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A broadband, stable, and non-iterative free-space method is proposed for dielectric constant ε′r determination of low-loss dielectric slabs from reflection-only measurements through simple calibration standards (reflect and air). It is applicable for dispersive samples and does not require thickness information. Simulations of non-disperive and dispersive samples are performed to validate our method. Dielectric constant measurements of polyethylene and Polyoxymethylene samples (9–11 GHz) are carried out to examine the accuracy of our method. IEEE

Let R be a commutative ring with identity. A proper ideal I is said to be an n-ideal of R if for a, b ∈ R, ab ∈ I and a∉0 imply b ∈ I. We give a new generalization of the concept of n-ideals by defining a proper ideal I of R to be a semi n-ideal if whenever a ∈ R is such that a2 ∈ I, then a∈0 or a ∈ I. We give some examples of semi n-ideal and investigate semi n-ideals under various contexts of constructions such as direct products, homomorphic images and localizations. We present various characterizations of this new class of ideals. Moreover, we prove that every proper ideal of a zero dimensional general ZPI-ring R is a semi n-ideal if and only if R is a UN-ring or R ≌ F1 × F2 × … × Fk, where Fi is a field for i = 1,…, k. Finally, for a ring homomorphism f: R → S and an ideal J of S, we study some forms of a semi n-ideal of the amalgamation R ⋈fJ of R with S along J with respect to f. © 2022, Institute of Mathematics, Czech Academy of Sciences.

Facial expression recognition using deep neural networks has become very popular due to their successful performances. However, the datasets used during the development and testing of these methods lack a balanced distribution of races among the sample images. This leaves a possibility of the methods being biased toward certain races. Therefore, a concern about fairness arises, and the lack of research aimed at investigating racial bias only increases the concern. On the other hand, such bias in the method would decrease the real-world performance due to the wrong generalization. For these reasons, in this study, we investigated the racial bias within popular state-of-the-art facial expression recognition methods such as Deep Emotion, Self-Cure Network, ResNet50, InceptionV3, and DenseNet121. We compiled an elaborated dataset with images of different races, cross-checked the bias for methods trained, and tested on images of people of other races. We observed that the methods are inclined towards the races included in the training data. Moreover, an increase in the performance increases the bias as well if the training dataset is imbalanced. Some methods can make up for the bias if enough variance is provided in the training set. However, this does not mitigate the bias completely. Our findings suggest that an unbiased performance can be obtained by adding the missing races into the training data equally.

Let R be a commutative ring with identity and M be a unitary R-module. The aim of this paper is to extend the notion of quasi J -ideals of commutative rings to quasi J -submodules of modules. We call a proper submodule N of M a quasi J -submodule if whenever r ∈ R and m ∈ M such that rm ∈ N and r /∈ (J(R)M: M), then m ∈ M-rad(N). We present various properties and characterizations of this concept (especially in finitely generated faithful multiplication modules). Furthermore, we provide new classes of modules generalizing presimplifiable modules and justify their relation with (quasi) J -submodules. Finally, for a submodule N of M and an ideal I of R, we characterize the quasi J -ideals of the idealization ring R(+)M. © TÜBİTAK doi:10.55730/1300-0098.3290

Let R be a commutative ring with non-zero identity.In this paper, we introduce the concept of weakly J-ideals as a new generalization of J-ideals. We call a proper ideal I of a ring R a weakly J-ideal if whenever a, b is an element of R with 0 not equal ab is an element of I and a is not an element of J(R), then b is an element of I. Many of the basic properties and characterizations of this concept are studied. We investigate weakly J-ideals under various contexts of constructions such as direct products, localizations, homomorphic images. Moreover, a number of examples and results on weakly J-ideals are discussed. Finally, the third section is devoted to the characterizations of these constructions in an amalgamated ring along an ideal.

A new deembedding technique is proposed for relative complex permittivity epsilon(r) determination of dielectric materials using gated free-space measurements. Its three main features are 1) it does not require any formal calibration procedure (calibration-free); 2) it is position-insensitive; and 3) it extracts ripple-free epsilon(r) due to gating process. The objective function derived to determine epsilon(r) by the proposed method is validated by free-space measurements of three dielectric samples (polypropylene, polyethylene, and polyoxymethylene). Besides, the accuracy of our method is compared with the accuracy of other calibrationfree and calibration-dependent methods in the literature.

The grid connected photovoltaic (PV) power plants (PVPPs) are booming nowadays. The main problem facing the PV power plants deployment is the intermittency which leads to instability of the grid. In order to stabilize the grid, either energy storage device - mainly batteries - or a power curtailment technique can be used. The additional cost on utilizing batteries make it not preferred solution, because it leads to a drop in the return on investment (ROI) of the project. A good alternative, is using a customized load (such as; cryptocurrency-based loads) which consumes the surplus energy. This paper investigating the usage of a customized load - cryptocurrency mining rig - to create an added value for the owner of the plant and increase the ROI of the project. These devices are widely used to perform the required calculations for validating the transactions on the network of the Blockchain. A comparison between the ROI of the mining rig and the battery have been conducted in this study. Based on this study the mining rig has superior ROI of 7.7% - in the case with the lowest ROI - compared to 4.5% for battery. Moreover, an improved controlling strategy is developed to combine both the battery and mining rig in the same system. The developed strategy is able to keep the profitability as high as possible during the fluctuation of the mining network.

In this paper, we introduce weakly 1-absorbing primary submodules of modules over commutative rings. Let [Formula: see text] be a commutative ring with a nonzero identity and [Formula: see text] be a nonzero unital module. A proper submodule [Formula: see text] of [Formula: see text] is said to be a weakly 1-absorbing primary submodule if whenever [Formula: see text] for some nonunit elements [Formula: see text] and [Formula: see text] then [Formula: see text] or [Formula: see text]-[Formula: see text] where [Formula: see text]-[Formula: see text] is the prime radical of [Formula: see text] Many properties and characterizations of weakly 1-absorbing primary submodules are given. We also give the relations between weakly 1-absorbing primary submodules and other classical submodules such as weakly prime, weakly primary, weakly 2-absorbing primary submodules. Also, we use them to characterize simple modules.

Let R be a commutative ring with $1\neq0$. In this paper, we introduce the concept of weakly 1-absorbing primary ideal which is a generalization of 1-absorbing ideal. A proper ideal $I$ of $R$ is called a weakly 1-absorbing primary ideal if whenever nonunit elements $a,b,c\in R$ and $0\neq abc\in I,$ then $ab\in I$ or $c\in\sqrt{I}$. A number of results concerning weakly 1-absorbing primary ideals and examples of weakly 1-absorbing primary ideals are given. Furthermore, we give the correct version of a result on 1-absorbing ideals of commutative rings., It is submitted on September,2019

A microwave method is proposed to determine the forward and backward propagation constants (gamma ⁺ and gamma ⁻) and the wave impedance ( $z_{w}$ ) of reciprocal and non-reciprocal microwave networks whose positions are not known within their measurement cells (position-insensitive). The proposed method relies purely on analytical expressions and can also evaluate the reference plane transformation distances. Scattering parameter measurements at the X-band (8.2-12.4 GHz) of a reciprocal network (a waveguide straight) and a non-reciprocal network (a microwave phase shifter) arbitrarily positioned into their measurement cells were conducted to retrieve gamma ⁺, gamma ⁻, and $z_{w}$ for validation of our method and testing its position-insensitive property. The importance of the method becomes apparent when compared to conventional methods whose accuracy is based on precise determination of the reference planes.

The ChaLearn large-scale gesture recognition challenge has been run twice in two workshops in conjunction with the International Conference on Pattern Recognition (ICPR) 2016 and International Conference on Computer Vision (ICCV) 2017, attracting more than $200$ teams round the world. This challenge has two tracks, focusing on isolated and continuous gesture recognition, respectively. This paper describes the creation of both benchmark datasets and analyzes the advances in large-scale gesture recognition based on these two datasets. We discuss the challenges of collecting large-scale ground-truth annotations of gesture recognition, and provide a detailed analysis of the current state-of-the-art methods for large-scale isolated and continuous gesture recognition based on RGB-D video sequences. In addition to recognition rate and mean jaccard index (MJI) as evaluation metrics used in our previous challenges, we also introduce the corrected segmentation rate (CSR) metric to evaluate the performance of temporal segmentation for continuous gesture recognition. Furthermore, we propose a bidirectional long short-term memory (Bi-LSTM) baseline method, determining the video division points based on the skeleton points extracted by convolutional pose machine (CPM). Experiments demonstrate that the proposed Bi-LSTM outperforms the state-of-the-art methods with an absolute improvement of $8.1\%$ (from $0.8917$ to $0.9639$) of CSR., 14 pages, 8 figures, 6 tables

A new formalism using line-line measurements is proposed to improve the accuracy of propagation constant measurement of reflection-asymmetric networks using non-calibrated scattering (S-) parameters. For this measurement, the method uses a reference network with arbitrary forward and backward impedance, propagation constant, and length, thus giving flexibility in the application of line-line methods. S-parameter measurements were carried out for propagation constant extraction of a reflection-asymmetric waveguide loaded with a bianisotropic metamaterial slab made by C-shaped split-ring-resonators using two different kinds of reference networks (two empty waveguide sections as the first kind and the same sections loaded by polyethylene samples as the second kind). It is observed that the standard deviation in the extracted real part of the propagation constant of this network by our method could be reduced by using the first kind of reference network, indicating that the accuracy of our method could be improved using a suitable reference network.

Let $R$ be a commutative ring with identity. In this paper, we introduce the concept of quasi $J$-ideal which is a generalization of $J$-ideal. A proper ideal of $R$ is called a quasi $J$-ideal if its radical is a $J$-ideal. Many characterizations of quasi $J$-ideals in some special rings are obtained. We characterize rings in which every proper ideal is quasi $J$-ideal. Further, as a generalization of presimplifiable rings, we define the notion of quasi presimplifiable rings. We call a ring $R$ a quasi presimplifiable ring if whenever $a,b\in R$ and $a=ab$, then either $a$ is a nilpotent or $b$ is a unit. It is shown that a proper ideal $I$ that is contained in the Jacobson radical is a quasi $J$-ideal (resp. $J$-ideal) if and only if $R/I$ is a quasi presimplifiable (resp. presimplifiable) ring.

Mechanical and electromagnetic properties (over 2-16 GHz) of self-compacted geopolymer concrete (SCGC) samples with different amounts of nanosilica (NS) and steel-fiber (SF) have been examined. From the mechanical tests, it is observed that, while the amount of NS added to SCGC samples does not make any noticeable change in compressive strength and modulus of elasticity values, an increase in the amount and/or aspect ratio of SF additives improves these values. From the electromagnetic tests, it is noted that the effect of SF on the reflection properties of SCGC samples is relatively smaller than the effect of NS. Besides, while the incorporation of NS improves the resonance characteristics of transmission properties, additives of SF decrease these properties over the entire frequency band. Finally, sample C7, which has 1% SF with a smaller diameter and 2% NS in reference to the mass of the binder, has the optimum NS and SF additives, producing maximum absorbance values.

Fused deposition modeling (FDM) is a 3D printing technology in which the melt extrusion method is used for the production of thermoplastic parts. 3D printed thermoplastic materials produced by this method suffer from a particularly significant problem, however, namely poor interfacial bond formation that results in weak mechanical performance. This work proposes a thermal process to enhance the strength of the interlayer adhesion of 3D printed PEI thermoplastic materials. The annealing process was determined as a suitable post-processing procedure and was the focus of this work. Annealing was carried out in an oven at temperatures of 220, 225, 230, and 235 degrees C; it was determined that annealing performed at 225 degrees C in particular was highly desirable in terms of enhancing interlayer adhesion strength. In this work, characterization (FTIR, XRD, and SEM) and mechanical (tensile, bending, and hardness) analyses of 3D printed PEI were performed to better understand the strength of interlayer adhesion and overcome a mechanical performance limitation of this material. According to the tensile, bending, and hardness test results, the greatest improvements were found as increase of 10, 5, and 12%, respectively.

Intensity of natural disasters has substantially increased; disaster management has gained importance along with this reason. In addition, social media has become an integral part of disaster management. Before, during and after disasters; people use social media and large number of output is obtained through social media activities. In this regard, Twitter is the most popular social media tool as micro blogging. Twitter has also become significant in complex disaster environment for coordinating events. It provides a swift way to collect crowd-sourced information. So, how do humanitarian organizations use Twitter platform? Humanitarian organizations utilize resources and related information while managing disasters. The effective use of social media by humanitarian agencies causes increased peoples’ awareness. The international federation of red cross and Red Crescent Societies (IFRC) is the most significant humanitarian organization that aims providing assistance to people. Thus, the aim of this paper is to analyze IFRC’s activities on Twitter and propose a perspective in the light of theoretical framework. Approximately, 5201 tweets are passed the pre-processing level, some important topics are extracted utilizing word labeling, latent dirichlet allocation (LDA model) and bag of Ngram model and sentiment analysis is applied based on machine learning classification algorithms including Naïve Bayes, support vector machine SVM), decision tree, random forest, neural network and k-nearest neighbor (kNN) classifications. According to the classification accuracies, results demonstrate the superiority of support vector machine among other classification algorithms. This study shows us how IFRC uses Twitter and which topics IFRC emphasizes more. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature.

This paper presents evolution of hyperbolic sinusoidal Gaussian (HSG) beam and its point-like scintillation while propagating through turbulent atmosphere. We benefit from random phase screen approach to evaluate received field and scintillation. We see that astigmatic beams, which source parameters are not equal, are resistive against atmosphere considering intensity distribution. In case of scintillation, all selected HSG beams have less scintillation index than Gauss beam. In addition, astigmatism decreases scintillation at constant Gaussian source size. We anticipate that optical wireless communication devices can be designed using our outputs.

Human activity recognition (HAR) is a wide research topic in a field of computer science. Improving HAR can lead to massive breakthrough in humanoid robotics, robots used in medicine and in the field of autonomous vehicles. The system that is able to recognise human and its activity without any errors and anomalies would lead to safer and more empathetic autonomous systems. During this research work, multiple neural networks models, with different complexity, are being investigated. Each model is re-trained on the proposed unique data set, gathered on automated guided vehicle (AGV) with the latest and the modest sensors used commonly on autonomous vehicles. The best model is picked out based on the final accuracy for action recognition. Best models pipeline is fused with YOLOv3, to enhance the human detection. In addition to pipeline improvement, multiple action direction estimation methods are proposed. © 2020, Springer-Verlag London Ltd., part of Springer Nature.

This paper deals with modeling and simulation of the total harmonic distortion of the current (THDI) dispatched from the inverter and connected to nonlinear load. The change of THDI was examined in relation to the ambient temperature (T) and solar irradiance (G).The developed model is being used to extract parameters for a given THDI as a function of temperature and solar radiation. This study outlines the working principle of photovoltaic (PV) panel as well as PV array. Off-grid PV system is modeled by using Matlab/Simulink program, and detailed analytical study has been carried out in this work. The design, modeling and simulation of this study are performed from 50 up to 988 W/m2 for solar irradiance. Harmonic components have negative effects on the steady-voltage stability of the PV system. Therefore, analytical expression is needed for steady-state stability analysis in order to reduce negative effects. Hence, two analytical expressions of THDI were obtained by two new different methods which are statistical package for the social sciences program and genetic expression programming. Eventually, two different methods have been verified by the Matlab/Simulink program in order to find out THDI and demonstrated the effectiveness of the proposed strategy. As a result of this study, it is observed that input current THDI of nonlinear load is too high at low irradiance. It is suggested that active harmonic filters should be used at low irradiance in order to produce better quality energy and avoid damages in the PV system. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

Due to tremendous reception on digital learning platforms, many online users tend to register for online courses in MOOC offered by many prestigious universities all over the world and gain a lot on cutting edge technologies in niche courses. As the reception of online courses is increasing on one side, there have been huge dropouts of participants in the online courses causing serious problems for the course owners and other MOOC administrators. Hence, it is deemed necessary to find out the root causes of course dropouts and need to prepare a workable solution to prevent that outcome in the future. In this connection, the authors made use of three machine learning algorithms such as support vector machine, random forest, and conditional random fields. The huge samples of datasets were downloaded from the Open University of China, that is, almost 7K student profiles were extracted for the empirical analysis. The datasets were loaded into a confusion matrix and analyzed for the accuracy, precision, recall, and f-score of the model. © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

This paper introduces, explains and illustrates real-life application of virtual training tool for electrical engineering education. The tool gives users the opportunity to interact with and manipulate 3D models of authentic devices. The users have a possibility to compare structural differences between devices, assemble and disassemble the machines and test them under extreme conditions, all of which would not be possible while working with a real device. The 3D devices are fully operational allowing the users to interact with them on every level, including analysis of impact of supply conditions i.e. modify voltage and frequency of a particular motor and monitor changes in performance while still operating. The main goal of this research was to evaluate effectiveness and educational values of the proposed tool. Early studies and feedback from educators and students prove this tool to be a great assistance to process of education, facilitating knowledge acquisition and providing an innovative way to put theory into practice.

Distortions such as dryness, wetness, blurriness, physical damages and presence of dots in fingerprints are a detriment to a good analysis of them. Even though fingerprint image enhancement is possible through physical solutions such as removing excess grace on the fingerprint or recapturing the fingerprint after some time, these solutions are usually not user-friendly and time consuming. In some cases, the enhancements may not be possible if the cause of the distortion is permanent. In this paper, we are proposing an unpaired image-to-image translation using cycle-consistent adversarial networks for translating images from distorted domain to undistorted domain, namely, dry to not-dry, wet to not-wet, dotted to not-dotted, damaged to not-damaged, blurred to not-blurred. We use a database of low quality fingerprint images containing 11541 samples with dryness, wetness, blurriness, damages and dotted distortions. The database has been prepared by real data from VISA application centres and have been provided for this research by GEYCE Biometrics. For the evaluation of the proposed enhancement technique, we use VGG16 based convolutional neural network to assess the percentage of enhanced fingerprint images which are labelled correctly as undistorted. The proposed quality enhancement technique has achieved the maximum quality improvement for wetness fingerprints in which 94% of the enhanced wet fingerprints were detected as undistorted. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.

The goal of this research is to integrate Virtual Reality (VR) with the bilateral stimulation used in EMDR as a tool to relieve stress. We created a 15 minutes relaxation training program for adults in a virtual, relaxing environment in form of a walk in the woods. The target platform for the tool is HTC Vive, however it can be easily ported to other VR platforms. An integral part of this tool is a set of sensors, which serves as physiological measures to evaluate the effectiveness of such system. What is more, the system integrate visual (passing sphere), auditory (surround sound) and tactile signals (vibration of controllers). A pilot treatment programme, incorporating the above mentioned VR system, was carried out. Experimental group consisting of 28 healthy adult volunteers (office workers), participated in three different sessions of relaxation training. Before starting, baseline features such as subjectively perceived stress, mood, heart rate, galvanic skin response and muscle response were registered. The monitoring of physiological indicators is continued during the training session and one minute after its completion. Before and after the session, volunteers were asked to re-fill questionnaires regarding the current stress level and mood. The obtained results were analyzed in terms of variability over time: before, during and after the session.

Metamaterials, which are not found in nature, are used to increase the performance of antennas with their extraordinary electromagnetic properties. Since metamaterials provide unique advantages, performance improvements have been made with many optimization algorithms. Objective: The article aimed to develop a deep learning model that, unlike traditional optimization algorithms, takes the desired reflection coefficients’ parameter as an input and gives the image of the corresponding metamaterial. Method: An amount of 29,722 metamaterial images and reflection coefficients corresponding to the metamaterials were collected. Nested-CNN, designed for this task, consisted of Model-1 and Model-2. Model-1 was designed to generate the shape of metamaterial with a reflection coefficient as the input. Model-2 was designed to detect the reflection coefficient of a given image of metamaterial input. Created by using Model-2 in Model-1’s loss function, the nested-CNN was updated by comparing the reflection coefficient of the produced image with the desired reflection coefficient. Secondly, imputation, which is usually the complete missing data before the process of training in machine learning algorithms, was proposed to use in the prediction side to improve the performance of the nested-CNN. The imputation for prediction was used for the non-interested part of the reflection coefficient to decrease the error of the interested region of the reflection coefficient. In the experiment, 27,222 data were used for the KNN-imputer, half of the reflection coefficient was considered as the non-interested region. Additionally, 40 neighbors and 50 neighbors were given the best mean absolute errors (MAE) for specified conditions. Result: The given results are based on test data. For Model-2, the MAE was 0.27, the R2 score was 0.96, and the mean correlation coefficient was 0.93. The R2 score for the nested-CNN was 0.9, the MAE of nested-CNN was 0.42, and the MAE of nested-CNN with 50 neighbors was 0.17.

Changes in the ungulate population density in the wild has impacts on both the wildlife and human society. In order to control the ungulate population movement, monitoring systems such as camera trap networks have been implemented in a non-invasive setup. However, such systems produce a large number of images as the output, hence making it very resource consuming to manually detect the animals. In this paper, we present a new dataset of wild ungulates which was collected in Latvia. Moreover, we demonstrate two methods, which use RetinaNet and Faster R-CNN as backbones, respectively, to detect the animals in the images. We discuss the optimization of training and impact of data augmentation on the performance. Finally, we show the result of aforementioned tune networks over the real world data collected in Latvia.

The wing of missile can be considered as an effective factor for determination of lift to drag ratio. However, there are few studies that investigate wing effect on missile aerodynamics. Therefore, the purpose of this study is to indicate wing effect on the missile aerodynamics and optimize wing geometry for enhancement of aerodynamic efficiency. The missile designed tail-fin configuration is selected from a previous study which contains experimental data. In the beginning of study, Computational Fluid Dynamics (CFD) simulations of selected missile are performed and compared with experimental data. Wing is then mounted to the selected missile and CFD solution is repeated for modified missile at 6º angle of attach (AoA) and subsonic and supersonic speeds. The modified missile shows good performance in point of aerodynamics when compared with baseline missile model. In addition, wing geometry is optimized to improve aerodynamic performance using Multi-Objective Genetic Algorithm (MOGA). Objective functions are determined as lift and drag coefficients. Wing geometry parameters are determined as design variables for optimization. After the optimization process, the results are showed that the aerodynamic coefficients are improved when compared with baseline geometry. In addition, response surface analysis is presented to show which design parameters are more effective on drag and lift forces. The findings of study show that optimum results are more efficient in terms of performance. CFD solution method and the optimization procedure can be applied to design or optimize for different geometry.

In this paper, we extend the notion of 2-nil ideal introduced by Yetkin Celikel in [E. Yetkin Celikel, 2-nil ideals of commutative rings, Bulletin of the Belgian Mathematical Society Simon Stevin 28(3) (2021).] to 2-nil submodule which is a subclass of 2-absorbing primary submodules. Let [Formula: see text] be an [Formula: see text]-module and [Formula: see text] be a proper submodule of [Formula: see text]. We say that [Formula: see text] is a 2-nil submodule of [Formula: see text] if whenever [Formula: see text], [Formula: see text] and [Formula: see text], then [Formula: see text] or [Formula: see text] or [Formula: see text] We study the properties of this concept and establish several characterizations. We also investigate the 2-nil ideals of amalgamation. The obtained results yield new original families of examples of 2-nil ideals.

Finding the equivalent circuit parameters for photovoltaic (PV) cells is crucial as they are used in the modeling and analysis of PV arrays. PV cells are made of silicon. These materials have a nonlinear characteristic. This distorts the sinusoidal waveform of the current and voltage. As a result, harmonic components are formed in the system. The PV cell is the smallest building block of the PV system and produces voltages between 0.5 V and 0.7 V. It serves as a source of current. The amount of radiation hitting the cell determines how much current it produces. In an ideal case, a diode and a parallel current source make up the equivalent circuit of the PV cell. In practice, the addition of a series and parallel resistor is made to the ideal equivalent circuit. There are many equivalent circuits in the literature on modeling the equivalent circuit of a PV cell. The PV cell single–diode model is the most used model due to its ease of analysis. In this study, the iterative method by Newton–Raphson was used to find the equivalent circuit parameters of a PV cell. This method is one of the most widely used methods for determining the roots of nonlinear equations in numerical analysis. In this study, five unknown parameters (Iph, Io, Rs, Rsh and m) of the PV cell equivalent circuit were quickly discovered with the software program prepared based on the Newton–Raphson method in MATLAB. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Let R be a commutative ring with a non-zero identity, S be a multiplicatively closed subset of R and M be a unital R-module. In this paper, we define a submodule N of M with (N:R M)∩S = ∅ to be weakly S-prime if there exists s ∈ S such that whenever a ∈ R and m ∈ M with 0 ≠ am ∈ N, then either sa ∈ (N:R M) or sm ∈ N. Many properties, examples and characterizations of weakly S-prime submodules are introduced, especially in multiplication modules. Moreover, we investigate the behavior of this structure under module homomorphisms, localizations, quotient modules, cartesian product and idealizations. Finally, we define two kinds of submodules of the amalgamation module along an ideal and investigate conditions under which they are weakly S-prime. © 2022 Korean Mathematical Society.

In renewable energy resources such as photovoltaic (PV) systems, fast charging is an emerging case for the battery charger. In this paper, constant-current (CC) and constant-voltage (CV) charging scheme has been studied since it has the highest possible reliability for lithium based batteries. In this work a new charging technique to expedite charging time is proposed. This is a multi-stage technique which improves the threshold voltage detection during CC-stage. Thus the transition to CV-stage occurs accurately at the knee voltage. The novelty of the proposed technique is in the charging algorithm. An experiment was setup based on PIC18f4520 microcontroller. The performance of the proposed technique and the conventional CC-CV Li-ion battery charger has been compared. The result of the proposed technique shows that there is 20% improvement in charging time compared to the conventional CC-CV Li-ion battery charger. © 2022 IEEE.

Integration of solar photovoltaic (PV) sources to power grid is increasing rapidly in recent years. Since the PV source is an intermittent source, this causes many challenges to distribution network. To overcome these challenges, a voltage regulation strategy using a developed power management technique for microgrid system is proposed. The technique is based on voltage ride through capability. The active and reactive power flow along with the voltage profile has been deeply investigated to improve the stability of the distribution network. As a testing environment, three microgrid configurations developed in MATLAB/Simulink have been investigated. The study shows a faster response time and lower circulating current in configuration 2. Moreover, it revealed the effectiveness of the power management technique when a cluster of dispatchable and non-dispatchable distributed generators is in operation.

Metamaterial (MM) slabs in close proximity can couple with one another. This coupling can modify the electromagnetic response of the overall MM structure involving individual MM resonators. The signal flow graph technique along with the ABCD parameters are applied to quantitatively and qualitatively examine this coupling from simulated/measured scattering parameters of cascade connection of closely or largely separated MM slabs. S-parameter measurements of a MM slab constructed by split-ring-resonators were carried out at X-band (8.2-12.4 GHz) to validate our theoretical analysis.

With the increase in accumulated data and usage of the Internet, social media such as Twitter has become a fundamental tool to access all kinds of information. Therefore, it can be expressed that processing, preparing data, and eliminating unnecessary information on Twitter gains its importance rapidly. In particular, it is very important to analyze the information and make it available in emergencies such as disasters. In the proposed study, an earthquake with the magnitude of Mw = 6.8 on the Richter scale that occurred on January 24, 2020, in Elazig province, Turkey, is analyzed in detail. Tweets under twelve hashtags are clustered separately by utilizing the Social Spider Optimization (SSO) algorithm with some modifications. The sum-of intra-cluster distances (SICD) is utilized to measure the performance of the proposed clustering algorithm. In addition, SICD, which works in a way of assigning a new solution to its nearest node, is used as an integer programming model to be solved with the GUROBI package program on the test data-sets. Optimal results are gathered and compared with the proposed SSO results. In the study, center tweets with optimal results are found by utilizing modified SSO. Moreover, results of the proposed SSO algorithm are compared with the K-means clustering technique which is the most popular clustering technique. The proposed SSO algorithm gives better results. Hereby, the general situation of society after an earthquake is deduced to provide moral and material supports.

A method has been proposed for accurate characterization of non-reciprocal networks without enforcing the passivity principle. Thanks to the introduced different even and odd coefficients, our method has no singularity-point problem as compared with the conventional method. The proposed method is validated by scattering parameter measurements of a ferrite-loaded waveguide shifter. In addition, it is demonstrated by measurements that our method, as compared with the conventional one, is more resistant to random noise due to post-calibration effects.

Due to the rapid incline in the number of documents along with social media usage, text categorization has become an important concept. There are tasks required to be fulfilled during the text categorization, such as extracting useful data from different perspectives, reducing the high feature space dimension, and improving effectiveness. In order to accomplish these tasks, feature selection, and feature extraction gain importance. This paper investigates how to solve feature selection and extraction problems. Also, this study aims to decide which topics are the focus of a document. Moreover, the Twitter data-set is utilized as a document and an Uncapacitated P-Median Problem (UPMP) is applied to make clustering. In this study, UPMP is used on Twitter data collection for the first time to collect clustered tweets. Therefore, a novel hybrid genetic bat algorithm (HGBA) is proposed to solve the UPMP for our case. The proposed novel approach is applied to analyze the Twitter data-set of the Nepal earthquake. The first part of the analysis includes the data pre-processing stage. The Latent Dirichlet Allocation (LDA) method is applied to the pre-processed text. After that, a similarity (distance) matrix is generated by utilizing the Jensen Shannon Divergence (JSD) model. The study's main goal is to use Twitter to assess the needs of victims during and after a disaster. To evaluate the applicability of the proposed approach, experiments are conducted on the OR-Library data-set. The results demonstrate that the proposed approach successfully extracts topics and categorizes text.

A general “line-line” (LL) method is proposed for propagation constant determination (γ+ and γ−) of nonreciprocal networks using multiple reference networks. The new formalism provides flexibility in implementation of LL methods so that not only more accurate γ+ (and γ−) could be retrieved but also the effect of inaccurate length information of the non-reciprocal network on γ+ (and γ−) evaluation could be suppressed. For validation of the method, γ+ and γ− of a microwave phase shifter (a nonreciprocal network) are determined using uncalibrated scattering parameter measurements at X-band (8.2–12.4 GHz). Two different statistical analyses based on normalized root-mean-square-error and goodness of fit and based on coefficient of variation and confidence interval are individually performed to evaluate the performance and accuracy of our method. © 2022

The usage of the Photovoltaic (PV) power systems has been increased dramatically, due to the abundant of the solar irradiation, and the government incentives everywhere. In most of the developed countries, the standards for connecting the PV systems to the grid has been set and is already applied. The incentives and regulations that supports PV systems are increasing day by day in Turkey. Because of this regulations more and more PV systems are connecting to the grid. Such high penetration of the PV systems in the distribution network leads to voltage disturbances. This paper studies the causes and effects of the voltage problem and proposes the best solutions to; mitigate the voltage disturbances and increase the distribution network stability. © 2021 IEEE.

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The concept of 2-nil ideal of a commutative ring R is introduced, as an alternative to the (2, n)-ideals from [6]. We study its relationship with previously introduced classes of ideals, such as 2-absorbing ideals and n-ideals. Various properties and examples are presented. Our main result is a characterization of rings for which every 2-nil ideal is prime. We give a description of 2-nil ideals of general ZPI-rings. © 2021 Belgian Mathematical Society. All rights reserved.

Let R be a commutative ring with nonzero identity, I(R) the set of all idealsof R and δ: I(R) → I(R) an expansion of ideals of R. In this paper, we introduce theconcept of 2-absorbing δ-semiprimary ideals in commutative rings which is an extensionof 2-absorbing ideals. A proper ideal I of R is called 2-absorbing δ-semiprimary idealif whenever a, b, c ∈ R and abc ∈ I, then either ab ∈ δ(I) or bc ∈ δ(I) or ac ∈ δ(I).Many properties and characterizations of 2-absorbing δ-semiprimary ideals are obtained.Furthermore, 2-absorbing δ1-semiprimary avoidance theorem is proved © Kyungpook Mathematical Journal

Purpose This study aims to propose a service quality evaluation model for health-care services. Design/methodology/approach In this study, a service quality evaluation model is proposed based on the service quality measurement (SERVQUAL) scale and machine learning algorithm. Primarily, items that affect the quality of service are determined based on the SERVQUAL scale. Subsequently, a service quality assessment model is generated to manage the resources that are allocated to improve the activities efficiently. Following this phase, a sample of classification model is conducted. Machine learning algorithms are used to establish the classification model. Findings The proposed evaluation model addresses the following questions: What are the potential impact levels of service quality dimensions on the quality of service practically? What should be prioritization among the service quality dimensions and Which dimensions of service quality should be improved primarily? A real-life case study in a public hospital is carried out to reveal how the proposed model works. The results that have been obtained from the case study show that the proposed model can be conducted easily in practice. It is also found that there is a remarkably high-service gap in the public hospital, in which the case study has been conducted, regarding the general physical conditions and food services. Originality/value The primary contribution of this study is threefold. The proposed evaluation model determines the impact levels of service quality dimensions on the service quality in practice. The proposed evaluation model prioritizes service quality dimensions in terms of their significance. The proposed evaluation model finds out the answer to the question of which service quality dimensions should be improved primarily?

Let $R$ be a commutative ring with identity and $I$ a proper ideal of $R$. In this paper we introduce the ideal-based quasi zero divisor graph $Q\Gamma_{I}(R)$ of $R$ with respect to $I$ which is an undirected graph with vertex set $V=\{a\in R\backslash\sqrt{I}:$ $ab\in I$ for some $b\in R\backslash\sqrt{I}\}$ and two distinct vertices $a$ and $b$ are adjacent if and only if $ab\in I$. We study the basic properties of this graph such as diameter, girth, dominaton number, etc. We also investigate the interplay between the ring theoretic properties of a Noetherian multiplication ring $R$ and the graph-theoretic properties of $Q\Gamma_{I}(R)$.

Let R be a commutative ring with non-zero identity and M be a unitary R-module. The goal of this paper is to extend the concept of 1-absorbing primary ideals to 1-absorbing primary submodules. A proper submodule N of M is said to be a 1-absorbing primary submodule if whenever non-unit elements a, b ∈ R and m ∈ M with abm ∈ N, then either ab ∈ (N : RM) or m ∈ M − rad(N). Various properties and chacterizations of this class of submodules are considered. Moreover, 1-absorbing primary avoidance theorem is proved.

Let $R$ be a commutative ring with non-zero identity. We define the set oftriple zero elements of $R$ by $TZ(R)=\{a\in Z(R)^{\ast}:$ there exists$b,c\in R\backslash\{0\}$ such that $abc=0$, $ab\neq0$, $ac\neq0$,$bc\neq0\}.$ In this paper, we introduce and study some properties of thetriple zero graph of $R$ which is an undirected graph $TZ\Gamma(R)$ withvertices $TZ(R),$ and two vertices $a$ and $b$ are adjacent if and only if$ab\neq0$ and there exists a non-zero element $c$ of $R$ such that $ac\neq0$,$bc\neq0$, and $abc=0$. We investigate some properties of the triple zerograph of a general ZPI-ring $R,$ we prove that $diam(TZ\Gamma(R))\in\{0,1,2\}$and $gr(G)\in\{3,\infty\}$.

Surface curing effect of hardened engineering cementitious mortar (ECM) samples with distinct water-to-binder ratios ( w / b ) is analyzed by recording amplitude of reflection response | Γ | or conductance term g measured by a microwave open-ended waveguide probe. Frequency dependencies (between 3.95–5.85 GHz) of | Γ | and g measured from various surfaces (top, bottom, and lateral) of ECM samples with w / b = 0 . 2 and 0.3 are presented at the 720th days of curing (hardened ECM). In addition, their temporal dependencies (over 1–9 and 720–815 days) are presented for the frequency value of 4.56 GHz. From our analysis, contrary to top and lateral surface behaviors, it is noted that crossover between g values measured from bottom surfaces of ECM samples with w / b = 0 . 2 and 0.3 delays for a long time (around 550 days). Propagation-related studies should take into account reflection profiles varying with wall height for accurate prediction.

In Theorem 6 of [1], if R is a von Neumann regular ring, then every 2-prime ideal of R is a prime ideal. But the converse of this implication does not hold. Thus, we correct Theorem 6 of [1] as follows: Theorem 6. Let R be a ring. If R is von Neumann regular, then every 2-prime ideal of R is a prime ideal. P r o o f . © 2020, Mathematical Institute, Academy of Sciences of Cz.

Let R be a commutative ring with nonzero identity, let I(R) be the set of all ideals of R and δ: I(R) → I(R) an expansion of ideals of R defined by I ↦ δ(I). We introduce the concept of (δ, 2)-primary ideals in commutative rings. A proper ideal I of R is called a (δ, 2)-primary ideal if whenever a, b ∈ R and ab ∈ I, then a2 ∈ I or b2 ∈ δ(I). Our purpose is to extend the concept of 2-ideals to (δ, 2)-primary ideals of commutative rings. Then we investigate the basic properties of (δ, 2)-primary ideals and also discuss the relations among (δ, δ-primary, δ-primary and 2-prime ideals. © 2020, Mathematical Institute, Academy of Sciences of Cz.

This article presents point-like, aperture averaged scintillation, and bit error rate(BER) performance of cylindrical-sinc Gaussian beam (CSGB). We model atmosphere utilizing random phase screen approach to be up to the complexity of source field expression. Our results indicate that it is possible to generate resistive CSGBs against turbulence considering point-like scintillation. Aperture averaged scintillation results show that all selected beams have lower scintillation index than Gauss beam. Major benefit of CSGBs is seen in BER evaluation in optical wireless communication systems. It is possible to decrease BER 10-7 times lower than Gauss beam at nearly 13 dB signal to noise ratio(SNR). © 2020 IOP Publishing Ltd Printed in the UK

The deployment of grid connected photovoltaic (PV) power plants is increasing dramatically recently. Due to the intermittent nature of the PV power plant, a battery and/or a power curtailment controller has to be installed to maintain the stability of the distribution network. The battery is an additional cost in the system so the return on investment (ROI) analysis has to be conducted. An alternative to the battery, a customized load can be used to consume the surplus energy. This load has to make an additional income to be profitable for the plant's owner. Such load can be crypto-currency mining rig that does calculation to validate the transaction in the Blockchain network. This study compared the ROI of the battery and the mining rig. The study shows that mining rig has higher ROI of 7.7% compared to 4.5% for battery. © 2020 IEEE.