Reviewerly/exHarmony huggingface dataset:
Improving the Project Risk Competence using M-Learning: A Case of Bachelors in Technical Fields

&lt;p class="0abstract"&gt;Mobile technology is a popular tool used to improve education efficiency. However, its impact on learners in risk assessment training is largely unknown. Projects are fraught with risks so individuals responsible for a project need to possess strong skills to handle the risky circumstances successfully. Unfortunately, candidates for a bachelor’s degree in technical fields in Russia have an insufficient risk competence. This study offers a five-unit program to solve this problem. The study involved 128 students recruited from the Noyabrsk Institute of Oil and Gas (Yamalo-Nenets Autonomous Okrug, Russia). All participants were divided in three groups: two experimental and one control. During a semester, participants in the experimental group followed the proposed program in a mobile setting, while the control group was offered the standard curriculum. The results showed an improvement in the student outcomes: the test scores of the experimental groups were higher by 24.78% and 32.75% than that of the control group. Furthermore, mobile learners were found to perform better than classroom learners: their test score was higher by 3.5% to 8%.&lt;/p&gt;
LibGuides: Sport : Other information

A comprehensive guide to the resources provided by the Library service to support you with your course.
Fully Automated 3D Segmentation of MR-Imaged Calf Muscle Compartments: Neighborhood Relationship Enhanced Fully Convolutional Network

Automated segmentation of individual calf muscle compartments from 3D magnetic resonance (MR) images is essential for developing quantitative biomarkers for muscular disease progression and its prediction. Achieving clinically acceptable results is a challenging task due to large variations in muscle shape and MR appearance. Although deep convolutional neural networks (DCNNs) achieved improved accuracy in various image segmentation tasks, certain problems such as utilizing long-range information and incorporating high-level constraints remain unsolved. We present a novel fully convolutional network (FCN), called FilterNet, that utilizes contextual information in a large neighborhood and embeds edge-aware constraints for individual calf muscle compartment segmentations. An encoder-decoder architecture with flexible backbone blocks is used to systematically enlarge convolution receptive field and preserve information at all resolutions. Edge positions derived from the FCN output muscle probability maps are explicitly regularized using kernel-based edge detection in an end-to-end optimization framework. Our FilterNet was evaluated on 40 T1-weighted MR images of 10 healthy and 30 diseased subjects by 4-fold cross-validation. Mean DICE coefficients of 88.00%--91.29% and mean absolute surface positioning errors of 1.04--1.66 mm were achieved for the five 3D muscle compartments.
Meaning and Approaches to Studying Musical Meaning Formation in the Russian Musical Science

The study aims to substantiate the necessity to upgrade methodology in the field of investigating musical meaning formation. The article reviews approaches to researching this issue from the standpoint of semantics and cognitive science. Scientific novelty of the paper lies in conducting a critical analysis of these approaches correlated with essential characteristics of meaning. As a result, it was found that there is discrepancy between fundamental properties of meaning formation and non-specific approaches to studying it, narrowing perception of the subject, which requires updating the methodological apparatus used in studying meaning formation on the basis of involving the categories immanent to it, which makes it possible to ascertain correlation between conceptual meaning and non-verbal nature of music.
A study on the vocabulary in the current National Language Textbooks for first-year middle school students in Korea and Japan

This paper aims to illuminate the socio-cultural characteristics of Korea and Japan in school textbooks by drawing on the significant differences between categories that appear in lexical distributions by areas of meaning of vocabulary in the current national language textbooks for first-year middle school students in Korea and Japan. Particularly, this paper has verified that as Korea introduced the free-semester system for the first year of middle school according to the current curriculum (2015), the total number of words decreased to 3/5 compared to the vocabulary in the previous textbooks, which is equivalent to about 9/10 compared to Japan.BR In order to examine the qualitative change, the lexical distributions in the major categories were compared according to Bunruigoihyou (1964). In the case of Korean textbooks, there were significant differences in the order of 〈1.3〉, 〈1.2〉, and 〈1.4〉 based on the total number of words. In the case of Japanese textbooks, significant differences were shown in the order of 〈1.5〉 and 〈1.1〉.BR These features were also observed in the middle categories. In the case of Korea, significant differences were found in 〈Race · Ethnicity〉, 〈Human Beings〉, and 〈Members · Position〉 in 〈1.2〉; but the difference between the two countries has decreased significantly compared to the past. There was also no significant difference in 〈Family〉 and 〈Organization〉 in the middle categories, as well as 〈Monarch〉, 〈Social Class〉, 〈The Military〉, and 〈Soldier〉 in the small categories. This can be interpreted as a desirable phenomenon. As for Korean textbooks, there were significant differences in 〈Duty〉 and 〈Economy〉 in 〈1.3〉. Particularly due to the influence of high frequency words such as “Theft · Sponsorship Activity · Money · Donation” it is also characteristic that there was no significant difference in 〈Creation · Writing〉 as there was before. There were significant differences in 6 items in 〈1.4〉 too, but it is difficult to interpret it in socio-cultural terms due to the influence of specific high frequency words.BR As for Japanese textbooks, even distribution is found in 〈1.12 Presence or Absence〉 and 〈Action〉 in addition to 〈Instruction〉, 〈Quantity〉, 〈Space · Location〉 which are related to information literacy. In particular, various technical terms were used in 〈Organism〉, 〈Space · Topography〉, 〈Animal〉, and 〈Nature · Object〉 as the present revision focuses on the global environment and ecology. A more comprehensive conclusion will be drawn in the future through analysis of texts and vocabulary before and after revision of textbooks in each country.
Secure Volume Hot-plugging for Containers (industry track)

Containers are becoming a common platform for companies to build and run their applications. We find many challenges we do not experience in VM-based virtualizations from our own experience of migrating and deploying various applications from Virtual Machines (VMs) to containers. One of the challenges arises from running stateful applications that not only read static data but also write and update data to storage. Specifically, to mount a volume (which includes NFS shares, network-attached storage, and block devices connected via networks) to a container becomes a task that requires various considerations due to security and maintenance of the host that runs containers. This paper presents a solution based on a sidecar container design pattern to the challenges of running stateful applications as containers. Our evaluation shows that the solution achieves better performance in terms of the time required to mount a new volume. Also, we share our 1-year experience of running the solution and present the lessons learned. Our solution is not only applicable to accessing storage from containers but also usable to connecting devices from IoT applications.
Modern Geriatric Home Health Care Architecture

In the last five years, Indonesia's Gross Domestic Product (GDP) has continued to grow positively and followed by an increase in general healthcare services. Thus, Indonesia has reached a new record of life expectancy rate of more than 70 years old.[1] However, health facilities especially home health care for geriatrics are still very limited. [2] Therefore in this paper, we propose an architecture and a scheme of modern geriatric home health care (GHHC) in order to overcome the disadvantages of the present GHHC such as paper-based transaction, lack of patient activity monitoring, and uncontrolled personal health record (PHR) data. In this research, we collaborated with the Medical Faculty of Universitas Katolik Indonesia Atma Jaya, and using the case of North Jakarta Region. This architecture accommodates four key technologies, namely Data Science, Cloud Computing, Internet of Things (IoT) and Artificial Intelligence (AI).
COMPUTER PREDICTION OF TECHNOLOGICAL REGIMES OF RAPID CONE-SHAPED ADSORPTION FILTERS WITH CHEMICAL REGENERATION OF HOMOGENEOUS POROUS LOADS

Mathematical models for predicting technological regimes of filtration (water purification from the present impurities), backwashing, chemical regeneration and direct washing of rapid cone-shaped adsorption filters, taking into account the influence of temperature effects on the internal mass transfer kinetics at constant rates of the appropriate regimes, are formulated. Algorithms for numerical-asymptotic approximations of solutions of the corresponding nonlinear singularly perturbed boundary value problems for a model cone-shaped domain bounded by two equipotential surfaces and a flow surface are obtained. The proposed models in the complex allow computer experiments to be conducted to investigate the change of impurity concentrations in the filtration flow and on the surface of the load adsorbent, temperature of the filtration flow, filtration coefficient and active porosity along the filter height due to adsorption and desorption processes, and on their basis, to predict a good use of adsorbents and increase the protective time of rapid cone-shaped adsorption filters with chemical regeneration of homogeneous porous loads.
Implementasi JSON Web Token Berbasis Algoritma SHA-512 untuk Otentikasi Aplikasi BatikKita

Batikkita is an android based application and web framework laravel web service architecture that is used to bring together between craftsmen and consumers of batik Trusmi and batikkita application with the e-commerce model used is business to customer. The backend system interface used is a web framework while the frontend system interface used is android. The problem that arises from the Batikkita application is that the security of users, both as sellers and consumers, is very vulnerable to being hacked, so it is very detrimental to both sellers and buyers. This study aims to implement the JSON Web Token based on the HMAC SHA-512 algorithm in the Batikkita application in order to provide a sense of security for both the seller and the buyer before entering the sales transaction page. The application development method used is Rapid Application Development because the cycle used to develop our batik application is very short so it is very helpful in this research. While the implementation of JSON Web Token with the HMAC SHA-512 algorithm in the Batikkita application is used to improve user security when logging in to the Batikkita application in the form of a token and the password used by the user is wrapped in a token given by the Batikkita application. As a comparison, the HMAC SHA-256 algorithm and the HMAC SHA-384 algorithm are used. The results obtained from testing the implementation of JSON Web Token with the SHA-512 algorithm in our batik application, for an average increase of speed between 138.8 milliseconds for SOAP and 122.7 milliseconds for REST compared to the HMAC SHA-256 algorithm and the HMAC SHA-algorithm. 384. While the required token size is greater between 2.13 kb for SOAP and 2.11 kb for REST compared to the HMAC SHA-256 algorithm and the HMAC SHA-384 algorithm.
Final exam: what is the result of studying at school?

What should be considered and evaluated in modern technological conditions as a result of school education? What are the consequences of "informational expansion of the individual"? How digitalization affects the fundamental psychophysiological processes of personal development. Without an answer to these questions, it is impossible to talk about understanding the significance of the development of digital educational technologies. It is proposed to identify invariants of learning outcomes in school based on the psychophysiology of human development.
An Improved Full-text Retrieval for Elementary Education Resource Database System

Abstract With the rapid development of Internet and information technology, ways of teaching and learning in China’s elementary education have begun to change. In the face of massive resources, how to optimize the searching results and improve users’ satisfaction through the search services, has now become a major priority. Based on the in-depth study of full-text retrieval technology, combined with the actual searching needs of the elementary education resources, this paper focuses on Chinese word segmentation technology, and proposes a user-defined professional dictionary based on cell lexicon. Experiments show that using this professional dictionary to segment words improves the professionalism of word segmentation results and the accuracy of search results. Meanwhile, an improved full-text retrieval for elementary education resource database system based on Lucene is designed and implemented, including resource collection, text pre-processing, content indexing and resource retrieval. This system is successfully integrated and applied to the massive knowledge base platform for elementary education, which meets the needs of full-text retrieval of textbooks and supplementary content, and makes a good effect.
Effective Job Execution in Hadoop Over Authorized Deduplicated Data

Existing Hadoop treats every job as an independent job and destroys metadata of preceding jobs. As every job is independent, again and again it has to read data from all Data Nodes. Moreover relationships between specific jobs are also not getting checked. Lack of Specific user identities creation and forming groups, managing user credentials are the weaknesses of HDFS. Due to which overall performance of Hadoop becomes very poor. So there is a need to improve the Hadoop performance by reusing metadata, better space management, better task execution by checking deduplication and securing data with access rights specification. In our proposed system, task deduplication technique is used. It checks the similarity between jobs by checking block ids. Job metadata and data locality details are stored on Name Node which results in better execution of job. Metadata of executed jobs is preserved. Thus by preserving job metadata re computations time can be saved. Experimental results show that there is an improvement in job execution time, reduced storage space. Thus, improves Hadoop performance.
BINARY KRIPKE SEMANTICS FOR A STRONG LOGIC FOR NAIVE TRUTH

I show that the logic $\textsf{TJK}^{d+}$, one of the strongest logics currently known to support the naive theory of truth, is obtained from the Kripke semantics for constant domain intuitionistic logic by (i) dropping the requirement that the accessibility relation is reflexive and (ii) only allowing reflexive worlds to serve as counterexamples to logical consequence. In addition, I provide a simplified natural deduction system for $\textsf{TJK}^{d+}$, in which a restricted form of conditional proof is used to establish conditionals.
Literary Cinematography in Alexey Ivanov’s Novel “Food Unit”

The research aims to identify peculiarities of using cinematic techniques in the novel “Food Unit” by A. V. Ivanov. The article studies involvement of horror images and motifs developed in cinema and reinterpreted by Ivanov; describes film techniques: editing, change of narrative perspectives, colour imagery. Scientific novelty of the work lies in defining the genre nature of “Food Unit” as a film novel, i.e. a literary work oriented towards intermedial perception. As a result, it is proved that Ivanov taps into cinema as a medium for horror motifs, which allows him to create his own model of the vampire world against the background of the cinematic tradition.
Performances of non-parameterised radial basis functions in pattern recognition applications

Abstract Pattern recognition appears in many applications with most popular scheme are those involved the so-called ‘Radial Basis Function (RBF)’. It is known that the shape parameter contained in some RBFs used has great influence on the final quality of prediction. This study focusses on RBFs which contains no parameters where three data patterns are used for performance validation. With a good choice of number of centres, it is clearly possible to obtain satisfactory results with no burden on choosing the suitable or optimal shape. This can well shed more light into applications with more complexity with less user’s judgment and be more automatic in the process.
Towards sample-efficient episodic control with DAC-ML

The sample-inefficiency problem in Artificial Intelligence refers to the inability of current Deep Reinforcement Learning models to optimize action policies within a small number of episodes. Recent studies have tried to overcome this limitation by adding memory systems and architectural biases to improve learning speed, such as in Episodic Reinforcement Learning. However, despite achieving incremental improvements, their performance is still not comparable to how humans learn behavioral policies. In this paper, we capitalize on the design principles of the Distributed Adaptive Control (DAC) theory of mind and brain to build a novel cognitive architecture (DAC-ML) that, by incorporating a hippocampus-inspired sequential memory system, can rapidly converge to effective action policies that maximize reward acquisition in a challenging foraging task.
Impact of the persistence layer implementation methods on application per-formance

There are various methods for creating web applications. Each of these methods has different levels of performance. This factor is measurable at every level of the application. The performance of the frontend layer depends on the response time from individual endpoint of the used API (Application Programming Interface). The way the data access will be programmed at a specific endpoint, therefore, determines the performance of the entire application. There are many programming methods that are often time-consuming to implement. This article presents a comparison of the available methods of handling the persistence layer in relation to the efficiency of their implementation.
Interoperability of Users, Developers, and Managers

This BoF is a continuation of the ADASS FADS tradition of yore, which aims tostimulate discussion (or at least awareness) about the non-technical aspects of our trade.This year, as we expected, it proved to be difficult to have a real discussion by means of Zoom. But the Metis polls and the DisCord log show that we have nevertheless beensuccesful in getting people to (begin to) think about the wayUsers, Developers andManagers work together, inside and between our MultiVerse of Bubbles. Next year wewill try to focus this discussion by means of a Proxy demonstrator. We feel that there isa world to be won.
Profiling NVIDIA Jetson Embedded GPU Devices for Autonomous Machines

This paper presents two methods, tegrastats GUI version jtop and Nsight Systems, to profile NVIDIA Jetson embedded GPU devices on a model race car which is a great platform for prototyping and field testing autonomous driving algorithms. The two profilers analyze the power consumption, CPU/GPU utilization, and the run time of CUDA C threads of Jetson TX2 in five different working modes. The performance differences among the five modes are demonstrated using three example programs: vector add in C and CUDA C, a simple ROS (Robot Operating System) package of the wall follow algorithm in Python, and a complex ROS package of the particle filter algorithm for SLAM (Simultaneous Localization and Mapping). The results show that the tools are effective means for selecting operating mode of the embedded GPU devices.
İnsan - Makine Etkileşiminde Hologram Kullanılarak İnsan Niyetinin Yönlendirilmesi

Decision making could be critically important for people in some situations. People have intentions to choose a side if it is time to make decision. These intentions are strongly related to the knowledge and experience. But sometimes outer effects could reshape their intentions easily. In this paper, an experimental work is studied for Human-Machine Interaction in which if holograms could change or affect the human intention. And also the question which asks whether people trust on a hologram agent while making decision or not is researched. To study this research, a memory game application is developed and this application is run on Microsoft Hololens device. Hololens is used to maintain the Augmented Reality (AR) environment with holograms. An algorithm with a Finite State Machines (FSM) is developed to manage the response of hologram agent while giving hint to the confused users. The accuracy of the hints changes nonlinearly. 3 different game stages are trained on users to see how they are affected by both virtual and real world noises. According to the results, intention of majority of users was affected by the hologram while making the decisions. Also it is observed that some users who were concentrated too much to memorize the order of objects did not realize the hologram, and some few could not understand the actions of hologram.
Re-engineering Approaches to Children’s Education in Zimbabwe after COVID-19: A Call to Innovative Approaches

Background: As fears of the corona virus pandemic (also known as the COVID-19 Pandemic) continue to spread around the world, Boma’s global network hosted an unprecedented online summit on the 23rd and 24th of March 2020, to discuss the early lessons learnt about this pandemic with regards to education and explore specific plans of action to address it. The summit inspired this study and its major findings show that COVID-19 has necessitated drastic changes in the education system.&#x0D; Objective: To explore new ways in which teachers can continue teaching the children using non-traditional means during the COVID-19 lockdown period and after; to assess the attitude of parents/guardians to the re-opening of schools after COVID-19 in terms of children’s safety; and examine the challenges posed by COVID-19 to children’s education during the lockdown period.&#x0D; Methods: This research is based on an exploratory design given the immediacy, novelty and emergency associated with COVID-19. This study seeks to have a better understanding of the existing problems relating to children in their education during the lock down period. The design utilizes both primary and secondary data collection methods.&#x0D; Results: The data of this study indicate that it is feasible to offer distance education to children in Zimbabwe despite the existence of COVID-19. Thestudy also indicates that changes to the education system are inevitable and the education system will never be the same after COVID-19.&#x0D; Conclusion: The study concludes that COVID-19 has had a telling effect on education in Zimbabwe and the lasting changes will remain with the system even after the lockdown period.
Subject and Course Guides: Beginning Your Research in English (Fall 2020): Citation/Reference Management Tools

A guide to beginning your research in English using only electronic resources, with physical material access shut down in 2020.