Optimizing Average-Maximum TTR Trade-off for Cognitive Radio Rendezvous

In cognitive radio (CR) networks, "TTR", a.k.a. time-to-rendezvous, is one of the most important metrics for evaluating the performance of a channel hopping (CH) rendezvous protocol, and it characterizes the rendezvous delay when two CRs perform channel hopping. There exists a trade-off of optimizing the average or maximum TTR in the CH rendezvous protocol design. On one hand, the random CH protocol leads to the best "average" TTR without ensuring a finite "maximum" TTR (two CRs may never rendezvous in the worst case), or a high rendezvous diversity (multiple rendezvous channels). On the other hand, many sequence-based CH protocols ensure a finite maximum TTR (upper bound of TTR) and a high rendezvous diversity, while they inevitably yield a larger average TTR. In this paper, we strike a balance in the average-maximum TTR trade-off for CR rendezvous by leveraging the advantages of both random and sequence-based CH protocols. Inspired by the neighbor discovery problem, we establish a design framework of creating a wake-up schedule whereby every CR follows the sequence-based (or random) CH protocol in the awake (or asleep) mode. Analytical and simulation results show that the hybrid CH protocols under this framework are able to achieve a greatly improved average TTR as well as a low upper-bound of TTR, without sacrificing the rendezvous diversity.Comment: Accepted by IEEE International Conference on Communications (ICC 2015, http://icc2015.ieee-icc.org/

Performance Investigation of CHP Equipment

The Cooling Heating & Power systems for Buildings (BCHP) are attracting more attention due to their advantages as compared to conventional energy systems. As a developing technology, there are still problems to be solved. Fuel flexibility and dynamic response between different machines in the system are two of the main issues to be investigated. This study presents research conducted on a BCHP system that is composed of a microturbine, an absorption chiller and a solid desiccant unit that are driven by the microturbine's exhaust gas to provide cooling and dehumidification. It demonstrates the feasibility of operating the microturbine that is originally designed for natural gas on propane and analyzes the reasons for the efficiency reduction when operating on propane. It further presents a model that describes the transient behavior of the absorption chiller, which requires a much longer period to reach its steady state compared with the microturbine

Research on Warnings with New Thought of Neuro-IE

AbstractSafety production is a seriously stubborn problem in modern industry engineering. Warnings, as the most fundamental and important measure used in safety management, especially in Mine Exploitation, have played a vital role in risk cognition, behaviors guide and accidents prevention. However, traditional researches are so subjective that it's hard to deeply explore the inner mechanism and process, which has been hidden behind the outer behaviors. As a result, the effectiveness of Warnings is much discounted. In this paper, we make use of neuroscience methods to study Warnings from the basically cognitive levels and have acquired preliminary achievements, which provide new evidence, discussion and introductions for former researches

SyNDock: N Rigid Protein Docking via Learnable Group Synchronization

The regulation of various cellular processes heavily relies on the protein complexes within a living cell, necessitating a comprehensive understanding of their three-dimensional structures to elucidate the underlying mechanisms. While neural docking techniques have exhibited promising outcomes in binary protein docking, the application of advanced neural architectures to multimeric protein docking remains uncertain. This study introduces SyNDock, an automated framework that swiftly assembles precise multimeric complexes within seconds, showcasing performance that can potentially surpass or be on par with recent advanced approaches. SyNDock possesses several appealing advantages not present in previous approaches. Firstly, SyNDock formulates multimeric protein docking as a problem of learning global transformations to holistically depict the placement of chain units of a complex, enabling a learning-centric solution. Secondly, SyNDock proposes a trainable two-step SE(3) algorithm, involving initial pairwise transformation and confidence estimation, followed by global transformation synchronization. This enables effective learning for assembling the complex in a globally consistent manner. Lastly, extensive experiments conducted on our proposed benchmark dataset demonstrate that SyNDock outperforms existing docking software in crucial performance metrics, including accuracy and runtime. For instance, it achieves a 4.5% improvement in performance and a remarkable millionfold acceleration in speed

Risk factors for high-altitude headache upon acute high-altitude exposure at 3700 m in young Chinese men: a cohort study.

BackgroundThis prospective and observational study aimed to identify demographic, physiological and psychological risk factors associated with high-altitude headache (HAH) upon acute high-altitude exposure.MethodsEight hundred fifty subjects ascended by plane to 3700 m above Chengdu (500 m) over a period of two hours. Structured Case Report Form (CRF) questionnaires were used to record demographic information, physiological examinations, psychological scale, and symptoms including headache and insomnia a week before ascending and within 24 hours after arrival at 3700 m. Binary logistic regression models were used to analyze the risk factors for HAH.ResultsThe incidence of HAH was 73.3%. Age (p =0.011), physical labor intensity (PLI) (p =0.044), primary headache history (p <0.001), insomnia (p <0.001), arterial oxygen saturation (SaO2) (p =0.001), heart rate (HR) (p =0.002), the Self-Rating Anxiety Scale (SAS) (p <0.001), and the Epworth Sleepiness Scale (ESS) (p <0.001) were significantly different between HAH and non-HAH groups. Logistic regression models identified primary headache history, insomnia, low SaO2, high HR and SAS as independent risk factors for HAH.ConclusionsInsomnia, primary headache history, low SaO2, high HR, and high SAS score are the risk factors for HAH. Our findings will provide novel avenues for the study, prevention and treatment of HAH