Using IQA to Extract Mental Models Concerning Quality Evaluation Factors for Social Networking Services on Smartphones

Although today’s users of mobile phones are afforded increasing control as the popularity and richness of information provided by smartphones increases, how these users make choices and evaluations cannot be explicitly expressed. This study uses an acute observation of designers of technology and aesthetics to conduct a mental-model analysis of smartphones with the purpose of explicitly identifying the differences in the schemas of users. This study also modifies the mental model to evaluate the practicability of the mental model. Hence, this study investigates groups of subjects, comparing freshmen and graduating students froma college of design, and adopts a schematized data collection and analysis approach, Interactive Qualitative Analysis (IQA), to ascertain the relationships between factors and establish a complete user mental model. The study results present 11 primary affinity factors: “Pricing,” “Advertisement,” “User Interface,” “Innovation Functions,” “System Maintenance,” “Privacy,” “Utility Functions,” “Personalization,” “Network Performance,” “Customer Service,” and “Multimedia Contents.” The primary driver in evaluating smartphones is found to be “Pricing” for graduating students and “Privacy” for freshmen. The two groups share the same final effect factor, “Multimedia Contents.” This study has successfully identified differences between the different mental models of the two groups, supporting the method that using IQA to perform a quality evaluation of social networking for smartphones is effective. Consequently, platform developers can understand user demand through a mental model and can design good platform functions to effectively improve users’ experience of smartphones.

Current Status and Evolution of Shared Mental Models Based on Bibliometric Analysis

The cornerstone of most management research revolves around improving productivity and team performance.A crucial factor influencing team performance is the shared mental model that team members hold regarding task and team member related issues.This concept has garnered increasing attention from scholars,resulting in an abundance of literature.However,there remains a noticeable scarcity of a comprehensive literature review that combines both quantitative and qualitative analyses of shared mental model studies.In order to grasp a comprehensive understanding of the current status and future trends in the area,this study employs a bibliometric approach to review the literature on shared mental models published in the Web of Science Core Collection database from 1992 to 2023.Co-citation analysis is employed to thoroughly scrutinize the structure of this research area,computationally highlighting research hotspots,revealing potential future research directions and applications,as well as pinpointing pivotal turning points and landmarks in the field.Through scientific bibliometric analysis of knowledge structures and emerging trends,this review makes a substantial contribution to the contemporary literature on shared mental models,providing valuable insights for researchers and practitioners in the field.

Explore of English reading strategies based on mental model pragmatic inference

With the continuous advance education reform and improvement of the quality of English teaching reform, it has become an important content to meet the needs of social development, and promote the comprehensive development of students＇ comprehensive quality and ability. In English teaching, learning English requires a lot of reading, and English reading effects and improve students＇ English scores are closely linked the relationship between the development of future good student. In this paper, the mental model of pragmatic reasoning and English reading give an overview of the psychological impact of the model, they were analyzed using the language to English reading brings reasoning, mental models proposed Pragmatic Inference in English reading, and it can effectively improve English reading efficiency, and promote English Reading level rise.

The Relationship between Psychological Suzhi and Mental Health among Chinese College Students

Object: To explore the relationship between psychological suzhi and mental health among Chinese college students, and to gain psychological suzhi factors that are predictors for mental health. Method: By using stratified sampling method, an investigation was conducted among 734 subjects. They were assessed with the College Student Psychological Suzhi Scale (CSPS, including 3 subscales, 28 factors) and General Health Questionnaire-20 item (GHQ-20, including 3 subscales). Results: 1) Psychological suzhi score for Chinese college students had negative correlation with the score of GHQ-20, GHQ-depression and GHQ-anxiety (p < 0.001), and positive correlation with the score of GHQ-self-affirmation (p < 0.001);2) Psychological suzhi score for Chinese college students was predictor of the score for GHQ-20 and its subscales namely GHQ-self-affirmation, GHQ-depression, and GHQ-anxiety (β = ?0.448, 0.439, ?0.262, ?0.259, p < 0.001);the variance explained by the score of GHQ-20 and its subscales were 19.9%, 19.1%, 6.7%, 6.5%;3) There were 12 psychological suzhi factors that were predictors for GHQ-self-affirmation which was known as the positive indicator of mental health (p < 0.05);11 psychological suzhi factors were predictors for GHQ-depression and GHQ-anxiety which was known as the negative indicator of mental health (p < 0.05). Conclusion: There exists a correlation between psychological suzhi and mental health, particularly in positive mental health. Indeed, the psychological suzhi factors are able to enhance the pertinence of mental health education.

Theoretical and exploratory research on sustainability mental model of the public in China:based on a typical survey in Guangdong province

This article aims to investigate the public's sustainability mental model(SMM), which can reveal the sustainability dilemma from the public respective, other than enterprise or government. In this article, SMM is defined as one's cognitive structure, thinking mode, and behavior tendency when someone deals with sustainability issues. After theoretical analysis, the authors developed reliable and valid measures systematically and conducted a typical survey with 581 participants from college students' families in Guangdong province in China. Based on those samples, the author used the exploratory factor analysis and confirmatory factor analysis to construct a measurement model of SMM, which includes three dimensions, i.e. sustainable cognition, sustainable thinking, and sustainable behavior intention. According to SMM survey and clustering analysis, the results indicate that SMM of those participants is inactive. Even though those samples do not represent the whole country comprehensively, but this survey was sampled typically and they came from around China. So, the authors consider the SMM scores can reflect Chinese people to some extent, leading to the assumption that SMM of Chinese people is not active presently.

Regional Oceanic Impact on Circulation and Direct Radiative Effect of Aerosol over East Asia

The Regional Integrated Environmental Model System （RIEMS 2.0） coupled with a chemistry-aerosol model and the Princeton Ocean Model （POM） is employed to simulate regional oceanic impact on atmospheric circulation and the direct radiative effect （DRE） of aerosol over East Asia. The aerosols considered in this study include both major anthropogenic aerosols （e.g., sulfate, black carbon, and organic carbon） and natural aerosols （e.g., soil dust and sea salt）. The RIEMS 2.0 is driven by NCEP/NCAR reanalysis II, and the simulated period is from 1 January to 31 December 2006. The results show the following： （1） The simulated annual mean sea-level pressure by RIEMS 2.0 with POM is lower than without POM over the mainland and higher without POM over the ocean. （2） In summer, the subtropical high simulated by RIEMS 2.0 with POM is stronger and extends further westward, and the continental low is stronger than without POM in summer. （3） The aerosol optical depth （AOD） simulated by RIEMS 2.0 with POM is larger in the middle and lower reaches of the Yangtze River than without POM. （4） The direct radiative effect with POM is stronger than that without POM in the middle and lower reaches of the Yangtze River and parts of southern China. Therefore, the authors should take account of the impact of the regional ocean model on studying the direct climate effect ＆aerosols in long term simulation.

Gesture-based target acquisition in virtual and augmented reality

Background Gesture is a basic interaction channel that is frequently used by humans to communicate in daily life. In this paper, we explore to use gesture-based approaches for target acquisition in virtual and augmented reality. A typical process of gesture-based target acquisition is: when a user intends to acquire a target, she performs a gesture with her hands, head or other parts of the body, the computer senses and recognizes the gesture and infers the most possible target. Methods We build mental model and behavior model of the user to study two key parts of the interaction process. Mental model describes how user thinks up a gesture for acquiring a target, and can be the intuitive mapping between gestures and targets. Behavior model describes how user moves the body parts to perform the gestures, and the relationship between the gesture that user intends to perform and signals that computer senses. Results In this paper, we present and discuss three pieces of research that focus on the mental model and behavior model of gesture-based target acquisition in VR and AR. Conclusions We show that leveraging these two models, interaction experience and performance can be improved in VR and AR environments.

Innovative Analysis Ready Data(ARD)product and process requirements,software system design,algorithms and implementation at the midstream as necessary-but-notsuffcient precondition of the downstream in a new notion of Space Economy 4.0-Part 1:Problem background in Artificial General Intelligence(AGI)

Aiming at the convergence between Earth observation(EO)Big Data and Artificial General Intelligence(AGI),this two-part paper identifies an innovative,but realistic EO optical sensory imagederived semantics-enriched Analysis Ready Data(ARD)productpair and process gold standard as linchpin for success of a new notion of Space Economy 4.0.To be implemented in operational mode at the space segment and/or midstream segment by both public and private EO big data providers,it is regarded as necessarybut-not-sufficient“horizontal”(enabling)precondition for:(I)Transforming existing EO big raster-based data cubes at the midstream segment,typically affected by the so-called data-rich information-poor syndrome,into a new generation of semanticsenabled EO big raster-based numerical data and vector-based categorical(symbolic,semi-symbolic or subsymbolic)information cube management systems,eligible for semantic content-based image retrieval and semantics-enabled information/knowledge discovery.(II)Boosting the downstream segment in the development of an ever-increasing ensemble of“vertical”(deep and narrow,user-specific and domain-dependent)value–adding information products and services,suitable for a potentially huge worldwide market of institutional and private end-users of space technology.For the sake of readability,this paper consists of two parts.In the present Part 1,first,background notions in the remote sensing metascience domain are critically revised for harmonization across the multidisciplinary domain of cognitive science.In short,keyword“information”is disambiguated into the two complementary notions of quantitative/unequivocal information-as-thing and qualitative/equivocal/inherently ill-posed information-as-data-interpretation.Moreover,buzzword“artificial intelligence”is disambiguated into the two better-constrained notions of Artificial Narrow Intelligence as part-without-inheritance-of AGI.Second,based on a betterdefined and better-understood vocabulary of multidisciplinary terms,existing EO optical sensory image-derived Level 2/ARD products and processes are investigated at the Marr five levels of understanding of an information processing system.To overcome their drawbacks,an innovative,but realistic EO optical sensory image-derived semantics-enriched ARD product-pair and process gold standard is proposed in the subsequent Part 2.

Innovative Analysis Ready Data(ARD)product and process requirements,software system design,algorithms and implementation at the midstream as necessary-but-notsufficient precondition of the downstream in a new notion of Space Economy 4.0-Part 2:Software developments

Aiming at the convergence between Earth observation(EO)Big Data and Artificial General Intelligence(AGI),this paper consists of two parts.In the previous Part 1,existing EO optical sensory imagederived Level 2/Analysis Ready Data(ARD)products and processes are critically compared,to overcome their lack of harmonization/standardization/interoperability and suitability in a new notion of Space Economy 4.0.In the present Part 2,original contributions comprise,at the Marr five levels of system understanding:(1)an innovative,but realistic EO optical sensory image-derived semantics-enriched ARD co-product pair requirements specification.First,in the pursuit of third-level semantic/ontological interoperability,a novel ARD symbolic(categorical and semantic)co-product,known as Scene Classification Map(SCM),adopts an augmented Cloud versus Not-Cloud taxonomy,whose Not-Cloud class legend complies with the standard fully-nested Land Cover Classification System’s Dichotomous Phase taxonomy proposed by the United Nations Food and Agriculture Organization.Second,a novel ARD subsymbolic numerical co-product,specifically,a panchromatic or multispectral EO image whose dimensionless digital numbers are radiometrically calibrated into a physical unit of radiometric measure,ranging from top-of-atmosphere reflectance to surface reflectance and surface albedo values,in a five-stage radiometric correction sequence.(2)An original ARD process requirements specification.(3)An innovative ARD processing system design(architecture),where stepwise SCM generation and stepwise SCM-conditional EO optical image radiometric correction are alternated in sequence.(4)An original modular hierarchical hybrid(combined deductive and inductive)computer vision subsystem design,provided with feedback loops,where software solutions at the Marr two shallowest levels of system understanding,specifically,algorithm and implementation,are selected from the scientific literature,to benefit from their technology readiness level as proof of feasibility,required in addition to proven suitability.To be implemented in operational mode at the space segment and/or midstream segment by both public and private EO big data providers,the proposed EO optical sensory image-derived semantics-enriched ARD product-pair and process reference standard is highlighted as linchpin for success of a new notion of Space Economy 4.0.