Adjusted quasi-maximum likelihood estimator for mixed regressive,spatial autoregressive model and its small sample bias

Under flexible distributional assumptions, the adjusted quasi-maximum likelihood ($\text{<mi mathsize="small" is="true">ADQML</mi>}$) estimator for mixed regressive, spatial autoregressive model is studied in this paper. The proposed estimation method accommodates the extra uncertainty introduced by the unknown regression coefficients. Moreover, the explicit expressions of theoretical/feasible second-order-bias of the $\text{<mi mathsize="small" is="true">ADQML</mi>}$ estimator are derived and the difference between them is investigated. The feasible second-order-bias corrected $\text{<mi mathsize="small" is="true">ADQML</mi>}$ estimator is then designed accordingly for small sample setting. Extensive simulation studies are conducted under both normal and non-normal situations, showing that the quasi-maximum likelihood ($\text{<mi mathsize="small" is="true">QML</mi>}$) estimator suffers from large bias when the sample size is relatively small in comparison to the number of regression coefficients and such bias can be effectively eliminated by the proposed $\text{<mi mathsize="small" is="true">ADQML</mi>}$ estimation method. The use of the method is then demonstrated in the analysis of the Neighborhood Crimes Data.     

Highly concurrent multi-word synchronization

The design of concurrent data structures is greatly facilitated by the availability of synchronization operations that atomically modify $k$ arbitrary items, such as $k$-read–modify–write ($k\text{<mi mathsize="small" is="true">RMW</mi>}$). Aiming to increase concurrency in order to exploit the parallelism offered by today’s multi-core and multi-processing architectures, we propose a highly concurrent software implementation of $k\text{<mi mathsize="small" is="true">RMW</mi>}$, with only constant space overhead. Our algorithm ensures that two operations delay each other only if they are within distance $O\left(k\right)$ in the conflict graph, induced by the operations’ data items.The algorithm uses double compare-and-swap (dcas). When dcas is not supported by the architecture, the algorithm of Attiya and Dagan (2001) [3] can be used to replace dcas with (unary) cas, with only a slight increase in the interference among operations.     

Extending the BSP model for multi-core and out-of-core computing: MBSP

We present an extension of the bulk-synchronous parallel (BSP) model to abstract and model parallelism in the presence of multiple memory hierarchies and multiple cores. We call the new model MBSP for multi-memory BSP. The BSP model has been used to model internal memory parallel computers; MBSP retains the properties of BSP and in addition can abstract not only traditional external memory-supported parallelism (e.g. that uses another level of slower memory) but also multi-level cache-based memory hierarchies such as those present in multi-core systems. Present day multi-core systems are limited parallelism architectures with fast inter-core communication but limited fast memory availability. Abstracting the programming requirements of such architectures in a useful and usable manner is the objective of introducing MBSP. We propose multi-core program and algorithm design that measures resource utilization through a septuplet $(p\text{,}l\text{,}g\text{,}m\text{,}L\text{,}G\text{,}M)$ in which $(p\text{,}l\text{,}g)$ are the BSP parameters for modeling processor component size and interprocessor communication through latency-based and throughput-based cost mechanisms, and $(m\text{,}L\text{,}G\text{,}M)$ are the new parameters that abstract additional memory hierarchies. Each processor component is attached to a memory of size M, and there are also m memory-units accessing a slower memory of unlimited size of latency-based and throughput-based cost $(L\text{,}G)$. A deterministic sorting algorithm is described on this model that is potentially both usable and useful.     

An automata-theoretic approach to constraint LTL

We consider an extension of linear-time temporal logic (LTL) with constraints interpreted over a concrete domain. We use a new automata-theoretic technique to show PSPACE decidability of the logic for the constraint systems ($\mathbb{Z}\text{,}<\text{,}=$) and ($\mathbb{N}\text{,}<\text{,}=$). Along the way, we give an automata-theoretic proof of a result of Balbiani and Condotta when the constraint system satisfies the completion property. Our decision procedures extend easily to handle extensions of the logic with past-time operators and constants, as well as an extension of the temporal language itself to monadic second order logic. Finally we show that the logic becomes undecidable when one considers constraint systems that allow a counting mechanism.