Abstract
Accurate identification of an uncertain underwater environment is one of the challenges of underwater robotics. Autonomous Underwater Vehicle (AUV) needs to understand its environment accurately to achieve autonomous tasks. The method proposed in this paper is a real-time automatic target recognition based on Side Scan Sonar images to detect and localize a harbor's wall. This paper explains real-time Side Scan Sonar image generation and compares three Deep Learning object detection algorithms (YOLOv5, YOLOvS-TR, and YOLOX) using transfer learning. The YOLOv5-TR algorithm has the most accurate detection with 99% during training, whereas the YOLOX provides the best accuracy of 91.3% for a recorded survey detection. The YOLOX algorithm realizes the flow chart validation's real-time detection and target localization.

Abstract

Abstract
The majority of virtual reality (VR) applications rely on audiovisual stimuli and do not exploit the addition of other sensory cues that could increase the potential of VR. This systematic review surveys the existing literature on multisensory VR and the impact of haptic, olfactory, and taste cues over audiovisual VR. The goal is to identify the extent to which multisensory stimuli affect the VR experience, which stimuli are used in multisensory VR, the type of VR setups used, and the application fields covered. An analysis of the 105 studies that met the eligibility criteria revealed that 84.8 percent of the studies show a positive impact of multisensory VR experiences. Haptics is the most commonly used stimulus in multisensory VR systems (86.6 percent). Non-immersive and immersive VR setups are preferred over semi-immersive setups. Regarding the application fields, a considerable part was adopted by health professionals and science and engineering professionals. We further conclude that smell and taste are still underexplored, and they can bring significant value to VR applications. More research is recommended on how to synthesize and deliver these stimuli, which still require complex and costly apparatus be integrated into the VR experience in a controlled and straightforward manner.

Abstract
The accelerated changes on our planet have led to a growing interest in climate change and its consequences: natural hazards and adverse socio-economic impacts. However, the development of climate research and the proliferation of datasets require an integrated and efficient approach to the analysis, investigation, and visualization of atmospheric meteorological data. Thus, we propose a literature review of existing systems viewing meteorological phenomena in four and three dimensions. Moreover, we evaluate meteorological occurrences to better understand the dynamics associated with a meteorological phenomenon and visualize different weather data. Based on the investigation of tools and methods, we consider the existence of different ways of representing meteorological data and methodologies. However, it was imperative to obtain knowledge and create our way of visualizing weather data. This article found eleven existing solutions for 4D meteorological visualization and meteorological phenomena.

Abstract
Classifying papers according to the fields of knowledge is critical to clearly understand the dynamics of scientific (sub)fields, their leading questions, and trends. Most studies rely on journal categories defined by popular databases such as WoS or Scopus, but some experts find that those categories may not correctly map the existing subfields nor identify the subfield of a specific article. This study addresses the classification problem using data from each paper (Abstract, Title, Keywords, and the KeyWords Plus) and the help of experts to identify the existing subfields and journals exclusive of each subfield. These exclusive journals are critical to obtain, through a pattern detection procedure that uses machine learning techniques (from software NVivo), a list of the frequent terms that are specific to each subfield. With that list of terms and with the help of optimization procedures, we can identify to which subfield each paper most likely belongs. This study can contribute to support scientific policy-makers, funding, and research institutions-via more accurate academic performance evaluations-, to support editors in their tasks to redefine the scopes of journals, and to support popular databases in their processes of refining categories.

Abstract
Purpose The present investigation aimed to evaluate the influence of envy on the predisposition to innovative behavior, starting from a conceptual model that considers not only the direct influence of envy but its indirect influence through ostracism and alignment with the negative behaviors of superiors. Design/methodology/approach Using a survey applied to 168 individuals, a conceptual model was developed based on the relationship ignored in the literature between envy and innovative behavior. The model was validated using the multivariate statistical technique of structural equation modeling with partial least squares estimation (Partial least squares structural equation modeling [PLS-SEM]). Findings The results of the study suggest that envy not only has a direct positive influence on alignment with negative boss behaviors and ostracism, but also an indirect influence on ostracism mediated by alignment with negative boss behaviors. Another important result of the present investigation refers to the negative effect of envy on the predisposition to innovative behavior. The results suggest that the greater the envy, the lower the innovative behavior. Practical implications This research provides evidence that envy can act as a barrier to innovation by triggering counterproductive behaviors such as ostracism and a decrease in predisposition to innovative behaviors, either due to innovative individuals prematurely exiting the organization or due to them lessening/dampening their innovativeness to avoid the negative consequences. Given this scenario, it becomes necessary to increase managerial awareness on the subject to manage negative emotions to promote the conditions for organizational innovation. Originality/value The present research contributes in both practical and theoretical ways to understanding the effects of envy on the predisposition to innovative behavior. Adding to this, this research represents a conceptual advance by linking envy to innovative behavior, providing a promising avenue for extending the psychological relevance of the envy construct to organizational and management studies, which are generally positive, normative and outcome-oriented.