Reviewerly/exHarmony huggingface dataset:
Classification of Phishing Website Using Hybrid Machine Learning Techniques

The problem with cyber security involves scam websites, stilling the information that exploit people's trust. It could be reduced to the act of enticing internet users even though that they can get their personal data, including user names and passwords. In this study, we present a method for identifying phishing websites. The technology works as an add-on to a web browser, alerting the user when it finds a phishing website. A machine learning technique, specifically supervised learning is proposed in our study. The Logistic regression, Principal Component Analysis (PCA) and Apriori algorithms are chosen because of its success in classification. By examining the characteristics of phishing websites and selecting strongest combination of them, we developed a classifier that performs better.
How to automatically convert TikZ images to SVG (with fonts!) from knitr

&lt;i&gt; &lt;/i&gt; Update #1 An update to knitr has made it a ton easier to embed fonts in SVG files from R. Jump to the update to see how. &lt;i&gt; &lt;/i&gt; Update #2 Also, it’s possible to change TikZ fonts and not use Computer Modern for everything! Jump to the second update to see how.
DIN SPEC 91411: A standardized representation of magnetic scales

When it comes to scales for magnetic length and angle measurement systems, there has been no uniform terminology, no common drawing rulesneither for the mechanical nor for the magnetic parameters -and this has often led to misunderstandings or even errors in de-sign drawings.This primarily affects manufacturers of magnets, magnetic scales and sen-sors as well as machine or device manufacturers.A consortium consisting of a total of 13 companies and research institutions, mainly members of the Innovation Platform for Mag-netic Microsystems INNOMAG e. V., has now developed a DIN SPEC standard for the uni-form representation of magnetic measuring scales.
Mathematical contact tracing models for the COVID-19 pandemic: A systematic review of the literature (Preprint)

<sec> <title>BACKGROUND</title> Background Contact tracing (CT) is a primary means of controlling infectious diseases such as Coronavirus disease 2019, especially in the first months of the pandemic. </sec> <sec> <title>OBJECTIVE</title> This work is a systematic review of mathematical models used during the COVID-19 pandemic that explicitly parameterize CT as potential mitigator of the effects of pandemic. </sec> <sec> <title>METHODS</title> This review is registered in Prospero. A comprehensive literature research was conducted on PubMed, EMBASE, Cochrane library through CINAHL, and Scopus databases. Two reviewers independently screened the title/abstract, full text, data extraction, and risk of bias. Disagreements were solved through discussion. Characteristics of the study and mathematical models were collected from each study. </sec> <sec> <title>RESULTS</title> A total of 53 articles out of 2101 were included. The modeling of the COVID-19 pandemic was the main objective of 23 studies; the remaining articles evaluate the forecast transmission of COVID-19. Most studies used compartmental models to simulate COVID-19 transmission (26, 49.1%), while others used agent-based (16, 34%), branching processes (5, 9.4%), or other mathematical models (6). Most studies applying compartmental models consider CT in separate compartments. Quarantine and basic reproduction numbers were also considered in the models. The quality assessment scores ranged from 13 to 26 out of 28. </sec> <sec> <title>CONCLUSIONS</title> Conclusions Despite the significant heterogeneity in models and the assumptions on relevant model parameters, this systematic review provides a comprehensive overview of the models proposed to evaluate the COVID-19 pandemic, including nonpharmaceutical public health interventions such as CT. </sec> <sec> <title>CLINICALTRIAL</title> Prospero registration: CRD42022359060 </sec>
Advancing Privacy and Accuracy with Federated Learning and Homomorphic Encryption

&lt;p&gt;In this paper, we present an integrated framework that combines Federated Learning (FL) with Homomorphic Encryption (HE) using the Artificial Intelligence (AI) models and the Cheon-Kim-Kim-Song (CKKS) algorithm to address the challenges of privacy and accuracy. FL facilitates collaborative training of Convolutional Neural Network (CNN) and Multi-Layer Perceptron (MLP) models across decentralized devices, allowing for data privacy preservation without sharing raw data. The integration of the CKKS algorithm for HE ensures secure computation on encrypted data during the FL process. Our experimental results on three diverse datasets demonstrate the efficacy of this approach, achieving an impressive highest average accuracy of 97.3%. Additionally, the CKKS algorithm is used to achieve efficient computation, making it a promising solution for privacy-conscious machine learning applications, and paving the way for practical deployment in various real-world scenarios, thereby revolutionizing the landscape of privacy-preserving machine learning.&lt;/p&gt;
Generators and Relations for 3-Qubit Clifford+CS Operators

We give a presentation by generators and relations of the group of 3-qubit Clifford+CS operators.The proof roughly consists of two parts: (1) applying the Reidemeister-Schreier theorem recursively to an earlier result of ours; and (2) the simplification of thousands of relations into 17 relations.Both (1) and ( 2) have been formally verified in the proof assistant Agda.The Reidemeister-Schreier theorem gives a constructive method for computing a presentation of a sub-monoid given a presentation of the super-monoid.To achieve (2), we devise an almost-normal form for Clifford+CS operators.Along the way, we also identify several interesting structures within the Clifford+CS group.Specifically, we identify three different finite subgroups for whose elements we can give unique normal forms.We show that the 3-qubit Clifford+CS group, which is of course infinite, is the amalgamated product of these three finite subgroups.This result is analogous to the fact that the 1-qubit Clifford+T group is an amalgamated product of two finite subgroups.
DIaC Unleashed: Transforming Data Governance in AI/ML-Driven Banking

DIaC Unleashed: Transforming Data Governance in AI/ML-DrivenBanking
Problematika Peserta Didik dalam Operasi Hitung di Kelas 1 SD Negeri 80 Muara Bulian

Mathematics is widely used in various fields of life. However, in reality, activities for every individual cannot always run as they should, there will be some problems, even in learning mathematics. This situation is influenced by a person's comprehension of a lesson. Examples of problems in learning mathematics can be seen in the technique of adding derivatives, which is the result of dozens or tens or two-digit numbers (often called storing numbers), which results in incorrectly determining the results of further arithmetic operations. This research activity uses a qualitative approach. When referring to the problems studied, using qualitative methods makes it possible to gain an understanding of the reality on the ground. Based on the results of observations at SDN 80 Muara Bulian in class 1C in learning to count there were some students who wrote numbers from below which should have been from above so that they looked neat in writing and the prohibition on writing numbers starting from the early grades, so that later students could write numbers correctly. Correct. Learning withdrawal is an activity that is accompanied by symptoms that hinder achieving the desired goal, so efforts are needed to overcome these symptoms. Completion of learning is a disability or imperfection that causes a person to have difficulty carrying out learning activities so that the learning process becomes ineffective. Expansion of learning is a collection of various disorders that vary in manifestations, which are inability to listen, speak, read, write, think, and do arithmetic. Students with learning difficulties tend to have low interest and motivation in learning mathematics, this is shown by students who are not active during class learning, they tend not to want to ask questions when the teacher gives them the opportunity to ask questions. In addition, students are lazy to do exercises or assignments given by the teacher. Students who have difficulties are also often noisy in class and do not pay attention to the teacher's explanation.
Applicability of blockchain technology in the Sri Lankan construction industry

Construction is one of the most significant drivers of economic growth for any nation. In addition to contributing heavily to economic development, it is one of the world's biggest industries. The industry's productivity or effectiveness has often been in doubt whether the industry is productive or effective. To upgrade the standards of the construction industry, different digital tools and software have been introduced. Among numerous innovative technologies spreading across the construction industry, blockchain is emerging as a breakthrough in streamlining the structure and development of various processes. Therefore, this research tends to study how blockchain technology can improve the key performance indicators in the construction industry via various blockchain applications that can be utilized in the construction industry. The correlation and the impact between the applications of blockchain and the construction industry performance were analysed through statistical analysis via SPSS software. A qualitative expert opinion survey with ten construction experts who have experience in blockchain technology, selected through purposive sampling to collect data in Sri Lankan context, was conducted to collect suggestions and recommendations to implement blockchain in the Sri Lankan construction industry. The gathered data was analysed using the content analysis method. The barriers that Sri Lanka must overcome to adopt blockchain technology and the way to mitigate them were included in the study. How can Sri Lanka be prepared to adopt blockchain technology and what applications can be applied in the Sri Lankan construction industry were discussed in this study.
Using African Policy Data to Monitor trends in Public Policy

titled ' Using African Policy Data to Monitor trends in Public Policy', with an aim to illuminate on the untapped potential of African policy data which when harnessed effectively can serve as a guiding light for policymakers and governments to steer decisions towards impactful outcomes.The webinar's theme was broken down into the following key sub-topics:
AI-Powered Data Governance: Ensuring Integrity in Banking's Technological Frontier

AI-Powered Data Governance: Ensuring Integrity inBanking's Technological Frontier
The Application of Mindsponge Framework and 3D Framework in Explaining The Production Process of COVID-19 Vaccines Globally

Global citizens have widely discussed the COVID-19 outbreak since the World Health Organization (WHO) announced the disease as a public health emergency of international concern on January 30, 2020, and a pandemic on March 11, 2020 [1]. Since then, tremendous efforts have been made by scientists and health professionals to innovate the COVID-19 vaccines, which safeguard against the virus. It is helpful to conduct an in-depth conceptual investigation into the process of producing, administrating, and distributing COVID-19 vaccines. Vuong et al. [2] explained the COVID-19 vaccine production process by using the serendipity-mindsponge-3D (SM3D) creativity management theory. The mindsponge theory explains how the human mind processes information in contextual settings [3], while the 3D creativity management theory explains how creativity and innovations are made through information processes [2]. Conceptually, the mindsponge framework consists of five components: 1) mindset, 2) comfort zone, 3) multi-filtering system, 4) cultural and ideological setting, and 5) cultural values [4]. Meanwhile, the 3D framework consists of three major blocks: (1) the information absorbing and filtering block, (2) the creativity processing block, and (3) the innovation outcome block [5]. Based on the mindsponge framework [4] and the 3D framework [5], the COVID-19 vaccines production process was explained through three main stages, such as: 1) vaccine-related information absorption or rejection based on usefulness, 2) information usage for developing vaccines in a short period, and 3) vaccines production, distribution, and administration, finally in late 2020 [2]. These insights may be beneficial for facilitating the subsequent production, administration, and distribution of modified vaccines and vaccination campaigns.
AGGRESSION: A PROVE OF SUCCESSFUL SELF-CONTROL

The world has changed dramatically in the last two decades, many of which are related to aggression. Millions of people have had to move from their homes and livelihoods due to violent conflict, terrorist attacks, mass shootings, hate speech, etc. Aggression refers to severe forms of physical violence and considers all forms of social behavior that are carried out with the intention to harm another person or groups of persons [1]. Aggressive impulses manifest in violence. Typically, most people explain violence as the product of poor self-control. The dominant narrative also suggests that aggression starts when self-control stops. In the heat of the moment, the individual often fails to inhibit his worst, most aggressive impulses. Surprisingly, a recent study proved that it is not necessarily correct. Aggression, in fact, can also arise from successful self-control [2]. By analyzing various studies, Chester found that this ‘low self-control syndrome’ approach to aggression fails to accommodate the numerous findings in which aggression arises from successful self-control [2]. To name just a few examples are: 1) a profoundly fearful teenager summons the courage to fight their friend’s bully, 2) a soldier deftly employs their years of training to assail multiple military targets on a foreign battlefield despite their gnawing fears that the war is unjust, etc. This type of successful self-control aggression is absent from the available aggression literature nowadays. A balanced perspective between aggression arising from both successful and failed self-control is needed. If self-control failure can cause aggression [3], so does successful self-control [2].
The Usage of Mindsponge Theory for Explaining The Willingness of Global Citizens to Provide Geospatial Global Positioning System (GPS) Data From Their Smartphones During The COVID-19 Pandemic

Global citizens have widely discussed COVID-19 and its transmission prevention since the World Health Organization (WHO) announced the disease as a public health emergency of international concern on January 30, 2020, and a pandemic on March 11, 2020 [1]. The COVID-19 pandemic has highlighted the importance of digital epidemiology based on public health data [2]. In the early stages of the pandemic, public health officials faced critical problems in collecting effective information input from the public. Specifically, the issues around the donation of digital data related to the context of mobile phone privacy became a major roadblock in fighting the COVID-19 pandemic [3].Hswen et al. [3] evaluated people’s willingness to provide their smartphone geospatial global positioning system (GPS) data during the COVID-19 pandemic. This study involved 1055 participants from 41 countries with a mean age of 34. Findings showed that participants living in India or Brazil were more willing to provide their GPS data than those living in the United States. No significant differences were seen between positive and negative valence framing messages. Monetary incentives of $5 significantly increased participants’ willingness to provide GPS data. Half of the participants in the self-interest and pro-social arms agreed to provide their GPS data, and almost two-thirds of participants were willing to provide their data in exchange for $5. Framing and incentivization can be used in combination to influence the acquisition of private GPS smartphone data. Financial incentives can increase data provision to a greater degree with no losses on these intrinsic motivations to fight the COVID-19 pandemic. The study’s findings have the ability to contribute to lowering the social cost of epidemic control by informing evidence-based policymaking efficiently [4].
Comparative Analysis of Centralized and Federated Learning Techniques for Sensor Diagnosis Applied to Cooperative Localization for Multi-Robot Systems

Cooperation in multi-vehicle systems has gained great interest, as it has potential and requires proving safety conditions and integration. To localize themselves, vehicles observe the environment using sensors with various technologies, each prone to faults that can degrade the performance and reliability of the system. In this paper, we propose the coupling of model-based and data-driven techniques in diagnosis to produce a fault-tolerant cooperative localization solution. Consequently, prior knowledge can guide a discriminative model that learns from a labeled dataset of appropriately injected sensor faults to effectively identify and flag erroneous readings. Going further in security, we conduct a comparative study on learning techniques: centralized and federated. In centralized learning, fault indicators generated by model-based techniques from all vehicles are collected to train a single model, while federating the learning allows local models to be trained on each vehicle individually without sharing anything but the models to be aggregated. Logistic regression is used for learning where parameters are established prior to learning and contingent upon the input dimensionality. We evaluate the faults detection performance considering diverse fault scenarios, aiming to test the effectiveness of each and assess their performance in the context of sensor faults detection within a multi-vehicle system.
Awareness and Perception of Farmers and Dealers on Nano Urea in Gondia District of Maharashtra, India

This study investigates farmers' and traders' perceptions of nano urea in the Gondia district of Maharashtra. By providing accurate and long-lasting nutrient management, nano urea, a fertilizer based on nanotechnology, has the potential to revolutionize agriculture. Nearly 120 farmers and 50 merchants were polled as part of the study utilizing a multistage random sampling method. The findings showed that most farmers use nano urea in their fields and are aware of it. The adoption of nano urea by farmers was found to be highly correlated with education. Dealers were well aware of nano urea and eager to sell it since they recognized its benefits in terms of compatibility, storage capacity, and ease of use. However, some farmers voiced their displeasure with lesser paddy field yields and comprehension challenges. The paper discusses the difficulties in implementing and using nano urea in agriculture while highlighting its promise.
Experimental realization of free-space continuous-variable quantum key distribution based on fiber Sagnac interferometer

The Gaussian-modulated coherent state (GMCS) is a well-known continuous-variable quantum key distribution (CV-QKD) protocol that is robust to incoherent background noise and can effectively suppress ambient light in free space. However, it is difficult to implement this protocol in free space using existing polarization coding schemes. In this Letter, we propose a polarization coding structure based on a self-compensating fiber Sagnac interferometer, which can reduce the required modulation voltage by two orders of magnitude and achieve fast and arbitrary polarization modulation, and experimentally demonstrate polarization coding-based GMCS CV-QKD for, it is believed, the first time. The proposed polarization modulation structure, which uses off-the-shelf fiber components, is compact, simple, and suitable for mobile terminals, such as flying lifts.
Efficient Docker Image Optimization using Multi-Stage Builds and Nginx for Enhanced Application Deployment

Abstract As virtualization and EC2 instances have been widely used for running servers. However, they often consume significant resources due to their large size. The introduction of Docker as a containerization concept has revolutionized the way applications are deployed. Docker provides pre-installed environments packaged into images, allowing users to easily pull and run containers without the need for extensive local system configurations or dependency installations. One of the key advantages of Docker is its ability to optimize image sizes, which directly impacts resource utilization, deployment speed and overall efficiency. This research paper focuses on Docker image size optimization, specifically using the Angular framework as an example. Several techniques are explored including "Being lazy couch potatoes," which involves eliminating unnecessary dependencies, optimizing the parent image, and utilizing multi-stage builds. Additionally, the integration of Nginx as a reverse proxy is investigated to enhance application performance. The objective of this research is to evaluate these techniques and determine which approach effectively reduces Docker image size.
IMPLEMENTASI METODE DRILL DALAM PEMBELAJARAN PEMAHAMAN TEKS INFORMASI: STUDI KASUS PADA SISWA SMP MA’ARIF 5 PUCUK KABUPATEN LAMONGAN

Implementation of the Drill Method in Learning Information Text Comprehension: A Case Study of Students at SMP Ma'arif 5 Pucuk, Lamongan Regency. This study aims to determine the implementation of the use of the drill method as a support for learning reading comprehension of information texts for class VIII students of SMP Ma'arif 5 Pucuk Lamongan. This research is a case study. The research instruments are interviews, observation, and documentation. The results of the study showed that the use of the drill method had an effect on increasing students' grades on informational text reading material. These results can be seen from the students' assessment scores on literacy skills, which show the lowest proportion of students' scores at as much as 7.6%, while the highest proportion of students' scores is 92.3%.
PENGARUH METODE KARYAWISATA TERHADAP HASIL BELAJAR MENULIS TEKS PUISI

The Effect of the Field Trip Method on Students' Poetry Text Writing Learning Outcomes. This study aims to determine the effect of the field trip method on the learning outcomes of writing poetry texts for class VII students of SMPN 1 Turikale Maros. This research is an experiment with a sample of 32 students. Data collection techniques used by researchers in the form of tests in the form of pretests and posttests The collected data is then processed and analyzed using inferential statistical analysis and descriptive statistics. The research results show that the use of the field trip method has an effect on learning to write poetry texts. The field trip method can provide a stimulus for students to express ideas and ideas in writing poetry based on objects that are felt, seen, and heard.