Reviewerly/exHarmony huggingface dataset:
Seismo-Acoustic Shockwave Isolation for Low-Yield Local Explosions

&amp;lt;p&amp;gt;Seismic and acoustic recordings have long been used for the forensic analysis of various natural and anthropogenic events, especially in the realm of nuclear treaty monitoring. More recently, multi-phenomenological analysis has been applied to these signals with great success, providing unique constraints for studying a broad range of source events, including man-made noise, earthquakes and explosions. In particular, the fusion of seismic and infrasonic data has proven valuable for the analysis of explosive yield, significantly improving on the yield estimates obtained from either seismic or acoustic analysis alone.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Unfortunately, the seismo-acoustic analysis of local explosions is complicated by the fact that the two phenomena are potentially co-dependent. Large seismic waves displace the earth like a piston, potentially inducing acoustic waves into the atmosphere as they pass. Similarly, large acoustic waves can couple into the earth, inducing ground motion along their path. This co-dependence can be problematic, particularly when the passing acoustic shockwave couples into the earth coincident with a seismic phase arrival, thereby corrupting the signal.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;To address this problem, we present a method for isolating the shockwave response of a seismic sensor, such that any underlying seismic phase arrivals can be recovered. This is accomplished by employing the adaptive noise cancellation model, where a co-located infrasound sensor is used as a reference measurement for the shockwave. In this model, the adaptive filter learns the transform between the relative atmospheric pressure (as recorded by the infrasound sensor), and the resulting ground motion (as recorded by the seismometer). In this way, the filtered infrasound recording approximates the seismic shockwave response, and can be subtracted from the seismograph to recover the phase arrivals.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The experimental data comes from a set of three low-yield near-surface chemical explosions conducted by LLNL as part of a field experiment, known as FE2. The explosions were recorded at eight stations, located at varying distances from the source (between 64m and 2km), with each station consisting of a co-located three-component seismic velocity transducer and differential infrasound sensor. The adaptive technique is demonstrated for recovering seismic arrivals in both the vertical and horizontal channels across all eight stations, and evaluated using leave-one-out cross-validation across the three explosions.&amp;lt;/p&amp;gt;
Aligning Realities: Correlating Content between Projected and Head Worn Displays

Enabling the effective representation of an object’s position and depth in augmented reality (AR) is crucial not just for realism, but also to enable augmented reality’s wider utilization in real world applications. Domains such as architecture and building design cannot leverage AR’s advantages without the effective representation of position. Prior work has examined how the human visual system perceives and interprets such cues in AR. However, it has focused on application systems that only use a single AR modality, i.e., head-mounted display, tablet/handheld, or projection. However, given the respective limitations of each modality regarding shared experience, stereo display, field of view, etc., prior work has ignored the possible benefits of utilizing multiple AR modalities together. By using multiple AR systems together, we can attempt to address the deficiencies of one modality by leveraging the features of other modalities. This work examines methods for representing position in a multi-modal AR system consisting of a stereo head-mounted display and a ceiling mounted projection system. Given that the AR content is now rendered across two separate AR realities, how does the user know which projected object matches the object shown in their head-mounted display? We explore representations to correlate and fuse objects across modalities. In this paper, we review previous work on position and depth in AR, before then describing multiple representations for head-mounted and projector-based AR that can be paired together across modalities. To the authors’ knowledge, this work represents the first step towards utilizing multiple AR modalities in which the AR content is designed directly to compliment deficiencies in the other modality.
UWM Libraries Research and Course Guides: Citation Managers: Zotero

Includes information on how to select a citation management tool and how to transfer your library into it from RefWorks.
Peningkatan Keakuratan Data Penelitian melalui Pengujian Instrumen dengan Metode Bivariate Pearson dan Split Half

A valid and reliable research instrument used in gathering research data is an instrument that has been tested for validity and reliability. Validity testing is done to see whether the questions in the research instrument are valid or biased, while the reliability test is done to see the level of reliability of the research instrument. Especially research that is a case study, collecting research data using research instruments (questionnaire or questionnaire). To assist researchers in testing research instruments, the results of this study will create a system for testing the validity and reliability of research instruments that are easy to use by researchers so that the research data to be collected is more accurate.
Papel de la biblioteca médica en el Proceso Docente Educativo durante la COVID-19

The Medical Library of the Academic Polyclinic Dr Ramon Claudio Delgado Amestoy Area VI,is a center that provides information to internal and external users of the Castillo- Cen Distrct .It is an institution that provides different services as a specialized center of biomedical sciences, giving a response in addition to the training and information needs from the different health problems that occur in the community. This research identifies the actions carried out by the staff of the Medical Library for the reorganization of the educational teaching process in COVID-19 times
Finland / Russia: Allegro rail services start on 12 December – UIC Communications

High-speed Allegro rail services between Helsinki and St. Petersburg start on 12 December. The travel time between the two cities will be cut by two hours to three and a half hours. Travel time…
Folk Song Lab : improvising folk songs

This is a presentation of an on-going project funded by the Swedish Research Council called Folk Song Lab - deconstruction, improvisation and flow”,The purpose of the project is to develop and exp ...
Review of Kalah Game Research and the Proposition of a Novel Heuristic–Deterministic Algorithm Compared to Tree-Search Solutions and Human Decision-Making

The Kalah game represents the most popular version of probably the oldest board game ever—the Mancala game. From this viewpoint, the art of playing Kalah can contribute to cultural heritage. This paper primarily focuses on a review of Kalah history and on a survey of research made so far for solving and analyzing the Kalah game (and some other related Mancala games). This review concludes that even if strong in-depth tree-search solutions for some types of the game were already published, it is still reasonable to develop less time-consumptive and computationally-demanding playing algorithms and their strategies Therefore, the paper also presents an original heuristic algorithm based on particular deterministic strategies arising from the analysis of the game rules. Standard and modified mini–max tree-search algorithms are introduced as well. A simple C++ application with Qt framework is developed to perform the algorithm verification and comparative experiments. Two sets of benchmark tests are made; namely, a tournament where a mid–experienced amateur human player competes with the three algorithms is introduced first. Then, a round-robin tournament of all the algorithms is presented. It can be deduced that the proposed heuristic algorithm has comparable success to the human player and to low-depth tree-search solutions. Moreover, multiple-case experiments proved that the opening move has a decisive impact on winning or losing. Namely, if the computer plays first, the human opponent cannot beat it. Contrariwise, if it starts to play second, using the heuristic algorithm, it nearly always loses.
Loma Linda University Libraries: Earth & Biological Sciences Guide: Off-Campus & Mobile Access

A guide to the information resources for students in the Department of Earth & Biological Sciences
Extreme Learning Machine for Multilayer Perceptron Based on Multi-swarm Particle Swarm Optimization for Variable Topology

Extreme Learning Machine for Multilayer Perceptron(H-ELM) is a newly developing learning algorithm for the generalized multiple hidden layer feed-forward neural networks, of which training architecture is structurally divided into two separate phases: 1) unsupervised hierarchical feature representation and 2) supervised feature classification. However, due to its hand-designed network structure, researchers need to spend a lot of effort on adjusting the structure, which is an error-prone process. To solve the issue, in this paper, a novel fully connected neural network architecture search method based on particle swarm optimization (PSO) algorithm is proposed for H-ELM. The proposed algorithm framework is divided into two main parts: 1) Architecture search based on PSO algorithm and 2) Weight analysis based on H-ELM. The novelties of the paper are as follows: 1) Optimizing the structure of fully connected neural networks by using multi-swarm particle swarm optimization algorithms, and improve it so that the structures of different hidden layer numbers can learn from each other. 2) Minimum principle of structure: Minimize the total number of nodes in the resulting network while ensuring the accuracy of network evaluation. A large number of experiments on various widely used classification datasets show that the algorithm could achieve higher accuracy with more compact network structure than the optimal results in the randomly generated structures.
Summarizing Dynamic Graphs using MDL

How can we succinctly describe a large, dynamic graph over time? Given a large dynamic graph, can we �find important patterns that evolve over time, so that we can easily summarize and visualize the graph? In real life, these patterns signify interaction between nodes over time -- for example, how the network traffic of a bank changes during the day, how calling patterns change season over season, or how people watch different genre of movies over different times of the year. Our work focuses on the problem of how to find and rank these patterns. To this end, we formalize this problem as minimizing the encoding cost in a data compression paradigm and propose Mango, an effective heuristic for discovering evolving patterns in dynamic graphs. We then apply our method to both synthetic and real datasets to show that Mango is able to summarize dynamic graphs by meaningful static and temporal patterns.
واقع استخدام تكنولوجيا السبورة الذكية يف معاهد العلوم اإلسالمية بسلطنة عمانThe reality of using smart board technology in Islamic Science institutes in Oman

This study aimed to reveal the reality of using smart-board technology in the Islamic institutes in the Sultanate of Oman. The study’s population consists of 80 teachers, all of them work at the Islamic Institutes in the Sultanate of Oman . The research was applied to the teachers in the institutes (67 teachers) selected in accordance with the intentional method of sampling.The researcher used the descriptive method. The data collection/research tool was designed and developed by the researcher. The research tool is a questionnaire consisting of six axes and 45 items. The results of the mathematical averages of the research questions showed, a medium degree of smart-board readiness (availability) for use in classrooms , and a large degree of challenges encountered by teachers in using smart-board. As for the teachers’ suggestions (proposed vision of implications) to develop smart-board use, holding workshops for teachers on how to make the best use of smart-board is revealed to be the most frequent response. Based on the results, the researcher recommended holding inductions and introductory workshops for teachers about smart-board and how to make the best use of it as one of the privileges available in the Islamic Institutes.
THE IMPLEMENTATION OF SUMMARIZING ACTIVITY BY USING SOMEBODY WANTED BUT SO (SWBS) STRATEGY TO IMPROVE STUDENTS’ READING COMPREHENSION

The aim of this research is to find out if there is a significant difference between the students who were taught through summarizing activity using somebody wanted but so (SWBS) strategy than those who were not taught through the strategy to improve the students’ reading comprehension in terms of finding out the main idea, specific information, word meaning, reference, and inference. This study employed a true experimental design in which there were two classes as the samples classified into experimental and control classes. The classes were chosen by using cluster random sampling and each class consisted of 36 students. In collecting the data, pre-test and post-test were used and the data were analyzed by using SPSS version 21. The result of the study found the post-test mean score at the experimental class is 84.78, and the post-test mean score at the control class is 73.33. Furthermore, the result of the z-score between both experimental and control classes is 6.05 at the level significance of 5% (0.05). Thus, it indicates that there is a significant difference between the students who were taught through SWBS strategy than those who were not taught through this strategy to improve the students’ reading comprehension.
GPGPU-Based Parallel MFCC using a Multi-Kernel Overlapping

Recently, machine learning applications using audio data are increasing. MFCC is widely used as a feature extraction technique to utilize audio data. It takes a long execution time to compute MFCC with a large amount of audio data. Also, a fast MFCC computation method is necessary for real-time inference. In this study, a GPU-based parallel MFCC using a multi-kernel overlap is proposed to fast compute MFCC. The proposed GPGPU-based parallel MFCC is 434 times faster than CPU-based MFCC. When processing 800 audio data, the proposed GPU-based MFCC using multi-kernel overlap was 2.87 times faster than the previous GPU-based MFCC. Besides, in case processing a long single streaming audio data, the proposed one achieved 1.3 times speed-up compared with the previous one.
Design of a scalable 2-party token exchange : An experimental study

Context: Blockchain technology is the latest buzzword in the fintech industry. It is hyped as a game-changer in several use-cases in the financial sector. One such leading use case is asset trading ...
Visualization of 4-component borehole strainmeter data in China

&amp;lt;p&amp;gt;With the accumulation of 4-component borehole strainmeter data&amp;amp;#160;and the improvement of observation reliability, it is a&amp;amp;#160;primary of current research to improve the efficiency of processing, analyzing&amp;amp;#160;and visualizing of these data. The visualization of borehole strain observation data is a key means to convey the information behind the data, display the data research results and extract the shallow surface stress state revealed by borehole strain.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Borehole strainmeter data are of great significance for earthquake prediction research due to its&amp;amp;#8217; high resolution in short-medium term time scale of earthquake prediction. With the progress of observation technology, many four-component borehole strain gauges in China had experienced the data stabilization period, the early years of establishing the instrument, and the borehole strain station began to obtain a batch of high-quality observation data.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;By using the normal stress petal diagram to show the change of the ground stress, it&amp;amp;#160;can not only qualitatively analyze the change of the relative ground stress of the station, but also quantitatively read &amp;amp;#160;the observed normal stress in any direction at a certain time.&amp;amp;#160;In this paper, the&amp;amp;#160;method&amp;amp;#160;of normal stress petals diagram&amp;amp;#160;is combined with map visualization technology to process and analyze the strain observation data of four-component borehole across the country. The main works are as follows: first of all,&amp;amp;#160;The construction of the stress petal visualization platform can display the dynamic stress effectively in all directions of 30 stations across the country; secondly, Variable sliding window length and sliding spacing added according to specific needs can not only directly display the change of the stress petal over&amp;amp;#160;the years, but also show the stress petal map of the solid tide strain all over the country; thirdly,&amp;amp;#160;The platform can display the co-seismic stress petal variation image observed at the national borehole strain stations and visually show the stress changes observed by the local borehole strain gauge during the seismic wave propagation. Finally,&amp;amp;#160;The borehole strainmeter data can monitor the relative geostress state of the fault near the borehole. Then the magnitude and direction of the maximum principal stress at the borehole strain station reflected by the stress petal can further calculate the corresponding changes of dynamic coulomb stress and static coulomb stress which can help to analyze seismic dynamic triggering problems.&amp;lt;/p&amp;gt;
ELM Algorithm Optimized by WOA for Motor Imagery Classification

The analysis of electroencephalogram (EEG) data is of considerable help to people with brain disease, and effective feature extraction classification approaches are needed to improve the recognition accuracy of EEG signals. In this paper, we propose an approach for EEG signal classification based on combination features and WOA-ELM algorithm. First, combination features take in account both principal component features by Principal Component Analysis (PCA) and label information of the training data by Linear Discriminant Analysis (LDA). Second, WOA-ELM algorithm is the optimized ELM algorithm to improve the ill-conditioned Single-hidden-Layer Feedforward neural Networks (SLFN) problem, the weights and biases between the input layer and the hidden layer of basic Extreme Learning Machine (ELM) are optimized by the Whale Optimization Algorithm (WOA) through bubble-net attacking strategy and shrinking encircling mechanism of humpback whales. The experimental results show that the highest classification accuracy of proposed method is 95.89% on motor imagery of BCI dataset. Compared with other methods, the proposed method has the competitive classification result.
Fashion and Related Intellectual Property Rights Issues

There is a substantial effort to create an intellectual capital in the domain of fashion and further its value addition. Fashion design is a form of art dedicated to the creation of clothing and other lifestyle accessories. Due to inadequate awareness on the subject, not only the individual fashion designers but many small and medium-sized enterprises do not appreciate protecting such intellectual assets. Now days, in the business environment, intellectual assets have proved the competitive advantage, including those in the fashion industry. Many fashion hoses earning a lot by commercializing their IPR in their fashion creations by licensing. Licensing means renting or leasing of an intangible asset. It is a process of creating and managing contracts between the owner of a brand and a company or individual who wants to use the brand in association with a product, for an agreed period of time, within an agreed territory.
Simulating One- and Two-Dimensional Ising Models in a Magnetic Field Using a Coherent Ising Machine

We report a coherent Ising machine (CIM) based on degenerate optical parametric oscillators with a magnetic field. The CIM successfully simulated behaviors of one- and twodimensional networks of 400 spins in a uniform magnetic field.
Construction of Internet Plus Standards System

The rapid development of information technology has brought new opportunities for the Internet Plus initiative. Meanwhile, the requirements of Internet Plus technologies, industries, and applications are difficult to satisfy by the current Internet Plus standards; therefore, an Internet Plus standards system needs to be constructed. This study aims to conduct theoretical research on the construction of the Internet Plus standards system. It analyzes the current status of general standards for key technologies, integration standards, and sub-sector standards systems related to Internet Plus and summarizes the problems facing future development. A preliminary plan for the Internet Plus standards system is proposed, covering six aspects: general standards, security, common support, service integration, guidelines and evaluation, and application. To meet the standardization needs of sub-sectors such as collaborative manufacturing, modern agriculture, smart energy, people-benefiting services, intelligent transportation, and green ecology, specific recommendations are proposed for Internet Plus standards formulation as well as its application and promotion mechanisms. Furthermore, effective pilot demonstration, scientific talent training, and a sound long-term mechanism are the effective guarantee for the Internet Plus standardization practice.
LibGuides: Guide to Dewey Decimal Classification: Introduction

Understanding the Dewey Decimal Classification system which is used to organise books in the Library.
Rater and algorithm data of maximum reading speed (MRS) and critical print size (CPS) of 101 low vision participants.

Rater and algorithm data of maximum reading speed (MRS) and critical print size (CPS) of 101 low vision participants.
Task Scheduling in the Cloud Amended Through Genetic Algorithms

At present, cloud computing is used far and wide in companies and institutions. Yet, there are some challenges in using cloud computing. The central challenge is resource management, as cloud computing provides IT resources (for example, CPU, memory, network, storage, etc.). Furthermore, it builds on the concept of virtualization and the pay-as-you-go principle. The management of these resources has been the subject of considerable research. A task scheduling algorithm is based on genetic algorithms (GA) to allocate and implement tasks specific to the application. The use of a genetic algorithm for the distribution of tasks and schedules seeks more and more attention from scholars. To solve the difficulty of resource scheduling in large-scale, nonlinear cluster systems, and has achieved ideal effects GA has been widely applied. By what means to make reasonable use of computing resources that creates total and average time complete a shorter and smaller task costing an important issue. Research spectacles that artificial methods can achieve, further optimal load balancing than traditional approaches.