The goal of this research was to develop stereochemically defined multimetallic systems for use as light absorbers and electron donor / light absorber dyads in photoinitiated electron transfer and electron collection. The basis for the stereochemical control was provided by the symmetric bridging ligands 2,3,5,6-tetra(pyridyl)pyrazine (tpp) and 2,2'-bipyrimidine (bpm). The symmetric bidentate ligand 4N-perylene was designed and the majority of the synthesis was completed. The bimetallic complexes [(tpy)M(tpp)Ru(LLL)]²⁺, where M = Ru or Os and LLL = Cl₃, (CH₃CN)₃, tpp, or (dpq)Cl, and the model monometallic complexes [(tpy)M(tpp)]²⁺, where M = Ru or Os, and [(tpy)Ru(CH₃CN)₃]²⁺ were synthesized and characterized using electrochemistry, UV-vis spectroscopy, and UV-vis spectroelectrochemistry. The bimetallic complexes were investigated as potential light-absorber / electron-donor complexes to be used in larger supramolecular devices for photoinitiated electron collection and electron transfer. The electrochemistry showed that the relative energy of the metal orbitals is suitable for the metal in the (tpy)M(tpp) coordination environment to act as an electron donor. These bimetallic complexes possess extremely complicated UV-vis spectroscopy due to the number of possible transitions. The assignment of the UV-vis spectroscopy and the electrochemistry of these complexes was greatly facilitated by the UV-vis spectroelectrochemistry. The metal-to-metal charge transfer spectra of the mixed-valence species of the bimetallic complexes were obtained using NIR spectroelectrochemistry and indicate a significant degree of metal-metal communication through the bridging tpp. The bimetallic complexes [(tpy)Ru(tpp)Ru(tpy)]⁴⁺, [(tpy)Ru(tpp)Ru(tpp)]⁴⁺ [(tpy)Os(tpp)Ru(tpp)]⁴⁺, and [(tpy)Ru(tpp)Ru(CH₃CN)₃]⁴⁺ were found to have emission lifetimes on the order of 100 ns. The complexes [(bpy)₂Ru(bpm)]²⁺, [(bpy)₂Ru(bpm)Ru(bpy)₂]⁴⁺, [(bpm)₂IrCl₂]⁺, and {[(bpy)₂Ru(bpm)]₂IrCl₂}⁵⁺ were synthesized and characterized using electrochemistry, UV-vis spectroscopy, and UV-vis spectroelectrochemistry. The complex {[(bpy)₂Ru(bpm)]₂IrCl₂}⁵⁺ is a LA-EC-LA device for photoinitiated electron collection. The UV-vis spectroelectrochemistry of these complexes facilitated the assignment of the UV-vis spectroscopy as well as the electrochemistry. The UV-vis spectrum of the electrochemically generated two electron reduced form of {[(bpy)₂Ru(bpm)]₂IrCl₂}⁵⁺ was obtained. This spectrum is critical in the understanding of future studies of the photochemically generated two electron reduced species. The symmetric, planar, bidentate bridging ligand 4N-perylene was designed. This ligand would eliminate some of the isomers associated with multimetallic complexes bridged by unsymmetric bidentate bridging ligands. The large π system of 4N-perylene would likely result in a low energy π* orbital compared to dpp, dpq, or bpm. The ligand 4N-perylene would hold bridged metals at a greater distance than 2,2'-bipyrimidine and should facilitate the formation of multimetallic complexes. The synthesis of 1,8-dichloro-2,7-naphthyridine has been completed. 1,8-dichloro-2,7-naphthyridine is a possible reactant in the homo-coupling reaction of a substituted 2,7-naphthyridine to form 4N-perylene. The stereochemically defined molecular systems developed in this work show great promise for use in larger supramolecular complexes designed for photoinitiated electron transfer and electron collection. / Ph. D.

Utility Accrual (UA) scheduling is a method of dynamic real-time scheduling that is designed to respond to overload conditions by producing a feasible schedule that heuristically maximizes a pre-defined metric of utility. Whereas utility accrual schedulers have traditionally focused on CPU overload, this dissertation explores memory overload conditions during which the aggregate memory demand exceeds a system's available memory bandwidth. Real-time systems are typically implemented in C or other languages that use explicit dynamic memory management. Taking advantage of modern type-safe languages, such as Java, necessitates the use of garbage collection (GC). The timeliness requirements of real-time systems, however, impose specific demands on the garbage collector. Garbage collection introduces a significant source of unpredictability in the execution timeline of a task because it unexpectedly interjects pauses of arbitrary length, at arbitrary points in time, with an arbitrary frequency. To construct a feasible schedule, a real-time scheduler must have the ability to predict the collector's activities and plan for them accordingly. We have devised CADUS (Collector-Aware Dynamic Utility Scheduler), a utility accrual algorithm that tightly links CPU scheduling with the memory requirements -and the corresponding garbage collection activities - of real-time tasks. By constructing and storing memory time allocation profiles, we address the problem of GC activation strategy. We estimate GC latency by using a real-time collector and modeling its behavior. We project GC frequency by planning, at schedule construction time, the memory bandwidth available to the collector. CADUS can point the collector's activities to any specific task in the system. The runtime system provides this ability by maintaining separate logical heaps for all tasks. We demonstrate the viability of CADUS through extensive simulation studies. We evaluated the behavior of CADUS under a wide range of CPU and memory load conditions and utility distributions. We compared its performance against an existing GC-unaware UA scheduler and found that CADUS consistently outperformed its GC-unaware counterpart. We investigated and identified the reasons for the superior performance of CADUS and quantified our results. Most significantly, we found that in an overloaded dynamic soft real-time system, a scheduler's preemption decisions have a highly significant impact on GC latency. A dynamic real-time scheduler therefore must predict the impact of its preemption decisions on GC latency in order to construct time-feasible schedules. / Ph. D.

In this research, an effort is made to analyze the costs of fare collection on heavy rail and motorbus systems in the U.S. Since existing ticketing and fare collection (TFC) systems are major elements of transit infrastructure and there are several new alternative TFC technologies available on the market, the need to evaluate the performance of existing TFC systems arises. However, very little research has been done, so far, to assess impacts of TFC technologies on capital and operating expenses in public transit. The two objectives of this research are: (1) to formulate a conceptual evaluation framework and a plan to assess the operating costs of existing TFC systems in transit and (2) to analyze the operating expenses associated with existing TFC systems on heavy rail and motorbus transit in the U.S. with the aid of the evaluation framework and plan. This research begins with a review of the current state of knowledge in the areas of transit TFC evaluation, the economics of public transit operations, and fare collection practices and technologies. It helps to determine the scope of work related to assessment of TFC operating costs on public transit and provides the basis for the development of a conceptual evaluation framework and an evaluation plan. Next, this research presents a systematic approach to define and describe alternative TFC systems and suggests that the major TFC system determinants are payment media, fare media, TFC equipment, and transit technology (mode). Following this is the development of measures of effectiveness to evaluate alternative TFC systems. These measures assess cost-effectiveness and labor-intensiveness of TFC operations. The development of TFC System Technology Index follows. This Index recognizes the fact that TFC systems may consist of different sets of TFC technologies both traditional and innovative. Finally, this research presents statistical results that support the hypothesis that TFC operating costs are related to transit demand, transit technology (mode) and TFC technologies. These results further suggest that: (1) TFC operating costs per unlinked passenger trip on heavy rail systems are higher than on motorbus systems and (2) TFC operating costs per unlinked passenger trip tend to increase as the use of non-electronic fare media increases. Actions for further research are also recommended. / Ph. D.

The era of modern computing has been the stage for numerous innovations that have led to cutting edge applications and systems. The characteristics of these systems and applications have been described and quantified by many, however such information is fragmented between various repositories of system and component information. In an effort to collate these disparate collections of information we propose iLORE, an extensible data framework for representing computer systems and their components. We describe the iLORE framework and the pipeline used to aggregate, clean, and insert system and component information into a database that uses iLORE's framework. Additionally, we demonstrate how the database can be used to analyze trends in computing by validating the collected data using previous works, and by showcasing new analyses that were created with said data. Analyses and visualizations created via iLORE are available at csgenome.org. / Master of Science / The era of modern computing has been the stage for numerous innovations that have led to cutting edge applications and computer systems. The characteristics of these systems and applications have been described and quantified by many, however such information is fragmented amongst different websites and databases. We propose iLORE, an extensible data framework for representing computer systems and their components. We describe the iLORE framework and the steps taken to create an iLORE database: aggregation, standardization, and insertion. Additionally, we demonstrate how the database can be used to analyze trends in computing by validating the collected data using previous works, and by showcasing new analyses that were created with said data. Analyses and visualizations created via iLORE are available at csgenome.org.

The design of unmanned material collection systems requires a great deal of foresight and innovative design on the engineer's part in order to produce solutions to problems operators may encounter in the field. In this thesis, the development of a particulate collection system for use onboard a lightweight, helicopter deployable ground robot is presented. The Unmanned Systems Laboratory at Virginia Tech is developing a ground sampling robot to be carried in the payload pod of a Yamaha RMAX unmanned aerial vehicle. The robot's ultimate objective is to collect material samples from a hazardous environment. The pneumatic system presented here is a novel design developed to collect particulate without draining the resources of the robot. Vacuum samplers have been developed in the past, but they are large and cumbersome and require large amounts of electrical energy to operate. The pneumatic particulate collection system utilizes the kinetic energy from the release of compressed air to transport the particulate to a collection chamber. Consideration is given to the drop in pressure of the air supply tank as it empties, and a feasible air supply tank design is presented. Two forms of particulate collection are investigated experimentally: jet impingement and particle entrainment (i.e. steep attack angle and parallel flow). Turbulent, free jet characteristics and critical velocities of particles are studied. Ultimately, a final design is presented that effectively collects particulate material from the top 5/8" layer of both thick and thin particle beds. / Master of Science

Nowadays, the apparent promise of Big Data is that of being able to understand in real-time people's behavior in their daily lives. However, as big as these data are, many useful variables describing the person's context (e.g., where she is, with whom she is, what she is doing, and her feelings and emotions) are still unavailable. Therefore, people are, at best, thinly described. A former solution is to collect Big Thick Data via blending techniques, combining sensor data sources with high-quality ethnographic data, to generate a dense representation of the person's context. As attractive as the proposal is, the approach is difficult to integrate into research paradigms dealing with Big Data, given the high cost of data collection, integration, and the expertise needed to manage them. Starting from a quantified approach to Big Thick Data, based on the notion of situational context, this thesis proposes a methodology, to design, collect, and prepare reliable and valid quantified Big Thick Data for the purposes of their reuse. Furthermore, the methodology is supported by a set of services to foster its replicability. The methodology has been applied in 4 case studies involving many domain experts and 10,000+ participants from 10 countries. The diverse applications of the methodology and the reuse of the data for multiple applications demonstrate its inner validity and reliability.

Advanced Traffic Management Systems (ATMS) and Advanced Traveler Information Systems (ATIS) utilize real-time information to apply measures improve the transportation system performance. Two key inputs for ATMS and ATIS are dynamic travel times and dynamic OD matrices. Bluetooth devices detection technology has been increasingly used to track vehicle movements on the network. This possibility naturally raises the question of whether this information can be used to improve the dynamic estimation of OD matrices. Previous research efforts rely entirely on the Bluetooth OD counts for estimation, which is why they require high penetration rates. In our study, we use Bluetooth data to supplement loop detector data while estimating dynamic OD matrices using Kalman filter. We use OD proportions as state variables and travel times, link counts, Bluetooth OD matrix and input and exit volumes as measurements. A simulation experiment is conducted in VISSIM and is designed such that the traffic network emulates the observed traffic patterns. Two case studies are performed for comparison. One uses Bluetooth OD matrices as input for estimation while the other does not. The Bluetooth ODs used in the Kalman filter estimation was found to improve the OD flow estimates. The developed methods were compared with synthetic OD estimation software (QueensOD) and were found to be more effective in obtaining dynamic OD flow estimates. A case of study with fewer detectors was also studied. When it was compared with a similar method developed by Gharat(2011), the errors were lower. / Master of Science

Most current methods used for the estimation of vehicular delay at intersections involve some form of manual data collection. These methods rely on statistical correlation to improve the accuracy of the delay estimates. In addition, most require significant data collection and reduction efforts. This work presents the theory, design, and operation of a microprocessor-based system for the collection of vehicular delay data at intersections. The hardware design is described in detail including schematic diagrams of the microprocessor system and the associated interface circuitry. Documented software listings and flowcharts are provided as well as a description of the data collection and reduction processes. A benefit/cost analysis was made based on the construction and operation of a prototype system. The system performance was evaluated both in the lab and through analysis of data collected in the field. Recommendations for further development of the device are presented as well as applications of the microprocessor to other forms of transportation and traffic engineering data. / M.S.

The traditional block-based interface used in flash-based Solid State Drives (SSDs) imposes limitations on performance and endurance due to write amplification and garbage collection overheads. In response to these challenges, the NVMe Zoned Namespaces (ZNS) devices introduces a novel storage interface organized into zones, optimizing garbage collection and reducing write amplification. This research delves into the exploration and profiling of ZNS device characteristics, aiming to enhance user comprehension and utilization. Additionally, the study investigates the integration of ZNS devices into disaggregated storage frameworks to improve resource utilization, proposing server-side management features to simplify client operations and minimize overhead. By offering insights for future development and optimization of ZNS-based storage solutions, this work contributes to advancing storage technology and addressing the shortcomings of traditional block-based interfaces. Through extensive experimentation and analysis, this study sheds light on the optimal configurations and deployment strategies for ZNS-based storage solutions. / Master of Science / Traditional storage drives, like those found in computers and data centers, face challenges that limit their performance and durability. These challenges stem from the way data is stored and managed within these drives, resulting in inefficiencies known as write amplification and garbage collection overheads. To address these issues, a new type of storage device called NVMe Zoned Namespaces (ZNS) has been developed. ZNS devices organize data in a smarter way, grouping it into specific areas called zones. This organization helps to reduce inefficiencies and improve performance. This research explores the characteristics of ZNS devices and how they can be used more effectively. By better understanding and using these devices, we can improve the way data is stored and accessed, leading to faster and more reliable storage solutions. Additionally, this research looks at how ZNS devices can be integrated into larger storage systems to make better use of available resources. Ultimately, this work contributes to advancing storage technology and overcoming the limitations of traditional storage interfaces. We aim to uncover the best ways to deploy and optimize ZNS-based storage solutions for a variety of applications.

The Drought is a collection of six stories set mostly in South Florida. Each story focuses on a young man or young men as they enter the world. Overall, there are many themes at play across the collection, with the most notable being overcoming anxiety, coming of age, and life as a middle-class millennial. The young men in these stories are being ushered into the real world, and they must learn quickly in order to adapt, and in some cases, survive. The collection also showcases the range of the middle class, and how different a person's story can be when comparing the lower middle to the upper middle. In the title story, "The Drought," a boy with a dying mother must decide if he's going to become a drug kingpin to make the money he needs to care for his little brother. In "What's the Jwett?" three friends decide if they want to get into the local weed trade. In "Turbulence," an up-and-coming DJ learns about the importance of patience and developing one's craft. The Drought is a snapshot of life as a youth in South Florida.