使用RealServer5.0建立影视服务器

引言RealAudio、RealVidio的出现,为网页中使用多媒体信息提供了压缩比很高的多媒体文件格式-RealMedia,使网络中的信息发布方式更灵活、方便、更多姿多彩。

Real-time Rescue Target Detection Based on UAV Imagery for Flood Emergency Response

Timely acquisition of rescue target information is critical for emergency response after a flood disaster.Unmanned Aerial Vehicles(UAVs)equipped with remote sensing capabilities offer distinct advantages,including high-resolution imagery and exceptional mobility,making them well suited for monitoring flood extent and identifying rescue targets during floods.However,there are some challenges in interpreting rescue information in real time from flood images captured by UAVs,such as the complexity of the scenarios of UAV images,the lack of flood rescue target detection datasets and the limited real-time processing capabilities of the airborne on-board platform.Thus,we propose a real-time rescue target detection method for UAVs that is capable of efficiently delineating flood extent and identifying rescue targets(i.e.,pedestrians and vehicles trapped by floods).The proposed method achieves real-time rescue information extraction for UAV platforms by lightweight processing and fusion of flood extent extraction model and target detection model.The flood inundation range is extracted by the proposed method in real time and detects targets such as people and vehicles to be rescued based on this layer.Our experimental results demonstrate that the Intersection over Union(IoU)for flood water extraction reaches an impressive 80%,and the IoU for real-time flood water extraction stands at a commendable 76.4%.The information on flood stricken targets extracted by this method in real time can be used for flood emergency rescue.

Insights and reviews on battery lifetime prediction from research to practice

The rising demand for energy storage solutions,especially in the electric vehicle and renewable energy sectors,highlights the importance of accurately predicting battery health to enhance their longevity and reliability.This article comprehensively examines various methods used to forecast battery health,including physics-based models,empirical models,and equivalent circuit models,among others.It delves into the promise of data-driven prognostics,utilizing both conventional machine learning and cuttingedge deep neural network techniques.The advantages and limitations of hybrid models are thoroughly analyzed,with a focus on the benefits of integrating diverse data sources to improve prognostic precision.Through practical case studies,the article showcases the effectiveness and flexibility of these approaches.It also critically addresses the challenges encountered in applying battery health prognostics in realworld scenarios,such as issues of scalability,complexity,and data anomalies.Despite these challenges,the article underscores the emerging opportunities brought about by recent technological,academic,and research advancements.These include the development of digital twin models for batteries,the use of data-centric AI and standardized benchmarking,the potential integration of blockchain technology for enhanced data security and transparency,and the synergy between edge and cloud computing to boost data analysis and processing.The primary goal of this article is to enrich the understanding of current battery health prognostic techniques and to inspire further research aimed at overcoming existing hurdles and tapping into new opportunities.It concludes with a visionary perspective on future research directions and potential developments in this evolving field,encouraging both researchers and practitioners to explore innovative solutions.

Real eigenvalues determined by recursion of eigenstates

Quantum physics is primarily concerned with real eigenvalues,stemming from the unitarity of time evolutions.With the introduction of PT symmetry,a widely accepted consensus is that,even if the Hamiltonian of the system is not Hermitian,the eigenvalues can still be purely real under specific symmetry.Hence,great enthusiasm has been devoted to exploring the eigenvalue problem of non-Hermitian systems.In this work,from a distinct perspective,we demonstrate that real eigenvalues can also emerge under the appropriate recursive condition of eigenstates.Consequently,our findings provide another path to extract the real energy spectrum of non-Hermitian systems,which guarantees the conservation of probability and stimulates future experimental observations.

A Stochastic Model to Assess the Epidemiological Impact of Vaccine Booster Doses on COVID-19 and Viral Hepatitis B Co-Dynamics with Real Data

A patient co-infected with COVID-19 and viral hepatitis B can be atmore risk of severe complications than the one infected with a single infection.This study develops a comprehensive stochastic model to assess the epidemiological impact of vaccine booster doses on the co-dynamics of viral hepatitis B and COVID-19.The model is fitted to real COVID-19 data from Pakistan.The proposed model incorporates logistic growth and saturated incidence functions.Rigorous analyses using the tools of stochastic calculus,are performed to study appropriate conditions for the existence of unique global solutions,stationary distribution in the sense of ergodicity and disease extinction.The stochastic threshold estimated from the data fitting is given by:R_(0)^(S)=3.0651.Numerical assessments are implemented to illustrate the impact of double-dose vaccination and saturated incidence functions on the dynamics of both diseases.The effects of stochastic white noise intensities are also highlighted.

Numerical Analysis of Perforation during Hydraulic Fracture Initiation Based on Continuous-Discontinuous Element Method

Perforation is a pivotal technique employed to establish main flow channels within the reservoir formation at the outset of hydraulic fracturing operations.Optimizing perforation designs is critical for augmenting the efficacy of hydraulic fracturing and boosting oil or gas production.In this study,we employ a hybrid finite-discrete element method,known as the continuous–discontinuous element method(CDEM),to simulate the initiation of post-perforation hydraulic fractures and to derive enhanced design parameters.The model incorporates the four most prevalent perforation geometries,as delineated in an engineering technical report.Real-world perforations deviate from the ideal cylindrical shape,exhibiting variable cross-sectional profiles that typically manifest as an initial constriction followed by an expansion,a feature consistent across all four perforation types.Our simulations take into account variations in perforation hole geometries,cross-sectional diameters,and perforation lengths.The findings show that perforations generated by the 39g DP3 HMX perforating bullet yield the lowest breakdown pressure,which inversely correlates with increases in sectional diameter and perforation length.Moreover,this study reveals the relationship between breakdown pressure and fracture degree,providing valuable insights for engineers and designers to refine perforation strategies.

The First Five Years of a Phase Theory for Complex Systems and Networks

In this paper,we review the development of a phase theory for systems and networks in its first five years,represented by a trilogy:Matrix phases and their properties;The MIMO LTI system phase response,its physical interpretations,the small phase theorem,and the sectored real lemma;The synchronization of a multi-agent network using phase alignment.Towards the end,we also summarize a list of ongoing research on the phase theory and speculate what will happen in the next five years.

Performance enhancement and active sites identification of Cu-Cd bimetallic oxide derived catalysts for electrochemical CO_(2) reduction

The development of earth-abundant electrocatalysts with high performance for electrochemical CO_(2)reduction(ECR)is of great significance.Cu-based catalysts have been widely investigated for ECR due to their unique ability to generate various carbonaceous products,but directing selectivity toward one certain product and identifying the real active sites during ECR are still full of challenge.Here,after the incorporation of CdO into CuO,the Cu_(0.5)Cd_(0.5)-O catalyst achieves a 10.3-fold enhancement for CO selectivity in comparison with CuO,and a CO faradic efficiency nearly 90%with a current density around20 mA cm^(-2)could maintain at least 60 h.Interestingly,a wide CO/H_(2)ratio(0.07-10)is reached on Cu_(x)Cd_(1-x)-O catalysts by varying the Cu/Cd ratio,demonstrating the potential of syngas production using such catalysts.The results of ex situ XRD,XPS,and in situ Raman reveal that the real active sites of Cu_(0.5)Cd_(0.5)-O catalysts for CO production during ECR reaction are the reconstructed mixed phases of CuCd alloy and CdCO_(3).In situ FTIR and theoretical calculations further implicate the presence of Cd related species promotes the CO desorption and inhibits the H_(2)evolution,thus leading to an enhanced CO generation.

Topographic seismic effects and avalanche hazard:A case study of Mount Siella(L’Aquila,Central Italy)

In mountainous areas,snow avalanches could be triggered by the shaking produced by earthquakes.The forces induced by the earthquake can cause an irregular increase of shear strength load down the slope,for the presence of complex surface and buried morphologies.Topographic irregularities generate maximum effects of waves amplification linked to wavelengths comparable to the horizontal dimension of the topographic feature.For this reason,the selected time-histories represent an appropriate input for the two-dimensional numerical response analyses when a dynamic phenomenon produce the resonant motion of a whole mountain.This represents an important earthquake-induced hazard in snow-covered mountain areas with high probability of seismic events.Some valleys are located in regions with scare ground motion data and investments on infrastructures are not always accompanied by adequate protection against earthquake-induced avalanches.The paper points out a simple deterministic approach for selecting a set of real accelerograms applied to a real case of Siella Mountain(Central Italy)where a large avalanche destroying a tourist facility of Rigopiano resort on 18 January 2017.The selected time histories were used as input for the two-dimensional numerical model of the subsoil to evaluate the topographic seismic amplification in ridge and compare it with the results of other authors.These methods suggest that morphology-related inertial effects should be considered as an overload action on snow layers when controlling multi-hazard studies and spatial planning.

Implementing and evaluating an automatic centroid moment tensor procedure for the Indonesia region and surrounding areas

The purpose of this research was to suggest an applicable procedure for computing the centroid moment tensor(CMT)automatically and in real time from earthquakes that occur in Indonesia and the surrounding areas.Gisola software was used to estimate the CMT solution by selecting the velocity model that best suited the local and regional geological conditions in Indonesia and the surrounding areas.The data used in this study were earthquakes with magnitudes of 5.4 to 8.0.High-quality,real-time broadband seismographic data were provided by the International Federation of Digital Seismograph Networks Web Services(FDSNWS)and the European Integrated Data Archive(EIDA)Federation in Indonesia and the surrounding areas.Furthermore,the inversion process and filter adjustment were carried out on the seismographic data to obtain good CMT solutions.The CMT solutions from Gisola provided good-quality solutions,in which all earthquake data had A-level quality(high quality,with good variant reduction).The Gisola CMT solution was justified with the Global CMT(GCMT)solution by using the Kagan angle value,with an average of approximately 11.2°.This result suggested that the CMT solution generated from Gisola was trustworthy and reliable.The Gisola CMT solution was typically available within approximately 15 minutes after an earthquake occurred.Once it met the quality requirement,it was automatically published on the internet.The catalog of local and regional earthquake records obtained through this technology holds great promise for improving the current understanding of regional seismic activity and ongoing tectonic processes.The accurate and real-time CMT solution generated by implementing the Gisola algorithm consisted of moment tensors and moment magnitudes,which provided invaluable insights into earthquakes occurring in Indonesia and the surrounding areas.

Data-Empowered High-Quality Economic Development: Mechanisms and Pathways

To achieve high-quality economic development,it is imperative to prioritize the real economy and foster new factors for economic growth.Data,as a new factor of production,plays a pivotal role in facilitating the seamless integration between digital technology and the real economy.It possesses inherent attributes and techno-economic characteristics that enable the extraction of value across various processes,including production,transaction,consumption,and regulatory supervision.The integration with digital technology enhances the productivity and efficiency of the real economy by facilitating service sector digitalization,accelerating the growth of the new real economy,and supporting the virtual economy in its role of serving the real economy.At present,unleashing the value of data is hindered by inadequate fundamental systems for the data,a lack of activity in the transaction market,and the underutilization of the data as a factor of production by enterprises in the real economy.Therefore,it is advised that data be fully utilized to develop the real economy through the four-pronged approach of“enhancing support for the high-quality provision of the data,expediting the integration of the data into the real economy,promoting the high-quality development of the real economy,and enhancing public service and governance systems”.

基于Real ESRGAN的视频修复系统研究

图像修复和视频修复是计算机视觉的一项重要任务,其中图像修复又是视频修复的基础。为此,如何有效提升图像质量是实现视频质量提升的关键。传统的图像修复算法主要以样本信息为基础,通过对样本内容的扩撒来实现对破损区域的修复;由于这种方式对于图像样本有一定要求,从而制约传统图像修复技术的发展。为此,以生成新图像内容为基础的神经网络如GAN的出现,为图像修复技术转向深度学习提供方向。该课题主要以Real ESRGAN网络的图像修复技术为基础,通过对音频视频数据的隔离处理以及相同帧数据的优化和标记,构建视频修复处理流程。通过对随机视频样本的测试,并通过对单帧图片质量和视频数据流畅性与协调性的评估,该视频处理方法表现出较好的系统性能。

Elementary Fermions: Strings, Planck Constant, Preons and Hypergluons

Using real fields instead of complex ones, it is suggested here that the fermions are pairs of coupled strings with an internal tension. The interaction between the two coupled strings is due to an exchange mechanism which is proportional to Planck’s constant. This may be the result of two massless bosons (hypergluons) coupled by a preon (prequark) exchange. It also gives a physical explanation to the origin of the Planck constant, and origin of spin.

Origin of Sexy Prime Numbers, Origin of Cousin Prime Numbers, Equations from Supposedly Prime Numbers, Origin of the Mersenne Number, Origin of the Fermat Number

We have found through calculations that the differences between the closest supposed prime numbers other than 2 and 3 defined in the articles are: 2;4: and 6. For those whose difference is equal to 6, we showed their origin then we classified them into two categories according to their classes, we showed in which context two prime numbers which differ from 6 are called sexy and in what context they are said real sexy prime. For those whose difference is equal to 4, we showed their origin then we showed that two prime numbers which differ from 4, that is to say two cousin prime numbers, are successive. We made an observation on the supposed prime numbers then we established two pairs of equations from this observation and deduced the origin of the Mersenne number and that of the Fermat number.

A Comparative Study between Landmark Based and Real Time Ultrasound Guided Sub Arachnoid Block

Background: Sub arachnoid block (SAB) performed by traditional landmark palpation technique can be inaccurate. This problem is exacerbated by altered patient anatomy due to obesity and age-related changes. A pre-procedural ultrasound scan of the lumbar spine has been shown to be of benefit in guiding lumbar epidural insertion in obstetric patients. Information on the use of real-time ultrasound (RUS) guided SAB, to date, been limited. This study compared RUS guided SAB to traditional landmark guided technique in patients undergoing spinal anesthesia for different surgical procedures. Methods: This was a prospective, single center, comparative observational study conducted in the department of anesthesiology at our center. 560 patients who underwent spinal anesthesia either by landmark based technique or real-time ultrasound-guided methods. The primary outcome was the first attempt success rate of dural puncture when employing the two methods. Results: Baseline characteristics were similar in the two study groups. The first attempt success rate of dural puncture in landmark guided group was 64.3% compared to 72.6% in the ultrasound guided group. This difference was not statistically significant. The procedure performance time was significantly shorter with landmark palpation compared to use of real-time ultrasound guided method. Conclusion: Use of RUS-guided technique does not significantly improve the first attempt success rate of SAB dural puncture during spinal anesthesia compared to the traditional landmark-guided technique.

Research on the Impact and Opportunities of the Digital Economy Promoting the Development of Real Economy

The digital economy has infused vitality into the transformation and development of the real economy,urging enterprises to break through core technological barriers,address bottleneck issues,and improve their core competitiveness.It fosters the comprehensive digital transformation of agriculture,manufacturing,and service sectors,improving the dynamism of the real economy and fostering more consumption hotspots.Efforts are underway to enhance industrial supply chains and innovation chains,optimize regional resource allocation,and promote a virtuous cycle within the real economy.Initiatives are being undertaken to standardize the development of digital economic platforms,promote the high-quality development of regional economies,and leverage the advantages of the socialist market economy with Chinese characteristics.

An Effective Prediction Method for Supporting Decision Making in Real Estate Area Selection

Real estate has been a dominant industry in many countries. One problem for real estate companies is determining the most valuable area before starting a new project. Previous studies on this issue mainly focused on market needs and economic prospects, ignoring the impact of natural disasters. We observe that natural disasters are important for real estate area selection because they will introduce considerable losses to real estate enterprises. Following this observation, we first develop a self-defined new indicator named Average Loss Ratio to predict the losses caused by natural disasters in an area. Then, we adopt the existing ARIMA model to predict the Average Loss Ratio of an area. After that, we propose to integrate the TOPSIS model and the Grey Prediction Model to rank the recommendation levels for candidate areas, thereby assisting real estate companies in their decision-making process. We conduct experiments on real datasets to validate our proposal, and the results suggest the effectiveness of the proposed method.

Research on Value Evaluation Method of Investment Project Based on Fuzzy Composite Real Options

Venture capital investments are characterized by high input,high yield,and high risk.Due to the complexity of the market environment,stage-by-stage investment is becoming increasingly important.Traditional evaluation methods like comparison,proportion,maturity,internal rate of return,scenario analysis,decision trees,and net present value cannot fully consider the uncertainty and stage characteristics of the project.The fuzzy real options method addresses this by combining real option theory,fuzzy number theory,and composite option theory to provide a more accurate and objective evaluation of Public-Private Partnership(PPP)projects.It effectively considers the interaction of options and the ambiguity of project parameters,making it a valuable tool for project evaluation in the context of venture capital investment.

Infinite Loop?What Is Behind the Ongoing Turmoil in the Banking Sector?

The war in Ukraine is unfortunately not over,to add insult to injury,Silicon Valley Bank collapses and Credit Suisse acquired by UBS under the Swiss emergency legislation.The merger of Credit Suisse with UBS,Switzerland’s biggest bank,has also raised concerns about the proliferation of more institutions deemed“too big to fail”.Through the study of four financial crises in the past 100 years,this paper believes that behind this potential financial crisis is still the real estate bubble,but the significant problems in the United States are the most worrying.Post-financial crisis recessions are costlier and last longer than normal recessions.When credit booms are superimposed with asset price bubbles,financial crises are highly likely and economic recovery will be slower.In this paper,relative data and regression model are used to analyze the causes of the crisis;further this paper discusses the reasons behind the financial crisis and related conjectures and gives relevant development speculations.

气象观测场在汽车试验场中的应用研究

汽车试验场作为汽车开展道路测试的重要场所,用于验证汽车产品的品质以及可靠性。除了场地道路外,气象条件作为汽车道路测试的重要一环,在《GB/T12534-1990汽车道路试验方法通则》中也有明确要求,如:试验时应是无雨无雾天气,相对湿度小于95%,气温0-40℃,风速不大于3m/s。同时气象条件也作为试验场道路管控的重要依据,实时风速、雨量、能见度等信息为场地管理者发布限速、限行、封场等通知提供必要参考依据,直接影响道路测试安全管控的及时性。因此,文章从气象观测场的建设、气象服务、异常天气道路管控等方面开展气象观测场在汽车试验场中的应用研究。