{"title":"Maximum Shannon Information Delivered in a Lecture","authors":"L. Alksne, A. Ozols","doi":"10.2478/lpts-2022-0008","DOIUrl":null,"url":null,"abstract":"Abstract The aim of our paper is to evaluate the maximum Shannon (syntactic) information carried through a video lecture. To achieve the aim, we have considered a natural lecture delivered by a lecturer as a signal transmitted over the physical communication channel consisting of a sound sub-channel and light sub-channel. Receivers are eyes and ears of listeners whose physical characteristics are taken into account. The physiological, neurological and cognitive aspects of the problem are neglected in calculations. The method has been developed to calculate the absolute maximum values of Shannon information characteristics of a natural lecture basing on the capacity formula of continuous communication channel and physical considerations taken into account for the first time, to our knowledge. Maximum Shannon information characteristics (entropies of sound and light frames, amounts of total acoustical and optical information, capacities of sound and light sub-channels, total amount of information and total capacity) of a natural lecture perceived by the audience have been calculated. These values are the upper bounds of a video lecture. The obtained results are discussed in the paper. After some modification, the proposed method can be practically applied for the optimization of both natural and video lectures because there is some correlation between syntactic and semantic information characteristics.","PeriodicalId":43603,"journal":{"name":"Latvian Journal of Physics and Technical Sciences","volume":"59 1","pages":"12 - 22"},"PeriodicalIF":0.5000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Latvian Journal of Physics and Technical Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/lpts-2022-0008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHYSICS, APPLIED","Score":null,"Total":0}
引用次数: 1
Abstract
Abstract The aim of our paper is to evaluate the maximum Shannon (syntactic) information carried through a video lecture. To achieve the aim, we have considered a natural lecture delivered by a lecturer as a signal transmitted over the physical communication channel consisting of a sound sub-channel and light sub-channel. Receivers are eyes and ears of listeners whose physical characteristics are taken into account. The physiological, neurological and cognitive aspects of the problem are neglected in calculations. The method has been developed to calculate the absolute maximum values of Shannon information characteristics of a natural lecture basing on the capacity formula of continuous communication channel and physical considerations taken into account for the first time, to our knowledge. Maximum Shannon information characteristics (entropies of sound and light frames, amounts of total acoustical and optical information, capacities of sound and light sub-channels, total amount of information and total capacity) of a natural lecture perceived by the audience have been calculated. These values are the upper bounds of a video lecture. The obtained results are discussed in the paper. After some modification, the proposed method can be practically applied for the optimization of both natural and video lectures because there is some correlation between syntactic and semantic information characteristics.
期刊介绍:
Latvian Journal of Physics and Technical Sciences (Latvijas Fizikas un Tehnisko Zinātņu Žurnāls) publishes experimental and theoretical papers containing results not published previously and review articles. Its scope includes Energy and Power, Energy Engineering, Energy Policy and Economics, Physical Sciences, Physics and Applied Physics in Engineering, Astronomy and Spectroscopy.