Reviewerly/exHarmony huggingface dataset:
Seismic Soundoff

The following is an excerpt from SEG's Seismic Soundoff podcast. The episode features Dean Mento discussing what's exciting about being a geophysicist, the career options available, the problems geophysicists solve, and more. If you like adventure and solving complex problems or need help explaining your work to friends and family — this episode is for you. Listen to the full episode at https://seg.org/podcast/post/6868/ .
Subject Independent Automatic Facial Expression Recognition from Partially Occluded Still Images by Employing Appearance Based Feature Extraction Schemes

Facial expression recognition is the process of identifying human emotion through expressions. The world around us is constantly changing and in this ever-changing scenario, development of a system which performs automatic detection and recognition of facial expressions in a given scene is of paramount importance, and at the same time highly challenging. It becomes even more challenging when the aforesaid scene is partially occluded, thus limiting the facial area which could be explored. As such, expression recognition from partially occluded images is still largely an unexplored area. The proposed work is an attempt towards subject independent automatic expression recognition from partially occluded images. Salient features of the proposed work involves careful approximation of contributions made by facial regions like eye, mouth, and nose towards recognition of each basic expression; determination of a particular region in face which contributes the most discriminative and abstract feature for recognition of a particular expression; identification of facial region wherein expression recognition is independent of any occlusion happening with respect to that particular region. The proposed work to begin with segments facial regions from a static facial image; discriminative and abstract features extracted from so segmented facial regions are experimented upon to better understand the contribution made by each region in recognition of a facial expression. Various appearance features such as HOG, LBP and OGBP have been incorporated in the experimentation, and results obtained thereby infer that mouth region convey lion’s share of the information about probabilistic determinant of an expression and its intensity when compared to remaining regions. The proposed system outperforms holistic approaches in connection with facial expression recognition.
A New Method for Dental Cast Analysis

Objectives: This study aimed to develop a new method of dental cast analysis using angular measurements. Materials and methods:One hundred study models belong to 100 Iraqi healthy adults with class I occlusion were assessed using Planmeca dimax software.Three angular measurements at the levels of maxillary canines, second premolar and second molars cusp tips with the tip of the angles at the midpoint between the two central incisors were measured.Gender difference was evaluated by unpaired t-test and the relation between the angles was assessed by Pearson's correlation coefficient test. Results:The results revealed higher mean values of the measured parameters in males with direct, moderate to strong, significant correlation. Conclusions:A new method was developed and could be used to assess the growth and treatment changes in the future researches.
Cover

Meteoritics & Planetary ScienceVolume 55, Issue 1 p. i-i CoverFree Access Cover First published: 24 January 2020 https://doi.org/10.1111/maps.13319AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Graphical Abstract Volume55, Issue1January 2020Pages i-i RelatedInformation
An Analysis of the Management Performance of Real Estate Development Company- Focusing on real estate development company in Seoul

This study focused on management performance analysis and productivity analysis on real estate development companies in Seoul among real estate development companies.Input variables were analyzed for efficiency and productivity through DEA through total asset, labor costs and non-current asset output variables through sales and net profit.By doing so, the government wanted to enhance the management efficiency of a real estate development company by analyzing its management performance.
Improved Performance for Secured Authentication in User Devices and Cloud Environment

In the last few years, various researchers have identified that securing the cloud environment requires quite a challenging decision to be made as identifying the correct security parameter is difficult. This paper presents” SRAAM: Secure Resource Access Authentication Mechanism”, a collaborative framework between user mobile device and cloud infrastructure, for authenticating user and device credentials. An experimental prototype is done for proof of concept and performance matrices are evaluated based on the important decision making parameters. Also, a novel model called as Integrated Framework for Cloud Security (IFCS) that performs mainly three task i) faster and robust user authentication, ii) maintaining anonymity of data storage location, and iii) securing the virtualization platform. An experimental approach is adopted in order to testify the proposed system. Total algorithm processing time in contrast to frequently adopted security protocols in existing system.
Literature Review

This chapter provides the literature survey. Prior work on multilingual speech recognition systems is provided. The use of AFs to improve performance of multilingual speech recognizers is briefly reviewed. The existing works related to the use of multilingual systems for code-switched speech recognition are described. Various approaches used in the development of multilingual speech recognition systems are briefly described.
Design of a hand gesture recognition system based on forearm surface electromyography feedback

This paper presents a study of using surface electromyography (SEMG) for hand gesture recognitions. A SEMG acquisition system is discussed in this paper. The characteristics of SEMG are introduced and the transformation characteristics are analysed as well. Then the selected gestures and the location for the SEMG sensor are determined. The process of pattern recognition and the reason of selecting SVM classifier are presented in detail, and the kernel function selection of SVM is discussed. Three optimisation methods of parameters are compared using the cross-validation method. Finally, the parameters obtained by the genetic algorithm are used to test the model and the recognition performance.
STUDY ON PROCESSING PERFORMANCE OF A DPDK AND GPU COMBINED PULSAR DATA REDUCTION SYSTEM

Pulsars are fast-rotating neutron stars which are some of the most extreme objects in the universe and important key probes for the fundamental physics.The massive amounts of data caused by high time resolution and wide bandwidth sampling poses a huge challenge to the realization of a reliable real-time process for pulsar observation systems.To achieve a real-time transmission and processing of up to several or even tens of gigabits per second for pulsar observations, this paper proposes a high performance and reliable real-time coherent dedispersion pipeline for the 40-m Radio Telescope of Yunnan Astronomical Observatories.We first introduce the specifications of the pulsar backend and analyze the requirements of coherent dedispersion pipeline of the telescope.After the design of the system architecture, we focus on the implementation of the high-performance pipeline.Two key techniques such as high-performance lossless data acquisition based on Data Plane Development Kit and real-time coherent dedispersion processing upon graphics processing unit platforms are presented in detail.The subsequent experiments and test observations demonstrate the proposed pipeline meets the requirements and enables long-term observations for the telescope.
Feature Extraction for Image Texture Classification

Surface request accept a critical activity in PC vision and picture taking care of utilizations. We propose an approach to manage concentrate picture features for surface portrayal. This procedure for removing picture features for request of surfaces is solid to picture insurgency, less sensitive to histogram leveling and bustle. It includes two courses of action of picture features: overpowering close-by twofold models (DLBP) in a surface picture and the beneficial features expelled by using circularly symmetric Gabor channel responses. The predominant close-by twofold model system use the most a great part of the time happened guide to find hypnotizing textural information, while the Gabor-based features go for giving additional overall textural information to the DLBP features
Issues in Urdu-Hindi NER Output of Google and Bing Translator: An Orthographic Perspective

Named Entity Recognition (NER) is a sub-task of information extraction in which names are extracted both from the text and linguistic corpora which is still a tough nut to crack for NLP researchers in existing Machine Translation (MT) system due to its long tail. Since decades, NER has been an area of great interest both in MT and computational linguistics, thus, several tools have been designed for their handling in different languages. Therefore, this paper aims to compare the end user output of both Google and Bing translator with special reference to Urdu-Hindi NER. This will provide more insights in the development of intelligent language tools. Thus, on the one hand, the paper deals with orthographic challenges pertaining to UrduHindi NER in general, while on the other hand, the paper also sheds light on the transliteration issues in particular. Further, we have also investigated the personal names, and named entity of Urdu, especially ezafat constructions. Consequently, the paper also proposes to handle NER from the language engineering point of view based on the existing end user output quality. Furthermore, the MT output of both Google and Bing has been ranked on the scale of 0 to 1, where 0 assigned to the correct output while 1 given to the wrong or inaccurate output.
PANTSA Influence in grouping Mixed and Incomplete Data

Obtaining high quality groups and processing mixed and incomplete data (DMI) are still problems in the data clustering. Recently a method was proposed that improves the results obtained by clustering algorithms, the PAntSA; but this was only designed and tested for numerical data. For this reason, this paper analyzes the influence of applying the PAntSA in the performance of DMI restricted clustering algorithms. For this, the results of different algorithms are compared before and after applying the PAntSA. The comparisons made provide experimental evidence that the PAntSA algorithm improves the quality of the groups obtained by traditional DMI clustering methods.
Build Dapps with Angular: Part I

In previous chapters, I covered different blockchains, and you learned how to create smart contracts that can interact with a blockchain. You created smart contracts in Ethereum, NEO, EOS, and Hyperledger. In Chapter 1 , I broke down the process into five layers: consensus layer, miner or booking layer, propagation layer, semantic layer, and application layer. Smart contracts are part of the application layer in the development cycle; however, the application layer is incomplete without having a front-end interface that enables a developer or end user to interact with the blockchain.
Using Smartphone Sensors to Generate Cryptographic Keys

The paper proposes an algorithm for generating random numbers based on sensors of a gyroscope, magnetometer, accelerometer on mobile devices, and discusses the sensors of a gyroscope, magnetometer and accelerometer. The random bit generator uses smartphone sensors as entropy source. It collects raw data from smartphone sensors and processes they by given algorithm. The degree of randomness of random bits generated using the proposed algorithm was tested using statistical tests NIST SP 800-22, and a test result was given. It is important to ensure the safe storage, transmission and use of data in these information systems. To solve these problems, cryptographic methods are used more often than other methods of data protection. Cryptographic algorithms are the basis of cryptographic data protection methods. Most cryptographic algorithms are publicly available and the key plays the role of a secret value when applied. The generations of these secret keys and sometime private keys are based on random number generations.
Competence of the cartographic literacy of schoolchildren: essence and methodological foundations of the formation

The purpose of this article is to characterize the theoretical foundations of the cartographic method in school geography and to highlight the competencies of schoolchildren’s cartographic literacy, the analysis of teaching methods for the formation and development of cartographic literacy of schoolchildren in the process of studying geography. The main material. The main attention is paid to the analysis of the elements of cartographic literacy of pupils, which is formed when studying geography at school. As such elements, not only theoretical knowledge of schoolchildren about the map, but also practical skills to work with the mathematical basis of the map, cartographic image, conventional signs, carry out measurements on the map, and find geographical coordinates are highlighted. Cartographic competencies higher level of pupils are the ability to analyze geographic objects using maps, determine their dynamics, make geographic forecasts, models, apply a map when conducting geographic expertise and design. At the same time, attention is focused on the fact that the competences of cartographic literacy of schoolchildren are initially formed at the initial stage of studying geography at school, and will be claimed and developed throughout the entire geographical education. Cartographic literacy of schoolchildren is based on the use of maps for studying objects and phenomena displayed on them. Its elements are consistently and systematically formed and developed in geography lessons and are of practical importance both in the educational process and in everyday life. Traditionally, in the process of teaching geography, tasks associated with determining the geographical coordinates of objects, measuring distances and orientation on the map are used. In order to increase the creative focus in the study of geography, you can use design tasks based on the use of maps, methods of cartometry and morphometry, modeling of geographical objects, solving tasks of a problem character. Conclusions and further research. These tasks of cartographic subjects significantly expand the competencies of schoolchildren and their horizons, increase the interest in the academic subject and introduce the creative component into the educational process. Further research may be related to the determination of the most effective methodologies for the development and expansion of the cartographic competencies of schoolchildren both in geography and extracurricular activities.
Spatial Data Warehousing for Integrated Urban Data Management

In this paper different special data management schemes pointing urban data environment are reviewed. The approach and the theory of Spatial Data Warehousing (SDW) pointing the urban data atmosphere is briefly discussed. Nature and architecture SDW are characterized. The use of SDW with the use of decision making is developed and analyzed for urban data environment. A three- tiered architecture for the SDW is proposed. The issues and solutions related to the designing of the SDW is addressed.
Multi-Index Image Retrieval Hash Algorithm Based on Multi-View Feature Coding

In recent years, with the massive growth of image data, how to match the image required by users quickly and efficiently becomes a challenge. Compared with single-view feature, multi-view feature is more accurate to describe image information. The advantages of hash method in reducing data storage and improving efficiency also make us study how to effectively apply to large-scale image retrieval. In this paper, a hash algorithm of multi-index image retrieval based on multi-view feature coding is proposed. By learning the data correlation between different views, this algorithm uses multi-view data with deeper level image semantics to achieve better retrieval results. This algorithm uses a quantitative hash method to generate binary sequences, and uses the hash code generated by the association features to construct database inverted index files, so as to reduce the memory burden and promote the efficient matching. In order to reduce the matching error of hash code and ensure the retrieval accuracy, this algorithm uses inverted multi-index structure instead of single-index structure. Compared with other advanced image retrieval method, this method has better retrieval performance.
Fault Diagnosis of Industrial Robot based on Fuzzy Multi-attribute Decision-making of Knowledge Graph

The internal structure and functions of industrial robots are complex, and the traditional text lookup method is inefficient in fault diagnosis because of knowledge is too scattered. Fragmented knowledge can be effectively integrated by knowledge graph. Therefore, knowledge model is designed based on text data and the fault knowledge graph of industrial robots is stored in the Neo4j database. Aiming at the shortcomings of low accuracy of knowledge graph decision-making, a fault evaluation methods combining knowledge graph and fuzzy multi-attribute decision-making (KG- FMADM) is proposed. The analytic hierarchy process(AHP) theory and the TOPSIS method are selected to establish an evaluation system. Then the sequencing results of multiple fault chains are inferred and analyzed in detail. Finally, the effectiveness of KG-FMADM in the fault evaluation is verified with the sets of fault chain data. The results show that the proposed method can improve the accuracy of fault assessment, so that it can ensure the scientiflcity and rationality of fault diagnosis.
Image Enhancement Filtering Techniques to Enhancect Images of Lung Cancer

Medical images are susceptible to noise and poor contrast. Improving the quality of image using different image enhancement techniques is an important area of image research. In this paper, various image enhancement techniques are applied over lung cancer CT images. Identifying mechanisms to detect lung cancer is very important since men and women are found to be most affected by Lung cancer compared to other types of cancer. As per the report from the World Health Organization, 2.09 million cases of Lung cancer were reported in the year 2018. Early detection and treatment of Lung cancer improve the chances of survival. Thus, this paper aims at applying and reviewing different frequency based Image enhancement techniques like Butterworth filter, Gaussian filter, Gabor filter, fast Fourier transform, and Discrete wavelet transform and finding the best filtering technique used to detect Lung cancer from a sample of Computed Tomography (CT) images. Peak to signal noise ratio is calculated to find the best filter since it is similar to reconstruction quality in human’s perception. The results from experiment analysis shows that Gabor filter has higher PSNR value and it’s the best enhancement technique out of the filters taken under study.
Copyright Infringement

American Chemical Society and Elsevier have filed a legal fight case against Research Gate. They blame Research Gate of “massive infringement of peer reviewed, published journal articles.” According to them the networking site—Research Gate is illegally making research papers available to the users which are copyrighted (McKenzie 2018). “Media organization files copyright infringement case against Saint Peters Blog owner”, the news on May 8, 2015, in Tampa Bay Business Journal, has created huge waves throughout the information and communication technology world (Huff 2015). Using media file contents for writing the blogs is a serious offence and comes under copyright infringement act. In the present day world, the number of Internet users has rapidly grown along with the growth of information and digital technology. With this development of the Internet and rapid increase in usage of digital multimedia, it has become very easy to generate unauthorized digital data.
AI theorist? Not yet

AI Feynman: A physics-inspired method for symbolic regression Authors: Silviu-Marian Udrescu and Max Tegmark Sci. Adv. 6 : eaay2631, 2020; DOI: 10.1126/sciadv.aay2631 Recommended with a commentary by Ilya Nemenman, Emory University |View Commentary (pdf)| This commentary may be cited as: DOI: 10.36471/JCCM_May_2020_02 https://doi.org/10.36471/JCCM_May_2020_02
Neuroevolution for deep reinforcement learning problems

tutorial Neuroevolution for deep reinforcement learning problems Share on Author: David Ha Research Scientist at Google Brain in Tokyo Research Scientist at Google Brain in TokyoView Profile Authors Info & Claims GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference CompanionJuly 2020 Pages 404–427https://doi.org/10.1145/3377929.3389859Online:08 July 2020Publication History 0citation314DownloadsMetricsTotal Citations0Total Downloads314Last 12 Months126Last 6 weeks11 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access