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To come up with a prudent decision on the installation of an appropriate green wall (GW) on buildings, this study presents a novel decision-making algorithm. The proposed algorithm considers the importance of barriers hampering GW adoption, as well as their relationships with regard to different types of GWs existing in a contextual setting.

The proposed methodological approach is based on the integration of qualitative and quantitative techniques by employing focus group discussion, fuzzy-based best-worst method and fuzzy TOPSIS.

Based on the experiences of qualified experts involved in related projects in Hong Kong, the following conclusions are drawn: (1) cost, installation and maintenance-related barriers are perceived to have the highest importance, (2) modular living wall system is the most suitable GW system for the context of Hong Kong and (3) existing barriers are found to have a pivotal role in the ranking of the most suitable GW systems.

The findings provide valuable insight not only for policymakers and stakeholders, but also for establishing a methodological approach that can assist decision-makers in identifying the most beneficial GW system rather than the most applicable one. This could have significant implications and introduce potential changes to the common way of practice within the industry and lay the foundation for wider adoption of GW.

While previous studies have investigated the sustainability-related issues of GW façade applications, the current body of knowledge is deprived of a comprehensive methodological approach for the selection of the most suitable GW systems.

This study aims to formulate a user-friendly pre-design model that could be a decision support tool for green wall systems to assist designers in selecting an optimal green wall system aligned with specified performance criteria while concurrently addressing project requirements linked to social and economic parameters. This approach seeks to enhance overall project satisfaction for the designer and the owner.

A correlation between the green wall context and design requirements and its performance on the buildings have been defined by considering its social and economic parameters, which represented the owner preferences to ensure the most satisfaction from installation as it achieves the required performance that is defined by the designer such as maximizing thermal insulation, improving indoor air quality, reducing the needed heating and cooling loads, etc. and also to achieve the satisfaction in social and economic requirements defined by the owner such as system installation cost, system maintenance cost, adding beauty value, etc.

The research developed an easy pre-design model to be a tool for green wall system decision-making for the most suitable system, which contains three main steps: the first one is defining the required performance of the green wall (designer requirements), the second step is limiting the context of the project which is made by designer and the owner requirements and finally the third step is choosing the system components that ensures achieving the requirements of both owners and designer, related to the building and climate context.

The added value lies in developing a green wall decision-making tool, essentially a pre-design model. This model considers the correlation between the project’s context, encompassing climate and building conditions. It provides a structured approach for decision-making in the early stages of green wall design. It offers valuable insights into the optimal choices related to system type, installation methods and plant characteristics. This enhanced decision-making tool contributes to more informed and efficient design processes, considering each project’s specific needs and conditions.

The purpose of this paper is to provide a comprehensive framework that identifies thematic clusters and their interconnections within Global Talent Management (GTM), global careers and talent management (TM).

In this paper, this study conducted a co-citation analysis using bibliographic data to unveil the intellectual connections and relationships among thematic articles related to GTM sourced from the Web of Science.

This review highlights three key research themes: experiences working abroad, TM approaches and the complex nature of GTM as a living system.

The main limitation of this research is the sample itself. Content analysis based on the co-citation method resulted in some more recent releases being omitted.

The practical implications of the paper include providing a structured framework for understanding the complexities of GTM.

Research into the academic literature in this area is divided into various clusters, empirically demonstrating how GTM and global mobility are intertwined, revealing the need for us to more thoroughly comprehend the social ramifications of GTM practices and activities and the need to further analyse the influencing social aspects in a GTM strategy, like diversity, increased mobility and virtual reality.

The analysis revealed the emergence of three distinct thematic groups: (1) global work experiences, (2) TM approaches and (3) GTM.

Despite the burgeoning popularity of virtual gifting in live streaming, research lacks an in-depth understanding of the drivers behind this behavior. Using para-social relationship (PSR), this study aims to capture viewers’ lively social feelings toward the streamer as the key factor leading to the purchase behavior of virtual gifts. It also aims to establish a theoretical link between PSR and viewers’ holistic experience in live streaming as captured by cognitive absorption and aims to investigates the role of technological features (i.e. viewer–streamer and viewer–viewer interactivity, streamer-level and viewer-level deep profiling and design aesthetics) in shaping viewers’ experience.

Based on 433 survey responses, this study employs a combination of structural equation modeling and neural networks to offer valuable insights into the relationships between the technological environment, viewer experience and viewer behavior.

Our results highlight the salience of PSR in promoting the purchase of virtual gifts through cognitive absorption and the importance of the technological environment in eliciting the viewer experience. This study sheds light on the development of PSR in a technological environment and its relationship with cognitive absorption.

By applying PSR to conceptualize viewers’ perceived connection with the streamer, this study extends the research on purchase behavior in the non-shopping context by providing an enlightened understanding of virtual gift purchase behavior in live streaming. Moreover, by theoretically linking PSR with cognitive absorption, virtual gift purchase and technological features of live streaming, it enriches the theory of PSR and bridges the gap between the design practice of supporting the IT infrastructure of live streaming and research.

This paper aims to present a novel lightweight distribution grid operating robot system with focus on lightweight and multi-functionality, aiming for autonomous and live-line maintenance operations.

A ground-up redesign of the dual-arm robotic system with 12-DoF is applied for substantial weight reduction; a dual-mode operating control framework is proposed, with vision-guided autonomous operation embedded with real-time manual teleoperation controlling both manipulators simultaneously; a quick-swap tooling system is developed to conduct multi-functional operation tasks. A prototype robotic system is constructed and validated in a series of operational experiments in an emulated environment both indoors and outdoors.

The overall weight of the system is successfully brought down to under 150 kg, making it suitable for the majority of vehicle-mounted aerial work platforms, and it can be flexibly and quickly deployed in population dense areas with narrow streets. The system equips with two dexterous robotic manipulators and up to six interchangeable tools, and a vision system for AI-based autonomous operations. A quick-change tooling system ensures the robot to change tools on-the-go without human intervention.

The resulting dual-arm robotic live-line operation system robotic system could be compact and lightweight enough to be deployed on a wide range of available aerial working platforms with high mobility and efficiency. The robot could both conduct routine operation tasks fully autonomously without human direct operation and be manually operated when required. The quick-swap tooling system enables lightweight and durable interchangeability of multiple end-effector tools, enabling future expansion of operating capabilities across different tasks and operating scenarios.

Indoor air quality monitoring is extremely important in urban, industrial areas. Considering the devastating effect of declining quality of air in major part of the countries like India and China, it is highly recommended to monitor the quality of air which can help people with respiratory diseases, children and elderly people to take necessary precautions and stay safe at their homes. The purpose of this study is to detect air quality and perform predictions which could be part of smart home automation with the use of newer technology.

This study proposes an Internet-of-Things (IoT)-based air quality measurement, warning and prediction system for ambient assisted living. The proposed ambient assisted living system consists of low-cost air quality sensors and ESP32 controller with new generation embedded system architecture. It can detect Indoor Air Quality parameters like CO, PM2.5, NO2, O3, NH3, temperature, pressure, humidity, etc. The low cost sensor data are calibrated using machine learning techniques for performance improvement. The system has a novel prediction model, multiheaded convolutional neural networks-gated recurrent unit which can detect next hour pollution concentration. The model uses a transfer learning (TL) approach for prediction when the system is new and less data available for prediction. Any neighboring site data can be used to transfer knowledge for early predictions for the new system. It can have a mobile-based application which can send warning notifications to users if the Indoor Air Quality parameters exceed the specified threshold values. This is all required to take necessary measures against bad air quality.

The IoT-based system has implemented the TL framework, and the results of this study showed that the system works efficiently with performance improvement of 55.42% in RMSE scores for prediction at new target system with insufficient data.

This study demonstrates the implementation of an IoT system which uses low-cost sensors and deep learning model for predicting pollution concentration. The system is tackling the issues of the low-cost sensors for better performance. The novel approach of pretrained models and TL work very well at the new system having data insufficiency issues. This study contributes significantly with the usage of low-cost sensors, open-source advanced technology and performance improvement in prediction ability at new systems. Experimental results and findings are disclosed in this study. This will help install multiple new cost-effective monitoring stations in smart city for pollution forecasting.

When teaching in or around the subject of care-experienced young people, it is important for information to be presented in a way that not only creates an understanding of the prevalence of care experience but also emphasises the myriad of life challenges associated with experiences of being involved in the care system.

It is known that out of the 12 million children living in England, just under 400,000 (3%) are known to the social care system at any one time and just over 82,000 of these children are ‘looked after’, under the legal guardianship of local authorities in England.

It will not be unusual for students to come to university with little or no exposure to or understanding of children in care, their lives or what it means to be care experienced. Therefore, teaching in this area needs to draw attention to the reasons as to why care experiences result in hardships, this can be done by identifying why care experience is a sensitive subject area. This chapter identifies some (but not all) of the common adversities that care-experienced young people often face inclusive of changes in accommodation and placement instability, insecure relationships, poor mental health, disrupted education, substance misuse, and poverty.

This conceptual article presents a schematic for use with extended cybernetic recursion in living systems and applies it to the issue of hyper vigilance as a demonstration of its utility.

The test-operate-test-exit (TOTE) schematic of Miller et al. (1960) is critically evaluated along with other schematics, including those of ordered cybernetics, and a new schematic is proposed, a recursive test-operate-test (rTOT), which emphasizes teleological purpose and hierarchical structure. The background psychophysiology of trauma is reviewed and then rTOT is applied to hyper vigilance, a cardinal component of post-traumatic stress disorder (PTSD).

Once the schematic was developed, it was applied to the behavior of hyper vigilance. Other applications are suggested.

As demonstrated, the rTOT schematic has potentially wide application because of its pragmatic and detailed structure.

The rTOT requires careful consideration of teleological purposes for its application and is simple enough, but also complex enough, for relevant utilization. Its compact nature and adjustable hierarchy scope are good mini-max complexity solutions for cybernetic, information modeling schematics.

The revealed teleological purpose of the trauma adaptation of hyper vigilance presents significant alternative formulation options for prevention and intervention.

While the rTOT schematic is derived from previous schematics, it is original in its emphasis on information processing, the teleological aspects of extended recursion and on the provision of a hierarchical structure for those recursions. It is considerably more compact than other schematics associated with the ordered cybernetics literature. The explication of the adaptation model for post-trauma consequences is significantly enhanced by the rTOT application.