Peat, pine stumps and people: interactions behind climate, vegetation change and human activity in wetland archaeology at Loch Farlary, Northern Scotland

First paragraph: In 1993, a peat-cutter, Bruce Field, working on the blanket peat bank he rented from the Sutherland Estate by Loch Farlary, above Golspie in Sutherland (fig 1), reported to Scottish Natural Heritage and Historic Scotland several pieces of pine wood bearing axe marks. Their depth in the peat suggested the cut marks to be prehistoric. This paper summarizes the work undertaken to understand the age and archaeological significance of this find (see also Tipping et al 2001 in press). The pine trees were initially thought to be part of a population that flourished briefly across northern Scotland in the middle of the Holocene period from c 4800 cal BP (Huntley, Daniell & Allen 1997). The subsequent collapse across northernmost Scotland of this population, the pine decline, at around 4200-4000 cal BP is unexplained: climate change has been widely assumed (Dubois & Ferguson 1985; Bridge, Haggart & Lowe 1990; Gear & Huntley 1991) but anthropogenic activity has not been disproved (Birks 1975; Bennett 1995). It was hypothesized that the Farlary find would allow for the first time the direct link between human woodland clearance and the Early Bronze Age pine decline.

Early Holocene vegetation, human activity and climate from Sarawak, Malaysian Borneo

A 40mcore from Loagan Bunut,Malaysian Borneo, yielded a high-resolution early Holocene (11.3e6.75 ka) sequence of marginal-marine deposits. Palynological analysis showed relatively stable fire-regulated lowland forest through this time, with the local development and regression of mangrove vegetation. A general trend of rising rainfall and thus strengthening North East monsoonal circulation linked to the migration of the mean position of the ICTZ was interrupted by what may be episodes of drier climate and weakening monsoonal activity at 9250-8890, 7900 and 7600-7545 cal. BP. Magnetic susceptibility peaks suggestmarked short-term ENSO-style activity superimposed upon this record. Repeated markers for openand disturbed habitats, plus occasional imported and probably-cultivated taxa, point towards human impact from the earliest Holocene on the wet tropical forest at Loagan Bunut.

Practical automated activity recognition using standard smartphones

This paper describes a simple application for mobile devices which automatically recognizes different physical activity. This application could be used to log exercise sessions for the purpose of aiding weight management or improving sporting performance. © 2012 IEEE.

Common-sense knowledge for a computer vision system for human action recognition

This work presents a novel approach for human action recognition based on the combination of computer vision techniques and common-sense knowledge and reasoning capabilities. The emphasis of this work is on how common sense has to be leveraged to a vision-based human action recognition so that nonsensical errors can be amended at the understanding stage. The proposed framework is to be deployed in a realistic environment in which humans behave rationally, that is, motivated by an aim or a reason. © 2012 Springer-Verlag.

Common-sense reasoning for human action recognition

This paper presents a novel method that leverages reasoning capabilities in a computer vision system dedicated to human action recognition. The proposed methodology is decomposed into two stages. First, a machine learning based algorithm - known as bag of words - gives a first estimate of action classification from video sequences, by performing an image feature analysis. Those results are afterward passed to a common-sense reasoning system, which analyses, selects and corrects the initial estimation yielded by the machine learning algorithm. This second stage resorts to the knowledge implicit in the rationality that motivates human behaviour. Experiments are performed in realistic conditions, where poor recognition rates by the machine learning techniques are significantly improved by the second stage in which common-sense knowledge and reasoning capabilities have been leveraged. This demonstrates the value of integrating common-sense capabilities into a computer vision pipeline. © 2012 Elsevier B.V. All rights reserved.

Episodic Reasoning for Vision-Based Human Action Recognition

Smart Spaces, Ambient Intelligence, and Ambient Assisted Living are environmental paradigms that strongly depend on their capability to recognize human actions. While most solutions rest on sensor value interpretations and video analysis applications, few have realized the importance of incorporating common-sense capabilities to support the recognition process. Unfortunately, human action recognition cannot be successfully accomplished by only analyzing body postures. On the contrary, this task should be supported by profound knowledge of human agency nature and its tight connection to the reasons and motivations that explain it. The combination of this knowledge and the knowledge about how the world works is essential for recognizing and understanding human actions without committing common-senseless mistakes. This work demonstrates the impact that episodic reasoning has in improving the accuracy of a computer vision system for human action recognition. This work also presents formalization, implementation, and evaluation details of the knowledge model that supports the episodic reasoning.

The Cyrenaican Prehistory Project 2011: Late-Holocene environments and human activity from a cave fill in Cyrenaica, Libya

Little is known about late Holocene environmental change in Cyrenaica. The late Holocene sequence in the Haua Fteah, the key regional site, is highly discontinuous and characterised by stable-burning deposits. The geoarchaeology of the late-Holocene cave fill of a small cave, CP1565, located close to the Haua Fteah, is described. The well-stratified sequence, dating from the fourth century AD to the present day, provides a glimpse of life at the bottom of the settlement hierarchy and of changing environments over the last 1600 years, with degraded vegetation and aridity in the ‘Little Ice Age’.