Project Collab Directory

Earthquake geology of Southeast Asia
Name of researcher: Dr Afroz Ahmad Shah
Research Summary:

In many parts of the world, active faults are too poorly understood to allow even rudimentary quantification of their role in regional neotectonic deformation or to make realistic estimates of seismic hazards, let alone seismic risk assessments.Such was the case before the infamous 1999 Chi-Chi earthquake in Taiwan. That rather late awakening in Taiwan to the value of using tectonic landforms in the characterization of active faults and folds led to the systematic application of geomorphic evidence to characterize the active tectonics throughout the island and offshore, which was carried out by J. Bruce H. Shyu (National Taiwan University, Taipei, Taiwan) and his group. Although the active fault that produced the earthquake had long been known from the interpretation of subsurface (stratum below the earth’s surface) data and outcrops (group of rocks that stick out of the ground), it had not been considered active. Surface fault ruptures and associated folding during the earthquake clearly revealed the fault’s location, danger and clear geomorphic evidence for recent, prior activity. A similar geomorphological investigation of the neotectonic elements of Myanmar is largely completed, as part of the Ph.D. work of Caltech graduate student Wang Yu.

The situation in western Indonesia after the 2004 Indian Ocean earthquake and tsunami illustrates well the state of SEAsian neotectonics. Soon after the devastating earthquake and tsunami of 2004, when theUnited States Geological Survey(USGS)was producing a Probabilistic Seismic Hazard Analysis (PSHA) of the western half of Indonesia,survey personnel found that there was little in the way of reliable active-fault mapping. We, at the Earth Observatory of Singapore,were asked to rapidly compile a map of the active faults of Sumatra, Java, Borneo and Bali to serve as a key element in their evaluation of probabilistic earthquake hazard. We spent a couple of months evaluating Shuttle Radar Topography Mission (SRTM) digital imagery and presented them with a very crude map of active structures, which they used in their analysis.

The active tectonic elements of many other regions within SE Asia are also not well understood. These include eastern Indonesia, Malaysia, Laos, Vietnam, Cambodia and many offshore tracts. Likewise, rates of fault slip and past seismic history are for the most part poorly known. This regional state-of-knowledge contrasts markedly with better-studied places such as Japan and California. More than two decades ago, earlier thorough mapping of active structures enabled creation of the first probabilistic seismic hazard maps of those places. The fact that nearly all of the dozen or so subsequent destructive earthquakes in California have occurred within the high-probability areas shown by the California maps attests to the reliability of these early PSHA maps. More recent PSHA maps covering the entirety of the US are the basis for today’s seismic zonation of the country. These maps, too, are based upon knowledge of the location of active faults and varying levels of understanding of their slip rates.

The Earth Observatory of Singapore was established in 2009 to fill the above-mentioned gaps in research and the aim is “to conduct fundamental research on earthquakes, volcanic eruptions, tsunami and climate change in and around SE Asia, toward safer and more sustainable societies”.It has successfully conducted research in most of the SE Asia. However, to the best of our knowledge, there has not been involvement of any scientist from Malaysia to conduct the earthquake research. We are aware that the need to undertake a thorough research study on earthquakes is more in Malaysia than in Singapore, potentially because of the tectonic settings and the dimensions of the country . This has not been done in any part of the country and therefore, it is extremely important to map all the active tectonic features in Malaysia.By observing the satellite images, many places in Malaysia with active faults should be mapped in greater detail, so that we can understand the potential of earthquake risk in the country and surrounding areas in the future. Also, the potential earthquake risk from the neighbouring regions (e.g. Indonesia) should be assessed. There are various seismic sources around this country (Figure 1, upper panel), which are partially mapped and based on these structures,the USGS has produced a generalised earthquake hazard map of the region (Figure 1, lower panel). Though it should be noted that this map is crude and therefore, it is compulsory to conduct a thorough research on risk of earthquakes in order to generate a more realistic earthquake hazard map of the region. Also, the paleoseismic (old earthquakes) research is required to understand the past earthquakes and their sources.


Figure 1: The tectonic setting (upper panel) and generalized seismic hazard (lower panel) of Malaysia and its surrounding areas

As a conclusion, the earth sciences education is extremely important to minimize the risks associated with natural hazards. Unfortunately,Malaysian higher education institutions do not offer a comprehensive geosciences degree program. To fill these obvious gaps, both in education and research, will require serious collaborations with earth scientists around the globe and therefore, we would be happy to work with any of the experts in Malaysia to spread the earth sciences awareness in this country.

Scientific Malaysian Profile:
https://www.scientificmalaysian.com/scimy/members/afrozshah/profile/  

Link:
TEDxNTU talk by Dr Afroz Ahmad Shah – Is earthquake prediction a possibility?

Contact Email: afroz[AT]ntu.edu.sg
Computing with artificial and biological neural networks
Name of researcher: Dr Tomas Maul
Research Summary:

My main research interests revolve entirely around Neural Computation. Together with several PhD students and collaborators, I am trying to unravel what computations are being carried out by different neural systems, and how and why they are being implemented. Therefore, I am interested in both biological and artificial aspects of neural computation.

On the biological side, my work falls mostly within the field of Computational Neuroscience concerned with how different biological neural systems solve different types of computational problems. In terms of problem domains, I have mostly been involved in the research of visual functions and therefore Computer Vision and Image Processing are central to my investigations. I am currently focusing on the simulation-modelling of the biological retina, through which I hope to:
1) answer several questions pertaining to the structure and function of different retinae,
2) propose new image processing techniques for low-level functions such as illumination normalization and colour correction, and
3) propose new designs for retinal prostheses.

So far, our models of the outer retina have revealed that the relatively simple micro-circuits established between photoreceptors, horizontal cells and bipolar cells are capable of a significant number of distinct image processing functions such as denoising, contrast and saturation enhancement, edge detection and colour normalization (see Figure 1 for an example of local illumination normalization and denoising). We are currently in the process of extending our models of the retina, by adding several amacrine and ganglion cell types, with the aim of understanding retinal colour coding and processing. This understanding should guide us towards achieving the goal of enhancing retinal prostheses for allowing users to experience coherent colour perception.

On the artificial or applied side we are developing new types of hybrid artificial neural networks with a particular emphasis on functional diversity, i.e., Neural Diversity Machines (NDM). The notion of diversity is borrowed from biological neural systems where we observe a significant diversity of neurons in terms of morphology, connectivity, electrophysiology, and other properties. The case of the retina, where on average (across species) there are approximately 55 different types of neuron, is one simple illustration of this point. Initial experiments have shown some promising results and our current priority is to improve the speed and reliability of optimization methods for NDM.

Although NDMs are intended to be general and have already been tested on several unrelated benchmarks from the UCI Machine Learning Repository, one of the target domains which ties NDMs with our more biologically oriented research pertains to the segmentation of histological images of the retina for automated or semi-automated reconstruction of retinal circuits (i.e. connectomics research). The motivation behind this application is to bridge one gap in the chain from biological specimens through data acquisition up to computational modelling. To completely bridge the gaps in this chain means that one day we will be able to scan a neural tissue (e.g., retina) and automatically generate computational insights. As collaboration is essential (e.g., biologists and computer scientists), I look forward to receiving any potential queries from interested parties.

Figure 1: Examples of image processing by a neural model of the outer retina.

Scientific Malaysian Profile:
https://www.scientificmalaysian.com/scimy/members/tomasmaul/profile/

Links:
[1] Research page – http://baggins.nottingham.edu.my/~kcztm/Research.html
[2] Interdisciplinary Computing and Complex Systems research group – http://icos.cs.nott.ac.uk/
[3] Cognitive and Sensory Systems research group – http://www.nottingham.edu.my/Psychology/Research/CognitiveandSensorySystemsGroup.aspx

Contact Email: Tomas.Maul[AT]nottingham.edu.my