Reviewerly/exHarmony huggingface dataset:
Using cloud computing to increase authentication and security in an IoT-enabled cancer predicative model

Cloud computing, machine learning, the Internet of Things, deep learning, and artificial intelligence are used in a variety of areas, including healthcare, transportation, smart cities, and agriculture, to create beneficial results for a variety of challenges in today’s world. This paper focuses on one of these applications in the cloud computing and IoMT domains. Several sensors were implanted in the human body to gather patient-specific information, such as body measurements temp deviations, and many other factors that contribute to changes in blood cells that develop into malignant cells. The major goal of this project is to create a cancer prediction system that uses the IoT to extract information from blood results in order to determine whether they are normal or abnormal. Furthermore, the findings of cancer patients’ blood tests are encrypted and saved in the cloud for quick access by a doctor or healthcare worker through the Internet to handle patient data in a secure manner. The AES technique is used for encryption and decryption in order to offer authentication and security when dealing with cancer patients. Because all of the required cancer treatment information is stored on the cloud, the main focus is on properly handling healthcare data for patients while they are away from home. Using virtual machines, the work completion time is decreased from 450 to 170 min. Simulations are used to test the proposed model’s performance, and the results show that it outperforms alternative options significantly.
The Implementation of Directed Reading Thinking Activity (DRTA) Strategy in Teaching Reading Recount Text at SMAN 6 Medan

This research aims to find out how teachers implement DRTA strategy in teaching reading recount text for tenth grade at SMAN 6 Medan. To achieve the purpose of this study, the analyst utilized descriptive qualitative strategy. The data were amassed via observing the teaching and learning process of recount text, interview with English teacher, and video recording for how the implementation of DRTA strategy. The teacher has implemented 3 stages of using DRTA strategy in teaching reading recount text, Before Reading: predicting, While reading: silent reading, After reading: confirming predictions. But in the prediction stage, the teacher did not guide the students to activate their previous knowledge.
TATHBĪQU THARĪQAT AL TAQLĪD WA AL TAHFĪZ LI TARQIYAT HIFZ AL MUFRADᾹT AL THULLᾹB BI AL MADRASAH AL TSANᾹWIYAH AL HUKŪMIYAH 1 BATANG HARI JAMBI

&lt;em&gt;Using appropriate methods in the teaching and learning process can make it easier for teachers to convey the knowledge they have. The proper technique for learning vocabulary is mimicry and memorization. This method is used by teachers at MTSN 1 Batang Hari Jambi. the application of this method is combined with the use of image media. Therefore, this research aims to analyze the application of the mimicry and memorization method in vocabulary learning, with the aim of understanding the application of the mimicry and memorization method in vocabulary learning at MTSN 1 Batang Hari, the supporting and inhibiting factors, and the impact of its application. This research is qualitative research with a descriptive approach. The data in this research was collected using three techniques, namely observation, interviews, and documentation. The data was analyzed using the Miles and Huberman model. The results of this research show that the application of this method is carried out in several ways, namely: the teacher reads the vocabulary several times by pointing to the picture on the whiteboard, and the students are only asked to listen after the students can understand the language then the teacher rereads it and is followed by all the students, after The teacher asks several students to read and is followed by other students and the teacher slowly covers the vocabulary and pictures on the whiteboard until the students have memorized them. The application of this method is supported by several factors, namely competent teachers, student focus, student activities, and learning media. Apart from that, there are inhibiting factors, namely facilities and infrastructure, student competence, and interests. Applying this method has a positive impact on vocabulary mastery and learning motivation. However, it has a partial effect on student learning outcomes.&lt;/em&gt;
PERANCANGAN APLIKASI RESEP MASAKAN TRADISIONAL INDONESIA MENGGUNAKAN PENDEKATAN AGILE PROCESS DENGAN MODEL EXTREME PROGRAMMING BERBASIS ANDROID

Almost all aspects of human life have now been touched by tehnological advances, one of which is food recipes. In the past, when you wanted to learn food recipes, you had to go through magazines and newspaper. Then was a change, food recipes can be found on the website in the form of the text and images. Then it developed in to video broadcast on youtube, which can access via a computer or smartphone. This development in the culinery field is indeed very helpful, but it still has weaknees namely, the information contained on the websites and videos is only for one type of food, if you want to find another dish you have to search again, this method also requires quite a lot of time to find food recipes according to your wants and needs, and the food recipes you are looking for are easily lost and easily forgotten because they cannot be stored permanently. So that with the application Android-based tradisional Indonesian food recipes, it can be accsessed mobile by using a smartphone.So this is quite helpful for users to make it easier to find information about the materials needed to how make to make them. The approach used is an agile process approach with an extreme programming model, then the design uses UML (Unified Modeling Language). Keywords: Food Recipes, Android, Agile Process, Extreme Programming
Social Networks, Self-Esteem, Locus of Control, and Academic Performance in University Students From Ayacucho-Peru During the COVID-19 Pandemic

This research aimed to verify whether there is a relationship between the use of social networks, self-esteem, academic performance, and the locus of control in university students of Ayacucho in the year 2020. Data collection was by three validated questionnaires: Addiction to Social Networks (ARS), Rosenberg Self-esteem Scale (EAR), and Rotter’s Locus of Control Test. A questionnaire for general data and self-reporting of students’ weighted average achieved was also used. The statistic for non-parametric samples (ANOVA) was used in the statistical package SPSS version 2.7. The results showed a stronger relationship between the use of social networks and self-esteem, and a weaker relationship with the locus of control. Regarding academic performance, no relationship was demonstrated.
CLICK: Integrating Causal Inference and Commonsense Knowledge Incorporation for Counterfactual Story Generation

Counterfactual reasoning explores what could have happened if the circumstances were different from what actually occurred. As a crucial subtask, counterfactual story generation integrates counterfactual reasoning into the generative narrative chain, which requires the model to preserve minimal edits and ensure narrative consistency. Previous work prioritizes conflict detection as a first step, and then replaces conflicting content with appropriate words. However, these methods mainly face two challenging issues: (a) the causal relationship between story event sequences is not fully utilized in the conflict detection stage, leading to inaccurate conflict detection, and (b) the absence of proper planning in the content rewriting stage results in a lack of narrative consistency in the generated story ending. In this paper, we propose a novel counterfactual generation framework called CLICK based on causal inference in event sequences and commonsense knowledge incorporation. To address the first issue, we utilize the correlation between adjacent events in the story ending to iteratively calculate the contents from the original ending affected by the condition. The content with the original condition is then effectively prevented from carrying over into the new story ending, thereby avoiding causal conflict with the counterfactual conditions. Considering the second issue, we incorporate structural commonsense knowledge about counterfactual conditions, equipping the framework with comprehensive background information on the potential occurrence of counterfactual conditional events. Through leveraging a rich hierarchical data structure, CLICK gains the ability to establish a more coherent and plausible narrative trajectory for subsequent storytelling. Experimental results show that our model outperforms previous unsupervised state-of-the-art methods and achieves gains of 2.65 in BLEU, 4.42 in ENTScore, and 3.84 in HMean on the TIMETRAVEL dataset.
UNRAVELLING THE VISION OF PEACE AND UNITY A CRITICAL DISCOURSE ANALYSIS OF JOHN LENNON'S IMAGINE

This research investigates the iconic and timeless masterpiece song "Imagine" by John Lennon, seeking to unravel the profound messages and ideologies that lie beneath its evocative lyrics for peace, unity, and social change. The study employs Critical Discourse Analysis (CDA) by Teun A. van Dijk to conduct a comprehensive analysis of macrostructure, superstructure, and microstructure of the song. This research adopts a qualitative approach, utilizing content analysis and thematic analysis to explore the meanings and messages conveyed in the lyrics. Content analysis is employed to examine the explicit messages and themes presented in the song, while thematic analysis delves into the implicit meanings and underlying ideologies. This study finds that in the level of macrostructure, the vision of a utopian world free from religious, national, and materialistic barriers emerges as the central message, emphasizing the value and dignity of every individual. The superstructure analysis delves into the construction of the song's elements and their cohesive arrangement, highlighting its universal appeal and global consciousness to participate actively in creating positive change to build a better world. The microstructure analysis investigates the nuanced meanings conveyed by specific linguistic elements, such as rhetorical devices, lexical choices, emotive language, and direct address. Beyond its explicit messages, "Imagine" serves as a critique of societal constructs that perpetuate divisions and inequalities, challenging listeners to imagine alternative ways of organizing society based on compassion and shared humanity.
A CORRELATION BETWEEN STUDENTS’ MASTERY OF FUNCTIONAL GRAMMAR AND THEIR ACHIEVEMENT IN WRITING RECOUNT: A STUDY AT AN ISLAMIC BOARDING SCHOOL

This study explores the correlation between students' mastery of functional grammar and their achievement in writing recount texts, conducted within the context of an Islamic boarding school. The research aims to address two main questions: (1) How do male and female students perform in grammar learning and writing skills and (2) Is there a correlation between the mastery of functional grammar and students’ writing skills in junior high school. The study collected the data from eighth-grade students and categorized the results according to gender. The findings demonstrated that male and female students performed slightly differently in functional grammar tests and writing tests. The lowest functional grammar exam score for male students was 58, while it was 52 for female students. In contrast, the top scores for both genders were 97. In the writing assessment, similar differences were found, with male students scoring as low as 60 and female students scoring as low as 48. A group of both male and female students obtained the highest maximum score of 100. This research also investigates the relationship between students' functional grammar mastery and their ability to write factual recount texts. The estimated r-count value of 0.9487 was found to be significantly higher than the r-table value of 0.3550, r-count (0.9487) &gt; r-table (03550) using the Pearson product-moment correlation and a significance level of 0.05, showing a significant positive correlation. Hence, it can be concluded that the implementation of functional grammar has a significant influence in developing students' writing skills on factual recount text with the aim that they are not only able to arrange words into a paragraph, but also able to convey the ideas and meanings they express in their writing.
MaMiH: a new data assimilation framework based on macro-micro hierarchical simulation model

The widespread transmission of infectious diseases is a significant threat to human safety and development, and predicting epidemic trends is a pressing concern for scholars. Data assimilation methods can improve prediction accuracy by incorporating real observation data into system models. However, current data assimilation in epidemic models is limited to macro models, which fail to reflect individual heterogeneity realistically. Conversely, micro models have a high-dimensional parameter space, and the computational complexity of using data assimilation to adjust the state of each individual is high. To address this issue, this paper proposes a new data assimilation framework based on a macro-micro hierarchical simulation model called MaMiH. The MaMiH framework integrates the SEIR model as the macro model, reducing the computational complexity of the data assimilation process, and a complex network model as the micro model to simulate the infection status of each node within the network, thus reflecting individual heterogeneity. This paper verifies the effectiveness of the framework using the early stages of the COVID-19 pandemic as a research background.
Study on the Event Framework with the Headlines of Local English News Reports on COVID-19 Vaccine -Taking the WeChat official account DongguanToday as an example

The digitization of news media is greatly accelerated due to the impact of COVID-19. The dissemination of local English news on vaccination makes a great contribution to the effective implementation of national epidemic prevention and control for foreign nationals. As a practical means, it is necessary to study the English news of local WeChat official accounts during the epidemic period. News headlines are an important application of event framework in semantics. Through sorting out and analyzing event types, event elements, and event structures, this paper tries to understand the event framework of news headlines of the COVID-19 vaccine and how they convey media views, attitudes, and values. In sum, the event types under this theme are mainly existential events and relational events, and the most important event element is the participant. The event structure presents a progressive structure of the scene.
A bibliometrics analysis of multimedia forensics and deep learning research based on Scopus index

Forensics of digital data are concerned with identifying, acquiring, processing, analysing, and reporting on electronic data. Multimedia forensics focuses on investigating computer crimes using forensic methods. The analysis of multimedia evidence is the role of multimedia forensics, on the other hand. In the analysis, digital evidence is evaluated scientifically to maintain its integrity, to find its source, and to authenticate it. There are several methods in multimedia forensics, such as the implementation of deep learning. The purpose of this research is to conduct bibliometric analysis in multimedia forensics and deep learning by using the data gathered from Scopus index on the keyword “multimedia forensics and deep learning”. The result is 68 relevant papers were found in the range of 2017-2022. The results of this research can be used by researchers as a reference when conducting research and determining the research themes to be pursued.
Deep Learning for Small and Tiny Object Detection: A Survey

In recent years, thanks to the development of Deep Learning methods, there has been significant progress in object detection and other computer vision tasks. While generic object detection is becoming less of an issue for modern algorithms, with the Average Precision for medium and large objects in the COCO dataset approaching 70 and 80 percent, respectively, small object detection still remains an unsolved problem. Limited appearance information, blurring, and low signal-to-noise ratio cause state-of-the-art general detectors to fail when applied to small objects. Traditional feature extractors rely on downsampling, which can cause the smallest objects to disappear, and standard anchor assignment methods have proven to be less effective when used to detect low-pixel instances. In this work, we perform an exhaustive review of the literature related to small and tiny object detection. We aggregate the definitions of small and tiny objects, distinguish between small absolute and small relative sizes, and highlight their challenges. We comprehensively discuss datasets, metrics, and methods dedicated to small and tiny objects, and finally, we make a quantitative comparison on three publicly available datasets.
A Convolutional Neural Network (CNN) Classification Model for Web Page: A Tool for Improving Web Page Category Detection Accuracy

Game and Online Video Streaming are the most viewed web pages. Users who spend too much time on these types of web pages may suffer from internet addiction. Access to Game and Online Video Streaming web pages should be restricted to combat internet addiction. A tool is required to recognise the category of web pages based on the text content of the web pages. Due to the unavailability of a matrix representation that can handle long web page text content, this study employs a document representation known as word cloud image to visualise the words extracted from the text content web page after data pre-processing. The most popular words are shown in large size and appear in the centre of the word cloud image. The most common words are the words that appear frequently in the text content web page and are related to describing what the web page content is about. The Convolutional Neural Network (CNN) recognises the pattern of words presented in the core portions of the word cloud image to categorise the category to which the web page belongs. The proposed model for web page classification has been compared with the other web page classification models. It shows the good result that achieved an accuracy of 85.6%. It can be used as a tool that helps to make identifying the category of web pages more accurate
THE IMPLEMENTATION OF SOCIAL LEARNING STRATEGY FOR LEARNING ENGLISH FOREIGN LANGUAGE IN VOCATIONAL HIGH SCHOOL

This study aims to investigate students' perceptions of Sosial Learning Strategies in improving various English as a Foreign Language (EFL) language skills in SMK N 4 Semarang. A descriptive qualitative method was used with a questionnaire survey to collect data from 66 students of SMK N 4 Semarang who completed the 4 items of the Strategy Inventory for Language Learning (SILL) questionnaire and a Background Characteristics survey. The study's findings indicate that how English is used in practice affects how well it is learned. The findings showed a connection between using social strategies and effectively learning English. The most commonly used social strategies are “I review English lessons with my closest friends”.
Role of Traffic Police in Managing Traffic in Dhaka City: Challenges and The Ways Forward

The most controversial issue for Bangladesh in the recent decade is traffic congestion in Dhaka city. The problem of the city dwellers suffer most is traffic congestion which kills a huge amount of time, severely affecting both the normalcy of life and the pace of the economy. Effective traffic management largely depends on traffic police personnel. This study explores the challenges of traffic police and recommends policy action to tackle them. This study employs a qualitative methodology consisting of in-depth interviews and field observations to understand the challenges faced by Dhaka City traffic police officers. The study used a purposive sampling technique. The data was collected from both primary and secondary sources. Primary data was collected through the semi-structured interview method. All interviews were audio-recorded and transcribed line by before being subjected to thematic analysis. The study's findings reveal that traffic officials confront numerous obstacles, including health concerns, poor coordination, a lack of proper awareness of traffic rules among drivers and pedestrians, and inadequate training The study's findings would provide policymakers with essential guidelines for resolving traffic police concerns to protect the transportation system by controlling traffic.
EMPOWERING ENGLISH LANGUAGE LEARNING THROUGH SOCIAL LEARNING STRATEGIES IN VOCATIONAL SCHOOL

This study aims to investigate students' perceptions of Social Learning Strategy (SLS) in empowering various English as a Foreign Language (EFL) language skills in SMK N 6 Semarang. A descriptive qualitative method was used with a questionnaire survey to collect data from 35 students from SMK N 6 Semarang who completed the first nine items of the Strategy Inventory for Language Learning (SILL) questionnaire and a background characteristics survey. The study's findings indicate that how English is used in practice affects how well it is learned. The findings showed a connection between using social strategies and effectively learning English. The most commonly used social strategies are to mix Indonesian and English words if students do not know the English word or practice English with the English teacher and classmates.
Hubungan Antara Pengetahuan Lingkungan Terhadap Sikap Peduli Lingkungan Mahasiswa Pendidikan Geografi Universitas Khairun

This research is a correlation study that aims to determine the relationship between environmental knowledge and the formation of environmental care attitudes of students of Geography Education FKIP Khairun University. The population in this study amounted to 322 people with a sample of 76 people selected. Primary data collection in this study was through the provision of test questions related to environmental knowledge and environmental care attitudes, each of it had 30 question items. The data in this study were analyzed using the SPSS program by analyzing both descriptively through frequency distribution analysis and statistically through product moment correlation analysis. Based on the results of the descriptive analysis, it was found that most of the Geography Education students of Khairun University who became respondents had high environmental knowledge (75%), as well as their environmental care attitude was classified as good (96.05%). Meanwhile, based on the results of the product moment correlation analysis, a significance value of 0.000 was obtained, which was smaller than 0.05 (0.000 &lt; 0.05), which means that there is a significant relationship between environmental knowledge and the formation of environmental care attitudes for Geography Education students at Khairun University.