Customer Active Probability and Customer Lifetime Value Analysis in Internet

As the age of digital information, marketers are in information overload. A mass of customers’ data is available but may be useless only if it can be turned into business intelligence and implement appropriate database marketing. This research aims to assist managers in discriminating and learning from their right customers that helps to serve high value customers and create successful marketing programs targeted at the prospected ones. Transaction data on the purchasing of VCD at an online retailer was used as empirical analysis; Pareto/NBD model and customer lifetime value model were applied to capture customer active probability and construct profitable customer profile. The results demonstrated four priority ranks of online customers for managers to choose the prospects that best match the profitable customer profile by observing their purchase behaviors

Ovarian cancer classification based on dimensionality reduction for SELDI-TOF data

<p>Abstract</p> <p>Background</p> <p>Recent advances in proteomics technologies such as SELDI-TOF mass spectrometry has shown promise in the detection of early stage cancers. However, dimensionality reduction and classification are considerable challenges in statistical machine learning. We therefore propose a novel approach for dimensionality reduction and tested it using published high-resolution SELDI-TOF data for ovarian cancer.</p> <p>Results</p> <p>We propose a method based on statistical moments to reduce feature dimensions. After refining and <it>t</it>-testing, SELDI-TOF data are divided into several intervals. Four statistical moments (mean, variance, skewness and kurtosis) are calculated for each interval and are used as representative variables. The high dimensionality of the data can thus be rapidly reduced. To improve efficiency and classification performance, the data are further used in kernel PLS models. The method achieved average sensitivity of 0.9950, specificity of 0.9916, accuracy of 0.9935 and a correlation coefficient of 0.9869 for 100 five-fold cross validations. Furthermore, only one control was misclassified in leave-one-out cross validation.</p> <p>Conclusion</p> <p>The proposed method is suitable for analyzing high-throughput proteomics data.</p

Source attack of decoy-state quantum key distribution using phase information

Quantum key distribution (QKD) utilizes the laws of quantum mechanics to achieve information-theoretically secure key generation. This field is now approaching the stage of commercialization, but many practical QKD systems still suffer from security loopholes due to imperfect devices. In fact, practical attacks have successfully been demonstrated. Fortunately, most of them only exploit detection-side loopholes which are now closed by the recent idea of measurement-device-independent QKD. On the other hand, little attention is paid to the source which may still leave QKD systems insecure. In this work, we propose and demonstrate an attack that exploits a source-side loophole existing in qubit-based QKD systems using a weak coherent state source and decoy states. Specifically, by implementing a linear-optics unambiguous-state-discrimination measurement, we show that the security of a system without phase randomization --- which is a step assumed in conventional security analyses but sometimes neglected in practice --- can be compromised. We conclude that implementing phase randomization is essential to the security of decoy-state QKD systems under current security analyses.Comment: 12 pages, 5 figure

Stunting and soil-transmitted-helminth infections among school-age pupils in rural areas of southern China

<p>Abstract</p> <p>Background</p> <p>Stunting and soil-transmitted helminth (STH) infections including ascariasis, trichuriasis and hookworm remain major public health problems in school-age pupils in developing countries. The objectives of this study were to determine the prevalence of stunting for children and its association with three major soil-transmitted helminths (STH) in rural areas of southern China. The study also aims to determine risk factors for stunting and to provide guidance on the prevention and control of stunting and STH infections for future studies in this field.</p> <p>Results</p> <p>A cross-sectional survey was carried out in the poor rural areas in Guangxi Autonomous Regional and Hainan Province where STH prevalence was higher between September and November 2009. Pupils were from 15 primary schools. All the school-age pupils aged between 9 and 12 years old (mean age 11.2 ± 3.2 years), from grades three to six took part in this study. Study contents include questionnaire surveys, physical examination and laboratory methods (stool checking for eggs of three major STH infections and haemoglobin determination was performed for the anaemia test). Finally 1031 school-age pupils took part in survey. The results showed that the overall prevalence of stunting (HAZ < 2SD) was 25.6%, based on the WHO Child Growth Standards (2007). Risk factors for stunting based on logistic regression analyses were: (1) STH moderate-to-heavy intensity infections (OR = 1.93;95%CI:1.19,3.11); (2) anaemia (OR = 3.26;95%CI: 2.02,5.27); (3) education level of mother (OR = 2.13; 95%CI: 1.39,3.25). The overall prevalence of major STH infections was 36.7%, STH moderate-to-heavy intensity infections was 16.7%. The overall prevalence of ascariasis, trichuriasis, hookworm and co-infection were 18.5%, 11.2%, 14.7% and 9.1% respectively. The prevalence of anaemic children (HB < 12 g/dl) was 13.1%.</p> <p>Conclusion</p> <p>The present study showed that stunting was highly prevalent among the study population and STH infection is one of the important risk factors for stunting, with moderate-to-heavy intensity infections being the main predictor of stunting. Hence, additional interventions measures such as to promote de-worming treatment, to enhance health education and to improve hygiene and sanitation in order to reduce stunting in this population, are needed throughout the primary school age group.</p