Real-life Events Research Articles

The use of augmented and virtual reality to enhance the customer experience

Digital technologies such as augmented reality (AR) and virtual reality (VR) offer businesses an opportunity to create a competitive advantage by providing a unique customer experience across the customer’s pre-purchase, purchase, and post-purchase journey. Several businesses have engaged with these technologies, yet, South African businesses are slow adopters. A qualitative study was conducted with AR and VR developers to determine how businesses can use AR and VR technologies to enhance their customer experience. Additionally, the study aimed to identify the factors contributing to and hindering the adoption of AR and VR technologies. The findings indicate that these technologies are mainly used for (1) marketing and (2) training purposes, enabling product customization, enhanced brand experience, and improved communication. Several factors contributing to adopting these technologies were identified, such as improved marketing campaigns, reduced training risks, reinforcing best practices, identifying and managing potential hazards, and offering simulations of real-life events. The factors that hinder the adoption include high cost, data usage, customer adoption, and lack of high-quality user experience designers. The findings of this study offer several practical contributions to assist businesses in the decision to implement and engage with these technologies.

Novel Multimedia Feature Fusion Classification (Mffc) Model for Sports Game Design Enhancement

Multimedia feature fusion is reshaping the landscape of sports game design, offering immersive and dynamic experiences for players and spectators alike. By integrating various multimedia elements such as audio, video, graphics, and interactive interfaces, game designers can create engaging environments that simulate the excitement and intensity of real-life sporting events. From lifelike player animations to realistic crowd reactions, multimedia feature fusion enhances the realism and authenticity of sports games, transporting players into the heart of the action. Furthermore, interactive interfaces enable players to customize their gaming experience, from choosing team strategies to controlling player movements, adding depth and complexity to gameplay. With advancements in technology, such as virtual reality and augmented reality, multimedia feature fusion is poised to revolutionize sports game design, offering unprecedented levels of immersion and interactivity for players worldwide. This paper explores the application of multimedia feature fusion in sports game design, utilizing the Multimedia Feature Fusion Classification (MFFC) framework alongside key feature extraction with the genetic model. By integrating various multimedia elements including audio, video, graphics, and interactive interfaces, the MFFC framework enhances the realism and excitement of sports games, offering immersive experiences for players. Through the genetic model, key features are extracted and optimized to improve gameplay dynamics, player interactions, and overall gaming experience. The effectiveness of the proposed approach is evaluated through simulated experiments and empirical validations, demonstrating significant enhancements in game realism, user engagement, and satisfaction. Results indicate a 30% increase in player immersion and a 25% improvement in gameplay dynamics compared to traditional game design methods.

How Literary Texts ‘Stage’ Code-Switching

Abstract This article explores the possibilities and limitations of the sociolinguistic notion of code-switching for the analysis of multilingual texts, in particular those belonging to literature as it is commonly understood (prose fiction, drama and poetry). In such (con)texts, I argue, code-switching is ‘staged’: produced rather than reproduced. Even when texts stage bilingual conversations with the aim of imitating real-life speech events, mimesis is mediated by the shift from spoken to written mode, which contrasts with the presence and proximity typical of (spoken) verbal interaction. While this mediation limits the applicability of sociolinguistic notions when discussing literary corpora, several examples from both North America (Junot Díaz, Gloria Anzaldúa and Ana Lydia Vega) and Europe (Lydie Salvayre, Ágota Kristóf, Franz Kafka and Leo Tolstoy) show how literary texts ‘stage’ code-switching.

Explicit and Implicit Pattern Relation Analysis for Discovering Actionable Negative Sequences.

Real-life events, behaviors, and interactions produce sequential data. An important but rarely explored problem is to analyze those nonoccurring (also called negative) yet important sequences, forming negative sequence analysis (NSA). A typical NSA area is to discover negative sequential patterns (NSPs) consisting of important nonoccurring and occurring elements and patterns. The limited existing work on NSP mining relies on frequentist and downward closure property-based pattern selection, producing large and highly redundant NSPs, nonactionable for business decision-making. This work makes the first attempt for actionable NSP discovery. It builds an NSP graph representation, quantifies both explicit occurrence and implicit nonoccurrence-based element and pattern relations, and then discovers significant, diverse, and informative NSPs in the NSP graph to represent the entire NSP set for discovering actionable NSPs. A DPP-based NSP representation and actionable NSP discovery method, EINSP, introduces novel and significant contributions to NSA and sequence analysis: 1) it represents NSPs by a determinantal point process (DPP)-based graph; 2) it quantifies actionable NSPs in terms of their statistical significance, diversity, and strength of explicit/implicit element/pattern relations; and 3) it models and measures both explicit and implicit element/pattern relations in the DPP-based NSP graph to represent direct and indirect couplings between NSP items, elements, and patterns. We substantially analyze the effectiveness of EINSP in terms of various theoretical and empirical aspects, including complexity, item/pattern coverage, pattern size and diversity, implicit pattern relation strength, and data factors.

Space For Children: improving mastery and reducing negative emotions about COVID-19 in youth via mobile interactive storytelling.

The COVID-19 pandemic has been a complex event for children and adolescents, significantly impacting their daily activities. In this scenario, our study aims at verifying if "Space for Children," an ad-hoc developed game based on interactive storytelling about the pandemic, can increase mastery and reduces negative emotions about COVID-19. The app Space for Children has been sponsored and spread online by email and social media platforms for a limited time period (from May 2021 to January 2022). Before and after the interactive storytelling, participants answered two questionnaires containing a couple of critical questions regarding their emotional state and their perceived mastery about COVID-19. Two hundred thirty-six participants (M=116; F=120) between 7 and 12 years old completed the Space for Children interactive experience. Our results show a significant effect of the game experience on emotional state and perceived mastery regarding COVID-19. Indeed, before the interactive storytelling unpleasant emotional states prevail (reported by 77% of participants) while after the game a clear prevalence of pleasant emotions emerges (reported by 68% of participants). Regarding perceived mastery, results show that self-reported very expert participants passed from 49% to 88%. All the results hold irrespective of age group and sex. This study presents preliminary findings that highlight the potential benefits of utilizing new technologies based on Interactive Storytelling for Children to effectively convey age-appropriate information about complex real-life events, such as the COVID-19 pandemic, while also mitigating associated negative emotional responses.

A hybrid machine learning with process analytics for predicting customer experience in online insurance services industry

It is essential to innovate and improve service levels by predicting possible process outcomes due to the growth of online service providers. This study estimates the customer satisfaction level based on customer experience analysis. In doing so, we answer recent calls for research about a more thorough exploration of customer behavior using predictive process monitoring techniques. In particular, a hybrid framework of supervised/unsupervised machine learning methods is proposed to predict the outcomes of customers’ experiences while dealing with the problem of high intra-class variance. This problem occurs due to the large dispersion of traces identified in the customer journeys. In this regard, customer journeys are first matched with the event log format aiming to implement a Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering technique based on the similarity between the customer journeys. After summarizing the journeys by removing low-value activities, the multi-class decision tree classification method is applied, and the level of customer satisfaction is predicted. Due to the imbalanced nature of the data, the oversampling for imbalanced classification is applied to achieve good results in accuracy indicators such as recall, precision, and F1-score. Finally, the proposed approach has been evaluated on a real-life event log, BPI Challenge 2016, to investigate unsatisfied customers. The results of the machine learning models on the test data show a high degree of accuracy in predicting customer dissatisfaction.

Predictive process model monitoring using long short-term memory networks

The field of predictive process monitoring focuses on case-level models to predict a single specific outcome such as a particular objective, (remaining) time, or next activity/remaining sequence. Recently, a longer-horizon, model-wide approach has been proposed in the form of process model forecasting, which predicts the future state of a whole process model through the forecasting of all activity-to-activity relations at once using time series forecasting.This paper introduces the concept of predictive process model monitoring which sits in the middle of both predictive process monitoring and process model forecasting. Concretely, by modelling a process model as a set of constraints being present between activities over time, we can capture more detailed information between activities compared to process model forecasting, while being compatible with typical predictive process monitoring objectives which are often expressed in the same language as these constraints. To achieve this, Processes-As-Movies (PAM) is introduced, i.e., a novel technique capable of jointly mining and predicting declarative process constraints between activities in various windows of a process’ execution. PAM predicts what declarative rules hold for a trace (objective-based), which also supports the prediction of all constraints together as a process model (model-based). Various recurrent neural network topologies inspired by video analysis tailored to temporal high-dimensional input are used to model the process model evolution with windows as time steps, including encoder–decoder long short-term memory networks, and convolutional long short-term memory networks. Results obtained over real-life event logs show that these topologies are effective in terms of predictive accuracy and precision.

Assessing the Performance of Fuel Cell Electric Vehicles Using Synthetic Hydrogen Fuel

The deployment of hydrogen fuel cell electric vehicles (FCEVs) is critical to achieve zero emissions. A key parameter influencing FCEV performance and durability is hydrogen fuel quality. The real impact of contaminants on FCEV performance is not well understood and requires reliable measurements from real-life events (e.g., hydrogen fuel in poor-performing FCEVs) and controlled studies on the impact of synthetic hydrogen fuel on FCEV performance. This paper presents a novel methodology to flow traceable hydrogen synthetic fuel directly into the FCEV tank. Four different synthetic fuels containing N2 (90–200 µmol/mol), CO (0.14–5 µmol/mol), and H2S (4–11 nmol/mol) were supplied to an FCEV and subsequently sampled and analyzed. The synthetic fuels containing known contaminants powered the FCEV and provided real-life performance testing of the fuel cell system. The results showed, for the first time, that synthetic hydrogen fuel can be used in FCEVs without the requirement of a large infrastructure. In addition, this study carried out a traceable H2 contamination impact study with an FCEV. The impact of CO and H2S at ISO 14687:2019 threshold levels on FCEV performance showed that small exceedances of the threshold levels had a significant impact, even for short exposures. The methodology proposed can be deployed to evaluate the composition of any hydrogen fuel.

Biomonitoring of polycyclic aromatic hydrocarbons exposure and short-time health effects in wildland firefighters during real-life fire events

Human biomonitoring data retrieved from real-life wildland firefighting in Europe and, also, worldwide are scarce. Thus, in this study, 176 Portuguese firefighters were biomonitored pre- and post- unsimulated wildfire combating (average:12–13 h; maximum: 55 h) to evaluate the impact on the levels of urinary polycyclic aromatic hydrocarbons hydroxylated metabolites (OHPAH; quantified by high-performance liquid chromatography with fluorescence detection) and the associated short-term health effects (symptoms, and total and differentiated white blood cells). Correlations between these variables and data retrieved from the self-reported questionnaires were also investigated. Firefighters were organized into four groups according to their exposure to wildfire emissions and their smoking habits: non-smoking non-exposed (NSNExp), non-smoking exposed (NSExp), smoking non-exposed (SNExp), and smoking and exposed (SExp). The most abundant metabolites were 1-hydroxynaphthalene and 1-hydroxyacenaphthene (1OHNaph + 1OHAce) (98–99 %), followed by 2-hydroxyfluorene (2OHFlu) (0.2–1.1 %), 1-hydroxyphenanthrene (1OHPhen) (0.2–0.4 %), and 1-hydroxypyrene (1OHPy) (0.1–0.2 %); urinary 3-hydroxybenzo(a)pyrene was not detected. The exposure to wildfire emissions significantly elevated the median concentrations of each individual and total OHPAH compounds in all groups, but this effect was more pronounced in non-smoking (1.7–4.2 times; p ≤ 0.006) than in smoking firefighters (1.3–1.6 times; p ≤ 0.03). The greatest discriminant of exposure to wildfire emissions was 1OHNaph + 1OHAce (increase of 4.2 times), while for tobacco smoke it was 2OHFlu (increase of 10 times). Post-exposure, white blood cells count significantly increased ranging from 1.4 (smokers, p = 0.025) to 3.7-fold (non-smokers, p < 0.001), which was accompanied by stronger significant correlations (0.480 < r < 0.882; p < 0.04) between individual and total OHPAH and total white blood cells (and lymphocytes > monocytes > neutrophils in non-smokers), evidencing the impact of PAH released from wildfire on immune cells. This study identifies Portuguese firefighters with high levels of biomarkers of exposure to PAH and points out the importance of adopting biomonitoring schemes, that include multiple biomarkers of exposure and biomarkers of effect, and implementing mitigations strategies.

The Eurovision song contest and the potential of unintended events and public diplomacy: how exposure to an international mega-event shapes external views of the EU

ABSTRACT This article focuses on the Eurovision Song Contest (ESC) as a potential tool for EU public diplomacy. Institutionally, the ESC, a pan-European international mega-event that forms images of Europe, is not related to the EU. Yet, given the strong link between the ESC and the notion of Europe, the article suggests that the ESC might have unintentionally become a public diplomacy tool for the EU. This argument is supported by showing how public views of the EU in a nonmember country, Israel, changed following its hosting of the ESC in 2019. A longitudinal survey was used to examine the impact of the ESC on Israelis’ sympathy for the EU six months before the 2019 ESC and immediately after hosting the contest. The findings indicated that watching the ESC final increased sympathy for the EU. This demonstrates the positive influence of exposure to the ESC on the views of the EU, highlighting the potential role of the ESC as a tool of public diplomacy for the EU. The findings also illustrate a broader potential for understanding public diplomacy consequences from real-life events.

Influence of Exhaust Aftertreatment System on Powertrain Vibration Behavior

&lt;div&gt;NVH refinement of commercial vehicles is the key attribute for customer acceptance. Engine and road irregularities are the two major factors responsible for the same. During powertrain isolators’ design alone, the mass and inertia of the powertrain are usually considered, but in practical scenarios, a directly coupled subsystem also disturbs the boundary conditions for design. Due to the upgradation in emission norms, the exhaust aftertreatment system of modern automotive vehicles becomes heavier and more complex. This system is further coupled to the powertrain through a flexible joint or fixed joint, which results in the disturbance of the performance of the isolators.&lt;/div&gt; &lt;div&gt;Therefore, to address this, the isolators design study is done by considering a multi-body dynamics model of vehicles with 16 DOF and 22 DOF problems, which is capable to simulate static and dynamic real-life events of vehicles. Design indicators are thoroughly analyzed and validated through the rigid body modes and real field events of the vehicle. As most of the research is done for four-point mounting powertrain systems by considering 6 DOF or 12 DOF in commercial vehicles but a novel approach with a 22 DOF model is proposed in this study to predict the impact of the inclusion of the exhaust aftertreatment system on torque roll axis and rigid body modes decoupling.&lt;/div&gt; &lt;div&gt;The results of the proposed system show that the rigid body mode decoupling of the powertrain system improved and consequently the overall NVH performance of the vehicle in real life is further improved. Therefore, it is suggested from the study that ignoring the inclusion of the exhaust aftertreatment system in the powertrain mounting system design reduces the NVH performance of the vehicle, hence it is recommended to include it in the early phase of design.&lt;/div&gt;

Exploring nurses’ experiences of performing basic life support in hospital wards: An inductive thematic analysis

AimThe aim of this study was to undertake an in-depth exploration of the lived experiences of in-hospital, non-intensive care, ward-based nurses’ experiences of real-life CPR events. BackgroundThere is growing evidence suggesting that may nurses not be able to successfully perform in a cardiac arrest situation. Reasons include a lack of clear leadership at the arrest, performance anxiety, role confusion and knowledge and skill degradation over time. MethodsIn-depth semi-structured interviews were conducted with fifteen ward-based hospital nurses from three hospitals. Interviews were recorded, transcribed verbatim and inductive thematic analysis was completed using NVivo 12 software. FindingsFour main themes emerged from data. The main themes are: (1) Not Being able to Perform When it Matters, (2) Working Really Well as a Team, (3) Reflecting on the Experience: The Good, the Bad & the Ugly and (4) Learning to get it Right for Next Time ConclusionPerforming BLS is a stressful and anxiety-provoking experience for ward-based nurses. Anxiety levels appear to decrease slightly only when nurses have had at least one previous real-life experience with resuscitation. Current BLS education does not prepare nurses for the complexities of resuscitation. Future BLS education should focus on in-depth scenarios, including interdisciplinary team training and with greater frequency than the current yearly mandatory sessions. Listening to the lived experiences of nurses who have performed BLS has given much needed insight into approaches that educators can use to improve BLS education delivery.

Sleep shapes the associative structure underlying pattern completion in multielement event memory

Sleep supports the consolidation of episodic memory. It is, however, a matter of ongoing debate how this effect is established, because, so far, it has been demonstrated almost exclusively for simple associations, which lack the complex associative structure of real-life events, typically comprising multiple elements with different association strengths. Because of this associative structure interlinking the individual elements, a partial cue (e.g., a single element) can recover an entire multielement event. This process, referred to as pattern completion, is a fundamental property of episodic memory. Yet, it is currently unknown how sleep affects the associative structure within multielement events and subsequent processes of pattern completion. Here, we investigated the effects of post-encoding sleep, compared with a period of nocturnal wakefulness (followed by a recovery night), on multielement associative structures in healthy humans using a verbal associative learning task including strongly, weakly, and not directly encoded associations. We demonstrate that sleep selectively benefits memory for weakly associated elements as well as for associations that were not directly encoded but not for strongly associated elements within a multielement event structure. Crucially, these effects were accompanied by a beneficial effect of sleep on the ability to recall multiple elements of an event based on a single common cue. In addition, retrieval performance was predicted by sleep spindle activity during post-encoding sleep. Together, these results indicate that sleep plays a fundamental role in shaping associative structures, thereby supporting pattern completion in complex multielement events.

Sustainable open innovation for ammunition waste management: Proposal for implementation in brazilian public security institutions

The study describes how looking at collaborative processes with a sustainable bias can effectively contribute, through sustainable open innovation, to opportunities for solving challenges of the same context. Therefore, we present a study proposal to improve the public security arena (reverse logistics of ammunition expended in training), aiming at recycling the generated waste. The research strategy was case study analysis, which is appropriate for investigating real-life events. It was necessary to understand which factors contribute to qualifying the requirements for reverse logistics and sustainable innovation in public security institutions. The specific objective is to link the maturity level of the public security institutions to its goals in reverse logistics, to give greater view to implement it. As a result, we were able to increase the current status of knowledge regarding the sustainable disposal of expended ammunition cases and get a better understanding of the economic gains by selling the brass scraps waste (expended ammunition) as a large expected benefit, collaborating to reduce the customer’s costs by enhancing their reverse logistics processes. Also, considering the solutions to complex problems through collaboration, knowledge of purposes, and organizational maturity, point out the relationship between sustainability and innovation.

STUDY OF BEHAVIORAL MODELS OF PERSONALITY IN UKRAINIAN AND RUSSIAN FAIRY TALES

STUDY OF BEHAVIORAL MODELS OF PERSONALITY IN UKRAINIAN AND RUSSIAN FAIRY TALES

Development of an open-source solution to facilitate the use of one-button wearables in experience sampling designs

The experience sampling method (ESM) allows for a high degree of ecological validity compared to laboratory research, at the cost of greater effort for participants. It would therefore benefit from implementations that reduce participant effort. In the present paper, we introduce a screenless wrist-worn one-button wearable as an unobtrusive measurement method that can be employed in ESM designs. We developed an open-source Android application to make this commercially available wearable easily configurable and usable. Over the course of six pilot studies, we explored the technical viability (e.g., battery life, reliability of inputs) of this wearable. We compared data quality between wearables and smartphones in a within-subjects design, exploring both the input options of using the number of button presses as a Likert scale, as well as using the angle of the device as a Physical Analogue Scale. Assessments of Extraversion made with either of these methods were highly correlated to comparable assessments made with comparable methods on a smartphone (i.e., Likert scale or a Visual Analogue Scale, respectively). Furthermore, in a preregistered ESM field experiment (N = 134, 4 weeks), we compared compliance to real-life event triggers between wearable devices and smartphones. We found higher numbers of logged events in the wearable group, indicating better adherence to the event-contingent scheduling. Overall, despite the device’s minimal capabilities and resulting limitations, one-button wearables can be beneficial for use in ESM designs.

Multidimensional subgroup discovery on event logs

Subgroup discovery (SD) aims at finding significant subgroups of a given population of individuals characterized by statistically unusual properties of interest. SD on event logs provides insight into particular behaviors of processes, which may be a valuable complement to the traditional process analysis techniques, especially for low-structured processes. This paper proposes a scalable and efficient method to search significant SD rules on frequent sequences of events, exploiting their multidimensional nature. With this method, it is intended to identify significant subsequences of events where the distribution of values of some target aspect is significantly different than the same distribution for the entire event log. A publicly available real-life event log of a Dutch hospital is used as a running example to demonstrate the applicability of our method. The proposed approach was applied on a real-life case study based on the public transport of a medium size European city (Porto, Portugal), for which the event data consists of 133 million smartcard travel validations from buses, trams and trains. The results include a characterization of mobility flows over multiple aspects, as well as the identification of unexpected behaviors in the flow of commuters (public transport). The generated knowledge provided a useful insight into the behavior of travelers, which can be applied at operational, tactical and strategic business levels, enhancing the current view of the transport services to transport authorities and operators.

Acoustic Correlates of Subtypes of Irony in Chilean Spanish

Utterances containing verbal irony display prosodic particularities that distinguish them from non-ironic speech. While some prosodic features of irony have been identified in Spanish, previous studies have not accounted for different subtypes, nor have they examined this phenomenon in Chilean Spanish despite the unique intonation patterns in this dialect. This study examined the acoustic and prosodic correlates of five subtypes of irony (jocularity, rhetorical questions, understatements, hyperbole, and sarcasm) spontaneously occurring in the casual speech of sociolinguistic interviews with fifteen Chilean women. We segmented 3907 syllable nuclei from 197 spontaneously occurring instances of irony and compared the syllables within the ironic utterances to those in the pre-ironic utterances, along seven acoustic and prosodic variables: pitch range, duration, F0, F1, F2, H1*–H2*, and HNR. The results showed that the speakers favored jocularity and did not produce sarcasm or understatements, and that jocularity, hyperbole, and rhetorical questions significantly differed from the baseline utterances along a variety of acoustic and prosodic measures. We argue that these cues contributed to marking the ironic utterances as salient, allowing these women to talk about difficult real-life events with a touch of humor. Our study provides additional evidence for the connection between prosody and pragmatics in Chilean Spanish and lays the groundwork for further examination of irony and prosody in this and other Spanish dialects.

Real life applications of mathematical model of Kifilideen trinomial theorem distribution of positive powers of &lt;i&gt;n&lt;/i&gt; with mathematical induction of the constituents of its negative powers of &lt;i&gt;n&lt;/i&gt; counterpart

Binomial system is a system of analysis which involves two chances or possible outcomes of event which are the extreme ends of such event. In real life, there exist the mid or intermediary chances or possible outcomes of some events, if not all events, making the possible outcomes of such events to be three. In any such scenario or instance of three possible outcomes, a trinomial system of analysis would be applicable. There is need to develop a model to analysis such scenarios of trinomial system. This research work presents real life applications of mathematical model of Kifilideen trinomial theorem distribution of positive powers of n with mathematical induction of negative powers of n counterpart. A mathematical model of the Kifilideen trinomial theorem distribution was formulated. This research work also develops alternate Kifilideen power combination formula, alternate Kifilideen term formula and alternate Kifilideen position formula for the negative powers of n, which conform but not the same, with the one developed for the positive powers of n counterpart. The formulated mathematical model of the Kifilideen trinomial theorem distribution was utilized to analysis real life events having three possible outcomes. The model invented in this paper can be used to determine the probability of the combination of different n outputs involving three possible categories of outcomes of events. The mathematical induction helps to support and prove that the developed Kifilideen formulas for the constituents of Kifilideen trinomial theorem of negative powers of n are valid and true.

An Examination of the Virtual Event Experience of Cyclists Competing on Zwift

The Virtual Sport Experience Design (VSX) framework, which was adapted from Funk’s Sport Experience Design (SX) framework, was used to examine the event experience of cyclists who competed on the mixed reality platform, Zwift. Using a mixed methods approach, the findings suggest that Zwift is a viable substitute for real-life cycling events in that it provides users with realistic and serious competition in a social environment. High levels of technological embodiment, the quality of the in-game graphics, and the gamification elements added to the experience by creating a sense of presence and control. However, it was the social dimension and the ability to communicate and create a sense of “communitas” with other riders that provided the most compelling argument that Mixed Reality can provide a digital alternative to real-life events.