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This article explores how homicide detectives make sense of and manipulate multiple physical, digital and informational artefacts when assembling case narratives. The authors introduce the concept of mosaicking to illuminate how different modes of information, deriving from different investigative methods, are used in concert at key moments of the investigative process – defining what type of crime has occurred; the incrimination and elimination of suspects; and decisions to charge key suspects.

The data qualitatively analysed include several hundred case papers, interview transcripts (n = 144) and detailed ethnographic fieldnotes relating to 44 homicide investigations across four police services. These were collected during a four-year ethnographic study of the use of forensic sciences and technologies (FSTs) in British homicide investigations.

Mosaicking describes how investigators blend and combine information, intelligence and evidence generated via different techniques and methods, to make sense of “who did what to whom and why?” Through processes of convergent and divergent mosaicking, detectives are able to “lean” on different kinds of material to reinforce or connect key points of evidence or intelligence.

The findings fill a gap in knowledge about how investigators blend and composite diverse sources of information in the construction of case narratives. The findings present a more complex and nuanced understanding of the epistemological and interpretative work conducted by contemporary detectives, given the array of investigative technologies they increasingly have at their disposal.

This paper aims to present a mosaicking method for underwater robotic applications, whose result can be provided to other perceptual systems for scene understanding such as real-time object recognition.

This method is called robust and large-scale mosaicking (ROLAMOS) and presents an efficient frame-to-frame motion estimation with outlier removal and consistency checking that maps large visual areas in high resolution. The visual mosaic of the sea-floor is created on-the-fly by a robust registration procedure that composes monocular observations and manages the computational resources. Moreover, the registration process of ROLAMOS aligns the observation to the existing mosaic.

A comprehensive set of experiments compares the performance of ROLAMOS to other similar approaches, using both data sets (publicly available) and live data obtained by a ROV operating in real scenes. The results demonstrate that ROLAMOS is adequate for mapping of sea-floor scenarios as it provides accurate information from the seabed, which is of extreme importance for autonomous robots surveying the environment that does not rely on specialized computers.

The ROLAMOS is suitable for robotic applications that require an online, robust and effective technique to reconstruct the underwater environment from only visual information.

This paper aims to design an automatic inspection system for the characters on tire molds, which involves a vision-based inspection method for the characters on tire molds.

An automatic inspection equipment is designed according to the features of the tire mold. To implement the inspection task, the corresponding image processing methods are designed, including image preprocessing, image mosaic, image locating and character inspection. Image preprocessing mainly contains fitting the contours of the acquired tire mold images and those of the computer aided design (CAD) as the arcs of two circles and polar transformation of the acquired images and the CAD. Then, the authors propose a novel framework to locate the acquired images into the corresponding mosaicked tire mold image. Finally, a character inspection scheme is proposed by combining an support-vector-machine-based character recognition method and a string matching approach. At the stages of image locating and character inspection, image mosaic is simultaneously used to label the defects in the mosaicked tire mold image, which is based on histograms-of-gradients features.

The experimental results indicate that the designed automatic inspection system can inspect the characters on the tire mold with a high accuracy at a reasonable time consumption.

The designed automatic inspection system can detect the carving faults for the characters on the tire molds, which are the cases that the characters are wrongly added, deleted or modified on the tire mold.

To the best of the authors’ knowledge, this is the first automatic vision-based inspection system for the characters on tire molds. An inspection equipment is designed and many novel image processing methods are proposed to implement the inspection task. The designed system can be widely applied in the industry.

Periodic inspection of large tonnage vessels is critical to assess integrity and prevent structural failures that could have catastrophic consequences for people and the environment. Currently, inspection operations are undertaken by human surveyors, often in extreme conditions. This paper aims to present an innovative system for the automatic visual inspection of ship hull surfaces, using a magnetic autonomous robotic crawler (MARC) equipped with a low-cost monocular camera.

MARC is provided with magnetic tracks that make it able to climb along the vertical walls of a vessel while acquiring close-up images of the traversed surfaces. A homography-based structure-from-motion algorithm is developed to build a mosaic image and also produce a metric representation of the inspected areas. To overcome low resolution and perspective distortion problems in far field due to the tilted and low camera position, a “near to far” strategy is implemented, which incrementally generates an overhead view of the surface, as long as it is traversed by the robot.

This paper demonstrates the use of an innovative robotic inspection system for automatic visual inspection of vessels. It presents and validates through experimental tests a mosaicking strategy to build a global view of the structure under inspection. The use of the mosaic image as input to an automatic corrosion detector is also demonstrated.

This paper may help to automate the inspection process, making it feasible to collect images from places otherwise difficult or impossible to reach for humans and automatically detect defects, such as corroded areas.

This paper provides a useful step towards the development of a new technology for automatic visual inspection of large tonnage ships.

Unmanned aerial/ground vehicles (UAV/UGV) collaboration systems are increasingly being used to perform reconnaissance and rescue missions autonomously, especially in disaster areas. The paper aims to discuss this issue.

To improve visibility, this study proposes a path-planning algorithm based on map matching. Continuous ground images are first collected aerially using the UAV vision system. Subsequently, a global map of the ground environment is created by processing the collected images using the methods of image correction, image mosaic and obstacle recognition. The local map of the ground environment is obtained using the 2D laser radar sensor of the UGV. A set of features for both global and local maps is established. Unknown values during map matching are determined via the least squares method. Based on the matched mapping, the traditional A* algorithm is used for the planning of global path in the global map, and the dynamic window method is used for adjustment of the local map.

Simulation experiments were carried out to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed algorithm can construct a global map of the wide environment and effectively bypass the obstacles missed by the UAV.

Prior to map matching, there is a need to extract the edge of obstacles in the global map.

This paper proposed a path planning algorithm based on map matching, yielding insights into the application of the UAV/UGV collaboration systems in disaster areas.

This study aims to analyze the changes in the ecosystem service value (ESV) in response to land use and contribute significantly to ecological construction and sustainable development.

The present study was conducted in the upper Zhanghe River region based on the moderate-resolution imaging spectroradiometer Land Cover Type product MCD12Q1 by using geographic information system (GIS) methods to process and re-classify the land-use data and using the Chinese ESV equivalent weight factors to investigate changes in land use and resulting changes in ESV between 2001 and 2013.

The results showed significant fluctuations in ESV between 2001 and 2013: there was a decline in ESV from 2001 to 2004, followed by a gradual rise after 2004, and the overall ESV exceeded 2001 levels by the end of 2013. However, the pattern of ESV change differed across geographic locations, and each administrative region contributed differently to the overall trend. The analysis confirmed that the land-use change was closely related to the change in its ESV, and the coefficients of sensitivity of ESV for all types of land use were less than one, indicating that the coefficient value of ESV lacked elasticity.

Therefore, to promote sustainable development in the upper Zhanghe River region, ESV should be taken into consideration when planning land use, especially for land types with high ESV, such as water bodies and forestlands.

The results can provide scientific support for the sustainable development of the ecological, economic and societal aspects of the upper Zhanghe River region. In addition, county-level administrative divisions were set as the basic research unit for the analysis and discussion of ESV changes in each unit within the research period and its impact on the overall ESV of the entire area to lay down a foundation for the analysis of the ESV spatial dynamic distribution in the entire research site.

An attempt is made to produce a susceptibility surface runoff hazard map for Kuwait by integrating four maps: paleodrainage; topography; vegetation cover (extracted from a Landsat image of 2001); and soil.

Local expert knowledge, weighting methods like the Delphi method and the analytical hierarchy process (AHP), and GIS techniques were used to evaluate the factors controlling surface runoff hazard in Kuwait.

The susceptibility surface runoff hazard map produced indicates that a moderate class of surface runoff hazard in Kuwait averages 45.5 percent, followed by a low class (21 percent). The very low, high and very high classes constitute about 8, 18.5 and 15 percent, respectively.

The surface hazard map obtained from this study may be presented to the authorities concerned to be used as basic data for designing runoff flood prevention and mitigation measures.

The approach adopted in this study is new to Kuwait.

This study aims to understand how climatic drivers of change will affect rural communities living in the hot semiarid region of Bhokardan Taluka of Jalna district in the Indian state of Maharashtra. In the context of the economic and social change they are experiencing, the concern is to evolve ways that enable them to cope with, adapt to and benefit from these challenges.

The focus of most of the climate change studies is on the short- to long-term trends of weather parameters such as rainfall, temperature and extreme weather events. The impact of climate variability and changing patterns on the local communities, the local economy, livelihoods and social life in specific geographies is less explored.

As the impacts of climatic and nonclimatic drivers of change are cross-sectoral, diverse, multidimensional, interlinked and dynamic, this study has adopted a transdisciplinary “research-in-use” approach involving multidisciplinary teams covering the aspects such as changes in land use and land cover, surface and groundwater status, edaphic conditions, crops and livestock, climate analysis including projected changes, socioeconomic analysis, people’s experience of climate variability and their current coping strategies and resilience (vulnerability) analysis of communities and various livelihood groups.

The study was based on the peoples’ perspective and recommendation based on the local communities ability to cope up with climate change. However, a statistical analysis perspective is missing in the present study.

Based on these findings, a set of implementation-focused recommendations are made that are aimed at conserving and enhancing the resilience of the foundations that uphold and sustain the social and economic well-being of the rural communities in Bhokardan taluka, namely, land, water, agriculture, livestock, food and nutrition security, livelihoods, market access and social capital.

The purpose of this paper is to illustrate the growing role of robots in environmental monitoring.

Following an introduction, this first considers aerial robots for monitoring atmospheric pollution. It then discusses the role of aerial, surface and underwater robots to monitor aquatic environments. Some examples are then provided of the robotic monitoring of the terrestrial environment, and finally, brief conclusions are drawn.

Robots are playing an important role in numerous environmental monitoring applications and have overcome many of the limitations of traditional methodologies. They operate in all media and frequently provide data with enhanced spatial and temporal coverage. In addition to detecting pollution and characterising environmental conditions, they can assist in locating illicit activities. Drones have benefited from the availability of small and lightweight imaging devices and sensors that can detect airborne pollutants and also characterise certain features of aquatic and terrestrial environments. As with other robotic applications, environmental drone imagery is benefiting from the use of AI techniques. Ranging from short-term local deployments to extended-duration oceanic missions, aquatic robots are increasingly being used to monitor and characterise freshwater and marine environments.

This provides a detailed insight into the growing number of ways that robots are being used to monitor the environment.