Reviewerly/exHarmony huggingface dataset:
NUMERALS IN MODEL OF HUMAN KNOWLEDGE REPRESENTATION

The purpose of this study was to create a system of knowledge representation in information systems most similar to the model of human knowledge representation. The problem of plain arithmetic operations and numerals representation was chosen as a main goal. Knowledge representation in general terms was chosen for the current problem as a first goal. For this purpose psychological theories and experiments about human knowledge representation models were overviewed. As en example, the "violin" experiment was given. This experiment confirms the idea of information representation in human's mind as a net of entities connected by associative relations. As an analogue of such structure in information technologies world semantic networks were considered. This structure was chosen because semantic networks use the same idea of knowledge representation as a graph. Ontology as a pattern of semantic networks construction is also considered. Following this pattern edges and their relations are joined into classes with common properties and behavior. Finally, technical and psychological approaches were compared to chose the most correct way to represent information as humans do. But the problem of numerals representation in human's mind also has its own psychological problems. Such concepts of numbers for adults and children differences were shown. Requirements for this concept were specified, such as: the measure and the sequence of information representation. Guided by this rules the concept of Church numerals was chosen. This concept exists in lambda calculus, which base ideas were described in the paper as well. Church numbers approach in terms of semantic networks was also given. For calculations simplification the addition table idea was used and applied with semantic networks context. But a human usually uses place-value notation when big numbers are required. And Church numbers use too much memory in this situation (an addition table grows too fast with maximum of number defined in Church notation). So the place-value notation which uses Church numbers as digits and as a position marker was given.
Denoising InSight’s marsquake recordings with deep learning

Marsquake recordings by NASA&amp;#8217;s InSight seismometer often have low signal-to-noise ratios (SNR) owing to low marsquake amplitudes - only a handful of events are over M3.5 and epicentral distances are large, due to the single station being located in a seismically quiet region, and highly fluctuating atmospheric, spacecraft and instrumental noise signals.We have previously shown [1] how deep convolutional neural networks (CNN) can be used for 1) event detection - thereby producing an event catalogue consistent with the manually curated catalogue by the Marsquake Service (MQS) [2], and further extending it from 1297 to 2079 seismic events - as well as for 2) separating event and noise signals in time-frequency domain. Due to the low number of events readily-available for network training, we trained the CNN on synthetic event data combined with recorded InSight noise.Here, we construct a semi-synthetic data set (with real marsquake &amp; noise data) to assess the denoising performance of the CNN w.r.t. to various evaluation metrics such as SNR, signal-distortion-ratio, cross-correlation, and peak amplitude of the recovered event waveforms, and compare modifications of the CNN architecture and the training data set.For a large number of identified events [1,2] no distance estimates are available (or only with high uncertainty), and for all but a small subset the back azimuth is unclear, as the relatively high background noise often obscures this information in the waveforms. We explore how the denoised waveforms can support the phase picking and polarisation analysis of marsquakes, and with that their localisation, as well as their general characterisation.&amp;#160;References:[1] Dahmen et al. (2022), doi: 10.1029/2022JE007503[2] Ceylan et al. (2022), doi: 10.1016/j.pepi.2022.106943
Review of existing data for the evaluation and estimation of the geothermal potential in the basement of western Spain.

The last few years have been characterized by tremendous global instability due to assure energy supply. Global growth demands more and more resources at the same time as the population&amp;#180;s concern about climate change is increasing. In this context, geothermal energy, a green and renewable energy with the capacity to contribute to the transition of the energy market, is becoming increasingly important. This, together with the improvement in geothermal studies and the development of new exploitation methods, has triggered new geothermal targets to be considered during the last decades.Geothermal studies in Spain were focused on sedimentary basins and volcanic settings during the 70&amp;#180;s and 80&amp;#180;s. In this framework, few investigations have been done on the western igneous massif of Spain. This study seeks to estimate and resume research on the geothermal potential of the Spanish basement. With that purpose this research analyzes high resolution airborne radiogenic data from Extremadura, Castilla La Mancha and Madrid (Geodata International Inc., 1980), acquired in the 70 and 80&amp;#180;s for uranium exploration, concentration measurements of Uranium, Thorium and Potassium from soil samples (Locutura et al. 2012) and temperature data from widespread hot springs along the studied area.We have analyzed the concentration of the three heat producing elements in 9 plutons and estimated the heat production of each of them. In this regard, the high airborne-constrained concentrations of the plutons located in the north of Extremadura and west of Salamanca are noteworthy. In this area Uranium reaches 16.43 ppm, Thorium 14.52 ppm and Potassium 6.26 %. Same way a remarkable peak in heat production is located is this area with values up to 5.02 &amp;#956;W/m3. When comparing these data with the values obtained from the soil samples, the correlation between the two is remarkable. Furthermore, the positive radiometric anomalies of both maps coincide with the outcropping of granitic rocks and the location of most of the hot springs.This work compiles vintage information of diverse origin in order to highlight areas with high geothermal potential in the basement of the westernmost Spain. The results of heat production and their relationship with the hot springs have shown that several of the Paleozoic plutons of the western igneous massif of Spain may have a great potential for geothermal projects.
Envirosciences - a multi-parametric low-cost and modular station for documenting geohazards: station specifications and time series products

Envirosciences is developing an integrated multi-parameter low-cost monitoring station encompassing the geohazard and geophysical community needs. It consists in integrating co-located sensors ((meteorology, seismology, GNSS) on the same data acquisition card with modular configurations compatible with the EPOS - European Plate Observing System- specifications (sensor type, data sampling, noise level, data and metadata format). On-line data dissemination sand on-demand processing services are further being developed in order to propose advanced products such as GNSS position time series, advanced hydro-meteorological variables and seismic/micro-seismic catalogues.A dense network of 45 stations is currently being implemented in the Western and Central Pyrenees (South France). The network consists of a seismological, meteorological and geodetic (GNSS) antennas. The measurement network is semi-permanent with at least ten years of observation. It will allow to create catalogues of hydro-geomorphological and tectonic events, to document Pyrenean tectonic uplift, and to better constrain local micro-meteorology from the valley bottoms to the summit ridges (by combining co-localised measurements of classic meteorological parameters - wind, temperature, pressure, humidity, precipitation - and tomography of vertical water vapor profiles from GNSS delays).The objective of the presentation is to present the technological development of the station which combines several types of sensors (2 Hz seismometers, dual-frequency GNSS receivers and meteorological stations), a high-frequency geophysical digitization module, a communication module (WiFi or4G) and a power supply module (by solar energy or 220V). Softwares to control the station have been created, as well as software to supervise the database and codes to interpret the measurements.We will further present the processing worklows and the time series of data acquired since November 2022 on 8 measurement stations already deployed in the Pyrenees. By the end of 2023, the full network of 45 autonomous real-time stations will be deployed with inter-station distances of around 5 km.
ANALYSIS OF THE IMPACT OF DISTORTION ON SOUND RECORDINGS AS ANTI FORENSIC ACTIVITIES

Anti-forensics on audio is aimed at complicating investigations on audio forensics, on sound recordings. Sound recordings can be altered or manipulated in various ways as well as the provision of distortion effects on sound recordings. Effect such distortions will make it difficult for investigators to find out the owner of the original voice. Analysis of distortion effects on sound recordings for anti-forensic activities, has not been widely carried out. Distortion can be an effective anti-forensic technique because the sound produced will be noisy, making it difficult for investigators to conduct investigations. In this study, testing was carried out using 3 types of distortion, namely Hard Clipping, Hard Overdrive and Odd Harmonics. To find out the extent to which the three types of distortions make it difficult to identify the owner of the original sound, the variables that affect each type of distortion are set at low, medium, and high levels. Formant values from the original and distorted sound samples were compared for later analysis using the Anova One-Way approach to show whether the original sound was identical and the other three voices were distorted. The test was carried out using 10 sound samples. From the results of the anova analysis, it is known that the types of Distortion of Hard Clipping and Odd Harmonics with variables at high levels can manipulate sound recordings, making it difficult to recognize the authenticity of a sound recording. Unlike the case with the type of Distortion of Hard Overdrive with variable level high – low and Hard Clipping and Odd Harmonics with variable level low – medium, it proves that sound recordings can still be identified.
FULL-STACK SOFTWARE SOLUTION MANAGEMENT ARCHITECTURE

The article proposes an architecture of web based Full Stack End To End Software Solution Management System.The Full Stack End-to-End Software Solution Management System (FSSSMS) is a powerful software platform that streamlines the entire lifecycle of software development, deployment, and maintenance.By serving as a centralized hub for software development teams, the FSSSMS facilitates planning, designing, developing, testing, deploying, and maintaining software applications.The FSSSMS comes equipped with a diverse set of tools and features tailored to support these functions, including project management tools, code repositories, testing tools, deployment automation, and monitoring and reporting tools.By leveraging these tools, teams can work collaboratively and efficiently, deliver high-quality software applications, and scale their operations as needed.
Model selection and signal extraction using Gaussian Process regression

A bstract We present a novel computational approach for extracting localized signals from smooth background distributions. We focus on datasets that can be naturally presented as binned integer counts, demonstrating our procedure on the CERN open dataset with the Higgs boson signature, from the ATLAS collaboration at the Large Hadron Collider. Our approach is based on Gaussian Process (GP) regression — a powerful and flexible machine learning technique which has allowed us to model the background without specifying its functional form explicitly and separately measure the background and signal contributions in a robust and reproducible manner. Unlike functional fits, our GP-regression-based approach does not need to be constantly updated as more data becomes available. We discuss how to select the GP kernel type, considering trade-offs between kernel complexity and its ability to capture the features of the background distribution. We show that our GP framework can be used to detect the Higgs boson resonance in the data with more statistical significance than a polynomial fit specifically tailored to the dataset. Finally, we use Markov Chain Monte Carlo (MCMC) sampling to confirm the statistical significance of the extracted Higgs signature.
GEOSCOPE: 40 years of global broadband seismic data

The GEOSCOPE observatory provides more than 4 decades of high-quality continuous broadband data to the scientific community. Started in 1982 with a few stations, the network has grown over the years thanks to numerous international partnerships. The 33 operational GEOSCOPE stations are now installed in 18 countries, across all continents and on islands throughout the oceans, filling important gaps in the global Earth coverage (in Africa, Antarctica, Indian Ocean, Pacific Ocean islands and more). Most of the first installed stations are still running today allowing for long term observations and new sites are being prospected for future installations.Over the years GEOSCOPE contributed to define today's global seismology standards through the FDSN (data format, data quality level, instrumentation requirements), being the french contribution to the international effort (with GSN, GEOFON and others) towards global seismic observations. The stations are equipped with the best quality seismometers (from the very first STS1 in the early 80's to the last STS-6A and Trilium T360 nowadays) and digitizers (Q330HR and Centaur), in order to record with a high fidelity the ground motions generated by all types of seismic sources. Furthermore, most of the stations are also equipped with accelerometers, pressure and temperature sensors allowing for a wider range of observable events such as the recent Hunga-Tonga eruption. All the data are sent in real-time to IPGP data center and are automatically transmitted to other data centers (IRIS-DMC and RESIF) and tsunami warning centers.In 2022, a workshop has been organized to celebrate the 40th anniversary of GEOSCOPE and illustrate the main scientific achievements made possible by all the global networks. After a brief look at the history of the network and a feedback on the workshop, the recent evolutions of the observatory (new stations in Africa, new generation 360s sensors upgrades, IT infrastructure) and the perspectives (future stations) will be presented.
Addressing pressing global societal research challenges through targeted harmonisation of macrosystems ecology data sets

Guided by the Framework Criteria of the Group of Senior Officials (GSO) on Global Research Infrastructures, 6 major ecosystem research infrastructures (SAEON/South Africa, TERN/Australia, CERN/China, NEON/USA, ICOS/Europe, eLTER/Europe) came together in 2020 under an MOU, establishing the Global Ecosystem Research Infrastructure (GERI). &amp;#160;With its goal of providing interoperable data and services based on terrestrial and coastal in-situ observations from a high number of observational sites, organized in a common hierarchical system and standardized in the highest possible degree, GERI provides a unique opportunity to advance our understanding of ecological processes across continents, decades, and disciplinary boundaries. Aggregating ecological and biogeophysical data is complex. Not only do those data cover a myriad of different types of natural phenomena, and the interactions between, but the data are generated in different jurisdictions using different standards and approaches. Thus, as a critical first step in understanding the challenges and potential of its multi-institutional, multi-country data landscape, GERI has identified and mapped all the data types from each of its members, grouping the data suites provided by each GERI member into the drivers of changes (causes) and the ecological processes (effects) and then visualizing it into broad (searchable) respective common ecological categories. This exercise has allowed evaluation of the potential for a targeted data harmonization effort based on a subset of data products with high relevance to specific use cases (e.g., drought across multiple continents). By using the subset of relevant data as a community test case, GERI can ascertain the efficacy of a specific harmonized data set in advancing a priority area of science. Such a prototype will set the stage for future efforts and ensures GERI addresses the most pressing global research challenges, i.e. those frontiers of knowledge where a global-critical-mass effort is required to achieve progress.&amp;#160; &amp;#160;
Hazy Image Enhancement Using DCP and AHE Algorithms with YIQ Colour Space

The use of hazy images is amongst the fastest ways to identify natural resources.Aerial photography has overcome the obstacles faced in land areas, such as rugged areas, swamps and sand dunes.It has important applications in tracking and monitoring studies during wars and peace.However, aerial images often suffer from the lack of contrast due to dust and pollutants.Therefore, this study attempts to improve aerial images by modified dark channel prior (DCP) and adaptive histogram equalisation (AHE) algorithms with YIQ.The images are first improved through DCP and then converted into YIQ colour space that saves the chromatic compounds (IQ).The lighting component comes out after improving the original aerial image via the stretch technique and AHE.Afterwards, all the compounds are merged, and reverse transformation is performed.The proposed method for improving aerial photographs was compared with several other methods.By analyzing the results, the proposed method obtained the best measures of quality, including an entropy value of (7.771), an average gradient value of (14.207) and a naturalness image quality evaluator value of (3.700).
Meta Triplet Learning for Multiview Sign Language Recognition

Multiview video processing for recognition is a hard problem if the subject is in continuous motion.Especially the problem becomes even tougher when the subject in question is a human being and the actions to be recognized from the video data are sign language.Although many deep learning models have been successfully applied for sign language recognition (SLR), very few have considered multiple views in their training set.In this work, we propose to apply meta metric learning for video-based sign language recognition.Contrasting to traditional metric learning where the triplet loss is constructed on the sample-based distances, the meta metric learns on the setbased distances.Consequently, we construct meta cells on the entire multiview dataset and perform a task-based learning approach with respect to support cells and query sets.Additionally, we propose a maximum view pooled distance on sub-tasks for binding intraclass views.The results of experiments conducted on the multiview sign language dataset and four action datasets show that the proposed multiview meta metric learning model (MVDMML) achieves 11% higher performance than the baselines.
Pengaruh Playstation Terhadap Prestasi Belajar Siswa Bidang Studi Aqidah Akhlak Kelas IV Di Madrasah Ibtidaiyah Muhammadiyah 03 Weru

In this study the author uses quantitative methods, while for data collection using questionnaires, documentation, observation, while the population is the entire number of fourth grade students at MI Muhammdiyah 03 Weru-Paciran, totaling 35 students and 25 being taken as samples. To analyze the final results the author uses the Product Moment formula with the formula: rxy= (?xy)/?((?x^2 )(?y²)).In this study, the results obtained from data analysis using the Product Moment formula which the results reached 1.0208 were rounded up to 1. So the results and conclusions can be obtained that playing Playstation games is very influential on student achievement in the Aqidah Akhlak class IV study at MI Muhammdiyah 03 Weru-Paciran.
Kickstarting scientific engagement with art: An EGU-situ experiment

Science, at its core, is about making sense of the world around us. So it is somewhat ironic that, more often than not, scientific results are presented in ways that leave specialist audiences baffled, and cause the general public to run in the opposite direction. This is worrying because scientific progress relies on effective scientific communication and knowledge exchange.In recent years, we&amp;#8217;ve seen a proliferation of examples illustrating how art (or at least a more creative approach) can help us, scientists, overcome some of the barriers between our science and the outside world. These range from contributions highlighting the &amp;#8220;how and why&amp;#8221; of creating scientifically accurate and universally accessible graphics (e.g. Crameri et al., 2022s-ink, colormaps?), to projects where scientific content is simply the inspiration behind abstract illustration (e.g. Wadsworth et al., Nat. Geosci. 15). The first puts the focus on the information being presented, whilst the second is aimed more strongly at catching the audience&amp;#8217;s attention, as the first critical step in engaging with potential readers for a science piece. Whilst they are fundamentally different, both of these extremes (and all the possible art-science crossovers in between) show us the huge power of visual storytelling for science communication.In this contribution, we will experiment withshare a series of interesting geoscientific data visualisations accompanied by short explanations created by a scientist and, illustrateding by an artistinteresting geoscientific facts. Our aim was to create pieces that, through their artistic quality, can originate a spark of curiosity in the viewer strong enough to prompt them to pay closer attention for the length of time required for them to interiorise the scientifically accurates&amp;#160; information being presented. We will collect direct feedback from engaging viewers (in this case EGU GA participants). In doing this, we hope to show, and understand better, the ability of art to kickstart that critical two-step process, where curiosity leads to engagement, which is fundamental for effective communication. And, to generate beautiful office wall decorations in the process.&amp;#160;Crameri, F., G.E. Shephard, and E.O. Straume (2022, Pre-print), Effective high-quality science graphics from s-Ink.org, EarthArXiv, https://doi.org/10.31223/X51P78Wadsworth, F.B., Vasseur, J., Anagnostopoulos, I. et al. Estimating pi using geoscience. Nat. Geosci. 15, 246&amp;#8211;247 (2022). https://doi.org/10.1038/s41561-022-00928-z
On the rank decoding problem over finite principal ideal rings

The rank decoding problem has been the subject of much attention in this last decade.This problem, which is at the base of the security of publickey cryptosystems based on rank metric codes, is traditionally studied over finite fields.But the recent generalizations of certain classes of rank-metric codes from finite fields to finite rings have naturally created the interest to tackle the rank decoding problem in the case of finite rings.In this paper, we show that solving the rank decoding problem over finite principal ideal rings is at least as hard as the rank decoding problem over finite fields.We also show that computing the minimum rank distance for linear codes over finite principal ideal rings is equivalent to the same problem for linear codes over finite fields.Finally, we provide combinatorial type algorithms for solving the rank decoding problem over finite chain rings together with their average complexities.