Client-based Logging: A New Paradigm of Distributed Transaction Management

The proliferation of inexpensive workstations and networks has created a new era in distributed computing. At the same time, non-traditional applications such as computer-aided design (CAD), computer-aided software engineering (CASE), geographic-information systems (GIS), and office-information systems (OIS) have placed increased demands for high-performance transaction processing on database systems. The combination of these factors gives rise to significant challenges in the design of modern database systems. In this thesis, we propose novel techniques whose aim is to improve the performance and scalability of these new database systems. These techniques exploit client resources through client-based transaction management. Client-based transaction management is realized by providing logging facilities locally even when data is shared in a global environment. This thesis presents several recovery algorithms which utilize client disks for storing recovery related information (i.e., log records). Our algorithms work with both coarse and fine-granularity locking and they do not require the merging of client logs at any time. Moreover, our algorithms support fine-granularity locking with multiple clients permitted to concurrently update different portions of the same database page. The database state is recovered correctly when there is a complex crash as well as when the updates performed by different clients on a page are not present on the disk version of the page, even though some of the updating transactions have committed. This thesis also presents the implementation of the proposed algorithms in a memory-mapped storage manager as well as a detailed performance study of these algorithms using the OO1 database benchmark. The performance results show that client-based logging is superior to traditional server-based logging. This is because client-based logging is an effective way to reduce dependencies on server CPU and disk resources and, thus, prevents the server from becoming a performance bottleneck as quickly when the number of clients accessing the database increases.

Characteristics of Biodiesel Oil Atomized by a Two-Fluid Nozzle Using PDA

Drop size and velocity distribution in a spray of fuel play an important role in determining combustion efficiency. The Phase Doppler anemometer (PDA) is a well-established technique allowing simultaneous measurement of velocity and size of droplets. In this work, effect of bio-substitute component on the size and velocity of biodiesel droplets which are generated by a two-fluid nozzle are investigated comprehensively using a PDA.

High electric current density-induced interfacial reactions in micro ball grid array (μBGA) solder joints

The effect of a high electric current density on the interfacial reactions of micro ball grid array solder joints was studied at room temperature and at 150 °C. Four types of phenomena were reported. Along with electromigration-induced interfacial intermetallic compound (IMC) formation, dissolution at the Cu under bump metallization (UBM)/bond pad was also noticed. With a detailed investigation, it was found that the narrow and thin metallization at the component side produced “Joule heating” due to its higher resistance, which in turn was responsible for the rapid dissolution of the Cu UBM/bond pad near to the Cu trace. During an “electromigration test” of a solder joint, the heat generation due to Joule heating and the heat dissipation from the package should be considered carefully. When the heat dissipation fails to compete with the Joule heating, the solder joint melts and molten solder accelerates the interfacial reactions in the solder joint. The presence of a liquid phase was demonstrated from microstructural evidence of solder joints after different current stressing (ranging from 0.3 to 2 A) as well as an in situ observation. Electromigration-induced liquid state diffusion of Cu was found to be responsible for the higher growth rate of the IMC on the anode side.

Delamination of oil paints from acrylic grounds

Many modern artists paint in oil or oil-modified alkyd paints over acrylic grounds. In some cases the oil based paints do not remain adhered to the ground. In a set of composite samples of oil or alkyd paints, over acrylic grounds, naturally aged for nine years, some of the samples delaminated. Samples were analyzed with X-ray fluorescence (XRF), inductively coupled plasma (ICP), Fourier transform infrared - attenuated total reflectance (FTIR-ATR), scanning electron microscopy (SEM), pyrolysis gas-chromatography mass-spectrometry (PY-GC/MS), laser desorption/ionization mass-spectrometry (LDI-MS), atomic force microscopy (AFM) and other methods, in order to find what the delaminating ones have in common. In addition, two examples of severely delaminating paintings were examined, to confirm the results from the laboratory-prepared samples. Results indicate the main cause of delamination is metal soaps in the oil paint and particularly zinc soaps. There is some evidence that metal soaps were more concentrated at the interface between the layers and this disrupted the adhesion. The ground is a minor consideration as well, rougher grounds providing better adhesion than smooth ones.

Oil on Troubled Waters-Multinational Corporations and Realising Human Rights in the Developing World with Particular Reference to Nigeria

This article examines the current state of tension in the Niger Delta of Nigeria. It locates the current unrest in the continued denial of economic, social and cultural rights to the oil-rich communities in the area. The author argues that this denial happened with the complicity and acquiescence of the international community. The Nigerian government as well as multinational corporations operating in the area have not been responsive to the development needs of the people. The article argues that, although the primary obligation for realising the economic, social and cultural rights of host communities rests on the government, multi-national corporations in developing countries, considering their awesome resources and influence on government policies, should be similarly obligated to respect, promote and protect those rights.

Lack of horizontal gene transfer of methicillin-resitance genetic determinants from PBP2a-positive, coagulase-negative Staphylococci to methicillin-sensitive Staphylococcus aureus using transcutaneous electric nerve stimulation (TENS),

Previous research shows that approximately half of the coagulase-negative staphylococci (CNS) isolated from patients in the intensive care unit (ICU) at Belfast City Hospital were resistant to methicillin. The presence of this relatively high proportion of methicillin-resistance genetic material gives rise to speculation that these organisms may act as potential reservoirs of methicillinresistance genetic material to methicillin-sensitive Staphylococcus aureus (MSSA). Mechanisms of horizontal gene transfer from PBP2a-positive CNS to MSSA, potentially transforming MSSA to MRSA, aided by electroporation-type activities such as transcutaneous electrical nerve stimulation (TENS), should be considered. Methicillin-resistant CNS (MR-CNS) isolates are collected over a two-month period from a variety of clinical specimen types, particularly wound swabs. The species of all isolates are confirmed, as well as their resistance to oxacillin by standard disc diffusion assays. In addition, MSSA isolates are collected over the same period and confirmed as PBP2a-negative. Electroporation experiments are designed to mimic the time/voltage combinations used commonly in the clinical application of TENS. No transformed MRSA were isolated and all viable S. aureus cells remained susceptible to oxacillin and PBP2a-negative. Experiments using MSSA pre-exposed to sublethal concentrations of oxacillin (0.25 µg/mL) showed no evidence of methicillin gene transfer and the generation of an MRSA. The study showed no evidence of horizontal transfer of methicillin resistance genetic material from MR-CNS to MSSA. These data support the belief that TENS and the associated time/voltage combinations used do not increase conjugational transposons or facilitate horizontal gene transfer from MR-CNS to MSSA.

NON-GAUSSIAN STATISTICS OF OIL PRICING TIME-SERIES: A CASE STUDY

The stochastic nature of oil price fluctuations is investigated over a twelve-year period, borrowing feedback from an existing database (USA Energy Information Administration database, available online). We evaluate the scaling exponents of the fluctuations by employing different statistical analysis methods, namely rescaled range analysis (R/S), scale windowed variance analysis (SWV) and the generalized Hurst exponent (GH) method. Relying on the scaling exponents obtained, we apply a rescaling procedure to investigate the complex characteristics of the probability density functions (PDFs) dominating oil price fluctuations. It is found that PDFs exhibit scale invariance, and in fact collapse onto a single curve when increments are measured over microscales (typically less than 30 days). The time evolution of the distributions is well fitted by a Levy-type stable distribution. The relevance of a Levy distribution is made plausible by a simple model of nonlinear transfer. Our results also exhibit a degree of multifractality as the PDFs change and converge toward to a Gaussian distribution at the macroscales.

HTS Machines as Enabling Technology for All-Electric Airborne Vehicles

Environmental protection has now become paramount as evidence mounts to support the thesis of human activity-driven global warming. A global reduction of the emissions of pollutants into the atmosphere is therefore needed and new technologies have to be considered. A large part of the emissions come from transportation vehicles, including cars, trucks and airplanes, due to the nature of their combustion-based propulsion systems. Our team has been working for several years on the development of high power density superconducting motors for aircraft propulsion and fuel cell based power systems for aircraft. This paper investigates the feasibility of all-electric aircraft based on currently available technology. Electric propulsion would require the development of high power density electric propulsion motors, generators, power management and distribution systems. The requirements in terms of weight and volume of these components cannot be achieved with conventional technologies; however, the use of superconductors associated with hydrogen-based power plants makes possible the design of a reasonably light power system and would therefore enable the development of all-electric aero-vehicles. A system sizing has been performed both for actuators and for primary propulsion. Many advantages would come from electrical propulsion such as better controllability of the propulsion, higher efficiency, higher availability and less maintenance needs. Superconducting machines may very well be the enabling technology for all-electric aircraft development.

Numerical simulation of a patent technology for sealing of deep-sea oil wells using nonlinear finite element method

For over 50 years bridge plugs and cement have been used for well abandonment and work over and are still the material of choice. However the failures of cement abandonments using bridge plugs has been reported on many occasions, some of which have resulted in fatal consequences. A new patented product is designed to address the shortcomings associated with using bridge plugs and cement. The new developed tools use an alloy based on bismuth that is melted in situ using Thermite reaction. The tool uses the expansion properties of bismuth to seal the well. Testing the new technology in real field under more than 2 km deep sea water can be expensive. Virtual simulation of the new device under simulated thermal and mechanical environment can be achieved using nonlinear finite element method to validate the product and reduce cost. Experimental testing in the lab is performed to measure heat generated due to thermite reaction. Then, a sequential thermal mechanical explicit/implicit finite element solver is used to simulate the device under both testing lab and deep water conditions.

Investigating Hydraulically Active Fractures in A Shallow Meta-Sedimentary Bedrock Aquifer Using Single Well Tracer Testing, Mount Stewart, Northern Ireland

Knowledge of groundwater flow/mass transport, in poorly productive aquifers which underlie over 65% of the island of Ireland, is necessary for effective management of catchment water quality and aquatic ecology. This research focuses on a fractured low-grade Ordovician/Silurian greywacke sequence which underlies approximately 25% of the northern half of Ireland. Knowledge of the unit’s hydrogeological properties remain largely restricted to localised single well open hole “transmissivity” values. Current hydrogeological conceptual models of the Greywacke view the bulk of groundwater flowing through fractures in an otherwise impermeable bedrock mass.
Core analysis permits fracture characterisation, although not all identified fractures may be involved in groundwater flow. Traditional in-situ hydraulic characterisation relies on cumbersome techniques such as packer testing or geophysical borehole logging (e.g. flowmeters). Queen’s University Belfast is currently carrying out hydraulic characterization of 16 boreholes at its Greywacke Hydrogeological Research Site at Mount Stewart, Northern Ireland.
Development of dye dilution methods, using a recently-developed downhole fluorometer, provided a portable, user-friendly, and inexpensive means of detecting hydraulically active intervals in open boreholes. Measurements in a 55m deep hole, three days following fluorescent dye injection, demonstrated the ability of the technique to detect two discrete hydraulically active intervals corresponding to zones identified by caliper and heat-pulse flowmeter logs. High resolution acoustic televiewer logs revealed the zones to correspond to two steeply dipping fractured intervals. Results suggest the rock can have effective porosities of the order of 0.1%.
Study findings demonstrate dye dilution’s utility in characterizing groundwater flow in fractured aquifers. Tests on remaining holes will be completed at different times following injection to identify less permeable fractures and develop an improved understanding of the structural controls on groundwater flow in the uppermost metres of competent bedrock.

Physical properties of a new Deep Eutectic Solvent based on lithium bis[(trifluoromethyl)sulfonyl]imide and N-methylacetamide as superionic suitable electrolyte for lithium ion batteries and electric double layer capacitors

Herein we present a study on the physical/chemical properties of a new Deep Eutectic Solvent (DES) based on N-methylacetamide (MAc) and lithium bis[(trifluoromethyl)sulfonyl]imide (LiTFSI). Due to its interesting properties, such as wide liquid-phase range from -60°C to 280°C, low vapor pressure, and high ionic conductivity up to 28.4mScm at 150°C and at x=1/4, this solution can be practically used as electrolyte for electrochemical storage systems such as electric double-layer capacitors (EDLCs) and/or lithium ion batteries (LiBs). Firstly, relationships between its transport properties (conductivity and viscosity) as a function of composition and temperature were discussed through Arrhenius' Law and Vogel-Tamman-Fulcher (VTF) equations, as well as by using the Walden classification. From this investigation, it appears that this complex electrolyte possesses a number of excellent transport properties, like a superionic character for example. Based on which, we then evaluated its electrochemical performances as electrolyte for EDLCs and LiBs applications by using activated carbon (AC) and lithium iron phosphate (LiFePO) electrodes, respectively. These results demonstrate that this electrolyte has a good compatibility with both electrodes (AC and LiFePO) in each testing cell driven also by excellent electrochemical properties in specific capacitance, rate and cycling performances, indicating that the LiTFSI/MAc DES can be a promising electrolyte for EDLCs and LiBs applications especially for those requiring high safety and stability. © 2013 Elsevier Ltd.

Evaluation of methodologies to determine vegetable oil species present in oil mixtures: Proposition of an approach to meet the EU legislation demands for correct vegetable oils labelling

Refined vegetable oils are widely used in the food industry as ingredients or components in many processed food products in the form of oil blends. To date, the generic term 'vegetable oil' has been used in the labelling of food containing oil blends. With the introduction of new EU Regulation for Food Information (1169/2011) due to take effect in 2014, the oil species used must be clearly identified on the package and there is a need for development of fit for purpose methodology for industry and regulators alike to verify the oil species present in a product. The available methodologies that may be employed to authenticate the botanical origin of a vegetable oil admixture were reviewed and evaluated. The majority of the sources however, described techniques applied to crude vegetable oils such as olive oil due to the lack of refined vegetable oil focused studies. Nevertheless, DNA based typing methods and stable isotopes procedures were found not suitable for this particular purpose due to several issues. Only a small number of specific chromatographic and spectroscopic fingerprinting methods in either targeted or untargeted mode were found to be applicable in potentially providing a solution to this complex authenticity problem. Applied as a single method in isolation, these techniques would be able to give limited information on the oils identity as signals obtained for various oil types may well be overlapping. Therefore, more complex and combined approaches are likely to be needed to identify the oil species present in oil blends employing a stepwise approach in combination with advanced chemometrics. Options to provide such a methodology are outlined in the current study.

A self-learning teaching-learning based optimization for dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads

Economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements. These two scheduling problems are commonly formulated with non-smooth cost functions respectively considering various effects and constraints, such as the valve point effect, power balance and ramp rate limits. The expected increase in plug-in electric vehicles is likely to see a significant impact on the power system due to high charging power consumption and significant uncertainty in charging times. In this paper, multiple electric vehicle charging profiles are comparatively integrated into a 24-hour load demand in an economic and environment dispatch model. Self-learning teaching-learning based optimization (TLBO) is employed to solve the non-convex non-linear dispatch problems. Numerical results on well-known benchmark functions, as well as test systems with different scales of generation units show the significance of the new scheduling method.

A new self-learning TLBO algorithm for RBF neural modelling of batteries in electric vehicles

One of the main purposes of building a battery model is for monitoring and control during battery charging/discharging as well as for estimating key factors of batteries such as the state of charge for electric vehicles. However, the model based on the electrochemical reactions within the batteries is highly complex and difficult to compute using conventional approaches. Radial basis function (RBF) neural networks have been widely used to model complex systems for estimation and control purpose, while the optimization of both the linear and non-linear parameters in the RBF model remains a key issue. A recently proposed meta-heuristic algorithm named Teaching-Learning-Based Optimization (TLBO) is free of presetting algorithm parameters and performs well in non-linear optimization. In this paper, a novel self-learning TLBO based RBF model is proposed for modelling electric vehicle batteries using RBF neural networks. The modelling approach has been applied to two battery testing data sets and compared with some other RBF based battery models, the training and validation results confirm the efficacy of the proposed method.

Optimal Scheduling Methods to Integrate Plug-In Electric Vehicles with the Power System: A Review

The introduction of the Tesla in 2008 has demonstrated to the public of the potential of electric vehicles in terms of reducing fuel consumption and green-house gas from the transport sector. It has brought electric vehicles back into the spotlight worldwide at a moment when fossil fuel prices were reaching unexpected high due to increased demand and strong economic growth. The energy storage capabilities from of fleets of electric vehicles as well as the potentially random discharging and charging offers challenges to the grid in terms of operation and control. Optimal scheduling strategies are key to integrating large numbers of electric vehicles and the smart grid. In this paper, state-of-the-art optimization methods are reviewed on scheduling strategies for the grid integration with electric vehicles. The paper starts with a concise introduction to analytical charging strategies, followed by a review of a number of classical numerical optimization methods, including linear programming, non-linear programming, dynamic programming as well as some other means such as queuing theory. Meta-heuristic techniques are then discussed to deal with the complex, high-dimensional and multi-objective scheduling problem associated with stochastic charging and discharging of electric vehicles. Finally, future research directions are suggested.