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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.

Poor performance remains a challenge for the construction industry worldwide. One of the key performance indicators of the construction industry is the timely delivery of projects. Despite the recent methodological and technological advances in the field, project-overrun remains a significant challenge for the industry. This paper seeks to propose practical solutions that allow overcoming the challenges and promote the opportunities for improving the performance of the construction projects in Dubai.

This study focussed on the construction projects in Dubai; therefore, this research adopted a sequential mixed approach in two stages. The first stage involved face-to-face interviews with seven carefully selected construction professionals. Their answers were analysed to provide with the literature study “the informed-basis for the development of the online questionnaire”. The second stage involved an online survey administrated to 425 carefully selected construction organisations working in Dubai. Accordingly, a meticulous analysis for the prime causes of project overruns has also been undertaken. This analysis assisted proposing the most suitable solutions-based technologies that enabled alleviating overruns in the construction projects.

The findings revealed that, there was a consensus agreement on the formidable opportunities for improving the performance of the construction industry in general and in particular in Dubai. These opportunities are intrinsically linked with the adoption of the latest technologies such as building information modelling, augmented reality, virtual reality and the artificial intelligence (AI). Whereas, adopting AI has already assisted two public authorities to release No Objection Certificates and work permits effectively within one day instead of 14 working days, which has saved 90% of the time and cost. Likewise, adoption of the AI has assisted delivering the construction project with a 9% of time saving and a 6% of cost saving due to embracing an automated system that enabled them to instantly detect and report the delays, once occurred.

The main limitation of this study is that the study was limited to the construction industry in the Emirate of Dubai. Therefore, future research could target the whole United Arab Emirates construction industry to propose the practical solution on the country level.

The literature study is replete with solutions, which tend to be theoretical more than practical. Therefore, the proposed practical recommendations will significantly assist the construction industry to improve its suboptimal performance to rescind the sovereignty of the irrelevant involvements. The research recommended establishing independent entity to lead the change in the construction industry; this entity will have the power of enacting rules and legislations. Furthermore, this independent entity will have the power and authority of dictations and impose sanctions on the non-committed organisations that are reluctant to adopt the recommended technologies and approaches.

Based on the findings of the study, this paper draws a road map for the construction industry by determining practical solutions for improvements starting with an establishment of an independent authority that selects and tests the most appropriate technologies and approaches to contribute to performance improvements.

Managing project completion within the stipulated time is significant to all firms' sustainability. Especially for software start-up firms, it is of utmost importance. For any schedule variation, these firms must spend 25 to 40 percent of the development cost reworking quality defects. Significantly, the existing literature does not support defect rework opportunities under quality aspects among Indian IT start-ups. The present study aims to fill this niche by proposing a unique mathematical model of the defect rework aligned with the Six Sigma quality approach.

An optimization model was formulated, comprising the two objectives: rework “time” and rework “cost.” A case study was developed in relevance, and for the model solution, we used MATLAB and an elitist, Nondominated Sorting Genetic Algorithm (NSGA-II).

The output of the proposed approach reduced the “time” by 31 percent at a minimum “cost”. The derived “Pareto Optimal” front can be used to estimate the “cost” for a pre-determined rework “time” and vice versa, thus adding value to the existing literature.

This work has deployed a decision tree for defect prediction, but it is often criticized for overfitting. This is one of the limitations of this paper. Apart from this, comparing the predicted defect count with other prediction models hasn’t been attempted. NSGA-II has been applied to solve the optimization problem; however, the optimal results obtained have yet to be compared with other algorithms. Further study is envisaged.

The Pareto front provides an effective visual aid for managers to compare multiple strategies to decide the best possible rework “cost” and “time” for their projects. It is beneficial for cost-sensitive start-ups to estimate the rework “cost” and “time” to negotiate with their customers effectively.

This paper proposes a novel quality management framework under the Six Sigma approach, which integrates optimization of critical metrics. As part of this study, a unique mathematical model of the software defect rework process was developed (combined with the proposed framework) to obtain the optimal solution for the perennial problem of schedule slippage in the rework process of software development.

In the reduction of food waste and the provision of food to the hungry, food banks play critical roles. However, as they are generally run by charitable organisations that are chronically short of human and other resources, their inbound logistics efforts commonly experience difficulties in two key areas: 1) how to organise stocks of donated food, and 2) how to assess the donated items quality and fitness for purpose. To address both these problems, the authors aimed to develop a novel artificial intelligence (AI)-based approach to food quality and warehousing management in food banks.

For diagnosing the quality of donated food items, the authors designed a convolutional neural network (CNN); and to ascertain how best to arrange such items within food banks' available space, reinforcement learning was used.

Testing of the proposed innovative CNN demonstrated its ability to provide consistent, accurate assessments of the quality of five species of donated fruit. The reinforcement-learning approach, as well as being capable of devising effective storage schemes for donated food, required fewer computational resources that some other approaches that have been proposed.

Viewed through the lens of expectation-confirmation theory, which the authors found useful as a framework for research of this kind, the proposed AI-based inbound-logistics techniques exceeded normal expectations and achieved positive disconfirmation.

As well as enabling machines to learn how inbound logistics are handed by human operators, this pioneering study showed that such machines could achieve excellent performance: i.e., that the consistency provided by AI operations could in future dramatically enhance such logistics' quality, in the specific case of food banks.

This paper’s AI-based inbound-logistics approach differs considerably from others, and was found able to effectively manage both food-quality assessments and food-storage decisions more rapidly than its counterparts.

The purpose of this study is to examine the risks of the metaverse ecosystem. This study provides an overview of the metaverse and its evolution and discusses the various fraud risks it poses for organizations (including boards of directors, forensic accountants, auditors and accountants). Given the advantages of the metaverse and the growing interest it is attracting from organizations, this paper sheds light on the importance of mitigating its risks.

Based on a systematic review of the literature on the metaverse and analysis of the fraud triangle, this study examines the different fraud risks it poses. More specifically, this study analyzes 21 articles on the metaverse published between 2021 and 2022 and attempts to answer the following research questions: What are the risks inherent in the metaverse? What are the fraud risks associated with it? What are the opportunities and pressures it brings? What is the rationalization underlying its use? This study conducts the analysis on two levels, that of the individual (user) and that of the organization. This paper summarizes the findings of publications on the metaverse in 2021 and 2022 to discover its various definitions and the opportunities and risks it represents.

This paper offers an insightful discussion of the advantages and risks the metaverse can bring. Because this analysis shows that any organization could be vulnerable to metaverse risks, this study provides organizations with strategies to deter, detect and prevent fraud and reputational risks. Regulatory bodies, financial authorities, board of directors and fraud investigators should all consider these risks before investing in the metaverse.

This paper adds new insights to the scarce research on the metaverse and cybersecurity by exploring the opportunities and risks it presents. It has several implications for organizations, boards of directors, management and regulatory authorities.

This paper aims to design a magnetostrictive tactile sensor for surface depth detection. Unlike the human finger, although most tactile sensors have high sensitivity to pressure, they cannot detect millimeter-level depth information on the surface of objects precisely. To enhance the ability to detect surface depth information, a piezomagnetic sensor combining inverse magnetostrictive effect and bionic structure is developed in this paper.

A magnetostrictive tactile sensor based on Galfenol [(Fe₈₃Ga₁₇)_99.4B_0.6] is designed and studied for surface depth measurement. The optimal structure of the sensor is determined by experiment and theory. The test platforms for static and dynamic characteristics are set up. The static and the dynamic sensing performance of the sensor are studied experimentally.

The sensor can detect 0–2 mm depth change with a sensitivity of 91.5 mV/mm. A resolution of 50 µm can be achieved in the depth direction. In 50 cycles of loading and unloading tests, the maximum error of the sensor output voltage amplitude is only 2.23%.

The sensor can measure the depth information of object surface precisely with good repeatability through sliding motion and provide reference for object surface topography detection.

The purpose of this paper is to show that the growing global trend of quality assurance indicates the potential of precast concrete (PC) to improve construction quality and productivity, reduce wasteful construction, and achieve design standardization and to accelerate construction time. However, its current approach for dynamic characteristics, such as stiffness and displacement on beam-column connection system design, is not effective in achieving the required quality and operational requirements.

A design tool based on the literature and data analysis in product planning and safety is proposed for the practice of PC building construction.

The results reveal the need for improvement of PC building performance in the construction industry, especially for the beam-column connection system. The issues include improper design, improper specification and defective concrete and steel components compared to other manufacturing methods.

A novel and sophisticated technique based on physical internet-enabled building information modeling (PI-BIM) is proposed to improve the planning process and safety for PC buildings in Malaysia.

The computing power of the legged robot is not enough to perform high-frequency updates for the full-body model predictive control (MPC) of the robot, which is a common problem encountered in the gait research of the legged robot. The purpose of this paper is to propose a high-frequency MPC control method for the bounding gait of a parallel quadruped robot.

According to the bounding gait characteristics of the robot, the quadruped robot model is simplified to an equivalent plane bipedal model. Under the biped robot model, the forces between the robot’s feet and the ground are calculated by MPC. Then, the authors apply a proportional differential controller to distribute these forces to the four feet of the quadruped robot. The robot video can be seen at www.bilibili.com/video/BV1je4y1S7Rn.

To verify the feasibility of the controller, a prototype was made, and the controller was deployed on the actual prototype and then fully analyzed through experiments. Experiments show that the update frequency of MPC could be stabilized at 500 Hz while the robot was running in the bounding gait stably and efficiently.

This paper proposes a high-frequency MPC controller under the simplified model, which has a higher working efficiency and more stable control performance.

This chapter provides the historical and intellectual context of studying inequality and domination using the symbolic interactionist perspective. Lonnie Athens' radical interactionism was identified as a useful framework to research the omnipresent and insidious inequality found in everyday life. Chapters presented in this volume represent a follow up of Volume 41 of Studies in Symbolic Interaction, edited by Athens, where he laid the ground work for the research of domination and subordination. Chapters in this volume demonstrate the advancements made in studying inequality in symbolic interactionist research.

Breast cancer has become the largest cancer in the world today. Health problems for women with breast cancer need to be addressed urgently. This study aims to select the best method for preparing temperature-sensitive sports underwear, and to verify the feasibility of using K-type thermocouple threads in underwear fabrics.

In the experiments, two samples were designed for temperature-sensitive performance tests and the effects produced by different outer layer structures were investigated. In the second step, K-type thermocouple wires were integrated into sports underwear. The comfort and feasibility of the temperature-sensitive underwear were investigated.

It was finally verified to obtain the best comfort and temperature-sensing performance of K-type thermocouple filaments integrated into sports underwear with plain stitching.

The underwear has a certain prospect for the application of smart apparel based on breast cancer health monitoring, which is of some significance for monitoring smart apparel.