Bio-inspired Adaptable Facade Control Reflecting User\u27s Behavior

The purpose of this research is to develop the process of methodology in designing adaptable façade. This study focuses on the processes of façade operation control for each resident’s unit according to the user’s lifestyle. This study aims to develop the design methods that are applicable to the adaptable facade, which is inspired by the design inspiration of the biomimicry. The ideal façade to increase comfort in internal space is an adaptable façade that can constantly respond to changes in the environments. This chapter attempts in active adoption of adaptable facade that makes it possible to respond to changing requirements and environments, eventually enabling the creation of customized services for users. This chapter explores the processes of designing an adaptable façade controlled by three rules inspired by the behaviors of flocks of birds. This chapter shows how adopted bird intelligence can produce various façade controls. Also, this chapter demonstrates biomimetic façade control that has been implemented by behavior-based design. Through this demonstration, this chapter identifies the potentials of biomimetic design in facade using rules of bird flocking as source of design inspiration. This study concludes that a behavior-based approach provides flexibly responding façade to environments increasing users’ quality of life

Understanding Consumer Churning Behaviors in Mobile Telecommunication Service Industry : Cross-national Comparison between Korea and China

It is crucial for telecom operators to shift from a subsidy-centered to a service-centered marketing strategy. As the market reaches its saturation point, the effectiveness of customer acquisition through the traditional subsidy decreases and offering differentiated services for existing customer retention is critical. This study aims at finding out factors affecting consumer churning intention based on PPM (Push-Pull-Mooring) theory in order to exactly understand consumer behaviors in the mobile telecommunication service industry (MTSI). This study also analyzes the difference between Korea (saturation market) and China (growth market) in terms of the causality between the intention to switch and the affecting factors. The research findings will encourage telecom operators to establish the effective service strategy that corresponds to their level of market maturity

The Woodpecker\u27s Beak: An Optimally Designed Structure/Material for Energy Absorption and Shock Mitigation

Woodpecker beaks have the ability to absorb shock energy without any damage to their body. In his book Origin of the Species Charles Darwin mentioned that the “woodpecker, with its feet, tail, beak, and tongue, so admirably adapted to catch insects under the bark of trees” in trying to explain how adaptation led to evolutionary changes in the woodpecker. Did the woodpecker with its beak, tongue, tail, and feet really adapt over long periods of evolutionary time or was it designed by its Creator to live in its particular environment and conditions. The analysis in this study shows the intense complexity of the woodpecker’s beak arguing for an engineering design by its Creator. In particular, this study focuses on the structure-property relationships of the woodpecker beak at multiple length scales. In particular, the woodpeckers’ beaks were examined through microscopy and nano/micro indentation to quantify the structure-property relationships with the perspective of mitigating shock waves. The beak of a woodpecker comprises three layers; exterior keratin layer (rhamphotheca) composed of overlapping scales, middle foam layer, and inner bony layer composed of mineral and collagen fiber. Indentation testing revealed that the hardness value of the inner layer is two to three times higher than that of the exterior layer. The overall design of the beak, tongue, and hyoid bone with their specific structure-property relationships in addition to the subsystem designed for shock mitigation appears to have been specifically designed for absorbing energy as they effectively dissipate energy as a whole. The perfection of the beak’s architectural complexity and fine systemization are highly indicative of it being designed by its Creator

Work-Related Stress and Psychological Distress among Law Enforcement Officers: The Carolina Blue Project

Law enforcement is a stressful occupation that places significant psychological demands on those serving in this role. However, little is known about the severity of work-related stress and psychological distress among law enforcement officers (LEOs) in North Carolina (NC). This cross-sectional study examined the severity of work-related stress and psychological distress among 283 LEOs in NC. The Maslach Burnout Inventory, the Operational Police Stress Questionnaire, the Depression, Anxiety, and Stress Scale, and the Post-Traumatic Stress Disorder (PTSD) Checklist were used to assess burnout, operational police stress, depression, anxiety, stress, and PTSD among LEOs. Descriptive statistics, independent t-tests, Mann–Whitney U tests, one-way ANOVA, and Kruskal–Wallis tests were performed. Rural and male LEOs reported higher burnout levels related to depersonalization (i.e., increased mental distance from one’s job) compared with their urban and female counterparts. LEOs exposed to toxic materials or performing patrol duties exhibited higher operational police stress levels than those who did not. Caucasian LEOs exhibited higher depression, anxiety, and stress than their African American counterparts. Rural LEOs and LEOs who were exposed to toxic materials displayed higher levels of PTSD than their counterparts. Our findings highlight the need for increased mental health support and better working environments for LEOs

Nursing needs assessment scale for women with infertility: development and validation

Purpose High-quality nursing care must be provided for women with infertility, and their nursing care needs must be identified. Although scales have been developed to assess infertility-related stress, quality of life, and psychosocial status, there is a lack of scales that assess the nursing care needs of women with infertility. The purpose of this study was to develop a needs assessment scale for nursing care in women with infertility and to verify its reliability and validity. Methods The 250 subjects in this study were women with infertility recruited from four hospitals. The scale was developed following the framework of DeVellis, through a literature review, in-depth interviews, development of preliminary items, verification of content validity, development of secondary items, verification of construct validity, and extraction of the final items. Date were analyzed using item analysis, factor analysis, confirmatory factor analysis, Pearson correlation coefficients, and Cronbach’s alpha. Reliability was tested using Cronbach’s alpha, and validity was evaluated using item analysis, exploratory factor analysis, and criterion validity. Results The final version of the nursing needs assessment scale for woman with infertility consisted of 18 items. Four factors (physical and psychological nursing needs, needs for information regarding treatment, needs for infertility-related understanding and concern, and supportive needs) explained 66.0% of the total variance. Cronbach’s alpha was .92 for the overall instrument and ranged from .88 to .91 for the subscales. Conclusion These results suggest that this needs assessment scale for nursing care in women with infertility demonstrated acceptable validity and reliability and contained items suitable for assessing the level of nursing care needed by women with infertility

Survey of Social Bias in Vision-Language Models

In recent years, the rapid advancement of machine learning (ML) models, particularly transformer-based pre-trained models, has revolutionized Natural Language Processing (NLP) and Computer Vision (CV) fields. However, researchers have discovered that these models can inadvertently capture and reinforce social biases present in their training datasets, leading to potential social harms, such as uneven resource allocation and unfair representation of specific social groups. Addressing these biases and ensuring fairness in artificial intelligence (AI) systems has become a critical concern in the ML community. The recent introduction of pre-trained vision-and-language (VL) models in the emerging multimodal field demands attention to the potential social biases present in these models as well. Although VL models are susceptible to social bias, there is a limited understanding compared to the extensive discussions on bias in NLP and CV. This survey aims to provide researchers with a high-level insight into the similarities and differences of social bias studies in pre-trained models across NLP, CV, and VL. By examining these perspectives, the survey aims to offer valuable guidelines on how to approach and mitigate social bias in both unimodal and multimodal settings. The findings and recommendations presented here can benefit the ML community, fostering the development of fairer and non-biased AI models in various applications and research endeavors

CReHate: Cross-cultural Re-annotation of English Hate Speech Dataset

English datasets predominantly reflect the perspectives of certain nationalities, which can lead to cultural biases in models and datasets. This is particularly problematic in tasks heavily influenced by subjectivity, such as hate speech detection. To delve into how individuals from different countries perceive hate speech, we introduce CReHate, a cross-cultural re-annotation of the sampled SBIC dataset. This dataset includes annotations from five distinct countries: Australia, Singapore, South Africa, the United Kingdom, and the United States. Our thorough statistical analysis highlights significant differences based on nationality, with only 59.4% of the samples achieving consensus among all countries. We also introduce a culturally sensitive hate speech classifier via transfer learning, adept at capturing perspectives of different nationalities. These findings underscore the need to re-evaluate certain aspects of NLP research, especially with regard to the nuanced nature of hate speech in the English language