Scout to launch air density and injun satellites news release no. 64-284

Injun-Explorer satellite combination for simultaneous measurements of air density and atmospheric heatin

On the inclusion of channel's time dependence in a hidden Markov model for blind channel estimation

In this paper, the theory of hidden Markov models (HMM) is applied to the problem of blind (without training sequences) channel estimation and data detection. Within a HMM framework, the Baum–Welch(BW) identification algorithm is frequently used to find out maximum-likelihood (ML) estimates of the corresponding model. However, such a procedure assumes the model (i.e., the channel response) to be static throughout the observation sequence. By means of introducing a parametric model for time-varying channel responses, a version of the algorithm, which is more appropriate for mobile channels [time-dependent Baum-Welch (TDBW)] is derived. Aiming to compare algorithm behavior, a set of computer simulations for a GSM scenario is provided. Results indicate that, in comparison to other Baum–Welch (BW) versions of the algorithm, the TDBW approach attains a remarkable enhancement in performance. For that purpose, only a moderate increase in computational complexity is needed.Peer Reviewe

On the inclusion of channel's time dependence in a hidden Markov model for blind channel estimation

In this paper, the theory of hidden Markov models (HMM) is applied to the problem of blind (without training sequences) channel estimation and data detection. Within a HMM framework, the Baum–Welch(BW) identification algorithm is frequently used to find out maximum-likelihood (ML) estimates of the corresponding model. However, such a procedure assumes the model (i.e., the channel response) to be static throughout the observation sequence. By means of introducing a parametric model for time-varying channel responses, a version of the algorithm, which is more appropriate for mobile channels [time-dependent Baum-Welch (TDBW)] is derived. Aiming to compare algorithm behavior, a set of computer simulations for a GSM scenario is provided. Results indicate that, in comparison to other Baum–Welch (BW) versions of the algorithm, the TDBW approach attains a remarkable enhancement in performance. For that purpose, only a moderate increase in computational complexity is needed.Peer Reviewe

Blind channel estimation and data detection using hidden Markov models theory

In this correspondence, we propose applying the hidden Markov models (HMM) theory to the problem of blind channel estimation and data detection. The Baum–Welch (BW) algorithm, which is able to estimate all the parameters of the model, is enriched by introducing some linear constraints emerging from a linear FIR hypothesis on the channel. Additionally, a version of the algorithm that is suitable for timevarying channels is also presented. Performance is analyzed in a GSM environment using standard test channels and is found to be close to that obtained with a nonblind receiver.Peer Reviewe

Ordering transactions with bounded unfairness:Definitions, complexity and constructions

An important consideration in the context of distributed ledger protocols is fairness in terms of transaction ordering. Recent work [Crypto 2020] revealed a connection of (receiver) order fairness to social choice theory and related impossibility results arising from the Condorcet paradox. As a result of the impossibility, various relaxations of order fairness were proposed in prior works. Given that distributed ledger protocols, especially those processing smart contracts, must serialize the input transactions, a natural objective is to minimize the distance (in terms of number of transactions) between any pair of unfairly ordered transactions in the output ledger — a concept we call bounded unfairness. In state machine replication (SMR) parlance this asks for minimizing the number of unfair state updates occurring before the processing of any request. This unfairness minimization objective gives rise to a natural class of parametric order fairness definitions that has not been studied before. As we observe, previous realizable relaxations of order fairness do not yield good unfairness bounds. Achieving optimal order fairness in the sense of bounded unfairness turns out to be connected to the graph theoretic properties of the underlying transaction dependency graph and specifically the bandwidth metric of strongly connected components in this graph. This gives rise to a specific instance of the definition that we call “directed bandwidth order-fairness” which we show that it captures the best possible that any ledger protocol can achieve in terms of bounding unfairness. We prove ordering transactions in this fashion is NP-hard and non-approximable for any constant ratio. Towards realizing the property, we put forth a new distributed ledger protocol called Taxis that achieves directed bandwidth order-fairness. We present two variations, one that matches the property perfectly but (necessarily) lacks in performance and liveness, and another that achieves liveness and better complexity while offering a slightly relaxed version of the property. Finally, we comment on applications of our work to social choice, a direction which we believe to be of independent interest

Physiological impacts of groundwater and surface water application on desert graminoids of different geographic origin

Desert plant communities are among the most sensitive to changes in soil water conditions. In areas with shallow aquifers, it is important to understand both the effects of groundwater alterations on vegetation and how changes in surface-soil water affect plant water uptake. Studies in arid environments have evaluated the effect of groundwater variation and simulated precipitation on plant production and vegetation condition but it is not clear if plants respond equally to the availability of surface water or groundwater. This study was conducted in a greenhouse to evaluate growth and physiology of three desert graminoids (Distichlis spicata, Leymus triticoides, and Juncus arcticus) as affected by surface water availability (mimicking precipitation) or subsurface water availability (mimicking groundwater). The species of study are amply distributed in wetlands and open rangelands of western USA and were collected from two sources of ecological distribution: an area near Bishop, California, and an area near Burns, Oregon. The Bishop, California area has a characteristic shallow aquifer and plants in this area are considered somewhat dependent on groundwater. The Burns, Oregon, area sustains the same species but in a variety of soil moisture conditions. We had two general hypotheses for this study: 1) that the use of surface water is favored over groundwater and 2) that there are ecotypic differences in the response of the species to water availability. The first hypothesis was partially supported by the results of the study, but variability existed among species. However, when all species had equal access to both surface soil water and groundwater plants tended to preferentially use surface water. The second hypothesis was clearly supported by our results. Although the mechanism is not clear, it is possible that an area with periodic and predictable shallow groundwater underlying a dry or saline soil layer, such as the California site, might favor plant ecotypes with high proficiency in water acquisition by deeper roots. Knowledge of water use characteristics of vegetation is essential to provide management guidelines for areas where plants depend on both surface-soil water and groundwater. This study contributed to that knowledge. Further studies on ecotypic variation and an expansion to different species that inhabit areas with shallow aquifers are recommended