• Membrane and Water Treatment
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• v.14 no.4
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• pp.181-189
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• 2023

The Covid-19 pandemic has increased demand for chlorine-based sanitizing solutions, most of which contain hypochlorous acid (HOCl) as an active agent. Free chlorine (HOCl) in these sanitizers is crucial for their efficacy. Disposable test strips are affordable and convenient tools for determining various qualitative and quantitative parameters. In this study, disposable opto-chemical test strips were developed by physically immobilizing 3,3',5,5'-tetramethylbenzidine (TMB) and o-dianisidine (o-D) reagents on chromatography and filter paper-based test strips for the visualization and detection of free chlorine in the form of HOCl. The reagents undergo a rapid color change upon reaction with chlorine through a redox reaction. The paper-based test strips showed rapid color change within a minute and a low sample volume requirement (1 ml). This portable, disposable paper-based test strip is a simple and cost-effective way to rapidly detect the presence of HOCl sanitizers for home and field applications. Both TMB and o-D successfully detected chlorine. Chromatography paper proved to be the more efficient option among the two papers used as substrates for the reagents (TMB and o-D). It exhibited high retention capacity and high performance in terms of color transformation when reacting with HOCl, even after two months of storage.

• Structural Engineering and Mechanics
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• v.90 no.1
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• pp.97-106
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• 2024

This paper presents a significant contribution to aided design by conducting an analytical examination of geometric links with the aim of establishing criteria for assessing an analogy measure of the extrinsic geometric and kinematic characteristics of the Variable Compression Ratio (VCR) engine with a Geared Mechanism (GBCM) in comparison to the existing Fixed Compression Ratio (FCR) engine with a Standard-Reciprocating Crankshaft configuration. Employing a mechanical approach grounded in projective computational methods, a parametric study has been conducted to analyze the kinematic behavior and geometric transformations of the moving links. The findings indicate that in order to ensure equivalent extrinsic behavior and maintain consistent input-output performance between both engine types, precise adjustments of intrinsic geometric parameters are necessary. Specifically, for a VCR configuration compared to an FCR configuration, regardless of compression ratio and gearwheel radius, for the same crankshaft ratios and stroke lengths, it is imperative to halve lengths of connecting rods, and crank radius. These insights underscore the importance of meticulous parameter adjustment in achieving comparable performance across different engine configurations, offering valuable implications for design optimization.

• Steel and Composite Structures
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• v.51 no.5
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• pp.473-485
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• 2024

This paper proposes a composite form of fuzzy adaptive control plan based on a robust observer. The fuzzy 2D control gains are regulated by the parameters in the LMIs. Then, control and learning performance indices with weight matrices are constructed as the cost functions, which allows the regulation of the trade-off between the two performance by setting appropriate weight matrices. The design of 2D control gains is equivalent to the LMIs-constrained multi-objective optimization problem under dual performance indices. By using this proposed smart tracking design via fuzzy nonlinear criterion, the data link can be further extended. To evaluate the performance of the controller, the proposed controller was compared with other control technologies. This ensures the execution of the control program used to track position and trajectory in the presence of great model uncertainty and external disturbances. The performance of monitoring and control is verified by quantitative analysis. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.

• Structural Engineering and Mechanics
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• v.89 no.2
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• pp.213-223
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• 2024

This paper proposes a composite design of fuzzy adaptive control scheme based on TMD RC structural system and the gain of two-dimensional fuzzy control is controlled by parameters. Monitoring and learning in LMI then produces performance indicators with a weighting matrix as a function of cost. It allows to control the trade-off between the two efficiencies by adjusting the appropriate weighting matrix. The two-dimensional Boost control model is equivalent to the LMI-constrained multi-objective optimization problem under dual performance criteria. By using the proposed intelligent control model, the fuzzy nonlinear criterion is satisfied. Therefore, the data connection can be further extended. Evaluation of controller performance the proposed controller is compared with other control techniques. This ensures good performance of the control routines used for position and trajectory control in the presence of model uncertainties and external influences. Quantitative verification of the effectiveness of monitoring and control. The purpose of this article is to ensure access to adequate, safe and affordable housing and basic services. Therefore, it is assumed that this goal will be achieved in the near future through the continuous development of artificial intelligence and control theory.

• Journal of Korean Association for Spatial Structures
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• v.24 no.2
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• pp.83-90
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• 2024

Machine learning is widely applied to various engineering fields. In structural engineering area, machine learning is generally used to predict structural responses of building structures. The aging deterioration of reinforced concrete structure affects its structural behavior. Therefore, the aging deterioration of R.C. structure should be consider to exactly predict seismic responses of the structure. In this study, the machine learning based seismic response prediction model was developed. To this end, four machine learning algorithms were employed and prediction performance of each algorithm was compared. A 3-story coupled shear wall structure was selected as an example structure for numerical simulation. Artificial ground motions were generated based on domestic site characteristics. Elastic modulus, damping ratio and density were changed to considering concrete degradation due to chloride penetration and carbonation, etc. Various intensity measures were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks and extreme gradient boosting algorithms present good prediction performance.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.107-114
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• 2024

Mobile ad hoc networks represent self-configuring networks of mobile devices that communicate without relying on a fixed infrastructure. However, traditional routing protocols in such networks encounter challenges in selecting efficient and reliable routes due to dynamic nature of these networks caused by unpredictable mobility of nodes. This often results in a failure to meet the low-delay and low-energy consumption requirements crucial for such networks. In order to overcome such challenges, our paper introduces a novel multi-objective and adaptive routing scheme based on the Q-learning reinforcement learning algorithm. The proposed routing scheme dynamically adjusts itself based on measured network states, such as traffic congestion and mobility. The proposed approach utilizes Q-learning to select routes in a decentralized manner, considering factors like energy consumption, load balancing, and the selection of stable links. We present a formulation of the multi-objective optimization problem and discuss adaptive adjustments of the Q-learning parameters to handle the dynamic nature of the network. To speed up the learning process, our scheme incorporates informative shaped rewards, providing additional guidance to the learning agents for better solutions. Implemented on the widely-used AODV routing protocol, our proposed approaches demonstrate better performance in terms of energy efficiency and improved message delivery delay, even in highly dynamic network environments, when compared to the traditional AODV. These findings show the potential of leveraging reinforcement learning for efficient routing in ad hoc networks, making the way for future advancements in the field of mobile ad hoc networking.

• Steel and Composite Structures
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• v.50 no.6
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• pp.609-625
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• 2024

This paper presents an in-depth analysis of the nonlinear vibration of microbeams, with a particular emphasis on their application in sports monitoring systems. The research utilizes classical beam theory, modified couple stress theory, and von-Kármán nonlinear parameters to explore the behavior of microbeams. These microbeams are characterized by a non-uniform geometry, with materials that continuously change along the beam radius and a thickness that varies along the beam length. The main contribution lies in its exploration of the stability of smart sensors in sports structures, particularly those with non-uniform geometries. The research findings indicate that these non-uniform microbeams, when used in smart systems made of functionally graded temperature-dependent materials, can operate effectively in thermal environments. The smart system developed in this study demonstrates significant potential for use in sports applications, particularly in monitoring and gathering information. The insights gained from this research contribute to the understanding of the performance and optimization of microbeams in sports applications, particularly in the context of non-uniform geometries. This research, therefore, provides a foundation for the development of advanced, reliable, and efficient monitoring systems in sports applications.

• Geomechanics and Engineering
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• v.37 no.2
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• pp.167-178
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• 2024

The natural frequency shift under cyclic environmental loads is a key issue in the design of monopile-based offshore wind power turbines because of their dynamic sensitivity. Existing evidence reveals that the natural frequency shift of the turbine system in sand is related to the varying foundation stiffness, which is caused by soil deformation around the monopile under cyclic loads. Therefore, it is an urgent need to investigate the effect of soil deformation on the system frequency. In the present paper, three generalized geometric models that can describe soil deformation under two-way cyclic loads are proposed. On this basis, the cycling-induced changes in soil parameters around the monopile are quantified. A theoretical approach considering three-spring foundation stiffness is employed to calculate the natural frequency during cycling. Further, a parametric study is conducted to describe and evaluate the frequency shift characteristics of the system under different conditions of sand relative density, pile slenderness ratio and pile-soil relative stiffness. The results indicate that the frequency shift trends are mainly affected by the pile-soil relative stiffness. Following the relevant conclusions, a design optimization is proposed to avoid resonance of the monopile-based wind turbines during their service life.

• Journal of Korea Water Resources Association
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• v.40 no.9
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• pp.677-685
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• 2007

The objective of this study is to evaluate the applicability of multi-objective genetic algorithm(MOGA) in order to calibrate the parameters of conceptual rainfall-runoff model, Tank model. NSGA-II, one of the most imitating MOGA implementations, is combined with Tank model and four multi-objective functions such as to minimize volume error, root mean square error (RMSE), high flow RMSE, and low flow RMSE are used. When NSGA-II is employed with more than three multi-objective functions, a number of Pareto-optimal solutions usually becomes too large. Therefore, selecting several preferred Pareto-optimal solutions is essential for stakeholder, and preference-ordering approach is used in this study for the sake of getting the best preferred Pareto-optimal solutions. Sensitivity analysis is performed to examine the effect of initial genetic parameters, which are generation number and Population size, to the performance of NSGA-II for searching the proper paramters for Tank model, and the result suggests that the generation number is 900 and the population size is 1000 for this study.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.3104-3104
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• 2001

The research described here was undertaken with the aim of monitoring, optimizing and ultimately controlling the production of heterofermentative microbes used as starters in the salami industry. The use of starter cultures in the fermented meats industry is a well-established technique used to shorten and standardize the ripening process, and to improve and control the organoleptic quality of the final product. Starter cultures are obtained by the submerged cultivation of suitable microorganisms in stirred, and sometimes aerated, fermenters where monitoring of key physiological parameters such as the concentration of biomass, substrates and metabolites suffers from the general lack of real-time measurement techniques applicable to aseptic processes. In this respect, the results of the present work are relevant to all submerged fermentation processes. Previous work on the application of on-line NIR spectroscopy to the lactic acid fermentation (Dosi et al. - Monreal NIR1995) had successfully used a system based on a measuring cell included in a circulation loop external to the fermenter. The fluid handling and sterility problems inherent in an external circulation system prompted us to explore the use of an in-line system where the NIR probe is immersed in the culture and is thus exposed to the hydrodynamic conditions of the stirred and aerated fluid. Aeration was expected to be a potential source of problems in view of the possible interference of air bubbles with the measurement device. The experimental set-up was based on an in-situ sterilizable NIR probe connected to the instrument by means of an optical fiber bundle. Preliminary work was carried out to identify and control potential interferences with the measurement, in particular the varying hydrodynamic conditions prevailing at the probe tip. We were successful in defining the operating conditions of the fermenter and the geometrical parameters of the probe (flow path, positioning, etc.) were the NIR readings were reliable and reproducible. The system thus defined was then used to construct and validate calibration curves for tile concentration of biomass, carbon source and major metabolites of two different microorganisms used as salami starters. Real-time measurement of such parameters coupled with the direct interfacing of the NIR instrument with the PC-based measurement and control system of the fermenter enabled the development of automated strategies for the interactive optimization of the starter production process.