scholarly journals A New Framework for Video Data Retrieval using Hierarchical Clustering Technique

2019 ◽  
Vol 8 (6S3) ◽  
pp. 2052-2055 ◽  
Keyword(s):  
Visual Motion ◽  
Experimental Studies ◽  
Data Retrieval ◽  
Video Data ◽  
Second Step ◽  
Huge Amount ◽  
New Techniques ◽  
Amount Of Information ◽  
Frame Work ◽  
New Framework

The amount of information produced every year is rapidly growing due to many factor among all media, video is a particular media embedding visual, motion, audio and textual information. Given this huge amount of information we need general framework for video data mining to be applied to the raw videos (surveillance videos, news reading, Person reading books in library etc.).We introduce new techniques which are essential to process the video files. The first step of our frame work for mining raw video data in grouping input frames to a set of basic units which are relevant to the structure of the video. The second step is charactering the unit to cluster into similar groups, to detect interesting patterns. To do this we extract some features (object, colors etc.)From the unit. A histogram based color descriptors also introduced to reliably capture and represent the color properties of multiple images. The preliminary experimental studies indicate that the proposed framework is promising

Application of Additives in 1,8-Cineole Purification

2013 ◽  
Vol 634-638 ◽  
pp. 382-385
Author(s):  
Ke Guo Liu ◽  
Li Li Gu ◽  
Hui Guang Hu ◽  
Rong Yang ◽  
Jun Tao
Keyword(s):  
Experimental Studies ◽  
Optimal Operation ◽  
Experimental Results ◽  
Second Step ◽  
Reflux Ratio ◽  
Batch Distillation ◽  
Operation Temperature ◽  
Operation Conditions ◽  
Vacuum Degree

The experimental studies for purification of 1,8-cineole by vacuum batch distillation as well as the application of additives in 1,8-cineole purification were carried out. There were two steps during the purification. In the first step, experimental results showed that the optimal operation conditions for purification of 1,8-cineole were the temperature of the reboiler at about 320.15 K under a certain vacuum degree. In the second step, the optimal operation temperature of the reboiler was 331.15 K. The optimal reflux ratio was generated finally. Vacuum degree was controlled between 1.1 kPa and 1.3 kPa.

scholarly journals Revision in Continuous Space: Unsupervised Text Style Transfer without Adversarial Learning

2020 ◽  
Vol 34 (05) ◽  
pp. 8376-8383
Author(s):  
Dayiheng Liu ◽  
Jie Fu ◽  
Yidan Zhang ◽  
Chris Pal ◽  
Jiancheng Lv
Keyword(s):  
Experimental Studies ◽  
Target Sentence ◽  
Sentence Length ◽  
Adversarial Learning ◽  
Style Transfer ◽  
Continuous Space ◽  
Fine Grained ◽  
Gradient Based ◽  
Transfer Tasks ◽  
New Framework

Typical methods for unsupervised text style transfer often rely on two key ingredients: 1) seeking the explicit disentanglement of the content and the attributes, and 2) troublesome adversarial learning. In this paper, we show that neither of these components is indispensable. We propose a new framework that utilizes the gradients to revise the sentence in a continuous space during inference to achieve text style transfer. Our method consists of three key components: a variational auto-encoder (VAE), some attribute predictors (one for each attribute), and a content predictor. The VAE and the two types of predictors enable us to perform gradient-based optimization in the continuous space, which is mapped from sentences in a discrete space, to find the representation of a target sentence with the desired attributes and preserved content. Moreover, the proposed method naturally has the ability to simultaneously manipulate multiple fine-grained attributes, such as sentence length and the presence of specific words, when performing text style transfer tasks. Compared with previous adversarial learning based methods, the proposed method is more interpretable, controllable and easier to train. Extensive experimental studies on three popular text style transfer tasks show that the proposed method significantly outperforms five state-of-the-art methods.

scholarly journals Visual odometry in local underwater navigation problems

2021 ◽  
Vol 2091 (1) ◽  
pp. 012053
Author(s):  
I M Azhmukhamedov ◽  
P I Tamkov ◽  
N D Svishchev ◽  
A V Rybakov
Keyword(s):  
Experimental Studies ◽  
Visual Odometry ◽  
Ecological Monitoring ◽  
Video Stream ◽  
Video Data ◽  
Work Processes ◽  
Underwater Robots ◽  
Advantages And Disadvantages ◽  
Local Navigation ◽  
Slam Algorithm

Abstract The work processes of the ORB-SLAM algorithm are presented. The results of experimental studies on temporal comparisons of the operation of the algorithm with different parameters and cameras are presented. The necessity of forming a visual odometry (VO) system as a local navigation of remote-controlled and autonomous underwater robots has been substantiated. The two most suitable odometry methods in the underwater environment are described, such as their advantages and disadvantages. The work processes of the ORB-SLAM algorithm are presented. The results of experimental studies on temporal comparisons of the operation of the algorithm with different parameters and cameras are presented. The procedure for preparing video data is described: processing a video stream, adjusting camera parameters for calibration. The experiments represent the testing of the ORB-SLAM3 algorithm on a sample of video filmed as part of the ecological monitoring of the Caspian shelf in 2020.

scholarly journals Art-Directed Composition in Dynamic Real Scenes

2021 ◽  
Author(s):  
Lohit Petikam
Keyword(s):  
Real World ◽  
Mixed Reality ◽  
New Techniques ◽  
Visual Elements ◽  
Lighting Conditions ◽  
Real Scene ◽  
Latent Space ◽  
Animated Films ◽  
Visual Style ◽  
New Framework

<p>Art direction is crucial for films and games to maintain a cohesive visual style. This involves carefully controlling visual elements like lighting and colour to unify the director's vision of a story. With today's computer graphics (CG) technology 3D animated films and games have become increasingly photorealistic. Unfortunately, art direction using CG tools remains laborious. Since realistic lighting can go against artistic intentions, art direction is almost impossible to preserve in real-time and interactive applications. New live applications like augmented and mixed reality (AR and MR) now demand automatically art-directed compositing in unpredictably changing real-world lighting. </p> <p>This thesis addresses the problem of dynamically art-directed 3D composition into real scenes. Realism is a basic component of art direction, so we begin by optimising scene geometry capture in realistic composites. We find low perceptual thresholds to retain perceived seamlessness with respect to optimised real-scene fidelity. We then propose new techniques for automatically preserving art-directed appearance and shading for virtual 3D characters. Our methods allow artists to specify their intended appearance for different lighting conditions. Unlike with previous work, artists can direct and animate stylistic edits to automatically adapt to changing real-world environments. We achieve this with a new framework for look development and art direction using a novel latent space of varied lighting conditions. For more dynamic stylised lighting, we also propose a new framework for art-directing stylised shadows using novel parametric shadow editing primitives. This is a first approach that preserves art direction and stylisation under varied lighting in AR/MR.</p>

scholarly journals Content profiling and translation scenarios

2016 ◽  
Vol 3 (1) ◽  
pp. 18-37 ◽  
Author(s):  
Sheila Castilho ◽  
Sharon O'Brien
Keyword(s):  
Strategic Management ◽  
End Users ◽  
Huge Amount ◽  
Amount Of Information ◽  
Different Content

Today’s companies are overwhelmed with the need to create a huge amount of content, faster, customized, and for numerous media platforms, in order to support their products. Struggling with managing this amount of information, companies have now realised that the strategic management of multilingual enterprise content has become essential. Strategic management involves profiling content, its uses, its end readers and deciding what should be translated, into which languages, using which translation processes and technology. Profiling enterprise content is necessary in order to maximize the quality of the content and its translation at minimum effort and cost by reducing complexity. By targeting the audience, content could be categorized according to the expectation of the end-users, and so, different translation scenarios can be applied to different content types. This article will discuss the challenges of profiling content within the enterprise, as well as translation scenarios focusing on the decisions that push content in one or another direction.

Beyond Scientometrics

2019 ◽  
pp. 177-181
Keyword(s):  
Bibliometric Indicators ◽  
Huge Amount ◽  
Scientometric Indicators ◽  
Amount Of Information ◽  
Research Outcomes ◽  
Tools And Techniques ◽  
Alternative Metrics

Numerous websites are currently being used by researchers for sharing and disseminating research, some of which are CiteULike, BibSonomy, Connotea, Mendeley, ResearchGate, etc. For measuring this data, scientists create alternative indicators related to traditional indicators like bibliometric indicators, scientometric indicators. The main purpose of these indicators is that with such huge amount of information available, some specific tools and techniques are required to filter and evaluate the research outcomes. These indicators reveal the societal and unknown impact of the work that traditional metrics are unable to do. The most prominent indicators for this purpose include Altmetrics or article metrics or alternative metrics. The detailed discussion is provided in this chapter.

Tuning Drone Data Delivery and Analysis on the Public Cloud

2021 ◽  
pp. 207-216
Author(s):  
Jose Lo Huang
Keyword(s):  
Web Services ◽  
Video Data ◽  
Data Delivery ◽  
Public Cloud ◽  
American Continent ◽  
Huge Amount ◽  
Single Node ◽  
The Public ◽  
Amazon Web Services ◽  
The Common

Currently, transfering a huge amount of video data from on premise to the public cloud is very slow. In this article, the researcher uses a set of self-developed software written in Python, C, and Bash to improve the speed of data transmission and analysis of drone-generated videos taken in eight different cities on the American continent to the public cloud of Amazon Web Services. The author uses several tools, compression, parallel threads execution, and the autoscaling feature of the public cloud vendor to tune the process of transmission and analysis in 78% of the speed compared to the common sequential transmission and single node option.

scholarly journals An Extensive Research on Knowledge Mining Systems:A Review

2018 ◽  
Vol 7 (3.6) ◽  
pp. 94
Author(s):  
K Kalaiselvi ◽  
J Sowmiya
Keyword(s):  
Higher Education ◽  
Review Paper ◽  
Research Area ◽  
Huge Amount ◽  
Research Knowledge ◽  
Mining System ◽  
Knowledge Mining ◽  
Amount Of Information ◽  
The Subject ◽  
Fertile Area

With the huge amount of information available, the analysis over the data is the fertile area of knowledge mining research. Knowledge mining is the recent hot and promising research area. Knowledge mining is defined as the process of obtaining relevant knowledge from the pool of resources. In this review paper, we surveyed about the prior works carried out in the knowledge mining systems. We explore the primitives of knowledge mining systems. Attribute imbalance is the primary issue prevails in the knowledge mining process. In the field of higher education, most of the attributes are shared among the data features. In addition a precise introduction to knowledge mining along with its process is presented to get acquainted with the vital information on the subject of knowledge mining system  

scholarly journals Quantum Dots—Assisted 2D Fluorescence for Pattern Based Sensing of Amino Acids, Oligopeptides and Neurotransmitters

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3655 ◽  
Author(s):  
Marcin Zabadaj ◽  
Patrycja Ciosek-Skibińska
Keyword(s):  
Amino Acids ◽  
Quantum Dots ◽  
Emission Spectra ◽  
Specific Interactions ◽  
High Quantum Yield ◽  
Huge Amount ◽  
Broad Absorption ◽  
Amount Of Information ◽  
Decay Times ◽  
Proof Of Principle

Quantum dots (QDs) are very attractive nanomaterials for analytical chemistry, due to high photostability, large surface area featuring numerous ways of bioconjugation with biomolecules, usually high quantum yield and long decay times. Their broad absorption spectra and narrow, sharp emission spectra of size-tunable fluorescence make them ideal tools for pattern-based sensing. However, almost always they are applied for specific sensing with zero-dimensional (0D) signal reporting (only peak heights or peak shifts are considered), without taking advantage of greater amount of information hidden in 1D signal (emission spectra), or huge amount of information hidden in 2D fluorescence maps (Excitation-Emission Matrixes, EEMs). Therefore, in this work we propose opposite strategy—non-specific interactions of QDs, which are usually avoided and regarded as their disadvantage, were exploited here for 2D fluorescence fingerprinting. Analyte-specific multivariate fluorescence response of QDs is decoded with the use of Partial Least Squares—Discriminant Analysis. Even though only one type of QDs is studied, the proposed pattern-based method enables to obtain satisfactory accuracy for all studied compounds—various neurotransmitters, amino-acids and oligopeptides. This is a proof of principle of the possibility of the identification of various bioanalytes by such fluorescence fingerprinting with the use of QDs.

Sign in / Sign up

Export Citation Format

Share Document