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Extracting Spatio-temporal Texture Signatures for Crowd Abnormality Detection
No full textIn order to achieve automatic prediction and warning of hazardous crowd behaviors, a Spatio-Temporal Volume (STV) analysis method is proposed in this research to detect crowd abnormality recorded in CCTV streams. The method starts from building STV models using video data. STV slices – called Spatio-Temporal Textures (STT) - can then be analyzed to detect crowded regions. After calculating the Gray Level Co-occurrence Matrix (GLCM) among those regions, abnormal crowd behavior can be identified, including panic behaviors and other behavioral patterns. In this research, the proposed STT signatures have been defined and experimented on benchmarking video databases. The proposed algorithm has shown a promising accuracy and efficiency for detecting crowd-based abnormal behaviors. It has been proved that the STT signatures are suitable descriptors for detecting certain crowd events, which provide an encouraging direction for real-time surveillance and video retrieval applications
Engineering Knowledge for Automated Planning: Towards a Notion of Quality
No full textAutomated planning is a prominent Artificial Intelligence challenge, as well as being a common capability requirement for intelligent
autonomous agents. A critical aspect of what is called domain-independent planning, is the application knowledge that must be added to the planner to create a complete planning application. This is made explicit in (i) a domain model, which is a formal representation of the persistent domain knowledge, and (ii) an associated problem instance, containing the details of the particular problem to be solved. Both these components are used by automated planning engines for reasoning, in order to synthesize a solution plan.
Formulating knowledge for use in planning engines is currently something of an ad-hoc process, where the skills of knowledge engineers significantly influence the quality of the resulting planning application. On top of that, a notion of quality of the knowledge
captured within a domain model is missing; it is therefore hard to provide useful guidelines to knowledge engineers.
This paper raises some issues relating to the engineering of application knowledge for automated planning, focussing on the domain
model. It uses the idea of a domain model as a formal specification of a domain, and considers what it means to measure the quality of such a specification. To do this it proposes definitions of the attributes of a domain model and its encoding language, which are needed by the automated planning community in order to improve tools for supporting the engineering of planning knowledge, and to advance toward a shared and inclusive definition of quality of
domain models
A year at usher's hill
No full textA year at usher’s hill is the final part of a trilogy of releases – following on from Rift Patterns (Audiobulb) and Residual Forms (Cronica), based on psychogeography and psychosonology. The fifty minute album was started in July 2016 and completed in July 2017 and is highly autobiographical, charting events, places, and most importantly the people associated with these experiences. For me, the process of creating this album was a re-discovery of memories and the connections between them across time. Composing became a reflective and meditative process: teasing out the meaning of events, celebrating the happenstance, and the pleasure of the moment
Training Transfer: The Case for 'Implementation Intentions'
No full textAs organizations adopt a more inclusive or pluralistic approach to talent management, there is an emphasis on the engagement of a broader segment of the workforce to deliver both strategic and operational objectives. Accompanying this is investment in learning, training and development activity which is intended to enhance the achievement of the objectives based on the assumption of the effective transfer of training to improve performance or behavioural outcomes. Ensuring that training investment is converted to measurable outcomes is therefore a priority for many organizations and Return on Investment in Training (ROIT) is increasingly sought in the same way as for any other corporate investment. This article synthesizes developments in goal setting theory and highlights a limitation with regards to the theory being applied to the contemporary workplace. It proposes that implementation intentions and the associated ‘if/then’ plans offer the chance to mediate this. Key to these plans being successful is for them to be embedded at the learning design stage creating a clear link between the need for the learning/training and agreed objectives. A large part of the success of implementation intentions is that control of behaviour is given to situational cues in the workplace and these can be reinforced by supportive line managers and peers. But it is essential that they are also aware of the implementation intention plan in order to offer informed support. A holistic learning environment is key to the success of any intervention but given the importance of situational cues when considering implementation intentions it is vital that both learners and those who support them in the workplace are aware of the specific roles they play and the impact they have
The Validation of an ACS-SSI based Online Condition Monitoring for Railway Vehicle Suspension Systems using a SIMPACK Model
No full textTo enhance the safe operation of modern railway vehicles, an online condition monitoring scheme is proposed for vehicle suspension systems. The core technology of the scheme is based on the average correlation signals based stochastic subspace identification (ACS-SSI) algorithm which allows system identification to be implemented reliably with output signals only that have strong noise and nonlinearity in vehicle applications. To validate the scheme, a series simulation studies were carried out based on a more realistic bogie model, developed in SIMPACK, under typical random excitations including vertical, lateral, rolling and gauging directions. ACS-SSI then applied to the signals from the model under common faults in the bogie suspensions to identify the system parameters. The agreeable results obtained by comparing the identified results with that calculated by SIMPACK shows that the proposed scheme performs reliably in obtaining the system parameters: modal frequency, damping and shape that are required for online diagnosis
Early Detection of Rolling Bearing Faults Using an Auto-correlated Envelope Ensemble Average
No full textBearings have been inevitably used in broad applications of rotating machines. To increase the efficiency, reliability and safety of machines, condition monitoring of bearings is significant during the operation. However, due to the influence of high background noise and bearing component slippages, incipient faults are difficult to detect. With the continuous research on the bearing system, the modulation effects have been well known and the demodulation based on optimal frequency bands is approved as a promising method in condition monitoring. For the purpose of enhancing the performance of demodulation analysis, a robust method, ensemble average autocorrelation based stochastic subspace identification (SSI), is introduced to determine the optimal frequency bands. Furthermore, considering that both the average and autocorrelation functions can reduce noise, auto-correlated envelope ensemble average (AEEA) is proposed to suppress noise and highlight the localised fault signature. In order to examine the performance of this method, the slippage of bearing signals is modelled as a Markov process in the simulation study. Based on the analysis results of simulated bearing fault signals with white noise and slippage and an experimental signal from a planetary gearbox test bench, the proposed method is robust to determine the optimal frequency bands, suppress noise and extract the fault characteristics
Do Individual Differences in Emotion Regulation Mediate the Relationship Between Mental Toughness and Symptoms of Depression?
Get PDFMental Toughness (MT) provides crucial psychological capacities for achievement in sports, education, and work settings. Previous research examined the role of MT in the domain of mental health and showed that MT is negatively associated with and predictive of fewer depressive symptoms in nonclinical populations. The present study aimed at (1) investigating to what extent mentally tough individuals use two emotion regulation strategies: cognitive reappraisal and expressive suppression; (2) exploring whether individual differences in emotion regulation strategy use mediate the relationship between MT and depressive symptoms. Three hundred sixty-four participants (M = 24.31 years, SD = 9.16) provided self-reports of their levels of MT, depressive symptoms, and their habitual use of cognitive reappraisal and expressive suppression. The results showed a statistically significant correlation between MT and two commonly used measures of depressive symptoms. A small statistically significant positive correlation between MT and the habitual use of cognitive reappraisal was also observed. The correlation between MT and the habitual use of expressive suppression was statistically significant, but the size of the effect was small. A statistical mediation model indicated that individual differences in the habitual use of expressive suppression mediate the relationship between MT and depressive symptoms. No such effect was found for the habitual use of cognitive reappraisal. Implications of these findings and possible avenues for future research are discussed
‘You shut up and go along with it’: an interpretative phenomenological study of former professional footballers’ experiences of addiction
Get PDFResearch evidence suggests that professional players across a variety of sports may be at greater risk of developing addictions and other mental illnesses than the general population, both during and post-career. In this paper, we report findings from a larger project on the experiences of career transition in UK professional footballers that provide some insight into this. Using an Interpretative Phenomenological approach, four ex-professional footballers who were attending the Sporting Chance Clinic for help with problems concerning alcohol and gambling were interviewed in depth about their experiences. Focussing on issues the players perceived to be relevant to their addictions, the data were analysed thematically, drawing on Van Manen’s phenomenological method, and individual case histories were also produced. The analysis suggested that club culture was key to understanding the players’ difficulties; a harsh, unsupportive psychological environment combined with expectations of manliness resulted in a culture of silence in the face of personal difficulties. Relationships within the culture of pro-football were fraught with anxiety and distrust, leaving the players feeling unable and unwilling to disclose their problems and feeling used and unvalued by their managers. The lack of supportive relationships in their clubs also resulted in loneliness and social withdrawal for the participants. We conclude with a number of recommendations for the governing bodies in professional football, clubs and individual players
Detecting Defective Bypass Diodes in Photovoltaic Modules using Mamdani Fuzzy Logic System
No full textIn this paper, the development of fault detection method for PV modules defective bypass diodes is presented. Bypass diodes are nowadays used in PV modules in order to enhance the output power production during partial shading conditions. However, there is lack of scientific research which demonstrates the detection of defective bypass diodes in PV systems. Thus, this paper propose a PV bypass diode fault detection classification based on Mamdani fuzzy logic system, which depends on the analysis of Vdrop, Voc , and Isc obtained from the I-V curve of the examined PV module. The fuzzy logic system depends on three inputs, namely percentage of voltage drop (PVD), percentage of open circuit voltage (POCV), and the percentage of short circuit current (PSCC). The proposed fuzzy system can detect up to 13 different faults associated with defective and non-defective bypass diodes. In addition, the proposed system was evaluated using two different PV modules under various defective bypass conditions. Finally, in order to investigate the variations of the PV module temperature during defective bypass diodes and partial shading conditions, i5 FLIR thermal camera was used
Successive Bacterial Colonisation of Pork and its Implications for Forensic Investigations
Get PDFAims: Bacteria are considered one of the major driving forces of the mammalian decomposition process and have only recently been recognised as forensic tools. At this point, little is known about their potential use as ‘post-mortem clocks’. This study aimed to establish the proof of concept for using bacterial identification as post-mortem interval (PMI) indicators, using a multi-omics approach.
Methods and Results: Pieces of pork were placed in the University’s outdoor facility and surface swabs were taken at regular intervals up to 60 days. Terminal restriction fragment length polymorphism (T-RFLP) of the 16S rDNA was used to identify bacterial taxa. It succeeded in detecting two out of three key contributors involved in decomposition and represents the first study to reveal Vibrionaceae as abundant on decomposing pork. However, a high fraction of present bacterial taxa could not be identified by T-RFLP. Proteomic analyses were also performed at selected time points, and they partially succeeded in the identification of precise strains, subspecies and species of bacteria that colonized the body after different PMIs.
Conclusion: T-RFLP is incapable of reliably and fully identifying bacterial taxa, whereas proteomics could help in the identification of specific strains of bacteria. Nevertheless, microbial identification by next generation sequencing might be used as PMI clock in future investigations and in conjunction with information provided by forensic entomologists.
Significance and Impact of the Study: To the best of our knowledge, this work represents the first attempt to find a cheaper and easily accessible, culture-independent alternative to high-throughput techniques to establish a ‘microbial clock’, in combination with proteomic strategies to address this issue
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