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in Architecture & Planning
Periodicals

Leveraging ChatGPT and other generative artificial intelligence (AI)-based applications in the hospitality and tourism industry: practices, challenges and research agenda

Purpose The hospitality and tourism sector has witnessed phenomenal growth in customer numbers during the postpandemic times. This growth has been accompanied by the use of technologies in customer interface and backend activities, including the adoption of self-serving technologies. This study aims to analyze the existing practices and challenges and establish a research agenda for the implementation of generative artificial intelligence (AI) (such as ChatGPT) and similar tools in the hospitality and tourism industry. Design/methodology/approach This study analyzes the existing literature and practices. This study draws upon these practices to outline a novel research agenda for scholars and practitioners working in this domain. Findings The integration of generative AI technologies, such as ChatGPT, will have a transformational impact on the hospitality and tourism industry. This study highlights the potential challenges of implementing such technologies from the perspectives of companies, customers and regulators. Research limitations/implications This study serves as a reference material for those who are planning to use generative AI tools like ChatGPT in their hospitality and tourism businesses. This study also highlights potential pitfalls that ChatGPT-enabled systems may encounter during service delivery processes. Originality/value This study is a pioneering work that assesses the applications of ChatGPT in the hospitality and tourism industry. This study highlights the potential and challenges in implementing ChatGPT within the hospitality and tourism industry.

Architecture & Planning• 2023• Emerald Publishing Limited
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Comparative Review of Energy Storage Systems, Their Roles, and Impacts on Future Power Systems

It is an exciting time for power systems as there are many ground-breaking changes happening simultaneously. There is a global consensus in increasing the share of renewable energy-based generation in the overall mix, transitioning to a more environmental-friendly transportation with electric vehicles as well as liberalizing the electricity markets, much to the distaste of traditional utility companies. All of these changes are against the status quo and introduce new paradigms in the way the power systems operate. The generation penetrates distribution networks, renewables introduce intermittency, and liberalized markets need more competitive operation with the existing assets. All of these challenges require using some sort of storage device to develop viable power system operation solutions. There are different types of storage systems with different costs, operation characteristics, and potential applications. Understanding these is vital for the future design of power systems whether it be for short-term transient operation or long-term generation planning. In this paper, the state-of-the-art storage systems and their characteristics are thoroughly reviewed along with the cutting edge research prototypes. Based on their architectures, capacities, and operation characteristics, the potential application fields are identified. Finally, the research fields that are related to energy storage systems are studied with their impacts on the future of power systems.

Architecture & Planning• 2018• Institute of Electrical and Electronics Engineers
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<b>ggtern</b>: Ternary Diagrams Using <b>ggplot2</b>

This paper presents the ggtern package for R, which has been developed for the rendering of ternary diagrams. Based on the well-established ggplot2 package (Wickham 2009), the present package adopts the familiar and convenient programming syntax of its parent. We demonstrate that ggplot2 can be used as the basis for producing specialized plotting packages and, in the present case, a package has been developed specifically for the production of high quality ternary diagrams. In order to produce ggtern, it was necessary to overcome a number of design issues, such as finding a means to modify existing geometries designed for a 2D Cartesian coordinate system and permitting them to function in an environment that requires an additional spatial aesthetic mapping. In the present paper, we provide examples of this package in its most basic form followed by a demonstration of its ease of use, particularly if one is familiar with, and has a predilection towards using ggplot2 on a regular basis.

Architecture & Planning• 2018• Foundation for Open Access Statistics
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Application of Big Data and Machine Learning in Smart Grid, and Associated Security Concerns: A Review

This paper conducts a comprehensive study on the application of big data and machine learning in the electrical power grid introduced through the emergence of the next-generation power system-the smart grid (SG). Connectivity lies at the core of this new grid infrastructure, which is provided by the Internet of Things (IoT). This connectivity, and constant communication required in this system, also introduced a massive data volume that demands techniques far superior to conventional methods for proper analysis and decision-making. The IoT-integrated SG system can provide efficient load forecasting and data acquisition technique along with cost-effectiveness. Big data analysis and machine learning techniques are essential to reaping these benefits. In the complex connected system of SG, cyber security becomes a critical issue; IoT devices and their data turning into major targets of attacks. Such security concerns and their solutions are also included in this paper. Key information obtained through literature review is tabulated in the corresponding sections to provide a clear synopsis; and the findings of this rigorous review are listed to give a concise picture of this area of study and promising future fields of academic and industrial research, with current limitations with viable solutions along with their effectiveness.

Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
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Opportunities and Challenges of Cloud Computing to Improve Health Care Services

Cloud computing is a new way of delivering computing resources and services. Many managers and experts believe that it can improve health care services, benefit health care research, and change the face of health information technology. However, as with any innovation, cloud computing should be rigorously evaluated before its widespread adoption. This paper discusses the concept and its current place in health care, and uses 4 aspects (management, technology, security, and legal) to evaluate the opportunities and challenges of this computing model. Strategic planning that could be used by a health organization to determine its direction, strategy, and resource allocation when it has decided to migrate from traditional to cloud-based health services is also discussed.

Architecture & Planning• 2011• JMIR Publications
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Microglia and Beyond: Innate Immune Cells As Regulators of Brain Development and Behavioral Function

Innate immune cells play a well-documented role in the etiology and disease course of many brain-based conditions, including multiple sclerosis, Alzheimer's disease, traumatic brain and spinal cord injury, and brain cancers. In contrast, it is only recently becoming clear that innate immune cells, primarily brain resident macrophages called microglia, are also key regulators of brain development. This review summarizes the current state of knowledge regarding microglia in brain development, with particular emphasis on how microglia during development are distinct from microglia later in life. We also summarize the effects of early life perturbations on microglia function in the developing brain, the role that biological sex plays in microglia function, and the potential role that microglia may play in developmental brain disorders. Finally, given how new the field of developmental neuroimmunology is, we highlight what has yet to be learned about how innate immune cells shape the development of brain and behavior.

Architecture & Planning• 2018• Frontiers Media
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Balancing Privacy and Progress: A Review of Privacy Challenges, Systemic Oversight, and Patient Perceptions in AI-Driven Healthcare

Integrating Artificial Intelligence (AI) in healthcare represents a transformative shift with substantial potential for enhancing patient care. This paper critically examines this integration, confronting significant ethical, legal, and technological challenges, particularly in patient privacy, decision-making autonomy, and data integrity. A structured exploration of these issues focuses on Differential Privacy as a critical method for preserving patient confidentiality in AI-driven healthcare systems. We analyze the balance between privacy preservation and the practical utility of healthcare data, emphasizing the effectiveness of encryption, Differential Privacy, and mixed-model approaches. The paper navigates the complex ethical and legal frameworks essential for AI integration in healthcare. We comprehensively examine patient rights and the nuances of informed consent, along with the challenges of harmonizing advanced technologies like blockchain with the General Data Protection Regulation (GDPR). The issue of algorithmic bias in healthcare is also explored, underscoring the urgent need for effective bias detection and mitigation strategies to build patient trust. The evolving roles of decentralized data sharing, regulatory frameworks, and patient agency are discussed in depth. Advocating for an interdisciplinary, multi-stakeholder approach and responsive governance, the paper aims to align healthcare AI with ethical principles, prioritize patient-centered outcomes, and steer AI towards responsible and equitable enhancements in patient care.

Architecture & Planning• 2024• Multidisciplinary Digital Publishing Institute
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Periodicals

Thrombus Composition and Efficacy of Thrombolysis and Thrombectomy in Acute Ischemic Stroke

Thrombi retrieved from patients with acute ischemic stroke are highly heterogeneous. Recent data suggest that thrombus composition may impact on mechanical thrombectomy, the number of recanalization manoeuvres, resistance to retrieval, and on thrombolytic potential. Our aim was to summarize evidence describing the impact of thrombus composition on efficacy of mechanical thrombectomy and thrombolysis in patients with acute ischemic stroke. The scoping review methodology guided by the Joanna Briggs Institute, an adaption of the Arksey and O'Malley, was followed. Comprehensive searches were conducted in MEDLINE, EMBASE, SCOPUS, and Web of Science. Articles were classified into 4 key themes: (1) composition of stroke thrombi, (2) thrombus composition and mechanical thrombectomy, (3) thrombus composition and thrombolytic therapy, and (4) novel imaging and endovascular approaches. Our search identified 698 articles published from 1987 to June 2020. Additional articles were extracted from reference lists of the selected articles. Overall, 95 topic-specific articles identified for inclusion published in 40 different journals were included. Reports showed that thrombus composition in stroke was highly heterogeneous, containing fibrin, platelets, red blood cells, VWF (von Willebrand Factor), and neutrophil extracellular traps. Thrombi could roughly be divided into fibrin- and red blood cell-rich clots. Fibrin-rich clots were associated with increased recanalization manoeuvres, longer procedure time, and less favorable clinical outcomes compared with red blood cell-rich clots. Advances in detection or treatment of thrombi that take into account clot heterogeneity may be able to improve future endovascular and thrombolytic treatment of stroke.

Architecture & Planning• 2021• Lippincott Williams & Wilkins
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Advances in greenhouse automation and controlled environment agriculture: A transition to plant factories and urban agriculture

Greenhouse cultivation has evolved from simple covered rows of open-fields crops to highly sophisticated controlled environment agriculture (CEA) facilities that projected the image of plant factories for urban agriculture. The advances and improvements in CEA have promoted the scientific solutions for the efficient production of plants in populated cities and multi-story buildings. Successful deployment of CEA for urban agriculture requires many components and subsystems, as well as the understanding of the external influencing factors that should be systematically considered and integrated. This review is an attempt to highlight some of the most recent advances in greenhouse technology and CEA in order to raise the awareness for technology transfer and adaptation, which is necessary for a successful transition to urban agriculture. This study reviewed several aspects of a high-tech CEA system including improvements in the frame and covering materials, environment perception and data sharing, and advanced microclimate control and energy optimization models. This research highlighted urban agriculture and its derivatives, including vertical farming, rooftop greenhouses and plant factories which are the extensions of CEA and have emerged as a response to the growing population, environmental degradation, and urbanization that are threatening food security. Finally, several opportunities and challenges have been identified in implementing the integrated CEA and vertical farming for urban agriculture. Keywords: smart agriculture, greenhouse modelling, urban agriculture, vertical farming, automation, internet of things (IoT), wireless sensor network, plant factories DOI: 10.25165/j.ijabe.20181101.3210 Citation: Shamshiri R R, Kalantari F, Ting K C, Thorp K R, Hameed I A, Weltzien C, et al. Advances in greenhouse automation and controlled environment agriculture: A transition to plant factories and urban agriculture. Int J Agric & Biol Eng, 2018; 11(1): 1–22.

Architecture & Planning• 2018• Chinese Society of Agricultural Engineering
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Particle Swarm Optimization: A Survey of Historical and Recent Developments with Hybridization Perspectives

Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has gained prominence in the last two decades due to its ease of application in unsupervised, complex multidimensional problems that cannot be solved using traditional deterministic algorithms. The canonical particle swarm optimizer is based on the flocking behavior and social co-operation of birds and fish schools and draws heavily from the evolutionary behavior of these organisms. This paper serves to provide a thorough survey of the PSO algorithm with special emphasis on the development, deployment, and improvements of its most basic as well as some of the very recent state-of-the-art implementations. Concepts and directions on choosing the inertia weight, constriction factor, cognition and social weights and perspectives on convergence, parallelization, elitism, niching and discrete optimization as well as neighborhood topologies are outlined. Hybridization attempts with other evolutionary and swarm paradigms in selected applications are covered and an up-to-date review is put forward for the interested reader.

Architecture & Planning• 2018• Multidisciplinary Digital Publishing Institute
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A critical investigation of Industry 4.0 in manufacturing: theoretical operationalisation framework

Increasing global competition on product quality and production costs, and the need for flexibility in production petition for transformed production processes which enable high level of connectivity and integration between business processes and systems. Much of the conventional computer- integrated efforts and advanced manufacturing technologies are limited in scope and restricted to only some organisational areas. Such limited scope, which stems from limited connectivity and integration between manufacturing and enterprise systems, confines the achievement of full potential of these systems within manufacturing. Industry 4.0, characterised by computing developments, can create a platform for addressing integration challenge through enabling comprehensive connectivity. Hence, this paper, through following deductive research paradigm and using systems theory as the theoretical base, aims to investigate recent academic research and industrial reports in the area of Industry 4.0 and smart manufacturing to provide detailed insights on execution of Industry 4.0, and to propose a theoretical framework for operationalisation of Industry 4.0 in manufacturing.

Architecture & Planning• 2018• Taylor & Francis
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LOCAL CLIMATE CHANGE AND URBAN HEAT ISLAND MITIGATION TECHNIQUES – THE STATE OF THE ART

Increase of the ambient air temperature in cities caused by the urban heat island phenomenon has a seri- ous impact on the economic and social system of cities. to counterbalance the consequences of the increased urban temperatures important research has been carried out resulting in the development of efficient mitigation technologies. the present paper aims to present the state of the art in terms of local climate change and urban heat island mitigation techniques. In particular, developments in the field on highly reflective materials, cool and green roofs, cool pavements, urban green and of other mitigation technologies are presented in detail, while examples of implemented projects are given.

Architecture & Planning• 2015• Taylor & Francis
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The What-If Tool: Interactive Probing of Machine Learning Models

A key challenge in developing and deploying Machine Learning (ML) systems is understanding their performance across a wide range of inputs. To address this challenge, we created the What-If Tool, an open-source application that allows practitioners to probe, visualize, and analyze ML systems, with minimal coding. The What-If Tool lets practitioners test performance in hypothetical situations, analyze the importance of different data features, and visualize model behavior across multiple models and subsets of input data. It also lets practitioners measure systems according to multiple ML fairness metrics. We describe the design of the tool, and report on real-life usage at different organizations.

Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
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Machine Learning-Based Network Vulnerability Analysis of Industrial Internet of Things

It is critical to secure the Industrial Internet of Things (IIoT) devices because of potentially devastating consequences in case of an attack. Machine learning (ML) and big data analytics are the two powerful leverages for analyzing and securing the Internet of Things (IoT) technology. By extension, these techniques can help improve the security of the IIoT systems as well. In this paper, we first present common IIoT protocols and their associated vulnerabilities. Then, we run a cyber-vulnerability assessment and discuss the utilization of ML in countering these susceptibilities. Following that, a literature review of the available intrusion detection solutions using ML models is presented. Finally, we discuss our case study, which includes details of a real-world testbed that we have built to conduct cyber-attacks and to design an intrusion detection system (IDS). We deploy backdoor, command injection, and Structured Query Language (SQL) injection attacks against the system and demonstrate how a ML-based anomaly detection system can perform well in detecting these attacks. We have evaluated the performance through representative metrics to have a fair point of view on the effectiveness of the methods.

Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
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Support Structures for Additive Manufacturing: A Review

Additive manufacturing (AM) has developed rapidly since its inception in the 1980s. AM is perceived as an environmentally friendly and sustainable technology and has already gained a lot of attention globally. The potential freedom of design offered by AM is, however, often limited when printing complex geometries due to an inability to support the stresses inherent within the manufacturing process. Additional support structures are often needed, which leads to material, time and energy waste. Research in support structures is, therefore, of great importance for the future and further improvement of additive manufacturing. This paper aims to review the varied research that has been performed in the area of support structures. Fifty-seven publications regarding support structure optimization are selected and categorized into six groups for discussion. A framework is established in which future research into support structures can be pursued and standardized. By providing a comprehensive review and discussion on support structures, AM can be further improved and developed in terms of support waste in the future, thus, making AM a more sustainable technology.

Architecture & Planning• 2018• Multidisciplinary Digital Publishing Institute
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Recurrent Neural Networks: A Comprehensive Review of Architectures, Variants, and Applications

Recurrent neural networks (RNNs) have significantly advanced the field of machine learning (ML) by enabling the effective processing of sequential data. This paper provides a comprehensive review of RNNs and their applications, highlighting advancements in architectures, such as long short-term memory (LSTM) networks, gated recurrent units (GRUs), bidirectional LSTM (BiLSTM), echo state networks (ESNs), peephole LSTM, and stacked LSTM. The study examines the application of RNNs to different domains, including natural language processing (NLP), speech recognition, time series forecasting, autonomous vehicles, and anomaly detection. Additionally, the study discusses recent innovations, such as the integration of attention mechanisms and the development of hybrid models that combine RNNs with convolutional neural networks (CNNs) and transformer architectures. This review aims to provide ML researchers and practitioners with a comprehensive overview of the current state and future directions of RNN research.

Architecture & Planning• 2024• Multidisciplinary Digital Publishing Institute
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Why Are Some Population Interventions for Diet and Obesity More Equitable and Effective Than Others? The Role of Individual Agency

We now find ourselves in a world in which one in three adults is overweight or obese Unhealthy diets are an important determinant of overweight and obesity and also contribute directly to a variety of other causes of disability and death. In fact, together with physical inactivity, dietary risk factors are responsible for 10% of disability-adjusted life years lost globally Like many risk factors, unhealthy diets are not evenly distributed in the population. In most developed countries, and increasingly in developing countries too, obesity and unhealthy diets are more common in more socioeconomically disadvantaged groups Socioeconomic inequalities in health and disease are at least partly due to these inequalities in diet and obesity.

Architecture & Planning• 2016• Public Library of Science
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Artificial General Intelligence: Concept, State of the Art, and Future Prospects

Abstract In recent years broad community of researchers has emerged, focusing on the original ambitious goals of the AI field - the creation and study of software or hardware systems with general intelligence comparable to, and ultimately perhaps greater than, that of human beings. This paper surveys this diverse community and its progress. Approaches to defining the concept of Artificial General Intelligence (AGI) are reviewed including mathematical formalisms, engineering, and biology inspired perspectives. The spectrum of designs for AGI systems includes systems with symbolic, emergentist, hybrid and universalist characteristics. Metrics for general intelligence are evaluated, with a conclusion that, although metrics for assessing the achievement of human-level AGI may be relatively straightforward (e.g. the Turing Test, or a robot that can graduate from elementary school or university), metrics for assessing partial progress remain more controversial and problematic.

Architecture & Planning• 2014• De Gruyter
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Cyber Threats Facing Autonomous and Connected Vehicles: Future Challenges

Vehicles are currently being developed and sold with increasing levels of connectivity and automation. As with all networked computing devices, increased connectivity often results in a heightened risk of a cyber security attack. Furthermore, increased automation exacerbates any risk by increasing the opportunities for the adversary to implement a successful attack. In this paper, a large volume of publicly accessible literature is reviewed and compartmentalized based on the vulnerabilities identified and mitigation techniques developed. This review highlighted that the majority of studies are reactive and vulnerabilities are often discovered by friendly adversaries (white-hat hackers). Many gaps in the knowledge base were identified. Priority should be given to address these knowledge gaps to minimize future cyber security risks in the connected and autonomous vehicle sector.

Architecture & Planning• 2017• Institute of Electrical and Electronics Engineers
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A paradigm shift: relationships in trauma-informed mental health services

Trauma-informed approaches emerged partly in response to research demonstrating that trauma is widespread across society, that it is highly correlated with mental health and that this is a costly public health issue. The fundamental shift in providing support using a trauma-informed approach is to move from thinking 'What is wrong with you?' to considering 'What happened to you?'. This article, authored by trauma survivors and service providers, describes trauma-informed approaches to mental healthcare, why they are needed and how barriers can be overcome so that they can be implemented as an organisational change process. It also describes how past trauma can be understood as the cause of mental distress for many service users, how service users can be retraumatised by 'trauma-uninformed' staff and how staff can experience vicariously the service user's trauma and can themselves be traumatised by practices such as restraint and seclusion. Trauma-informed mental healthcare offers opportunities to improve service users' experiences, improve working environments for staff, increase job satisfaction and reduce stress levels by improving the relationships between staff and patients through greater understanding, respect and trust. LEARNING OBJECTIVES: •Appreciate broad-based definitions of trauma•Gain an understanding of what trauma-informed approaches are and why they have emerged, including the potential for (re)traumatisation in the mental health system•Consider how to practise trauma-informed approaches, including in 'trauma-uninformed' organisations, and the potential barriers to and opportunities from doing so. DECLARATION OF INTEREST: A. S. is funded by a National Institute for Health Research (NIHR) Post-Doctoral Fellowship. This article presents independent research partially funded by the NIHR. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR or the Department of Health.

Architecture & Planning• 2018• Cambridge University Press
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New Games, New Rules: Big Data and the Changing Context of Strategy

Big data and the mechanisms by which it is produced and disseminated introduce important changes in the ways information is generated and made relevant for organizations. Big data often represents miscellaneous records of the whereabouts of large and shifting online crowds. It is frequently agnostic, in the sense of being produced for generic purposes or purposes different from those sought by big data crunching. It is based on varying formats and modes of communication (e.g., texts, image and sound), raising severe problems of semiotic translation and meaning compatibility. Crucially, the usefulness of big data rests on their steady updatability, a condition that reduces the time span within which this data is useful or relevant. Jointly, these attributes challenge established rules of strategy making as these are manifested in the canons of procuring structured information of lasting value that addresses specific and long-term organizational objectives. The developments underlying big data thus seem to carry important implications for strategy making, and the data and information practices with which strategy has been associated. We conclude by placing the understanding of these changes within the wider social and institutional context of longstanding data practices and the significance they carry for management and organizations.

Architecture & Planning• 2014• SAGE Publishing
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Role of Digital Transformation for Achieving Sustainability: Mediated Role of Stakeholders, Key Capabilities, and Technology

Sustainability through digital transformation is essential for contemporary businesses. Embracing sustainability, micro-, small-, and medium-sized enterprises (MSMEs) can gain a competitive advantage, attracting customers and investors who share these values. Moreover, incorporating sustainable practices empowers MSMEs to drive innovation, reduce costs, and enhance their reputation. This study aims to identify how owners or senior managers of MSMEs can initiate a sustainable digital transformation project. A systematic literature review was carried out, including 59 publications from 2019 to 2023. As a result, this research identifies the first steps owners of MSMEs can take to begin the transition by identifying critical organizational capabilities necessary for successful transformation, explores the technologies that can support MSMEs in their sustainability goals, and emphasizes the significance of stakeholders in achieving a successful digital transformation journey. Firstly, owners or senior managers should change the organizational culture to support decisions and strategies focus on sustainability. Secondly, the leading role of stakeholders is in the innovation process that allows businesses to be more competitive locally and globally. Finally, big data is the technology that can provide the most significant benefit to MSMEs because it will enable analyzing data of all kinds and contributes disruptively to decision-making.

Architecture & Planning• 2023• Multidisciplinary Digital Publishing Institute
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Multi-Sensor Fusion in Automated Driving: A Survey

With the significant development of practicability in deep learning and the ultra-high-speed information transmission rate of 5G communication technology will overcome the barrier of data transmission on the Internet of Vehicles, automated driving is becoming a pivotal technology affecting the future industry. Sensors are the key to the perception of the outside world in the automated driving system and whose cooperation performance directly determines the safety of automated driving vehicles. In this survey, we mainly discuss the different strategies of multi-sensor fusion in automated driving in recent years. The performance of conventional sensors and the necessity of multi-sensor fusion are analyzed, including radar, LiDAR, camera, ultrasonic, GPS, IMU, and V2X. According to the differences in the latest studies, we divide the fusion strategies into four categories and point out some shortcomings. Sensor fusion is mainly applied for multi-target tracking and environment reconstruction. We discuss the method of establishing a motion model and data association in multi-target tracking. At the end of the paper, we analyzed the deficiencies in the current studies and put forward some suggestions for further improvement in the future. Through this investigation, we hope to analyze the current situation of multi-sensor fusion in the automated driving process and provide more efficient and reliable fusion strategies.

Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
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