Privacy-Preserving Data Mining and Analytics in Big Data

Privacy concerns have gotten more attention as Big Data has spread. The difficulties of striking a balance between the value of data and individual privacy have led to the emergence of privacy-preserving data mining and analytics approaches as a crucial area of research. An overview of the major ideas, methods, and developments in privacy-preserving data mining and analytics in the context of Big Data is given in this abstract. Data mining that protects privacy tries to glean useful insights from huge databases while shielding the private data of individuals. Commonly used in traditional data mining methods, sharing or pooling data might have serious privacy implications. On the other hand, privacy-preserving data mining strategies concentrate on creating procedures and algorithms that enable analysis without jeopardizing personal information. Finally, privacy-preserving data mining and analytics in the Big Data age bring important difficulties and opportunities. An overview of the main ideas, methods, and developments in privacy-preserving data mining and analytics are given in this abstract. It underscores the value of privacy in the era of data-driven decision-making and the requirement for effective privacy-preserving solutions to safeguard sensitive personal data while facilitating insightful analysis of huge datasets

Stabilization of residual soil with rice husk ash and cement

Stabilization of residual soils is studied by chemically using cement and rice husk ash. Investigation includes the evaluation of such properties of the soil as compaction, strength, and X-ray diffraction. Test results show that both cement and rice husk ash reduce the plasticity of soils. In term of compactability, addition of rice husk ash and cement decreases the maximum dry density and increases the optimum moisture content. From the viewpoint of plasticity, compaction and strength characteristics, and economy, addition of 6-8 cement and 10-15 rice husk ash is recommended as an optimum amount

Privacy-Preserving Data Mining and Analytics in Big Data

Privacy concerns have gotten more attention as Big Data has spread. The difficulties of striking a balance between the value of data and individual privacy have led to the emergence of privacy-preserving data mining and analytics approaches as a crucial area of research. An overview of the major ideas, methods, and developments in privacy-preserving data mining and analytics in the context of Big Data is given in this abstract. Data mining that protects privacy tries to glean useful insights from huge databases while shielding the private data of individuals. Commonly used in traditional data mining methods, sharing or pooling data might have serious privacy implications. On the other hand, privacy-preserving data mining strategies concentrate on creating procedures and algorithms that enable analysis without jeopardizing personal information. Finally, privacy-preserving data mining and analytics in the Big Data age bring important difficulties and opportunities. An overview of the main ideas, methods, and developments in privacy-preserving data mining and analytics are given in this abstract. It underscores the value of privacy in the era of data-driven decision-making and the requirement for effective privacy-preserving solutions to safeguard sensitive personal data while facilitating insightful analysis of huge datasets

Impact of lifestyle and dietary habits on hypovitaminosis D in type 1 diabetes mellitus and healthy children from Qatar, a sun-rich country

Background: There are no population-based studies that have examined the association between vitamin D and type 1 diabetes mellitus (T1DM) and the role of lifestyle habits and dietary factors in young children in the Arabian Gulf and Middle East region. Little data on the intake of these nutrients in Mediterranean countries exist, and predictors of their suboptimal intake are not well defined. Objective: The objective of this study was to determine the association between vitamin D status and T1DM and assess the impact of lifestyle and dietary habits on hypovitaminosis D in the young population of the State of Qatar. A matched case-control study was carried out among T1DM children and healthy subjects <16 years of age at the pediatric endocrinology outpatient clinics of the Hamad General Hospital and the primary health care clinics center. The survey was conducted over a period from 6 August to 25 December 2007. The sample included 170 cases and 170 controls matched by age, gender and ethnicity. Methods: Face to face interviews were based on a questionnaire that included variables such as sociodemographic information, assessment of non-dietary covariates, assessment of dietary intake including vitamin D, type of feeding, clinical manifestations and laboratory investigations. Their health status was assessed by medical conditions, family history, body mass index, past or present clinical manifestations, serum 25(OH) vitamin D, calcium, alkaline phosphates, phosphorus, hemoglobin A1C, parathyroid hormone, magnesium and creatinine analysis. Results: The study revealed that the incidence of severe vitamin D deficiency was considerably higher in T1DM (28.8%) compared with healthy children (17.1%). Although the mean serum level of vitamin D was significantly lower in T1DM children (15.80 ± 9.23 ng/ml), compared with nondiabetic children (18.45 ± 9.56 ng/ml), both groups belonged to the mild-moderate vitamin D deficiency category. A family history of vitamin D deficiency (35.3%; p = 0.012) and diabetes mellitus (56.5%; p < 0.001) was significantly higher in diabetic children. More than half of the diabetic (67.1%) and healthy children (51.2%) had no physical activity in their daily life. Both groups (65.9 vs. 62.9%) had very limited exposure to sunlight. Vitamin D supplement intake was very poor in diabetic children compared with healthy children; 60% of diabetic and 40.6% of healthy children never had any vitamin D supplement. The study revealed that vitamin D serum concentration, phosphorus, hemoglobin A1C, magnesium and creatinine show statistically significant differences between T1DM and healthy control subjects. A significant difference was noted between diabetic and healthy children for fractures (p = 0.005), weakness (p = 0.001) and gastroenteritis (p = 0.025). Conclusions: The present study revealed that vitamin D deficiency is a common problem in Qatari children, but the incidence of vitamin D deficiency becomes very severe in T1DM children, compared with healthy children. This suggests that there is an association between vitamin D deficiency and T1DM. The data show that vitamin D status is dependent on sunshine exposure and dietary vitamin D intake. The results suggest the necessity of nutrition education to promote healthy eating habits among adolescents and their parents

Supplementary Material for: Early Hemodynamic Changes during Head-Up Tilt Table Testing Can Predict a Neurocardiogenic Response in an African-American Patient Population

<b><i>Background:</i></b> Head-up tilt table testing (HUTT) is time-consuming and associated with increased patient morbidity. Hemodynamic changes that occur during the early phase of HUTT may be predictive of neurocardiogenic syncope. <b><i>Methods:</i></b> A retrospective chart review was performed in 119 consecutive African Americans ( 57 ± 19) who underwent HUTT for evaluation of syncope of unknown etiology. Positive responses were defined as the development of symptoms linked with a systolic blood pressure (BP) <90 mm Hg, heart rate <50 b.p.m. or sinus arrest >3 s. Hemodynamic variables during the passive phase of HUTT were analyzed and results were then classified as a function of various predictors. <b><i>Results:</i></b> Sixty-two subjects (52%) had positive HUTT, and 57 (48%) had negative HUTT. Early changes in BP variables from baseline significantly predicted HUTT responses (p < 0.05). There was also a significant interaction between age and BP. An algorithm based on age and BP was developed which had positive and negative predictive values of 67.7 and 93%, respectively, with an accuracy of 79.8%. <b><i>Conclusion:</i></b> A novel algorithm utilizing the patients' age and changes in both systolic and diastolic BP during the early phase of HUTT enables the prediction of HUTT results without the use of vasoactive stimulation, allowing for rapid diagnosis, decreased patient morbidity and reduction in costs