Reviewerly/exHarmony huggingface dataset:
Identification and Extraction of Circular Markers in 3D Reconstruction

This paper presents a method for the identification and location of circular markers in 3D reconstruction. The input image is processed with gray scale and gaussian filter to remove noise interference and improve the accuracy of edge detection. The size and direction of the gradient of the image were calculated to obtain the edge features of the circular marker, and the circle degree of the closed edge was judged, and the center of the marker was obtained by fitting the edge features with the ellipse of the least square method. Hu moment similarity of each marker was obtained, and the non-marker was deleted and the real marker was retained by similarity judgment. Experiments show that the algorithm has good robustness, high precision, can effectively reduce the probability of false detection, and has high accuracy in complex environments.
Coronavirus public sentiment analysis with BERT deep learning

Microblog has become a central platform where people express their thoughts and opinions toward public events in China. With the sudden outbreak of coronavirus, the posts related to coronavirus are ...
EVALUASI PROGRAM PELATIHAN PENGOLAHAN BAHAN PUSTAKA DI PUSDIKLAT PERPUSTAKAAN NASIONAL RI

This research was intended to see how the Kirkpatrick four level evaluation model is applied in the Library Material Processing training program organized by the Education and Training center of National Library of Indonesia. This evaluation research uses the Kirkpatrick evaluation model (Reaction, Learning, Behavior, Result). The subject of this research is training organizers, training instructors and training participants in the processing of library materials. Data collection techniques in this study used observation, documentation and interviews. Data validity test is done using triangulation of sources and methods.&#x0D; The results of this study show that the implementation of the Library Material Processing Training program has not gone well based on the aspect that being evaluated. 1) In the Reaction evaluation aspect, the implementation of training at this stage goes well. It can be seen from the results of the evaluator's last evaluation score which has a score of 93.88 or very satisfied and the last evaluation score of the instructor who has a score of 90.66 or very satisfied. 2) In the aspect of learning evaluation, the training process goes well according to the plan that was made before. This can be seen from the final score of all participants who have a score above the least limit. 3) in the Behavior aspect, the training organizers have not carried out observations of the participants' behavior after the training. 4) Then in the Result aspect, the training organizers also have not carried out observations on the participants' contributions or the use of participant's knowledge of the library performance.&#x0D; &#x0D; Keywords: Program Evaluation, Library Material Processing Training, Kirkpatrick Evaluation Model
Interpretation of crypto-assets and taxation specificity of digital assets in developed countries and Russia

The article explores various types of crypto-assets and justification of differentiated regime for their regulations. The purpose of the article is to determine the main economic and legal approaches of interpreting crypto-assets and identify the features of taxation of various types of crypto-assets in developed countries and Russia. Drawing on economic and functional features of crypto-assets, the study offers the classification of virtual assets. Having analyzed various approaches to crypto-assets tax regulation in the UK, Switzerland and Singapore, the authors determine the specificity of crypto-assets taxation and offer recommendations for crypto-assets taxation in Russia. The paper concludes that in countries where regulatory authorities make a clear distinction between different types of crypto-assets the taxation of virtual assets is also differentiated. A differentiated approach to taxation of crypto assets in Russia seems to be most promising since it encourages the development of certain segments of crypto asset market and offers a clearer mechanism for tax control over the turnover of crypto assets in the country.
Automatic Brain Tissue Segmentation on TOF MRA Image

For the segmentation of brain vessels from MRA images, brain tissue is used in the head, eye, skull, etc. must be separated from the structures. For this reason, studies are carried out for the segmentation of brain tissue. In this study, the method that automatically segregates brain tissue from magnetic resonance angiography images taken with time of flight (TOF) technique is presented. The method in the study consists of five steps. First of all, the tip contrast values in the image are filtered by anisotropic diffusion filtering method. Parameters of anisotropic diffusion method are determined automatically by the natural image quality evaluator method. Sudden density transitions are detected by applying LoG edge detection filter on the filtered image. It is made ready for image analysis by applying etching on the image with density transitions. According to the conditions determined in image analysis, brain tissue is obtained separated from other head structures. As a result of this study, an easy-to-apply, fast-delivering, high-accuracy automatic algorithm has been introduced.
Robust User Watching System using Multiple Technologies

In the super-aged society, the number of elderly people who go missing due to dementia is increasing year by year. The police and local governments are speeding up efforts for early detection of the missing people, because cases of late detection and death are increasing. There are systems to collect location information by having elderly people carry smartphones, etc., but they don't always carry these devices with them. Therefore, the mechanisms which matches and tracks the person from the images of the security cameras are under consideration. There are methods using face information as person matching technologies, but many countries have started to avoid using the information from the viewpoint of privacy. Recently, as matching technologies capable of privacy protection, methods using gait information and ear information is noticed. However, accuracy degradation occurs in the matching technology using gait information, because there are many cases in which the foot is hidden in the image of actual security camera. Also, since the ear image area is smaller than the gait image area and the image quality tends to deteriorate, matching may fail. Therefore, the matching technology with high accuracy even with the images in which environmental change and image quality degradation occur is desired. In this paper, we propose a method which can match person more accurately than the conventional method by using multiple information such as gait and ear from the images of upper body only which are simulated occlusion of security cameras. And, we report that proposed method achieved 70.7% accuracy as a result of evaluating using gait images of the elderly people with different date, and the accuracy is improved than the conventional method using each information independently. By making the proposed method more robust, it can be used to search the elderly people while protecting their privacy using images from security cameras.
Reading on paper and screens? Advantages, disadvantages and digital inequality

Digitalization of all spheres of society has brought significant changes in the practices and forms of reading in the XXI century. Along with the traditional (analog, reading from a paper), a new format of reading has appeared and widespread – digital format (computer, electronic, from screen). It changes the nature of the reader's interaction with the text, has potential opportunities (social reading) and risks (digital inequality). In this regard, the role of libraries (as well as cultural and educational institutions) in enculturation society to the new digital literacy and elimination of negative consequences of digital inequality is increasing. The purpose of the article is to study the specifics of the development of reading in the modern world, to ground characteristic features of reading from the paper and the screen. For this purpose, various points of view of scientists on the originality of reading activities in various formats, the effectiveness of perception of a printed and an electronic text are given; the results of research projects conducted in many countries of the world to identify the characteristics, opportunities, risks and prospects for the development of traditional and digital reading are analyzed and summarized. It is concluded that there have emerged and continue to evolve screen reading practices. Reading in the digital environment as a new way of contacts via electronic texts dynamically changes the communication environment, speeding up and simplifying consumer access to information, has many opportunities and advantages, and transforms reading skills and habits of society. Moreover, at a new technological stage of development, it revives social reading, intensifies digital inequality, leading to a secondary mental-­cognitive digital gap, and modifies personal reading experience of contemporaries.
A Unifying Approach for Nonmonotonic S4F, (Reflexive) Autoepistemic Logic, and Answer Set Programming

This paper presents a general strategy, bringing together some major types of nonmonotonic reasoning under a monotonic bimodal setting. Such formalisms are also of interest to the fields of knowledge representation and declarative programming. We exemplify the methodology, capturing minimal model reasoning that underlies nonmonotonicity over S4F first, but then we also show how to apply the technique to other nonmonotonic logics respectively based on the modal logics KD45 and SW5. We naturally succeed it, by modifying only the axioms of the underlying modal logic and show that it successfully works. The last two formalisms are also known as autoepistemic logic (AEL) and its reflexive extension (RAEL) in the given order: AEL is an important form of nonmonotonic reasoning, introduced by Robert C. Moore in order to allow an agent to reason about his own knowledge. Equilibrium logic (EL) is a general-purpose nonmonotonic reasoning formalism, proposed more recently by David Pearce as a semantical framework for answer set programming (ASP). The latter is an efficient declarative problem solving approach with lots of applications to science and technology. Fariñas et al. have embedded EL (and so ASP) into a monotonic bimodal logic. We take this work as an initiative and successfully apply a similar methodology to closely aligned nonmonotonic modal logics. We finally discuss the potential capability to subsume the epistemic extensions of ASP within our unified paradigm.
Improving coverage method of autonomous drones for environmentalmonitoring

With the rapid developments of unmanned aerial vehicles (UAVs), usage of UAVs is increasing to bring autonomy for complicated processes such as environmental monitoring.Because of the complexity of the problem, environmental monitoring tasks are highly demanding in terms of time and resources.To reduce expensive costs of operations, improvements on autonomous observation capabilities has a key role.In this work, we offer coverage improvements for our autonomous environmental monitoring system.We compared different path planning approaches to find out the optimum path planning solution.Simulation results showed that required task execution time and required resources are decreased by usage of improved decomposition of the coverage field.
New Perspectives for NoSQL Database Design: A Systematic Review

The use of NoSQL databases has increasingly become a trend in software development, mainly due to the expansion of Web 2.0 systems. However, there is not yet a standard to be used for the design of this type of database even with the growing number of studies related to this subject. This paper presents a systematic review looking for new trends regarding strategies used in this context. The result of this process demonstrates that there are still few methodologies for the NoSQL database design and there are no design methodologies capable of working with polyglot persistence.
Real-Valued Logics for Typological Universals: Framework and Application

This paper proposes a framework for the expression of typological statements which uses realvalued logics to capture the empirical truth value (truth degree) of a formula on a given data source, e.g. a collection of multilingual treebanks with comparable annotation.The formulae can be arbitrarily complex expressions of propositional logic.To illustrate the usefulness of such a framework, we present experiments on the Universal Dependencies treebanks for two use cases: (i) empirical (re-)evaluation of established formulae against the spectrum of available treebanks and (ii) evaluating new formulae (i.e.potential candidates for universals) generated by a search algorithm.
Gabor systems on positive half line via Walsh-Fourier transform

Gabor systems play a vital role not only in modern harmonic analysis but also in several fields of applied mathematics, for instances, detection of chirps, or image processing. In this paper, we investigate Gabor systems on positive half line via Walsh-Fourier transform. We provide the complete characterization of orthogonal Gabor systems on positive half line. Furthermore, we provide the characterization of tight frames and orthonormal bases of Gabor systems on positive half line in Fourier domain.
Design and Implementation of Efficient RGB to Gray scale Converter Architectures Using Reversible Logic

Reversible logic is considered to be a major promising alternative to traditional digital logic circuits. It eliminates the possibility of information loss and makes the system run in the backward direction there by allowing the recovery of the inputs from the generated outputs. Converting an image from RGB to gray scale is crucial for majority of the image and video processing applications and also various computer vision applications as they reduce the computational complexity, storage space and increase the system speed. In this paper we have proposed three efficient reversible logic based schemes for the implementation of the color space converter units. We have implemented the RGB to gray scale converter units using three different techniques namely average method, desaturation and luminosity methods. The implementation of the proposed design and its functionality verification was done on XILINX 14.7 ISE and using Verilog HDL. The proposed design finds applications in many of the fields including image processing, video processing and high speed low power digital signal processing applications as well as computer vision applications like face & gesture recognition, object detection, traffic monitoring systems and surveillance systems.
What Role Do Social Media Play for Robo-Advisors?

Looking at the current number of users, it becomes clear that social media today play an important role both privately and professionally.
TRANSFORMING SOUTH AFRICA’S UNIVERSITIES OF TECHNOLOGY: A ROADMAP THROUGH 4IR LENSES

Since their birth in the 6th century, universities have undergone different forms of transformations, especially of structural, ideological, and epistemological nature. Recently, the emergence of the fourth industrial revolution (4IR) has triggered a wave of such transformations and just like other industrial revolutions, university management ought to be cautious as such transformations could exacerbate existing inequalities between the rich and the poor students. To this end, a clear roadmap for such a transformation becomes critical. This is the contribution of this paper. We achieve this through a bibliometric analysis of the state of scientific research into the ‘university transformation’ topic, with a special focus on South Africa’s (RSA) context. The content of the identified scientific publications on RSA was further subjected to thematic analysis leading to the revelation that decolonisation, community engagement and structural transformation, are the main research themes. It also emerges that RSA universities have not embraced 4IR as a lens through which to pursue transformation. On the other hand, the RSA government launched the project: “Transformation at Public Universities” during the 2017/18 planning year. Subsequently, all universities in the country adopted and rolled out a customised transformation agenda. Among these universities, are the six universities of technology (UoTs), which, for historical reasons, the transformation project presents unique challenges and opportunities. Created slightly after the millennium, UoTs are still seen as critical role players in the third mission of universities, that of “achieving economic growth and social progress”. These findings, as wells as the existence of systemic exclusion, marginalisation, and discrimination (especially along racial lines) in RSA universities, defines our proposed roadmap. Using one of the UoTs and Massive Open Online Courses (MOOCs) as the reference, the proposed university transformation roadmap is supported by empirical data on the assessment of the readiness of students to adopt 4IR technologies.
Korean-to-Japanese Neural Machine Translation System using Hanja Information

In this paper, we describe our TMU neural machine translation (NMT) system submitted for the Patent task (Korean→Japanese) of the 7th Workshop on Asian Translation (WAT 2020, Nakazawa et al., 2020). We propose a novel method to train a Korean-to-Japanese translation model. Specifically, we focus on the vocabulary overlap of Korean Hanja words and Japanese Kanji words, and propose strategies to leverage Hanja information. Our experiment shows that Hanja information is effective within a specific domain, leading to an improvement in the BLEU scores by +1.09 points compared to the baseline.
Classification of Malignant Lymphoma Types Using Convolutional Neural Network

In this study, it is intended to increase the clas- sification accuracy results of malignant lymphoma images by evaluating spatial relations. As a first step, convolutional neural network (CNN) based features are extracted in the original RGB color space of digital histopathalogical images. Classification models of each feature vectors are obtained by employing CNN, support vector machines (SVM) and random forest (RF) methods. For comparison purposes, the classification accuracy results obtained from supervised learning methods are presented in the experimental results section.
Increasing the Trustworthiness of Deep Neural Networks via Accuracy Monitoring.

Inference accuracy of deep neural networks (DNNs) is a crucial performance metric, but can vary greatly in practice subject to actual test datasets and is typically unknown due to the lack of ground truth labels. This has raised significant concerns with trustworthiness of DNNs, especially in safety-critical applications. In this paper, we address trustworthiness of DNNs by using post-hoc processing to monitor the true inference accuracy on a user's dataset. Concretely, we propose a neural network-based accuracy monitor model, which only takes the deployed DNN's softmax probability output as its input and directly predicts if the DNN's prediction result is correct or not, thus leading to an estimate of the true inference accuracy. The accuracy monitor model can be pre-trained on a dataset relevant to the target application of interest, and only needs to actively label a small portion (1% in our experiments) of the user's dataset for model transfer. For estimation robustness, we further employ an ensemble of monitor models based on the Monte-Carlo dropout method. We evaluate our approach on different deployed DNN models for image classification and traffic sign detection over multiple datasets (including adversarial samples). The result shows that our accuracy monitor model provides a close-to-true accuracy estimation and outperforms the existing baseline methods.
Using Game Theory in Public Domains: The Potential and Limitations of Security Games

Abstract Since its origins, when it was mainly connected to the field of economics, game theory has brought important theoretic insights into many domains. Besides biology, philosophy or computer science, its findings have been applied to various fields of public policy. One specific area of public policy is that of security. Within the last two decades we have been witnesses to a significant increase in efforts to model security issues using tools of game theory and to derive political implications. The paper deals with the model of a Stackelberg security game and its real-world applications in security domains. The main aim and purpose of the paper is to provide a survey of selected cases of real-world deployed applications of the game-theoretic Stackelberg model in the area of public security and, based on the literature analysis, to discuss the potential and limitations of the model for policy- and decision-makers that are dealing with security measures on various governmental levels. Existing cases clearly indicate that the model can contribute to a better design and implementation of the security policy and help implement a better allocation of resources and thus potentially improve the effectiveness of security measures. On the other hand, the paper also discusses some limitations and potential future adjustments of the model together with points for further research.
Penerapan Algoritma C4.5 Dalam Meningkatkan Kemampuan Bahasa Inggris Pada Mahasiswa

In this world, many languages ??from other countries can be used as a communication tool. One of them is English. Students who have education must know that learning English is very much needed. Because nobody knows what will happen in the years to come. It could be one factor to get a job the next few years is our expertise in speaking English. English is a global language used by people to communicate with other people. On this occasion, researchers conducted research to determine what factors can improve students' ability to speak English. To complete this research, researchers resolve by applying the existing algorithm in data mining, namely C4.5 Algorithm. The result of this research can be concluded that the factors that influence to improve students’s ability in English are hearing from the environment. This research has goals is to motivating student in improving their ability of English. &#x0D; &#x0D; Keywords: c4.5 algorithm, English, data mining, ability, improving
Action Modelling for Interaction and Analysis in Smart Sports and Physical Education

This paper briefly overviews the first workshop on Action Modelling for Interaction and Analysis in Smart Sports and Physical Education (MAIStroPE). It focuses on the main aspects intended to be discussed in the workshop reflecting the main scope of the papers presented during the meeting. The MAIStroPE 2020 workshop is held in conjunction with the 22nd ACM International Conference on Mulitmodal Interaction (ICMI 2020) taking place in Utrecht, the Netherlands, in October 2020.
Developing of NbN films for superconducting microstrip single-photon detector

Abstract We optimized NbN films on a Si substrate with a buffer SiO 2 layer to produce superconducting microstrip single-photon detectors with saturated dependence of quantum efficiency (QE) versus normalized bias current. We varied thickness of films and observed the maximum QE saturation for device based on the thinner film with the lowest ratio R S 300 / R S 20 .