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Heat exchanger network optimization by differential evolution method
No full textNoThe synthesis of heat exchanger network (HEN) is a comprehensive approach to optimize energy utilization in process industry. Recent developments in HEN synthesis (HENS) present several heuristic methods, such as Simulated Annealing (SA), Genetic Algorithm (GA), and Differential Evolution (DE). In this work, DE method for synthesis and optimization of HEN has been presented. Using DE combined with the concept of super-targeting, the ΔTmin optimization is determined. Then DE algorithm is employed to optimize the global cost function including the constraints, such as heat balance, the temperatures of process streams. A case study has been optimized using DE, generated structure of HEN and compared with networks obtained by other methods such as pinch technology or mathematical programming. Through the result, the proposed method has been illustrated that DE is able to apply in HEN optimization, with 16.7% increase in capital cost and 56.4%, 18.9% decrease in energy, global costs respectively
A study of deep learning-based face recognition models for sibling identification
Get PDFYesAccurate identification of siblings through face recognition is a challenging task. This is predominantly because of the high degree of similarities among the faces of siblings. In this study, we investigate the use of state-of-the-art deep learning face recognition models to evaluate their capacity for discrimination between sibling faces using various similarity indices. The specific models examined for this purpose are FaceNet, VGGFace, VGG16, and VGG19. For each pair of images provided, the embeddings have been calculated using the chosen deep learning model. Five standard similarity measures, namely, cosine similarity, Euclidean distance, structured similarity, Manhattan distance, and Minkowski distance, are used to classify images looking for their identity on the threshold defined for each of the similarity measures. The accuracy, precision, and misclassification rate of each model are calculated using standard confusion matrices. Four different experimental datasets for full-frontal-face, eyes, nose, and forehead of sibling pairs are constructed using publicly available HQf subset of the SiblingDB database. The experimental results show that the accuracy of the chosen deep learning models to distinguish siblings based on the full-frontal-face and cropped face areas vary based on the face area compared. It is observed that VGGFace is best while comparing the full-frontal-face and eyes—the accuracy of classification being with more than 95% in this case. However, its accuracy degrades significantly when the noses are compared, while FaceNet provides the best result for classification based on the nose. Similarly, VGG16 and VGG19 are not the best models for classification using the eyes, but these models provide favorable results when foreheads are compared
Performance of thermally enhanced geo-energy piles and walls
Get PDFYesThis study aims to evaluate the impacts of using thermally enhanced concrete on the thermal performance of geoenergy
structures and interaction between the thermo-active-structures and adjacent dry and partly saturated
soils. Experiments using a fully instrumented testing rig were carried out on prototypes of energy pile and
diaphragm wall made from normal concrete and thermally enhanced concrete by the addition of graphTHERM
powder. Results illustrated that adding 36% of graphTHERM powder to the concrete by weight of cement was
found to double the thermal conductivity of concrete and improve the stiffness by 15% without detrimental
effects on the compressive strength. The heat transfer efficiency of energy pile and energy diaphragm wall made
from thermally enhanced concrete was significantly improved by 50% and 66% respectively, in comparison with
the efficiency of the same type of energy structure that was made from a typical normal concrete
Approximate Analytical Solution and Laboratory Experiments for Dam-Break Wave Tip Region in Triangular Channels
Get PDFYesSolutions for dam-break flow mainly developed for rectangular channels are not applicable to prediction of the propagation of the dam-break wave in frictional triangular channels. This study presents an approximate solution considering the frictional effect on the dam-break flow in a dry horizontal triangular channel. Wave tip velocity is solved by an implicit formula for the product of time and resistance coefficients. All other hydraulic properties in the wave tip region can be expressed as explicit functions of wave tip velocity. Meanwhile, laboratory experiments have been performed for obtaining water surface profiles of dam-break flow from which the position and velocity of the wave tip front have been derived. Results show that retardation of the wave front position is more significant with the increases in both resistance and time. The proposed analytical solution shows satisfactory agreement with measurements, and clarifies how the behavior of the dam-break wave tip is affected by channel geometry
Flow characteristics in partially vegetated channel with homogeneous and heterogeneous layouts
Get PDFYesThis study presents the experimental results of the flow characteristics, such as the flow adjustment, velocity profiles, mixing layer, and the momentum exchange, in the partially vegetated channel with homogeneous and heterogeneous layouts. Three cases are considered, including two homogeneous canopies with uniform sparse and dense vegetation patches respectively, and a heterogeneous canopy consisting of alternating patches of both densities. Results show that heterogeneous canopy requires a longer adjustment distance to reach the quasi-equilibrium region, compared with the homogenous canopy of the same density. In heterogeneous canopy flow, the mixing layer width and the momentum thickness fluctuates with the alternation of vegetation density. The increased values for these two parameters compared to those values for the homogeneous canopies indicate that the greater resistance and momentum loss occur for the heterogeneous layout. A wavy region of the enhanced in-plane turbulence kinetic energy (TKE) is observed in the heterogeneous canopy, suggesting a comparatively more chaotic flow condition, whereas the contours of in-plane TKE are smooth in homogeneous canopies. The presence of the coherent structures in heterogeneous canopy is identified by spectral analysis and the quasi-periodic fluctuations of velocities. The Reynolds stress associated with the coherent structures is found to be the dominator of the contribution to the total Reynolds stress. The comparison between the homogenous canopies of different density is also conducted. These results will be of practical importance for the design of vegetation layouts in water ecological restoration projects and for river management.National Natural Science Foundation of China (grant numbers 52020105006 and 11872285) and the Open Funding of State Key Laboratory of Water Resources and Hydropower Engineering Science (WRHES), Wuhan University (Project number 2018HLG01
A multi-objective optimisation framework for MED-TVC seawater desalination process based on particle swarm optimisation
Get PDFYesOwing to the high specific energy consumption associated with thermal desalination technologies such as Multi Effect Distillation (MED), there is a wide interest to develop a cost-effective desalination technology. This study focuses on improving the operational, economic, and environmental perspectives of hybrid MED-TVC (thermal vapour compression) process via optimisation. Application of particle swarm optimisation (PSO) in several engineering disciplines have been noted but its potential has not been exploited fully in desalination technologies especially MED-TVC in the past. A multi-objective non-linear optimisation framework based on PSO is constructed here. Two of our earlier models have been used to predict the key process performance and cost indicators. The models are embedded within the PSO optimisation algorithm to develop a new hybrid optimisation model which minimises the total freshwater production cost, total specific energy consumption and brine flow rate while maintaining a fixed freshwater production for a given number of effects and seawater conditions. The steam flow rate and temperature are considered as control variables of the optimisation problem to achieve the objective function. The PSO has successfully achieved the optimum indexes for the hybrid MED-TVC process for a wide range of number of effects. It also shows a maximum reduction of freshwater production cost by 36.5%, a maximum energy saving by 32.1% and a maximum reduction of brine flow rate by 38.3%, while maintaining the productivity of freshwater
General discriminative optimization for point set registration
Get PDFYesPoint set registration has been actively studied in computer vision and graphics. Optimization algorithms are at the core of solving registration problems. Traditional optimization approaches are mainly based on the gradient of objective functions. The derivation of objective functions makes it challenging to find optimal solutions for complex optimization models, especially for those applications where accuracy is critical. Learning-based optimization is a novel approach to address this problem, which learns the gradient direction from datasets. However, many learning-based optimization algorithms learn gradient directions via a single feature extracted from the dataset, which will cause the updating direction to be vulnerable to perturbations around the data, thus falling into a bad stationary point. This paper proposes the General Discriminative Optimization (GDO) method that updates a gradient path automatically through the trade-off among contributions of different features on updating gradients. We illustrate the benefits of GDO with tasks of 3D point set registrations and show that GDO outperforms the state-of-the-art registration methods in terms of accuracy and robustness to perturbations
Applying a new technique, the interferon gamma liposomal delivery system to improve drug delivery in the treatment of Lung Cancer
Get PDFLung cancer is one of the main causes of death worldwide, with most patients
suffering from an advanced unresectable or metastatic non-small cell lung
cancer. The mortality trends are mostly related to patterns of tobacco use,
specifically from cigarettes. Tobacco is the basic etiological agent found as a
consequence of the inhalation of tobacco smoke. Published data show the use
of interferons (IFNs) in the treatment of lung tumours due to their potential in
displaying antiproliferative, anti-angiogenic, immunoregulatory, and proapoptotic
effects. Type1 IFNs have been employed as treatments for many types of cancer,
both for haematological cancers and solid tumours. The IFN-γ (naked) functions
as an anticancer agent against various forms of cancer. Hence, this study aimed
to investigate the genoprotective and genotoxic effects of IFN-γ liposome (nano)
on 42 blood samples from lung cancer patients, compared to the same sample
size from healthy individuals. The effectiveness of IFN- γ liposome against
oxidative stress was also evaluated in this study. A concentration of 100U/ml
of IFN-γ liposome was used to treat the lymphocytes in: Comet and
micronucleus assays, Comet repair, Western blotting and real-time polymerase
chain reaction (qPCR) were based on a preliminary test for the optimal dose.
The lymphocytes from lung cancer patients presented with higher DNA damage
levels than those of healthy individuals. IFN-γ liposome was not found to induce any DNA damage in the lymphocytes. Also, it caused a significant reduction in
DNA damage in the lymphocytes from lung cancer patients in; Comet, Comet
repair and micronucleus assays. Furthermore, the 100U/ml of IFN-γ liposome
significantly reduced the oxidative stress caused by H2O2 and appeared to be
effective in both groups using the Comet and micronucleus assays. Results
from; Comet, Comet repair and micronucleus assays were consistent.
The data obtained indicated that IFN-γ in both forms (naked INF-γ and INF-γ
nano-liposome) may potentially be effective for the treatment of lung cancer and
showed the ability of IFN-γ liposome to reduce the DNA damage more than the
naked form.
The IFN-γ in both forms has also shown anti-cancer potential in the lymphocytes
from lung cancer patients by regulating the expression of p53, p21, Bcl-2 at
mRNA and protein levels by up-regulating the p53 and p21 to mediate cell cycle
arrest and DNA repair in lung cancer patients.
The findings of this study are consistent with the view that the naked IFN-γ and
liposome could have a significant role in cancer treatment, including lung cancer.Mutah University in Jorda
What is the Role of a Pharmacist in a Parkinson’s Disease Interdisciplinary Team?
Get PDFThe care of people with Parkinson’s disease (PD) involves input from different
healthcare professionals (HCPs). A literature search identified that the HCPs
involved in PD multidisciplinary (MDT) clinics, including interdisciplinary team
(IDT), varied both in the number and type of HCPs. None of the studies
identified involved pharmacists. Pharmacists have shown benefits when
working in MDTs for other long-term conditions (LTCs); however, their role in
PD MDTs was identified as a gap in the literature.
The aim of the study was to determine the role of pharmacists in a PD IDT.
Patients attended a PD IDT clinic comprising PD nurse, physiotherapist,
occupational therapist and pharmacist. A mixed methods convergent design
was used to collect both qualitative and quantitative data. Qualitative focus
group and interview data were analysed using The Framework Method.
Quantitative data analysis involved counts of HCP interventions.
Pharmacists can support PD IDTs as they have in other LTC MDTs by
conducting holistic medication reviews. Three new roles were identified for
pharmacists in PD IDTs as: 1) independent prescribing, 2) supporting HCPS in
their roles by supporting staff knowledge, and 3) leading the PD IDT clinics.
Quantitative data showed the pharmacist made a medication review
intervention for all patients.
HCPs and patients identified the roles and value of involving pharmacists in PD
IDTs. The PD IDT clinics offer a holistic approach to patient care and a greater
opportunity for patients to be involved. The findings identified a ‘review-shared care template’
for PD IDTs and recommends development of a ‘pharmacist’s PD competency framework’