scholarly journals Connecting the Digital and Physical World: Improving the Robustness of Adversarial Attacks

2019 ◽  
Vol 33 ◽  
pp. 962-969 ◽  
Author(s):  
Steve T.K. Jan ◽  
Joseph Messou ◽  
Yen-Chen Lin ◽  
Jia-Bin Huang ◽  
Gang Wang
Keyword(s):  
Large Scale ◽  
Physical World ◽  
Transformation Process ◽  
Physical Domain ◽  
Learning Models ◽  
Image Translation ◽  
Physical Transformation ◽  
Adversarial Examples ◽  
Core Idea ◽  
High Level

While deep learning models have achieved unprecedented success in various domains, there is also a growing concern of adversarial attacks against related applications. Recent results show that by adding a small amount of perturbations to an image (imperceptible to humans), the resulting adversarial examples can force a classifier to make targeted mistakes. So far, most existing works focus on crafting adversarial examples in the digital domain, while limited efforts have been devoted to understanding the physical domain attacks. In this work, we explore the feasibility of generating robust adversarial examples that remain effective in the physical domain. Our core idea is to use an image-to-image translation network to simulate the digital-to-physical transformation process for generating robust adversarial examples. To validate our method, we conduct a large-scale physical-domain experiment, which involves manually taking more than 3000 physical domain photos. The results show that our method outperforms existing ones by a large margin and demonstrates a high level of robustness and transferability.

scholarly journals Accurate Prediction of Earthquake-Induced Landslides Based on Deep Learning Considering Landslide Source Area

2021 ◽  
Vol 13 (17) ◽  
pp. 3436
Author(s):  
Yao Li ◽  
Peng Cui ◽  
Chengming Ye ◽  
José Marcato Junior ◽  
Zhengtao Zhang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Prediction Accuracy ◽  
Large Scale ◽  
Source Area ◽  
Spatial Prediction ◽  
Disaster Mitigation ◽  
Support Vector ◽  
Learning Models ◽  
Elevation Model ◽  
High Level

An earthquake-induced landslide (EQIL) is a rapidly changing process occurring at the Earth’s surface that is strongly controlled by the earthquake in question and predisposing conditions. Predicting locations prone to EQILs on a large scale is significant for managing rescue operations and disaster mitigation. We propose a deep learning framework while considering the source area feature of EQIL to model the complex relationship and enhance spatial prediction accuracy. Initially, we used high-resolution remote sensing images and a digital elevation model (DEM) to extract the source area of an EQIL. Then, 14 controlling factors were input to a stacked autoencoder (SAE) to search for robust features by sparse optimization, and the classifier took advantage of high-level abstract features to identify the EQIL spatially. Finally, the EQIL inventory collected from the Wenchuan earthquake was used to validate the proposed model. The results show that the proposed method significantly outperformed conventional methods, achieving an overall accuracy (OA) of 91.88%, while logistic regression (LR), support vector machine (SVM), and random forest (RF) achieved 80.75%, 82.22%, and 84.16%, respectively. Meanwhile, this study reveals that shallow machine learning models only take advantage of significant factors for EQIL prediction, but deep learning models can extract more effective information related to EQIL distribution from low-value density data, which is why its prediction accuracy is growing with increasing input factors. There is hope that new knowledge of EQILs can be represented by high-level abstract features extracted by hidden layers of the deep learning model, which are typically acquired by statistical methods.

PELAKSANAAN MODEL PEMBELAJARAN KOOPERATIF TIPE STAD UNTUK MENINGKATKAN HASIL BELAJAR PPKn SISWA SMP NEGERI 3 TELUK KUANTAN

2018 ◽  
Vol 2 (5) ◽  
pp. 789
Author(s):  
Maria Yulianti
Keyword(s):  
Cooperative Learning ◽  
Initial Data ◽  
Student Learning ◽  
Learning Outcomes ◽  
Student Learning Outcomes ◽  
Learning Model ◽  
Learning Models ◽  
The Subject ◽  
High Level

The background of this study was the low student learning outcomes of PPKn, from 28 students who achievedthe completeness criteria at least only 11 students (39.29%). The low student learning outcomes are caused bythe high level of individuality between students so that the achievement of competence among studentsexperiences a very distant difference. Based on this, the researchers made improvements to student learningoutcomes through the application of STAD cooperative learning models. This research is a classroom actionresearch, with the subject of class VII of SMP Negeri 3 Teluk Kuantan. The data used in this study is PPKnlearning outcomes data. The results stated that after applying the STAD type cooperative learning model studentlearning outcomes had increased in the initial data the number of students who completed were 11 students, incycle I had an increase with the number of 18 students, and in cycle II the number of students who completedcontinued to increase by the number 22 student.

THE IMPACT OF UKRAINE'S EXCISE DUTY POLICY ON THE TRANSFORMATION PROCESSES OF THE TOBACCO MARKET

2020 ◽  
Vol 2020 (10) ◽  
pp. 19-33
Author(s):  
Nadiia NOVYTSKA ◽  
◽  
Inna KHLIEBNIKOVA ◽  
Keyword(s):  
Structural Changes ◽  
Tax Avoidance ◽  
Transformation Process ◽  
State Regulation ◽  
Tobacco Products ◽  
Excise Duty ◽  
Increasing Demand ◽  
High Level ◽  
The Impact ◽  
Transformation Processes

The market of tobacco products in Ukraine is one of the most dynamic and competitive. It develops under the influence of certain factors that cause structural changes, therefore, the aim of the article is to conduct a comprehensive analysis of transformation processes in the market of tobacco and their alternatives in Ukraine and identify the factors that cause them. The high level of tax burden and the proliferation of alternative products with a potentially lower risk to human health, including heating tobacco products and e-cigarettes, are key factors in the market’s transformation process. Their presence leads to an increase in illicit turnover of tobacco products, which accounts for 6.37% of the market, and the gradual replacement of cigarettes with alternative products, which account for 12.95%. The presence on the market of products that are not taxed or taxed at lower rates is one of the reasons for the reduction of excise duty revenues. According to the results of 2019, the planned indicators of revenues were not met by 23.5%. Other reasons for non-fulfillment of excise duty revenues include: declining dynamics of the tobacco products market; reduction in the number of smokers; reorientation of «cheap whites» cigarette flows from Ukraine to neighboring countries; tax avoidance. Prospects for further research are identified, namely the need to develop measures for state regulation and optimization of excise duty taxation of tobacco products and their alternatives, taking into account the risks to public health and increasing demand of illegal products.

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.

Epigenetic Target Prediction with Accurate Machine Learning Models

2021 ◽  
Author(s):  
Norberto Sánchez-Cruz ◽  
Jose L. Medina-Franco
Keyword(s):  
Machine Learning ◽  
Small Molecules ◽  
Predictive Models ◽  
Large Scale ◽  
Target Prediction ◽  
Quantitative Measure ◽  
Learning Models ◽  
Discovery Research ◽  
Drug Discovery Research ◽  
Machine Learning Models

<p>Epigenetic targets are a significant focus for drug discovery research, as demonstrated by the eight approved epigenetic drugs for treatment of cancer and the increasing availability of chemogenomic data related to epigenetics. This data represents a large amount of structure-activity relationships that has not been exploited thus far for the development of predictive models to support medicinal chemistry efforts. Herein, we report the first large-scale study of 26318 compounds with a quantitative measure of biological activity for 55 protein targets with epigenetic activity. Through a systematic comparison of machine learning models trained on molecular fingerprints of different design, we built predictive models with high accuracy for the epigenetic target profiling of small molecules. The models were thoroughly validated showing mean precisions up to 0.952 for the epigenetic target prediction task. Our results indicate that the herein reported models have considerable potential to identify small molecules with epigenetic activity. Therefore, our results were implemented as freely accessible and easy-to-use web application.</p>

IMPLEMENTING SIM-OVG MODEL IN LEARNING ECONOMICS AT SMA NEGERI 10 SAMARINDA

2019 ◽  
Vol 1 (2) ◽  
pp. 151-164
Author(s):  
Watini Watini
Keyword(s):  
Learning Outcomes ◽  
Classroom Observation ◽  
Second Grade ◽  
Learning Models ◽  
Group Presentation ◽  
Second Grade Students ◽  
High Level ◽  
Work Method ◽  
High Level Thinking ◽  
Passing Grade

The reason underlying the implementation of the present study was because there was a finding revealing that there were still several students from cross-economics class of XI MIPA having difficulties in understanding the lessons. In addition, the students also had a kind of thought that economics was just about memorizing things which was not interesting and challenging that resulted in their unsatisfied learning outcomes. Therefore, the SIM-OVG model needed to be implemented in the learning process. The instruments of the present study were observation and, students’ learning reports and work method. The population of the study was the second grade students (4 classes) who enrolled economics subject at SMA Negeri 10 Samarinda, whereas the samples of the study were the students of XI MIPA-1 class (cross-economics class) at SMA Negeri 10 Samarinda. The number of the population and samples was 101 and 23 students respectively. The study lasted for one semester. The description of the classroom observation, the students’ scores and the group presentation were obtained for the data analysis. After implementing the SIM-OVG model, the results showed that; 1) in the affective aspect, the students showed a better attitude, 2) in the cognitive aspect, there was an improvement on the students’ learning outcomes (before the implementation of SIM-OVG model in XI MIPA-1 class, 52,17% of the students did not reach the passing-grade, but after the implementation, 100% of the students reached the passing-grade, and they also looked enthusiastic in doing their assignments, and 3) in the psychomotor aspect, the students became more skillful, creative, and be able to perform high level thinking. The researcher suggested that the dissemination should be done through MGMP forum and SIM-OVG model workshop. In addition, the researcher also suggested the integration of SIM-OVG model with other learning models and hoped that every school provided adequate facilities to support the implementation of SIM-OVG model.

scholarly journals Statistical and machine learning models for optimizing energy in parallel applications

2019 ◽  
Vol 33 (6) ◽  
pp. 1079-1097 ◽  
Author(s):  
Mark Endrei ◽  
Chao Jin ◽  
Minh Ngoc Dinh ◽  
David Abramson ◽  
Heidi Poxon ◽  
...  
Keyword(s):  
Machine Learning ◽  
Energy Efficiency ◽  
High Performance ◽  
Large Scale ◽  
Energy Use ◽  
Parallel Applications ◽  
Learning Models ◽  
Trade Off ◽  
Time Required ◽  
Machine Learning Models

Rising power costs and constraints are driving a growing focus on the energy efficiency of high performance computing systems. The unique characteristics of a particular system and workload and their effect on performance and energy efficiency are typically difficult for application users to assess and to control. Settings for optimum performance and energy efficiency can also diverge, so we need to identify trade-off options that guide a suitable balance between energy use and performance. We present statistical and machine learning models that only require a small number of runs to make accurate Pareto-optimal trade-off predictions using parameters that users can control. We study model training and validation using several parallel kernels and more complex workloads, including Algebraic Multigrid (AMG), Large-scale Atomic Molecular Massively Parallel Simulator, and Livermore Unstructured Lagrangian Explicit Shock Hydrodynamics. We demonstrate that we can train the models using as few as 12 runs, with prediction error of less than 10%. Our AMG results identify trade-off options that provide up to 45% improvement in energy efficiency for around 10% performance loss. We reduce the sample measurement time required for AMG by 90%, from 13 h to 74 min.

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 &gt;500 seedling-lethal mutants, completed cosegregation analysis of the insertion and the lethal phenotype for &gt;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 Spatial multiplexing holographic combiner for glasses-free augmented reality

Nanophotonics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 3003-3010
Author(s):  
Jiacheng Shi ◽  
Wen Qiao ◽  
Jianyu Hua ◽  
Ruibin Li ◽  
Linsen Chen
Keyword(s):  
Augmented Reality ◽  
Large Scale ◽  
Motion Parallax ◽  
Visible Spectrum ◽  
Physical World ◽  
Spatial Multiplexing ◽  
White Balance ◽  
Full Color ◽  
Entire Visible Spectrum ◽  
3D Scene

AbstractGlasses-free augmented reality is of great interest by fusing virtual 3D images naturally with physical world without the aid of any wearable equipment. Here we propose a large-scale spatial multiplexing holographic see-through combiner for full-color 3D display. The pixelated metagratings with varied orientation and spatial frequency discretely reconstruct the propagating lightfield. The irradiance pattern of each view is tailored to form super Gaussian distribution with minimized crosstalk. What’s more, spatial multiplexing holographic combiner with customized aperture size is adopted for the white balance of virtually displayed full-color 3D scene. In a 32-inch prototype, 16 views form a smooth parallax with a viewing angle of 47°. A high transmission (>75%) over the entire visible spectrum range is achieved. We demonstrated that the displayed virtual 3D scene not only preserved natural motion parallax, but also mixed well with the natural objects. The potential applications of this study include education, communication, product design, advertisement, and head-up display.

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