Reviewerly/exHarmony huggingface dataset:
Investigating EFL Pre-Service Teachers ability in Promoting Self-Regulated Reading in Reading Class

Reading is a systematic activity involving many strategies, such as cognitive and metacognitive. Self-regulated reading exists when participants use metacognitive strategies to govern the reading process, such as preparation, performance monitoring, and evaluation. As future teachers, EFL pre-service teachers must be able to teach self-regulated learning in their future classes since self-regulated learning is teachable and equips practical activities for class instruction. This study investigates pre-service teachers' abily to design activities that promote self-regulated reading in their lesson plan. This study uses a qualitative method with a case study design. There were about 10 EFL pre-service teachers who participated in this study. The data was taken from the lesson plan made by EFL Pre-service teachers. The data analysis results show that EFL pre-service teachers do not have adequate ability to design activities that cover all processes (personal, behavior, and environment) in promoting Self-regulated reading. Hopefully, the findings of this study will benefit the English Education Department, which is responsible for training programs for future English teachers.&#x0D;
Post Pandemic Public Acceptance Map Toward Ijen Geopark Using Aspect Based Sentiment Analysis Technique

Tourism is one of the sectors that has been seriously hit by the impact of the Covid-19 pandemic indicated by the sharp decrease in the number of both domestic and foreign tourists visit. The decrease has also been experienced by the popular tourist destination located in the border of Bondowoso and Banyuwangi Regency namely Ijen Geopark. Since the tourism sector has shown a significant role as a driver of economic activity, the aim of this work is to build public acceptance map toward Ijen Geopark as the government reduce the limitation of the prohibition policy to handle the spread of Covid-19. Sentiment analysis is adopted to build the public acceptance map by using TripAdvisor dataset. To gain a fine grained, results we extent the technique using our proposed aspect-based sentiment analysis making use cosine similarity algorithm and several keywords. Using several keywords and cosine similarity algorithm, we succesfully extract aspect of the topic. Employing Naïve Bayes, we then labeled the sentiment orientation of the associated aspect extracted from sentence. During 2022, we highlight the fact that most tourist positively accept Ijen Geopark. Some parts that need to be evaluated by the decision maker and related party is Sulfur Mining and the cost since both aspect received more negative comment compared to the positive ones.
An Analysis of EFL Students’ Digital Literacy Competence

In the modern era as it is today, technology is increasingly advanced and growing rapidly. Students must certainly have digital literacy skills in facing this fast-changing era. Digital literacy has a lot of coverage to which the students can use it as a media and learning resource. This research aimed to investigate the profile of the EFL students’ digital literacy competence. The research method used was case study with qualitative approach. The population in this study were the students of the English Education Study Program, Faculty of Teacher Training and Education, Universitas Muhammadiyah Cirebon in the 4th semester, totaling 21 people. The research sample taken were 12 people. The data were collected by using observation, digital literacy competence questionnaire, and unstructured interview. The result showed that in general the respondents were categorized as having good competence in the aspects of ICT literacy and media literacy. Meanwhile, in the aspect of information literacy the respondents were in the acceptable category. Furthermore, based on the results of data analysis of the interview results, it was found that even though they were good in the two aspects of digital literacy, and acceptable in competence of information literacy, they confessed that they tended not to practice the competence of ICT literacy in learning activities.
Design and Development Bineka: A Platformer 2D Game for Learning Indonesian Language

In this era, the usage of game-based language learning is common.This is caused by the habits of students who are curious about the existence of games in their daily lives.This study outlines the procedures and methodology for designing and developing 2D game platforms for Indonesian language instruction.The problem-defining, genre-designing, theme-designing, gameplay-designing, and game-functionality-testing phases of this game's development.During the early stages of development of a 2D platformer game for Indonesian language study, positive findings were obtained.
Real-Time Missing Data Estimation in Water Networks

Estimating missing data (e.g., pressure) in geographically distributed nodes is one of the fundamental challenges in a water distribution network (WDN). The Model-Based Kalman Filter is a simple solution that can estimate missing data in systems with a linear Gaussian state model. However, in large WDN, the state model is non-linear, and accurate system dynamics are unknown. Thus, we investigate the use of Data-Driven Kalman Filter (DDKF), in which the Recurrent Neural Network (RNN) updates the Kalman Gain. This data-driven approach has the potential to reduce approximation errors caused by the state model’s nonlinearity. As a result, this work demonstrates the application of a DDKF in a WDN. In addition, we demonstrate numerically that the DDKF can overcome approximation errors caused by flow equations and can estimate missing data in a WDN.
Influence of Belbin's Role on Database Design: An Exploratory Experiment

Software process has been studied from various perspectives, among them, the human factor is one of the most important due to the intrinsic social aspect of the discipline. This study aims to explore the benefits of using Belbin's role theory in tasks —team and individual— related to the software development process, particularly in Database Design (DB) Design. In this paper two controlled experiments with students are presented. In the first experiment integrated teams with compatible roles identified in the students and teams integrated through a traditional strategy were compared, during the task of DB conceptual design. In the second experiment, individual students were the experimental subjects, the performance of the Belbin roles identified in them were compared, in the task of the DB logical design. The dependent variables in both experiments were the effort in the task, and the quality of the generated design. Results in the first experiment did not show significant differences in both variables, a possible limitation was the complexity of the task. The second experiment also did not show significant differences in the effort variable; however, in the variable related to the quality of the logical design, the monitor-evaluator role presented significant differences when compared with the other six identified roles; these results are consistent with previous studies identified in the literature. We plan to continue experimenting with other tasks in order to get a deeper understanding of applying the Belbin’s theory in software process to accumulate experiences.
Aplikasi Pemakaian Gedung Pendopo dan Peminjaman Peralatan Pada Bagian Umum Kantor Walikota Dumai Berbasis Web

Providing excellent public services is the goal of every local government. The Dumai City Government is currently competing to implement and take advantage of advances in information technology to help create effective public services. With the lack of efficiency in borrowing the pavilion building and equipment in the general section of the Dumai Mayor's office, still using letter requests is the cause of this problem. Therefore, making this web-based application called the application for the use of the Pendopo Building and borrowing equipment at the general part of the Dumai Mayor's office was carried out as an effort to overcome this problem. This application development is based on PHP programming. This application provides various kinds of facilities for borrowing the building and the equipment that is therein.
An analysis of Sentiments of Tweets about Patents

Patents are documents about inventions that provide legal protection from which we can learn about technological development.Firms hold the monopoly of producing the relevant technology for a certain period of time, and in order to protect their technological superiority, they prepare the invention notification forms and complete their official applications to the patent office.The number of patents is a strong indicator of the R&D activities of a firm, country or region.For this reason, it is possible to write a large number of scientific articles that specifically analyze a technology or a region.Thus, what does society think of these official monopoly documents?One of the ways to find out what the society thinks about a subject is to follow the flow on the social media channel twitter.This study presents a partial analysis of what the public is talking about on twitter about patents.The tweets written in English, collected for a total of 2 months (106415 tweets), are subjected to a content analysis.When the hashtags of the tweets were examined, it was determined that the patents of some technologies (VR, crypto, blockchain, vaccine) were much trendy.In addition, sentiment analysis of tweet contents was also performed.It has been determined that while the emotional state is neutral in tweets about crypto patents, the average emotional intensity of tweets about vaccines is negative.In addition, it has been revealed through analyzes that these results differ according to countries and gender.
Network Forensics Against Address Resolution Protocol Spoofing Attacks Using Trigger, Acquire, Analysis, Report, Action Method

This study aims to obtain attack evidence and reconstruct commonly used address resolution protocol attacks as a first step to launch a moderately malicious attack. MiTM and DoS are the initiations of ARP spoofing attacks that are used as a follow-up attack from ARP spoofing. The impact is quite severe, ranging from data theft and denial of service to crippling network infrastructure systems. In this study, data collection was conducted by launching an test attack against a real network infrastructure involving 27 computers, one router, and four switches. This study uses a Mikrotik router by building a firewall to generate log files and uses the Tazmen Sniffer Protocol, which is sent to a syslog-ng computer in a different virtual domain in a local area network. The Trigger, Acquire, Analysis, Report, Action method is used in network forensic investigations by utilising Wireshark and network miners to analyze network traffic during attacks. The results of this network forensics obtain evidence that there have been eight attacks with detailed information on when there was an attack on the media access control address and internet protocol address, both from the attacker and the victim. However, attacks carried out with the KickThemOut tool can provide further information about the attacker’s details through a number of settings, in particular using the Gratuitous ARP and ICMP protocols.
COMPARATIVE ANALYSIS OF QUALITY OF SERVICE PERFORMANCE OF VIDEO STREAMING SERVICES USING OSPF AND EIGRP NETWORKS

In the era of globalization, computer networks are developing very rapidly and complex human needs make it possible to exchange information and communicate over long distances. In order for video streaming service providers from servers to be accessed by service users, it requires a process of sending data packets through a path called routing. OSPF is a routing protocol that applies network speed based on metrics to consider paths to other networks. EIGRP is a routing protocol that applies bandwidth and delay-based formulas to calculate metrics to determine routes. EIGRP is a type of Dynamic routing protocol. Throughput on OSPF and EIGRP differs depending on video quality. Jitter values on OSPF and EIGRP vary depending on the quality of the video used. There is a difference in the delay time experienced for each video quality when using OSPF and EIGRP. At all video quality levels, no packets are lost using either OSPF or EIGRP routing. OSPF and EIGRP performance is sufficient in sending video data. Throughput parameters, EIGRP has better performance than OSPF for all video qualities. However, for the jitter parameter, OSPF has better performance than EIGRP at 360p and 480p video quality. While on the delay parameter, both protocols have the same good performance. In the packet loss parameter, both protocols have the same performance without packet loss.
Implementing Privacy on Public Digital Displays Using Smart Glasses

The lack of privacy in public digital displays such as those used in Kiosks or Automated teller machines (ATM) is problematic for an individual's sensitive information. This paper proposes the utilization of smart glasses, cryptography, and augmented reality to implement privacy on public digital displays. Smart glasses have become increasingly popular and are becoming vital in the advancement in many visual technologies. Cryptography allows the transmission of secure data by applying services such as confidentiality, data integrity, authenticity, and non-repudiation. Augmented Reality enhances the physical world using digital, sound, or sensory stimulation. The paper prototypes the proposed privacy scheme through a use case that applies visual privacy on ATM displays and demonstrates that only the legitimate user will be able to observe sensitive information while preventing potential intruders from observing this information.
Keynote: AI for Scientific Discovery and a Sustainable Future

Artificial Intelligence (AI) is a rapidly advancing field.Novel machine learning methods combined with reasoning and search techniques have led us to reach new milestones: from computer vision, machine translation, and Go worldchampion level play, to self-driving cars. These ever-expanding AI capabilities open exciting avenues for advances in new domains. I will discuss our AI research for advancing scientific discovery for a sustainable future. In particular, I will talk about our research in a new interdisciplinary field, Computational Sustainability, which aims to develop computational models and methods to help balance the environmental, economic, and societal needs for a sustainable future. I will provide examples of computational sustainability problems, ranging from biodiversity conservation to multi-criteria strategic planning of hydropower dams in the Amazon basin and materials discovery for renewable energy materials. I will also highlight our work on AI to accelerate the discovery of new solar fuels materials. In this work, we propose an approach called Deep Reasoning Networks (DRNets), which requires only modest amounts of (unlabeled) data, in sharp contrast to standard deep learning approaches. DRNets reach superhuman performance for crystal-structure phase mapping, a core, long-standing challenge in materials science, enabling the discovery of solar-fuels materials. DRNets provide a general framework for integrating deep learning and reasoning for tackling challenging problems. Finally, I will highlight cross-cutting computational themes and challenges for AI
ANÁLISE DO COMPORTAMENTO DOS PEDESTRES ATRAVÉS DE UM ESTUDO NATURALÍSTICO E INFLUÊNCIA DA INFRAESTRUTURA

Observing the behavior of pedestrians during circulation and crossing through a naturalistic study brings notions about the vulnerability and the need to ensure their safety in the road system.Thus, the objective of this research is to evaluate relevant aspects related to pedestrian circulation and crossings in the urban environment, as well as the influence of the infrastructure.For this, an analysis of the behavior of 1 945 pedestrians was performed through a naturalistic study with car drivers in a region of Curitiba, and also a survey of the infrastructure to analyze its influence.The results of the study showed that among the pedestrians who cross the street in the middle of the street, 42.17% of them were less than 50 meters away from the closest crosswalk, and for pedestrians involved in some kind of secondary activity, 11.37% of the cases circulated in an inadequate place and 18.54% crossed the street incorrectly.Thus, through this study we can conclude that even in environments that provide all the necessary infrastructure and signs for the safe crossing and circulation of pedestrians, a portion still chooses to compromise their safety on the road system.
INTERPRETING THE PROVISIONS OF THE CYBERCRIMES ACT 19 OF 2020 IN THE CONTEXT OF CIVIL PROCEDURE: A FUTURE JOURNEY

It is accepted nowadays that cyberspace is used extensively to commit cybercrimes and cybersecurity offences. Victims of cybercrime can use civil procedure to institute claims for damages. Civil procedure is a branch of law that allows victims of cyberspace crimes to institute claims for damages. This article examines the impact of the Cybercrimes Act 19 of 2020 (Cybercrimes Act) on South African civil procedure. It appears that a contravention of the Cybercrimes Act may result in financial problems for the plaintiff, which then enables the latter to institute a civil claim against the defendants. The authors determine whether contravening the provisions of the Cybercrimes Act gives rise to a cause of action that permits the plaintiff to institute civil proceedings for damages suffered. While the Cybercrimes Act is lauded for its provisions addressing cybercrime, room for improvement is identified. Lastly, the authors conduct a comparative analysis between the provisions of the Cybercrimes Act and the Budapest Convention.
Project Guidance and Management System

Abstract: In the academic environment of today, students must do projects as part of their coursework in order to earn a degree, but they often do not know where to begin. Project Guidance and Management System is a web-based application designed to address this issue by enabling students to access and exposure to projects developed by their seniors and mentors. The system aims to serve as a reference tool for students and help them better understand the intricacies of a project. Students can discover from a project list and seek guidance from their mentors and contact developers. The Mentors can manage their students' project work and choose to accept or reject it, this acts as a check that only legitimate projects are uploaded on the portal providing authenticity. Users can enquire by asking queries and get replied to by the developer. There is an enquiry list which acts as a discussion forum
Probabilistic Matrix Completion

Collaborative filtering (CF) is typically a matrix completion (MC) problem where the unknown values of the rating matrix are predicted by finding similar rating patterns based on the given entries. The most common paradigm of MC is to factorize the rating matrix into two low-rank matrices. The basic matrix factorization (MF) and its extensions, i.e. conventional MF-based models, have achieved great success in the past and recently models based on deep learning have become popular. However, some recent works have pointed out that many newly proposed methods are outperformed by conventional MF-based models, which demonstrates the simplicity but effectiveness of the basic MF and its extensions. Finding the basic MF cannot be formulated by Probabilistic Matrix Factorization (PMF), this paper proposes a new model called Probabilistic Matrix Completion (PMC), which can interpret the basic MF from a probabilistic perspective. Unlike PMF, which samples each latent vector for each row in the rating matrix indiscriminately, PMC considers different sample frequency between rows (and columns) and computes the prior distribution based on the observed entries. To further demonstrate the difference between PMF and PMC, we incorporate geometric structure into PMC and finally get a model named GPMC that can outperform various state-of-the-art CF methods in terms of rating prediction. We validate our claims on six real-world datasets.
Language Driven Image Editing via Transformers

With the emergence of specifically tailored neural architectures that cope with both modalities, cross-modal language and image processing has attracted increasing attention. A major motivation has been the search for a quantum leap in language understanding supported by visual grounding, which has been oriented mostly to solve tasks where language descriptions of images are to be provided, and vice-versa, where images are to be generated on the basis of keywords. Adopting a distinct angle of inquiry, this paper addresses rather the cross-modal challenge of language driven image design, focusing on the task of editing an image on the basis of language instructions to modify it. And adopting as well a distinct research path, which dispenses with specifically tailored architectures, the approach proposed here resorts rather to a general purpose, suitably instantiated neural architecture of the Transformer class. Experimentation with this approach delivered very encouraging results, empirically demonstrating that this is an effective methodology for language driven image design and the basis for further advances in cross-modal processing and its applications with affordable compute and data.
Similarity-Driven Adaptive Prototypical Network for Class-incremental Few-shot Named Entity Recognition

Class-incremental Few-shot Named Entity Recognition (CFNER) aims to learn novel entity categories step by step and keep recognizing old classes simultaneously, in which only a few examples of novel classes are added at each incremental step. Many previous works have proved that decoupled two-phase (entity span detection and entity class discrimination) NER models are more suitable for handling CFNER. However, we find that in the second phase, discriminating entity spans has a large performance loss due to feature overlapping (i.e., samples of different categories appear relatively densely in the same region of the feature space). To solve this problem, we propose a Similarity-Driven Adaptive Prototypical Network (SDAPN) for enhancing current CFNER models. Specifically, we reserve a part of feature space for novel categories at the previous step and further mitigate the bias brought by anomalous samples according to the relative similarity of new samples and old class prototypes. Experimental results on two NER datasets show that our proposed approach significantly outperforms prior state-of-the-art approaches. A serial of analytical experiments is conducted to verify the effectiveness of our SDAPN model.