Reviewerly/exHarmony huggingface dataset:
Deep Residual Flow for Novelty Detection.

The effective application of neural networks in the real-world relies on proficiently detecting out-of-distribution examples. Contemporary methods seek to model the distribution of feature activations in the training data for adequately distinguishing abnormalities, and the state-of-the-art method uses Gaussian distribution models. In this work, we present a novel approach that improves upon the state-of-the-art by leveraging an expressive density model based on normalizing flows. We introduce the residual flow, a novel flow architecture that learns the residual distribution from a base Gaussian distribution. Our model is general, and can be applied to any data that is approximately Gaussian. For out of distribution detection in image datasets, our approach provides a principled improvement over the state-of-the-art. Specifically, we demonstrate the effectiveness of our method in ResNet and DenseNet architectures trained on various image datasets. For example, on a ResNet trained on CIFAR-100 and evaluated on detection of out-of-distribution samples from the ImageNet dataset, holding the true positive rate (TPR) at $95\%$, we improve the true negative rate (TNR) from $56.7\%$ (current state-of-the-art) to $77.5\%$ (ours).
PROBLEMS OF TRAINING OF A COMPETENT TEACHER OF PHYSICS IN THE FRAMEWORK OF IMPLEMENTATION OF THE NEW SCHOOL PROJECT

The article is devoted to the research of the problems that led to the crisis in science education in general and the training of physics teachers in particular. It is emphasized that for our country the tendency to increase the humanitarian component in the education system has become harmful. Based on the analysis of the results of the introductory campaigns of the last years, it is ascertained that today there is a pronounced shift towards the specialties of humanitarian and social orientation. The opinion was expressed and substantiated that the Ministry of Education and Science of Ukraine should review the approaches to state procurement planning, which should be tailored to the needs of industries and the balance of labor resources, and not the demand of entrants. It is emphasized that the restoration and replenishment of the scientific and technical potential of Ukraine should start with giving priority to the training of physics teachers and correcting the situation with a specialty “Secondary education (physics)”, since otherwise in the near future competent teachers will not remain in secondary education institutions. Concerns have been expressed about the fact that under such conditions it will not be possible to provide specialized education, which will lead to further decline of physical and physical and technical education, and ultimately to the intellectual degeneration of our people. Priority measures for improvement of the state of preparation of the teacher of physics in Ukraine and increase of its prestige are offered, among which are highlighted such as revival of work of physical-mathematical pedagogical classes at institutions of pedagogical higher education, improvement and expansion for pupils of such classes and schools of higher education. to institutions of pedagogical higher education, renewal of the target set of students in the specialty “Secondary education (physics)”. It is noted that to prepare highly competent Ukrainian physics teachers who will be able to implement the New Ukrainian School project, it takes time and a set of activities that can be implemented only through the joint efforts of the entire teaching community. Key words: physical and physical-technical education, training of physics teacher.
KOMPARASI METODE INTERPOLASI UNTUK SISTEM PENGENALAN SEL DARAH PUTIH

The over time role of technology becomes very important. That is because the function of technology is to facilitate human work. Because human needs are increasingly complex, technological developments are created in such a way as to meet human needs. The experts in the medical field are currently very dependent on technology to do their jobs, in order to obtain effective and efficient results. Application system designed aims to help experts in the medical field to diagnose diseases through introduction to white blood cell types. The recognition system was developed using the Nearest Feature Line (NFL) method. In this NFL method, characteristic lines are formed using the method of linear interpolation, linear spline, quadratic spline, and cubic spline. Aside from introducing an introduction system, this paper also discusses comparisons between interpolation methods to form characteristic lines. The test was carried out using FTI Untar Pattern Recognition laboratory blood cell data. The test results show that the formation of characteristic lines using the linear interpolation method provides better recognition results compared to the spline interpolation method.
Hybrid cryptosystem multi-power RSA with N=P<sup>m</sup>Q and VMPC

Abstract In digital world, data and information is very valuable and much targeted by unauthorized parties. One way to secure messages is cryptography. Cryptography itself is a branch of science in concealing messages. In further development a hybrid cryptosystem was formed which combines symmetrical and asymmetric cryptography, which in this paper uses VMPC and Multi-Power.. The RSA Multi-Power algorithm is an asymmetric algorithm that is excellent at message encryption but requires a long process time because it uses very complicated calculations. While VMPC has advantages in the process with fast time and relatively small size of ciphertext. Here we have analyzed the performance of various variants of RSA that have been hybridized with VMPC and given the results.
Application of Extended Kalman Filter to Dynamic Tracking Problem in R-LATs

Abstract Many applications requiring dynamic tracking have been needed in large-scale. As a novel distributed measurement system, RLATs is presented and the key techniques are shown in detail. Because of the intrinsical drawback of distributed measurement systems, the Extend Kalman Filter approach is introduced to eliminate the tracking error and improve the tracking accuracy. State space model of RLATs are formulated, and an analytical expression for the linearized measurement function is derived. Comparison with the method of LS simulated data which presented a considerable improvement and stability in accuracy and the proposed EKF method while target’s moving speed is less than 100 mm/s.
FlowMorph - Exploring the human-material interaction in digitally augmented craftsmanship

It has been proposed that, after the internet age, we are now entering a new era of the '/Augmented Age/' (King, 2016). Physician Michio Kaku imagined the future of architects will be relying heavily on Augmented Reality technology (Kaku, 2015). Augmented reality technology is not a new technology and has been evolving rapidly. In the last three years, the technology has been applied in mainstream consumer devices (Coppens, 2017). This opened up possibilities in every aspect of our daily lives and it is expected that this will have a great impact on every field of consumer's technology in near future, including design and fabrication. What is the future of design and making? What kind of new digital fabrication paradigm will emerge from inevitable technological development? What kind of impact will this have on the built environment and industry? FlowMorph is a research project developed in the Bartlett School of Architecture, B-Pro AD with the collaboration of the authors and students as a 12 month MArch programme, we developed a unique design project trying to answer these questions which will be introduced in this paper.
EXAMINING THINK TALK WRITE (TTW) STRATEGY IN STUDENTS’ VOCABULARY MASTERY

This research aimed at finding out the effect of Think-Talk-Write (TTW) in students’ vocabulary mastery. This research was conducted in the first-grade students of Junior High School 5 Praya in the academic year 2019/2020. This research used an experimental design in which it employed two groups pre-test and post-test. The experimental group was treated by using TTW, while the control group was treated by using Acrostic strategy. The two classes were chosen as the samples in this research which consist of 46 students. In analyzing the data, researchers applied statistical analysis. The result of the research showed that there was a significant effect of Think-Talk-Write (TTW) in students’ vocabulary mastery. The finding shows that the t-test value was higher than the t-table (8.693&gt;1.680). Therefore, it comes to the conclusion that the hypothesis set is accepted (Ha).
Aggregate Signature Consensus Scheme Based on FPGA

With the rapid development of cryptocurrency, such as the Bitcoin, block chain technology, as the bottom technology of Bitcoin, has been widely concerned by researchers. Block chain has the characteristics of decentralization, anonymity and non-tampering, which realizes the transformation from social trust to machine trust. As an important part of block chain system, digital signature is relatively inefficient. For this reason, this paper proposes an aggregation signature scheme based on FPGA, which combines the aggregation signature technology with the reconfiguration of FPGA, realizes the aggregation of multiple user signatures into one signature, and has multiple ECC acceleration modules in FPGA. The efficiency of digital signature calculation is improved. Through experimental analysis and comparison, the scheme uses FPGA reconstruction and aggregate signature technology, which not only improves the computational efficiency of ECC, but also improves the efficiency of signature verification and improves the performance of block chain system.
Reality check voor de kwantitatieve Nederlandse taalkunde: laveren tussen de Scylla van het conservatisme en de Charybdis van de zelfgenoegzaamheid

In this article, we assess the merits of Digital Humanities, and argue that this approach has advanced the field of Dutch linguistics considerably, but at the same time holds some dangers and misconceptions, like (i) the assumption that the new-fangled studies clash with older, more traditional research, (ii) a conceited but unwarranted disdain for current-day non-quantitative work, (iii) the idea that the early adoption of quantitative methods in linguistics created an unbridgeable gap with its neighbouring discipline, the literary studies, and (iv) the risk of the dialectics of lead. We then detect the weak spot of the Digital Humanities approach in linguistics. Though we acknowledge that great strides are currently being made and that earlier research grappled with the issue as well, what turns out to be frus tratingly elusive is the whole field of ‘semantics’, especially given the insights from cognitive linguistics about its complicated nature, including encyclopaedic and contextual knowledge. The aporia of semantics is coped with differently in linguistics and literature. While linguistics has sought a rapprochement with the ex act sciences, it steered clear from interpretation as much as possible. The field of literary studies, by contrast, remains loyal to its original ‘humanities’ mission, but is now no longer exclusively – or primarily – driven by critically interpreting the meaning of texts as such. Instead, its focus has shifted to offering a critical investi gation of the field itself, and of society at large. Both approaches are in danger of derailing: the ‘semanticophobia’ of some linguists dismisses a real and fascinating part of language from its purview; the ‘critical discourse’ approach of some literary colleagues runs the risk of ignoring some useful text-based techniques for empir ical research. The main task of Digital Humanities, in both fields, will be to navi gate between these pitfalls.
Knowledge Mapping and Scientometric Overview on Global Blockchain Research

In the past few years, block-chain research literatures have increased rapidly, but there have been fewer attempts and efforts to map global research in block-chain related research. The main purpose of this study is to assess global progress and explore the current trends in block-chain studies. Scientific quantitative measurement methods were utilized targeting the Science Citation Index Extension (SCI-E) and Social Science Citation Index (SSCI) from the WoS database until 2018. The block-chain related literatures were investigated as a whole in this paper. This paper adopts the literature measurement method and knowledge visualization technology to clarify the status of authoritative publications in global block-chain documents. The CiteSpace software was used to conduct a research on the subject categories, author cooperation networks, national cooperation networks as well as the institutional cooperation networks. The authors of the literature and the cited references were thoroughly examined, highlighting the main aspects and providing research frontier for block-chain research.
Incremental matrix factorization for simultaneous learning from parallel data streams

Matrix factorization techniques have proven to be useful and reliable for solving largescalemachine learning problems. The data sparsity and cold-start problems found inreal-world applications, such as recommender systems, can be indirectly alleviated byconsidering multiple heterogeneous data sources, while at the same time the successfulutilization of data fusion resolves in a higher predictive accuracy. However, incrementallyhandling models upon multiple data streams remains a crucial and only partiallysolved problem.This work presents one way of fusing multiple data streams through matrix factorization.Our proposed method models heterogeneous and asynchronous data streamsand provides predictions in real time. As a result of incremental updating, the proposedmethod successfully adapts to changes in data concepts, while application of data fusionimproves prediction accuracy and reduces effects of the cold-start problem. Usingthe proposed methodology we develop a streaming recommender system and show howprediction accuracy can be substantially increased by considering multiple data sources.Nevertheless, evaluating data fusion, recommender and other incremental algorithms,such as our presented method, is inherently difficult due to the scarcity of obtainabledata sources. In order to address this problem, we conjointly propose a synthetic datagenerator, capable of generating multiple temporal and inter-dependent data streams ofrelational data. Data streams generated in this way successfully mimic real-life datasetsin terms of statistical data properties and comparable performance of various machinelearning models.Proposed methodologies help in development of solutions for collective modeling ofstreaming data in real-time. Apart from recommender systems, the versatility of matrixfactorization further allows for its use in solving several other machine learning problems,such as dimensionality reduction, clustering and classification.
Unsupervised Monocular Depth Estimation with Encoder-decoder Network*

Although fully supervised learning methods could achieve good results for monocular depth estimation, it is very expensive to obtain ground truth depth data for training. In this paper, an encoder-decoder network is proposed to estimate monocular depth with unsupervised learning. During training, this network is able to enhance the weight of the effective features in the image by learning. Therefore, the encoder is able to extract more effective features and the decoder generates more targeted results. Compared to supervised learning, the proposed network is trained by stereo pairs and image reconstruction error, rather than ground truth depth. The proposed network achieves competitive results for monocular depth estimation on the KITTI driving dataset.
Realm Crossover for SASL and GSS-API via Diameter

SASL and GSS-API are used for authentication in many applicationprotocols. This specification extends them to allow credentials of ahome realm to be used against external services. To this end, itintroduces end-to-end encryption for SASL that is safe to relay to theclient's home realm.
An Analytical Survey on Data Access Control Mechanism in Cloud using Blockchain

Cloud storage is known for its huge infrastructure, this property of the cloud inevitably invites attackers. However, to overcome this data stored in encrypted form, this security measure is not enough to handle the issue of data privacy. The other threat to the data arises during the process of accessing these data through various forms like by auditors, other users, data owners and some time by cloud owner itself. To handle these issues quite effectively strict access control mechanism is deployed at cloud end. However, this is not enough to make sure the data is safe, as now a days data is accessed in multiple tiers by the users, so the block chain is used to effectively to monitor the data sharing between the owners and users. This paper working towards the analysis of the attacks and handling of these attacks using block chain. As the bit towards this paper also proposed to handle data integrity effectively by the usage of block chain and bilinear pairing mechanism together to provide the best solution for data access control mechanism incloud inevitably. Rushabh Rajendra Desarda | Nishant Ganesh Chavan | Amit Gunaji Chaure | Pankaj Ramanlal Gandhi | Prof. S. E. Ingale An Analytical Survey on Data Access Control Mechanism in Cloud using Blockchain Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29724.pdf
Analisis Kebiasaan Konsumen Menggunakan Asosition Rule Metode Apriori Pada Central Retail X

The sustainability of a company will not be separated from the role of consumers in conductingtransactions. In fact, a consumer has different behaviour and character, therefore as a company owner mustbe able to analysis the patterns or habits of consumers in making transactions. This also happens in theretail center X, which has problems in the sales process, such as products running out of stock and unsoldproducts and the most popular products and products that are not in demand by consumers. Therefore weneed an analysis of consumer habits in conducting transactions. The method of association rule with apriori algorithm is able to be applied well in the analysis of the habits of consumer transactions in thecentral retail X. The results of the calculation obtained an average percentage of the value of support 33%40%and the value of confidence 43%-80%. The results of applying the association rule method with apriori algorithm can help recommend central retail X owners in structuring product and determine strategicsteps in increasing sales, such as providing discounts or promos for certain products.Keywords: Analysis, Consumer, Association Rule, Apriori, Retail.
STUDENTS’ CLIP THINKING: A PROBLEM APPROACH

Purpose: The aim of the paper is to discuss the phenomenon of students’ clip thinking, its roots and ways of handling the problem in a higher education establishment. The research reflects concerns of domestic and foreign scholars and educational professionals about the students having the mosaic worldview devoid of logical reasoning rather than the integral picture of the world. Methodology: The methodological basis of the study is the data of the general and special scientific methodology. Dialectics has determined the reasoning. The philosophical principle of the universal connection of objects and phenomena of objective reality, the principle of determinism and systematicity are taken as a basis as well. Result: The research has sparked the students’ interest in the problem of clip thinking under study, the reasons for its occurrence, and ways to handle it. Although most students have a clear idea of the term “clip thinking”, and, therefore, succeed in analysing the reasons for its development, few of them are able to practise what they intuitively (and correctly) regard as appropriate. As seen from the research, all the students involved in the experiment need a closer communication with the university professors and a greater engagement in the academic and extra-curricular activities in order to develop integral thinking, imagination, memory, oratorical skills and many others essential for future professionals. Application: The research can be useful to university and school professionals, scholars and students.
What Do Students Need Regarding Layout and Compatibility of Learning Materials in Chamilo Platform

This article is the chunk of the research regarding learning object innovation in Chamilo Platform. One of the activities is organizing preliminary test field to users. The objective of writing the article is clarifying students’ response in learning the materials through Chamilo in term of layout and compatibility. The product development method on the research is Design-Based Research. The research involved 38 students of 4 th semester who had already enrolled face-to-face class as the sample. The students were given opportunity to study the pre-developed online materials in Chamilo for a week. Later, they were expected to deliver feedback regarding material, message design, and the access easiness. The result of the test shown that: 1) Layout is more comfortable in portrait than landscape; 2) 78% response pointed on learning message compatibility aspect when it was implemented in different media: computer (or notebook) and mobile phone. Easy and interesting materials became difficult when the message layout did not fit multiple media while students had tendency to access the material through mobile phone than computer. Thus, this article would recommend the message design for online learning tools while consider the message compatibility for different devices that used by students. Keywords: chamilo platform, learning materials, millennial,  online learning.
LibGuides: Database Searching: Selecting a Database

Learn how to select a library database for your research topic and how to use the databases to find sources on your topic.
Cloud Euphoria✿: A post-analysis on the networked effects of emotions

Abstract Nowadays we live in a maze of perplexity and contradiction, treating feelings as data, like augmenting them, compress them, duplicating them and erasing them. Data like 'happiness' or 'sadness' are becoming abstractions because there is never a single moment when we can explicitly feel one or another. Let us click into these 'files' and explore these techno-cultural forms of communicational imperfection.