Reviewerly/exHarmony huggingface dataset:
POSSIBILITIES OF IMPLEMENTING VIRTUAL GAMES IN ORDER TO INCREASE THE EFFICIENCY OF TRAINING IN JUNIOR HANDBALL PLAYERS

The accelerated development of technology in recent years, coupled with lower prices for electronic components and easy access to information via the Internet, has led to the emergence of computer-aided devices/interfaces that can be used in various fields and implicitly in sports. In this context, the purpose of the paper is to highlight the effects of using the Microsoft Kinect 360 device in order to increase the efficiency of specific training in the handball game. Microsoft Kinect 360 is a versatile multimedia device that can be used as a 3D scanner that provides a variety of functions. In our application, we have exploited the space perception capability of the Kinect sensor that is placed in front of a wall on which the image of the game is also projected; the sensor is mounted and calibrated so as to fully display the projection image; the calibration is done using the LKB program; the LKB system (Linguistic Knowledge Builder) is a grammar and lexicon development environment for unification-based linguistic formalisms. The software part is specifically designed for the training of handball players. The paper presents handball-specific virtual games applied to a group of 22 female players born in 2005/2006, members of the ACS Sporting Ghimbav team. The virtual games applied in the training lessons are aimed at the practice of handball-specific technical elements in an entertaining environment, on an interactive wall, in order to educate the subjects' specialised perceptions. The conclusions of the study highlight useful information on the way of improving the sports training of female players aged 12 to 15 years.
Automatic labeling of the Training Dataset for Individual and Group Activities Detection

Real-time activity detection is one of the interesting fields of research due to its wide range of applications in human-computer interaction, health monitoring, security, workers' performance monitoring, safety, etc. Computer vision and deep learning is one of the most popular solutions to detect human activities. However, these solutions often suffer from inadequate training datasets in terms of quantity and quality. Additionally, the procedure of data labeling is time-consuming and expensive. This paper proposes an automated method for labeling data for automatic individual and group activity detection. The proposed algorithm takes advantage of combining simple object classes (such as hands, and persons) and spatial relationship rules to label the training dataset for detecting activities like covering coughs with an arm or hand, hugging, and hand-shaking. These activities were used for Covid risky activities monitoring at workplaces. To implement this algorithm, we used You Only Look Once (YOLO) and Mask Reginal Convolutional Neural Network (Mask-RCNN) object detection and we applied the transfer learning from the Common Object in Context (COCO) CNN model. The results showed 96% precision of data labeling for covering coughs with a hand, 93% for covering coughs with an arm, 89% for hugging, and 87% for handshaking activities. This is while, the average precision of activity detection using automatically annotated data, only decreased by 3% for Mask RCNN and 5% for YOLO. Also, the separation of the individual and group activity classes led to more detection precision. In conclusion, the proposed automatic data labeling algorithm preserved the quality of data annotation while outperforming the training-data annotation speed.&amp;#160;
Modeling the waveforms of induced seismicity sequences with application to Utah FORGE

We present a modeling workbench for generating hours-long synthetic sequences of induced seismic events. As input, this tool takes observed or synthetic catalogs of induced seismicity including the location, seismic moment and source mechanism of the induced events. It outputs synthetic seismic waveform recordings with added noise.The purpose of this tool is two-fold: First, it serves to generate synthetic test data that can be used to train detection and location algorithms for induced seismicity monitoring, and to test their efficacy. Monitoring induced seismicity is a key task for the risk management of enhanced geothermal systems, but the relative scarcity of manually labeled data hampers rigorous testing of newly developed algorithms. We intend to partially close the gap in labeled data with synthetics, which can furthermore be used to enhance training data sets for deep learning approaches.Second, the tool serves as an extension to physics-based models of induced seismicity in geothermal reservoirs, such as hydro-mechanical models, providing an efficient way of turning their induced event clouds into seismic &amp;#8220;recordings&amp;#8221;.The workflow is based on the spectral-element solver Salvus and on Python, and relies on source-receiver reciprocity to decrease computational cost for large sets of induced events. As first application site, we chose the Utah Frontier Observatory for Research in Geothermal Energy &amp;#8211; FORGE. This first application comprises a realistic digital representation of the reservoir and its surroundings, including topography, geologic structure and crustal scattering. We will show exemplary synthetic induced seismicity sequences based on an observed catalog from the 2022 stimulation at the Utah FORGE, as well as on a hydro-mechanically modeled synthetic catalog. The output waveform sequences are to be publicly shared for benchmarking monitoring workflows for induced events, in an effort to contribute to the de-risking of enhanced geothermal systems.
Geodatabase of structural data from North Victoria Land (Antarctica): a useful tool for geodynamic modelling

Here we present an open access GIS project associated to a structural database which includes the geo-structural measurements (over 6000) collected in the field during the past Italian PNRA (National Antarctic Research Program) scientific expeditions from the year 1988 to 2021. The targeted research area is the North Victoria Land (NVL), Antarctica, between the 70&amp;#176;-76&amp;#176; S latitude and the 159&amp;#176;-171&amp;#176; E longitude.NVL is an area difficult to be accessed for direct geological studies on rocks due to the extensive ice/snow coverage (~5%) and few published studies with complete structural datasets are available so far.Our database is organized in various fields which include: number/code of the expedition, date, code of the site of field structural measurement, geographical coordinates of the field measurement site, elevation, toponyms, lithological classification, geological unit, description of any collected sample, name of the field data collector, classification, attitude of measured structural element (strike/trend, dip/plunge, dip/plunge direction), local magnetic declination at the date of the field survey. &amp;#160;Fault attributes include fault type (normal, reverse, strike-slip), rake of the slickenlines and sense of motion. Attributes of the extensional fractures/joints also include their dimension (height, H) and spacing (S).Moreover, the GIS project includes basic georeferenced maps such as: i) geological maps of NVL available in literature at 1:250.000 and 1:500.000 scale; ii) DEM of the bedrock and of the ice surface (from Bedmap 2); iii) the Radarsat mosaic of Antarctica; and iv) the MODIS mosaic of Antarctica.This queryable database allows to perform multiple geostatistical analyses and realise geothematic maps such as: i) the spatial variability of the main azimuthal structural trends at the regional scale; ii) the intensity of brittle deformation quantified by the H/S parameter (see contribution of Cianfarra et al. in this meeting); and iii) thematic geostructural maps (e.g: maps of the foliation traces, of strain partitioning or fractures distribution).These analyses, pivotal to better understand the tectonic framework of complex regions such as the NVL and to provide constraints supporting any geodynamic modelling, will greatly benefit from the extreme pliability and interoperability of such a database, which can be easily modified and expanded according to different scientific research needs by the production of newly derived data.
Evaluation of Spectral Mixing Techniques for Geological Mixture in a Laboratory Setup: Insights on the nature of mixing

Geological mixtures having endmembers mixed at a fine scale pose a challenge to estimating their fractional abundances. Light incident on these mixtures interacts both at multilayered and surface levels, resulting in volumetric and albedo scattering, respectively. Accounting for these effects necessitates a nonlinear spectral mixing model approach rather than conventional linear mixing. In this study, we evaluate the performances of linear and various nonlinear spectral mixing models for an intimately mixed geological mixture, i.e., a banded hematite quartzite (BHQ) sample. The BHQ sample with distinct endmembers of hematite and quartzite facilitated our study of the behavior of light on two-component nonlinear mixtures. In a laboratory-based experimental setup, we used a spectroradiometer of full spectral range in the visible and near-infrared regions (350 to 2500nm) to acquire a hyperspectral image of the BHQ sample. It was followed by the identification of nonlinearly mixed regions and inferring changes in their spectral features. The nonlinearity induced in these regions was attributed to two significant causes- (1) the fine scale of spectral mixing and (2) the spectroradiometer sensor&amp;#8217;s limited ability to spatially distinguish between focused and neighboring points, thereby producing a point spread effect. We observed the effects of nonlinear spectral mixing for our sample by changing the sensor&amp;#8217;s height from 1mm to 5mm, to simulate fine and coarse-resolution images, respectively. The spectral mixing was modeled using the existing mapped ground truth fractional abundances and library endmembers&amp;#8217; spectra by linear mixing and established nonlinear techniques of the generalized bilinear model (GBM), polynomial post-nonlinear model (PPNM), kernel-based support vector machines (k-SVMs). The evaluated performance metric of reconstruction error revealed the nonlinearity effect in image pixels through statistical tests and nonlinearity parameters used in these models. It was further observed that the associated nonlinearity increases from fine to coarse-resolution images. The minimum error of image reconstruction was observed for the polynomial post-nonlinear model, with a single nonlinearity parameter and an average reconstruction error (ARE) of 0.05. Our study provided insights into the nature of nonlinear mixing with endmember composition and particle sizes.
Seismic methods to investigate the interplay between magmatism and tectonics in the Northern Apennines hinterland, Tuscan Magmatic province, Italy

The Northern Apennines hinterland is normally referred to as a back-arc area affected by magmatism since the late Neogene, with intrusive and extrusive magmatic rocks being scattered through the southern Tuscany and the Tuscan Archipelago. This setting makes this geothermal area one of the most important worldwide.&amp;#160; The very high geothermal gradient of the Tuscan Magmatic Province (up to 200&amp;#8211;1000 mW/m2 in the central part of the Larderello-Travale geothermal field) fuels vigorous fluid flow that promotes a widespread geothermal activity. The plumbing magmatic systems progressively migrated eastwards. In Tuscany, the Elba Island is proposed to be the ancient (and now exhumed) analogue of the Larderello-Travale geothermal system where Pliocene to Pleistocene granites have been found at about 3 km depth. The occurrence of such magmatic bodies links to one of the most debated structures of the region, namely the K-horizon seismic reflector. Early authors suggest that this level may represent the transition between ductile and brittle geological units. Other authors propose that the k-horizon may represent a level where the magmatic brines released by the cooling plutons are stored at super-critical conditions.To understand the spatial and temporal relationship between tectonics and eastwards migration of magmatism, we deployed a seismic network composed of 30 broadband sensors that complemented the permanent INGV network from September 2020 to August 2021. We used QuakeMigrate to build the seismic catalogue and identified 915 events. The seismic activity is well spread across the region and occurs in swarm sequences in areas marked by higher geothermal gradients, particulary in the Larderello-Travale geothermal field. We investigate the seismic clusters and compare them against the locations obtained with the permanent monitoring network. Our results significantly reduce the magnitude of completeness for the Northern Appennines hinterland and provide new insights into the tectonics of the region. This study will be continued with a newly funded project that will use ambient noise methods acquired by nodal networks to provide high-resolution tomographic inversions of the geothermal systems of the Tuscan Magmatic Province.
Rancang Bangun Jaringan Hotspot Menggunakan LINUX ClearOS Dengan Konsep Security Gateway

Hotspot checks certain places (usually public places) that have Internet services with wireless LAN technology, like universities, shopping malls, squares, libraries, restaurants or airports. Internet services like these are available for a fee and free. a sensible approach is required to manage server protection, namely by protecting the prevailing network. Where there's level of security to secure access and access rights to existing hotspots. A gateway may be a tool that's wont to connect a network to at least one or more computer networks that use different communication protocols, so information from an system is provided to other computer networks that use different protocols. to form this method, the author uses Linux ClearOS for the protection concept. this method is applied to the case study of PT. XYZ, which uses the hotspot. The author describes how security systems are installed and built on network servers, and describes gateways as network infrastructure. so the present hotspot medium can maximize its working system by using Linux software, which is another hotspot.
Spatial clustering of seismic events analysis using the Discrete Perfect Sets (DPS)algorithm: Pribaikalye

The study aims to get new insights in the evolving clustering of seismicity to be the preconditions for the further effective use of the improved SHA technique in earthquake-prone regions. Discrete Mathematical Analysis DMA (Gvishiani et al. 2008; Agayan et al. 2018) is a series of algorithms for analyzing discrete data, united by a common formal basis, which is fuzzy models of discrete analogs of the fundamental concepts of classical mathematical analysis: limits, continuity, smoothness, connectivity, monotonicity, extremum, etc. In this study, the use of DMA is associated with clustering: it has to select clusters of discrete observations according to a given criterion (classification of discrete observations belonging to one of the clusters) (Gordon, 1981). The results of application of the Discrete Perfect Sets DPS topological filtering algorithm to seismic events in the Baikal area are presented. For the purpose of our analysis, we consider the Baikal Division of the Geophysical Survey, Federal Research Center of the Russian Academy of Sciences, BDRGS (2020) catalogue data. Specifically the epicenters for magnitudes equal to or more than 2.6 (energy class K&amp;#8805;8.6, accepted in catalogue homepage) for the period 1989&amp;#8211;2018 within 48&amp;#8211;58&amp;#176;N and 99&amp;#8211;122&amp;#176;E. The study was carried out as part of the Russian Federation State task of Scientific Research Works on "Seismic hazard assessment, development and testing of earthquake prediction methods"(No. 0143-2019-0006).
Detecting and mapping the induced seismicity of a planned EGS in Helsinki/Espoo, Finland

The company ST1 Oy planned to construct an Enhanced Geothermal System (EGS) with two boreholes drilled down to ca. 6 km depth beneath the Aalto University campus in Otaniemi, Espoo, on the border of Helsinki. The company performed two stimulations, in June&amp;#8211;July 2018 and in May 2020, with a goal of opening up a water reservoir and achieving water circulation between the boreholes. The stimulation periods, which induced thousands of earthquakes, and their immediate surroundings were monitored by both permanent and temporary seismic networks with over 100 stations located within a few tens of kilometers of the site. Between and after the stimulations, the site was and is still being monitored by a relatively dense, consisting in total of ca. 20 stations, regional surface station and company installed borehole station networks.We have developed a cross-correlation based event detector which uses the existing ISUH manually analysed catalogues primarily of the 2018 and 2020 stimulation period seismicity, complemented by automatically picked catalogues from IMS, to detect events from the collected continuous waveform database. The 4-step detector &amp;#8211; templating, detecting, event filtering &amp; relocating &amp;#8211; can run on varying station configuration and is able to detect events down to ML -0.5 &amp;#8211; -1.0 with the station-event geometry around the EGS. We present here the results of the detector run from the beginning of the dense stimulation monitoring in May 2018 to the end of 2022 providing a comprehensive anatomy of the EGS induced seismicity.
Accurate Earthquake Locations of the Adriatic Thrust Fault of the 2021 Seismic Sequence with sP Depth Phases.

We re-located 70 earthquakes belonging to the seismic sequence started on 2021 March 27th, with a mainshock of Mw 5.2 at 13:47 UTC, in the Central Adriatic region (Italy off-shore) by using the on-purpose designed code by Zhao et al. (2007, 2011), modeling the sP converted phases.The mainshock of the 2021 seismic sequence occurred about 20 km north of the Palagruza island, 80 km from the Gargano promontory and about 40 km from the Croatian island of Lastovo. It was felt in many central-southern Italian regions, from Ancona to Foggia, and in Central Dalmatia. All the epicenters of this seismic sequence lie in the open sea, about 100km to the SE and about 50 km to the NW of the 2003 Jabuka seismic sequence, and the 1988 Palagruza seismic sequence, respectively.Though the seismicity in the central Adriatic Sea has been recorded by improving seismic networks, especially in recent decades, the precise location of the Adriatic offshore earthquakes was hampered mainly by the large distance of the closest stations, and by the large gap in the distribution of seismic stations.The possibility to model the sP depth phases enables us to estimate the epicentral parameters and focal depths of these offshore earthquakes more accurately, thanks to the peculiar ray-path that mimics the presence of a receiver approximately on top of the hypocenter. The refined earthquake locations allow us to make inferences on the structure responsible for the seismicity of the 2021 seismic sequence, a thrust fault NW-SE striking and ~35&amp;#176; NE-dipping, and on its seismotectonic context.The use of depth-phase arrival times to constrain the off-network events' locations is of particular interest to Italy due to both the peculiar shape of the peninsula and the extreme scarcity of seafloor stations, whose cost and management are very expensive and complex.We present the first attempt to apply this off-network location technique to the Italian offshore seismicity with the aim of improving the hazard estimation of these hard-to-monitor regions.
Exploring the particle size effect on the geochemical composition using experimental soil mixtures

The impact of particle size on elemental content in soils is difficult to predict because the positive linearity between them does not apply equally to all elements. This assumption needs to be constantly examined and considered for fingerprinting studies. Overall, higher element enrichment in the fine fractions reflects the increasing adsorption potential of larger specific surface area (SSA), however, this relationship is often non-linear or more complex. Previous studies have been reported that the relationship between SSA and elemental geochemistry is different in terms of linearity, magnitude, and even direction for each element, and it could also depend on the type of sample. Fingerprinting approach is founded on the assumption that the properties of source and sediment mixtures are directly comparable, however, when a particle size correction (PSC) is needed because of the enrichment of sediment mixtures in fine particles, the use of a single PSC factor based on SSA could negatively affect unmixing results. Based on our previous study, in which we examined the behavioural characteristics of geochemical tracers in artificial mixtures with different grain size, we demonstrated that the source apportionment estimated with unmixing models was sensitive to particle size. In this contribution, we explore in detail, and tracer by tracer, the effect of the particle size variation on the correct estimation of source apportions. Artificial mixtures with known percentages contribution from three experimental sources have been used, comparing i) sources and mixtures at &lt;63 &amp;#956;m, ii) sources at &lt;63 &amp;#956;m and mixtures at &lt;20 &amp;#956;m simulating fine enrichment and iii) sources at &lt;63 &amp;#956;m and mixtures at &lt;20 &amp;#956;m with particle size correction factor (PSC). These results support the need to develop alternatives to improve the use of correction factors in fingerprinting studies.
A Flexible and Investigation Approach for Encrypted Features Space Using Neural Network

Replication, in general, is defined as repeating a study's technique and assessing whether the previous finding re-occurs. Research can become replicable when a person can copy the same content and arrive at the same conclusion as the original study. In this paper, an approach control mechanism for article observation replicas is been proposed. The usage of encrypted pictures or encoded attribute plots has been shown to be successful in preventing unwanted approach to models. The approach's efficiency has only been verified in image organization models and semantic analysis models but not in article recognition models. For the first time, encoded feature plots have proved to be successful in the control of article observation replicas. A safe and efficient technique based on completely homomorphic encryption is used and its usefulness for a variety of real data is been demonstrated. The suggested technique is the first to directly replicate an algorithm on ciphertext, which is one of the best performers on the plaintext feature selection problem. Furthermore, the suggested protocol is extensible to the scenario of more than three data owners.