ℽ-Aminobutyric acid (GABA) is a non-proteinaceous amino acid. In the mammalian nervous system, GABA functions as an inhibitory neurotransmitter. The present study focused on screening and optimization of ℽ-aminobutyric acid (GABA) yield by lactic acid bacteria by using soymilk as basal media. Lactobacillus fermentum (Lb. fermentum) was isolated from sourdough. The qualitative confirmation of GABA production

In this paper, the nonlinear vibrational behavior of a sandwich plate with embedded viscoelastic material is studied through the use of constitutive equations with fractional derivatives. The studied sandwich structure is consisted of a viscoelastic core that is located between the faces of functionally graded magneto-electro-elastic (FG-MEE). In order to determine the frequency-dependent feature of

Adaptive structures have the ability to modify their shapes in different operational conditions. Multi-stable structures are one of the methods of making adaptive structures. In the bi-stable square laminates, due to geometric symmetry and equality of strain energy between stable states, it is possible to continue actuating between stable states, specially when using dynamic or thermal load. The bi-stability

In an integrated energy system (IES), the operating state of each energy subsystem changes relatively frequently, which can seriously threaten the security of IES operation. A systematic data-driven approach is proposed for detecting anomalies and analyzing the dynamics of IES vulnerability. Firstly, an anomaly detection method is introduced to determine whether there are anomalies in the system operation

Heatsinks have quasi-antenna behavior in many cases and cause interference both at the system level and at the PCB design level. Therefore, determination or prediction of both resonance frequencies and maximum radiated emission are crucial at any design step. In this paper, as a novelty, in 2–8 GHz band, a model based on deep learning is developed to predict resonance frequencies in parallel plate-fin

This paper introduces a novel evolutionary algorithm namely modified exchange market algorithm (MEMA) to solve the various problems in the power system operation topics such as combined heat and power economic emission dispatch (CHPEED), and multi-area economic dispatch (MAED) in the presence of renewable energy sources (RESs). The MEMA is a new version of the EMA that has been modified to improve

Providing efficient support mechanisms for renewable energy promotion has drawn much attention from researchers in the recent years. The connection of a new renewable power plant to the transmission system has impacts on different electricity market indices since the other strategic generation units change their behaviour in the new multi-agent environment. In this paper, as the main contribution to

A time–frequency resolution technique based recognition of power system faults is proposed in the present work. Superlet transformation, a modified and super-resolution form of the wavelet transform, has been used to recognize the type of power system faults occurring in an interconnected power system. The Superlets were tested for sample power system disturbances and found advantageous. An IEEE-9

Electric vehicles (EVs) have a high potential in reducing greenhouse gas emissions and are able to achieve other advantages such as a reduction in local air pollution and increasing energy security. As a result, EVs are rapidly increasing in popularity, electrifying the transportation sector. This poses a serious problem for the grid as existing distribution grids were mainly sized in the pre-EV era

Manual detection of ColoRectal Cancers (CRC) is subject to bias and time-consuming. To be objective and efficient, this study proposes a semiautomated method to predict CRC based on the number of Circulating Tumor Cells (CTCs). To count CTCs, this method uses SVM to find possible CTCs using features such as cell size, the ratio of the image area of the nucleus to that of the cytoplasm, and the color

This research work highlight the newly developed concept of Rosseland approximation and gyrotactic microorganisms in steady, two-dimensional, incompressible flow of Walter's-B nanofluid (non-Newtonian) over a stretchable surface of sheet. Buongiorno nanofluid model, which represents seven important slip mechanisms (i.e., Brownian motion, inertia, Magnus impact, thermophoresis, diffusion-phoresis, gravity

The high levels of iron and manganese found in ground water and utilized by living habitats has made it mandatory to seek a local low cost effective technique to decrease their concentrations. In this study, vermiculite clay and cation exchange resin were used as adsorbent and filter media to examine their ability in the removal and retention of those soluble metal. Different initial concentrations

This paper presents a design and analysis for the PV system with a DC-DC boost converter controlled by the Fractional Order PI controller (FOPI). The study includes obtaining the optimal parameters for the PV model and the operating parameters for the FOPI controller. The first part’s objective function is to search a five-parameter model based on the data-sheet given by commercial PV modules for a

As the botnet makes the way for many illegal activities, it is considered as the most critical threats to cybersecurity. Although many detection models have been presented by the researchers, they couldn’t detect the botnets in an early stage. So to overcome this issue, an enhanced support vector neural network (ESVNN) is presented as the detection model in this paper. For enhancing the classification

The hob forms key component in gear hobbing machine and its health condition directly affects the reliability and safety of entire machine. This paper proposes a multiscale feature extraction scheme based on spectral graph wavelet transform combined with improved random forest, forming a novel hob fault diagnosis technique and realizing multi-scale analysis of vibration signals from the perspective

The article deals with a piezoelectric force sensor, that bases on the use of piezo ceramics PZK 850. These types of sensors were used due to characteristic of the piezo-material (i.e. crystal) particularly for dynamic force measurement only. The developed sensor is suitable to measure static forces up to 50 N; the principle of the measurement of static forces bases on the crystal vibration being damped

Infrared thermography is employed by different methodologies and techniques to perform characterisations and evaluations in solids, typically related to fracture mechanics and damage, based on monitoring heat generation or temperature changes. In this study, the limits of the current technology for Thermoelastic Stress Analysis (TSA), usually employed under low-frequency loads, are explored to characterise

For tunnels with large cross-sections, demolition of the temporary shoring of the tunnel can pose a very serious threat to the safety of the structure; Therefore it is very important to ascertain the deformation behavior of the tunnel in this stage. In this study, a tunnel settlement inversion model, based on the strain measurements of distributed optical fiber, has been proposed and the feasibility

In recent years, many artificial intelligence - based approaches are proposed for remaining useful life (RUL) prediction of bearings. However, most existing studies neglected the following problems: (1) Run-to-failure data of bearings of are generally less available; (2) Degradation trends of bearings under different working conditions are diverse; (3) Unlabeled data of bearings acquired in the online

For the application of deep learning in the field of fault diagnosis, its recognition accuracy is limited by the size and quality of the training samples, such as small size samples, low signal-to-noise ratio and different working conditions. In order to solve above problems, one novel method for fault classification is proposed based on a Bidirectional Long Short-Term Memory (Bi-LSTM) and a Capsule

This study investigates the performance and robustness of regression machine-learning models in the presence of variability in the experimental database. The main objective of this work is to predict the ultimate load of circular concrete-filled steel tubes. The simulations were designed by combining size of the learning dataset, random realizations and prediction models. The variability (i.e. probability

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This article proposes a novel biogeography-based optimization (NBBO) algorithm to solve the distributed assembly permutation flow-shop scheduling problem with sequence-dependent set-up times (DAPFSP-SDST). The optimization objective of this problem is minimizing the maximum completion time (makespan). In the initialization phase, NBBO generates two kinds of feasible solutions. Secondly, the linear

ABSTRACT The conventional assignment problem is unable to handle scenarios that may arise due to different working modes of machines leading to multiple cost and time entries corresponding to a job–machine pair. The present article deals with this problem and models it as a multi-choice bi-objective assignment problem, the two objectives being assignment cost and bottleneck time. Two different solution

Mine disasters, as associated problems in the development of coal resources, always threaten the life safety of miners and the production safety of enterprises. In coal roadway excavation, the coal in front of the excavation face is in a state of concentrated stress and the deformation is serious. The instability of the coal seam under stress is an important cause of the occurrence of coal and gas

In this paper, we study the use of the mean empirical likelihood (MEL) method in a first-order random coefficient integer-valued autoregressive model. The MEL ratio statistic is established, its limiting properties are discussed, and the confidence regions for the parameter of interest are derived. Furthermore, a simulation study is presented to demonstrate the performance of the proposed method. Finally

This paper explains a region-division-linearization algorithm for solving a class of generalized linear multiplicative programs (GLMPs) with positive exponent. In this algorithm, the original nonconvex problem GLMP is transformed into a series of linear programming problems by dividing the outer space of the problem GLMP into finite polynomial rectangles. A new two-stage acceleration technique is put

Extended Kalman filter (EKF) plays an important role in the acoustic signal processing of underwater positioning. However, accumulative errors and model inaccuracies lead to divergence. Then, attenuation memory EKF is created in response to this issue which needs to manually select all or part of the parameters. Thus, a dynamic-weighted attenuation memory EKF is proposed. Firstly, several underwater

With the widespread use of social networks, social recommendation algorithms that add social relationships between users to recommender systems have been widely applied. Existing social recommendation algorithms only introduced one type of social relationship to the recommendation system, but in reality, there are often multiple social relationships among users. In this paper, a new matrix factorization

A singularly perturbed reaction-diffusion problem with a discontinuous source term is considered. A novel rational spectral collocation combined with a singularity-separated method for this problem is presented. The solution is expressed as , where is the solution of corresponding auxiliary boundary value problem and is a singular correction with direct expressions. The rational spectral collocation

This study focuses on the power allocation (PA) problem in code division multiple access (PDMA) networks with amplify-and-forward (AF) relays. We provide two wireless communication technical performance indexes, which are system throughput and outage probability. A multiobjective version of particle swarm optimization is proposed to solve Pareto-optimal solutions for optimal PA problems. A novel programming

The aging population has become a growing worldwide problem. Every year, deaths and injuries caused by elderly people's falls bring huge social costs. To reduce the rate of injury and death caused by falls among the elderly and the following social cost, the elderly must be monitored. In this context, falls detecting has become a hotspot for many research institutions and enterprises at home and abroad

Planetary gears are widely used in mechanical transmission systems, but the vibration and noise affect their reliability and life. In this paper, the torsional dynamic model of an encased differential planetary gear with coaxial contrarotating outputs considering the time-varying meshing stiffness, damping, and phase difference of all gear pairs is established. By solving the equations of the derived

The coronavirus disease (COVID-19) outbreak started in December 2019 in Wuhan. The virus has spread around the whole world, and it has caused a strong and serious pandemic. Symptoms such as cough, respiratory distress, diarrhea, and fatigue associated with COVID-19 are typical clinical findings. Coronavirus infection has become an important public health concern because of its increasing prevalence

In recent years, companies have increasingly been taking measures to reduce their carbon footprint to minimize environmental impact. However, research that looks at factors that influence carbon emissions is scarce. We address this gap by empirically examining the impact of internal and external initiatives on firms' carbon footprints, as captured by their Scope 1, 2 and 3 emissions. Using secondary

Quantitative evaluation of the impact of traffic accessibility within large cities on innovation quality is conducive to a better understanding of urban governance and sustainable development. This paper analyzed the impact of traffic accessibility on regional and enterprise innovation using the big data from a floating car track monitored by the platform in five large cities in China. The study found

Purpose The purpose of this study is to analyse the effect of different forms of service supplier involvement on the service business dimensions necessary for servitisation and on the resulting servitisation performance. Design/methodology/approach Three different configurations of service supplier involvement are considered in this study: black box (service design and execution driven by the service

Purpose This study proposes the Smart SME Technology Readiness Assessment (SSTRA) methodology which aims to enable practitioners to assess the SMEs Industry 4.0 technology readiness throughout the end-to-end engineering across the entire value chain; the smart product design phase is the focus in this paper. Design/methodology/approach The proposed SSTRA utilises the analytic hierarchy process to prioritise

Purpose This paper aims to examine the role of rational culture in the relationship between lean manufacturing practices and operational productivity in the machinery and equipment industry. Design/methodology/approach This study uses a cross-sectional quantitative approach to conduct the research. Using an online survey questionnaire, 118 responses were collected. SPSS was used to assess validity

Purpose Recent research has shown that the implementation of Industry 4.0 requires companies to (re)adjust their human resource (HR) policies. This article focuses on the relationship between Industry 4.0 and three HR practices: i.e. employee involvement, job design and skill development. Design/methodology/approach We use data of the European Company Survey (ECS) (2019). This nationally representative

Forensic-based investigation (FBI) is recently developed metaheuristic algorithm inspired by the suspect investigation–location–pursuit operations of police officers. This study focuses on the search processes of the FBI algorithm, called Step A and Step B, to improve and increase its performance. For this purpose, opposition-based learning is adopted to Step A to enhance diversity, while Cauchy-based

Monte Carlo Tree Search (MCTS) is a search technique that in the last decade emerged as a major breakthrough for Artificial Intelligence applications regarding board- and video-games. In 2016, AlphaGo, an MCTS-based software agent, outperformed the human world champion of the board game Go. This game was for long considered almost infeasible for machines, due to its immense search space and the need

This work addresses a hybrid scheme for the numerical solutions of time fractional Tricomi and Keldysh type equations. In proposed methodology, Haar wavelets are used for discretization in space while \(\theta\)-weighted scheme coupled with second order finite differences and quadrature rule are employed for temporal discretization and fractional derivative respectively. Stability of the proposed scheme

Single Linkage algorithm is a hierarchical clustering method which is most unsuitable for large dataset because of its high convergence time. The paper proposes an efficient accelerated technique for the algorithm for clustering univariate data with a merging threshold. It is a two-stage algorithm with the first one as an incremental pre-clustering step that uses the farthest neighbour principle to

The problem of attaining energy efficiency in distributed systems is of importance, but a general, non-domain-specific theory of energy-minimal scheduling is far from developed. In this paper, we classify the problems of energy-minimal scheduling and present theoretical foundations of the same. We derive results concerning energy-minimal scheduling of independent jobs in a distributed system with functionally

Electrolyte is very critical to the performance of the high-voltage lithium (Li) metal battery (LMB), which is one of the most attractive candidates for the next-generation high-density energy-storage systems. Electrolyte formulation and structure determine the physical properties of the electrolytes and their interfacial chemistries on the electrode surfaces. Localized high-concentration electrolytes