Reviewerly/exHarmony huggingface dataset:
Blockchain-Based Secure and Verifiable Deduplication Scheme for Cloud-Assisted Internet of Things

With the rapid proliferation of IoT infrastructure and edge computing, more and more IoT data is outsourced to cloud storage service provider (CSP). To achieve efficient space-saving, data deduplication based on convergent encryption (CE) has been widely applied on the cloud-assisted IoT since it can eliminate redundant data while maintaining data confidentiality. However, most existing works based on CE are susceptible to the brute-force attack for low-entropy data due to its deterministic property. Furthermore, prior works are unsatisfactory since they usually treat the edge nodes (ENs) as the fully trusted entities and overlook their security threat, which may suffer from the leakage of outsourced data and forgeability of deduplication result. In this paper, a blockchain-based secure and verifiable deduplication scheme for cloud-assisted IoT is proposed to protect the IoT data privacy and achieve the data auditability. Leveraging the blockchain, our scheme constructs a trustworthy and auditable deduplication framework to prevent the IoT data from illegal modification and forgery by malicious ENs and CSP, where any entity in IoT can track and check the validity of deduplication result by the tamper-proof record (TPR) on blockchain without learning the data content itself. Moreover, our scheme can generate random convergent key and build distributed key management mechanism for the user, to resist the brute-force attack and single point attack. Eventually, formal security analysis and performance evaluation are provided to demonstrate the security and the practicability of our proposed scheme, respectively.
Privacy-Preserving for Dynamic Real-Time Published Data Streams Based on Local Differential Privacy

Real-time data collected from users can help various applications provide services, but there is a risk that sensitive information will be leaked. Existing LDP-based approaches mainly perturb each data point, which severely affects the time-series patterns, leading to sensitive information being leaked out from multiple consecutive significant patterns. In this paper, we focus on dynamic data streams under honest but curious servers and propose a privacy-preserving method called PP-LDP to protect data privacy while preserving data stream patterns and improving the utility of published data. To this end, our approach consists of three main parts. First, we sample the points that can represent the data stream patterns by improving the popular Least Squares Segmented Linear Fit method. Then, we use an adaptive budget allocation method to perturb the sampling points and provide w-event level privacy. Finally, we perform post-processing optimization of the data streams with Kalman filters to further improve the utility of the data streams. Extensive experimental results on realistic datasets show that our proposed scheme can not only protect the data streams’ privacy but also effectively preserve patterns and guarantee the utility of private data.
The Impact of Doing Assignments with Chatbots on The Students’ Working Memory

This study aimed to investigates the effects of chatbot usage on working memory in students who do their assignments with chatbots. The research employed a Single-Subject AB design involving three participants, with each phase consisting of four measurements. Remarkably, the study revealed diverse outcomes: one participant exhibited no significant change in working memory, another showed a decrease, and the third experienced a gradual increase. These varied results suggest that chatbots can have differential impacts on working memory, potentially explained by cognitive load theory. This theory emphasizes the importance of optimizing technology use in learning environments to support working memory functions. The study's findings indicate that chatbots, as an educational tool, can have complex and varying effects on students' cognitive abilities, particularly in terms of working memory.
Optimal Quantization From the Numerical Side (Static)

A general rule is that the deterministic (or mean-field) avatars of these procedures can only be implemented in a low-dimensional (at most 3) framework, even, for some of them, in one dimension, whereas the stochastic versions, usually suffering from a slower convergence rate, can be implemented in any dimension. A final general remark is that the quadratic versions of these stochastic algorithms (𝑟 = 2) are usually more stable. It is also in this quadratic setting that most theoretical results have been obtained.
Optimal and Stationary Quantizers

We introduce the functional quantization problem for stochastic processes as a quantization problem for random vectors taking values in an infinite-dimensional Banach space. The role of the Kantorovich metric is explained. The basic features of optimal and stationary quantizers (depending on the underlying Banach space structure) like the existence of optimal quantizers and characterizations of stationarity are derived.
The Finite-Dimensional Setting I

We introduce a new general approach to universal upper bounds and asymptotics of the quantization errors based on the integrability of radial functions. The asymptotics of the increments of quantization errors is determined (for nonsingular distributions), which has a great impact on subsequent sections.
Spectral Methods for Gaussian Processes

The quantization theory of Gaussian random vectors in a Hilbert space is ruled by the eigenvalues and eigenvectors of their covariance operators. Under regular variation of the eigenvalues, the sharp asymptotics of the quantization errors is derived. The proof in Section 5.3 is constructive and relies on the famous notion of Shannon entropy. We establish a sharp link relating the Shannon entropy and the quantization errors. The genuine (or asymptotic) critical dimension of the quantization problem plays a crucial role. In Section 5.6 we investigate the performances of rate optimal scalar and block product quantizations and their distortion mismatch features as well as constructive asymptotic optimality.
Applications: Quantization-Based Cubature Formulas

In this chapter we establish several cubature formulas for numerical integration and conditional expectation computation taking advantage of the fact that, for a large enough quantization level, $$ \widehat{\textit{X}} \simeq \textit{X} $$ , where $$ \widehat{\textit{X}} $$ denotes an optimal (usually a quadratic optimal) quantization of the random variable X at level n.
Machine learning methods to predict amyloid positivity using domain scores from cognitive tests (P4-6.003)

Sunday, April 3May 3, 2022Free AccessMachine learning methods to predict amyloid positivity using domain scores from cognitive tests (P4-6.003)Guogen Shan, Jiong Shi, and Charles BernickAuthors Info & AffiliationsMay 3, 2022 issue98 (18_supplement)https://doi.org/10.1212/WNL.98.18_supplement.858 Letters to the Editor
Innovative Way of Using AI and ML to Create and Audit Crypto Token Smart Contract Addresses in Any Block chain

It can be noted that cryptocurrencies have gained huge popularity in recent years and blockchain technology is serving as the backbone of this digital revolution. Due to the increase in technology, the demand for cryptocurrencies and blockchain-based applications continues to grow. Therefore, there is a need for secure and reliable smart contracts. Based on these points, the article will show some innovative ways to use machine learning and artificial intelligence to create and audit crypto token contracts and provide information on different blockchain platforms. with the comprehensive literature review and explanation of how machine learning and artificial intelligence techniques can be used to enhance the security and efficiency of crypto token contract address management.
One-Way Analysis of Variance

Statistics Using R introduces the most up-to-date approaches to R programming alongside an introduction to applied statistics using real data in the behavioral, social, and health sciences. It is uniquely focused on the importance of data management as an underlying and key principle of data analysis. It includes an online R tutorial for learning the basics of R, as well as two R files for each chapter, one in Base R code and the other in tidyverse R code, that were used to generate all figures, tables, and analyses for that chapter. These files are intended as models to be adapted and used by readers in conducting their own research. Additional teaching and learning aids include solutions to all end-of-chapter exercises and PowerPoint slides to highlight the important take-aways of each chapter. This textbook is appropriate for both undergraduate and graduate students in social sciences, applied statistics, and research methods.
Inferences Involving the Mean when <i>σ</i> is Not Known: One- and Two-Sample Designs

Statistics Using R introduces the most up-to-date approaches to R programming alongside an introduction to applied statistics using real data in the behavioral, social, and health sciences. It is uniquely focused on the importance of data management as an underlying and key principle of data analysis. It includes an online R tutorial for learning the basics of R, as well as two R files for each chapter, one in Base R code and the other in tidyverse R code, that were used to generate all figures, tables, and analyses for that chapter. These files are intended as models to be adapted and used by readers in conducting their own research. Additional teaching and learning aids include solutions to all end-of-chapter exercises and PowerPoint slides to highlight the important take-aways of each chapter. This textbook is appropriate for both undergraduate and graduate students in social sciences, applied statistics, and research methods.
Indonesian Language Important but Undervalued at Home: Theme and Thematic Progression Analysis

A text's cohesion can be seen through the thematic progression used in the text itself. Thematic progression patterns can be divided into three patterns, namely zigzag theme patterns, reiteration theme patterns, and multiple theme patterns. This research aims to analyze the thematic progression patterns in an article in The Magdalene Online Magazine. The researchers have chosen an article entitled “Indonesian Language Important but Undervalued at Home” in the Magdalene online magazine. This research used a descriptive qualitative approach. The researchers found there are sixteen zigzag theme patterns and four reiteration theme patterns in the article. The multiple theme patterns were not found in the article. The writer of the article used the zigzag thematic pattern to make cohesion in a text and introduces new information of a text, the reiteration theme pattern used when the writer tries to focus the reader about the thing that is being discussed, and the multiple theme pattern is not used because the writer does not make a Rheme becomes a number of different pieces of information in another Theme on the text.
Back to the Future of The Art of Noises: The After-Life of Futurism in Twentieth-Century Music

By exploring the aesthetic implications of historical Futurism, this essay offers an approach to Neo-Futurist tendencies in the music of subsequent decades. From 1913 onwards, the manifestos published by Luigi Russolo (1885-1947) on music and the construction of noise-producing instruments (intonarumori) contributed to the emancipation of noise as musical material and set an aesthetic impulse that was significant for the music history of the twentieth century. However, Futurism’s rôle in this development was underestimated for a long time, largely because of the movement’s affiliation with Fascism and because Futurist manifestos were given a superficial interpretation by contemporary composers. The intention of this essay is to extrapolate, with reference to historical Futurism, aesthetic criteria for a type of music that can be considered to exhibit a Neo-Futurist tendency. Starting from this, the Futurist definition of noise as musical material will be shown in its consequences for modes of production and reception in later periods. Futurist musical aesthetics focussed on a scientific approach to acoustic material. In the second half of the twentieth century, the modes of production and reception of music developed further, in parallel to the availability of technical possibilities of sound production. This process will be exemplified in this essay by composers who had different attitudes towards Futurism: some were positively or negatively disposed towards it; others adopted some but rejected other features of Russolo’s demand for a separation of noise from its sources of inspiration (such as the metropolis, the street and the factory). In any case, Russolo paved the way for musical abstraction, a transformation that was shaped significantly by technologies of sound production and reproduction. Edgard Varèse (1883-1965), John Cage (1912- 1992), Pierre Schaeffer (1910-1995) and György Ligeti (1923-2006) developed compositional practices that gave noise a musical form and created works that became examples of a music that ultimately turned noise into abstract sounds.
The Effect of Education Through Power Point Media and Infographic Media on Knowledge, Attitude and Action Improvement on Vegetables and Fruits In School Children at Elementary School Sidosermo 1 Surabaya

Food is needed by all age groups, including school-age children for the process of growth and development. The results of the 2018 East Java Province Riskesdas showed that the percentage of the age group ≥ 5 years was lacking in vegetable and fruit consumption, namely 93.9%. The purpose of this study was to determine the effect of education through power point media and infographic media about vegetables and fruit for school children at SDN Sidosermo 1 Surabaya. The type of research used is Quasi Experimental with the type of One-Group Pretest Posttest Design. Data collection is done by questionnaire. The number of research samples was 40 people. Statistical test using the Wilcoxon Signed Rank Test. Based on the results of the study, it was obtained that the value of p = 0.00, namely p &lt;a 0.05, which indicates that there is an effect before and after being given education through power point media and infographic media on increasing knowledge, attitudes and actions about vegetables and fruit in class school children 5 at SDN Sidosermo 1 Surabaya.
STUDENTS' DIFFICULTIES IN WRITING EXPOSITORY ESSAY: A PHENOMENOLOGICAL STUDY

Writing, one of the language skills, is considered difficult for some students, especially EFL students. The present research, a phenomenological study, aims to find out the students’ difficulties, the factors affecting their difficulties, and the strategies for overcoming their difficulties in writing expository essays. The participants were three students, taken by using purposive sampling, in a private university in Surabaya. The instruments used in this research were observational fieldnotes, rubrics, Focus Group Discussion guidelines, and Interview protocols. The research findings show that the research participants had difficulties in the five components of writing, namely content, vocabulary, language use, mechanics, and organization. The common difficulties the participants faced were related to word choice, finding and developing ideas, verb tense, run-on sentences, spelling, punctuation, and writing the thesis statements and topic sentences. There were internal and external factors that affected their difficulties, but most of the factors were internal. The most common factors were that the participants did the assignments at the last minute or in a hurry, felt sleepy and lazy, and were afraid of plagiarism. Some ways of overcoming their difficulties were finding more ideas and materials on the Internet, discussing the topic and content with their friends and lecturers, writing the ideas in Indonesian before translating them into English, using common vocabulary, learning new vocabulary, finding the opposites and synonyms of some words, doing paraphrase, using Grammar-checking tools, learning from the previous mistakes, paying more attention to the essay structure, making an outline, learning more basic English grammar, revising the mistakes based on the lecturer’s feedback, and listening to music when writing the essays.
SISTEM INFORMASI ANTREAN BERBASIS WEB DAN LED MATRIX DISPLAY

Queues are often encountered in daily activities. The queuing process is a process related to the arrival of customers at a service facility, waiting to get service until they finally get service and leave the service facility. Many queue models use single-server, single-phase system and multiple-server, single-phase system. Currently, there are still service facilities that have not utilized technology to provide convenience for the users.&#x0D; One way to improve service quality is by using a queuing system. The method applied in building this system is Prototype method. The prototype method consists of communication, which is the stage of data collection through the method of literature, observation, experiments which are described in use cases, activity and sequence diagrams as well as device requirements. Modeling Quick Design is the stage of making a brief description of the design in the form of architecture and appearance design. Construction of Prototype is the design stage, built using PHP MVC, MySQL, C++, JavaScript, JSON, NodeMCU ESP8266 microcontroller as a link for each device via a Wi-Fi network as well as a P10 led matrix display controller. P10 led matrix and monitor displays the queue number. The web server installed on the PC acts as a center for managing queue numbers, queue voice calls via text to speech as a voice generator in the Edge browser. Deployment Delivery &amp; Feedback are the testing stages. the results obtained are to produce a web-based queue number information system and led matrix display that has been tested using black box testing that this system can run well
Study on the Improvement of Educational Management and Teaching in the Context of Education Informatization

Information technology has been advancing rapidly, allowing education informatization and the improvement of educational management and teaching. This paper describes the relationship between educational management and teaching through a literature review and inductive summarization. Besides, the significance of improving education management and teaching under the background of information technology and the challenges faced in applying information technology in education are also discussed in this paper. Several educational management strategies on the basis of information technology are proposed in this paper. This includes diversifying education management bodies and building hybrid teaching modes, so as to help colleges improve their education management and teaching.
Implementasi Data Mining Menggunakan Algoritma Apriori Untuk Menemukan Frequent Itemset Penjualan Sneakers

Every small or large company that wants to stay afloat in an increasingly fierce business competition requires the right sales strategy, including at the Yasa Collection Sport Store. One way is to perform data mining analysis on the sales transaction database using the a priori algorithm of the association rule method. This method makes it possible to find combinations of items that often (often) appear from a collection of items (itemset), so that store management knows market conditions, consumer tastes and sales patterns. Based on the results of research and data analysis conducted with a minimum support value of 0.33 and a minimum confidence value of 0.80, three association rules were obtained, in which the frequent itemset information that had been found using the a priori algorithm, could be utilized by the store management in determining sales strategies, such as discount promotion, packaging and stocking goods.
Implementasi Metode Clustering Algoritma K-Means untuk Menentukan Kelompok Tahfidz dan Tahsin di Pesantren Siswa Al-Ma’soem

Determining the tahfidz and tahsin groups with computer programs is an effort that needs to be done to find out the ability of students during this tahfidz program. At this time, in the process of grouping tahfidz and tahsin at pesantren Siswa Al Ma'soem, it is necessary to Cluster with data so that the ability of students in answering the test can be known the student's self-limit and enter the tahfidz or tahsin group. In this study, 349 data were used as the main data for clustering using the K-Means algorithm with tests carried out on Rapidminer and Microsoft Excel. Based on the results of the analysis in the research conducted, it can be concluded that from 4 attributes. In Cluster 1 with a total of 177 students, it was declared into the tahfidz group. In addition, other cluster with a total of 172 students who entered the tahsin group with validation of 0.312 and 0.238 in Microsoft Excel and Rapidminer which stated that the smaller the validation number, the better the cluster used.
Implementasi Analisis Big Data untuk Memprediksi Kelulusan Mahasiswa Fakultas Teknik Universitas Langlangbuana

The Faculty of Engineering at the University of Langlangbuana has a large number of students who do not graduate on time. Based on observations and data available at the Faculty of Engineering, Langlangbuana University, there are still many students who do not graduate on time which causes a decrease in the score in the accreditation assessment criteria. The timely graduation of students is one of the criteria for accreditation assessment at Langlangbuana University. To get good accreditation results, it is necessary to predict the graduation rate with a method Big Data Analytic so that it can anticipate delays in graduating students at the Faculty of Engineering, Langlangbuana University. The database owned by Langlangbuana University can be used as a reference as material for predicting student graduation at the Faculty of Engineering. With the digitization of data which has resulted in a very rapid data spike, Langlangbuana University requires Big Data Analytic. The results showed that using Big Data Analytics can improve decision making to improve student performance and success and also all related aspects, especially at the Faculty of Engineering, Langlangbuana University.
A Study on Informatization Teaching Efficacy in Higher Vocational Education in Guangzhou, China

China has been vigorously promoting the construction and development of Informatization teaching efficacy education. Informatization teaching efficacy was used as an indicator of the psychological state of teachers. This article analyzes relevant literature at home and abroad and determines the five dimensions that affect teachers’ informatization teaching efficacy in informatization teaching.
Cluster Barang Elektronik Mengguanakan Algoritma Fuzzy C-Means dengan Optimize Parameter Grid

Electronic products are goods that are really needed at this time, because electronic goods really help humans in carrying out various daily activities, such as television, computers, cellphones, etc. The problem is how to apply the Fuzzy C-means method with Optimize Parameter Grid in the form of grouping electronic goods data for the needs of consumers used, and how to determine the optimum number of clusters from the use of the method used in grouping electronic goods data sets to find the best accuracy value. The purpose of this study was to apply the use of the fuzzy c-means algorithm in the case of grouping electronic data and produce an output to find out the best value of the electronic data used. While this research uses one method, namely the fuzzy cmeans algorithm with Optimize grid parameters which are included in the grouping rules in data mining. The research results are expected to be able to find the best electronic data set grouping based on the Davies Bouldin Index value resulting from the analysis of the fuzzy c-means algorithm at measure_type : NumericalMeasure, Dbi = 0.516 and measure_type : MixedMeasure, Dbi = 0.627.