Optimal control for linear discrete-time systems with persistent disturbances

This paper is concerned with the optimal control problem for a class of linear discrete-time systems affected by external persistent disturbances with known dynamic characteristics but unknown initial conditions. The existence and uniqueness of an optimal control law are proven. A disturbance observer is designed to get a physically realizable controller. To demonstrate the effectiveness of the control scheme, the offshore platform performance is investigated. The simulations are based on the tuned mass damper (TMD) and the active mass damper (AMD) control devices. It is demonstrated that the control scheme is efficient in reducing the displacement response of jacket-type offshore platforms and more robust than the classic state feedback optimal control law with respect to errors produced by the external disturbances

Learning from improvisation in New Ventures

The rapid pace of digitalization forces new ventures to cope with external changes they cannot foresee. Improvisation is a crucial way for companies to respond effectively to sudden changes. However, the mechanisms underlying the improvisation–performance link are not fully understood. This paper focuses on how improvisation affects a firm's performance. We identify two mediators for this relationship: entrepreneurial learning and routines. Our sample includes 243 new ventures in China. The results of structural equation modelling show that learning from improvisation in start-ups contributes to establishing new routines that serve as drivers of firm performance. We discuss the implications for practice and future research.</p

Weighted multi-error information entropy based you only look once network for underwater object detection

Underwater object detection is considered as one of the most challenging issues in computer vision. In this paper, a weighted multi-error information entropy based YOLO (You Only Look Once) network is proposed to address underwater illumination noise affecting the detection accuracy. First, underwater illumination is essentially structural and non-uniform, and it is modeled as an independent and piecewise identical distribution, which is a generic noise model to describe the complex underwater illuminating environment and accommodates the traditional Gaussian distribution as a special case. Second, assisted by the proposed illumination noise model, a minimum weighted error entropy criterion, which is an information-theoretic learning method, is introduced into the loss function of YOLO network, and then the network parameters are trained and optimized to improve the detection performance. Furthermore, a multi-error processing strategy is simultaneously used to handle vector errors during information back-propagation in order to accelerate convergence. Experiments on underwater object detection datasets including URPC2018, URPC2019 and Enhanced dataset, show the proposed weighted multi-error information entropy based YOLOv8 network gets mean average precision (MAP) of 88.7%, 91.8% and 96.7% respectively, and average frames per second (FPS) of 116.6. These two evaluation metrics are better than the baseline YOLOv8 and the existing advanced non-YOLO approaches by at least 5.2% and 5.3% respectively. The results verify the effectiveness and superiority of the proposed network for underwater object detection in complex underwater environment.</p

Enabling Scalable and Unlinkable Payment Channel Hubs with Oblivious Puzzle Transfer

Payment channel networks (PCNs) are effective techniques for extending the scalability of cryptocurrencies. It achieves this by establishing a direct off-line channel from the sender to the receiver, going through one intermediary (aka. the hubs). In such scenarios, the hubs know the origin and destination of each transaction flowing through them, which jeopardizes the privacy of the underlying systems. Unfortunately, former efforts in ensuring transaction unlinkability either rely on trusted mixing services, are inefficient constructed (e.g., constructed inefficient cryptographic primitives), or have limited applicability. In this paper, we present ObliHub, an efficient payment channel scheme that conceals transaction direction information to the hubs. The core technique of ObliHub in achieving unlinkability is our tailored oblivious puzzle transfer protocol (OPT), which enables puzzle solving among the payer, the hub, and the receiver to be conducted in an oblivious manner – the hub center neither knows where a puzzle hint came from nor who acquired it. The implementation of ObliHub only requires efficient cryptographic primitives, and compared with   (a state-of-the-art Bitcoin-compatible PCH using homomorphic encryption), ObliHub saves 0.2 seconds in computation time over previous solutions and improves transfer throughput. Besides, our scheme is in accord with Universal Composability (UC) framework and we provide a comprehensive security analysis of it.</p

SWIPENET: Object detection in noisy underwater scenes

Deep learning based object detection methods have achieved promising performance in controlled environments. However, these methods lack sufficient capabilities to handle underwater object detection due to these challenges: (1) images in the underwater datasets and real applications are blurry whilst accompanying severe noise that confuses the detectors and (2) objects in real applications are usually small. In this paper, we propose a Sample-WeIghted hyPEr Network (SWIPENET), and a novel training paradigm named Curriculum Multi-Class Adaboost (CMA), to address these two problems at the same time. Firstly, the backbone of SWIPENET produces multiple high resolution and semantic-rich Hyper Feature Maps, which significantly improve small object detection. Secondly, inspired by the human education process that drives the learning from easy to hard concepts, we propose the noise-robust CMA training paradigm that learns the clean data first and then move on to learns the diverse noisy data. Experiments on four underwater object detection datasets show that the proposed SWIPENET+CMA framework achieves better or competitive accuracy in object detection against several state-of-the-art approaches.</p

Experimental investigation of dehumidification and regeneration of zeolite coated energy exchanger

Zeolite desiccant particles are well known for their strong affinity to adsorb water vapor molecules; however, they require significant regeneration energy to be created. This paper presents an experimental study of the adsorption and regeneration processes of a monolayer zeolite for indoor dehumidification to the 13X zeolite beads with a 4 × 8 mesh bead size and a pore opening 10 A⁰ were used as this monolayer. An experimental investigation was conducted to determine the effects of the relative humidity, temperature, and air flow rate on the adsorption and regeneration processes. The results show the effectiveness of the monolayer coating method and the relative humidity significantly affects the adsorption process, and that the airflow rate surrounding and through the zeolite beads increases the adsorption and desorption of the water vapor molecules. In the absence of the meniscus radius formation due to the monolayer arrangement prevents external condensation. With an airflow rate of Re = 1773, the full adsorption process at a relative humidity of 99% was obtained within 37 min; meanwhile, the regeneration process proceeded at 100 °C within 66 min. The adsorption time was reduced by 27% and 43% as the Reynold number increases to 2586 and 3325, respectively. Likewise, the effectiveness of the regeneration time is decreased by 0.07% and 14% within the same Reynold number increases. Results obtained from this research can be used to guide the future development of polymer-coated energy exchangers

Endovascular thrombectomy versus standard bridging thrombolytic with endovascular thrombectomy within 4·5 h of stroke onset: an open-label, blinded-endpoint, randomised non-inferiority trial

Background: The benefit of combined treatment with intravenous thrombolysis before endovascular thrombectomy in patients with acute ischaemic stroke caused by large vessel occlusion remains unclear. We hypothesised that the clinical outcomes of patients with stroke with large vessel occlusion treated with direct endovascular thrombectomy within 4·5 h would be non-inferior compared with the outcomes of those treated with standard bridging therapy (intravenous thrombolysis before endovascular thrombectomy). Methods: DIRECT-SAFE was an international, multicentre, prospective, randomised, open-label, blinded-endpoint trial. Adult patients with stroke and large vessel occlusion in the intracranial internal carotid artery, middle cerebral artery (M1 or M2), or basilar artery, confirmed by non-contrast CT and vascular imaging, and who presented within 4·5 h of stroke onset were recruited from 25 acute-care hospitals in Australia, New Zealand, China, and Vietnam. Eligible patients were randomly assigned (1:1) via a web-based, computer-generated randomisation procedure stratified by site of baseline arterial occlusion and by geographic region to direct endovascular thrombectomy or bridging therapy. Patients assigned to bridging therapy received intravenous thrombolytic (alteplase or tenecteplase) as per standard care at each site; endovascular thrombectomy was also per standard of care, using the Trevo device (Stryker Neurovascular, Fremont, CA, USA) as first-line intervention. Personnel assessing outcomes were masked to group allocation; patients and treating physicians were not. The primary efficacy endpoint was functional independence defined as modified Rankin Scale score 0–2 or return to baseline at 90 days, with a non-inferiority margin of –0·1, analysed by intention to treat (including all randomly assigned and consenting patients) and per protocol. The intention-to-treat population was included in the safety analyses. The trial is registered with ClinicalTrials.gov, NCT03494920, and is closed to new participants. Findings: Between June 2, 2018, and July 8, 2021, 295 patients were randomly assigned to direct endovascular thrombectomy (n=148) or bridging therapy (n=147). Functional independence occurred in 80 (55%) of 146 patients in the direct thrombectomy group and 89 (61%) of 147 patients in the bridging therapy group (intention-to-treat risk difference –0·051, two-sided 95% CI –0·160 to 0·059; per-protocol risk difference –0·062, two-sided 95% CI –0·173 to 0·049). Safety outcomes were similar between groups, with symptomatic intracerebral haemorrhage occurring in two (1%) of 146 patients in the direct group and one (1%) of 147 patients in the bridging group (adjusted odds ratio 1·70, 95% CI 0·22–13·04) and death in 22 (15%) of 146 patients in the direct group and 24 (16%) of 147 patients in the bridging group (adjusted odds ratio 0·92, 95% CI 0·46–1·84). Interpretation: We did not show non-inferiority of direct endovascular thrombectomy compared with bridging therapy. The additional information from our study should inform guidelines to recommend bridging therapy as standard treatment. Funding: Australian National Health and Medical Research Council and Stryker USA