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Electroencephalogram (EEG) is a widely used tool for the study and diagnosis of epilepsy. The patients subjected to epilepsy require long term monitoring of EEG. Automatic seizure detection will eliminate chances of missing any seizure, make detection easy and reduce burden on physicians. In this work, different combination of Pythagorean means (time domain features) namely arithmetic mean (AM), geometric mean (GM) and harmonic mean (HM) of energy per epoch are used as features to classify EEG data into normal, seizure free and seizure classes by using a linear classifier. The classification accuracy of 100% is achieved in two and three class problem with a single feature/epoch and in five class problem with two features/epoch. The novelty of this work is use of new and simple features (in epileptic EEG signal classification), reduced complexity and high performance.

Tuberculosis (Tb) is a chronic infectious disease in which the cellular immunity (specifically CD4+ and CD8 lymphocytes) provides the most important defense in controlling infection. CD4 lymphopenia is a well-defined risk factor for the development of active tuberculosis in patients infected with Human Immunodeficiency Virus. In HIV - negative patients, CD4 and CD8 cell count suppression has been associated with Tb infection. Our study was designed to deter mine the baseline and post-treatment values of CD4 and CD8 in HIV negative patients diagnosed with active Tb in Saudi Arabian patients. We recruited twentyeight, non-HIV patients with tuberculosis for the study group comprising 16 males and 12 females with either disseminated or localized active Tb infection. Two control groups were selected - one of twenty one matched healthy controls and the second of fortytwo subjects from pool of controls of an ongoing study in same population for normal CD4 and CD8 counts. The baseline pre-treatment CD4 and CD8 counts in the study group were significantly lower than either control group. Specifically the mean ± SD of CD4 counts were 556.79 ± 298.81 in the study group vs 1,132.38 ± 259.90 in control group 1 and 1,424.38 ± 870.98 in control group 2 (p 0.000). Likewise the CD8 counts in the study group were 1,136.00 ± 512.06 vs. 1,461.90 ± 367.02 in control group 1 and 1,495.90 ± 565.32 in control group 2 (p 0.000) respectively. After treatment of tuberculosis, the study patients experienced a significant increase in their mean ± SD CD4 and CD8 cell counts, from 556.79 ± 297.81 to 954.29 ± 210.90 for CD4 cells (p 0.005) and 1136.00 ± 512.06 to 1,316.54 ± 286.17 for CD8 cells (p 0.002). Analysis of study patients with disseminated disease found significantly lower CD4 cells (but not lower CD8 cells) compared to study patients with localized disease, both at baseline and after treatment. The mean ± SD baseline CD4 cells were 247.60 ± 187.80 with disseminated vs 728.56 ± 186.32 for localized disease (p = 0.000) which rose to 842.30 ± 93.55 vs 1016.50 ± 233.51 (p = 0.033) respectively. We conclude that tuberculosis may be associated with CD4 and CD8 lymphopenia even in patients without human immunodeficiency virus infection, there was the tendency of recovery towards normality especially of the CD4 and CD8 counts after treatment, and that disseminated disease is associated specifically with profound CD4 lymphopenia.

In this paper, Admissible Wavelet Packet (AWP)-based features are proposed for the recognition of isolated Hindi digit. AWPs are used to design a set of filter banks to follow the Mel scale. Finally, a Hidden Markov Model (HMM) is developed for recognition. The database used was collected from 48 subjects with a repetition of each digit five times. Features based on both Linear Predictive Coefficients (LPCs) as well as Mel Frequency Cepstral Coefficients (MFCCs) were extracted and their performance compared with the AWP-based features. It was found that the recognition performance using AWP-based features was superior when compared with LPC- and MFCC-based features.

Hot rolled plate steel is heat treatable steel made in Indonesia for commercially developed to Quenched and Tempered Steel. This steels made by PT. Krakatau Steel (Persero) Cilegon, Banten, Indonesia. The aim of this study to improve the hardness and energy impact through heat treatment of double quench + temper. The method used is heating up to 900degC (maintained for 30 minutes and cooled by water) for fives specimen hot rolled plate steel and produce the quenched 900 steel (Q900 Steel). Four Q900 steel specimens were heated at 750degC, 800degC, 850degC, and 900degC (maintained for 30 minutes) each. Then five specimens (include Q900 Steel) are tempered at 150degC (maintained for 30 minutes) and produced Q900 & T Steel, Q900+750 & T Steel, Q900+800 & T Steel, Q900+850 & T Steel, Q900+900 & T Steel. Results of the study were changes in microstructure, hardness and impact energy. Hardness and impact energy absorbed of Q900+750&T Steel higher than Q900 &T Steel.