Reviewerly/exHarmony huggingface dataset:
DoubleFaceAD

The broad adoption of fanout queries on distributed datastores has made asynchronous event-driven datastore drivers a natural choice due to reduced multithreading overhead. However, through extensive experiments using the latest datastore drivers (e.g., MongoDB, HBase, DynamoDB) and YCSB benchmark, we show that an asynchronous datastore driver can cause unexpected performance degradation especially in fanout-query scenarios. For example, the default MongoDB asynchronous driver adopts the latest Java asynchronous I/O library, which uses a hidden on-demand JVM level thread pool to process fanout query responses, causing a surprising multithreading overhead when the query response size is large. A second instance is the traditional wisdom of modular design of an application server and the embedded asynchronous datastore driver can cause an im-balanced workload between the two components due to lack of coordination, incurring frequent unnecessary system calls. To address the revealed problems, we introduce DoubleFaceAD--a new asynchronous datastore driver architecture that integrates the management of both upstream and downstream workload traffic through a few shared reactor threads, with fanout-query-aware priority-based scheduling to reduce the overall query waiting time. Our experimental results on two representative application scenarios (YCSB and DBLP) show DoubleFaceAD outperforms all other types of datastore drivers up to 34% on throughput and 1.9× faster on 99th percentile response time.
The role and professional development of a teacher at a contemporary University

This article is devoted to the study of the role of the present teacher in the period of transformation of the traditional education system and transition to a digital environment. The article analyzes possible ways and strategies to improve the quality of vocational teacher education in the current conditions. Particular emphasis is given to the necessity of changing the correlations between different components of teaching skills in the digital educational process, as well as the personality and professional competence of the teacher as the most important component of ensuring the success and effectiveness of the educational process in a digital learning environment.
Analysis of OWA operators for automatic keyphrase extraction in a semantic context

Automatic keyphrase extraction from texts is useful for many computational systems in the fields of natural language processing and text mining. Although a number of solutions to this problem have been described, semantic analysis is one of the least exploited linguistic features in the most widely-known proposals, causing the results obtained to have low accuracy and performance rates. This paper presents an unsupervised method for keyphrase extraction, based on the use of lexico-syntactic patterns for extracting information from texts, and a fuzzy topic modeling. An OWA operator combining several semantic measures was applied to the topic modeling process. This new approach was evaluated with Inspec and 500N-KPCrowd datasets. Several approaches within our proposal were evaluated against each other. A statistical analysis was performed to substantiate the best approach of the proposal. This best approach was also compared with other reported systems, giving promising results.
Art therapy techniques in psychological correction of child-parent relations in substitute families raising children with disabilities

The subject of this research is the child-parent relations in substitute families raising children with disabilities. The goal is to determine the areas of possible application of art therapy techniques in psychological correction of child-parent relations in substitute families raising children with disabilities. The theoretical-methodological framework contains subject-activity and systemic approaches, as well as provisions on the structure and functions of child-parent relations, views on child-parent relations of N. Y. Sinyagina; the concept of systemic art therapy by A. I. Kopytin. In the course of this study, the author applies the methods of testing, interview, psychological experiment, and observation. The theoretical importance of this work consists in systematization of theoretical provisions on the problem and substantiation of possibilities of application of art therapy techniques in psychological correction of child-parent relations in substitute families raising children with disabilities. The acquired results obtained can be valuable for psychologists dealing with foster families that raise children with disabilities, which defines the practical significance of this research. The scientific novelty lies in development of the program of art therapy classes for correction of child-parent relations in substitute families raising children with disabilities. The research results may significantly contribute to the extension of representations on capabilities of psychological correction of child-parent relations in substitute families raising children with disabilities via implementation of art therapy techniques. The author indicates the improvement in child-parent relations: alleviation of child&amp;rsquo;s the sense of deprivation; better emotional contact between parent and child; emotional closeness; increase of the authoritative strategy of family upbringing; higher level of parents&amp;rsquo; acceptance; optimization of parenting
Extracurricular activities as a factor of students’ personal development and education (as exemplified by the Faculty of Foreign Languages of Samara State University of Social Sciences and Education)

Extracurricular activities are an integral part of the educational process of a university. The authors consider extracurricular work as a holistic entity with all the attributes of a system (goal, objectives, functions, structure, content, forms, methods and means). The authors of the paper believe that extracurricular work with students is an important part of education and it is carried out with the aim of creating a system of tools and actions that are responsible for solving urgent problems of education, creating favorable conditions for personal and professional development of university graduates, who should combine deep professional knowledge and skills, high spiritual and moral qualities, be noted for legal and communicative culture, creative self-expression and an active citizenship. The paper discusses extracurricular work features as a factor of students personal development and education, reveals the significance of the problem and suggests solutions. The authors examine the effectiveness of extracurricular activities and analyze the structure of free time of the students of the faculty of foreign languages at Samara State University of Social Sciences and Education, which allows to take a fresh look at the organization of extracurricular work.
Suppression in Quality Variation for 360-Degree Tile-Based Video Streaming

For 360-degree video streaming, a 360-degree video is divided into segments temporally (i.e. some seconds). Each segment consists of multiple video tiles spatially. In this paper, we propose a tile quality selection method for tile-based video streaming. The proposed method suppresses the spatial quality variation within the viewport caused by a change of the viewport region due to user head movement. In the proposed method, the client checks whether the difference in quality level between the viewport and the region around the viewport is large, and if so, reduces it when assigning quality levels. Simulation results indicate that when the segment length is long, quality variation can be suppressed without significantly reducing the perceived video quality (in terms of bitrate). In particular, the quality variation within the viewport can be greatly suppressed. Furthermore, we verify that the proposed method is effective in reducing quality variation within the viewport and across segments without changing the total download size.
Implementation of Organization Goal-Oriented Requirements Engineering (OGORE) Method in Designing a Muhammadiyah High School Library Information System

The use of information systems in an organization has become an obligation to support the organization's business process. However, the development of an Information System still often faces problems, the most important problem occurs in the requirements engineering phase where developers try to meet user needs, these problems can also increase when user needs are not following the standards in general. The objective of this research is to design a digital library information system based on the organization goal-oriented requirements engineering (OGORE) method. OGORE is a Requirements Engineering method that focuses on organizational needs and is expected to eliminate the (noise) needs of users. The OGORE method has been used since its goal is to reduce the risks that arise because of user needs based on personal desires. The Development Method used is the Extreme Programming (XP) method. Data collection methods used were observation, interview, and literature study. With OGORE method, the results of a Library Information System can fulfil all the vision and mission of the library.
Simple Area Coverage by a Dynamic Set of Unmanned Aerial Vehicles

The coordination of cooperating Unmanned Aerial Vehicles (UAVs) has become an active area of research. The approaches to coordinate these so-called swarms generally include a solution to a class of problems called Area Coverage as a building block. Area coverage problems consist in obtaining information about a certain interest area (commonly a polygon or a polyhedron) using a set of UAVs, generally with decentralized coordination and minimal human intervention. This problem models the requirements of different types of applications, such as in the case of emergencies and disasters, gas leak detection, seeking lost people, among many others. In this paper we describe a specific strategy to coordinate dynamic sets of UAVs to solve a specific area coverage problem. Existing solutions to the problem typically consider a fixed set of UAVs. In dynamic sets, UAVs might enter or leave the set. Beyond describing a specific strategy to the problem, we introduce the framework we are building on top of ROS/Gazebo to implement it. This framework eases the implementation of different strategies for multiple UAVs coordination and the assessment of their quality.
Agile management and long-term strategy in exploration: the ‘lucky’ discovery of the Sinclair Pollucite Deposit, Eastern Goldfields, Western Australia

Behind the inevitable headlines describing the ‘lucky discovery’ of the Sinclair Pollucite Deposit by Pioneer Resources in a drilling campaign targeting lithium mineralisation, the identification, delineation and development of this resource present a deeper and more substantial tale of fundamental mineral exploration strategy and agile management. A window of opportunity provided by booming global interest in Li exploration delivered Pioneer the impetus and capital to leverage deep geological knowledge of the Pioneer District, innovative exploration technologies, and lean and agile management practices in the development and implementation of a successful exploration campaign targeting the previously unappreciated pegmatites of the Pioneer Dome. While not the target of the original drilling, the intersection of high-grade pollucite at Sinclair was fully consistent with the mineral systems model underlying Pioneer’s exploration plan. By pursuing a flexible process-based targeting approach and retaining the capacity to pivot the focus of their exploration team onto this find, Pioneer were able to rapidly define and exploit the pollucite resource at Sinclair, despite the absence of national precedent.KEY POINTSThe Sinclair pollucite resource is without precedent in Australia.Discovery of this deposit followed from consistent long-term investment in district mineral exploration.Responsiveness and rapid decision-making were critical to the successful development of this unexpected discovery.
The effectiveness of the pedagogical conditions for organizing the educational process using distance educational technologies at the university

Abstract This article solves such a significant scientific problem as the identification of effective pedagogical conditions for organizing the educational process using distance educational technologies at a university. The article discusses three options for organizing the educational process at a university: traditional full-time and part-time education, part-time education with partial use of distance learning technologies, completely distance learning. The study defines the following conditions as pedagogical conditions, grouped into 4 clusters: training content, training time, training methodology, training control. The study examines motivation for learning, training level, learning ability, and the strength of learning outcomes (residual knowledge) as criteria that make it possible to compare the effectiveness of certain pedagogical conditions in the implementation of the educational process in traditional and remote forms. To determine the statistical significance of the research results, the Student’s t-test is used. The study was conducted on the basis of the Yelets State University named after I. A. Bunin in the period of 2018-2020. The study involved 3567 students and 440 teachers. The study revealed pedagogical conditions, the effectiveness of which is determined by general pedagogical mechanisms, as well as pedagogical conditions that are effective only for distance education.
A model of parallel sorting neural network of discrete-time

A model of parallel sorting neural network of discrete-time is presented. The model is described by a system of differential equations and by step functions. The network has high speed, any finite resolution of input data and it can process unknown input data of finite values located in arbitrary finite range. The network is characterized by moderate computational complexity and complexity of hardware implementation. The results of computer simulation illustrating the efficiency of the network are provided.
Practical Active Revocation

We propose Knob, a practical active revocation scheme allowing to efficiently revoke users' access to encrypted data banks stored in public clouds. Knob leverages Trusted Execution Environments and All-or-Nothing Data Transforms in order to re-encrypt only small portions of the content directly in the cloud, using a scalable swarm of re-encryption workers. It prevents malicious users from being able to predict which portions of the files will be re-encrypted upon a revocation, effectively disabling pre-provisioning attacks. Our evaluation using industry workloads shows that Knob outperforms active revocation using full re-encryption by up to 3 orders of magnitude while being on average 3 to 7 times faster than state-of-the-art partial re-encryption.
Schema Matching Using Word-level Clustering for Integrating Universities’ Courses

Schema matching is the process of determining the similarities among multiple schemas of databases or websites structure. Several matching approaches have been depicted in the literature. The most adequate and accurate approach is related to the textual analysis. In this approche, the schemas are being examined in terms of its text information. Various studies used textual-based matching by addressing the character-level string similarity. However, the character-level similarity would have some limitations regarding the words with similar characters but different meanings. Therefore, this study aims to propose a word-level similarity method based on term frequency and cosine similarity. Consequentially, a K-means clustering will utilize the proposed matching analysis to group the correspondences among the schemas. A dataset for universities’ courses is being used to test the proposed method. Experimental results showed that the proposed word-level similarity method had outperformed the character-level by obtaining 73% accuracy. This indicates the significance of using word-level similarity when using cluster-based schema matching.
Using multivariate long short-term memory neural network to detect aberrant signals in health data for quality assurance

The data quality of electronic health records (EHR) has been a topic of increasing interest to clinical and health services researchers. One indicator of possible errors in data is a large change in the frequency of observations in chronic illnesses. In this study, we built and demonstrated the utility of a stacked multivariate LSTM model to predict an acceptable range for the frequency of observations.We applied the LSTM approach to a large EHR dataset with over 400 million total encounters. We computed sensitivity and specificity for predicting if the frequency of an observation in a given week is an aberrant signal.Compared with the simple frequency monitoring approach, our proposed multivariate LSTM approach increased the sensitivity of finding aberrant signals in 6 randomly selected diagnostic codes from 75 to 88% and the specificity from 68 to 91%. We also experimented with two different LSTM algorithms, namely, direct multi-step and recursive multi-step. Both models were able to detect the aberrant signals while the recursive multi-step algorithm performed better.Simply monitoring the frequency trend, as is the common practice in systems that do monitor the data quality, would not be able to distinguish between the fluctuations caused by seasonal disease changes, seasonal patient visits, or a change in data sources. Our study demonstrated the ability of stacked multivariate LSTM models to recognize true data quality issues rather than fluctuations that are caused by different reasons, including seasonal changes and outbreaks.
GradSA: Gradient Sparsification and Accumulation for Communication-Efficient Distributed Deep Learning

Large-scale distributed deep learning is of great importance in various applications. For distributed training, the inter-node gradient communication often becomes the performance bottleneck. Gradient sparsification has been proposed to reduce the communication overhead. However, the sparsification only arbitrarily selects a small fraction of gradients, while the efficiency of selection dimension has been overlooked. Furthermore, gradient staleness is inevitable after applying the sparsification which will ultimately lead to model divergence. In this paper, we propose a staleness-compensated sparse stochastic gradient descent algorithm, GradSA, to improve the training efficiency. Layer-level gradients are sparsified to reduce the communication overhead, which conform to the characteristics of the network structure, and historical accumulation of the approximated gradients is utilized to speed up convergence. We demonstrate the model convergence acceleration and the efficiency of our layer-level selection over existing state-of-the-art works, such as DGC, TernGrad, and 8-Bit quantization.
An Improved of Joint Reversible Data Hiding Methods in Encrypted Remote Sensing Satellite Images

Data protection security is very necessary when distributing high resolution remote sensing satellite images from LAPAN to users via electronic media. Reversible data hiding and encryption are two very useful methods for protecting privacy and data security. This paper proposes an increase in the method of joint reversible data hiding on remote sensing satellite images based on the algorithm of Zhang's work, Hong et al.'s work, and Fatema et al.'s work. To evaluate the smoothness of the blocks, a modification of the fluctuation calculation function is presented. The experimental results show that the modified calculation function gives better estimation results. Then, the proposed method gives a lower extracted bit error rate and the visual quality of the image from the proposed method is better than the three references. For example, when the block size is 8 × 8, the extracted-bit error rate (EER) of the SPOT-6 test image of the proposed modified function was 8.40%, which is quite lower than the 14.14% EER of Zhang's function, 9.62% EER of Hong et al.'s function and 11.87% EER of Fatema's et al.'s method. Likewise, the quality of SPOT-6 image recovery represented by the peak signal-to-noise ratio (PSNR) of proposed modified function is 50.52 dB, which is slightly higher than the 48.23 dB PSNR of Zhang's function, 49.93 dB PSNR of Hong et al.'s function and 49.00 dB PSNR of Fatema's et al.'s function.
Monocular 3D Detection for Autonomous Vehicles by Cascaded Geometric Constraints and Depurated Using 3D Results

3D object detection is a key task in 3D vision perception of autonomous vehicles. In this paper, we present a novel two-stage 3D object detection method aimed to get a more accurate 3D location of an object. We modify existing 3D properties regressing network by adding two additional components, viewpoints classification and the center projection regression of a 3D box's bottom face (CBF). The center projection is associated with a similar triangle constraint to acquire an initial 3D location of a closed-form solution. For no truncated objects, the previous predicted location is involved in the initial value of over-determined equations constructed by the 2D-3D boxes fitting constraint with the configuration determined by the classified viewpoint. Then the recovered 3D information is utilized to purify the detection results. Results of comparison with state-of-the-art methods on the KITTI dataset show that although conceptually simple, our method outperforms more complex and computationally expensive methods. Furthermore, our method can filter out false alarms and false detection in both 2D and 3D results.
Security Analysis on Remote Authentication against Man-in-the-Middle Attack on Secure Socket Layer

Abstract One of the biggest SSL assaults is Man-In-The-Middle. ARP poisoning and phishing are some of the principal attacks against SSL. Phishing offends the user by using false certificates or fake websites to steal certificate information. As for ARP poisoning, the attacker may act as a representative on the client/server communication channel. The MITM attack makes it difficult for users to know if they have linked to an original secured link or not. Since the certificate issued during the connection setup is not secure, an intruder can alter the details in the certificate and grant user authorization. Because a number of cliens have not been well trained above the whereabouts and their attacks, they can recognize the certificates that allow attackers to perform the attack. They can also acknowledge the attack. Two techniques have been suggested in order to cope with such assaults: first for ARP poisoning and secondly for phishing.
A Survey on Speckle Noise Reduction for SAR Images

Speckle noise disturbance is the most essential factor that affects the quality and the visual appearance of the synthetic aperture radar (SAR) coherent images. For remote sensing systems, the initial step always involves a suitable method to reduce the effect of speckle noise. Several non-adaptive and adaptive filters have been proposed to enhance the noisy SAR images. In this chapter, we introduce a compressive survey about speckle noise reduction in SAR images followed by two proposed non-adaptive filters. These proposed filters utilize traditional mean, median, root-mean square values, and large size filter kernels to improve the SAR image appearance while maintaining image information. The performance of the proposed filters are compared with a number of non-adaptive filters to assess their abilities to reduce speckle noise. For quantitative measurements, four metrics have been used to evaluate the performances of the proposed filters. From the experimental results, the proposed filters have achieved promising results for significantly suppressing speckle noise and preserving image information compared with other well-known filters.