Disk failure prediction based on multi-layer domain adaptive learning

Large scale data storage is susceptible to failure. As disks are damaged and replaced, traditional machine learning models, which rely on historical data to make predictions, struggle to accurately predict disk failures. This paper presents a novel method for predicting disk failures by leveraging multi-layer domain adaptive learning techniques. First, disk data with numerous faults is selected as the source domain, and disk data with fewer faults is selected as the target domain. A training of the feature extraction network is performed with the selected origin and destination domains. The contrast between the two domains facilitates the transfer of diagnostic knowledge from the domain of source and target. According to the experimental findings, it has been demonstrated that the proposed technique can generate a reliable prediction model and improve the ability to predict failures on disk data with few failure samples

An improved CTGAN for data processing method of imbalanced disk failure

To address the problem of insufficient failure data generated by disks and the imbalance between the number of normal and failure data. The existing Conditional Tabular Generative Adversarial Networks (CTGAN) deep learning methods have been proven to be effective in solving imbalance disk failure data. But CTGAN cannot learn the internal information of disk failure data very well. In this paper, a fault diagnosis method based on improved CTGAN, a classifier for specific category discrimination is added and a discriminator generate adversarial network based on residual network is proposed. We named it Residual Conditional Tabular Generative Adversarial Networks (RCTGAN). Firstly, to enhance the stability of system a residual network is utilized. RCTGAN uses a small amount of real failure data to synthesize fake fault data; Then, the synthesized data is mixed with the real data to balance the amount of normal and failure data; Finally, four classifier (multilayer perceptron, support vector machine, decision tree, random forest) models are trained using the balanced data set, and the performance of the models is evaluated using G-mean. The experimental results show that the data synthesized by the RCTGAN can further improve the fault diagnosis accuracy of the classifier

Differential combination of cytokine and interferon- gamma +874 T/A polymorphisms determines disease severity in pulmonary tuberculosis.

Background:Mycobacterium tuberculosis infects nearly 1/3 of the world population and this reservoir forms the largest pool from which new cases arise. Among the cytokines, IFN-gamma is a key determinant in protection against tuberculosis. Single nucleotide polymorphisms (SNPs) in IFN-gamma gene (+874 T/A) which determine TT high ((hi)), AA low ((lo)) and TA intermediate ((int)) responder phenotypes have shown variable associations with tuberculosis disease outcome in different ethnic populations. The objective of the current study was to analyze IFN-gamma gene combinations with other IFN-gamma regulating cytokine genes (IL-10, TNF -alpha, IL-6) to see the effect of gene- combinations on disease severity outcome in pulmonary tuberculosis. Methods andFindings:Study groups comprised of pulmonary TB Patients stratified according to lung tissue involvement into mild (Pmd = 74) or advance (Pad = 23) lung disease and compared with healthy controls (TBNA = 166). Genotype analysis was carried out using amplification refractory mutation system-PCR (ARMS-PCR). IFN-gamma gene (+874 T/A) functional SNP combinations in TNFalpha (-308 G/A), IL-10 (-1082 A/G) and IL-6 (-174 G/C) were analyzed. Single gene analysis (Pearson chi) showed a dominant association of IFN-gamma TT (hi) genotype (p = 0.001) and T allele (p = 0.001) with mild disease. IFN-gamma(lo) -IL-10(lo) genotype combination was associated with advanced disease (p = 0.002). IFN-gamma(hi) -IL-6(hi) combination was associated with mild disease (p = 0.0005) while IFN-gamma(lo) -IL-6(int) was associated with protection against both forms of pulmonary disease (p = 0.002).Conclusion:Our results show that a limited number of IFN-gamma gene combinations with other cytokine functional SNPs determine the outcome of disease severity in tuberculosis

Characterization , Classification and Prediction of Soil Map Units Boundaries by Using Remote Sensing and GIS in Bahar Al-Najaf / Iraq

The study area is located in the west of the Al-Najaf Al-Ashraf city center, It is bounded by 32o 8’ 8” - 31o 39’ 16” N and 44o 3’ 15” – 43o 4’ 11” E, It covers an area of (1970 ) Km2 lying within the land of Al-Najaf sea. The study relied on Satellite Image for Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) which captured on 07/13/2014 from the USGS site, The study area was truncated by using ERDAS package, and followed by choose the mix of False color Composite RGB (753) to be the best being a specialist to study the soil and minerals. Some improvements have been made (radiation and spectral and spatial) and Unsupervised classification as well as the use of Earth indicators such as the heterogeneity of the characteristics of field perspective on the ground such as soil Color, texture and natural plants in addition to topographical in determining the movement paths to select 16 Pedon sites . The results showed a variation in spectral reflectivity values both between studied pidons within the same spectral range or between the spectral bands used in this study, reflecting the state of the contrast between the characteristics of soils for studied pidons as well as the variation in susceptibility sensor spectral bands among them. The reflectance of B2 , B3 bands were low comparing with others in all pedons sites, this mean that ability of soil materials to absorb them were more than the rest, for this their sensitivity appear low. On other hand, B5 , B6 bands show higher reflectivity than others of OLI sensor in all pedons sites. As the NDVI index values were 0.1 or less, this mean that most of study areas were bare soils or covered with low vegetation. Thermal Infrared bands B10 , B11 show the highest values of DN comparing with others, this identifying that soil surface salts were thermal incentive. Spectral bands appear positive correlation with sand and clay grains but negative with Silt grains and bulk density. Electrical conductivity and gypsum appear negative correlation with all bands and studied spectral indices except B2,B3 bands were positive. Calcite shows positive correlation with all spectral bands and indices, but negative with B2 and NDWI index

Differential Combination of Cytokine and Interferon- γ +874 T/A Polymorphisms Determines Disease Severity in Pulmonary Tuberculosis

BACKGROUND: Mycobacterium tuberculosis infects nearly 1/3 of the world population and this reservoir forms the largest pool from which new cases arise. Among the cytokines, IFN-γ is a key determinant in protection against tuberculosis. Single nucleotide polymorphisms (SNPs) in IFN-γ gene (+874 T/A) which determine TT high ((hi)), AA low ((lo)) and TA intermediate ((int)) responder phenotypes have shown variable associations with tuberculosis disease outcome in different ethnic populations. The objective of the current study was to analyze IFN-γ gene combinations with other IFN-γ regulating cytokine genes (IL-10, TNF -α, IL-6) to see the effect of gene- combinations on disease severity outcome in pulmonary tuberculosis. METHODS AND FINDINGS: Study groups comprised of pulmonary TB patients stratified according to lung tissue involvement into mild (Pmd = 74) or advance (Pad = 23) lung disease and compared with healthy controls (TBNA = 166). Genotype analysis was carried out using amplification refractory mutation system-PCR (ARMS-PCR). IFN-γ gene (+874 T/A) functional SNP combinations in TNFα (-308 G/A), IL-10 (-1082 A/G) and IL-6 (-174 G/C) were analyzed. Single gene analysis (Pearson χ²) showed a dominant association of IFN-γ TT (hi) genotype (p = 0.001) and T allele (p = 0.001) with mild disease. IFN-γ(lo) -IL-10(lo) genotype combination was associated with advanced disease (p = 0.002). IFN-γ(hi) -IL-6(hi) combination was associated with mild disease (p = 0.0005) while IFN-γ(lo) -IL-6(int) was associated with protection against both forms of pulmonary disease (p = 0.002). CONCLUSION: Our results show that a limited number of IFN-γ gene combinations with other cytokine functional SNPs determine the outcome of disease severity in tuberculosis

MRI Guided Stereotactic Biopsies or Aspirations in Deep Seated Brain Lesions: An Experience of 146 Cases at Nishtar Hospital, Multan

Objective: To determine frequency of positive biopsies or aspirates and safety in deep seated brain lesion, with use of Magnetic Resonance Imaging compatible stereotactic system.Study Design: Prospective cross sectional.Setting: The study was performed at Neurosurgery Department Nishtar Hospital, Multan.Duration of Study: From 01-07-2008 to 30-06-2012.Material and Methods: A total of 146 patients of age between 12 – 18 years of either sex having deep, intrinsic cystic lesion of the brain less or equal to 4 cm2 in size and excluding the extensively vascular lesion diagnosed on Computed Tomography and Magnetic Resonance Imaging underwent Stereotactic biopsy or aspiration with Mag-netic Resonance Imaging compatible Leksell’s stereotactic system. The tissue specimens were analyzed by stan-dard histopathological methods. The safety was measured in context of absence of complications i.e. hemorrhage, new onset of neurological deficit and fits. Data was analyzed via computer software SPSS 10 version for win-dows.Results: Among 146 patients with deep seated cystic brain lesions were selected for aspiration by using MRI guided stereotactic system. Their age ranged from 12 years to 80 years with Mean = 37.73 ± Standard deviation (SD) = 18.12. Among them 86 (58.9%) were male and 60 (41.1%) female. Biopsies or aspirates were positive in 136 (93.2%) cases while negative in 10 (6.8%) cases.Conclusion: We conclude that MRI assisted stereotactic brain aspiration is safe and effective procedure with a high diagnostic yield at our center

Thermal Model of Rotary Friction Welding for Similar and Dissimilar Metals

Friction welding is one of the foremost welding processes for similar and dissimilar metals. Previously, the process has been modeled utilizing the rudimentary techniques of constant friction and slip-stick friction. The motivation behind this article is to present a new characteristic for temperature profile estimation in modeling of the rotary friction welding process. For the first time, a unified model has been exhibited, with an implementation of the phase transformation of similar and dissimilar materials. The model was generated on COMSOL Multiphysics® and thermal and structural modules were used to plot the temperature curve. The curve for the welding of dissimilar metals using the model was generated, compared and analyzed with that of practical curves already acquired through experimentation available in the literature, and then the effect of varying the parameters on the welding of similar metals was also studied

Cohen’s criteria for interpreting practical significance indicators: A critical study

The present study aimed at clarifying the various shortcomings of the Cohen’s criteria for the interpretation of the values of the practical significance indicators. The hypothetical data were used for two experimental and control groups and calculating the paired-samples t-test. To clarify the inadequacy of Cohen’s criteria in interpreting practical significance indicators, it was compared with another criterion which is Black’s Modified Gain Ratio. Through the compatibility of mathematical equations to calculate the practical significance and the values of the interpretations of the correlation coefficient, the present study suggested that a criterion for the practical significance should be as follows: small when the values of the index (d) are less than (0.631), medium when the values are between 0.631 and 1.50 and large when the values are equal to or greater than (1.51). The study showed the justifications that distinguish this criterion from the Cohen criterion