Reviewerly/exHarmony huggingface dataset:
Student’s View on Hate Speech: Gamified Annotation for Educational Use

Online hate speech gains growing attention by educators and scientific researchers. Adolescents are highly active social media users and the majority of them experience or witness online hate speech. Therefore, educators are facing the challenge of how to handle the topic in an engaging and modern way. In prior work it has been shown that the understanding of hate speech varies depending on time, language, and topic. Another challenge is the small number of available data sets. This research addresses the problem of obtaining information to understand hate speech from the perspective of adolescents. Due to the difficulties of working with adolescents (e.g. data protection), it is challenging to create data sets for this specific subgroup. This research closes the gap by presenting a gamified annotation tool to be used in educational workshops within schools. Students are enabled to perform hate speech annotations in a controlled gamified environment. The gamified solution supplies schools with a live and realistic setting for a modern and motivational way to interact with the topic. This research demonstrates how to use the setting of educating students on the topic of hate speech in a safe space while understanding their perspective on hate speech.
What You Need is What You Get: Adapting Word Prediction of Augmentative and Alternative Communication Aids to Youth Language

This paper focuses on the development of prediction models for Augmentative and Alternative Communication (AAC) that are tailored specifically to child and young users. A new native-speaking corpus for child and adolescent languages is introduced, which allows the training of models that better fit the needs of this user category. The experiments conducted on real texts show that adapting the prediction models for children and young users leads to an improvement in keystroke savings, which in turn reduces the number of predicted words to be displayed. This opens up new possibilities for rethinking the virtual keyboard organization and interaction styles, with the aim of reducing cognitive load during text entry.
Detecting Minors According to South African Law Using Computer Vision Methods

Age estimation is one of the areas of interest in computer vision, which is evident from the increased amount of related research over the last few years. This is largely due to the exceptional levels of classification accuracy demonstrated by Convolutional Neural Networks (CNNs) in computer vision tasks. One of the main challenges faced when training age detection models are accounting for people's diversity, which raises the importance of using datasets with as much diversity as possible. Another important factor to consider is the reason behind performing age estimation, which can either classify people's age or detect if someone's age exceeds (or is below) a specific threshold. This paper presents work done to detect minors according to South African law (which is under 18 years of age). South Africa is a very diverse country. As such, the UTKFace dataset, containing face images with a wide range of ethnicities, was used to train the Inception Resnet V2 to detect minors according to South African Law. The dataset was reduced to only include relevant images with the aim of obtaining an equal distribution of gender and ethnicity to ensure relevance to the South African context. A model accuracy of 99.73% was achieved, demonstrating the model's ability to distinguish between underage and legal age classes. It was also noted that class imbalance and the reduced number of samples were inhibiting factors to the model's performance in terms of precision and recall.
Emotion Recognition via Facial Expressions to Improve Virtual Communication in Videoconferences

One of the most important things for successful projects is communication. Especially in agile software development face-to-face communication plays a central role. Face-to-face conversations are also one of the most direct and most emotional forms of human interaction. Facial expressions communicate emotions to others and can have a strong impact on conversations, perception, and decision-making. Due to the Covid-19 pandemic and digitalization more and more meetings and workshops take place virtually or hybrid. Many social cues and non-verbal signals are more difficult to share in a virtual set-up or are getting lost completely. Since face-to-face communication and facial expressions are so important for the success of a project and the perception of emotions, we are trying to find ways to bridge the gap of emotion recognition between on-site meetings and videoconferences. We are investigating, how software could support participants of videoconferences to improve virtual communications efficiently with empirical and qualitative research. In this paper, we present the results of two experimental user studies of facial expression recognition (FER) during videoconferences. In one study we did an analysis of emotion recognition after the meeting with a FER-tool, a human observer, and self-assessments of the participants. In another study, we visualized emotional states in real-time during a business meeting with the help of human observers and a simulation. We realized that both, humans, and the FER-tool, had difficulties to recognize emotions in specific situations and that there is room for improvement. In general, positive emotions were easier to identify than negative ones. Most participants were open to visualizing emotions and considered the information during a meeting as helpful, but also mentioned that it can be distracting. Therefore, a suitable form of emotion recognition and visualization which takes the productivity and wellbeing of the participants into account needs to be developed and evaluated.
Pilot Study on Interaction with Wide Area Motion Imagery Comparing Gaze Input and Mouse Input

Recent sensor development allows capturing Wide Area Motion Imagery (WAMI) covering several square kilometers including a vast number of tiny moving vehicles and persons. In this situation, human interactive image exploitation is exhaustive and requires support by automated image exploitation like multi-object tracking (MOT). MOT provides object detections supporting finding small moving objects; moreover, MOT provides object tracks supporting if an object has to be identified because of its moving behavior. As WAMI and MOT are current research topics, we aim to get first insight in interaction with both. We introduce an experimental system comprising typical system functions for image exploitation and for interaction with object detections and object tracks. The system provides two input concepts. One utilizes a computer mouse and a keyboard for system input. The other utilizes a remote eye-tracker and a keyboard; as in prior work, gaze-based selection of moving objects in Full Motion Video (FMV) appeared as an efficient and manually less stressful input alternative to mouse input. We introduce five task types that might occur in practical visual WAMI exploitation. In a pilot study (N = 12; all non-expert image analysts), we compare gaze input and mouse input for those five task types. The results show, that both input concepts allow similar user performance concerning error rates, completion time, and perceived workload (NASA-TLX). Most features of user satisfaction (ISO 9241-411 questionnaire) were rated similar as well, except general comfort being better for gaze input and eye fatigue being better for mouse input.
Investigating the Psychological Impact of Emotion Visualization and Heart Rate Sharing in Online Communication

In recent years, the integration of physical and cyber spaces has rapidly progressed. Sensing data from various sources is increasingly being fed back into physical space, and there are increasing cases of sensing and utilizing human biosignal information and emotions as well. This study investigates the psychological effects of visualizing and sharing people’s emotions and heart rate through two case studies. The first case study examines the psychological effects and usefulness of sharing others’ emotion and heart rate by displaying them beside he or she in physical space using a prototype of an augmented reality application called “Emo-Space”. The second case study proposes chat systems called “Emo-Circle” and “Heart-View” that allow for the visualization and sharing of emotions and heart rate and examines the effects of using the system on interpersonal relationships and self-awareness of emotions. We provide insights from the two case studies into that how such data of emotions and heart rate data indicating the physical and mental states of individuals can be applied to daily lives, including communication with others.
Research on Usability Evaluation of Online Exhibition Applications

The Covid-19 pandemic has caused people to stay at home, and online exhibitions have become a good alternative for people to enjoy arts remotely. To learn more about the user interface and user experience design, this research used three online exhibition applications (apps) (NTMOFA, NPM, A&C) to conducts task analysis, observation, and semi-structured interviews to develop exploratory research. Thirty participants were invited to take part in the experiment, and the time they spent finishing each task was regarded as the objective results; the SUS and NASA-TLX and interview responses were the subjective results. The results showed that the time performance of moving, watching, playing audio, searching and sharing functions of each app was significantly different with NPM and A&C, respectively for VR and AR online exhibitions, usually taking more time. Besides, participants thought that NPM is slightly more user-friendly than the other two apps; however, they preferred the AR online exhibition for its immersion experience. In the interviews, participants also indicated that some elements, such as social interaction and sensory experience, are expected to be added to online exhibition. To sum up, those elements which can create presence of visiting physical exhibitions and can interact with others are critical for the future design of online exhibition apps.
Designing for Wide Adoption: An Inexpensive and Accessible Extended Reality (XR) Device

With the increased adoption of Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), the question of how to make these technologies more accessible to more people becomes more relevant and urgent [1, 2]. HoloWorld is an Extended Reality (XR) accessory inspired by the illusion of Pepper’s Ghost [3]. Our prototype fits onto most tablets and smartphones, providing users with a digital experience that is more spatial and immersive than what a flat screen can provide. In order to find wide adoption, HoloWorld has been developed using a combination of the diegetic [4] and iterative design methods to deliver a few key features. For one, the product is easy to use. HoloWorld is portable and easy to configure with any smartphone. Similar to Google Cardboard [5], it uses a smartphone to provide power, connectivity, and source display. Additionally, the product is inexpensive. Great care has been given to the design of HoloWorld for manufacturability. The materials – corrugated plastic and acetate sheet – can easily be die cut, and produced for pennies on the dollar. Finally, HoloWorld is accessible and designed for broad adoption. The product can be easily branded and is an ideal vehicle for marketing campaigns. Because HoloWorld is inexpensive to produce, and it can be easily branded with content such as logos, QR codes, and demo videos, it presents itself as an ideal vehicle for businesses to reduce their customer acquisition costs.
Body-Centric Vibrotactile Display for Social Support During Public Speaking

The expression and impact of social support have been studied over the years in different fields. The purpose of this study is a preliminary exploration of how to mediate social support through touch remotely by using a vibrotactile device during a public presentation. With this study, we aim to explore (1) what are the patterns of expressing social support through touch during public speaking and (2) how can these patterns be mediated through technology. Through the User Enactment method, we identified common ways of providing social support and when to express physical support during the public speaking scenario. We gathered insights on the perceived meaning and overall experience of receiving vibrotactile feedback as a form of social support during public speaking.
A Study on the Students’ Understanding in Guessing Synonym Word at the Eighth Grade Students of SMP Negeri 2 Mandau

This paper entitled “A Study on the Students’ Understanding in Guessing Synonym Word of the Eighth Grade Students at SMP Negeri 2 Mandau”. The research is a descriptive research, intended to know students understanding in guessing synonym word of the eighth grade students at SMP Negeri 2 Mandau. The subject of this research is the eighth grade student of SMP Negeri 2 Mandau. The object of this research is the students understanding in guessing synonym word. The population of this research is the eighth grade student of SMP Negeri 2 Mandau. There is eight class of population. Total numbers of students are 320.The researcher uses the Simple Random Sampling. From eighth classes, the researcher takes two random classes as sample. The sample is class VIII.1 and VIII.2. Total of the sample is 80 students. The result of this research showed that students understanding in guessing synonym word of the eighth grade students at SMP Negeri 2 Mandau falls to good level. This can be seen on the results of the test conducted by the researcher. The researcher got the total score of the whole students is 5600. So, the average score of the students is 70. Based on the score above, students understanding in guessing synonym word of the eighth grade students at SMP Negeri 2 Mandau falls to good level.
LEGO and Low-fidelity Materials as prototyping Tools in Co-Creation Activities involving Multidisciplinary Participants

This study examines co-creation prototyping with LEGO and low-fidelity materials. 122 people from the fields of design, the pure sciences, forestry, and tourism are involved in this 6-hour co-creation program. The advantages of early design prototyping with LEGO and low-fidelity materials are examined in this study. LEGO and low-fidelity materials enable multidisciplinary participants to explore, analyse, and modify ideas in three dimensions, validating design solutions, idea formulation, and idea evaluation. It can be concluded that LEGO and low-fidelity materials are good co-design prototyping tools for team and strategy building because they motivate members to participate more during group discussions, manage design modifications, and demonstrate new design directions.
Designer Perception and Design Thinking in Industrial Ceramic Product Development

This paper discusses the methods used to conduct designer perception and design thinking in industrial ceramic product development. The designers themselves struggle to clarify how they make the association that immediately them to be the outcome and why those decisions are rational because the thinking behind design is not completely comprehended. This research attempt to identify product design development in critical design situations, empirically test the design thinking process towards industrial ceramic design processes and establish an innovative technique for capturing the ceramic designer’s thinking process. Exploiting a mix of aesthetics, ethics, and knowledge, design thinking is a contemplative longing to maneuver a new schematic in design development.
CREDIT SALES MANAGEMENT SYSTEM IN PT ANDALAN SEJAHTERA PEKANBARU

The Sanjaya shop is a shop that sells various kinds of machines such as pumps, diesel and many more. Sales of their PT Andalan Sejahtera Pekanbaru is one of the companies engaged in the sale of Spare Parts for Heavy Equipment, Machinery, Vehicles and so on. In addition to cash sales, credit sales are also applied. Transaction processing is carried out almost every day. In managing transaction data, especially for credit sales transactions, it is still done manually. Therefore, an application, namely General Ledger, is proposed to facilitate more effective sales transactions. The purpose of this study is to analyze the credit sales management system. The data collection method used was the observation method, by making direct observations on the object of research.
SISTEM PAKAR IDENTIFIKASI PSIKOPAT DENGAN METODE FORWARD CHAINING BERBASIS WEB

Psychopaths (Antisocial Personality Disorder) are mental disorders that can be used as a reference to create an expert system. The purpose of this research is to design and build an expert system to identify psychopaths with a web-based forward chaining method and to analyze and find out the symptoms of a psychopath in order to make sufferers and society feel at ease. The type of data used in this study is qualitative data which emphasizes the description of the process and words rather than the results such as the results of mathematical calculations or in the form of numbers. The author has several conclusions that expert systems can replace the role of experts who can provide suggestions or problem solutions to users, expert systems are often made using the PHP and MySQL programming languages, and the forward chaining method is suitable for use in web-based psychopath identification expert systems. This is because by asking questions first, conclusions can be drawn from the problem. The suggestions for the next researchers are the development of this software becomes practical for users, this web-based psychopath identification expert system can be created into android-based and an expert system in order to make it more and more practical because it relates to the cure of human soul.
Hindi-Handwritten-Character- Recognition using Deep Learning

Abstract: Hindi-Handwritten-Character- Recognition is animportant problem in the field of machine learning andcomputer vision. With the increasing digitization of India, there is a growing need to develop accurate and efficient algorithms for recognizing handwritten Hindi characters, which can be used in a variety of applications such as document analysis, postal automation, and data entry. In recent years, deep learning has emerged as a powerful tool for solving complex recognition problems. In this work, we propose a deep learning-based approach to the Hindi-Handwritten Character-Recognition. Specifically, we use a convolutional neural network (CNN) to extract features from the input images, and are current neural network (RNN) to model the temporal dependencies in the sequence of characters. Our approach is evaluated on a benchmark dataset of handwritten Hindi characters, achieving state-of- the-art results in terms of recognition accuracy. We also demonstrate the effectiveness of our approach on real-worldapplications, such as recognizing handwritten postal addresses on envelopes. Overall, our work provides a promising solution to the problem of Hindi-Hand-written- Character-Recognition, which can havea significant impact on the digitization of India and other similar regions.
As a solution during COVID-19, mandarin language learning system development to support HSK certification exams

The COVID-19 epidemic has prompted an increase in self-study; as a result, preparation for HSK Certification exams should also be stepped up. The Hanyu Shuiping Kaoshi (HSK) Exam can be taken either digitally or on paper. Students taking an exam through the internet are not limited by time or location when taking the test. The HSK test is designed to objectively and accurately assess a student's level of proficiency in Mandarin Chinese. Examinees' comprehension of the HSK exam's material and the quantity and quality of time spent working through sample HSK questions both play a role in whether or not they pass the exam. In order to help test takers prepare for the HSK, an online practice exam system is required. The primary goal of the online artificial HSK examination system is to allow prospective examinees to attempt to replicate the HSK test through the system and receive the same outcomes as the provisions of the genuine HSK exam. As one of the coordinators of the HSK exam in East Java, Nurul Jadid Probolinggo put this medium through its paces with a group of high school pupils. This article discusses issues of user approval of the program in addition to the analysis of its features
Best Practices to Implement and Pitfalls to Avoid in Cloud Application Security

This paper explores the importance of reevaluating the application security posture in the context of modern software development practices and the shift towards cloud computing. It highlights the challenges posed by the evolving threat landscape and emphasizes the need for a comprehensive and proactive security strategy. The paper also discusses various techniques and best practices for securing applications from the code level to the cloud environment, encompassing secure coding practices, and the effective utilization of cloud security services. By adopting a holistic approach to application security, organizations can mitigate risks and protect their applications and data throughout the software development lifecycle. Keywords: Application Security, Software Development, Cloud Computing, Secure Coding, Vulnerability Assessment, Penetration Testing, Cloud Security Services Proceedings Citation Format Oyitso, E.J. &amp; Ordia, E.D. (2023): Best Practices to Implement and Pitfalls to Avoid in Cloud Application Security. Proceedings of the Cyber Secure Nigeria Conference. Nigerian Army Resource Centre (NARC) Abuja, Nigeria. 11-12th July, 2023. Pp 41-48. https://cybersecurenigeria.org/conference-proceedings/volume-2-2023/ dx.doi.org/10.22624/AIMS/CSEAN-SMART2023P6
Internet of Things (IoT) Security and Private Concerns: An Overview

The number of Internet of Things (IoT) applications has greatly increased during the last two decades. Globally, more than half a billion electronic devices are connected. Due to their constant connection to the Internet, IoT applications are frequently targeted by a wide range of conventional threats, such as Trojan horses, worms, malware, spyware, and malicious code injections. It is apparent that traditional threats offer services like accountability, authorization, authentication, and these factors are typically used to identify a subject and determine whether the person is qualified to access the object. With the large numbers of connected devices, it is likely that IoT systems may become more vulnerable to threats and attacks with high-frequency electromagnetic radiation and more advanced viruses. Therefore, there is a pressing need to address these privacy and security concerns because it is insufficient to rely on currently used conventional procedures. This study identifies the knowledge and research gaps in this field by exploring the various dangers that IOT devices are vulnerable to, how these dangers operate and create a recovery mechanism to mitigate the harms. The study concludes by suggesting cutting-edge authentication methods like one-time password (OTP) ID- and password-based, three-factor/multi-factor and blockchain. Keywords: Architecture, Authentication, Internet of Things, Privacy, Security Proceedings Citation Format Mosud, Y. O., Ajulo, E.B. &amp; Yinusa, A.B. (2023): Internet of Things (IoT) Security and Private Concerns: An Overview. Proceedings of the Cyber Secure Nigeria Conference. Nigerian Army Resource Centre (NARC) Abuja, Nigeria. 11-12th July, 2023. Pp 49-58 https://cybersecurenigeria.org/conference-proceedings/volume-2-2023/ dx.doi.org/10.22624/AIMS/CSEAN-SMART2023P7