The Congregation\u27s Right to Choose Its Pastor

The image of the pastor or religious leader, his authority, function and role, is currently a lively topic for discussion, as church groups merge and emerge, as clergy are robed and disrobed, as town and gown and church and state issues erupt and disrupt the peace of the church and the parish. Therefore this translation of Carl Ferdinand Wilhelm Walther\u27s essay, Das Gemeindewahlrecht, delineating the voting rights of the congregation, appears at an appropriate time. The Lutheran Church-Missouri Synod has not beenhttps://scholar.csl.edu/ebooks/1036/thumbnail.jp

Web-Based Specialist Support for Spinal Cord Injury Person's Care: Lessons Learned

Persons with disability from spinal cord injury (SCI) are subject to high risk of pathological events and need a regular followup even after discharge from the rehabilitation hospital. To help in followup, we developed a web portal for providing online specialist as well as GP support to SCI persons. After a feasibility study with 13 subjects, the portal has been introduced in the regional healthcare network in order to make it compliant with current legal regulations on data protection, including smartcard authentication. Although a number of training courses have been made to introduce SCI persons to portal use (up to 50 users), the number of accesses remained very low. Reasons for that have been investigated by means of a questionnaire submitted to the initial feasibility study subjects and included the still easier use of telephone versus our web-based smartcard-authenticated portal, in particular, because online communications are still perceived as an unusual way of interacting with the doctor. To summarize, the overall project has been appreciated by the users, but when it is time to ask for help to, the specialist, it is still much easier to make a phone call

Report on ARGOS' second qualitative interview

The primary objective of the ARGOS project is the transdisciplinary examination of the condition of sustainable agriculture in New Zealand (including environmental, economic and social aspects). In pursuit of this objective to date, considerable effort has been dedicated to assessing the comparative sustainability or resilience of designated management panels in three branches of the New Zealand agricultural sector (dairy, kiwifruit and sheep/beef). For this purpose, farms of comparable size and similar location were assigned panel membership as determined by an individual farmer’s compliance (or lack thereof) with existing market audit schemes which – to varying degrees – regulate farm management practice. By sector, the panels are comprised of conventional and organic methods of dairy farming, integrated pest management (Hayward, green, and Hort 16a, gold) and organic (Hayward) methods of kiwifruit production, and conventional, integrated and organic methods of sheep and beef farming. Due to the distinct nature of practices associated with each panel, differences in the assessed ecological, economic and social features of the participating farms and farm households offer the potential to distinguish the relative sustainability of systems based on these practices

Detecting violent and abnormal crowd activity using temporal analysis of grey level co-occurrence matrix (GLCM)-based texture measures

The severity of sustained injury resulting from assault-related violence can be minimized by reducing detection time. However, it has been shown that human operators perform poorly at detecting events found in video footage when presented with simultaneous feeds. We utilize computer vision techniques to develop an automated method of violence detection that can aid a human operator. We observed that violence in city centre environments often occur in crowded areas, resulting in individual actions being occluded by other crowd members. Measures of visual texture have shown to be effective at encoding crowd appearance. Therefore, we propose modelling crowd dynamics using changes in crowd texture. We refer to this approach as Violent Crowd Texture (VCT). Real-world surveillance footage of night time environments and the violent flows dataset were tested using a random forest classifier to evaluate the ability of the VCT method at discriminating between violent and non-violent behaviour. Our method achieves ROC values of 0.98 and 0.91 on our own real world CCTV dataset and the violent flows dataset respectively

Violent behaviour detection using local trajectory response

Surveillance systems in the United Kingdom are prominent, and the number of installed cameras is estimated to be around 1.8 million. It is common for a single person to watch multiple live video feeds when conducting active surveillance, and past research has shown that a person’s effectiveness at successfully identifying an event of interest diminishes the more monitors they must observe. We propose using computer vision techniques to produce a system that can accurately identify scenes of violent behaviour. In this paper we outline three measures of motion trajectory that when combined produce a response map that highlights regions within frames that contain behaviour typical of violence based on local information. Our proposed method demonstrates state-of-the-art classification ability when given the task of distinguishing between violent and non-violent behaviour across a wide variety of violent data, including real-world surveillance footage obtained from local police organisations

Between images and built form: Automating the recognition of standardised building components using deep learning

Building on the richness of recent contributions in the field, this paper presents a state-of-the-art CNN analysis method for automatingthe recognition of standardised building components in modern heritage buildings. At the turn of the twentieth century manufacturedbuilding components became widely advertised for specification by architects. Consequently, a form of standardisation across varioustypologies began to take place. During this era of rapid economic and industrialised growth, many forms of public building wereerected. This paper seeks to demonstrate a method for informing the recognition of such elements using deep learning to recognise'families' of elements across a range of buildings in order to retrieve and recognise their technical specifications from the contemporarytrade literature. The method is illustrated through the case of Carnegie Public Libraries in the UK, which provides a unique butubiquitous platform from which to explore the potential for the automated recognition of manufactured standard architecturalcomponents. The aim of enhancing this knowledge base is to use the degree to which these were standardised originally as a means toinform and so support their ongoing care but also that of many other contemporary buildings. Although these libraries are numerous,they are maintained at a local level and as such, their shared challenges for maintenance remain unknown to one another. Additionally,this paper presents a methodology to indirectly retrieve useful indicators and semantics, relating to emerging HBIM families, byapplying deep learning to a varied range of architectural imagery

Lava penetrating water: Submarine lava flows around the coasts of Pico Island, Azores

Bathymetry data collected with a multibeam echo sounder around Pico Island, Azores (Portugal), reveal a remarkable series of lava flows on the island's shelf with a variety of pristine structures that suggest how lava behaves on entering water. Many flows are dendritic in plan view, some with channels and tumuli. Dendritic geometries are interpreted to arise from flow fronts repeatedly arrested by enhanced cooling and magma pressure subsequently causing new breakouts. Cascades of elongated flow fingers also occur, with individual fingers of comparable diameters to the largest known megapillows. Some flows have wide transverse clefts, in cases separating flows into segments, which are interpreted as caused by their upper surfaces having solidified, while their still-fluid cores allowed the surfaces to extend. A number of flows moved onto the shelf as large bodies, stopped, and then sourced smaller lobes forming the dendritic patterns. This two-stage evolution and the tumuli (which lie on a low gradient immediately below a steep nearshore gradient) suggest that, after initial emplacement and development of a crust by cooling, some flows pressurized. Once movements ceased and viscous stresses dissipated, magma static pressure developed from the weight of flow interiors passing over cliffs and nearshore gradients. One group of flows traverses the island's submarine slope, so direct supply of lava to the slopes is possible, although volumetrically how important it is to the island's internal composition is difficult to tell from these data. On the basis of observed strong surf erosion of historical flows, these delicate structures probably could not have survived passage through a moving sea level unmodified by erosion so they are unlikely to be pre-Holocene subaerial flows. They are interpreted to have formed in the Holocene from flows penetrating sea level or possibly some from nearshore tube openings or vents. Such flows and abundant clastic deposits are ephemeral features that become remobilized by surf during times of lower sea level. The shelves of active volcanic islands are therefore active geologically and are far from being simple products of erosional truncation as was once envisaged

Excitability in autonomous Boolean networks

We demonstrate theoretically and experimentally that excitable systems can be built with autonomous Boolean networks. Their experimental implementation is realized with asynchronous logic gates on a reconfigurabe chip. When these excitable systems are assembled into time-delay networks, their dynamics display nanosecond time-scale spike synchronization patterns that are controllable in period and phase.Comment: 6 pages, 5 figures, accepted in Europhysics Letters (epljournal.edpsciences.org

An open-data, agent-based model of alcohol related crime

The allocation of resources to challenge city centre violent crime traditionally relies on historical data to identify hot-spots. The usefulness of such data-driven approaches is limited when historical data is scarce or unavailable (e.g. planning of a new city) or insufficiently representative (e.g. does not account for novel events, such as Olympic Games). In some cities, crime data is not systematically accumulated at all. We present a graph-constrained agent based simulation model of alcohol-related violent crime that is capable of predicting areas of likely violent crime without requiring any historical data. The only inputs to our simulation are publicly available geographical data, which makes our method immediately applicable to a wide range of tasks, such as optimal city planning, police patrol optimisation, devising alcohol licensing policies. In experiments, we evaluate our model and demonstrate agreement of our model's predictions on where and when violence will occur with real-world violent crime data. Analyses indicate that our agent based model may be able to make a significant contribution to attempts to prevent violence through deterrence or by design