Optimal algorithms for the online time series search problem

AbstractIn the problem of online time series search introduced by El-Yaniv et al. (2001) [1], a player observes prices one by one over time and shall select exactly one of the prices on its arrival without the knowledge of future prices, aiming to maximize the selected price. In this paper, we extend the problem by introducing profit function. Considering two cases where the search duration is either known or unknown beforehand, we propose two optimal deterministic algorithms respectively. The models and results in this paper generalize those of El-Yaniv et al. (2001) [1]

Cross-Layer Active Predictive Congestion Control Protocol for Wireless Sensor Networks

In wireless sensor networks (WSNs), there are numerous factors that may cause network congestion problems, such as the many-to-one communication modes, mutual interference of wireless links, dynamic changes of network topology and the memory-restrained characteristics of nodes. All these factors result in a network being more vulnerable to congestion. In this paper, a cross-layer active predictive congestion control scheme (CL-APCC) for improving the performance of networks is proposed. Queuing theory is applied in the CL-APCC to analyze data flows of a single-node according to its memory status, combined with the analysis of the average occupied memory size of local networks. It also analyzes the current data change trends of local networks to forecast and actively adjust the sending rate of the node in the next period. In order to ensure the fairness and timeliness of the network, the IEEE 802.11 protocol is revised based on waiting time, the number of the node's neighbors and the original priority of data packets, which dynamically adjusts the sending priority of the node. The performance of CL-APCC, which is evaluated by extensive simulation experiments. is more efficient in solving the congestion in WSNs. Furthermore, it is clear that the proposed scheme has an outstanding advantage in terms of improving the fairness and lifetime of networks

General Predictive Framework for Droplet Detachment Force

Liquid droplets hanging from solid surfaces are commonplace, but their physics is complex. Examples include dew or raindrops hanging onto wires or droplets accumulating onto a cover placed over warm food or windshields. In these scenarios, determining the force of detachment is crucial to rationally design technologies. Despite much research, a quantitative theoretical framework for detachment force remains elusive. In response, we interrogated the elemental droplet surface system via comprehensive laboratory and computational experiments. The results reveal that the Young Laplace equation can be utilized to accurately predict the droplet detachment force. When challenged against experiments with liquids of varying properties and droplet sizes, detaching from smooth and microtextured surfaces of wetting and non wetting chemical makeups, the predictions were in an excellent quantitative agreement. This study advances the current understanding of droplet physics and will contribute to the rational development of technologies

Liquefaction identification based on instantaneous H/V spectrum ratio

The strong vibration record contains a lot of information on the site during the earthquake, and the dynamic characteristics of the soil layer in the site can be expressed through this information. Currently, the H/V spectral ratio recorded by acceleration is often used to study the seismic effect of the site. Inspired by this, the thesis puts forward the idea of using the instantaneous H/V spectral ratio and its corresponding instantaneous frequency to judge the site liquefaction. The time-varying VARMA model is used to represent the horizontal ground motion component as the output of a time-varying system with vertical ground motion component as input. According to the time-varying VARMA parameters, the instantaneous spectral ratio, instantaneous frequency of the system and instantaneous damping ratio are used to judge the site liquefaction