Painted Into a Corner by Communities and Collections? Free Yourself with Metadata

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

A tale of two communities

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Development of remote monitoring process tools for biomass fired bubbling fluidized bed boilers

Remote monitoring of a power boiler allows the supplying company to make sure that equipment is used as supposed to and gives a good chance for process optimization. This improves co-operation between the supplier and the customer and creates an aura of trust that helps securing future contracts. Remote monitoring is already in use with recovery boilers but the goal is to expand especially to biomass-fired BFB-boilers. To make remote monitoring possible, data has to be measured reliably on site and the link between the power plant and supplying company’s server has to work reliably. Data can be gathered either with the supplier’s sensors or with measurements originally installed in the power plant if the plant in question is not originally built by the supplying company. Main goal in remote monitoring is process optimization and avoiding unnecessary accidents. This can be achieved for instance by following the efficiency curves and fouling in different parts of the process and comparing them to past values. The final amount of calculations depends on the amount of data gathered. Sudden changes in efficiency or fouling require further notice and in such a case it’s important that dialogue toward the power plant in question also works.

Let Go and Remember. How Finnish Communities Experienced and Memorialized School Shootings

This study examines the aftermath of mass violence in local communities. Two rampage school shootings that occurred in Finland are analyzed and compared to examine the ways in which communities experience, make sense of, and recover from sudden acts of mass violence. The studied cases took place at Jokela High School, in southern Finland, and at a polytechnic university in Kauhajoki, in western Finland, in 2007 and 2008 respectively. Including the perpetrators, 20 people lost their lives in these shootings. These incidents are part of the global school shooting phenomenon with increasing numbers of incidents occurring in the last two decades, mostly in North America and Europe. The dynamic of solidarity and conflict is one of the main themes of this study. It builds upon previous research on mass violence and disasters which suggests that solidarity increases after a crisis, and that this increase is often followed by conflict in the affected communities. This dissertation also draws from theoretical discussions on remembering, narrating, and commemorating traumatic incidents, as well as the idea of a cultural trauma process in which the origins and consequences of traumas are negotiated alongside collective identities. Memorialization practices and narratives about what happened are vital parts of the social memory of crises and disasters, and their inclusive and exclusive characteristics are discussed in this study. The data include two types of qualitative interviews; focused interviews with 11 crisis workers, and focused, narrative interviews with 21 residents of Jokela and 22 residents of Kauhajoki. A quantitative mail survey of the Jokela population (N=330) provided data used in one of the research articles. The results indicate that both communities experienced a process of simultaneous solidarity and conflict after the shootings. In Jokela, the community was constructed as a victim, and public expressions of solidarity and memorialization were promoted as part of the recovery process. In Kauhajoki, the community was portrayed as an incidental site of mass violence, and public expressions of solidarity by distant witnesses were labeled as unnecessary and often criticized. However, after the shooting, the community was somewhat united in its desire to avoid victimization and a prolonged liminal period. This can be understood as a more modest and invisible process of “silent solidarity”. The processes of enforced solidarity were partly made possible by exclusion. In some accounts, the family of the perpetrator in Jokela was excluded from the community. In Kauhajoki, the whole incident was externalized. In both communities, this exclusion included associating the shooting events, certain places, and certain individuals with the concept of evil, which helped to understand and explain the inconceivable incidents. Differences concerning appropriate emotional orientations, memorialization practices and the pace of the recovery created conflict in both communities. In Jokela, attitudes towards the perpetrator and his family were also a source of friction. Traditional gender roles regarding the expression of emotions remained fairly stable after the school shootings, but in an exceptional situation, conflicting interpretations arose concerning how men and women should express emotion. The results from the Jokela community also suggest that while increased solidarity was seen as important part of the recovery process, some negative effects such as collective guilt, group divisions, and stigmatization also emerged. Based on the results, two simultaneous strategies that took place after mass violence were identified; one was a process of fast-paced normalization, and the other was that of memorialization. Both strategies are ways to restore the feeling of security shattered by violent incidents. The Jokela community emphasized remembering while the Kauhajoki community turned more to the normalization strategy. Both strategies have positive and negative consequences. It is important to note that the tendency to memorialize is not the only way of expressing solidarity, as fast normalization includes its own kind of solidarity and helps prevent the negative consequences of intense solidarity.

From genes to communities : stress tolerance in eelgrass (Zostera marina)

Shallow coastal areas are dynamic habitats that are affected by a variety of abiotic and biotic factors. In addition to the natural environmental stress, estuarine and coastal seagrass ecosystems are exposed to effects of climate change and other anthropogenic impacts. In this thesis the effect of different abiotic (shading stress, salinity and temperature) and biotic stressors (presence of co-occurring species) and different levels and combinations of stressors on the performance and survival of eelgrass (Zostera marina) was assessed. To investigate the importance of scale for stress responses, varying levels of biological organization (genotype, life stage, population and plant community) were studied in field and aquarium experiments. Light limitation, decreased salinity and increased temperature affected eelgrass performance negatively in papers I, II and III, respectively. While co-occurring plant species had no notable effect on eelgrass in paper IV, the presence of eelgrass increased the biomass of Potamogeton perfoliatus. The findings in papers II and III confirmed that more extreme levels of salinity and temperature had stronger impacts on plant performance compared to intermediate levels, but intermediate levels also had more severe effects on plants when they were exposed to several stressors, as illustrated in paper II. Thus, multiple stressors had negative synergetic effects. The results in papers I, II and III indicate that future changes in light climate, salinity and temperature can have serious impacts on eelgrass performance and survival. Stress responses were found to vary among genotypes, life stages and populations in papers I, II and III, respectively, emphasizing the importance of study scale. The results demonstrate that while stress in general affects seagrass productivity negatively, the severity of effects can vary substantially depending on the studied scale or level of biological organization. Eelgrass genotypes can differ in their stress and recovery processes, as observed in paper I. In paper II, eelgrass seedlings were less prone to abiotic stress compared to adult plants, but stress also decreased their survival considerably. This indicates that recruitment and re-colonization through seeds might be threatened in the future. Variation among population responses observed in paper III indicates that long-term local adaptation under differing selection pressures has caused divergence in salinity tolerance between Baltic eelgrass populations. This variability in stress tolerance observed in papers I and III suggests that some eelgrass genotypes and populations have a better capacity to adapt to changes and survive in a changing environment. Multiple stressors and biological level-specific responses demonstrate the uncertainty in predicting eelgrass responses in a changing environment. As eelgrass populations may differ in their stress tolerance both within and across regions, conservation strategies at both local and regional scales are urgently needed in order to ensure the survival of these important ecosystems.

Along-scan radiometric gradient in Landsat images: understanding the relation between floristic and remote sensing information in tropical forests

The along-scan radiometric gradient causes severe interpretation problems in Landsat images of tropical forests. It creates a decreasing trend in pixel values with the column number of the image. In practical applications it has been corrected assuming the trend to be linear within structurally similar forests. This has improved the relation between floristic and remote sensing information, but just in some cases. I use 3 Landsat images and 105 floristic inventories to test the assumption of linearity, and to examine how the gradient and linear corrections affect the relation between floristic and Landsat data. Results suggest the gradient to be linear in infrared bands. Also, the relation between floristic and Landsat data could be conditioned by the distribution of the sampling sites and the direction in which images are mosaicked. Additionally, there seems to be a conjunction between the radiometric gradient and a natural east-west vegetation gradient common in Western Amazonia. This conjunction might have enhanced artificially correlations between field and remotely-sensed information in previous studies. Linear corrections may remove such artificial enhancement, but along with true and relevant spectral information about floristic patterns, because they can´t separate the radiometric gradient from a natural one.

Fluvio-morphological processes of meander bends - Combining conventional field measurements, close-range remote sensing and computational modelling

Meandering rivers have been perceived to evolve rather similarly around the world independently of the location or size of the river. Despite the many consistent processes and characteristics they have also been noted to show complex and unique sets of fluviomorphological processes in which local factors play important role. These complex interactions of flow and morphology affect notably the development of the river. Comprehensive and fundamental field, flume and theoretically based studies of fluviomorphological processes in meandering rivers have been carried out especially during the latter part of the 20th century. However, as these studies have been carried out with traditional field measurements techniques their spatial and temporal resolution is not competitive to the level achievable today. The hypothesis of this study is that, by exploiting e increased spatial and temporal resolution of the data, achieved by combining conventional field measurements with a range of modern technologies, will provide new insights to the spatial patterns of the flow-sediment interaction in meandering streams, which have perceived to show notable variation in space and time. This thesis shows how the modern technologies can be combined to derive very high spatial and temporal resolution data on fluvio-morphological processes over meander bends. The flow structure over the bends is recorded in situ using acoustic Doppler current profiler (ADCP) and the spatial and temporal resolution of the flow data is enhanced using 2D and 3D CFD over various meander bends. The CFD are also exploited to simulate sediment transport. Multi-temporal terrestrial laser scanning (TLS), mobile laser scanning (MLS) and echo sounding data are used to measure the flow-based changes and formations over meander bends and to build the computational models. The spatial patterns of erosion and deposition over meander bends are analysed relative to the measured and modelled flow field and sediment transport. The results are compared with the classic theories of the processes in meander bends. Mainly, the results of this study follow well the existing theories and results of previous studies. However, some new insights regarding to the spatial and temporal patterns of the flow-sediment interaction in a natural sand-bed meander bend are provided. The results of this study show the advantages of the rapid and detailed measurements techniques and the achieved spatial and temporal resolution provided by CFD, unachievable with field measurements. The thesis also discusses the limitations which remain in the measurement and modelling methods and in understanding of fluvial geomorphology of meander bends. Further, the hydro- and morphodynamic models’ sensitivity to user-defined parameters is tested, and the modelling results are assessed against detailed field measurement. The study is implemented in the meandering sub-Arctic Pulmanki River in Finland. The river is unregulated and sand-bed and major morphological changes occur annually on the meander point bars, which are inundated only during the snow-melt-induced spring floods. The outcome of this study applies to sandbed meandering rivers in regions where normally one significant flood event occurs annually, such as Arctic areas with snow-melt induced spring floods, and where the point bars of the meander bends are inundated only during the flood events.

Remote sensing for three-dimensional modelling of hydromorphology

Successful management of rivers requires an understanding of the fluvial processes that govern them. This, in turn cannot be achieved without a means of quantifying their geomorphology and hydrology and the spatio-temporal interactions between them, that is, their hydromorphology. For a long time, it has been laborious and time-consuming to measure river topography, especially in the submerged part of the channel. The measurement of the flow field has been challenging as well, and hence, such measurements have long been sparse in natural environments. Technological advancements in the field of remote sensing in the recent years have opened up new possibilities for capturing synoptic information on river environments. This thesis presents new developments in fluvial remote sensing of both topography and water flow. A set of close-range remote sensing methods is employed to eventually construct a high-resolution unified empirical hydromorphological model, that is, river channel and floodplain topography and three-dimensional areal flow field. Empirical as well as hydraulic theory-based optical remote sensing methods are tested and evaluated using normal colour aerial photographs and sonar calibration and reference measurements on a rocky-bed sub-Arctic river. The empirical optical bathymetry model is developed further by the introduction of a deep-water radiance parameter estimation algorithm that extends the field of application of the model to shallow streams. The effect of this parameter on the model is also assessed in a study of a sandy-bed sub-Arctic river using close-range high-resolution aerial photography, presenting one of the first examples of fluvial bathymetry modelling from unmanned aerial vehicles (UAV). Further close-range remote sensing methods are added to complete the topography integrating the river bed with the floodplain to create a seamless high-resolution topography. Boat- cart- and backpack-based mobile laser scanning (MLS) are used to measure the topography of the dry part of the channel at a high resolution and accuracy. Multitemporal MLS is evaluated along with UAV-based photogrammetry against terrestrial laser scanning reference data and merged with UAV-based bathymetry to create a two-year series of seamless digital terrain models. These allow the evaluation of the methodology for conducting high-resolution change analysis of the entire channel. The remote sensing based model of hydromorphology is completed by a new methodology for mapping the flow field in 3D. An acoustic Doppler current profiler (ADCP) is deployed on a remote-controlled boat with a survey-grade global navigation satellite system (GNSS) receiver, allowing the positioning of the areally sampled 3D flow vectors in 3D space as a point cloud and its interpolation into a 3D matrix allows a quantitative volumetric flow analysis. Multitemporal areal 3D flow field data show the evolution of the flow field during a snow-melt flood event. The combination of the underwater and dry topography with the flow field yields a compete model of river hydromorphology at the reach scale.

A new & accurate map of the North Pole with all the countries hitherto discovered situated near or adjacent to it as well as some others more remote. Drawn from the latest and best authorities and regulated by astronom.l observat.ns by Eman. Bowen.

0-meridiaani: Lontoo. - Koordinaattiasteikko: N90°-55°[50°].

Sensor communication in Smart cities and regions: An efficient IoT-based remote health monitoring system

Recent advances in Information and Communication Technology (ICT), especially those related to the Internet of Things (IoT), are facilitating smart regions. Among many services that a smart region can offer, remote health monitoring is a typical application of IoT paradigm. It offers the ability to continuously monitor and collect health-related data from a person, and transmit the data to a remote entity (for example, a healthcare service provider) for further processing and knowledge extraction. An IoT-based remote health monitoring system can be beneficial in rural areas belonging to the smart region where people have limited access to regular healthcare services. The same system can be beneficial in urban areas where hospitals can be overcrowded and where it may take substantial time to avail healthcare. However, this system may generate a large amount of data. In order to realize an efficient IoT-based remote health monitoring system, it is imperative to study the network communication needs of such a system; in particular the bandwidth requirements and the volume of generated data. The thesis studies a commercial product for remote health monitoring in Skellefteå, Sweden. Based on the results obtained via the commercial product, the thesis identified the key network-related requirements of a typical remote health monitoring system in terms of real-time event update, bandwidth requirements and data generation. Furthermore, the thesis has proposed an architecture called IReHMo - an IoT-based remote health monitoring architecture. This architecture allows users to incorporate several types of IoT devices to extend the sensing capabilities of the system. Using IReHMo, several IoT communication protocols such as HTTP, MQTT and CoAP has been evaluated and compared against each other. Results showed that CoAP is the most efficient protocol to transmit small size healthcare data to the remote servers. The combination of IReHMo and CoAP significantly reduced the required bandwidth as well as the volume of generated data (up to 56 percent) compared to the commercial product. Finally, the thesis conducted a scalability analysis, to determine the feasibility of deploying the combination of IReHMo and CoAP in large numbers in regions in north Sweden.

Underwater Remote Welding Technology for Offshore Structures

The construction of offshore structures, equipment and devices requires a high level of mechanical reliability in terms of strength, toughness and ductility. One major site for mechanical failure, the weld joint region, needs particularly careful examination, and weld joint quality has become a major focus of research in recent times. Underwater welding carried out offshore faces specific challenges affecting the mechanical reliability of constructions completed underwater. The focus of this thesis is on improvement of weld quality of underwater welding using control theory. This research work identifies ways of optimizing the welding process parameters of flux cored arc welding (FCAW) during underwater welding so as to achieve desired weld bead geometry when welding in a water environment. The weld bead geometry has no known linear relationship with the welding process parameters, which makes it difficult to determine a satisfactory weld quality. However, good weld bead geometry is achievable by controlling the welding process parameters. The doctoral dissertation comprises two sections. The first part introduces the topic of the research, discusses the mechanisms of underwater welding and examines the effect of the water environment on the weld quality of wet welding. The second part comprises four research papers examining different aspects of underwater wet welding and its control and optimization. Issues considered include the effects of welding process parameters on weld bead geometry, optimization of FCAW process parameters, and design of a control system for the purpose of achieving a desired bead geometry that can ensure a high level of mechanical reliability in welded joints of offshore structures. Artificial neural network systems and a fuzzy logic controller, which are incorporated in the control system design, and a hybrid of fuzzy and PID controllers are the major control dynamics used. This study contributes to knowledge of possible solutions for achieving similar high weld quality in underwater wet welding as found with welding in air. The study shows that carefully selected steels with very low carbon equivalent and proper control of the welding process parameters are essential in achieving good weld quality. The study provides a platform for further research in underwater welding. It promotes increased awareness of the need to improve the quality of underwater welding for offshore industries and thus minimize the risk of structural defects resulting from poor weld quality.

Use of airborne laser scanner data in demanding forest conditions

Most of the applications of airborne laser scanner data to forestry require that the point cloud be normalized, i.e., each point represents height from the ground instead of elevation. To normalize the point cloud, a digital terrain model (DTM), which is derived from the ground returns in the point cloud, is employed. Unfortunately, extracting accurate DTMs from airborne laser scanner data is a challenging task, especially in tropical forests where the canopy is normally very thick (partially closed), leading to a situation in which only a limited number of laser pulses reach the ground. Therefore, robust algorithms for extracting accurate DTMs in low-ground-point-densitysituations are needed in order to realize the full potential of airborne laser scanner data to forestry. The objective of this thesis is to develop algorithms for processing airborne laser scanner data in order to: (1) extract DTMs in demanding forest conditions (complex terrain and low number of ground points) for applications in forestry; (2) estimate canopy base height (CBH) for forest fire behavior modeling; and (3) assess the robustness of LiDAR-based high-resolution biomass estimation models against different field plot designs. Here, the aim is to find out if field plot data gathered by professional foresters can be combined with field plot data gathered by professionally trained community foresters and used in LiDAR-based high-resolution biomass estimation modeling without affecting prediction performance. The question of interest in this case is whether or not the local forest communities can achieve the level technical proficiency required for accurate forest monitoring. The algorithms for extracting DTMs from LiDAR point clouds presented in this thesis address the challenges of extracting DTMs in low-ground-point situations and in complex terrain while the algorithm for CBH estimation addresses the challenge of variations in the distribution of points in the LiDAR point cloud caused by things like variations in tree species and season of data acquisition. These algorithms are adaptive (with respect to point cloud characteristics) and exhibit a high degree of tolerance to variations in the density and distribution of points in the LiDAR point cloud. Results of comparison with existing DTM extraction algorithms showed that DTM extraction algorithms proposed in this thesis performed better with respect to accuracy of estimating tree heights from airborne laser scanner data. On the other hand, the proposed DTM extraction algorithms, being mostly based on trend surface interpolation, can not retain small artifacts in the terrain (e.g., bumps, small hills and depressions). Therefore, the DTMs generated by these algorithms are only suitable for forestry applications where the primary objective is to estimate tree heights from normalized airborne laser scanner data. On the other hand, the algorithm for estimating CBH proposed in this thesis is based on the idea of moving voxel in which gaps (openings in the canopy) which act as fuel breaks are located and their height is estimated. Test results showed a slight improvement in CBH estimation accuracy over existing CBH estimation methods which are based on height percentiles in the airborne laser scanner data. However, being based on the idea of moving voxel, this algorithm has one main advantage over existing CBH estimation methods in the context of forest fire modeling: it has great potential in providing information about vertical fuel continuity. This information can be used to create vertical fuel continuity maps which can provide more realistic information on the risk of crown fires compared to CBH.