Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform wit

Several previous investigations and studies utilized silica fume (SF) or (micro silica) particles as supplementary cementitious material added as a substitute to cement-based mortars and their effect on the overall properties, especially on physical properties, strength properties, and mechanical properties. This study investigated the impact of the inclusion of silica fume (SF) particles on the residual compressive strengths and microstructure properties of cement-based mortars exposed to severe conditions of elevated temperatures. The prepared specimens were tested and subjected to 25, 250, 450, 600, and 900 °C. Their residual compressive strengths and microstructure were evaluated and compared with control samples (C

Abstract in English  The aim of this study is to identify the effectiveness of rehabilitation exercises in conjunction with aquatic therapy for those suffering from sacroiliitis in football players. The researcher used the experimental approach, using the experimental design (pre-measurement, post-measurement). Similar to the objectives and procedures of the research, the researcher assumed the following: the existence of significant differences. Statistics between pre- and post-measurements in variables in favor of post-measurement for the following variables (degree of pain and level of balance). The experimental approach was used with a pre- and post-measurement design on one group of football players with sacroiliitis, nu

Background: Acute leukemias (ALs) are a heterogeneous group of malignancies with various clinical, morphological, immunophenotypic, and molecular characteristics. Distinguishing between lymphoid and myeloid leukemia is often performed by flow cytometry. This study aimed to evaluate the immunophenotypic characterization and expression of immuno-markers in both acute myeloid leukemia (AML-M0) and acute T-cell lymphoblastic leukemia (T-ALL).

Methods: A retrospective cross-sectional study was conducted in the Pathology Department/Teaching Laboratories/Medical City/Iraq and included all patients newly diagnosed with AL from 5 January to 10 December 2018. Immunophenotypic analysis wa

Background: This study aimed to examine the efficacy of methylene blue (MB) and toluidine blue O (TBO) photodynamic therapy (PDT) as adjuncts to root surface debridement (RSD). Methods: This split-mouth, randomized, controlled clinical trial included eighteen patients, and a total of 332 sites (control = 102, MB = 124 and TBO = 106) were examined. Two sessions of PDT were completed at baseline and two weeks after RSD. Clinical parameters of bleeding on probing (BOP), plaque index (PI), probing pocket depth (PPD), and clinical attachment level (CAL) were measured pre- and post-treatment. Results: PPD and BOP reductions in sites treated by RSD with adjunctive photosensitizers (MB and TBO) were significantly higher than in control site

The properties of capturing of peristaltic flow to a chemically reacting couple stress fluid through an inclined asymmetric channel with variable viscosity and various boundaries are investigated. we have addressed the impacts of variable viscosity, different wave forms, porous medium, heat and mass transfer for peristaltic transport of hydro magnetic couple stress liquid in inclined asymmetric channel with different boundaries. Moreover, The Fluid viscosity assumed to vary as an exponential function of temperature. Effects of almost flow parameters are studied analytically and computed. An rising in the temperature and concentration profiles return to heat and mass transfer Biot numbers. Noteworthy, the Soret and Dufour number effect resul

Olfactory impairment and abnormal frontal EEG oscillations are recognized as early markers of Alzheimer’s disease (AD). Using a publicly available olfactory EEG dataset of 35 subjects spanning normal cognition, amnestic mild cognitive impairment (aMCI), and AD, each with MMSE scores and demographics, stimulus-locked epochs from four electrodes (Fp1, Fz, Cz, Pz) were processed with wavelet-based time–frequency analysis. Band-limited power ratios (delta, theta, alpha, beta) were computed as log-transformed post-odor/baseline values and aggregated to subject-level features. Statistical analyses revealed graded attenuation of odor-evoked frontal (Fp1) band-power ratios across groups, with significant differences in several band–od

A calamitic symmetric liquid crystalline consisting of an azo group containing 5H-Thiazolo[3,4-b][1,3,4]thiadiazole moiety compound[III] was synthesized via sequence reactions starting from reaction terephthaldehyde with mercaptoacetic acid and thiosemicarbazide in the presence of concentrated sulfuric acid to synthesized 5,5'-(1,4-phenylene)bis(5Hthiazolo[4,3-b][1,3,4]thiadiazol-2-amine)[I] then the azo compound [II] synthesized by coupling between diazonium salt of the compound [I] with phenol at (0-4) ̊C., after that the compound [III] was synthesized by the reaction of the compound [II] with methyl bromide in alkaline media. The compounds are characterized by melting points, FTIR and 1HNMR spectroscopy. The mesomorphic behavior was stu

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices