Reviewerly/exHarmony huggingface dataset:
The Voice of ELT Students at Islamic College on Academic Life

Research shows that student voice might be an influencing factor in the future transformation and innovation of English language teaching (ELT). The voice has long been believed to be an instrument that could provide ELT practitioners and policymakers with meaningful feedback for the betterment of curricula, materials, and classroom practices. However, there are limited discussions exploring ELT student voice in such particular educational contexts as Islamic colleges. This article aims to contribute to our understanding of that rarely discussed voice with a particular focus on: (a) the students’ best experience as English education students at an Islamic college; (b) the students’ perceptions related to dress code and exams; and (3) the students’ self-assessment of English language skills. This study presents a survey study on 278 students in the English language education department at an Islamic college in Lampung province, Indonesia. The data are drawn from a survey consisting of open-ended questions distributed to the respondents at the end of the semester. Data analysis was conducted qualitatively, ranging from preparing and organizing the data to interpreting the meaning of the data in line with the research questions and theoretical review. The findings reveal that among the students' best experiences were the Islamic atmosphere, affordable tuition fees, religious education, professional lecturers, and scholarship availability. The majority of students agreed with the dress code regulation and had problems with cheating on the final examinations. The findings also show that more than half of the respondents are not sure about their English competency. This study offers important implications for English teacher education in Islamic educational contexts.
WEB-BASED SPP PAYMENT INFORMATION SYSTEM WITH MIDTRANS PAYMENT GATEWAY

ABSTRACT- The tuition payment system at Taufiq Islamic Middle School is still manually using ledger media in transaction activities and data recap. The system still needs to be revised and is prone to errors in calculating incoming payments and reporting payment data. This research was conducted to facilitate the school in the payment management process so that the recording error rate no longer occurs. The system development method used in this study is the Waterfall model and uses the Midtrans payment gateway in the online payment process. The results of this study are in the form of a tuition payment website that can facilitate all parties, both the school and students. This system makes the payment and recording process better and more efficient. Keywords: information system, waterfall, payment gateway, Midtrans.
Improving Students Reading Comprehension Through Probing-Prompting Technique At The Eighth Grade Of SMP Negeri 4 Pancarijang

The objective of the research are find out whether or not the use of Probing- Pompting Technique improves te students reading comprehension and student interest at the eighth grade of SMP Negeri 4 Pancarijang. His research employed pre- experimental method with on group pre-test and post-test design. The population was Theeighth grade student of SMP Negeri 4 Pancarijang in academic 2014-2015. Total number of population was 66 student consist of 3 classes and one class (VIII.2) was taken as sample by using cluster sampling techniquetotal of sample 20 students’. The research instrument are reading test an questionnaire. The result this research showed that the pre-test got the mean score (56.00) while the post-test goat mean score (69.00). This showed that there was significant difference between pretest and posttest. The result of the t-test value (5.378) was higher than t-table (2.093). This mean that H1was accepted. The researcher concluded that teaching reading comprehension by using probing-prompting increased the students’ ability in reading comprehension of SMP Negeri 4 Pancarijangand the mean score of the questionnaire was 84.75 categorized as a strongly interested. The researcher concluded that teaching reading comprehension by using probing-prompting improve the students’ ability in reading comprehension at the eighth grade SMP negei 4 Pancarijang
Research on Innovation Path of Dark Tourism Based on Micro-Niche market

The rapid development of the global Internet has caused a lot of unknown information about disputes and suffering to appear in media reports. The human being is not satisfied passively accepting these reports, and then turning to the consumption of this information. These "pathological curiosities" gave birth to the development of dark tourism. This not only increases the number of tourists to dark destinations but also brings more inspiration and education to tourists. This paper conducts market segmentation from the perspective of micro-niche market through the study of dark tourism history and literature. Based on recent product classification and innovation, speculate on the potential development direction of dark tourism in the future.
Power Apps

In the previous chapter, you learned how to customize forms using JSON formatting. In this chapter, we explore one of the most modern solutions for customizing list or library forms and creating interactive web parts. This approach does not require extensive coding.
Model View View-Model (MVVM)

We discussed the MVC design in the previous chapter and applied it to our Photo Stream example. To illustrate potential scaling challenges, we discussed adding a reactions component. To show navigation challenges, we linked our application to our coordinator example from earlier. In this chapter, we will apply a similar format to explain the MVVM pattern and apply it to our Photo Stream application while considering our architecture decisions from the previous chapter.
The Importance of Good Architecture

This chapter marks the start of Part 2 of this book. In the previous chapters, we discussed Swift and iOS ecosystem concepts critical for correct coding. Without those fundamentals, programs will not execute correctly. However, as a senior engineer working on a production application, it is not just about the code; there is also a need for a well-defined architecture. A well-defined architecture promotes easier modification, ease of testing, and better developer experience. In Part 2, we will discuss application architecture, starting with the components and building up to the overall application.
Concurrent Programming

Concurrent programming is essential to application development; it allows your iOS application to perform multiple operations simultaneously while allowing the user to interact with the application seemlessly. However, with great power comes great responsibility, as concurrent programming presents some of the most challenging aspects of application development. To mitigate some of the challenges when using concurrent programming, it is crucial to have a well-designed system that considers the fundamental concepts of concurrent programming and the capabilities of the iOS ecosystem.
Model View Controller (MVC)

In Chapter 6 , we discussed common foundational design patterns in iOS and how they help form the foundation of good architecture by helping you to structure your code and improve modularity and testability. In addition to the previously mentioned design patterns, there is a class of design patterns geared toward the iOS application layer design, application-wide design patterns. Application-wide design patterns address the application layer structure, how it is modularized, the control flow, and the data flow. This is the first chapter where we will address application-wide architecture patterns, and we will start with the most basic of them all, the model view controller (MVC) pattern.
Practical Example

This chapter is a culmination of the different parts in this book. We will outline the role of engineers at various levels to show their day-to-day activities and how they utilize specific skills to accomplish their jobs. We will see how very senior engineers (staff and principal) rely on communication, software architecture, and breadth of knowledge, while ground-team senior engineers rely more heavily on technical depth. In all cases, a certain amount of technical depth is required to ensure projects adhere to project goals, timelines, and budget constraints.
The Reactive Programming Paradigm

In Chapter 9 , we completed our tour of the data presentation layer (UI) architecture design patterns for iOS. In addition to data presentation design patterns, we covered broader iOS architecture design, including how to abstract our networking and local database code to a separate module and common design patterns to abstract code within modules. This chapter will cover a common approach for data flow across the entire application. In each architecture chapter (MVC, MVVM, and VIPER), we covered data flow at a high level and how to utilize it to manage the application's state more efficiently. One pattern we used to format and display our data was reactive programming. This chapter will cover the reactive data flow in more detail and explain how and why we have applied functional reactive programming in our applications using Combine.
Leading Multiple Teams

We have made it through quite a journey thus far. Now, we must discuss how to put together the different portions of this book (iOS fundamentals, software architecture, SDLC skills, and project leadership best practices) in the context of expectations and soft skills necessary for success. At engineering levels past senior, it takes more than just engineering chops to prioritize and execute projects especially over long periods where building up junior engineers and cultivating good relationships across the broader organization are essential.
Memory Management

Understanding memory management is key to developing programs that perform correctly and efficiently. This section dives into how computer memory is allocated and released for Swift programs, how the Swift memory model is structured, and best practices for memory management.
Enhancing investment opportunities through building institutional capacity in Tigray, evidence from Mekelle City

The study research design includes a mix of focused group discussion, and key informants interview. Moreover, the research applied the Multilateral Investment Guarantee Agency (MIGA) of the World Bank Group approach called global Enterprise Benchmarking Program (EBP). Local investors make up the largest group in the investments in Mekele City, implying a sense of sustainability. However, local investors are limited in terms of capital, knowledge, insufficient amount of credit and market linkages for which the regional government has to design a policy to supply finance, provide training and create market linkage forums. Nevertheless, a small number of foreign and Diasporas investors are also engaged in the city's investments. Other findings worth mentioning include a backward bureaucratic procedure, discrimination by officials on investors, and delayed decisions. The city administration should promote the city and the regional investment opportunities to attract Diasporas and foreign investors. The city administration and the regional government should also promote joint ventures between local and foreign investors as it helps technology and knowledge transfer and capital in-flow.
Leveraging Gametic Heredity in Oversampling Techniques to Handle Class Imbalance for Efficient Cyberthreat Detection in IIoT

In recent years Cyber-Physical Systems (CPS) and Industrial Internet of Things (IIoT) have gained significant attraction; however, it remains a vulnerable target for cyberattacks. Machine learning techniques have garnered interest in security applications due to their rapid processing capabilities and real-time predictions. However, imbalanced data distribution is a prevalent issue in IIoT environments, adversely affecting ML-based attack detection systems. In this work, we present a novel gametic heredity-based oversampling technique for addressing imbalanced data challenges in cybersecurity applications, specifically targeting IIoT systems. The proposed model enhances diversity in the minority classes by generating unique synthetic minority samples, creating diverse synthetic data while restricting instances to the minority class region. The proposed model outperforms complex and conventional methods in terms of precision, recall & F-Score while mitigating over-generalization by evenly distributing newly generated samples within minority class boundaries and regions. To validate the proposed model and verify its efficacy in identifying cyber threats, we used the UNSW-NB15 dataset. Simulation results demonstrate that the proposed model efficiently detects attacks with high performance compared to state-of-the-art techniques. Our research contributes to developing robust & efficient machine learning models for enhancing the security of IIoT systems while handling class imbalance issues.
An Offline Learning Approach to Propagator Models

We consider an offline learning problem for an agent who first estimates an unknown price impact kernel from a static dataset, and then designs strategies to liquidate a risky asset while creating transient price impact. We propose a novel approach for a nonparametric estimation of the propagator from a dataset containing correlated price trajectories, trading signals and metaorders. We quantify the accuracy of the estimated propagator using a metric which depends explicitly on the dataset. We show that a trader who tries to minimise her execution costs by using a greedy strategy purely based on the estimated propagator will encounter suboptimality due to so-called spurious correlation between the trading strategy and the estimator and due to intrinsic uncertainty resulting from a biased cost functional. By adopting an offline reinforcement learning approach, we introduce a pessimistic loss functional taking the uncertainty of the estimated propagator into account, with an optimiser which eliminates the spurious correlation, and derive an asymptotically optimal bound on the execution costs even without precise information on the true propagator. Numerical experiments are included to demonstrate the effectiveness of the proposed propagator estimator and the pessimistic trading strategy.
Prior Indicator Guided Anchor Learning for Multi-view Subspace Clustering

Despite multi-view subspace clustering (MVSC) has the widespread utilization in practical scenarios, the majority of existing methods face challenges when confronted with large-scale data. To address this issue, the anchor strategies have been proposed, but they mainly face the following problems: (1) most methods use heuristic anchor sampling results in weak discrimination of anchors, as it separates anchor sampling and graph construction; (2) the distribution of anchors within the cluster is uneven, and have low goodness-of-fit between anchors and raw data. To tackle the aforementioned issues effectively, we propose a method named Prior Indicator Guided Anchor Learning for Multi-view Subspace Clustering (PIAL). Specifically, PIAL proposes a unified framework, which can adaptively learn anchors and bipartite graph. Most importantly, PIAL introduces the prior indicator to constrain the bipartite graph learning. In this way, these two frameworks synergistically promote each other to acquire a high-quality anchor graph, such that more flexible and discriminant anchors can be obtained. Moreover, PIAL allows large-scale data to be processed in linear time, which is beneficial for large tasks. Experiments are carried out on several real-world benchmarks and compared with some state-of-the-art methods to verify the comparability and availability of PIAL.
Sharing Logistic Information Files Securely Using Cryptographic Algorithms AES and SHA

As technology advances, data security has become a significant concern when using the internet. Because of rapid development, there has been a rapid change in the logistics industry, making logistics more informational, and allowing for the development of new business strategies. However, several issues must be addressed, such as ransomware and phishing attacks during file sharing or on unsecured remote desktops. As a result, to provide authenticity, confidentiality, and transparency to logistic information during file sharing, we propose a scheme using the advanced encryption standard (AES or Rijndael), an algorithm for symmetric encryption that maintains the confidentiality of logistic information, and SHA-256 for authenticating the data. Therefore, this project proposes an effective way to secure file transferring in cloud using AES and SHA algorithms.
The role of English grammar in acquiring English in ESL/EFL situations

As Celce-Murcia and Larson-Freeman (1999) point out, the role of grammar is not to explain rules but to intuit them. Thus, this study investigates how we can intuit grammatical rules and teach them in ESL/EFL contexts. As a possible answer to this question, we derived the linguistic intuitions that native speakers are assumed to have on grammatical systems and represented them as semantic features. Specifically, we proposed [±abstract] and [±definite] for the article system, according to which nouns with the [+abstract] feature take the null article ∅, nouns with the [-definite] feature take the indefinite article a(n), and nouns with the [+definite] feature take the definite article the. We also proposed [±transfer] for the structure of dative verbs, on which if a dative verb has the [+transfer] feature, it licenses the sequence to+IO, and if it has the [-transfer] feature, it licenses the sequence for+IO. Finally, for infinitives/gerundives, we established [±pastivity] and [±actuality], which explains the linguistic sense that if a matrix verb has the [+futurity]/[-actuality] feature, it takes infinitives, and if it has the [+pastivity]/[+actuality] feature, it takes gerundives. This approach to intuitionizing grammar systems can provide insights into the desirable direction to grammar teaching in the AI era.
An analysis of effects on affective domain in level differentiated English classes

As a follow-up study for meta-analysis on cognitive domain (Park &amp; Yun, 2019), this study aims to investigate the overall effect on affective domain in level differentiated English classes. The procedure of meta-analysis consists of literature search with criteria for inclusion as well as data analysis including data coding and cleaning. After heterogeneity tests, random-effect model, subgroup analyses, and publication bias are conducted using Comprehensive Meta-Analysis software. Moderators used for subgroup analyses were; affective domains, schools, grades, and teaching methods and periods of level differentiated English classes. The results indicate that affective domain in level differentiated English classes had an overall mean effect size (d = 0.33) showing lower effect size than in cognitive domain (d = 0.74). More specific findings of meta-analysis are as follows: First, grouping factors based on affective domain had medium effects in confidence (d = 0.68), interest (d = 0.57) and participation (d = 0.51). Second, according to grade and to students in elementary school through university, the effects were larger with higher grade elementary school students and high school freshmen students. Third, among teaching methods, affective domain showed a large effect in extra supplementary classes. Lastly, the pedagogical implication and suggestions were further discussed.
An Educational Method for Creation of Animation Story Using AI through Self-Directed Learning

In this study, the possibility of an animation story education method using AI was identified. First, as a theoretical background, we identified Keller's ARCS theory, animation story creation and education methods, self-directed learning, and generative AI as a learning motivation design model. Additionally, a new method of creating animation stories using generative AI was proposed. In the experiment, 40 subjects were divided into 20 groups of two each, and one person was randomly selected and divided into a control group and an experimental group to conduct a comparative experiment. And the results were verified with t-test. Based on Keller's ARCS theory, a learning motivation theory, through the concepts of attention and relevance, the number of instructors' instruction was used as the main parameter. The experimental results extracted valid results using AI for 12 groups and invalid results for 8 groups. The results of the study showed that the number of teachers' guidance in the traditional method, which was the comparison group, was high, and in the experimental group using AI, it was relatively low. Therefore, we proposed a new creation method that reduces teacher intervention by integrating animation story, teaching method, and AI use in the animation story creation education method, and secured its possibility.
Effective movie recommendation based on improved densenet model

In recent times, recommendation systems provide suggestions for users by means of songs, products, movies, books, etc. based on a database. Usually, the movie recommendation system predicts the movies liked by the user based on attributes present in the database. The movie recommendation system is one of the widespread, useful and efficient applications for individuals in watching movies with minimal decision time. Several attempts are made by the researchers in resolving these problems like purchasing books, watching movies, etc. through developing a recommendation system. The majority of recommendation systems fail in addressing data sparsity, cold start issues, and malicious attacks. To overcome the above-stated problems, a new movie recommendation system is developed in this manuscript. Initially, the input data is acquired from Movielens 1M, Movielens 100K, Yahoo Y-10-10, and Yahoo Y-20-20 databases. Next, the data are rescaled using a min-max normalization technique that helps in handling the outlier efficiently. At last, the denoised data are fed to the improved DenseNet model for a relevant movie recommendation, where the developed model includes a weighting factor and class-balanced loss function for better handling of overfitting risk. Then, the experimental result indicates that the improved DenseNet model almost reduced by 5 to 10% of error values, and improved by around 2% of f-measure, precision, and recall values related to the conventional models on the Movielens 1M, Movielens 100K, Yahoo Y-10-10, and Yahoo Y-20-20 databases.
Analysis of a new approach in education: Smart education

In this article, educational platforms have been studied and analyzed, including the adaptive implementation of the educational process, which is possible through the use of SMART educational technologies, the implementation of the SMART educational paradigm is educational and is aimed at shaping the educational process, as well as opinions and comments on SMART which makes it possible to use the global information society to meet educational needs and interests.