• Wind and Structures
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• v.29 no.1
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• pp.15-32
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• 2019

Much advancement has been made in wind power due to modern technological developments. The wind energy technology is the world's fastest-growing energy option. More power can be generated from wind energy by the use of new design and techniques of wind energy machines. The geographical areas with suitable wind speed are more favorable and preferred for wind power deployment over other sources of energy generation. Today's wind turbines are mainly the horizontal axis wind turbines (HAWTs) and vertical axis wind turbines (VAWTs). HAWTs are commercially available in various sizes starting from a few kilowatts to multi-megawatts and are suitable for almost all applications, including both onshore and offshore deployment. On the other hand, VAWTs finds their places in small and residential wind applications. The objective of the present work is to review the technological development, available sizes, efficiencies, structural types, and structural stability of VAWTs. Structural stability and efficiencies of the VAWTS are found to be dependent on the structural shape and size.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5234-5251
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• 2018

It is well-known that virtualization technology can bring many benefits not only to users but also to service providers. From the view of system security and resource utility, higher resource sharing degree and higher system reliability can be obtained by the introduction of virtualization technology in distributed cloud. The small size time-sharing multiplexing technology which is based on virtual machine in distributed cloud platform can enhance the resource utilization effectively by server consolidation. In this paper, the concept of memory block and user satisfaction is redefined combined with user requirements. According to the unbalanced memory resource states and user preference requirements in multi-virtual machine environments, a model of proper memory resource allocation is proposed combined with memory block and user satisfaction, and at the same time a memory optimization allocation algorithm is proposed which is based on virtual memory block, makespan and user satisfaction under the premise of an orderly physical nodes states also. In the algorithm, a memory optimal problem can be transformed into a resource workload balance problem. All the virtual machine tasks are simulated in Cloudsim platform. And the experimental results show that the problem of virtual machine memory resource allocation can be solved flexibly and efficiently.

• Smart Structures and Systems
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• v.26 no.6
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• pp.753-763
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• 2020

The early prediction of Compressive Strength of Concrete (CSC) is a significant task in the civil engineering construction projects. This study, therefore, is dedicated to introducing two novel hybrids of neural computing, namely Shuffled Complex Evolution (SCE) and Teaching-Learning-Based Optimization (TLBO) for predicting the CSC. The algorithms are applied to a Multi-Layer Perceptron (MLP) network to create the SCE-MLP and TLBO-MLP ensembles. The results revealed that, first, intelligent models can properly handle analyzing and generalizing the non-linear relationship between the CSC and its influential parameters. For example, the smallest and largest values of the CSC were 17.19 and 58.53 MPa, and the outputs of the MLP, SCE-MLP, and TLBO-MLP range in [17.61, 54.36], [17.69, 55.55] and [18.07, 53.83], respectively. Second, applying the SCE and TLBO optimizers resulted in increasing the correlation of the MLP products from 93.58 to 97.32 and 97.22%, respectively. The prediction error was also reduced by around 34 and 31% which indicates the high efficiency of these algorithms. Moreover, regarding the computation time needed to implement the SCE-MLP and TLBO-MLP models, the SCE is a considerably more time-efficient optimizer. Nevertheless, both suggested models can be promising substitutes for laboratory and destructive CSC evaluative models.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.858-876
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• 2021

Although widely used, the design of the bulbous bow for ships has been difficult due to the complex interference between the wave system generated by the bulb and the wave system of the ship hull. Until now, a bulbous bow has been often designed using Kracht charts, which were established based on model test data, but these charts apply only to ships with a block coefficient C_B = 0.56-0.82, Froude number Fn = 0.20-0.40, and the obtained bulb sizes are only close to optimal. This paper presents a new method for the optimal design of bulbous bow, starting from the design of an initial bulb using Kracht charts for ships with any block coefficient or Froude number, then resizing this initial bulb to define the optimal bulb sizes based on a multi-objective function of the required power reduction, and a combined solution of Computation Fluid Dynamics (CFD) analysis and surrogate models. This study was applied to a fishing vessel FAO 75, which has been model tested and used to design steel fishing vessels in Vietnam recently. The obtained quantitative results showed the same trend as the theory and practice, with a reduction of the ship's required power by about 14%.

• SUVANNABHUMI
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• v.12 no.2
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• pp.141-155
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• 2020

How might historians secure for the river a larger berth in the recent macro-historical turn? This question cannot find a greater niche than in the emerging critique of the existing spatial configuration of regionalism in mainland Southeastern Asia. The Brahmaputra, Irrawaddy, Salween, Mekong and Yangtze rivers spread out like a necklace around Yunnan and cut across parts of the territories that are known as South, Southeast and East Asia. Each of these rivers has a different topography and fluvial itinerary, giving rise to different political, economic and cultural trajectories. Yet these rivers together form a connected "water-world". These rivers engendered conversations between multi-agentive mobility and large-scale place-making and were at the heart of inter-Asian engagements and integration until the formal end of the European empires. Being both a subject and a sponsor of transregional crossings, the paper argues, these rivers point to the need for a new historical approach that registers the connections between parts of the Southeast Asian massif through to the expansive plain land and the vast coastal rim of the Bay of Bengal and the China Seas. A connection that could be framed through the concept of Holon.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.220-228
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• 2022

The directed tests produce an expectation model to assist the organization's heads and professionals with settling on the right and speedy choice. A directed deep learning strategy has been embraced and applied for SCADA information. In this paper, for the load shedding expectation overall power organization of Libya, a convolutional neural network with multi neurons is utilized. For contributions of the neural organization, eight convolutional layers are utilized. These boundaries are power age, temperature, stickiness and wind speed. The gathered information from the SCADA data set were pre-handled to be ready in a reasonable arrangement to be taken care of to the deep learning. A bunch of analyses has been directed on this information to get a forecast model. The created model was assessed as far as precision and decrease of misfortune. It tends to be presumed that the acquired outcomes are promising and empowering. For assessment of the outcomes four boundary, MSE, RMSE, MAPE and R2 are determined. The best R2 esteem is gotten for 1-overlap and it was 0.98.34 for train information and for test information is acquired 0.96. Additionally for train information the RMSE esteem in 1-overlap is superior to different Folds and this worth was 0.018.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.177-187
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• 2022

Theoretical literature agrees on the interaction between financial instability and economic activity but explains it's dynamic in two points of view: one is that the transmission mechanism occurs in one unique regime and the other reckons a shift of regime leads to the alteration of the transmission mechanism. This study aims to find evidence of the multi-regime transmission for ASEAN developing countries. The author employs the technique of Threshold vector auto regression using the financial stress index standing for financial instability. Monthly data is collected, covering a period long enough with many episodes of high stress in recent decades. There are two conclusions: (1) A financial shock has a negative and stronger impact on economic activity during a high-stress period than it does during a low-stress period; (2) the response of economic activity to a negative financial shock during high-stress periods is stronger than it is during normal times. The findings point to the importance of the financial stress index as an additional early warning indicator for the real economy sector, as well as the positive effect that a reduction in financial stress may have on economic activity, implying the importance of "unconventional" monetary policy in times of high financial stress.

• Geomechanics and Engineering
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• v.34 no.5
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• pp.507-527
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• 2023

Accurately estimation of the geo-mechanical parameters in Artificial Ground Freezing (AGF) is a most important scientific topic in soil improvement and geotechnical engineering. In order for this, one way is using classical and conventional constitutive models based on different theories like critical state theory, Hooke's law, and so on, which are time-consuming, costly, and troublous. The others are the application of artificial intelligence (AI) techniques to predict considered parameters and behaviors accurately. This study presents a comprehensive data-mining-based model for predicting the Young's Modulus of frozen sand under the triaxial test. For this aim, several single and hybrid models were considered including additive regression, bagging, M5-Rules, M5P, random forests (RF), support vector regression (SVR), locally weighted linear (LWL), gaussian process regression (GPR), and multi-layered perceptron neural network (MLP). In the present study, cell pressure, strain rate, temperature, time, and strain were considered as the input variables, where the Young's Modulus was recognized as target. The results showed that all selected single and hybrid predicting models have acceptable agreement with measured experimental results. Especially, hybrid Additive Regression-Gaussian Process Regression and Bagging-Gaussian Process Regression have the best accuracy based on Model performance assessment criteria.

• Structural Engineering and Mechanics
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• v.88 no.6
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• pp.521-533
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• 2023

In the present study, the finite volume method is applied for the thermal performance prediction of the natural ventilation system using vertical solar chimney whereas, design parameters are optimized through the response surface methodology (RSM). The computational simulations are performed for various parameters of the solar chimney such as absorber temperature (40≤T_abs≤70℃), inlet temperature (20≤T₀≤30℃), inlet height of (0.1≤h≤0.2 m) and chimney width (0.1≤d≤0.2 m). Analysis of variance (ANOVA) was carried out to identify the design parameters that influence the average Nusselt number (Nu) and mass flow rate (ṁ). Then, quadratic polynomial regression models were developed to predict of all the response parameters. Consequently, numerical and graphical optimizations were performed to achieve multi-objective optimization for the desired criteria. According to the desirability function approach, it can be seen that the optimum objective functions are Nu=25.67 and ṁ=24.68 kg/h·m, corresponding to design parameters h=0.18 m, d=0.2 m, T_abs=46.81℃ and T₀=20℃. The optimal ventilation flow rate is enhanced by about 96.65% compared to the minimum ventilation rate, while solar energy consumption is reduced by 49.54% compared to the maximum ventilation rate.

• Korean Journal of Radiology
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• v.23 no.5
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• pp.517-528
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• 2022

Due to its excellent diagnostic performance, CT is the mainstay of diagnostic test in adults with suspected acute appendicitis in many countries. Although debatable, extensive epidemiological studies have suggested that CT radiation is carcinogenic, at least in children and adolescents. Setting aside the debate over the carcinogenic risk of CT radiation, the value of judicious use of CT radiation cannot be overstated for the diagnosis of appendicitis, considering that appendicitis is a very common disease, and that the vast majority of patients with suspected acute appendicitis are adolescents and young adults with average life expectancies. Given the accumulated evidence justifying the use of low-dose CT (LDCT) of only 2 mSv, there is no reasonable basis to insist on using radiation dose of multi-purpose abdominal CT for the diagnosis of appendicitis, particularly in adolescents and young adults. Published data strongly suggest that LDCT is comparable to conventional dose CT in terms of clinical outcomes and diagnostic performance. In this narrative review, we will discuss such evidence for reducing CT radiation in adolescents and young adults with suspected appendicitis.