Prediction of the undrained shear strength of remolded soil with non-linear regression,fuzzy logic,and artificial neural network

This study aims to predict the undrained shear strength of remolded soil samples using non-linear regression analyses,fuzzy logic,and artificial neural network modeling.A total of 1306 undrained shear strength results from 230 different remolded soil test settings reported in 21 publications were collected,utilizing six different measurement devices.Although water content,plastic limit,and liquid limit were used as input parameters for fuzzy logic and artificial neural network modeling,liquidity index or water content ratio was considered as an input parameter for non-linear regression analyses.In non-linear regression analyses,12 different regression equations were derived for the prediction of undrained shear strength of remolded soil.Feed-Forward backpropagation and the TANSIG transfer function were used for artificial neural network modeling,while the Mamdani inference system was preferred with trapezoidal and triangular membership functions for fuzzy logic modeling.The experimental results of 914 tests were used for training of the artificial neural network models,196 for validation and 196 for testing.It was observed that the accuracy of the artificial neural network and fuzzy logic modeling was higher than that of the non-linear regression analyses.Furthermore,a simple and reliable regression equation was proposed for assessments of undrained shear strength values with higher coefficients of determination.

Design of an Efficient and Provable Secure Key Exchange Protocol for HTTP Cookies

Cookies are considered a fundamental means of web application services for authenticating various Hypertext Transfer Protocol(HTTP)requests andmaintains the states of clients’information over the Internet.HTTP cookies are exploited to carry client patterns observed by a website.These client patterns facilitate the particular client’s future visit to the corresponding website.However,security and privacy are the primary concerns owing to the value of information over public channels and the storage of client information on the browser.Several protocols have been introduced that maintain HTTP cookies,but many of those fail to achieve the required security,or require a lot of resource overheads.In this article,we have introduced a lightweight Elliptic Curve Cryptographic(ECC)based protocol for authenticating client and server transactions to maintain the privacy and security of HTTP cookies.Our proposed protocol uses a secret key embedded within a cookie.The proposed protocol ismore efficient and lightweight than related protocols because of its reduced computation,storage,and communication costs.Moreover,the analysis presented in this paper confirms that proposed protocol resists various known attacks.

Model Identification and Control of Electromagnetic Actuation in Continuous Casting Process With Improved Quality

This paper presents an original theoretical framework to model steel material properties in continuous casting line process. Specific properties arising from non-Newtonian dynamics are herein used to indicate the natural convergence of distributed parameter systems to fractional order transfer function models. Data driven identification from a real continuous casting line is used to identify model of the electromagnetic actuator device to control flow velocity of liquid steel. To ensure product specifications, a fractional order control is designed and validated on the system. A projection of the closed loop performance onto the quality assessment at end production line is also given in this paper.

Determination of AVR System PID Controller Parameters Using Improved Variants of Reptile Search Algorithm and a Novel Objective Function

Two novel improved variants of reptile search algorithm(RSA),RSA with opposition-based learning(ORSA)and hybrid ORSA with pattern search(ORSAPS),are proposed to determine the proportional,integral,and derivative(PID)controller parameters of an automatic voltage regulator(AVR)system using a novel objective function with augmented flexibility.In the proposed algorithms,the opposition-based learning technique improves the global search abilities of the original RSA algorithm,while the hybridization with the pattern search(PS)algorithm improves the local search abilities.Both algorithms are compared with the original RSA algorithm and have shown to be highly effective algorithms for tuning the PID controller parameters of an AVR system by getting superior results.Several analyses such as transient,stability,robustness,disturbance rejection,and trajectory tracking are conducted to test the performance of the proposed algorithms,which have validated the good promise of the proposed methods for controller designs.The performances of the proposed design approaches are also compared with the previously reported PID controller parameter tuning approaches to assess their success.It is shown that both proposed approaches obtain excellent and robust results among all compared ones.That is,with the adjustment of the weight factorα,which is introduced by the proposed objective function,for a system with high bandwitdh(α=1),the proposed ORSAPS-PID system has 2.08%more bandwidth than the proposed ORSA-PID system and 5.1%faster than the fastest algorithm from the literature.On the other hand,for a system where high phase and gain margins are desired(α=10),the proposed ORSA-PID system has 0.53%more phase margin and 2.18%more gain margin than the proposed ORSAPS-PID system and has 0.71%more phase margin and 2.25%more gain margin than the best performing algorithm from the literature.

A Novel Hybrid Model Based on Machine and Deep Learning Techniques for the Classification of Microalgae

Classification and monitoring of microalgae species in aquatic ecosystems are important for understanding population dynamics.However,manual classification of algae is a time-consuming method and requires a lot of effort with expertise due to the large number of families and genera in its classification.The recognition of microalgae species has become an increasingly important research area in image recognition in recent years.In this study,machine learning and deep learning methods were proposed to classify images of 12 different microalgae species in order to successfully classify algae cells.8 Different novel models(MobileNetV3Small-Lr,MobileNetV3Small-Rf,MobileNetV3Small-Xg,MobileNetV3Large-Lr,MobileNetV3Large-Rf,MobileNetV3Large-Xg,Mobile-NetV3Small-Improved and MobileNetV3Large-Improved)have been proposed to classify these microalgae species.Among these proposed model structures,the best classification accuracy rate was 92.22%and the loss rate was 0.72,obtained from the MobileNetV3Large-Improved model structure.In addition,as a result of the experimental results obtained,metrics such as the confusion matrix,which can meet the experts in the correct diagnosis of microalgae species,were also evaluated.This research may in the future open a new avenue for the development of a cost-effective,highly sensitive computer-based system for the use of image analysis and deep learning techniques for the identification and classification of different microalgae.

HybridGAD: Identification of AI-Generated Radiology Abstracts Based on a Novel Hybrid Model with Attention Mechanism

Class Title:Radiological imaging method a comprehensive overview purpose.This GPT paper provides an overview of the different forms of radiological imaging and the potential diagnosis capabilities they offer as well as recent advances in the field.Materials and Methods:This paper provides an overview of conventional radiography digital radiography panoramic radiography computed tomography and cone-beam computed tomography.Additionally recent advances in radiological imaging are discussed such as imaging diagnosis and modern computer-aided diagnosis systems.Results:This paper details the differences between the imaging techniques the benefits of each and the current advances in the field to aid in the diagnosis of medical conditions.Conclusion:Radiological imaging is an extremely important tool in modern medicine to assist in medical diagnosis.This work provides an overview of the types of imaging techniques used the recent advances made and their potential applications.

Slope stability evaluation and monitoring of a landslide: a case study from NE Turkey

Landslides are quite common natural hazards in the eastern Black Sea region of NE Turkey.Following the heavy rainfall in the K?prülü(Rize)village settlement area,located in this region where the slope debris overlies the agglomerates,a failure occurred.Due to the developed tension cracks and deformations on the ground,houses,tea gardens,and roads were damaged completely.To figure out the causes and mechanism of the sliding and to suggest the precautions,a detailed geotechnical study was carried out.Along the five survey lines,twelve boreholes were drilled with a total depth of 300 meters.Also,the geophysical surveys on ten profiles were conducted and the inclinometer measurements were taken in five boreholes.Undisturbed and disturbed samples were collected and laboratory experiments were performed.Inclinometer measurements indicated that the sliding started in the slope debris and then spread to the agglomeratic bedrock.The slope stability was examined using the limit equilibrium(LE)and finite element(FEM)analysis methods.The results of the slope stability analyses showed that the failure mode is talus slide with composite shape and outputs coincide with the inclinometer monitoring results.Based on the collected data,it is determined that there will be unavoidable engineering problems if no precautions are taken.Because of the negative reasons which make the application of supporting methods meaningless in the study area,it is considered that transferring the residences to a safer place without risk of natural hazards will be economical and reliable.

Determination of the Normal Contact Stiffness and Integration Time Step for the Finite Element Modeling of Bristle-Surface Interaction

In finite element modeling of impact,it is necessary to define appropriate values of the normal contact stiffness,Kn,and the Integration Time Step(ITS).Because impacts are usually of very short duration,very small ITSs are required.Moreover,the selection of a suitable value of Kn is a critical issue,as the impact behavior depends dramatically on this parameter.In this work,a number of experimental tests and finite element analyses have been performed in order to obtain an appropriate value of Kn for the interaction between a bristle of a gutter brush for road sweeping and a concrete surface.Furthermore,a suitable ITS is determined.The experiments consist of releasing a steel bristle that is placed vertically at a certain distance from a concrete surface and tracking the impact.Similarly,in the finite element analyses,a beam is modeled in free fall and impacting a surface;contact and target elements are attached to the beam and the surface,respectively.The results of the experiments and the modeling are integrated through the principle of conservation of energy,the principle of linear impulse and momentum,and Newton’s second law.The results demonstrate that,for the case studied,Kn and the impact time tend to be independent of the velocity just before impact and that Kn has a very large variation,as concrete is a composite material with a rough surface.Also,the ratio between the largest height of the bristle after impact and the initial height tends to be constant.

Evaluation of in vitro and in vivo immunostimulatory activities of poly(lactic-co-glycolic acid) nanoparticles loaded with soluble and autoclaved Leishmania infantum antigens: A novel vaccine candidate against visceral leishmaniasis

Objective: To prepare and characterize poly lactic-co-glycolic acid(PLGA) nanoparticles loaded with soluble leishmanial antigen or autoclaved leishmanial antigen and explore in vitro and in vivo immunogenicity of antigen encapsulated nanoparticles. Methods: Water/oil/water double emulsion technique was employed to synthesize PLGA nanoparticles, and scanning electron microscopy, Fourier transform infrared spectroscopy and Zeta-potential measurements were used to identify the characteristics of nanoparticles. Cytotoxicity of synthetized nanoparticles on J774 macrophage were investigated by MTT assays. To determine the in vitro immunostimulatory efficacies of nanoparticles, griess reaction and ELISA was used to measure the amounts of NO and cytokines. During the in vivo analysis, Balb/c mice were immunized with vaccine formulations, and protective properties of nanoparticles were measured by Leishman Donovan unit in the liver following the infection. Cytokine levels in spleens of mice were determined by ELISA. Results: MTT assay showed that neither soluble leishmanial antigen nor autoclaved leishmanial antigen encapsulated nanoparticles showed cytotoxicity against J774 macrophage cells. Contrary to free antigens, both autoclaved leishmanial antigen-nanoparticle and soluble leishmanial antigen-nanoparticle formulations led to a 10 and 16-fold increase in NO amounts by macrophages, respectively. Leishman Donovan unit calculations revealed that soluble leishmanial antigen-nanoparticles and autoclaved leishmanial antigen-nanoparticles yielded 52% and 64% protection against visceral leishmaniasis in mouse models. Besides, in vitro and in vivo tests demonstrated that by increasing IFN-γ and IL-12 levels and inhibiting IL-4 and IL-10 secretions, autoclaved leishmanial antigen-nanoparticles and soluble leishmanial antigennanoparticles triggered Th1 immune response. Conclusions: Both autoclaved leishmanial antigen-nanoparticles and soluble leishmanial antigen-nanoparticles formulations provide exceptional in vitro and in vivo immunostimulatory activities. Hence, PLGA-based antigen delivery systems are recommended as potential vaccine candidates against visceral leishmaniasis.

Effect of die inlet geometry on extrusion of clover sections through curved dies:Upper bound analysis and experimental verification

The effect of die inlet and transition geometry on the extrusion loads and ~aaterial flow for extrusion of clover sections were investigated and presented both theoretically and experimentally. For this purpose, four different die geometries including straight tapered and cosine transition profile and each of them having round and clover inlet geometries were chosen. In the experimental study, commercially pure lead was used because of its hot forming characteristic at room temperature. A newly kinematical admissible velocity field to analyze different profiles of extrusion dies of clover section from round bars was proposed by upper bound analysis. It is clear that the extrusion loads obtained from the theoretical analysis for various die inlet-die transition geometry combinations are in good agreement with the experimental results. Axis deviations of the parts which define the dimensional quality of the products were also investigated.

Investigation of the compressibility and sinterabilty of AZ91 powder production and particle production by gas atomisation method

This study intends to determine the pressability and sinterability of AZ91 powder production by gas atomisation method and that of the produced powder for partial production.Therefore,first,a gas atomisation unit has been designed and manufactured in the laboratories of the Karabiik University,Department of Manufacturing Engineering.Atomised powder production has been achieved at a temperature of 795℃,with nozzle diameters of 2 and 4 mm and four different gas pressures(5,15,25,35 bars).Argon gas has been used for atomisation and as a protective gas atmosphere.Scanning electron microscope(SEM)is used to determine the shape of the produced AZ91 powder,and a laser particle size analyzer is used to analyze the powder size.Additionally,a microhardness(HV0.025)measurement has been conducted to determine the hardness of the produced powders.To achieve a homogeneous distribution,the produced powders are mixed in a three-dimensional moving turbulator for 30 min.Mixed powders have been pressed at 300,400,500 and 600 MPa and have been sintered at 500℃,550℃and 600℃.Additionally,the density values have been determined before and after sintering of the materials.SEM images have been obtained from the fractured surfaces of the samples before and after sintering.XRD and EDX analyses have been performed to determine the chemical composition.Further,microhardness(HV0.5)is obtained from the pressure surfaces of the samples to determine the effects of the pressing pressure and the sintering temperature on the hardness.As a result of the experimental studies,it has been observed that the powder size decreases with the increase in gas pressure and that the powder shape generally changes from ligament and complex shape to droplet and spherical shape.From the XRD,XRF and EDX results,it has been determined that the structure comprises an a phase(Mg main matrix)and Mg17Al12 interphase,which isβphase,and very small amounts of MgO have been observed.The hardness of the produced powders increased based on the increase in gas pressure.The densities of the samples increased with both increasing pressing pressure and sintering temperature.It has been observed from the fractured surface SEM images that the number of pores formed in the samples decrease with an increase in the pressing pressure.It has been determined that the post-sintering structure exhibitsαtypical dendritic structure.In addition to theα-Mg matrix phase,β(Mg17Al12)intermetallic andα+βeutectic were formed in the structure.The microhardness values of the samples decreased depending on the sintering temperature;the highest hardness value was measured as 64,02 HV0.5 at a pressing pressure of 300 MPa and a sintering temperature of 500℃,whereas the lowest hardness value was measured as 54,86 HV0.5 at a pressing pressure of 600 MPa and a sintering temperature of 600℃.

A Synthesis of Electronically Controllable Current-Mode PI, PD and PID Controllers Employing CCCDBAs

This paper presents a synthesis of current-mode PI, PD and PID controllers employing current controlled current differential buffer amplifiers (CCCDBAs). The features of these controllers are that: the output parameters can be electronically/independently controlled by adjusting corresponding bias currents in the proportional, integral, and deviation controllers;circuit description of the PID controller is simply formulated, it consists of four CCCDBAs cooperating with two grounded capacitors, and PI and PD controllers are composed of three CCCCDBAs and a grounded capacitor. Without any external resistor, the proposed circuits are very suitable to develop into integrated circuit architecture. The given results from the PSpice simulation agree well with the theoretical anticipation. The approximate power consumption in a closed loop control system consisting of the PI, PD and PID controller with low-pass filter passive plant are 4.03 mW, 4.85 mW and 5.71 mW, respectively, at ±1.5 V power supply voltages.

An Optimum and Effective Drawing Teaching System in Engineering

In this study, the authors shall illustrate the difficulties, pros and cons of ＂Technical Drawing＂ courses in engineering curriculums. The authors also show the efficiency, effectiveness of students＇ grasping the engineering drawing concepts in depth. The authors have conducted a survey on students and their instructors for teaching the course. Whether the course should be taught with manual handling and then computerized or starting with computer aid and finishing the content of the course, the authors shall also go in detail of syllabus how the drawing rooms and aid tools will be. This part of study shall look into the ergonomics, safety and conditions of classrooms. Responses of 300 students will be shared in this presentation. Statistical analysis will detect the effects of different factors involved in the questionnaire.

A New Hybrid Approach Using GWO and MFO Algorithms to Detect Network Attack

This paper addresses the urgent need to detect network security attacks,which have increased significantly in recent years,with high accuracy and avoid the adverse effects of these attacks.The intrusion detection system should respond seamlessly to attack patterns and approaches.The use of metaheuristic algorithms in attack detection can produce near-optimal solutions with low computational costs.To achieve better performance of these algorithms and further improve the results,hybridization of algorithms can be used,which leads to more successful results.Nowadays,many studies are conducted on this topic.In this study,a new hybrid approach using Gray Wolf Optimizer(GWO)and Moth-Flame Optimization(MFO)algorithms was developed and applied to widely used data sets such as NSL-KDD,UNSW-NB15,and CIC IDS 2017,as well as various benchmark functions.The ease of hybridization of the GWO algorithm,its simplicity,its ability to perform global optimal search,and the success of the MFO algorithm in obtaining the best solution suggested that an effective solution would be obtained by combining these two algorithms.For these reasons,the developed hybrid algorithm aims to achieve better results by using the good aspects of both the GWO algorithm and the MFO algorithm.In reviewing the results,it was found that a high level of success was achieved in the benchmark functions.It achieved better results in 12 of the 13 benchmark functions compared.In addition,the success rates obtained according to the evaluation criteria in the different data sets are also remarkable.Comparing the 97.4%,98.3%,and 99.2% classification accuracy results obtained in the NSL-KDD,UNSW-NB15,and CIC IDS 2017 data sets with the studies in the literature,they seem to be quite successful.

Assessing the effects of long-term recreational activities on landscape changes in Abant Natural Park,Turkey

Natural, protected areas offer many possibili- ties for recreation in rural areas such as camping, one of the most popular activities. The system established for pro- tected areas in Turkey aims to provide a foundation for conserving areas for recreation. One such area, Abant Natural Park, is convenient for visits from Turkey＇s two most populated metropolitan areas, Istanbul and Ankara. It also attracts tourists from other regions and countries. The aim of the present study was to evaluate the vegetation loss and land cover changes due to picnic/camping, transhu- mance, and construction over 40 years （1966-2004） in the park using data on visitor numbers, vegetation patches, corridors and connectivity. For evaluating landscape vari- ables, remote sensing data and aerial photos were used. When aerial photos were imported into the ERDAS Imagine program, ground control points identified, and individual images orthorectified, land degradation was not found in the use of camping areas. Moreover, manmade areas （road, car park and hotel） observably increased, thus decreasing the forest lands. The findings show that the land use types that have had the greatest ecological impact are transhumance and construction of hotels, which also require infrastructure development. The intensity of the ecological effects mandates precautions to lessen the impacts and the need for continuing assessment to ensure sustainable use of the area.

An Efficient Numerical Scheme for Biological Models in the Frame of Bernoulli Wavelets

This article considers three types of biological systems:the dengue fever disease model,the COVID-19 virus model,and the transmission of Tuberculosis model.The new technique of creating the integration matrix for the Bernoulli wavelets is applied.Also,the novel method proposed in this paper is called the Bernoulli wavelet collocation scheme(BWCM).All three models are in the form system of coupled ordinary differential equations without an exact solution.These systems are converted into a system of algebraic equations using the Bernoulli wavelet collocation scheme.The numerical wave distributions of these governing models are obtained by solving the algebraic equations via the Newton-Raphson method.The results obtained from the developed strategy are compared to several schemes such as the Runge Kutta method,and ND solver in mathematical software.The convergence analyses are discussed through theorems.The newly implemented Bernoulli wavelet method improves the accuracy and converges when it is compared with the existing methods in the literature.

Modeling and Predicting of News Popularity in Social Media Sources

The popularity of news,which conveys newsworthy events which occur during day to people,is substantially important for the spectator or audience.People interact with news website and share news links or their opinions.This study uses supervised learning based machine learning techniques in order to predict news popularity in social media sources.These techniques consist of basically two phrases:a)the training data is sent as input to the classifier algorithm,b)the performance of prelearned algorithm is tested on the testing data.And so,a knowledge discovery from the data is performed.In this context,firstly,twelve datasets from a set of data are obtained within the frame of four categories:Economic,Microsoft,Obama and Palestine.Second,news popularity prediction in social network services is carried out by utilizing Gradient Boosted Trees,Multi-Layer Perceptron and Random Forest learning algorithms.The prediction performances of all algorithms are examined by considering Mean Absolute Error,Root Mean Squared Error and the R-squared evaluation metrics.The results show that most of the models designed by using these algorithms are proved to be applicable for this subject.Consequently,a comprehensive study for the news prediction is presented,using different techniques,drawing conclusions about the performances of algorithms in this study.

The synthesis of boronic-imine structured compounds and identification of their anticancer, antimicrobial and antioxidant activities

Boronic acid compounds with different substituted groups were handled to synthesize various ligands encoded as B1, B2, B3, B4, BS, B6, B7 and BS. B5 and B7 were tested for the cytotoxic activity against the prostate cancer cells and it was found that the cell viability of cancer cells was decreased while most of the healthy cells could still be viable. 5 μM solutions of B5 and B7 decreased the cell viability to 33% and 44%; whereas healthy cells were 71% and 95%, respectively, after treatment. Antimicrobial properties were explored against the bacterial and fungal microorganisms with B1, B5 and BZ The inhibition zones were evaluated for all boronic structures, and the growth inhibition zones were determined in a range of 7-13 mm diameter for different microorganism species. Staphylococcus aureus was the common micro- organism that three boronic compounds with imine ligands showed the activity. Antioxidant features of B2, B3, B4, B5, B6, B7 and B8 were investigated by different processes such as Beta-carotene bleaching （BCB）, 2,2-diphenyl picryl hydrazyl （DPPH）, 2,2″-azino-bis（ 3-ethylbenzothiazoline-6-sulphonic acid） （ABTS） and CUPric reducing antioxidant capacity （CLIPRAC） methods. Significant antioxidant activity was achieved by the phenyl boronic based ligands and these compounds demonstrated as much activity as standards （α-Toc and BHT）. In addition, all structures were applied properly without any decomposition during the experiments. They were rather stable both in aqueous media and solid state.

Numerical Analysis of Tilted Cutting and F128 Brushes

Road sweeping is an essential service that has to be conducted for public health,as well as aesthetic purposes.In many countries,sweeping vehicles are used for this activity.They usually comprise a gutter brush that sweeps the debris that is located in the road gutter.This work studies the performance of two kinds of gutter brushes:a cutting brush and a flicking(F128)brush.This is carried out by means of a 3-D dynamic,nonlinear Finite Element(FE)brush model developed by the authors.In this model,inertia forces are applied to the bristle,and its clamped end is fixed.Consequently,the surface(road)is rotated,translated,and raised.Bristle-road interaction is modelled as flexible-to-rigid contact.In particular,the aim of this article is to compare the performance of a conventional brush and a brush rotating at variable speed.As brushes normally work tilted,FE analyses are carried out for tilted cutting and F128 brushes,rotating at speeds that fluctuate at different frequencies.It is concluded that brush oscillations have a significant effect on bristle tip velocities and bristle-road forces.Also,at certain frequencies,oscillations seem to improve sweeping performance of the F128 brush.However,they do not appear to improve significantly the performance of the cutting brush.

Regarding on the Fractional Mathematical Model of Tumour Invasion and Metastasis

In this paper,we analyze the behaviour of solution for the system exemplifying model of tumour invasion and metastasis by the help of q-homotopy analysis transform method(q-HATM)with the fractional operator.The analyzed model consists of a system of three nonlinear differential equations elucidating the activation and the migratory response of the degradation of the matrix,tumour cells and production of degradative enzymes by the tumour cells.The considered method is graceful amalgamations of q-homotopy analysis technique with Laplace transform(LT),and Caputo–Fabrizio(CF)fractional operator is hired in the present study.By using the fixed point theory,existence and uniqueness are demonstrated.To validate and present the effectiveness of the considered algorithm,we analyzed the considered system in terms of fractional order with time and space.The error analysis of the considered scheme is illustrated.The variations with small change time with respect to achieved results are effectively captured in plots.The obtained results confirm that the considered method is very efficient and highly methodical to analyze the behaviors of the system of fractional order differential equations.