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The performance of large-scale projects is often challenged due to major environmental changes that occur during their life. However, literature has paid little attention to the governance adaptations required to respond effectively to these changes. This paper aims to study changes in the project environment over time, the corresponding governance adaptations and their impact on project performance.

To ensure triangulation between two sources of evidence, we used both primary and secondary data sources and examined 14 projects through 2 studies, the first focused on seven documented, illustrative case projects and the second on interviews with senior and project managers involved in seven additional projects.

We found the key environmental changes that should trigger appropriate governance adaptations to be market evolutions, technological advancements and sociopolitical events. However, we also found that these necessary governance adaptations are not commonly implemented timely, sufficiently or effectively.

The paper distills the dynamics of large-scale projects in achieving project effectiveness and raises theoretical propositions on the combination of environmental changes and deficient governance adaptations that, over time, turns efficient projects into ineffective projects and discusses implications for theory and practice.

This conceptual paper aims to contribute to a better understanding of value creation and value capture with smart resources in the Internet of Things (IoT)-driven business models against the backdrop of an increasingly networked and connectivity-based environment. More specifically, the authors screen strategic management theories and adapt them to the specificities of new types of smart resources by focusing on a conceptual analysis of isolating mechanisms that enable value creation and value capture based upon different types of smart resources.

By adapting the state of the art of the contemporary resource-based discussion (resource-based view, dynamic capabilities view, relational view, resource-based view for a networked environment) to the context of IoT-driven business models, the paper typifies valuable intra- and inter-organisational resource types. In the next step, a discursive discussion on the evolution of isolating mechanisms, which are assumed to enable the translation of value creation into value appropriation, adapts the resource-based view for a networked environment to the context of IoT-driven business models.

The authors find that connectivity shapes both opportunities and challenges for firms, e.g. focal firms, in such business models, but it is notably social techniques that help to generate connectivity and transform inter-organisational ties into effective isolating mechanisms.

This paper lays a foundation for a theoretically underpinned understanding of how IoT can be exploited through designing economically sustainable business models. In this paper, research propositions are established as a point of departure for future research that applies strategic management theories to better understand business models that work with the digitisation and connectivity of resources on different levels.

Nanotechnology (NT) advancements in personal protective textiles (PPT) or personal protective equipment (PPE) have alleviated spread and transmission of this highly contagious viral disease, and enabled enhancement of PPE, thereby fortifying antiviral behavior.

Review of a series of state of the art research papers on the subject matter.

This paper expounds on novel nanotechnological advancements in polymeric textile composites, emerging applications and fight against COVID-19 pandemic.

As a panacea to “public droplet prevention,” textiles have proven to be potentially effective as environmental droplet barriers (EDBs).

PPT in form of healthcare materials including surgical face masks (SFMs), gloves, goggles, respirators, gowns, uniforms, scrub-suits and other apparels play critical role in hindering the spreading of COVID-19 and other “oral-respiratory droplet contamination” both within and outside hospitals.

When used as double-layers, textiles display effectiveness as SFMs or surgical-fabrics, which reduces droplet transmission to <10 cm, within circumference of ∼0.3%.

NT advancements in textiles through nanoparticles, and sensor integration within textile materials have enhanced versatile sensory capabilities, robotics, flame retardancy, self-cleaning, electrical conductivity, flexibility and comfort, thereby availing it for health, medical, sporting, advanced engineering, pharmaceuticals, aerospace, military, automobile, food and agricultural applications, and more. Therefore, this paper expounds on recently emerging trends in nanotechnological influence in textiles for engineering and fight against COVID-19 pandemic.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

This study aims to highlight that security and flexibilities remain the main points of contention in the cordiality business. This research points to planning a framework that empowers hotel users to get to the room using a mobile access key. Advancing secured facilities, mobile phone “Near Field Communication” (NFC) innovation as the entrance device by carrying out an application containing an imitated mobile key for explicit verification access is used.

The proposed system is evaluated by triangulation of experimental, numerical and rational evaluation using partial least square structural equation modeling (PLS-SEM) with Malaysian hotel guests and employees.

The discoveries with the hypothesis supported validated that the suggested solution can eliminate physical cards, boost protection and encourage a contactless ecosystem. Theoretical, management and societal contributions are discussed here.

This experiment comes with the constraints that it was conducted in only two hotels and does not fully reflect the choices of a wider range of travellers. Secondly, the cost of existing NFC smart locks is still relatively high, and along with the development of technology, the price will decrease when supply exceeds demand.

To promote high-security attributes, NFC technology as the access system by implementing an application containing an emulated smart key for specific authentication access is used. The host-card emulation enables cost-effectiveness profit and initiating a defence system in the pandemic era.

To promote high-security attributes, NFC technology is used as the access system by implementing an application containing an emulated smart key for specific authentication access. The host-card emulation enables cost-effectiveness profit and initiating a defence system in the pandemic era.

The novelty of this study comes from the use of commonly available smartphone NFC features that are yet to be applied in the tourism ecosystem. The research provokes the applied concept of mobile smartkeys.

Engineering graduates are expected to have certain attributes in addition to technical expertise that includes development in personal and interpersonal skills with societal concern. Pedagogical strategies have been continuously evolving to improve the graduate attributes. An efficient framework for blended learning that improves the graduate attributes is the need of the hour now.

A blended course model based on TPACK is proposed and the same is evaluated with Kirkpatrick evaluation method to assess the attainment of the attributes. A mapping strategy is developed for the relation between course outcomes and graduate attributes. The proposed model is tested with “Microcontroller” course in undergraduate program with students of three consecutive years in three different learning environments: offline, online and blended. The performance of the students in assessments, students’ feedback and their interest towards additional learning, project skills and job recruitment are the different elements taken for analysis.

The results obtained show that the impact of the proposed blended learning framework in improving the graduate attributes is greater than the offline environments. The analysis is done based on Kirkpatrick evaluation, which demonstrates the improvement in graduate attributes in blended learning by 18% compared to offline mode.

It is seen that blended learning shall be implemented using TPACK model effectively and the proposed model results in improvement of graduate attributes. Though the findings are good enough, the case study is limited to a particular organization and so, the various underlying parameters may vary for different institutions.

The methodology proposed is viable in any institution and may be tested for any program. The effectiveness of the blended learning is known and in this case study, the analysis from the course to the level of program is done.

The research work highlights the integration of technology, pedagogy and content knowledge to enhance engineering students' skills. Hence, it explores a new required norms of education, potentially shaping future teaching learning methodologies. By employing the Kirkpatrick evaluation, it offers insights into the model's effectiveness and influences educational practices in the need of the hour.

The proposed method and results signifies an innovative endeavor that combines technological expertise, pedagogical methods and subject matter knowledge to enhance the attributes of engineering graduates. Kirkpatrick evaluation adds a distinct dimension by objectively assessing the model's impact. The results are analyzed from the original data obtained from a particular institution.

The purpose of this paper is to approach predictive maintenance (PdM) of brushless direct current (BLDC) motors using audio signal processing and extracting statistical and spectral features to train classical machine learning (ML) models.

The proposed methodology relies on classification predictive model that shows the motors prone to failure. To verify this, the model was implemented and tested with audio data. The trained models are then deployed to an Industrial Internet of Things (IIoT) application built using Django.

The implementation of the methodology allows for achieving performance as high as 92% accuracy, proving that spectral features should be considered when training ML models for PdM.

The proposed model is an effective decision-making tool that provides an ideal solution for preventive maintenance scheduling problems for BLDC motors.

The aim of this paper is to enhance the control performance of dexterous hands, enabling them to handle the high data flow from multiple sensors and to meet the deployment requirements of deep learning methods on dexterous hands.

A distributed control architecture was designed, comprising embedded motion control subsystems and a host control subsystem built on ROS. The design of embedded controller state machines and clock synchronization algorithms ensured the stable operation of the entire distributed control system.

Experiments demonstrate that the entire system can operate stably at 1KHz. Additionally, the host can accomplish learning-based estimates of contact position and force.

This distributed architecture provides foundational support for the large-scale application of machine learning algorithms on dexterous hands. Dexterity hands utilizing this architecture can be easily integrated with robotic arms.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.