Novel low power CAM architecture

One special type of memory use for high speed address lookup in router or cache address lookup in a processor is Content Addressable Memory (CAM). CAM can also be used in pattern recognition applications where a unique pattern needs to be determined if a match is found. CAM has an additional comparison circuit in each memory bit compared to Static Random Access Memory. This comparison circuit provides CAM with an additional capability for searching the entire memory in one clock cycle. With its hardware parallel comparison architecture, it makes CAM an ideal candidate for any high speed data lookup or for address processing applications. Because of its high power demand nature, CAM is not often used in a mobile device. To take advantage of CAM on portable devices, it is necessary to reduce its power consumption. It is for this reason that much research has been conducted on investigating different methods and techniques for reducing the overall power. The objective is to incorporate and utilize circuit and power reduction techniques in a new architecture to further reduce CAM’s energy consumption. The new CAM architecture illustrates the reduction of both dynamic and static power dissipation at 65nm sub-micron environment. This thesis will present a novel CAM architecture, which will reduce power consumption significantly compared to traditional CAM architecture, with minimal or no performance losses. Comparisons with other previously proposed architectures will be presented when implementing these designs under 65nm process environment. Results show the novel CAM architecture only consumes 4.021mW of power compared to the traditional CAM architecture of 12.538mW at 800MHz frequency and is more energy efficient over all other previously proposed designs

Robust Inference in High Dimensional Linear Model with Cluster Dependence

Cluster standard error (Liang and Zeger, 1986) is widely used by empirical researchers to account for cluster dependence in linear model. It is well known that this standard error is biased. We show that the bias does not vanish under high dimensional asymptotics by revisiting Chesher and Jewitt (1987)'s approach. An alternative leave-cluster-out crossfit (LCOC) estimator that is unbiased, consistent and robust to cluster dependence is provided under high dimensional setting introduced by Cattaneo, Jansson and Newey (2018). Since LCOC estimator nests the leave-one-out crossfit estimator of Kline, Saggio and Solvsten (2019), the two papers are unified. Monte Carlo comparisons are provided to give insights on its finite sample properties. The LCOC estimator is then applied to Angrist and Lavy's (2009) study of the effects of high school achievement award and Donohue III and Levitt's (2001) study of the impact of abortion on crime

Preconditioned conjugate-gradient methods for low-speed flow calculations

An investigation is conducted into the viability of using a generalized Conjugate Gradient-like method as an iterative solver to obtain steady-state solutions of very low-speed fluid flow problems. Low-speed flow at Mach 0.1 over a backward-facing step is chosen as a representative test problem. The unsteady form of the two dimensional, compressible Navier-Stokes equations is integrated in time using discrete time-steps. The Navier-Stokes equations are cast in an implicit, upwind finite-volume, flux split formulation. The new iterative solver is used to solve a linear system of equations at each step of the time-integration. Preconditioning techniques are used with the new solver to enhance the stability and convergence rate of the solver and are found to be critical to the overall success of the solver. A study of various preconditioners reveals that a preconditioner based on the Lower-Upper Successive Symmetric Over-Relaxation iterative scheme is more efficient than a preconditioner based on Incomplete L-U factorizations of the iteration matrix. The performance of the new preconditioned solver is compared with a conventional Line Gauss-Seidel Relaxation (LGSR) solver. Overall speed-up factors of 28 (in terms of global time-steps required to converge to a steady-state solution) and 20 (in terms of total CPU time on one processor of a CRAY-YMP) are found in favor of the new preconditioned solver, when compared with the LGSR solver

Hygienic determinants of residential buildings in Hong Kong

Thesis (B.Sc)--University of Hong Kong, 2004.published_or_final_versio

Two- and three-dimensional viscous computations of a hypersonic inlet flow

The three-dimensional parabolized Navier-Stokes code has been used to investigate the flow through a Mach 7.4 inlet. A two-dimensional parametric study of grid resolution, turbulence modeling and effect of gamma has been done and compared with experimental results. The results show that mesh resolution of the shock waves, real gas effects and turbulence length scaling are very important to get accurate results for hypersonic inlet flows. In addition a three-dimensional calculation of the Mach 7.4 inlet has been done on a straight sideplate configuration. The results show that the glancing shock/boundary layer interaction phenomena causes significant three-dimensional flow in the inlet

Systematic reviews of occupational therapy interventions: summarizing research evidence and highlighting the gaps

As services are commissioned based on effectiveness, occupational therapists are under pressure to demonstrate the efficacy of their interventions. Occupational therapists also need to know that the interventions they are providing are effective. Robertson et al (2013) demonstrated that the occupational therapy literature is important for clinicians and is an essential part of their practice. However, as more research is published, it can be increasingly time-consuming and confusing for clinicians to keep abreast of the current literature. Occupational therapy-related research may be published in different forms, in a range of locations, and be of varying methodological quality. Furthermore, readily available published studies that investigate occupational therapy efficacy may not be sufficiently powered, or may lack external validity, when applied to different clinical settings. When well conducted, systematic reviews provide a useful way of synthesizing and evaluating the evidence on a particular topic and, to some extent, provide a solution to this problem. This paper focuses upon reviews of randomized controlled trials, as these provide the highest quality of evidence on the question of a particular intervention’s effectiveness. The merits of reviews of qualitative studies are also considered, together with the possibility of combining more than one type of review

The Mediation Influence of Job Satisfaction on Organisational Commitment amongst Quantity Surveyors

Some researchers claimed that job satisfaction directly affected organisational commitment but others considered it had a mediation effect on the relationship between some independent variables and organisational commitment. Thus, this paper aimed to examine whether job satisfaction mediated the relationship between work group identification and the two forms of organisational commitment amongst quantity surveyors. A quantitative approach with questionnaire survey was employed for data collection. Questionnaires were sent to the chartered quantity surveyors and 71 valid responses were obtained for analysis. A bootstrapping approach was applied to the survey data to test the mediating effect of job satisfaction between work group identification and organisational commitment. The bootstrapping results supported most hypotheses. The findings suggested that surveying companies should focus their efforts on improving quantity surveyors’ job satisfaction through the organisation of social activities. Special measures should also be taken by the work group leaders to improve the working relationship among quantity surveyors to foster job satisfaction.Paper Type: Research articl

Fatigue Assessment using ECG and Actigraphy Sensors

Fatigue is one of the key factors in the loss of work efficiency and health-related quality of life, and most fatigue assessment methods were based on self-reporting, which may suffer from many factors such as recall bias. To address this issue, we developed an automated system using wearable sensing and machine learning techniques for objective fatigue assessment. ECG/Actigraphy data were collected from subjects in free-living environments. Preprocessing and feature engineering methods were applied, before interpretable solution and deep learning solution were introduced. Specifically, for interpretable solution, we proposed a feature selection approach which can select less correlated and high informative features for better understanding system's decision-making process. For deep learning solution, we used state-of-the-art self-attention model, based on which we further proposed a consistency self-attention (CSA) mechanism for fatigue assessment. Extensive experiments were conducted, and very promising results were achieved.Comment: accepted by ISWC 202