Reviewerly/exHarmony huggingface dataset:
The Basic Concept of Cyber Crime

Cyber Crime is a common phenomenon in the world. Cyber Crime is that group of activities made by the people by creating disturbance in network, stealing others important and private data, documents, hack bank details and accounts and transferring money to their own. Cyber Crime, especially through the Internet, has grown in importance as the computer has become central to commerce, entertainment, and government. Cyber crime, also called computer crime, the use of a computer as an instrument to further illegal ends, such as committing fraud, Trafficking in child pornography and intellectual property, stealing identities, or violating privacy. The cyber crime and they its impacts over the society in the form of economical disrupt, psychological disorder, threat to National defense etc. Restriction of cyber crimes is dependent on proper analysis of their behavior and understanding of their impacts over various levels of society. Now a day’s Cyber crime is increasing day by day. People have been greatly suffering for it. It is not only creates human suffering but also put effect on it. So Cyber Crime is one of the major crimes done by computer expert. This paper gives the basic concept of cyber crime.
Semantic Web Recommender System over Different Operating Platforms

Semantic-Web Recommender System (SWRS) evaluation over different operating systems (OSs) used to facilitate and improve human electronic recommendation management (HERM). The HERM is address the needs of user and dataset of movie in our proposed system through internetworking means which increase the speed of automated recommendation and enhance the goodness of SWRS and services also electronically to select right movies-title to user demand. Furthermore, it will be a benefit for selection a right favor by user for right selection from (i.e., 3000 records in dataset of movie-Lens) in the backend. There are a direct relation between time-consume of selection movie-title, also the time-consume, and accuracy. The two-mentioned parameters, namely, time-consume and accuracy over two different operation system (OSs) which designed by web technology Python. In our research, SWR system is proposed; it is provide with some recommendation methods. The system designed and improved using content-based algorithm (CBA). Investigational results indicate that the developed algorithm technique confident a reasonable performance such as accuracy and time consuming compared to other existing works with a testing average accuracy of 85.63 for windows and 88.35 for Linux operating system. In conclusion, SWRS investigated on two different operating platforms and could be seen that the Linux is faster than windows in accuracy and time consuming.
Pengaruh Penerapan Literasi Berbasis Web terhadap Peningkatan Minat Baca Peserta Didik Kelas V

In an all-digital era like today, the development of digital media and information technology poses challenges for users in accessing, selecting, and utilizing information from the times accompanied by digital developments which are expected to form a better increase in student learning. This study aims to determine the effect of implementing web-based literacy to increase students reading interest. This research uses quantitative methods with experimental research type, true experimental design. The results showed that there was an effect of implementing web-based literacy on increasing students reading interest, this was seen in the acquisition of a pretest score of 51.62 and an increase in the posttest score of 82.81 with a significant value of 0.000 &lt; 0.05. After experiencing changes, it is seen that there is an increase in students reading interest, the application of web-based literacy will greatly help the effectiveness of learning and can also help students access the internet in more useful ways
Miners' Reward Elasticity and Stability of Competing Proof-of-Work Cryptocurrencies

The efficient processing of payments is crucial in transaction systems, particularly in those reliant on key cryptocurrencies like Bitcoin (BTC). However, the decentralized nature of these systems, coupled with the algorithmic incentives and competition among multiple cryptocurrencies for miners, poses significant challenges in analyzing transaction speed determination in Proof-of-Work (PoW) cryptocurrencies. To address these challenges, we developed a dynamic model of the multicurrency mining market where miners switch which currency to mine and identified the necessary and sufficient conditions for competing cryptocurrencies to maintain stable transaction speeds. We documented evidence of competition among cryptocurrencies for miners and estimated miners' hash supply reward elasticity using a discontinuity caused by "halving". We also conducted counterfactual simulations to examine the factors contributing to stability. Our results indicate that Bitcoin's stability heavily relies on external factors such as historical low hash-supply elasticity and interactions with other cryptocurrencies. Interestingly, despite their smaller size, Bitcoin's forks and their efficient difficulty adjustments significantly contribute to Bitcoin's stability. These findings imply that an algorithm upgrade to stabilize Bitcoin is highly recommended.
Multivariate analysis of brain activity patterns as a tool to understand predictive processes in speech perception

Speech perception is heavily influenced by our expectations about what will be said. In this review, we discuss the potential of multivariate analysis as a tool to understand the neural mechanisms underlying predictive processes in speech perception. Multivariate pattern analysis might allow us to quantify the amount of information carried by the spatial or temporal patterns of brain activity ranging from the phonetic form of speech, over syllable identity to its semantic content. We suggest that using multivariate techniques to measuring informational content across the hierarchically organised speech-sensitive brain areas might enable us to specify the mechanisms by which prior knowledge and sensory speech signals are combined. Specifically, this approach might allow us to decode how different priors, e.g., about a speaker’s voice or about the topic of the current conversation, are represented at different processing stages and how thereupon the incoming speech signal is differently represented.
Thoughtless Intelligence

This is a commentary on G. Gigerenzer's "How to stay smart in a smart world." It follows up on a review of his book and Gigerenzer's reply to it. The central issue is whether AI may not only succeed in replicating (and surpassing) human performance but also whether it may attain a similarity in kind; that is is in what it is and not only in what it does.
Studi Kasus SDGs 4.4.1: Kemampuan ICT Mahasiswa Pendidikan Matematika dalam Mendesain Perangkat Pembelajaran 21st CLD

In this era of digital revolution, education is slowly being sought to use technology in its implementation. Besides the many products that are created to support the learning process, this of course needs to be in line with the capabilities of its users, namely students, educators and prospective educators. The ability to operate technology is needed so that educational technology products that are created are effective, especially to meet the learning needs of the 21st century. Therefore, the researcher intends to research with the aim of analyzing the ICT ability of Mathematics Education students at Sultan Ageng Tirtayasa University in designing learning devices that involve technology as one of the dimensions of 21st Century Learning Design (CLD). This study uses a qualitative descriptive method by distributing a test instrument about ICT knowledge and rating scale questionnaires. This study collects information from result of test insrument, questionnaires and various supporting literature that can be used as a basis for research. Based on this, it was found that the students' ICT abilities were on a good scale on average overall but there were still skills that didn’t reach the indicators.
Pelatihan Pembuatan Website Pembelajaran Menggunakan Google Site Learning Website Development Training Using Google Site

Working and studying from home is a demand that must be done at this time, since the Covid-19 pandemic due to the Corona virus. Schools were closed, teaching and learning activities were transferred online at home. Due to these demands, many teachers and parents are required to start adapting to distance learning activities, using technology. Bridging this, Google Indonesia launched the Teaching from Home initiative. Google provides a special website for teaching and learning activities for school students, in the Indonesian version. With this facility, anyone, including teachers, can create internal project hubs, team sites, publicly displayed sites, and more. Everything is done without the help of designers, programmers and IT. With the new Google Sites, creating a site is easy. This training is intended for teachers who are still not clear and looking confused how to create Google Sites to support distance learning between teachers and students to make it more interesting and fun.
The Development of Critical Thinking Skills in Mobile Learning: Fact-Checking and Getting Rid of Cognitive Distortions

The study aims to reveal the attitude of students and teachers to mobile learning; explore the possibility of developing critical thinking skills in mobile learning; and also evaluate knowledge after a short training course involving the use of mobile technologies in the context of the development of critical thinking. The research relies on an interview and a test. It was attended by 275 people (93 teachers and 182 students). The results showed that 58% of teachers and 55% of students believe that mobile learning does not contribute to the development of critical thinking. The test results showed that the study participants who pre-listened to the course of lectures on their mobile devices did not cope with the questions well enough, and cognitive errors were identified. The research has shown that improving the skills of interpreting, analyzing, evaluating and explaining information can increase the effectiveness of mobile learning. The research is a contribution to the study of various aspects of the impact of mobile learning on students and will be of interest to teachers, students, academic administration, parents, as well as to those who are interested in modern pedagogy and educational psychology.
Research on the Analysis of Correlation Factors of English Translation Ability Improvement Based on Deep Neural Network

This paper adopts the algorithm of the deep neural network to conduct in-depth research and analysis on the factors associated with the improvement of English translation ability. This study focuses on text complexity, adding discourse complexity features in addition to focusing on lexical and syntactic dimensions, exploring the application of neural network algorithm in the construction of text complexity grading model based on feature optimization, and examining the performance and generalization ability of the model. The rationality of the grading of the material is verified. After determining the model input features and training corpus, different classification algorithms were used to build the models and compare their performance. Meanwhile, compared with the models constructed based on common traditional readability formulas and other single-dimensional features, the models constructed based on the feature set of this study have significant advantages, with 20 to 30 percentage points higher in each performance evaluation index. The pseudo-parallel corpus is constructed, back translation is performed after obtaining the pseudo-parallel corpus, and finally, the data migration effect is measured and recorded on the low-resource Chinese-English parallel corpus and Tibetan-Chinese parallel corpus, and the cycle continues until the model performance is no longer improved. The low-resource neural machine translation model based on model migration learning improved 3.97 and 2.64 BLEU values in the low-resource English translation task, respectively, and reduced the training time; based on this, the data migration learning method further improved 2.26 and 2.52 BLEU values.
Digital Image Filtering with New Generalized Order-k Jacobsthal Numbers

In this paper, a new generalized order-k Jacobsthal and Jacobsthal–Lucas numbers are investigated and used in the digital image processing for filtering of the image. The Gaussian, Morphological operation with “Motion”, Morphological operation with “Disk” specification, Poisson method and Jacobsthal method is used for the filtering. The Structural similarity, Multiscale structural similarity and Peak SNR are used for evaluation of the results. For implementation of the proposed method the Matlab 2021a version is used.
MSMEs in Jatirasa, Bekasi: Design and Implementation of SAK-EMKM Financial Reports Using Microsoft Excel

In the last two years, there has been an increase in the number of MSME actors during the Covid-19 pandemic. However, MSMEs' development is not accompanied by knowledge of financial statement preparation. MSMEs face a number of challenges, including: a) a lack of knowledge about the preparation of accountable financial statements; and b) a lack of soft skills training about the accounting system. The proposed community service activities are expected to solve problems, such as: a) providing soft skills in the form of knowledge about financial reporting; and b) providing training on the preparation of financial statements using a computerized accounting system. The goals of this activity are as follows: a) increasing awareness of accountability for every transaction carried out in its business operations; and b) being consistent and sustainable in preparing financial statements for future business continuity.
Development of University Admission Based on Knowledge Management System

The study will develop a prototype to implement a knowledge management system using the information retrieval method. As a study case, the knowledge about university admission will be used. The users of the system consist of guests, admin, and admission staff. The guest can search for information in the dashboard and give suggestions. The admission staff can add new knowledge or modify the existing knowledge. The new knowledge should be verified and approved by the admin. The testing was performed to verify that the system works as it should be, especially for information searching. The results show that searchingusing lowercase and without stopword, or punctuation gives better similarity index. Searching using unigram also has better similarity index.
Designing of Registration System based on Estimated Patient Consultation Time for Crowded Prevention

Along with the increase in population and the development of information technology, it is necessary to have a system that is able to support the process of improving health care. One of the weaknesses of the current health care system is the patient waiting time which is still below the established standard, which is less than 60 minutes. This study designed a patient registration system that can estimate the patient's arrival time based on the input symptoms. The use of QR Code technology and meeting applications helps to support patient registration and consultation. The research methodology uses the waterfall method by involving doctors and patients as data sources. Test results using black boxes indicate that the system is able to categorize patient care as expected. The system has also been able to function well functionally. It takes a process of updating symptoms periodically by doctors so that the system is able to recognize new symptoms that have not been recorded previously. With the estimated arrival time, the queue or crowd of patients in the waiting room can be minimized properly.
HUBUNGAN TOTAL TES DENGAN RASIO POSITIF (POSITIVITY RATE) COVID-19

The Corona Virus That Causes COVID-19 Has Infected More Than 917,015 People In Indonesia And Continues To Increase, Especially Since The Signs Of The Pandemic Subside Have Not Yet Come To Light. In Addition To Vaccination For The Community To Create Herd Immunity, To Accelerate The Completion Of COVID-19 Cases In Indonesia, The Application Of The 3T (Testing, Tracing, Treatment) System Is Still One Solution In Overcoming The COVID-19 Pandemic. The Correct Application Of The 3T System Will Get Valid Data On The Number Of People Diagnosed With COVID-19 And Can Determine The Areas With A Lot Of Covid-19 Diagnoses. This Study Aims To Obtain Analytical Results That Confirm The Relationship Between The Number Of People Tested And A Decrease In The Positive Ratio Of COVID-19. The Method Used Is The Ordinary Least-Square (OLS) Panel Data Method Where This Method Is A Two-Dimensional Regression To Determine The Relationship Between The Dependent Variable And The Independent Variable. The Results Obtained Can Explain The Close Relationship Between The Number Of People Tested And The Positive Ratio, Where From The Estimation Results The Pooledols Value Gets A P-Value &lt;0.005 Or 2.76e-6, The Test Regression Coefficient Shows A Value Of -0.03493 And An R-Square Value Of 0.4306 Which Means That There Is A Negative Relationship Between The Number Of People Tested With A Positive Ratio And The Influence Of The Relationship Between The Two Variables Is Sufficient But Not Too Strong. From The Results, It Was Found That The More Number Of Tests Carried Out Will Be Able To Reduce The Exposure Of People Affected By COVID-19 Â Keywords:(Positivityrate),COVID-19,Total Tes
Hybrid Successive CFA Image Encryption-Watermarking Algorithm Based on the Quaternionic Wavelet Transform (QWT)

In this paper, we present a new robust hybrid algorithm combining successively chaotic encryption and blind watermarking of images based on the quaternionic wavelet transform (QWT) to ensure the secure transfer of digital data.The calculations of the different evaluation parameters have been performed in order to determine the robustness of our algorithm to certain attacks.The application of this hybrid algorithm on CFA (Color Filter Array) images, allowed us to guarantee the integrity of the digital data and to propose an autonomous transmission system.The results obtained after simulation of this successive hybrid algorithm of chaotic encryption and then blind watermarking are appreciated through the values of the evaluation parameters which are the peak signal-to-noise ratio (PSNR) and the correlation coefficient (CC), and by the visual observation of the extracted watermarks before and after attacks.The values of these parameters show that this successive hybrid algorithm is robust against some conventional attacks.
Key Information Extraction Algorithm of Different Types of Digital Archives for Cultural Operation and Management

In order to improve the effect of key information extraction from digital archives, a key information extraction algorithm for different types of digital archives is designed. Preprocess digital archive information, taking part of speech and marks as key information. Self-organizing feature mapping network is used to extract the key information features of digital archives, and the semantic similarity calculation results are obtained by combining the feature extraction results. Combine with mutual information collection, take that word with the highest mutual information value as the collection cent, traverse all keywords, and take the central word as the key information of digital archives to complete the extraction of key information. Experiments show that the recall rate of the algorithm ranges from 96% to 99%, the extraction accuracy of key information of digital archives is between 96 and 98%, and the average extraction time of key information of digital archives is 0.63 s. The practical application effect is good.
Research on Influencing Factors of Supply Chain Trust and Commitment Based on Transaction Cost and Social Exchange Theory

In the past, the literature often mentioned the relationship of trust and commitment, and believed that the lack of trust among supply chain members would lead to poor performance in transaction costs.Some studies believe that specific assets, behavioral uncertainty, and information sharing in the transaction cost theory have an impact on the trust level of supply chain partners.Other studies have pointed out the satisfaction of transaction partners and the reputation of partners in the market in social exchange theory.The degree and the cognition of both parties to the transaction will also affect the performance of the supply chain.This study attempts to integrate the above two theories and proposes an overall model of the factors affecting trust and commitment, and then uses the structural equation model (SEM) to carry out measurement models, structural models and the overall model is tested, and the research results indicate that the trust level is significantly related to the commitment level, while the manufacturer's investment in specific assets, the uncertainty of both parties' behavior, and the cognition level of both parties in the transaction in the theory of social exchange are all significantly related to the level of trust.Negative correlation; in transaction cost theory, partners' investment in special assets, information sharing, and social exchange theory, satisfaction with trading partners, trading partners' reputation and trust levels are significantly positively correlated, research results can provide supply chain management.As a reference, we will carry out partnership maintenance and management decision-making options.
Four-party quantum operation sharing with 7-qubit mixing state

<p indent="0mm">In this paper, a four-party quantum operation protocol is proposed using a 7-qubit mixing state, which originates from a 7-qubit Brown state due to a 2-qubit confusion. The security, determinacy, and sharer symmetry, as well as the experiment feasibility of the present protocol, are analyzed and discussed. Notably, the protocol is secure, a quantum operation can be shared by the sharer entity so that it can be successfully executed on a remote target qubit on one sharer’s side, two of the three sharers are symmetric as the reconstruction of the conceivable state is concerned, and the protocol is experimentally feasible in terms of the current technique. The present protocol is concisely compared with four 4-party quantum operation protocols, which are different from the employed quantum channel or the qubit distribution. The present protocol is the first to utilize the entangled mixing state as the quantum channel.
A Feature Based Approach on Automatic Stopword Detection

Abstract In information retrieval, words that contribute little to the semantic information within a text are called stopwords. Identification of stopwords is considered an asset for many retrieval tasks as removal of such words from the text collection increase the regularization within the dataset and reduce the volume and computational complexity. Traditional techniques for identification of stopwords either involve manual construction of stopword lists by analyzing terms individually or employing sorting-based techniques that uses global term characteristics as a proxy. Due to the context-dependant and non-precise definition of what really classifies as a stopword, transfer and application of these traditional methodologies to different languages or domains leaves room for generalized and interpretable results. To address this concern, we propose a feature based supervised machine learning technique for automatic detection of stopwords. We have tested the validity of the proposed technique with extensive experiments and compared the results with a general English stopword list. Furthermore, we have evaluated the proposed technique with both formal written and social media text. The results reveal that the proposed technique leads to promising results and is also capable of addressing the changes in the dialect.