scholarly journals Knowledge Integration Networks for Action Recognition

2020 ◽  
Vol 34 (07) ◽  
pp. 12862-12869
Author(s):  
Shiwen Zhang ◽  
Sheng Guo ◽  
Limin Wang ◽  
Weilin Huang ◽  
Matthew Scott
Keyword(s):  
Action Recognition ◽  
Large Scale ◽  
Knowledge Integration ◽  
Scene Recognition ◽  
Teacher Networks ◽  
Medium Level ◽  
Meaningful Context ◽  
Context Knowledge ◽  
High Level ◽  
Context Features

In this work, we propose Knowledge Integration Networks (referred as KINet) for video action recognition. KINet is capable of aggregating meaningful context features which are of great importance to identifying an action, such as human information and scene context. We design a three-branch architecture consisting of a main branch for action recognition, and two auxiliary branches for human parsing and scene recognition which allow the model to encode the knowledge of human and scene for action recognition. We explore two pre-trained models as teacher networks to distill the knowledge of human and scene for training the auxiliary tasks of KINet. Furthermore, we propose a two-level knowledge encoding mechanism which contains a Cross Branch Integration (CBI) module for encoding the auxiliary knowledge into medium-level convolutional features, and an Action Knowledge Graph (AKG) for effectively fusing high-level context information. This results in an end-to-end trainable framework where the three tasks can be trained collaboratively, allowing the model to compute strong context knowledge efficiently. The proposed KINet achieves the state-of-the-art performance on a large-scale action recognition benchmark Kinetics-400, with a top-1 accuracy of 77.8%. We further demonstrate that our KINet has strong capability by transferring the Kinetics-trained model to UCF-101, where it obtains 97.8% top-1 accuracy.

scholarly journals Refugees and Host State Security: An Empirical Investigation of Rohingya Refuge in Bangladesh

2021 ◽  
Author(s):  
Sarwar J. Minar
Keyword(s):  
Large Scale ◽  
Research Question ◽  
Economic Security ◽  
Host Community ◽  
Security Threats ◽  
Security Threat ◽  
Low Level ◽  
Medium Level ◽  
Level I ◽  
High Level

While it is conventionally believed that large scale refugees pose security threats to the host community or state. So, since the massive influx of Rohingyas in Bangladesh in 2017, which resulted a staggering total of 1.6 million Rohingyas refuge in Bangladesh, it was argued that Bangladesh will face severe security threats. This article investigates the security experience of Bangladesh in case of Rohingya influx in a span of three years, August 2017 to August 2020. The research question I intend to address is, has Bangladesh faced security threat due to massive Rohingya influx? If so in what ways? I test four security threat areas, which include, societal security, economic security, internal security, and public security. I have used newspaper reports or newspaper content analysis over past three years along with interview data collected from interviewing local people in cox’s bazar area in the first half of 2019 where the Rohingya camps are located. The identity of the interviewees is kept anonymous as per request. In order to assess if the threats are low level, medium level, or high level, I look into both the frequency of reports and the way they are interpreted. I find that Bangladesh has not experience any serious security threat in the last three years. There are some criminal activities and offenses, but these are only low-level security threat at best. My research presents empirical evidence that challenges conventional assertions that refugees are security threats or challenges in the host states.

Social inequality in the evolution of human societies

2019 ◽  
pp. 98-120
Author(s):  
Georgi Derluguian
Keyword(s):  
Social Inequality ◽  
Large Scale ◽  
Human Beings ◽  
Mass Violence ◽  
Public And Private ◽  
Tangible Assets ◽  
Transition To Agriculture ◽  
New Institutions ◽  
High Level ◽  
Political Economic

The author develops ideas about the origin of social inequality during the evolution of human societies and reflects on the possibilities of its overcoming. What makes human beings different from other primates is a high level of egalitarianism and altruism, which contributed to more successful adaptability of human collectives at early stages of the development of society. The transition to agriculture, coupled with substantially increasing population density, was marked by the emergence and institutionalisation of social inequality based on the inequality of tangible assets and symbolic wealth. Then, new institutions of warfare came into existence, and they were aimed at conquering and enslaving the neighbours engaged in productive labour. While exercising control over nature, people also established and strengthened their power over other people. Chiefdom as a new type of polity came into being. Elementary forms of power (political, economic and ideological) served as a basis for the formation of early states. The societies in those states were characterised by social inequality and cruelties, including slavery, mass violence and numerous victims. Nowadays, the old elementary forms of power that are inherent in personalistic chiefdom are still functioning along with modern institutions of public and private bureaucracy. This constitutes the key contradiction of our time, which is the juxtaposition of individual despotic power and public infrastructural one. However, society is evolving towards an ever more efficient combination of social initiatives with the sustainability and viability of large-scale organisations.

scholarly journals NPU RGB+D Dataset and a Feature-Enhanced LSTM-DGCN Method for Action Recognition of Basketball Players

2021 ◽  
Vol 11 (10) ◽  
pp. 4426
Author(s):  
Chunyan Ma ◽  
Ji Fan ◽  
Jinghao Yao ◽  
Tao Zhang
Keyword(s):  
Action Recognition ◽  
Large Scale ◽  
Short Term Memory ◽  
Evaluation Criteria ◽  
Image Data ◽  
Basketball Player ◽  
Basketball Players ◽  
Convolutional Network ◽  
Atomic Actions ◽  
New Feature

Computer vision-based action recognition of basketball players in basketball training and competition has gradually become a research hotspot. However, owing to the complex technical action, diverse background, and limb occlusion, it remains a challenging task without effective solutions or public dataset benchmarks. In this study, we defined 32 kinds of atomic actions covering most of the complex actions for basketball players and built the dataset NPU RGB+D (a large scale dataset of basketball action recognition with RGB image data and Depth data captured in Northwestern Polytechnical University) for 12 kinds of actions of 10 professional basketball players with 2169 RGB+D videos and 75 thousand frames, including RGB frame sequences, depth maps, and skeleton coordinates. Through extracting the spatial features of the distances and angles between the joint points of basketball players, we created a new feature-enhanced skeleton-based method called LSTM-DGCN for basketball player action recognition based on the deep graph convolutional network (DGCN) and long short-term memory (LSTM) methods. Many advanced action recognition methods were evaluated on our dataset and compared with our proposed method. The experimental results show that the NPU RGB+D dataset is very competitive with the current action recognition algorithms and that our LSTM-DGCN outperforms the state-of-the-art action recognition methods in various evaluation criteria on our dataset. Our action classifications and this NPU RGB+D dataset are valuable for basketball player action recognition techniques. The feature-enhanced LSTM-DGCN has a more accurate action recognition effect, which improves the motion expression ability of the skeleton data.

scholarly journals Arabidopsis Genes Essential for Seedling Viability: Isolation of Insertional Mutants and Molecular Cloning

Genetics ◽  
2001 ◽  
Vol 159 (4) ◽  
pp. 1765-1778
Author(s):  
Gregory J Budziszewski ◽  
Sharon Potter Lewis ◽  
Lyn Wegrich Glover ◽  
Jennifer Reineke ◽  
Gary Jones ◽  
...  
Keyword(s):  
Large Scale ◽  
Protein Translocation ◽  
Gene Families ◽  
Mutant Phenotype ◽  
Lethal Mutant ◽  
A Genome ◽  
Genes Encoding ◽  
High Level ◽  
Mutant Lines ◽  
Genome Scale

Abstract We have undertaken a large-scale genetic screen to identify genes with a seedling-lethal mutant phenotype. From screening ~38,000 insertional mutant lines, we identified >500 seedling-lethal mutants, completed cosegregation analysis of the insertion and the lethal phenotype for >200 mutants, molecularly characterized 54 mutants, and provided a detailed description for 22 of them. Most of the seedling-lethal mutants seem to affect chloroplast function because they display altered pigmentation and affect genes encoding proteins predicted to have chloroplast localization. Although a high level of functional redundancy in Arabidopsis might be expected because 65% of genes are members of gene families, we found that 41% of the essential genes found in this study are members of Arabidopsis gene families. In addition, we isolated several interesting classes of mutants and genes. We found three mutants in the recently discovered nonmevalonate isoprenoid biosynthetic pathway and mutants disrupting genes similar to Tic40 and tatC, which are likely to be involved in chloroplast protein translocation. Finally, we directly compared T-DNA and Ac/Ds transposon mutagenesis methods in Arabidopsis on a genome scale. In each population, we found only about one-third of the insertion mutations cosegregated with a mutant phenotype.

scholarly journals Natural Language Description of Videos for Smart Surveillance

2021 ◽  
Vol 11 (9) ◽  
pp. 3730
Author(s):  
Aniqa Dilawari ◽  
Muhammad Usman Ghani Khan ◽  
Yasser D. Al-Otaibi ◽  
Zahoor-ur Rehman ◽  
Atta-ur Rahman ◽  
...  
Keyword(s):  
Natural Language ◽  
Feature Recognition ◽  
Scene Recognition ◽  
Video Data ◽  
Surveillance Video ◽  
Video Footage ◽  
Parallel Pipeline ◽  
September 11 Attacks ◽  
Description Framework ◽  
High Level

After the September 11 attacks, security and surveillance measures have changed across the globe. Now, surveillance cameras are installed almost everywhere to monitor video footage. Though quite handy, these cameras produce videos in a massive size and volume. The major challenge faced by security agencies is the effort of analyzing the surveillance video data collected and generated daily. Problems related to these videos are twofold: (1) understanding the contents of video streams, and (2) conversion of the video contents to condensed formats, such as textual interpretations and summaries, to save storage space. In this paper, we have proposed a video description framework on a surveillance dataset. This framework is based on the multitask learning of high-level features (HLFs) using a convolutional neural network (CNN) and natural language generation (NLG) through bidirectional recurrent networks. For each specific task, a parallel pipeline is derived from the base visual geometry group (VGG)-16 model. Tasks include scene recognition, action recognition, object recognition and human face specific feature recognition. Experimental results on the TRECViD, UET Video Surveillance (UETVS) and AGRIINTRUSION datasets depict that the model outperforms state-of-the-art methods by a METEOR (Metric for Evaluation of Translation with Explicit ORdering) score of 33.9%, 34.3%, and 31.2%, respectively. Our results show that our framework has distinct advantages over traditional rule-based models for the recognition and generation of natural language descriptions.

Urban network of China from the perspective of population mobility: Three-dimensional co-occurrence of nodes and links

2021 ◽  
pp. 0308518X2199781
Author(s):  
Xinyue Luo ◽  
Mingxing Chen
Keyword(s):  
Three Dimensional ◽  
Geographical Distance ◽  
Two Dimensional ◽  
Population Mobility ◽  
Urban Network ◽  
Urban Networks ◽  
Low Level ◽  
Medium Level ◽  
High Level ◽  
External Connections

The nodes and links in urban networks are usually presented in a two-dimensional(2D) view. The co-occurrence of nodes and links can also be realized from a three-dimensional(3D) perspective to make the characteristics of urban network more intuitively revealed. Our result shows that the external connections of high-level cities are mainly affected by the level of cities(nodes) and less affected by geographical distance, while medium-level cities are affected by the interaction of the level of cities(nodes) and geographical distance. The external connections of low-level cities are greatly restricted by geographical distance.

New Harvesting and Curing Techniques in the Production of Breeder's Seed Peanuts1

1979 ◽  
Vol 6 (2) ◽  
pp. 70-72
Author(s):  
T. A. Coffelt ◽  
F. S. Wright ◽  
J. L. Steele
Keyword(s):  
Large Scale ◽  
Combine Method ◽  
Frost Damage ◽  
New Method ◽  
Experimental Equipment ◽  
Harvesting Method ◽  
Curing Methods ◽  
Labor Requirements ◽  
High Level ◽  
Varietal Purity

Abstract A new method of harvesting and curing breeder's seed peanuts in Virginia was initiated that would 1) reduce the labor requirements, 2) maintain a high level of germination, 3) maintain varietal purity at 100%, and 4) reduce the risk of frost damage. Three possible harvesting and curing methods were studied. The traditional stack-pole method satisfied the latter 3 objectives, but not the first. The windrow-combine method satisfied the first 2 objectives, but not the last 2. The direct harvesting method satisfied all four objectives. The experimental equipment and curing procedures for direct harvesting had been developed but not tested on a large scale for seed harvesting. This method has been used in Virginia to produce breeder's seed of 3 peanut varieties (Florigiant, VA 72R and VA 61R) during five years. Compared to the stackpole method, labor requirements have been reduced, satisfactory levels of germination and varietal purity have been obtained, and the risk of frost damage has been minimized.

Results from a Large-Scale Epidemiologic Look-Back Investigation of Improperly Reprocessed Endoscopy Equipment

2012 ◽  
Vol 33 (07) ◽  
pp. 649-656 ◽  
Author(s):  
Mark Holodniy ◽  
Gina Oda ◽  
Patricia L. Schirmer ◽  
Cynthia A. Lucero ◽  
Yury E. Khudyakov ◽  
...  
Keyword(s):  
Genetic Testing ◽  
Large Scale ◽  
Bloodborne Pathogens ◽  
Medical Centers ◽  
B Virus ◽  
Immunodeficiency Virus ◽  
Viral Testing ◽  
Veterans Affairs Medical Centers ◽  
High Level ◽  
Nose And Throat

Objective.To determine whether improper high-level disinfection practices during endoscopy procedures resulted in bloodborne viral infection transmission.Design.Retrospective cohort study.Setting.Four Veterans Affairs medical centers (VAMCs).Patients.Veterans who underwent colonoscopy and laryngoscopy (ear, nose, and throat [ENT]) procedures from 2003 to 2009.Methods.Patients were identified through electronic health record searches and serotested for human immunodeficiency virus (HIV), hepatitis C virus (HCV), and hepatitis B virus (HBV). Newly discovered case patients were linked to a potential source with known identical infection, whose procedure occurred no more than 1 day prior to the case patient's procedure. Viral genetic testing was performed for case/proximate pairs to determine relatedness.Results.Of 10,737 veterans who underwent endoscopy at 4 VAMCs, 9,879 patients agreed to viral testing. Of these, 90 patients were newly diagnosed with 1 or more viral bloodborne pathogens (BBPs). There were no case/proximate pairings found for patients with either HIV or HBV; 24 HCV case/proximate pairings were found, of which 7 case patients and 8 proximate patients had sufficient viral load for further genetic testing. Only 2 of these cases, both of whom underwent laryngoscopy, and their 4 proximates agreed to further testing. None of the 4 remaining proximate patients who underwent colonoscopy agreed to further testing. Mean genetic distance between the 2 case patients and 4 proximate patients ranged from 13.5% to 19.1%.Conclusions.Our investigation revealed that exposure to improperly reprocessed ENT endoscopes did not result in viral transmission in those patients who had viral genetic analysis performed. Any potential transmission of BBPs from colonoscopy remains unknown.

scholarly journals Revealing the constituents of Egypt’s oldest beer using infrared and mass spectrometry

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Mohamed A. Farag ◽  
Moamen M. Elmassry ◽  
Masahiro Baba ◽  
Renée Friedman
Keyword(s):  
Large Scale ◽  
Beer Brewing ◽  
Chemical Signatures ◽  
Chemical Determination ◽  
Materials Used ◽  
High Level ◽  
Beer Production ◽  
First Time ◽  
Detailed Chemical

Abstract Previous studies have shown that the Ancient Egyptians used malted wheat and barley as the main ingredients in beer brewing, but the chemical determination of the exact recipe is still lacking. To investigate the constituents of ancient beer, we conducted a detailed IR and GC-MS based metabolite analyses targeting volatile and non-volatile metabolites on the residues recovered from the interior of vats in what is currently the world’s oldest (c. 3600 BCE) installation for large-scale beer production located at the major pre-pharaonic political center at Hierakonpolis, Egypt. In addition to distinguishing the chemical signatures of various flavoring agents, such as dates, a significant result of our analysis is the finding, for the first time, of phosphoric acid in high level probably used as a preservative much like in modern beverages. This suggests that the early brewers had acquired the knowledge needed to efficiently produce and preserve large quantities of beer. This study provides the most detailed chemical profile of an ancient beer using modern spectrometric techniques and providing evidence for the likely starting materials used in beer brewing.

scholarly journals Equity Effects of Congestion Charges: An Exploratory Analysis with MATSim

2017 ◽  
Vol 2670 (1) ◽  
pp. 75-82 ◽  
Author(s):  
Lucas Meyer de Freitas ◽  
Oliver Schuemperlin ◽  
Milos Balac ◽  
Francesco Ciari
Keyword(s):  
Travel Time ◽  
Large Scale ◽  
Agent Based ◽  
Promising Tool ◽  
Travel Time Savings ◽  
Time Savings ◽  
Time Changes ◽  
High Level ◽  
Congestion Charging ◽  
Equity Effects

This paper shows an application of the multiagent, activity-based transport simulation MATSim to evaluate equity effects of a congestion charging scheme. A cordon pricing scheme was set up for a scenario of the city of Zurich, Switzerland, to conduct such an analysis. Equity is one of the most important barriers toward the implementation of a congestion charging system. After the challenges posed by equity evaluations are examined, it is shown that agent-based simulations with heterogeneous values of time allow for an increased level of detail in such evaluations. Such detail is achieved through a high level of disaggregation and with a 24-h simulation period. An important difference from traditional large-scale models is the low degree of correlation between travel time savings and welfare change. While traditional equity analysis is based on travel time savings, MATSim shows that choice dimensions not included in traditional models, such as departure time changes, can also play an important role in equity effects. The analysis of the results in light of evidence from the literature shows that agent-based models are a promising tool to conduct more complete equity evaluations not only of congestion charges but also of transport policies in general.

Sign in / Sign up

Export Citation Format

Share Document