OPTIMIZATION OF AIRPORT TAXIING PLANNING DURING CONGESTED HOURS BASED ON IMMUNE CLONAL SELECTION ALGORITHM

In order to ease congestion and ground delays in major hub airports, an aircraft taxiing scheduling optimization model is proposed with schedule time as the object function. In the new model, the idea of a classical job shop-schedule problem is adopted and three types of special aircraft-taxi conflicts are considered in the constraints. To solve such nondeterministic polynomial time-complex problems, the immune clonal selection algorithm（ICSA） is introduced. The simulation results in a congested hour of Beijing Capital International Airport show that, compared with the first-come-first-served（FCFS） strategy, the optimization-planning strategy reduces the total scheduling time by 13.6 min and the taxiing time per aircraft by 45.3 s, which improves the capacity of the runway and the efficiency of airport operations.

A Deep Learning Approach for Crowd Counting in Highly Congested Scene

With the rapid progress of deep convolutional neural networks,several applications of crowd counting have been proposed and explored in the literature.In congested scene monitoring,a variety of crowd density estimating approaches has been developed.The understanding of highly congested scenes for crowd counting during Muslim gatherings of Hajj and Umrah is a challenging task,as a large number of individuals stand nearby and,it is hard for detection techniques to recognize them,as the crowd can vary from low density to high density.To deal with such highly congested scenes,we have proposed the Congested Scene Crowd Counting Network(CSCC-Net)using VGG-16 as a core network with its first ten layers due to its strong and robust transfer learning rate.A hole dilated convolutional neural network is used at the back end to widen the relevant field to extract a large range of information from the image without losing its original resolution.The dilated convolution neural network is mainly chosen to expand the kernel size without changing other parameters.Moreover,several loss functions have been applied to strengthen the evaluation accuracy of the model.Finally,the entire experiments have been evaluated using prominent data sets namely,ShanghaiTech parts A,B,UCF_CC_50,and UCF_QNRF.Our model has achieved remarkable results i.e.,68.0 and 9.0 MAE on ShanghaiTech parts A,B,199.1 MAE on UCF_CC_50,and 99.8 on UCF_QNRF data sets respectively.

The Dilemma of “Backward Countryside” and “Congested City” to Be Tackled

Statistics shed light on a tremendous imbalance inherent inChina’s urbanization process.Secondary and tertiary industriesmake up the lion’s share of GDP with figures of48.9%and39.4%respectively,while the primary industry only accounts for11.7%.By this measure,China can be said to be an industrializedcountry,or at least to have entered the intermediate phase ofindustrialization.In terms of demographic composition,

Science Letters:Model for cascading failures in congested Internet

Cascading failures often occur in congested networks such as the Internet. A cascading failure can be described as a three-phase process： generation, diffusion, and dissipation of the congestion. In this account, we present a function that represents the extent of congestion on a given node. This approach is different from existing fimctions based on betweenness centrality. By introducing the concept of ＇delay time＇, we designate an intergradation between permanent removal and nonremoval. We also construct an evaluation fimction of network efficiency, based on congestion, which measures the damage caused by cascading failures. Finally, we investigate the effects of network structure and size, delay time, processing ability and packet generation speed on congestion propagation. Also, we uncover the relationship between the cascade dynamics and some properties of the network such as structure and size.

Allocation of congestion relief cost based on flow change on the congested facilities

Congestion management in an electricity market is introduced in this paper and a new method of allocating congestion cost to transactions is proposed. The proposed method is a two-step process, in which the total congestion cost is firstly allocated to congested facilities and then to each transaction involved. The cost of relieving a congested facility allocated to each transaction is proportional to the power flow change on the congested facility caused by the transaction. The more the power flow change is on the congested facility caused by the transaction, the deeper the degree of involvement by the transaction. Therefore, cutting down the magnitudes of such transactions contributes to relieving congestion. Test results on a 5-bus system indicate that the proposed method can reflect reasonably the degree of involvement by each transaction in the congestion and provide correct price signals contributing to relieving congestion.

Sensitivity Analysis of Key Input Parameters in Microscopic Simulation of Congested and Uncongested Arterial Signals

This study involved investigating the sensitivity of Measures of Effectiveness （MOEs） to different simulation initialization time （7, 10, and 13 minutes）; observing the trend of variation of MOEs with increasing simulation runs; and identifying the major contributors of variation in MOEs using CORSIM and SimTraffic. The results showed that （1） the MOEs of a simulated intersection approaches were indeed sensitive to initialization times; （2） the variation within MOEs reached a steady state with increased number of simulation runs, while CORSIM required at least 50 simulation runs, SimTraffic required even higher number of runs for congested approaches; （3） lane changing and gap acceptance parameters play a major role as a source of variation of MOEs （delay/vehicle） in CORSIM and SimTraffic respectively.

The characteristics of driver lane-changing behaviour in congested road environments

Lane-changing behaviour is one of the complex|driving behaviours.The lane-changing behaviour of drivers may exacerbate congestion,however driver behavioural characteristics are difficult to accurately acquire and quantify,and thus tend to be simplified or ignored in existing lane-changing models.In this paper,the Bik-means clustering algorithm is used to analyse the urban road congestion state discrimination method.Then,simulated driving tests were conducted for different traffic congestion conditions.Through the force feedback system and infrared camera,the data of driver lane-changing behaviours at different traffic congestion levels are obtained separately,and the definitions of the start and end points of a vehicle changing lanes are determined.Furthermore,statistical analysis and discussion of key feature parameters including driver lane-changing behaviour data and visual data under different levels of traffic congestion were conducted.It is found that the average lane-change intention times in each congestion state are 2 s,4 s,6 s and 7 s,while the turn-signal duration and the number of rear-view mirror observations have similar patterns of change to the data on lane-changing intention duration.Moreover,drivers’pupil diameters become smaller during the lane-changing intention phase,and then relatively enlarge during lane-changing;the range of pupil variation is roughly 3.5 mm to 4 mm.The frequency of observing the vehicle in front of the target lane increased as the level of congestion increased,and the frequency of observation in the driver’s mirrors while changing lanes approximately doubled compared to driving straight ahead,and this ratio increased as the level of congestion increased.

Venous Doppler flow patterns,venous congestion,heart disease and renal dysfunction:A complex liaison

The World Journal of Cardiology published an article written by Kuwahara et al that we take the pleasure to comment on.We focused our attention on venous congestion.In intensive care settings,it is now widely accepted that venous congestion is an important clinical feature worthy of investigation.Evaluating venous Doppler profile abnormalities at multiple sites could suggest adequate treatment and monitor its efficacy.Renal dysfunction could trigger or worsen fluid overload in heart disease,and cardio-renal syndrome is a well-characterized spectrum of disorders describing the complex interactions between heart and kidney diseases.Fluid overload and venous congestion,including renal venous hypertension,are major determinants of acute and chronic renal dysfunction arising in heart disease.Organ congestion from venous hypertension could be involved in the development of organ injury in several clinical situations,such as critical diseases,congestive heart failure,and chronic kidney disease.Ultrasonography and abnormal Doppler flow patterns diagnose clinically significant systemic venous congestion.Cardiologists and nephrologists might use this valuable,noninvasive,bedside diagnostic tool to establish fluid status and guide clinical choices.

Identify Congested Links Based on Enlarged State Space

When paths share a common congested link, they will all suffer from a performance degradation. Boolean tomography exploits these performance-level correlations between different paths to identify the congested links. It is clear that the congestion of a path will be distinctly intensive when it traverses multiple congested links. We adopt an enlarged state space model to mirror different congestion levels and employ a system of integer equations, instead of Boolean equations, to describe relationships between the path states and the link states. We recast the problem of identifying congested links into a constraint optimization problem, including Boolean tomography as a special case. For a logical tree, we propose an up-to-bottom algorithm and prove that it always achieves a solution to the problem. Compared with existing algorithms, the simulation results show that our proposed algorithm achieves a higher detection rate while keeping a low false positive rate.

Ultrasound unveiling:Decoding venous congestion in heart failure for precision management of fluid status

This editorial discusses the manuscript by Di Maria et al,published in the recent issue of the World Journal of Cardiology.We here focus on the still elusive pathophysiological mechanisms underlying cardio-renal syndrome(CRS),despite its high prevalence and the substantial worsening of both kidney function and heart failure.While the measure of right atrial pressure through right cardiac catheterization remains the most accurate albeit invasive and costly procedure,integrating bedside ultrasound into diagnostic protocols may substantially enhance the staging of venous congestion and guide therapeutic decisions.In particular,with the assessment of Doppler patterns across multiple venous districts,the Venous Excess Ultrasound(VExUS)score improves the management of fluid overload and provides insight into the underlying factors contributing to cardio-renal interactions.Integrating specific echocardiographic parameters,particularly those concerning the right heart,may thus improve the VExUS score sensitivity,offering perspective into the nuanced comprehension of cardio-renal dynamics.A multidisciplinary approach that consistently incorporates the use of ultrasound is emerging as a promising advance in the understanding and management of CRS.

Portal vein pulsatility:An important sonographic tool assessment of systemic congestion for critical ill patients

In this editorial we comment on the article by Kuwahara et al,published in the recent issue of the World Journal of Cardiology.In this interesting paper,the authors showed a correlation between portal vein pulsatility ratio,examined by bedside ultrasonography,and prognosis of hospitalized patients with acute heart failure.Systemic congestion is being notoriously underdetected in the acutely ill population with conventional methods like clinical examination,biomarkers,central venous pressure estimation and X-rays.However,congestion should be a key therapeutic target due to its deleterious effects to end organ function and subsequently patient prognosis.Doppler flow assessment of the abdominal veins is gaining popularity worldwide,as a valuable tool in estimating comprehensively congestion and giving a further insight into hemodynamics and patient management.

Real-Time Prediction of Urban Traffic Problems Based on Artificial Intelligence-Enhanced Mobile Ad Hoc Networks(MANETS)

Traffic in today’s cities is a serious problem that increases travel times,negatively affects the environment,and drains financial resources.This study presents an Artificial Intelligence(AI)augmentedMobile Ad Hoc Networks(MANETs)based real-time prediction paradigm for urban traffic challenges.MANETs are wireless networks that are based on mobile devices and may self-organize.The distributed nature of MANETs and the power of AI approaches are leveraged in this framework to provide reliable and timely traffic congestion forecasts.This study suggests a unique Chaotic Spatial Fuzzy Polynomial Neural Network(CSFPNN)technique to assess real-time data acquired from various sources within theMANETs.The framework uses the proposed approach to learn from the data and create predictionmodels to detect possible traffic problems and their severity in real time.Real-time traffic prediction allows for proactive actions like resource allocation,dynamic route advice,and traffic signal optimization to reduce congestion.The framework supports effective decision-making,decreases travel time,lowers fuel use,and enhances overall urban mobility by giving timely information to pedestrians,drivers,and urban planners.Extensive simulations and real-world datasets are used to test the proposed framework’s prediction accuracy,responsiveness,and scalability.Experimental results show that the suggested framework successfully anticipates urban traffic issues in real-time,enables proactive traffic management,and aids in creating smarter,more sustainable cities.

Congestive Heart Failure: Treatment of Symptoms or Causes

This paper is based on the author’s 20+ years of experience treating patients with congestive heart failure (CHF) as a cardiologist. In the 20+ years, 64 patients were treated, including both with reduced and preserved left ventricular function. Most patients had a 4 - 5 days hospitalization in their first admission with one readmission (1.6%) over seven years. This paper will help us understand the physiology and pathophysiology of congestive heart failure, especially how to use beta blockers and diuretics. It will shorten the length of hospitalization and lower the readmission rate and cost of CHF treatment. This paper will help us to open another research direction for CHF.

Sound waves and solutions:Point-of-care ultrasonography for acute kidney injury in cirrhosis

This article delves into the intricate challenges of acute kidney injury(AKI)in cirrhosis,a condition fraught with high morbidity and mortality.The complexities arise from distinguishing between various causes of AKI,particularly hemodynamic AKI,in cirrhotic patients,who experience hemodynamic changes due to portal hypertension.The term"hepatocardiorenal syndrome"is introduced to encapsulate the intricate interplay among the liver,heart,and kidneys.The narrative emphasizes the often-overlooked aspect of cardiac function in AKI assessments in cirrhosis,unveiling the prevalence of cirrhotic cardiomyopathy marked by impaired diastolic function.The conventional empiric approach involving volume expansion and vasopressors for hepatorenal syndrome is critically analyzed,highlighting potential risks and variable patient responses.We advocate for a nuanced algorithm for AKI evaluation in cirrhosis,prominently featuring point-of-care ultrasonography(POCUS).POCUS applications encompass assessing fluid tolerance,detecting venous congestion,and evaluating cardiac function.

Point-of-care ultrasonography spotlight:Could venous excess ultrasound serve as a shared language for internists and intensivists?

Point-of-care ultrasonography(POCUS),particularly venous excess ultrasound(VExUS)is emerging as a valuable bedside tool to gain real-time hemodynamic insights.This modality,derived from hepatic vein,portal vein,and intrarenal vessel Doppler patterns,offers a scoring system for dynamic venous congestion assessment.Such an assessment can be crucial in effective management of patients with heart failure exacerbation.It facilitates diagnosis,quantification of congestion,prognostication,and monitoring the efficacy of decongestive therapy.As such,it can effectively help to manage cardiorenal syndromes in various clinical settings.Extended or eVExUS explores additional veins,potentially broadening its applications.While VExUS demonstrates promising outcomes,challenges persist,particularly in cases involving renal and liver parenchymal disease,arrhythmias,and situations of pressure and volume overload overlap.Proficiency in utilizing spectral Doppler is pivotal for clinicians to effectively employ this tool.Hence,the integration of POCUS,especially advanced applications like VExUS,into routine clinical practice necessitates enhanced training across medical specialties.

Smart Parking Management System “MOTAH”

With a surge in the university’s student and staff population, parking problems and congestion have rapidly intensified. The recent inclusion of women drivers, particularly during official working hours, has exacerbated these challenges. This pressing issue underscores the critical necessity for a structured approach to managing university entries and overseeing parking at the gates. The proposed smart parking management system aims to address these concerns by introducing a design concept that restricts unauthorized access and provides exclusive parking privileges to authorized users. Through image processing, the system identifies available parking spaces, relaying real-time information to users via a mobile application. This comprehensive solution also generates detailed reports (daily, weekly, and monthly), aiding university safety authorities in future gate management decisions.

Investigating the Correlation between Patient Education on Web-Based Portal Functionality and the Reduction in 30-Day Hospital Readmission Rates

Background: The growing use of web-based patient portals offers patients valuable tools for accessing health information, communicating with healthcare providers, and engaging in self-management. However, the influence of educating patients on these portals’ functionality on clinical outcomes, such as all-cause readmission rates, remains underexplored. Objective: This research proposal tested the hypothesis that educating a subset of patients with Chronic Obstructive Pulmonary Disease (COPD) and Congestive Heart Failure (CHF), on how to effectively access and utilize the functionality of web-based patient portals can reduce all-cause readmission rates. Methods: We performed a prospective, quasi-experimental study at Bon Secours St. Mary’s Hospital in Richmond, Virginia, USA;dividing participants into an intervention group, receiving education about accessing and navigating “My Chart”, the Bon Secours Web based portal, and a control group, receiving standard care. We then compared 30-day readmission rates, patient engagement, and self-management behaviors between the groups. Data was analyzed using statistical tests to assess the intervention’s impact. Results: We projected that educated patients will exhibit lower readmission rates, improved engagement, and better self-management. The results of the study showed that there was a significant decrease in 30-day readmissions in the intervention group in comparison with the control group (22.7% and 40.9%, respectively). This reduction of 18. 2% of readmissions evaluated here for a trial of meaningful clinical effect is statistically insignificant (p = 0. 184). The practical significance of the intervention is considered small-to-moderate (Cramer V = 0. 20) suggesting that the observed difference has a potential clinical importance even though the difference was not statistically significant. Conclusion: These results imply that the proposed educational intervention might have a positive impact on readmissions;nonetheless, the patient’s characteristics that make him or her capable of readmission cannot be changed and are assessed by the RoR (Risk of Readmission) score. The potential impact of the intervention may be offset, in part, by these baseline risk factors. The study’s power may be limited by sample size, potentially affecting the detection of significant differences. Future studies with larger, multi-center samples and longer follow-up periods are recommended to confirm these findings.

Congestion Control Algorithms for the Internet-A Secondary Publication

In the last five years,there has been a V-shaped recovery in the number of papers on congestion control algorithms on the Internet.In this paper,congestion problems on the Internet are discussed,such as congestion collapse and bufferbloat from the perspective of the necessity of congestion control algorithms.The typical congestion control algorithms are introduced,and the research areas and methods of congestion control algorithms are described.Recent research trends and future prospects of congestion control algorithms are also presented.

A Study on How Urban Rail Operators Can Secure New Growth Engines for the Future Approach: The Case of Underground Urban Logistics System

Seoul Metro is Seoul’s leading metro company, transporting up to 3 billion people annually. However, future ridership is expected to plummet due to an aging and shrinking population with one of the fastest declining total fertility rates in the world. The COVID-19 pandemic in 2019 accelerated this phenomenon. On the contrary, the e-commerce and home delivery industries have developed significantly since COVID-19. Seoul’s current logistics infrastructure cannot handle it. Under the inflection point of declining passenger transportation demand and increasing urban logistics demand, urban rail operators need new growth engines. Therefore, it is necessary to consider the introduction of an UULS (underground urban logistics system) that transports parcels instead of passengers through urban railways. If the UULS becomes a reality, it can be expected to secure scarce logistics land in cities, protect the environment and prevent traffic congestion by operating eco-friendly mass urban transportation, and acquire new revenue sources for urban rail operators. The UULS’s B/C ratio is 1.32. The sensitivity analysis shows that the ratio is above 1 in most cases where the unit cost of transportation is not significantly reduced.

An Effective Optimization Algorithm for Ant Colony Vehicular Congestion Management

Adaptability and dynamicity are special properties of social insects derived from the decentralized behavior of the insects. Authors have come up with designs for software solution that can regulate traffic congestion in a network transportation environment. The effectiveness of various researches on traffic management has been verified through appropriate metrics. Most of the traffic management systems are centered on using sensors, visual monitoring and neural networks to check for available parking space with the aim of informing drivers beforehand to prevent traffic congestion. There has been limited research on solving ongoing traffic congestion in congestion prone areas like car park with any of the common methods mentioned. This study focus however is on a motor park, as a highly congested area when it comes to traffic. The car park has two entrance gate and three exit gates which is divided into three Isle of parking lot where cars can park. An ant colony optimization algorithm (ACO) was developed as an effective management system for controlling navigation and vehicular traffic congestion problems when cars exit a motor park. The ACO based on the nature and movement of the natural ants, simulates the movement of cars out of the car park through their nearest choice exit. A car park simulation was also used for the mathematical computation of the pheromone. The system was implemented using SIMD because of its dual parallelization ability. The result showed about 95% increase on the number of vehicles that left the motor park in one second. A clear indication that pheromones are large determinants of the shortest route to take as cars followed the closest exit to them. Future researchers may consider monitoring a centralized tally system for cars coming into the park through a censored gate being.