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human perception of Group Synchronization Error in Remote Learning: Dependencies of Voice and Video Contents in One-Way Communication

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International Journal of Communications, Network and System Sciences 2022年第3期15卷 31-42页

作者： Hay Mar Mo Mo Lwin Yutaka Ishibashi Khin Than Mya Faculty of Computer Systems and Technologies University of Computer Studies Yangon Yangon Myanmar Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan

This paper examines dependencies of voice and video contents on human perception of group (or inter-destination) synchronization error in remote learning by Quality of Experience (QoE) assessment. In our assessment, we use two videos and three voices (two voices for one video and one voice for the other video). We also investigate influences of silence periods in the voices and temporal relations between the voices and videos (called the tightly-coupled and loosely-coupled contents here). The voices are spoken by a teacher according to the videos. Each subject as a student assesses the group synchronization quality by watching each lecture video and the corresponding explanation voice, and then the subject answers whether he/she perceives the group synchronization error or not. As a result, assessment results illustrate that silence periods mitigate the perception rate of the error, and we can also find that we can more easily perceive the error for tightly-coupled contents than loosely-coupled ones.

关键词： Remote Learning Voice Video Group Synchronization Error human perception QoE Assessment

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Bridging the semantic gap with human perception based features for scene categorization

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International Journal of Intelligent Computing and Cybernetics 2017年第3期10卷 387-406页

作者： Padmavati Shrivastava K.K.Bhoyar A.S.Zadgaonkar Dr.C.V.Raman University BilaspurIndia Department of Information Technology Yeshwantrao Chavan College of EngineeringNagpurIndia

Purpose–The purpose of this paper is to build a classification system which mimics the perceptual ability of human vision,in gathering knowledge about the structure,content and the surrounding environment of a real-world natural scene,at a quick glance accurately.This paper proposes a set of novel features to determine the gist of a given scene based on dominant color,dominant direction,openness and roughness features.Design/methodology/approach–The classification system is designed at two different levels.At the first level,a set of low level features are extracted for each semantic feature.At the second level the extracted features are subjected to the process of feature evaluation,based on inter-class and intra-class distances.The most discriminating features are retained and used for training the support vector machine(SVM)classifier for two different data sets.Findings–Accuracy of the proposed system has been evaluated on two data sets:the well-known Oliva-Torralba data set and the customized image data set comprising of high-resolution images of natural landscapes.The experimentation on these two data sets with the proposed novel feature set and SVM classifier has provided 92.68 percent average classification accuracy,using ten-fold cross validation approach.The set of proposed features efficiently represent visual information and are therefore capable of narrowing the semantic gap between low-level image representation and high-level human perception.Originality/value–The method presented in this paper represents a new approach for extracting low-level features of reduced dimensionality that is able to model human perception for the task of scene classification.The methods of mapping primitive features to high-level features are intuitive to the user and are capable of reducing the semantic gap.The proposed feature evaluation technique is general and can be applied across any domain.

关键词： Openness Roughness human perception JND p-value Scene classification Semantic gap Feature elevation Dominant direction

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An interactive approach to investigate brightness perception of daylighting in Immersive Virtual Environments:Comparing subjective responses and quantitative metrics

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Building Simulation 2022年第1期15卷 41-68页

作者： Muhammad Hegazy Kensuke Yasufuku Hirokazu Abe Graduate School of Engineering Osaka UniversityYamadaoka 2-1 Suita Osaka567-0047Japan Cybermedia Center Osaka UniversityJapan

Daylighting plays an eminent role in the performance of indoor environments and their occupants,thus necessitating the need to investigate daylight perception of potential occupants at early design stages.The present study introduces an interactive approach to collect and visualize brightness perception of daylighting in a large-scale immersive virtual environment using a game engine as a daylight simulation tool.The developed system allows users to explore building models freely at different day times set in virtual reality and report their perceptions in real time.Following a validation study(N=36)to investigate the consistency of brightness perceptions in a real environment and its virtual replica,a set of 24 participants were recruited to use the system to report their brightness perception in a virtual model of a daylit art museum,through snapshotting the scenes where they perceive as one of the following in terms of daylighting:(very dark,dark,bright,or very bright).Using an output of 419 snapshots,a"Perceptual Light Map"(PLM)was developed to visualize the collective brightness perception of participants as a heat map.Subjective responses were found to be positively correlated with four daylight metrics,with the highest correlation to mean luminance and the lowest to luminance ratio.The findings of this exploratory study represent a step towards a user-oriented supplement tool to the existing quantitative daylight metrics,validating game engines’adequacy as a daylight simulation tool,and illustrating the potentials of immersion and interaction principles for the perception of daylit spaces in virtual reality.

关键词： immersive virtual environment daylighting game engine human perception mean luminance

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Investigation of indoor air quality in shopping malls during summer in Western China using subjective survey and field measurement

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建筑节能(中英文) 2016年第11期 128-128页

作者： Yuzhen Shang Baizhan Li A.N.Baldwin Yong Ding Wei Yu Li Cheng 侯恩哲《建筑节能》杂志社

Thermal parameters and concentrations of CO2, TVOC and formaldehyde were monitored in shopping malls in four western cities in China during summer. Simultaneously, questionnaire subjective surveys were carried out to investigate the indoor perception of air quality and Sick Building Syndrome(SBS) among staffs in the shopping malls. It was found that stuffy odor had significant correlation with the overall odors perception and staff in the shopping malls had noticeable SBS. Instrument measurement showed that mall C had higher pollution levels of TVOC, while formaldehyde concentrations were higher in mall X and L. Pollution level in the malls is influenced by many factors, and three factors(customer density, ventilation conditions, emission characteristic of merchandise) were discussed in the analysis of data from the four malls. For customer density, the concentrations of CO2 on weekends were higher than on weekdays. Daily CO2 concentration was positively correlated with customer flow rate, but there was no significant strong correlation between customer flow rate and TVOC/formaldehyde concentrations. Underground floors had poorer indoor air quality than over-ground because of lack of fresh air. As for the merchandise sections, the formaldehyde in the home textile section in mall X reached 1.15 mg/m3 with an over standard rate of 83.3% due to the new merchandise added. This paper makes a contribution to knowledge relating to the reasons for discomfort in shopping malls by contributing multiple investigations on contaminants together with information on human perception and the operation of air conditioning systems within the stores.

关键词： Indoor air quality Shopping malls Formaldehyde CO2 TVOC human perception

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