Anas Alfaris

Hierarchical Decomposition and Multidomain Formulation for the Design of Complex Sustainable Systems

Designing a large-scale complex system, such as a city of the future, with a focus on sustainability requires a systematic approach toward integrated design of all subsystems. Domains such as buildings, transportation, energy, and water are all coupled. Designing each one in isolation can lead to suboptimality where sustainability is achieved in one aspect but at the expense of other aspects. Traditional ad hoc allocations of design parameter precedence and dependence cannot be used for cases where new (instead of only mature) architectures are to be explored. A methodology is introduced for addressing design problems of complex sustainable systems that is comprised of, on the one hand, a hierarchical decomposition that includes multilevel abstraction and design parameter identification, and on the other hand, a multidomain formulation, which includes parameter dependency identification, design cycle identification and decision structuring, and scoping. The application of the methodology for the design of a new urban development, Masdar City in Abu Dhabi, with over 220 different form and behavior parameter sets is shown.

A malicious activity detection system utilizing predictive modeling in complex environments

Complex enterprise environments consist of globally distributed infrastructure with a variety of applications and a large number of activities occurring on a daily basis. This increases the attack surface and narrows the view of ongoing intrinsic dynamics. Thus, many malicious activities can persist under the radar of conventional detection mechanisms long enough to achieve critical mass for full-fledged cyber attacks. Many of the typical detection approaches are signature-based and thus are expected to fail in the face of zero-day attacks. In this paper, we present the building-blocks for developing a Malicious Activity Detection System (MADS). MADS employs predictive modeling techniques for the detection of malicious activities. Unlike traditional detection mechanisms, MADS includes the detection of both network-based intrusions and malicious user behaviors. The system utilizes a simulator to produce holistic replication of activities, including both benign and malicious, flowing within a given complex IT environment. We validate the performance and accuracy of the simulator through a case study of a Fortune 500 company where we compare the results of the simulated infrastructure against the physical one in terms of resource consumption (i.e., CPU utilization), the number of concurrent users, and response times. In addition to an evaluation of the detection algorithms with varying hyper-parameters and comparing the results.

The influence of social norms on synchronous versus asynchronous communication technologies

Extensive theoretic work attempts to address the role of social norms in describing, explaining and predicting human behaviors. However, traditional methods of assessing the effect can be expensive and time consuming. In this work, we utilize data generated by the call detail records (CDRs) and geo-tagged Tweets (GTTs) as enabling proxies for understanding human activity patterns. We present preliminary results on the effect of social norms on communication patterns during different times of the day, including prayer times. Specifically, we investigate the variations in population behavioral patterns with respect to social norms between asynchronous (i.e., Twitter) and synchronous (i.e., phone calls) communication mediums in the city of Riyadh, the capital of Saudi Arabia.

Interaction Design in a Tangible Collaborative Decision Support System: The City Schema DSS

In this paper, we introduce a decision support system (DSS) platform (City Schema) that is designed to connect a tangible interface within a 3D modeling environment (City Form) with a simulation engine for analyzing the data of the urban, transportation, energy and water systems of the city (City Analytics) to support collaborative city planning. This DSS connects two completely independent systems into one integrated system. The first system is a physical 3D model of a city with a tangible user interface that supports interactive and collaborative activities and provides users with direct manipulation interaction and intuitive interfaces. The second system is an urban modeling design tool which is a simulation engine that has several simulation modules such as operational energy, mobility, daylight, transportation and others. The DSS we present here can be used to describe a real world problem and identify possible solutions to the modeled problem through the computation of many scenarios/alternatives so that users of the DSS can evaluate, compare and select a potential solution. Our City Schema DSS consists of: database management component, simulation modules management component, and an interactive user interface with dynamic visualization and decision scenario simulations. Human factors for supporting multi-user co-located collaboration to assist decision makers in making better decisions are examined. Design implications of different interaction modalities for decision support systems and their impact on providing intuitive and engaging user experiences are discussed.

A multi-attribute decision support framework for conventional generation capacity expansion

In order to be mindful of the overarching theme of reducing global dependency on oil for energy production, careful execution of current thermal and gas fired conventional capacity must be taken into consideration. Given the high energy demand profiles experienced in some developing countries, heavy investments in renewable and alternative generation may not be enough to suffice this ever growing demand. This is especially the case when dealing with high seasonality demand. This paper develops a modeling framework by which policy makers can examine a wide range of possible solutions to this problem through a multi-attribute scenario analysis approach developed. Through rapid prototyping of multiple curated what if scenarios, energy planners can analyze a wide range of complimentary conventional capacity portfolios that work hand in hand with the existing renewable and alternative efforts to achieve an overall desired energy outlook. The framework was developed and applied with the Kingdom of Saudi Arabia as a case study. The scenarios analyzed herein span various demand growths, nuclear and renewable deployment plans, as well as various conventional capacity expansion options. Finally a selected set of scenarios are evaluated across multiple trade-off spaces and discussed.

The Multidimensional Hierarchically Integrated Framework (MHIF) for Modeling Complex Engineering Systems

In recent years, the interest in modeling complex engineering systems has grown rapidly. Due to their highly nonlinear nature coupled with their critical importance, the task of modeling such systems becomes a high-risk, high-payoff endeavor. There are many complexities associated with understanding and modeling the dynamics of such systems, these include functional, spatial and temporal complexities. The main objective of this paper is to present a modeling framework that enables the planning and evaluation of complex engineering systems taking into account these multidimensional complexities. The framework uses a multidimensional hierarchical decomposition of complex engineering systems combined with modeling techniques such as System Dynamics and Agent Based Modeling. Decomposition and modeling are integrated to simulate possible future states of the system and to evaluate different plans and scenarios for system evolution using key performance indicators (KPIs). The paper also presents a case study demonstrating the use of the proposed framework for an integrated water model applied to the kingdom of Saudi Arabia.

CoPI: a web-based collaborative planning interface platform

In this paper we present the Collaborative Planning Interface (CoPI), a web-based multiuser collaboration interface platform for planning of complex systems. The interface provides analytical and visualization components to support decision makers. The Interface is designed using a user-centered design approach, while considering existing tools and environments in the field of decision support systems. The architecture and structure of the Interface are described as well as the flow of the user experience within the system. Finally, a case study explains the use of CoPI in collaborative policy planning for large-scale infrastructures.

Towards Cloud-Based Decision Support Platform for Group Decision Making

Nowadays, the shift towards cloud computing services is rapidly increasing. Organizations are leaning more towards adopting cloud-based services to increase their computation and processing power with reduced operational and maintenance costs. Similarly, being in the information age where huge amounts of information are generated daily from multiple interconnected systems makes it more challenging to absorb this information and make accurate informed decisions. Thus, the need for an automated well-structured approach for decision making is evident. Decision Support Systems (DSS) are interactive software-based systems that play a fundamental role as a technology enabler to provide analytical and visualization capabilities to support decision makers make accurate decisions. In this paper, we present an architecture framework for building a cloud-based distributed DSS to facilitate the decision making process for the planning and design of complex systems. The framework provides a group decision making platform to be utilized by different stakeholders. The framework offers a web portal that leverages a collection of new, open-source technologies and protocols as well as open standards. These are important for interoperable access across technologies, platforms, and mobile devices.

Coding Schemes for Observational Studies of Usability in Collaborative Tangible User Interfaces

With the growing complexity in Tangible User Interfaces (TUIs) and their integration in the decision-making process, user acceptance of these TUI systems continues to be an important issue. Drawing upon recent findings in computer-mediated communication, human computer interaction, computer-supported-cooperative work, and social psychology, the present research extends the coding schemes for observational video analysis by incorporating the variables of communication and collaboration in the context of systems designed for urban planning and modeling.

The Integrated Energy Decision Support System

In this paper we introduce a decision support system framework termed the Integrated Energy Decision Support System IEDSS. IEDSS was developed for energy planning at national and regional levels to inform energy planners at multiple levels of government. IEDSS employs system dynamics modeling to enable the rapid evaluation of the outcomes of different supply and demand policies at the national level. Agent-Based models are used to mimic the interactions between different entities when applying the framework at the regional level of government. Within the IEDSS framework policy makers specify a set of policy decisions and choose from a set of uncertain futures to investigate the performance of their policy decisions. Together these form a scenario for which IEDSS computes a set of output parameters that are used to evaluate the resulting outcome. As a model-driven DSS, IEDSS can be utilized in two ways. The first is as a single-user DSS that deploys a scenario-based planning approach which informs decision makers by mapping the solution space and the resultant effects caused by their policy choices. The second is as a group-based DSS that enhances communication and collaborative decision making between multiple entities. IEDSS is developed on a software platform that utilizes the front-end computation to handle templates, style sheets, and visualizations, while the backend is focused on data retrieval, models execution, and performance optimization. IEDSS was developed to address the power sector of the Kingdom of Saudi Arabia as a case study, but the framework and capabilities of its platform are applicable to any generalized case.