Reviewerly/exHarmony huggingface dataset:
CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing

In this work we propose a capsule-based approach for semi-supervised video object segmentation. Current video object segmentation methods are frame-based and often require optical flow to capture temporal consistency across frames which can be difficult to compute. To this end, we propose a video based capsule network, CapsuleVOS, which can segment several frames at once conditioned on a reference frame and segmentation mask. This conditioning is performed through a novel routing algorithm for attention-based efficient capsule selection. We address two challenging issues in video object segmentation: 1) segmentation of small objects and 2) occlusion of objects across time. The issue of segmenting small objects is addressed with a zooming module which allows the network to process small spatial regions of the video. Apart from this, the framework utilizes a novel memory module based on recurrent networks which helps in tracking objects when they move out of frame or are occluded. The network is trained end-to-end and we demonstrate its effectiveness on two benchmark video object segmentation datasets; it outperforms current offline approaches on the Youtube-VOS dataset while having a run-time that is almost twice as fast as competing methods. The code is publicly available at this https URL.
Graph Neural Networks Exponentially Lose Expressive Power for Node Classification

Graph Neural Networks (graph NNs) are a promising deep learning approach for analyzing graph-structured data. However, it is known that they do not improve (or sometimes worsen) their predictive performance as we pile up many layers and add non-lineality. To tackle this problem, we investigate the expressive power of graph NNs via their asymptotic behaviors as the layer size tends to infinity. Our strategy is to generalize the forward propagation of a Graph Convolutional Network (GCN), which is a popular graph NN variant, as a specific dynamical system. In the case of a GCN, we show that when its weights satisfy the conditions determined by the spectra of the (augmented) normalized Laplacian, its output exponentially approaches the set of signals that carry information of the connected components and node degrees only for distinguishing nodes. Our theory enables us to relate the expressive power of GCNs with the topological information of the underlying graphs inherent in the graph spectra. To demonstrate this, we characterize the asymptotic behavior of GCNs on the Erdős -- Rényi graph. We show that when the Erdős -- Rényi graph is sufficiently dense and large, a broad range of GCNs on it suffers from the "information loss" in the limit of infinite layers with high probability. Based on the theory, we provide a principled guideline for weight normalization of graph NNs. We experimentally confirm that the proposed weight scaling enhances the predictive performance of GCNs in real data. Code is available at https://github.com/delta2323/gnn-asymptotics.
Research on Blockchain: A Descriptive Survey of the Literature

Distributed ledger technologies, and particularly blockchain, have attracted significant attention recently and we believe that it is right time to look back the literature and digest the accumulated knowledge. The purpose of this study is to contribute to the existing knowledge of blockchain technology by surveying the stock of research about this newly rising technology. We conducted a descriptive analysis of current academic and business research on blockchain technology and categorized the studies according to source, field, approach, geography, affiliation, and cryptocurrency-focus. We accompanied this with a global patent publication analysis and presented our insights and takeaways from our analyses.
ANALYSIS OF JAVANESE LANGUAGE VOCABULARY SKILL FOR ELEMENTARY SCHOOL STUDENTS IN KEBUMEN DISTRICT

&lt;em&gt;Students are more proficient in foreign languages and Indonesian, this can be seen from everyday conversations that rarely use Javanese. This study aims to determine the vocabulary mastery of Javanese language in elementary school students. This research method uses qualitative descriptive research method. The subjects of this study were the fifth grade students of Kutosari 7 State Elementary School and Pekunden Elementary School. Data collection was carried out using questionnaire instruments and tests in the form of student worksheets. The results of this study indicate that elementary school students lack mastery of Javanese language.&lt;/em&gt;
Vietnamese Document Classification Using Hierarchical Attention Networks

Automatic document classification is considered to be an important part of managing and processing document in digital form, which is increasing. While there are a number of studies addressing the problem of English document classification, there are few studies that deal with the problem of Vietnamese document classification. In this paper, we propose to employ a hierarchical attention networks (HAN) for Vietnamese document classification. The HAN network has the two-level architecture with attention mechanisms applied to the word level and sentence level from which it reflects the hierarchical structure of the document. Experimental results are conducted on the Vietnamese news Database which is collected from the Vietnamese news Web sites. The results show that our proposed method is promising in the Vietnamese document classification problem.
Performance of XMPP-Based Gateway for IoT Device Communication Services

This study examines the performance of a communication gateway for IoT devices by utilizing the XMPP protocol so that these devices can be connected and communicate using the Internet. The sensor nodes, which are IoT devices, were implemented using NodeMCU connected to the DHT11 sensor module and LED lights to simulate the incoming data. Sensor nodes can communicate using the XMPP protocol gateway and process the request-response data. Gateway data transmission performance with size variations from 10-100 MB gets an average delay time of 9.3 ms, an average jitter of 0.00178 ms, and an average throughput of 161.4 kbps. The CPU usage parameter has an average increase of 12%, and memory usage tends to be constant when data transmission occurs.
Gaussian Mixture Clustering Using Relative Tests of Fit

We consider clustering based on significance tests for Gaussian Mixture Models (GMMs). Our starting point is the SigClust method developed by Liu et al. (2008), which introduces a test based on the k-means objective (with k = 2) to decide whether the data should be split into two clusters. When applied recursively, this test yields a method for hierarchical clustering that is equipped with a significance guarantee. We study the limiting distribution and power of this approach in some examples and show that there are large regions of the parameter space where the power is low. We then introduce a new test based on the idea of relative fit. Unlike prior work, we test for whether a mixture of Gaussians provides a better fit relative to a single Gaussian, without assuming that either model is correct. The proposed test has a simple critical value and provides provable error control. One version of our test provides exact, finite sample control of the type I error. We show how our tests can be used for hierarchical clustering as well as in a sequential manner for model selection. We conclude with an extensive simulation study and a cluster analysis of a gene expression dataset.
READ ALOUD: A LITERACY ACTIVITY IN ELEMENTARY SCHOOL

Reading literacy is the main key on develop knowledge. Reading literacy in elementary schools was developed through the implementation of the school literacy movement. The literacy activities are carried out as evidence of the implementation of the school literacy movement. This study aims to describe the implementation of reading literacy activity and read aloud in elementary schools. The research method used was descriptive qualitative through data collection based on a questionnaire and documentation study at ten elementary schools in Majalengka. The results show that literacy activities have been implemented in primary schools, although they have not been routinely carried out. Reading literacy methods used include read aloud, review, alphabetical methods, and reading comprehension. There are schools that have used read aloud as an effort to increase the reading literacy of elementary school students. Generally teachers in schools do not yet know the read aloud and its implementation. Training is needed for teachers to developing literacy activities in primary schools, so that could optimizing literacy activities through the use of various reading strategies.
Bottleneck-Aware Task Scheduling Based on Per-Stage and Multi-ML Profiling

In distributed computing clusters, assigning tasks and jobs to nodes that could lead to bottlenecks is detrimental to performance. Recent research has made extensive use of machine learning techniques to profile workloads, in order to predict their performance and schedule tasks to mitigate bottlenecks. However, those solutions take the entire workload as a single event, profiling at a coarse grained level and resulting in losses to model accuracy that limit the power of bottleneck detection to further improve on task allocation and cluster performance. Popular data analytics frameworks such as Spark utilize directed acyclic graphs to break down jobs into several smaller components such as stages, which allows for finer granularity for profiling. In this paper, we propose and develop Gargalo, a new bottleneck aware scheduler, that leverages a fine-grained, per-stage multi-machine learning profiling. As such we can find better model fitting for each stage of the job execution, and give the scheduler more accurate information to assign tasks to nodes. We leverage the use of multiple machine learning techniques for modeling performance and through a consensus we can combine the results for increased accuracy in each step. Our experiments with a Spark implementation, utilizing several popular benchmarking workloads, show that Gargalo improves speedup by up to 81% over the state-of-the-art bottleneck aware scheduler, 164% over the default speculation mechanism, and accuracy of up to 97% in predicting bottleneck detection. Gargalo is robust across different scenarios.
Silas: High Performance, Explainable and Verifiable Machine Learning

This paper introduces a new classification tool named Silas, which is built to provide a more transparent and dependable data analytics service. A focus of Silas is on providing a formal foundation of decision trees in order to support logical analysis and verification of learned prediction models. This paper describes the distinct features of Silas: The Model Audit module formally verifies the prediction model against user specifications, the Enforcement Learning module trains prediction models that are guaranteed correct, the Model Insight and Prediction Insight modules reason about the prediction model and explain the decision-making of predictions. We also discuss implementation details ranging from programming paradigm to memory management that help achieve high-performance computation.
Dynamic Means Of Graphical Clarity

For the formation of students metadisciplinary competencies and, first of all, universal educational skills of graphic clarity, graphic visualization tools are used. Dynamic means of graphic visualization are graphic objects capable of interactive transformation to obtain the most favorable conditions for the observation of physical phenomena and the study of physical laws. Working with ready-made means of graphic visualization - reading and analysis – is a kind of analytical activity, the results of which are allocation from the graphic object of all the essential information on the subject matter (text, question, task, etc.). Work on creation of means of graphic visualization – construction and representation – forms a type of design activity, which results in allocation of the essential properties from the subject matter and the method of coding (tables, schemes or graphics, etc.). The article provides examples of dynamic graphical visualization tools developed by the authors and built in the Geogebra multi-system. Dynamic means of graphic visualization "Collecting lens" and "Scattering lens" can be used at all stages of the process of teaching physics, by conducting a virtual experimental study. Design and research work on the introduction of dynamic graphic visualization tools was carried out in secondary educational institutions of Moscow on the basis of the instrumental capabilities of the platform IRBIS: ActivInspire – Studio, which allowed the widest possible dissemination of methodological experience in educational practice.
Biochemistry Procedure-oriented Ontology: A Case Study

Ontologies must provide the entities, concepts, and relations required by the domain being represented. The domain of interest in this paper is the biochemistry experimental procedure. The ontology language being used is OWL-DL. OWL-DL was adopted due to its well-balanced flexibility among expressiveness (e.g., class description, cardinality restriction, etc.), completeness, and decidability. These procedures are composed of procedure steps which can be represented as sequences. Sequences are composed of totally ordered, partially ordered, and alternative subsequences. Subsequences can be represented with two relations, directlyFollows and directlyPrecedes that are used to represent sequences. Alternative subsequences can be generated by composing a oneOf function in OWL-DL, referred to it as optionalStepOf in this work, which is a simple generalization of exclusiveOR. Alkaline Agarose Gel Electrophoresis, a biochemistry procedure, is described and examples of these subsequences are provided.
Evaluation and Protection of Library Collections with Heritage Value. Establishing Ante-Digitization and Post-Digitization Measures

In this article, the authors present, on the basis of the scientific arguments obtained through laboratory experiments, some pertinent aspects regarding: the evaluation and preservation of the digitized collections; presentation of conditions for the digitization of valuable library documents; presentation of ante- and post-digitization measures for library collections that are subject to digitization. This scientific approach is designed to preserve digitized libraries, collections and documents, being an essential scientific activity that takes place in parallel with the conservation of information from digitized products.
Concept Of Research Training Of Technical Universities Students

The relevance of the problem is due to the discrepancy between the competencies acquired by technical universities students in the process of training, the increasing requirements of employers, high-tech industries, designing organizations. The aim of the study is to develop and implement the concept of research training of technical universities students. On the basis of the analysis, the authors systemized and developed the existing scientific and pedagogical approaches to solving the problem. They also identified the main approaches and principles considered as methodological bases in the process of creating the concept of research training of technical universities students. The concept is presented as a system of provisions, which provides for the application of a program-targeted approach to the quality management of education, taking into account the employers’ requirements to the level of graduates’ readiness for research activities; specific features of research training and their impact on the formation of new didactics of a technical university in order to implement the requirements of educational and professional standards. The concept defines the need to monitor the quality of education, including the students’ research competence formation. Empirical methods allowed to determine the level of technical universities students’ research competence formation at all the stages of experimental work. To interpret the results of the experiment, the methods of mathematical statistics were used: they allowed to prove their reliability and the research training concept effectiveness. The materials of the paper are of practical importance for the teaching staff of technical universities.
BUZz: BUffer Zones for defending adversarial examples in image classification

We propose a novel defense against all existing gradient based adversarial attacks on deep neural networks for image classification problems. Our defense is based on a combination of deep neural networks and simple image transformations. While straightforward in implementation, this defense yields a unique security property which we term buffer zones. We argue that our defense based on buffer zones offers significant improvements over state-of-the-art defenses. We are able to achieve this improvement even when the adversary has access to the {\em entire} original training data set and unlimited query access to the defense. We verify our claim through experimentation using Fashion-MNIST and CIFAR-10: We demonstrate $&lt;11\%$ attack success rate -- significantly lower than what other well-known state-of-the-art defenses offer -- at only a price of a $11-18\%$ drop in clean accuracy. By using a new intuitive metric, we explain why this trade-off offers a significant improvement over prior work.
Evaluation of The Implementation of The School Literacy Movement in Elementary Schools in The District and City of Tangerang

This study aims to describe the evaluation of the implementation of the School Literacy Movement in Elementary Schools in the Regency and City of Tangerang. The approach used in this research is a qualitative approach with descriptive evaluation methods. The Context Input Process and Product model as a model used in this evaluation study consist of four stages, namely context, input, process, and product. Data collection techniques used by researchers in this study were interviews, observation, and documentation. The results of the context implementation evaluation indicate that the reasons underlying the implementation of the School Literacy Movement in 6 schools are because of the lack of interest in reading students, the need for varied reading material or references and the availability of supporting facilities for the program. The results of the input evaluation are that the school implements several strategies that can be done to achieve the School Literacy Movement, the adequacy of facilities and infrastructure, have guidelines or Standard Operating Procedures, the implementation of the program is carried out at the beginning of teaching and learning activities or includes in the process of teaching and learning activities, the allocation of funds using independent funds schools or funds from the Regional Revenue and Expenditure Budget or School Operational Assistance.
Using a Wearable Device to Assist the Training of the Throwing Motion of Baseball Players

In this paper, we design a wearable device utilizing a microcontroller, a 3-axis accelerometer, a 3-axis gyroscope and a Bluetooth wireless transmission module. The baseball player wears the wearable device on the wrist of the dominant hand and records the movement with the high-speed sports camera. As the recorded data of these two 3-axis sensors in the wearable device is then transmitted to the computer using the Bluetooth wireless transmission module, coaches and players can observe the recorded data of these two 3-axis sensors. In addition, by comparing the recorded data with the preset threshold value, the coach can ask the player to adjust the movements or the postures to a more accurate setting in order to reach the training goal. Experimental results show that this wearable device with this analysis method can be a training tool that can assist with the training of baseball players.
Analysis of the development Android’s runtime

The article presents the development of the Android runtime. Own application for Android is presented, which implements performance benchmarks used to test different versions of the Android runtime. The methods measure the benchmark execution times in different versions of the Android runtime environment.
Multiple Algorithm Aperiodic Cryptosystem

MAACS is a software architecture which layers multiple standard cipher algorithms together to increase the overall strength of the encrypted data stream, without modifying the standard algorithms, which have been heavily vetted from a cryptanalysis perspective and are already widely deployed. This layering technique makes the combination of algorithms significantly more resistant to traditional cryptanalysis attacks, while also addressing increased concerns over future quantum computing attacks against these algorithms. For example, concerns over published attacks against 256-bit AES and potential future attacks emanating from Grover&amp;rsquo;s algorithm and other unknowns in the quantum computing era are explored. Several approaches for evolving AES are considered. MAACS uses a concept termed "aperiodic modulation", whereby of a set of cryptographic algorithms are modified by an- other, independent software algorithm in an unpredictable, pseudo-random manner. In the MAACS reference architecture, a 256-bit ChaCha20 cryptographically secure pseudorandom number generator (CSPRNG) drives an aperiodic modulator that orchestrates encryption/decryption processes multiplexed across eight parallel 128-bit AES instances, yielding a cryptosystem with a composite strength of 1,376 bits or more in larger configurations.
Actual Problems of Education and Science in Russia

The article discusses the main problems of education and science in modern Russia.On the actual material, the authors show not only the main achievements, but also certain shortcomings both in the education system and in the development of science during the reign of President V. Putin.The purpose of this study is to study the problems that Russia must solve in order for its education and science to become the basis of the knowledge economy and contribute to improving the quality of human capital.Based on this goal, the authors tried to justify the new priorities of state policy in the field of education and science.In this regard, this study raises the following main questions. 1.To determine the role and place of the education system in the formation of human capital and the development of the knowledge economy.2. To analyze the reasons for its low competitiveness of domestic education and science in comparison with the leading countries of the world.3. Investigate the effectiveness of public administration of education and science in Russia and show the ways for its further improvement.The authors hope that the implementation of the ambitious goals and objectives published in the May (2018) decree of President V. Putin will improve the condition and quality of Russian education and science. Keywordss-education, science, human capital, problems of Russia I. The cost of living is the minimum level of income that is necessary to meet a person's vital needs.In 2019, it did not even reach $200.