The use of fog computing in the Internet of Things(IoT)has emerged as a crucial solution,bringing cloud services closer to end users to process large amounts of data generated within the system.Despite its advantages,...The use of fog computing in the Internet of Things(IoT)has emerged as a crucial solution,bringing cloud services closer to end users to process large amounts of data generated within the system.Despite its advantages,the increasing task demands from IoT objects often overload fog devices with limited resources,resulting in system delays,high network usage,and increased energy consumption.One of the major challenges in fog computing for IoT applications is the efficient deployment of services between fog clouds.To address this challenge,we propose a novel Optimal Foraging Algorithm(OFA)for task placement on appropriate fog devices,taking into account the limited resources of each fog node.The OFA algorithm optimizes task sharing between fog devices by evaluating incoming task requests based on their types and allocating the services to the most suitable fog nodes.In our study,we compare the performance of the OFA algorithm with two other popular algorithms:Genetic Algorithm(GA)and Randomized Search Algorithm(RA).Through extensive simulation experiments,our findings demonstrate significant improvements achieved by the OFA algorithm.Specifically,it leads to up to 39.06%reduction in energy consumption for the Elektroensefalografi(EEG)application,up to 25.86%decrease in CPU utilization for the Intelligent surveillance through distributed camera networks(DCNS)application,up to 57.94%reduction in network utilization,and up to 23.83%improvement in runtime,outperforming other algorithms.As a result,the proposed OFA algorithm enhances the system’s efficiency by effectively allocating incoming task requests to the appropriate fog devices,mitigating the challenges posed by resource limitations and contributing to a more optimized IoT ecosystem.展开更多
Gemlik olive was studied by a combined strategy consisting of physic-chemical, sensorial analyses and mathematical relationship among these parameters. Moisture contents of olive fruits decreased from 36.64% to 23.86%...Gemlik olive was studied by a combined strategy consisting of physic-chemical, sensorial analyses and mathematical relationship among these parameters. Moisture contents of olive fruits decreased from 36.64% to 23.86%, both salt concentration and firmness increased to 9.35 g NaCI/100 g and 51.6% respectively. Total phenols of olive fruits changed from 1714.5 mg GAE/kg to 451.4 mg GAE/kg and radical scavenging activity （DPPH %） decreased from 91.48% to 32.14% respectively. L＊, a＊ and b＊ values of Gemlik olives were decreased during fermentation. There was a close relationship among physicochemical parameters of Gemlik olives in mathematically. In order to model this mathematical relation, Vandermonde matrix based 3th degree polynomial equations was used because it gave best model fits for the data of physical and chemical parameters of olive fruits. On the other hand, according to the results of sensory evaluation, the attributes of saltness and crispiness were highly scored （7.21-7.34） but the sensory scores of astringency and bitterness were evaluated from 4.56 to 5.61 by participants. The physico-chemical characteristic changes during the fermentation of Gemlik olives subjected to dry salting method for producing table olives were modeled and suggested with the determined physico-chemical evaluation scores to future studies.展开更多
With the creation of logic gates and algorithms for quantum computers and entering our lives, it is predicted that great developments will take place in this area and important efforts are made. Spin rotation processo...With the creation of logic gates and algorithms for quantum computers and entering our lives, it is predicted that great developments will take place in this area and important efforts are made. Spin rotation processors are quantum mechanical rotation processors and have no classic counterparts. The rotation operators of spin 1/2 are well known and can be found in related textbooks. But rotation operators of other spins greater than 1/2 can be found numerically by evaluating the series expansions of exponential operator obtained from Schr<span style="white-space:nowrap;">?</span>dinger equation, by evaluation of Wigner-d formula or by recently established expressions in polynomial forms discussed in the text. In a previous paper, rotation operators for spins 1/2 to 2 were published. In this work, explicit symbolic expressions of <em>x</em>, <em></em><em>y</em> and <em>z</em> components of rotation operators for spin 5/2, 3 and 7/2 are worked via exponential operator for each element of related spin operators and utilizing simple linear curve fitting process. The procedures gave out exact expressions of each element of the rotation operators.展开更多
We have considered the basic dynamic homogeneous system of partial differential equations of generalized Green-Lindsay couple-stress thermodiffusion on the plane for homogeneous, isotropic elastic media with the centr...We have considered the basic dynamic homogeneous system of partial differential equations of generalized Green-Lindsay couple-stress thermodiffusion on the plane for homogeneous, isotropic elastic media with the centre of symmetry. We have constructed regular solution of the boundary problems on the line. In the works are obtained in quadrates the solution of the boundary-value problem of the generalized Green-Lindsay theory of couple-stress thermodiffusion, when on border of area are given： the component of normal of displacement vector, the component of touching of stress vector, rotations, flow of heat and flow of diffusion.展开更多
Solar energy is also a major renewable energy source that is clean and can be sustained at a minimum cost. CSP systems are another highly developed solar energy system that is environmentally friendly and can be insta...Solar energy is also a major renewable energy source that is clean and can be sustained at a minimum cost. CSP systems are another highly developed solar energy system that is environmentally friendly and can be installed with simple technology and rational cost. PV solar panels generate electric power when sunlight exists. Similarly, CSP system also generates electric power for immediate consumption when there is sunlight, but it also stores some of the solar energy as heat to be able to continue generating electric power when the weather is cloudy or during the night. In this study, an algorithm and software for effective heliostat were developed. Six districts were selected in Adana province to design and calculate solar power received by heliostat mirrors and delivered to the heat exchanger on top of the tower. Because a solar tracking mechanism is necessary for correct and instant orientation of mirrors, the developed software can calculate the orientation angles of each mirror at any moment of a day of the year. The algorithm also calculates the power received by PV solar panels with fixed orientation and with the same surface area as those of mirrors to compare the energy yields.展开更多
Deep learning(DL)techniques,which do not need complex preprocessing and feature analysis,are used in many areas of medicine and achieve promising results.On the other hand,in medical studies,a limited dataset decrease...Deep learning(DL)techniques,which do not need complex preprocessing and feature analysis,are used in many areas of medicine and achieve promising results.On the other hand,in medical studies,a limited dataset decreases the abstraction ability of the DL model.In this context,we aimed to produce synthetic brain images including three tumor types(glioma,meningioma,and pituitary),unlike traditional data augmentation methods,and classify them with DL.This study proposes a tumor classification model consisting of a Dense Convolutional Network(DenseNet121)-based DL model to prevent forgetting problems in deep networks and delay information flow between layers.By comparing models trained on two different datasets,we demonstrated the effect of synthetic images generated by Cycle Generative Adversarial Network(CycleGAN)on the generalization of DL.One model is trained only on the original dataset,while the other is trained on the combined dataset of synthetic and original images.Synthetic data generated by CycleGAN improved the best accuracy values for glioma,meningioma,and pituitary tumor classes from 0.9633,0.9569,and 0.9904 to 0.9968,0.9920,and 0.9952,respectively.The developed model using synthetic data obtained a higher accuracy value than the related studies in the literature.Additionally,except for pixel-level and affine transform data augmentation,synthetic data has been generated in the figshare brain dataset for the first time.展开更多
It is one of the topics that have been studied extensively on maximum power point tracking(MPPT)recently.Traditional or soft computing methods are used for MPPT.Since soft computing approaches are more effective than ...It is one of the topics that have been studied extensively on maximum power point tracking(MPPT)recently.Traditional or soft computing methods are used for MPPT.Since soft computing approaches are more effective than traditional approaches,studies on MPPT have shifted in this direction.This study aims comparison of performance of seven meta-heuristic training algorithms in the neuro-fuzzy training for MPPT.The meta-heuristic training algorithms used are particle swarm optimization(PSO),harmony search(HS),cuckoo search(CS),artificial bee colony(ABC)algorithm,bee algorithm(BA),differential evolution(DE)and flower pollination algorithm(FPA).The antecedent and conclusion parameters of neuro-fuzzy are determined by these algorithms.The data of a 250 W photovoltaic(PV)is used in the applications.For effective MPPT,different neuro-fuzzy structures,different membership functions and different control parameter values are evaluated in detail.Related training algorithms are compared in terms of solution quality and convergence speed.The strengths and weaknesses of these algorithms are revealed.It is seen that the type and number of membership function,colony size,number of generations affect the solution quality and convergence speed of the training algorithms.As a result,it has been observed that CS and ABC algorithm are more effective than other algorithms in terms of solution quality and convergence in solving the related problem.展开更多
Purpose:This study aims to research the impact of the e-learning environment,in which gamebased education software was used,on the learning of students with intellectual disabilities.Design/Approach/Methods:The study ...Purpose:This study aims to research the impact of the e-learning environment,in which gamebased education software was used,on the learning of students with intellectual disabilities.Design/Approach/Methods:The study group consisted of 34 students with intellectual disabilities studying at a special education vocational school in Canakkale,Turkey.In this study,the true experimental method was used.For 5 weeks,the experimental group received blended learning that was supported by the usage of a game-based education software designed by the researcher,which includes interactive educational game applications.At the same time,control group students only received the teaching process in the classroom with the traditional teaching method.Acourse attitude scale and an achievement test were used fordata collection.Findings:The analysis of the findings showed that there was a significant increase between precourse and post-course attitudes and academic achievement scores of the students.There wasn't a significant difference between pre-course and post-course attitudes and academic achievement scores according to the gender and academic achievement scores.Males'academic achievement and attitude post-test scores were higher than females'scores.Students having upper daily mobile devices usage experience had higher post-test and academic achievement scores than students havinglowerdaily mobile devices usage experience.展开更多
文摘The use of fog computing in the Internet of Things(IoT)has emerged as a crucial solution,bringing cloud services closer to end users to process large amounts of data generated within the system.Despite its advantages,the increasing task demands from IoT objects often overload fog devices with limited resources,resulting in system delays,high network usage,and increased energy consumption.One of the major challenges in fog computing for IoT applications is the efficient deployment of services between fog clouds.To address this challenge,we propose a novel Optimal Foraging Algorithm(OFA)for task placement on appropriate fog devices,taking into account the limited resources of each fog node.The OFA algorithm optimizes task sharing between fog devices by evaluating incoming task requests based on their types and allocating the services to the most suitable fog nodes.In our study,we compare the performance of the OFA algorithm with two other popular algorithms:Genetic Algorithm(GA)and Randomized Search Algorithm(RA).Through extensive simulation experiments,our findings demonstrate significant improvements achieved by the OFA algorithm.Specifically,it leads to up to 39.06%reduction in energy consumption for the Elektroensefalografi(EEG)application,up to 25.86%decrease in CPU utilization for the Intelligent surveillance through distributed camera networks(DCNS)application,up to 57.94%reduction in network utilization,and up to 23.83%improvement in runtime,outperforming other algorithms.As a result,the proposed OFA algorithm enhances the system’s efficiency by effectively allocating incoming task requests to the appropriate fog devices,mitigating the challenges posed by resource limitations and contributing to a more optimized IoT ecosystem.
文摘Gemlik olive was studied by a combined strategy consisting of physic-chemical, sensorial analyses and mathematical relationship among these parameters. Moisture contents of olive fruits decreased from 36.64% to 23.86%, both salt concentration and firmness increased to 9.35 g NaCI/100 g and 51.6% respectively. Total phenols of olive fruits changed from 1714.5 mg GAE/kg to 451.4 mg GAE/kg and radical scavenging activity （DPPH %） decreased from 91.48% to 32.14% respectively. L＊, a＊ and b＊ values of Gemlik olives were decreased during fermentation. There was a close relationship among physicochemical parameters of Gemlik olives in mathematically. In order to model this mathematical relation, Vandermonde matrix based 3th degree polynomial equations was used because it gave best model fits for the data of physical and chemical parameters of olive fruits. On the other hand, according to the results of sensory evaluation, the attributes of saltness and crispiness were highly scored （7.21-7.34） but the sensory scores of astringency and bitterness were evaluated from 4.56 to 5.61 by participants. The physico-chemical characteristic changes during the fermentation of Gemlik olives subjected to dry salting method for producing table olives were modeled and suggested with the determined physico-chemical evaluation scores to future studies.
文摘With the creation of logic gates and algorithms for quantum computers and entering our lives, it is predicted that great developments will take place in this area and important efforts are made. Spin rotation processors are quantum mechanical rotation processors and have no classic counterparts. The rotation operators of spin 1/2 are well known and can be found in related textbooks. But rotation operators of other spins greater than 1/2 can be found numerically by evaluating the series expansions of exponential operator obtained from Schr<span style="white-space:nowrap;">?</span>dinger equation, by evaluation of Wigner-d formula or by recently established expressions in polynomial forms discussed in the text. In a previous paper, rotation operators for spins 1/2 to 2 were published. In this work, explicit symbolic expressions of <em>x</em>, <em></em><em>y</em> and <em>z</em> components of rotation operators for spin 5/2, 3 and 7/2 are worked via exponential operator for each element of related spin operators and utilizing simple linear curve fitting process. The procedures gave out exact expressions of each element of the rotation operators.
文摘We have considered the basic dynamic homogeneous system of partial differential equations of generalized Green-Lindsay couple-stress thermodiffusion on the plane for homogeneous, isotropic elastic media with the centre of symmetry. We have constructed regular solution of the boundary problems on the line. In the works are obtained in quadrates the solution of the boundary-value problem of the generalized Green-Lindsay theory of couple-stress thermodiffusion, when on border of area are given： the component of normal of displacement vector, the component of touching of stress vector, rotations, flow of heat and flow of diffusion.
文摘Solar energy is also a major renewable energy source that is clean and can be sustained at a minimum cost. CSP systems are another highly developed solar energy system that is environmentally friendly and can be installed with simple technology and rational cost. PV solar panels generate electric power when sunlight exists. Similarly, CSP system also generates electric power for immediate consumption when there is sunlight, but it also stores some of the solar energy as heat to be able to continue generating electric power when the weather is cloudy or during the night. In this study, an algorithm and software for effective heliostat were developed. Six districts were selected in Adana province to design and calculate solar power received by heliostat mirrors and delivered to the heat exchanger on top of the tower. Because a solar tracking mechanism is necessary for correct and instant orientation of mirrors, the developed software can calculate the orientation angles of each mirror at any moment of a day of the year. The algorithm also calculates the power received by PV solar panels with fixed orientation and with the same surface area as those of mirrors to compare the energy yields.
文摘Deep learning(DL)techniques,which do not need complex preprocessing and feature analysis,are used in many areas of medicine and achieve promising results.On the other hand,in medical studies,a limited dataset decreases the abstraction ability of the DL model.In this context,we aimed to produce synthetic brain images including three tumor types(glioma,meningioma,and pituitary),unlike traditional data augmentation methods,and classify them with DL.This study proposes a tumor classification model consisting of a Dense Convolutional Network(DenseNet121)-based DL model to prevent forgetting problems in deep networks and delay information flow between layers.By comparing models trained on two different datasets,we demonstrated the effect of synthetic images generated by Cycle Generative Adversarial Network(CycleGAN)on the generalization of DL.One model is trained only on the original dataset,while the other is trained on the combined dataset of synthetic and original images.Synthetic data generated by CycleGAN improved the best accuracy values for glioma,meningioma,and pituitary tumor classes from 0.9633,0.9569,and 0.9904 to 0.9968,0.9920,and 0.9952,respectively.The developed model using synthetic data obtained a higher accuracy value than the related studies in the literature.Additionally,except for pixel-level and affine transform data augmentation,synthetic data has been generated in the figshare brain dataset for the first time.
文摘It is one of the topics that have been studied extensively on maximum power point tracking(MPPT)recently.Traditional or soft computing methods are used for MPPT.Since soft computing approaches are more effective than traditional approaches,studies on MPPT have shifted in this direction.This study aims comparison of performance of seven meta-heuristic training algorithms in the neuro-fuzzy training for MPPT.The meta-heuristic training algorithms used are particle swarm optimization(PSO),harmony search(HS),cuckoo search(CS),artificial bee colony(ABC)algorithm,bee algorithm(BA),differential evolution(DE)and flower pollination algorithm(FPA).The antecedent and conclusion parameters of neuro-fuzzy are determined by these algorithms.The data of a 250 W photovoltaic(PV)is used in the applications.For effective MPPT,different neuro-fuzzy structures,different membership functions and different control parameter values are evaluated in detail.Related training algorithms are compared in terms of solution quality and convergence speed.The strengths and weaknesses of these algorithms are revealed.It is seen that the type and number of membership function,colony size,number of generations affect the solution quality and convergence speed of the training algorithms.As a result,it has been observed that CS and ABC algorithm are more effective than other algorithms in terms of solution quality and convergence in solving the related problem.
文摘Purpose:This study aims to research the impact of the e-learning environment,in which gamebased education software was used,on the learning of students with intellectual disabilities.Design/Approach/Methods:The study group consisted of 34 students with intellectual disabilities studying at a special education vocational school in Canakkale,Turkey.In this study,the true experimental method was used.For 5 weeks,the experimental group received blended learning that was supported by the usage of a game-based education software designed by the researcher,which includes interactive educational game applications.At the same time,control group students only received the teaching process in the classroom with the traditional teaching method.Acourse attitude scale and an achievement test were used fordata collection.Findings:The analysis of the findings showed that there was a significant increase between precourse and post-course attitudes and academic achievement scores of the students.There wasn't a significant difference between pre-course and post-course attitudes and academic achievement scores according to the gender and academic achievement scores.Males'academic achievement and attitude post-test scores were higher than females'scores.Students having upper daily mobile devices usage experience had higher post-test and academic achievement scores than students havinglowerdaily mobile devices usage experience.
