Hebrew College collection, 1928-1996

Louis Hurwich, then superintendent of the Bureau of Jewish Education of Boston, founded Hebrew Teacher’s College in 1921. Hurwich was concerned about Jewish teachers leaving the field of Jewish education for other professions and sought an educational system that promoted Hebrew literacy at all levels. Hebrew Teacher’s College was also responsible for maintaining Hebrew High School (Prozdor), located at 14 Crawford Street in Roxbury, Massachusetts. Those students who graduated from the high school could matriculate to Hebrew Teacher’s College without having to take an exam. In 1943, the high school offered Talmud classes in addition to its regular curriculum, with studies in the Bible, Hebrew, Jewish History, and codes and customs. In 2002, the College moved to its current location in Newton, Massachusetts. One year later, it opened its Rabbinical School. This collection contains brochures, catalogs, commencement addresses, event fliers, invitations, pamphlets and publications.

A note on the movement of single large liquid bubbles in vertical tubes

The flow of single large liquid bubbles under gravity in closed tubes is studied here for the case when the liquid bubble exhibits micropolar behaviour. The film thickness, velocity profile in the bubble and film, and nonNewtonian effects are studied and compared with those for the correspondingNewtonian fluid. The investigation is restricted to the case where the bubble length is far greater than the tube radius.

Elements of Volatility at High Frequency

Volatility is central in options pricing and risk management. It reflects the uncertainty of investors and the inherent instability of the economy. Time series methods are among the most widely applied scientific methods to analyze and predict volatility. Very frequently sampled data contain much valuable information about the different elements of volatility and may ultimately reveal the reasons for time varying volatility. The use of such ultra-high-frequency data is common to all three essays of the dissertation. The dissertation belongs to the field of financial econometrics. The first essay uses wavelet methods to study the time-varying behavior of scaling laws and long-memory in the five-minute volatility series of Nokia on the Helsinki Stock Exchange around the burst of the IT-bubble. The essay is motivated by earlier findings which suggest that different scaling laws may apply to intraday time-scales and to larger time-scales, implying that the so-called annualized volatility depends on the data sampling frequency. The empirical results confirm the appearance of time varying long-memory and different scaling laws that, for a significant part, can be attributed to investor irrationality and to an intraday volatility periodicity called the New York effect. The findings have potentially important consequences for options pricing and risk management that commonly assume constant memory and scaling. The second essay investigates modelling the duration between trades in stock markets. Durations convoy information about investor intentions and provide an alternative view at volatility. Generalizations of standard autoregressive conditional duration (ACD) models are developed to meet needs observed in previous applications of the standard models. According to the empirical results based on data of actively traded stocks on the New York Stock Exchange and the Helsinki Stock Exchange the proposed generalization clearly outperforms the standard models and also performs well in comparison to another recently proposed alternative to the standard models. The distribution used to derive the generalization may also prove valuable in other areas of risk management. The third essay studies empirically the effect of decimalization on volatility and market microstructure noise. Decimalization refers to the change from fractional pricing to decimal pricing and it was carried out on the New York Stock Exchange in January, 2001. The methods used here are more accurate than in the earlier studies and put more weight on market microstructure. The main result is that decimalization decreased observed volatility by reducing noise variance especially for the highly active stocks. The results help risk management and market mechanism designing.

Rate Model and Mechanism of Liquid-Phase Oxidation of Propionaldehyde

A rate equation is developed for the liquid-phase oxidation of propionaldehyde with oxygen in the presence of manganese propionate catalyst in a sparged reactor. The equation takes into account diffusional limitations based on Brian's solution for mass transfer accompanied by a pseudo m-. nth-order reaction. Sauter-mean bubble diameter, gas holdup, interfacial area, and bubble rise velocity are measured, and rates of mass transfer within the gas phase and across the gas-liquid interface are computed. Statistically designed experiments show the adequacy of the equation. The oxidation reaction is zero order with respect to oxygen concentration, 3/2 order with respect to aldehyde concentration, and order with respect to catalyst concentration. The activation energy is 12.1 kcal/g mole.

Motherland [dramaturg]

'Motherland' is one of three new performance works that were a component of Kathryn Kelly's PhD by Performance at the University of Queensland: 'Pedagogy of Dramaturgy: A Practice Framework to train Dramaturgs." Kathryn Kelly was engaged as a dramaturg for the performance of this work.

Waters Wars [Dramaturg]

'Water Wars' is one of three new performance works that were a component of Kathryn Kelly's PhD by Performance at the University of Queensland: 'Pedagogy of Dramaturgy: A Practice Framework to train Dramaturgs." Kathryn Kelly was engaged as a dramaturg on each performance work, and each is the basis of case study material used in the training program developed as part of the PhD.

The Rat Trap [Dramaturg]

"The Rat Trap" is a new performance work undertaken as part of Kathryn Kelly's "PhD by Performance" at the University of Queensland: "The Pedagogy of Dramaturgy: A Practice Framework to Train Dramaturgs." Kathryn Kelly worked as dramaturg on each project, which served as case study material for the training program I developed as part of the thesis.

Vertical distribution of aerosols over the east coast of India inferred from airborne LIDAR measurements

The information on altitude distribution of aerosols in the atmosphere is essential in assessing the impact of aerosol warming on thermal structure and stability of the atmosphere.In addition, aerosol altitude distribution is needed to address complex problems such as the radiative interaction of aerosols in the presence of clouds. With this objective,an extensive, multi-institutional and multi-platform field experiment (ICARB-Integrated Campaign for Aerosols, gases and Radiation Budget) was carried out under the Geosphere Biosphere Programme of the Indian Space Research Organization (ISRO-GBP) over continental India and adjoining oceans during March to May 2006. Here, we present airborne LIDAR measurements carried out over the east Coast of the India during the ICARB field campaign. An increase in aerosol extinction (scattering + absorption) was observed from the surface upwards with a maximum around 2 to 4 km. Aerosol extinction at higher atmospheric layers (>2 km) was two to three times larger compared to that of the surface. A large fraction (75-85%) of aerosol column optical depth was contributed by aerosols located above 1 km. The aerosol layer heights (defined in this paper as the height at which the gradient in extinction coefficient changes sign) showed a gradual decrease with an increase in the offshore distance. A large fraction (60-75%) of aerosol was found located above clouds indicating enhanced aerosol absorption above clouds. Our study implies that a detailed statistical evaluation of the temporal frequency and spatial extent of elevated aerosol layers is necessary to assess their significance to the climate. This is feasible using data from space-borne lidars such as CALIPSO,which fly in formation with other satellites like MODIS AQUA and MISR, as part of the A-Train constellation.

Inferring neuronal network connectivity from spike data: A temporal data mining approach

Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent d evelopments in electrophysiology and imaging allow one to simultaneously record activities of hundreds of neurons. Inferring the underlying neuronal connectivity patterns from such multi-neuronal spike train data streams is a challenging statistical and computational problem. This task involves finding significant temporal patterns from vast amounts of symbolic time series data. In this paper we show that the frequent episode mining methods from the field of temporal data mining can be very useful in this context. In the frequent episode discovery framework, the data is viewed as a sequence of events, each of which is characterized by an event type and its time of occurrence and episodes are certain types of temporal patterns in such data. Here we show that, using the set of discovered frequent episodes from multi-neuronal data, one can infer different types of connectivity patterns in the neural system that generated it. For this purpose, we introduce the notion of mining for frequent episodes under certain temporal constraints; the structure of these temporal constraints is motivated by the application. We present algorithms for discovering serial and parallel episodes under these temporal constraints. Through extensive simulation studies we demonstrate that these methods are useful for unearthing patterns of neuronal network connectivity.

Scheduling techniques to optimise sugarcane rail transport systems

In Australia, railway systems play a vital role in transporting the sugarcane crop from farms to mills. In this paper, a novel job shop approach is proposed to create a more efficient integrated harvesting and sugarcane transport scheduling system to reduce the cost of sugarcane transport. There are several benefits that can be attained by treating the train scheduling problem as a job shop problem. Job shop is generic and suitable for all trains scheduling problems. Job shop technique prevents operating two trains on one section at the same time because it considers that the section or the machine is unique. This technique is more promising to find better solutions in reasonable computation times.

Deploying speaker verification techniques to vision-based RPA detect and avoid

Detect and Avoid (DAA) technology is widely acknowledged as a critical enabler for unsegregated Remote Piloted Aircraft (RPA) operations, particularly Beyond Visual Line of Sight (BVLOS). Image-based DAA, in the visible spectrum, is a promising technological option for addressing the challenges DAA presents. Two impediments to progress for this approach are the scarcity of available video footage to train and test algorithms, in conjunction with testing regimes and specifications which facilitate repeatable, statistically valid, performance assessment. This paper includes three key contributions undertaken to address these impediments. In the first instance, we detail our progress towards the creation of a large hybrid collision and near-collision encounter database. Second, we explore the suitability of techniques employed by the biometric research community (Speaker Verification and Language Identification), for DAA performance optimisation and assessment. These techniques include Detection Error Trade-off (DET) curves, Equal Error Rates (EER), and the Detection Cost Function (DCF). Finally, the hybrid database and the speech-based techniques are combined and employed in the assessment of a contemporary, image based DAA system. This system includes stabilisation, morphological filtering and a Hidden Markov Model (HMM) temporal filter.

Preparation of reticulated MAX-phase support with morphology-controllable nanostructured ceria coating for gas exhaust catalyst devices

Reticulated porous Ti3AlC2 ceramic, a member of the MAX-phase family (Mn+1AXn phases, where M is an early transition metal, A is an A-group element, and X is carbon and/or nitrogen), was prepared from the highly dispersed aqueous suspension by a replica template method. Through a cathodic electrogeneration method, nanocrystalline catalytic CeO2 coatings were deposited on the conductive porous Ti 3AlC2 supports. By adjusting the pH value and cathodic deposition current, coatings exhibiting nanocellar, nanosheets-like, or bubble-free morphologies can be obtained. This work expects to introduce a novel practically feasible material system and a catalytic coating preparation technique for gas exhaust catalyst devices.

Sensitivity of Eigen Value to Damage and Its Identification

The reduction in natural frequencies,however small, of a civil engineering structure, is the first and the easiest method of estimating its impending damage. As a first level screening for health-monitoring, information on the frequency reduction of a few fundamentalmodes can be used to estimate the positions and the magnitude of damage in a smeared fashion. The paper presents the Eigen value sensitivity equations, derived from first-order perturbation technique, for typical infra-structural systems like a simply supported bridge girder, modelled as a beam, an endbearing pile, modelled as an axial rod and a simply supported plate as a continuum dynamic system. A discrete structure, like a building frame is solved for damage using Eigen-sensitivity derived by a computationalmodel. Lastly, neural network based damage identification is also demonstrated for a simply supported bridge beam, where the known-pairs of damage-frequency vector is used to train a neural network. The performance of these methods under the influence of measurement error is outlined. It is hoped that the developed method could be integrated in a typical infra-structural management program, such that magnitudes of damage and their positions can be obtained using acquired natural frequencies, synthesized from the excited/ambient vibration signatures.

Lateral impact derailment mechanisms, simulation and analysis

Lateral collisions between heavy road vehicles and passenger trains at level crossings and the associated derailments are serious safety issues. This paper presents a detailed investigation of the dynamic responses and derailment mechanisms of trains under lateral impact using a multi-body dynamics simulation method. Formulation of a three-dimensional dynamic model of a passenger train running on a ballasted track subject to lateral impact caused by a road truck is presented. This model is shown to predict derailment due to wheel climb and car body overturning mechanisms through numerical examples. Sensitivities of the truck speed and mass, wheel/rail friction and the train suspension to the lateral stability and derailment of the train are reported. It is shown that improvements to the design of train suspensions, including secondary and inter-vehicle lateral dampers have higher potential to mitigate the severity of the collision-induced derailments.

Comparison of the sensitivity of different sensor technologies to imbalance severity in low speed wind turbines

Imbalance is not only a direct major cause of downtime in wind turbines, but also accelerates the degradation of neighbouring and downstream components (e.g. main bearing, generator). Along with detection, the imbalance quantification is also essential as some residual imbalance always exist even in a healthy turbine. Three different commonly used sensor technologies (vibration, acoustic emission and electrical measurements) are investigated in this work to verify their sensitivity to different imbalance grades. This study is based on data obtained by experimental tests performed on a small scale wind turbine drive train test-rig for different shaft speeds and imbalance levels. According to the analysis results, electrical measurements seem to be the most suitable for tracking the development of imbalance.