A disaster risk assessment model for the conservation of cultural heritage sites in Melaka Malaysia

There exist ongoing efforts to reduce the exposure of Cultural Heritage Sites (CHSs) to Disaster Risk (DR). However, a complicated issue these efforts face is that of ‘estimation’ whereby no standardised unit exist for assessing the effects of Cultural Heritage (CH) exposed to DR as compared to other exposed items having standardised assessment units such as; ‘number of people’ for deaths, injured and displaced, ‘dollar’ for economic impact, ‘number of units’ for building stock or animals among others. This issue inhibits the effective assessment of CHSs exposed to DR. Although there exist several DR assessment frameworks for conserving CHSs, the conceptualisation of DR in these studies fall short of good practice such as international strategy for disaster reduction by United Nations which expresses DR to being a hollistic interplay of three variables (hazard, vulnerability and capacity). Adopting such good practice, this research seeks to propose a mechanism of DR assessment aimed at reducing the exposure of CHSs to DR. Quantitative method adopted for data collection involved a survey of 365 respondents at CHSs in Melaka using a structured questionnaire. Similarly, data analysis consisted of a two-step Structural Equation Modelling (measurement and structural modelling). The achievement of the recommended thresholds for unidimensionality, validity and reliability by the measurement models is a testimony to the model fitness for all 8 first-order independent variables and 2 first-order dependent variables. While hazard had a ‘small’ but negative effect, vulnerability had a ‘very large’ but negative effect on the exposure of CHSs to DR. Likewise, capacity had a ‘small’ but positive effect on the exposure of CHSs to DR. The outcome of this study is a Disaster Risk Assessment Model (DRAM) aimed at reducing DR to CHSs. The implication of this research is providing insights on decisions for DR assessment to institutions, policymakers and statutory bodies towards their approach to enhancing the conservation of CHSs

Towards Full Automated Drive in Urban Environments: A Demonstration in GoMentum Station, California

Each year, millions of motor vehicle traffic accidents all over the world cause a large number of fatalities, injuries and significant material loss. Automated Driving (AD) has potential to drastically reduce such accidents. In this work, we focus on the technical challenges that arise from AD in urban environments. We present the overall architecture of an AD system and describe in detail the perception and planning modules. The AD system, built on a modified Acura RLX, was demonstrated in a course in GoMentum Station in California. We demonstrated autonomous handling of 4 scenarios: traffic lights, cross-traffic at intersections, construction zones and pedestrians. The AD vehicle displayed safe behavior and performed consistently in repeated demonstrations with slight variations in conditions. Overall, we completed 44 runs, encompassing 110km of automated driving with only 3 cases where the driver intervened the control of the vehicle, mostly due to error in GPS positioning. Our demonstration showed that robust and consistent behavior in urban scenarios is possible, yet more investigation is necessary for full scale roll-out on public roads.Comment: Accepted to Intelligent Vehicles Conference (IV 2017

A dynamic model for real-time tracking of hands in bimanual movements

The problem of hand tracking in the presence of occlusion is addressed. In bimanual movements the hands tend to be synchronised effortlessly. Different aspects of this synchronisation are the basis of our research to track the hands. The spatial synchronisation in bimanual movements is modelled by the position and the temporal synchronisation by the velocity and acceleration of each hand. Based on a dynamic model, we introduce algorithms for occlusion detection and hand tracking

leave a trace - A People Tracking System Meets Anomaly Detection

Video surveillance always had a negative connotation, among others because of the loss of privacy and because it may not automatically increase public safety. If it was able to detect atypical (i.e. dangerous) situations in real time, autonomously and anonymously, this could change. A prerequisite for this is a reliable automatic detection of possibly dangerous situations from video data. This is done classically by object extraction and tracking. From the derived trajectories, we then want to determine dangerous situations by detecting atypical trajectories. However, due to ethical considerations it is better to develop such a system on data without people being threatened or even harmed, plus with having them know that there is such a tracking system installed. Another important point is that these situations do not occur very often in real, public CCTV areas and may be captured properly even less. In the artistic project leave a trace the tracked objects, people in an atrium of a institutional building, become actor and thus part of the installation. Visualisation in real-time allows interaction by these actors, which in turn creates many atypical interaction situations on which we can develop our situation detection. The data set has evolved over three years and hence, is huge. In this article we describe the tracking system and several approaches for the detection of atypical trajectories