Reviewerly/exHarmony huggingface dataset:
End-to-end User Recognition using Touchscreen Biometrics.

We study the touchscreen data as behavioural biometrics. The goal was to create an end-to-end system that can transparently identify users using raw data from mobile devices. The touchscreen biometrics was researched only few times in series of works with disparity in used methodology and databases. In the proposed system data from the touchscreen goes directly, without any processing, to the input of a deep neural network, which is able to decide on the identity of the user. No hand-crafted features are used. The implemented classification algorithm tries to find patterns by its own from raw data. The achieved results show that the proposed deep model is sufficient enough for the given identification task. The performed tests indicate high accuracy of user identification and better EER results compared to state of the art systems. The best result achieved by our system is 0.65% EER.
Northwest Mineral Province - update on Deposit Atlas and other compilation datasets

NW Mineral Province Deposit Atlas entries have now been made for many of the major deposits in the Mount Isa region. In this webinar, we will provide an overview of the atlas entries that have been produced to date, some of the information that has been compiled in those atlases, and applications for exploration. We will also make mention of some of the other datasets that have been compiled from previous studies in the NW Mineral Province, and how to obtain and use them.
Scale-Adaptive Context-Aware Correlation Filter with Output Constraints for Visual Target Tracking

Context-aware correlation filter tracker is one of the most advanced target trackers, and it has significant improvement in tracking accuracy and success rate compared with traditional trackers. However, because the complexity of background in the process of tracking can lead to inaccurate output response of target tracking, an accurate tracking model is difficult to be established. Moreover, the drift problem is easy to occur during the tracking process due to the imprecise tracking model, especially when the target has large area occlusion, fast motion, and deformation. Aiming at the drift problem in the target tracking process, a novel algorithm is proposed in this paper. The developed method derives the specific representation of constraint output by assuming that the output response is Gaussian distribution, and a variable update parameter is obtained based on the output constraint relationship at first, then the tracking filter is selectively updated with changeable update parameters and fixed update parameters, and finally, the target scale is updated with maximizing posterior probability distribution. The effectiveness of developed algorithm is verified by comparing with other trackers on OTB-50 and OTB-100 evaluation benchmark datasets, and the experimental results have shown that the suggested tracker has higher overall object tracking performance than other trackers.
Variable-Bitrate Neural Compression via Bayesian Arithmetic Coding

Deep Bayesian latent variable models have enabled new approaches to both model and data compression. Here, we propose a new algorithm for compressing latent representations in deep probabilistic models, such as variational autoencoders, in post-processing. The approach thus separates model design and training from the compression task. Our algorithm generalizes arithmetic coding to the continuous domain, using adaptive discretization accuracy that exploits estimates of posterior uncertainty. A consequence of the plug and play nature of our approach is that various rate-distortion trade-offs can be achieved with a single trained model, eliminating the need to train multiple models for different bit rates. Our experimental results demonstrate the importance of taking into account posterior uncertainties, and show that image compression with the proposed algorithm outperforms JPEG over a wide range of bit rates using only a single machine learning model. Further experiments on Bayesian neural word embeddings demonstrate the versatility of the proposed method.
Augmentation of Effectiveness of New Product Development through Social Media: An Empirical Validation

The world is changing dramatically. These changes can be witnessed in different macro-environmental factors. Organisations are also witnessing a constant change in their business environment. In such high volatile environment, business firms need to innovate and change themselves. Therefore, it becomes vital for firms to adjust and alter their offerings to keep pace with the changes. New product development (NPD) is the lifeblood for any firm and their success contributes towards profitability and growth. New products are not only crucial for the profitability of any firm but also provide a competitive edge. However, only a small percentage of new products become successful in comparison to the number of new products introduced in the market. This portrays that the users are unwilling to accept the new products. Therefore, there lies a strong need to involve and inculcate the viewpoints of customers while designing a product so that they are not mere receivers of products but also active participants in the creation of products. Further, as per this study, the involvement of other vital elements such as the sales department, R&D department and the company level drivers play a critical role in the success of a new product.
Hey #edu407 when thinking text structure first ...

Hey #edu407 when thinking text structure first identify the overall shape of story. Two pieces, first expository piece: https://www.science.org.au/curious/space-time/gravity second compare/contrast: https://www.science.org.au/curious/space-time/gravity-How are they different?-The
A Strength and Weakness of Regression Analysis and Quartile and IQR Deviation by using Test- Driven Development

Test-Driven Development (TDD) derives an evolutionary approach which needs unit test cases to be made before implementation of the code. The goal of this paper is to examine product code quality and programmer productivity using test-driven development approach. This paper establishes regression analysis and quartile &amp; inter-quartile range deviation to evaluate the process effect on external code quality and developer productivity. The results of this paper are that if developer productivity is the actual effect, external code quality will be fewer decreased and external code quality is the actual effect if developer productivity will be fewer reduced. Test-Driven Development can produce the clear of code, simple and bug-release. Defect numbers decreased when automated unit tests are written iteration related to test-driven development. If necessary, the code refactoring is acted TDD. This proposed system evaluates regression analysis and quartile &amp; inter-quartile range deviation based on a fixed time-frame.
Using Images for Real-Time Violence Detection in the Edge

Surveillance cameras have become commonplace in urban scenarios. These cameras are currently proving to be a valuable aid in apprehending criminals after the camera feed is analyzed. Their utility can be further enhanced if detection capabilities are provided, via additional hardware for realizing specific functionality. Currently, Deep Neural Networks are the most popular set of tools for image classification and have also been successfully adapted for other modalities such as video, speech and ECG signals. However, many of these Deep Nets are designed for very complex multi-class problems and hence do not allow for real-time functionality on an embedded platform, due to the large number of parameters involved during the classification task. In this work, we use a modified version of an existing dataset that can be easily trained with published networks to give reasonably good detection accuracy. It is shown via experiments that even smaller nets perform as well as state-of-the-art networks and provide the same level of detection accuracy as the more complex networks. Hence, the simpler networks can be used for a detection task by downloading it to an embedded system and allowing for classification to happen in real time.
How avatar gender may influence users intention to use Second Life environment: An empirical study

The use of virtual environments to transform individuals? use of modern technology has gained a special attention lately. The role of gender in the virtual space has also been viewed as a contributor to individuals? use of modern technology. This study investigated the impact of avatar gender on users? intention to use the Second Life (SL) environment in a university context. Two avatars of male and female characteristics were designed and used in the SL environment. A total of 74 SL users were involved in two learning sessions (with male female avatars). A questionnaire was used to capture users? perceptions of ease of use, usefulness, attitude, and behavioral intention to use the SL space. SL users had positive intentions to use the SL environment for various learning purposes when they are provided with the preferred gender appearance. Offering opposite gender characteristics can help stimulate users? interaction with the avatar, thus facilitating the learning process and building the sense of technology effectiveness.
Analysis of 3S Technology Application in Land Improvement Project

In the process of land improvement project implementation, field survey and reconnaissance studio in the early stage is an important link for the whole project to be completed efficiently and with high quality.Traditional field expeditions need to carry different instruments and equipment and paper drawings. The data obtained is slow in efficiency and low in accuracy. The diverse and complex data generated is not conducive to data integration in the later stage, and the team's information sharing and cooperation ability are greatly reduced.Using GIS, RS, GPS combination of 3 s technology, with high penetration rate, low cost of mobile terminal pad, mobile phone to gather in the early period of the carrier used in land reclamation engineering reconnaissance survey work, from the information acquisition, storage, management, analysis and sharing of multiple link efficiency are enhanced greatly, this article is based on 3 s technology and intelligent mobile side field reconnaissance work patterns of designing new land control, forming new tools and means, to reduce costs, improve efficiency colleagues better serve the construction of land reclamation engineering.
Research on the Influence of Information Technology on Education Under the Background of Big Data

In the big data environment, information technology has penetrated into all aspects of education, and has a profound impact on education. It is of great significance to study the impact of information technology on education and improve the quality of education in the context of big data. Through the elaboration of big data and information technology, this paper analyzes the impact of information technology on education and teaching, and its positive and negative impact on curriculum design, education methods, education innovation, etc. The purpose is to give full play to the positive impact of information technology on education and teaching and avoid the negative impact of information technology on education. Using information technology to improve the quality and level of education and teaching, and promote the overall development of talents.
항공서비스 전공학생의 전공선택동기가 전공만족도 및 취업준비행동에 미치는 영향

A study of purpose is identify and analyze The Effects of Major Selection Motivation of Students Majoring in Airline Service on their Major Satisfaction and Employment Preparation Behavior, to open better departmental education programs for students and to present efficient directions in the employment preparation process, which is a step for future career goals and preparation. In summary, the results of hypothesis testing in this study are as follows, First, it was found that the higher Major Selection Motivation of Airline Service Students, the more likely it was to affect the Major Satisfaction. It has been shown that personal motivations of Students Majoring in Airline Service have a significant impact on the satisfaction of their majors, but social motivations do not have a significant impact. The higher the degree of satisfaction with the major, the more likely it is to affect job preparation behavior, and the less significant impact on full-scale job preparation actions. The implications of this study were intended to use the motivation for majors in college entrance exams so that students can live a smooth college life and achieve their desired jobs after admission.
Foreword to the special section on smart tool and applications for graphics (STAG 2019)

Abstract This special issue contains extended and revised versions of the best papers presented at the 6th Smart Tools and Applications in Graphics (STAG 2019), held in Cagliari, on 14–15 November, 2019. The three selected papers span different visual computing domains: (i) a framework for fully interactive non-linear spatio-temporal exploration of massive time-varying rectilinear scalar volumes on commodity platforms, (ii) a visualization system for reviewers for identifying researchers working on a certain topic, analyzing their contributions over time, and highlighting co-authorship relations and conflicts, (iii) a VR environment for editing and proofreading medial axis representations of nanoscale brain cell morphologies.
Componentes del habla de Dell Hymes en el aprendizaje del idioma inglés

The purpose of this research was to identify the elements of a communicative event with a more significant impact on the development of oral skills in English language learning. The most useful communicative events that facilitate the improvement of verbal skills in students are also identified. For this, a qualitative-quantitative methodology was used; a survey was applied to the 49 students of a higher-level educational institution. The data analysis was performed using the Chi-square test, which suggests a complete adaptation of all the speech components proposed in the Dell Hymes taxonomy in activities related to the development of oral skills in English language learning. Results were obtained on the proper use of speech components, according to the Dell Hymes taxonomy, in each communicative event applied in class for English language learning. The main objective was to denote the importance of the development of oral skills in university students of two different basic levels. In conclusion, it can be stated that the Dell Hymes Speech Components have a positive effect on the development of oral proficiency in English language learning.
Research on Control Method of Intelligent Air-Conditioning System in Smart City

In order to realize the intellectualization of intelligent urban air-conditioning system, this paper puts forward a novel control method of intelligent air-conditioning system based on a variety of advanced science and technology. This method integrates a variety of advanced science and technology, such as big data technology, cloud computing technology, Internet of things technology and so on. The research results show that this method can fundamentally scientifically and effectively improve the stability and safety of air-conditioning operation, and achieve the goal of energy saving and green development.
Distributed implementation of the graphs clusterization goodness metrics calculation using mapreduce and vertex-oriented graph processing model

Goal. Research of the implementation features of the graph clusterization goodness metrics using the vertexoriented graph computing model and MapReduce. Materials and methods. The basic concepts of graph theory were used to define the goodness metrics, and the MapReduce with a vertex-oriented graph-computational approach were used to develop the goodness metrics calculation algorithms. Results. Distributed algorithms for calculating graph clustering goodness metrics are proposed and tested. Conclusion. The results can be used to analyze the quality of the partitioning of large graphs that obtained using an arbitrary distributed clustering algorithm.
Basic Geophysics - Properties of Rock

Does the earth resemble a rubber ball or a putty?Presentation of the elastic and plastic properties of the earth and their effect on the propagation of seismic waves
Making the Data and Services FAIR: A Multidisciplinary Perspective

Presentation delivered during the Webinar III: Making the data and services FAIR organised by the e-IRG Workshop within the framework of Croatia's Presidency of the Council of the European Union, on May 26, 2020. More information available at the website of e-IRG e-Infrastructure Reflection Group http://e-irg.eu/workshop-2020-05-programme.
Efficient schemes with diverse of a pair of circulant matrices for AES MixColumns-InvMixcolumns transformation

Recently, AES is a commonly used encryption-decryption algorithm applied to wireless communication protocols. However, confidentiality and speed both associated with Cipher-InvCipher that are a very important issue in many current communication systems. In this paper, the key idea here is to propose a method with more variations in circulant matrix for enhancing security in AES MixColumns-InvMixColumns step. The paper is also to propose a method minimizes the number of multiplications for matrix multiplication theoretically based on two-point cyclic convolution properties of circulant matrix. The conventional 44 matrix multiplication typically needs 16 multiplications and 12 additions; however, the proposed method, described herein as Scheme 3, can reduce the matrix multiplications into 5 multiplications and 15 additions, which is used for encryption and decryption. Using Scheme 3 and Horner’s rule-based multiplication running on Intel CPU, the computational cost of the matrix multiplication can be reduced by ~63%. Furthermore, experiments using Scheme 3 along with Horner’s rule-based multiplication by means of AES keys lengths with 128, 192, 256 bits were tested by running on STM32L476VG MCU, result leads to the reduction of encryption and decryption time respectively by ~60%. Finally, the proposed procedure enables found many a pair of the circulant matrices for AES Cipher-InvCipher so that diverse of a pair of the circulant matrices can enhance security of the data transmission.
PENGEMBANGAN VIDEO PEMBELAJARAN MENGGUNAKAN ProShow UNTUK KELAS IV SEKOLAH DASAR

ABSTRAK Dunia pendidikan saat ini sudah mulai berkembang, dengan berbagai macam pembaharuan telah dilakukan untuk dapat meningkatkan kualitas pendidikan, peningkatan kualitas perlu segera dibenahi untuk meningkatkan peran aktif peserta didik, yang mengakibatkan terbentuknya pengetahuan dan keterampilan yang mengarah pada peningkatan kemampuan pemecahan masalah. penelitian pengembangan (RD Prosedur pengembangan menggunakan desain pengembangan Borg & Gall, dengan bantuan ProShow Dari hasil uji-diperoleh tobs = 2,95 > ttabel= 2,022, artinya bahwa kedua kelompok memiliki prestasi belajar yang berbeda atau tidak sama. Hasil post test menunjukkan bahwa rerata prestasi belajar kelompok yang menggunakan media pembelajaran yang dikembangkan lebih besar daripada rerata prestasi belajar kelompok yang mengunakan media buku bergambar (71,3 > 63,5). Dari perolehan tersebut dapat ditarik kesimpulan bahwa media yangdikembangkan efektif dalam meningkatkan prestasi belajar. Kata kunci : pengembangan, Video pembelajaran, SD Abstract The education has been grown rapidly nowadays. The number of change has been executed to develop the quality of education. The improvement of quality needs to be implemented urgently to engage students. Furthermore, it is expected to enhance of problem solving skill from the formed knowledge and skill. This research was in form of Research and Development (R&D) in accordance to Borg & Gall design. ProShow was the application used to proceed the video-based teaching media. The data were collected through interview, observation, giving questionnaire, and test. The result of interview and observation was analyzed in form of descriptive qualitative meanwhile questionnaire and test was analyzed quantitatively. The use of media in teaching Social Science for IV grade students was not implemented well. The procedure of research was adopted from Borg & Gall using ProShow as the developing media. The result shows that t.obs is 2,95 > t.table is 2,022. This can be interpreted that both groups have different achievement. The result of post-test shows that the average of students’ achievement that have exposure to implemented developed teaching media which is higher than the students’ achievement using media of picture based book (71,3> 63,5). Thus, developed media is effective to improve students’ achievement. Keywords: development, teaching video, Elementary School.
Using the isolation forest algorithm to solve the problem of detecting anomalies in the operation of microprocessor plastic cards

Anomaly detection is an important issue in data science. The purpose of detection is to determine the system and stochastic violations of the signal structure, the regularity of repetition of characteristic sites, as well as the localization of artifacts of natural or artificial origin. These can be failures in the data collection process, sensor failure, or external unexpected events, such as an intentional violation of the microcontroller’s security. In addition, with the help of the proposed methods of anomaly detection, it is possible not only to analyze the security of devices, but also to determine the efficiency of the use of computing resources and check the operation of hardware modules. In General, the introduction of such methods is advisable at all stages of the life cycle of microprocessors and microcontrollers.
Contradistinguisher: A Vapnik's Imperative to Unsupervised Domain Adaptation

A complex combination of simultaneous supervised-unsupervised learning is believed to be the key to humans performing tasks seamlessly across multiple domains or tasks. This phenomenon of cross-domain learning has been very well studied in domain adaptation literature. Recent domain adaptation works rely on an indirect way of first aligning the source and target domain distributions and then train a classifier on the labeled source domain to classify the target domain. However, this approach has the main drawback that obtaining a near-perfect alignment of the domains in itself might be difficult/impossible (e.g., language domains). To address this, we follow Vapnik's imperative of statistical learning that states any desired problem should be solved in the most direct way rather than solving a more general intermediate task and propose a direct approach to domain adaptation that does not require domain alignment. We propose a model referred Contradistinguisher that learns contrastive features and whose objective is to jointly learn to contradistinguish the unlabeled target domain in an unsupervised way and classify in a supervised way on the source domain. We achieve the state-of-the-art on Office-31 and VisDA-2017 datasets in both single-source and multi-source settings. We also demonstrate that the contradistinguish loss improves the model performance by increasing the shape bias.
INDIVIDUAL CRIMINAL RESPONSIBILITY FOR WAR CRIMES RESULTING FROM THE USE OF AUTONOMOUS WEAPONS SYSTEMS

Autonomous weapons systems (AWS) are one of the emerging modern military technologies that are attracting more and more attention of the international community. While they raise a lot of questions with respect to various fields of law, the biggest worry is that there will be no accountability for their wrongful use. This article focuses on the individual criminal responsibility for war crimes committed with the use of AWS. Four modes of responsibility, which could be potentially applied to AWS-related war crimes, are considered in turn with the aim of ascertaining, whether the current rules of international criminal law provide sufficient basis to assign responsibility for these crimes.