scholarly journals Sample Generation with Self-Attention Generative Adversarial Adaptation Network (SaGAAN) for Hyperspectral Image Classification

2020 ◽  
Vol 12 (5) ◽  
pp. 843 ◽  
Author(s):  
Wenzhi Zhao ◽  
Xi Chen ◽  
Jiage Chen ◽  
Yang Qu
Keyword(s):  
Hyperspectral Image ◽  
Domain Adaptation ◽  
Hyperspectral Data ◽  
Generative Adversarial Networks ◽  
High Quality ◽  
Hyperspectral Image Analysis ◽  
Spectral Bands ◽  
Training Samples ◽  
The Impact

Hyperspectral image analysis plays an important role in agriculture, mineral industry, and for military purposes. However, it is quite challenging when classifying high-dimensional hyperspectral data with few labeled samples. Currently, generative adversarial networks (GANs) have been widely used for sample generation, but it is difficult to acquire high-quality samples with unwanted noises and uncontrolled divergences. To generate high-quality hyperspectral samples, a self-attention generative adversarial adaptation network (SaGAAN) is proposed in this work. It aims to increase the number and quality of training samples to avoid the impact of over-fitting. Compared to the traditional GANs, the proposed method has two contributions: (1) it includes a domain adaptation term to constrain generated samples to be more realistic to the original ones; and (2) it uses the self-attention mechanism to capture the long-range dependencies across the spectral bands and further improve the quality of generated samples. To demonstrate the effectiveness of the proposed SaGAAN, we tested it on two well-known hyperspectral datasets: Pavia University and Indian Pines. The experiment results illustrate that the proposed method can greatly improve the classification accuracy, even with a small number of initial labeled samples.

scholarly journals How Different Fermentation Type Affects Volatile Composition of Plum Jerkums

2021 ◽  
Vol 11 (10) ◽  
pp. 4658
Author(s):  
Magdalena Januszek ◽  
Paweł Satora
Keyword(s):  
Volatile Compounds ◽  
Current Paper ◽  
Higher Alcohols ◽  
High Quality ◽  
Volatile Composition ◽  
Spontaneous Fermentation ◽  
Fermentation Efficiency ◽  
Yeast Strains ◽  
The Impact

Quality of plum jerkum is significantly associated to the profile of volatile compounds. Therefore, we decided to assess the impact of various fermentation types on selected properties of plum jerkums, especially compounds which contribute to the aroma of the finished product. We used the following yeast strains: S. cerevisiae S1, H. uvarum H2, and Ethanol RED (S. cerevisiae). Moreover, we considered spontaneous fermentation. S. cerevisiae and H. uvarum strains were isolated during the fermentation of Čačanska Lepotica or Węgierka Dąbrowicka (plum cultivars), respectively. As for fermentation type, spontaneous fermentation of H. uvarum H2 provided the best results. It could be associated to the fact that plum juices fermented with H. uvarum H2 presented the highest concentration of terpenoids, esters, or some higher alcohols. In the current paper, application of indigenous strains of yeasts resulted in the required oenological characteristics, e.g., highest fermentation efficiency and concentration of ethanol was determined in juices fermented with Ethanol RED (S. cerevisiae) and also with S. cerevisiae S1. Our results suggested that indigenous strains of yeasts present in plums demonstrate great potential for the production of plum jerkums of high quality.

scholarly journals Health-Related Quality of Life of Elderly Women with Fall Experiences

2021 ◽  
Vol 18 (15) ◽  
pp. 7804
Author(s):  
Jiyoung Song ◽  
Eunwon Lee
Keyword(s):  
Quality Of Life ◽  
Elderly Women ◽  
The Elderly ◽  
Basic Data ◽  
Health Related Quality ◽  
High Quality ◽  
Related Quality ◽  
Health Related ◽  
The Impact

This study aimed to describe the health-related quality of life of elderly women with experience in fall treatment as well as to prepare basic data for the development of interventions to improve the quality of life for this group. The study was based on raw data from the 2019 Korea Community Health Survey. Using the SPSS program, the characteristics of the subjects were tested by frequency, percentage, and chi-square test. To establish the impact of fall experience on the health-related quality of life of elderly women, the OR and 95% CI were calculated using multiple logistic regression analysis. Of the 4260 people surveyed, 44.7% of the elderly women said they had a high quality of life, whereas 55.3% of the elderly women said they had a low quality of life. A younger age was associated with a better-rated health-related quality of life. Those who lived in a city and had a high level of education tended to describe a high quality of life. The quality of life was considered high by those who exercised, but low by those who were obese or diabetic. The results of this study can lead to a better understanding of the experiences of elderly women who have experienced falls, and they can be used as basic data for the development of related health programs.

scholarly journals An Adaptive Bitrate Switching Algorithm for Speech Applications in Context of WebRTC

2021 ◽  
Vol 17 (4) ◽  
pp. 1-21
Author(s):  
Mohannad Alahmadi ◽  
Peter Pocta ◽  
Hugh Melvin
Keyword(s):  
Real Time ◽  
Data Exchange ◽  
Quality Of Experience ◽  
End User ◽  
High Quality ◽  
Content Type ◽  
Switching Algorithm ◽  
Wide Range ◽  
The Impact

Web Real-Time Communication (WebRTC) combines a set of standards and technologies to enable high-quality audio, video, and auxiliary data exchange in web browsers and mobile applications. It enables peer-to-peer multimedia sessions over IP networks without the need for additional plugins. The Opus codec, which is deployed as the default audio codec for speech and music streaming in WebRTC, supports a wide range of bitrates. This range of bitrates covers narrowband, wideband, and super-wideband up to fullband bandwidths. Users of IP-based telephony always demand high-quality audio. In addition to users’ expectation, their emotional state, content type, and many other psychological factors; network quality of service; and distortions introduced at the end terminals could determine their quality of experience. To measure the quality experienced by the end user for voice transmission service, the E-model standardized in the ITU-T Rec. G.107 (a narrowband version), ITU-T Rec. G.107.1 (a wideband version), and the most recent ITU-T Rec. G.107.2 extension for the super-wideband E-model can be used. In this work, we present a quality of experience model built on the E-model to measure the impact of coding and packet loss to assess the quality perceived by the end user in WebRTC speech applications. Based on the computed Mean Opinion Score, a real-time adaptive codec parameter switching mechanism is used to switch to the most optimum codec bitrate under the present network conditions. We present the evaluation results to show the effectiveness of the proposed approach when compared with the default codec configuration in WebRTC.

scholarly journals A study of the impact of information disclosure quality on the efficiency of corporate investment—Based on civil engineering listed companies

2020 ◽  
Vol 198 ◽  
pp. 03032
Author(s):  
Liying Zhang
Keyword(s):  
Life Cycle ◽  
Civil Engineering ◽  
Listed Companies ◽  
Investment Efficiency ◽  
Disclosure Quality ◽  
High Quality ◽  
Life Cycle Stages ◽  
Quality Disclosure ◽  
The Impact

Most of the existing studies on the impact of disclosure quality of listed companies on the investment efficiency of enterprises are based on the static level, and the article investigates the evolution of disclosure quality on the investment efficiency of enterprises from the dynamic level by dividing the life cycle of enterprises. Taking the data of Shenzhen civil engineering companies from 2013-2017 as the research sample, it uses multiple regression analysis to empirically test the impact of disclosure quality of listed companies on the investment efficiency of enterprises at different life cycle stages. The results show that when no distinction is made between life cycle stages, high quality disclosure can significantly inhibit the inefficient investment behavior of firms; in the growth and maturity samples, high quality disclosure can significantly inhibit underinvestment and overinvestment; in the recessionary samples, high quality disclosure can significantly inhibit underinvestment and has no significant effect on overinvestment.

scholarly journals Quality Metrics Evaluation of Hyperspectral Images

2014 ◽  
Vol XL-8 ◽  
pp. 1221-1226 ◽  
Author(s):  
A. K. Singh ◽  
H. V. Kumar ◽  
G. R. Kadambi ◽  
J. K. Kishore ◽  
J. Shuttleworth ◽  
...  
Keyword(s):  
Hyperspectral Image ◽  
Signal To Noise Ratio ◽  
Principal Component ◽  
Quality Parameters ◽  
Quality Metrics ◽  
Hyperspectral Data ◽  
Hyperspectral Images ◽  
Error Ratio ◽  
Classified Image

In this paper, the quality metrics evaluation on hyperspectral images has been presented using k-means clustering and segmentation. After classification the assessment of similarity between original image and classified image is achieved by measurements of image quality parameters. Experiments were carried out on four different types of hyperspectral images. Aerial and spaceborne hyperspectral images with different spectral and geometric resolutions were considered for quality metrics evaluation. Principal Component Analysis (PCA) has been applied to reduce the dimensionality of hyperspectral data. PCA was ultimately used for reducing the number of effective variables resulting in reduced complexity in processing. In case of ordinary images a human viewer plays an important role in quality evaluation. Hyperspectral data are generally processed by automatic algorithms and hence cannot be viewed directly by human viewers. Therefore evaluating quality of classified image becomes even more significant. An elaborate comparison is made between k-means clustering and segmentation for all the images by taking Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), Maximum Squared Error, ratio of squared norms called L2RAT and Entropy. First four parameters are calculated by comparing the quality of original hyperspectral image and classified image. Entropy is a measure of uncertainty or randomness which is calculated for classified image. Proposed methodology can be used for assessing the performance of any hyperspectral image classification techniques.

Durability and Permanence in the Quality – Contemporary Parameters, Defining the Papers and Cardboards for Printing Art

2019 ◽  
Vol 3 (2) ◽  
Author(s):  
Denitsa Ivanova-Alexandrova ◽  
◽  
◽  
Keyword(s):  
Chemical Composition ◽  
Quality Parameters ◽  
High Quality ◽  
Graphic Art ◽  
Long Period ◽  
External Influences ◽  
Two Factors ◽  
Composition Properties ◽  
The Impact

The long lifecycle, also known as durability and the permanence / invariability in the quality of papers and cardbords for graphic art, are today the basic requirements, imposed by printed art in terms of high quality parameters. These two factors are a manifestation, depending on different internal chemical-composition properties of the paper consistency and external influences of the ambience. Longevity and permanence are perceived as a function of aging and are actually observed at a later point in time. It is important to clarify that they are terms with different contents where „durability” is perceived as the ability of the paper or cardboard to resist the impact of wear during use, and the „permanence” is the possibility of product to remain chemically and physically stable for a long period of time.

scholarly journals Accreditation of research in the thermo-climatic chamber - various aspects

2018 ◽  
Vol 183 ◽  
pp. 01009
Author(s):  
Artur Gawlik ◽  
Piotr Kucybała ◽  
Danuta Owczarek ◽  
Janusz Pobędza
Keyword(s):  
Quality Management ◽  
Environmental Conditions ◽  
Quality Management System ◽  
New Products ◽  
Heavy Duty ◽  
Climatic Chamber ◽  
High Quality ◽  
University Of Technology ◽  
The Impact

One of the important aspects in the implementation of new products for production in the open field is the assessment of the impact of environmental conditions on their operation. Typically thermo-climatic research is carried out for such project. The laboratory of Techno-climatic Research and Heavy Duty Machines of Cracow University of Technology, equipped with a large-sized thermo-climatic chamber conducts this type of research. Bearing in mind the assurance of high quality of the conducted research, the quality management system (QMS) was developed and implemented. The article describes the requirements, scope and process of obtaining a Polish Centre for Accreditation (PCA) certificate.

scholarly journals The Impact of Virtual Human Voice on Learner Trust

2019 ◽  
Vol 63 (1) ◽  
pp. 2272-2276 ◽  
Author(s):  
Scotty D. Craig ◽  
Erin K. Chiou ◽  
Noah L. Schroeder
Keyword(s):  
Female Voice ◽  
Self Report ◽  
Virtual Human ◽  
Instructional Video ◽  
Text To Speech ◽  
High Quality ◽  
Human Voice ◽  
Synthetic Voices ◽  
The Impact

The current study investigates if a virtual human’s voice can impact the user’s trust in interacting with the virtual human in a learning setting. It was hypothesized that trust is a malleable factor impacted by the quality of the virtual human’s voice. A randomized alternative treatments design with a pretest placed participants in either a low-quality Text-to-Speech (TTS) engine female voice (Microsoft speech engine), a high-quality TTS engine female voice (Neospeech voice engine), or a human voice (native female English speaker) condition. All three treatments were paired with the same female virtual human. Assessments for the study included a self-report pretest on knowledge of meteorology, which occurred before viewing the instructional video, and a measure of system trust. The current study found that voice type impacts a user’s trust ratings, with the human voice resulting in higher ratings compared to the two synthetic voices.

Near Infrared Hyperspectral Image Analysis Using R. Part 5: Animated Visualisation of Hyperspectral Data Using R and ImageJ

NIR news ◽  
2014 ◽  
Vol 25 (7) ◽  
pp. 15-17 ◽  
Author(s):  
Y. Dixit ◽  
R. Cama ◽  
C. Sullivan ◽  
L. Alvarez Jubete ◽  
A. Ktenioudaki
Keyword(s):  
Image Analysis ◽  
Near Infrared ◽  
Hyperspectral Image ◽  
Hyperspectral Data ◽  
Hyperspectral Image Analysis

scholarly journals A Sparse Representation-Based Sample Pseudo-Labeling Method for Hyperspectral Image Classification

2020 ◽  
Vol 12 (4) ◽  
pp. 664 ◽  
Author(s):  
Binge Cui ◽  
Jiandi Cui ◽  
Yan Lu ◽  
Nannan Guo ◽  
Maoguo Gong
Keyword(s):  
Sparse Representation ◽  
Image Classification ◽  
Information Entropy ◽  
Hyperspectral Image ◽  
Hyperspectral Data ◽  
Hyperspectral Images ◽  
Hyperspectral Image Classification ◽  
Training Set ◽  
Training Samples ◽  
Labeling Method

Hyperspectral image classification methods may not achieve good performance when a limited number of training samples are provided. However, labeling sufficient samples of hyperspectral images to achieve adequate training is quite expensive and difficult. In this paper, we propose a novel sample pseudo-labeling method based on sparse representation (SRSPL) for hyperspectral image classification, in which sparse representation is used to select the purest samples to extend the training set. The proposed method consists of the following three steps. First, intrinsic image decomposition is used to obtain the reflectance components of hyperspectral images. Second, hyperspectral pixels are sparsely represented using an overcomplete dictionary composed of all training samples. Finally, information entropy is defined for the vectorized sparse representation, and then the pixels with low information entropy are selected as pseudo-labeled samples to augment the training set. The quality of the generated pseudo-labeled samples is evaluated based on classification accuracy, i.e., overall accuracy, average accuracy, and Kappa coefficient. Experimental results on four real hyperspectral data sets demonstrate excellent classification performance using the new added pseudo-labeled samples, which indicates that the generated samples are of high confidence.

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