Since the introduction of the HTTP/3, research has focused on evaluating its influences on the existing adaptive streaming over HTTP (HAS). Among these research, due to irrelevant transport protocols, the cross-protocol unfairness between the HAS over HTTP/3 (HAS/3) and HAS over HTTP/2 (HAS/2) has caught considerable attention. It has been found that the HAS/3 clients tend to request higher bitrates than the HAS/2 clients because the transport QUIC obtains higher bandwidth for its HAS/3 clients than the TCP for its HAS/2 clients. As the problem originates from the transport layer, it is likely that the server-based unfairness solutions can help the clients overcome such a problem. Therefore, in this paper, an experimental study of the se

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

Abstract

Objective / Purpose: Online social relationships through the emergence of Web 2.0 applications have become a new trend for researchers to study the behavior of consumers to shop online, as well as social networking sites are technologies that opened up opportunities for new business models. Therefore, a new trend has emerged, called social trade technology. In order to understand the behavioral intentions of the beneficiaries to adopt the technology of social trade, the current research aims at developing an electronic readiness framework and UTAUT model to understand the beneficiary's adoption of social trade technology.

Design/ methodology/ Approach: To achieve the obje

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

Interval methods for verified integration of initial value problems (IVPs) for ODEs have been used for more than 40 years. For many classes of IVPs, these methods have the ability to compute guaranteed error bounds for the flow of an ODE, where traditional methods provide only approximations to a solution. Overestimation, however, is a potential drawback of verified methods. For some problems, the computed error bounds become overly pessimistic, or integration even breaks down. The dependency problem and the wrapping effect are particular sources of overestimations in interval computations. Berz (see [1]) and his co-workers have developed Taylor model methods, which extend interval arithmetic with symbolic computations. The latter is an ef

This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar

Includes search unemployment concept ... types, graduate unemployment a model introduction to the researcher tackled the problem of unemployment being dangerous to the community, it's also growing in size year after year is a waste of a clear human capabilities, also addressed the importance of the research being a touch on the problem of unemployment and its concept and try to find solutions to them , and then came the goals set by the search researcher identifies unemployment and their causes and consequences and to provide a true picture of the situation of unemployed graduates and disclosure about how they treat their graduates for jobs provide him with a decent life problem. And adopted a researcher on the use of a questionnaire add

الخلاصة

اهتم الفكر السياسي في القرنين الاخيرين بدراسة الطبقات على نحو غير مسبوق, واصبح موضوع التحليل الطبقي المعني بالطبقات من حيث تعريفها, وتحديد موقعها في السلم الاجتماعي, فضلاً عن نوعية العلاقة بين شرائحها وفئاتها المختلفة من حيث الصراع والتناغم, المادة الرئيسة والموضوع الاكثر اهمية في دراسات الفكر السياسي والاجتماعي.ومن بين الطبقات, احتلت الطبقة الوسطى مكا

This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar