Miracle-dz/UniFAR-FTUs huggingface dataset:
The psychological reality of procedural rhetoric

Game scholars make arguments that depend on the idea that games are capable of conveying meaning and making arguments via their mechanics, an information channel unique to games (and other forms of system-driven media) which Bogost has termed "procedural rhetoric. " This concept is not intended to just be an interpretive technique for experts, but is also meant to describe the way the general player population experiences games. However, there has never (to our knowledge) been any attempt to use the tools of psychology to ascertain whether procedural rhetoric is a psychological reality for players in general and, if so, under what circumstances and in which ways it is experienced. This paper reports on the first steps in such an investigation. We found (a) that procedural rhetoric has psychological reality, with players accurately understanding that two games meant to have arguments have them, and the purely abstract game we included did not; (b) the understanding of procedural rhetoric appears to be strongly shaped by accompanying media, with the more abstract of the rhetorical games we studied much less clearly understood; and (c) as with any media, even when audiences understand the goal of a procedural rhetoric argument, the impact on their thoughts and feelings may not be as authors intend.
Simulating Clinical Guidelines for Medical Education

Education is notoriously a challenging task in the healthcare context, where several new methodologies are being introduced to complement "traditional" learning. In particular, the importance of approaches based on (i) simulation and on (ii) clinical practice guidelines is continuously growing. While until now such approaches have been developed separately, in this paper we propose the first approach to education in medicine exploiting both techniques (i) and (ii). Indeed, clinical practice guidelines encode the best medical practices, and, in conjunction with simulation techniques, are suitable to teach "how to operate" on patients, but without the need of "physically" having\acting on real patients. In this paper, we propose such a new methodology, based on GLARE-Edu, an educational extension of GLARE (Guideline Acquisition, Representation and Execution), a domain-independent system for the management of GLs. GLARE-Edu can be used to "simulate" the direct application of GL "best practices" to a (simulated) patient or to provide a "second opinion" simulation: a student must indicate how s\he would treat a (real or invented) patient, and the system is used to indicate to the student where s\he has followed the recommendations of the GL, and where s\he has violated them.
Red or blue pill: fostering identification and transportation through dialogue choices in RPGs

Through free choice, individuals can exert control over the environment and experience agency. Research has suggested that tailoring aspects of choice to a player's type can provide benefits; however, commercial Role Playing Games (RPGs) generally provide static opposing options from a spectrum (e.g., paragon versus renegade). To inform the design of choices in RPGs, we conducted three studies comparing configurations of dialogue choices across the morality spectrum in an RPG prototype. Study 1 compared two polar (opposing) choices with two moral or two immoral choices. Study 2 contrasted polar choices with similar choices tailored to the player's morality, modelled from their initial 10 decisions. Study 3 compared polar choices with two tailored and one opposing choice. Our results consistently show that including the opposing choice is important to a player's identification with their character, even when we can reliably predict the decision that they will make.
What Makes User Switch Technology?: Enabler and Inhibitor Factors of Converting to Mobile Application

Along with the advancement in the technology, a lot of newer and better technology are introduced. However, there are many cases where users don't want to adopt new and better technology, instead, they keep using the old technology. This problem of users' inertia, not wanting to switch to new technology, is now being faced by Cookpad Indonesia. Only a few Cookpad mobile web users that want to switch to use Cookpad mobile application. The purpose of this research is to identify the factors, enablers and inhibitors, that influence Cookpad mobile website users to switch to use Cookpad mobile application. Two-factor theory, which states that there are enablers and inhibitors that work independently to influence behavior, is used as a theoretical framework for this research. Quantitative data using Likert scale was collected through questionnaire survey targeting Cookpad Indonesia users. There were 406 questionnaires collected, with 331 of them are valid. SEM covariant based was used to analyze survey result using AMOS software. Functional deprivation, interactivity, and social identification were identified as enablers, while inertia was identified as inhibitors for users' intention to switch from mobile website to mobile application.
A Systematic Review on Imbalanced Data Challenges in Machine Learning

In machine learning, the data imbalance imposes challenges to perform data analytics in almost all areas of real-world research. The raw primary data often suffers from the skewed perspective of data distribution of one class over the other as in the case of computer vision, information security, marketing, and medical science. The goal of this article is to present a comparative analysis of the approaches from the reference of data pre-processing, algorithmic and hybrid paradigms for contemporary imbalance data analysis techniques, and their comparative study in lieu of different data distribution and their application areas.
A Survey on 360° Video Streaming

Head-mounted displays and 360° videos have become increasingly more popular, delivering a more immersive viewing experience to end users. Streaming 360° videos over the best-effort Internet, however, faces tremendous challenges, because of the high resolution and the short response time requirements. This survey presents the current literature related to 360° video streaming. We start with 360° video streaming systems built for real experiments to investigate the practicality and efficiency of 360° video streaming. We then present the video and viewer datasets, which may be used to drive large-scale simulations and experiments. Different optimization tools in various stages of the 360° video streaming pipeline are discussed in detail. We also present various applications enabled by 360° video streaming. In the appendices, we review the off-the-shelf hardware available at the time of writing and the open research problems.
You have my sword; and my bow; and my axe: player perceptions of odd shaped dice for dungeons & dragons

Tabletop role-playing Games (RPG), such as Dungeons & Dragons (D&D) use dice in order to control the outcome actions by characters when the Game Master needs to introduce randomness. While dice are fundamental to such games, the examination of dice as objects of design has not been explored. This study examines fifty-nine participants (thirty familiar with the D20 set system) and asks them to examine two 7-die sets commonly used in D&D, the first set being a common set of polyhedrons, and the other set designed to replicate the objects used by a Wizard. It examines the fairness perceptions of the participants and finds that players who have experience with the polyhedral set in the past are more likely to accept the fairness of Wizard dice, and that all players are more likely to accept the fairness of the Wizard set after a play session.
Transformer Fault Diagnosis Model Based on Iterative Nearest Neighbor Interpolation and Ensemble Learning

In order to improve the accuracy of fault diagnosis of power transformer in the presence of missing values, we propose a missing value imputation method by iterative k nearest neighbor (KNN), and ensemble learning is used to diagnose the power transformer. First, according to importance of different attributes of dissolved gas data in the ensemble classification method, interpolation order of missing data is determined. Then, in order to take advantage of valid information from data with missing values, the missing values are interpolated in an iterative manner by KNN. Finally, the ensemble learning model is used for fault diagnosis of transformers. The experimental results show that the average accuracy of transformer fault diagnosis after using this method to interpolate DGA data sets is increased by 15.4%, and the average accuracy can reach 82%.
E-coaching for Pre-service Teacher Internship: Thais and Flemish' Perceptions

The purpose of this qualitative research is to investigate the perceptions of Flemish and Thai pre-service teachers and university supervisors on e-coaching during their internship programs. Data was obtained by conducting interviews and with in-depth semi-structured questions with N=40 participants. The instrument was based on an integrated model of the Theory of Planned Behaviour (TPB) and the Technology Acceptance Model (TAM). The interviews were audio-recorded and encrypted in NVivo 11. The results revealed that both Flemish and Thai participants perceived the value of e-coaching. The subjective norms of the participants show that Thai students and supervisors influence each other to use e-coaching. For Flemish, the supervisors have an essential role in influencing students. Both Thai and Flemish perceived the use of e-coaching as a comfortable mode of communication. The results explained by the theoretical framework of Planned Behavior and Technology Acceptance (TPB -TAM) variables also show some differences between the two contexts. The Thai participants are positive about the use of e-coaching because of its ease of use, and have intention to increase the use in the future; however, Flemish participants are skeptical towards this future. In general, Thai participants believe that using Information Communication Technology (ICT) tools can enrich their coaching process, while Flemish participants feel uncertain. Nevertheless, almost all participants agree that e-coaching is crucial for an effective coaching but should always be complemented to a face-to-face coaching.
Reliable Risk Management for Autonomous Vehicles based on Sequential Bayesian Decision Networks and Dynamic Inter-Vehicular Assessment

Guaranteeing the safety of an autonomous vehicle (AV) is a challenging task, especially if the perceived environment is highly uncertain and other road users deviate from their expected trajectories. In this paper, we propose a probabilistic overall strategy for risk assessment and management of AV in highway through a Sequential Level Bayesian Decision Network (SLBDN) and an appropriate analytical formalization of criteria for anomaly detection based on a Dynamic Predicted Inter-Distance Profile (DPIDP) between vehicles. Accordingly, the proposed system is designed to take the suitable maneuver decision, have a safety retrospection and verification over the current maneuver risk and take appropriate evasive action autonomously from moving obstacles. Moreover, this probabilistic framework accounts for measurements uncertainty through an Extended Kalman Filter (EKF) and for vehicles' maximum capacities. Since the proposed strategy has a short response time, integrating safety verification in the decision-making process makes real time evasive decisions possible. Several simulation results show the good performance of the overall proposed control architecture, mainly in terms of efficiency to handle probabilistic decision-making even for risky scenarios.
Heat transfer coefficients in a coupled 3-D model of a liquid-cooled IPM traction motor compared with measurements

Modelling of electrical machines is constantly refined and it is now possible to couple numerical thermal models and electromagnetic models, thereby considering the thermal effects on motor materials. In this paper it is shown how a 3-D model of an interior permanent magnet (IPM) motor, including losses in the end windings and the effect of air and liquid cooling can be made where simulation results are compared with measurements. Further, it is shown how the coolant inlet temperature and volumetric flow rate affects the heat transfer coefficient of the cooling duct for some load points within the torquespeed range of the motor.
Construction of High-Degree Ramanujan Graphs With Applications to Matrix Completion

The matrix completion problem can be stated as follows: Suppose $X\in \mathbb{R}^{n_{1}\times n_{2}}$ is unknown except for an upper bound $r$ on its rank. By measuring a small number $m\ll n_{1}n_{2}$ of elements of $X$, is it possible to recover $X$ exactly, or at least, to construct a reasonable approximation of $X$? There are two existing approaches to choosing the elements to be measured, namely: choosing them at random or in some deterministic fashion. Practically all of the existing literature focuses on the case where the sampled locations are chosen at random. In contrast, the focus in the present paper is on deterministic methods for choosing the elements to be sampled. Specifically, we choose the measurement matrix to be the adjacency or biadjacency matrix of a so-called Ramanujan graph. Existing explicit techniques for constructing Ramanujan graphs lead to graphs whose degree $d$ is bounded by $n^{1/3}$ where $n$ is the number of vertices. However, for the matrix completion problem, this degree is too small. We point out that the well-known Lubotzky-Phillips-Sarnak construction of Ramanujan graphs can be used to generate graphs of very high degree, and use these for the matrix construction problem. Then we carry out numerical studies of “phase transition” in the matrix completion problem, by comparing the behavior of sampling at random with choosing the sampled locations using a Ramanujan graph. Specifically, we show that for a fixed sampling pattern, there is a maximum rank $\bar{r}$ for which randomly generated matrices of rank $r\leq\overline{r}$ can be recovered with probability one, and the recovery probability drops very sharply to zero if $r$ is increased by just two or three beyond $\bar{r}$. The technique proposed here is applicable only to the recovery of square matrices. The recovery of rectangular matrices requires so-called asymmetric Ramanujan graphs, and is studied in a separate paper.
Optimal Multi-group Multicast Beamforming Structure

This paper considers the multi-group multicast beamforming optimization problem, of which the optimal solution has been unknown due to the non-convex and NP-hard nature. By exploring the successive convex approximation method and Lagrangian duality, we obtain the optimal multicast beamforming solution structure. We show that the optimal multicast beamforming has an MMSE filter structure based on a weighted sum of channel directions in the group and a weighted sum of channel covariance matrices. We also show that the inherent low-dimensional structure in the optimal solution benefits significantly the numerical computation, especially for systems with large antenna arrays. We propose algorithms to obtain the multicast beamforming solution based on the optimal structure. Simulation shows that our proposed algorithms achieve near-optimal performance with substantially low computational complexity that does not increase with the number of antennas and increase only mildly with the number of users.
Infrastructure Support for Cooperative Maneuvers in Connected and Automated Driving

Connected and automated vehicles can exploit V2X communications to coordinate their maneuvers and improve the traffic safety and efficiency. To support such coordination, ETSI is currently defining the Maneuver Coordination Service (MCS). The current approach is based on a distributed solution where vehicles coordinate their maneuvers using V2V (Vehicle-to-Vehicle) communications. This paper proposes to extend this concept by adding the possibility for the infrastructure to support cooperative maneuvers using V2I (Vehicle-to-Infrastructure) communications. To this aim, we propose a Maneuver Coordination Message (MCM) that can be used in cooperative maneuvers with or without road infrastructure support. First results show the gains that cooperative maneuvers can achieve thanks to the infrastructure support. This paper also analyses and discusses the need to define MCM generation rules that decide when MCM messages should be exchanged. These rules have an impact on the effectiveness of cooperative maneuvers and on the operation and scalability of the V2X network.
Predictive cruise control behind a stationary or slow moving object

This paper presents an energy-efficient velocity control technique for a truck driving behind a slow moving truck. An observer is designed to estimate the acceleration capability of the leading vehicle, which is then used to predict the velocity and time trajectory of the leading vehicle. This information, together with information of road topography, is used by the ego vehicle to optimally plan its velocity along a look-ahead horizon. The optimal planning is achieved by nonlinear model predictive control, where constraints are set to keep a safe distance to the leading vehicle and arrive at the destination within a given time. The designed controller is tested on various driving cycles. The proposed technique is also tested on a traffic light scenario, where information about the position of the traffic light and timing of its signals is considered to be known. The simulations results show that the proposed technique can save a significant amount of fuel.
The many dimensions underlying perceived softness: How exploratory procedures are influenced by material and the perceptual task*

Haptic research has traditionally often equated softness with compliance. However, in a recent study we have suggested that compliance is not the only perceived object dimension underlying what is commonly called softness [1]. Here, we investigate how the different perceptual dimensions of softness affect how materials are haptically explored. Participants freely explored and rated 19 materials on 15 adjectives. The adjectives defined different perceptual tasks by being associated with different softness dimensions. Materials were chosen to represent extreme values separately for each dimension; some materials served as control. Hand movements were recorded on video and subsequently categorized into different exploratory procedures (EPs). A multivariate analysis of variance (MANOVA) yielded significant effects of material, of the perceptual task and of their interaction. Taken together, the results suggest that participants actively adapt their EPs to both the type of material being explored, and to the judged softness dimension, and thus support the notion of different dimensions of softness.
Optimal Control of an Integrated Energy and Thermal Management System for Electrified Powertrains

This paper proposes an integrated energy and thermal management system (IETMS) to quantify the influence of a cold-start on the fuel-saving potential and the gain of utilizing waste heat recovery (WHR) technologies on the ultimate fuel saving of a plug-in hybrid electric vehicle with cabin heating. A cold-start indicates a low engine temperature, which increases the frictional power loss, resulting in excess fuel consumption. A dual source WHR (DSWHR) system harvests waste heat from exhaust gases and the recovered power is temporarily stored into the battery and can be retrieved when needed. Furthermore, it recuperates waste energy from a continuously variable transmission and an electric machine including power electronics to increase the heating performance of a heat pump, which reduces the load on the battery. For a known driving cycle, New European Driving Cycle, the IETMS aims to maximize the fuel efficiency. Numerical results demonstrate that a cold-start has a remarkable impact on the fuel-saving potential, 7.1%, yet a small influence on the optimization strategy. The DSWHR system shows a significant improvement on the ultimate fuel saving, up to 13.1%, from which insights into the design of WHR technologies can be drawn.
Perceptual Space of Regular Homogeneous Haptic Textures Rendered Using Electrovibration

This paper is concerned with the perceptual structure of homogeneous and deterministic haptic textures rendered by an electrovibration display. Textures were modeled using 32 regular tessellations of polygons by changing the polygon, density, edge width, pixel intensity, and image reversal. We conducted a perceptual experiment to estimate the pairwise dissimilarities between the 32 textures using the cluster sorting procedure. We then applied multi-dimensional scaling to the data and obtained a perceptual space that accounted for the effects of the five design variables on texture perception. The subjective impressions of the textures were also rated against eight adjective pairs. We projected the rating results into the perceptual space to find adequate perceptual dimensions for the texture perception. Our results contribute to designing perceptually distinctive textures elicited by electrovibration with an appropriate understanding of their subjective qualities.
SDF-Loc: Signed Distance Field based 2D Relocalization and Map Update in Dynamic Environments

To empower an autonomous robot to perform long-term navigation in a given area, a concurrent localization and map update algorithm is required. In this paper, we tackle this problem by providing both theoretical analysis and algorithm design for robotic systems equipped with 2D laser range finders. The first key contribution of this paper is that we propose a hybrid signed distance field (SDF) framework for laser based localization. The proposed hybrid SDF integrates two methods with complementary characteristics, namely Euclidean SDF (ESDF) and Truncated SDF (TSDF). With our framework, accurate pose estimation and fast map update can be performed simultaneously. Moreover, we introduce a novel sliding window estimator which attains better accuracy by consistently utilizing sensor and map information with both scan-to-scan and scan-to-map data association. Real-world experimental results demonstrate that the proposed algorithm can be used for commercial robots in various environments with long-term usage. Experiments also show that our approach outperforms competing approaches by a wide margin.
Effects of Harmonic Distortions on the Accuracy of Energy and Power Losses Measurements in a Water Treatment Industry

Harmonic distortions in electric power system are the main power quality concerns, mostly generated by nonlinear loads such as Variable Frequency Drive (VFD). A water treatment industry usually utilizes VFD to control their water pump motors during the operation. In this study, we investigated the effects of harmonic distortion resulted from VFD on the measurement accuracy in the distribution system operated by state-owned electric utility. The results showed that the VFD that employed the pulse width modulation (PWM) technique has adjusted the supply frequency of 50 Hz into specific number to control the speed of motors. Data recorded on energy meter for seven days exhibited the THDV of 3.27% and THDI of 36.37%. We found that the harmonic distortion has caused the energy measurement error of 1.2%, and this becomes potential losses for the utility because it could not be charged to customers due to the government tariff regulation