The Carboniferous and Permian sequences in north and south of the Longmucuo-Shuanghu suture zone in Tibet

The location of the Palaeo-tethys suture in Tibet has been in great dispute for past two decades. The Longmucuo-Shuanghu suture has long been considered as the Palaeo-tethys in Tibet. Restudy of the Carboniferous and Permian sequences in the north and south of this suture reveal that: (1) the Carboniferous and Permian sequence of the North Qiangtang Block is characterized by containing compound corals and intact fusulinids zones from Moscovian Fusulinella, Fusulina to Changhsingian Palaeofusulina zones; (2) the Early Permian of the South Qiangtang Block is

Good lives sexual offender treatment for mentally disordered offenders

Purpose – The main aim of this paper is to describe the content, structure and preliminary evaluation of a new Good Lives sexual offender treatment group (SOTG) for male mentally disordered offenders.

Design/methodology/approach – As evaluation and work on the SOTG is necessarily ongoing, case study descriptions of each patient who attended the SOTG and of their progress throughout SOTG are described.

Findings – Overall, the case study progress reports suggest that mentally disordered male patients made some notable progress on SOTG despite their differential and complex needs. In particular, attention to each patient's life goals and motivators appeared to play a key role in promoting treatment engagement. Furthermore, patients with lower intelligence quotient and/or indirect pathways required additional support to understand the links between the Good Lives Model (GLM) and their own risk for sexual offending.

Research limitations/implications – Further evaluations of SOTG groups, that incorporate higher numbers of participants and adequate control groups, are required before solid conclusions and generalisations can be made.

Practical implications – Practitioners should consider providing additional support to clients when implementing any future SOTGs for mentally disordered patients.

Originality/value – This is the first paper to outline and describe implementation of the GLM in the sexual offender treatment of mentally disordered male patients group format. As such, it will be of interest to any professionals involved in the facilitation of sexual offender treatment within this population.

Fast mining of non-derivable episode rules in complex sequences

Researchers have been endeavoring to discover concise sets of episode rules instead of complete sets in sequences. Existing approaches, however, are not able to process complex sequences and can not guarantee the accuracy of resulting sets due to the violation of anti-monotonicity of the frequency metric. In some real applications, episode rules need to be extracted from complex sequences in which multiple items may appear in a time slot. This paper investigates the discovery of concise episode rules in complex sequences. We define a concise representation called non-derivable episode rules and formularize the mining problem. Adopting a novel anti-monotonic frequency metric, we then develop a fast approach to discover non-derivable episode rules in complex sequences. Experimental results demonstrate that the utility of the proposed approach substantially reduces the number of rules and achieves fast processing.

Subsequence frequency measurement and its impact on knowledge discovery in single sequences

Subsequence frequency measurement is a basic and essential problem in knowledge discovery in single sequences. Frequency based knowledge discovery in single sequences tends to be unreliable since different resulting sets may be obtained from a same sequence when different frequency metrics are adopted. In this chapter, we investigate subsequence frequency measurement and its impact on the reliability of knowledge discovery in single sequences. We analyse seven previous frequency metrics, identify their inherent inaccuracies, and explore their impacts on two kinds of knowledge discovered from single sequences, frequent episodes and episode rules. We further give three suggestions for frequency metrics and introduce a new frequency metric in order to improve the reliability. Empirical evaluation reveals the inaccuracies and verifies our findings.

Highly efficient serial episode discovery in streams and complex sequences

This research proposed a series of methodologies and algorithms for highly efficient serial episode discovery in streams and complex sequences, and applied the developed techniques to quantitative analysis of the effects of price promotions. This research has outputted nine ERA ranking AlB papers published in international journals and conferences.

Qualitative estimation of camera motion parameters from video sequences

We propose a simple technique for extracting camera motion parameters from a sequence of images. The method can estimate qualitatively camera pan, tilt, zoom, roll, and horizontal and vertical tracking. Unlike most other comparable techniques, the present method can distinguish pan from horizontal tracking, and tilt from vertical tracking. The technique can be applied to the automated indexing of video and film sequences.

Two-dimensional string notation for representing video sequences

Most current work on video indexing concentrates on queries which operate over high level semantic information which must be entirely composed and entered manually. We propose an indexing system which is based on spatial information about key objects in a scene. These key objects may be detected automatically, with manual supervision, and tracked through a sequence using one of a number of recently developed techniques. This representation is highly compact and allows rapid resolution of queries specified by iconic example. A number of systems have been produced which use 2D string notations to index digital image libraries. Just as 2D strings provide a compact and tractable indexing notation for digital pictures, a sequence of 2D strings might provide an index for a video or image sequence. To improve further upon this we reduce the representation to the 2D string pair representing the initial frame, and a sequence of edits to these strings. This takes advantage of the continuity between frames to further reduce the size of the notation. By representing video sequences using string edits, a notation has been developed which is compact, and allows querying on the spatial relationships of objects to be performed without rebuilding the majority of the scene. Calculating ranks of objects directly from the edit sequence allows matching with minimal calculation, thus greatly reducing search time. This paper presents the edit sequence notation and algorithms for evaluating queries over image sequences. A number of optimizations which represent a considerably saving in search time is demonstrated in the paper.

Generating comprehensible summaries of rushes sequences based on robust feature matching

This paper describes our first attempt at tackling a pilot task in Trecvid: video summarization of rushes data [3]. Our method is based on the tight clustering produced via SIFT matching. In this first attempt, we try to examine how our approach performs without complex implementation in terms of concept detection and excerpt assembly (i.e, no picture-in-picture, split screen and special transitions). Although we do not perform very well in terms of concept inclusion, we rank very well in terms of the summary being easy to understand and relevancy of included segments.

Finding the optimal temporal partitioning of video sequences

The existing techniques for shot partitioning either process each shot boundary independently or proceed sequentially. The sequential process assumes the last shot boundary is correctly detected and utilizes the shot length distribution to adapt the threshold for detecting the next boundary. These techniques are only locally optimal and suffer from the strong assumption about the correct detection of the last boundary. Addressing these fundamental issues, in this paper, we aim to find the global optimal shot partitioning by utilizing Bayesian principles to model the probability of a particular video partition being the shot partition. A computationally efficient algorithm based on Dynamic Programming is then formulated. The experimental results on a large movie set show that our algorithm performs consistently better than the best adaptive-thresholding technique commonly used for the task.

Explicit state duration HMM for abnormality detection in sequences of human activity

The importance of explicit duration modelling for classification of sequences of human activity and the reliable and timely detection of duration abnormality was highlighted. The normal classes of behavior were designed to highlight the importance of modelling duration given the limitations of the tracking system. It was found that HMM was the weakest model for classification of the unseen normal sequences with 81% accuracy. Long term abnormality was investigated by artificially varying the duration of primary activity in a randomly selected test sequence. The incorporation of duration in models of human behavior is an important consideration for systems seeking to provide cognitive support and to detect deviation in the behavorial patterns.

Towards detecting patterns of human behaviour from image sequences

This paper details research that will explore the analysis of human behaviour via video surveillance. Digital computer images will be obtained from video footage of a real world scene, and positions of people in the scene will be identified and tracked through each frame in the sequence.

The noted positions will build into a pattern of motion that can be examined and classified. It is proposed that specific events, such as panic or fight situations, will have unique, and therefore identifying, characteristics that will enable automatic detection of such events.

It is envisaged that active cameras will be used when a situation of interest occurs, to enable more information to be extracted from the scene (e.g., panning to follow action, or zooming to enhance detail.)