Reviewerly/exHarmony huggingface dataset:
The Influence of Reading Habits and Vocabulary Mastery on English Writing Skills

The purpose of this research is (1) to determine the influence of reading habits and vocabulary mastery on the English writing ability of high school students in East Lampung Regency. (2) to determine the influence of reading habits on the English writing ability of high school students in East Lampung Regency, (3) to determine the influence of vocabulary mastery on the English writing ability of high school students in East Lampung Regency. This study is a survey conducted in high schools in East Lampung Regency during the academic year 2020/2021. The sample consisted of 85 randomly selected students from several public high schools in East Lampung Regency. Data collection was carried out through questionnaires. Data analysis included descriptive statistics, validity tests, reliability tests, and multiple regression analysis. The research results indicate that (1) There is a significant combined influence of reading habits and vocabulary mastery on the English writing ability of high school students in East Lampung Regency. This is evidenced by the obtained significance value (Sig.) of 0.000 &lt; 0.05 and the computed F-value of 14.573. (2) There is a significant influence of reading habits on the English writing ability of high school students in East Lampung Regency. This is evidenced by the obtained Sig. value of 0.000 &lt; 0.05 and the computed t-value of 3.779. (3) There is a significant influence of vocabulary mastery on the English writing ability of high school students in East Lampung Regency. This is evidenced by the obtained Sig. value of 0.008 &lt; 0.05 and the computed t-value of 2.705.
Odgovornost za štetu nastalu upotrebom automatizovanog vozila

Advanced technology enables driverless vehicles powered by artificial intelligence (AI) to appear in the near future. The paper analyzes the need to improve the legal regulations on liability for damage from the use of partially and full automated (autonomous) vehicles. Based on good examples from foreign laws and recent EU laws, the author believes that the strict liability of manufacturers for robotic cars should be regulated in Serbian law. Moreover, the liability should move from the driver and/or the car owner to the vehicle manufacturer (including the software design company and company operating the software). In order to protect victims of traffic accidents, compulsory auto insurance should be prescripted as well as the insurance of the manufacturer's liability based on the risk of damage caused by AI. Just exceptional damages caused by a cyber attack on AI (hacking) should be compensated under restrictive conditions from a special fund.
Ultrasound Probe Calibration Method of Single-Wire Phantom Using Levenberg-Marquardt Algorithm

A freehand three-dimensional (3D) ultrasound system is a method of acquiring images using a 3D ultrasound probe or conventional two-dimensional (2D) ultrasound probe to give a 3D visualization of an object inside the body. Ultrasounds are used extensively in clinical applications since they are advantageous in that they do not bring dangerous radiation effects and have a low cost. However, a probe calibration method is needed to transform the coordinate position into a 3D visualization display, especially for image-guided intervention. The current ultrasound probe calibration system usually uses the numerical regression method for the N-wire phantom, which has problems in accuracy and reliability due to nonlinear point scattered ultrasound image data. Hence, a method for ultrasound probe positional calibration of single-wire phantom using the Levenberg-Marquardt algorithm (LMA) was proposed to overcome this weakness. This experiment consisted of an optical tracking system setup, a 2D ultrasound probe with marker, an ultrasound machine, and a single-wire object in a water container equipped with a marker. The position and orientation of the marker in a 2D ultrasound probe and the marker in the water container were tracked using the optical tracking system. A 2D ultrasound probe was equipped with a marker connected wirelessly using an optical tracking system to capture the single-wire object. The resulting sequences of 2D ultrasound images were reconstructed and visualized into 3D ultrasound images using three transformations, ultrasound beam to ultrasound probe’s marker, single-wire phantom position to container’s marker, and the 3D visualization transformation. The LMA was used to determine the best optimization parameters for determining the exact position and representing that 3D visualization. The experiment result showed that the lowest mean square error (MSE), rotation error, and translation error were 0.45 mm, 0.25°, and 0.3828 mm, respectively.
A Safe and Effective Online Voting System Based on The Blockchain as A Concept

Blockchain is offering new opportunities to develop new types of digital services. While research on the topic is still emerging, it has mostly focused on the technical and legal issues instead of taking advantage of this novel concept and creating advanced digital services. In this paper, we are going to leverage the open source Blockchain technology to propose a design for a new electronic voting system that could be used in local or national elections. The Blockchain-based system will be secure, reliable, and anonymous, and will help increase the number of voters as well as the trust of people in their governments.
Oracle-based data generation for highly efficient digital twin network training

Recent advances in Graph Neural Networks (GNNs) has opened new capabilities to analyze complex communication systems. However, little work has been done to study the effects of limited data samples on the performance of GNN-based systems. In this paper, we present a novel solution to the problem of finding an optimal training set for efficient training of a RouteNet-Fermi GNN model. The proposed solution ensures good model generalization to large previously unseen networks under strict limitations on the training data budget and training topology sizes. Specifically, we generate an initial data set by emulating the flow distribution of large networks while using small networks. We then deploy a new clustering method that efficiently samples the above generated data set by analyzing the data embeddings from different Oracle models. This procedure provides a very small but information-rich training set. The above data embedding method translates highly heterogeneous network samples into a common embedding spac, wherein the samples can be easily related to each other. The proposed method outperforms state-of-the-art approaches, including the winning solutions of the 2022 Graph Neural Networking challenge.
Pengembangan Media Pembelajaran Booklet Pada Materi Menulis Surat Pribadi Berbasi Direct Instruction di SMP Negeri 2 Gunungsitoli

The purpose of this research is to develop a decent, practical, and effective Direct Instruction-based booklet learning media. This research is development research using the ADDIE model which consists of Analysis, Design, Development, Implementation, Evaluation. Booklet development research was carried out at SMP Negeri 2 Gunungsitoli. The results of the research are in the form of Direct Instruction-based booklet products on personal letter writing material. The results of the questionnaire assessment of individual trial student responses obtained a score of 97.7% in the very practical category. In the small group trial, a score of 98.5% was obtained in the very practical category. In the field trial, a score of 90.1% was obtained in the very practical category. Assessment of student learning outcomes tests obtained a percentage of classical completeness in individual trials of 95.0% very effective category. In the small group trial 95.05 the category was very effective. In field trials 94.1% category is very effective. So, the research above, it was concluded that the Direct Instruction-based booklet learning media is feasible, practical, and effective to use so that it fulfills the research objectives.
IMPLEMENTASI ALGORITMA APRIORI DALAM PEMODELAN POLA PEMBELIAN PRODUK PADA EDUKITS BTC

In competition in the business world, especially the retail industry, requires developers to find an appropriate strategy in order to increase sales of school equipment, one way is to know the sales pattern of school equipment so that we can apply the right steps to provide more facilities, in order to increase selling power. A priori algorithm is a type of association rule in data mining. A priori is a very famous algorithm for finding high frequency patterns. A high frequency pattern is an item pattern in the database that has frequency or support above a certain threshold which is called the minimum support term. Using an a priori algorithm can help develop a marketing strategy. The results showed that with a minimum support of 30%, there were 4 combination patterns of one item set that achieved minimum support, with the highest support for Stationery Office of 72.6%, for a combination of 2 itemsets there were 4 combination patterns with the highest support (School Stationery, Stationery Office) namely 54.8%, for a combination of 3 itemsets there was 1 combination pattern with the highest support (Art &amp; Craft, School Stationery, Office Stationery) namely 32.9%.
Law Enforcement and Digital Policing of the Dark Web: An Assessment of the Technical, Ethical and Legal Issues

This chapter aims to investigate the challenges that law enforcement agencies (LEAs) face in policing the dark web and explore ways in which these challenges impact the effectiveness of law enforcement responses to crime. Following a comprehensive review of the literature, the main trend discovered is that these challenges arise especially due to the anonymous profile of the dark web and the ethics involved in detecting criminal activity. The issues examined have led to recommendations for reducing the negative impact of the Dark Web on policing activities. Conclusions drawn from the analysis support the recommendations in the need for increased cyber threat intelligence, the need for new regulations and a deeper concern for ethics. The findings also reveal the importance of ensuring a right balance between policing the Dark Web and respecting individuals’ civil liberties. In order to achieve a common objective, cross-jurisdictional law enforcement co-ordination and international co-operation are essential. In addition, the results suggest that in order for digital policing to be effective, the techniques used must also be unpredictable to criminals.
Challenge of Detecting Personal Deviations and Trends in Sensor Based Activity Data

Physical activity and health are closely linked. Therefore, monitoring movement behavior is of great interest e.g., to monitor a patient's physical state. Nowadays it is easy to record movement with a smartphone. The aim of this work was to develop a concept to detect trends based on personalized movement behavior recorded with a smartphone.A first prototype with a control chart was designed. Since this approach did not prove suitable for analyzing activity data for trends in practice, a second prototype was subsequently developed with a statistical trend test (Mann-Kendall test (MK test)). It was extended by the Yue-Wang correction approach to be able to deal effectively with serial correlation. Furthermore, the traditional trend modeling using Theil-Sen slope was extended by three additional models to be able to represent non-linear trend shapes.Movement behavior can be highly variable, which leads to wide control limits when using control charts. As the lower control limit was always in the negative range the use of a control chart was impossible for this use case. The evaluation results of the second prototype confirm the choice of a non-parametric test, as well as the decision for the Yue-Wang correction factor. Furthermore, it could be determined that the MK test is robust against outliers. The number of detected trends increases with increasing significance level. The MK test is also suitable for detecting step-like trends.Live trend detection is not straightforward with the MK test but can be simulated by overlapping time periods. In the future, trend modeling should be extended even further, as it plays a major role in the concept. The sensitivity of the test can be increased by means of various parameters.
DE-Lemma: A Maximum-Entropy Based Lemmatizer for German Medical Text

When processing written German language, it is helpful, to use the base form (or: lemma) of possibly inflected words, such as verbs, nouns or named entities. However, for German text from the (bio)medical domain, e.g., discharge letters, or entries stored in electronic medical or health records (EMR, EHR), difficulties exist in finding the correct lemma, as, for instance, the medical language has roots in Latin or Greek. In such cases, stemming techniques might provide inaccurate results for text written in German. This study demonstrates a Machine Learning approach for training Apache OpenNLP-based lemmatizer models from publicly available German treebanks. The resulting four "DE-Lemma" models were evaluated against a sample of (bio)medical nouns, randomly selected from real-world discharge letters. The most promising DE-Lemma model achieved an accuracy of 88.0% (F1 = .936).
Skeleton-based Visual Recognition of Diver’s Gesture

Divers have developed a specific gesture language for efficient communication underwater. As companion robot drones are increasingly used to help divers, it is essential that these robots can understand basic commands. This paper focuses on diver gestures classification using geometrical features extracted from the diver’s upper limb movements on underwater RGB-video. The extraction of upper limb skeleton points relies on pre-existing skeleton detection algorithms. Three geometric features are examined: angles, joint-line projections, and joint-joint distances. The classification is conducted using a 3-layer Bi-LSTM neural network for 11 different gestures. The database is acquired in a pool with 4 subjects and contains a total of 200 hand-cut videos. The recognition results show an accuracy of about 50% for the anangles and joint-lines features, this validates the potential of the method based on 2D skeleton extraction in videos.This study shows that the classification results are strongly related to the type of geometric feature used and to the characteristics of the gesture.
Supplemental Material: Neogene faulting, basin development, and relief generation in the southern Klamath Mountains (USA)

&lt;p&gt;Figure 3 (interactive). Geologic and geophysical maps of southern Klamath Mountains province. Use the radio buttons to toggle between different maps. (A) Geologic map modified from Irwin (1994) showing interpretations of the La Grange fault (LGF) from Cashman and Elder (2002) with hachures on hanging wall, Browns Meadow fault (BMF) (Davis, 1968; this study), and fault-bounded grabens that preserve Weaverville Formation (Irwin 2009, 2010; this study). Faults are solid where known, dashed where inferred, and dotted where concealed. New bedrock apatite (U-Th)/He (AHe) mean age locations are shown by large circles; previously published AHe ages are shown by small circles, and apatite fission-track (AFT) ages from Batt et al. (2010b) and Piotraschke et al. (2015) are shown with triangles. Sample locations of new detrital zircon U-Pb age distributions are shown by gray squares. Geologic cross section lines A-A′ (Fig. 4A) and B-B′ (Fig. 4B) are indicated. (B) Isostatic gravity map. Contour interval = 4 mGal. Data are from Snyder et al. (1981), Smith (1984), Pan-American Center for Earth and Environmental Studies (2015), and Langenheim et al. (2023). (C) Isostatic gravity map with horizontal gravity gradient maxima. (D) Aeromagnetic map (North American Magnetic Anomaly Group, 2002).&lt;/p&gt; &lt;p&gt;Figure 10 (interactive). Simplified geologic, gravity, and basin depth maps of the Hayfork graben using water well data. Use the radio buttons to toggle between different maps. (A) Simplified geologic map, modified slightly from Irwin (2010). Quaternary deposits are not shown. (B) Isostatic gravity map. (C) Basin depth map based on inversion of gravity data. &lt;/p&gt;
Supplemental Material: Neogene faulting, basin development, and relief generation in the southern Klamath Mountains (USA)

&lt;p&gt;Figures include effective uranium (eU) versus apatite (U-Th)/He individual grain ages, Wetherill Concordia plots of Miocene detrital U-Pb ages, and structure contour map of Weaverville basin and Lowden Ranch graben. Tables include HeFTy inverse and forward model parameters, all detrital U-Pb ages and isotope ratios, and all Lu-Hf isotopic values. &lt;/p&gt;
Use of a local computer network in the process of teaching Mathematics at school

At present in the context of modernization of the educational system, a modern teacher cannot succeed without knowledge of the possibilities of information and communication technologies (ICT). As the works of domestic researchers show [1; 3; 5], these technologies in Mathematics lessons can significantly increase the effectiveness of teaching. However, in the education system, the experience of using a private component of ICT – local computer networks (LCN) is not as long as, for example, in enterprises [9]. On the basis of the foregoing, the research problem is to form methodology for the use of LCN in the process of teaching Mathematics. The purpose of the research is to reveal the possibilities of using the LCN in the process of teaching Mathematics at school. To achieve this goal, the works devoted to the problems of using information technologies in teaching Mathematics have been analyzed, and a stating experiment in MBOU Lyceum No. 35 in Stavropol have been conducted to identify the possibilities of using LCN. In the course of the research the methods of analysis, synthesis and systematization of material on the problem of the use of LCN in education, questionnaires and conversations with teachers have been used. On the basis of literature analysis and the conducted ascertaining experiment, the authors have classified the LCN tools according to their methodological purpose, and have given the possibilities and requirements for the use of a local network in teaching Mathematics at the levels of basic and secondary general education. Along with this, the article reveals the demand for the use of LCNs at the levels of basic and secondary general education.
The Initial Explosion of Metaverse Technologys Impact on Accounting

Contemporary Metaverse programs all over the world demonstrate an upward trend, opening up a glorious prospect of the development of the digital economy. The meta-universe is achieved through and by using communication and arithmetic power, VR/AR devices, and artificial intelligence technology to virtualize and digitize the real-world process, which also provides a new imagination for the digital transformation of financial accounting. This paper aims to analyze how to transform and upgrade finance because of the principle of blockchain technology through reference and diagram analysis. The results of the research indicate that digital transformation like digitalization and intelligence of finance will be the trend, and the difference between financial accounting departments and sales departments might disappear. On this basis, it can be concluded that the accounting work would not be replaced or overturned, instead, workflow enhancement and a changing of work means occurred under the metaverse.
M-score and F-score from the Financial Statement for Company Fraud Prediction

This paper investigates the circumstances where M-score and F-score are predicted to find out company fraud from financial statement. The first part goes over the background information for company fraud by answering three questions. The second part introduces the important parameters cited in the research and calculation. The third part shows the result by providing charts and analysis. The last part summarizes this paper. The importance of these two scores is hypothesized to increase the public ability to be conscious of company fraud from hidden data and false statements. However, under specific circumstances, M-score and F-score are not reliable reflections of other parameters like net income and accruals. The results of the data analysis are consistent with our prediction. This work shows the importance of individual thinking as a result does not agree with the accuracy of the model. One of the most significant creative thoughts in this work is about how to break through the traditional blind faith in established model when the result does not follow the standards.
Identifying Financial Report Frauds

Misreporting numbers in a companys financial statements is not negligible, as manipulations will not reflect a reliable disclosure. With financial manipulation becoming more and more regular, it is obvious that solving financial manipulation is an issue that needs to be addressed gently. It becomes a necessity to find techniques or mechanisms that can effectively identify the potential of financial report fraud, increase the credibility of the corporation and boost the confidence of investors. In this paper, we argue that the M-score and F-score as two reliable tools for predicting the possibilities of financial manipulations. In this essay, we will introduce the background and principles of these two mechanisms, then verify their reliability and effectiveness on sample Us-listed Chinese companies, which include those associated with financial report frauds in the past. In addition, we will lay out our discovery and full verifying procedure to help readers have a better understanding of our research and perspectives.
EFL Students' Perception on Vocabulary Learning with Quizlet

Vocabulary plays a crucial role in communication and is considered one of the important aspects of the English language. Insufficient vocabulary knowledge can impede the process of learning English. Technology can serve as a valuable option for learning English vocabulary, as it provides various resources such as language learning apps that can enhance vocabulary and language skills. Quizlet is one such application that assists students in learning vocabulary concepts interactively and enjoyably. Student perceptions in learning activities are important things to know. This study aims to find out how students perceive the use of the Quizlet application in learning vocabulary whether they have negative or positive perceptions. This study uses qualitative methods in data collection. Ten students from grade seven became participants in this study. Researchers used two instruments, namely questionnaires and interviews. After distributing the questionnaires to students, the researcher also conducted interviews with five students to obtain more detailed information. The results showed that students had a positive perception of using Quizlet.
PENGEMBANGAN APLIKASI PENERJEMAH BAHASA ISYARAT INDONESIA (BISINDO) MENGGUNAKAN METODE LONG-SHORT TERM MEMORY

The Indonesian Sign Language Translator (BISINDO) application is intended for individuals who are deaf and mute assist them in communicating with normal people. Due to the limitations of technology to assist individuals who are deaf and mute, the Indonesian Sign Language Translator application was developed. Additionally, it is hoped that this application will enable individuals who are deaf and mute to learn Indonesian Sign Language in real-time. LSTM generally consists of a cell, input, gate, and forget gate. LSTM is highly suitable for classifying, processing, and making predictions based on time series data. In this research, hand landmark recognition is used as a medium to store finger gestures from user inputs, which will then be saved in the form of coordinate points and stored in a file in csv format. Subsequently, this file will be trained and called back to determine the output.