In the context of emerging non-volatile memory (NVM) where data structures can persist in-memory and are accessed through CPU loads and stores, we study how to efficiently manage data evolution. This is an extensively applied problem in both the scientific and business domains and is rapidly becoming an important component for a wider range of applications. We argue that the best way to achieve a smoother transition to the new programming model is to design a solution that is non-intrusive and generic i.e. not bound to a specific data model. We propose a novel library-level approach where the user can manage historical data directly from programming language code. This is achieved with a combination of two software layers: REWIND and VARIANT. At the bottom, lies REWIND (REcovery Write-Ahead System for In- Memory Non-Volatile Data Structures) which handles the low level specifics of NVM by dealing with write-ordering problems that arise in such context and allows recoverability of arbitrary data structures. Then, VARIANT (Versioning ARbItrary dAta structures in Non-volatile memory for Time-travel) focuses on versioning and time travel (moving between versions). We adopt a logging approach and we tightly integrate both systems for best performance by utilizing a common physical log of memory operations. With REWIND, we propose a novel recoverable log structure that permits atomic and durable appends and removals of log records. This is the keystone for building recoverable systems on top of NVM. Because latencies in recent NVM technologies such as Phase-change memory (PCM) are asymmetric, we propose novel techniques for reducing the write pressure of the recoverable log as well as mitigating the effect of synchronization control primitives such as memory fences (enhanced for NVM), i.e. barriers that enforce ordering and persistence to preceding instructions. We also propose different implementations for trading logging performance for rollback performance when this is appropriate. Finally, we revisit state-of-the-art recovery algorithms for the new context given the different latencies and synchronization control. Our results clearly indicate that current approaches for recoverability are ill-fitted for persisting data structures in the new context and it is possible to achieve low-overhead logging with customized mechanisms. Next, we focus on data evolution. We expose a simple API that allows versioning and time travel with minimal intrusiveness. We propose mechanisms for efficient and transparent cloning of Versionable data structures. This allows high concurrency since past images are returned as copies of the original data structure which remains intact. Then, we propose novel indexing techniques that significantly improve time travel performance as well as cloning with lazy schemes. We achieve a low overhead architecture by employing a mix of volatile and non-volatile data structures as well as hybrid structures that reside in both volatile and non-volatile memories. We perform an extensive evaluation of the proposed techniques and conclude that, in our context, by carefully mitigating the drawbacks of physical logging it is possible to create efficient systems for managing data evolution that are both data structure agnostic and non-intrusive.

京都大学 / 0048 / 新制・課程博士 / 博士(エネルギー科学) / 甲第22794号 / エネ博第408号 / 新制||エネ||78(附属図書館) / 京都大学大学院エネルギー科学研究科エネルギー社会・環境科学専攻 / (主査)教授 石原 慶一, 准教授 奥村 英之, 教授 佐川 尚 / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DFAM

Diploma thesis evaluates the influence of the thermal insulation of municipal buildings and expenses associated with the running of these properties. First is analyzed the issue of energy demands of buildings then the possibilities of reducing heat loss and possible material variants . Using the method of building insulation ETICS is analyzed in detail. Thermal insulation is designed in several versions for each building . The thesis includes thermal assessment of the original state of the building and subsequently heat- assessment after each variant insulation. The conclusion evaluates the payback period of each variant.

In this dissertation research, we design and analyze resilient cyber-physical systems (CPSs) under high network dynamics, adversarial attacks, and various uncertainties. We focus on three key system attributes to build resilient CPSs by developing a suite of the autonomous cyber defense mechanisms. First, we consider network adaptability to achieve the resilience of a CPS. Network adaptability represents the network ability to maintain its security and connectivity level when faced with incoming attacks. We address this by network topology adaptation. Network topology adaptation can contribute to quickly identifying and updating the network topology to confuse attacks by changing attack paths. We leverage deep reinforcement learning (DRL) to develop CPSs using network topology adaptation. Second, we consider the fault-tolerance of a CPS as another attribute to ensure system resilience. We aim to build a resilient CPS under severe resource constraints, adversarial attacks, and various uncertainties. We chose a solar sensor-based smart farm as one example of the CPS applications and develop a resource-aware monitoring system for the smart farms. We leverage DRL and uncertainty quantification using a belief theory, called Subjective Logic, to optimize critical tradeoffs between system performance and security under the contested CPS environments. Lastly, we study system resilience in terms of system recoverability. The system recoverability refers to the system's ability to recover from performance degradation or failure. In this task, we mainly focus on developing an automated intrusion response system (IRS) for CPSs. We aim to design the IRS with effective and efficient responses by reducing a false alarm rate and defense cost, respectively. Specifically, We build a lightweight IRS for an in-vehicle controller area network (CAN) bus system operating with DRL-based autonomous driving. / Doctor of Philosophy / In this dissertation research, we design and analyze resilient cyber-physical systems (CPSs) under high network dynamics, adversarial attacks, and various uncertainties. We focus on three key system attributes to build resilient CPSs by developing a suite of the autonomous cyber defense mechanisms. First, we consider network adaptability to achieve the resilience of a CPS. Network adaptability represents the network ability to maintain its security and connectivity level when faced with incoming attacks. We address this by network topology adaptation. Network topology adaptation can contribute to quickly identifying and updating the network topology to confuse attacks by changing attack paths. We leverage deep reinforcement learning (DRL) to develop CPSs using network topology adaptation. Second, we consider the fault-tolerance of a CPS as another attribute to ensure system resilience. We aim to build a resilient CPS under severe resource constraints, adversarial attacks, and various uncertainties. We chose a solar sensor-based smart farm as one example of the CPS applications and develop a resource-aware monitoring system for the smart farms. We leverage DRL and uncertainty quantification using a belief theory, called Subjective Logic, to optimize critical tradeoffs between system performance and security under the contested CPS environments. Lastly, we study system resilience in terms of system recoverability. The system recoverability refers to the system's ability to recover from performance degradation or failure. In this task, we mainly focus on developing an automated intrusion response system (IRS) for CPSs. We aim to design the IRS with effective and efficient responses by reducing a false alarm rate and defense cost, respectively. Specifically, We build a lightweight IRS for an in-vehicle controller area network (CAN) bus system operating with DRL-based autonomous driving.

Любое железорудное сырье представляет собой минеральную композицию железосодержащих фаз, состав, микроструктура и физико-механические свойства которой зависят от химического и фазового состава исходной шихты. Повышение качественных характеристик железорудных материалов является одним из наиболее эффективных способов улучшения технико-экономических показателей доменного процесса. Качество готовой продукции зависит от целого ряда технологических параметров, одним из которых является горячая прочность железорудного сырья. Сырье должно обладать высокой горячей прочностью и выдерживать без разрушения ряд фазовых превращений при восстановлении в доменной печи вплоть до отделения шлака от металла. Помимо этого, сырье должно обладать хорошей восстановимостью, то есть способностью легко отдавать кислород, связанный в оксиды газообразному восстановителю. Химический состав железорудного сырья оказывает существенное влияние на его восстановимость и горячую прочность. Поэтому управление химическим составом позволит подобрать оптимальный состав сырья для наилучших показателей плавки. Исследования горячей прочности сырья важны для существующего доменного процесса, так как образование мелочи во время восстановления негативно сказывается на газопроницаемости столба шихтовых материалов; более высокая восстановимость способствует сокращению времени пребывания железорудного сырья в доменной печи и росту доли косвенного восстановления окислов железа, что приведёт к снижению удельного расхода кокса; исследования в области восстановимости железорудного сырья способствуют развитию новых технологий и инноваций в металлургической отрасли, может привести к разработке новых методов восстановления и использования рудного сырья. / Any iron ore raw material is a mineral composition of iron-containing phases, the composition, microstructure and physico-mechanical properties of which depend on the chemical and phase composition of the initial charge. Improving the quality characteristics of iron ore materials is one of the most effective ways to improve the technical and economic performance of the blast furnace process. The quality of the finished product depends on a number of technological parameters, one of which is the hot strength of iron ore raw materials. The raw material must have high hot strength and withstand without destruction a number of phase transformations during reduction in a blast furnace up to the separation of slag from metal. In addition, the raw material must have good reducibility, that is, the ability to easily transfer oxygen bound into oxides to a gaseous reducing agent. The chemical composition of iron ore raw materials has a significant effect on its reducibility and hot strength. Therefore, chemical composition management will allow you to select the optimal composition of raw materials for the best melting performance. Studies of the hot strength of raw materials are important for the existing blast furnace process, since the formation of fines during recovery negatively affects the gas permeability of the column of charge materials; higher recoverability reduces the residence time of iron ore raw materials in the blast furnace and an increase in the proportion of indirect reduction of iron oxides, which will lead to a decrease in the specific consumption of coke; research in the field of recoverability of iron ore raw materials contributes to the development of new technologies and innovations in the metallurgical industry may lead to the development of new methods for the recovery and use of ore raw materials.

Multidatabases are being actively researched as a relatively new area in which many aspects are not yet fully understood. This area of transaction management in multidatabase systems still has many unresolved problems. The problem areas which this dissertation addresses are classification of multidatabase systems, global concurrency control, correctness criterion in a multidatabase environment, global deadlock detection, atomic commitment and crash recovery. A core group of research addressing these problems was identified and studied. The dissertation contributes to the multidatabase transaction management topic by introducing an alternative classification method for such multiple database systems; assessing existing research into transaction management schemes and based on this assessment, proposes a transaction processing model founded on the optimal properties of transaction management identified during the course of this research. / Computing / M. Sc. (Computer Science)

Thesis (MFor)--Stellenbosch University, 2011. / ENGLISH ABSTRACT: This study is aimed at testing the possibility of using woody biomass from three invasive woody vegetation types (Spider Gum, Myrtle and Acacia) for production of bioenergy in the Cape Agulhas Plain. Physical recoverability of the woody biomass was studied by means of a semi-mechanized harvesting system to evaluate potential productivity, operational costs and the estimated yield energy gain. The system consisted of five components: manual harvesting, motor-manual harvesting, extraction, chipping and road transport. Data on the system productivity was obtained using activity sampling and time study techniques. Activity sampling was applied on manual and motor-manual harvesting in order to record harvesting time and standard time study techniques were used to obtain time data for extraction, chipping and road transport operations. Findings revealed benefits associated with the utilisation of invasive woody vegetation as energy feedstock. Therefore, the problem of exotic tree species can be dealt with by transforming them into energy feedstock, thus minimising the effect of invasive plants. At the same time essential biomass energy can be produced, while some of the cost of production could be offset by the benefits accruing from the biomass energy. The Acacia site, characterized by larger mature dense trees, had the highest amount of harvested biomass compared to the rest of the vegetation types (i.e. Myrtle and Spider Gum). The overall system productivity was found to be significantly influenced by a low equipment utilisation rate, estimated at 50%. This resulted in low production rates in general. The low supply rate of material to the chipper by the three-wheeled loader (1.5 – 5.3 oven-dry tonne per production machine hour) was found to be a major constraint in the chipping process, especially when considering that the chipper is potentially capable of chipping 4 – 9.4 ODT PMH-1 at the harvesting sites. This resulted in a significant energy balance of 463 GJ between output and input energy of the system. The overall total supply chain system costs based various road transport distances of species ranged from R 322.77 ODT-1 to R 689.76 ODT-1 with an average of R 509 ODT-1. This was found to be costly compare to the case where high machine utilisation rate and optimal productivity are used (average of R 410 ODT-1), biomass recoverability in this field trial had a higher total system cost due to low productivity, resulting from the low equipment utilisation rate applied. / AFRIKAANSE OPSOMMING: Hierdie studie was gemik daarop om die moontlikheid van die gebruik van houtagtige biomassa, afkomstig van uitheemse plantegroei (Bloekom, Mirte en Akasias) op die Agulhasvlakte vir bio-energie te ondersoek. Potensiële produktiwiteit, bedryfskostes en die geskatte energie opbrengs toename is gebruik, om die fisiese opbrengs van houtagtige biomassa van ʼn semi-gemeganiseerde ontginningstelsel te evalueer. Die stelsel het uit vyf komponente bestaan: Handontginning, motor-handontginning, uitsleep, verspandering en padvervoer. Data oor die stelselproduktiwiteit is uit tydstudie en aktiwiteit steekproewe verkry. Aktiwiteit steekproewe is toegepas op hand- en motorhandontgining om ontginingstyd te verkry, terwyl tydstudie standaardtegnieke gebruik is om tyd data vir uitsleep, verspandering en padvervoer werksaamhede te verkry. Bevindings het die voordele met bettrekking tot die gebruik van uitheemse plantegroei as energiebron bevestig. Die uitdaging rondom die verspreiding van uitheemse plantegroei kan dus aangespreek word deur dit as energiebron te benut. Die produksiekoste vir die toegang tot die bruikbare biomassa kan moontlik voorsien word uit die voordele van die gebruik van die energie wat uit die benutting van die biomassa verkry word. Die groter meer volwasse en digte Akasia opstand het die meeste ontginde biomassa gelewer vergeleke met die ander opstande in die studie (d.i. Mirte en Bloekom). Die stelselproduktiwiteit is beduidend beïnvloed deur die lae toerustinggebruik wat minder as 50% beloop het. Dit het ook laer produksievermoë in die algemeen tot gevolg gehad. In die verspandering werksaamheid blyk die lae invoer tempo (1.5 – 5.3 oonddroog ton per produktiewe masjienuur) van die driewiellaaier die beperking op die proses te wees, veral as in ag geneem word dat die verspandering teen 4-9.4 ODT PMH-1 kan geskied. Die resultaat was ʼn beduidende energie balans van 463 GJ tussen uitset- en invoerenergie van die stelsel. Die totale toevoerketting kostes gegrond op verskeie padvervoer afstande van die spesies was tussen R 322.77 ODT-1 tot R 689.76 ODT-1, met ʼn gemiddelde rondom R 509 ODT-1. Die resultaat is duur gevind in vergeleke met gevalle waar hoë masjiengebruik en optimale produktiwiteit (gemiddeld van R 410 ODT-1), moontlik was. Die biomassaherwinning in die studie het ʼn hoër totale stelselkoste gehad veroorsaak deur lae produktiwiteit, wat verwant is aan die laer toerusting gebruikstempo wat verkry is.

Multidatabases are being actively researched as a relatively new area in which many aspects are not yet fully understood. This area of transaction management in multidatabase systems still has many unresolved problems. The problem areas which this dissertation addresses are classification of multidatabase systems, global concurrency control, correctness criterion in a multidatabase environment, global deadlock detection, atomic commitment and crash recovery. A core group of research addressing these problems was identified and studied. The dissertation contributes to the multidatabase transaction management topic by introducing an alternative classification method for such multiple database systems; assessing existing research into transaction management schemes and based on this assessment, proposes a transaction processing model founded on the optimal properties of transaction management identified during the course of this research. / Computing / M. Sc. (Computer Science)

The issue of learner engagement is an important question for education and for instructional design. It is acknowledged that computer games in general are engaging. Thus, one possible solution to learner engagement is to integrate computer games into education; however, the literature indicates that pedagogical, logistical and political barriers remain. Another possible solution is to derive principles for the design of engaging experiences from a critical examination of computer game design. One possible application of the derived design principles is that instruction may be designed to be inherently more engaging. The purpose of this dissertation was to look for operational principles underlying the design of computer games in order to better understand the design of engaging experiences. Core design components and associated operational principles for the design of engaging experiences were identified. Selected computer games were analyzed to demonstrate that these components and principles were present in the design of successful computer games. Selected instructional units were analyzed to show evidence that these operational principles could be applied to the design of instruction. An instructional design theory—called Challenge-driven Instructional Design—and design considerations for the theory were proposed. Finally, suggestions were made for continued development and research of the instructional design theory.