Effectiveness of Mobile Phone Customer Retention Strategies

Using the 419,194 customers of a mobile operator as the sample, this research investigates the effectiveness of the company’s retention strategies. It examines the effect of such strategies on extending customer life cycle. We find that the retention policies and the incremental average revenue per user (ARPU) in the retention period over the month prior are positively correlated. In addition, the correlation between the retention polices and the increments of consumer consumption variables, such as the number of calls, the number of short messages and the value-added services, are also positive. Moreover, the significantly positive interaction terms between the retention bonus and the consumption increments suggest that the bonus affects the relative ARPU through the consumption variables. Finally, the retention strategies demonstrate the different effectiveness according to the three different calling plans. The managerial implications of our findings are discussed

Data-driven offline learning approach for excavating control of cutter suction dredgers

Cutter suction dredgers (CSDs) play a very important role in the construction of ports, waterways and navigational channels. Currently, most of CSDs are mainly manipulated by human operators, and a large amount of instrument data needs to be monitored in real time in case of unforeseen accidents. In order to reduce the heavy workload of the operators, we propose a data-driven offline learning approach, named Preprocessing-Prediction-Learning Control (PPLC), for obtaining the optimal control policy of the excavating operation of CSDs. The proposed framework consists of three modules, i.e., a data preprocessing module, a dynamics prediction module realized by a Convolutional Neural Network (CNN), and a deep reinforcement learning based control module. The first module is responsible for filtering out irrelevant variables through correlation analysis and dimensionality reduction of raw data. The second module works as a state transition function that provides the dynamics prediction of the excavating operation of a CSD. To realize the learning control, the third module employs the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm to control the swing speed during the excavating operation. The simulation results show that the proposed framework can provide an effective and reliable solution to the automated excavating control of a CSD

学会抄録

Details for the selection of physicochemical properties from AAIndex database. (DOC 31 kb

OpenSARUrban: A Sentinel-1 SAR Image Dataset for Urban Interpretation

Sentinel-1 mission provides a freely accessible opportunity for urban interpretation from synthetic aperture radar (SAR) images with specific resolution, which is of paramount importance for earth observation. In parallel, with the rapid development of advanced technologies, especially deep learning, it is urgently needed to construct a large-scale SAR dataset leading urban interpretation. This paper presents OpenSARUrban: a Sentinel-1 dataset dedicated to urban interpretation from SAR images, including a well-defined hierarchical annotation scheme, the data collection, the well-established procedures for dataset construction and organizations, the properties, visualizations, and applications of this dataset. Particularly, the OpenSARUrban provides 33358 image patches of SAR urban scene, covering 21 major cities of China, including 10 different categories, 4 kinds of formats, 2 kinds of polarization modes, and owning 5 essential properties: large-scale, diversity, specificity, reliability, and sustainability. These properties guarantee the achievable of several goals for OpenSARUrban. The first is to support urban target characterization. The second is to help develop applicable and advanced algorithms for Sentinel-1 urban target classification. The dataset visualization is implemented from the perspective of manifold to give an intuitive understanding. Besides a detailed description and visualization of the dataset, we present results of some benchmark algorithms, demonstrating that this dataset is practical and challenging. Notably, developing algorithms to enhance the classification performance on the whole dataset and considering the data imbalance are especially challenging

Research on the influence of fuel detergent synergist on engine fuel supply system

This paper selects 6 gasoline detergent synergists and 6 diesel detergent synergists that are mainstream in the market. The changes in mass, volume, hardness, size and surface morphology of the main components of the engine fuel supply system after being immersed in fuel containing detergent synergists for 28 days were studied,and these changes are compared with the benchmark fuel. The results show that most of the fuel detergent synergists have almost no corrosive effect on the engine fuel supply system components or are close to the reference fuel, but some gasoline detergent synergists have a slight corrosive swelling effect on the gasoline fuel supply system

Metal-insulator transition in vanadium dioxide nanobeams: probing sub-domain properties of strongly correlated materials

Many strongly correlated electronic materials, including high-temperature superconductors, colossal magnetoresistance and metal-insulator-transition (MIT) materials, are inhomogeneous on a microscopic scale as a result of domain structure or compositional variations. An important potential advantage of nanoscale samples is that they exhibit the homogeneous properties, which can differ greatly from those of the bulk. We demonstrate this principle using vanadium dioxide, which has domain structure associated with its dramatic MIT at 68 degrees C. Our studies of single-domain vanadium dioxide nanobeams reveal new aspects of this famous MIT, including supercooling of the metallic phase by 50 degrees C; an activation energy in the insulating phase consistent with the optical gap; and a connection between the transition and the equilibrium carrier density in the insulating phase. Our devices also provide a nanomechanical method of determining the transition temperature, enable measurements on individual metal-insulator interphase walls, and allow general investigations of a phase transition in quasi-one-dimensional geometry.Comment: 9 pages, 3 figures, original submitted in June 200

Effect of diesel detergent synergists on VOCs emissions from engine

In this study, the volatile organic compounds (VOCs) emissions from engine fueled diesel with and without detergent synergist were measured by gas chromatography mass spectrometry(GC-MS). The test results show that compared with reference diesel fuel (without diesel detergent synergist), the use of different diesel detergent synergists has different effects on the VOCs emissions while without after-treatment device. Whether with or without after-treatment device, alkanes always account for the highest proportion of VOCs emissions while engine fuels with different diesel detergent synergists. After-treatment device diesel oxidation catalyst coupled with diesel particulate filter (DOC+DPF) has high catalytic efficiency for VOCs emissions from engine fueled with different fuels, and most of the catalytic efficiency could reach more than 95%. With the catalytic treatment of after-treatment device,the concentrations of carcinogens (detected in this study) in VOCs emissions from engine fueled with and without detergent synergist are far lower than that specified in reference standard GBZ 2.1-2007 “Occupational Exposure Limits for Hazardous Factors in the Workplace and Chemical Hazardous Factors”, respectively. The test results indicate that the use of diesel detergent synergist will not have an adverse impact on human health and it can be safely used

Development and validation of a novel necroptosis-related gene signature for predicting prognosis and therapeutic response in Ewing sarcoma

Ewing sarcoma (ES) is the second most common malignant bone tumor in children and has a poor prognosis due to early metastasis and easy recurrence. Necroptosis is a newly discovered cell death method, and its critical role in tumor immunity and therapy has attracted widespread attention. Thus, the emergence of necroptosis may provide bright prospects for the treatment of ES and deserves our further study. Here, based on the random forest algorithm, we identified 6 key necroptosis-related genes (NRGs) and used them to construct an NRG signature with excellent predictive performance. Subsequent analysis showed that NRGs were closely associated with ES tumor immunity, and the signature was also good at predicting immunotherapy and chemotherapy response. Next, a comprehensive analysis of key genes showed that RIPK1, JAK1, and CHMP7 were potential therapeutic targets. The Cancer Dependency Map (DepMap) results showed that CHMP7 is associated with ES cell growth, and the Gene Set Cancer Analysis (GSCALite) results revealed that the JAK1 mutation frequency was the highest. The expression of 3 genes was all negatively correlated with methylation and positively with copy number variation (CNV). Finally, an accurate nomogram was constructed with this signature and clinical traits. In short, this study constructed an accurate prognostic signature and identified 3 novel therapeutic targets against ES

Ethnic discordance in serum anti-Müllerian hormone in healthy women: a population study from China and Europe

Research question: Chinese women are known to have an earlier age of natural menopause than their European counterparts, but whether they also have a lower functional ovarian reserve is unknown. This study was designed to assess whether there are ethnic differences in anti-Müllerian hormone (AMH) concentrations in women of reproductive age. Design: Women in China and Europe with regular menstrual cycles, not on hormonal contraception and with no medical history of note, were recruited to provide a day 2–5 early follicular phase sample. AMH concentration was determined using the Roche Elecsys assay. Decline in AMH was modelled with linear, quadratic and quadratic with interaction on age equations to assess the impact of ethnicity. Results: A total of 887 European and 461 Chinese women participated in the study. Despite the Chinese population being slightly younger (34.1 ± 8.4 years) than their European counterparts (34.8±8.9 years), their median AMH was lower, at 1.87 ng/ml (interquartile range [IQR] 0.28–3.64) compared with 2.11 ng/ml (IQR 0.73–3.96), with evidence of increasing discordance from age 25 years. In all regression models of the age-related decline in AMH, there was evidence of a difference between Chinese and European women. Although AMH was 28.1% (95% confidence interval [CI] 18.2–36.7%) lower in the Chinese population at age 30, this decline increased to 79.4% (95% CI 75.4– 82.9%) at age 45. Conclusions: There were independent effects of age and ethnicity on serum AMH concentrations, with Chinese women having a substantially lower AMH in adult life than their European counterparts from age 25 onwards