Current and emerging large-scale networks, for example the current Internet and the future Internet of Things, target supporting billions of networked entities to provide a wide variety of services and resources. Such complexity results in network-data from different sources with special characteristics, such as widely diverse users and services, multiple media (e.g., text, audio, video, etc.), high-dimensionality (i.e., large sets of attributes) and various dynamic concerns (e.g., time-sensitive data). With huge amounts of network data with such characteristics, there are significant challenges to a) recognize emergent and anomalous behavior in network traffic and b) make intelligent decisions for efficient and effective network operations. Fortunately, numerous analyses of Internet traffic have demonstrated that network traffic data exhibit multi-dimensional patterns that can be learned in order to enable discovery of data semantics. We claim that extracting and managing network semantics from traffic patterns and building conceptual models to be accessed on-demand would help in mitigating the aforementioned challenges. The current Internet, contemporary networking architectures and current tools for managing large network-data largely lack capabilities to 1) represent, manage and utilize the wealth of multi-dimensional traffic data patterns; 2) extract network semantics to support Internet intelligence through efficiently building conceptual models of Internet entities at different levels of granularity; and 3) predict future events (e.g., attacks) and behaviors (e.g., QoS of unfamiliar services) based on learned semantics. We depict the limited utilization of traffic semantics in networking operations as the “Internet Semantics Gap (ISG)”. We hypothesize that endowing the Internet and next generation networks with a “memory” system that provides data and semantics management would help resolve the ISG and enable “Internet Intelligence”. We seek to enable networked entities, at runtime and on-demand, to systematically: 1) learn and retrieve network semantics at different levels of granularity related to various Internet elements (e.g., services, protocols, resources, etc.); and 2) utilize extracted semantics to improve network operations and services in various aspects ranging from performance, to quality of service, to security and resilience. In this dissertation, we propose a distributed network memory management system, termed NetMem, for Internet intelligence. NetMem design is inspired by the functionalities of human memory to efficiently store Internet data and extract and utilize traffic data semantics in matching and prediction processes, and building dynamic network-concept ontology (DNCO) at different levels of granularity. The DNCO provides dynamic behavior models for various Internet elements. Analogous to human memory functionalities, NetMem has a memory system structure comprising short-term memory (StM) and long-term memory (LtM). StM maintains highly dynamic network data or data semantics with lower levels of abstraction for short time, while LtM keeps for long time slower varying semantics with higher levels of abstraction. Maintained data in NetMem can be accessed and learned at runtime and on-demand. From a system’s perspective, NetMem can be viewed as an overlay network of distributed “memory” agents, called NMemAgents, located at multiple levels targeting different levels of data abstraction and scalable operation. Our main contributions are as follows: • Biologically-inspired customizable application-agnostic distributed network memory management system with efficient processes for extracting and classifying high-level features and reasoning about rich semantics in order to resolve the ISG and target Internet intelligence. • Systematic methodology using monolithic and hybrid intelligence techniques for efficiently managing data semantics and building runtime-accessible dynamic ontology of correlated concept classes related to various Internet elements and at different levels of abstraction and granularity that would facilitate: ▪ Predicting future events and learning about new services; ▪ Recognizing and detecting of normal/abnormal and dynamic/emergent behavior of various Internet elements; ▪ Satisfying QoS requirements with better utilization of resources. We have evaluated the NetMem’s efficiency and effectiveness employing different semantics reasoning algorithms. We have evaluated NetMem operations over real Internet traffic data with and without using data dimensionality reduction techniques. We have demonstrated the scalability and efficiency of NetMem as a distributed multi-agent system using an analytical model. The effectiveness of NetMem has been evaluated through simulation using real offline data sets and also via the implementation of a small practical test-bed. Our results show the success of NetMem in learning and using data semantics for anomaly detection and enhancement of QoS satisfaction of running services. / Ph. D.

Stigmergy refers to indirect communication that was originally found in biological systems. It is used for self-organization by ants, bees, and flocks of birds, by allowing individuals to focus on local information. Through local communication among individuals, larger patterns are formed without centralized communication. This self-organization is just one type of system studied within complex systems. Systems of ants, bees, and flocks of birds are considered complex because they exhibit emergent behavior: the outcome is more than the sum of the individual parts. Emergent behavior can be found in many other systems as well. One example is the Internet, which is a series of computers organized in a self-organized fashion. Complexity can also be defined through properties other than emergent behavior, such as existing on multiple scales. Many biological systems are multi-scale. For instance, cancer exists on many scales, including the sub-cellular and cellular levels. Many computing systems are also multi-scale, as there may be both individual and system-wide controls interacting together to determine the output. Many multi-agent systems would fall into this category, as would many large software systems. In this dissertation I examine complex systems in artificial intelligence and biology: the growth of cancer, population dynamics, emotions, multi-agent fault tolerance, and real-time strategic AI for games. My goal is twofold: a) to develop novel computational models of complex biological systems, and b) to tackle key AI research questions by proposing new algorithms and techniques that are inspired by those complex biological systems. In all of these cases I design variations on stigmergic communication to accomplish the task at hand. My contributions are a new agent-based cancer growth model, a proposed use of location communication for removing cancer, improved multi-agent fault tolerance through localized messaging, a new approach to modeling predator-prey dynamics using computational emotions, and improved strategic game AI through computational emotions.

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Thermal systems involve multiple components assembled to store or transfer heat for power, cooling, or insulation purpose, and this research focuses on modeling the performance of two novel thermal systems that are capable of functioning in environments subjected to high heat fluxes. The first investigated thermal system is a cascaded thermoelectric generator (TEG) that directly converts heat into electricity and offers a green option for renewable energy generation. The presented cascaded TEG allows harvesting energy in high temperatures ranging from 473K to 973K, and being a solid-state device with no moving parts constitutes an excellent feature for increase device life cycle and minimum maintenance in harsh, remote environments. Two cascaded TEG designs are analyzed in this research: the two-stage and three-stage cascaded TEGs, and based on the findings, the two-stage cascaded TEG produces a power output of 42 W with an efficiency of 8.3% while the three-cascaded TEG produces 51 W with an efficiency of 10.2%. The second investigated novel thermal system is a thermal protection system inspired by the porous internal skeleton of the cuttlefish also known as cuttlebone. The presented bio- inspired thermal protection has excellent features to serve as an integrated thermal protection system for spacecraft vehicles including being lightweight (93% porosity) and possessing high compressive strength. A large amount of heat flux is generated from friction between air and spacecraft vehicle exterior, especially during reentry into the atmosphere, and part of the herein presented research involves a thermomechanical modeling analysis of the cuttlebone bio-inspired integrated thermal protection system along with comparing its performance with three conventional structures such as the wavy, the pyramid, and cylindrical pin structures. The results suggest that the cuttlebone integrated thermal protection system excels the best at resisting deformation caused by thermal expansion when subjected to aerodynamic heat fluxes. / Doctor of Philosophy / Operating engineering systems in extremely hot environments often decreases systems' reliability, life cycle, and creates premature failure. This research investigates two novel thermal systems capable of functioning in high temperatures including a cascaded thermoelectric generator (TEG) and a bio-inspired thermal protection system. The first evaluated novel thermal systems is a cascaded TEG that directly converts waste heat into power, and being a solid-state device with no moving parts forms an excellent feature for device life cycle improvement and minimum maintenance in harsh, remote environments. The research findings show that the designed cascaded TEGs can produce power when subjected to high temperatures ranging from 473K to 973K. The remaining part of the research presented in this dissertation models the thermomechanical performance of a lightweight structure, which is inspired by the internal skeleton of the cuttlefish, also knows as the cuttlebone. The cuttlefish's natural ability to support high-deep sea pressure translates into possessing high compressive strength, and when added the fact of being lightweight (up to 93% porosity), the cuttlebone forms an excellent candidate to serve as integrated thermal protection for spacecraft vehicles. The last part of the presented research discuss the thermomechanical analysis of the cuttlebone when subjected to high aerodynamics heat flux generated from friction between the air and spacecraft vehicle exterior, and it was found that the cuttlebone structure resists deformation associated with the steep temperature gradient experienced by the spacecraft vehicle during travel.

Modern parallel computing techniques are subject to poor scalability. Their performance tends to suffer diminishing returns and even losses with increasing parallelism. Some methods of intelligent computing, such as neural networks and genetic algorithms, lend themselves well to massively parallel systems but come with other drawbacks that can limit their usefulness such as the requirement of a training phase and/or sensitivity to randomness. This thesis investigates the feasibility of a novel method of intelligent parallel computing by implementing a true multiple instruction stream, single data stream (MISD) computing system that is theoretically nearly perfectly scalable. Computational dreaming (CD) is inspired by the structure and dreaming process of the human brain. It examines previously observed input data during a 'dream phase' and is able to develop and select a simplified model to use during the day phase of computation. Using mazes as an example problem space, a CD simulator is developed and successfully used to demonstrate the viability and robustness of CD. Experiments that focused on CD viability resulted in the CD system solving 15% of mazes (ranging from small and simple to large and complex) compared with 2.2% solved by random model selection. Results also showed that approximately 50% of successful solutions generated match up with those that would be generated by algorithms such as depth first search and Dijkstra's algorithm. Experiments focusing on robustness performed repeated trials with identical parameters. Results demonstrated that CD is capable of achieving this result consistently, solving over 32% of mazes across 10 trials compared to only 3.6% solved by random model selection. A significant finding is that CD does not get stuck on local minima, always converging on a solution model. Thus, CD has the potential to enable significant contributions to computing by potentially finding elegant solutions to, for example, NP-hard or previously intractable problems. / Master of Science

The wings of most species of owl have been shown to possess three unique physical attributes which allow them to hunt in effective silence: a comb of evenly-spaced bristles along the wing leading-edge; a compliant and porous fringe of feathers at the trailing-edge; and a velvety down material distributed over the upper wing surface. This investigation focuses on the last of the mechanisms as a means to reduce noise from flow over surface roughness. A microscopic study of several owl feathers revealed the structure of the velvety down to be very similar to that of a forest or a field of crops. Analogous surface treatments (suspended canopies) were designed which simulated the most essential geometric features of the velvety down material. The Virginia Tech Anechoic Wall-Jet Facility was used to perform far-field noise and surface pressure fluctuation measurements in the presence of various combinations of rough surfaces and suspended canopies. All canopies were demonstrated to have a strong influence on the surface pressure spectra, and attenuations of up to 30 dB were observed. In addition, all canopies were shown to have some positive effects on far-field noise, and optimized canopies yielded far-field noise reductions of up to 8 dB across all frequencies at which roughness noise was observed. This development represents a new passive method for roughness noise control with possibility for future optimization and application to engineering structures. / Master of Science

No / In this paper, low profile planar Metamaterial-Inspired coplanar fed waveguide antenna is presented for WLAN and Ultra-Wideband applications. The antenna is based on a simple strip loaded to a rectangular patch and zigzag E-shape metamaterial-inspired unit cell. The idea behind the proposed antenna is to enable miniaturization effect. The proposed antenna can provide dual band operation, the first one is a Wi-Fi band at 2.45 GHz having impedance bandwidth of 150MHz, the second one is an ultra wide band extended from 4.2 GHz to 6.5 GHz. Two antennas are designed and fabricated with and without metamaterial-inspired loading. The simulated and measured results regarding Return loss (S11), Gain and Radiation pattern are discussed.

Yes / Millimetre-wave frequencies are promising for sensitive detection of glucose levels in the blood, where the temperature effect is insignificant. All these features provide the feasibility of continuous, portable, and accurate monitoring of glucose levels. This paper presents a metamaterial-inspired resonator comprising five split-rings to detect glucose levels at 24.9 GHz. The plexiglass case containing blood is modelled on the sensor's surface and the structure is simulated for the glucose levels in blood from 50 mg/dl to 120 mg/dl. The novelty of the sensor is demonstrated by the capability to sense the normal glucose levels at millimetre-wave frequencies. The dielectric characteristics of the blood are modelled by using the Debye parameters. The proposed design can detect small changes in the dielectric properties of blood caused by varying glucose levels. The variation in the transmission coefficient for each glucose level tested in this study is determined by the quality factor and resonant frequency. The sensor presented can detect the change in the quality factor of transmission response up to 2.71/mg/dl. The sensor's performance has also been tested to detect diabetic hyperosmolar syndrome. The sensor showed a linear shift in resonant frequency with the change in glucose levels, and an R2 of 0.9976 was obtained by applying regression analysis. Thus, the sensor can be used to monitor glucose in a normal range as well as at extreme levels. / This study is funded by Ministry of Higher Education (MoHE) Malaysia under Fundamental Research Grant Scheme Vot No. FRGS/1/2019/TK04/UTHM/02/13, and it is partially sponsored by Universiti Tun Hussein Onn Malaysia (UTHM).

The purpose of this thesis is to explore the performance of a bio-inspired plate undergoing oscillatory heave motions and active shape change. The shape change will be achieved using a panel embedded with Fluidic Flexible Matrix Composite (F2MC) tubes for actuation. A beam, or plate strip, model is presented as a means of verifying that F2MC tubes can effectively serve as a means of actuation. This model was actuated in air and water at several internal tube pressures. The static experimental deflections were compared to two beam models relying on Euler-Bernoulli and Timoshenko beam theories with concentrated tip moments and a distributed moment. It was found that the Euler-Bernoulli model with a concentrated tip moment best approximated the static experimental deflections. Following the success of the plate strip, and panel with 10 embedded F2MC tubes was manufactured. The plate panel was constructed with Dragon Skin Silicone and embedded with two rows of five F2MC tubes which provide the means of shape actuation. Experimental results from actuating the panel in static conditions showed that F2MC tubes are an effective means of prescribing a repeatable shape change to a silicone panel. Then, Classical Plate Theory and First-Order Shear Deformation Plate Theory were used with a concentrated tip moment at the free edge to provide a means of modeling the full panel. When comparing the static experimental results to the numerical models, it was found that the deflected plate shape could be most accurately predicted at lower pressures for upward deflection and higher pressures for downward deflections. When tested in unsteady conditions in a heaving experiment (0.5 Hz to 2.3 Hz), the force measured at frequencies above 1.5 Hz were up to 3.6 times greater than those measured for frequencies below 1.5 Hz. Additionally, the phase difference between the tip deflection and force with respect to the keel position decreased for force as frequency increased, while the opposite was true for the tip deflection. At 1.5 Hz, the tip deflection and force were equally out of phase with the keel. When the panel was subjected to an oscillatory heaving motion while asymmetrically actuated, it was found that faster heaving frequencies resulted in higher maximum force values for all actuation pressures, actuation directions, and depths below the free surface. However, when subjected to dual actuation by pressurizing the top and bottom tubes at the same pressure, the tip amplitude was highly dependent on specific combinations of heaving frequency, actuation pressure, and depth below the free surface. This indicates that the actuation pressure must be tuned to the depth and frequency of operation to obtain the desired tip amplitude for a given application. These findings further the knowledge of shape-changing F2MC panels operating near a free surface and lay a groundwork for developing flapping propulsors that mimic marine animals. / Master of Science / The purpose of this thesis is to explore the performance of a bio-inspired plate undergoing oscillatory (up and down) heave motions and active shape change. The active shape change is achieved using Fluidic Flexible Matrix Composite (F2MC) tubes, which act as an artificial muscles to deflect the panel. To verify that F2MC tubes are capable of prescribing a repeatable deflection, a simple beam model with two embedded tubes was manufactured and tested statically in air and water. It was found that the F2MC tubes were able to prescribe a repeatable deflection, and when comparing to two beam models, Euler-Bernoulli and Timoshenko, it was found that the Euler Bernoulli model with a concentrated tip moment best approximated the static experimental deflections. Following the success of the beam model with 2 embedded tubes, a panel was made with 10 embedded F2MC tubes, 5 along the bottom and 5 along the top, was created. This panel was tested statically and dynamically. Static results showed strong deflection repeatability. When subjected to heaving motions, it was found that the force in the system increased with increasing heaving frequency. The phase difference measured between the tip deflection and force with respect to the keel position decreased for force as frequency increased, while the opposite was true for the tip deflection. It was also observed that there exists a point where the tip deflection and force were equally out of phase with the keel. When the panel was subjected to dual actuation by pressurizing the top and bottom tubes at the same pressure, the tip amplitude was highly dependent on specific combinations of heaving frequency, actuation pressure, and depth below the free surface. This indicates that the actuation pressure must be tuned to the depth and frequency of operation to obtain the desired tip amplitude for a given application. These findings further the knowledge of shape-changing F2MC panels operating near a free surface and lay a groundwork for developing flapping propulsors that mimic marine animals.