To protect the sustainability of the benefits from seas and near coastal areas,which have under the effect of the very complex hydrodynamic conditions and intensive human activities,without disrupting the balance of n...To protect the sustainability of the benefits from seas and near coastal areas,which have under the effect of the very complex hydrodynamic conditions and intensive human activities,without disrupting the balance of nature,it is necessary to image the status of the seafloor features.Therefore,this study presents the deformations,depositional conditions,underwater constructions,and the other non-natural impacts on the seafloor of the nearshore area at western Istanbul(between Küçükçekmece and Büyükçekmece lagoons)where it intensely used by the citizens.The results of the study may provide some guidance for understanding the impacts and risk factors of uses that are or will be conducted in coastal and/or near-coastal areas.Construction planning for civil coastal structures and areas should be done in great harmony with nature,minimizing negative environmental impacts.Although sediment distribution in the area is generally quite complex,the current state of the region,wave action,hydrodynamic conditions,the amount of material transported from the land,and bathymetry are important influencing factors.The seafloor has been damaged primarily by anchor deformation and associated bottom scanning,as well as disturbing trawl tracks.The seafloor was observed as partially shallowing near the constructions(such as natural gas pipelines,fishermen’s shelter,and port piles)of coastal areas and associated with sand deposits.Therefore,scanning the seafloor using side-scan sonar may provide valuable frequency data to prevent future disruptions.展开更多
Transportation sector is one of the most important elements of a country’s economy with its highway,railway,airway and seaway modes,besides the information and communication infrastructure.Transportation sector has a...Transportation sector is one of the most important elements of a country’s economy with its highway,railway,airway and seaway modes,besides the information and communication infrastructure.Transportation sector has a pattern that affects the society continuously with its economic and social inputs that has a significant role in economies of countries in terms of being an important part of manufacturing process and effects of sizable investments on economy.Demands of more comfortable,more reliable,more safe and more punctual transport in developing economy is an arising trend worldwide and this shows an increase the importance of the transportation sector.Establishment of an efficient and functional transportation system is closely related with traffic safety,intermodal integration and balanced modal distribution.In Turkey,an important improvement has been achieved in these issues,but also some basic constitutive problems are still continuing.These constitutional problems can be summarized as providing traffic safety,integration of innovative implementations to transportation system,enhancing of infrastructure and an effective usage of existing infrastructure.展开更多
Today,urban traffic,growing populations,and dense transportation networks are contributing to an increase in traffic incidents.These incidents include traffic accidents,vehicle breakdowns,fires,and traffic disputes,re...Today,urban traffic,growing populations,and dense transportation networks are contributing to an increase in traffic incidents.These incidents include traffic accidents,vehicle breakdowns,fires,and traffic disputes,resulting in long waiting times,high carbon emissions,and other undesirable situations.It is vital to estimate incident response times quickly and accurately after traffic incidents occur for the success of incident-related planning and response activities.This study presents a model for forecasting the traffic incident duration of traffic events with high precision.The proposed model goes through a 4-stage process using various features to predict the duration of four different traffic events and presents a feature reduction approach to enable real-time data collection and prediction.In the first stage,the dataset consisting of 24,431 data points and 75 variables is prepared by data collection,merging,missing data processing and data cleaning.In the second stage,models such as Decision Trees(DT),K-Nearest Neighbour(KNN),Random Forest(RF)and Support Vector Machines(SVM)are used and hyperparameter optimisation is performed with GridSearchCV.In the third stage,feature selection and reduction are performed and real-time data are used.In the last stage,model performance with 14 variables is evaluated with metrics such as accuracy,precision,recall,F1-score,MCC,confusion matrix and SHAP.The RF model outperforms other models with an accuracy of 98.5%.The study’s prediction results demonstrate that the proposed dynamic prediction model can achieve a high level of success.展开更多
Transportation sector is one of the most important elements of a country’s economy with its highway,railway,airway and seaway modes,besides the information and communication infrastructure.Transportation sector has a...Transportation sector is one of the most important elements of a country’s economy with its highway,railway,airway and seaway modes,besides the information and communication infrastructure.Transportation sector has a pattern that affects the society continuously with its economic and social inputs that has a significant role in economies of countries in terms of being an important part of manufacturing process and effects of sizable investments on economy.Demands of more comfortable,more reliable,more safe and more punctual transport in developing economy is an arising trend worldwide and this shows an increase the importance of the transportation sector.Establishment of an efficient and functional transportation system is closely related with traffic safety,intermodal integration and balanced modal distribution.In Turkey,an important improvement has been achieved in these issues,but also some basic constitutive problems are still continuing.These constitutional problems can be summarized as providing traffic safety,integration of innovative implementations to transportation system,enhancing of infrastructure and an effective usage of existing infrastructure.展开更多
BACKGROUND Inadequate glycemic control in patients with type 2 diabetes(T2DM)is a major public health problem and a significant risk factor for the progression of diabetic complications.AIM To evaluate the effects of ...BACKGROUND Inadequate glycemic control in patients with type 2 diabetes(T2DM)is a major public health problem and a significant risk factor for the progression of diabetic complications.AIM To evaluate the effects of intensive and supportive glycemic management strategies over a 12-month period in individuals with T2DM with glycated hemoglobin(HbA1c)≥10%and varying backgrounds of glycemic control.METHODS This prospective observational study investigated glycemic control in patients with poorly controlled T2DM over 12 months.Participants were categorized into four groups based on prior glycemic history:Newly diagnosed,previously well controlled with recent worsening,previously off-target but now worsening,and HbA1c consistently above 10%.HbA1c levels were monitored quarterly,and patients received medical,educational,and dietary support as needed.The analysis focused on the success rates of good glycemic control and the associated factors within each group.RESULTS The study showed significant improvements in HbA1c levels in all participants.The most significant improvement was observed in individuals newly diagnosed with diabetes:65%achieved an HbA1c target of≤7%.The results varied between participants with different glycemic control histories,followed by decreasing success rates:39%in participants with previously good glycemic control,21%in participants whose glycemic control had deteriorated compared to before,and only 10%in participants with persistently poor control,with mean HbA1c levels of 6.3%,7.7%,8.2%,and 9.7%,respectively.After one year,65.2%of the“newly diagnosed patients”,39.3%in the“previously controlled group”,21.9%in the“previously off-target but now worsened'”group and 10%in the“poorly controlled from the start”group had achieved HbA1c levels of 7 and below.CONCLUSION In poorly controlled diabetes,the rate at which treatment goals are achieved is associated with the glycemic background characteristics,emphasizing the need for tailored strategies.Therefore,different and comprehensive treatment approaches are needed for patients with persistent uncontrolled diabetes.展开更多
Spermatozoa have a highly complex RNA profile.Several of these transcripts are suggested as biomarkers for male infertility and contribute to early development.To analyze the differences between sperm RNA quantity and...Spermatozoa have a highly complex RNA profile.Several of these transcripts are suggested as biomarkers for male infertility and contribute to early development.To analyze the differences between sperm RNA quantity and expression of protamine(PRM1 and PRM2)and testis-specific histone 2B(TH2B)genes,spermatozoa from 33 patients who enrolled in assisted reproduction treatment(ART)program were analyzed.Sperm RNA of teratozoospermic(T),oligoteratozoospermic(OT),and normozoospermic(N)samples was extracted,and the differences in transcript levels among the study groups were analyzed by quantitative real-time polymerase chain reaction(qRT-PCR).The correlations of total RNA per spermatozoon and the expression of the transcripts were evaluated in relation to sperm characteristics and preimplantation embryo development.The mean(±standard deviation)RNA amount per spermatozoon was 28.48(±23.03)femtogram in the overall group and was significantly higher in the OT group than that in N and T groups.Total sperm RNA and gene expression of PRM1 and PRM2 genes were related to preimplantation embryo development and developmental arrest.Specific sperm characteristics were correlated with the expressions of PRM1,PRM2,or TH2B genes.We conclude that the sperm RNA amount and composition are important factors and might influence early embryonic development and also differ in different cases of male infertility.展开更多
This study evaluates the use of predictive analytics to forecast customer turnover in subscription-based Services in order to develop a predictive model to help small and medium-sized enterprises manage customer churn...This study evaluates the use of predictive analytics to forecast customer turnover in subscription-based Services in order to develop a predictive model to help small and medium-sized enterprises manage customer churn in the face of digital disruption.The research uses a quantitative approach focusing on empirical customer data to accurately predict buying trends and adapt marketing techniques.Demand forecasts in the health sector are important,as in every sector.In particular,the material forecast and stock forecasting of the purchasing unit of hospitals are among the areas that receive significant attention.Four classifiers(Random Forest,Logistic Regression,Gradient Boosting and XGBoost)are trained and evaluated using various performance indicators as part of a systematic approach involving Kaggle data collection,preparation and model selection.The results show excellent accuracy in predicting customer attrition,but there are limitations in precision and recall,indicating room for improvement.Confusion matrices provide information about the performance of each classifier,allowing for continuous improvement of predictive analytics techniques.Ethical concerns are rigorously addressed throughout the work process to guarantee appropriate data and machine learning methodologies.The proposals emphasize the proactive use of predictive analytics to identify at-risk customers and implement targeted retention strategies.Incorporating new data sources,improving customer experience,and utilizing collaborative churn management methods are recommended to increase forecast accuracy and business outcomes.Finally,this research provides important insights into the usefulness of predictive analytics for customer churn forecasting as well as practical recommendations for businesses seeking to increase customer retention and reduce churn risk.By leveraging empirical research findings and implementing ethical and rigorous churn control strategies,businesses can achieve long-term success in today’s changing market environment.展开更多
People have been engaged in sports activities both individually and collectively for years.Sports consumption,which refers to the process that covers many issues related to sports in the form of playing,watching,liste...People have been engaged in sports activities both individually and collectively for years.Sports consumption,which refers to the process that covers many issues related to sports in the form of playing,watching,listening or reading,is a form of human behavior.The satisfaction of the four marketing components of product,price,distribution and promotion by using the leisure time of the sports consumer effectively and ensuring its continuity in the future process can be ensured by effective utilization of facilities and quality recreation activities.Consumer behaviors,which have a very complex structure,are seen in the form of choosing,buying,using and obtaining.With this study,it is aimed to determine the mediating role of consumer decision-making styles in determining the effect of marketing components in the consumption of sports activities on the satisfaction of sports consumers.In this direction,data were collected in the province of Istanbul,which was determined as the sample.Data were obtained with a questionnaire form created on Google Form.These data were analyzed in line with the model and hypotheses created with these data and it was determined that the marketing components of sports consumption have an impact on the sports consumer and it was concluded that consumer decision-making styles have a positive mediating effect in this regard.展开更多
While people met in order to socialize on public spaces in the past, these areas are perceived as a ‘alone in the crowds’ by people who are in the loneliness of modern era, as well as these areas still serve as a so...While people met in order to socialize on public spaces in the past, these areas are perceived as a ‘alone in the crowds’ by people who are in the loneliness of modern era, as well as these areas still serve as a social area. Individuals from all of society, especially minority groups, feel that they are accepted and they show themselves in a way in the public space. Even though the perception and usage of public space have changed in time, people still feel free themselves in these areas. However, ‘terrorism’, which is a reality in today's world, is one of the cases which pose danger to the public spaces. Thus, the image of these areas has changed from “the areas where individuals they feel freer” to “the areas where people are vulnerable to many potential attacks”. This study tells you how the public perception has changed over time and examine the intended use of the public due to these changes. Terrorist activities increased all of the World and public spaces of the individual in the face of this reality, perception and Jane Jacobs, urban life and public relations with the charm of the terrorist phenomenon is one of the main problems the 21st century in the context of views on security are discussed. Also in this report, in order to provide a team recommendation for safe public space taking into account the author's views on security was available. For this purpose, the metropolis of Istanbul is selected as the study area were interviewed and the people living in Istanbul with internet environment. At the end of the 90s until today has changed the perception of how the public and in the public domain when individuals are discussed how they use.展开更多
With the developing and rapidly changing technology,marketing strategies have necessarily changed in order to meet the demands and needs of consumers.The inability of businesses to keep up with this changing system pu...With the developing and rapidly changing technology,marketing strategies have necessarily changed in order to meet the demands and needs of consumers.The inability of businesses to keep up with this changing system pushes them out of the process.In daily life,where consumption never ends,marketing strategies are also consumed very quickly.Although the name changes according to age,the main goal is always more profitability.Digitalization of sales and marketing has made shopping in virtual environments widespread.Most customer services are performed by chatbots.It is seen that these studies are also carried out in the field of health services.From Siri to augmented reality applications,they are in our lives.These intelligent systems date back to the 1970s.So,where are the artificial intelligence and intelligent robots that have taken their place in almost every sector,from health to defense,which has been the favorite of recent years?Although the answer to this question has only recently begun to be researched,it seems that it will be one of the most important issues in the near future.In this study,which seeks a definitive answer to this question,the place and future of artificial intelligence in marketing strategies are discussed.In addition to contributing to the academic world,the study is thought to be useful in artificial intelligence studies.展开更多
Reinforced concrete buildings may experience partial damage after earthquakes or some human-induced actions.A decision about the future of those buildings requires detailed analyses,while determining the dynamic chara...Reinforced concrete buildings may experience partial damage after earthquakes or some human-induced actions.A decision about the future of those buildings requires detailed analyses,while determining the dynamic characteristics of a real building in its pre-and post-event situations can guide the analysis.Hence,this study was planned to monitor the dynamic response of an existing six-story,reinforced concrete building with regard to structural damage.The modal characteristics of the original building were initially determined by the use of operational modal analysis.Next,three steps of progressive structural damage were applied to the building.The first damage level peeled off the clear cover of a beam and three columns on a corner of the building’s ground floor.whereas the second and third levels completely razed the damaged columns.Operational modal analysis was repeated at each damage stage to extract the frequencies and detailed mode shapes.Moreover,numerical models based on the finite element method were constructed to confirm the obtained experimental findings.The well-agreed experimental and numerical findings revealed the damage sensitivity of the building’s dynamic response.The quantified amount of frequency change favored a retrofit of the partially damaged buildings rather than their replacement.展开更多
Organizations often use sentiment analysis-based systems or even resort to simple manual analysis to try to extract useful meaning from their customers’general digital“chatter”.Driven by the need for a more accurat...Organizations often use sentiment analysis-based systems or even resort to simple manual analysis to try to extract useful meaning from their customers’general digital“chatter”.Driven by the need for a more accurate way to qualitatively extract valuable product and brand-oriented consumer-generated texts,this paper experimentally tests the ability of an NLP-based analytics approach to extract information from highly unstructured texts.The results show that natural language processing outperforms sentiment analysis for detecting issues from social media data.Surprisingly,the experiment shows that sentiment analysis is not only better than manual analysis of social media data for the goal of supporting organizational decision-making,but may also be disadvantageous for such efforts.展开更多
Due to their superior properties, the interest in nanostructures is increasing today in engineering. This study presents a new two-noded curved finite element for analyzing the in-plane static behaviors of curved nano...Due to their superior properties, the interest in nanostructures is increasing today in engineering. This study presents a new two-noded curved finite element for analyzing the in-plane static behaviors of curved nanobeams. Opposite to traditional curved finite elements developed by using approximate interpolation functions, the proposed curved finite element is developed by using exact analytical solutions. Although this approach was first introduced for analyzing the mechanical behaviors of macro-scale curved beams by adopting the local theory of elasticity, the exact analytical expressions used in this study were obtained from the solutions of governing equations that were expressed via the differential form of the nonlocal theory of elasticity. Therefore, the effects of shear strain and axial extension included in the analytical formulation are also inherited by the curved finite element developed here. The rigidity matrix and the consistent force vector are developed for a circular finite element. To demonstrate the applicability of the method, static analyses of various curved nanobeams subjected to different boundary conditions and loading scenarios are performed, and the obtained results are compared with the exact analytical ones. The presented study provides an accurate and low computational cost method for researchers to investigate the in-plane static behavior of curved nanobeams.展开更多
Liquefaction is one of the prominent factors leading to damage to soil and structures.In this study,the rela-tionship between liquefaction potential and soil parameters is determined by applying feature importance met...Liquefaction is one of the prominent factors leading to damage to soil and structures.In this study,the rela-tionship between liquefaction potential and soil parameters is determined by applying feature importance methods to Random Forest(RF),Logistic Regression(LR),Multilayer Perceptron(MLP),Support Vector Machine(SVM)and eXtreme Gradient Boosting(XGBoost)algorithms.Feature importance methods consist of permuta-tion and Shapley Additive exPlanations(SHAP)importances along with the used model’s built-in feature importance method if it exists.These suggested approaches incorporate an extensive dataset of geotechnical parameters,historical liquefaction events,and soil properties.The feature set comprises 18 parameters that are gathered from 161 field cases.Algorithms are used to determine the optimum performance feature set.Compared to other approaches,the study assesses how well these algorithms predict soil liquefaction potential.Early findings show that the algorithms perform well,demonstrating their capacity to identify non-linear connections and improve prediction accuracy.Among the feature set,σ,v(psf),MSF,CSRσ,v,FC%,Vs*,40f t(f ps)and N1,60,CS are the ones that have the highest deterministic power on the result.The study’s contribution is that,in the absence of extensive data for liquefaction assessment,the proposed method estimates the liquefaction potential using five parameters with promising accuracy.展开更多
This study aims to develop a quantum computing-based neurocognitive architecture that allows an agent to perform autonomous behaviors.Therefore,we present a brain-inspired cognitive architecture for autonomous agents ...This study aims to develop a quantum computing-based neurocognitive architecture that allows an agent to perform autonomous behaviors.Therefore,we present a brain-inspired cognitive architecture for autonomous agents that integrates a prefrontal cortex-inspired model with modern deep learning(a transformer-based reinforcement learning module)and quantum algorithms.In particular,our framework incorporates quantum computational routines(Deutsch-Jozsa,Bernstein-Vazirani,and Grover’s search)to enhance decision-making efficiency.As a novelty of this research,this comprehensive computational structure is empowered by quantum computing operations so that superiority in speed and robustness of learning compared to classical methods can be demonstrated.Another main contribution is that the proposed architecture offers some features,such as meta-cognition and situation awareness.The meta-cognition aspect is responsible for hierarchically learning sub-tasks,enabling the agent to achieve the master goal.The situation-awareness property identifies how spatial-temporal reasoning activities related to the world model of the agent can be extracted in a dynamic simulation environment with unstructured uncertainties by quantum computation-based machine learning algorithms with the explainable artificial intelligence paradigm.In this research,the Minecraft game-based simulation environment is utilized for the experimental evaluation of performance and verification tests within complex,multi-objective tasks related to the autonomous behaviors of a smart agent.By implementing several interaction scenarios,the results of the system performance and comparative superiority over alternative solutions are presented,and it is discussed how these autonomous behaviors and cognitive skills of a smart agent can be improved in further studies.Results show that the quantum-enhanced agent achieves faster convergence to an 80%task 2×success rate in exploration tasks and approximately 15%higher cumulative rewards compared to a classical deep RL baseline.These findings demonstrate the potential of quantum algorithms to significantly improve learning and performance in cognitive agent architectures.However,advantages are task-specific and less pronounced under high-uncertainty,reactive scenarios.Limitations of the simulation environment are acknowledged,and a structured future research roadmap is proposed involving highfidelity simulation validation,hardware-in-the-loop robotic testing,and integration of advanced hybrid quantum-classical architectures.展开更多
In this article,a well-known anisotropic solution,the Tolman-Finch-Skea(TFS)solution,is studied using the gravitational decoupling approach within the framework of 4D Einstein-Gauss-Bonnet(EGB)gravity.The radial metri...In this article,a well-known anisotropic solution,the Tolman-Finch-Skea(TFS)solution,is studied using the gravitational decoupling approach within the framework of 4D Einstein-Gauss-Bonnet(EGB)gravity.The radial metric potential is modified linearly through the minimal geometric deformation approach,while the temporal component of the metric remains unchanged.The system of EGB field equations is decomposed into two distinct sets of field equations:one corresponding to the standard energy-momentum tensor and the other associated with an external gravitational source.The first system is solved using the aforementioned known solution,while the second is closed by imposing the mimic constraint on pressure.Moreover,the junction conditions at the inner and outer surfaces of the stellar object are examined,considering the Boulware-Deser 4D space-time as the external geometry.The physical properties of the stellar model are analyzed using parameters such as energy conditions,causality conditions,compactness,and redshift.展开更多
Fontan operation is indicated in a single ventricle congenital heart disease which creates a shunt between superior vena cava and pulmonary arteries leading to increased pressure in central venous system and congestiv...Fontan operation is indicated in a single ventricle congenital heart disease which creates a shunt between superior vena cava and pulmonary arteries leading to increased pressure in central venous system and congestive hepatopathy,namely,Fontan-associated liver disease(FALD)[1].Recently,the long-term prognosis after Fontan operation has been improving and the number of patients diagnosed with hepatocellular carcinoma(HCC)arising from FALD is increasing[1].There are several publications on the safety of laparoscopic,conventional surgery and interventional radiological modalities in FALD-HCC patients[2-5].However,there are no reports regarding the robotic hepatectomy for the FALD-HCC patients.This was the first report showing the safety of robotic anatomical hepatectomy in FALD-HCC patients.展开更多
This study presents the results of a Monte Carlo simulation to compare the statistical power of Siegel-Tukey and Savage tests.The main purpose of the study is to evaluate the statistical power of both tests in scenari...This study presents the results of a Monte Carlo simulation to compare the statistical power of Siegel-Tukey and Savage tests.The main purpose of the study is to evaluate the statistical power of both tests in scenarios involving Normal,Platykurtic and Skewed distributions over different sample sizes and standard deviation values.In the study,standard deviation ratios were set as 2,3,4,1/2,1/3 and 1/4 and power comparisons were made between small and large sample sizes.For equal sample sizes,small sample sizes of 5,8,10,12,16 and 20 and large sample sizes of 25,50,75 and 100 were used.For different sample sizes,the combinations of(4,16),(8,16),(10,20),(16,4),(16,8)and(20,10)small sample sizes and(10,30),(30,10),(50,75),(50,100),(75,50),(75,100),(100,50)and(100,75)large sample sizes were examined in detail.According to the findings,the power analysis under variance heterogeneity conditions shows that the Siegel-Tukey test has a higher statistical power than the other nonparametric Savage test at small and large sample sizes.In particular,the Siegel-Tukey test was reported to offer higher precision and power under variance heterogeneity,regardless of having equal or different sample sizes.展开更多
The increase in user mobility and density in modern cellular networks increases the risk of overloading certain base stations in popular locations such as shopping malls or stadiums,which can result in connection loss...The increase in user mobility and density in modern cellular networks increases the risk of overloading certain base stations in popular locations such as shopping malls or stadiums,which can result in connection loss for some users.To combat this,the traffic load of base stations should be kept as balanced as possible.In this paper,we propose an efficient load balancing-aware handover algorithm for highly dynamic beyond 5G heterogeneous networks by assigning mobile users to base stations with lighter loads when a handover is performed.The proposed algorithm is evaluated in a scenario with users having different levels of mobility,such as pedestrians and vehicles,and is shown to outperform the conventional handover mechanism,as well as another algorithm from the literature.As a secondary benefit,the overall energy consumption in the network is shown to be reduced with the proposed algorithm.展开更多
文摘To protect the sustainability of the benefits from seas and near coastal areas,which have under the effect of the very complex hydrodynamic conditions and intensive human activities,without disrupting the balance of nature,it is necessary to image the status of the seafloor features.Therefore,this study presents the deformations,depositional conditions,underwater constructions,and the other non-natural impacts on the seafloor of the nearshore area at western Istanbul(between Küçükçekmece and Büyükçekmece lagoons)where it intensely used by the citizens.The results of the study may provide some guidance for understanding the impacts and risk factors of uses that are or will be conducted in coastal and/or near-coastal areas.Construction planning for civil coastal structures and areas should be done in great harmony with nature,minimizing negative environmental impacts.Although sediment distribution in the area is generally quite complex,the current state of the region,wave action,hydrodynamic conditions,the amount of material transported from the land,and bathymetry are important influencing factors.The seafloor has been damaged primarily by anchor deformation and associated bottom scanning,as well as disturbing trawl tracks.The seafloor was observed as partially shallowing near the constructions(such as natural gas pipelines,fishermen’s shelter,and port piles)of coastal areas and associated with sand deposits.Therefore,scanning the seafloor using side-scan sonar may provide valuable frequency data to prevent future disruptions.
文摘Transportation sector is one of the most important elements of a country’s economy with its highway,railway,airway and seaway modes,besides the information and communication infrastructure.Transportation sector has a pattern that affects the society continuously with its economic and social inputs that has a significant role in economies of countries in terms of being an important part of manufacturing process and effects of sizable investments on economy.Demands of more comfortable,more reliable,more safe and more punctual transport in developing economy is an arising trend worldwide and this shows an increase the importance of the transportation sector.Establishment of an efficient and functional transportation system is closely related with traffic safety,intermodal integration and balanced modal distribution.In Turkey,an important improvement has been achieved in these issues,but also some basic constitutive problems are still continuing.These constitutional problems can be summarized as providing traffic safety,integration of innovative implementations to transportation system,enhancing of infrastructure and an effective usage of existing infrastructure.
文摘Today,urban traffic,growing populations,and dense transportation networks are contributing to an increase in traffic incidents.These incidents include traffic accidents,vehicle breakdowns,fires,and traffic disputes,resulting in long waiting times,high carbon emissions,and other undesirable situations.It is vital to estimate incident response times quickly and accurately after traffic incidents occur for the success of incident-related planning and response activities.This study presents a model for forecasting the traffic incident duration of traffic events with high precision.The proposed model goes through a 4-stage process using various features to predict the duration of four different traffic events and presents a feature reduction approach to enable real-time data collection and prediction.In the first stage,the dataset consisting of 24,431 data points and 75 variables is prepared by data collection,merging,missing data processing and data cleaning.In the second stage,models such as Decision Trees(DT),K-Nearest Neighbour(KNN),Random Forest(RF)and Support Vector Machines(SVM)are used and hyperparameter optimisation is performed with GridSearchCV.In the third stage,feature selection and reduction are performed and real-time data are used.In the last stage,model performance with 14 variables is evaluated with metrics such as accuracy,precision,recall,F1-score,MCC,confusion matrix and SHAP.The RF model outperforms other models with an accuracy of 98.5%.The study’s prediction results demonstrate that the proposed dynamic prediction model can achieve a high level of success.
文摘Transportation sector is one of the most important elements of a country’s economy with its highway,railway,airway and seaway modes,besides the information and communication infrastructure.Transportation sector has a pattern that affects the society continuously with its economic and social inputs that has a significant role in economies of countries in terms of being an important part of manufacturing process and effects of sizable investments on economy.Demands of more comfortable,more reliable,more safe and more punctual transport in developing economy is an arising trend worldwide and this shows an increase the importance of the transportation sector.Establishment of an efficient and functional transportation system is closely related with traffic safety,intermodal integration and balanced modal distribution.In Turkey,an important improvement has been achieved in these issues,but also some basic constitutive problems are still continuing.These constitutional problems can be summarized as providing traffic safety,integration of innovative implementations to transportation system,enhancing of infrastructure and an effective usage of existing infrastructure.
文摘BACKGROUND Inadequate glycemic control in patients with type 2 diabetes(T2DM)is a major public health problem and a significant risk factor for the progression of diabetic complications.AIM To evaluate the effects of intensive and supportive glycemic management strategies over a 12-month period in individuals with T2DM with glycated hemoglobin(HbA1c)≥10%and varying backgrounds of glycemic control.METHODS This prospective observational study investigated glycemic control in patients with poorly controlled T2DM over 12 months.Participants were categorized into four groups based on prior glycemic history:Newly diagnosed,previously well controlled with recent worsening,previously off-target but now worsening,and HbA1c consistently above 10%.HbA1c levels were monitored quarterly,and patients received medical,educational,and dietary support as needed.The analysis focused on the success rates of good glycemic control and the associated factors within each group.RESULTS The study showed significant improvements in HbA1c levels in all participants.The most significant improvement was observed in individuals newly diagnosed with diabetes:65%achieved an HbA1c target of≤7%.The results varied between participants with different glycemic control histories,followed by decreasing success rates:39%in participants with previously good glycemic control,21%in participants whose glycemic control had deteriorated compared to before,and only 10%in participants with persistently poor control,with mean HbA1c levels of 6.3%,7.7%,8.2%,and 9.7%,respectively.After one year,65.2%of the“newly diagnosed patients”,39.3%in the“previously controlled group”,21.9%in the“previously off-target but now worsened'”group and 10%in the“poorly controlled from the start”group had achieved HbA1c levels of 7 and below.CONCLUSION In poorly controlled diabetes,the rate at which treatment goals are achieved is associated with the glycemic background characteristics,emphasizing the need for tailored strategies.Therefore,different and comprehensive treatment approaches are needed for patients with persistent uncontrolled diabetes.
基金supported by the Scientific Research Projects Coordination Unit of Istanbul University(No.13930).
文摘Spermatozoa have a highly complex RNA profile.Several of these transcripts are suggested as biomarkers for male infertility and contribute to early development.To analyze the differences between sperm RNA quantity and expression of protamine(PRM1 and PRM2)and testis-specific histone 2B(TH2B)genes,spermatozoa from 33 patients who enrolled in assisted reproduction treatment(ART)program were analyzed.Sperm RNA of teratozoospermic(T),oligoteratozoospermic(OT),and normozoospermic(N)samples was extracted,and the differences in transcript levels among the study groups were analyzed by quantitative real-time polymerase chain reaction(qRT-PCR).The correlations of total RNA per spermatozoon and the expression of the transcripts were evaluated in relation to sperm characteristics and preimplantation embryo development.The mean(±standard deviation)RNA amount per spermatozoon was 28.48(±23.03)femtogram in the overall group and was significantly higher in the OT group than that in N and T groups.Total sperm RNA and gene expression of PRM1 and PRM2 genes were related to preimplantation embryo development and developmental arrest.Specific sperm characteristics were correlated with the expressions of PRM1,PRM2,or TH2B genes.We conclude that the sperm RNA amount and composition are important factors and might influence early embryonic development and also differ in different cases of male infertility.
文摘This study evaluates the use of predictive analytics to forecast customer turnover in subscription-based Services in order to develop a predictive model to help small and medium-sized enterprises manage customer churn in the face of digital disruption.The research uses a quantitative approach focusing on empirical customer data to accurately predict buying trends and adapt marketing techniques.Demand forecasts in the health sector are important,as in every sector.In particular,the material forecast and stock forecasting of the purchasing unit of hospitals are among the areas that receive significant attention.Four classifiers(Random Forest,Logistic Regression,Gradient Boosting and XGBoost)are trained and evaluated using various performance indicators as part of a systematic approach involving Kaggle data collection,preparation and model selection.The results show excellent accuracy in predicting customer attrition,but there are limitations in precision and recall,indicating room for improvement.Confusion matrices provide information about the performance of each classifier,allowing for continuous improvement of predictive analytics techniques.Ethical concerns are rigorously addressed throughout the work process to guarantee appropriate data and machine learning methodologies.The proposals emphasize the proactive use of predictive analytics to identify at-risk customers and implement targeted retention strategies.Incorporating new data sources,improving customer experience,and utilizing collaborative churn management methods are recommended to increase forecast accuracy and business outcomes.Finally,this research provides important insights into the usefulness of predictive analytics for customer churn forecasting as well as practical recommendations for businesses seeking to increase customer retention and reduce churn risk.By leveraging empirical research findings and implementing ethical and rigorous churn control strategies,businesses can achieve long-term success in today’s changing market environment.
文摘People have been engaged in sports activities both individually and collectively for years.Sports consumption,which refers to the process that covers many issues related to sports in the form of playing,watching,listening or reading,is a form of human behavior.The satisfaction of the four marketing components of product,price,distribution and promotion by using the leisure time of the sports consumer effectively and ensuring its continuity in the future process can be ensured by effective utilization of facilities and quality recreation activities.Consumer behaviors,which have a very complex structure,are seen in the form of choosing,buying,using and obtaining.With this study,it is aimed to determine the mediating role of consumer decision-making styles in determining the effect of marketing components in the consumption of sports activities on the satisfaction of sports consumers.In this direction,data were collected in the province of Istanbul,which was determined as the sample.Data were obtained with a questionnaire form created on Google Form.These data were analyzed in line with the model and hypotheses created with these data and it was determined that the marketing components of sports consumption have an impact on the sports consumer and it was concluded that consumer decision-making styles have a positive mediating effect in this regard.
文摘While people met in order to socialize on public spaces in the past, these areas are perceived as a ‘alone in the crowds’ by people who are in the loneliness of modern era, as well as these areas still serve as a social area. Individuals from all of society, especially minority groups, feel that they are accepted and they show themselves in a way in the public space. Even though the perception and usage of public space have changed in time, people still feel free themselves in these areas. However, ‘terrorism’, which is a reality in today's world, is one of the cases which pose danger to the public spaces. Thus, the image of these areas has changed from “the areas where individuals they feel freer” to “the areas where people are vulnerable to many potential attacks”. This study tells you how the public perception has changed over time and examine the intended use of the public due to these changes. Terrorist activities increased all of the World and public spaces of the individual in the face of this reality, perception and Jane Jacobs, urban life and public relations with the charm of the terrorist phenomenon is one of the main problems the 21st century in the context of views on security are discussed. Also in this report, in order to provide a team recommendation for safe public space taking into account the author's views on security was available. For this purpose, the metropolis of Istanbul is selected as the study area were interviewed and the people living in Istanbul with internet environment. At the end of the 90s until today has changed the perception of how the public and in the public domain when individuals are discussed how they use.
文摘With the developing and rapidly changing technology,marketing strategies have necessarily changed in order to meet the demands and needs of consumers.The inability of businesses to keep up with this changing system pushes them out of the process.In daily life,where consumption never ends,marketing strategies are also consumed very quickly.Although the name changes according to age,the main goal is always more profitability.Digitalization of sales and marketing has made shopping in virtual environments widespread.Most customer services are performed by chatbots.It is seen that these studies are also carried out in the field of health services.From Siri to augmented reality applications,they are in our lives.These intelligent systems date back to the 1970s.So,where are the artificial intelligence and intelligent robots that have taken their place in almost every sector,from health to defense,which has been the favorite of recent years?Although the answer to this question has only recently begun to be researched,it seems that it will be one of the most important issues in the near future.In this study,which seeks a definitive answer to this question,the place and future of artificial intelligence in marketing strategies are discussed.In addition to contributing to the academic world,the study is thought to be useful in artificial intelligence studies.
基金supported by the Scientific and Technological Research Council of Türkiye(TUBITAK)under Research Grant 116M254.
文摘Reinforced concrete buildings may experience partial damage after earthquakes or some human-induced actions.A decision about the future of those buildings requires detailed analyses,while determining the dynamic characteristics of a real building in its pre-and post-event situations can guide the analysis.Hence,this study was planned to monitor the dynamic response of an existing six-story,reinforced concrete building with regard to structural damage.The modal characteristics of the original building were initially determined by the use of operational modal analysis.Next,three steps of progressive structural damage were applied to the building.The first damage level peeled off the clear cover of a beam and three columns on a corner of the building’s ground floor.whereas the second and third levels completely razed the damaged columns.Operational modal analysis was repeated at each damage stage to extract the frequencies and detailed mode shapes.Moreover,numerical models based on the finite element method were constructed to confirm the obtained experimental findings.The well-agreed experimental and numerical findings revealed the damage sensitivity of the building’s dynamic response.The quantified amount of frequency change favored a retrofit of the partially damaged buildings rather than their replacement.
文摘Organizations often use sentiment analysis-based systems or even resort to simple manual analysis to try to extract useful meaning from their customers’general digital“chatter”.Driven by the need for a more accurate way to qualitatively extract valuable product and brand-oriented consumer-generated texts,this paper experimentally tests the ability of an NLP-based analytics approach to extract information from highly unstructured texts.The results show that natural language processing outperforms sentiment analysis for detecting issues from social media data.Surprisingly,the experiment shows that sentiment analysis is not only better than manual analysis of social media data for the goal of supporting organizational decision-making,but may also be disadvantageous for such efforts.
基金supported by Scientific Research Projects Department of Istanbul Technical University.Project Number:MGA-2018-41546.Grant receiver:E.T.
文摘Due to their superior properties, the interest in nanostructures is increasing today in engineering. This study presents a new two-noded curved finite element for analyzing the in-plane static behaviors of curved nanobeams. Opposite to traditional curved finite elements developed by using approximate interpolation functions, the proposed curved finite element is developed by using exact analytical solutions. Although this approach was first introduced for analyzing the mechanical behaviors of macro-scale curved beams by adopting the local theory of elasticity, the exact analytical expressions used in this study were obtained from the solutions of governing equations that were expressed via the differential form of the nonlocal theory of elasticity. Therefore, the effects of shear strain and axial extension included in the analytical formulation are also inherited by the curved finite element developed here. The rigidity matrix and the consistent force vector are developed for a circular finite element. To demonstrate the applicability of the method, static analyses of various curved nanobeams subjected to different boundary conditions and loading scenarios are performed, and the obtained results are compared with the exact analytical ones. The presented study provides an accurate and low computational cost method for researchers to investigate the in-plane static behavior of curved nanobeams.
文摘Liquefaction is one of the prominent factors leading to damage to soil and structures.In this study,the rela-tionship between liquefaction potential and soil parameters is determined by applying feature importance methods to Random Forest(RF),Logistic Regression(LR),Multilayer Perceptron(MLP),Support Vector Machine(SVM)and eXtreme Gradient Boosting(XGBoost)algorithms.Feature importance methods consist of permuta-tion and Shapley Additive exPlanations(SHAP)importances along with the used model’s built-in feature importance method if it exists.These suggested approaches incorporate an extensive dataset of geotechnical parameters,historical liquefaction events,and soil properties.The feature set comprises 18 parameters that are gathered from 161 field cases.Algorithms are used to determine the optimum performance feature set.Compared to other approaches,the study assesses how well these algorithms predict soil liquefaction potential.Early findings show that the algorithms perform well,demonstrating their capacity to identify non-linear connections and improve prediction accuracy.Among the feature set,σ,v(psf),MSF,CSRσ,v,FC%,Vs*,40f t(f ps)and N1,60,CS are the ones that have the highest deterministic power on the result.The study’s contribution is that,in the absence of extensive data for liquefaction assessment,the proposed method estimates the liquefaction potential using five parameters with promising accuracy.
文摘This study aims to develop a quantum computing-based neurocognitive architecture that allows an agent to perform autonomous behaviors.Therefore,we present a brain-inspired cognitive architecture for autonomous agents that integrates a prefrontal cortex-inspired model with modern deep learning(a transformer-based reinforcement learning module)and quantum algorithms.In particular,our framework incorporates quantum computational routines(Deutsch-Jozsa,Bernstein-Vazirani,and Grover’s search)to enhance decision-making efficiency.As a novelty of this research,this comprehensive computational structure is empowered by quantum computing operations so that superiority in speed and robustness of learning compared to classical methods can be demonstrated.Another main contribution is that the proposed architecture offers some features,such as meta-cognition and situation awareness.The meta-cognition aspect is responsible for hierarchically learning sub-tasks,enabling the agent to achieve the master goal.The situation-awareness property identifies how spatial-temporal reasoning activities related to the world model of the agent can be extracted in a dynamic simulation environment with unstructured uncertainties by quantum computation-based machine learning algorithms with the explainable artificial intelligence paradigm.In this research,the Minecraft game-based simulation environment is utilized for the experimental evaluation of performance and verification tests within complex,multi-objective tasks related to the autonomous behaviors of a smart agent.By implementing several interaction scenarios,the results of the system performance and comparative superiority over alternative solutions are presented,and it is discussed how these autonomous behaviors and cognitive skills of a smart agent can be improved in further studies.Results show that the quantum-enhanced agent achieves faster convergence to an 80%task 2×success rate in exploration tasks and approximately 15%higher cumulative rewards compared to a classical deep RL baseline.These findings demonstrate the potential of quantum algorithms to significantly improve learning and performance in cognitive agent architectures.However,advantages are task-specific and less pronounced under high-uncertainty,reactive scenarios.Limitations of the simulation environment are acknowledged,and a structured future research roadmap is proposed involving highfidelity simulation validation,hardware-in-the-loop robotic testing,and integration of advanced hybrid quantum-classical architectures.
基金partially supported by the National Natural Science Foundation of China under Grant No.11988101。
文摘In this article,a well-known anisotropic solution,the Tolman-Finch-Skea(TFS)solution,is studied using the gravitational decoupling approach within the framework of 4D Einstein-Gauss-Bonnet(EGB)gravity.The radial metric potential is modified linearly through the minimal geometric deformation approach,while the temporal component of the metric remains unchanged.The system of EGB field equations is decomposed into two distinct sets of field equations:one corresponding to the standard energy-momentum tensor and the other associated with an external gravitational source.The first system is solved using the aforementioned known solution,while the second is closed by imposing the mimic constraint on pressure.Moreover,the junction conditions at the inner and outer surfaces of the stellar object are examined,considering the Boulware-Deser 4D space-time as the external geometry.The physical properties of the stellar model are analyzed using parameters such as energy conditions,causality conditions,compactness,and redshift.
文摘Fontan operation is indicated in a single ventricle congenital heart disease which creates a shunt between superior vena cava and pulmonary arteries leading to increased pressure in central venous system and congestive hepatopathy,namely,Fontan-associated liver disease(FALD)[1].Recently,the long-term prognosis after Fontan operation has been improving and the number of patients diagnosed with hepatocellular carcinoma(HCC)arising from FALD is increasing[1].There are several publications on the safety of laparoscopic,conventional surgery and interventional radiological modalities in FALD-HCC patients[2-5].However,there are no reports regarding the robotic hepatectomy for the FALD-HCC patients.This was the first report showing the safety of robotic anatomical hepatectomy in FALD-HCC patients.
文摘This study presents the results of a Monte Carlo simulation to compare the statistical power of Siegel-Tukey and Savage tests.The main purpose of the study is to evaluate the statistical power of both tests in scenarios involving Normal,Platykurtic and Skewed distributions over different sample sizes and standard deviation values.In the study,standard deviation ratios were set as 2,3,4,1/2,1/3 and 1/4 and power comparisons were made between small and large sample sizes.For equal sample sizes,small sample sizes of 5,8,10,12,16 and 20 and large sample sizes of 25,50,75 and 100 were used.For different sample sizes,the combinations of(4,16),(8,16),(10,20),(16,4),(16,8)and(20,10)small sample sizes and(10,30),(30,10),(50,75),(50,100),(75,50),(75,100),(100,50)and(100,75)large sample sizes were examined in detail.According to the findings,the power analysis under variance heterogeneity conditions shows that the Siegel-Tukey test has a higher statistical power than the other nonparametric Savage test at small and large sample sizes.In particular,the Siegel-Tukey test was reported to offer higher precision and power under variance heterogeneity,regardless of having equal or different sample sizes.
基金supported in part by the Istanbul Technical University Scientific Research Projects Coordination Unit under Grant FHD-2024-45764in part by TUBITAK 1515 Frontier R&D Laboratories Support Program for Turkcell 6GEN LAB under Grant 5229902Turkcell Technology R&D Center(Law no.5746)has partially supported this study。
文摘The increase in user mobility and density in modern cellular networks increases the risk of overloading certain base stations in popular locations such as shopping malls or stadiums,which can result in connection loss for some users.To combat this,the traffic load of base stations should be kept as balanced as possible.In this paper,we propose an efficient load balancing-aware handover algorithm for highly dynamic beyond 5G heterogeneous networks by assigning mobile users to base stations with lighter loads when a handover is performed.The proposed algorithm is evaluated in a scenario with users having different levels of mobility,such as pedestrians and vehicles,and is shown to outperform the conventional handover mechanism,as well as another algorithm from the literature.As a secondary benefit,the overall energy consumption in the network is shown to be reduced with the proposed algorithm.
