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- Tabiri, S, et al.
(författare)
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- 2021
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swepub:Mat__t
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- Thomas, HS, et al.
(författare)
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- 2019
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swepub:Mat__t
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- Bravo, L, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 8. |
- Homod, Raad Z., et al.
(författare)
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Deep clustering of cooperative multi-agent reinforcement learning to optimize multi chiller HVAC systems for smart buildings energy management
- 2023
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Ingår i: Journal of Building Engineering. - : Elsevier. - 2352-7102. ; 65
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Tidskriftsartikel (refereegranskat)abstract
- Chillers are responsible for almost half of the total energy demand in buildings. Hence, the obligation of control systems of multi-chiller due to changes indoor environments is one of the most significant parts of a smart building. Such a controller is described as a nonlinear and multi-objective algorithm, and its fabrication is crucial to achieving the optimal balance between indoor thermal comfort and running a minimum number of chillers. This work proposes deep clustering of cooperative multi-agent reinforcement learning (DCCMARL) as well-suited to such system control, which supports centralized control by learning of agents. In MARL, since the learning of agents is based on discrete sets of actions and stats, this drawback significantly affects the model of agents for representing their actions with efficient performance. This drawback becomes considerably worse when increasing the number of agents, due to the increased complexity of solving MARL, which makes modeling policy very challenging. Therefore, the DCCMARL of multi-objective reinforcement learning is leveraging powerful frameworks of a hybrid clustering algorithm to deal with complexity and uncertainty, which is a critical factor that influences to the achievement of high levels of a performance action. The results showed that the ability of agents to manipulate the behavior of the smart building could improve indoor thermal conditions, as well as save energy up to 44.5% compared to conventional methods. It seems reasonable to conclude that agents' performance is influenced by what type of model structure.
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| 9. |
- Abd Al Qahar Al-Kubaisy, Waqar, et al.
(författare)
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Hepatitis C virus prevalence and genotyping among hepatocellular carcinoma patients in Baghdad
- 2014
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Ingår i: Asian Pacific Journal of Cancer Prevention. - : Asian Pacific Organization for Cancer Prevention. - 1513-7368. ; 15:18, s. 7725-7730
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Tidskriftsartikel (refereegranskat)abstract
- Hepatocellular carcinoma (HCC) is the third most common cause for cancer death in the world, now being especially linked to chronic hepatitis C virus (HCV) infection. This case-control study consisting of 65 HCC patients and 82 patients with other malignant tumours as controls was conducted to determine the association of HCV markers with HCC. Serum of each participant was obtained for detection of HCV Ab and RNA by DNA enzyme immunoassay (DEIA). Twenty six per cent (26.0%) of HCC patients had positive anti-HCV which was significantly greater than the control group (p=0.001). HCC patients significantly have a risk of exposure to HCV infection almost 3 times than the control group (OR=2.87, 95% C.I=1.1-7). Anti-HCV seropositive rate was significantly (p=0.03) higher among old age HCC patients and increases with age. Males with HCC significantly showed to have more than 9 times risk of exposure to HCV infection (OR=9.375, 95 % CI=1.299-67.647) than females. HCV-RNA seropositive rate was (70.8%) significantly higher among HCC patients compared to (22.2%) the control group (p=0.019). The most prevalent genotype (as a single or mixed pattern of infection) was HCV-1b. This study detected a significantly higher HCV seropositive rate of antibodies and RNA in HCC patients.
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| 10. |
- Alawi, Omer A., et al.
(författare)
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Heat transfer and hydrodynamic properties using different metal-oxide nanostructures in horizontal concentric annular tube : An optimization study
- 2021
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Ingår i: Nanomaterials. - : MDPI AG. - 2079-4991. ; 11:8
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Tidskriftsartikel (refereegranskat)abstract
- Numerical studies were performed to estimate the heat transfer and hydrodynamic properties of a forced convection turbulent flow using three-dimensional horizontal concentric annuli. This paper applied the standard k–ε turbulence model for the flow range 1 × 104 ≤ Re ≥ 24 × 103. A wide range of parameters like different nanomaterials (Al2O3, CuO, SiO2 and ZnO), different particle nanoshapes (spherical, cylindrical, blades, platelets and bricks), different heat flux ratio (HFR) (0, 0.5, 1 and 2) and different aspect ratios (AR) (1.5, 2, 2.5 and 3) were examined. Also, the effect of inner cylinder rotation was discussed. An experiment was conducted out using a field-emission scanning electron microscope (FE-SEM) to characterize metallic oxides in spherical morphologies. Nano-platelet particles showed the best enhancements in heat transfer properties, followed by nano-cylinders, nano-bricks, nano-blades, and nano-spheres. The maximum heat transfer enhancement was found in SiO2, followed by ZnO, CuO, and Al2O3, in that order. Meanwhile, the effect of the HFR parameter was insignificant. At Re = 24,000, the inner wall rotation enhanced the heat transfer about 47.94%, 43.03%, 42.06% and 39.79% for SiO2, ZnO, CuO and Al2O3, respectively. Moreover, the AR of 2.5 presented the higher heat transfer improvement followed by 3, 2, and 1.5.
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