Reviewerly/exHarmony huggingface dataset:
Fraud Detection in Credit Card Data Using Unsupervised Machine Learning Algorithm

Abstract: We are living in the technology world in which Development of communication and e-commerce has made credit card as the most common technique of payment for both online and offline mode of purchases. As the e-commerce has increased, the buying and selling the product online is becoming very easy and comfortable to everyone in the daily life. Due to this, the online payment and online banking with credit card is increased. The fraud also happens when we lost our credit card or it get stole. Recently due to COVID-19 everything has become contactless so the use of credit card has increased. The transaction is done on online shopping and online payment is done from many places so it become difficult to recognise the real transaction and the fraud transaction. So, it becomes difficulty for the bank to stop fraud detection. In this paper it clearly explains about how fraud can be detected by using the Unsupervised Machine Learning using the algorithm and by using the algorithm technique like Isolated Forest, Local Outlier Factor and One class SVM. Keywords: Introduction, Machine learning, Supervised learning, Unsupervised learning
Penerapan Model Quantum Learning Untuk Meningkatkan Hasil Belajar Peserta Didik Kelas V MI Muhammadiyah Banjarsari

The problem in this research is the low learning outcomes in thematic learning of the fifth grade students of MI Muhammadiyah Banjarsari. The purpose of research is to improve student learning outcomes by implementation of quantum learning model. Type of research method was classroom action research implemented in two cycles that consist of planning, action, observation, and reflection. The subjects of this study were students of class V MI Muhammadiyah Banjarsari with a total of 20 students. Data was collected by test technique. The instrument of data collection used instrument test. The techniques of analyse used qualitative and quantitative analyse. The results of this study indicate that the application of the quantum learning model in thematic learning can improve student learning outcomes in class V MI Muhammadiyah Banjarsari each cycle. In the first cycle the average value of student learning outcomes is 70.08 with a completeness percentage of 65.00%. Then in the second cycle the average value of student learning outcomes increased to 88.50 with a mastery percentage of 85.00%. The results of this study can be a suggestion for teachers and schools to continue to vary the science learning with appropriate models, especially quantum learning, so as to increase student learning outcomes.
The Impact of Lexical and Syntactic Simplification of Materials on Listening Comprehension of Intermediate EFL Learners

The Impact of Lexical and Syntactic Simplification of Materials on Listening Comprehension of Intermediate EFL Learners
A Comparative Study on the Keywords of the Festival before and after COVID-19 through Social Media Text Mining: Focusing on Boryeong Mud Festival

Purpose - This study aims to examine and compare the opinions of social media users on the Boryeong Mud Festival, which has experience in holding face-to-face festivals before Covid-19 and non-face-to-face festivals afterwards. Design, data, and methodology - Using Textom, social media data were text-mined for the Boryeong Mud Festival, two years before and after Covid-19. Based on the collected data, TF and TF-IDF analysis, Degree Centrality, and LDA topic modeling were performed. Result - The ''where'' was important for the face-to-face festival, while there were many comments on ''how'' to participate for the non-face-to-face festival. For companion, the face-t o-face festival were mainly ''friend'', while the non-face-to-face festival were ''children''. Conclusions - It can be seen that the interest in non-face-to-face festivals have decreased since COVID-19. In order to hold a non-face-to-face festival, evaluations of festivals from the past and specific plans must be made thoroughly. Therefore, this study is meaningful in comparing and examining data so that non-face-to-face festivals can be prepared with differentiation from face-to-face festivals, and using these as basic data to prepare for non-face-to-face festivals. However further research was suggested so that data collection can be balanced and sentiment analysis for each word would be necessary.
Artifacts in the co-production of knowledge in social design

Social Design Research is a design and research approach that is characterised by an attempt to make a difference for marginalized, underprivileged or vulnerable groups in society through participatory processes and the use of knowledge artifacts.This article demonstrates how knowledge is generated co-productively and shows the interplay between different types of tacit or explicit forms of knowledge and models the knowledge exchange between design researchers, practitioners and the participating citizens.
Highly Efficient Structural Learning of Sparse Staged Trees

Several structural learning algorithms for staged tree models, an asymmetric extension of Bayesian networks, have been defined. However, they do not scale efficiently as the number of variables considered increases. Here we introduce the first scalable structural learning algorithm for staged trees, which searches over a space of models where only a small number of dependencies can be imposed. A simulation study as well as a real-world application illustrate our routines and the practical use of such data-learned staged trees.
Vibrating shapes : Design and evolution of a spatial augmented reality interface for actuated instruments

In this paper we propose a Spatial Augmented Reality interface for actuated acoustic instruments with active vibration control.We adopt a performance-led research approach to design augmentations throughout multiple residences.The resulting system enables two musicians to improvise with four augmented instruments through virtual shapes distributed in their peripheral space: two 12-string guitars and 1 drum kit actuated with surface speakers and a trumpet attached to an air compressor.Using ethnographic methods, we document the evolution of the augmentations and conduct a thematic analysis to shine a light on the collaborative and iterative design process.In particular, we provide insights on the opportunities brought by Spatial AR and on the role of improvisation.
User study on link-service usage and information processing in the context of the world wide web

Associating information by means of linking it is a universal concept of human thinking, and by constructivist means, a possible way of learning through exploring and constructing individual information spaces related to a topic or cross topics. An application, facilitating and externalizing this activity by enabling users to create individual hyperlinks inside the environment of the Web, is a promising way to satisfy this exploratory use of information. The focus on an augmentative approach by lining hypertext's linking paradigm, in conjunction with the Web's vast amount of information, opens up for a broad spectrum of potential use scenarios. The possibilities reflect potential complexities concerning usability and limitations of usage. Therefore, preliminary and iterative evaluations are indispensable for meeting these challenges. We discuss a preliminary evaluation of usability and user behavior of said application by a conducted study based on cross-sectional quasi experimental design, using a controlled test scenario and collected client side data that serves as basis for interpretation on user behavior. Results indicate a strong habituation to document-centric processing and storing of information, and the tendency for transferring this behavior onto the more versatile linking mechanism introduced by the application. We argue for applying additional supportive features, specific for facilitating the reduction of complexity on user-side, and a longer testing period, in order to gain better insight into the possible overcome of habitual patterns concerning the tested use scenario.
The Effect of Visualisation Level and Situational Visibility in Co-located Digital Musical Ensembles

Digital Musical Instruments (DMIs) offer new opportunities for collaboration, such as exchanging sounds or sharing controls between musicians. However, in the context of spontaneous and heterogeneous orchestras, such as jam sessions, collective music-making may become challenging due to the diversity and complexity of the DMIs and the musiciansâ unfamiliarity with the othersâ instruments. In particular, the potential lack of visibility into each musicianâs respective contribution to the sound they hear, i.e. who is playing what, might impede their capacity to play together. In this paper, we propose to augment each instrument in a digital orchestra with visual feedback extracted in real-time from the instrumentâs activity, in order to increase this awareness. We present the results of a user study in which we investigate the influence of visualisation level and situational visibility during short improvisations by groups of three musicians. Our results suggest that internal visualisations of all instruments displayed close to each musicianâs instrument provide the best awareness.
A Local Optima Network Analysis of the Feedforward Neural Architecture Space

This study investigates the use of local optima network (LON) analysis, a derivative of the fitness landscape of candidate solutions, to characterise and visualise the neural architecture space. The search space of feedforward neural network architectures with up to three layers, each with up to 10 neurons, is fully enumerated by evaluating trained model performance on a selection of data sets. Extracted LONs, while heterogeneous across data sets, all exhibit simple global structures, with single global funnels in all cases but one. These results yield early indication that LONs may provide a viable paradigm by which to analyse and optimise neural architectures.
Does a Technique for Building Multimodal Representation Matter? -- Comparative Analysis

Creating a meaningful representation by fusing single modalities (e.g., text, images, or audio) is the core concept of multimodal learning. Although several techniques for building multimodal representations have been proven successful, they have not been compared yet. Therefore it has been ambiguous which technique can be expected to yield the best results in a given scenario and what factors should be considered while choosing such a technique. This paper explores the most common techniques for building multimodal data representations -- the late fusion, the early fusion, and the sketch, and compares them in classification tasks. Experiments are conducted on three datasets: Amazon Reviews, MovieLens25M, and MovieLens1M datasets. In general, our results confirm that multimodal representations are able to boost the performance of unimodal models from 0.919 to 0.969 of accuracy on Amazon Reviews and 0.907 to 0.918 of AUC on MovieLens25M. However, experiments on both MovieLens datasets indicate the importance of the meaningful input data to the given task. In this article, we show that the choice of the technique for building multimodal representation is crucial to obtain the highest possible model's performance, that comes with the proper modalities combination. Such choice relies on: the influence that each modality has on the analyzed machine learning (ML) problem; the type of the ML task; the memory constraints while training and predicting phase.
Queen Domination of Even Square Boards

The queen's graph $Q_{m \times n}$ has the squares of the $m \times n$ chessboard as its vertices; we identify the $m \times n$ chessboard with a rectangle of width $m$ and height $n$ in the Cartesian plane, having sides parallel to the coordinate axes and placed so that square centers have integer coordinates. Two squares are adjacent if they are in the same row, column, or diagonal of the board. A set $D$ of squares of $Q_{m \times n}$ is a dominating set for $Q_{m \times n}$ if every square of $Q_{m \times n}$ is either in $D$ or adjacent to a square in $D$. The minimum size of a dominating set of $Q_{m \times n}$ is the domination number, denoted by $\gamma(Q_{m \times n})$.&#x0D; We give a new proof of the bound $\gamma(Q_{m \times n}) \geq \min \left\{m, n, \left\lceil \frac{m+n-2}{4} \right\rceil\right\}$, with implications for queen domination problems, and then consider square boards.&#x0D; Let $n$ be an even integer and assume $Q_{n \times n}$ has a dominating set $D$ of size $n/2$ (which implies $\gamma(Q_{n \times n}) = n/2$). For $p \in \{ 0, 1 \}$, let $D_{p} = \{ (x, y) \in D \mbox{ : } x + y \equiv p \mbox{ (mod 2)}$. Say that $D$ is monochromatic if $D = D_{p}$ for some $p$; otherwise bichromatic. We show that if $D$ is bichromatic then $||D_{0}| - |D_{1}|| \leq 2$ and conjecture that if $n &gt; 4$ then $D$ is monochromatic.&#x0D; Assume further that $D$ is monochromatic. If $n \equiv 0 \mbox{ (mod 4)}$ then $n \in \{ 4, 12 \}$. If $n \equiv 2 \mbox{ (mod 4)}$ then odd integers $k = n/2, e, d$ with $1 \leq d, e \leq k$ satisfy the equation $d^{2} + (k-1)e^{2} = k(k^{2} + 2)/3$. We analyze six infinite sequences of solutions of this equation arising from Fermat-Pell equations, give monochromatic dominating sets of $Q_{n \times n}$ of size $n/2$ for $n = 2, 4, 6, 10, 12, 18, 30 \text{ (new)}$, and $130$, and show there are no others with $n &lt; 238$.
Streaming Videos: Subject Area Usage Trends

The usage of streaming videos at The Ohio State University is examined, focusing on the University Libraries’ multi-subject vendors Alexander Street, Films on Demand, and Kanopy. Videos with at least one view per month (amount viewed not considered) are examined and assigned disciplines (Arts, Humanities, Sciences, Social Sciences, or Multi) and subjects (one out of over 100 options). The usage of the videos within the context of these disciplines and subjects is then examined for overall and average use. Finds from this indicate volume of titles being higher for some subject areas but with higher average use for other subjects, pointing to differences in the way in which instructors may be using content. These different usage patterns indicate implications for those dealing with collections and instruction aspects of streaming videos.
Improve Ranking Correlation of Super-net through Training Scheme from One-shot NAS to Few-shot NAS

The algorithms of one-shot neural architecture search(NAS) have been widely used to reduce computation consumption. However, because of the interference among the subnets in which weights are shared, the subnets inherited from these super-net trained by those algorithms have poor consistency in precision ranking. To address this problem, we propose a step-by-step training super-net scheme from one-shot NAS to few-shot NAS. In the training scheme, we firstly train super-net in a one-shot way, and then we disentangle the weights of super-net by splitting them into multi-subnets and training them gradually. Finally, our method ranks 4th place in the CVPR2022 3rd Lightweight NAS Challenge Track1. Our code is available at https://github.com/liujiawei2333/CVPR2022-NAS-competition-Track-1-4th-solution.
INTERDISCIPLINARY SHARED RESEARCH FACILITIES "GEOANALYST" UB RAS: OPERATING EXPERIENCE AND PROSPECTS

The article presents general information about the interdisciplinary Shared Research Facilities "Geoanalyst" of the Ural Branch of the Russian Academy of Sciences, the main directions of its work, analytical equipment and types of work that allow obtaining quantitative information on the chemical (elemental and isotopic) and phase composition, parameters of the crystal and electronic structure, type and concentration of the lattice defects, optical properties of samples including minerals, rocks, bottom sediments, ores, products of their enrichment and processing, natural and drinking water, as well as synthetic compounds, techno- and biogenic objects. Consideration is being given to the techniques involved in the Shared Research Facilities such as electron probe microanalysis and electron microscopy; X-ray fluorescence, atomic emission and atomic absorption analysis; X-ray structural and thermal analysis; microelement mass spectrometric analysis; isotope mass spectrometric analysis and geochronology; physics and spectroscopy of minerals. Emphasis has been placed on the fundamental and applied sciences based on the Shared Research Facilities, its scientific and educational activities and the experience of working with users. Details have been provided for the formulation, testing and use of microanalytical methods for in situ study of the composition, structure and properties of minerals-concentrators of transition, rare-earth and radioactive d- and f-elements (zircon, titanite, etc.) with a spatial resolution from units to tens of micrometers. There have been analyzed the application and development of research methods; their metrological parameters; the procedure for selection and certification of internal laboratory reference samples; the possibilities for solving problems of fundamental and applied physics and chemistry of mineral matter, as well as geochronological problems.
Digital toys as tangible, embodied, embedded interactions

Our research aims to explore the potential that tangible, embedded, embodied interactions (TEIs) has in enabling children's (age 3-5 years old) active play.This paper describes our study of 66 commercially available digitally augmented toys that have the potential to get children moving, and how these digital toys may be conceptualised as TEIs.During our analysis, the type and persistence of digital feedback from the toys was an important factor in our conceptualisation of these toys as tangible and embodied.We also encounter issues when conceptualising children's toys, particularly toys for pretend play, as embedded interaction.These findings offer the opportunity to refine our definition of embeddedness to capture children's play and highlights the importance of designing toys with strong feedback for physical activity.
Editing Compression Dictionaries toward Refined Compression-Based Feature-Space

This paper investigates how to construct a feature space for compression-based pattern recognition which judges the similarity between two objects x and y through the compression ratio to compress x with y (’s dictionary). Specifically, we focus on the known framework called PRDC, which represents an object x as a compression-ratio vector (CV) that lines up the compression ratios after x is compressed with multiple different dictionaries. By representing an object x as a CV, PRDC makes it possible to apply vector-based pattern recognition techniques to the compression-based pattern recognition. For PRDC, the dimensions, i.e., the dictionaries determine the quality of the CV space. This paper presents a practical technique to modify the chosen dictionaries in order to improve the performance of pattern recognition substantially: First, in order to make the dictionaries independent from each other, our method leaves any word shared by multiple dictionaries in only one dictionary and assures that any pair of dictionaries have no common words. Next, we transfer words among the dictionaries, so that all the dictionaries may keep roughly the same number of words and acquire the descriptive power evenly. The application to real image classification shows that our method increases classification accuracy by up to 8% compared with the case without our method, which demonstrates that our approach to keep the dictionaries independent is effective.
IMPLICIT REFLECTIONS OF RUSSIA-UKRAINE WAR IN ARABIC INTERNET MEMES

The reaction to the news of Russian invasion of Ukraine is expressed in the Arab world through various communicative means, including Internet memes. Language of social media is utilised to convey the non-official public opinion, both explicitly and implicitly. This paper deals with a complex study of the Arabic humorous discourse, in particular Ukraine war memes, involving their linguistic, sociolinguistic, and pragmatic peculiarities. The research is based on the works of R. Bassiouney [1], M. Bulatovic [2], M. R. Enverga [3], and others. Arabic narratives about the Russian war against Ukraine on social networks have been outlined in the Ukrainian mass media [4]. However, a more in-depth linguistic analysis is necessary to examine the language as a tool affecting the public opinion online.
TRISODIUM PHOSPHATE 2% EFFECT ON SETTING TIME ALGINAT MATERIALS

Alginate is widely used in dentistry as an impression material. Manipulation of commercial alginate impression materials with the addition of Trisodium Phosphate (TSP). It is known to prolong the setting time of alginate by reacting it first with calcium sulfate. Dental students in their first grade sometimes have difficulty manipulating alginate so they need a longer manipulation time. There is no alginate product with a longer setting time in the market. From this study, we added 2% TSP to add setting time for dental education. The purpose of this study to characterize was to determine the compressive strength of alginate molding materials that have been added with TSP to commercial alginate products with factory standards. Setting time, compressive strength, EDS, and SEM was used as a characterization. This research was true experimental research. It was conducted using normal type printed materials with one of the brands available in the market. The results of this study were then analyzed using paired T-test, the compressive strength of alginate without and without TSP 2% was a significant difference. The addition of 2% TSP affected the compressive strength of the alginate impression material.
Il faticoso procedere della persona umana tra i crinali della storia

In recent decades, new rights have been established in case-law, not recognised previously by any constitution or international declaration. The phenomenon is itself positive, but we must avoid individualistic drifts, which clash with the model of society, personalist and pluralist, underlying not only the Italian Constitution of 1948, but in general the majority of modern constitutional states. That is why emerges the need to elaborate and structure a statute of the person’s rights, the most universally valid: in this regard, the fundamental criterion of discernment is the recognition of the dignity and reasonableness of every human person, starting from the formation of the genome. Even in ethically sensitive matters, the identification of a reasonable balance of the opposing needs is primarily the responsibility of national legislators, but the national constitutional courts are responsible of verifying the reasonableness and proportionality of the balance achieved in the legislative process. The reasoned analysis of the solutions reached, also in critical function respect to possible involutions contrary to the Constitution, and the well-argued development of possible alternatives are one of the most important contributions that the Academy can make to contemporary legal experience.
Effective Image Tagging: A Survey on Techniques to Improve Image Retrieval Experience

Images are generally searched using textual queries. For relevant images to retrieved effectively, they need to properly tagged. Tagging can be done manually or automatically. This paper is a survey on techniques to improve image retrieval experience by computing better tags for images. It also discusses some problems with the current techniques which opens up opportunities for further research. Key Words: image, tagging, searching