Search results

This paper aims to conduct a systematic literature review of the research in the field of Artificial Intelligence (AI) and Big Data Analytics (BDA) in Supply Chain Risk Management (SCRM). Finally, future research directions in this field have been suggested.

The papers were searched using a set of keywords in the SCOPUS database. These papers were filtered using the Title abstract keywords principle. Further, more papers were found using the forward-backward referencing method. The finalized papers were then classified into eight categories.

The previous papers in AI and BDA in SCRM were studied. These papers emphasized various modelling and application techniques for AI and BDA in making the supply chain (SC) more resilient. It was found that more research has been done into conceptual modelling rather than real-life applications. It was seen that the use of AI-based techniques and structural equation modelling was prominent.

AI and BDA help build the risk profile, which will guide the decision-makers and risk managers make their decisions quickly and more effectively, reducing the risks on the SC and making it resilient. Other than this, they can predict the risks in disasters, epidemics and any further disruption. They also help select the suppliers and location of the various elements of the SC to reduce the lead times.

The paper suggests various future research directions that fellow researchers can explore. None of the previous research examined the role of BDA and AI in SCRM.

Pressure, being one of the key variables investigated in scientific and engineering research, requires critical and accurate measurement techniques. With the advancements in materials and machining technologies, there is a large leap in the measurement techniques including the development of micro electromechanical systems (MEMS) sensors. These sensors are one to two orders smaller in magnitude than traditional sensors and combine electrical and mechanical components that are fabricated using integrated circuit batch-processing technologies. MEMS are finding enormous applications in many industrial fields ranging from medical to automotive, communication to electronics, chemical to aviation and many more with a potential market of billions of dollars. MEMS pressure sensors are now widely used devices owing to their intrinsic properties of small size, light weight, low cost, ease of batch fabrication and integration with an electronic circuit. This paper aims to identify and analyze the common pressure sensing techniques and discuss their uses and advantages. As per our understanding, usage of MEMS pressure sensors in the aerospace industry is quite limited due to cost constraints and indirect measurement approaches owing to the inability to locate sensors in harsh environments. The purpose of this study is to summarize the published literature for application of MEMS pressure sensors in the said field. Five broad application areas have been investigated including: propulsion/turbomachinery applications, turbulent flow diagnosis, experimentalaerodynamics, micro-flow control and unmanned aerial vehicle (UAV)/micro aerial vehicle (MAV) applications.

The first part of the paper deals with an introduction to MEMS pressure sensors and mathematical relations for its fabrication. The second part covers pressure sensing principles followed by the application of MEMS pressure sensors in five major fields of aerospace industry.

In this paper, various pressure sensing principles in MEMS and applications of MEMS technology in the aerospace industry have been reviewed. Five application fields have been investigated including: Propulsion/Turbomachinery applications, turbulent flow diagnosis, experimental aerodynamics, micro-flow control and UAV/MAV applications. Applications of MEMS sensors in the aerospace industry are quite limited due to requirements of very high accuracy, high reliability and harsh environment survivability. However, the potential for growth of this technology is foreseen due to inherent features of MEMS sensors’ being light weight, low cost, ease of batch fabrication and capability of integration with electric circuits. All these advantages are very relevant to the aerospace industry. This work is an endeavor to present a comprehensive review of such MEMS pressure sensors, which are used in the aerospace industry and have been reported in recent literature.

As per the author’s understanding, usage of MEMS pressure sensors in the aerospace industry is quite limited due to cost constraints and indirect measurement approaches owing to the inability to locate sensors in harsh environments. Present work is a prime effort in summarizing the published literature for application of MEMS pressure sensors in the said field. Five broad application areas have been investigated including: propulsion/turbomachinery applications, turbulent flow diagnosis, experimental aerodynamics, micro-flow control and UAV/MAV applications.

Barge-type offshore floating wind turbine (OFWT) commonly exhibits an under-actuated phenomenon in an offshore environment, which leads to a potential vibration-damping hazard. This article aims to provide a new robust output feedback anti-vibrational control scheme for the novel translational oscillator with rotational actuator (TORA) based five-degrees of freedom (5-DOF) barge-type OFWT in the presence of unwanted disturbances and modeling uncertainties.

In this paper, an active control technique called TORA has been used to design a 5-DOF barge-type OFWT model, where the mathematical model of the proposed system is derived by using Euler–Lagrange's equations. The robust hierarchical backstepping integral nonsingular terminal sliding mode control (HBINTSMC) with an adaptive gain is used in conjunction with extended order high gain observer (EHGO) to achieve system stabilization in the presence of unwanted disturbances and modeling uncertainties. The numerical simulations based on MATLAB/SIMULINK have been performed to demonstrate the feasibility and effectiveness of the proposed model and control law.

The numerical simulation results affirm the accuracy and efficiency of the proposed control law for the TORA based OFWT system. The results demonstrate that the proposed control law is robust against unwanted disturbances and uncertainties. The unknown states are accurately estimated by EHGO which enables the controller to exhibit improved stabilization performance.

A new mathematical model of the 5-DOF barge-type OFWT system based on TORA is the major contribution of this research paper. Furthermore, it provides a new adaptive anti-vibration control scheme by incorporating the EHGO for the proposed model.

This volume explores the intersection of youth agency, media representation, and conflict, urging a reevaluation of the roles of youth in contemporary socio-political contexts. Media serves as a tool for and a site of resistance. Chapters in this volume highlight ways in which children and youth leverage digital platforms to reshape narratives around conflict and peace. The compilation draws from a wide range of contexts, from the Balkan Wars to the current conflicts in Syria and Ukraine, offering in-depth analyses of the transformative potential of the (re)imagining of youth experiences, thus shifting from passive subjects to active narrators. This reorientation emphasizes the role of new technologies, including digital media and artificial intelligence, in supporting these endeavors, especially in enhancing mental health and psychological resilience among children affected by conflict.

Poverty is a powerful context that affects billions of consumers around the world. An appreciation of this context and the ways it shapes thoughts, feelings, and behaviors is essential to understanding the vulnerabilities of low socioeconomic status (SES) consumers. We synthesize research on consumption in poverty by reviewing some of the social vulnerabilities and frequent neglect, discrimination, and stigmatization encountered by low-SES consumers, as well as the cognitive challenges emerging from the experience of financial scarcity. These social, cognitive, and societal vulnerabilities highlight the importance of behaviorally informed programs and policies to address consumer vulnerability in contexts of poverty.

Data literacy – the ability to read, analyze, interpret, evaluate and argue with data and data visualizations – is an essential competency in social studies. This study aims to examine the degree to which US state standards require teachers to teach data literacy in social studies, addressing the questions: to what extent are US social studies teachers required to teach data literacy? If they are required to teach it, are they provided with guidance about competencies to address at each school or grade level and with respect to particular content?

The study used content analysis, using a variety of priori and emergent codes, to review social studies standards documents from all 50 states and the District of Columbia.

Findings indicate that although state standards suggest that data visualizations should play a role in social studies instruction, they provide poor guidance for a coherent, progressive and critical approach across grade levels.

Researchers currently know little about if and how teachers address data literacy in social studies education. This study provides a snapshot of guidance teachers across states are given for teaching data literacy, and by extension, the quality of data literacy instruction recommended for students across the USA.

Pakistan is one of the most climate change and natural disaster-affected countries in the globe, where the lives and livelihoods of people are repeatedly affected due to these natural disasters. Over the past few decades, the country has been impacted by numerous devastating floods, droughts, and storms. As a result, households face enormous complications, particularly those dwelling in disaster-prone areas. Therefore, this study intends to explore the status of household vulnerability and resilience practices of hazard-prone communities in Pakistan from existing literature. This study has identified the 17 most relevant documents. It argues that household vulnerability is increasing consistently with the increasing rate of disaster intensity. Frequent flooding, landslide, erosion, and crop loss are the leading causes of household vulnerability. This study reveals five types of household vulnerability components which look into several livelihood vulnerability indicators of Pakistani households. Moreover, the study unfolds that the main causes of disaster vulnerability are widespread crop loss, a lack of water, loss of soil fertility, and low socioeconomic situations. The major vulnerability components of dwellers are exposure (increasing summer duration, the rapid increase of population house build-up in the riparian areas, and increasing occurrence of hailstorms), sensitivity, low access to education facilities, human loss, diseases infestation, food insecurity, and social conflict), and less adaptive capacity (social networks, migration, poor emergency services, multiple income sources, and less access to the health facility). To address the household vulnerability, this study has also identified four key aspects of resilience, like social resilience, economic resilience, institutional resilience, and physical resilience. The findings will effectively help to understand the dynamics of household vulnerability and resilience and its measurement and management strategy from developed indicators.

The nineties of the 20th century were marked by wars at the breakup of Yugoslavia, by a generation of children whose lives turned overnight. Many had to leave their homes and become refugees. What was a reality for many children is also reflected in literature whose protagonists are coming-of-age children. The novels Ukulele Jam by Alen Mešković and Hotel Zagorje by Ivana Simić Bodrožić as a primary motive take European tragedy whose consequences still resonate today. There are two ways in which youth literature represents war – as the scenery or as the central theme of a story. War is a political and social event whose effects are transmitted to everyone regardless of gender, age, or social status. As the portrayal of literary heroes strives to be as believable and authentic as possible, the lives of literary characters trapped in the vortex of war reflect the same characteristics. Life routines change; there is often a school dropout, lack of food, children’s play changes, and children, in addition to the general poverty and chaos, also face the loss of friends, family members, violence, and home. The environment often begins to reject them. In the formerly known world, they appear as aliens who need to be removed or adapted to the new society. The transition from the socialist to the capitalist socio-economic system was based on repeated repatriarchalization, in particular in strengthening the old public and private dichotomies and reviving conservative ideologies on the family and gender.

Meal ordering apps (MOAs) have transformed the customers' dining habits, particularly during mobility restrictions of the COVID-19 pandemic. Under the theoretical cover of the extended stimulus–organism–response (SOR) model, this paper attempts to explore the critical antecedents and outcomes of customer MOA engagement which predict the continuous purchase intentions using these apps. A multigroup analysis is conducted to investigate the difference between the hypothesized relationships between the Chinese and Indonesian consumers.

A mixed-method approach, including a systematic literature review, an open-ended essay (qualitative) with 139 MOA users and an online survey (quantitative) with 1,207 MOA users in total, was used for hypotheses testing.

The structural equation model results revealed that customer MOA experience factors such as mobile online reviews (MR), food quality (FQ), restaurant reputation (RR), service quality and system quality (SyQ) are the absolute positive factors that influence customer MOA cognitive, affective and behavioral engagement, which in turn affect continuous purchase intentions. The multigroup analysis results reveal that Chinese customers prioritized MR and FQ for customer MOA engagement (cognitive, affective and behavioral). Comparatively, Indonesian customers placed most importance on RR and SyQ.

Considering a market-specific setting and based on the extended SOR framework, this study is one of the first to take a comprehensive look at the critical antecedents and outcome of multidimensional customer MOA engagement in the developing countries’ (China and Indonesia) online to offline meal delivery context. Further, this study investigates the customer continuous purchase intentions as an outcome of MOA engagement during the COVID-19 pandemic. The findings also reveal the differences in consumer behavior across the two developing but culturally diverse countries samples during the pandemic.

This chapter examines the transformative role of artificial intelligence (AI) in supporting children and youth affected by armed conflicts, focusing on the integration of AI with humanitarian aid and child psychology. While AI is predominantly recognized for its capability in logistical and analytical tasks, we highlight its potential to address the emotional and psychological needs of vulnerable populations in armed conflict. By employing an interdisciplinary approach, the study bridges the gaps between technology, psychological support, and humanitarian efforts. The discussion extends into the ethical dimensions of AI application in conflict environments, emphasizing the importance of developing international regulations and standards that ensure responsible technology use. AI has the potential to enhance traditional humanitarian operations and innovate the means of delivering emotional and psychological support to affected children. AI-driven tools, such as empathetic computing and Natural Language Processing, can amplify the voices of young individuals, facilitating better understanding and support by capturing and analyzing their experiences and emotional states. By influencing policymakers, technologists, and humanitarian workers, there is scope for thoughtful development and deployment of AI technologies to improve the resilience and recovery of children in conflict spaces to ensure their psychological well-being and emotional safety.