Description Of Scenario Research Articles

Phase Change Memory: A Review on Electrical Behavior and Use in Analog In‐Memory‐Computing (A‐IMC) Applications

AbstractRecent development and progress of Artificial Intelligence (AI) algorithms made clear that this topic is a paradigm shift with respect to the past. High throughput and ability to do complex tasks makes AI a great field of opportunity. This advancement is somehow limited by the physical implementation of the chips that are still bound to the historical von‐Neumann Architecture with processing units and memory hardware spatially separated. The way data is bussed and processed needs disruptive innovation, rather than an evolutionary approach, too. In Analog In‐Memory Computing (A‐IMC) the typical properties of resistance‐based memory technologies are used to both store and compute information. This allows for incredibly high parallelism and removes the problems related to the known von‐Neumann bottleneck. In the present work, A‐IMC networks based on resistive memories and on the Phase Change Memory (PCM) technology, in particular, are extensively discussed. After a first review of the general features of PCM devices, their application to A‐IMC is described, aiming at a full description of the current technological scenario.

Singular viscoelastic perturbation to soft lubrication

Soft lubrication has been shown to drastically affect the mobility of an object immersed in a viscous fluid in the vicinity of a purely elastic wall. In this theoretical article, we develop a minimal model incorporating viscoelasticity, carrying out a perturbation analysis in both the elastic deformation of the wall and its viscous damping. Our approach reveals the singular-perturbation nature of viscoelasticity to soft lubrication. Numerical resolution of the resulting nonlinear, singular, and coupled equations of motion reveals peculiar effects of viscoelasticity on confined colloidal mobility, opening the way towards the description of complex migration scenarios near realistic polymeric substrates and biological membranes. Published by the American Physical Society 2024

Evolution of Unmanned Surface Vehicle Path Planning: A Comprehensive Review of Basic, Responsive, and Advanced Strategic Pathfinders

Unmanned Surface Vehicles (USVs) are rapidly becoming mission-indispensable for a variety of naval operations, from search and rescue to environmental monitoring and surveillance. Path planning lies at the heart of the operational effectiveness of USVs, since it represents the key technology required to enable the vehicle to transit the unpredictable dynamics of the marine environment in an efficient and safe way. The paper develops a critical review of the most recent advances in USV path planning and a novel classification of algorithms according to operational complexity: Basic Pathfinders, Responsive Pathfinders, and Advanced Strategic Pathfinders. Each category can adapt to different requirements, from environmental predictability to the desired degree of human intervention, and from stable and controlled environments to highly dynamic and unpredictable conditions. The review includes current methodologies and points out the state-of-the-art algorithmic approaches in their experimental validations and real-time applications. Particular attention is paid to the description of experimental setups and navigational scenarios showing the realistic impact of these technologies. Moreover, this paper goes through the key, open challenges in the field and hints at the research direction to leverage in order to enhance the robustness and adaptability of path planning algorithms. This paper, by offering a critical analysis of the current state-of-the-art, lays down the foundation of future USV path planning algorithms.

Towards Integrated Safety Assurance Methodology for Autonomous Vessel Navigation Systems

Abstract Safety assurance remains paramount for the realization of autonomous vessels. A robust assurance methodology that can provide traceability throughout the design and verification process is necessary to demonstrate safety equivalence to that of conventional ships. However, there are few references that propose a holistic safety assurance scheme for autonomous ships, using actual engineering processes of ships as examples. This study proposes a design and development method for an autonomous navigation system that integrates Model-Based Systems Engineering (MBSE), System Theoretic Process Analysis (STPA), Failure Modes and Effects Analysis (FMEA), and several verification methods including simulation-based tests to develop a comprehensive safety assurance scheme. This safety assurance scheme is being conducted as a case study for a newly constructed autonomous vessel. First, STPA can be performed on the conceptual design established by MBSE to extract additional safety requirements from the identified loss scenarios. Focusing on the process model in the loss scenario description leads to a deeper understanding of the system behavior. FMEA in addition identify potential component failure modes and their impact on system safety. The multi-level requirements that emerge from these activities are validated in test scenarios. Simulators are used to evaluate whether the autonomous navigation system’s safety can meet predefined pass criteria in some of the scenarios. These activities ensure traceability from safety goals to design decisions, allowing design changes and their impact on safety to be evaluated throughout the development lifecycle and allowing for more systematic ongoing monitoring during operations.

Physics basis for the divertor tokamak test facility

Abstract This paper is dealing with the physics basis used for the design of the Divertor Tokamak Test facility (DTT), under construction in Frascati (DTT 2019 DTT interim design report (2019)) Italy, and with the description of the main target plasma scenarios of the device. The main goal of the facility will be the study of the power exhaust, intended as a fully integrated core-edge problem, and eventually to propose an optimized divertor for the European DEMO plant. The approach used to design the facility is described and their main features are reported, by using simulations performed by state-of-the-art codes both for the bulk and edge studies. A detailed analysis of MHD, including also the possibility to study disruption events and Energetic Particles physics is also reported. Eventually, a description of the ongoing work to build-up a Research Plan written and shared by the full EUROfusion community is presented.

Statistical mechanics description of an empirical scenario in which gravity was discussed when coupled to a harmonic oscillator

Statistical mechanics description of an empirical scenario in which gravity was discussed when coupled to a harmonic oscillator

Многофакторный анализ эффективности автономных транспортных средств на основе метода анализа среды функционирования

The design of robotic and unmanned vehicles includes a virtual commissioning stage that provides an analysis of the operation of objects using digital twins. Conducting a large number of experiments on models leads to the use of methods for evaluating the results obtained to choose the best design solution. A method of multifactorial anal-ysis of the efficiency of the complex of autonomous vehicles (AV) for agro-industrial purposes is proposed. Multivariate analysis is performed at the virtual commissioning stage in order to plan early maintenance and repair activities. The paper uses the method of analyzing the operating environment for a comparative assessment of various operating scenarios. The method is based on solving a complex of optimization problems of linear programming. A formal description of virtual test scenarios is proposed. The method of multifactorial analysis is implemented in the process of virtual tests using optimal purpose system models and AV simulation. A procedure for virtual AV tests has been developed, including step-by-step modeling and multivariate analysis. The sets of input and output key parameters of the AV and analyzed scenarios are determined. It is proposed to perform two consecutive efficiency assessment tasks. The first task is to compare the effectiveness of individual AV and determine the limits of their effectiveness. The solution of the second task makes it possible to evaluate the effectiveness of AV system operation scenarios. The target values of changes in the key parameters of the AV and operating scenarios are obtained, leading to an increase in the efficiency of operation and maintenance. Conducting a multifactorial analysis of the results of virtual tests allows you to formulate requirements and recommendations for the design of AV maintenance systems.

The role of scenarios in paradoxes

This paper fills a gap in the existing metaphilosophical research on paradoxes by focusing on the role of scenarios. Typical philosophical paradoxes contain a scenario description whose contribution to paradoxes remains unexplored. I argue that scenarios are examples or instantiations of the abstract schema of paradoxes. As such, scenarios contribute to paradoxes on two levels. First, they make the argument more concrete, thus enhancing the dialectical force of paradoxes and facilitating their understanding, especially for non-experts. This function is external to the paradox itself, but has important practical implications for the use of paradoxes and their effect on philosophical debates, and it contributes to explaining why philosophical paradoxes are usually introduced by a scenario. Second, and more crucially, scenarios are essential to the epistemic dimension of paradoxes. By definition, paradoxes have two necessary components: the argumentative structure and the plausibility/implausibility of the premises/conclusion. By providing examples of the abstract schema, scenarios contribute to making the premises plausible. In particular, scenarios are the source of plausibility and justification for those premises that contain an empirically grounded assertion of existence. Examples of such paradoxes are the Sorites paradox, the Lottery paradox, and the Grue paradox. Contrary to the dialectical role, the epistemic function of scenarios is indispensable, as it connects paradoxes to the real world and underscores their significance in specific debates.

Study on uneven settlement and correction of steel frame structures based on numerical simulation method.

Lifting-correction is a technique to restore buildings experiencing uneven settlement, while ensuring the safety and integrity of the main structural system. This study was based on a real light-steel building structure and provided a detailed description of scenarios involving uneven settlement and the process of lifting and correction. Additionally, a sophisticated finite element (FE) model was established using the generic FE software ABAQUS, with refined material constitutive models to ensure the accuracy of simulation results. Firstly, the impact of uneven settlement on the structure was examined, including modal and stress field analyses. Different methods of breaking column (BC) and lifting column (LC) were compared and scrutinized to identify optimal approaches and minimize damage and disturbance to the building. Four methods have been proposed and compared, including simultaneously breaking columns, breaking columns with chessboard style, simultaneously lifting columns and lifting columns in multiple stages. The four methods were comprehensively evaluated from the perspectives of stress fields, displacement responses, damage and energy dissipation. The results indicated that after uneven settlement, the eigenvalues and frequencies of the structure decrease, the structure tended to be unstable. Simultaneously, as stress increases, some joints' materials enter the yielding stage, affecting the overall structural stability and safety. When damage occurs in some joints, the structural safety was compromised. The comparison between the two BC methods, including the chessboard style and simultaneously BC methods, it was revealed that the former causes less disturbance to structural initial stress field. The comparison between the two LC methods, including, simultaneously and LC in multiple stages, it was revealed that the latter performs slightly better in terms of stress fields, displacement fields, damage, energy dissipation and internal forces. Therefore, the methods of BC in chessboard style and LC in multiple stages were recommended to use in engineering practice to ensure less structural disturbance. The findings obtained from this study can provide guidance for structural engineers to solve the uneven settlement of buildings.

Pre-crash scenarios for safety testing of autonomous vehicles: A clustering method for in-depth crash data

Autonomous vehicles (AVs) provide an opportunity to enhance traffic safety. However, AVs market penetration is still restricted due to their safety concerns and dependability. For widespread adoption, it is crucial to thoroughly assess the safety response of AVs in various high-risk scenarios. To achieve this objective, a clustering method was used to construct typical testing scenarios based on the China In-depth Mobility Safety Study-Traffic Accident (CIMSS-TA) database. Initially, 222 car-to-powered two-wheelers (PTWs) crashes and 180 car-to-car crashes were reconstructed from CIMSS-TA database. Second, six variables were extracted and analyzed, including the motion of the two vehicles involved, relative movement, lighting condition, road condition, and visual obstruction. Third, these variables were clustered using the k-medoids algorithm, identifying five typical pre-crash scenarios for car-to-PTWs and seven for car-to-car. Additionally, we extracted the velocities and surrounding environmental information of the crash-involved parties to enrich the scenario description. The approach used in this study used in-depth case review and thus provided more insightful information for identifying and quantifying representative high-risk scenarios than prior studies that analyzed overall descriptive variables from Chinese crash databases. Furthermore, it is crucial to separately test car-to-car scenarios and car-to-PTWs scenarios due to their distinct motion characteristics, which significantly affect the resulting typical scenarios.

On information value and decision analyses

This paper addresses value of information, structural health information, and decision analyses in built environment engineering. Decision analyses are used for the joint optimization of information collection and the identification of physical measures for the management and enhancement of the expected utility of built environment systems. To these ends, this paper contains (1) principal descriptions of decision scenarios and the model basis in conjunction with the objective functions, embedded in (a) a summary of the historical background and (b) the origins of the methods of decision and value of information analyses, (2) an overview of methods for decision analyses highlighting solution strategies to handle comprehensiveness and computational challenges, (3) principal application areas and case studies, and (4) insights into recent advances. The main insights and an outreach to potential future research perspectives are summarised at the end of this paper.

Observing heroic behavior and its influencing factors in immersive virtual environments

Studying heroism in controlled settings presents challenges and ethical controversies due to its association with physical risk. Leveraging virtual reality (VR) technology, we conducted a three-study series with 397 participants from China to investigate heroic actions. Participants unexpectedly witnessed a criminal event in a simulated scenario, allowing observation of their tendency to physically intercept a thief. We examined situational factors (voluntariness, authority, and risk) and personal variables [gender, impulsivity, empathy, and social value orientation (SVO)] that may influence heroism. Also, the potential association between heroism and social conformity was explored. In terms of situational variables, voluntariness modulated participants' tendency to intercept the escaping thief, while perceived risk demonstrated its impact by interacting with gender. That is, in study 3 where the perceived risk was expected to be higher (as supported by an online study 5), males exhibited a greater inclination toward heroic behavior compared to females. Regarding other personal variables, the tendency to engage in heroic behavior decreased as empathy levels rose among males, whereas the opposite trend was observed for females. SVO influenced heroic behavior but without a gender interaction. Finally, an inverse relationship between heroism and social conformity was observed. The robustness of these findings was partly supported by the Chinese sample (but not the international sample) of an online study 4 that provided written descriptions of VR scenarios, indicating cultural variations. These results advance insights into motivational factors influencing heroism in the context of restoring order and highlight the power of VR technology in examining social psychological hypotheses beyond ethical constraints.

Math Word Problem Generation via Disentangled Memory Retrieval

The task of math word problem (MWP) generation, which generates an MWP given an equation and relevant topic words, has increasingly attracted researchers’ attention. In this work, we introduce a simple memory retrieval module to search related training MWPs, which are used to augment the generation. To retrieve more relevant training data, we also propose a disentangled memory retrieval module based on the simple memory retrieval module. To this end, we first disentangle the training MWPs into logical description and scenario description and then record them in respective memory modules. Later, we use the given equation and topic words as queries to retrieve relevant logical descriptions and scenario descriptions from the corresponding memory modules, respectively. The retrieved results are then used to complement the process of the MWP generation. Extensive experiments and ablation studies verify the superior performance of our method and the effectiveness of each proposed module. The code is available at https://github.com/mwp-g/MWPG-DMR .

Linking undergraduates’ future work self and employability: a moderated mediation model

BackgroundThe career intentions of students play a crucial role in shaping the growth of the hospitality and tourism industry. Previous research underlines the significance of future work self in predicting outcomes related to one’s career. However, there is limited knowledge regarding the precise ways, timing, and conditions under which the future work self of undergraduate students can enhance their employability.MethodsThis paper aims to address the existing research gap by employing career construction theory and self-determination theory to propose a moderated mediation model—i.e., career exploration serves as a mediator and job market knowledge functions as a moderator in the relationship between future work self and employability. We conducted two independent studies (i.e., an experimental study and a time-lagged field study) to test the proposed model. Specifically, in Study 1 we employed an experimental research design to recruit 61 students majoring in tourism management to participate. They were randomly assigned to two scenarios (future work self: high vs. low), and we manipulated different levels of future work self by means of scenario descriptions. In Study 2, we used the time-lagged research design to collect data via submitting questionnaires among 253 Chinese undergraduates who majored in hospitality and tourism at a university in the middle area of China.ResultsThe results indicate a positive correlation between undergraduates’ future work self and their employability. Furthermore, this relationship is mediated by a mediator of career exploration. It is important to note that this mediating relationship is also contingent upon the moderator variable of undergraduates’ job market knowledge when considering the impact of career exploration on employability.ConclusionThe findings contribute to enriching the current understanding of the positive effects of future work self on undergraduates’ desirable outcomes in employability.

Semantic-guided fuzzing for virtual testing of autonomous driving systems

Autonomous driving systems (ADS) have achieved spectacular development and have been utilized in numerous safety-critical tasks. Nonetheless, in spite of their considerable advancement, ADS perception components with high complexity and low interpretability often demonstrate unexpected corner-case behaviors. Several real-world accidents involving self-driving cars even lead to fatalities. Before rolling the autonomous vehicles out to the end-users, it is vital to test and guarantee the safety of ADS. As one of the most critical autonomous driving testing techniques, the prevailing virtual testing depends on the tester using tool-specific languages to code traffic simulation programs correctly. However, this process often requires plenty of effort, and it may fail to capture various rare events from complex driving situations that require sophisticated awareness of the surroundings.In this paper, we design and implement a semantic-guided scene fuzzing framework for autonomous driving systems, namely FuzzScene, based on the metamorphic testing theory. It employs driving scenario description language for scenario representation and equips a tree-based mutation strategy to generate tests with proper oracle information. To improve the testing efficiency and detect misbehaviors under different settings, we propose a unique sampling strategy and construct a testing guidance criterion to optimize FuzzScene. We experiment FuzzScene with multiple steering controllers to evaluate its performance on different tasks. The experiment results show that the semantic transformed driving scenarios generated by FuzzScene efficiently detect hundreds of inconsistent behaviors of ADS. Also, the results confirm that FuzzScene can improve steering precision by retraining with the generated scenes.

Research on economic dispatching strategy of electric vehicles participating in frequency regulation ancillary service

Electric vehicles (EVs) are demand-side resources capable of rapid power adjustments. When clustered as aggregators in frequency regulation (FR) services, EVs have the advantages of low deployment cost and fast response speed. This passage studies description of uncertain scenarios when aggregators participate in FR services. With a focus on the optimization of charging and frequency reserve capacity for aggregators participating in FR, a conversion method from FR signal sequence to FR demand is proposed based on historical data of FR signals. The intent is to address the uncertainty of both system FR and load electricity consumption. This passage provides an uncertain characterization of FR demand, which performs as a key indicator of proposed economic dispatching strategy. The result shows how different levels of risk appetite affects the real-time responsiveness, thus mentoring the strategic decision of how much reserve capacity should be provided for FR.

Abstract 123: Emotional Prosody and Facial Expressions Differentially Augment Comprehension of Discourse for Left and Right Hemisphere Stroke Survivors

Deficits in spoken discourse comprehension are common after left hemisphere (LH) and right hemisphere (RH) stroke. Thus, it is important to identify factors that facilitate comprehension and enhance communication between stroke survivors and their care partners. Emotional prosody and facial expression cues can facilitate comprehension, but this may depend on an intact RH. To determine if such cues are facilitatory to LH and RH stroke survivors, we compared discourse comprehension between the groups across 3 conditions. We hypothesized that RH participants would not benefit as much from these cues as LH participants due to concomitant impairments in recognition of prosody and facial expression. We assessed 72 stroke survivors within 3 months of unilateral ischemic stroke, including 40 LH (15 female; aged 62±13 yrs) and 32 RH (17 female; aged 68±10 yrs), and 29 healthy controls (19 female; aged 72±15 yrs). Participants listened to a series of recorded spoken descriptions of scenarios and selected 1 picture from 4 to match each scenario. Targets and foils were balanced across spatial positions. Each description was presented in 3 conditions: read with neutral prosody (Trial 1), read with emotional prosody (Trial 2), and read with emotional prosody + facial expressions (Trial 3, audio + video). If 100% accuracy was achieved on a trial, the next trial was not presented. We used a Kruskal-Wallace test and paired samples t -tests for analyses and corrected for multiple comparisons. Accuracy differed significantly between groups on Trial 1, H (2) = 26.68, p < .001. Controls achieved higher accuracy than LH ( p < .01) and RH participants ( p < .01). LH and RH participants did not differ, p = .51. LH participants achieved significant gains in accuracy from Trial 1 to 2 ( t (32) = 4.16, p = .001) and from Trial 1 to 3 ( t (32) = 5.49, p < .001), but not from Trial 2 to 3 ( t (32) = 1.79, p = .08). RH participants did not achieve significant gains in accuracy from Trial 1 to 2 ( t (23) = 1.59, p = .13), Trial 2 to 3 ( t (23) = 0, p = 1.0), or Trial 1 to 3 ( t (23) = 1.21, p = .24). To conclude, emotional prosody and facial expressions significantly improved discourse comprehension for LH but not for RH stroke survivors. Different/additional strategies to improve discourse comprehension after RH stroke are needed.

Randomized trial of dentists' understanding: treatment benefit in absolute numbers vs relative risk reduction.

This study aimed to assess whether dentists correctly understand the benefit of a dental treatment when it is presented using absolute numbers or relative risk reduction (RRR). This parallel-group randomized controlled trial recruited dentists from 3 postgraduate courses in Rio de Janeiro, Brazil. Participants received, in sequentially numbered sealed opaque envelopes, the description of a hypothetical scenario of the benefit (avoidance of multiple tooth loss) of nonsurgical periodontal treatment without or with antibiotics. Treatment benefit was presented in 2 different formats: absolute numbers or RRR. Dentists were given 10 minutes to read the treatment scenario and answer 5 questions. The final sample for analysis included 101 dentists. When asked to estimate the number of patients out of 100 who would avoid multiple tooth loss without antibiotics, 17 dentists (33%) in the absolute numbers group and 12 (25%) in the RRR group provided the correct response (p = 0.39). Regarding treatment with antibiotics, 26 dentists (50%) in the absolute numbers group and 14 (29%) in the RRR group provided the correct response (p = 0.04). Only 16 dentists (31%) in the absolute numbers group and 12 (25%) in the RRR group gave correct answers for both questions (p = 0.51). Most dentists did not correctly understand the benefit of the treatment, irrespective of the format it was presented. Slightly more dentists correctly understood the benefit of the treatment when it was presented as absolute numbers than as RRR.

Automatically Improving Scenario Descriptions Derived From Recorded Traffic

Automatically Improving Scenario Descriptions Derived From Recorded Traffic

Heterogeneity‐oriented ensemble learning for rail monitoring based on vehicle‐body vibration

AbstractIn this study, railway vehicle‐body vibration was applied to rail detection for convenient sensor deployment and cost‐effectiveness. However, the waveform is difficult to analyze due to damping and interference. Data‐driven methods can help concatenate multidimensional signals and complex rail‐surface irregularities but are impressionably uncertain. This study proposes a method in which a deep learning framework is coupled with heterogeneous factors at every link in its ensemble strategy. The instantiation, module foundation, and scenario description establish a concrete system for dealing with the dilemma that an insufficient database hinders feature extraction, causing unproductive capacity. The performance is quantitatively discussed by combining different levels of on‐site rail‐surface conditions, reaching prediction errors of 4.7% and 6.5% and classifier accuracies of 98.4% and 93.7% for irregularities and defect severities, respectively. This work describes a way to extend self‐learner applicability in industry and will facilitate new support for railway track management.