Search

In the cases of designing fuzzy control systems, tuning and optimizing fuzzy controllers are challenging problems. This work proposes an optimal fuzzy system to control the operations of two-wheeled balancing mobile robots (2WBMRs). The proposed control system is designed with a combination of three control loops using three different fuzzy controllers. The first loop is used for position control, the second loop for balance control and the third control loop for the direction of the 2WBMR. The proposed fuzzy controllers are designed based on relational models and optimized to obtain the best performances. The designed fuzzy controllers using the optimal membership functions for the output linguistic variables with the shapes are determined by the cross-entropy optimization method. The designed fuzzy controllers are tested and evaluated by a real-time system using the STM32F4 microcontroller. The analytical and simulation results in the real-time system for the 2WBMR have shown the efficiency of the proposed control process. The optimal fuzzy controllers are highly effective to control the translational and rotational motion of the body, which is also successfully implemented using a hardware model.

Abstract: Alzheimer’s disease (AD) is the most common cause of dementia in the elderly, leading to a slow and irreversible decline in mental function. Cholinergic impairment has been recognized as one of the reasons leading to cognitive degradation in this disease; therefore, the inhibitors of acetylcholinesterase (AChE) are current important therapeutic agents. This study aimed to evaluate the AChE inhibitory activities of sesquiterpenoids from the rhizomes of Homalomena pendula. Among fourteen isolates, teucmosin showed a significant AChE inhibition with an IC50value of 4.53 ± 0.39 μM, which was comparable to berberine (positive control, IC50= 3.78 ± 0.51 μM). The in silico investigations indicated that teucmosin possessed good pharmacokinetic properties, drug-likeness, and low toxicities on most common targets in AD. The molecular docking study and molecular dynamics simulation revealed the mode of interaction of teucmosin with the enzyme and indicated that this compound could serve as a dual binding site (CAS and PAS) inhibitor of AChE. Teucmosin could be considered as a promising candidate for AD due to its significant anti-cholinesterase activity. Graphical abstract:

ABSTRACTSmart city initiatives have the potential to address many contemporary urban challenges, utilizing information and technology. Increasingly, smart cities are considered as social innovation processes to achieve sustainable and inclusive urban development, being influenced by broader socio-economic and institutional contexts of cities. This paper explores ‘smart city transitions’ across varied urban contexts, in particular, how smart city transitions are enacted and how they contribute to inclusive urban transformation and public value. Using a multiple case studies approach, the research investigated infrastructure planning practices in Amsterdam in the Netherlands, Seoul in Korea, Portland in the U.S. and Ho Chi Minh City (HCMC) in Vietnam, cities that were known for strong efforts to establish integrated platforms to enhance societal benefits. Our analysis showed that each city has addressed its goals around sustainability, equity and affordability by reinforcing the engagement of multiple actors with the support of integrated platforms that facilitate open and multi-directional information flow in a transparent manner. In Amsterdam, innovative solutions for sustainable use of resources have been invented and distributed through multi-level social networks, contributing to the transformation into a circular economy.In Seoul and HCMC, the city's persistent efforts to utilize an open and integrated platform resulted in proactive engagement and collaboration of public and private actors in improving quality, equity and efficiency of transit services. Portland has tackled inequitable access and mistrust issues by setting principles for data governance and facilitating equity in the adoption of innovative technologies. Our research revealed that four cities established different forms of integrated platforms such as a centrally-controlled platform and a community-centred platform in order to address specific socio-economic issues within an institutional setting of each city. We concluded that building an integrated platform is not easy, but it is a critical prerequisite for the process of sustainable transformation to truly achieve smart cities across the globe.

Pavement management systems include road surveying, data analysis, identification of rehabilitated sections, determination of treatment methods, and budget optimization for maintenance and rehabilitation (M&R). These complex processes challenge many agencies in determining the most appropriate M&R strategies for the current year and choosing rehabilitation alternatives using life cycle cost analysis. In addition, these are time-consuming processes since the analysis and interpretation are done separately. In this study, an automated integrated algorithm is developed to help agencies determine the appropriate rehabilitated homogeneous section and optimize the budget at the network level for single and multilane roads. The algorithm was developed based on the pruned exact linear time and changepoints for a range of penalties methods in determining homogeneous sections from distresses on the surfaces being surveyed on single lanes. An additional algorithm is then proposed to identify homogeneous sections by considering adjacent multilane sections. Finally, the prioritized homogeneous sections for rehabilitation are determined by optimizing the available budget at the network level, considering the distress index and recommended rehabilitation type. During optimization, different budget constraint scenarios were considered to satisfy several requirements from agencies considering a random search approach. The proposed algorithm was applied to real field data where it was found that the recommended M&R strategies for the homogenized sections using the proposed approach are feasible, practical, and reasonable. It is recommended that the performance model used in this study be developed further to improve the proposed integrated algorithm.

It is shown that the attractor of an autonomous Caputo fractional differential equation of order α∈(0,1)in Rdwhose vector field has a certain triangular structure and satisfies a smooth condition and dissipativity condition is essentially the same as that of the ordinary differential equation with the same vector field. As an application, we establish several one-parameter bifurcations for scalar fractional differential equations including the saddle-node and the pichfork bifurcations. The proof uses a result of Cong & Tuan [2] which shows that no two solutions of such a Caputo FDE can intersect in finite time.

We consider a version of the pole placement problem for one-sided linear discrete time-varying linear systems. Our purpose is to prove that uniform complete controllability is equivalent to possibility of arbitrary assignment of the dichotomy spectrum. [ABSTRACT FROM AUTHOR]

Rainfall intensity expected great changes under changing climate. Therefore, using the intensity-duration-frequency (IDF) curves based on historic rainfall data likely leads to the underestimation of related-risks to the design of drainage systems. For future conditions, probability distributions used in the establishment of IDF curves might need to be re-evaluated. This study investigates the distributions of Gumbel, generalised extreme value, generalised Laplace and generalised exponential in rainfall frequency analysis for Lower Da River Basin, Northern Vietnam. The results indicated that generalised Laplace best-fitted to observation data, but generalised extreme value is the most appropriate distribution for generating IDF curves under changing climate. Importantly, at level of 50% percentile, the strongest changes in rainfall intensity range from 2.7% at 10 years to 41.4% at 200 years and from 5.5% at 25 years to 22.0% at 200 years of return period under RCP4.5 and RCP8.5, respectively for duration of 72 hours.

Cracks are an acute distress in an asphalt pavement, which must be detected and quantified to diagnose the pavement’s health. Hence, many researchers have developed methods to detect cracks based on three main techniques: image processing, machine learning (ML), and deep learning (DL). Among these three techniques, DL has been recognised as an excellent method for crack detection because it assures high accuracy with an adequate analysis time. However, choosing an appropriate DL algorithm to identify cracks in an asphalt pavement is challenging for both transportation agencies and researchers. This study has identified the bigger picture of DL methods for crack identification in asphalt pavement. The authors evaluated several DL-based crack identification algorithms from the literature, such as crack classification, crack object detection, pixel-level crack segmentation, generative adversarial networks (GANs) for crack segmentation, and crack identification using unsupervised learning. Moreover, 26 DL-based crack detection models (25 supervised learning models and one unsupervised learning model) were analysed on the same dataset to test the performance of each model using consistent assessment metrics. The testing results suggest that ResNet and DenseNet are the best options for crack classification, while Faster R-CNN should be used for crack object detection and pix2pix is suggested for crack segmentation. It is also recommended that semi-supervised and unsupervised learning be further studied to efficiently detect cracks in an asphalt pavement.

An autonomous Caputo fractional differential equation of order α∈ (0,1) in a finite dimensional space whose vector field satisfies a global Lipschitz condition is shown to generate a semi-dynamical system in the function space Cof continuous functions with the topology uniform convergence on compact subsets. This contrasts with a recent result of Cong and Tuan (J. Integral Equ. Appl.: 29, 585–608, 2017), which showed that such equations do not, in general, generate a dynamical system on the state space.

A numerical model based on the particle finite element method (PFEM) combined with a hypoplastic constitutive model is proposed for the analysis of soft soil excavations by means of single and multiple excavation tools. The PFEM allows to efficiently account for large deformations of the excavated soil material and free surfaces characterizing the simulation of tool–soil interaction during excavation. The utilization of a hypoplastic model, formulated in rate form, allows for a straightforward coupling with the standard velocity-based PFEM. Furthermore, effects such as pressure and density dependency of the soil stiffness are consistently incorporated into the formulation. The solution of the governing equations is performed implicitly, while an adaptive sub-stepping scheme is employed for the explicit time integration of the constitutive equation. Thus, the accuracy of the solution is improved at both global and local (constitutive) levels. The performance of the method is evaluated by means of the numerical re-analysis of selected geotechnical benchmark examples and soft soil excavations in 2D and 3D setups.

Obesity, characterized by excessive adipose tissue accumulation, has emerged as a crucial determinant for a wide range of chronic medical conditions. The identification of effective interventions for obesity is of utmost importance. Widely researched antiobesity agents focus on pancreatic lipase, a significant therapeutic target. This study presented the evaluation of ten flavonoid compounds in terms of their inhibitory activities against pancreatic lipase, utilizing both in vitro and in silico approaches. The results indicated that all tested compounds demonstrated modest and weaker inhibitory activities compared to the reference compound, orlistat. Among the compounds investigated, F01 exhibited the highest potency, with an IC50 value of 17.68 ± 1.43 µM. The enzymatic inhibition kinetic analysis revealed that F01 operated through a competitive inhibition mechanism with a determined Ki of 7.16 μM. This value suggested a moderate binding affinity for the pancreatic lipase enzyme. Furthermore, the associated Vmax value was quantified at 0.03272 ΔA·min−1. In silico studies revealed that F01 displayed a binding mode similar to that of orlistat, despite lacking an active functional group capable of forming a covalent bond with Ser152 of the catalytic triad. However, F01 formed a hydrogen bond with this crucial amino acid. Furthermore, F01 interacted with other significant residues at the enzyme’s active site, particularly those within the lid domain. Based on these findings, F01 demonstrates substantial potential as a candidate for further investigations.

The current thermoremendable polyurethanes (PUs) based on reversible Diels–Alder (DA) chemistry featuring both good mechanical properties and efficient macrodamage healability are up to now built with the DA bonds located in the hard domains with restricted mobility, which hinders the DA reversibility. Thus, the healing process in these materials requires predissociation of DA bonds via the retro reaction at high temperatures (110–180 °C) followed by DA re-formation, which may compromise the material performance integrity. Here, we show a design of thermoset PUs containing dynamic DA entities engineered at the interface between the hard and soft domains that combine high modulus and toughness with mild-temperature-triggered molecular mobility, which is a prerequisite for efficient healing capability. This concept of molecular design enables PUs to have great mechanical properties (Young’s modulus ∼80–225 MPa, ultimate tensile strength ∼16–30 MPa, and toughness ∼26–96 MJ m–3) and simultaneously remarkable healing ability at mild temperatures (60–70 °C) of macroscratches, punctures, and complete cuts. The mechanical and healing properties can be tuned by varying the DA bond content. These materials are the first reported DA-based PU materials showing excellent healing efficiency at mild temperatures without compensation of their great mechanical properties.

Multiple studies investigating the use of focused cardiac ultrasound (FCU) in lower and middle-income countries and in medically underserved areas of the United States have demonstrated utility in echocardiographic screening algorithms performed by a variety of operators at different levels of training. No study to date has employed previously untrained nurses in a medically underserved setting to identify older adults with cardiac disorders. The aim of this study was to assess the accuracy of nurse-performed FCU to screen adult subjects at a village health center in Vietnam.

This study presents numerical and experimental models for the analysis of the excavation of soft soils by means of a cutting tool. The computational model is constructed using an Updated Lagrangean (UL) velocity-based Finite Element approach. A hypoplastic formulation is employed to describe the constitutive behavior of soft soils. Large displacements and deformations of the ground resulting from the cutting tool-soil interaction are handled by means of the Particle Finite Element method, characterized by a global re-meshing strategy and a boundary identification procedure called α-shape technique. The capabilities and performance of the proposed model are demonstrated through comparative analyses between experiments and simulations of cutting tool-soft soil interactions. The experiments are performed using an excavation device at Ruhr-Universität Bochum (RUB), Germany. The main details concerning the setup and calibration and evolution of the measured draft forces are discussed. Selected computational results characterizing the cutting tool-soft soil interaction including the topology of the free surface, void ratio distribution ahead of the tool, spatio-temporal evolution of the reaction forces and abrasive wear behavior are evaluated.

This paper presents a generalized procedure to optimize cable nets by using the Genetic Algorithm (GA). The finite element program employing 2-, 3- and 4-node isoparametric curved cable elements is utilized to deal with the nonlinear behavior of cable nets under static loads. The allowable stress and the maximum displacement are considered as optimization constraints while the minimum volume is selected as an objective function. To validate the accuracy and efficiency of the proposed procedure, four optimization examples originated from nonlinear analysis problems of cable nets are introduced.

This paper presents a novel, reversible, data hiding and compression scheme that hides secret data into an SMVQ-compressed image and obtains reversibility of the reconstructed SMVQ indices. The SMVQ indices are divided into index block sized 2 × 2 , and four indices in each index-block are processed simultaneously. Fifteen types and four cases are defined for data embedding. Four index values in the sequence are considered together to find a corresponding case and type. Then, the pre-determined number of secret bits is embedded into each index block based on to which case or type of index block the secret bits belong. By processing a block of indices simultaneously, the proposed scheme obtains high embedding capacity, high embedding rate, and low compression rate. In addition, three different configurations, i.e., normal hiding, under hiding, and over hiding schemes, are used to achieve better improvement of the proposed scheme than several previous applications. As shown in the experimental results, the proposed scheme obtains greater efficiency than various existing schemes in terms of embedding capacity, embedding rate, and compression rate. [ABSTRACT FROM AUTHOR]

An efficient seismic fragility assessment method is proposed for underground tunnel structures in this paper. The ground response acceleration method for buried structure (GRAMBS), an efficient quasi-static method considering soil-structure interaction (SSI) effect, is used in the proposed approach to estimate the dynamic response behavior of the underground tunnels. In addition, the pushover analyses are conducted to identify the damage states of tunnels and Latin Hypercube sampling technique is used to consider uncertainties in the design variables. A large set of artificially generated ground motions satisfying a design spectrum for specific earthquake intensity are generated and fragility curves are developed. The seismic fragility curves are represented by two-parameter lognormal distribution function and its two parameters, namely the median and log-standard deviation, are estimated using the maximum likelihood estimates method.

Reversible data hiding recovers the original images without distortion after the secret data are extracted, so it has received considerable attention among researchers in recent years. This work presents a novel reversible data hiding scheme based on the search-order coding (SOC) algorithm and side match vector quantization (SMVQ). The compression performance is improved by encoding the index with either SOC or SMVQ during the data embedding phase. The index of an image block also is encoded by using a few bits, thus improving the compression rate. During the extracting phase, the receiver uses simple steps to extract the secret data and reconstruct the original SMVQ compression code. Our experimental results indicated that, using a size 64 state codebook, the average compression rate with our scheme was 0.41 bpp, which is much better than the compression rates of Chang et al.’s, Yang and Lin’s, and Yang et al.’s schemes, i.e., 0.50, 0.54, and 0.56 bpp, respectively. Furthermore, in addition to reducing the time required for the embedding and extracting phases, the proposed scheme yields a higher embedding rate than the schemes of Yang and Lin and Yang et al. [ABSTRACT FROM AUTHOR]

This paper aims to develop a new numerical model to evaluate the flexural damage behavior of pervious concrete from its compositions. By considering this material within the framework of the quasi elasto-brittle approach, failure is modeled by the phase field method. Then, a taking-placing generation process of the extensive Monte Carlo simulation-type was constructed to account for the statistical effect of the pervious concrete structure. Various numerical investigations have been performed using this model. First, the modeling parameters were calibrated with the three-point bending test, then numerical-experimental correlations were well captured for both elastic and post softening regimes for the different structure sizes. Archived crack pattern analyses were used to examine the influence of the pore structure on certain values of peak load. Finally, the linear relationship between the flexural strength and the porosity was confirmed by agreement with the simulation results, which comprised of empirical references.

We establish the link between linear Lyapunov functions for positive switched systems and corresponding Collatz-Wielandt sets. This leads to an algorithm to compute a linear Lyapunov function whenever a Lyapunov function exists. [ABSTRACT FROM AUTHOR]

Recently, the results of an electrodeposition of nickel showed that the coating plated in supercritical carbon dioxide, Sc-CO 2 , emulsion has smaller grain size, higher hardness, excellent coverage, low surface roughness and pinhole-free microstructure over its conventional counterpart. It was found that, even without the addition of surfactant in the electrolyte, similar improvement over the coating properties was also obtained. However, the presence of surfactant in the Sc-CO 2 electrolyte resulted in a predominant preferred {111} texture. Meanwhile, adjusting boric acid up to 15 g/L and decreasing current density to 5 A/dm 2 resulted in more preferred {111} Ni crystalline as well. In addition, the use of pulse current in the Sc-CO 2 electroplating further modified Ni crystal from {200} to {111} orientation.

In the mining industry, conventional methods such as GPS and total station technology are used most extensively for data collection and in return used to compute volume of extracted materials (ore and waste). In situation where the ore body is bigger in size, and changes dynamically, the use of conventional method to measure volume of ore is not practicable and economically viable because of the workload involved, precision and accuracy of the survey and safety of workers. In this paper a method and work flow of ore heap volume measurement by using 3D laser scanning technique to acquire point cloud data was introduced. RiSCAN PRO and Geomagic studio was used to process the original data (registration, noise elimination, georeferencing, resampling etc.), 3D modeling and volume computations. A comparison on precision of geodetic control points coordinate measured by GPS receivers and 3D laser scanner was carried out. The results indicate that 3D laser scanning technique can effectively be applied to ore output volume measurement since it satisfies the requirement of ore volume measurement.

The advantage of infinite-impulse response (IIR) filters over finite-impulse response (FIR) ones is that the former require a much lower order (much fewer multipliers and adders) to obtain the desired response specifications. However, in contrast with well-developed FIR filter bank design theory, there is no satisfactory methodology for IIR filter bank design. The well-known IIR filters are mostly derived by rather heuristic techniques, which work in only narrow design classes. The existing deterministic techniques usually lead to too high order IIR filters and thus cannot be practically used. In this paper, we propose a new method to solve the low-order IIR filter bank design, which is based on tractable linear-matrix inequality (LMI) optimization. Our focus is the quadrature mirror filter bank design, although other IIR filter related problems can be treated and solved in a similar way. The viability of our theoretical development is confirmed by extensive simulation. [ABSTRACT FROM AUTHOR]

Abstract: Reversible data hiding can restore the original image from the stego image without any distortion after the embedded secret message is exactly extracted. In this paper, a novel, reversible, data hiding scheme for high quality images is proposed in spatial domain. To increase embedding capacity and enhance image quality, the proposed scheme classifies all pixels as wall pixels and non-wall pixels. For wall pixel, the interpolation error is used to embed secret data over the interpolation prediction method. In contrast, the difference value between the non-wall pixel and its parent pixel, which is defined by the direction order, is computed to hide secret data based on the histogram shifting. The experimental results demonstrate that our scheme provides a larger payload and a better image quality than some existing schemes. Moreover, the performance of the proposed scheme is more stable for different images. [Copyright &y& Elsevier]

Abstract: The determination of fuzzy information granules including the estimation of their membership functions play a significant role in fuzzy system design as well as in the design of fuzzy rule based classifiers (FRBCSs). However, although linguistic terms are fundamental elements in the process of elucidating expert’s knowledge, the problem of linguistic term design along with their fuzzy-set-based semantics has not been fully addressed, since term-sets of attributes have not been interpreted as a formalized structure. Thus, the essential relationship between linguistic terms, as syntax, and the constructed fuzzy sets, as their quantitative semantics, or in other words, the problem of the natural semantics of terms behind the linguistic literal has not been addressed. In this paper, we introduce the problem of the design of optimal linguistic terms and propose a method of the design of FRBCSs which may incorporate with the design of linguistic terms to ensure that the presence of linguistic literals are supported not only by data but also by their natural semantics. It is shown that this problem plays a primordial role in enhancing the performance and the interpretability of the designed FRBCSs and helps striking a better balance between the generality and the specificity of the desired fuzzy rule bases for fuzzy classification problems. A series of experiments concerning 17 Machine Learning datasets is reported. [Copyright &y& Elsevier]