Reviewerly/exHarmony huggingface dataset:
Experience Analysis for the Use of Desafiate Serious Game for the Self-assessment of Students

In recent years, the development and use of serious games for the educational field has proliferated. One of the aspects linked to this phenomenon is the motivation achieved with the activities offered in them. On the other hand, there is another technology that has been growing for some time now, which are the Virtual Learning and Teaching Environments (VLTEs). These environments allow carrying out various activities and usually include self-assessment. In this article, we analyze the use of the serious mobile game Desafiate, aimed at student self-assessment and integrated into the IDEAS VLTE. The analysis is based on the intrinsic motivation achieved when using this game, compared to other methods used for self-assessment. Three contrasting groups are used for the analysis – one of them uses the serious game, another one uses pen and paper for their self-assessment, and the third one uses the IDEAS VTLE (and its assessment tool). As an instrument to measure intrinsic motivation, the Intrinsic Motivation Inventory (IMI) questionnaire is used. This questionnaire considers utility, perceived usefulness, pressure/tension, and effort during the activity as variables that affect motivation, among other factors that are not contemplated in this work. Results show that students value self-assessment as a useful activity, and they have shown greater interest in this process when working with Desafiate.
An adaptive cooperation with reinforcement learning for robot soccer games

A strategy system with self-improvement and self-learning abilities for robot soccer system has been developed in this study. This work focuses on the cooperation strategy for the task assignment and develops an adaptive cooperation method for this system. This method was inspired by reinforcement learning (RL) and game theory. The developed system includes two subsystems: the task assignment system and the RL system. The task assignment system assigns one of the four roles, Attacker, Helper, Defender, and Goalkeeper, to each separate robot with the same physical and mechanical conditions to achieve cooperation. The assigned role to robots considers the situation in the game field. Each role has its own behaviors and tasks. The RL helps the Helper and Defender to improve the ability of their policy selection on the real-time confrontation. The RL system can not only learn to figure up how Helper helps its teammates to form an attack or a defense type but also learn to stand a proper defensive strategy. Some experiments on FIRE simulator and standard platform have been demonstrated that the proposed method performs better than the competitors.
The Comparison of Data Mining Algorithms for Classification of Suggestions from Computer-Based Written Exam Participants

The Computer-Based Written Exam is a mandatory requirement for taking the State University Joint Entrance Test. As a form of implementation evaluation, each test participant is required to comment on the questionnaire given. The number of comments collected was 663 comments. Data processing used data mining methods. One form of utilization of data mining is classification. These comments were classified into 10 categories. This study compared the performance of classification algorithms based on parameter values of accuracy, precision, and recall. The classification algorithm compared was Naïve Bayes, Support Vector Machine (SVM), and Decision Tree. The SVM algorithm had better performance with an average value of accuracy, precision, and recall of 77.46%, 77.05%, and 74.65%.
Multi-party qutrit-state sharing under decoherence

Quantum state sharing plays an important role in both transmitting and protecting a quantum secret information. However, in a realistic situation, quantum communication protocol is inevitably affected by the decoherence and noise induced by the interaction between quantum system and environment, which often destroys quantum resource, such as degrading entangled state that is often used as the key resource of quantum communication. In this paper, we intend to investigate the influence of amplitude damping (AD) decoherence on multi-party qutrit-state sharing (MQSS) scheme. We firstly construct the noisy model of MQSS, and then analyze the effect of decoherence on the MQSS. In addition, the relation of variations between MQSS performance and quantum coherence is illustrated. Furthermore, we propose a partial measurement to enhance the performance of the MQSS under noisy environment.
Static Code Analyzer for Detecting Web Application Vulnerability Using Control Flow Graphs

Errors were made during software developments. In web applications, those errors could lead to security vulnerabilities that end in exploitation or information security incidents. Those errors will later be fixed by programmers, however. Since vulnerabilities repeatedly happened and are similar to each other, patterns of vulnerability can be found to detect vulnerabilities in later codes. Control flow graphs, as one of software execution representation, can be used as a representation to extract those patterns. In our approach, control flow graphs of vulnerable and fixed codes are constructed and compared to find their difference. By using the difference between vulnerable and fixed version's control flow graphs, subgraphs that lead to security vulnerabilities can be found. The subgraphs are generalized afterwards in order to eliminate code-specific functions or variables using predefined rules. The resulting subgraphs can then be used as a pattern to find security vulnerabilities in codes. After experimenting on how to compare the vulnerability pattern, comparing similarity values between the scanned codes to vulnerable and fixed models yields the best result with 46% accuracy and 50% recall with unoptimized graph generalization.
A Non-Connectionist Two-Stage Approach to Digit Recognition in the Presence of Noise

This paper introduces a two-stage approach to digit detection and recognition. The approach is cognitively-inspired to the extent that it integrates the dichotomy between the preattentive processing and the attentive processing that is present in the theories of human attention. It is non-connectionist to the extent that it does not require extensive training data, and thus may help in coping with the ever-present problem of lacking representative and balanced training corpora. The approach is demonstrated through a real-life case study of automatic electricity meter reading in the presence of noise.
A Heuristic Approach for Sensitive Pattern Hiding with Improved Data Quality

Frequent itemset mining can be used to discover various interesting patterns present in dataset. However, this imposes a great privacy threat when data is shared with other organisations. There are some business critical frequent patterns that are considered as sensitive from organization’s or individual’s perspective because revealing such patterns can disclose confidential information. Privacy preserving data mining (PPDM) provides various techniques to hide sensitive patterns to make sure that they cannot be revealed by applying data mining models on shared datasets. Heuristic based sensitive pattern hiding techniques are widely adopted PPDM techniques due to their fast execution time but causes high side effects. In this paper, we propose a heuristic approach for sensitive pattern hiding based on deletion of Victim items which is named MinMax. In the proposed algorithm, Misses Cost Impact (MCI) value of each tentative Victim item is calculated and item with minimum MCI is selected as Victim item resulting in low Misses Cost. Experimental results on benchmark datasets show that proposed algorithm achieves better data quality with less execution time as compared to existing heuristic based techniques.
Pseudo-random scalar multiplication based on group isomorphism

Elliptic curve cryptography is an essential cryptography which is widely used in data encryption, key agreement, digital signature, and other applications. Scalar multiplication is the fundamental operation in all ECC schemes, such as ECDSA, ECIES, and ECMQV. Even a slight improvement of scalar multiplication is precious. Various methods have been proposed for improving efficiency of the scalar multiplication, including the windows method, the NAF method, and the w-NAF method. However, the endeavour in this direction almost exhausted in the past several years since it is hard to find a method substantially better than the w-NAF method. This paper focuses on the scalar multiplication algorithm for the case when the scalar is a pseudo-random number. A faster pseudo-random scalar multiplication method is proposed based on a group isomorphism between the pseudo-random number group and elliptic curve point group. Experimental results show that the proposed method can considerably reduce the computation time compared with those traditional methods. The pseudo-random scalar multiplication accounts for a significant proportion of total scalar multiplication operations in almost all ECC schemes. Therefore, the proposed method is promising and applicable for various ECC applications in the fields such as Internet of things, edge computing, and swarm robotics.
Investigating Bubble Mechanism for Ray-Casting to Improve 3D Target Acquisition in Virtual Reality

Ray-casting, i.e., a ray cast from a hand-held controller to select targets, is widely used in 3D environments. Inspired by the bubble cursor [12] which dynamically resizes its selection range on 2D surfaces, we investigate a bubble mechanism for ray-casting in virtual reality. Bubble mechanism identifies the target nearest to the ray, with which users do not have to accurately shoot through the target. We first design the criterion of selection and the visual feedback of the bubble. We then conduct two experiments to evaluate ray-casting techniques with bubble mechanism in both simple and complicated 3D target acquisition tasks. Results show the bubble mechanism significantly improves ray-casting on both performance and preference, and our Bubble Ray technique with angular distance definition is competitive compared with other target acquisition techniques. We also discuss potential improvements to show more practical implementations of ray-casting with bubble mechanism.
Designing a Unity Game Using the Haptic Feedback Gloves, VMG 30 Plus

We present a Virtual Reality (VR) game that uses haptic feedback gloves VMG-30 Plus as the input device, which allows users to interact with the virtual environment through arm movements. In addition to increasing the user’s sense of immersion, games such as this would have the secondary benefits of promoting physical activity, as well as being an alternate form of entertainment. We also present a game mechanics developer framework allowing game developers to add glove technologies such as VMG-30 Plus to their games.
Evolved ensemble of detectors for gross error detection

In this study, we evolve an ensemble of detectors to check the presence of gross systematic errors on measurement data. We use the Fisher method to combine the output of different detectors and then test the hypothesis about the presence of gross errors based on the combined value. We further develop a detector selection approach in which a subset of detectors is selected for each sample. The selection is conducted by comparing the output of each detector to its associated selection threshold. The thresholds are obtained by minimizing the 0-1 loss function on training data using the Particle Swarm Optimization method. Experiments conducted on a simulated system confirm the advantages of ensemble and evolved ensemble approach.
The mechanism of credit transfers via the Blockchain

Subject. Money transfers via Blockchain-based banking and payment systems employ a procedure combining the traditional mechanism of gross settlements and P2P network, which is also run with the Blockchain. Therefore, the relationship between payment peers is mixed too. Objectives. The study aims to set up a legal mechanism of credit transfers which synergistically combines two payment procedures, i.e. traditional gross settlements via the national banking system and P2P payments based on the Blockchain. Methods. The study relies upon systemic-structural, dialectical, logic methods, induction, deduction, legal forecast, legal modeling and comparative method (legal comparison). Results. I examine how advantages of Blockchain-based payment systems and banking payment systems can be combined. This will streamline and smooth settlements, allowing to use the fiat currency in the beginning and at the end of credit transfers. The article highlights four phases of a mixed money transfer, i.e. the preliminary creation of a Blockchain-based node, accession to the protocol, opening of cryptocurrency accounts and e-wallets; the commencement of a money transfer under traditional rules of payment laws; interbanking settlements via the Blockchain and crediting of money under ordinary rules of the payment laws. Conclusions and Relevance. When credit transfers migrate from conventional bank accounts to the Blockchain, the fiat currency converts into the cryptocurrency and vice versa. I analyzed types of social relations emerging through the above phases and sources of legal regulations. The findings can be used in the theory of civil and banking laws, law making processes for the preparation of regulatory documents on cashless payments, and IT regulations.
Enhancing Proxy-Based Haptics in Virtual Reality

Rich haptic sensations in interactive virtual reality (VR) applications support immersive experiences. This position paper outlines my research efforts aiming to bring enhanced haptic interactions to VR users. Leveraging the highly realistic haptic feedback provided by real, physical proxy objects, I present two orthogonal research directions attempting to overcome the central drawbacks of conventional passive haptics. The first research direction leverages physical manipulations to enhance scalability through reusable yet low-complexity dynamic passive haptic proxy objects. Orthogonal to this, I explore hand redirection techniques in a second, more software-focused research direction based on virtual manipulations. In a concluding section, this position paper outlines how both approaches could be combined to further enhance haptics in VR.
Evaluation of Open Source Tools for Requirements Management

Requirements management is a critical task in any Software Engineering project. It implies both a technological defy and a complex social process. Engineering Requirements tools (ER) help speed up and optimize ER processes through a formal and systematical management of requirements, change management and traceability. In general, tools available for that use are proprietary software, costly and difficult to work with. Open source tools offer a great potential to cover these needs. This work aims to analyze open source requirements management tools to evaluate their capabilities and contribution for each step of the ER process. It includes a comparative analysis of their performance in three scenarios, representing different levels of software development organizations’ requests. Results show that development of open source requirements management tools is more oriented towards elicitation and requirements analysis phases than modeling.
Quantifying Empathy in Virtual Reality: An Outline

The purpose of this paper is to provide an outline of the research undertaken hitherto on quantifying empathy in virtual reality (VR). In this paper we have discussed various methodologies used for testing the impact on empathy vis-à-vis virtual reality, and then classified the end-results of the research in various categories such as the racial discrimination, ethnic and religious prejudice, the poor and the homeless, children who are differently-abled, war victims and disease induced typecasting. We have also proposed three niches which provide a framework to group various categories as aforementioned. The paper discusses how effectively virtual reality has addressed or contributed in alleviating biases or predispositions people have towards various stereotyped classes and how virtual reality has aided to empathize with the people impacted by the numerous difficulties. The paper also recommends how further research and various methods need to be integrated with the existing modus operandi to study the impact on empathy meticulously.
The Impact of Multi-sensory Stimuli on Confidence Levels for Perceptual-cognitive Tasks in VR

Supporting perceptual-cognitive tasks is an important part of our daily lives. We use rich, multi-sensory feedback through sight, sound, touch, smell, and taste to support better perceptual-cognitive things we do, such as sports, cooking, and searching for a location, and to increase our confidence in performing those tasks in daily life. Same with real life, the demand for perceptual-cognitive tasks exists in serious VR simulations such as surgical or safety training systems. However, in contrast to real life, VR simulations are typically limited to visual and auditory cues, while sometimes adding simple tactile feedback. This could make it difficult to make confident decisions in VR.In this paper, we investigate the effects of multi-sensory stimuli, namely visuals, audio, two types of tactile (floor vibration and wind), and smell in terms of the confidence levels on a location-matching task which requires a combination of perceptual and cognitive work inside a virtual environment. We also measured the level of presence when participants visited virtual places with different combinations of sensory feedback. Our results show that our multi-sensory VR system was superior to a typical VR system (vision and audio) in terms of the sense of presence and user preference. However, the subjective confidence levels were higher in the typical VR system.
A Systematic Mapping Study of Innovative Cloud Applications

Abstract Cloud computing is a business paradigm wherein computers and computing related services are provided by Cloud Service Providers to consumers either as software, development platform, or infrastructure. Innovative applications are growing in a productive manner on the cloud landscape. Innovative applications are being developed for use in the area of e-learning, automotive processes, cloud containers and machine learning. The objective of this paper is to conduct a systematic mapping study of innovative cloud applications and experiences. The systematic map provided a structured overview of research work carried out and the frequency of publications, presenting them pictorially in form of a map. The obtained results showed that 7.34% of the publications were on development of innovative cloud applications in terms of model. Architecture and modelling, and simulation in relation to model were both at 13.76%, 11.93% of the papers respectively, while 8.26% of the articles were on deployment in terms of process. Architecture had most publication in the area of solution research, with 15.2%. For articles published on deployment and development, most were on solution research with 8.80% and 14.40% respectively. The outcome of this study will be beneficial to practitioners in the industry and academic researchers alike.
Improving Job Recommendation Using Ontological Modeling and User Profiles

The recommendation system uses prior obtained information about the user to present user inteseted data. Personalized results aim to provide relevant information to the user based on the user's basic information or activity with the system. The user's basic information can be modeled into a user profile using ontology. Ontology is the systematic representation of various entities in a domain and the relationships between them. In this paper, we aim to present the conceptual model for a job recommendation system that uses ontology-based user profiles. The system collects basic information and models into a user profile. The dynamic aspects such as favorite jobs list and recently viewed jobs are then used as a source of data for the system. The recommendation algorithm works on the input given to present the list of relevant jobs to the user.
Interactive Case Practice Teaching on Mathematical Modelling Course

The design of one kind of interactive case practice teaching in a tertiary mathematical modelling course is outlined in this chapter. The process of interactive case creation and problem-solving between students and teacher is constructed with the aim of promoting students’ creativity, initiative, and interest in learning, as well as teaching efficiency. The interactive case practice teaching process has four stages: interactive case creation, subject activity, open learning, and feedback and evaluation. The students in these stages experience the whole teaching process including problem creation, problem analysis, problem-solving, and knowledge application. Finally, a case, the sensitive question survey, is used to demonstrate the interactive case teaching process in practice.
Effects of volumetric capture avatars on social presence in immersive virtual environments

Recent advances in 3D reconstruction and tracking technologies have made it possible to volumetrically capture human body and performance at real time. In the field of human-computer interaction, however, no works have been reported on the user study made with such volumetric capture avatars. This paper investigates how the volumetric capture avatar affects users' sense of social presence in immersive virtual environments. In our experiments, the volumetric capture avatar of an actor is compared with the actor captured in 2D video and another 3D avatar obtained by pre-scanning the actor. The experiment results show that users have the highest sense of social presence with the volumetric capture avatar when performing dynamic tasks whereas they have higher sense of social presence with the volumetric capture avatar and 2D video than with the pre-scanned avatar when performing static tasks. These imply that the emerging volumetric capture techniques can be an attractive tool for mixed reality, telepresence, and many other 3D applications.
Research and Application of Reservoir Safety Monitoring System for Intelligent Water Conservancy

Safety monitoring systems are an important part of intelligent water conservancy projects. Based on the overall scheme requirements of intelligent water conservancy in the new era, we analyzed the new requirements of the current safety monitoring system. Intelligent perception, infrastructure, data resources, intelligent analysis and application display of reservoir safety monitoring system under the background of intelligent water conservancy are described respectively. Combined with the exploration of the intelligent safety monitoring system of Hekou Village reservoir, the functions of the system are introduced for further improvement. References and suggestions are provided for the construction of safety monitoring systems for intelligent water conservancy projects.
Addressing Cyber Threats in Biology

This article provides a high-level, introductory description of the biological sciences and technology landscape to enable a more complete understanding of the digital-physical connections that may be vulnerable to cyberattack.
Modified Playback of Avatar Clip Sequences Based on Student Attention in Educational VR

We demonstrate a system that sequences teacher avatar clips considering student eye tracking. We are investigating subjective suitability of avatar responses to student misunderstandings or inattention. Three different avatar behaviors are demonstrated to allow a teacher pedagogical agent to behave more appropriately to student attention or distraction. An in-game mobile device provides an experiment control mechanism for 2 levels of distractions.