Innovative Projects Realized

optimization of Software Systems driven by the Wisdom of Crowds

The popularity of smartphones is leading to an ever growing number of mobile apps that are published in official app stores. However, users might experience failures and crashes for some apps installed on their devices. For developers, diagnosing failures that users experience is a major challenge, since the diversity of contextual conditions makes it difficult to reproduce unexpected behaviors that emerge in the field. This project aims to drastically improve the quality of mobile apps by assisting developers to reproduce failures, based on the experience faced by a multitude of individuals.

Modéliser les données multi-relationnelles comme des séquences / Modeling multi-relational data as sequences

The objective of the project is to automatically learn missing information in knowledge bases (KBs), which are becoming essential tools to deal with big data, since they provide means to organize, manage and retrieve all this knowledge. These databases are huge directed multi-relational graphs, whose nodes correspond to entities connected by edges representing a certain relationships between them. These databases are far from being complete, so new tools are needed to complete them by adding new facts; this is termed link prediction. This project proposes to tackle this problem by learning representations for each of the elements of the graph. However up to now, all proposed solutions do that by modeling of triples in isolation. We have

observed several limitations in these models that we attribute to this fact, so we aim at modeling sequences of triples, that could capture longer–term interactions. We propose to do such modeling using Recurrent Neural Networks, which have recently shown to be very powerful for dealing with sequences.

Biogas Production using Thermophilic Anaerobic Digestion with Compressed Gas Mixing in a Mixed Plug Flow Digester

The project will be taking in agricultural waste sources to produce biogas. Biogas after being purified is equivalent to the natural gas supplied by your local utility. The core of the research will be to investigate methods to speed up gas production for a given waste input and increase gas extraction. The production will be sped up by controlling the temperature at a higher point and the extraction will be increased by recirculating the produced gas into the biomass to unsettle and release trapped pockets of gas.

Evaluation of Tristetraprolin in a Lipopolysaccharide-induced mouse model of fetal loss

Maternal complications such as miscarriage or fetal loss are important reproductive issues that can affect up to 30% of pregnant women worldwide. While these complications are worldwide health problems, their mechanisms are not yet clear. Using a well-established mouse model of fetal loss, our goal is to detect localization patterns of important genes that may play a role in fetal loss. We also aim to detect and measure expression levels of these genes in the same samples as well. We anticipate to ascertain varying degrees of cellular localization of our genes of interest with a differing pattern between our control and treated (lipopolysaccharide) groups. From this project, we aim to elucidate how some important genes may interact with each other and potentially contribute to fetal loss.

Computer Simulation of Geospatial Dynamics: How Do Cities Grow and Evolve?

Cities are the engines of creativity, wealth creation and economic growth in our society. Despite the increasing importance of cities in modern world, our ability to understand them scientifically and to manage them well in practice is limited. The greatest difficulties and challenges to any scientific approach to cities have resulted from their many interdependent facets, such as social, economic, infrastructural, and temporal-spatial processes. The problems associated with urban research and city management lie in the treatments of those facets as independent issues. This frequently results in ineffective policies which often lead to unfortunate and sometimes disastrous unintended consequences. This research is going to treat city as complex system to investigate the mechanics behind urban land use growth and evolution. The ultimate goal of this research is going to build a computer-based simulation model to simulate the dynamic processes of urban growth and evolution by integrating urban system theory, complex system theory, and Artificial Intelligent (AI) technologies. The model will be based on an integration of Cellular Automata (CA), Agent-based Modeling (ABM) and evolutionary algorithms. Shanghai and Calgary will be selected as implementation cases of this research.

Data Mining of Urban Mobility Pattern Using Taxi Trajectory Data

Urban mobility results from human movements from one region to another for interaction such as working, trading goods and other social events. Urban mobility has caused not only urban prosperity, but also some problems in the urban system, such as congestion, air pollution, energy consumption, public health and disease transmission. Therefore, understanding urban mobility is very important for urban planning and management. Urban mobility usually has certain patterns such as origin-destination pattern and spatio-temporal pattern. This project aims to discover the potential mobility patterns based on taxi trajectory data from Shenzhen city, China. Firstly, the entire city is partitioned into several regions. The functions of each region will be studied using a statistical method, and be represented as a vector; Secondly, regions will be clustered into several categories, and regions with similar functions will be grouped together, and finally it aims to discover frequent origin-destination pattern among regions and spatiotemporal pattern based on the probability distribution of taxi pick-up time and location.

A case study on the influence of fuel quality on the concentration and chemical components of PM2.5 from vehicle emission

Recently, poor air quality due to fine particles (PM2.5) in large areas of China has gained much international attention, and vehicle emission is a significant source of PM2.5. Fuel quality is one of the influencing factors on vehicle emission. However, due to a large number of potential factors including fuel attributes, emission control devices, and driving conditions, there is a lack of systematic investigations on the relationship between fuel quality and PM2.5 emission quantities as well as its compositions. This study aims to improve our understanding of current practice and knowledge gaps in the fuel quality-PM2.5 emission relationship. This will be archived by a literature review and a pilot experimental study. A better understanding of relationship between fuel quality and vehicular PM2.5 emission will provide decision makers useful information. This information will lead to improved fuel quality thus to reduce discharge of air pollutants and to mitigate its health effects

Investigating Social Network Models in Knowledge Building Teacher Communities

This proposed researched aims to examine online Knowledge Building Communities (KBC) for teacher professional development. KBC is a community, which is composed of a group of individuals working collaboratively to create collective knowledge rather than construction of a specific product or completion of a task. There is a commitment among the members of KBC to invest its resources in the collective pursuit of understanding (Hewitt, Brett, Scardamalia, Frecker, & Webb, 1995). In this research, I will focus on professional development in a KBC in order to define ideal conditions and constraints that constitute an optimal Knowledge Building professional development. In order to do this, I will examine a variety of network models of the participants and the ideas that are emerged in online KBC. Furthermore, the evolution of these models and the factors that affect the formation and evolution of them will be scrutinized. Accordingly, the results will be used to inform the development of the network models framework.

A Security and Privacy Model for M-Services in Toy Computing

The research project aims to develop a systematic methodology to link safety policy in terms of security and privacy considerations to the realization of Bring Your Own Device (BYOD), which encourages users to use their own mobile devices, such as smart phones and tablet PCs, to access various services to support a workflow in a Cloud infrastructure. Since the services may contain sensitive information or even trade secrets of an enterprise, the safety policy usually specifies the security and privacy rules in End User Level Agreement (EULA) format as realistic regulatory measures and assessment. The first phase of the project will develop a methodology to support security and privacy assessment over services via BYOD in the context of Cloud infrastructure. The second phase will develop hardware and software prototypes to test feasibility and usability of the methodology in a scalable and interoperable approach. Sample workflow scenarios with mobile devices, such as Android tablet PCs, involving security and privacy features will be developed with the support of business intelligence modules which then undergo data analytics and data mining tools for information retrieval and knowledge discovery.

Development of agricultural machinery emission inventory of Beijing, Tianjin, and Hebei

In China, with the rapid advancement of agricultural practice, agriculture machineries have become an essential tool. The widely use of agriculture machineries also make them a significant source of air pollutants, including nitrogen oxides (NOx) and particulate matter (PM), because most agricultural machineries are not equipped with an emission treatment system and some are poorly maintained. This study will develop an agricultural machinery air emission inventory of Beijing, Tianjin, and Hebei; this region often experiences the worst air quality in China. Survey questionnaires will be used to collect inventory and usage data of agriculture machineries. Emission factors will be selected from the literature. An estimation of air emissions in Beijing, Tainjin and Hebei will provide valuable information on the current impact of agricultural machinery on regional air quality and identify direction of improvement. The information collected will help policy makers enforce necessary regulations to improve air quality in the region.

The Spice of Life: Cardamom cultivation, trade networks, and livelihoods in Yunnan, China

Agricultural production and trade are central to Chinese economic development and the livelihoods of millions of people throughout the country. In China’s southwest Yunnan province, cardamom is an important cash crop that many rural communities cultivate and trade to make an income. This research project will focus on the current cardamom cultivation practices and trade networks in the Yunnan province, to determine how resources are managed and how knowledge is disseminated. My host institution is in the provincial capital of Kunming, but most of my fieldwork will be completed in the southern rural counties of Hekou and Maguan on the Sino-Vietnamese borderlands. I will employ qualitative research methods such as semistructured and unstructured interviews with cultivators, traders, and municipal officials. I expect to learn how cardamom travels throughout the province, how different traders at different scales interact with one another, and what socio-political relationships are present in trade networks.

Socio-cultural Impact Management in Mexico’s Marine Protected Areas

network of Marine Protected Areas (MPAs). My research will include case studies on two Mexican MPAs to examine what forms of impact assessment, monitoring, and management are taking place, as well as to investigate the perceived effectiveness of these methods by relevant community stakeholders. Using two MPA sites will allow me to compare how social impact management varies between different governance regimes. The case studies will include a) interviews with key informants, MPA managers and community members to understand the status of social and cultural impact monitoring and management and b) participatory mapping and focus groups with decision makers and community representatives to explore how impact management might be improved. I expect this research to make theoretical contributions to current understanding of social and cultural consequences of marine protected areas, including insights toward improving marine conservation practices globally through the adaptive management of these impacts.