Hybrid systems for analyzing big data integrate an analytic tool and a dedicated data-management platform, storing data and operating on the data at both components. While hybrid systems have benefits over alternative architectures, in order to be effective, data movement between the two hybrid components must be minimized. Extant hybrid systems either fail to address performance problems stemming from inter-component data movement, or else require the user to explicitly reason about and manage data movement. My work presents the design, implementation, and evaluation of a hybrid analytic system for array-structured data that automatically minimizes data movement between the hybrid components. The proposed research first motivates the need for automatic data-movement minimization in hybrid systems, demonstrating that under workloads whose inputs vary in size, shape, and location, automation is the only practical way to reduce data movement. I then present a prototype hybrid system that automatically minimizes data movement. The exposition includes salient contributions to the research area, including a partial semantic mapping between hybrid components, the adaptation of rewrite-based query transformation techniques to minimize data movement in array-modeled hybrid systems, and empirical evaluation of the approach's utility. Experimental results not only illustrate the hybrid system's overall effectiveness in minimizing data movement, but also illuminate contributions made by various elements of the design.

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I takt med att efterfrågan på trådlös kommunikation med hög hastighet ökar och det ökande antalet enheter som är trådlöst anslutna har forskare börjat utforska kompletterande teknologier. Hybridnätverk bestående av LiFi och WiFi är en kombination av Light-Fidelity och Wireless-Fidelity som kombinerar dataöverföring över både radiovågor och ljus. Hybridnätverk med LiFioch WiFi är ett lovande system där hastigheter över 10 Gbps är möjliga och teknikerna inte kan störa ut varandra. Den systematiska litteraturstudie som genomförts syftade till att kartlägga fördelar, nackdelar och utmaningar vid implementationen av dessa hybridnätverk. Sökningar efter litteratur för studien gjordes i fem olika databaser med hjälp av en specifik sökterm, vilket resulterade i 43 accepterade artiklar. En kvalitativ metod, tematisk kodning, användes för att hitta svaren, vilket resulterade i att 20 subteman identifierades spridda över de tre olika huvudteman. Analysen visade att den mest frekvent rapporterade fördelen var prestanda, den vanligaste nackdelen var handover och den mest framträdande utmaningen var load balancing. / With the increasing demand for high-speed wireless communication and the growing numberof devices connected wirelessly, researchers have started exploring complementary technologies. Hybrid LiFi and WiFi networks are a combination of Light-Fidelity and Wireless-Fidelity, which combine data transmission over Radio Frequency and light. Hybrid LiFi and WiFi networks are a promising system that offers speeds above 10 Gbps without interference from one another. The conducted systematic literature review aimed to discover the advantages, disadvantages, and challenges of implementing a hybrid LiFi and WiFi network. The search for literature was conducted in five different databases using one search term, resulting in 43 accepted articles. A qualitative approach using thematic coding was conducted to find the answers, resulting in 20 sub-themes divided over the three main themes. The analysis showed that the most frequently reported advantage was performance, the most common disadvantage was handover, and the most appearing challenge was load balancing.

Indiana University-Purdue University Indianapolis (IUPUI) / Today transportation is one of the rapidly evolving technologies in the world. With the stringent mandatory emission regulations and high fuel prices, researchers and manufacturers are ever increasingly pushed to the frontiers of research in pursuit of alternative propulsion systems. Electrically propelled vehicles are one of the most promising solutions among all the other alternatives, as far as; reliability, availability, feasibility and safety issues are concerned. However, the shortcomings of a fully electric vehicle in fulfilling all performance requirements make the electrification of the conventional engine powered vehicles in the form of a plug-in hybrid electric vehicle (PHEV) the most feasible propulsion systems. The optimal combination of the properly sized components such as internal combustion engine, electric motor, energy storage unit are crucial for the vehicle to meet the performance requirements, improve fuel efficiency, reduce emissions, and cost effectiveness. In this thesis an application of Particle Swarm Optimization (PSO) approach to optimally size the vehicle powertrain components (e.g. engine power, electric motor power, and battery energy capacity) while meeting all the critical performance requirements, such as acceleration, grade and maximum speed is studied. Compared to conventional optimization methods, PSO handles the nonlinear constrained optimization problems more efficiently and precisely. The PHEV powertrain configuration with the determined sizes of the components has been used in a new vehicle model in PSAT (Powertrain System Analysis Toolkit) platform. The simulation results show that with the optimized component sizes of the PHEV vehicle (via PSO), the performance and the fuel efficiency of the vehicle are significantly improved. The optimal solution of the component sizes found in this research increased the performance and the fuel efficiency of the vehicle. Furthermore, after reaching the desired values of the component sizes that meet all the performance requirements, the overall emission of hazardous pollutants from the PHEV powertrain is included in the optimization problem in order to obtain updated PHEV component sizes that would also meet additional design specifications and requirements.

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Purpose: The purpose of this study is to explore how employees apprehend leadership qualities to develop an effective, cohesive and communicative workgroup in the hybrid environment. By using the employee’s perspective, it will help us to elucidate what a successful leader is in the hybrid environment. Method: We have conducted a case study with a qualitative and abductive approach. The empirical data has been collected through semi-structured interviews with eight different employees who work in a company's customer service and works or has worked in a hybridenvironment. Empirical data has also been collected by using the company's internal documents. To examine the collected empirical data, a thematic analysis has been used. Conclusion: This study indicates that the leader of a hybrid workgroup seems to need functional qualities to integrate several areas while the relational ties it together in a different way. One of the studies' conclusions is that employees perceive different components in each area that are important to elaborate efficiency, cohesion and communication in the hybrid environment, and to do this the study shows that different leadership qualities are important. Another conclusion in the study is that the leadership quality to organize will manage the three areas simultaneously and can in theory be seen as the most important to possess for a successful leader in the hybrid environment. The study also empirical indicates that the leadership qualities of being socially competent, responsive, plainness and determined which only handles two areas simultaneously are important for a leader to be considered successfulin a hybrid environment. The conclusion shows that the leader doesn't always have to develop the three areas simultaneously to be perceived as successful.

<p dir="ltr">Engine downsizing with the assistance of turbomachinery and/or energy storage system has been realized to be one of the most promising and cost-effective solutions in pursuit of cleaner and more efficient engine products. Fundamental challenges however, exist in terms of control and energy management of advanced powertrain featuring turbocharged engines due to their complex dynamics, inherent coupling nature, and strict emission regulations concerning environmental preservation. For the purpose of addressing those challenges, this dissertation develops an integrated framework for modeling, robust coordinated control, and power management of advanced powertrains featuring turbocharged engines.</p><p dir="ltr">This dissertation first studies an advanced turbocharged lean-burn SI natural gas engine manufactured by Caterpillar, and develops an intuitive physics-based, control-oriented model. The obtained control-oriented model is validated against a high-fidelity truth-reference model and serves as the basis on which a robust coordinated control system is developed. The dissertation then proposes a comprehensive procedure for synthesizing a robust coordinated control system applying optimization-based H_infinity control theory. Specifically, this framework outlines a methodology of modeling uncertainties to account for system robustness, and providing valuable insights into the tuning of general coordinated control system design. For performance testing, the synthesized robust coordinated control system is implemented on the high-fidelity truth-reference model. A parallel closed-loop simulation strategy is adopted so that direct comparison between the robust coordinated control system and benchmark production control system (composed of multiple fine-tuned PID controllers) developed by Caterpillar can be carried out. Simulation results manage to demonstrate the merit of utilizing the robust coordinated control system, with better performances observed in terms of steady-state tracking, transient response, and disturbance attenuation.</p><p dir="ltr">The second part of this dissertation focuses on the development of a proposed novel hybrid electric wheel loader which features a downsized engine assisted by turbocharger and an energy storage system. Research efforts documented in this dissertation involve system configuration, controller design (both component-level and supervisory-level), simulation development (both software-in-the-loop and hardware-in-the-loop) and simulated validation for the proposed novel wheel loader. Inspired by the successful simulation results, John Deere assembled a real demo vehicle with the proposed powertrain and conducted some in-field testing, from which encouraging experimental results are observed.</p>

No / The Job Shop Scheduling Problem (JSSP) is a hard combinatorial optimisation problem. This paper presents a heuristic-based Genetic Algorithm (GA) or Hybrid Genetic Algorithm (HGA) with the aim of overcoming the GA deficiency of fine tuning of solution around the optimum, and to achieve optimal or near optimal solutions for benchmark JSSP. The paper also presents a detail GA parameter analysis (also called sensitivity analysis) for a wide range of benchmark problems from JSSP. The findings from the sensitivity analysis or best possible parameter combination are then used in the proposed HGA for optimal or near optimal solutions. The experimental results of the HGA for several benchmark problems are encouraging and show that HGA has achieved optimal solutions for more than 90% of the benchmark problems considered in this paper. The presented results will provide a reference for selection of GA parameters for heuristic-based GAs for JSSP.