SADDAS, a. Self-contained Analog to Digital Data Acquisition System, converts analog voltage inputs to formatted BCD (binary coded decimal digital magnetic tape. SADDAS consists of a 16 channel multiplexer, a 17 bit (4 digits + sign) 40 microsecond analog to digital converter, a 512 byte 8 bit core memory, a 30 IPS (inches per second) digital tape recorder at a density of 556 cpi (characters per inch), and a controller which integrates these instruments into a flexible and easy-to-use system. Sampling rates in excess of 360 samples per second may be used when converting seven channels of data, such as IRIG (Inter Range Instrumentation Group) analog magnetic tapes.

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The onarm water storage (OFWS) systems at Metcalf and Pitts farm in Porter Bayou Watershed were monitored for changes in nutrient levels and water withdrawal for irrigation from March 2012 to April 2013. Nitrogen and phosphorus levels were generally higher during the early part of the growing season. The OFWS systems can reduce nitrate and phosphorus in runoff up to 81% and 85%, respectively. However, the systems did not consistently reduce sediment and nutrients especially after significant rainfall and runoff events. The systems provided a total of 130 and 233 acreeet of recycled water for irrigating crops at Metcalf and Pitts, respectively, during the 2012 growing season. These amounts reflect significant savings in terms of groundwater. This study highlights the advantages of OFWS systems as structural BMPs to reduce nutrient loading into the Gulf of Mexico and to minimize groundwater withdrawals from the Mississippi Alluvial Aquifer.

Social network data analysis becomes increasingly important today. In order to improve the integration and reuse of their data, many social networks start to apply RDF to present the data. Accordingly, one common approach for social network data analysis is to employ SPARQL to query RDF data. As the sizes of social networks expand rapidly, queries need to be executed in parallel such as using the MapReduce framework. However, the state-of-the-art translation from SPARQL queries to MapReduce jobs mainly follows a two layer rule, in which SPARQL is first translated to SQL join, is not efficient. In this thesis, we introduce two primitives to enable automatic translation from SPARQL to MapReduce, and to enable efficient execution of the SPARQL queries. We use multiple-join-with-filter to substitute traditional SQL multiple join when feasible, and merge different stages in the MapReduce query workflow. The evaluation on social network benchmarks shows that these two primitives can achieve up to 2x speedup in query running time compared with the original two layer scheme.

Sig sigma is a methodology where companies strive to reproduce results ending up having a 99.9996% chance their product will be void of defects. In order for companies to reach six sigma, statistical process control (SPC) needs to be introduced. SPC has many different tools associated with it, control charts being one of them. Control charts play a vital role in managing how a process is behaving. Control charts allow users to identify special causes, or shifts, and can therefore change the process to keep producing good products, free of defects. There are many factories and manufacturing facilities having implemented some sort of statistical process control. St. Jude Medical implemented control charts to monitor different tools on the manufacturing line. How the data is entered and stored poses a difficult situation for the person monitoring the processes. The program used to keep the control charts is not user friendly and difficult to use. Another program can be produced to provide a greater level of efficiency. The goals of this project are to stress how important control charts are in the manufacturing world, what problems are currently seen for operators and supervisors, and how a new and improved program can help fix the current situation. This paper goes into the reasons for the change as well has what has been improved.

Main memory remains a scarce computing resource. Even though main memory is becoming more abundant, software applications are inexorably engineered to consume as much memory as is available. For example, expert systems, scientific computing, data mining, and embedded systems commonly suffer from the lack of main memory availability. This thesis introduces JDiet, an innovative memory management system for Java applications. The goal of JDiet is to provide the developer with a highly configurable framework to reduce the memory footprint of a memory-constrained system, enabling it to operate on much larger working sets. Inspired by buffer management techniques common in modern database management systems, JDiet frees main memory by evicting non-essential data to a disk-based store. A buffer retains a fixed amount of managed objects in main memory. As non-resident objects are accessed, they are swapped from the store to the buffer using an extensible replacement policy. While the Java virtual machine naïvely delegates virtual memory management to the operating system, JDiet empowers the system designer to select both the managed data and replacement policy. Guided by compile-time configuration, JDiet performs aspect-oriented bytecode engineering, requiring no explicit coupling to the source or compiled code. The results of an experimental evaluation of the effectiveness of JDiet are reported. A JDiet-enabled XML DOM parser is capable of parsing and processing over 200% larger input documents by sacrificing less than an order of magnitude in performance.

Amaethon is a web application that is designed for enterprise farm management. It takes a job typically performed with spreadsheets, paper, or custom software and puts it on the web. Farm administration personnel may use it to schedule farm operations and manage their resources and equipment. A survey was con- ducted to assess Amaethon’s user interface design. Participants in the survey were two groups of students and a small group of agriculture professionals. Among other results, the survey indicated that a calendar interface inside Amaethon was preferred, and statistically no less effective, than a map interface. This is despite the fact that a map interface was viewed by some users as a potentially important and effective component of Amaethon.

Contemporary small office phone systems are specialized computers that connect a variety of phones within the office and to the local phone company. These systems use digital signaling processors (DSPs) to convert signals from analog to digital and vice-versa. Many different types of applications run on the DSPs and different businesses have varying application needs. Given the systems have limited amounts of DSP resources and growing numbers of applications for a phone system, an administrator needs a way to configure the uses of resources based on their individual business needs. This thesis provides an overview of a system for configuring resources on various types of DSP hardware some of which are removable and have differing tradeoffs between application uses. The system has to be able to change resource allocations while the phone system is running with minimal interruptions to calls. The configuration system needs to be designed to be flexible enough that new applications or DSP hardware could be supported without major changes to code. This thesis presents a system that uses a database-driven model along with algorithms that optimize configuration of DSP hardware given the administrator’s individual application needs.

This thesis report provides a comprehensive analysis of the regulatory landscape governing Battery Energy Storage Systems (BESS) in Spain and offers insights into their operational optimization and economic viability. The study centers on a 40 MW BESS and explores three distinct case studies, each representing varying system durations (one, two, and four hours) and two different electricity price scenarios (2019 and 2022). A techno-economic analysis encompassing all scenarios concludes the investigation. The research findings reveal that BESS projects can be financially lucrative when operating under the 2022 scenario, particularly when participating in Spain's Wholesale and Secondary Regulation service (aFRR) markets. Notably, as the system duration increases, project profitability also rises, with Net Present Values (NPVs) amounting to 29.6 M€, 50.4 M€, and 80.6 M€ for one-hour, two-hour, and four-hour BESS durations, respectively. However, this trend is not consistent, as observed in the 2019 scenario, where the opposite holds true due to significantly lower prices in both Wholesale and Secondary Regulation service markets, resulting in negative NPVs that increase with longer BESS durations (specifically, -3.3 M€, -6.9 M€, and -17.7 M€ for one-hour, two-hour, and four-hour BESS durations, respectively). In terms of optimal dispatching strategy, the study identifies consistent patterns across all case studies and scenarios. The BESS prioritizes participation in the Secondary Regulation service due to its higher remuneration compared to arbitrage activities in the Wholesale market. Despite Spain's efforts to promote the adoption of BESS technologies, several barriers exist that could impede their deployment. Key challenges include the absence of Capacity Markets (CM), restrictions on BESS participation in technical constraints and black-start markets, and the lack of remunerated markets for Frequency Control Reserve (FCR) and voltage control. In summary, this study highlights the need for a more investor-friendly environment characterized by greater revenue stream certainty and streamlined administrative processes. / Denna avhandling ger en omfattande analys av den reglerande landskapskontexten som styr batterilagringssystem (BESS) i Spanien och ger insikter om deras drifts- och ekonomiska livskraft. Studien fokuserar på en 40 MW BESS och utforskar tre olika fallstudier, var och en representerar varierande systemtider (en, två och fyra timmar) och två olika elprisscenarier (2019 och 2022). En teknisk-ekonomisk analys som omfattar alla scenarier avslutar undersökningen. Forskningsresultaten visar att BESS-projekt kan vara ekonomiskt lönsamma när de verkar enligt 2022-scenariot, särskilt när de deltar i Spaniens grossist- och sekundärregleringstjänst (aFRR) marknader. Inte minst ökar lönsamheten i projektet när systemtiden förlängs, med nuvärdet (NPV) uppgår till 29,6 M€, 50,4 M€ och 80,6 M€ för BESS-varaktigheter på en timme, två timmar respektive fyra timmar. Denna trend är dock inte konsekvent, som observerats i 2019-scenariot, där motsatsen gäller på grund av betydligt lägre priser både på grossist- och sekundärregleringsmarknaderna, vilket resulterar i negativa NPV-värden som ökar med längre BESS-varaktigheter (specifikt -3,3 M€, -6,9 M€ och -17,7 M€ för BESS-varaktigheter på en timme, två timmar respektive fyra timmar). När det gäller optimal distributionsstrategi identifierar studien liknande mönster i alla fallstudier och scenarier. BESS prioriterar deltagande i sekundärregleringstjänsten på grund av dess högre ersättning jämfört med arbitrageaktiviteter på grossistmarknaden. Trots Spaniens ansträngningar att främja antagandet av BESS-teknologier finns det flera hinder som kan hämma deras utrullning. Viktiga utmaningar inkluderar frånvaron av kapacitetsmarknader (CM), begränsningar för BESS-deltagande i tekniska begränsningar och svartstartmarknader, samt avsaknaden av marknader med ersättning för frekvensreglering (FCR) och spänningsreglering. Sammanfattningsvis belyser denna studie behovet av en mer investerarvänlig miljö präglad av större säkerhet i intäktsströmmar och förenklade administrativa processer.

Collaboration has become a key feature of modern software, allowing teams to work together effectively in real-time while in different locations. In order for a user to communicate their intention to several distributed peers, computing devices must exchange high-frequency updates with transient metadata like mouse position, text range highlights, and temporary comments. Current peer-to-peer awareness solutions have high time and space complexity due to the ever-expanding logs that each client must maintain in order to ensure robust collaboration in eventually consistent environments. This paper proposes an awareness Conflict-Free Replicated Data Type (CRDT) library that provides the tooling to support an eventually consistent, decentralized, and robust multi-user collaborative environment. Our library is tuned for rapid iterative updates that communicate fine-grained user actions across a network of collaborators. Our approach holds memory constant for subsequent writes to an existing key on a shared resource and completely prunes stale data from shared documents. These features allow us to keep the CRDT's memory footprint small, making it a feasible solution for memory constrained applications. Results show that our CRDT implementation is comparable to or exceeds the performance of similar data structures in high-frequency read/write scenarios.