Reviewerly/exHarmony huggingface dataset:
Evidence Propagation

We exploit the efficient representations for expert and domain knowledge to draw inferences when new information (evidence) becomes known. The objective is to propagate the evidence through the underlying network to reach and update all relevant attributes.
Towards integrating information about strain rates in PSHA models in Europe: comparison between seismic moment rates from ESHM20 model and geodetic estimates

&amp;lt;p&amp;gt;Most national and international seismic regulations require quantifying seismic hazard based on probabilistic seismic hazard assessment (PSHA) methods. The probabilities of exceeding ground-motion levels at sites of interest over a future time window are determined by combining a source model and a ground-motion model. This research work aims at understanding how the measurement of strain rates by geodesy can provide constraints on the source model.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Earthquake catalogs, merging instrumental and historical data, are usually used to establish earthquake recurrence models. Although these catalogs extend over several centuries, the observation time windows are often short with respect to the recurrence times of moderate-to-large events and in some regions the recurrence models can be weakly constrained.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Here, we compute different realizations of strain rates maps over Europe using a combined velocity field (Pi&amp;amp;#241;a Valdes et al., JGR submitted). These strain rates are compared to the source model of the new European seismic hazard model (ESHM20, Danciu et al. 2021). More precisely, the moment rates estimated from the earthquake recurrence models are compared to the geodetically-derived moment rates.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We explore the different uncertainties in both models. For geodesy, we integrate uncertainties on the velocities at each station, and the epistemic uncertainties on the different steps of the computation of the geodetic moment rate : filtering of the velocity field (outliers&amp;amp;#8217; removal and smoothing) (Pi&amp;amp;#241;a-Vald&amp;amp;#233;s et al, JGR submitted), parameters used to drive the strain inversion with VISR software (Shen et al. 2015), constants and formula used for the moment computation. The goal is to quantify the impact of each parameter uncertainty or decision on the moment computation.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The first results show that a correlation exists between the seismically and geodetically derived moment rates. In general, the main uncertainty is on the velocities at each stations, followed by the depth taken into account for the moment computation. In areas characterized by high activity, such as Betics or Apennines for example, the moment rates derived by both methods are comparable. In areas of lower activity, such as at the interior of plates, the error associated with geodetic measurements is of the same order of magnitude as the measured strain, and the relation between catalog-based and strain-based moment is not straightforward. &amp;lt;/p&amp;gt;
F6: Computer Systems Under Attack - Paying the Performance Price for Protection

Attacks on chip security are a clear and present danger.State of the art DARPA research aims to ease the burden of developing secure chips by creating novel, automated chip design flows that will allow security mechanisms to be automatically inserted into a design.Such tool chains seek to support power, area, speed and security (PASS) trade-offs during high-level IC design and offer support for rapid evaluation of architectural alternatives vis-à-vis PASS metrics.
New Movement Strategy of Cuckoo Search for achieving higher profit rate in milling operation

This paper proposes a newly developed algorithm named the New Movement Strategy of Cuckoo Search (NMS-CS), for solving the manufacturing optimization problem. Attainment of a higher profit rate is intended. NMS-CS is a variant of the popular Cuckoo Search (CS) method. Presented here is the initial implementation of NMS-CS to the machining parameter selection problem in the literature. The effectiveness of NMS-CS is demonstrated by considering the milling optimization problem as a case study. The obtained results were compared with other established Swarm Intelligence (SI) approaches including the original CS algorithm reported in the literature. The findings reveal that NMS-CS is very efficacious and powerful in dealing with machining parameter optimization problems targeted to attain a better profit rate.
The Perception and Implementation Plan for Augmented Reality-Based Classes for Young Children With Moderate Disabilities

The purpose of this study is to examine the necessity and implementation strategy of augmented reality(AR)-based classes for young children with moderate disabilities. Regarding the research method, a conceptual diagram analysis was performed to confirm the perception of AR-based classes and the empirical and theoretical knowledge of experts. First, in-depth interviews were conducted with 22 experts in the special education, educational engineering, and engineering fields. Afterwards, a multidimensional scale analysis, hierarchical cluster analysis, and validity evaluation were performed on the developed statements to analyze the conceptual map of AR-based classes for young children with moderate disabilities. As a result of the study, first, experts positively recognized the need for AR-based classes for young children with severe disabilities. Second, we confirmed that AR-based classes require the development of teaching strategies according to the systematic instructional design process. Third, we suggested methods such as action induction, context maintenance, and sensory information to improve the usability of AR contents for young children with moderate disabilities. Based on the above study results, we discussed the necessity and implementation plan for AR-based classes for young children with moderate disabilities, and the characteristics and usability improvement principles of AR contents. Subsequent research requires the development of various empirical studies and instructional models for the AR-based teaching strategy developed in this study. In addition, it is necessary to develop immersive content based on the curriculum and centered on teachers, students with disabilities, and developers.
Educational training in Physical Education in the context of current technological virtuality

The study's primary purpose focused on analyzing educational training in Physical Education and the use of technological tools in the current context as a way of perceiving the reality of the use of technological platforms in academic exchanges in a virtual way. The research is methodologically attached to descriptive field studies. The data collection instrument was the survey, made up of 12 items, with their alternatives, which allowed the informants to extract the information from which the analyzes were based. For validity, expert judgment was applied, and reliability was determined using the Cronbach Coefficient, whose result was 0.89. As conclusions, the students stated that ICTs represent a significant fact for understanding educational realities. Likewise, they showed disagreement about Physical Education being versatile under the virtual modality.
Study On Go Programming Language

When developing software today, we still use old tools and ideas. Maybe it is time to start from scratch and try tools and languages that are more in line with how we actually want to develop software. The Go Programming Language was created at Google by a rather famous trio: Rob Pike, Ken Thompson and Robert Griesemer. Before introducing Go, the company suffered from their development process not scaling well due to slow builds, uncontrolled dependencies, hard to read code, poor documentation and so on. Go is set out to provide a solution for these issues. The purpose of this master’s thesis was to review the current state of the language. This is not only a study of the language itself but an investigation of the whole software development process using Go. The study was carried out from an embedded development perspective which includes an investigation of compilers and cross-compilation. We found that Go is exciting, fun to use and fulfills what is promised in many cases. However, we think the tools need some more time to mature.
Automatic detection and classification of seismic signals of the Popocatepetl volcano, Mexico, using machine learning methods.

&amp;lt;p&amp;gt;Many studies highlight the benefits of using machine learning algorithms for the classification of volcano-seismic signals. However, when it comes to their widespread application, volcano observatories and researchers face two important challenges. i) The performance of these models highly depends on the size of the training set, where large amounts of labeled signals (thousands and sometimes even hundreds of thousands) are needed to get sufficient accuracy. ii) Most of them use data recorded by a single station and from only one component. This &amp;amp;#8220;master&amp;amp;#8221; station is generally one of the closest to the crater and, in volcanoes, it is common to face technical difficulties that interrupt the continuous recording, especially during periods of increased activity.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;This strongly limits the possibility of applying machine learning approaches for efficient monitoring of volcanoes, especially during unrest periods.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Here, we show a simple method that addresses these difficulties using the information provided by the entire network of stations operating at Popocatepetl volcano (about 18 stations among permanent and temporal) and using all the components. Initially, we used a mid-size catalog of 507 single-channel labeled events recorded between 2019 and 2020. Later, to increase the size of our dataset and exploit the information provided by different channels, we added the signals of the three components of all the events, as well as signals of selected events recorded at different stations. This enlarged training set comprises 1725 signals of six classes: 345 noise, 324 explosions, 321 long periods (LP), 306 volcano-tectonics (VT), 264 tremors, and 165 regionals. To characterize the data, we used a previously proposed set of 102 features that describe the shape, statistics, and entropy of the signals. Then we applied two classification algorithms, random forest and support vector machines, to both our datasets. Our results show that the model of the enlarged dataset increases the overall accuracy by over 8% compared with the one produced using one station and only one component, with the additional benefit of guarantying continuous monitoring even when the &amp;amp;#8220;master&amp;amp;#8221; station is not working.&amp;lt;/p&amp;gt;
French feedback from urban soil geochemical data archive to data sharing: state of mind and intent&amp;#160;

&amp;lt;p&amp;gt;Urban territories collect many types of geochemical and physico-chemical data relative to, e.g., soil quality or soil functions. Such data may serve for various purposes like verifying the compatibility with current or future uses, defining (pedo)geochemical backgrounds, establishing levels of exposure to soil pollutants, identifying management options for polluted sites or for excavated soils, verifying the evolution of infiltration ponds, assessing carbon storage, etc. They may also serve to prioritize soil functions and associated ecosystem services such as, e.g., soil fertility, surface and groundwater storage or supply, purification of infiltrated rainwater, etc. Gathering such data in national databases and making them available to stakeholders raises many issues that are technical, legal and social. &amp;amp;#160;Should all of the data be made available or only selected portions? How can access and reuse of the data be ensured in a legal fashion? Are statistical and geostatistical methods able to deal with data from heterogeneous origins, allowing their reuse for other purposes than the initial one? In this context, it is necessary to take into account scientific as well as practical considerations and to collect the societal needs of end-users like urban planners.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;To illustrate the complexity of these issues and ways to address them, we propose to share the French experience:&amp;lt;/p&amp;gt;&amp;lt;ul&amp;gt;&amp;lt;li&amp;gt;on gathering urban soil geochemical data in the French national database BDSolU. We will present how this database was created, the choices made in relation with the national context, the difficulties encountered, and the questions that are still open.&amp;lt;/li&amp;gt; &amp;lt;li&amp;gt;on a new interrogation system linking agricultural and urban soil databases (DoneSol and BDSolU), which have different requirements, and the corresponding standards. Such linkage based on interoperability is important in the context of changes of soil use, with for example agricultural soils becoming urbanised soils, or soils from brownfields intended for gardening. It is also necessary to ensure a territorial continuity for users.&amp;lt;/li&amp;gt; &amp;lt;/ul&amp;gt;&amp;lt;p&amp;gt;The objective is to define a robust and standardised methodology for database conceptualisation, sharing and final use by stakeholders including scientists&amp;lt;/p&amp;gt;
Online Learning of Students with Special Needs: Teachers’ Perspectives

This research was an attempt to find an effective vocabulary-teaching method order for Iraqi young foreign language learners. An experiment was conducted during regular Iraqi class sessions for seven weeks, from April 13th to May 29th, 2019. In this experiment, two vocabulary-teaching method orders, explicit-first order and implicit-first order, were compared for effectiveness, using a within-group design. The participants of the groups were fourth graders at Al-Hadi Primary School in Babil Governorate, Iraq. Each group had almost thirty students. They had the same background when it came to learning English. Flashcards were used for the explicit vocabulary-teaching method, while stories were used for the implicit vocabulary teaching method. For the first three weeks, Group 1 was taught English vocabulary using the explicit method at the beginning of each session, followed by the implicit method. On the other hand, during each session, Group 2 was taught using the implicit method first, followed by the explicit method. Both groups had a one-week break in week four. After the break, the orders of vocabulary teaching methods were switched for each group for the next three weeks. The amount of words that the students could recall was measured by a multiple choice test at the end of each session. As a result of the experiment, slight differences were found between the two orders and two groups, but it is difficult to say which order is more effective than the other one because the difference was not remarkable. Rather, it is now assumed that the homeroom teacher's influence and the students' personalities, as well as environmental and affective factors, could be more critical to students' foreign language learning.
The Use of Diorama Learning Media Towards Learning Motivation of Students in Class X IPS 2

The research entitled The Use of Diorama Learning Media on Student Motivation in Class X Social Sciences 2 SMA Negeri 1 Rundeng District". This study aims to determine the effect of using diorama learning media on students' motivation to learn history at SMA Negeri 1 Rundeng District. This study uses a qualitative approach while the type of research is descriptive. The subjects in this study were all students of class X IPS 2 SMA Negeri 1 Rundeng District, totaling 17 students. Sampling technique using purposive sample or sample purpose. selecting this sample was based on the teacher's reference which allowed the data collection techniques to be used were observation, interviews and documentation.Meanwhile, the data analysis technique in this study begins with data reduction, then data model (data display), and ends with verification (conclusion) Based on the data analysis carried out, the average level of motivation obtained by students in class X IPS 2 SMA Negeri 1 R undeng District is highly motivated. Based on the calculation of the percentage scores obtained by students in class X IPS 2 consisting of 82%, 90%, 94%, 96%, 98%, 100% and if added as a whole, the average percentage score is 88%, the results fall into the category very motivated. It can be concluded that there is an effect of using diorama learning media on the motivation to learn the history of students in class X IPS 2 SMA Negeri 1 Rundeng District.
(Retracted) Target recognition and localization based on lightweight single-shot multibox detector network for robotics

Target recognition and localization are essential in computer vision and pattern recognition in robotics. The artificial extraction of features was omitted with the emergence of deep convolutional neural networks, reducing the influence of human factors on the results. The single-shot multibox detector (SSD) network has achieved excellent recognition by high precision and fast speed in target recognition and positioning. However, some small real-time systems are difficult to implement because of their demanding hardware and extended training time. Based on the digital normalization and residual network structure, the depth-wise separable convolution is proposed to replace the traditional convolution. The improved SSD network structure was used for identification and positioning in our work. The speed of training and testing increased without a decline in the accuracy, thus reducing the dependence on hardware. The method has achieved good results on the PASCAL VOC dataset after testing. It can also be applied to the field of intelligent inspection robots and intelligent security robots.
The use of electronic evidence in court: a comparative legal analysis in the world practice

The article is devoted to such a topical issue as the use of electronic evidence in court. The purpose of the article is to determine the basic principles of electronic evidence, study domestic and foreign legislation on the use of electronic evidence in court, determine their place in the system of evidence, and identify problems with evidence in court. It was found that electronic evidence should be understood as factual data that are displayed in digital forms and recorded on any type of media, as well as after processing by electronic computers become possible and accessible to human perception. It has been established that in most of the European countries we study, electronic evidence is unquestionably classified as written and is not singled out. It has been identified that electronic documents have the same legal force in some countries as paper documents. It was concluded that in Azerbaijan the procedure for collecting and examining electronic evidence in domestic proceedings should be improved to avoid various technical errors, as well as to strengthen cybersecurity measures and increase basic knowledge of judges in the field of information technology.
The Effectiveness of Hangeul Phonics CAI Instruction for Students With Learning Difficulties: Comparison of the Real-Time Distance Learning Group and Distance Learning-In Class Learning Combination Group

This study was designed to investigate whether CAI Hangeul phonics instruction, which was developed based on direct instruction, is also as effective when it was delivered via the real-time distance learning system only, and compared to when it was delivered in a combined setting, in-class learning, and real-time distance learning. Thirty-nine first and second graders were recruited from 20 elementary schools across four school districts. The combination group of 18 students received Hangeul phonics CAI instruction by visiting reading support centers run by the school districts. They also received CAI instruction via the real-time distance learning system. The real-time distance learning only group received the same CAI instruction from their schools or from their own homes. The results revealed that both the combination group and the distance learning only group improved their phonics abilities across all measures. Also, no difference was found regarding the students’ improvements between the two CAI groups. This study revealed an interesting result: When the teachers used a scientifically proven instructional software program, and if there is an adult present who supports the distance learning environments, CAI distance learning can bring sufficient improvements in young students’ phonics skills whether in-class instruction was added or not.
Robust Actor-Critic With Relative Entropy Regulating Actor

The accurate estimation of Q-function and the enhancement of agent’s exploration ability have always been challenges of off-policy actor–critic algorithms. To address the two concerns, a novel robust actor–critic (RAC) is developed in this article. We first derive a robust policy improvement mechanism (RPIM) by using the local optimal policy about the current estimated Q-function to guide policy improvement. By constraining the relative entropy between the new policy and the previous one in policy improvement, the proposed RPIM can enhance the stability of the policy update process. The theoretical analysis shows that the incentive to increase the policy entropy is endowed when the policy is updated, which is conducive to enhancing the exploration ability of agents. Then, RAC is developed by applying the proposed RPIM to regulate the actor improvement process. The developed RAC is proven to be convergent. Finally, the proposed RAC is evaluated on some continuous-action control tasks in the MuJoCo platform and the experimental results show that RAC outperforms several state-of-the-art reinforcement learning algorithms.
Comparison of Formats for Profiled Training in Selected Matriculation Subjects and Forecast for the Expected Results from Them

The article attempts an informal, partial assessment of the impact of changes in the training and examination programs of some state matriculation exams for profiled training. Certain problems and risks arising from the different formats of the certain matriculation exams and the presumed, but still unknown, unified scale for their assessment, with an increased lower threshold value, have been highlighted. A forecast is given for the expected average success, in comparative order, of the state matriculation exams in biology, physics and chemistry on the one hand, and those in geography, history and philosophy on the other.
The Digital Context of At-Risk Textual Archives

By describing the case study of a large collection of Assyrian tablets, this chapter illustrates the benefits of digital curation and textual analysis for re-establishing the missing context of looted and unprovenienced ancient artifacts. It tackles the main theme of heritage at-risk from a different perspective than other chapters in the book. The author details the creation of an ontological structure for data analysis using digital curation methods combined with innovative machine learning and network analysis and visualization techniques. The result is an important new research tool for scholars focusing on reinterpreting ancient Assyrian cuneiform writing from unprovenienced texts.