Reviewerly/exHarmony huggingface dataset:
Detection and identification method of the tor bundle use

This paper presents the result of author’s research aimed at developing a detecting and identifying method of the Tor Bundle use in data transmission networks, in particular, on the Internet. Based on these characteristics, an algorithm has been developed that allows legitimate blocking of user access to a global network by a popular anonymizer. The subject of the study was an SSL/TLS encryption certificate, which is transmitted by the Tor network server to the user of the Tor Bundle and which contains the set of data necessary for its identification during the implementation of the TLS “handshake”. In the course of the study of the certificates features, several distinguishing features were identified, namely: the name of the subject and issuer of the certificate, which is a random set of letters and numbers; port used when connecting to an anonymous network; certificate size. Based on the data received, a method is proposed that allows the provider’s server to block the connection during which a certificate with certain characteristics is transmitted.
Peer Review A Study about Principle Component Analysis and Eigenface for Facial Extraction

Hasil Peer Review A Study about Principle Component Analysis and Eigenface for Facial Extraction
Positive Response of Library Users to Librarians According to Cognitive, Affective, and Conative Aspects

Background : Various ironic portraits of the librarian profession are coupled by the low interest of young people in the librarian profession. However, librarians of Universitas Airlangga and Petra Christian University Surabaya have changed the attitude of the librarian for the better than before.Objective  : The purpose of this study is to determine the attitude responses generated by library users in cognitive, affective, and conative aspects based on the services of the librarians in the reading room services.Methods : This study used a descriptive research method with a survey approach of 100 respondents. Sampling was done by purposive sampling with the criteria of having visited the library in the last six months, having visited at least three times, and having interacted with librarians in the library services. The data were obtained through questionnaires and probing interviews.Results : Based on the results of the research, cognitive aspects were good at a score of 2.27, affective aspects were also good at a score of 2.15, and conative aspects were also good at a score of 2.38. The cognitive response was good because the help of librarians was very useful and accurate. Then, the affective response was also good because the librarians always listened to complaints from users. Moreover, the conative response was also good because the librarians always offered help to the users.Conclusion : The response of library users is overall satisfied with the services of librarians with indicators of three aspects: cognitive, affective, and conative. This makes the librarian's image as a proud profession in the view of the users.
Improved Complexities for Stochastic Conditional Gradient Methods under Interpolation-like Conditions

We analyze stochastic conditional gradient methods for constrained optimization problems arising in over-parametrized machine learning. We show that one could leverage the interpolation-like conditions satisfied by such models to obtain improved oracle complexities. Specifically, when the objective function is convex, we show that the conditional gradient method requires $\mathcal{O}(\epsilon^{-2})$ calls to the stochastic gradient oracle to find an $\epsilon$-optimal solution. Furthermore, by including a gradient sliding step, we show that the number of calls reduces to $\mathcal{O}(\epsilon^{-1.5})$.
Learning Quantum Phases by Visualization

Identifying quantum phases of interacting many-body systems is key to understand the emergent phenomena in condensed matter physics. However, such tasks are often extremely challenging due to the exponentially large dimensionality of the associated Hilbert space. Conventional practices usually require the order parameters to specify the quantum states. In this work, we propose a different strategy to access quantum phases by visualization based on the distribution of ground states in Hilbert space. By mapping the quantum states in Hilbert space onto a two-dimensional feature space using an unsupervised nonlinear dimensionality reduction method, the quantum states can be explicitly visualized, from which distinct phases can be easily specified and the phase transition point can be well identified. Our scheme is benchmarked on the phases of several strongly correlated spin systems, including gapped, critical, and topological phases. As our strategy directly learns the quantum phases and phase transitions from the distributions of the quantum states, it does not depend on priori knowledge of order parameters or any other specific physical properties of the quantum systems. This work indicates a highly perceptual route to identify quantum phases and phase transitions particularly in the complex systems of condensed matter by visualization through learning.
In memoriam: Alan S. Rodger

It is with great sadness that we report that Prof. Alan Rodger, Editor of the Journal of Geophysical Research (Space Physics) and former Interim Director of the British Antarctic Survey (BAS), passed away on January 3, 2020.
Instance Scale Normalization for image understanding

Scale variation remains a challenging problem for object detection. Common paradigms usually adopt multiscale training &amp; testing (image pyramid) or FPN (feature pyramid network) to process objects in a wide scale range. However, multi-scale methods aggravate more variations of scale that even deep convolution neural networks with FPN cannot handle well. In this work, we propose an innovative paradigm called Instance Scale Normalization (ISN) to resolve the above problem. ISN compresses the scale space of objects into a consistent range (ISN range), in both training and testing phases. This reassures the problem of scale variation fundamentally and reduces the difficulty of network optimization. Experiments show that ISN surpasses multi-scale counterpart significantly for object detection, instance segmentation, and multi-task human pose estimation, on several architectures. On COCO test-dev, our single model based on ISN achieves 46.5 mAP with a ResNet-101 backbone, which is among the state-of-the-art (SOTA) candidates for object detection.
Optimizing Smart Grid Aggregators and Measuring Degree of Privacy in a Distributed Trust Based Anonymous Aggregation System

A smart grid is an advanced method for supplying electricity to the consumers alleviating the limitations of the existing system. It causes frequent meter reading transmission from the end-user to the supplier. This frequent data transmission poses privacy risks. Several works have been proposed to solve this problem but cannot ensure privacy at the optimal level. This work is based on a distributed trust-based data aggregation system leveraging a secret sharing mechanism. In this work, we show that {\em three aggregators} are enough for ensuring consumer's privacy in a distributed trust-based system. We leverage the idea of anonymity in our research and show that neither an active attacker nor a passive attacker can breach consumer's privacy. We show proof of our concept mathematically and in a cryptographic game based mechanism. We name our new proposed system \emph{"Distributed Trust Based Anonymous System (DTBAS)"}.
Explicit formulas for the joint third and fourth central moments of the multinomial distribution

We give the first explicit formulas for the joint third and fourth central moments of the multinomial distribution, by differentiating the moment generating function. A general formula for the joint factorial moments was previously given in Mosimann (1962).
PENGEMBANGAN E-LEARNING GUNA MENDUKUNG PELAKSANAAN DIKLAT DI BALAI PENDIDIKAN DAN PELATIHAN KEAGAMAAN DENPASAR

This research aims to produce learning in the form of e-learning as a blended learning that is valid, practical, and effective in the execution of training preparation of learning materials in Balai Diklat Keagamaan Denpasar. This development research is based on the lack of a variety of media and learning materials that are used in the training process, the learning methods applied are still conventional, and the limited communication between lecturer with participants. The development procedure uses the ADDIE model consists of five stages: (1) analysis, (2) design, (3), development, (4) implementation, and (5) evaluation. The results showed that the teaching materials developed have met the aspects of validity, practicality, and effectiveness. The results of the validity test shows that e-learning as a blended learning is at a very good category based on test experts. E-learning also has fulfilled the practical aspect seen from the participants's response related to ease of use and interface attractiveness. The t-test results show that there is a significant difference between the mean score of learning outcomes before and after using e-learning as blended learning. Where the posttest average value is greater than the average value of pretest and has met the minimum predefined criteria that have been set. Based on this, e-learning as a blended learning is considered effective in improving learning outcomes.
UM SISTEMA DE VOTO ELETRÔNICO BASEADO EM BLOCKCHAIN

Among the various voting systems existing currently, those based on electronic voting are viewed as the most efficient ones, because they allow greater speed in tabulating results and offer minimal guarantees for validating the deposited votes.Although the current Brazilian voting system is viewed as a model for the rest of the world, some of its characteristics present room for improvements.This dissertation is about the study and implementation of an electronic voting system based on the blockchain, a decentralized, cryptographic database.This proposed system, in addition to offer even more security to the voting process, would enable more flexibility for voters to deposit and audit their votes.Being strongly based on cryptography, this system was implemented with high performance processors, such as multi-core CPUs.
Library: PRISM: Advanced Search

PRISM (formerly known as DSpace) is University of Calgary's Digital Repository used to collect, preserve and disseminate the academic works of faculty, students, and research groups.
Legal Regulation of Countering Cyberterrorism in the Context of the Fourth Industrial Revolution

The Problem of ensuring cybersecurity in the context of accelerated implementation of digital technologies in the activities of public administration and business systems is relevant. The authors show that the development and implementation of digital technologies in Russia should take into account the need to ensure national security.
Automatic Photo to Ideophone Manga Matching

Photo applications offer tools for annotation via text and stickers. Ideophones, mimetic and onomatopoeic words, which are common in graphic novels, have yet to be explored for photo annotation use. We present a method for automatic ideophone recommendation and positioning of the text on photos. These annotations are accomplished by obtaining a list of ideophones with English definitions and applying a suite of visual object detectors to the image. Next, a semantic embedding maps the visual objects to the possible relevant ideophones. Our system stands in contrast to traditional computer vision-based annotation systems, which stop at recommending object and scene-level annotation, by providing annotations that are communicative, fun, and engaging. We test these annotations in Japanese and find they carry a strong preference and increase enjoyment and sharing likelihood when compared to unannotated and object-based annotated photos.
Upaya Meningkatkan Hasil Belajar IPA Melalui Strategi Multiple Inteligences

This study is motivated by the low ability of grade IV SD Parakan students in science lessons on subject matter Force. The purpose of this study is improving the learning process and improving students' ability in science lessons on Force subject matter through applying multiple intelligence approaches. The method used was the Classroom Action Research and it was carried out in two cycles. Based on the data analysis, the ability of students after the research action increases in each cycle. The highest score changes at each stage, from 80 to 90 and finally to 95; the lowest value has increased from 45 before the action and in cycle I to 45 at the end of the second cycle. The average value also increased from the initial 63.3; to 70.5; then 75.2. While the increasing in presentation of minimal completeness criteria achievement was initially 45.2%, to 65.6%, and finally to 81.3%. The observation results show that science learning activities by using Multiple Intelligences strategy in Cycle I and Cycle II can run well. In the first cycle of the first meeting, the teacher's activity scored 14 or 67% in the good category. Teachers’ activity was increased at the next meeting, which the score is 16 with a percentage of 76% at the second and third meetings. The scoring shows that the learning given by teacher belonging to excellent category. Whereas in the second cycle, each meeting obtained a score with a very good category, namely a score of 18 or 86% in the first and second meetings, and a score of 19 with a percentage of 90% in the third meeting. From the research data obtained it was concluded that there has been an increasing in science ability of Grade IV students in Force subject matter through the using of multiple intelligence methods in SD Negeri Parakan, Pamulang District, South Tangerang City.
Eigenstructure involving the histogram for image thresholding

The idea of the proposed image thresholding scheme is simply to consider the histogram as a 2D plot rather than a 1D function. The data can now be represented as a two-row matrix. The first row is simply the grey levels of the image and the second row is the corresponding histogram values. Multiplying this matrix by its transpose will result in a power-type matrix of size 2 × 2. The best threshold is the one producing a power matrix closer to that of the original image. Many combinations of the eigenvalues are suggested. To increase the correlation with the first row of the matrix, the histogram is replaced by the cumulative histogram. It is noticed that the trace of the matrix produces the best results. Comparative results show the effectiveness of the proposed schemes.
Edge computing based incentivizing mechanism for mobile blockchain in IOT

Mining in the blockchain requires high computing power to solve the hash puzzle for example proof-of-work puzzle. It takes high cost to achieve the calculation of this problem in devices of IOT, especially the mobile devices of IOT. It consequently restricts the application of blockchain in mobile environment. However, edge computing can be utilized to solve the problem for insufficient computing power of mobile devices in IOT. Edge servers can recruit many mobile devices to contribute computing power together to mining and share the reward of mining with these recruited mobile devices. In this paper, we propose an incentivizing mechanism based on edge computing for mobile blockchain. We design a two-stage Stackelberg Game to jointly optimize the reward of edge servers and recruited mobile devices. The edge server as the leader sets the expected fee for the recruited mobile devices in Stage I. The mobile device as a follower provides its computing power to mine according to the expected fee in Stage. It proves that this game can obtain a uniqueness Nash Equilibrium solution under the same or different expected fee. In the simulation experiment, we obtain a result curve of the profit for the edge server with the different ratio between the computing power from the edge server and mobile devices. In addition, the proposed scheme has been compared with the MDG scheme for the profit of the edge server. The experimental results show that the profit of the proposed scheme is more than that of the MDG scheme under the same total computing power.
Data Driven Approach to Image, Classify and extract Seismic Discontinuities in Complex Geological Settings

Summary Automation of many geoscience interpretation tasks is a hot topic in the geoscience community. Automated fault interpretation is one of them and have been around for many years. Many attributes have been specifically designed around discontinuities and fault detection and extraction. One such attribute is fault likelihood developed by Dave Hale. Thanks to this open source research that many software vendors have incorporated this attribute and developed an end to end workflow from data conditioning to fault likelihood and fault thinning, leading to automated fault extraction. Owing to the calculation involved, the fault attributes are also calculated along the way that helps to classify the faults based on area, size, dip and azimuth. We put this method to test on couple of fields in Kingdom of Saudi Arabia and test the robustness, accuracy and efficiency brought to the automated fault interpretation workflow through this attribute. A summary of results and computation time on desktop vs clusters is also discussed for the benefit of audience.
Tvorcheskie umeniia starsheklassnikov v uchebno-issledovatel'skoi deiatel'nosti

On the basis of psycho-pedagogical literature analysis the concept of “high school pupils’ creative abilities” is concretized, its types and structure are defined; the analysis of the concept of “educational and research activity” is presented; the introduction of educational and research activities in high school age is substantiated; the role of this activity of students in the acquisition of scientific knowledge and the possibility of their creative application is revealed; the pupils’ creative abilities being formed in educational and research activity and providing its effective performance are pointed out.
متطلبات اعداد روضة ذکية بمحافظة بورسعيد لتحسين نواتج التعلم للروضات الحکومية

تهدف الدراسة الحالیة إلى معرفة متطلبات اعداد روضة ذکیة بمحافظة بورسعید لتحسین نواتج التعلم للروضات الحکومیة من خلال إعداد استبانة لمتطلبات الروضة الذکیة. وقد تکونت عینة الدراسة الحالی من (150) من االمتخصصین فی مجال تکنولوجیا التعلیم، للعام الجامعی 2019/ 2020 م، واستخدمت الباحثة استبانة لمتطلبات الروضة الذکیة (إعداد/ الباحثة). وأشارت نتائج الدراسة الحالی إلی أهمیة توافر متطلبات الروضة الذکیة واستخدام تکنولوجیا المعلومات والاتصالات فی تحسین نواتج التعلم للروضات الحکومیة.AbstractThe current research aims to know the requirements for preparing a smart kindergarten in Port Said Governorate to improve learning outcomes for government kindergartens by preparing a questionnaire for the requirements of smart kindergarten. The present research sample consisted of (150) of specialists in the field of educational technology, for the academic year 2019/2020, and the researcher used a questionnaire for the requirements of the smart kindergarten (prepared / researcher).The results of the current research indicated the importance of fulfilling the requirements of smart kindergarten and the use of information and communication technology to improve learning outcomes for government kindergartens.
Regulating Artificial Intelligence - How to De-Mystify the Alchemy of Code?

Algorithms have a profound and growing influence on our lives, but partially remain a black box to us. Keeping the risks that arise from rule-based and learning systems in check is a challenging task for both: society and the legal system. The essay undertakes the challenge to examine existing and adaptable legal solutions and to complement them with further proposals. It designs a regulatory model in four steps along the time axis: preventive regulation instruments, accompanying risk management, ex post facto protection and the vision of an algorithmic responsibility code. Together, they form a legislative blueprint to further regulate applications of artificial intelligence.
Volumetric Capture of Humans with a Single RGBD Camera via Semi-Parametric Learning

Volumetric (4D) performance capture is fundamental for AR/VR content generation. Whereas previous work in 4D performance capture has shown impressive results in studio settings, the technology is still far from being accessible to a typical consumer who, at best, might own a single RGBD sensor. Thus, in this work, we propose a method to synthesize free viewpoint renderings using a single RGBD camera. The key insight is to leverage previously seen "calibration" images of a given user to extrapolate what should be rendered in a novel viewpoint from the data available in the sensor. Given these past observations from multiple viewpoints, and the current RGBD image from a fixed view, we propose an end-to-end framework that fuses both these data sources to generate novel renderings of the performer. We demonstrate that the method can produce high fidelity images, and handle extreme changes in subject pose and camera viewpoints. We also show that the system generalizes to performers not seen in the training data. We run exhaustive experiments demonstrating the effectiveness of the proposed semi-parametric model (i.e. calibration images available to the neural network) compared to other state of the art machine learned solutions. Further, we compare the method with more traditional pipelines that employ multi-view capture. We show that our framework is able to achieve compelling results, with substantially less infrastructure than previously required.
Web-quest as a means of pedagogical stimulation of students’ positive motivation to mind work

The article is devoted to the consideration of peculiarities of the use of web-quest technology in the mathematical preparation of students for the formation of positive motivation for mental work. The structure of the web-quest is considered. It is pointed up that 4 elements must be present necessarily in every educational web-quest: introduction, assignment, execution, evaluation. The classification of all forms of web-quests is given. The main stages of working on a web-quest are stood out.
ДЕТОЦЕНТРИЧЕСКИЙ ПОДХОД КАК ГУМАНИСТИЧЕСКАЯ ПАРАДИГМА СОВРЕМЕННОГО ПСИХОЛОГИЧЕСКОГО СОПРОВОЖДЕНИЯ РАЗВИТИЯ ДЕТЕЙ С ОСОБЫМИ ОБРАЗОВАТЕЛЬНЫМИ ВОЗМОЖНОСТЯМИ

The article is devoted to the strategic and tactical tasks of the psychologist from the standpoint of the child-centric approach in the psychological and pedagogical support of the education of children with special educational opportunities.
Limiting Freedom During the Covid-19 Emergency in Italy: Short Notes on the New “Populist Rule of Law”

Abstract The implications of the severe lockdown regime introduced in Italy in the context of the Covid-19 emergency can be correctly understood only through a broader look at how the text of the provisions adopted by the government is transformed by media reporting and law enforcement practice. From such a perspective, it appears clearly that we are witnessing nothing more than the most recent segment of a populist approach to the use of legal tools, the history of which starts well before the pandemic.