussion of the future prospects and challenges in the field of quantum cryptography
Merging or plagiarizing? The role of originality and derivative works in AI-aimed news production

The emergence of artificial intelligence systems applied to news production raises a series of legal questions that we examine in this short article. The central concept is, in our opinion, that of originality and creativity, legal requirements for attributing authorship and setting in motion the mechanisms of legal protection for a work, be it simple or collaborative, or even composite. The type of work that raises most questions is the derivative work, obtained from the transformation of pre-existing work(s), whose rights of authorship and economic exploitation must be respected at all times. The practices of learning systems based on artificial intelligence, which explicitly recognise that they rely on a wide variety of works protected by copyright, pose many doubts, and are not clearly able to benefit from the fair use exception, which, moreover, is only applicable to works produced in Common law jurisdictions, but not in other countries with an authorial system of intellectual property protection.
Implementation of the Gamification Concept in the Development of a Learning Management System to Improve Students' Cognitive In Basic Programming Subjects Towards a Smart Learning Environment

Rapidly developing technology has produced many inventions that can help facilitate human life in various fields one of which is the field of education which can help teachers and students in the learning process, one of the technologies that helps is the application of a Learning Management System in e-learning, where by This e-learning learning activities can be carried out flexibly by both teachers and students. The role of motivation has an important position in achieving learning objectives, one of which is to improve cognitive, therefore various methods are used to motivate students in the learning process. In this research, an effort was made in the form of applying Gamification which is a learning approach by bringing and applying game elements into the Learning Management System with the aim of increasing students' motivation and cognitive in the learning process using the ADDIE method, towards a Smart Learning Environment. Analysis of the results of the pre-test and post-test using the N-Gain calculation was carried out in both groups, where the average N-Gain score for the gamification group was 26.6111 and for the Non-LMS group it was -19.8889. This explains that the gamification group has more cognitive improvement than the non-LMS group.
Closing the Gap between Quantum Algorithms and Machines with Hardware-Software Co-Design

Quantum computing is at an inflection point, where 127-qubit machines are deployed, and 1000-qubit machines are only a few years away. These machines have the potential to fundamentally change our concept of what is computable and demonstrate practical applications in areas such as quantum chemistry, optimization, and quantum simulation.
Deep variational Hilbert quantitative phase imaging

Quantitative phase imaging is the representative of state-of-the-art marker-free full-field optical metrology techniques based on principles of interferometry, holography, microscopy and numerical processing. The measurand is encoded in the phase distribution (optical path delay) of the recorded fringe pattern. To retrieve the measured information the phase demodulation process needs to be performed. Considering the analysis of biomedical samples, the development of very accurate single-frame interferogram/hologram demodulation method is especially important because of the changing nature of the studied phenomenon. In that case the whole process of information recovery can be divided into two steps: (1) interferogram/hologram preprocessing and (2) phase demodulation. We are proposing the “black-box” algorithmic solution called Deep Variational Hilbert Quantitative Phase Imaging (Deep-VHQPI), where convolutional neural networks were used for automation, facilitation and acceleration of the previously complicated and arduous multi-step fringe pattern filtration and orientation estimation processes. It is worth to mention that convolutional neural networks in this work were used for the support of mathematically rigorous quantitative phase imaging algorithm (Hilbert transformation), not with aim to supersede it. For the sake of metrological figure of merit deep learning based solutions were employed to accelerate powerful and well-established VHQPI approach, not to bypass it completely. Deep-VHQPI algorithm enables analysis of variety of biological samples and constitutes an important step towards simplifying optical measurement of complicated and fragile biological samples. Phase decoding results are compared with reference algorithms, i.e., classical VHQPI, the Hilbert-Huang and Fourier transforms. Versatility of the proposed method and its potentially ubiquitous applications in full-field optical metrology are highlighted.