A Survey on Soft Subspace Clustering

Subspace clustering (SC) is a promising clustering technology to identify clusters based on their associations with subspaces in high dimensional spaces. SC can be classified into hard subspace clustering (HSC) and soft subspace clustering (SSC). While HSC algorithms have been extensively studied and well accepted by the scientific community, SSC algorithms are relatively new but gaining more attention in recent years due to better adaptability. In the paper, a comprehensive survey on existing SSC algorithms and the recent development are presented. The SSC algorithms are classified systematically into three main categories, namely, conventional SSC (CSSC), independent SSC (ISSC) and extended SSC (XSSC). The characteristics of these algorithms are highlighted and the potential future development of SSC is also discussed.Comment: This paper has been published in Information Sciences Journal in 201

Fault Diagnosis of Rotating Machinery Bearings Based on Improved DCNN and WOA-DELM

A bearing is a critical component in the transmission of rotating machinery. However, due to prolonged exposure to heavy loads and high-speed environments, rolling bearings are highly susceptible to faults, Hence, it is crucial to enhance bearing fault diagnosis to ensure safe and reliable operation of rotating machinery. In order to achieve this, a rotating machinery fault diagnosis method based on a deep convolutional neural network (DCNN) and Whale Optimization Algorithm (WOA) optimized Deep Extreme Learning Machine (DELM) is proposed in this paper. DCNN is a combination of the Efficient Channel Attention Net (ECA-Net) and Bi-directional Long Short-Term Memory (BiLSTM). In this method, firstly, a DCNN classification network is constructed. The ECA-Net and BiLSTM are brought into the deep convolutional neural network to extract critical features. Next, the WOA is used to optimize the weight of the initial input layer of DELM to build the WOA-DELM classifier model. Finally, the features extracted by the Improved DCNN (IDCNN) are sent to the WOA-DELM model for bearing fault diagnosis. The diagnostic capability of the proposed IDCNN-WOA-DELM method was evaluated through multiple-condition fault diagnosis experiments using the CWRU-bearing dataset with various settings, and comparative tests against other methods were conducted as well. The results indicate that the proposed method demonstrates good diagnostic performance

A Design for a Lithium-Ion Battery Pack Monitoring System Based on NB-IoT-ZigBee

With environmental issues arising from the excessive use of fossil fuels, clean energy has gained widespread attention, particularly the application of lithium-ion batteries. Lithium-ion batteries are integrated into various industrial products, which necessitates higher safety requirements. Narrowband Internet of Things (NB-IoT) is an LPWA (Low Power Wide Area Network) technology that provides IoT devices with low-power, low-cost, long-endurance, and wide-coverage wireless connectivity. This study addresses the shortcomings of existing lithium-ion battery pack detection systems and proposes a lithium-ion battery monitoring system based on NB-IoT-ZigBee technology. The system operates in a master-slave mode, with the subordinate module collecting and fusing multi-source sensor data, while the master control module uploads the data to local monitoring centers and cloud platforms via TCP and NB-IoT. Experimental validation demonstrates that the design functions effectively, accomplishing the monitoring and protection of lithium-ion battery packs in energy storage power stations

Modulation of Excited State Property Based on Benzo[a, c]phenazine Acceptor: Three Typical Excited States and Electroluminescence Performance

Throwing light upon the structure-property relationship of the excited state properties for next-generation fluorescent materials is crucial for the organic light emitting diode (OLED) field. Herein, we designed and synthesized three donor-acceptor (D-A) structure compounds based on a strong spin orbit coupling (SOC) acceptor benzo[a, c]phenazine (DPPZ) to research on the three typical types of excited states, namely, the locally-excited (LE) dominated excited state (CZP-DPPZ), the hybridized local and charge-transfer (HLCT) state (TPA-DPPZ), and the charge-transfer (CT) dominated state with TADF characteristics (PXZ-DPPZ). A theoretical combined experimental research was adopted for the excited state properties and their regulation methods of the three compounds. Benefiting from the HLCT character, TPA-DPPZ achieves the best non-doped device performance with maximum brightness of 61,951 cd m−2 and maximum external quantum efficiency of 3.42%, with both high photoluminescence quantum efficiency of 40.2% and high exciton utilization of 42.8%. Additionally, for the doped OLED, PXZ-DPPZ can achieve a max EQE of 9.35%, due to a suppressed triplet quenching and an enhanced SOC

Temporal Factors and Missed Doses of Tuberculosis Treatment: A Causal Associations Approach to Analyses of Digital Adherence Data

Rationale: Tuberculosis treatment lasts for 6 months or more. Treatment adherence is critical; regimen length, among other factors, makes this challenging. Globally, analyses mapping common types of nonadherence are lacking. For example, is there a greater challenge resulting from early treatment cessation (discontinuation) or intermittent missed doses (suboptimal dosing implementation)? This is essential knowledge for the development of effective interventions and more "forgiving" regimens, as well as to direct national tuberculosis programs.Objectives: To granularly describe how patients take their tuberculosis medication and the temporal factors associated with missed doses.Methods: The present study included patients with pulmonary tuberculosis enrolled in the control arm of a pragmatic, cluster-randomized trial in China of electronic reminders to improve treatment adherence. Treatment was the standard 6-month course (180 d), dosed every other day (90 doses). Medication monitor boxes recorded adherence (box opening) without prompting reminders. Patterns of adherence were visualized and described. Mixed-effects logistic regression models examined the temporal factors associated with per-dose suboptimal dosing implementation, adjusting for clustering within a participant. Cox regression models were used to examine the association between early suboptimal dosing implementation and permanent discontinuation.Results: Across 780 patients, 16,794 (23.9%) of 70,200 doses were missed, 9,487 of which were from suboptimal dosing implementation (56.5%). By 60 days, 5.1% of participants had discontinued, and 14.4% had discontinued by 120 days. Most participants (95.9%) missed at least one dose. The majority of gaps were of a single dose (71.4%), although 22.6% of participants had at least one gap of 2 weeks or more. In adjusted models, the initiation-continuation phase transition (odds ratio, 3.07 [95% confidence interval, 2.68-3.51]) and national holidays (1.52 [1.39-1.65]) were associated with increased odds of suboptimal dosing implementation. Early-stage suboptimal dosing implementation was associated with increased discontinuation rates.Conclusions: Digital tools provide an unprecedented step change in describing and addressing nonadherence. In our setting, nonadherence was common; patients displayed a complex range of patterns. Dividing nonadherence into suboptimal dosing implementation and discontinuation, we found that both increased over time. Discontinuation was associated with early suboptimal dosing implementation. These apparent causal associations between temporal factors and nonadherence present opportunities for targeted interventions.Clinical trial registered with the ISRCTN Registry (ISRCTN46846388)

Laser in Glaucoma and Ocular Hypertension Trial (LIGHT) in China - A Randomized Controlled Trial: Design and Baseline Characteristics

PURPOSE: To describe the baseline characteristics of a trial to evaluate whether selective laser trabeculoplasty (SLT), as a first-line treatment, provides superior economic and health-related quality of life outcomes to medical treatment in China. DESIGN: The LiGHT China trial is an unmasked, single-center, pragmatic, randomized controlled trial. METHODS: A total of 771 previously undiagnosed patients with primary open angle glaucoma (POAG, 622 patients) or ocular hypertension (OHT, 149 patients) at Zhongshan Ophthalmic Center were recruited from March 2015 to January 2019. Subjects were randomized to SLT-1st (followed by medication then surgery when required) or Medicine-1st (medication followed by surgery when required). The primary outcome was health-related quality of life (HRQL). The secondary outcomes were clinical outcomes, cost, cost-effectiveness, Glaucoma Utility Index, Glaucoma Symptom Scale, visual function, and safety. RESULTS: The mean age of POAG patients was 49.8 years and 38.8 years for OHT. The median intraocular pressure was 20 mm Hg for the 1,105 POAG eyes and 24 mm Hg for the 271 OHT eyes. POAG eyes had thinner central cornea thickness (CCT, 536 µm) than OHT eyes (545 µm). Median mean deviation of the visual field in POAG eyes was -4.2 dB. Median refractive error was -1.5 D for OHT eyes and -1.25 D for POAG eyes. There was no difference between POAG and OHT patients on baseline scores of GUI, GSS and VF-14. The difference between OHT and POAG on the EQ-5D-5L was 0.024. CONCLUSIONS: Compared with participants in the LiGHT UK trial, participants in this trial were younger, more myopic and had more severe visual field defects

Evaluation of a medication monitor-based treatment strategy for drug-sensitive tuberculosis patients in China: study protocol for a cluster randomised controlled trial.

BACKGROUND: Treatment for drug-sensitive tuberculosis (TB) is taken for at least 6 months and problems with adherence are common. Therefore, there is substantial interest in the possible use of eHealth interventions to support patients to take their treatment. Electronic medication monitors have been shown to improve adherence to TB medication, but the impact on clinical outcomes is unknown. We aim to evaluate the impact of a medication monitor-based treatment strategy for drug-sensitive TB patients on a composite poor outcome measured over 18 months from start of TB treatment. METHODS/DESIGN: We will conduct an open, pragmatic, cluster randomised superiority trial, with 24 counties/districts in three provinces in China, randomised 1:1 to implement the intervention or standard of care. Adults (aged ≥ 18 years) with a new episode of GeneXpert-positive and rifampicin-sensitive pulmonary TB, who plan to be in the study area for the next 18 months, and will receive daily fixed-dose combination tablets for 6 months of treatment are eligible. The intervention is centred around a medication monitor that holds a 1-month supply of medication and has three key functions: as an audio and visual reminder for patients to take their daily medication; reminds patients of upcoming monthly visit; and records date and time whenever the box is opened. At the monthly follow-up visit, the doctor downloads these data to generate a graphical display of the last month's adherence record for discussion with the patient and potentially to switch the patient to more intensive management. The primary outcome is a composite poor outcome measured over 18 months from start of TB treatment, defined as either of poor outcome at the end of treatment (death, treatment failure, or loss to follow-up) or subsequent recurrence (culture positive for TB at 12 or 18 months or re-starting TB treatment in the follow-up period). An economic evaluation will also be conducted as part of this study. DISCUSSION: This trial will assess whether a medication monitor-based treatment strategy can improve clinical outcomes for TB patients. Several trials of other eHealth interventions for TB treatment are ongoing and are summarised in this paper. This trial will provide an important part of the emerging evidence base for the potential of eHealth to improve TB treatment outcomes. TRIAL REGISTRATION: This trial was registered with Current Controlled Trials (identifier: ISRCTN35812455 ). Registered on May 19, 2016