Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.
Abstract. In this research, the uranium concentration in (16) water samples collected from some agricultural areas surrounded with AlTuwitha nuclear site in Baghdad-Iraq was measured by using a CR-39 detector. The concentration of uranium in this study was from (0.6 ± 0.33mg/l) to (2.51 ± 0.49 mg/l), and the weighted average for the concentrations (1.262 ± 0.402 mg/l). The results showed it is a concentration of uranium level in water samples studied is higher than the allowed limit recommended by WHO and ICRP.
Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co
... Show MoreThe fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t
ABSTRACT Backgrounds: Maxillary canine impaction is complicated and time consuming to treat, for being highly diverse in inclination and location; it may be a companied by root resorption of the neighboring teeth. CBCT has been used for its' diagnostic reliability in localization of impacted canine and revealing its' serious local complications. Objectives: Localization of maxillary impacted canine using cone beam computed tomography for assessment of angulation, distance from occlusal plane, alveolar width and proximity to adjacent teeth. Subjects and Methods: The study sample was 33 subjects 16 females and 17 males attended to Al-Wasitti general hospital in Baghdad city-Oral and maxillofacial radiology department for CBCT scan investigati
... Show MoreThe - mixing ratios of -transitions from levels in populated in the reactions are calculated in present work using - ratio, constant statisticalTensor and least squares fitting methods The results obtained are in general, in good agreement or consistent, within the associated uncertainties, with these reported in Ref.[9],the discrepancies that occurs are due to inaccuracy existing in the experimental data The results obtained in the present work confirm the –method for mixed transitions better than that for pure transition because this method depends only on the experimental data where the second method depends on the pure or those considered to be pure -transitions, the same results occur in – method
Objective: To identify causes of maternal death in Mizan Aman and Gebretsadik shawo general hospitals
Methodology: A case control study on 595 charts, 119 cases and 476 controls was conducted in Mizan
Aman & Gebretsadik shawo general hospitals. Data was analyzed by STATA 13.1. Propensity score
matching analysis was used to see causes of maternal death.
Results: Hemorrhage were the main direct causes of maternal death which accounts 47.9% (β =0.58
(95% CI (0.28,0.87)) in hospital but when projected to population based the sample (β =0.26 (95% CI
(0.22,0.31)). Followed by infection 36 (25.21%) (β = 0.50 (95% CI (0.08, 0.92)). when projected to
population based the sample PIH 7.6%) is significant cause (β = 0.16
Furfural is a toxic aromatic aldehyde that can cause a severe environmental problem especially the wastewater drown from petroleum refinery units. In the present work, a useless by-product from local furniture manufacturing industry; sawdust was used as raw material for the preparation of activated carbon which is chemically activated with phosphoric acid. The effect of adsorption variables which include initial pH of solution (2-9), agitation speed (50-250) rpm, agitation time (15-120) min, initial concentration of furfural (50-250) ppm, and amount of adsorbent material (0.5-2.5) g for the three adsorbents used (prepared activated carbon, commercial activated carbon and raw sawdust) were investigated in a batch process
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