Reviewerly/exHarmony huggingface dataset:
High-order Table-based Conversion Algorithms and Masking Lattice-based Encryption

Masking is the main countermeasure against side-channel attacks on embedded devices. For cryptographic algorithms that combine Boolean and arithmetic masking, one must therefore convert between the two types of masking, without leaking additional information to the attacker. In this paper we describe a new high-order conversion algorithm between Boolean and arithmetic masking, based on table recomputation, and provably secure in the ISW probing model. We show that our technique is particularly efficient for masking structured LWE encryption schemes such as Kyber and Saber. In particular, for Kyber IND-CPA decryption, we obtain an order of magnitude improvement compared to existing techniques.
Asynchronous Learning: An Answer in the Era of Pandemic

The condition of the COVID19 pandemic has changed the habits of the world, including the education sector in Indonesia. For schools with strong economic strength, both students and educators will have no significant difficulties in implementing face-to-face online learning in a full manner (synchronous). On the other hand, there are many obstacles to implementing synchronous learning in schools with low economic abilities for both students and educators. One learning method that can be done with minimal barriers is asynchronous learning. Akademi Maritim Nusantara Cilacap and IAIN Syekh Nurjati Cirebon, both school have low economic strength, both students and lecturers. This study aims to see the benefits and problems that arise in applying asynchronous learning in Maritime English II of Akademi Maritim Nusantara Cilacap and English I of IAIN Syekh Nurjati Cirebon course. The researcher uses Google Classroom, YouTube, WhatsApp and Telegram media in lecture activities. The researcher then conducted a mini-survey to find out the advantages and obstacles experienced by students. The data is then explained using a qualitative descriptive method. The results showed at least 5 (five) advantages and 1 (one) weakness in asynchronous learning. The five benefits are material enrichment, access to learning materials, social interaction, personal interaction, and ease in discussing student work. Meanwhile, the constraints found were related to cost-effectiveness.
Into the unknown: Do people in low literacy rate areas practise digital reading?

Various initiatives have been taken to bridge the urban-rural digital divide in Malaysia, which has impacted the change of mindset among the rural community in terms of acceptance and assimilation of digital technologies in their daily life. This includes digital literacy-related activities for self-development, especially in cultivating reading habits. The main purpose of this study is to investigate digital reading practices among rural communities in low literacy rate areas in promoting reading culture in Malaysia under the 10-year National Reading Decade (DMK) 2021-2030 programme. A quantitative design of the study which involved 400 rural community respondents from 4 selected states in Malaysia (Kedah, Kelantan, Sarawak, and Sabah) using the multi-stage and mixed sampling method in administering the survey questionnaires. This study found that rural communities in low literacy rate areas in Malaysia did practice digital reading, primarily on smartphone. The empowerment of digital literacy in terms of digital reading practices is believed to be able to narrow down the digital divide among rural communities. The findings are expected to provide useful guidance for rural development in ICT and create better understanding and awareness among policymakers to create a rural society which is learned and well-informed through a more inclusive digital reading practices.
The Influence of the School Literacy Movement, Reading Interest, and Reading Materials on Reading Comprehension Skill of Class XI Students of MAN Bengkulu City Academic Year 2020/2021

This study aims to determine the influence of the School Literacy Movement, reading interest, and reading materials on reading comprehension skills. This study uses descriptive method and quantitative approach, and also multiple regression technique. The population in this study amounted to 278 students. The sample is 74 students taken by random sampling. Data collection technique used instruments in the form of questionnaires and tests. The data analysis technique used multiple regression. The results showed that there were (1) significant influence between School Literacy Movement on reading comprehension skill, (2) significant influence of reading interest on reading comprehension skill, (3) significant influence of reading material on reading comprehension skill. Thus, it can be concluded that there is a significant influence of the School Literacy Movement, reading interest, and reading materials simultaneously on reading comprehension skill.
Measuring User Satisfaction in Website Usability by Considering Stress Level

Usability testing, part of the human-computer interaction problem, is a method commonly used to evaluate the performance of a website interface. Today's study of human-computer interaction is important. It is now developed into UI UX (User Interface / User Experience). The website interface can affect user satisfaction and is a principal factor in a website being liked by users and meeting user needs. When a website is first developed, it can be difficult for a developer to understand the need for a website interface that matches the user persona of that website. Therefore, this research is important as an evaluation material for websites that are developed in the context of a website interface to provide a satisfactory appearance according to user personas. This study evaluates a website by conducting a usability test using the ISO-9241 aspect and getting an average result of 50,967, which is categorized as a bad website is taken from all users in the experiment. This study can also prove the psychological factors of users that influence usability testing, namely differences in the perceptions of website ratings between users with normal and (mild, moderate, severe, too severe) psychological stress levels. Users with normal stress levels will have better usability test results than users with stress levels. This study shows better results than user ratings with a normal stress level of 73,750, so it is categorized as a reliable website.
Methods for image noise level estimation

The article presents a method for estimating the level of discrete white noise in an image, based on the use of linear difference operators with a vector mask. Two variants of a new method for estimating the noise level are proposed, which differ in the accuracy of the obtained estimates and computational complexity. The first version of the method can be attributed to the class of block methods, whereas the second one is intended for the rapid image analysis and is based on processing a small number of rows or columns of an image.
GraphPlan: Story Generation by Planning with Event Graph

Story generation is a task that aims to automatically generate a meaningful story. This task is challenging because it requires high-level understanding of the semantic meaning of sentences and causality of story events. Naivesequence-to-sequence models generally fail to acquire such knowledge, as it is difficult to guarantee logical correctness in a text generation model without strategic planning. In this study, we focus on planning a sequence of events assisted by event graphs and use the events to guide the generator. Rather than using a sequence-to-sequence model to output a sequence, as in some existing works, we propose to generate an event sequence by walking on an event graph. The event graphs are built automatically based on the corpus. To evaluate the proposed approach, we incorporate human participation, both in event planning and story generation. Based on the largescale human annotation results, our proposed approach has been shown to provide more logically correct event sequences and stories compared with previous approaches.
Investigating Non-local Features for Neural Constituency Parsing

Thanks to the strong representation power of neural encoders, neural chart-based parsers have achieved highly competitive performance by using local features.Recently, it has been shown that non-local features in CRF structures lead to improvements.In this paper, we investigate injecting non-local features into the training process of a local span-based parser, by predicting constituent n-gram non-local patterns and ensuring consistency between non-local patterns and local constituents.Results show that our simple method gives better results than the self-attentive parser on both PTB and CTB.Besides, our method achieves state-of-the-art BERT-based performance on PTB (95.92 F1) and strong performance on CTB (92.31 F1).Our parser also achieves better or competitive performance in multilingual and zero-shot cross-domain settings compared with the baseline.
Creating Community Based Environmental Awareness with Social Media: A Kenyan perspective

One of the roles of community education is keeping citizens more informed on the need to conserve their environment. However, for this to be effective in the digital era, the use of modern communication tools is required to keep pace with current technological developments. One of these tools is social media, which is enormously popular and is used by both individuals and organisations for online communication. This paper analyses the role of social media in community-based organisations (CBOs) in creating environmental awareness through community education in Kenya. A non-probability sample comprising nine CBOs in Nakuru City was used to explore activities focused on environmental issues. Data were collected and analysed from a total of 98 respondents who participated in an online survey. It was concluded that the use of social media for environmental awareness in CBOs was minimal, but there is potential in its use as a social learning environment for creating environmental awareness. The study recommends capacity building and open online communication as a means of promoting the use of social media in creating environmental awareness through community education programmes.&#x0D; Keywords: environmental management, environmental awareness, community based organisation (CBO), community education, social media
Novel Algorithm for Agent Navigation Based on Intrinsic Motivation Due to Boredom

We propose a novel algorithm for the navigation of agents based on reinforcement learning, using boredomas an element of intrinsic motivation. Improvements obtained with the inclusion of this element over classicstrategies are shown through simulations. Boredom is modeled through a chaotic element that generates conditionsfor the creation of routes when the environment does not offer any reward, allowing prompting the robotto navigate. Our proposal seeks to avoid what classical algorithms suffer in scenarios without rewards, generatinglosses of time in the resolution. We demonstrate experimentally that by adding the element of boredomit is possible to generate routes in scenarios in which rewards do not exist, allowing the use of these strategiesin real circumstances and facilitating the robot's navigation towards its objective. The most important contributionsustained by this work corresponds to the fact that it is possible to improve navigation in completelyadverse scenarios for a navigation algorithm based on rewards.
Performance Analysis of Clear Sky Global Horizontal Irradiance Models: Simple Models Adapted for Local Conditions

Evaluation of the maximum solar energy potential of a given area for possible deployment of solar energy technologies requires assessment of clear sky solar irradiance for the region under consideration. Such localized assessment is critical for optimal sizing of the technology to be deployed in order to realize the anticipated output. As the measurements are not always available where they are needed, models may be used to estimate them. In this study, three different models were adapted for the geographical location of the area under study and used to estimate clear sky global horizontal irradiance (GHI) at three locations in the subtropical desert climate of Namibia. The three models, selected on the basis of input requirements, were used to compute clear sky GHI at Kokerboom, Arandis, and Auas. The models were validated and evaluated for performance using irradiance data measured at each of the sites for a period of three years by computing statistical parameters such as mean bias error (MBE), root mean square error (RMSE), and the coefficient of determination (R2), normalized MBE, and normalized RMSE. Comparative results between modelled and measured data showed that the models fit well the measured data, with normalized root mean square error values in the range 4–8%, while the R2 value was above 98% for the three models. The adapted models can thus be used to compute clear sky GHI at these study areas as well as in other regions with similar climatic conditions.
Multirobot Formation with Sensor Fusion-Based Localization in Unknown Environment

Multirobot cooperation enhancing the efficiency of numerous applications such as maintenance, rescue, inspection in cluttered unknown environments is the interesting topic recently. However, designing a formation strategy for multiple robots which enables the agents to follow the predefined master robot during navigation actions without a prebuilt map is challenging due to the uncertainties of self-localization and motion control. In this paper, we present a multirobot system to form the symmetrical patterns effectively within the unknown environment deployed randomly. To enable self-localization during group formatting, we propose the sensor fusion system leveraging sensor fusion from the ultrawideband-based positioning system, Inertial Measurement Unit orientation system, and wheel encoder to estimate robot locations precisely. Moreover, we propose a global path planning algorithm considering the kinematic of the robot’s action inside the workspace as a metric space. Experiments are conducted on a set of robots called Falcon with a conventional four-wheel skid steering schematic as a case study to validate our proposed path planning technique. The outcome of our trials shows that the proposed approach produces exact robot locations after sensor fusion with the feasible formation tracking of multiple robots system on the simulated and real-world experiments.
Deep learning techniques for physical abuse detection

&lt;span&gt;Physical abuse has become a societal problem. Mostly children, women and old age people are vulnerable to it especially in cases of domestic violence or workplace aggression. Reporting it is in itself a challenge especially if there is a pre-existing relationship between the abuser and victim. In this paper we propose a deep learning technique for human action recognition and human pose identification to tackle physical abuse by detecting it in real time. 3D convolution neural network (CNN) architecture is built using 3D convolution feature extractors which extract both temporal and spatial data in the video. With multiple convolution layer and subsampling layer, the input video has been converted into feature vector. Human pose estimation is done using the detection of key points on the body. Using these points and tracking them from one frame to another gives spatial-temporal features to feed into neural network (NN). We present metrics to measure the accuracies of such systems where real time reporting and fault tolerance capabilities are of utmost importance. Weighted metrics shows accuracy of about 89.42% with precision of about 85.82% and thus shows the effectiveness of the system.&lt;/span&gt;
English Teachers' Reflections and Lessons Learned in Language Teaching During COVID-19 Pandemic

This study seeks to find out the English teachers' reflections and lessons learned in language teaching during the pandemic. The method used was a guided narrative frame in which the teachers from the suburban wrote down their feelings and lived experiences. The data was analysed using thematic analysis and presented in themes. The findings indicate that the teachers found it challenging at the beginning of their online teaching. Both the teachers and students faced problems including economic situations, tech problems and mental struggles. Interestingly, this finding is similar to the outskirt teachers and students' problems. Besides, the teachers have learned the most vital things during their language teaching in the early year of the pandemic. They continuously shift their teaching strategies, provide personalised feedback to support the students' engagement, and become adaptable teacher-learners. Suggestions are provided for both teachers and policymakers.
STUDENTS’ MOTIVATION IN WRITING CLASS USING OF CANVA: STUDENTS’ PERCEPTION

This study aims to investigate students’ perception of using canva in writing class. This study used a qualitative descriptive approach and the research adapted questionnaire and also an interview to collect the data with ten students’ at Senior High School Bingin Teluk. The results of this study indicate that the use of Canva in the writing class has a positive impact on the participants. The positive impact is that Canva can increase students' motivation in writing classes, Canva can improve students' abilities in writing classes and Canva can also help students in writing classes. not only the positive impact that students have, but also obstacles in using Canva such as students having to have more time to design programs using Canva, and Canva has a premium account that we should pay for and there are some pictures which will appear and be provided without watermark.
Characteristics and Challenges of Low-Code Development: The Practitioners' Perspective

Background: In recent years, Low-code development (LCD) is growing rapidly, and Gartner and Forrester have predicted that the use of LCD is very promising. Giant companies, such as Microsoft, Mendix, and Outsystems have also launched their LCD platforms. Aim: In this work, we explored two popular online developer communities, Stack Overflow (SO) and Reddit, to provide insights on the characteristics and challenges of LCD from a practitioners' perspective. Method: We used two LCD related terms to search the relevant posts in SO and extracted 73 posts. Meanwhile, we explored three LCD related subreddits from Reddit and collected 228 posts. We extracted data from these posts and applied the Constant Comparison method to analyze the descriptions, benefits, and limitations and challenges of LCD. For platforms and programming languages used in LCD, implementation units in LCD, supporting technologies of LCD, types of applications developed by LCD, and domains that use LCD, we used descriptive statistics to analyze and present the results. Results: Our findings show that: (1) LCD may provide a graphical user interface for users to drag and drop with little or even no code; (2) the equipment of out-of-the-box units (e.g., APIs and components) in LCD platforms makes them easy to learn and use as well as speeds up the development; (3) LCD is particularly favored in the domains that have the need for automated processes and workflows; and (4) practitioners have conflicting views on the advantages and disadvantages of LCD. Conclusions: Our findings suggest that researchers should clearly define the terms when they refer to LCD, and developers should consider whether the characteristics of LCD are appropriate for their projects.
Towards Achieving Personal Privacy Protection and Data Security on Integrated E-Voting Model of Blockchain and Message Queue

The growing number of e-voting applications indicates the need in resolving issues that exist in the traditional election model. By integrating with blockchain technology, we could extend the model’s capabilities by presenting transparency in logic execution and integrity in data storage. Despite these advantages, blockchain brings in new challenges regarding system performance and data privacy. Due to distributed nature of blockchain, any new updating request needs to be reflected in all network’s peers before proceeding to the subsequence requests. This process produces delay and possibility in request rejection due to update conflict. In addition, data removal is no longer feasible since each record is protected by immutable hashed link. To overcome these limitations, the integration model of blockchain and message queue is proposed in this paper. The design addresses security concerns in data exchanging patterns, voter anonymization, and proof of system actor’s legitimacy. Performance tests are conducted on system prototypes which were deployed on two different settings. The result shows that the system can perform well in production environment, and introduction of message queue handling scheme can cope with blockchain’s errors in unexpected scenarios.
Development of Encyclopedia Media Based on Indonesian Cultural Diversity

Based on a survey of the Central Bureau of Statistics (BPS) conducted ( 2018) in 181 districts and 34 provinces involving 12,056 respondents found that 10% of respondents did not memorize Pancasila and only about 67-78% of respondents knew about the Unitary State of the Republic of Indonesia and Bhineka Tunggal Ika.Indonesia National Board for Disaster Management (BNPT) survey results in 2019 found that diversity education content has a low score compared to other dimensions.Education can be used as a preventive means of prevention of intolerant behaviors that are currently rife in Indonesia.The fading of the nation's cultural values among the younger generation due to the negative impact of globalization should certainly be a concern of many parties, including education.Diversity education has often been considered to interfere with the learning process in the classroom.Diversity materials can actually be integrated into materials taught in the classroom, especially in social science subjects.Problematic of learning that is still lacking in the variety of learning media and not contextual causes the material of Indonesian cultural diversity is not delivered optimally and students are not interested in learning it.Analysis conducted to teachers and students shows the need for learning media that can help teachers and students learn diversity.Researchers developed encyclopedia media as an alternative learning medium to study diversity, especially in the field of culture.This research is an Research and Development study using 4D models.The 4D development model consists of 4 main stages, namely: Define, Design, Develop and Disseminate.The media is validated by material experts and media experts to assess the feasibility of the media encyclopedia diversity, especially in the field of culture.This study examined the condition of geographic areas in each region, then identified various forms of culture.Furthermore, this study tries to explore everything about the ins and outs of philosophy or meaning and values of each existing culture.The results of this study are encyclopedia media based on Indonesian culture which includes geographical location, language, traditional house, traditional dance, traditional clothing, food, traditional tools and local traditions.