Int. J. Semantic Comput.最新文献_第3页

A Hybrid NDN-IP Architecture for Live Video Streaming: From Host-Based to Content-Based Delivery to Improve QoE 用于实时视频流的混合NDN-IP架构:从基于主机到基于内容的交付以提高QoE

Int. J. Semantic Comput. Pub Date : 2022-05-18 DOI: 10.1142/s1793351x22400074

Ishita Dasgupta, Susmit Shannigrahi, M. Zink

{"title":"A Hybrid NDN-IP Architecture for Live Video Streaming: From Host-Based to Content-Based Delivery to Improve QoE","authors":"Ishita Dasgupta, Susmit Shannigrahi, M. Zink","doi":"10.1142/s1793351x22400074","DOIUrl":"https://doi.org/10.1142/s1793351x22400074","url":null,"abstract":"With live video streaming becoming accessible in various applications on all client platforms, it is imperative to create a seamless and efficient distribution system that is flexible enough to choose from multiple Internet architectures best suited for video streaming (live, on-demand, AR). In this paper, we highlight the benefits of such a hybrid system for live video streaming as well as present a detailed analysis with the goal to provide a high quality of experience (QoE) for the viewer. For our hybrid architecture, video streaming is supported simultaneously over TCP/IP and Named Data Networking (NDN)-based architecture via operating system and networking virtualization techniques to design a flexible system that utilizes the benefits of these varying Internet architectures. Also, to relieve users from the burden of installing a new protocol stack (in the case of NDN) on their devices, we developed a lightweight solution in the form of a container that includes the network stack as well as the streaming application. At the client, the required Internet architecture (TCP/IP versus NDN) can be selected in a transparent and adaptive manner. Based on a prototype, we have designed and implemented maintaining efficient use of network resources, we demonstrate that in the case of live streaming, NDN achieves better QoE per client than IP and can also utilize higher than allocated bandwidth through in-network caching. Even without caching, as opposed to IP-only, our hybrid setup achieves better average bitrate and better perceived visual quality (computed via VMAF metric) over live video streaming services. Furthermore, we present detailed analysis on ways adaptive video streaming with NDN can be further improved with respect to QoE.","PeriodicalId":217956,"journal":{"name":"Int. J. Semantic Comput.","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121679212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

HSP Datasets: Insights on Song Popularity Prediction HSP数据集:歌曲流行度预测的见解

Int. J. Semantic Comput. Pub Date : 2022-05-12 DOI: 10.1142/s1793351x22400104

M. Vötter, Maximilian Mayerl, Günther Specht, Eva Zangerle

{"title":"HSP Datasets: Insights on Song Popularity Prediction","authors":"M. Vötter, Maximilian Mayerl, Günther Specht, Eva Zangerle","doi":"10.1142/s1793351x22400104","DOIUrl":"https://doi.org/10.1142/s1793351x22400104","url":null,"abstract":"Estimating the success of a song before its release is an important music industry task. This work uses audio descriptors to predict the success (popularity) of a song, where typical measures of success are chart measures such as peak position and streaming measures such as listener-count. Currently, a wide range of datasets is used for that purpose, but most of them are not publicly available; likewise, available datasets are restricted either in size, available features, or popularity measures. This substantially impedes the evaluation of the predictive power of a wide range of models. Therefore, we present two novel datasets called HSP-S and HSP-L based on data from AcousticBrainz, Billboard Hot 100, the Million Song Dataset, and last.fm. Both datasets contain audio features, mel-spectrograms as well as streaming listener- and play-counts. The larger HSP-L dataset contains 73,482 songs, whereas the smaller HSP-S dataset contains 7736 songs and additionally features Billboard Hot 100 chart measures. In contrast to the previous publicly available datasets, our datasets contain substantially more songs and richer and more diverse features. We solely utilize data from the public domain, allowing us to evaluate and compare a wide range of models on our datasets. To demonstrate the use of the datasets, we perform regression and classification (popular/unpopular) tasks on both datasets using a wide variety of models to predict song popularity for all provided target measures of success.","PeriodicalId":217956,"journal":{"name":"Int. J. Semantic Comput.","volume":" 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120834258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

ItemSB: Itemsets with Statistically Distinctive Backgrounds Discovered by Evolutionary Method ItemSB:采用进化方法发现具有统计差异背景的项目集

Int. J. Semantic Comput. Pub Date : 2022-05-08 DOI: 10.1142/s1793351x22420028

Kaoru Shimada, T. Arahira, Shogo Matsuno

引用次数: 0

Flexible-Joint Manipulator Trajectory Tracking with Two-Stage Learned Model Utilizing a Hardwired Forward Dynamics Prediction 基于硬连线前向动力学预测的两阶段学习模型柔性关节机械臂轨迹跟踪

Int. J. Semantic Comput. Pub Date : 2022-05-08 DOI: 10.1142/s1793351x22430036

D. Pavlichenko, Sven Behnke

引用次数: 0

A Non-parametric Bayesian Learning Model Using Accelerated Variational Inference on Multivariate Beta Mixture Models for Medical Applications 基于加速变分推理的非参数贝叶斯学习模型在医学上的应用

Int. J. Semantic Comput. Pub Date : 2022-05-08 DOI: 10.1142/s1793351x22500039

Narges Manouchehri, N. Bouguila

引用次数: 2

A Generalized Search Construct for Imperative Languages to Facilitate Declarative Programming 命令式语言促进声明式编程的通用搜索结构

Int. J. Semantic Comput. Pub Date : 2022-05-08 DOI: 10.1142/s1793351x2242003x

James Smith, Chris Henderson, A. Bansal

引用次数: 0

Integrating Scene Image and Conversational Text to Develop Human-Machine Dialogue 结合场景图像与对话文本发展人机对话

Int. J. Semantic Comput. Pub Date : 2022-05-08 DOI: 10.1142/s1793351x22430012

Hao-Yi Wang, Jhih-Yuan Huang, Wei-Po Lee

引用次数: 1

Guest Editors' Introduction 特邀编辑介绍

Int. J. Semantic Comput. Pub Date : 2022-04-20 DOI: 10.1142/s1793351x22020019

G. Glesener, Julienne A. Greer

引用次数: 0

AccTEF: A Transparency and Accountability Evaluation Framework for Ontology-Based Systems AccTEF:基于本体系统的透明度和问责性评估框架

Int. J. Semantic Comput. Pub Date : 2022-04-09 DOI: 10.1142/s1793351x22400013

M. Basereh, A. Caputo, R. Brennan

{"title":"AccTEF: A Transparency and Accountability Evaluation Framework for Ontology-Based Systems","authors":"M. Basereh, A. Caputo, R. Brennan","doi":"10.1142/s1793351x22400013","DOIUrl":"https://doi.org/10.1142/s1793351x22400013","url":null,"abstract":"This paper proposes a new accountability and transparency evaluation framework (AccTEF) for ontology-based systems (OSysts). AccTEF is based on an analysis of the relation between a set of widely accepted data governance principles, i.e. findable, accessible, interoperable, reusable (FAIR) and accountability and transparency concepts. The evaluation of accountability and transparency of input ontologies and vocabularies of OSysts are addressed by analyzing the relation between vocabulary and ontology quality evaluation metrics, FAIR and accountability and transparency concepts. An ontology-based knowledge extraction pipeline is used as a use case in this study. Discovering the relation between FAIR and accountability and transparency helps in identifying and mitigating risks associated with deploying OSysts. This also allows providing design guidelines that help accountability and transparency to be embedded in OSysts. We found that FAIR can be used as a transparency indicator. We also found that the studied vocabulary and ontology quality evaluation metrics do not cover FAIR, accountability and transparency. Accordingly, we suggest these concepts should be considered as vocabulary and ontology quality evaluation aspects. To the best of our knowledge, it is the first time that the relation between FAIR and accountability and transparency concepts has been found and used for evaluation.","PeriodicalId":217956,"journal":{"name":"Int. J. Semantic Comput.","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127170865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Cultural Algorithms as a Framework for the Design of Trustable Evolutionary Algorithms 作为可信赖进化算法设计框架的文化算法

Int. J. Semantic Comput. Pub Date : 2022-04-08 DOI: 10.1142/s1793351x22400062

Anas Al-Tirawi, R. Reynolds

{"title":"Cultural Algorithms as a Framework for the Design of Trustable Evolutionary Algorithms","authors":"Anas Al-Tirawi, R. Reynolds","doi":"10.1142/s1793351x22400062","DOIUrl":"https://doi.org/10.1142/s1793351x22400062","url":null,"abstract":"One of the major challenges facing Artificial Intelligence in the future is the design of trustworthy algorithms. The development of trustworthy algorithms will be a key challenge in Artificial Intelligence for years to come. Cultural Algorithms (CAs) are viewed as one framework that can be employed to produce a trustable evolutionary algorithm. They contain features to support both sustainable and explainable computation that satisfy requirements for trustworthy algorithms proposed by Cox [Nine experts on the single biggest obstacle facing AI and algorithms in the next five years, Emerging Tech Brew, January 22, 2021]. Here, two different configurations of CAs are described and compared in terms of their ability to support sustainable solutions over the complete range of dynamic environments, from static to linear to nonlinear and finally chaotic. The Wisdom of the Crowds method was selected for the one configuration since it has been observed to work in both simple and complex environments and requires little long-term memory. The Common Value Auction (CVA) configuration was selected to represent those mechanisms that were more data centric and required more long-term memory content. Both approaches were found to provide sustainable performance across all the dynamic environments tested from static to chaotic. Based upon the information collected in the Belief Space, they produced this behavior in different ways. First, the topologies that they employed differed in terms of the “in degree” for different complexities. The CVA approach tended to favor reduced “indegree/outdegree”, while the WM exhibited a higher indegree/outdegree in the best topology for a given environment. These differences reflected the fact the CVA had more information available for the agents about the network in the Belief Space, whereas the agents in the WM had access to less available knowledge. It therefore needed to spread the knowledge that it currently had more widely throughout the population.","PeriodicalId":217956,"journal":{"name":"Int. J. Semantic Comput.","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115252078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0