Bashar Ourabi is a principle consultant at arabianconsult of Syria where he has been chairman since 2003. He holds Bsc. Eng., A Grad. Certificate in Project engineering from the University of Central Florida; and a MS. in Public Administration from the Doha Graduate Institute in Qatar.
Bashar completed his graduate studies at Doha Institute for Graduate Studies and his undergraduate studies at the Unversity of Central Florida. His research interests lie in the area of systems modelling, ranging from theory to design to implementation. He has collaborated actively with researchers in several other disciplines of computer science, system design, and bigData Artificial Intellegence, particularly BigData Expert System and Automated decision Making.
He has served on many international posts overlooking public infrastructure design and operations, varying from public transport, urban design and operations management. These posts spanned over the the US and the Middle East including Florida, UAE and Qatar.
Bashar has served on many conferences and workshop program committees and has succesfully delivered many corporate training programs..
Web Based Decision Making and Expert Systems
Discret Event Simulation
Corporate Support Systems
Dr. Chairi Kiourt is a research associate with the ATHENA - Research and Innovation Centre in Information, Communication and Knowledge Technologies - Xanthi’s Division, multimedia department since 2014. Also, as of December 2017, heis PostDoctoral researcher with the Hellenic Open University, School of Science and Technology, and as of 2018, visiting Lecturer at the Department of Informatics Engineering, Eastern Macedonia and Thrace Institute of Technology, Greece.
In 2003, he received his BSc degree in Electrical Engineering from the Electrical Engineering Department of the Eastern Macedonia and Thrace Institute of Technology, Greece. He also received an M.Sc. in System Engineering and Management in the specialty area: A. Information and Communication Systems Management from the Democritus University of Thrace, Greece. In 2017, received his PhD in Artificial Intelligence and Software Engineering from the Hellenic Open University. He has participated in several national and European research programs and co- authored to the writing of several scientific publications in international peer-reviewed journals and conferences with judges in the fields of collective artificial intelligence, multi-agent systems, reinforcement learning agents, virtual worlds, virtual museums and gamification.
Game playing multi-agent systems, reinforcement learning, colelctive artificial intelligence, distributed computing systems, virtual worlds, gamification
I am a computational archaeologist interested in how individuals and groups respond to both large scale processes such as climate change and local processes such as violence and wealth inequality. I am currently a PhD Candidate in the Department of Anthropology at Washington State University.
My dissertation research focuses on experimenting with paleoecological data (e.g., pollen) to assess whether or not different approaches are feasible for paleoclimatic field reconstructions. In addition, I will also use pollen data to generate vegetation (biome) reconstructions. By using tree-ring and pollen data, we can gain a better understanding of the paleoclimate and the spatial distribution of vegetation communities and how those changed over time. These data can be used to better understand changes in demography and how people responded to environmental change.
In Summer 2019, I attended the Santa Fe Institute‘s Complex Systems Summer School, where I got to work in a highly collaborative and interdisciplinary international scientific community. For one of my projects, I got to merry my love of Sci-fi with complexity and agent-based modeling. Sci-fi agent-based modeling is an anthology and we wanted to build a community of collaborators for exploring sci-fi worlds. We also have an Instagram page (@Scifiabm).
The goal of my research program is to improve our understanding about highly integrated natural and human processes. Within the context of Land-System Science, I seek to understand how natural and human systems interact through feedback mechanisms and affect land management choices among humans and ecosystem (e.g., carbon storage) and biophysical processes (e.g., erosion) in natural systems. One component of this program involves finding novel methods for data collection (e.g., unmanned aerial vehicles) that can be used to calibrate and validate models of natural systems at the resolution of decision makers. Another component of this program involves the design and construction of agent-based models to formalize our understanding of human decisions and their interaction with their environment in computer code. The most exciting, and remaining part, is coupling these two components together so that we may not only quantify the impact of representing their coupling, but more importantly to assess the impacts of changing climate, technology, and policy on human well-being, patterns of land use and land management, and ecological and biophysical aspects of our environment.
To achieve this overarching goal, my students and I conduct fieldwork that involves the use of state-of-the-art unmanned aerial vehicles (UAVs) in combination with ground-based light detection and ranging (LiDAR) equipment, RTK global positioning system (GPS) receivers, weather and soil sensors, and a host of different types of manual measurements. We bring these data together to make methodological advancements and benchmark novel equipment to justify its use in the calibration and validation of models of natural and human processes. By conducting fieldwork at high spatial resolutions (e.g., parcel level) we are able to couple our representation of natural system processes at the scale at which human actors make decisions and improve our understanding about how they react to changes and affect our environment.
land use; land management; agricultural systems; ecosystem function; carbon; remote sensing; field measurements; unmanned aerial vehicle; human decision-making; erosion, hydrological, and agent-based modelling
performance of urban water service provision, high levels of inequities and inefficiency persist. In terms of water distribution and cost, these undesirable patterns have a high impact on peri-urban areas usually populated by marginalized and poor populations. The high levels of Non-Revenue Water (NRW), together with the existence of corrupt practices and mismanagement of water utilities, remain a highly controversial issue.
This situation confronts rent-seeking theory directly, explaining the performance-corruption relationship (Repetto, 1986). The presumption is that low performance in water supply service provision results from corruption because rent-seeking occurs. Hence, the implementation of performance-oriented reforms in the water supply sector, such as regulation or private sector participation, will reduce corruption, increasing the efficiency of water service provision. Nevertheless, latest evidence shows that “key elements of good political governance have a positive effect on the access to water services in developing countries. In turn, private sector participation has little influence other than increasing internal efficiency of water providers” (Krausse, 2009).
Indeed the relation between governance, corruption and performance seems to be more complex than theory wants to acknowledge. It must be reviewed further than a simple cause-effect relationship. It appears that poor management of water utilities, evidenced by high levels of NRW, justifies new investments. Such practices can be encouraged by an “opportunistic management”, whilst at the same time maintaining an influential “hydrocratic elite” in the sphere of water control.
The present research proposal aims to understand the relation between mismanagement and corruption of water control practices in water supply service provision. The research examines how this relationship affects the performance of water service provision and relates to water supply governance models at municipal peri-urban level in three African countries.
To understand the mismanagement-corruption relationship, we look at different case studies of water supply service provision in Senegal, Ghana and Kenya. Each case represents a different governance model in terms of management practices, institutional and organizational settings, and the actors in place, which affects the performance of water service provision in terms of allocative efficiency and access to water (equity). Whether regulation, decentralization and private sector participation constitute possible ways to reduce corruption is examined in the context of water sector reform.
In a second step, we propose a theoretical model based on Agent Based Modelling (ABM) (Pahl-Wostl, 2007) to reproduce complex social networks under a Socio-Ecological System (SES) framework approach. The model will allow us to test whether collaborative governance in the form of collective action in a participatory and negotiated decision-making process for water control, can reduce corruption and increase performance.
The present research benefits from the project “Transparency and Integrity in Service Delivery in Sub-Saharan Africa”. This project, carried out by Transparency International (TI) in 8 Sub-Saharan countries, aims to increase access to education, health and water by improving transparency and integrity in basic service delivery. The proposal retains focus on Senegal, Ghana and Kenya in the water sector.
Key words: water control, mismanagement, corruption, performance, collaborative governance, modelling, collective action, negotiation, participation