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The purpose of this paper is to propose a whole set of methods for underwater target detection, because most underwater objects have small samples, low quality underwater images problems such as detail loss, low contrast and color distortion, and verify the feasibility of the proposed methods through experiments.

The improved RGHS algorithm to enhance the original underwater target image is proposed, and then the YOLOv4 deep learning network for underwater small sample targets detection is improved based on the combination of traditional data expansion method and Mosaic algorithm, expanding the feature extraction capability with SPP (Spatial Pyramid Pooling) module after each feature extraction layer to extract richer feature information.

The experimental results, using the official dataset, reveal a 3.5% increase in average detection accuracy for three types of underwater biological targets compared to the traditional YOLOv4 algorithm. In underwater robot application testing, the proposed method achieves an impressive 94.73% average detection accuracy for the three types of underwater biological targets.

Underwater target detection is an important task for underwater robot application. However, most underwater targets have the characteristics of small samples, and the detection of small sample targets is a comprehensive problem because it is affected by the quality of underwater images. This paper provides a whole set of methods to solve the problems, which is of great significance to the application of underwater robot.

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.

The purpose of this paper is to compile a comprehensive status report on pipes/piping networks across different industrial sectors, along with specifications of materials and sizes, and showcase welding avenues. It further extends to highlight the promising friction stir welding as a single solid-state pipe welding procedure. This paper will enable all piping, welding and friction stir welding stakeholders to identify scope for their engagement in a single window.

The paper is a review paper, and it is mainly structured around sections on materials, sizes and standards for pipes in different sectors and the current welding practice for joining pipe and pipe connections; on the process and principle of friction stir welding (FSW) for pipes; identification of main welding process parameters for the FSW of pipes; effects of process parameters; and a well-carved-out concluding summary.

A well-carved-out concluding summary of extracts from thoroughly studied research is presented in a structured way in which the avenues for the engagement of FSW are identified.

The implications of the research are far-reaching. The FSW is currently expanding very fast in the welding of flat surfaces and has evolved into a vast number of variants because of its advantages and versatility. The application of FSW is coming up late but catching up fast, and as a late starter, the outcomes of such a review paper may support stake holders to expand the application of this process from pipe welding to pipe manufacturing, cladding and other high-end applications. Because the process is inherently inclined towards automation, its throughput rate is high and it does not need any consumables, the ultimate benefit can be passed on to the industry in terms of financial gains.

To the best of the authors’ knowledge, this is the only review exclusively for the friction stir welding of pipes with a well-organized piping specification detailed about industrial sectors. The current pipe welding practice in each sector has been presented, and the avenues for engaging FSW have been highlighted. The FSW pipe process parameters are characteristically distinguished from the conventional FSW, and the effects of the process parameters have been presented. The summary is concise yet comprehensive and organized in a structured manner.

Scuba diving tourism is reputed to be a potential low-impact recreational activity that allow environmental conservation and socioeconomic benefits for local communities. Few studies have addressed the issue of sustainability of scuba diving tourism through the simultaneously investigation on the economic and socio-cultural aspects and its implications for tourism development. This study aims to examine the scuba diving tourism in three under-explored North African tourism destinations with high ecotourist potential. The authors present an exploratory picture of scuba diving tourist demand, divers' preferences, motivations for recreational diving experiences and their propensity towards conservation.

The authors developed a case study research strategy collecting profile data on 123 divers. Furthermore, regression analysis was performed to investigate the divers' preferences, motivations and propensity towards conservation.

The divers' limited number, the presence of mainly local seasonal tourists and a moderate propensity towards conservation influence the potential of the diving tourism segment to generate significant socioeconomic benefits for local sustainable development in these destinations. However, establishing a marine protected area (MPA) could foster the development of a long-term strategy for scuba diving tourism, improve conservation awareness and increase divers' satisfaction.

Diverse profiles, preferences and motivations can provide tools to sustainably manage and preserve coastal and marine biodiversity, while also maximising the quality of the recreational experience. One of the most effective site-based strategies to orient the diving sector towards sustainability involves the design and strengthening of MPAs.

The research provides an original contribution to the debate on sustainable tourism strategies by demonstrating how the study of economic and socio-cultural aspects of scuba diving could provide guidelines to orient the tourism development of marine and coastal areas towards the principles of sustainability (also through the establishment of MPAs). The findings present an overview of the sustainability of the scuba diving tourism segment by investigating the preferences, motivations and inclination towards conservation among tourists for whom the diving experience is not a core holiday activity.

This study aims to design and validate a theoretical model for capacitive imaging (CI) sensors that incorporates the interelectrode shielding and surrounding shielding electrodes. Through experimental verification, the effectiveness of the theoretical model in evaluating CI sensors equipped with shielding electrodes has been demonstrated.

The study begins by incorporating the interelectrode shielding and surrounding shielding electrodes of CI sensors into the theoretical model. A method for deriving the semianalytical model is proposed, using the renormalization group method and physical model. Based on random geometric parameters of CI sensors, capacitance values are calculated using both simulation models and theoretical models. Three different types of CI sensors with varying geometric parameters are designed and manufactured for experimental testing.

The study’s results indicate that the errors of the semianalytical model for the CI sensor are predominantly below 5%, with all errors falling below 10%. This suggests that the semianalytical model, derived using the renormalization group method, effectively evaluates CI sensors equipped with shielding electrodes. The experimental results demonstrate the efficacy of the theoretical model in accurately predicting the capacitance values of the CI sensors.

The theoretical model of CI sensors is described by incorporating the interelectrode shielding and surrounding shielding electrodes into the model. This comprehensive approach allows for a more accurate evaluation of the detecting capability of CI sensors, as well as optimization of their performance.

In complex environments, a spherical robot has great application value. When the pendulum spherical robot is stopped or disturbed, there will be a periodic oscillation. This situation will seriously affect the stability of the spherical robot. Therefore, this paper aims to propose a control method based on backstepping and disturbance observers for oscillation suppression.

This paper analyzes the mechanism of oscillation. The oscillation model of the spherical robot is constructed and the relationship between the oscillation and the internal structure of the sphere is analyzed. Based on the oscillation model, the authors design the oscillation suppression control of the spherical robot using the backstepping method. At the same time, a disturbance observer is added to suppress the disturbance.

It is found that the control system based on backstepping and disturbance observer is simple and efficient for nonlinear models. Compared with the PID controller commonly used in engineering, this control method has a better control effect.

The proposed method can provide a reliable and effective stability scheme for spherical robots. The problem of instability in real motion is solved.

In this paper, the oscillation model of a spherical robot is innovatively constructed. Second, a new backstepping control method combined with a disturbance observer for the spherical robot is proposed to suppress the oscillation.

Through a theoretical lens of psychological ownership, this study aims to investigate how technology mindfulness may stimulate metaverse tourism users’ feelings of individual psychological ownership, aesthetic value and conversational value, which in turn fosters intention to engage in prosocial behaviors.

The study used a scenario-based survey that allowed U.S.-based participants to create their own avatars and imagine using their avatars to explore heritage sites in the metaverse. Structural equality modeling was applied for data analysis.

The results from 357 valid responses indicate that technology mindfulness arouses tourists’ individual psychological ownership, aesthetic value, conversational value and prosocial behavioral intentions. The moderating role of biospheric value orientation on willingness to donate and intention to volunteer is investigated.

The research sheds light on the significance of technology mindfulness, conversational value and psychological ownership perspectives in the metaverse, which have been previously overlooked. The authors used a scenario-based survey for mental stimulation due to current metaverse technology limitations.

The study is one of the first to explore the possibility of encouraging prosocial behaviors using metaverse-facilitated technology. The research offers guidelines to engage hospitality and tourism customers in the metaverse that can blend their virtual experiences into the real world.

This study represents one of the pioneering efforts to gain an in-depth understanding of the application of metaverse in triggering prosocial behavior toward heritage sites, explained via a technology mindfulness-driven model with a psychological ownership perspective.

This paper aims to examine and compare extant literature on the application of multi-criteria decision-making (MCDM) techniques in humanitarian operations (HOs) and humanitarian supply chains (HSCs). It identifies the status of existing research in the field and suggests a roadmap for academicians to undertake further research in HOs and HSCs using MCDM techniques.

The paper systematically reviews the research on MCDM applications in HO and HSC domains from 2011 to 2022, as the field gained traction post-2004 Indian Ocean Tsunami phenomena. In the first step, an exhaustive search for journal articles is conducted using 48 keyword searches. To ensure quality, only those articles published in journals featuring in the first quartile of the Scimago Journal Ranking were selected. A total of 103 peer-reviewed articles were selected for the review and then segregated into different categories for analysis.

The paper highlights insufficient high-quality research in HOs that utilizes MCDM methods. It proposes a roadmap for scholars to enhance the research outcomes by advocating adopting mixed methods. The analysis of various studies revealed a notable absence of contextual reference. A contextual mind map specific to HOs has been developed to assist future research endeavors. This resource can guide researchers in determining the appropriate contextual framework for their studies.

This paper will help practitioners understand the research carried out in the field. The aspiring researchers will identify the gap in the extant research and work on future research directions.

To the best of the authors’ knowledge, this is the first literature review on applying MCDM in HOs and HSCs. It summarises the current status and proposes future research directions.

This paper aims to examine the role of technological Innovation in ensuring resource sustainability in the water, energy and food (WEF) nexus, as there exists a shortage of statistical research on the extent of the influence of technological Innovation on the WEF nexus.

The study used a quantitative research method, using a well-structured questionnaire to collect data from management staff in the WEF departments in South Africa. The collected data were analyzed by using mean score ranking, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) for structural equation modelling (SEM).

The findings show that the technological process of technological innovation is significant for resource sustainability. The result also showed that technological innovations directly and statistically significantly affect WEF nexus. The EFA resulted in three components of WEF nexus product innovation, WEF nexus process innovation and WEF nexus novel innovations. Furthermore, the CFA and SEM analysis reveals that six technological innovation indicators influence the sustainability of the nexus: smart water metering technology, smart metering technology, food quality monitoring technology, agricultural technology solutions, new technological design and eco-friendly WEF products.

The sustainability of these three inevitable resources for man’s survival is dependent on technological innovations, and this study has shown the major categories of innovations needed, thus establishing a pathway for engineering design.

This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner.

This study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies.

None of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields.

This study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.